Lecture Notes in Civil Engineering

Arun Sharma
Radha Goyal
Richie Mittal   Editors

Indoor
Environmental
Quality
Select Proceedings of the 1st ACIEQ
Lecture Notes in Civil Engineering

Volume 60

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Ioannis Vayas, Institute of Steel Structures, National Technical University of
Athens, Athens, Greece
Sanjay Kumar Shukla, School of Engineering, Edith Cowan University, Joondalup,
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Anuj Sharma, Iowa State University, Ames, IA, USA
Nagesh Kumar, Department of Civil Engineering, Indian Institute of Science
Bangalore, Bangalore, Karnataka, India
Chien Ming Wang, School of Civil Engineering, The University of Queensland,
Brisbane, QLD, Australia
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Arun Sharma Radha Goyal Richie Mittal
• •

Editors

Indoor Environmental
Quality
Select Proceedings of the 1st ACIEQ

123
Editors
Arun Sharma Radha Goyal
Department of Community Medicine Indian Pollution Control Association
University College of Medical Sciences New Delhi, Delhi, India
New Delhi, Delhi, India

Richie Mittal
Overdrive Engineering Solutions Pvt. Ltd
Noida, Uttar Pradesh, India

ISSN 2366-2557 ISSN 2366-2565 (electronic)

Lecture Notes in Civil Engineering
ISBN 978-981-15-1333-6 ISBN 978-981-15-1334-3 (eBook)
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Foreword

It gives immense pleasure that the first Asian Conference on Indoor Environmental
Quality 2019 (ACIEQ 2019) is being organized by ISHRAE, SIE and IAQA.
ACIEQ 2019 is the first of its kind conference dealing with indoor environment,
which is an area less explored in India. This conference will initiate a tradition of
bringing together researchers, academics, professionals and experts in Indoor
Environment science, from all over the world.
This conference will particularly encourage the interaction of research students
and developing academics with the more established academic community and
professionals in an informal setting to present and to discuss new and current work
on Indoor environment. Their contributions will help to make the Conference an
outstanding one with papers contributing the most recent scientific knowledge
known in the field of exposure assessment, thermal comfort, acoustics, indoor
environment and Sustainable Development.
In addition to the contributed papers, three invited keynote presentations will be
given by Prof. Alan Hedge, Cornell University, Prof Paolo Carrer from University
of Milan and Prof. Richard D. Dear from University of Sydney representing all
aspects of indoor environment ranging from building design, health and ventilation
and thermal comfort will be discussed at the conference.
I wish the organizers and delegates, attending this conference, a good knowledge
transfer and betterment of application based scientific temperament through this
conference.
FOR A HEALTHY INDOOR ENVIRONMENT!

24 January 2019 (Hardik Shah)

PS to Hon’ble Minister

v
Preface

Indoor environmental quality (IEQ) plays an important role in maintaining the

health and well-being of the individuals especially in urban areas as people spend
almost 90% of their time indoors. IEQ is gaining importance in developing India as
new infrastructures are on the rise. So, it has become imperative to strike the
balance between the IEQ, ventilation, human health and productivity. Indoor air
quality (IAQ) is a prime area of concern coupled with efficient lighting, adequate
thermal comfort and manageable acoustics, determining the health and productivity
of the urban population in India.
Keeping in mind the need to create a platform to bring all the stakeholders
of IEQ together to discuss the issues, challenges and possible solutions for better
IEQ, Indian Society for Heating Refrigeration and Air Conditioning Engineers
(ISHRAE), Society for Indoor Environment (SIE) and Indoor Air Quality
Association (IAQA) together had organized the first edition of Asian Conference
on “Indoor Environmental Quality” which took place at Indian Aviation Academy,
Vasant Kunj, New Delhi, India, on February 1 and 2, 2019. It is for the first time
that an international conference on the subject of IEQ was being organized in India.
The conference theme was entitled “Habitable Built Environment—Experience
the Unseen.”
For this conference, research papers were invited under four major themes, i.e.,
Indoor Air Quality, Thermal Comfort, Lighting, and Acoustics. The conference
received a total of 62 abstracts of papers, out of which only 40 were selected by the
scientific committee for full paper submission. On full paper call, the conference
received only 22 full papers, out of which only 17 papers were accepted for oral
presentation and three papers were accepted for poster presentation. Remaining oral
presentations were from the invited speakers.
The proceedings of the conference (having 18 chapters in all—17 chapters are
from oral presentation and one from poster presentation) are being brought to you in
this book form for wider dissemination of the presentations made at the conference.
It will not only be an update on IEQ research but also a trigger for research work
that needs to be undertaken in Asia to tackle the challenges of IEQ head on.
Included here are the papers on indoor environment quality monitoring and

vii
viii Preface

modeling; the influence of confounding factors like thermal comfort parameters,

such as temperature and relative humidity with respect to different building types
(e.g., residential, commercial, institutional); ventilation characteristics and lighting.
The research papers on people’s performance, productivity and behavior with
respect to their exposure to various indoor air pollutants and parameters influencing
the overall indoor environmental quality are also included.

New Delhi, India Arun Sharma

New Delhi, India Radha Goyal
Noida, India Richie Mittal
Message

Of three types of air pollution, the ambient, household, and indoor, the last one
receives little focus in India, in particular that of researchers. It is understandable
given the magnitude of poor air quality that most investigators have pursued
research in ambient air pollution and associated dimensions. However, with the use
of new materials and compact building designs the indoor air quality has undergone
sea change. Since it does not cause acute effects, and rarely ever kills, the issue has
not caught the imagination of researchers and communities.
Poor indoor air quality and environment are cause of several building related
illnesses that many physicians are not familiar with. One of the deadliest is
Legionnaires disease that can be fatal in case of elderly and is a key health disorder
resulting from poor maintenance of cooling towers. The lack of prescribed stan-
dards for Indoor Air Quality is another reason for lack of awareness about this
important subject. Environmentalists and health professionals must become aware
of these issues and try to understand the environment triggering an altered bio-
logical and pathological response of human body. I hope the conference will shed
light on various aspects of IAQ issue and bring it to the attention of policy makers,
regulators, building and construction lobbies and last but not the least HVAC
engineers. I send my best wishes for the success of the conference.

T K Joshi
Fellow Collegium Mazzini
Adviser, Environmental Health
MoEFCC, GOI

ix
Message

The health concerns due to poor indoor air quality have been increasing rapidly in
India and other parts of the world. Initially, the sources of indoor pollutants were
limited to fuel used for cooking and for heating purposes. This pattern has been
changing due to additional sources prevalent indoors mainly from mixture of
products and material used for comfortable living. These starts from apparel, per-
fumes, and insecticides used indoors, personal care products etc. Growth rate of
personal care products including use of mosquitoes repellent are very high and
consequent health complaints have also been on a serious growth path. Mere use of
technologies alone will not be able to address this issue. It is important that we
undertake comprehensive scientific and social awareness for people to know what is
likely to cause harm. In addition, the scientific community must work with man-
ufacturers of the products to reduce emission when used indoors. The partnership of
all the stakeholders will go a long way in addressing this problem. The event “Asian
Conference on Indoor Environmental Quality” will be able to bring all partners
together to debate and recommend the best path forward for the India and the world.
Best wishes.

28 January 2019 (Rakesh Kumar)

Director, CSIR—NEERI

xi
Message

Air pollution has become a serious concern, particularly for health of the people.
People are exposed to unacceptable levels of air pollution in the outdoor as well as
indoor environment. Growing population, rapid urbanization, multiplicity and
complexity of sources, inadequate capacities and pace of technology and infras-
tructure upgradation, lack of public awareness & participation are some of the
factors that make air pollution more challenging. Many policy initiatives and
interventions have been taken in the recent past—introduction of BS-IV and firm
roadmap for BS-VI auto fuel and emission norms, stricter emission standards for
major industrial sectors, Swatchh Bharat Mission, National Solar Mission and
Ujjawala Scheme for LPG proliferation. However, most of the actions pertain to
outdoor air pollution. Indoor air pollution, though reported to be a larger health
issue, has got little attention.
I am glad Society for Indoor Environment, ISHRAE and IAQA, India Chapter
are jointly organizing 1st Edition of Asian Conference on Indoor Environmental
Quality. It would provide a platform to initiate discussion with various stakeholders
(research, academia, industry, societies, government and regulatory bodies) on the
subject and help setting a clear roadmap for guiding future actions, particularly with
regard to research studies, policies, regulatory framework, IEC, and technology.
CPCB would be happy to extend all possible support to this event and look forward
to successful deliberations and outcome.
My best wishes!

(Prashant Gargava)

xiii
ACIEQ 2019 Committees

Organizing Committee

Chairman

Mr. C. Subramaniam, ISHRAE

Co-chairman

Prof. Mukesh Khare, SIE

Convener

Mr. Richie Mittal, IAQA/ISHRAE

Co-convener

Mr. Gaurav Vasudev, ISHRAE

xv
xvi ACIEQ 2019 Committees

Scientific Committee
Chairman

Dr. Prasad Modak, SIE

Co-chairman

Dr. Jyotirmaya Mathur, ISHRAE

Convener

Dr. Radha Goyal, SIE/IPCA

Co-convener

Dr. Priyanka Kulshreshtha, SIE/IPCA

Coordinator

Ms. Rakhi Ghosh, IPCA

Secretary

Mr. Barun Agarwal, IAQA/ISHRAE

Treasurer

Mr. Amit Goel, ISHRAE

ACIEQ 2019 Committees xvii

Administration

Mr. Vishal Kapur, ISHRAE

Chair Speakers

Dr. Nitin Deodhar, ISHRAE

Dr. Arun Sharma, SIE
Mr. Ashish Jain, SIE/IPCA

Chair Marketing

Mr. Vikram Murthy, ISHRAE

Mr. Kedar Patki, ISHRAE

Chair Sponsorship

Mr. Ashish Rakheja, ISHRAE

Chair—Travel and Hospitality

Mr. Nitin Nayak, IAQA

Chair—Event

Mr. Anoop Ballaney, ISHRAE

Chair Social and Website

Mr. Ashu Gupta, IAQA

xviii ACIEQ 2019 Committees

Chair Delegate

Mr. Kedar Patki, ISHRAE

Mr. Aakash Patel, ISHRAE

Partners

Knowledge Partners National Environmental Engineering Institute (NEERI)

Central Pollution Control Board (CPCB)
Centre of Excellence for Research on Clean Air (CERCA)
Camfil
Silver Partners ABS Airtech Pvt. Ltd.
Aeropure
PureAir
Vehicle Tracking System (VTS)
Honeywell
Renson
Swaroski Partners IntelliGreen Technologies Pvt. Ltd.
Durkee
DRI—Innovative Air Solutions
Table Partners HUMIDIN
Airveda
Smoke Solution India
Kaiterra
Magneto Clean Tech
EI
Workshop Partners TSI Incorporated
BE—Breathe Easy
PARTICLES PLUS, INC.
Springer
Supporting Partners Indian Institute of Technology, Madras
Green Business Certification Inc. (GBCI)
IEQ-Global Alliance
GRIHA Council—Green Rating for Integrated Habitat
Assessment
Indian Pollution Control Association (IPCA)
International Facility Management Association (IFMA)
The Associated Chambers of Commerce & Industry of India
(ASSOCHAM, India)
Federation of European Heating, Ventilation and Air
Conditioning Associations (REHVA)
Environmental Management Centre (EMC)
GREEN TELS
Contents

Comparison of Indoor Air Quality for Air-Conditioned and Naturally

Ventilated Office Spaces in Urban Area . . . . . . . . . . . . . . . . . . . . . . . . . 1
Supreme Jain, Divyam Garg and Anubha Goel
Status of Carbonaceous Aerosol at Indoor Environment
of a Cafeteria in Delhi, India—A Case Study . . . . . . . . . . . . . . . . . . . . . 9
Papiya Mandal, M. Sri Nagesh and Anubha Mandal
Assessment of Indoor Fine and Ultra-Fine Particulate Matter
in a Research Laboratory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
Amit K. Mishra, P. Mishra, Sunil Gulia and S. K. Goyal
Air Pollution in Rural Households Due to Solid Biomass Fuel
Use and Its Health Impacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Khaiwal Ravindra, Maninder Kaur-Sidhu and Suman Mor
Characteristics of PM from Different South Indian Cooking Methods
and Implications in Health Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Yaparla Deepthi, S. M. Shiva Nagendra and Sathyanarayana N. Gummadi
Chamber Studies for Indoor Air Quality Modeling
and Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Sumanth Chinthala, Sunil Gulia and Mukesh Khare
Hospital Indoor Air Quality in Respect to Transmission
of Infection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
Prabir Kumar Sen and Parijat Sen
Environmental Monitoring of PM2.5 and CO2 in Indoor Office Spaces
of Delhi, India . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Akansha Gupta, Radha Goyal, Priyanka Kulshreshtha and Ashish Jain

xix
xx Contents

Examination of Particle Characteristics and Quantification

of Emission Factors for Smoke Generated from a Popular Indian
Incense Burnt in an Experimental Chamber . . . . . . . . . . . . . . . . . . . . . 77
Anubha Goel, Radhika Mundra and Deepshikha Ola
Comparison of Efficiency of Active and Passive Methods
of Bioaerosols’ Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
Palak Balyan, Chirashree Ghosh, Shukla Das and B. D. Banerjee
Impact of Lighting on Performance of Students in Delhi Schools . . . . . 95
Pratima Singh, Renu Arora and Radha Goyal
Exposure to Particulate Matter in Classrooms and Laboratories
of a University Building . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Abinaya Sekar, Prem Mohan, George K. Varghese and M. K. Ravi Varma
Assessment of Indoor Environmental Quality and Impacts
on Occupants: Case Study of MNIT Jaipur . . . . . . . . . . . . . . . . . . . . . . 119
Nivedita Kaul and Khushbu Parik
Classroom Ventilation and Its Impact on Concentration
and Performance of Students: Evidences from Air-Conditioned
and Naturally Ventilated Schools of Delhi . . . . . . . . . . . . . . . . . . . . . . . 125
Pratima Singh, Renu Arora and Radha Goyal
Indoor Air Quality and Thermal Comfort in Green Building:
A Study for Measurement, Problem and Solution Strategies . . . . . . . . . 139
Praveen Babu and Gourav Suthar
Heterogeneous Photocatalysis for Indoor Air Purification: Recent
Advances in Technology from Material to Reactor Modeling . . . . . . . . 147
Mohan V. Lekshmi, S. M. Shiva Nagendra and M. P. Maiya
Experimental Investigation of ISHRAE IEQ Standard Focusing
on Implementation Aspects Through Pilot Study . . . . . . . . . . . . . . . . . . 167
Shailendra Kumar, Nikhil Jain and Jyotirmay Mathur
About the Editors

Arun Sharma is a Professor in the Department of Community Medicine and Head

of the Department of Bio-statistics and Medical Informatics at the University
College of Medical Sciences, India. He has done his MBBS from University of
Calcutta and MD in Community Medicine from Banaras Hindu University, in
addition to having done fellowships with the University of Illinois, Urbana-
Champain (USA), University of Pennsylvania (USA), and the Johns Hopkins
Bloomberg School of Public Health (USA). Prof Sharma’s research work studies
the impact of pollutants on the respiratory health of urban populations.

Radha Goyal is the Deputy Director of the Indian Pollution Control Association
(IPCA), where she is responsible for all research and development related activities
and projects of IPCA in area of air and waste management. Dr Goyal is in-charge
of the Air Quality Management Services (AQMS) division of IPCA, specifically
working on indoor air quality, in addition to being a principal investigator for a
number of projects mapping air quality in Delhi NCR and assessing it’s impact. She
has done her PhD from the Department of Civil Engineering, Indian Institute of
Technology, Delhi.

Richie Mittal is the Managing Director of OverDrive Engineering Private Limited,

which specialized in energy efficient design and engineering of air conditioning and
cooling systems for enclosed facilities. He has served on the Board of Directors
of the Indoor Air Quality Association (USA), and is a member of many professional
societies and associations.

xxi
Comparison of Indoor Air Quality
for Air-Conditioned and Naturally
Ventilated Office Spaces in Urban Area

Supreme Jain, Divyam Garg and Anubha Goel

Abstract Indoor air quality (IAQ) is affected by indoor pollution sources that release
gases or particles into the air and depending on ventilation conditions, outdoor ambi-
ent air quality can also be contributing factor. Inadequate ventilation by limiting
inflow-outflow of pollutants, proximity to field or busy road can increase indoor
pollutant levels. For this study, two offices, one with natural ventilation and other
with central AC system, within residential campus of IIT Kanpur were selected. Air
quality in offices with varying ventilation conditions was monitored simultaneously
indoor and outdoor. The aim was to compare the data for the two locations and elicit
influence of ventilation conditions on indoor pollutant levels. Size segregated mass
concentration of ambient aerosols and particle number concentration (PNC) were
determined for indoor using cascade impactor, MOUDI and OPC, respectively. Out-
door coarse particle concentration (PM10 ) was determined using HVS sampler. The
PM concentration was found to be highest in naturally ventilated office. As per the
recently released ISHRAE standards for indoor environment (ISHRAE Standard—
10001:2016), minimum acceptable limits for Class C are PM10 < 100 µg/m3 and
PM2.5 < 25 µg/m3 . Levels of particles recorded in these office spaces were 4–6 times
higher than ISHRAE acceptable limits for PM2.5 and PM10, respectively. Particle
number concentration (PNC) was also higher in naturally ventilated office space as
concentration was more than 400,000 particles/cm3 (<1 µm) as compared to air-
conditioned office space (160,000 particles/cm3 ). The I/O ratio for PM10 was found
to be 0.64 and 2.93 for Office 1 and Office 2, respectively.

Keywords IAQ · Office microenvironment · Particles · Ventilation · Activity level

S. Jain · D. Garg · A. Goel (B)

Department of Civil Engineering, Indian Institute of Technology, Kanpur, India
e-mail: anubha@iitk.ac.in
A. Goel
Centre for Environment Science and Engineering,
Indian Institute of Technology, Kanpur, India

© Springer Nature Singapore Pte Ltd. 2020 1

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_1
2 S. Jain et al.

1 Introduction

Indoor air quality (IAQ) which refers to the quality of air inside and around closed
structures where a living being can reside is related to the comfort and health of
the occupants. IAQ is represented by the concentrations of pollutants and thermal
conditions. Common issues associated with IAQ are improper or inadequately main-
tained heating and ventilation systems, contamination by construction materials,
glues, fibreglass, particle boards, paints, chemicals, increase in number of build-
ing occupants and time spent indoors. All these issues give rise to indoor air con-
taminants that mainly include chemicals and organics like dust, moulds or fungi,
bacteria, gases, vapours and odours. Importance of air quality indoors can be consid-
ered by the statement that people spend about 90% of their time in different indoor
microenvironments.
Studies related to measurement of outdoor pollution from India are numerous
[1–5] as compared to a lesser number associated with examination of indoor air
quality [6–10]. Proliferation of chemical pollutants in consumer and commercial
products, the tendency towards tighter building envelopes and reduced ventilation to
save energy and pressures to defer maintenance and other building services to reduce
costs have fostered IAQ problems in most of the buildings. Knowledge of emissions
from indoor sources is increasing but more information is required to be gathered for
clearer understanding of the factors which impact indoor air particles concentration.
The objective of the current study is to measure and compare the variation in
particulate matter mass and number concentration in two different office buildings
of different ventilation system, i.e. air-conditioned and natural, inside the residential
campus of IIT Kanpur. This information will enable efficient IAQ management.

2 Methodology

2.1 Site Description

The two offices microenvironment considered in this study differed in ventilation

mechanism: one was fully air-conditioned (O-1) and other naturally ventilated (O-
2). Postgraduate student office O-1 is a closed air-conditioned room having a seating
capacity of 24 people. Post office in the premises of IIT Kanpur (O-2) is a natu-
rally ventilated official single-storeyed building with staff of 8–10 people and rest is
customers that come for the services. It is located near to the road having greenery
on all four sides with some patches of dusty floors. The Offices O-1 and O-2 were
occupied throughout the working hours by 10–30 and 50–70 occupants, respectively
(more details listed in Table 1).
Comparison of Indoor Air Quality for Air-Conditioned … 3

Table 1 Details of microenvironment selected for this study

O-1 O-2
Location Postgraduate office inside Post Office near shopping
academic building centre
Proximity to traffic routes Distant from busy road Distant from busy road but
close to secondary road
Land use type near site Office space Office space
Occupants 10–30 >15

Table 2 Instrument used in this study

Instruments Parameters examined for Instrument description
MOUDI (Micro-Orifice Size segregated mass MOUDITM Model 110:
Uniform Deposit Impactors) concentration without rotator MSP
Corporation, USA
OPC (Optical Particle Particle number OPC 1.108, GRIMM Aerosol
Counter) concentration Technik GmbH & Co. KG,
Germany
HVS (High Volume sampler) PM10 concentration Model No. APM 460
PUF Envirotech Instruments
Private Limited, India

2.2 Instrumentation

Real-time air samples for five days were collected inside both offices (O-1 and 0-2)
in the months of March and April 2018 in this study. The instruments used for this
purpose are listed in Table 2.
The MOUDI and OPC were utilised to measure mass concentration and number
concentration inside the offices whereas HVS was used outdoors to measure the
ambient PM10 mass concentration. A 47 mm tissue quartz filter was used to col-
lect size segregated particulate matter on six-stage MOUDI. The six-stage MOUDI
contain 0.18, 0.32, 0.56, 1.0, 1.56 and 3.16 µm cut size nozzles. Flow discharge of
30 lpm was maintained in MOUDI using a rotameter. The filter substrates of MOUDI
were cleaned with 99.99% ethanol after every run to minimise the clogging.

3 Results and Discussion

3.1 Particle Mass Concentration Inside the Offices

The particle mass concentration was observed to be higher inside the premises of
naturally ventilated Office (O-2). Here particle concentrations were found to be
4 S. Jain et al.

600.53 ± 132.61 µg/m3 and 255.22 ± 79.81 µg/m3 for PM10 and PM1, respectively.
These values are 30–40% higher than values recorded in the air-conditioned office
O-1 where concentration was found to be 416.48 ± 45.72 µg/m3 and 194.81 ±
32.21 µg/m3 for PM10 and PM1, respectively. The reason for large particle mass
concentration in Office 2 is its ventilation condition. The transport of outdoor particles
across the building envelope (i.e. penetration) is an important physical behaviour that
contributes to the particle concentration [11]. Office 2 is post office inside the Campus
of IIT, Kanpur which is naturally ventilated with open windows and doors being used
continuously throughout the day by visitors.
Particle size distribution in air-conditioned office (O-1). Figure 1 shows the per-
centage contribution of particulate matter of different size bins used for sampling
on different days in Office1 (O-1). The table attached with the figure is the mass
concentration in µg/m3 of different sizes on different days. Concentration of parti-
cles in all the six stages on all five days of sampling shows consistent results. O-1
is air-conditioned office space for postgraduates next to the laboratory and remains
engaged throughout the week. Frequent movement of the students and staff is very
common in this microenvironment and results in regular opening and closing of
gates. Also, some construction activity was taking place in the backyard of the office
during sampling time raising possibility of higher loading for both coarser and finer
particles. From Fig. 1, loading in finer and coarser range shows little variation. Thus,
it can be inferred that even if the rooms are air-conditioned, frequent movement may
lead to higher particle loading and it may not satisfy standards for indoor air quality
in terms of particulate matter.
Particle size distribution in naturally ventilated post office building (O-2). Similar
to Figs. 1 and 2 presents particle size distribution for post office inside IIT Kanpur.
From Fig. 2, it can be seen that major contribution in particulate matter is of coarser
range particles, S3 to S5 stages, which arise due to re-suspension of dust due to
movement of people and bags of post that are prepared in different duration of the

Fig. 1 Percentage contribution of different size bins to PM10 (Left) and distribution of particle
mass larger than PM1 and smaller than PM1 concentration (Right) inside Office 1 (O-1)
Comparison of Indoor Air Quality for Air-Conditioned … 5

Fig. 2 Percentage contribution of different size bins to PM10 (Left) and distribution of particle
mass larger than PM1 and smaller than PM1 concentration inside Office 2 (O-2)

day. Day 5 of sampling was Saturday which is holiday in the campus and shows con-
siderably lower concentrations in comparison with the first four days. Lesser number
of people visit post office on holiday affecting particle concentrations observed. The
sources of finer particles in the office can be vehicular emissions and the printer used
for the posts [12, 13].

3.2 Effect of Occupant Activity on Diurnal Trends in Particle

Number Concentrations Inside Office Space

Figures 3 and 4 show the time series of particle number concentration during the
sampling period in the offices. Particle sizes presented have been divided into three
ranges: smaller than 1 µm, 1–3 µm and 3–10 µm. The particles seem to follow
consistent trend throughout the sampling duration at both the locations.
In case of O-1, particle counts are high in the morning then decrease continuously
till 2 p.m. and follow consistent trend till 5:30 pm (Fig. 3a–c). After 5:30 pm, there
is sudden rise and particle count follows consistent trend for few hours. The trend
followed is consistent with occupant activities. In morning, people start coming to
the office, and frequent opening and closing of doors cause re-suspension of dust.
This falls in the lunchtime as people start settling for rest. Again, in evening during
winding up of work to and fro movement starts causing rise in the concentrations of
particle.
The naturally ventilated Office (O-2) also showed the trend of particle con-
centration rising and falling throughout the day according to the activities of the
occupants. From Fig. 4a–c, this can be seen that day starts with high particle con-
centration in the morning and falls continuously till 3 pm. After that particle count
again increases and remains high till the completion of the sampling. Morning is the
6 S. Jain et al.

Fig. 3 Particle number concentration in particle/cm3 inside Office 1 (O-1)

Fig. 4 Particle number concentration in particle/cm3 inside Office 2 (O-2)

time of high activity when office workers start arriving to work. The routine bags
of post to be distributed on that day are opened around 10:30 am. Till 3–3:30 pm
regular posts are accepted. After 3:30 pm., bags were prepared for the posts that were
collected for the day and office cleaning was conducted during the evening time.
Comparison of particle count with activity level shows that occupant movement,
indoor cleaning and other activity can be the prime reason for high particle count
indoor.
Comparison of Indoor Air Quality for Air-Conditioned … 7

3.3 Indoor-Outdoor (I/O) Relationship

Concentration of indoor air pollutants is affected by intrusion of outdoor pollutants

into the buildings and indoor sources. Indoor/outdoor (I/O) concentrations can vary
largely due to many factors including locations, building design and different activi-
ties. To measure the influence of outdoor air and indoor sources on indoor air quality,
I/O ratios were calculated. The I/O ratio for PM10 was found to be 0.64 and 2.93
for Office 1 (O-1) and Office 2 (O-2), respectively. For O-2, I/O ratio greater than 1
indicates that there are more particles generated indoor than outdoors. In the absence
other specific source of particulate matter, human activity was seemingly the most
important factor contributing to higher indoor coarse particles levels inside O-2. This
has also been shown in many studies that mass movement or other human activity
may lead to high particulate emission [6, 9, 14–16]. On the other hand, concentra-
tion of particulate matter inside the furnished buildings may also decrease due to
sedimentation onto surface, turbulent diffusion and electrical effects. Office 1 is well
furnished with respect to Office 2, supporting the reason for low I/O ratio.

4 Conclusion

The office spaces in our study have high levels of particles and do not even fall in the
Class C category of the recently released ISHRAE standards for indoor environment
(ISHRAE Standard—10001:2016), minimum acceptable limits for Class C category
are PM10 < 100 µg/m3 and PM2.5 < 25 µg/m3 . For both the office spaces, the particle
concentrations exceed more than 4 times the National Ambient Air Quality Standards
for ambient environment, India (NAAQS, PM10 : 100 µg/m3 , PM2.5 : 60 µg/m3 ),
which is quite alarming. It was found that the naturally ventilated open office space
is quite more polluted with respect to the closed air-conditioned space.
Factors affecting the indoor air quality can be attributed to the frequency of usage
of building, proximity to the roads and building type (public, private, etc.) as it con-
trols the level of maintenance and cleanliness. Particle levels noted in indoor office
spaces can be considered an environmental health threat, which reduces productivity
and requires implementation of mitigation measures at the earliest. A multidisci-
plinary approach should be taken to mitigate the impact of pollutants inside indoor
microenvironments with involvement of all stakeholders.

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8 S. Jain et al.

2. Izhar S, Goel A, Chakraborty A, Gupta T (2016) Annual trends in occurrence of submicron

particles in ambient air and health risk posed by particle bound metals. Chemosphere 146:582–
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Status of Carbonaceous Aerosol
at Indoor Environment of a Cafeteria
in Delhi, India—A Case Study

Papiya Mandal, M. Sri Nagesh and Anubha Mandal

Abstract The present study investigated the carbonaceous aerosol with respect to
organic carbon (OC), elemental carbon (EC) and total carbon (TC) in particulate
matter (PM10 ) in indoor environment of cafeteria located at Netaji Subhash Place,
one of the hotspot locations for pollution in northwest district of Delhi during 2014–
15 winter season. The collections of samples were carried out during the period of
three months (December 2014 to February 2015). PM10 samples were collected by
APM 800 samplers (Envirotech Pvt. Ltd., India) on Whatman 37 mm microfiber
quartz filter papers for 2–3 hourly bases in the dining area of food court. The flow
rate varied from 2.4 lpm to 3 lpm during the period of collection of samples. Indoor
PM10 concentrations varied from 1830 to 3212 µg/m3 . The concentration of OC, EC
and TC in PM10 size of particulate matter varied from 54 to 318, 11 to 71 and 70
to 364 µg/m3 , respectively. The percentage contribution of OC and EC in TC were
varied from 80 to 90% and 10 to 20%, respectively. The percentage contribution of
TC in PM10 varied from 10 to 20%, respectively. The concentration of PM10 at indoor
environment of cafeteria was alarmingly high as compared to National Ambient Air
Quality Standard (NAAQS), 2009. The present study revealed that concentrations of
PM10 , OC and EC at indoor environment of cafeteria were influenced by indoor and
outdoor air pollution, meteorological parameters and guest count.

Keywords Aerosol · Indoor air pollution · Particulate matter · Delhi

1 Introduction

Indoor air quality (IAQ) is still relatively unexposed as compared to outdoor air
quality. People spend their major time at indoor environment. Cafeteria may be
considered as public indoor environment [1] where people love to spend their time

P. Mandal (B)
CSIR—NEERI, Zonal Centre, Delhi, India
e-mail: p_mandal@neeri.res.in
M. Sri Nagesh · A. Mandal
Department of Environmental Engineering, Delhi Technological University, Delhi, India
© Springer Nature Singapore Pte Ltd. 2020 9
A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_2
10 P. Mandal et al.

with favorite food, happy moments and discussions. Healthy IAQ of cafeteria not
only provide the enjoyment to the public and workers of cafeteria but also protect
them from the exposing to harmful air pollutants of the outdoor environment. A
few studies have reported that IAQ is worst as compared to outdoor air quality. But
people cannot understand because they spent short duration inside the cafeteria. At
present scenario, air pollution at indoor environment is a grave problem in most
of the mega cities in India and is receiving a lot of interest to the researchers. It is
linked with socio-economic status of the public. Mostly, scientists are concentrated to
atmospheric aerosols in present-day scenario due to growing anthropogenic activities
as well as in terms of their effects on human health and climate change. Carbonaceous
aerosols are one of the dominating contributors to atmospheric aerosols. They are the
single largest absorber of solar radiation, and their heterogeneous reactions change
the dynamics of the atmospheric boundary layer which reduces visibility and also
create health hazard. Carbonaceous aerosol in terms of total carbon (TC) classified
into two categories, i.e., organic carbon (OC) and elemental carbon (EC), which
are the important constituents of PM10 (particulate matter 10 micrometers or less in
diameter). OC is emitted from biogenic and anthropogenic sources, whereas EC is
emitted only from anthropogenic sources.
Poor IAQ might be due to tiny particles (dust, pollen, animal fur, hair, etc.), harmful
gases (cigar, fragrances, cooking odor, mosquito repeller, etc.), volatile compounds
(floor cleaning substances, paint, glues, preservatives, etc.) and microorganisms (bac-
teria, fungus, virus, etc.) The major sources of poor IAQ might be due to combustion,
furniture, building materials, outdoor air pollution and its penetration to indoor envi-
ronment. IAQ also affected by building characteristics such inside space, orientation
of the building, custom habit and tradition of the inhabitant, usage of equipment
inside the building and ventilation system. The concentration of air pollutants at
indoor environment also varies from location to location and season to season due
to change in meteorological parameters (viz, wind speed, wind direction, tempera-
ture, relative humidity, mixing height, etc.). The common symptoms of indoor air
pollution are headache, irritation of eyes, running nose, cough and cold, itchy throat,
nausea, vomiting, etc. The potential health effect like respiratory infections, chronic
bronchitis, development of cancers to multiple organs are due to outdoor air pollu-
tion or indoor air pollution or combination of exposure to both indoor–outdoor air
pollution are still now on debate.
Despite arduous efforts put in research, the predominant sources contributing
to indoor air pollution remained debatable. This is because, unlike other dining
restaurants, cooking is carried out throughout the day in cafeteria. The varieties
of food preparation use a wide variety of cooking oils as well as cooking fuels
like LPG/PNG or coal. The heating of cooking oil and cooking fuels are the major
source of indoor carbonaceous aerosol. It is evident from the study that inflated
concentrations of particulate matter (PM10 ) (particulate matter 10 micrometers or
less in diameter), organic carbon (OC) and elemental carbon (EC) prevailed in the
cafeteria. OC, a submicron particle [2] of combustion, and EC, an essential primary
pollutant [3] emitted by incomplete combustion of fossil fuels [4], are the significant
contributors to particulate matter [5]. Yearlong observation of concentration of OC
Status of Carbonaceous Aerosol at Indoor Environment … 11

and EC by various researchers revealed a trend in indoor air pollution which is

particularly high during winter season and low during the monsoon season. People
spending their maximum time at indoors (such as in offices, cafeterias and houses)
are mostly exposed to greater concentrations of pollutants in urban areas [6]. There
is the need for continuous monitoring and analysis of carbonaceous aerosols (OC,
EC and TC) in size segregated size of particulate matter at indoor environment. Till
date, no studies have been reported in India regarding the concentrations of indoor
air pollutants with respect to PM10 , and its correlation with carbonaceous aerosols
(OC, EC and TC). The effort was made to put-forth the scenario of PM10 and TC
that comprised of OC and EC during the winter season at cafeteria located in Netaji
Subhash Place, one of the hotspot locations at northwest district of Delhi, India.

2 Methodology

2.1 Sampling Location

Delhi, the capital of India, is considered to be one of the most polluted cities in
the world by [7]. The inland position and the continental air prevalence influenced
the semi-arid climatic condition in Delhi. The climate of Delhi varies from arid to
semi-arid. Winter season is moderately cold and pre-monsoon is extremely hot with
frequent dust storms. The annual rainfall in Delhi varies from 600 to 800 mm and
maximum rainfall occurs during the monsoon season only. The temperature ranges
between 1 °C and 48 °C during winter to summer season. Minimum temperatures and
foggy conditions during winters trigger inversion condition, which leads to the accu-
mulation of atmospheric air pollutants [8]. The air samples were collected from inside
the cafeteria of Netaji Subhash Place at ground level during the period of December
2014 to February 2015. The sampling location of cafeteria at Netaji Subhash Place
is shown in Fig. 1.
The instrument was placed at the juncture of dining and kitchen activities, within
the premises of the cafeteria. The cafeteria is situated in hotspot location of West Delhi
adjacent to major arterial busy traffic roads. During the air sampling, precautionary
measures were taken not to expose the instrument directly to the outdoor environment.
The cafeteria is located at the ground level. Flow rate of the monitoring instrument
was maintained almost the same for the time period of monitoring. The sampling
location inside the cafeteria is shown in Fig. 2.

3 Meteorological Condition

The data of meteorological parameters (such as temperature, wind speed, wind direc-
tion and relative humidity) were collected from the India Meteorological Department
12 P. Mandal et al.

Cafeteria

Fig. 1 Sampling location of cafeteria at Netaji Subhash Place (Google Map)

Fig. 2 The sampling

location inside the cafeteria

(IMD) and also from the Bhuvan Panchayat developed by NRSC–ISRO [9], respec-
tively. The minimum and maximum temperatures of Delhi varied between 2 °C
and 29 °C, respectively during the study period. The average temperature, relative
humidity and wind speed of Delhi were 12.5 °C, 59.5%, and 4.00 knots, respectively.
Status of Carbonaceous Aerosol at Indoor Environment … 13

Fig. 3 Wind rose plot over Delhi (December 2014 to February 2015)

The prevailing wind directions were west and northwest directions during the study
period. The wind rose plot over the study period is shown in Fig. 3.

4 Instrumentation (PM10 and Carbonaceous Aerosol)

PM10 samples were collected on Whatman microfiber quartz filter papers during the
peak hours (1:00 p.m. to 4:00 p.m.) claimed by the cafeteria manager at a flow rate
variation of 2.4 to 3.0 lpm using APM 800 sampler (make Envirotech Pvt. Ltd., Delhi,
India). The filter papers were pre-baked in a muffle furnace at 550 °C for 6 h only
to remove organic impurities. They were also pre-desiccated and post-desiccated
for 24 h [10]. The concentrations of PM10 (µg/m3 ) were measured by gravimetric
method using Sartorius microbalance with accuracy till six decimals.
OC (composition of aliphatic, aromatic compounds, acids etc.) and EC (primary
pollutant) analyses were carried through Carbon Analyzer by Interagency Monitoring
of Protected Visual Environment (IMPROVE) and thermal optical reflectance (TOR)
protocol (The DRI Model 2001). The basic principle of the analyzer is to oxidize
OC and EC at different temperatures to get their respective fractions [11]. Analysis
sequence of the IMPROVE protocol is OC, pyrolyzed carbon fraction (PY) and EC.
OC is further divided into OC1, OC2, OC3 and OC4 at temperatures 140 °C, 280 °C,
480 °C and 580 °C, respectively; and EC is further divided into EC1, EC2 and EC3 at
temperatures 580 °C, 740 °C and 840 °C, respectively and analyzed. Predefined OC
14 P. Mandal et al.

by the IMPROVE protocol is: OC = OC1 + OC2 + OC3 + OC4 + PY. Similarly,
EC is predefined as: EC = EC1 + EC2 + EC3 – PY and TC is predefined as: TC =
OC + EC [12, 13].

5 Results and Discussion

The collected particulate matter (PM10 ) samples during the period of December 2014
to February 2015 were analyzed for organic carbon (OC), elemental carbon (EC) and
total carbon (TC) for both weekdays and weekends to understand the maximum con-
centrations of indoor air pollution at cafeteria during the winter season. No standards
or guidelines were established till date in India to control the increasing PM10 con-
centration at indoor environment. In fact, no studies have been carried out in India
regarding the concentrations of air pollutants with respect to PM10 and its correla-
tion with carbonaceous aerosols (OC, EC and TC). The statistics of concentrations
of PM10 , OC, EC and TC at cafeteria, during the study period (December 2014 to
February 2015) is shown in Table 1.
The concentrations of PM10 in weekdays and weekends varied from 2347 to 2976
and 1830 to 3212 µg/m3 with an average concentration of 2711 ± 161 (weekdays)
and 2708 ± 494 (weekends) in µg/m3 , respectively. The concentrations of PM10 at
indoor environment of cafeteria were alarmingly high and beyond the permissible
limit (100 µg/m3 ) of National Ambient Air Quality Standards (NAAQS) formulated
by Central Pollution Control Board, 2009 [14]. The highest concentrations of PM10 in
both weekdays and weekends were observed in the month of December 2014 due to
celebration of enjoyable moments of Christmas and New Year. Festive season, people
prefer to celebrate inside the cafeteria, which indicated visiting of maximum guest
count in the cafeteria. The maximum visiting guest count of the cafeteria indicated
maximum concentration of particulate matter (PM10 ) might be due to maximum

Table 1 Statistics of PM10 , OC, EC and TC at indoor environment of cafeteria in Delhi, India
PM10 (µg/m3 ) OC (µg/m3 ) EC (µg/m3 ) TC (µg/m3 ) OC/EC
Weekdays
Min 2347 99 11 116 3
Max 2976 318 61 364 12
Average 2711 174 29 203 7
Std. Dev. 161 76 17 88 3
Weekends
Min 1830 54 11 70 3
Max 3212 214 71 280 9
Average 2708 141 31 171 5
Std. Dev. 494 60 19 74 2
Status of Carbonaceous Aerosol at Indoor Environment … 15

cooking activities and maximum penetration of outdoor air pollutants inside the
cafeteria. The unfavorable meteorological conditions during the winter season such
as stability of atmosphere, slow dispersion and low-average mixing height were
the additional parameters which increased the concentration of PM10 at the indoor
environment of cafeteria.
The concentrations of OC, EC and TC in PM10 in weekdays varied from 99 to
318 and 11 to 61 and 116 to 364 µg/m3 with an average concentration of 174 ± 76,
29 ± 17 and 203 ± 88in µg/m3 , respectively. The concentrations of OC, EC and TC
in PM10 in weekends varied from 54 to 214 and 11 to 71 and 70 to 280 µg/m3 with
an average concentration of 141 ± 60, 31 ± 19 and 171 ± 74 in µg/m3 , respectively.
There was not much variation of concentration of EC in both weekdays and week-
ends as it is the primary pollutant. In general, EC increased in the air environment
due to emission of soot particles from usage of biofuels, vehicular and industrial
emission. The concentration of OC concentration varied in large extent might be
due to gas to particle conversation and emission from anthropogenic sources like
tobacco smoking, usage of, emission of soot particles from usage of biofuels, vehic-
ular and industrial emission. Weekdays OC concentrations were higher as compared
to weekends might be due to movement of less vehicles in weekends as compared
to weekdays. The percentage contribution of OC and EC in TC was varied season
to season. It was observed that concentration of OC and EC in TC in PM10 in an
average varied from 80 to 90% and 10 to 20%, respectively. The concentration of TC
is one of the major constituents in PM10 and at indoor environment the percentage
contribution of TC in PM10 varied from 10 to 20%, respectively. The average OC and
EC concentration inside the cafeteria, varied from 3 to 12. This indicated the burning
of biomass was the major source [15]. In general, the ratio of OC and EC greater than
two indicated the presence of secondary organic carbon (SOC), but mostly ignored
due to prevailing low temperatures, especially during the winter season, which may
contribute to meager formations of SOC [16] in TC in the indoor environment.

6 Conclusions

The present IAQ study with respect to PM10 associated OC and EC during winter
season at cafeteria revealed that poor IAQ. PM10 concentration was abnormally high
as compared to NAAQS in Delhi, the capital of India. People inside the cafeteria
are exposed to high concentrations of PM10 bound OC and EC for short duration of
time which may not be realized. The most effective way to improve IAQ is to reduce
the sources of chemical emissions which may include usage of cleaning substances,
furnishings, furniture, flooring, paint, textiles building materials, etc. Tobacco smok-
ing, cooking activities, fuel usages, exchange of indoor and outdoor air pollutants
Meteorological conditions are also the governing factors to increase indoor concen-
tration of PM10 and carbonaceous aerosols. In the fully centralized air conditioning
cafeterias, periodical cleaning of air conditioning systems is essential. The frequent
16 P. Mandal et al.

cleaning of floor of the cafeterias may reduce the emission of resuspension of floor
dust. The provision to place indoor dust-capturing plants will definitely reduce the
concentration of PM10 as well as PM10 bound OC and EC of the cafeterias.

Acknowledgements The authors are thankful to the Director, CSIR NEERI to grant them the
permission to conduct study at the Zonal Centre in Delhi. The authors are thankful to Environmental
Engineering Department, DTU to allow and to publish the research work.

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60.11.1282
Assessment of Indoor Fine
and Ultra-Fine Particulate Matter
in a Research Laboratory

Amit K. Mishra, P. Mishra, Sunil Gulia and S. K. Goyal

Abstract Indoor air quality (IAQ) has drawn the attention of all the scientific
community around the globe as it ranked one of the top five risks to public health
throughout the world. People spend most of their time in indoor environments, be
it in their home or workplace, without knowing that they are inhaling substantially
high concentrations of different indoor air pollutants (IAPs). In developing countries,
IAP concentrations are generally found high due to poor ventilation and numerous
indoor sources. Poor IAQ can adversely obstruct the mental, physical and social abil-
ity of a person, which can affect the working efficiency and result into loss in overall
productivity. Along with other IAPs, high level of PM in indoor environments is one
of the major concerns. The present study is an attempt to assess the exposure levels of
PM10 , PM2.5 and PM1 in one of the research laboratories, located in an industrial area
of Delhi city. The monitoring is carried out at different indoor environments of the
building. The preliminary results indicate that average concentration of PM10 , PM2.5
and PM1.0 are highest in chemical laboratory, i.e., 114 ± 25 µg/m3 , 58 ± 10 µg/m3 ,
33 ± 5 µg/m3 , respectively and lowest at un-disturbed area, i.e., 42 ± 4 µg/m3 , 33
± 2 µg/m3 , 22 ± 2 µg/m3 , respectively. Ratio of PM2.5 /PM10 and PM1.0 /PM2.5 are
found higher at un-disturbed area, i.e., 0.79 and 0.75, respectively as compared to
other areas. It indicates that fine and ultra-fine particles travel more from outdoor
compared to larger particle and suspend for longer time in the environment. Further,
the study also discusses the possible measures to control the indoor air pollution and
prioritize the indoor air-purifying plants based on their efficiency.

A. K. Mishra · P. Mishra · S. Gulia (B) · S. K. Goyal

CSIR-National Environmental Engineering Research Institute (NEERI), Delhi Zonal Centre,
Naraina, New Delhi 110028, India
e-mail: sunilevs@gmail.com

© Springer Nature Singapore Pte Ltd. 2020 19

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_3
20 A. K. Mishra et al.

Keywords Indoor air quality · Particulate matter · IAQ purifying plants ·

Ventilation

1 Introduction

Indoor air pollution is one of the major causes of global burden diseases in the world
and ranked as one of the top five risks to public health. Most of the cases, indoor
air pollution is more harmful than the outdoor air pollution, because confined areas
enable potential pollutants to build up extra than open spaces. Most of the people
spend their maximum time in indoor and exposed higher compared to outdoors.
On average 80% of time people spend indoors [1, 2]. Yu et al. [3] reported that
unhealthy indoor air quality is the main contributor of “sick building syndrome”
(SBS). High exposure in poor indoor pollution causes allergies, respiratory dysfunc-
tion, nasal irritations headache and fatigue to building occupants [3]. Additionally,
exposure in polluted indoor workplace can reduce the work performance, output and
the wellbeing of building occupants [4].
IAQ of any building is related to a different range of physical, chemical and
biological factors like emission rate of chemicals and dust particle, the frequency of
indoor air to exchange with ambient air, atmospheric circulation efficiency inside the
building. The major indoor air pollution sources are combustion, building material,
indoor activities and penetration of outdoor air pollution. The incomplete combus-
tion of fuel emits particulate matters, hydrocarbons and other gaseous pollutants
such as carbon monoxide, nitrogen oxides, sulfur dioxide. Some of the sources
are associated with (i) indoor activities as housekeeping and maintenance like
cleansers, disinfectants, air fresheners, mats and lubricants; (ii) occupant-related
sources are tobacco product, office equipment (computers, printers and copiers),
cooking stoves/microwaves, paper products and dirt/pollens; and (iii) building mate-
rials, i.e., plywood/compressed wood, wall panels, construction adhesives, carpets,
tiles and also heating, ventilation and air conditioning systems like boilers, furnaces,
generators and stoves.
Meng et al. [5] stated that ambient air can contribute about 25–65% of indoor air
pollution [5]. In one of the studies, it was found that penetration of outdoor air pollu-
tion is one of the major sources of indoor air pollution in a typical building [6]. They
reported that indoor/outdoor (I/O) ratio of any pollutant significantly affects outside
meteorological factors and air exchange rate of the building [7, 8]. Researcher also
found that in the absence of intense indoor and ambient sources plays an important
role for high pollution level in indoor greater outdoor concentrations rather than
indoor values [9, 10].
High level of fine particulate matter in the indoor environment mainly due to
penetration from outdoor PM is one of the common sources in the naturally ventilated
building. This problem is more complex in city like Delhi where ambient PM level is
very high and exceeding the specified standards. PM is a composition of very small
particles and composed of various chemicals such as heavy metals, organic and
Assessment of Indoor Fine and Ultra Fine Particulate Matter … 21

inorganic carbon, secondary ions and acids [11]. The toxicity of the PM varies based
on its composition and types of sources. Chitra and Nagendra [12] have done a study
in a naturally ventilated school in Chennai and found that 24-h average suspended
particulate matter (SPM), PM10 , PM2.5 and PM1.0 concentrations were 168.64 µg/m3 ,
135.88 µg/m3 , 42.95 µg/m3 and 25.89 µg/m3 , respectively. Similarly, Singh et al.
[13] have also done indoor air quality assessment in selected schools of Delhi-NCR
and concluded that the average PM2.5 concentrations in both air-conditioned and
naturally aired school buildings were much above the levels suggested in National
Ambient Air Quality Standards, India. Indoor air quality standards are not yet defined
in India that is why compared with ambient standards. It seems that indoor PM level
is found higher in Indian cities and need to be reduced for better indoor air quality.
Numerous techniques are available for removal of indoor air pollutants. These
are mechanically removal of pollutants through air purifier; mechanically ventilation
with high air exchange rate, removal of VOCs from high adsorbing building materials
and planting air-purifying plants. Improvement of indoor air quality through plants
is one of the efficient and economical methods [14–18]. Indoor air-purifying plants
have many benefits. Plants can improve air quality through several mechanisms as
they can use carbon dioxide and give oxygen during photosynthesis. By the process of
transpiration, they can increase the humidity through very small leaf pores, and also
they can absorb pollutants on the external surface of leaves and the plant root–soil
system. Gawronska and Bakera [14] have found that spider plants help to accumulate
PM. Troy and Zavattaro [15] were tested Chlorophytum comosum (spider plant) and
Epipremnum aureum (pothos) for removal of pollutant from indoors and found that
each species could significantly reduce PM.
The present study is mainly focusing on the assessment of different size PM in a
research laboratory located in one of the industrial area of Delhi city, India. Further,
the importance of indoor air pollution and related health issues were discussed along
with possible solution through air-purifying plants.

2 Methodology

2.1 Site Description

The study is conducted in a research laboratory located in the Naraina Industrial area
where various activities carried out in the surrounding area. A research laboratory
is a workplace where anyone can find different work environments such as typical
administrative office, scientific staff office, trainee student room and chemical labo-
ratory area. The major sources outside the office area are commercial activities and
vehicular movement. A slum area also presents near to the study site where domestic
emission and open burning of biomass are common practices which also generates
huge amount of PM.
22 A. K. Mishra et al.

Fig. 1 Indoor air monitoring locations

2.2 Indoor PM Monitoring

Indoor air quality monitoring was carried out three days in the last week of August
2018 (August 23–25, 2018). The PM10 , PM2.5 and PM1.0 measurements were made
in each of the selected indoor environment at a sampling frequency of 1 min using
calibrated aerosol dust monitor (make GRIMM, R-11 model). The monitor performs
on the principle of light scattering by sucking air with multiple size particle at a flow
rate of 1.2 lit/min and passed through a laser beam. This is capable of measuring
particle mass concentrations in the range of 1-6500 µg/m3 . A 31-channel pulse height
analyzer for size classification detects the scattering signals in the size range of 0.3–
25 µm. The monitoring is carried out at chemical laboratory, administration office,
scientific/technical staff room, canteen area, guesthouse and storeroom (un-disturbed
area). Figure 1 shows the photographs of different office area where monitoring
performed. The monitoring is carried out for three consecutive days at the same time
in the respective area, during working hours only.

3 Results and Discussion

The monitored data of PM10 , PM2.5 and PM1.0 were analyzed statistically and com-
pared relatively. Tables 1 and 2 show 15 min average concentrations of PM10 , PM2.5
and PM1.0 for all the six indoor air environment.
The preliminary results indicate that 15 min average concentration of PM10 , PM2.5
and PM1.0 were found maximum in the chemical laboratory, i.e., 114 ± 25 µg/m3 , 58
± 10 µg/m3 , 33 ± 5 µg/m3 , respectively and minimum at storeroom (un-disturbed
Assessment of Indoor Fine and Ultra Fine Particulate Matter … 23

Table 1 Average PM concentration in different indoor chambers

Location PM10 (µg/m3 ) PM2.5 (µg/m3 ) PM1 (µg/m3 )
Avg. SD Avg. SD Avg. SD
Chemical laboratory 114 25 58 10 33 5
Admin room 56 11 32 5 23 3
Staff room 50 7 33 4 22 3
Store room 42 4 33 2 25 2
Canteen 104 28 57 9 34 3
Guest house 80 23 46 3 29 5
Avg.—average, SD—standard deviation

Table 2 Average ratio of PM 2.5 /PM 10 , PM 1.0 /PM 10 and PM 1.0 /PM 2.5
Location PM2.5 /PM10 PM1.0 /PM10 PM1.0 /PM2.5
Chemical laboratory 0.51 0.29 0.56
Admin room 0.58 0.41 0.71
Staff room 0.65 0.45 0.69
Store room 0.79 0.59 0.75
Canteen 0.55 0.33 0.59
Guest house 0.57 0.36 0.63

area), i.e., 42 ± 4 µg/m3 , 33 ± 2 µg/m3 , 22 ± 2 µg/m3 , respectively. Further, the

ration of PM2.5 /PM10 and PM1.0 /PM2.5 were calculated to evaluate the proportion of
different size particles in the indoor air. It is observed that ratio of PM2.5 /PM10 and
PM1 /PM2.5 were found higher at store area, i.e., 0.79 and 0.75, respectively as com-
pared to other office environments where these values were found less than 0.59 and
0.70, respectively. The higher ration of PM2.5 /PM10 , PM1.0 /PM10 and PM1.0 /PM2.5 in
storeroom which opens rarely were indicates that fine and ultra-fine particles travel
more from outdoor through leakages present in the door/window compared to larger
particle. The proportion of PM1.0 in PM10 was found in the range of 0.29 (chemical
laboratory)–0.59 (storeroom). The larger particles are generally resuspended in the
indoor environment through movement and other activities which is indicated in the
monitored level. Figure 2 shows the average concentration of PM10 , PM2.5 and PM1.0
for the study period at different workplace which indicates a high variation in the
PM10 and PM2.5 level. However, there is not much variation in PM1.0 level and found
more or less similar at all place.
In the past, researchers also reported similar pattern of PM concentration in the
indoor environment. In one of the studies, assessed IAQ in an office building and
found average PM10 and PM2.5 concentrations of 21.2 µg/m3 and 15.5 µg/m3 , respec-
tively [19]. Goyal and Kumar [20] found that I/O ratio for PM10 , PM2.5 and PM1.0
varied from 0.37–3.1, 0.2–3.2 and 0.17–2.9 µg/m3 , respectively, at commercial build-
ing in Delhi city. In a school building in Delhi, the I/O ratio of PM10 , PM2.5 and PM1.0
24 A. K. Mishra et al.

Fig. 2 Graphical representation of PM concentration in different indoor chambers

were found to be 2.52 ± 2.71, 1.44 ± 0.67 and 0.97 ± 0.18, respectively, which indi-
cate higher value because of occupant’s activities inside the building due to research
scholar movements and lower value due to outdoor air pollution [12].
The aerosol dust monitor measured particles having size range from 0.25 µm to
32.0 µm. The proportion of concentration of different particle size is plotted and
compared between different indoor work environments (Fig. 3). It is observed that
pattern of storeroom areas (non-active area) are totally different than other indoor
environments of the office which are generally active area. In storeroom, maximum
portion is due to finer particle, i.e., 69% by PM2.5 and 95% by PM10 when compared
to other workplaces where higher portion is due to larger size particles. The con-
centration pattern up to PM2.5 is almost similar in all indoor environments except
storeroom. However, pattern in guest hour and canteen are more or less similar and
staff room, admin area and chemical laboratory are similar. Further, this correlates

Fig. 3 Proportion of different size particles in different work environment

Assessment of Indoor Fine and Ultra Fine Particulate Matter … 25

well with the type of activity level. It is indicated that particle having size between
2.5 and 10 µm are highly influenced by indoor activity and resuspended due to
movement and other cleaning activities.

4 Conclusion

Indoor air pollution is one of the major causes of global burden diseases and reduces
the work performance in the office. Indoor PM10 , PM2.5 and PM1.0 were monitored
at different work environment of a research laboratory in Delhi city. The results
indicate that average concentration of PM10 , PM2.5 and PM1.0 were found maximum
in the chemical laboratory, i.e., 114 ± 25 µg/m3 , 58 ± 10 µg/m3 , 33 ± 5 µg/m3 ,
respectively and minimum at storeroom (un-disturbed area), i.e., 42 ± 4 µg/m3 ,
33 ± 2 µg/m3 , 22 ± 2 µg/m3 , respectively. High variations were observed in the
level of PM10 and PM2.5 between different office areas, however, not much variation
observed in the PM1.0 level. This indicates that resuspension of PM is one of the
major sources of Indoor PM10 concentrations. It is also observed that portion of ultra
and fine particles in PM concentration were observed in the indoor environment
with minimum disturbance compared to office area where activities are more. High
concentration of indoor PM should be removed through indoor air-purifying plants
as they provide cleaner and healthier air to us. They can also absorb pollutant on
their outer surface. Leaf size, structure, the thicker layer of waxes, pubescence and
surface roughness usually correspond to a higher absorption of pollutants from both
indoor and outdoor polluted air [15–17].

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Air Pollution in Rural Households Due
to Solid Biomass Fuel Use and Its Health
Impacts

Khaiwal Ravindra, Maninder Kaur-Sidhu and Suman Mor

Abstract Air pollution has become a major environmental health risk factor in
lower- and middle-income countries. There are several policies and regulations to
control outdoor air pollution, but household air pollution is ignored. Children, elderly,
and women, who spend most of their time in the indoor environment are at the higher
risks of exposure due to the uses of solid biomass fuels for household energy. The
exposure to toxic household air pollutants from incomplete combustion of solid
biomass fuels has been linked with chronic obstructive pulmonary disease, acute
lower respiratory infections, lung cancer, stroke, ischaemic heart disease, etc. How-
ever, evidence from countries where household air pollution has the highest adverse
impact, lacks to convince the policymakers. Hence, there is a need to focus on per-
sonal exposure assessment to establish the causal effect relationship. Recently, sev-
eral governments in Asia, including India, have taken initiatives to curb the use of
solid biomass fuels. This provides an opportunity to examine the benefits of better
health and the environment.

Keywords Household air pollution · Biomass fuels · Noncommunicable diseases

1 Air Pollution and Health

Pollution is the largest environmental cause of disease with a significant contribu-

tion from air pollution. The vulnerable population living in developing countries
are highly exposed to household and ambient air pollutants, as depicted in Fig. 1
[1]. Figure 2 shows the traditional cookstove, which uses solid biomass such as
cow dung cake, wood, or crop residue as fuel. Approximately, three billion people
globally are dependent on inefficient, polluting fuels, which contribute to 85% of

K. Ravindra (B) · M. Kaur-Sidhu

Department of Community Medicine and School of Public health, Post Graduate Institute of
Medical Education and Research (PGIMER), Chandigarh 160012, India
e-mail: khaiwal@yahoo.com
S. Mor
Department of Environmental Studies, Panjab University, Chandigarh, India

© Springer Nature Singapore Pte Ltd. 2020 27

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_4
28 K. Ravindra et al.

Air Pollution

Pollution Indoor Air Household Ambient Air

Pollution Air Pollution
Air

Radon,VOC, CO CO2

HCOH, lead CO2 O3, HCs

Pollutants
Key Air

Bioaerosols SOx NOx

Biological PM10, PM10, PM2.5

Sick building Low birth COPD, ALRI,

Syndrome, weight, COPD, wheezing,
Health

Rhinitis, asthma, ALRI, bronchitis,

Risks

lethargy, lung function lung cancer,

dizziness, eye reduction stroke and
irritation and IHD

Premature Deaths

~ 7 million [6]; ~ 6.5 million [1]; 8.8 Million [28]

Fig. 1 Type of air pollution, key pollutants, and associated health risks

air-borne particulate pollution [2–5]. Household air pollution is recognized to be

the second major environmental health risk factor leading to ill-health effects and
majorly responsible for the total burden of disease, accounting to 2.6 million deaths
yearly [6]. Worldwide non-communicable diseases are the primary cause of pre-
mature mortality, considering this India becomes the first nation to adopt the tenth
target dedicated to address the household air pollution in addition to nine specific
national targets under the World Health Organization’s global action plan for the
prevention and control of non-communicable diseases [7]. As per the Lancet com-
mission on pollution and health, acute and chronic exposure to particulate matter
has been recognized to be an emerging public health issue amongst lower-middle
income countries where it accounts for much of morbidity and over a million deaths
annually. A study from North India highlighted that the particulate emissions could
be above 10–20 times than the guidelines and standards for outdoor concentrations
and worsen indoor pollutant concentrations due to limited and poor ventilation [8,
9]. The vulnerable population—women, elderly peoples, and children—are at most
considerable risk to be affected by household air pollution [10].
The main source of household air pollution in developing nations is the use of
solid biomass fuels, in inefficient, traditional cooking stoves [11–13]. Incomplete
Air Pollution in Rural Households Due to Solid Biomass Fuel … 29

Fig. 2 Traditional cookstove based on solid biomass fuels being used by rural communities for
cooking

burning of solid biomass fuels in kitchens with poor ventilation helps to increase the
levels of various harmful household air pollutants. This includes the emissions of
particulate matter of variable size (e.g. PM2.5 , PM10 ), carbon monoxide (CO), oxides
of nitrogen and sulphur (NOx, SOx), black carbon, etc. [14–16]. PM2.5 is considered
more harmful than PM10 due to its deeper penetration into lungs, greater surface
area, and more adsorption capacity.
Several studies predicted that emissions due to household energy choice are
responsible for 73,000–460,500 premature deaths in India annually [17, 18]. House-
hold energy sector is leading to 67% emissions of PM2.5 in India in comparison to
other sectors such as land transport, agriculture, and industrial. Recently, a study
reported that household energy sector contributes largely to PM2.5 emissions, which
is the primary cause of various diseases in India [19]. The reduction of about 52%
population-weighted annual mean in PM2.5 emissions could be attained by simply
reducing emissions from the household sector, which attributes 511,000 premature
deaths every year. Thus, this could considerably reduce the health burden. Thus, it is
essential to target the reduction in PM2.5 emissions to address the increasing health
implications from increasing air pollution [20, 21]. For effectively mitigating house-
hold air pollution, personal exposure studies considering factors such as ventilation
and kitchen structure volume that are significant predictors of household air pollution
should be studied to further develop exposure assessment models [22]. This would
30 K. Ravindra et al.

aid in informed interventions, policies, and future epidemiological studies intended

for reducing household air pollution exposure.

2 Health Impacts of Household Air Pollution

Majority of rural households being much more dependent on biomass fuels, low-
quality inefficient cookstoves, and poorly ventilated kitchens lead to building up of
health-damaging pollutants [23–26]. The pollutants from these cookstoves constitute
a significant contributor to household air pollution and are the biggest cause of
respiratory problems. Also, the use of solid biomass fuels raises the risk of pneumonia
by >80% [27]. Other major health issues associated with household air pollution
are low birth weight, chronic obstructive pulmonary disease (COPD), acute lower
respiratory infections (ALRI), lung cancer, stroke and ischaemic heart disease (IHD),
etc. [28]. About 25% of the premature deaths that occur from household air pollution
exposure are due to a stroke, which is linked with short-term exposure to particulate
matter [29]. Approximately, 1.4 million deaths are caused by stroke and amongst
which 50% are in women. 15% of the total deaths are due to ischaemic heart disease
and are mostly associated with long-term exposure to particulate matter. Another
study highlighted that more than 33% of premature deaths take place from chronic
obstructive pulmonary disease in lower-middle income countries, around 17% of
lung cancer due to carcinogens released from biomass combustion [30]. However,
till date, studies are lacking to establish the association between the effects of variable
sizes of particulate matter and the duration of exposure on the occurrence of stroke
and related diseases.
The data of premature deaths owing to household air pollution listed by WHO
(2012) were used to create a region-specific plot for diseases namely, chronic obstruc-
tive pulmonary disease, acute lower respiratory infections, lung cancer, stroke,
and ischaemic heart disease as shown in Fig. 3 [31]. Statistics reveal that deaths
attributable to household air pollution are significantly elevated in regions of South-
East Asia, Western Pacific, low-middle income countries (LMICs). The increasing
burden nevertheless indicates that diseases associated with exposure to SBF have
become a serious problem throughout India.
WHO has estimated that each year household air pollution is responsible for
the deaths of 4.3 million people globally. In India, the incidence of several deaths
due to household air pollution was found 18% higher for females than for males
(0.26 million:0.22 million) [32]. Long-term impacts of such exposure can hamper
the overall development in children and can pose a serious impact on maternal health,
especially during pregnancy. Pregnant women are at most risk for infection, malnu-
trition, anaemia, gestational diabetes, and hypertension, and some of these factors
may be exacerbated by household air pollution implicated in their development. The
long-lasting health diseases caused due to household air pollution exposure could be
Air Pollution in Rural Households Due to Solid Biomass Fuel … 31

Fig. 3 Total deaths attributable to household air pollution, region-specific

addressed by choosing clean cooking technologies, framing strategic legislative poli-

cies and by enhancing effective user-behaviour focused interventions for adoption,
and sustained use of clean fuels [33, 34].
Diseases attributable to pollution are reported to cause over 9 million premature
deaths, which are thrice the number of deaths caused by AIDS, tuberculosis, and
malaria [1]. Another study by the International Energy Agency observed that the
deaths related to biomass would increase in the future. These reports also highlight
that premature deaths related to biomass uses will continue to increase at a linear
rate from 2008 to 2030 as compared to other common diseases like AIDS, malaria,
and tuberculosis. Hence, there is a need to understand household air pollution and
their exposure better. This can be achieved by generating more regional evidence
through air pollution monitoring having coverage of geographic variations. Personal
exposure studies can provide better exposure data and associated health risks, but
they are costly. This can be achieved by bringing private partners through social
corporate responsibilities, which can promote efficient stove and clean fuel usage.

3 Conclusion

Global Burden of Disease and the Lancet Commission on Air Pollution and Health
have highlighted that household air pollution is becoming a major health risk. Hence,
long-term strategies are required to better address the issue. This can be achieved
32 K. Ravindra et al.

through proper policies addressing the indoor air quality with the support of the
World Health Organization (WHO) guidelines. Reduction in household air pollu-
tion will also lead to a decline in ambient air pollution concentration. The success
stories of clean household energy and benefits should be communicated to formu-
late evidence-based policies. Reducing household air pollution through legislation
will also reduce the associated health and environmental burden, which will lead to
achieving sustainable development goals and accompanying targets finally.

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Characteristics of PM from Different
South Indian Cooking Methods
and Implications in Health Effects

Yaparla Deepthi, S. M. Shiva Nagendra and Sathyanarayana N. Gummadi

Abstract Indoor air pollution (IAP) predominantly contributed from biomass burn-
ing in rural households is a major health hazard. Cooking activities are significant
sources of indoor particulate matter (PM). The present study focuses on characteris-
ing PM emissions from different cooking methods that are primarily prepared in rural
areas of South India, in a simulated kitchen relying on biomass as fuel and estimation
of respiratory dosage. Controlled experiments were carried out to study PM concen-
trations generated while performing different cooking methods including boiling
(rice, urad dal and preparation of tea) and pan-frying (wheat roti and omlette). Mul-
tiple Particle Path Dosimetry (MPPD) was used to estimate deposition fractions in
head, tracheobronchial and pulmonary regions of the human respiratory tract (HRT)
for women. Further, PM dosage was assessed by entering the captured PM measure-
ments and evaluated amongst different cooking methods. PM concentrations from
pan-frying were ~1.6 times greater than boiling, primarily due to usage of oil for
frying. Furthermore, pan-frying displayed higher dosage (412–2240 µg) compared
to the boiling (258–1119 µg). However, urad dal displayed extreme amplification of
8.7 times than preparation of tea due to longer cooking duration. It is evident from
above results that cooking methods are major attributes impacting IAP in rural areas
with severe health impacts.

Keywords Indoor air pollution · Biomass · Cooking methods · MPPD · Dosage

1 Introduction

One of the foremost health hazards in India is Indoor air pollution (IAP). As per
World Health Organisation (WHO), India carries the largest burden of diseases due
to IAP [1] which is designated as one of the four most critical global environmental

Y. Deepthi · S. M. Shiva Nagendra (B)

Department of Civil Engineering, Indian Institute of Technology Madras, Chennai 600 036, India
e-mail: snagendra@iitm.ac.in
Y. Deepthi · S. N. Gummadi
Department of Biotechnology, Indian Institute of Technology Madras, Chennai 600 036, India
© Springer Nature Singapore Pte Ltd. 2020 35
A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_5
36 Y. Deepthi et al.

problems along with ischaemic heart disease (IHD) and stroke and chronic obstruc-
tive pulmonary disease (COPD). The most common source of IAP in rural India
is burning of solid fuels including biomass and coal for cooking activities [2]. It is
estimated that of the 2.8 billion biomass users across the world, India alone is home
to more than 0.82 billion people, a majority of which comes from its rural areas [3].
Fuel wood (FW) is predominantly used as domestic fuel in rural India. Additionally,
assessing IAP activity wise, particulates in rural households are mostly contributed
from biomass combustion for cooking, smoking and re-suspension of household
dust and through in-filtration of outdoor sources like agricultural residue burning
and unpaved roads. Fine and ultrafine particulate matter (PM) generated in these
activities have greater health consequences due to higher mass concentration levels
and the presence of toxic substances in its composition [4]. Amongst the various
activities, cooking is one of the major sources contributing towards fine and ultrafine
PM. Past studies reported high levels of PM mass and number concentrations, chem-
ical and morphological compositions from cooking activities across the globe [5,
6]. Furthermore, these PM characteristics depend on various attributes like cooking
method, cooking style, type of the energy source and its quality, varied oil types, raw
materials, additives, cooking pan, position of cooking pan and burner size [5, 7, 8].
However, most of these studies focused on cooking activity performed on gas cook-
ing either in controlled cooking experiments or in real-world residential kitchens [5,
7, 9].
In addition, cooking methods differ across the world which in turn impacts the PM
characteristics. Wet cooking, for example, includes cooking that primarily requires
water, i.e. boiling, stewing and steaming and frying consists of stir-frying, pan-
frying and deep-frying, while dry cooking comprises broiling, grilling, oven baking,
toasting and microwaving that are the most common cooking methods [10]. PM10
and PM2.5 concentrations during steaming were low followed by boiling and highest
from frying in a study performed by Lee et al. [11]. See and Balasubramanian [5]
studied particle number concentrations for boiling, steaming, stir-frying, pan-frying
and deep-frying and observed that frying resulted in higher concentration compared
to steaming and boiling. Also, Alves et al. [12] measured PM2.5 concentration for
different cooking methods and a similar trend was observed, i.e. frying > grilling >
stewing > boiling. In a review study by Torkmahalleh et al. [10], various studies were
analysed and concluded that low particle concentrations were released during boiling
and steaming compared to oil-based frying. However, very few studies compared
these cooking methods for Indian cooking styles [5, 13]. Thus, it is very essential to
evaluate PM characteristics with different cooking methods so as to assess the health
risks associated with the cooking activities.
PM measurements in conjunction with the analysis of deposition of particulates
those inhaled in vulnerable regions of respiratory systems comprehend particulate
pollution and its allied health hazards [14]. Various models have been reported to
estimate particulates deposition fraction in HRT to predict deposition plus clearance
[15–17]. However, the Multiple Particle Path Dosimetry (MPPD) model (developed
by the Environment and Chemical Industry Institute of Toxicology (CIIT, USA) and
Characteristics of PM from Different South Indian Cooking … 37

Dutch National Institute for Public Health) is widely used as it is more represen-
tative for studies associated with particle dosimetry as it contemplates asymmetric
branching pattern in respiratory systems [18–20].
Several past studies have been carried out to comprehend PM characteristics from
different cooking activities across the globe [6–9, 12] but a few numbers of studies
for Indian cooking styles [5]. Since the cooking characteristics significantly depend
on cooking method, cooking style, varied oil types, raw materials and additives, the
disparity in terms of significance of the studies is the subject for the present study.
Furthermore, only handful studies are conducted on woman specifically, during cook-
ing, for particulate respiratory dosage [20]. Hence, the objectives of the present study
are to evaluate PM characteristics for different cooking methods including boiling
(rice, urad dal and preparation of tea) and pan-frying (wheat roti and omlette) with
constant cooking conditions and fuel wood, followed by assessment of respiratory
dosage for women and associated health impacts.

2 Methodology
2.1 Monitoring Campaign, Site and Instruments

The samplings were carried out in a controlled room (3 m × 3 m × 3 m) with two

windows (1.15 m × 1.15 m) and one door (2.3 m × 1.10 m) (Fig. 1) located in IIT
Madras campus. Fuel wood was used for cooking which is predominantly used in
rural households of South India. No wood was present and all the glass windows
were kept closed during the experiments so as to control ventilation. Thus, the PM
concentrations monitored are primarily from cooking activities.
PM mass and number distribution ranging from 300 nm to 20 µm were measured
using 16-channel GRIMM optical particle counter (1.108) (Fig. 2a). The instrument
uses a semiconductor laser as the light source as it works on the principle of light
scattering technology (Fig. 2b). Periodic calibration of instrument was performed to
ensure precision of data collected with reproducibility of ±2%. Before each monitor-
ing, all the necessary flow and background checks of the instrument were performed
that was kept at 1.5 m away from cooking activity at respirable height (1 m) dur-
ing each cooking experiment. Further, using instrument software, the PM data was
extracted at 1-min resolution and subsequently data was analysed using Microsoft
Excel (MS Office 2013) and origin pro (8.5 version).

2.2 Sample Collection

The experiments carried out in this study were designed to simulate the PM concen-
trations (PM10 , PM2.5 and PM1 ) arising in domestic Indian cooking style primarily
in rural households of South India. The cooking methods considered for the study
38 Y. Deepthi et al.

Fig. 1 Photograph of controlled room along with women performing cooking activity

include boiling, i.e. rice, preparation of tea and dal and pan-frying, i.e. wheat roti
and omlette (Table 1). Above cooking methods were duplicated keeping fuel wood
and quantity prepared as constants. Each experiment was performed on a single day
so as to disperse the air that would have attributed from the previous experiments.

3 Particle Dosimetry Model

Deposition fraction (DF) is the most common metric used to determine depositions
in head (H), tracheobronchial (TB) and pulmonary (P) regions of HRT. DF is a func-
tion of mass median aerodynamic diameter (MMAD), tidal volume, breathing rate,
geometric standard deviation (GSD) and anatomy of lungs. DF could be calculated
by different mathematical models like International Commission on Radiological
Protection (ICRP) model, the National Council on Radiation Protection and Mea-
surements (NCRP) and MPPD. ICRP 66 is a semi-empirical approach based on
algebraic equations resulting from experimental and theoretical results developed
in 1994. It is a single path model with simplified morphometry which is a major
limitation [17, 21]. MPPD model (MPPD v 3.04, https://www.ara.com/products/
multiple-path-particle-dosimetry-model-mppd-v-304) in contrast is single as well as
Characteristics of PM from Different South Indian Cooking … 39

Fig. 2 Instruments used for monitoring a GRIMM (Model 1.108) and b GRIMM working principle

Table 1 Experiment
S. No. Cooking Item Cooking time
procedure for different
method (min)
cooking methods
1 Boiling Rice 22
2 Boiling Preparation of 10
tea
3 Boiling Dal 42
4 Frying Wheat roti 23
5 Frying Omlette 20

multi-path model. This model relies on real measurements of single airways and cor-
responding asymmetric branching structure of the lung [22]. Consequently, it leads to
a representative estimation of DFs in all regions of the lung and provides the prospect
to have detail assessment of dosage and subsequently associated health risks. Thus,
for the present study, the MPPD model was considered. So as to assess regional
and whole lung depositions, the combination of various deposition mechanisms like
inertial impaction, diffusion and sedimentation was considered [23–25]. Stochastic
lung model (60th percentile) was considered as it is the most accurate models for
40 Y. Deepthi et al.

Table 2 Physiological/morphological parameters for adult during lightweight activity

Activity Time Height Body BF TV (ml) URT
(min) (cm) weight (breaths/min) (ml)
(kg)
Light indoor 10–42 151 44.2 22 820 2110
activity
(Cooking)

human depositions. The input parameters included (a) particle properties (density,
size and shape distribution) (b) specific activity (cooking: light indoor activity) (c)
women characteristics such as age, gender, weight and height (d) respiratory phys-
iological parameters like tidal volume (TV), breathing frequency (BF), functional
residual capacity (FRC) and upper respiratory tract (URT) volume. For each cooking
method, MMAD and GSD were calculated [20]. Additionally, only nasal breathing
scenario with uniformly expanding flow and 0.5 inspiratory fraction was assumed.
Table 2 provides the input parameters obtained from the literature specific to women
[26–28].
Dosage is the amount of pollutant a person inhales during exposure to different
activities (cooking) for certain duration of time. It largely depends on deposition
fraction (dependent on particle size), the pollutant concentration (particulate matter),
duration of exposure and breathing pattern. The DF obtained from MPPD model
during each cooking method is used to estimate equivalent dose (expressed in µg)
by Eq. (1)

Dose = PM × DF × TV × f × t (1)

‘DF’ is deposition fractions (dimensionless), ‘PM’ is cooking concentration

(µg/m3 ), ‘TV’ is tidal volume of women during cooking activity (m3 /breath), ‘f ’
is breathing frequency of women during cooking activity (breaths/min), and ‘t’ is
cooking time exposure (min) [20].

4 Results and Discussion

4.1 PM Mass Concentrations for Different Cooking Methods

The PM10 , PM2.5 and PM1 mean mass concentrations released during different cook-
ing methods are presented in Fig. 3. PM concentrations from pan-frying were ~1.6
times greater than boiling, primarily due to usage of oil for frying [29]. The following
trend was observed, wheat roti > dal > omlette > rice > tea (Table 3).
These values were comparable to the past studies carried out across the globe.
The trend was similar to the studies carried out by Lee et al. [11], See and
Characteristics of PM from Different South Indian Cooking … 41

14000
PM10 PM2.5 PM1
PM concentration (μg/m3 )
12000
10000
8000
6000
4000
2000
0
Rice Tea Dal Wheat Roti Omlet
Boiling Pan Frying

Fig. 3 PM mass concentrations for different cooking methods

Table 3 Trends of PM10 ,

Cooking PM10 PM2.5 PM1
PM2.5 and PM1 during
item (µg/m3 ) (µg/m3 ) (µg/m3 )
various items of cooking
Rice 3350 3211 2776
Preparation 2236 2087 2004
of tea
Dal 5495 5215 3669
Wheat roti 7615 7295 4374
Omlette 3524 3365 2840

Balasubramanian, [5], Alves et al. [12], Abdullahi [13], i.e. frying followed by
boiling.

4.2 PM Number Concentrations for Different Cooking

Methods

Quantification and sub-classification of coarse and fine particles in the size ranges
considered by Deepthi et al. [20] in their study (Table 4) were used to understand the

Table 4 Particle size-based concentrations for different cooking methods

Type of house 0.3–0.9 µm 0.9–1.8 µm 1.8–4.5 µm
(particles/cm3 ) (particles/cm3 ) (particles/cm3 )
Rice 16.7 × 106 3.4 × 104 2.5 × 103
Tea 12.6 × 106 5.8 × 103 1.7 × 103
Dal 16.2 × 106 2.4 × 105 7.4 × 103
Wheat roti 16.1 × 106 6.1 × 105 1.3 × 104
Omlette 16.1 × 106 4.7 × 104 2.9 × 103
42 Y. Deepthi et al.

0.35
Rice Tea Dal Wheat Roti Omlet
0.3
Deposition Fraction 0.25
0.2
0.15
0.1
0.05
0
H TB P H TB P H TB P
PM1 PM2.5 PM10

Fig. 4 PM deposition fractions in HRT for different cooking methods

particle concentrations for different cooking methods. It was observed that number
concentrations were comparable in size range 0.3–0.9 µm for all the cooking meth-
ods. However, concentrations from wheat roti were one power higher compared to
other cooking methods for 0.9–1.8 and 1.8–4.5 µm. As, roti preparation itself results
in increased generation of the number of particles emitted apart from oil frying. These
number concentrations were comparable to past studies reported in Chinese cook-
ing methods by Zhang et al. [8] and See and Balasubramanian [5]. Apart from this,
number concentrations also establish the size-dependent deposition in the different
regions of HRT.

5 PM Deposition Fraction in HRT

For all the particles sizes and all the cooking methods, it was observed that the DFs
were considerably higher in H region of HRT (Fig. 4). The variance in DFs with
variable particle sizes was primarily reliant on the deposition mechanisms in the
HRT, i.e. inertial deposition, gravitational setting and diffusional deposition. The
difference in DFs is also majorly reliant on breathing pattern and ventilation that
vary with age (women) and activities (cooking).

6 PM Dosage in HRT

Dosages were calculated for different cooking methods for PM1 , PM2.5 and PM10
that are summarised in Fig. 5. Pan-frying demonstrated higher dosage (412–2240 µg)
compared to the boiling (258–1119 µg). Amongst each method, dal unveiled extreme
amplification of 8.7 times compared to preparation of tea due to longer cooking
duration. The trend observed was dal > wheat roti > omelette > rice > tea.
Characteristics of PM from Different South Indian Cooking … 43

1400
Rice Tea Dal Wheat Roti Omlet
1200

1000
Dosage (μg)

800

600

400

200

0
H TB P H TB P H TB P
PM1 PM2.5 PM10

Fig. 5 PM1 , PM2.5 and PM10 dosage in women

7 Conclusions

The present study records PM1, PM2.5 and PM10 levels reported from various cooking
methods that are typically prepared in rural households of South India and also
estimation of respiratory dosage for women in different regions, i.e. H, TB and P
of HRT. It was observed that PM concentrations were highest during pan-frying
and lowest from boiling. Additionally, cooking activities emitted millions of aerosol
particles (~106 particles/cm3 ) from all the cooking methods. Furthermore, the study
provides a comprehension to amount of particulates deposition for women in different
regions of HRT from varied cooking methods. The results revealed that pan-frying
displayed higher dosage (412–2240 µg) compared to boiling (258–1119 µg). Thus,
it was comprehended once again that different cooking methods are major attributes
impacting IAP and have health implications which need serious attention.

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Chamber Studies for Indoor Air Quality
Modeling and Monitoring

Sumanth Chinthala, Sunil Gulia and Mukesh Khare

Abstract Evaluating the status of indoor air quality using scientific techniques has
become a necessity at both urban and rural habitats. The process generally involves
monitoring of pollutants, investigation of its dispersion characteristics, formation and
destruction of pollutants, and rate of addition and removal from the sources and sinks,
respectively. In order to assess the above, the usage of sophisticated instruments
or low-cost sensors has become a prerequisite. However, their unavailability and
affordability have a significant effect on the indoor air quality studies at various
scales. To an extent, these studies can be performed using the computational fluid
dynamics (CFD) models which can simulate the pollutant dispersion characteristics
based on predefined numerical solvers. Moreover, information about the fate and
transport of the pollutant in the real time at the full-scale level remains unexplained.
Chamber studies enable us to supplement the monitoring studies conducted at full-
scale levels along with the monitoring studies and CFD simulations. The current paper
discusses the various types of indoor air quality chambers and their applications in
the investigation of different air quality parameters. The paper also presents the case
studies in development of ECO-SEE wall panels and the ability of the construction
materials to absorb pollutants.

Keywords Indoor air quality · CFD · Chambers · Modeling · Monitoring

S. Chinthala (B)
National Institute of Technology Warangal, Warangal, India
e-mail: sumanthchinthala@nitw.ac.in
S. Gulia
National Environmental Engineering Research Institute, Delhi Zonal Centre, New Delhi, India
M. Khare
Civil Engineering Department, Indian Institute of Technology Delhi, New Delhi, India

© Springer Nature Singapore Pte Ltd. 2020 45

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_6
46 S. Chinthala et al.

1 Introduction

The indoor air quality in buildings is dependent on both the nature of air movement
within the building systems and the nature and location of contaminant sources. Emis-
sion of indoor air pollutants like volatile organic compounds has direct influence on
people’s well-being and health. High exposure of indoor air pollutants concentra-
tion may cause conjunctival irritation, nose and throat discomfort headache, allergic
skin reaction, dyspnea declines in serum cholinesterase levels, nausea, emesis, epis-
taxis, fatigue, and dizziness [1]. Further, these higher concentrations cause various
health problems that may result into “sick building syndrome.” The indoor air pollu-
tants can originate from outdoor sources (e.g., traffic and other forms of combustion
(CO, NO2 , SO2 ) or from indoor sources, such as occupants and their activities,
tobacco smoke, electronic equipment, cleaning products or heating, ventilating, air-
conditioning (HVAC) systems, and building and furnishing materials. Additionally,
volatile organic compounds (VOCs) in indoor air may be found in paints, wood
preservatives, aerosol sprays, cleansers and disinfectants, moth repellents and air
fresheners, stored fuels and automotive products, and building materials [1]. More-
over, the degradation and deterioration of artificial and natural) building materials
may also release harmful pollutants. Hence, it is important to know the influence of
these pollutants not only on the health of the humans but also on the building mate-
rials. In this context, the study of the transport, deposition, and re-emission of these
materials in environmental chambers allows us to predict their behavior in confined
indoor spaces. Nowadays, many advanced materials are used specially in construction
and restoration works in indoor spaces. Environmental chambers have to be designed
to perform controlled experiments to evaluate the environmental variables which can
be used in the development of indoor air quality models. The developed models shall
be validated by performing full-scale testing under controlled environments to give
a complete overview of the pollutant transfer within the domain.

2 Environmental Chambers: An Overview

An environmental chamber is an enclosure used to test the effects of specified environ-

mental conditions on species, industrial products, materials, and electronic devices
and components. They artificially replicate the conditions under which the specimen
and their components might be exposed. They are also employed to accelerate the
effects of exposure to the environment to predict future scenarios. These scenarios
may include large, swift variations in temperature, very high or low relative humidity,
high and low pressures, etc. Few studies conducted on monitoring pollutants using
environmental chambers are listed in Table 1.
Chamber Studies for Indoor Air Quality Modeling and Monitoring 47

Table 1 Chamber studies conducted for monitoring air pollutants

S. No. Chamber description Pollutants monitored References
1 Stone exposure rig SO2 [2]
2 Atmospheric flow chambers SO2 , NO2 , NO, HCL [3]
3 NO2 exposure apparatus NO2 [4]
4 Environmental recirculation flow chamber SO2 , NO2 , O3 [5]
5 Atmospheric flow chamber SO2 [6]
6 Small-scale chamber VOCs [7]
7 Acrylic chamber CO2 [8]

3 Chamber Studies for VOCs Emitted from Building

Materials

Building materials may also affect the transport and removal process of indoor VOCs
by their adsorption and desorption properties. Re-emission of adsorbed VOCs may
significantly increase indoor VOC concentrations for months or years after a source
event [9]. The sorption properties on a material for VOC can be evaluated in two
ways, i.e., experimental investigation and emission modeling [10, 11]. In principle,
the experimental measurement methods provide more realistic results than the math-
ematical modeling. However, such methodologies require expensive well-controlled
instrumentation and time. Many researchers have addressed the importance of sim-
ulating VOC emissions from building materials and furnishings using mathematical
models.

4 Interaction of VOCs with Building Materials

The interaction process between materials and pollutant involves transfer of pollu-
tants (from the bulk air phase to the material–air interface), dynamic exchange of
VOCs between air phase and material surface, and diffusion of VOCs in the inte-
rior of the material, if it is permeable [12]. Further, the exchange of VOCs at the
air–material interphase may involve physisorption and chemisorption.
Moreover, studies conducted by Tichenor et al. [13] on impacts of VOCs on
materials indicate that VOC concentration has no significant influence on the sorption
capacity of a material-VOC combination. Hence, sorption tests may be preferably
conducted under relatively higher concentrations to improve accuracy. The studies
also found that the adsorption–desorption and rate of tetrachloroethylene on carpet
at 35 °C was significantly higher than those at 23 °C.
Generally, the sorption models are classified as equilibrium-interface models and
first-order rate models. For the interfacial mass transfer, a constant coefficient is used
to represent the ratio between the interfacial VOC concentrations for the two phases.
48 S. Chinthala et al.

On the other hand, the first-order rate model assumes that adsorption and desorption
processes are, respectively, proportional with the VOC concentration in the air and
on the surface of the material. At a later stage, Zhang et al. [7] have reviewed various
sorption models and their explaining their assumptions and applications. Table 2
describes the detailed assessment of various sorption models.

5 Monitoring and Modeling of VOCs Using Chamber

Studies

The methods of studying characteristics of VOC sources and sinks mainly fall into
two categories: experimental investigation and emission modeling [10, 11]. In princi-
ple, the experimental measurements provide the most realistic results than the mod-
eling results. However, it requires expensive and well-controlled instrumentation.
The experiments are set up using a small-scale or a full-scale stainless steel or glass
chamber to measure the sorption properties of a test material. The tests are usually
conducted under a set of specific environmental conditions (e.g., 25 °C, 50% RH,
and 1 ACH). The experiments are generally completed in two phases, the dynamic
adsorption phase and the dynamic desorption phase. In adsorption phase, the com-
pounds generated from the pollutant generator are carried by the conditioned, clean
air from the conditioner to the chamber containing the test specimen. The pollutants
concentration in the chamber is measured by analyzing air samples taken from the
chamber exhaust. After the system reaches an apparent equilibrium (the concentra-
tions at the chamber exhaust does not increase any more), the dynamic desorption
phase starts whereby the pollutant supply is stopped and the chamber is continuously
flushed out by the clean air.
Owing to the limitation of the experimental approach, many researchers have
addressed the importance of simulating VOC emissions from building materials and
furnishings using mathematical models. In literature, the sorption model is gener-
ally two types, i.e., first-order adsorption/desorption rate models and equilibrium-
interface models [11]. The linear Langmuir model is probably the most widely used
sorption model. It is based on physisorption process and considers only the relatively
fast surface sorption process. It does not consider the slow diffusion of pollutant inside
the material. The linear Langmuir model is described by the following equation [13].

dM
= ka C − kd M (1)
dt
where
dM/dt = net mass rate of change of VOCs adsorbed on the material surface
(µg m−2 h−1 ); C = concentration in chamber (µg/m3 ); k a = adsorption rate coeffi-
cient (m h−1 ); k d = desorption rate coefficient (h−1 ); and M = mass of pollutant per
unit area on material surface (µg m−2 ).
Table 2 Detailed assessment of various sorption models
Models Governing equations Parameters a b c d e References
Linear Langmuir dM/dt = ka Ca − kd M ka , kd N Y N C-F Y [13]
K-diffusion model dW1 /dt = k3 V Ca − k4 W1 k3 , k4 , k5 , k6 N Y N C-F Y [14–16]
dW2 /dt = k5 V Ca − k6 W2
Sorption–diffusion hybrid model ∂2Cm (x, t) Dm N Y Y C-F Y [17]
∂Cm (x, t)/∂t = Dm
∂ x2
Cm (+0, t) = Ca (t)
Sorption–diffusion ∂2Cm (x, t) Dm , k 3 , k 4 N Y Y C-F Y [17]
∂Cm (x, t)/∂t = Dm
hybrid model ∂ x2
dW (t)/dt = k3 V Ca (t) + ADm
∂Cm(x, t)/∂ x|x=+0 − k4 W (t)
Cm (+0, t) = W (t)/A
Chamber Studies for Indoor Air Quality Modeling and Monitoring

a Consideration of VOC transport in the air

b Consideration of surface sorption
c Consideration of VOC diffusion in the material
d Determination of model parameters: C-F: curve fitting
e Application for IAQ prediction and coupling with CFD code
49
50 S. Chinthala et al.

Table 3 Application of CFD for adsorption and environmental chamber studies

S. No. Application References
1 Simulation of binary adsorption [12]
2 Adsorption/desorption processes in carbon [19]
3 Dispersion of exhaled air in a ventilation room [20]
4 CFD simulation of respiration [21]
5 CFD in a test chamber [18]
6 Modeling adsorption using CFD for cooling system [22]
7 CFD simulation for adsorption separation in chromatography [23]
8 Modeling protein adsorption using CFD [24]

It is difficult to measure the values of k a and k d experimentally. However,

researchers used statistical tools to estimate the value of these coefficients based
on monitoring data of concentration and emission rate.

6 CFD Simulations—An Overview

Computational fluid dynamics (CFD) has been widely used as a method of simulating
room airflow, studying indoor environment issues, and producing data that may be
otherwise difficult to obtain through in situ measurements [18]. The application of
CFD for simulating the adsorption and desorption kinetics has been investigated in
various studies [12, 19]. Additionally, the dispersion of the pollutants in the controlled
environmental chambers has also been investigated widely [20, 21]. Further, White,
2012, has conducted a study comparing CFD simulations with experimental results
(Table 3).

7 Adsorption–Desorption Experiments in 2 L Chambers

and Simulation Studies in ECO-SEE

In order to determine the behavior of test materials when exposed to VOCs, “2 L”

cylindrical chambers developed by Building Research Establishment (BRE), Lon-
don, were used (actual internal volume 1.7–1.9 L). Due to the different types of test
materials, use of such chambers was preferred to the use of other methods such as
Field and Laboratory Test Cell (FLEC).
The VOCs selected for the studies were: toluene (a surrogate for benzene),
limonene (a ubiquitous terpene used in consumer products as a fragrance), dodecane
(a hydrocarbon representing those present in fuels and as a solvent in decorative
finish products), and formaldehyde (a VVOC).
Chamber Studies for Indoor Air Quality Modeling and Monitoring 51

The same VOCs and their adsorption and desorption on the test materials were
performed using FLUENT 14.0. The boundary conditions and the duration of the
simulations were same as that of the experimental conditions. The simulations are
primarily targeted toward numerically predicting behavior of materials for selected
pollutants, i.e., whether they act as sink or re-emitter. The behavior of the materials
under various conditions has been described in [25, 26]. The obtained results indicate
that the combined results obtained from chamber studies, CFD simulations, and the
numerical studies are essential to estimate the behavior of pollutants and materials
in the indoor environments.

Acknowledgements The results presented in this paper are part of the ECO-SEE project which
has received funding from the European Union’s Seventh Framework Programme for research,
technological development and demonstration under grant agreement No. 609234 (www.eco-see.
com).

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Hospital Indoor Air Quality in Respect
to Transmission of Infection

Prabir Kumar Sen and Parijat Sen

Abstract Airborne organisms, common in the hospital environment, can pose seri-
ous threats to patients—immune-suppressed and immune-deficient patients in par-
ticular. Though many of the infections in hospitals are transmitted through hand
contact, surgical appliances, catheterization, intubation, or while on ventilation, it is
an accepted fact that most of the opportunistic pathogens causing hospital-acquired
infections (HAI) are at least partly airborne. They may be non-respiratory, but they
get partly airborne before settling on the wound, or medical equipment/appliances.
Setting in proper indoor air quality (IAQ) parameters, like temperature, humidity,
dilution, filtration, pressurization, properly locating air terminal units, supported by
planned installation, operation and maintenance through a robust protocol, reduces
growth, count and transportability of infectious pathogens in hospital environment.
Various codes and standards of American Society for Heating Refrigeration and Air
Conditioning Engineers (ASHRAE), World Health Orhanisation (WHO), National
Building code (NBC) and Facility Guideline Institute (FGI) give guidance in regard
to IAQ in hospitals. A snapshot of healthcare industry shows that many hospitals are
not following the guidelines. Advanced infection control measures, like ultraviolet
germicidal irradiation (UVGI) and photocatalytic oxidation (PCO), though being
used, are not being located properly. Even IAQ is not being mentioned as an impor-
tant parameter in the infection control manuals for hospitals. This is causing large
number of hospital-acquired infection and associated deaths.

Keywords Healthcare · Indoor air quality · Infection control · Current status

P. K. Sen (B)
Consulting Engineer—HVAC, Kolkata, India
e-mail: prabirkumarsen@yahoo.co.in
P. Sen
Department of Pulmonary, Critical Care and Sleep Medicine, University of Kentucky, Lexington,
KY, USA

© Springer Nature Singapore Pte Ltd. 2020 53

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_7
54 P. K. Sen and P. Sen

1 Introduction

Healthcare facilities house together individuals with infections and individuals sus-
ceptible to infections in close proximity, risking transmission of infections from
one to another. It is not just patients, but even hospital workers, who are at risk of
contracting infections in hospital.
A patient, during his stay in a hospital, may pick up infection. This is known as
nosocomial infection. It is an infection which was not present, or incubated in the per-
son, when he was admitted in hospital. He acquired it during his hospitalization. Being
also known as healthcare-associated infection (HAI), or hospital-acquired infection,
it can be caused by viral, bacterial or fungal pathogens. Typically, it manifests within
48 h of hospital admission to 30 days after discharge from the hospital.
Outpatient clinics and the patient waiting areas may have undiagnosed infected
patients. However, these areas are generally air-conditioned similar to standard
office areas. Emergency rooms (ER) are also at risk, as often people with undi-
agnosed infectious diseases may be taken in these rooms right away without detailed
evaluation.
Hospitals often deal with immuno-compromised patients, comprising of both
immuno-deficient and immuno-suppressed types. Failure or weakening of normal
functioning of one or more elements of one’s immune system may make him immuno-
deficient. This includes patients with genetic immuno-deficient conditions, patients
with infections like HIV, as well as patients undergoing chemotherapy. Individuals
with autoimmune diseases, or those undergoing organ transplants, are often immune-
suppressed deliberately with medications. These immuno-compromised patients are
more susceptible to healthcare-associated infections.

Fig. 1 Types of nosocomial infections [1]

Hospital Indoor Air Quality in Respect to Transmission … 55

The most common types of healthcare-associated infections (Fig. 1) are blood-

stream infection (BSI), pneumonia (including ventilator-associated pneumonia, or
VAP), urinary tract infection (UTI) and surgical site infection (SSI).
Prevention of healthcare-associated infections has received much attention in
recent years as they create a large health risk and economic burden on individu-
als, as well as the society. A good and sustainable indoor air quality (IAQ) has a
great role in preventing transmission of infections in a hospital. A large number
of healthcare facilities, all over the world, are still away from meeting the heating
ventilation and air conditioning (HVAC) requirements for infection control. Inter-
disciplinary coordination, between HVAC engineers and healthcare personnel, is a
key to raising awareness on these critical issues, and tackling healthcare-associated
infections.

2 Fact Sheet

WHO fact sheet [2] states that, of every 100 hospitalized patients at any given time, 7
in developed countries and 10 in developing countries acquire at least one healthcare-
associated infection. Centre for Disease Control (CDC), USA [3], estimates that
there are 722,000 HAIs in acute care hospitals and 75,000 associated deaths in the
USA each year. Unfortunately, not much organized data on occurrence of healthcare-
associated infections is available for low- and middle-income countries (LMIC).
HAIs have large prevalence in intensive care units (ICUs) and in acute surgical and
orthopaedic wards. In high-income countries, approximately 30% of the patients [3]
in intensive care units (ICU) are affected by at least one healthcare-associated infec-
tion. In low- and middle-income countries (LMIC), the frequency of ICU-acquired
infections are about 2–3 folds higher. Device-associated infections are also up to
13 times higher [3] than that in the developed countries. In ICUs, a third of the
healthcare-associated infections are respiratory type.

3 Mechanism of Infection Transmission

Infection occurs when all of the following elements of its transmission chain are
present in a healthcare environment.
• An infectious agent, i.e. an infectious micro-organism.
• A source (of the agent), i.e. a patient with infection.
• A susceptible host, i.e. an immune-compromised (including immune-weakened,
immune-deficient and immune-suppressed) person, to receive the agent.
• And most critically, a pathway for the agent to travel from the source to the host.
56 P. K. Sen and P. Sen

Generally, the severity of the impact of infection on a person depends on the length
of exposure to infection, virulence of the microbes to which he is exposed, location
of the exposure and the infection load.
The infections may take following routes.
• Contact—through touch, stethoscope, bedpans, catheters, dressing, gloves, nee-
dles, appliances, instruments, ventilators, etc.
• Aerial route/airborne—through droplets and secretions on surface and air, inhala-
tion of infectious particles, etc.
• Oral route.
• Vectorborne through flies, mosquitoes, rats, etc.

4 Role of Indoor Air Quality in Infection Control

Some studies indicate that only 10% healthcare-associated infections is airborne,

while others state that 16% HAIs in ICUs is airborne. The fact still remains that
more than a third of HAI agents possibly get airborne at some part of their trans-
mission. Though many of the infections are transmitted through contact, more so on
sites of invasive procedures (like surgery, catheterization, intubation or putting on
ventilation), it is possible that the infectious microbes have taken an aerial path at
some stage of their travel. Many opportunistic pathogens though non-respiratory, get
partly airborne before settling on the wound or medical equipment/appliances.
Formation of aerosols from contaminated water, and their getting airborne, is
also a major mode of spread of infection, like Legionella, causing sporadic cases of
Legionellosis (a healthcare-associated pneumonia).
Given the above nature of transmission of infections, indoor air quality (IAQ) has
a major role in the healthcare industry, particularly in combating spread of infec-
tions. Among other measures, proper engineering design and planning of HVAC
systems, supported by selection, of proper technology, equipment, material, con-
trol, air intake/exhaust locations, appropriate protocols, and periodic monitoring and
maintenance can contribute greatly to reduce healthcare-associated infections. Unfor-
tunately, most healthcare facilities, in low- and medium-income developing countries
in particular, do not identify this as a critical aspect of infection control.

5 Control of IAQ Parameters for Control of Infection

Infection control science is a complex blend of engineering, particle physics, micro-

biology and medicine. Good HVAC systems can help to control infections by control-
ling different IAQ parameters, like temperature and humidity (reducing growth), dilu-
tion (reducing exposure time), filtration (reducing count), properly locating supply air
Hospital Indoor Air Quality in Respect to Transmission … 57

Fig. 2 Effect of air change rates on particle removal [4]

terminal units (preventing patient discomfort and coughing) and controlling airflow
patterns by suitable pressure gradient (reducing induction and transportability).
Temperature and humidity control not only aid in wound healing and patient
comfort, but also prevent growth of potential infectious agents. Patients may also
start coughing/sneezing in low relative humidity (RH) situation. Location of supply
air terminals is equally important, as a direct blast of cold air on patients’ body may
prompt them to cough/sneeze and release innumerable droplets, which may have
infectious microbes that may travel a long distance in air stream, particularly when
the air flow is turbulent.
Rate of dilution, of room air by outdoor air, controls the number of micro-
organisms present in a room and their exposure time on individuals. ASHRAE HVAC
Design Manual for Hospitals and Clinics [4] presents a table (Fig. 2) relating room
air change rates and particle removal time. It indicates that it will take 23 min to
remove 99% of the particles from a room with a dilution rate of 12 air changes per
hour.
Some researchers suggest that only about 7% of the hospital area needs air fil-
tration with MERV 14, or better class of filters. This may be an understatement
considering the submicron size of bacteria, complexity of patient mix and space
crunch in present day hospitals, where a large number of facilities are packed in
one building in a congested area. Orthopaedic surgery and bone marrow transplant
rooms should use HEPA filters (MERV 17) to keep their submicron bacteria level
low. Protective environment (PE) rooms for immune-compromised patients should
also use HEPA filters. General operating rooms, ICUs, recovery rooms, and in fact,
in all in-patient areas, diagnostic and treatment areas should use MERV 14 filters
to keep the bacteria level low. Even the exhaust air from negative pressure isolation
rooms for contagious patients should pass through HEPA filters before being released
in the congested surrounding.
Use of other additional advanced devices of air purification can enhance indoor air
quality further. Ultraviolet (UV) radiation inactivates micro-organisms by damaging
their DNA and RNA strands (Fig. 3) by penetrating their cell walls, and making
58 P. K. Sen and P. Sen

Fig. 3 UV ray inactivates

micro-organisms [5]

them unable to replicate and propagate infections. This can effectively reduce the
virulence of micro-organisms and, therefore, can reduce infection rates.
Photocatalytic oxidation (PCO) units are air purification devices, next generation
to ultraviolet germicidal irradiation (UVGI) units. It uses broad-spectrum UV light
to impinge (Fig. 4) on a thin film of titanium dioxide, to create free hydroxyl (OH+ )
radicals that can neutralize micro-organisms. It can eliminate particles as small as
0.001 microns, compared to 0.3 microns with HEPA filters.
Both UVGI and PCO units are especially effective while used on static particles.
They can keep cooling coils, filters and drain pans of air handling units free of
microbial colony. Efficacy of these devices are yet to be ascertained while acting on
fast-moving micro-organisms, like the ones in air inside the ducting, or in room air.
The fast-moving micro-organisms get much less exposure of UV/free radicals.
The UV/free radical dose has to be high in such event.
Some areas in a hospital are maintained at positive or negative pressure (with
respect to surrounding areas) to control transmission of infection. Operating rooms

Fig. 4 Working of photocatalytic oxidation unit [5]

Hospital Indoor Air Quality in Respect to Transmission … 59

and rooms for immune-compromised patients are maintained at a positive pressure in

contrast to airborne infection isolation (AII) rooms, which are kept at a negative pres-
sure. Objective of pressurization is to direct potentially infectious micro-organisms
from the more sterile to less sterile areas. An anteroom is suggested with pressurized
rooms to prevent sudden change in room pressure. The following areas in a hospital
are recommended to be positively pressurized as per Facility Guidelines Institute
(FGI) guidelines/standard 170-2013.
• Operating rooms
• Delivery rooms
• Trauma rooms
• Newborn intensive care (NICU)
• Laser eye surgery rooms
• Protective environment rooms for immuno-compromised patients
• Pharmacy
• Laboratory, media transfer
• Central Medical and Surgical Supply Clean workrooms
• Central Medical and Surgical Supply Sterile Storage.
Following are the areas in a hospital that should be maintained at negative pressure
as per FGI guidelines.
• ER waiting rooms
• Radiology waiting rooms
• Triage
• Toilet rooms
• Airborne infection isolation (AII) rooms
• Darkrooms
• Cytology, glass washing, histology, microbiology, nuclear medicine, pathology
and sterilizing laboratories
• Autopsy rooms
• Soiled workrooms or holding rooms
• Soiled or decontamination room for central medical and surgical supply
• Soiled linen and trash chute rooms
• Janitors’ closets.

6 Sample Survey

A sample survey was carried out in a metropolitan city in India to get an idea of
the current status of IAQ control in healthcare facilities. Two corporate multidisci-
plinary hospitals, three Govt. tertiary care centres and three small healthcare facilities
were visited in September, 2017 with an objective to study their HVAC systems and
IAQ control measures in relevance to controlling healthcare-associated infections.
Emphasis was on HVAC systems for operation rooms and intensive care units, the
60 P. K. Sen and P. Sen

two major areas for propagation of healthcare-associated infections. The observa-

tions vis-a-vis recommendations of various codes/standards/guidelines are presented
in Table 1.

7 Discussion

Air conditioning, in many healthcare facilities, more so in low and medium income
countries (LMIC), is still considered as just a comfort measure for the rich patients.
Certain protocol imposed hygiene control measures (like taking off shoes, floor
mopping and using sterile equipment) are in practice. Maintenance of hand hygiene
is also gaining importance. IAQ control, on the other hand, is hardly considered a
measure for controlling healthcare-associated infection. It is considered, somehow,
important only in controlling airborne respiratory infections. Relationship between
IAQ and healthcare-associated infections in general is not given its due importance
while designing, operating and maintaining HVAC system of a healthcare facility.
This is quite evident from the observations of the small sample survey. Even some
operation manuals for hospital infection control do not mention the importance of
indoor air quality. Emphasis seems to be more on treating the patients with HAI,
instead of preventing healthcare-associated infections, a very important root cause
of which is IAQ.
Cost is a major constraint in implementing the desired level of indoor air quality in
a healthcare set-up, particularly in LMICs. However, what is often missed is the final
burden that arises out of ignoring this aspect. A few of these issues, such as spacing
the exhaust and outdoor air intake and keeping the AHU rooms free from unwanted
materials, can be taken care through awareness and planning, and at no additional
cost. Stake holders should also understand that the benefit of 100% exhaust from an
OR is lost once they place its outdoor air intake in close proximity of the OR exhaust
duct. It was seen in the survey that using AHU rooms as a free storage space is a
popular practice. This increases the pollution load in critical areas of the hospital.
When HEPA/MERV 14 filters are used for a positive pressure OR, or a protective
environment room, it is always better to continuously monitor (Fig. 5) its pressure
levels with alarm systems to alert in case of any eventual depressurization making a
pathway for the micro-organisms.
Standard commercial type package AC units generally do not have high static
pressure evaporator fans. Using MERV 14 filters in supply air duct with them will
compromise on the supply air rate. This may lead to micro-organisms staying longer
in the room, increasing the chances of infection.
In the survey, the ICUs were found to be a neglected area as far as the control of IAQ
is concerned. NBC of India and ASHRAE guidelines should be followed for outdoor
air and supply air change rates in ICUs. Recirculating type residential/commercial air
conditioners (Fig. 6) are being used largely in the ICUs, though they do not meet any
infection control requirement (outdoor air, filtration and ACPH rates). Curtain type
partitions may provide some visual privacy with flexibility, but using such partitions
Hospital Indoor Air Quality in Respect to Transmission … 61

Table 1 Observations vis-a-vis recommendations of various codes/standards/guidelines

Feature Observation Recommendations
1 Air change Some ORs are using 40% outdoor air, National Building Code
per hour in some are using 60% and some are using (NBC) of India [6] suggests
operation 100% outdoor air for dilution. that recirculation of air should
rooms and In one hospital (using 100% outdoor be avoided in ORs. Outdoor
ICUs air) from the sample, outdoor air intake air with minimum 5 air
for OR is just adjacent to OR exhaust changes per hour (ACPH) and
duct, causing recirculation. room supply air with 25
Most ICUs in smaller healthcare ACPH shall be used.
facilities, and about 16% of ORs in the ICUs and recovery rooms shall
sample are using commercial packaged have 6 ACPH of room supply
air conditioners rendering no concern air and 2 ACPH of outdoor air.
about outdoor and supply air change per ASHRAE 170 suggests
hour (ACPH) rates. minimum outdoor air at 4
Even residential/commercial ACPH, room supply air at 20
recirculating type hi-wall split air ACPH for ORs, and 6 ACPH
conditioners/cassette type units (Fig. 6) of room supply and 2 ACPH
with zero outdoor air are quite popular of outdoor air for ICUs.
in ICUs of smaller healthcare facilities. Both ASHRAE 170 and NBC
of India suggest that air
exhaust and intake points
should be separated by at least
8 m distance.
ASHRAE HVAC Design
Manual for Hospitals and
Clinics [4] says that use of
standard recirculating room
HVAC units are not accepted
for ICUs.
2 Air filtration 37% of the hospitals from the sample ASHRAE HVAC Design
in operation are using HEPA Filters (MERV 17) in Manual for Hospitals and
rooms and ORs, while others are using duct Clinics and NBC of India
ICUs mounted fine filters (MERV 14). Some suggest MERV 14 filters for
are using duct mounted MERV 14 filters general ORs and ICUs. They
with standard package air conditioners. suggest HEPA filters in
Many ICUs, PICUs, NICUs and even orthopaedic ORs and bone
some ORs are using packaged air marrow/organ transplant
conditioners with MERV 7/MERV 14 rooms and also in pressurized
filters, though the evaporator fans of protective environment (PE)
these units do not develop adequate rooms.
static pressure required for use with The Facility Guidelines
MERV 14 filters in supply air duct. Institute (FGI) suggests a
In some cases, common PAC units are filtration level of MERV 14 for
being used for OR, Recovery Room, all patient care areas, whether
ICU and patient ward. in clinics or in full-service
hospitals.
(continued)
62 P. K. Sen and P. Sen

Table 1 (continued)
Feature Observation Recommendations
3 Room air Many ICUs, and even ORs, are using NBC of India recommends
supply continuous grille (Fig. 7) for inline that supply air outlets shall be
system. supply and return air. located at, or near the ceiling,
Locations of supply air grilles in many and return/exhaust be collected
ICUs are right over/near the patient bed. near the floor level to ensure
clean conditioned air to move
through the patient/working
space before it collects room
particles and moves to
return/exhaust at floor level.
ASHRAE HVAC Design
Manual for Hospitals and
Clinics says that patients can
be especially sensitive to cold
air currents from a supply air
diffuser
4 Pressurization Most ORs have been designed to ASHRAE 170 suggests both
maintain ‘+ve’ pressure. But ORs and ICUs shall have
over-pressure monitoring device (Fig. 5) positive pressure, whereas
is present only in 25% of the places. NBC of India suggests
Most ICUs are having dormitory type positive pressure for ORs and
layout with no positive/negative neutral pressure for ICUs and
pressure rooms. There are some curtain recovery rooms.
partitioned spaces (Fig. 6) in some of ASHRAE HVAC Design
these open plan ICUs. A few of them Manual for Hospitals and
have separate once through supply air Clinics suggests continuous
system to use them as ‘−ve’ pressure monitoring of pressurization in
rooms. ‘+ve’/‘-ve’ pressure rooms.
Some ICU floors have a few rigid NBC of India, however,
partitioned ‘+ve’ and ‘−ve’ pressure suggests pressure verification
rooms. But the return air (RA) from semi-annually.
these rooms are taken in a common duct There is no guideline on
and re-circulated through a common air whether, or not, ICUs shall
handling unit (AHU), which is also have rigid partition. A number
catering to the adjoining dormitory type of professional and scientific
ICU floor. bodies now emphasize the
importance of rigid isolation
facilities in ICUs—at least one
cubicle for high-risk patients
per eight ICU beds.
5 Ducted return Return air is not ducted in many ORs NBC of India suggests that
air and ICUs. Space above false ceiling is both supply air and return air
used as return air (RA) plenum. shall be ducted for critical
In some cases, even after ducting the areas.
room return air to AHU rooms, the RA NBC of India also suggests
is left open in the AHU rooms, which that access to equipment
have free access rooms shall be controlled.
(continued)
Hospital Indoor Air Quality in Respect to Transmission … 63

Table 1 (continued)
Feature Observation Recommendations
6 Use of UVGI and PCO units are being used in NBC of India suggests their
ultraviolet some ICUs, HDUs and ORs. They are use on evaporator coil, either
germicidal used over AHU cooling coils/SA on its upstream or downstream
irradiation grilles/RA duct, or at upper level of OR side.
(UVGI) and and ICU floors.
photocatalytic
oxidation
(PCO) units
7 Other Only a few hospitals conduct periodic NBC of India suggests that
observations particle count on indoor air of ORs and testing, adjusting, balancing
ICUs to assess bacteria level. (TAB) and evaluation of IAQ
shall be performed and
recorded once every year.
Fumigation of ORs and ICUs are rarely National Accreditation Board
done. for Hospitals & Healthcare
Providers (NABH), India,
suggests fumigation in the
high-risk areas like ICU,
PICU, NICU, labour room and
OT.
Most AHU rooms are used as storage NBC of India cautions that air
space for redundant handling unit rooms shall not
material/filters/components, be used as a storage space for
installation/maintenance tools and even storing files and waste
housekeeping accessories, like mops, materials.
brooms, spades and buckets.
Even a data server has been installed
inside the AHU room of PICU and
NICU of the paediatric centre of a
hospital.
Outdoor air intake, in one case, has been ASHRAE 170 suggests that
found to be close to cooling tower. outdoor air intakes for air
handling units shall be located
at least 8 m away from cooling
towers and all exhaust and
vent discharges.
Maintenance work over false ceiling NBC of India suggests that this
was found being done in one working should be done by sealing off
ICU without any sealing of the work the areas to make certain that
area. airborne maintenance debris is
unable to get into the air.
Soiled scrubs are dumped in one corner ASHRAE 170 suggests that
of the corridor of OR and recovery soiled utilities shall be kept in
room area a negative pressure room with
100% exhaust.
64 P. K. Sen and P. Sen

Fig. 5 Room pressurization monitor outside door (circled red)

Fig. 6 Curtain partitioned ICUs with commercial air conditioners

to build a negative pressure isolation room cannot eliminate chances of propagation

of infection within the ICU complex. Though there is no definite recommendation
in place, use of rigid partitioned cubicles in ICUs are getting popular. This may be
costly, but is definitely a step forward towards infection control in ICUs. Positive
pressure and negative pressure rooms should have solid partitions, and be equipped
with separate individual air systems, instead of running it through a common air
handling unit. In case, a single room is used as both ‘−’ve and ‘+’ve pressure rooms,
it should be properly disinfected before switching its use from ‘−’ve pressure to
‘+’ve pressure application.
Hospital Indoor Air Quality in Respect to Transmission … 65

Fig. 7 Continuous supply and return air grille in an ICU

Location of supply air grilles over a patient’s bed may make patients cough and
sneeze, and release infectious droplets in the air. Using continuous grilles for inline
supply and return air will mix up supply air with all the pathogens in the room (Fig. 7)
before it reaches the patient level. Hence, supply air should be from the top and return
air from bottom as suggested by the codes.
Using the space above false ceilings as return air plenum may induct moisture
in this negative pressure space from the surrounding areas. This may lead to damp
patches leading to growth of moulds and spores, which may finally get into the room
air system. Both supply and return air in hospitals should be ducted. The ducting
should be checked for leaks and connected directly to air handling units instead of
leaving return air open in the AHU rooms.
UVGI and PCO devices maybe used to irradiate static parts, like coils, filters
and drain pans, which normally collect the room micro-organisms. Trying to target
micro-organisms in airborne condition in ducting, or room air by UVGI/PCO units
is unlikely to be effective. Lockout switches should be used to switch off UVGI/PCO
units before accessing the air handling units.

8 Conclusion

Healthcare-associated infections are major concern for healthcare facilities in any

country. The threat has got even bigger with the emergence of drug-resistant infection.
Though new standards, protocols and thoughts are coming in to mitigate the
problem of healthcare-associated infections, a large number of healthcare facilities
(particularly the old ones) all over the world are lagging behind. There is a need for
their review and upgradation in light of current norms.
Prevention of HAIs is possible, but it will need a conscious effort from all indi-
viduals including clinicians, healthcare administrators, system (including HVAC)
teams, public health officials, quality improvement groups and the government bod-
ies. All should work together towards improving hospital indoor air quality, which
in the long run will serve in protecting the patients.
66 P. K. Sen and P. Sen

Finally, formation of a regulatory body for monitoring and regulating HVAC

systems and IAQ standards in healthcare system will help in streamlining this effort.

References

1. Kowalski W (2007) Air-treatment systems for controlling hospital-acquired infections. HPAC

Engineering 79
2. World Health Organisation—Healthcare associated infections FACT SHEET
3. Centre for Disease Control (CDC), USA—https://www.cdc.gov/hai/surveillance/index.html
4. ASHRAE HVAC Design Manual for Hospitals and Clinics, Second edition
5. Product brochure, Aeropure UV System Pvt. Ltd. Pune, India
6. National Building Code of India (2016)
7. Prevention of Hospital–Acquired Infection, A Practical Guide (2nd Edition, 2002), World Health
Organisation
8. ICU Planning and Design in India—Guidelines 2010, Guideline Committee, Indian Society of
Critical Care Medicine
Environmental Monitoring of PM2.5
and CO2 in Indoor Office Spaces
of Delhi, India

Akansha Gupta, Radha Goyal, Priyanka Kulshreshtha and Ashish Jain

Abstract Delhi ranks highest among the most polluted city in the world in terms of
air pollution. Its health impact may include diseases like asthma, lung cancer, COPD,
increased long-term risk of cardiopulmonary mortality. Degraded indoor air quality
inside commercial buildings such as offices may affect the health of the workers
and can indirectly affect their productivity. In the present study, indoor air quality
has been studied in four different air-conditioned office buildings located in Delhi
NCR for the criteria pollutant PM2.5 and the CO2 as ventilation parameter. The total
hazard ratio indicator has also been calculated from the data of PM2.5 and CO2 for all
selected office premises. The results of the study show the highest concentration of
PM2.5 in building A1 (116.5 ± 67 µg/m3 ) and highest CO2 concentration in building
A2 (1600 + 30.5 ppm). Higher concentration of PM2.5 in building A1 could be
due to its maximum proximity to urban busy roads and poorly maintained HVAC
ducting system, which may lead to infiltration and more leakages of PM2.5 from
outdoors. Similarly, the highest concentration of CO2 in building A2 could be due
to insufficient ventilation condition. In each studied building, the concentration of
CO2 and PM2.5 are recorded to be higher than the NAAQS and ASHRAE standards.
The health hazard ratio indicates that both CO2 and PM2.5 plays an important role
in determining the health of the building. However, the health impacts of increased
PM2.5 could be more severe than CO2 depending upon the sources of PM2.5 .

Keywords PM2.5 · CO2 · Offices · Indoor air quality · Total hazard ratio

1 Introduction

In 2014, World Health Organization (WHO) recognized air pollution exposure as the
single largest environmental health risk which causes one-eighth of total deaths in
2012. Currently, around 80% of the total population living in India relies on combus-
tion of biomass fuels for cooking purpose [1]. Many people link air pollution, only

A. Gupta (B) · R. Goyal · P. Kulshreshtha · A. Jain

Indian Pollution Control Association, New Delhi, India
e-mail: akanshagupta05.ag@gmail.com

© Springer Nature Singapore Pte Ltd. 2020 67

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_8
68 A. Gupta et al.

with the outdoor pollution, however, high concentrations of pollutants, commonly

occur in the indoor environment. According to the United States Environmental Pro-
tection Agency (USEPA) [1] in urban environment, the concentration of indoor air
pollutants is much higher than the outdoor pollutants which affect the quality of life
and the well-being of the population in general. People spend more than 70% of
their time indoors such as inside residential houses, school, college, commercial or
industrial buildings [2, 3]. It is ranked among the top five environmental health risks
to the public by USEPA. In India, indoor air pollution is one of the top 10 deaths,
disease risk factors according to WHO. Delhi being a metropolitan city of India ranks
highest in terms of air pollution which has caused an alarm for people and health
experts. It is estimated that in Delhi 3000 metric tons of air pollutants are emitted
everyday in which the major contribution is from vehicular emissions (67%) and
emission from coal-based thermal power plants which hold 12% [4].
Poor indoor air quality (IAQ) can be harmful to susceptible groups such as chil-
dren, elderly, and those with chronic respiratory disease and cardiovascular like
asthma. Apart from its profound effect on health, the poor indoor air quality reduces
the comfort and productivity of occupants of the building. In commercial buildings,
such as offices, poor IAQ may affect the health of the employees as well as indirectly
affect their productivity. The researches on IAQ in offices are very limited in com-
parison to the magnitude of the population in commercial buildings. Most published
literature in India has focused on indoor air pollution caused by biomass fuel burning
from traditional cookstoves. Many indoor pollutants are responsible for indoor air
pollution such as poor ventilation system, prevalent use of tobacco smoke, electron-
ics printers, furniture’s, paints, and computers in urban settings. Particulate matter
of the size 2.5 µg/m3 concentration in Delhi/NCR is the highest among many cities
around the world [5] Exposure to PM2.5 is associated with an increased long-term
risk of cardiopulmonary mortality by 6–13% and is also associated with a reduction
in life expectancy up to 20 months [6]. Due to inefficient air circulation in the indoor
environment, most of the outdoor pollutant enters inside such as building materials
(cement, wood, etc.), industrial and vehicular exhaust, etc. [7].
Ventilation plays an important factor in determining the indoor air quality in
a building, to minimize the energy cost, and minimizing the outdoor air used for
ventilation is a common practice adopted by buildings. This lead to compromising
the health and comfort of the occupants [8] CO2 concentration inside is an important
factor in determining the IAQ with respect to ventilation. CO2 has been majestically
associated with a variety of outcomes including an increase in sick leaves at an office
[9], symptoms of influenza and sick building syndrome. It may also adversely affect
human cognition and decision-making performance [10]. A study was conducted by
Allen et al. where participants were exposed to 550, 945, and 1400 ppm concentration
of CO2 for 8 h and found that cognitive function scores were 15 and 50% lower from
the concentration level at 550 ppm. This indicates that effects of CO2 on human
cognitive performance.
Thus, the indoor of the office buildings become the subject of much attention.
Various studies had been conducted on the indoor air quality in office buildings
from different parts of the world [11, 12]. However, India has few studies related to
Environmental Monitoring of PM2.5 and CO2 in Indoor … 69

IAQ in offices [13–15]. In this study, continuous (8 h/day), PM2.5 and CO2 levels
in different types of an air-conditioned office building located in Delhi/NCR during
the winter season were measured. To compare the health effects of the different
indoor environment, integrated IAQ total hazardous ratio indicator (THRI) was also
calculated. This study aims at analyzing and comparing the indoor air quality in
commercial buildings of central Delhi with its impact on health and productivity.

2 Methodology

2.1 Site Description

The present study aimed at assessing the indoor air quality in four office buildings
(A1, A2, A3, and A4) located in the commercial areas of Delhi/NCR (National Capital
Region). The study was conducted during the month of January and February 2018,
which was a critical winter period with mean ambient temperature and humidity of
14 °C and 79%, respectively.

Satellite view of Building A1 Satellite view of Building A2

Delhi Map showing the location of the sample sites

Satellite view of Building A4 Satellite view of Building A3

Fig. 1 Delhi map showing the location of the sampling sites

70 A. Gupta et al.

Table 1 Building characters of the selected buildings

Characteristics A1 A2 A3 A4
Age of building 50 years 20 years 35 years 10 years
Type of flooring Brick-walled Brick and Brick-walled Brick and
with marble concrete with with marble concrete with
flooring marble and flooring marble and
carpet flooring carpet flooring
Location of the The central part Central part of Central part of Industrial area
building of the Delhi, the Delhi, one the Delhi, two of Noida
two sides facing side of the sides of the
the busy roads building is building were
facing busy facing the roads
traffic
Number of 4 15 4 12
floors
Type of HVAC Centrally Centrally Split and Centrally
system air-conditioned air-conditioned cassette air-conditioned
two-way
air-conditioning
units
Condition of The ducting Fairly Open gallery in Fairly
HVAC system system at maintained between, which maintained
building A1 was ducting system. was the source ducting system.
very old and The building of fresh air The building
was not cleaned was negatively inside the was negatively
properly. The pressurized building. The pressurized
building was building was
negatively negatively
pressurized pressurized
Building activity Regular office Regular office Regular office Regular office
activities activities activities activities
Occupancy 34 45 56 123

Three office buildings (A1, A2, and A3) were located in central part of Delhi and
one (A4) in the Noida Region of NCR (Fig. 1). During the monitoring period, the
ambient air quality index [16] in all the locations was under unhealthy (Table 1).

3 Building Characteristics

3.1 Monitoring and Analysis

The IAQ sampling/monitoring of all four selected buildings had been conducted dur-
ing regular office hours (8 h) in weekdays. The indoor and outdoor concentration
Environmental Monitoring of PM2.5 and CO2 in Indoor … 71

Table 2 Average concentration of PM2.5 and CO2 at each location

Site Location Temp. rH (%) CO2 (ppm) PM2.5 PM2.5 I/O
(°C) indoor outdoor Ratio
(µg/m3 ) (µg/m3 )
A1 Ground 24.8 ± 1 44.8 ± 1 1578 ± 273 124 ± 26 187.53 0.66
floor
First 22 ± 2 48 + 1013 ± 197 109 ± 49 187.53 0.58
floor 6±1
A2 7th floor 24.6 ± 2 44.7 ± 3 1443.7 ± 968 74.6 ± 12 187.53 0.40
11th 24.8 ± 1 47 ± 2 1758 ± 365 73.6 ± 49 187.53 0.39
floor
A3 Ground 23.2 ± 1.5 49.6 ± 5 894 ± 159 53.3 ± 56 95.3 0.28
floor
A4 Ground 25.8 ± 1 50.6 ± 3 1918 ± 298 76 ± 31 76.0 1.07
floor
Prescribed limit 23–26b 30–70b 1000b 60a 60a
a PM
2.5 standard from National Ambient Air Quality Standard (NAAQS)-2011
b CO standard is from American National Standard Institute (ANSI)/ American Society for Heating,
2
Refrigeration and Air conditioning Engineers (ASHRAE) Standard 62.1-2007

of PM2.5 and CO2 in each building was monitored at every 5 min interval by pre-
calibrated DustTrak Aerosol Monitor II–Model-8533 (TSI, USA) and Testo IAQ
Monitor 435-2 (Testo, Vienna, Austria), respectively. The DustTrak is a real-time
optical scattering instrument that measures PM2.5 . The concentration range of Dust-
Trak is 0.001 to 150 mg/m3 with the resolution of +0.1% of reading with the flow rate
of 3.0 L/min with +5% accuracy. The DustTrak was zero calibrated before starting
of monitoring each day using zero calibrator instruments. The CO2 measurement
range of the Testo IAQ Monitor was 0 to +100,000 ppm with +75 ppm accuracy
and 1.0 ppm resolution. Indoor humidity, temperature, and air pressure were also
recorded. The 8-h average concentration along with standard deviation of all moni-
tored parameters has been shown in Table 2 along with the average indoor–outdoor
ratio which was also calculated for PM2.5 for all buildings.

4 Total Hazard Ratio Indicator

The total hazard ratio was calculated for the recorded PM2.5 and CO2 concentration
at each building and compared with reference values [17]. Mean reference concen-
tration of PM2.5 for this study was taken as 60 µg/m3 (NAAQS, 2011); whereas,
that of CO2 was considered as 1000 ppm [18]. The hazard ratio for each air quality
parameter, i.e., PM2.5 and CO2 (HR) were calculated by dividing the average concen-
tration of selected air quality parameter, by its corresponding reference concentration
(RfC), both expressed in the same unit:
72 A. Gupta et al.

HRi = Ci /RfCi

The total hazard ratio was also calculated to assess the global inhalation exposure
risk of occupants in each studied building, for each building.

THRsite = HRi

5 Results and Discussion

According to the ambient air quality index, the ambient air in the sampled locations
was under highly or severely polluted category round the year. During the sampling
period, the average temperature inside the offices on each floor was between 22 °C
and 25 °C. The relative humidity was maintained between the limit, i.e., 30–60%
according to the ASHRAE standard, 2013. All the four sampled locations were
negatively pressurized; therefore, it can lead to contamination of indoor air with
suspended particles or other particulate pollutants from the ambient air infiltration.
In all the sampled locations, windows were closed properly and there was no
source of infiltration from them. However, in each building, there was no air curtain
which made the main entry door is a major source of infiltration from the ambient
air. The data collected was analyzed in depth to conclude the findings of the study
which are discussed below.

6 Indoor PM2.5 Concentration

In all the sampled location, the indoor concentration of PM2.5 was recorded higher
than the standards laid by NAAQS, i.e., 60 µg/m3 due to higher ambient concentra-
tion. The average concentration of PM2.5 at both ground (124 ± 26 µg/m3 ) and first
floor (109 ± 49 µg/m3 ) of A1 building was recorded to be highest among all the
buildings, i.e., 116 µg/m3 . This could be due to its highest proximity from busy roads
and poorly maintained HVAC system. Further, the concentration at ground floor was
higher than the first floor due to higher occupancy level and infiltration through the
front and back door (entrance). The air-conditioning system was mostly switched
off during the monitoring period, which may lead to lower circulation of air and
accumulation of PM2.5 levels. The PM2.5 levels in buildings A2 (7th Floor), A2 (11th
Floor), A3 and A4 are 74.6 ± 42 µg/m3 , 73.6 ± 49 µg/m3 , 53.3 ± 56 µg/m3 , and
76 ± 31 µg/m3 , respectively. Building A3 reported the lowest indoor PM2.5 levels
compare to others. This may be due to building design and ventilation system, which
allows proper circulation of the air [24, 25]. The site also installed with exhaust fan,
which helped to reduce the indoor PM2.5 levels. In buildings, A2 and A4 indoor
Environmental Monitoring of PM2.5 and CO2 in Indoor … 73

PM2.5 levels are comparatively higher. The observation datasheet indicates that the
building A4 was having the highest occupancy and was fully carpeted, which may
induce more indoor PM2.5 levels.

7 Indoor CO2 Concentration

The CO2 concentration indoor is the surrogate index of ventilation in an occupied

enclosed space. The ASHRAE recommends that indoor air CO2 levels should be
1000 ppm (ambient + 645 ppm). The average CO2 level in all the buildings except
building A3 (894 ± 159 ppm) was exceeding the prescribed limit by ASHRAE
(Table 1). It could be due to the passageway which was acting like a ventilation shaft
and helping in maintain the CO2 concentration exhaled by the occupants within the
permissible limits. The highest CO2 levels were reported in building A4 1918 ±
298 ppm due to the highest occupancy (123 employees) and no dedicated treated
fresh air ventilation system installed in the building. The CO2 concentration at A1
building was recorded 1578 ± 27 ppm and 1013 ± 197 1013 ppm, respectively at
ground and first floor. In building A2, the CO2 levels were recorded as 1443.7 ±
968 ppm at 7th floor and 1758 ± 365 ppm at 11th floor which makes the existing
ventilation system inadequate for the present occupancy level [26, 27].
The CO2 monitoring results also show that CO2 concentration was continuously
increased after post lunch period, i.e., after 2:00 PM (Fig. 2). This could be attributed
because of the accumulation of the CO2 concentration over the period of time, effect
of food intake which leads to higher exhalation of CO2 by the occupants [19] and

Fig. 2 Time scale graph of the CO2 level for each sampled location
74 A. Gupta et al.

also the movement of visitors inside the buildings increases in the afternoon hours
in comparison with morning hours.

8 Indoor/Outdoor Ratio Analysis

The I/O ratio for the PM2.5 levels was found to be highest in building A4 (1.07),
which indicates that there is indoor PM2.5 sources exist in the building apart from
infiltration from outdoors. The I/O ratio of building A1 of ground and first floor, A2
7th and 11th floor and A3 are 0.66, 0.58, 0.40, 0.39, and 0.28, respectively which
indicated that the major source of increase in PM2.5 concentration indoor was due to
higher concentration at the ambient level.

9 Total Hazard Ratio Indicator (THRI)

With the reference concentration of PM2.5 and CO2 for daily exposure of 8 hours, the
total hazard ratio of indoor air pollution was calculated at each building (Table 3). It
was based on the non-carcinogenic risk assessment of the pollutant PM2.5 and CO2 .
The HR of PM2.5 was highest at A1 building among all the buildings. However, the
HR of CO2 was significantly higher at the Y1 location of the A2 building. The Indoor
THRI value was highest at A1 and A4 buildings. In building A1, highest THRI is
due to highest PM2.5 concentration, whereas in building A4, it is due to highest CO2
levels. The calculated values of THRI at all study sites were much higher than earlier
reported study [17, 20] in office buildings in Delhi and school in Italy.

Table 3 Total hazard ratio of the sampled buildings

Site Location HR THR THRI
PM2.5 CO2
A1 Ground floor 2.1 1.6 3.6 3.2
First floor 1.8 1.0 2.8
Total 3.9 2.6 6.5
A2 7th floor 0.8 2.3 3.1 3.1
11th floor 1.8 1.4 3.2
Total 2.6 3.7 6.3
A3 Ground floor 0.9 1.0 1.9 1.9
A4 Ground floor 1.3 1.9 3.2 3.2
Environmental Monitoring of PM2.5 and CO2 in Indoor … 75

10 Conclusion

The results of IAQ monitoring and assessment study conducted in four air-
conditioned office buildings in Delhi NCR concludes that all the studied four build-
ings were violating the standards for CO2 and PM2.5 levels as prescribed by ASHRAE
and NAAQS, respectively. The higher PM2.5 in all buildings was due to higher ambi-
ent outdoor concentrations. The buildings with more proximity to the roads (building
A1) and with more prominent indoor sources (building A4) were having compara-
tively higher PM2.5 concentration compare to others. Poorly maintained air condi-
tioning and ducting system (building A1) were also one of the main causes of higher
indoor PM2.5 levels. The results of CO2 monitoring also conclude that indoor CO2
concentrations are surrogate index of ventilation in occupied indoor spaces as the
building with highest occupancy (A4) found to have highest CO2 levels [21, 22].
Exhaust fans and proper shafts and vents in the building design (building A3) helps
circulation of air and in reducing the CO2 levels. The total hazard ratio indicator was
found to be equally high in building A1 and A4. However, the impacts of poor IAQ on
occupants will depend upon the sources of PM2.5 inside the building if compare with
equal THRI due to CO2 concentration. Further research study is needed to identify
the sources of PM2.5 inside the selected indoor microenvironments.

References

1. EPA Indoor air quality (2013) http://www.eea.europa.eu/signals/signals-2013/articles.

Accessed on Feb 2018
2. Fuentes-Leonarte V, Ballester F, Tenias JM (2009) Sources of indoor air pollution and respi-
ratory health in preschool children. J Environ Public Health. 727516. https://doi.org/10.1155/
2009/727516
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Examination of Particle Characteristics
and Quantification of Emission Factors
for Smoke Generated from a Popular
Indian Incense Burnt in an Experimental
Chamber

Anubha Goel, Radhika Mundra and Deepshikha Ola

Abstract Smoke released from the burning of incenses, a quotidian practice in India,
is found to contain many toxic chemicals on particles making it a prominent source
of indoor air pollution. This study analyzes the smoke and ash particles emitted from
a popular incense brand in India, inside an experimental chamber. Emission factor
(EF) for PM3.2 generated from burning the incense is found to be 12.5 ± 4.2 mg/g
which is higher than the EF of biomass like sugarcane, rice straw and fuelwood
(range: 1.69–10.9 mg/g). This EF value is either in the same range or higher than
some of the incenses from Japan, Taiwan, and Thailand. From 60 to 70% of the
PM3.2 mass collected consists of particles less than 1 µm in size. The maximum
particle number count emitted from the incense exceeds 107 which is three orders
of magnitude (i.e., 103 ) higher than the number count reported in another study
from Italy (104 ). The composition of water-soluble ions and particle-bound metals
in the smoke is similar to that reported for incense-based studies worldwide. This
is the first study in India focusing on emission characteristics from burning incense
in an experimental chamber, eliminating any external interference. Toxic elements
like iron, zinc, and lead, affecting health substantially, on regular exposure are also
detected. Studies have revealed that the toxicity associated with incense emissions
can be higher than cigarette smoke. More comprehensive chemical analysis of the
incense smoke and relevant health risk exposure is highly recommended.

Keywords Incense · Chamber study · Emission factor · Particle count

A. Goel · R. Mundra · D. Ola

Department of Civil Engineering, IIT Kanpur, Kanpur 208016, India
A. Goel (B)
Center for Environmental Science and Engineering (CESE), IIT Kanpur, Kanpur 208016, India
e-mail: anubha@iitk.ac.in

© Springer Nature Singapore Pte Ltd. 2020 77

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_9
78 A. Goel et al.

1 Introduction

Incense burning has been a part of ceremonial and ritual practices for centuries [3]. It
is burnt in various forms like sticks, dhoops, cone, and joss sticks for deity worship,
religious practices, and for aromatic purposes at homes [1, 6, 10].
Studies reveal that the burning of incenses can generate extensive amounts of
particulate matter, chemical and gaseous pollutants [2]. The compounds detected in
the smoke include fine size particulate matter, oxides of carbon and nitrogen, heavy
metals, and black carbon and are known to have effects on the environment as well as
the health of the people. Fine and ultrafine particles are known to be functional carriers
of toxic compounds (PAHs, VOCs, and metals). These small particles penetrate more
efficiently into the respiratory tract than the coarser ones and can cause biological
changes inside the cells. Incense smoke is reported to be more toxic than cigarette
smoke [9, 10].
The chemical composition of the incense smoke is crucial in determining the
extent of the risks associated with exposure. Such studies on chemical characteriza-
tion of incense smoke alone with no interferences have been lacking in India. The
primary objective of this study is to quantify emissions of particles from burning
of commercially popular incense in an experimental chamber. Parameters examined
include particle count and mass, water-soluble ions, and elements present.

2 Methodology

A commercially popular incense was chosen according to the survey conducted in

shops and information available online. Physical characteristics of the incense, i.e.,
average values obtained from six separate incenses from the same box, are shown in
Table 1.

2.1 Experimental Setup

A stainless-steel closed chamber with a volume of 1.35 m3 was used for collection
of emissions generated from burning of incense sticks inside the chamber (Fig. 1).
Loss in particle mass due to sorption on chamber walls was observed to be minimal
and is assumed not to impact particle levels captured significantly. The chamber has

Table 1 Physical
Combustible portion Incombustible portion
characteristics of the incense
used for the experiment Length (cm) Weight (gm) Length (cm) Weight (gm)
14.70 ± 0.179 0.79 ± 0.031 5.48 ± 0.172 0.06 ±0.011
Examination of Particle Characteristics and Quantification … 79

Fig. 1 Experimental Setup

three nozzles each on two opposite sides and a small gate on the third side. High-
Efficiency Particulate Air (HEPA) absorber was connected on one face to clean
the chamber. On the other side, Optical Particle Counter (OPC), for particle count
measurement, and a cascade impactor MOUDI for the collection of particles were
connected through different nozzles. A mini fan was kept inside the chamber to
ensure that continuous circulation of air was maintained. The particle-free air was
pushed inside the chamber before every run to purge all the particulate impurities,
and particle count was monitored continuously on OPC. The process was stopped
when the particle count in OPC stabilized to a minimum level of below 103 (the
“blank value”). The burning of incense was started in the chamber after this.

2.2 Sampling Method

The sampling was conducted in the month of December 2017 when temperature
ranged around 23 ± 2 °C. The humidity range recorded inside the chamber was 42–
52%. A five-stage Cascade Impactor MOUDI and Optical Particle Counter (OPC)
were used to collect the particles and to determine the number concentration of the
particles emitted by the incense smoke, respectively. The size of the particles collected
80 A. Goel et al.

by MOUDI was in the range of fine particles with a diameter of 0.18–3.16 µm while
the particles detected by OPC were in the range of 0.3–10 µm.
After the minimum particle count had been reached, as noted through OPC, pre-
weighed incense stick was ignited and placed in the middle of the chamber on a
blank paper. The blank paper was pre-weighed and used to collect the ash. The time
of start and OPC reading were noted just after the closing of the door. This was
denoted as “start value”. MOUDI was connected to one of the outlet nozzles and was
turned on approximately after 45–50 min of start time when the incense had burnt
completely. With time, the particle count started decreasing to reach its “blank value”.
At this point, MOUDI is assumed to have collected all the particles present in the
chamber emitted from burning incense. The experiment was replicated three times.
Post-sampling, the incombustible incense, ash, and the filter papers were weighed to
determine emission factors and for further analyses.

2.3 Sample Analysis

Filters from differnet stages of MOUDI were collectively used for the extraction
of water-soluble ions (WSI) and particle-bound metals to determine the cumulative
emission from 0.18–3.2 µm. The extracted samples were analyzed for water-soluble
ionic concentrations of primary cations and ions (K+ , Na+ , Ca++ , NH4 + , NO3 − ,
SO4 2− , and Cl− ) on IC (Compact IC 761 Metrohm). Elemental analysis of metals
(K, Mg, Na, Co, Cr, Ni, Pb, Al, Cu, Fe, Mn, and Zn) was carried out on MP-AES
(Agilent 4200 MP-AES, Agilent Technologies). The ions and elements chosen for
analysis are based on the results reported in other studies.

3 Results and Discussion

3.1 Emission Factor for Particles and Ash from Incense

Burning

The concentration of PM3.2 emitted from the smoke is 9.073 ± 0.191 mg/m3 . Emis-
sion factor (EF) of particulate matter is defined as the mass of the smoke particles
collected on the filter paper divided by the weight of the incense lost during burning.
Similarly, EF of ash is the amount of ash obtained by burning per gram of incense.
The average PM3.2 EF obtained for the incense is 12.5 ± 4.2 mg/g, whereas for ash
it is 26.4 ± 3.5 mg/g which is more than twice the EF of PM3.2 . The EF of PM3.2
from incense is higher than EF of PM2.5 incenses from various parts of the world
including Taiwan, Thailand (11.09–23.38 mg/g), and Italy (10–26.3 mg/g) [4, 5, 9,
12]. The EF in the study is also higher than 14 out of 23 incenses experimented by
Jetter et al. [3] which includes the incenses from India, USA, Thailand, and Canada.
Examination of Particle Characteristics and Quantification … 81

Table 2 EFs obtained

Sources Size EF (g/kg or mg/g)
through laboratory burning of
different biomasses [8] Forest biomass PM2.5 18.15 ± 14.36
Fuelwood TSP 1.69 to 5.36
Sugarcane PM2.5 2.17
Rice straw (MC > 10%) PM2.5 4.01 to 10.9
Agricultural residue TSP 9.31 ± 8.59
Dung cake TSP 12.44 ± 6.13
Agricultural biomass burning in TSP 8.03 ± 3.57
residences

From a review study [8] which reports the EFs of different types of biomass burnt
in laboratory conditions, it is interesting to note that the EF of the incense is much
higher than many primary biomass sources like forest biomass, dung cake, and agri-
cultural residue (Table 2). This implies that the incense burning is a crucial source
of smoke emission and can be of great concern like any of the stated sources.

3.2 Particle Mass and Count

The size segregated analysis of the incense smoke reveals that 60–70% of the particle
mass (PM3.2 ) is composed of finer particles with size less than 1 µm (PM1 ) (Fig. 2).
This could be an underestimation since the instrument only collected particles up to
0.32 µm. The higher the percentage of finer and ultrafine particles in the smoke, the
more health risk it is likely to possess.
OPC measures particle number count (PNC) in the range 0.3–20 µm. In all the
test runs the particle number count exceeded the instrument’s limit (2x107 ) within 30
minutes of the burning of the incense inside the chamber. This number exceeds the
maximum PNC reported by Stabile [9] for incenses and mosquito coils by at least
the magnitude of 4.

Fig. 2 Concentration of PM emitted and the % contribution of PM1

82 A. Goel et al.

Fig. 3 Water-soluble ions in incense smoke

3.3 Water-Soluble Ions and Particle-Bound Element

The major ions detected in incense smoke emission in previous studies [7, 11] have
been chosen for this study. The total EF for water-soluble ions for the incense is 2.32
± 0.25 mg/g which is almost 20% of the total PM3.2 mass. The water-soluble ions
are predominated by sodium and chlorides with the least amount of sulfates (Fig. 3).
No qualitative trend has been observed in the ionic composition of incense smoke,
and it can be said that it depends on the composition of the material used for the
manufacture of incenses.

3.4 Elements

Of the 13 elements analyzed, minerals K, Mg, and Na comprised almost 85% of the
total mass. Ni was below the detection limit in all the cases. EFs for all the elements
are presented in Fig. 4. The presence of toxic elements Pb and Cr has been reported
which can cause harmful health effects even in small quantities. Zn, Fe, and Al are
present in trace amounts. The EF of the total elements is 1.31 ± 0.13 mg/g (Fig. 4).
The qualitative composition of the elements is similar to the emission rates from
PM2.5 reported by See and Balasubramanian [7] where the authors determined the
PM2.5 emission rates of various elements released from the incense smoke. They
reported a maximum abundance of Al and Fe, after mineral elements, which is also
the case in this study.

4 Conclusion

Examination of emissions from incense burning in an experimental chamber in this

study reveals the significant contribution of PM1 in PM3.2 generated. These finer
particles are likely to have more adverse effects on human health in case of extensive
Examination of Particle Characteristics and Quantification … 83

Fig. 4 EF of particle-bound elements

exposure. Emission factors of PM2.5 are found to be higher than some prominent
biomass sources bringing to attention the need for more intensive chemical charac-
terization of the incense smoke along with other indoor pollution sources. Since no
particular trend has been observed for ash and ions and differs widely among reported
studies, we can say that the emissions are the source, or input material, dependent.
We suggest the need to closely monitor the input materials used in manufacturing
the incense and look for alternatives that are more eco-friendly on burning, i.e., they
produce less smoke and acceptable levels of toxic materials.

References

1. Dewangan S, Chakrabarty R (2013) Emission of volatile organic compounds from religious

and ritual activities in India. Environ Monit Assess 185(11):9279–9286
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coarse (PM2.5–10 ), and metallic elements of suspended particulates for incense burning at Tzu
Yun Yen temple in central Taiwan. Chemosphere 51(9):983–991
3. Jetter JJ, Guo Z, Mcbrian JA, Flynn MR (2002) Characterization of emissions from burning
incense. Sci Total Environ 295(1–3):51–67
4. Kuo S, Tsai YI, Sopajaree K (2016) Emission characteristics of carboxylates in PM2.5 from
incense burning with the effect of light on acetate. Atmos Environ 138:125–134
5. Lee S, Wang B (2004) Characteristics of emissions of air pollutants from the burning of incense
in a large environmental chamber. Atmos Environ 38:941–951
6. Liao C-M, Chen S-C, Chen J-W, Liang H-M (2006) Contributions of Chinese-style cooking
and incense burning to personal exposure and residential PM concentrations in Taiwan region.
Sci Total Environ 358(1):72–84
7. See SW, Balasubramanian R (2011) Characterization of fine particle emissions from incense
burning. Build Environ 46(5):1074–1080
8. Simões Amaral S, Andrade de Carvalho J, Martins Costa M, Pinheiro C (2016) Particulate
matter emission factors for biomass combustion. Atmosphere 7(11):141
9. Stabile L, Fuoco FC, Buonanno G (2012) Characteristics of particles and black carbon emitted
by combustion of incenses, candles and anti-mosquito products. Build Environ 56:184–191
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10. Suryawanshi S, Singh A, Verma R, Gupta T (2016) Identification and quantification of indoor
air pollutant sources within a residential academic campus. Sci Total Environ 570:46–52
11. Wang B, Lee SC, Ho KF, Kang YM (2007) Characteristics of emissions of air pollutants from
burning of incense in temples, Hong Kong. Sci Total Environ 377:52–60
12. Yang T, Lin S, Lin T, Hong W (2012) Characterization of polycyclic aromatic hydrocarbon
emissions in the particulate phase from burning incenses with various atomic hydrogen/ carbon
ratios. Sci Total Environ 414:335–342
Comparison of Efficiency of Active
and Passive Methods of Bioaerosols’
Estimation

Palak Balyan, Chirashree Ghosh, Shukla Das and B. D. Banerjee

Abstract Passive settle plate method and active impaction method are two most
commonly used methods for bioaerosols’ sampling and surveillance. Passive method
is a relatively low-cost method for bioaerosols’ surveillance. The current study
intends to compare the efficiency of active and passive methods of bioaerosol sam-
pling for temporal surveillance at different source sites. It was observed that the
temporal measurements of bioaerosol by both methods were strongly correlated.
Thus, both methods can be used for bioaerosol surveillance. The results of effect of
putative factors by both methods were relatively comparable to a larger extent. This
finding is highly significant for resource constraint setting where the use of active
method is not cost effective for temporal surveillance and research purpose.

Keywords Bioaerosols · Active bioaerosol sampling · Passive settle plate

method · Season and cascade impactor

1 Introduction

Microbial air surveillance has gained attention in recent years because of the improve-
ment in knowledge regarding potential health effects associated with them. Many
guidelines regarding bioaerosols’ exposure levels are made by various countries and
organizations [1–9].

P. Balyan (B) · C. Ghosh

Environmental Pollution Laboratory, Department of Environmental Studies,
University of Delhi, New Delhi 110007, India
e-mail: balyan.palak@gmail.com
S. Das
Department of Microbiology, University College of Medical Sciences & GTB Hospital,
University of Delhi, New Delhi 110095, India
B. D. Banerjee
Department of Biochemistry, University College of Medical Sciences & GTB Hospital,
University of Delhi, New Delhi 110095, India

© Springer Nature Singapore Pte Ltd. 2020 85

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_10
86 P. Balyan et al.

Increasing incidences of nosocomial, gastrointestinal infections had made regular

surveillance of bioaerosol in hospital setting, food processing, and pharmaceutical
industries a necessary requirement. Studies have correlated nosocomial infection rate
with number of airborne bacteria [10]. A proper identification and quantification of
bioparticles in the air are thus necessary for chalking out effective preventive and
control strategies for aerosol-borne infections.
Air sampling enables monitoring of microbial load in an environment [10]. More-
over, the microbial surveillance can also be used to check the efficiency of insulating
mechanisms, disinfectant, and sterilization techniques [10, 11]. However, standards
of air sampling are yet to be firmly established. In fact, international standards offer
various techniques with different samplers, thus leaving ambiguity regarding the
choice of technique for microbiological surveillance [12, 13].
The different methods of counting microbes which are in use are the count of
colony-forming units per cubic meter of air (CFU/m3 ); the count of CFU on settle
plates; measurement of a chemical component of the microbial cells/m3 of air; the
count under the microscope [11].
At the moment, the most common and widely used method of quantifying airborne
microbes is limited to the count of CFU [14]. The CFU count measures the microbes
which are viable, can grow, and multiply. Air sampling to measure CFU is conducted
in two ways: by active bioaerosol sampling or by passive bioaerosol sampling (settle
plate method).

1.1 Active Bioaerosol Sampling

In active sampling, a fixed volume of air is drawn by the sampling device and passed
through a collection medium. Bioaerosols thus captured are cultured and quantified
as CFU/m3 of air [10, 11]. The active method of sample collection allows sampling
of aerosols independent of its size, inertia, etc., and thus able to capture the smaller
particle missed by passive method due to low inertia. However, active samplers
are expansive, need regular calibration and sterilization. Further, a sizable num-
ber of aerosols lose their viability during active sampling, reducing the observable
bioaerosols’ count.

1.2 Passive Bioaerosol Sampling: Settle Plate Method

Passive air sampling is based on gravitational force. Petri dishes having a suitable
solid medium are exposed open to air for a stipulated period. Microbes fall onto the
Petri plate based on their inertia. Plates were incubated at an appropriate temperature
for optimum duration. Colonies grow in the plate proportional to microbial level of
the air.
Comparison of Efficiency of Active and Passive Method … 87

Settle plate is a convenient and inexpensive method and allows to obtain data from
multiple places, by different operators simultaneously, thereby opening avenues for
designing studies requiring large-scale bioaerosol sampling in a cheap, inexpensive,
and reliable way [15].
The settle plate method is said to be biased toward selective collection of those
particles large enough to be pulled by gravity or impacted by turbulence onto col-
lecting surface. This property, in fact, is advantageous in certain situations such as
operation theater, pharmaceutical, and food processing industry. Charnley [16] and
French [17] favored settle plate method in comparison to active sampling in the oper-
ation theater where type and number of bacteria falling on the wound and instrument
are of prime importance.
Conflicting results were obtained by various studies conducted to compare the
relative efficacy of active and passive methods for bioaerosol monitoring. Thus, it
is imperative to assess the effect of sampling technique on monitoring temporal
variation of bioaerosol exposure and on understanding the role of various putative
factors affecting bioaerosol exposure [12, 13, 18–20].
To achieve this, the current study intends to compare efficiency of active and
passive methods of bioaerosol sampling for temporal surveillance and to understand
the effect of putative factors on bioaerosols’ levels at two different source sites.

1.3 Methodology

Two sites namely health center and central library of a university were selected for
the study. Sampling of bioaerosol was conducted in the waiting hall of out-patient
department (OPD) of the health center and in the main hall of central library.

1.4 Sampling Procedure

The experiments were set up so as to sample air using both the methods namely
active Anderson cascade impactor and passive gravitational plate methods for a
duration of 20 min. The culturable count of aerosolized bacteria and fungi was
measured at center of each sampling site. The samplings were conducted weekly
from May 2016 to April 2017. The samples were collected between 12 o’clock
and 2 o’clock at sampling sites on consecutive days in order to minimize variation in
seasonal patterns, meteorological parameters, etc., and to avoid diurnal variation. The
Anderson impactor and Petri plate were placed at a distance of minimum 3 m in order
to avoid the effect of turbulence created by Anderson impactor. The normal activities
were allowed to be carried out during sampling so that the observed culturable count
remained near to real culturable count. The colony counts of viable bacteria and
fungi were read after 48 h and 72 h, respectively.
88 P. Balyan et al.

1.5 Statistical Analysis

The mean of culturable counts measured by both methods were calculated to analyze
the trend of seasonal variation and variability during different sampling spell within
a season, respectively. The normality and homogeneity of variance of total viable
count (TVC) data were checked by conducting Shapiro-Wilk test and Levene’s test.
Since the data was unbalanced and had significant homogeneity of variance, the
mixed model analysis of statistical package SPSS 23 was used to analyze the effect
of season and site, by both active and passive methods. Since the objective of the
study was to do a comparative analysis of TVC across different seasons and sites, both
season and sites were entered in mixed model as fixed effects. Pearson’s correlation
coefficients were measured between meteorological variables and bioaerosols’ levels
measured by both methods. Correlations were determined to compare the efficiency
of both methods in estimating the effect of putative factors on microbial counts. The
Pearson correlation coefficients were calculated between the culturable counts of
microbes measured by both methods in order to compare the relative efficiency and
reliability of passive settle plate method relative to active impaction method.

2 Results and Discussion

The bioaerosol sampling was conducted by two methods simultaneously, the passive
settle plate method and active Anderson cascade impactor method at both sites. The
average counts of bacteria and fungi at each site are shown in Figs. 1 and 2.
There were more bacteria at the health center compared to the central library
(Fig. 1a, b), whereas the fungal concentration at health center and library was
comparable (Fig. 2a, b).
The microbial (both bacterial and fungal) counts had not shown any seasonal
variation in the central library, whereas a definitive seasonal trend was observed in
the health center. The minimum microbial load in air at health center was noted
during pre-monsoon season followed by a rise in load during monsoon and post-
monsoon seasons. Microbial load was maximum during winter at health center. The
central library had not shown any conspicuous seasonal variation in both bacterial
and fungal levels, and no typical pattern was observed.
The spatial and seasonal trends observed by both methods of sampling were thus
comparable though the level varied as denomination unit and mechanism of sampling
differed with the method.
The fixed effect of season (p < 0.01 at health center and p > 0.05 at central
library) and source site (p < 0.01) on aerosolized bacteria count showed similar
statistical significance by both methods (Table 1). The fixed effect of source site on
aerosolized fungal count was statistically non-significant by both methods (p > 0.05)
(Table 1).
Comparison of Efficiency of Active and Passive Method … 89

(a) Health Centre

(b) Central Library

Fig. 1 Bacterial counts at health center and central library by both passive and active methods of
bioaerosols’ sampling

The fixed effect of season on aerosolized fungal count was significant at the health
center (p < 0.01) but not at the central library (p > 0.05). Hence, microbial counts
in the air samples and their seasonal variation at both sites varied with the location.
However, the spatial and seasonal trends observed at each site were similar by both
methods.
The effect of meteorological variables on microbial counts, calculated by both
methods, was also compared, as shown in Table 2. The correlation between the
microbial count and meteorological parameters was not uniform among two sites.
The correlations were very weak for microbial counts at central library by both
methods of sampling. Pearson’s coefficient was negative between microbial count and
temperature, and statistically significant strong positive correlations were observed
between microbial count and relative humidity at health center.
The correlation between the bacterial and fungal counts measured by passive
plate method and Anderson cascade impactor at both sites is presented in Fig. 3.
The correlations were statistically significant for both bacteria and fungi at both
sites. Strong correlations were noted between the bioaerosol level obtained by two
methods of samplings (ranged from r = 0.61 for bacteria at the central library to
r = 0.84 for fungi at the health center) despite different influences of temperature
and relative humidity noted at different land use sites (significant correlation at health
center and non-significant correlation at central library) (Fig. 3).
90 P. Balyan et al.

(a) Health center

(b) Central Library

Fig. 2 Fungal counts at health center and central library by both passive and active methods of
bioaerosols’ sampling

Table 1 Fixed effect of season and site on microbial counts

Site Passive method Active method
Season Site Season Site
Bacterial counts
Health center <0.01 <0.01 <0.01 lt;0.01
Central library >0.05 >0.05
Fungal counts
Health center <0.01 >0.05 <0.01 gt;0.05
Central library >0.05 >0.05
Significant level p < 0.05

Anderson cascade impactor method had captured more microbes in this study
as also noted in various previous studies conducted earlier. However, this fact does
not edge the use of active method as a preferred one. The quantitative comparison
between the two methods is not justified in light of fact that the two methods use
different denominating units and are based on different principles [21].
Comparison of Efficiency of Active and Passive Method … 91

Table 2 Correlation matrix of bacterial and fungal counts with temperature and relative humidity
Sites Bacteria Fungi
Passive Active Passive Active
r-value p-value r-value p-value r-value p-value r-value p-value
Temperature
Health −0.76 <0.01 −0.73 <0.01 −0.74 <0.01 −0.67 <0.01
Centre
Central 0.24 0.84 0.30 0.30 0.03 0.83 0.09 0.49
library
Relative humidity
Health 0.32 0.01 0.30 0.02 0.53 0.01 0.48 0.04
Centre
Central 0.19 0.16 0.04 0.76 −0.06 0.05 −0.08 0.54
library
Significant level p < 0.05

The settle plate method could be more informative in hospital wards and food
processing units where settling rate of microbes is more important than their presence
in the air.
In light of our findings, it can be endorsed that either method can be used for
spatiotemporal monitoring of air contamination for surveillance programs or for
conducting research on understanding the influence of various factors on bioaerosol
levels. Further, the results of past research conducted by either of the methods can be
compared and analyzed together provided that denomination units have no bearing on
objectives of research work. It justifies the use of passive plate method for bioaerosol
monitoring as a cheap and reliable method especially for spatial and temporal compar-
ison. Studies by Napoli [10] and Saha [22] also reported similar correlation between
bioaerosols’ levels obtained by both methods. On the contrary, Sayer [20] reported
active sampling to be superior to passive sampling. There is skewed distribution of
studies with regard to sampling methods used in favor of active methods. It could
be due to the fact that most of bioaerosol research studies are being conducted in
the developed countries. There is paucity of bioaerosols’ research in developing and
low-income countries. In view of this fact and findings of the present study, further
research for standardization of passive method of bioaerosols’ monitoring is hence
recommended.

3 Conclusion

The present research intended to study the relative efficiency of passive and active
method of bioaerosol surveillance. The study concludes that the temporal measure-
ment of bioaerosol by both methods was strongly correlated. Thus, both methods can
92 P. Balyan et al.

r-value = 0.86 r-value = 0.79

(a) Health center

r-value = 0.61 r-value = 0.83

(b) Central library
x axis = Passive settle plate method, y axis = Active cascade method

Fig. 3 Correlation matrix of microbial counts measured by active and passive methods of
bioaerosols’ sampling

be used interchangeably for bioaerosol surveillance. The results of effect of putative

factor by both methods are relatively comparable to a large extent. This finding is
highly significant for resource constraint setting where the use of active method is
not cost effective for temporal surveillance and research purpose. Research for stan-
dardization of low-cost passive plate methods to develop standard guidelines is thus
highly recommended.

Acknowledgements Authors are thankful to Department of Science and Technology (DST) Purse
Grant and Ministry of Environment, Forest and Climate Change (MoEF), Government of India, for
supporting the research work financially.
Comparison of Efficiency of Active and Passive Method … 93

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Impact of Lighting on Performance
of Students in Delhi Schools

Pratima Singh, Renu Arora and Radha Goyal

Abstract Importance of lighting on human health and performance is well estab-

lished. Optimal lighting conditions help in enhancing the performance and well-being
of people. Whereas, glare caused by bright and direct lighting may become source
of discomfort and impair visual performance. A very little research data is available
correlating lighting with performance of young children in schools. Realizing the
need of research in this area, the present cross-sectional study (2016–2017) investi-
gated the impact of classroom lighting on the performance of 738 students, studying
in schools in Delhi, selected through systematic sampling technique. The classroom
lighting levels were represented through illuminance data recorded using lux meter
‘Testo-545’. Students’ performance was assessed by d2 test for speed and accuracy
developed by Brickencamp and Zilmer. Questionnaire-cum-interview was used as
data tool for assessing students’ perception towards classroom lighting. The results
conclusively revealed that classroom lighting had significant impact on the concen-
tration and performance of the students (P < 0.05). Classroom illuminance between
250 and 500 lux was linked with increased concentration of the students, which
translated into higher scores and increased performance. Based on the results it is
recommended to increase natural light inside classrooms through strategically placed
windows and doors or artificial light through appropriate lamps and luminaires. The
findings further indicate the need for extensive and detailed research in the area of
lighting in educational spaces.

Keywords Lighting · Illuminance · Indoor environmental quality · Glare ·

School · Performance · Perception

P. Singh (B) · R. Arora

Institute of Home Economics, University of Delhi, F-4, Hauz Khas Enclave,
New Delhi 110016, India
e-mail: pratima.singh@ihe.du.ac.in
R. Goyal
Indian Pollution Control Association, Hargobind Enclave, New Delhi 110092, India

© Springer Nature Singapore Pte Ltd. 2020 95

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_11
96 P. Singh et al.

1 Introduction

Good quality lighting is critically important to carry out tasks efficiently and safely in
work and educational environment. Significance of lighting is widely researched and
claimed to be vital for occupants’ performance. Classroom lighting does not only
help students to see instruction-board clearly but also assist them to comfortably
read and write during classroom learning activities [1]. Also, lighting helps to cre-
ate visually stimulating environment which enhances the appearance of the indoor
space [2]. Research studies have shown influence of lighting on biological health
of humans such as circadian rhythm, heart rate, and blood pressure. Lighting may
stimulate certain psychological behaviours like mood swings. Besides emotional and
biological effects, studies have indicated positive effects of lighting conditions on
speed and accuracy of completion of tasks and productivity of the occupants [3, 4].
However, most of these empirical studies have focused on offices, retail, and other
work environments [4]. Research data on the effect of lighting in educational spaces
are sparse even today. Understanding the relationship of lighting and environment
can help to improve indoor environmental quality for better performance of students.

1.1 Impact of Lighting on Human Health

Interest of researchers on the effects of lighting on physical and psychological health

of human being is rapidly advancing. The positive health effects of natural light were
even acknowledged by Egyptians, Romans, and the ancient Greeks, who worshipped
the Sun Gods. Even in India during the Mughal era, environment-friendly techniques
of using Jaali-Numa (perforated) walls or windows were used to increase the entry
of daylight and control glare inside the buildings [5]. The significance of lighting
goes beyond its functional aspect.

1.1.1 Effect on Physical Health

Lighting must be designed in a human-centric way, keeping in mind the tasks to be

performed and comfort of all the occupants. Many research studies have claimed
that insufficient illuminance, flickering of lights, and absence of lighting controls
in buildings can lead to health problems like eye strain, headache, increased body
temperature, etc. [6, 7]. On the other hand, excessive light and luminance contrasts
can cause glare which can cause eye strain, blurred, and weak vision.

Effect on Cognitive Health and Circadian Rhythm

Light is known to control circadian rhythm in humans, by regulating stress hormone
cortisol and sleep hormone melatonin. These hormones control an organism’s internal
clocks [8] (Fig. 1). Researches have indicated the effect of inadequate daylight on
Impact of Lighting on Performance of Students in Delhi Schools 97

Fig. 1 Typical circadian pattern in humans [10]

reduced circadian cycle, as a result of which melatonin is secreted at wrong times

causing chronic fatigue, depression, and other illnesses. Children need to receive
adequate light in the morning hours and avoid light with similar wavelength in the
evening to maintain a regular sleep cycle pattern. As majority of their daytime is
spent in schools, the windows of the classrooms must be designed to allow sufficient
daylight, as natural light helps in synchronizing internal body clock of human beings.
Daylight controls circadian rhythmicity which regulates many cognitive processes
in humans such as attention, concentration, and memory [9].

Psychological Effects of Lighting

Other than physical health effects, the psychological impact of lighting is more
profound. Appropriate lighting and colours may uplift mood and make people feel
joyful and happy [11]. On the other hand, poorly lit spaces may cause feeling of dull-
ness, irritation, lethargy, and depression. The seasonal depression usually profound
amongst people living in northern latitudes, also referred to as seasonal affective dis-
order (SAD), which is caused by lack of daylight and is an obvious evidence which
proves the psychological effects of natural light on humans [12]. Furthermore, many
research studies indicate that presence of daylight enhances mental performance and
decreases aggressive behaviour [13].

1.2 Lighting and Performance

Provision of adequate lighting in learning places is important because of the direct

relationship of good lighting with performance of the students [8, 14]. The purpose of
lighting in educational spaces is to create visually stimulating environment in which
98 P. Singh et al.

the act of learning can be done in the best way with minimal discomfort. A study
by Heschong Mahone Group indicated positive correlation between daylight and
academic performance of the students [15]. It is well recognized that good quality
lighting increases the comfort of students and that comfort often translates into higher
scores, increased performance [16, 17], and concentration [4].
However, more lighting does not always have positives effects on occupants.
Excessive light, flickering of bulbs or tube-lights, and glare produced by the fluores-
cent lighting and interactive boards can become the cause of discomfort, headaches,
and impaired vision, and may influence cognitive performance of the students in
schools [7]. A Research conducted in Brazilian classrooms provided an upper limit
to classroom lighting, above which the lighting had negative effects [18]. Along with
the appropriate lighting levels, uniformity of lighting throughout the classroom is
also important to create pleasant and comfortable work environment.
Significance of natural or daylighting is acknowledged more than artificial lighting
[19, 20]. However, when daylight is not sufficient to provide comfortable visual
environment, it must be supplemented with artificial light [21].

1.3 Lighting Recommendations and Guidelines

for Educational Spaces

Lighting and illuminance are the most important physical parameters of indoor envi-
ronmental quality of any school or classroom. Carefully designed artificial light
and provision of adequate natural light are prerequisites of any intellectual learning
space. As cited by Pulay (2010), Benya defined a well-lit classroom as the one which
includes controlling glare, having balanced brightness and higher reflectance [22].
Students engage in varied activities in classrooms like reading on desks, learning
from projectors and blackboards, and thus, they often have to shift their gaze up
and down. Therefore, all-around optimal lighting on walls as well as on desks is
very critical and important [22, 23]. While designing the learning spaces focus on
appropriate lighting, occupants’ comfort and energy usage must be kept in mind for
providing optimal visual environment.
Many research studies suggest that for appropriate lighting and visual comfort,
the illuminance of school classrooms must be 300 lx or more at any point on the work
surface. However, where lighting of a space is achieved by a combination of daylight
and artificial light, the minimum illuminance of 350 lx is recommended in ATL-
the Education School Premises Regulations, 1981 [24]. Similarly, National Building
Code (NBC-2005) of India has recommended a range of illuminance (200 lx-300 lx-
500 lx) for all type of classroom activities [25]. However, NBC does not provide rec-
ommendations for specific classroom-related tasks. The European norm EN 12464-1
provides guidelines for maintaining task-based illuminations inside classrooms [26].
Table 1 illustrates the summary of lighting and illuminance recommendations and
guidelines for schools and classrooms given by various organizations.
Impact of Lighting on Performance of Students in Delhi Schools 99

Table 1 Illuminance recommendations and guidelines for schools and classrooms

Standard Recommended Task Source
illuminance (in lx)
National Building Code, 200-300-500 All classroom tasks [25]
2005, India
European norm EN 500 Blackboard tasks [26]
12464-1 300 Writing, reading, drawing
300 Looking at projector
screen
ATL-The School 350 All classroom tasks [24]
Education Premises
Regulations, 1981
CIBSE-2006 300 General teaching spaces [7, 27]
500 Seminar rooms, teaching
spaces, and lecture halls

Though it is evident from the reviewed literature that lighting has an important role
to play in indoor environment, availability of evidences on the extent to which lighting
affects school performance of young children is still sparse and more attention of
researchers needs to be drawn in this area. Hence, the present research was designed
to study the impact of classroom lighting on the performance of the students in
schools located in Delhi.

2 Methodology

This cross-sectional research study tried to identify the impact of classroom lighting
on students’ perceptions and performance. The data was collected from four private
schools located in Delhi (Fig. 2). The research encompassed of the specific objectives
of studying the design features of the classrooms of the selected schools; monitoring
existing lighting/illuminance in the classrooms of the selected schools; and assessing
students’ perceptions and satisfaction regarding their classroom lighting conditions.
Students’ concentration and performance (CP) was also assessed to find out the
impact of classroom lighting on their performance scores (CP scores).
The information regarding students’ perception was assessed through structured
questionnaire-cum-interview tool administered on 738 students (384 students in non-
winter season and 354 students in winter season) selected through systematic sam-
pling technique. Further, students’ performance and concentration were assessed by
using a standardized d2 test, which was created by Brickencamp and Zilmer in 1998.
The test is also known as cancellation task and takes approximately 8–10 min to
complete. The test consisted of 14 rows of 47 randomly mixed letters: p or d. In
each line, the letters d and p were printed with each up to two marks above or under-
neath the letters. All the d’s with two marks altogether were to be crossed out within
100 P. Singh et al.

Fig. 2 Location of selected schools A, B, C, and D on map of Delhi [28]

Fig. 3 Illuminance monitoring in classroom of school B using lux meter ‘Testo-545’

20 s per line. The attention score of the students was calculated from the number of
d’s crossed out correctly minus the number of letters crossed out incorrectly (error
of commission), which is also termed as concentration performance (CP). It is a
measure of coordination of speed and accuracy of performance.
The lighting levels were represented through illuminance data collected from
three classrooms of each school in both non-winter and winter seasons during the
year 2016–2017. The illuminance monitoring was done thrice a day, i.e., at 9:00 am,
Impact of Lighting on Performance of Students in Delhi Schools 101

Table 2 General observations of the selected schools

School Classroom Direction of windows Area (m2 ) Window-to-floor area ratio
(WFR)
A A1 166° North-East 37.51 01:24
A2 9° North 42.31 01:20
A3 96° North 37.76 01:21
B B1 214° South-West 68.89 01:12
B2 109° South 47.19 01:06
B3 185° South 54.72 01:06
C C1 185° South 28.07 01:20
C2 343° North 35.61 01:15
C3 190° South 29.75 01:25
D D1 204° South-West 41.37 01:26
D2 223° South-West 41.37 01:26
D3 258° West 41.37 01:26

at 12:00 noon and at 2:00 pm in each selected classroom using lux meter ‘Testo-
545’ (Fig. 3). The instrument works on the principle of silicon photodiode and has
measurement range from 0 to 100,000 lx with the accuracy of ±5%.

3 Results and Discussion

3.1 General Classroom Observations

Structured checklist was used for studying design features of the classrooms of
selected schools. The results highlighted that the area of the classrooms ranged from
28.07 to 68.89 m2 . It was also found that window-to-floor area ratios (WFRs) of
classrooms of schools A, C, and D were well within recommended range (more than
1:10), except school B (Table 2). School B classrooms had very narrow windows
limiting the entry of daylight. The glass used on the windows was also glazed, and
hence entry of sunlight was restricted in school B classrooms.

3.2 Comparison of School-Wise Lighting Data

with Recommended Limits

It was observed that the highest mean illuminance in non-winter season was in class-
room D1 (991.1 lx) and in winter season, it was in classroom A3 (1145.3 lx). The
lowest mean illuminance in both the seasons was recorded in classrooms of school B,
102 P. Singh et al.

Fig. 4 Class-wise mean illuminance in non-winter season and winter season

i.e., classroom B2 had 190.2 lx in non-winter season and classroom B3 had 218.1 lx
in winter season (Fig. 4). Overall, it was observed that in winter season, approxi-
mately 58% classrooms had lighting levels within the prescribed range (200–500 lx)
as suggested by NBC-2005. However, in non-winter season, only 33% classrooms
had lighting within recommended range. Almost 50% of the classrooms were over
illuminated.
NBC-2005 has recommended lighting/illuminance levels between 200 and 500 lx
to carry out all type of classroom activities comfortably [21]. Illuminance levels
inside the schools were analyzed in detail to assess the existing lighting conditions
inside the school classrooms and whether they fall within the recommended range
or not. In non-winter season, the mean values of illuminance inside schools were
584.8 lx (school A), 197.0 lx (school B), 521.7 lx (school C), and 703.1 lx (school
D); whereas, in winter season the observed mean values of illuminance were 661.3 lx
(school A), 228.0 lx (school B), 458.2 lx (school C), and 380.0 lx (school D).
On comparing lighting of schools in winter season with the recommended limits
suggested in NBC-2005 (lower limit: 200 lx, upper limit: 500 lx), it was found that
mean illuminance of schools B, C, and D was within the recommended range and
school A was over illuminated. On contrary to winter season, none of the schools
met the recommended range in non-winter season. Lighting in schools A, C, and D
were exceeding the upper limit and school B was poorly illuminated having lighting
less than minimum prescribed limit (Fig. 5).
Due to smaller WFR and use of glazed glass on windows, the entry of natural light
was limited in school B. Therefore, in both the seasons, school B had lowest mean
illuminance in comparison to other schools. The results pointed out that placement
and size of the windows in relation to room size or WFR significantly affects the
total light available inside the classroom. The room with the lowest WFR also had
lowest lighting levels. Hence, if windows are not able to provide enough daylight,
there must be provision of enough artificial light in the classroom. Also, the use of
window curtains can prove to be beneficial to avoid over illuminance and problem
of glare in the rooms.
Impact of Lighting on Performance of Students in Delhi Schools 103

Fig. 5 School-wise mean illuminance in non-winter season and winter season

3.3 Perception of Students Towards Their Classroom

Lighting

Researches have indicated that appropriate lighting quality can increase productivity
and performance, and decrease eye strain and fatigue amongst occupants [29]. Ade-
quate lighting is an important aspect of classroom environment as it enhances the
ability of students to clearly read, write, and carry out other activities comfortably.
In the present research, an attempt was also made to find out perception of students
towards general lighting conditions inside their classrooms.
Analysis of the results indicated that in winter as well as non-winter season,
majority of the students from schools A, C, and D felt presence of sufficient natural
light inside their classrooms; whereas, in case of school B, a great percentage of
students reported insufficient natural lighting inside their classrooms (32.90% in
non-winter season and 18.50% in winter season) (Figs. 6 and 7). These findings
were in line with the lighting (illuminance) data, wherein, the school B was also
found to have lowest mean illuminance (Fig. 5) and lowest WFR (Table 2). The
reason for insufficient natural lighting inside school B classrooms was placement
and size of the windows in relation to the room size.

Fig. 6 Perception of
students towards natural
lighting inside classroom in
non-winter season
104 P. Singh et al.

Fig. 7 Perception of
students towards natural
lighting inside classroom in
winter season

It was also found that students faced difficulty in reading or copying from the
blackboard/whiteboard due to the glare caused by glossy surface or excessive contrast
between the dark areas and bright areas in the direction of viewing. In extreme cases,
glare can also cause eye fatigue, headache, etc., and can impair visual performance
by reducing task visibility. The analysis of the results indicated that in non-winter
season, a significant number of students from school B (53.2%) and from school
D (41.7%) complained of the problem of glare on the blackboard; whereas, only
21.1% students from school A and 24.2% from school C complained about problem
of glare. During the winter season, almost 70.8% students from school B, 55.6%
from school D and 42.2% from school C complained of glare on the instruction-
board (Table 3). School-wise statistically significant difference was found in the
perception of students towards experience of glare inside their classroom in both the
seasons (P < 0.05).
The reason for higher percentage of students facing the problem of glare in school
B was the usage of whiteboard for instructions, whereas, in schools C and D, the
reason was reflectance of sunlight on the blackboard. A very few students faced the

Table 3 Students perception towards experience of glare inside classroom

Season Non-winter season (n-384) Winter season (n-354)
School A B C D A B C D
n-90 n-79 n-95 n-120 n-89 n-65 n-83 n-117
Do you experience glare on the blackboard/chalkboard/whiteboard?
No (%) 46.7 29.1 56.8 28.3 51.7 16.9 42.2 29.9
Don’t know (%) 32.2 17.7 18.9 30.0 29.2 12.3 15.7 14.5
Yes (%) 21.1 53.2 24.2 41.7 19.1 70.8 42.2 55.6
Total (%) 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
χ2 37.425 48.398
p-value 0.000* 0.000*
* p-value significant at 0.05
Impact of Lighting on Performance of Students in Delhi Schools 105

problem of glare in school A as this school heavily relied on projector-based teaching.

School A had window screens, and whenever projector was used window screens
were lowered to avoid glare. Another important finding of the study was that most
of the students from the schools where classrooms faced west, south or south-west
direction [i.e., school B and school D] experienced glare on the board. North-facing
windows provide good quality daylight and general teaching spaces that face north
receive even and consistent light in all the seasons.

3.4 Relationship of Lighting with Performance of Students

Results highlighted that the mean performance score (CP score) of the students of
school A was 207.03, school B was 183.93, school C was 189.74, and school D
was 189.06 (Fig. 8). It was also observed that schools which had higher lighting
(illuminance) also had higher CP scores. The results indicated that the students’
performance scores had positive correlation with classroom lighting/illuminance (p-
value < 0.05). These results were in parity with the reviewed research studies which
had also indicated a positive correlation between lighting and students’ performance
[4, 11].
Further, binary logistic regression was performed between the performance score
(CP scores) and lighting (illuminance) at 0.05 level of significance to assess impact

Fig. 8 School-wise mean illuminance in non-winter season and winter season

106 P. Singh et al.

Table 4 Logistic regression analysis for association of illuminance with CP scores of students
Variables df Sig. Exp (B) 95% Confidence interval
Lower Upper
Illuminance (0) 2 0.002* – – –
Illuminance (1) 1 0.005* 2.273 1.278 4.042
Illuminance (2) 1 0.003* 1.973 1.261 3.085
df degree of freedom for Wald chi-square test, Exp(B) exponentiation of the B coefficient/odds
ratio for predictors
*p-value significant at 0.05

of classroom lighting on performance of the students. The results indicated that class-
room lighting had a high significance in affecting the outcome variable, i.e., perfor-
mance score (CP score) of the students (Table 4). Classroom lighting/illuminance
between 250 and 500 lx was linked with increased concentration of the students,
which translated into higher scores and increased performance. The analysis also indi-
cated that the performance of the students increased with the increase in illuminance
till a certain comfort limit after which it started declining.

4 Conclusion

The study showed that strong correlation exists between classrooms lighting and
performance of the students. Classroom lighting between 250 and 500 lx was linked
with increased concentration of students, which translated into higher scores and
improved performance [13]. Optimal lighting in schools can create favourable view-
ing conditions for students to read and copy from the instruction-board. Schools
are advised to make effective use of window blinds or curtains in the classrooms to
avoid glare caused by excessive daylight or highly reflective work surfaces which
may lead to eye strain and fatigue amongst students. As classroom environment plays
an important role in the overall performance of the students, and hence they need
to be planned and designed according to the standards and comfort needs of the
students. The findings further suggest the need for extensive and detailed research
in the area of lighting in educational spaces and student learning.

Acknowledgements We acknowledge grant received from Research Council, University of Delhi

for funding monitoring instrument under Research and Development Project 2013, Reference no:
DRCH/R&D/2013-14/4155.
Impact of Lighting on Performance of Students in Delhi Schools 107

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Exposure to Particulate Matter
in Classrooms and Laboratories
of a University Building

Abinaya Sekar, Prem Mohan, George K. Varghese and M. K. Ravi Varma

Abstract In India, around 1.3 million deaths occur every year due to indoor air pol-
lution. The most common indoor pollutants include asbestos, biological pollutants,
carbon monoxide, formaldehyde, lead, nitrogen dioxide, pesticides, radon, indoor
particulate matter (IPM), second-hand smoke and volatile organic compounds. In
this study, the concentrations of IPM10 , IPM2.5 and IPM1 were as measured using
Laser Aerosol Spectrometer (Grimm MiniLAS 11-R) in the major laboratories and
classrooms of the Department of Civil Engineering at National Institute of Technol-
ogy, Calicut, India. The sampling was carried out during working days and found that
the highest level of particulate matter IPM10 and IPM2.5 were found in the concrete
laboratory, where the major source for dust particles could be cement. The highest
level of IPM1 was found in the dumping yard within the structural engineering block.
The IPM10 and IPM2.5 levels in almost all the laboratories exceeded the permissi-
ble value prescribed by WHO. The faculty and research scholars’ cabin within the
laboratory space is highly prone to particulate matter pollution.

Keywords Indoor particulate matter · Classrooms · Laboratories · Laser Aerosol

Spectrometer

1 Introduction

Studies conducted over the past two decades reveal that there is a very high correlation
between health-related issues and the level of pollution in the outdoor and indoor
environment [1–5]. Some studies have shown that in spite of the absence of sources

A. Sekar · P. Mohan · G. K. Varghese (B)

Department of Civil Engineering, National Institute of Technology Calicut, Kozhikode, Kerala,
India
e-mail: gkv@nitc.ac.in
M. K. R. Varma
Department of Physics, National Institute of Technology Calicut, Kozhikode, Kerala, India

© Springer Nature Singapore Pte Ltd. 2020 109

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_12
110 A. Sekar et al.

like smoking and cooking, particulate matter pollution levels in laboratories and
classrooms were higher when compared to that in residential and other commercial
buildings [6, 7].
In India, particulate matter is one of the major pollutants, and the level exceeds
the permissible limit in many of the major cities [8]. Indoor air quality is often
influenced by outdoor air in the case of naturally ventilated buildings. Monitoring
of indoor particulate matter 2.5 (IPM2.5 ), indoor particulate matter 10 (IPM10 ) and
indoor particulate matter 1 (IPM1 ) is very important in micro-environments like
classrooms and laboratories due to their impact on health globally [9].
Maintaining good environmental quality in classrooms is part of providing a
healthy and comfortable learning atmosphere for the students and faculty which in
turn will influence their health, productivity, performance and comfort in a variety
of ways [10]. Exposure to indoor pollutants is one of the major health issues in many
fast-developing countries [11]. In India alone, around 1.3 million deaths are caused
every year due to indoor air pollution. The health effects caused due to indoor air
quality are usually called as building-related issues or sick building syndrome. Sick
building syndrome is mainly due to poor ventilation and the high density of population
in a particular area [12]. Among IPM, respirable fraction causes pneumoconiosis and
silicosis, whereas larger size fraction causes bronchitis and obstructive changes in
pulmonary function. Sampling and analyzing the PM10 and PM2.5 concentrations give
crude exposure rates but will not give accurate results to correlate to adverse health
impacts associated with it. For this, a detailed analysis of the size-wise concentration
of particulates can be more useful [13].
In this study, the focus was mainly on measuring IPM10 , IPM2.5 and IPM1 in
laboratories and classrooms of the Civil Engineering Department (CED), National
Institute of Technology, Calicut (NITC). The Department has a number of specialized
laboratories which include Geotechnical Engineering, Environmental Engineering,
Transportation Engineering, Coastal Engineering, Construction Engineering, Struc-
tural Engineering, Hydraulics and Water Resource Engineering, Geoinformatics and
Engineering Geosciences. In many of these laboratories, the work involves the use of
cement, sand, soil, chemicals and other construction materials which can contribute
particulate matter concentration in the indoor environment. Since research scholars,
faculties and most of the postgraduate students spend around 8–10 h every day in
their laboratory workspace and cabins inside the laboratory space, it is important
and necessary to frequently monitor the pollution levels and take necessary steps
to control pollution in these indoor environments. In addition, studies similar to the
present study will help to develop IAQ standards in India.

2 Methodology

The general outline of the study is given in the form of a flowchart in Fig. 1, and
detailed description of the entire methodology is given in subsequent sections.
Exposure to Particulate Matter in Classrooms and Laboratories … 111

Fig. 1 General methodology

2.1 Sampling Location

Kozhikode is the second largest urban agglomeration in Kerala, India, with a pop-
ulation of around 2 million as per 2011 census. The city is located 250 km west of
Bangalore, 235 km south of Mangalore and 525 km northeast of Chennai. NITC is
located in the foothills of western ghats, 22 km northeast to the city of Kozhikode
(11º19 19.00 N and 75º56 00.8 E). In the study, sampling was done in classrooms
and laboratories of Civil Engineering Department during the month of April 2018.
The Department has 582 undergraduate students, 170 postgraduate students, 53 full-
time research scholars, 41 faculty members and 20 non-teaching staff. It is worth
mentioning that the campus is cleaner and greener when compared with other parts
of the city. The blue blocks in the map (Fig. 2) indicate the sampling blocks, and red
points indicate the location where outdoor samples were collected.

Fig. 2 Monitoring site location. Source Wikipedia and Google map

112 A. Sekar et al.

Table 1 Instrument
Parameter Details/value
details [14]
Instrument name Mini laser aerosol spectrometer
Model 11-R
Make GRIMM
Size channels 31 channels from 0.25 to 32 µm
Sample flow rate 1.2 l/min ±5%
Rinse flow rate 0.3 l/min
Reproducibility ±3% over the total measuring range
Laser wavelength 660 nm
Count range 1–2,000,000 particles/l
Particle mass 0.1 µg/m3 –100 mg/m3

2.2 Sampling Design and Instrumentation

The sampling was carried out in 30 different locations within and surrounding the
Department to measure both ambient and indoor concentrations. The instrument
was kept 1.5 m above the ground surface at the breathing zone of an average human
being. The monitoring was done in each location, and the mean value was tabulated.
Pollution level was monitored in such a way that all the sampling points could be
covered in a single day and that would help us in providing a better comparison
of results. The technical information about the instrument used for the sampling is
given below (Table 1).

2.3 Data Processing and Comparison with Standards

Data processing was carried out using the software Version 1.178, LabView® for
further comparison with air quality standards. Since India does not have its own
indoor air quality standards, the obtained results were compared with the National
Ambient Air quality standard of India (NAAQS) and WHO air quality standards. In
addition to that, the results were compared with European Union Standard EN 481,
1993 for inhalable fraction, thoracic fraction and respirable fraction values (Table 2).

3 Results and Discussions

The IPM10 concentrations exceeded Indian National Ambient Air Quality Standards
(100 µg/m3 , 24-h average) at 30% of the locations and exceeded WHO indoor air
quality standards (50 µg/m3 , 24-h average) at 92.5% of the locations. The only loca-
tions where the concentrations were within WHO limits were the air-conditioned
Exposure to Particulate Matter in Classrooms and Laboratories … 113

Table 2 Classification of particle fraction [15]

Classification Definition Description
Inhalable fraction Mass fraction of the particle which Particles < 100 µm
is inhaled by nose and mouth
Thoracic fraction Mass fraction of the particle that Median of the particle size:
passes through the larynx 11.64 µm
Geometric standard deviation:
1.5 µm. 50% of particles with aero
diameter of 10 µm
Respirable fraction Mass fraction that reaches the Median of the particle size:
alveoli 4.25 µm
Geometric standard deviation:
1.5 µm. 50% of particles with aero
diameter of 4 µm

rooms where the IPM concentrations were 42.4 and 48 µg/m3 . The highest PM10
concentration was found in the concrete laboratory where the level exceeded 10 times
the National Ambient Air Quality Standard. The levels of particulate matter at the
outdoor sampling stations were less than the indoor lab space except for sampling
locations OP6 and OP9 where construction works were going on. The level of IPM10
was higher in the structural and concrete laboratory may be because of improper ven-
tilation, dumping of construction and demolition waste, cement and sand particles.
Faculties and scholars whose cabin is within the laboratory were highly exposed
to IPM10 , which in turn will have serious health effects. Details of the sampling
locations and the corresponding sampling IDs are shown in Table 3 and Fig. 3.

Table 3 Sampling location description

SP 1: Faculty cabin 1 SP 11: Dumping yard SP 21: Classroom 1 SP 31: Auditorium
SP 2: Faculty cabin 2 SP 12: Structures lab SP 22: Classroom 2 SP 32: Canteen
SP 3: Envi. research SP 13: Strength of SP 23: Scholar room OP1: Near SP3–7
lab materials lab 4 (AC)
SP 4: Scholar room 1 SP 14: Scholar room SP 24: Scholar room OP2: Near SP 26, 27
2 5
SP 5: Envi. lab room SP 15: Scholar room SP 25: Center for OP3: Near SP 30
1 3 transportation
SP 6: Envi. lab room SP 16: Conference SP 26: Geotechnical OP4: Road 1
2 room lab
SP 7: Lab assistant SP 17: Office room 1 SP 27: Lab assistant OP5: Road 2
room room
SP 8: GC/MS and SP 18: Office room 2 Sp 28: Transportation OP6: Road 3
AAS room lab
SP 9: Faculty cabin 3 SP 19: HOD cabin SP 29: Offshore lab OP7: Road 4
SP 10: Concrete lab SP 20: Faculty cabin SP 30: Scholar room OP8: Road 5
4 6
114 A. Sekar et al.

Fig. 3 PM10 level

IPM2.5 concentration exceeded Indian NAAQS (60 µg/m3 , 24-h average) at 20%
of the locations, and it exceeded WHO standards (25 µg/m3 , 24-h average) at all
the sampling locations. As in the case of PM10 , the highest concentration of IPM2.5
was observed in the concrete laboratory. Since IPM1 does not have any standards
for ambient air quality and indoor air quality, the values cannot be compared with
any of the standards. But the concentrations were found to follow a slightly different
trend when compared with that of IPM10 and IPM2.5 . The highest concentration was
found in dumping yard of the structural engineering laboratory (Figs. 4 and 5).
Since the instrument has 31 different size channels, it is directly possible to obtain
data under different classes, viz. inhalable fraction, thoracic fraction and respirable
fraction. The data sets are tabulated in Table 4. As the instrument measures particles
of size 30 µm or less, the inhalable fraction shown does not include particle size above
30 µm. On an average, 78% of the inhalable fraction enters the thoracic region, and
51% of the inhalable fraction enters the alveoli region which will give rise to acute
and chronic respiratory illness. The transport of particulate matter in the respiratory
system of human beings is demonstrated in Fig. 6.

Fig. 4 IPM2.5 level

Exposure to Particulate Matter in Classrooms and Laboratories … 115

Fig. 5 IPM1 level

Table 4 Level of IPM inhalable, thoracic and respirable fraction (µg/m3 )

Location Inhalable Standard Thoracic Standard Respirable Standard
fraction deviation fraction deviation fraction deviation
mean mean mean
SP 1 77.7 37.9 66.7 6.1 53.4 2
SP 2 103.3 31.6 79.4 11.4 54.4 3.4
SP 3 112.5 62 74.3 20.5 45.1 4.9
SP 4 99.1 47.6 79.4 18.6 54.5 2.6
SP 5 105.7 110.2 78.7 11.7 56.6 3.1
SP 6 74.9 28.5 63.1 7.1 51.4 2.3
SP 7 70.9 26.6 63.3 7.8 51.3 2.5
SP 8 63.9 16.8 55.3 8.3 42.6 3.3
SP 9 277.7 57.5 247.5 19.1 139.3 9.7
SP 10 1181.7 264 1023.9 214.7 383.3 69.5
SP 11 727.2 279.7 564.4 192.9 210.6 55.5
SP 12 809.6 355 655.4 225.1 285.5 67.4
SP 13 147 55.8 113 27.1 58 6.2
SP 14 177.1 46.7 136.9 20.1 70.2 5.1
SP 15 261.2 244.9 165.8 27.3 84.3 5.4
SP 16 118.7 69.1 82.7 24 50.8 4.8
SP 17 166.2 143.8 110.1 22.8 63.9 5
SP 18 146.3 212.7 79 11.5 51 3.1
SP 19 66.2 10.9 62 6.6 46.9 3
SP 20 88.9 35.6 72.6 13.5 50.5 3.4
SP 21 69.7 16.1 64.2 8 47.7 3.1
(continued)
116 A. Sekar et al.

Table 4 (continued)
Location Inhalable Standard Thoracic Standard Respirable Standard
fraction deviation fraction deviation fraction deviation
mean mean mean
SP 22 109.7 88.8 74.4 14.1 48.8 3.1
SP 23 56.1 33.4 44.1 6.7 35.5 1.8
SP 24 57.4 24.7 48.2 8.1 36.2 2.2
SP 25 85.4 111.2 57.5 8.2 42.5 2.3
SP 26 144.5 80 106 20.4 55.9 5
SP 27 98 26.1 80.1 11.7 48.6 3.4
SP 28 65.7 26.7 56.8 11.4 42.2 2.8
SP 29 121.5 94.4 82.7 35.3 48.5 9.4
SP 30 92.7 48.3 68.6 17.6 45.5 4.1

Fig. 6 Schematic representation of the human respiratory tract (reproduced from [16] with
permission)

4 Conclusion

Indoor particulate matter of size 10, 2.5 and 1 µm was monitored in laboratories,
classrooms and faculty cabin of Civil Engineering Department. IPM concentration in
all laboratories exceeded the standards specified by WHO on air quality, and scholars
working in structural engineering and concrete lab were exposed to 10 times more
pollution when compared with standards prescribed by Indian NAAQS. The level of
pollution in the outdoor environment was less when compared to the level of indoor
pollution in most of the sampling points. Frequent cleaning and disposal of waste are
highly recommended to reduce the pollution level. Moreover, all the scholars should
be advised to wear a nose mask when working in the lab to reduce the exposure to
IPM.
Exposure to Particulate Matter in Classrooms and Laboratories … 117

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5. Yang T, Liu W (2018) Does air pollution affect public health and health inequality? Empirical
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7. Oeder S (2012) Toxicity and elemental composition of particulate matter from outdoor and
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particulates in classrooms located close to an urban roadway. J Air Waste Manag Assoc
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in Middle Eastern classrooms. Atmos Environ 80:389–397
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of existing information. Indoor Air 13:53–64
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12. Apte MG (2000) Indoor carbon dioxide concentrations and SBS in office workers. Proc Healthy
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Assessment of Indoor Environmental
Quality and Impacts on Occupants: Case
Study of MNIT Jaipur

Nivedita Kaul and Khushbu Parik

Abstract Indoor environmental quality (IEQ) is one of the major factors for
producing a favourable and productive environment in any educational building.
Various studies show the effect and consequences of poor IEQ on grasping capa-
bility of students. Today institute buildings are expected to provide enhanced IEQ,
higher occupant satisfaction and less risks of occupant health. With reference to
various results available, a study has been conducted in Malaviya National Institute
of Technology, Jaipur, Rajasthan, for analysing the IEQ conditions in the institute’s
building. The study is conducted in two parts, first includes quantitative analysis of
various IEQ parameters like temperature, relative humidity, noise, air ventilation, par-
ticulate matter, volatile organic carbon, light intensity and CO2 concentration. These
parameters are further analysed as per the ASHRAE and various other standards.
The second one includes survey for determining the student’s perception towards
the current environment and comfort in the building. The study included various
classrooms, offices and working areas of the institute to analyse the difference in
concentration of parameters as per the usage and occupancy of the area. In this
research, it is evident that level of satisfaction for majority of users in the academic
building of MNIT is moderate. The reason accounted for the discomfort of various
students may be indoor noise generated by some of the ACs, improper ventilation in
summer season and construction activities in the vicinity. A few actions should be
taken into consideration to produce a good IEQ environment at the academic building
and increasing the productivity of the students and workers of the institute.

Keywords IEQ · Occupant health

N. Kaul (B) · K. Parik

Department of Civil Engineering, Malaviya National Institute of Technology,
Jaipur, Rajasthan, India
e-mail: kaulmnitj@gmail.com

© Springer Nature Singapore Pte Ltd. 2020 119

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_13
120 N. Kaul and K. Parik

1 Introduction

The effects of IEQ on cognitive performance on the students are largely under per-
ceived in India. Poor IEQ can give negative impact to facilities, buildings and occu-
pants, thus affecting the teaching and learning process adversely. Thermal comfort
levels and indoor air quality (IAQ) play a crucial role in producing a favourable envi-
ronment that supports educational and health outcomes. There is enough evidence
in the literature to support the fact that indoor pollutants and thermal conditions
in educational institutes may influence student’s performance or attendance. Addi-
tionally, there is significant evidence that institute exposure to various indoor air
pollutants (IAP) may have health and comfort implications on the students, which
may impair performance indirectly. For example, exposure to noise, excessive heat
and poor lighting conditions may affect the concentration of student and their grasp-
ing power of the subject delivered. Indoor environmental quality (IEQ) must become
an important component of providing quality education in our learning institutes.
Today institute buildings are expected to provide enhanced IEQ, higher occupant
satisfaction and less risks of occupant health. A study has been undertaken in various
institutional areas of MNIT, Jaipur, to evaluate the existing conditions of IEQ and
their effect on the performance and well-being of the students.

2 Methodology

Malaviya National Institute of Technology (MNIT) is located in Malviya Nagar,

Jaipur, Rajasthan. There are hospitals, business centre, residential and commercial
areas located adjacent to the main campus, i.e. within 1 km radius. The study focuses
on various indoor micro-environments including classrooms, laboratories and offices
of MNIT. Locations (13) have been considered for data collection.
The present study consists of two parts. First includes measurement of IEQ param-
eters on selected locations to determine the quantitative data in the present conditions.
The second part includes survey for understanding the perception of respondents on
the present IEQ conditions of the building. The major IEQ parameters that have been
considered in the present study are: temperature, relative humidity, noise, air ven-
tilation, particulate matter, volatile organic compounds (VOCs), light intensity and
CO2 concentration. Various instruments used for the data collection are temperature
and humidity metre (FLUKE 971), air quality monitor (RAVE), lux metre (MECO),
anemometre and sound level metre. The study sites have been selected on the basis
of size of the room, purpose of the room (lecture theatre/laboratory/staff cabin etc.),
ventilation conditions (natural/air-conditioned), age of the building (new/old build-
ing), possibility of persistent IAQ problems due to proximity to toilets, ongoing
construction activities etc. Measurements have been taken for a duration of 1 h at
Assessment of Indoor Environmental Quality … 121

each location selected for study in summer season. In each classroom, the measure-
ment has been taken at different times of the day and at different locations to record
more precise data.
For studying the occupant’s perception, questionnaire survey forms have been
distributed to the students in classrooms. Questionnaire has been developed based
on research objectives to collect research data through various Likert scale questions
and some opinion-based questions, on the following parameters

Thermal Comfort Odour Intensity Background Noise

Rating Comfort Level Rating Intensity Rating Noise Level
1 Uncomfortable 1 No Odour 1 Very high
2 Poor 2 Very Weak 2 High
3 Moderate 3 Weak 3 Moderate
4 Good 4 Distinct 4 Low
5 Comfortable 5 Strong 5 Silent
6 Very Strong

Lighting conditions Audibility Problem

Sufficient Yes
Not sufficient No

Dust Problem Stuffy feeling

Yes Yes
No No

Cleanliness
Always
Frequently
Never

3 Results and Discussion

The data collected is analysed as per American Society for Heating Refrigeration
and Air Conditioning Engineers (ASHRAE), Illuminating Engineering Society of
North America (IESNA), IAQ index, World Health Organisation (WHO) and Indian
Standard (IS) standards. Relative humidity (RH) of the atmosphere is an important
parameter determining thermal comfort. As per ASHRAE, RH should be between
30 and 65%. In the present study, the relative humidity at six locations is within
the range. The VOCs have been observed to be within permissible limit of 1 ppm
at all the locations. Though the lighting intensity at most of the locations has been
observed to be less than 400 lx (IESNA standard), still the perception towards lighting
122 N. Kaul and K. Parik

condition is satisfactory which may be due to the natural light from the windows. The
carbon dioxide concentration is in good category at maximum of the places as per
ASHRAE. However, a high concentration of CO2 (1990 ppm) is observed at one of
the locations which may be due to improper ventilation and higher occupancy at the
time of measurement. PM10 and PM2.5 have been observed within the satisfactory
limit except at two locations. The reason for higher concentration may be due to
ongoing construction activity near the location. The variation in temperature should
range between 22.8 and 26.1 °C in summer and 20 and 23.6 °C in winters as per the
ASHRAE standards. However, the observed temperature is higher than the prescribed
limits for summer seasons.
In order to analyse the perception of IEQ elements at MNIT, Jaipur, a survey has
been carried out at the locations under consideration by distributing 320 question-
naires to the occupants of the study sites. Responses (232) were completed and have
been analysed for the perception of various IEQ parameters. The perception of the
noise comfort belongs to subjective feeling, and surrounding noise may disturb the
people even if the noise level does not exceed the relevant standards. The survey
results show that 8.29% students have reported that classrooms are subject to very
noisy conditions, 9.46% have reported high noise, and 31.36% have reported mod-
erate noisy conditions, while 40.23% and 10.65% have reported low and silent level
of noise, respectively.
Lighting can change the mood of people and affects their psychology. In this study,
74.14% students have reported sufficient lighting conditions while 25.85% have
problems with lighting conditions and reported it unsatisfactory. 43.54% students
have reported the feeling of stuffiness in the classrooms. This problem may be due
to improper ventilation in the class. The survey has been done in summer season,
and the number of occupants is high which also contributes to comfort issues at the
location. Dust has not been reported a problem by majority of respondents (66.2%)
due to frequent cleaning in the classrooms. Audibility condition in the classrooms
has been reported to be unsatisfactory by 56% of students which may be due to
the construction activities at the time and other indoor noises. For odour intensity,
perception varied from ‘no’ (39.58%) to ‘weak odour’ (19.27%). Some of the odour
problems can be due to sensitive to a particular cleaning agent. In spite of high
temperature than the suggested limits, 46.66% students reported moderate thermal
comfort level in summers, while 53.12 reported good comfort level in winter season.

4 Conclusion

The study shows that the administration must give substantial importance to IEQ
parameters and provide adequate thermal comfort, proper audibility conditions, ven-
tilation and efficient lighting so as to ensure good teaching and learning condition
in educational institutes. In this research, it is evident that the level of satisfac-
tion for majority of users in the academic building of MNIT is moderate. A few
actions should be taken into consideration to produce a good IEQ environment at
Assessment of Indoor Environmental Quality … 123

the academic building. Improper maintenance will affect the building’s environment
quality, and it highly influences productivity and well-being of the facility manage-
ment. Priority should be given on the maintenances aspect as this will affect the core
functioning of the institute.
Classroom Ventilation and Its Impact
on Concentration and Performance
of Students: Evidences
from Air-Conditioned and Naturally
Ventilated Schools of Delhi

Pratima Singh, Renu Arora and Radha Goyal

Abstract Carbon dioxide (CO2 ) concentration acts as an important indicator of

indoor air quality inside school premises. CO2 concentration above 1000 ppm inside
a building is an indicator of insufficient ventilation which may cause health com-
plaints to the occupants and may directly or indirectly impair concentration and
performance of the students. Realizing the need for research in this area, an attempt
was made to investigate the relationship between classroom ventilation and Con-
centration Performance (CP) of school children. In this paper, the classroom venti-
lation was evaluated through the concentration of CO2 inside air-conditioned (AC)
and naturally ventilated (NV) urban school buildings located in South Delhi. The
results indicated the evident problem of elevated concentrations of CO2 inside the
AC schools which often exceeded the ASHRAE’s recommended limit of 1000 ppm.
The results from the d2 test reflected that mean CP score of students was higher in
the schools with lower CO2 concentrations than students from schools with higher
CO2 values. However, the differences in their mean were not significantly different
(p-value > 0.05). The current research suggested the need for longitudinal study to
explore the relationship of CO2 with students’ performance inside the classrooms.

Keywords Indoor air quality · Carbon dioxide · School · Performance · Student ·

Ventilation

1 Introduction

According to the World Health Organization (WHO), clean air is the basic require-
ment for human health and well-being [1]. As we normally breathe about 12,000 l
of air every day, it is essential for our health to have clean air in our environment [2].

P. Singh (B) · R. Arora

Institute of Home Economics, University of Delhi, F-4 Hauz Khas Enclave,
New Delhi 110016, India
e-mail: pratima.singh@ihe.du.ac.in
R. Goyal
Indian Pollution Control Association, Hargobind Enclave, New Delhi 110092, India

© Springer Nature Singapore Pte Ltd. 2020 125

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_14
126 P. Singh et al.

Central Pollution Control Board’s (CPCB) Indoor Air Pollution Report (2014) refers
indoor air quality (IAQ) to the quality of air inside the buildings as represented by
the concentrations of the pollutants and thermal conditions (temperature and relative
humidity) that affect the health and performance of the occupants [3]. Along with the
pollutants in ambient air, building-related conditions such as building materials and
their permeability, air-conditioning and ventilation systems used also affect quality
of air inside a space [4].
Understanding the impact of the indoor air on children is important as they spend
most of their time indoors (approximately 80–90%), either at school or at home.
Within a school, students spend most of their time inside classrooms, engaging in
varied activities which require a considerable amount of concentration and attention.
Several research studies have indicated that the air quality inside classrooms is often
poor and CO2 concentrations frequently exceed recommended levels prescribed by
the American Society of Heating, Refrigerating and Air-Conditioning Engineers
(ASHRAE) for indoor environments, which might be due to high student density
or poor ventilation strategies adopted in schools [5]. Faulty heating, ventilation,
and air-conditioning systems in schools can exacerbate air quality problems inside
classrooms leading to ‘sick building syndrome’ manifestation on children’s health
in the form of various health issues. If air inside classrooms is deteriorated, it may
cause several health effects that may directly impair concentration or memory of
students or cause other health effects that indirectly affect their learning.
Carbon dioxide (CO2 ) is colourless, odourless, and tasteless gas which is non-
flammable. The indoor concentration of CO2 can be a good measure of the ventilation
per person inside the space [6]. In most locations, the CO2 level in outdoor air is
reported to be in a range of 350–450 ppm [7, 8]. The higher CO2 concentrations in
the outdoor environment can be due to heavy vehicular traffic, industries, and varied
sources of combustion, whereas, the elevated indoor concentration of CO2 can be a
direct result of respiration by building’s occupants and inadequate ventilation (Fig. 1).
As classrooms are being densely occupied by a large number of students, they
may exhibit elevated levels of CO2 resulting in drowsiness, lethargy, and a general
sense that the air is stale as reported by students and staff in a number of research

Fig. 1 Factors contributing to CO2 generation and accumulation inside the space
Classroom Ventilation and Its Impact on Concentration … 127

studies [5]. This general discomfort amongst students may further translate into poor
performance inside the classrooms.
Hence, the present research was designed to study the impact of classroom ven-
tilation on the Concentration Performance (CP) of the students studying in air-
conditioned (AC) and naturally ventilated (NV) schools located in Delhi. The specific
objectives of the research study included:
• To examine the physical space design of the classrooms of selected AC and NV
schools.
• To measure the existing indoor CO2 concentrations in the classrooms of selected
schools.
• To analyze the variations in CO2 concentrations in the AC and NV schools and
their relationship with the concentration and performance of the students.

2 Methodology

2.1 Sample Selection

For the purpose of the research, the data was gathered from two AC (schools A
and B) and two NV (schools C and D) schools located in South Delhi; which were
selected through purposive sampling technique. All the schools were selected from
South Delhi for two reasons:
• Limitation of taking all the schools from near proximity of the Delhi Pollution
Control Committee (DPCC)’s air quality monitoring station located in RK Puram,
Delhi.
• Majority of the AC schools were located in South Delhi.
Three classrooms from each school were selected for CO2 monitoring based on the
permission given by the school authorities. Systematic sampling technique was used
for selecting student respondents from the four schools—A, B, C, and D. Informed
consent was taken from all the students studying in the selected classrooms and their
parents. Finally, a total of 738 students (i.e. 384 in non-winter season and 354 in
winter season) were selected from these classrooms as cohorts of this study. The
detailed procedure followed to select schools is illustrated in Fig. 2.

2.2 Data Collection

The design features of the classrooms viz., orientation, area, dimensions, ventilation
type, number of doors, windows, etc., were studied using a structured checklist and
observation tool. The ultrasonic measuring tape ‘Bosch GLM 50 Professional’ was
used for taking measurements of room and window dimensions.
128 P. Singh et al.

Fig. 2 Procedure followed for sample selection (Note: DPCC—Delhi Pollution Control Com-
mittee, AAQMS—Ambient Air Quality Monitoring Station, AC—air-conditioned, NV—naturally
ventilated)

The protocol for monitoring of CO2 was planned from July 2016 till February 2017
(non-winter season: July–October 2016; winter season: November 2016–February
2017) in order to consider seasonal variations. CO2 monitoring was carried out for
6–7 working hours at continuous 5 min in each classroom on one working day and
one non-working day (Saturday) in each school in both the seasons using indoor air
quality monitor ‘Testo-435’ (Tables 1 and 2). The sampling instrument was placed
in the centre (highest student density area) of the class at approximately 1 m above
the floor level, corresponding to the breathing zone of the occupants. Class activity
pattern of the children was also recorded to make valid interpretations of the results.
Further, students’ concentration and performance were evaluated through stan-
dardized d2 test for speed and accuracy of task completion. The test was created

Table 1 Specifications of indoor air quality monitor ‘Testo-435’

Monitoring Working principle Range Accuracy Measurement
instrument type
IAQ Monitor: Non-dispersive 0 to + ± (75 ppm Continuous
Testo-435 infrared sensor 10,000 ppm CO2 ± 3%
(NDIR) of mv)
Classroom Ventilation and Its Impact on Concentration … 129

Table 2 CO2 monitoring protocol followed in non-winter (July–October 2016) and winter
(November 2016–February 2017) seasons
Type of day Working days Non-working days
Number of classrooms 3 classrooms × 4 schools 1 classroom × 4 schools
monitored in each school
CO2 monitoring duration NV school classrooms: Both AC and NV schools’
For 6½ h at 5 min interval classrooms:
(7.30 am to 2.00 pm) For 6 h at 5 min interval (8:00
AC school classrooms: am to 2:00 pm)
7½ h (7.30 am to 3.00 pm)
Total number of days Non-winter season: 12 days Non-winter season: four days
Winter season: 12 days Winter season: four days

by Brickencamp and Zilmer (1998) and is also known as cancellation task and
takes approximately 8–10 min to complete [9]. The Concentration Performance (CP)
scores of the students were calculated by subtracting the total incorrect responses
from the total correct responses. Descriptive statistics and other statistical analysis
parameters were determined through SPSS software and Microsoft Excel.

3 Results and Discussion

3.1 Space Design Observations

Design features of the classrooms of all the selected schools were studied in detail
using structured checklist. It was observed that classrooms of AC schools had non-
operable compact windows (Fig. 3) in order to reduce heat exchange for desired
thermal insulation, which limited the supply of fresh air inside the classrooms. The
doors of the classrooms were usually kept closed throughout the day resulting in

(a) School A classroom (b) School B classroom

Fig. 3 Non-operable compact windows in classrooms of AC schools
130 P. Singh et al.

(a) School C classroom (b) School D classroom

Fig. 4 Operable windows in classrooms of NV schools

CO2 build-up inside the classrooms. It was also observed that though the school with
heating, ventilation, and air-conditioning (HVAC) system, i.e. school B had provision
for exhaust fans for removal of excess CO2 and stale air, they were never used pre-,
during or post-occupancy. Whereas in NV schools, windows and doors were kept
open most of the time which helped in reducing the CO2 concentration in the classes
of NV schools (Fig. 4).

3.2 Average Concentrations of CO2

The mean CO2 on working days for each school is a representation of average of
CO2 values obtained from the three different classrooms of each school on three
different working days. The given Fig. 5 represents the non-winter and winter trends
for concentrations of CO2 in schools A, B, C, and D.

Fig. 5 School-wise mean concentrations of indoor CO2 on working days in non-winter and winter
seasons
Classroom Ventilation and Its Impact on Concentration … 131

In non-winter season, the mean values of CO2 on working days in AC schools

were 2479.1 ppm ± 1146.0 ppm (school A) and 1954.7 ppm ± 852.2 ppm (school
B) and in NV schools were 581.9 ppm ± 152.6 ppm (school C) and 593.5 ppm ±
141.3 ppm (school D). Whereas in winter season, the mean values of CO2 on working
days in AC schools were 1726.2 ppm ± 861.6 ppm (school A) and 1952.1 ppm ±
695.0 ppm (school B) and in NV schools were 791.5 ppm ± 309.0 ppm (school C)
and 751.4 ppm ± 224.0 ppm (school D).The results indicated that the concentrations
of CO2 varied between schools based on the type of ventilation systems used, closing
and opening of windows, and classroom occupancy.
Further, it was observed that the AC schools recorded mean CO2 (i.e. 2207.9
and 1839.13 ppm) much above the limit of 1000 ppm prescribed by ASHRAE stan-
dards [10]. However, in both the seasons, the mean concentrations of CO2 in NV
schools were lower than in AC schools and were within recommended limits (587.7–
771.5 ppm) (Fig. 6). The open windows and doors of NV classrooms led to higher
air exchange rate resulting in lower accumulation of CO2 , whereas closed doors and
windows in AC classrooms resulted in higher accumulation of CO2 generated as
a result of occupants’ respiration. Research studies by Jurado et al. [11] and Yang
Razali et al. [12] also linked high concentrations of CO2 with human respiration and
different ventilation systems used in the classrooms.
The results further highlighted that the mean values of CO2 on non-working days
were lower than on working days in all schools in both the seasons (Table 3), as
the sources of CO2 generation were negligible on weekends due to no classroom
occupancy. In a similar research study by Yang Razali et al., a high concentration

Fig. 6 Mean concentrations of indoor CO2 in AC and NV schools in non-winter and winter seasons

Table 3 Comparison of CO2 on working and non-working days

Mean CO2 concentration (in ppm)
Schools A B C D
Day WD NWD WD NWD WD NWD WD NWD
Non-winter season 2461.1 484.2 1954.7 407.2 581.9 462.5 593.5 388.1
Winter season 1726.2 509.6 1952.1 347.8 791.5 351.0 751.4 360.0
Note A and B: AC schools, C and D: NV schools, WD: working day, NWD: non-working day
132 P. Singh et al.

of CO2 was found to be closely related to human respiration and closed windows
and doors [12]. Similarly, in the current research, values of CO2 were considerably
lower on non-working days due to no human respiration in classrooms.

3.3 Effect of Classroom Occupancy and Activities on CO2

Concentrations

The concentration of CO2 is considerably higher during the full occupancy periods
due to human respiration than when classrooms are vacant or have lesser occupancy
[12]. To study the effect of classroom occupancy on the variations of CO2 , data was
collected at 5 min interval for a complete working day from each classroom.
School A: The high values of CO2 indicated poor ventilation in all the classrooms
of school A. All the windows of classrooms of school A were non-operable except for
one small emergency window. It was observed that whenever emergency windows
or doors were opened or when the classrooms were empty, CO2 levels showed a
declining trend in both the seasons in the classrooms of school A.
Non-winter season: As the day progressed, increased room occupancy resulted
in an upward trend in CO2 values. CO2 started to accumulate inside the classrooms
during full occupancy hours. As the students dispersed at 2:20 pm, after which the
classrooms were empty, CO2 started showing a declining trend in all the classrooms
(Fig. 7a).
Winter season: In winter season, classrooms experienced higher CO2 levels (often
exceeding 1000 ppm) in early morning hours due to previous days CO2 build-up
indoors, thereby, exposing students to unhealthy indoor conditions (Fig. 7b). The
doors and one small emergency window were sometimes opened for occupants’
comfort in winter season. Hence, the mean CO2 in winter season was lower than in
non-winter season in school A.

(a) Non-winter Season (b) Winter Season

Fig. 7 Variations in concentrations of CO2 during working days in classrooms A1, A2, and A3 in
a non-winter season and b winter season
Classroom Ventilation and Its Impact on Concentration … 133

(a) Non-winter Season (b) Winter Season

Fig. 8 Variations in concentrations of CO2 during working days in classrooms B1, B2, and B3 in
a non-winter season and b winter season

School B: The windows of classrooms of school B were non-operable and hence,

the classrooms were completely dependent on HVAC system for ventilation. There-
fore, all the classrooms showed almost similar trends of CO2 in both the seasons
(Fig. 8a, b). The values of CO2 were low during morning hours in all the three
classrooms, since CO2 was in an early building upstage. As the day progressed
and students started to settle, CO2 values started to gradually increase. A few sharp
peaks were also observed in CO2 values. These were the time periods when class-
room occupancy was full and doors were closed. These peaks slowly declined when
room occupancy was less or classrooms were empty. On some occasions, in spite of
the room occupancy being same, opening of door for a longer duration resulted in a
drop in CO2 readings for some time, which again shoot up with the closing of doors.
School C: Classroom of school C relied mainly on fans and windows for
ventilation.
Non-Winter Season: Throughout the day, doors and windows were kept open in all
the classrooms for circulation of fresh air. This resulted in almost consistent values
of CO2 for the entire duration of monitoring. Also, the CO2 values did not exceed
1000 ppm in any of the classrooms in non-winter season.
Winter Season: Relative to non-winter season, CO2 levels in winter season were
higher and few peaks were also observed because of few incidences of closing of
doors and windows. In winter season, CO2 values occasionally crossed 1000 ppm
on certain time periods. However, the mean values of CO2 were less than 1000 ppm
in both seasons (Fig. 9a, b).
It was observed that though the ventilation was adequate in both the seasons in
school C classrooms, the mean concentrations of CO2 in the winter season were
greater than of non-winter season. The reason for the same was intermittent closing
of doors and windows in winter season to protect occupants from cool wind waves.
Closing of windows for a short period of time was also linked with fluctuations in
CO2 readings.
134 P. Singh et al.

(a) Non-winter Season (b) Winter Season

Fig. 9 Variations in concentrations of CO2 during working days in classrooms C1, C2, and C3 in
a non-winter season and b winter season

School D: Similar to school C, the doors and windows were kept open in all the
classrooms of school D in non-winter season which resulted in consistent values
of CO2 for the entire monitoring period in non-winter season. Whereas in winter
season, the mean values of CO2 in all the classrooms of school D were more than in
non-winter season (Fig. 10a, b) because of intermittent closing of doors and windows
for occupants’ thermal comfort.
Overall, seasonal variations were observed in mean values of CO2 in all the class-
rooms (except school B). CO2 concentrations were directly related to low ventilation
rates in densely populated classrooms.

(a) Non-winter Season (b) Winter Season

Fig. 10 Variations in concentrations of CO2 during working days in classrooms C1, C2, and C3 in
a non-winter season and b winter season
Classroom Ventilation and Its Impact on Concentration … 135

3.4 Effect of Classroom Ventilation (CO2 Concentrations)

on Concentration and Performance of Students

When comparisons were made between the mean Concentration Performance (CP)
scores of students of the NV and AC schools, the results highlighted that the mean
score of the students of NV schools (197.06) was higher than of students of AC
schools (189.13) (Fig. 11). However, the differences in their mean were not sig-
nificantly different (p-value > 0.05) (Table 4). As the students of AC schools were
exposed to higher CO2 concentrations often exceeding 1000 ppm, the effect of ele-
vated CO2 was evidently reflected on their lower CP scores compared to the students
of NV schools who rarely experienced elevated CO2 inside their classrooms. Pre-
vious research studies also showed similar results, wherein, students’ task speed
increased with the increase in ventilation rate and decrease in CO2 levels [13]. Their
study provided strong evidence of linkage between low ventilation rates to reduced
students’ attention and vigilance and negative effects on memory and concentration.

Fig. 11 Comparison of mean CP scores and mean CO2 concentrations of AC and NV schools

Table 4 Mean CP scores of the students

School/season Mean Std. deviation t p-value
NV (n-415) 197.06 54 1.763 0.078*
AC (n-323) 189.13 65
Total (n-738) 193.09 61
Note Independent sample t test, p-value is significant at 0.05*
136 P. Singh et al.

4 Conclusion

The study decisively indicated that the inward flow of outside fresh air and occupancy
of a room played important roles on the concentrations of CO2 inside the classrooms.
Open doors and windows helped in diluting accumulated CO2 ; thus, helping in
improving the quality of air indoors. The elevated indoor CO2 concentrations in AC
schools may indicate inadequate ventilation per occupant, which may severely affect
students’ health and performance in schools.
Based on the observations of the current study, the AC schools are advised to
increase ventilation rate so that CO2 levels can be controlled. The CO2 sensors
must be installed inside the classrooms and exhaust fans can be used whenever CO2
concentrations go beyond the permissible limits. Length of breaks should be adequate
so that the accumulated CO2 can be removed via adequate ventilation techniques
during break periods. The doors and windows of the classrooms must also be opened
well in advance before and at the end of the working day for re-circulating fresh air
from outside.

Acknowledgements We acknowledge technical help and support provided by Indian Pollution

Control Association during data collection for this research.

Ethical Approval The research design and related protocols for the study have been approved by
the Institutional Ethical Committee, Institute of Home Economics, University of Delhi on 1 June
2016.

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Indoor Air Quality and Thermal
Comfort in Green Building: A Study
for Measurement, Problem and Solution
Strategies

Praveen Babu and Gourav Suthar

Abstract Indoor air quality (IAQ) has become a global health issue due to rapid
urbanization resulting into construction of air tight high rise buildings affecting the
indoor environment. Majority of the people spend an average of 87% of their time
within enclosed buildings; living, working and studying. Various types of pollutants
are present indoor that are emitted either by natural or anthropogenic activities thus
adversely affecting the health of occupants within the building. Major sources of
indoor air pollutants are occupants/building users, their activity, appliances, building
materials and infiltration of pollutants from outdoors. The concept of sustainabil-
ity of green buildings includes a wide range of socio-economic and environmental
problem. The increase in concentration of indoor pollutant has decreases the indoor
air quality and the inadequate design of the green building may cause lower thermal
comfort. The pollutant released from the building material and furnishings causes
more harm to the occupants but still, there is a scope of improving the IAQ and
thermal comfort by implementing the proper natural or mechanical ventilation, air
cleaning, proper design of the building material, etc. Through a literature review, a
study has been carried out by elaborating the major causes of poor IAQ and thermal
comfort. This study also depicts the measurement techniques and strategies for the
same. It was concluded from the study that indoor environment could be improved by
implementing proper methods and system by following the standards and codes from
the different organization before designing the green building, i.e. American Society
of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) and Leader-
ship in Energy and Environmental Design (LEED) standards and many more such
available standards.

Keywords Indoor air quality · Ventilation · Green building · Comfort

P. Babu (B) · G. Suthar

Department of Civil Engineering, Amity University Haryana, Gurugram, India
e-mail: praveenb@ggn.amity.edu
G. Suthar
e-mail: suthargourav7@gmail.com

© Springer Nature Singapore Pte Ltd. 2020 139

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_15
140 P. Babu and G. Suthar

1 Introduction

1.1 Indoor Air Quality

Measurement of indoor air quality is the most important factor in the green building
since it provides more fresh air than the conventional building by avoiding sources
contaminants, which causes air pollution, controls the thermal comfort and improves
the maintenance [1, 2]. There are many gases emitted with consumption of building
energy causes the change in climate [3]. Indoor air quality (IAQ) has been the main
concern for any green building because poor air quality causes severe health prob-
lems. Therefore, maintaining a green environment inside the building contributes
7.5% in green building certification [4]. Contact to indoor air pollutants like par-
ticulate matter (PM), volatile organic compounds (VOCs), environmental tobacco
smoke (ETS) and nitrogen dioxide (NO2 ) have been related with the poor health
consequences, i.e. asthma, cancer and to overcome from this type of problems, an
assessment of IAQ was carried out which reduces numerous indoor exposures and
enhanced health results for community shifting from their conventional housing
into green buildings [5–7]. Environmental impact studies for green building and its
energy consumption were carried out for reducing the severe health effects [8–10].
It was found that there is a relationship between IAQ and the ventilation rate; a good
IAQ is attained by satisfactory ventilation with fresh outdoor air. Therefore, keeping
the building clean and to make better operations and maintenance, and control on
source of indoor air pollution by the selection of suitable building material, isola-
tion of source, etc., is essential [10]. ASHRAE, 2009 is the standard for document
determine the indoor air pollution, document for contractors, designers, and others to
gain data for achieving a good IAQ. Indoor air difficulties in new houses were mostly
instigated from building materials, household products and furnishings [11, 12]. It
was observed that advanced mechanical and ventilating systems had been used to
increase flow of air and decrease inhabitant interaction with the airborne infectious
agents [13].

1.2 Thermal Comfort in the Indoor Environment

The construction sector has changed its trend from conventional sustainable con-
struction [14]. In building, the major cause was found behind the poor air quality
and thermal comfort is the inadequate ventilation, and so, a traditional method of the
natural ventilation could be applied for the thermal comfort [15]. As per ASHRAE,
standard 55 (2013), there are six factors are responsible for change in thermal com-
fort inside the green building which are air temperature, metabolic rate, radiant
temperature, humidity and air speed. IAQ and thermal comfort are the two important
features of indoor environment of a building that has significant consideration by
current building designers. International and local standards recommend conditions
Indoor Air Quality and Thermal Comfort in Green … 141

envisioned to adoptive situations that are satisfactory to residents [17–19]. Majority

of the people spend an average of 87% of their time within enclosed environments. It
has been acknowledged that the inhalation of indoor air is the major determinant of
human exposure to numerous pollutants [20]. Providing improved thermal comfort
settings must go simultaneously with the disparagingly vital better goal of plummet-
ing the level of energy use in the green buildings [21]. The conventional buildings
could have huge source of contamination, but the situation differs in green building;
health, aesthetics and economics have become more imperative for good ventilation
and better thermal comfort [22]. Thermal atmospheres, satisfaction and suitability
are all prejudiced by the contest among one’s prospects regard to the indoor envi-
ronment in a specific situation [23]. Excessive energy savings attained by permitting
air-conditioning process a broader variety of the indoor temperature variation [24].
There have been numerous factors affecting thermal comforts such as behavioural
and cultural aspects, space layout, option of regulate over the situation, thermal
antiquity and separate predilections [25].

2 Methodology

2.1 Measurement of Indoor Air Quality

Through three ways, IAQ could be improved, i.e. ventilation, measurement of indoor
air and control of source emission. Measurement of indoor air could be carried out
place in new construct buildings earlier or later indoor habitation, depending upon the
certification requires [4]. Liang et al. (2014) performed an environmental monitoring
study in few buildings climatic change as well as to determine change in IAQ [26].
The study also included air temperature, globe temperature, relative humidity, sound
level, airspeed, VOCs and concentration of CO2 , Similar study conducted by Pei et al.
(2015), by using digital instruments to measure the indoor and outdoor pollutant. In
his study, a questionnaire was developed to take update on resident’s habit and their
satisfaction [27]. Only in a few researches, the real assessment of IAQ was carried
out by recording the CO2 level or additional pollutants, and determining the rate of
ventilation, so that the definite exposures in the green constructions could be defined
[2, 26, 28]. In many studies, endeavouring to match green buildings and conventional
buildings to regulate for perplexing issues could be sparse [29]. In China, to examine
the IAQ and inhabitant gratification of green buildings, the study group had taken a
dozen methodical researches of office buildings. Contineous/periodic evaluation of
indoor environmental quality must be ensured through building users questionnaire
survey [30].
142 P. Babu and G. Suthar

2.2 Measurement of Thermal Comfort

Abdallah et al. (2014) carried out a study of the consequence of a combined system,
i.e. windcatcher for evaporative cooling on the ventilation and IAQ for a warm and
dry climate in Egypt. The aim of the study was to achieve the high performance and
the compact design by means of a satisfactory range of thermal comfort for indoor
environment and IAQ, and important dimension limits such as air gap, inclination
angle, chimney width along with this windcatcher’s width and depth were enhanced
with numerical imitation [31]. According to ASHRAE standard 55 describes the
amount and the rate of ventilation necessary to achieve acceptable IAQ. The natural
ventilation system not only used for providing an adequate fresh air rate within
the indoor environments, but also used for refining thermal comfort conditions. A
numerical research of a windcatcher was conducted in semiarid and arid zone of
Mexico for the thermal comfort for residential buildings [32]. In order to identify the
thermal comfort environments, the mean temperature and velocity of various zones
inside the residential building were measured [33, 34].
Heat balance models (HBM): It is considered that the thermoregulatory system
of human body must keep the fundamentally continuous inside temperature of the
body. Analogously, the consequences of the instant thermal comfort environment
could be arbitrated by the mass and heat transmission among the bodies and the
neighbouring environment. To sustain a continual body temperature, people should
reply physiologically to the thermal unevenness with its environment for thermal
comfort inside the building. It was presumed that thermal sensations for inhabitant,
i.e. feeling cold and hot were normally comparative to the extent of these answers
must measure the mean skin temperature and latent heat loss which must come in the
standard temperature and relative humidity range. The IAQ guidelines have been set
and describe thermal comfort parameters and the control of known and specifiable
contaminants to achieve acceptable IAQ [35, 36].

2.3 Problems Associated with Green Building

There are five major issues which affect the indoor environment of the green build-
ing such as inter-individual variances and satisfaction, climate situation, the role of
nations, outside thermal objectivity and inadequate thermal comfort [23, 35]. It was
found that resident with “pro-environmental” defiance towards more “forgiving” to
accept their instantaneous environment inside the green buildings [37]. Comfort-
ing culturally persuaded clothing standard and inhabitant prospects of meticulously
measured the indoor environments to substantial development in attaining an appro-
priate equilibrium between the energy use, thermal comfort and minimum impact
on the environment [38]. Additional effort in the cultural and socio-economic area
must essential, and post-tenancy assessment of current environment and the equiv-
alent energy ingesting to make better thoughtful regarding the issues influencing
Indoor Air Quality and Thermal Comfort in Green … 143

indoor environment [35]. Issues arise like sick building syndrome (SBS), illness and
increase in indoor pollutants could affect the overall efficiency of the inhabitants.
Various illnesses which are related to mental health and the illnesses which are not
simply perceptible in the limited terms could cause major difficulties in the lengthy
term, i.e. cardiovascular diseases, obesity and asthma due to poor IAQ [39, 40].
Therefore, in extremely polluted cities, old people and kids/infants could be affected
due to microclimatic circumstances considered as thermal discomfort which in the
body for longer time intervals. Few research studies also carriedout to resolve the dif-
ferent natural ventilation systems by comparing the thermal comfort indices within
the buildings [41]. According to ASHRAE Standard 62.1 (2013), describes the prac-
tice of ethics in building through codes and guidelines essential ventilation rates,
filtration, outside air quality and the precise pollutants of attention and pollutant
concentration parameters [16, 42]. The main problem for energy and thermal com-
fort regulation in building mechanization was to stability the struggle between the
people’s comfort and the energy consumption. Therefore, the thermal discomfort
was happened due to the low relative humidity [43, 44].

2.4 Solutions for Thermal Comfort and Indoor Air Quality

The energy efficiency of the green building measured the reduction in the cooling and
heating loads by enhancing envelope’s thermal integrity. It also raises the effective-
ness of cooling and heating of the equipment and depleting system’s energy through
efficient control methods [42]. Solution for newly constructed buildings such as
removal of specific source emissions from the building materials, air cleaning through
chemical and physical process and by increasing natural or mechanical ventilation
systems [13]. Selection of furnishings and other building materials must have low
toxicity. The control approaches must have implemented to decrease the amount of
pollutant in an indoor environment below the standard limits. Basically, there were
three strategies utilized for improving the IAQ inside the green buildings such as
source elimination, weakening of the interior pollutants by ventilation and control
of local source (Table 1).

3 Conclusion

IAQ is the major issue facing by the occupants, and it may cause due to daily activ-
ity and its specific source emission within the building. The concentrations of indoor
air pollutants mainly depend upon their generation rate, volume of the indoor environ-
ment, mixing efficiency in the indoor space and the decay rates of the pollutants and
improper ventilation and inadequate design of the buildings. This study suggested
some strategies by providing a proper natural or mechanical ventilation system for
both the IAQ and thermal comfort through which these problems can be solved.
144 P. Babu and G. Suthar

Table 1 Strategies used for improving the IAQ [42]

Approaches Discussion
Ventilation through heat recovery The rate of outdoor air is maintained
Outdoor air systems Reduce energy consumption and enhance IAQ
with simplifying controls. More suppleness in
cooling and heating strategies
Ventilation through displacement Outdoor air is less, improved IAQ in living
zone but not relevant in entire spaces
Natural ventilation Mechanical cooling is less, outdoor air is
more, improve thermal comfort and IAQ
Envelope tension Permeation is depraved for IAQ and thermal
comfort
Adequate distribution of air Energy efficiency, thermal comfort and good
IAQ could be achieved
More efficient particle filtration Improved equipment efficiency, cleaner supply
air filter installation and maintenance critical
Source control and make the lower ventilation Outdoor air is less with the same or improved
IAQ and thermal comfort
Source characterization must necessary

Thus, the reduction of air pollutant such as NOX , SOX , PM10 , VOCs, CO, CO2 can
be observed. The study provides the detail insights of the health issues caused due
to poor IAQ which may be acute or chronic in nature. Overall, a green building can
attain the full efficiency with respect to IAQ and thermal comfort by considering
the rule and guidelines given the various standard codes of international or regional
levels.

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Heterogeneous Photocatalysis for Indoor
Air Purification: Recent Advances
in Technology from Material to Reactor
Modeling

Mohan V. Lekshmi, S. M. Shiva Nagendra and M. P. Maiya

Abstract Heterogeneous photocatalytic oxidation (PCO) has attracted much atten-

tion in indoor air-purification applications. Recently, researches focus on developing
novel photocatalyst based filters for integrating with the heating, ventilation, and
air conditioning (HVAC) systems as well as portable air purifiers. A comprehensive
knowledge on factors influencing the indoor volatile organic compounds (VOCs)
degradation has been established both in bench-scale and pilot-scale experiments.
This paper reviews the current status of PCO material technologies, coating meth-
ods, performance test methods, and modeling for real-world indoor air-purification
application. Due attention to the basic principle of PCO and the effect of operating
parameters is provided, followed by a discussion on the modes of PCO application
for buildings. The review also concentrates on the practical limitations in scaling-up
PCO air purifiers for large-scale applications. Some recommendations for the future
research on improving material selection and reactor design to minimize by-product
generation and to promote commercialization are also discussed.

Keywords Titanium dioxide · Volatile organic compounds · PCO building

material · HVAC filter · Air purifier

1 Introduction

Indoor air quality (IAQ) has attracted much research interest in the past decades.
Poor IAQ has a significant influence on occupant satisfaction, comfort, productivity,
and health. Previously, it was reported that the indoor levels of certain air contam-
inants such as the volatile organic compounds (VOCs) could be five times higher

M. V. Lekshmi · S. M. Shiva Nagendra (B)

Environmental and Water Resources Engineering Laboratory, Department of Civil Engineering,
Indian Institute of Technology Madras, Chennai 600036, India
e-mail: snagendra@iitm.ac.in
M. P. Maiya
Refrigeration and Air Conditioning Laboratory, Department of Mechanical Engineering,
IIT Madras, Chennai 600036, India

© Springer Nature Singapore Pte Ltd. 2020 147

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_16
148 M. V. Lekshmi et al.

than outdoor air. VOCs are major class of indoor air pollutants common in domestic
and commercial buildings. In indoors, VOCs can be majorly emitted from furniture,
building decorations, consumer products, cooking, smoking or outdoor traffic [1].
The adverse health implications of VOCs range from sick building syndrome (SBS)
symptoms and respiratory illnesses to even cancer and death. Also, VOCs take part in
secondary organic aerosol (SOA) formation in indoor air and thus, exacerbates occu-
pant exposure to undesirable air pollutants. Several air-cleaning technologies have
been studied in the past for VOC abatement, i.e., adsorption, non-thermal plasma,
ozonation, ultraviolet germicidal irradiation, etc. [2–4]. While adsorption, the typi-
cally used technology for VOC removal requires regular filter replacement, advanced
oxidation processes such as photocatalytic oxidation (PCO) completely mineralize
organic pollutants rather than accumulating them and hence, has a longer lifetime.
Other advanced technologies such as non-thermal plasma and ozonation were stud-
ied for potential VOC removal. However, the high energy consumption and toxic
by-product (i.e., ozone) formation from such technologies have posed a significant
challenge.
Heterogeneous photocatalysis has emerged as a promising technology for indoor
air-purification applications due to its room-temperature operation, non-selectivity
to a wide range of indoor VOCs, and cost-effectiveness [5]. Although numerous
researches have reported on various aspects of PCO for indoor air purification, namely
material development [6], effect of controlling parameters [7], modeling [8], by-
product quantification [9] and scale-up [10], the commercialization and practical
application of the technology are still in developmental stages.
PCO uses a semiconductor material as catalyst and a light source to convert
organic pollutants into harmless end products, namely CO2 and H2 O [5]. Recently,
several novel photocatalysts are being investigated for indoor air purification [6, 11,
12]. Not to mention, titanium dioxide (TiO2 ) is still the most common photocatalyst
reported in studies, mainly due to its stability, easy availability, non-toxicity, and
relatively less cost [13]. However, overall degradation efficiency using TiO2 depends
upon reducing the recombination rate of charge carriers (electrons and holes) and
expanding photoactivity in visible light spectra [14]. Several modifications to TiO2
photocatalyst, namely doping, coupling, and addition of co-adsorbent have been
reported to overcome its wide band gap and improve photodegradation efficiency in
the visible region [13].
PCO technology is investigated for building applications due to its air purifica-
tion, self-cleaning, and anti-bacterial properties [15]. TiO2 -coated filter are studied
for use in portable air purifiers and in-duct heating, ventilation, and air condition-
ing (HVAC) systems [15, 16]. The application of photocatalyst integrated building
materials is not uncommon since the early 1990s. TiO2 has been investigated for its
use in construction materials (pavement blocks, concrete, and tiles) and furnishings
(cement mortar, wallpapers, glass, paint, etc.) due to its mechanical stability and
photocatalytic activity [15].
However, the practical application of PCO suffers from two important drawbacks,
namely by-product formation and accumulation of intermediates on catalyst surface
progressively leading to catalyst deactivation and reduction in degradation efficiency.
Heterogeneous Photocatalysis for Indoor Air Purification … 149

Fig. 1 Review framework of PCO in indoor air purification

The past studies have not addressed the issues in scaling-up PCO technology for
real-world applications. Thus, there is a need for research in the development of an
efficient PCO purifier for large-scale indoor air-purification applications.
The present paper intends to review the current advances in the area for PCO for
indoor air purification including photocatalyst materials, influencing factors, building
applications, test methods, and models available as shown in Fig. 1. The review,
finally, comprehends the limitations and the future scope of PCO for indoor air-
cleaning applications.

2 UV-PCO Principles

The photodegradation initiates when the electrons are excited by incident light energy
exceeding the band gap of semiconductor material (Fig. 2). As the electron gets
shifted from valence band (VB) to conduction band (CB), a hole is formed which
acts as a powerful oxidizing agent. In this way, the electron–hole pairs are formed.
The excited electrons reduce O2 into superoxide radical O·2− and the holes (h+ ) oxi-
dizes water molecule into hydroxyl radical (OH· ). The charge pairs are formed in
femtoseconds (fs) and recombined within a few tens of nanoseconds [13]. The effec-
tiveness of VOC degradation, therefore, lies on effective charge transfer from the
semiconductor surface to the organic contaminants.
For TiO2 in the anatase form, UV light (λ = 360 nm) can be suitable to excite
its band gap of 3.2 eV. While excited with UV irradiation, TiO2 forms electron–hole
pairs as given in Eq. (1).
150 M. V. Lekshmi et al.

Fig. 2 Schematic
representation of PCO
mechanism

TiO2 + hϑ → h + + e− (1)

The photogenerated electrons must be accepted by electron acceptors within the

few nanoseconds before it recombines with the holes to reduce charge recombination.
Nanostructured materials such as nanorods, nano-fibers, nanotubes, and nanospheres
can reduce the transfer distance between the surface and electron acceptors and are,
hence, preferred [13]. Various parameters such as surface area, pore size, crystalline
phase, and size affect the photocatalytic performance.

3 PCO Materials

Among semiconductor photocatalysts, TiO2 has become attractive in air and water
treatment due to its non-toxicity, relatively less cost, photo-stability, and rapid elec-
tron transfer to molecular oxygen [17]. TiO2 in both pure and modified form has
been proven to be effective for a wide range of indoor VOCs.
As discussed in the previous section, the photocatalytic activity of catalyst depends
on the crystallinity of TiO2 [18]. TiO2 photocatalysts are available in three crystal
phases namely, anatase, rutile, and brookite. The former type is more active than
rutile due to higher electron-hole pair generation, greater affinity toward O2 , higher
number of surface hydroxyl groups, and lower recombination rate [19]. In this regard,
degussa-P25 TiO2 is the most commonly used photocatalyst in past studies due to the
presence of both anatase and rutile phases (75% anatase and 25% rutile), rutile particle
band bending in presence of anatase phase, and single crystallites nature of P25
[20–22]. Besides the crytallinity, the surface area and porosity of TiO2 significantly
influence the photoactivity. Larger catalyst surface area and smaller pore size is
known to enhance the photocatalytic activity [23]. Photocatalyst loading density on
the support is another major factor influencing the decomposition of pollutants as it
determines the available catalyst surface area and number of active sites. The higher
the catalyst layer thickness, higher is catalyst surface area available for adsorption of
Heterogeneous Photocatalysis for Indoor Air Purification … 151

Fig. 3 PCO material modifications

contaminants [24]. However, excessive catalyst loading can cause shadowing effect
and masks part of catalyst surface wherein no charge carriers are generated. Several
studies have reported optimum catalyst loading beyond which the photocatalytic
activity declines [23, 25, 26].
Recent studies are focused on developing visible light-responsive photocatalysts
which can be easily employed indoors and inside vehicles. Doping the photocatalyst
is a surface modification technique to lower the band gap energy of catalyst and
shift toward the visible light region. Several studies on doping TiO2 with metals
(Mn [27], Ni [28], Fe [29], and Pt [30]) and non-metals (C [31], N [32], and F [33])
are available. The metal ion dopants in the crystalline matrix of TiO2 significantly
improve photoactivity apart from reducing recombination rate [34]. Similarly, binary
catalysts are developed by integrating TiO2 with other semiconductors such as WO3 ,
Ag3 VO4 , SiO2 , SnO2 , MnCO3 , CdS, ZnO, and porous materials such as activated
carbon with the aim to expand its photo-activation into visible spectra. The different
TiO2 modifications reported in previous studies are summarized in Fig. 3.

4 Preparation Methods of the Photocatalyst

The surface properties of the semiconductor material determine its photocatalytic

activity [35]. The physical properties of the catalyst such as pore size, pore thick-
ness, and distribution and crystalline structure need to be tuned which greatly depends
upon the preparation technique adopted. Various preparation methods of TiO2 photo-
catalyst have been reported in published literature, namely sol–gel method [26, 27],
vapor decomposition of titanium alkyloxides [36], gas-phase hydrolysis of TiCl4
[37], and hydrothermal technique [38]. Yu et al. [35] prepared a porous TiO2 coat-
ing using sol–gel method using tetrabutylorthotinate as precursor and polyethylene
glycol as organic polymer followed by calcination at 520 °C. A similar study by Mar-
tins et al. [39] evaluated the photocatalytic performance of TiO2 -coated AC prepared
by sol–gel technique compared to TiO2 P25. The TiO2 -coated AC obtained using
titanium isopropoxide as precursor followed by pyrolysis at 500 °C showed bet-
ter structural properties for photodegradation [39]. Rubio et al. [36] prepared titania
powder by gas-phase hydrolysis of titanium tetrabutroxide/butanol mixture in a pres-
surized (N2 atmosphere) and thermostatically controlled glass container at 180 °C.
152 M. V. Lekshmi et al.

In the process, titanium tetrabutroxide and water were sprayed inside the hydrolysis
chamber (25°) where they react to form TiO2 particles which was further calcinated
at 450 °C for 2 h [36]. In the case of hydrothermal method, the reactions are carried
out in a closed vessel containing the aqueous solution and the products are recovered
and used after attaining room temperature. Liu et al. [38] prepared a highly active
TiO2 /AC composite by adding TiCl4 dropwise into (NH4 )2 SO4 /HCl/water mixture
followed by heating at 98 °C for 1 h. Among various techniques, the sol–gel method
has been recognized as an efficient and frequently reported method to fabricate a
porous coating of TiO2 [35].

5 PCO Substrates and Coating Techniques

Catalyst immobilization onto the substrate is one of the key determinants affecting
PCO efficiency for degrading indoor air pollutants. The coating technique and type
of substrate need to be carefully selected for effective immobilization. In previous
studies, substrates such as carbon nanotube [40], activated carbon filter (ACF) fibers
[41], zeolites [42], glass [43], glass fiber filter (FGF) [44], stainless steel [45], silica
materials [46] etc. have been used as substrate. Activated carbon filters have high
porosity with higher surface area for adsorption and enhance the photocatalytic activ-
ity against organic pollutants [47, 48]. Some commonly used carbon substrates in
previous studies are carbon felt (ACFF) [49, 50], carbon cloth [44], carbon paper
[51], carbon powder [45], granular carbon [52], graphene [53] etc. Studies have
compared the photocatalytic activity of TiO2 /ACF against TiO2 /FGF systems and
concluded that the synergetic adsorption–photodegradation using the former has a
higher efficiency for gas-phase VOCs removal [10, 12, 47].
In the case of PCO building materials, a TiO2 -coating on the glass, concrete
blocks, filter, etc., was obtained by dispersing the nanoparticles solvents such as
ethanol, polymer matrix, etc., followed by ultrasonication treatment to form a uni-
form suspension. The PCO-coating technique adopted should provide a stable coat-
ing, proper contact between the catalyst and pollutant molecules, be cost-effective
and non-selective to substrate types. Commonly adopted coating techniques are dip
coating [54] and spray coating [55]. Other methods such as electrophoretic deposi-
tion (EPD) [56], sol–gel method [57], and chemical vapor deposition (CVD) [58]
are also reported in published literature. The dip-coating technology is an especially
suitable method for flat substrates (concrete blocks, glass, etc.) to form a uniform
thin layer of TiO2 from the suspension [59] (Table 1).

6 PCO for Indoor Air Purification

Photocatalytic oxidation is an economical and effective method for degrading organic

pollutants and bioaerosols in indoor air. The technology is characterized by lower
Heterogeneous Photocatalysis for Indoor Air Purification … 153

Table 1 Effect of substrate material on removal efficiency of VOCs

Pollutant, Photocatalyst/substrate Removal efficiency (%) Reference
concentration With substrate Pure TiO2
BTEX, 20 ppb Activated carbon felt Benzene: 74; Benzene: 57; [41]
Toluene: 78; Toluene: 69;
Ethylbenzene: Ethylbenzene:
73; Xylene: 86 67; Xylene: 72
Formaldehyde, Activated carbon filter 79.4 25.7 [50]
1 ppm
Acetaldehyde Activated carbon Acetaldehyde: Acetaldehyde: [43]
and toluene, powder 60, Toluene: 47 75, Toluene: 36
5 ppm
Toluene, Activated carbon felt 57–100 41 [47]
230–1150 ppm
Toluene, Activated carbon felt 100 65.4 [60]
80–174 ppm

power consumption and maintenance requirements [34]. However, high recombina-

tion rate of charge carriers (electrons and holes) and limited photocatalytic activity
under visible light is the major drawback of the process and reduces the overall
degradation efficiency [13]. A few studies reported TiO2 -coated activated carbon
filters for HVAC applications which showed enhanced photocatalytic activity due
to the large surface area of the catalyst and lower charge recombination [47, 46,
60, 61]. However, past studies were conducted in laboratory-scale reactors and scal-
ing up of technology to operate under real-world conditions has many limitations.
For example, most studies considered low airflow velocities and high inlet pollutant
concentration (ppm) which is very different from realistic conditions [62]. There-
fore practical design and application of PCO for indoor air purification need more
extensive research addressing these knowledge gaps.

7 Portable Air Purifiers

An efficient PCO air purifier should have a low-pressure drop, sufficient mass transfer
between the gas phase to the solid catalyst, and better light utilization [16]. There-
fore, a PCO air purifier uses an air mover, catalyst supported on the suitable substrate
and a light source. Past studies investigated the effectiveness of PCO air purifiers to
remove individual VOC and mixture of VOCs present in real-world indoor condi-
tions. Kolarik et al. [63] evaluated the improvement in perceived indoor air quality
using a PCO air purifier in test rooms doped with typical building chemicals. The
study showed that the use of PCO air purifier significantly improved the perceived
air quality, reduced odor, and pollutant levels. Another study by Gunschera et al.
154 M. V. Lekshmi et al.

[64] tested PCO air cleaners in 24 and 48 m3 test chambers for degradation of sub-
ppm levels of common indoor VOCs (aldehyde, toluene, α-pinene, decane, etc.). The
study concluded that significant levels of by-products (aldehyde and acetone) formed
during reaction need to be addressed carefully before real-world application. How-
ever, portable PCO purifiers can be easily deployed and maintained when compared
with PCO integrated into HVAC ducts.

8 PCO Coated HVAC Filter

Urban buildings are provided with HVAC systems to provide ventilation and maintain
adequate IAQ. For this purpose, HVAC ducts are equipped with various air-cleaning
technologies operating at lower energy costs. An extensive research database on the
application of PCO for indoor air-cleaning in an HVAC system based on laboratory-
scale experiments has been published to date [22–24]. The study results showed
that PCO is attractive for integrating with existing and new HVAC systems due to
its room-temperature operation, modular design, lower pressure drop, and better
mass transfer rate [18, 25]. Yu et al. [65] tested the VOC removal efficiency of
PCO filter under various conditions (air change rate = 0.5–1.5 h−1 and RH = 30–
70%) and reported that efficiency increased with RH and decreased with filter face
velocity. Yang et al. [16] developed TiO2 -coated foam nickel air purifier for HVAC
systems and optimized the design and energy consumption. The study pointed out
that adjusting the purifier configuration can increase the residence time of pollutants
and decrease the flow resistance. Therefore, there is a need to develop an efficient
PCO technology for integrating with HVAC ducts and reducing building energy
consumption. However, a knowledge gap exists on the behavior of the PCO air
cleaners under real-world conditions such as high air flow rates, low residence time,
ppb level pollutant concentration, and presence of a mixture of organic vapors.

9 Building Materials

TiO2 photocatalysts can be integrated with building materials such as concrete with-
out altering its properties and can be activated under solar irradiation. It can be used
in other forms such as cement mortar [66], glass [67], wallpapers [68], paint [69],
etc. Photocatalytic paints are the most commonly used PCO material for improving
indoor air quality. Maggos et al. [70] tested a TiO2 -containing paint for degrading
NOx gas emitted in a closed parking area whose ceiling was covered with acrylic
TiO2 -containing paint. The results indicated a significant reduction in NO (19%) and
NO2 (20%) levels. Auvinen and Wirtanen [69] investigated six different photocat-
alytic paints containing different binders such as lime, silica sol–gel, polyorganic
siloxane, and organic binders for degrading formaldehyde as well as a mixture of
indoor VOCs. The study did not show any significant removal of VOCs but showed
Heterogeneous Photocatalysis for Indoor Air Purification … 155

an increase in formaldehyde levels due to the reaction. Also, the study also examined
different substrates such as glass, polymeric plaster, and gypsum which did not have
any influence on photocatalytic activity.
Similarly, another study by Kolarik and Toftum [71] examined improvement in
perceived air quality using a cement-based photocatalytic paint coated on gypsum
board (13 m2 ). The study could not conclude any improvement in perceived air quality
using photocatalytic paint. Also, the photocatalytic activity of TiO2 can reduce the
long-term durability of polymeric paints. Recent studies reported that photocatalytic
materials such as lanthanum and graphene-doped TiO2 could be used for paints which
can suppress and tune photoactivity of TiO2 to balance between the mechanical
stability of coating and improving indoor air quality [29, 30].

10 Factors Influencing PCO

This section briefly explains the effects of relative humidity, airflow velocity, light
source, and pollutant characteristics on the photodegradation of gas-phase VOCs.
The comprehensive review of the factors affecting PCO is available in Mamaghani
et al. [72].

11 Relative Humidity (RH)

RH can have either a positive or negative influence on PCO efficiency. In other

words, the water molecules act both as a precursor for the formation of hydroxyl
radical (oxidizing agent) and as a competitor for active adsorption sites on TiO2
surface. The competitive adsorption reduces the adsorption capacity of VOC and
reduces the reaction rate. Therefore, change in RH can have a significant impact
on PCO efficiency. Some studies have reported improvement in PCO efficiency
for toluene and benzene oxidation with an increase in RH [73]. A similar effect
on benzene removal was achieved by Bouazza et al. [74]. However, the propene
conversion efficiency reduced with an increase in RH. Another study by Mo et al. [75]
reported a negative effect of an increase in RH on toluene removal efficiency with inlet
concentration in the range of 90–250 ppb. However, at higher toluene concentrations
(400–800 ppb), an optimum RH value was reached achieving maximum removal
efficiency [75]. Additionally, doped TiO2 can improve the photocatalytic efficiency
when compared to undoped TiO2 at the same RH level [13]. Therefore, it can be
concluded that the effect of RH on conversion efficiency depends upon the type and
level of pollutant and also the type of photocatalyst used.
156 M. V. Lekshmi et al.

12 Airflow Velocity and Residence Time

Airflow rate is a key determinant affecting the PCO efficiency for VOC oxidation.
With the increase in airflow velocity, two antagonistic effects were brought forth,
namely the decrease in residence time of the pollutant molecules near catalyst sur-
face and the increase in the mass transfer of pollutant molecules from bulk to cat-
alyst surface [76]. The reduction in residence time inside the photoreactor reduces
the adsorption of pollutant molecules and lowers the photodegradation efficiency
whereas the increase in mass transfer enhances the PCO reaction rate. But consider-
ing the airflow velocities consistent with HVAC systems, the improvement in PCO
efficiency due to increase in mass transfer is offset by the significant reduction in res-
idence time [72]. Similarly, under the shorter residence time encountered in portable
air cleaners, the probability of contaminants contacting the hydroxyl radicals may
be meager. Sleiman et al. [77] observed around 30% reduction in toluene removal
efficiency with increase in airflow rate from 0.07 to 0.35 m3 min−1 . Use of the syn-
ergetic adsorption–photodegradation effect of TiO2 combined with activated carbon
can have more significant in such cases.

13 Light Source and Intensity

Light intensity is another crucial factor affecting the VOC photodegradation rate
(Table 2). Generally, it is agreed that PCO efficiency increases with an increase in
light intensity [78]. The increase in light intensity enhances the formation of oxidant
species, enhances the photoactivity, and degradation of pollutants [79, 80]. Some

Table 2 Different light sources, their merits and demerits

Light source Merits Demerits Reference
Visible light Can degrade pollutants at Lower degradation efficiency [82]
visible range, ease of compared to UV-PCO
commercialization, lower
operational cost
LED light Inexpensive, high current to Wavelength of LED is above [83]
light conversion with negligible 360 nm and therefore requires a
heating, longer life special LED responsive catalyst
UV-PCO Moderate to high VOC Catalyst deactivation or [84]
destruction efficiency poisoning, needs catalyst
replacement, catalyst activity
only in UV region restricting
use in indoors and inside
vehicles
VUV PCO Higher degradation efficiency, Produces ozone as by-product [79]
lower catalyst deactivation
Heterogeneous Photocatalysis for Indoor Air Purification … 157

studies reported the use of vacuum UV (VUV) lamps wherein pollutant degradation
takes place through photolysis, radical oxidation, and ozonation [36, 37]. The use
of VUV lamps has been reported to improve the degradation efficiency compared
to conventional UV lamps irradiating at 254–365 nm [7]. It was also reported that
VUV lamps provide strong oxidation and prevent the formation and accumulation
of intermediates which in turn reduces the catalyst deactivation [81]. However, PCO
using VUV lamps produces ozone as a by-product which needs to be treated properly
[36, 39].

14 Inlet Pollutant Concentration

One of the main gap in the published literature on PCO of gas-phase VOCs is that most
of the past studies focused on high inlet pollutant concentrations (ppm level) whereas,
in real-world indoor conditions, VOCs are present only in ppb levels. Interpolating
the results from previous studies can be misleading as the rate of reaction in the
presence of high inlet concentrations will be entirely different compared to low
concentrations. The past studies have reported that PCO efficiency decreases with an
increase in inlet pollutant concentration irrespective of the type of target VOC [31,
38]. In general, at higher pollutant concentrations, the ratio of the sum of reactive
species and active sites on catalyst surface to pollutant molecules decrease resulting
in incomplete degradation of VOCs.

15 PCO Performance Testing

Performance evaluation of PCO for VOC degradation under real indoor conditions
needs to be carried out before using the technology for envisaged applications. Exten-
sive research in the past focused on VOC removal using PCO in bench-scale, pilot-
scale, and full-scale experiments. Most of the studies applied formaldehyde [65],
toluene [47], benzene [85], and trichloroethylene [86] as typical indoor VOCs for
performance evaluation. However, so far, there is no standard test method available
for assessing the air-cleaning performance of photocatalytic systems. Therefore, it is
difficult, the compare the result across available studies which are conducted under
different environmental conditions such as RH, airflow rate, light source, etc. [87]. A
recent study [10] evaluated the photocatalytic degradation of toluene and isobutanol
obtained by using a bench-scale, pilot-scale, and full-scale reactor under real-world
conditions (low pollutant concentration, short residence time, and high airflow rates)
by maintaining the RH value at 50 ± 5%. The study also compared the effect of UV
light type (UVC and vacuum UV lamps) on photodegradation efficiency. The study
concluded that the removal efficiency obtained using bench-scale reactors are higher
than the pilot and full-scale reactors. Thus, scale-up of large-scale PCO systems
for indoor air purification based on laboratory-scale results may be inaccurate. The
158 M. V. Lekshmi et al.

removal efficiency also depends upon the type of reactor design adopted due to the
variation in incident radiation flux as well as the contact between photocatalyst and
target pollutant [59].
Clean air delivery rate (CADR) is one method typically adopted for evaluating
the air-cleaning performance of PCO reactors [34]. Higher the CADR value, faster
the air purifier cleans the air. For PCO air purifiers, CADR can be written as [88]:

CADR = G × η (2)

where G is the airflow rate of the PCO air purifier, and ï is the fractional VOC
removal efficiency. However, this index does not account for the by-product formation
from PCO chemical reactions. Therefore, extensive studies have to be conducted to
investigate the absence of carcinogenic by-product (i.e., formaldehyde, benzene)
formation from PCO purifiers before large-scale application.

16 PCO Modeling

An effective PCO reactor design is necessary before scale-up and commercialization

of the technology [89]. A properly designed PCO system should have the following
characteristics, namely low pressure drop, adequate mass transfer from the gas bulk
to solid catalyst surface, proper utilization of incident radiation, low power consump-
tion, and complete mineralization of the contaminants. Thus, design of a proper PCO
reactor requires insights on the reaction kinetics (adsorption, desorption, and pho-
todegradation), mass transfer rates from the gas phase to catalyst surface and also
the photon transfer. Optimization of radiation (light intensity) and reactor design
enabling effective mass transfer are inevitable for developing an energy-efficient
PCO air-purification system. PCO models can be a useful tool for design, optimiza-
tion as well as scale-up of PCO reactors for large-scale applications. In the past,
studies have focused on various aspects of modeling, namely flow dynamics [90],
reaction kinetics [76, 91], and radiation modeling [92, 93]. Recently, CFD models
have been reported to accurately predict kinetic parameters along with fluid flow
simulation [94, 95]. A combined modeling of radiation field along with these CFD
models is required for proper design of PCO system for the future scale-up.

17 Kinetic Rate Models

The kinetic rate models give information on how the reactants are converted into final
end products. PCO mechanism can be explained to be surface catalysis where reaction
rate depends upon the surface coverage of pollutant molecules on the catalyst surface.
The commonly used surface catalysis model is Langmuir–Hinshelwood model. The
reaction rate (r) according to the L-H model can be given as follows:
Heterogeneous Photocatalysis for Indoor Air Purification … 159

K p K a Co
r= (3)
1 + K a Co

where K a is Langmuir adsorption constant or reaction kinetic constant in m3 g−1 , K p is

degradation rate constant mg m−3 min−1 , and C o is the inlet pollutant concentration
in mg m−3 . The value of the kinetic rate can be estimated by using curve-fitting
methods. Therefore, the reaction rate models can be used to predict the speed at
which pollutants can be removed by knowing the inlet pollutant concentration.

18 Radiation Field Models

The radiation field models can be used to optimize the distribution of light radiation
intensity inside the PCO reactor to get uniform irradiation on the catalyst surface.
For this purpose, steady-state mathematical-based models such as first-principles
and predictive engineering models have been used in the previous studies [60, 51].
In general, these models combine the energy conservation and momentum conser-
vation principles of fluid flow and pollutant species accounting for target pollutant,
by-product and product concentration fields. Raupp et al. [96] reviewed the use of a
radiation field model for the design of monolith PCO purifiers. Hossain et al. [90]
developed a three-dimensional convection–diffusion model for monolith PCO reac-
tors using first-principle radiation field sub model. Imoberdorf et al. [92] proposed a
Monte Carlo based model coupling with the ray tracking method. The model takes
into account the interaction between the TiO2 particle and photons with due con-
sideration toward the shadowing effect of the particles, reflection and absorption by
the TiO2 films. The study concluded that radiation field models are capable of accu-
rately predicting the photodegradation of formic acid on catalyst surface [92]. Thus,
radiation models can be used to optimize the design of air-purification systems and
to scale-up for commercial applications.

19 CFD-Based Models

Previous studies have reported that CFD models can be employed to predict the
PCO reaction mechanism. In addition to steady-state reaction data, the CFD-based
models can provide spatial and temporal variation in pollutant removal both in bulk
and catalyst surface. Verbruggen et al. [94] presented a CFD-based model for mod-
eling adsorption and degradation of acetaldehyde on a photocatalytic filter fiber. The
study concluded that the adsorption constant and maximum adsorption capacity data
obtained from CFD modeling could be valuable inputs to kinetic rate models and
hence, can be used for the future air purifier designs. A recent study by Roegiers
et al. [95] reported a combined computational fluid dynamics (CFD)-radiation field-
reaction kinetic model for modeling acetaldehyde degradation in multi-tube PCO
160 M. V. Lekshmi et al.

reactor. By integrating the CFD models with L-H kinetics and uniform irradiance
distribution, it will be possible to precisely model PCO air-purification systems [95].

20 Limitations

Although the use of PCO for indoor air purification has been proposed in earlier
researches, there are some technical aspects that are still unanswered. The major
drawbacks of PCO technology are the deactivation of the photocatalyst, low photo-
catalytic activity, and generation of by-products [87]. Undesirable by-products can
be more toxic and irritating than the target VOCs [59]. The photocatalyst lifetime is
important in overall process cost as it determines the frequency of catalyst replace-
ment [97]. Previous studies clearly stated that PCO reactions produce by-products
such as aldehydes, ketones, and organic acids besides CO2 and H2 O. The formation
of intermediate compounds and their accumulation on catalyst surface causes catalyst
deactivation. This deactivation may be addressed by expanding the adsorption band
of the photocatalyst to visible range, reducing the electron-hole pair recombination,
and proper reactor design maximizing light utilization [87].

21 Summary and Future Perspectives

In developed and developing countries, people spend a major portion of their time in
indoor environments. Therefore, providing a safe indoor space has become a priority
to building designers and policy makers. Reduction in ventilation rate in modern
buildings has exacerbated human exposure to harmful volatile organic compounds
(VOCs). Available studies showed that VOCs are the major group of indoor air pol-
lutants present in common indoor environments such as houses, offices, cars, and
eateries. Ultraviolet photocatalysis has been reported to have immense potential for
indoor air-purification applications. Despite numerous researches have focused on
the technology, commercialization and scaling-up of PCO are still in its nascent
stages. The knowledge gap between available laboratory-based studies and actual
application of PCO technology for air decontamination needs to be addressed. Some
limitations of the technology, namely by-product generation and catalyst deactivation
have impeded the commercialization of technology. Certain catalyst modifications
such as doping and addition of adsorbents were shown to enhance the photocat-
alytic activity, increase the lifetime of PCO reactors reduce deactivation, and reduce
intermediate formation. Therefore, studies in the future should focus on developing
novel, efficient, and environmentally friendly photocatalytic materials and reactor
designs minimizing the generation of toxicants. Further, comprehensive modeling
study which couples, flow dynamics, reaction kinetics, and radiation modeling is
Heterogeneous Photocatalysis for Indoor Air Purification … 161

inevitable for a proper design of PCO reactor for real-world air-purification applica-
tions. The performance test methods should be standardized in the future for ease in
scaling-up the PCO reactors for real-world applications.

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Experimental Investigation of ISHRAE
IEQ Standard Focusing
on Implementation Aspects Through
Pilot Study

Shailendra Kumar, Nikhil Jain and Jyotirmay Mathur

Abstract In the year 2016, Indian Society for Heating, Refrigerating and Air-
Conditioning Engineers (ISHRAE) released India’s first indoor environmental qual-
ity (IEQ) standard. The present study demonstrates review of this IEQ standard and
shows the effect of seasonal variation on IEQ parameters. Measurements are taken in
two buildings having zones such as individual offices, open-plan offices, classrooms,
etc. Observations spanning over 12 months revealed that the arithmetic mean value
of thermal comfort parameters, indoor operative temperature, relative humidity (RH)
and floor surface temperature, are 26.6 ± 3.9 °C, 46 ± 17% and 26.7 ± 4.5 °C,
respectively. Indoor air quality (IAQ) parameters, CO2 , PM2.5 and PM10 concentra-
tions, are 570 ± 176 ppm, 46 ± 22 µg/m3 and 116 ± 37 µg/m3 , respectively. Lighting
comfort parameters, illuminance and circadian lighting design, are 326 ± 140 lx and
341 ± 146 EML, respectively. Occupant satisfaction survey is also conducted, and
it is observed that occupant satisfaction for indoor air quality, thermal and lighting
comfort is 80%, 81% and 89%, respectively. Majority of the IEQ parameters in both
the buildings are found to be meeting the minimum threshold.

Keywords Indoor environmental quality · Field study · Standard

1 Introduction

Healthy and comfortable indoor environment is primary requirement of the build-

ing occupants as in urban environment residents spent most of their time indoors
[8]. IEQ is affected by building location, orientation, climatic conditions, occupant
behaviour and building systems and typology [15]. Indoor air pollutants have clear
association with the sense of well-being, occupant health and productivity. In addi-
tion to long-term, they can worsen conditions such as asthma, headache, respiratory
diseases, allergies, etc. Furthermore, both too high or too low temperature and humid-
ity, excessively bright or deficient lighting system, high noise level leads to increase

S. Kumar · N. Jain · J. Mathur (B)

Centre for Energy and Environment, Malaviya National Institute of Technology, Jaipur, India
e-mail: jmathur.mech@mnit.ac.in

© Springer Nature Singapore Pte Ltd. 2020 167

A. Sharma et al. (eds.), Indoor Environmental Quality,
Lecture Notes in Civil Engineering 60,
https://doi.org/10.1007/978-981-15-1334-3_17
168 S. Kumar et al.

in mental and physical stress levels in human body leading to health problems such
as concentration impairment, memory loss, digestive problem, sleep disorder, etc.
[9, 10]. Thermal comfort can be defined as “the state of mind which expresses
the satisfaction with thermal environment” [1]. It relates to the physical factors in
air-conditioned as well as naturally ventilated environment and therefore strongly
correlated with building energy consumption [4].
Improper lighting conditions such as too bright or too dark can create visual
discomfort. Lighting comfort directly affects the occupant’s work productivity and
efficiency. It is a subjective measure and directly dependent on factors like illumina-
tion, the risk of glare, luminous spectrum, brightness and luminance [6]. A proper
visual environment condition causes an increment in the productivity and well-being
of the building occupants [16].
IAQ is recognised to cause chronic and acute effects on the building occupant’s
health. It is directly connected to the concentration of pollutants and ventilation rates,
which is directly linked to Sick Building Syndrome [18]. For indoor environment,
indoor air quality is associated to chemical as well as physical causes which are
concentrations of CO2 , CO, respirable suspended particulate matter (PM2.5 , PM10 ),
total volatile organic compounds (TVOC), formaldehyde (CH2 O), SO2 , NO2, etc.
In the year 2016, ISHRAE released India’s first IEQ standard [11]. In this standard,
thermal comfort, indoor air quality, acoustic comfort and lighting comfort are defined
as elements of IEQ, and they have been further divided into parameters as shown in
Fig. 1.
Standard includes definitions for the elements affecting health and comfort, thresh-
old values of parameters contributing to these elements, measurement methodology,

Fig. 1 IEQ elements and parameter affecting these elements

Experimental Investigation of ISHRAE IEQ Standard … 169

Fig. 2 Geographical location of Building 1 and Building 2. Source Google Maps: https://www.
google.com/maps/place/Malaviya+National+Institute+of+Technology+Jaipur/@26.8617377,75.
8091142,824m/data=!3m1!1e3!4m5!3m4!1s0x396db66fe2879c7f:0xdfc843bf9b6f869a!8m2!
3d26.8630144!4d75.810592

specifications of measurement instruments and satisfaction survey. The threshold

values of parameters have been defined as three levels such as Class A (aspirational),
Class B (acceptable) and Class C (marginally acceptable). Class A level is compara-
ble to international standards. As this standard is applicable to residential as well as
commercial buildings which can have conditioned as well as unconditioned spaces,
some of the parameters are excluded in Class B and Class C.
In this study, measurement methodology proposed in ISHRAE’s IEQ standard is
reviewed and analysed through a pilot testing on two buildings in terms of where,
when and how to take measurements. Also, effect of seasonal variations on IEQ
parameter are analysed. Furthermore, along with physical parameter measurements,
occupant satisfaction surveys are also conducted.

2 Methodology

2.1 Overall Approach

In this study, IEQ measurements and survey are done three times a day and twice
a season at every potential measurement location. Time slot for measurement and
survey during a day is morning session (10.00 a.m. to 11.00 a.m.), afternoon session
(2.00 p.m. to 3.00 p.m.) and evening session (4.00 p.m. to 5.00 p.m.).
170 S. Kumar et al.

2.2 Site Description

The study is carried out at Malaviya National Institute of Technology, Jaipur

(26.8630° N, 75.8106° E). Jaipur is categorised in composite climate zone. Four
seasons are considered in composite climate zone. Summer seasons start from April
and last till June, July and August are considered as monsoon season, September
as post-monsoon season (considered as summer for present study), November to
February as winter season, whereas, October and March are moderate seasons [13].
Two buildings which are part of educational institutional have been selected for IEQ
investigations. Buildings are occupied between 8 a.m. and 5 p.m. during weekdays.
The detailed descriptions of both buildings are shown in Table 1.
The first building named hereafter as ‘Building 1’ is located away from heavy
traffic and is situated in an area with rich natural vegetation, while second building
named hereafter as ‘Building 2’ is only 65 m away from the roadway. Both buildings
have shared as well as individual offices, classrooms, conference halls and waiting
rooms in which some are air-conditioned, and others are unconditioned. Further,
pictorial views and geographical locations of Building 1 and Building 2 are shown
in Figs. 3 and 2, respectively.

Table 1 Building description

Parameters Building 1 Building 2
Area (Sq. Metre) 1400 (distributed over three 165 (single floor and three
floors having 25 rooms) rooms)
Construction materials Stone walls (Ground floor), Stone walls, asbestos roofing,
Brick walls (First and Second acoustic ceiling tiles
floor), RCC roofing
Orientation South-East, North-West South-East, North-West
Ventilation type Mixed mode Mixed mode
Occupancy 75 and variable 13 and variable
Measured occupant locations 66 10

Fig. 3 Pictorial view of Building 1 and Building 2

Experimental Investigation of ISHRAE IEQ Standard … 171

Fig. 4 Floor plan and potential occupant location at old administration and CEE building

3 Potential Measurement Locations

All parameters are measured at different potential measurement locations in the

identified buildings. Potential measurement locations are those where extreme value
of IEQ parameters can be observed such as near and away to the closed and open
window, door, ventilation system, artificial light source, under ceiling fan and air-
conditioning unit. Also, centre of the room is also considered potential measurement
location to cover overall effect within specified space [7, 11]. All locations are marked
in Fig. 4. Both occupant satisfaction survey and IEQ parameter measurements are
recorded at every potential measurement location. In this study, total 1824 occupant
responses are collected which include responses of 1520 males and 204 females.
This has done for four seasons spanning June 2017 and May 2018.

4 Instruments

Measurements are done by the instruments meeting the accuracy and resolution cri-
teria specified in IEQ standard [11]. The instruments are procured from the standard
manufacturers, and the details of the instruments used are given in Table 2.
172 S. Kumar et al.

Table 2 Specifications of instrument used

Instrument name Parameter Resolution Accuracy Measurement
(manufacturer methodology/sensor
name-model) type
Thermal comfort Air temperature 0.1 °C ± 0.5 °C Thermistor effect of
analyser (Testo-480) metals
Mean radiant 0.1 °C ±0.5 °C Thermocouple type
temperature K
Relative humidity 1% ±3%
Air velocity 0.01 m/s ±0.05 m/s Hot wire
anemometer
CO2 1 ppm ±5% NDIR
Illuminance 1 lx ±5% V-lambda curve
Surface Floor surface 0.5 °C ±1 °C Contact
thermometer (Testo temperature thermometer
905-T2)
Air quality monitor PM2.5 1 µg/m3 ±5% Light scattering
(ATS-Y09-PM) PM10 1 µg/m3 ±5% Light scattering

5 Measurement Methodology

All IEQ parameters are measured and analysed as specified in ISHRAE IEQ standard
[11]. Parameters such as mean radiant temperature, room air temperature, air veloc-
ity and relative humidity representing thermal comfort are recorded at 0.6 m and
1.1 m above floor for seating and standing positions, respectively [11, 14]. Operative
temperature can be obtained as the average value of room air temperature and mean
radiant temperature for occupants involved in sedentary physical activity (1.0 < met
< 1.3) provided the occupant is not exposed to direct sunlight and for air velocities
lower than 0.2 m/s. For air velocity up to 0.2 m/s, the acceptable range of operative
temperature is given in ISHRAE standard [11]. Higher air velocity attributed towards
an increase in comfortable operative temperature, the required acceptable range can
be obtained by using approach given in ISO 7730 [12], and the same is suggested in
ISHRAE IEQ standard [11]. IAQ parameters, CO2 , PM2.5 and PM10 , are measured at
occupant locations and at possible fresh air intake locations in an occupant zone. CO2
concentration is measured when there is at least 90% occupancy. As defined in IEQ
standard, illuminance of task area is calculated by taking arithmetic mean values of
illuminance at different points within the task area. Equivalent melanopic lux (EML)
is calculated as combined effect of the illuminance and melanopic ratio. Melanopic
ratio is dependent on specifications of light source such as correlated colour temper-
ature and light source type of light source. Uniformity of illuminance is calculated
as the ratio of minimum illuminance to the average illuminance of different points
within considered the task area [5, 11].
Experimental Investigation of ISHRAE IEQ Standard … 173

6 Results and Discussions

6.1 Thermal Comfort

In this section, seasonal influence on parameters of thermal comfort such as operative

temperature, air velocity, relative humidity and floor surface temperature is analysed.
Operative temperature measures the effects of radiation and convection heat trans-
fers in actual nonuniform indoor climate [1]. Seasonal variations in operative tem-
perature and air velocity are presented in Figs. 5 and 6, respectively. During pre-
monsoon, ambient temperature and indoor operative temperature for the month of
June are observed quite low as compared to other months of summer season. For the
winter season, operative temperature is found within comfortable range without using
artificial heating source. Further, in summer and monsoon season, ceiling fans are
used for cooling purpose in naturally ventilated as well as at times in air-conditioned
rooms. However, due to an increase in air velocity, some of the potential occupant
locations are found in the acceptable range even at a higher operative temperature
up to 30.5 °C.
Since Jaipur lies in composite climate where RH varies substantially across the
year and observed to be 32%, 59%, 34% and 28%, in summer, monsoon, winter and
moderate season, respectively. Most data obtained for RH falls within as ISHRAE
IEQ standard acceptable range. However, discomfort due to low RH arises because
of high-temperature conditions around the year. Moreover, the occupant satisfaction
level achieved for threshold range of RH is found to be 80%. Seasonal variations

Fig. 5 Seasonal variations in operative temperature

174 S. Kumar et al.

Fig. 6 Seasonal variations in air velocity

in relative humidity and floor surface temperature are presented in Figs. 7 and 8,
respectively.
Floor surface temperature is measured as occupant may feel discomfort because of
too warm or too cool temperature of floor. As per ISHRAE IEQ standard, floor surface

Fig. 7 Seasonal variations in relative humidity

Experimental Investigation of ISHRAE IEQ Standard … 175

Fig. 8 Seasonal variations in floor surface temperature

temperature for the occupants heaving feet contacts with floor shall be 17–31 °C
within the occupant zone. In this study, the mean value of floor surface temperature
for summer, monsoon, winter and moderate seasons is found to be 33.4 °C, 29.7 °C,
21.3 °C and 28.2 °C, respectively. During summer, the floor surface temperature
exceeds the comfort limit since the ambient temperature in the aforesaid location
hits more than 40 °C.

6.2 Indoor Air Quality

Another important element of IEQ is indoor air quality which specifies the indoor
air characteristics in terms of concentrations of CO2 , PM2.5 and PM10 . The details
of each have been discussed in this section.
The concentration of CO2 is measured at each potential occupant locations in
the room with minimum 90% occupancy. Due to high natural vegetation in MNIT
campus, the ambient CO2 concentration is found to be 400 ± 25 ppm. The sea-
sonal variations in CO2 concentration are illustrated in Fig. 9. In the present study,
the mean value of CO2 concentrations for summer, monsoon, winter and moderate
seasons are found to be 534 ppm, 443 ppm, 512 ppm and 479 ppm, respectively.
The CO2 concentration range for all seasons is falling under Class A, as specified by
ISHRAE IEQ standard, and insignificant seasonal influence is observed. Higher CO2
concentration is recorded in the classrooms and split air-conditioned rooms which
are due to high occupancy [17] and less fresh air intake, respectively.
176 S. Kumar et al.

Fig. 9 Seasonal variations in CO2 concentration

The presence of particulate matter (PM) in environment affects the indoor air
quality to large extent. The seasonal variations in PM2.5 and PM10 concentration
are illustrated in Figs. 10 and 11, respectively. The mean value of PM2.5 concentra-
tions for summer, monsoon, winter and moderate seasons is found to be 27 µg/m3 ,

Fig. 10 Seasonal variations in PM2.5 concentration

Experimental Investigation of ISHRAE IEQ Standard … 177

Fig. 11 Seasonal variations in PM10 concentration

25 µg/m3 , 61 µg/m3 and 44 µg/m3 , respectively. Further, the mean value of PM10
concentration for summer, winter and moderate seasons is found to be 68 µg/m3 ,
107 µg/m3 and 89 µg/m3 , respectively. In monsoon season, the lower concentra-
tions of particulate matters are observed due to washout of the particles from the
local environment. In the summer season, lower particulate matter concentrations
are observed because of better dispersion of particulates due to high temperature,
hot air to move upwards. During winter, the particulate matter concentrations are
recorded high due to less dispersion caused by lower temperature [2].

6.3 Lighting Comfort

Lighting is another IEQ element which influences many bodily functions like the
nervous system, circadian rhythms, pituitary gland, endocrine system, pineal gland
and alertness due to its different wavelength [11]. Illuminance and circadian lighting
design are interrelated with each other. The equivalent melanopic lux (EML) is the
measurement of circadian lighting design and can be calculated by multiplying the
illuminance (Lux) and melanopic ratio. The EML expresses the biological effects of
light on the human body [11]. In the present study, the mean value of illuminance
for summer, monsoon, winter and moderate seasons is found to be 286 lx, 310 lx,
346 lx and 316 lx, respectively. Further, the mean value of circadian lighting design
for summer, monsoon, winter and moderate seasons is found to be 304 EML, 328
EML, 365 EML and 334 EML, respectively.
178 S. Kumar et al.

Seasonal variations of illuminance and circadian lighting design are depicted in

Figs. 12 and 13, respectively. During monsoon season, relatively low mean values of
illuminance and corresponding EML are observed because of cloudy sky. In winter,
relatively high values of illuminance and EML are observed because of occupants
open blinds and curtains to gain more solar heat leading to more daylight in occupant

Fig. 12 Seasonal variations of illuminance

Fig. 13 Seasonal variations of circadian lighting design

Experimental Investigation of ISHRAE IEQ Standard … 179

Fig. 14 Seasonal variations of uniformity of illuminance within task area

zone. In summer season, lowest values of illuminance and EML are observed because
of occupant tendency to close blinds and curtains to avoid solar heat transmission
into the space leading to less daylight in occupant zone.
The distribution of light across the task area should be uniform for better visual
comfort [5]. The ratio of illuminance available in task area to the illuminance avail-
able in immediate adjacent surrounding should be within the threshold limits as per
standard. Seasonal variations of same are shown in graphs as shown in Figs. 14 and
15. Both uniformity of illuminance and ratio of illuminance of task area to imme-
diately adjacent surroundings are in acceptable range. However, occupant location
near to East and West facing windows get direct sunlight leads both parameters (uni-
formity of illuminance and ratio of illuminance in task area to immediate adjacent
surrounding) in the unacceptable range.

6.4 Occupant Satisfaction Surveys

In present study, subjective assessment of IEQ elements (thermal comfort, lighting

comfort and indoor air quality) is conducted using anonymous occupant satisfaction
survey, and responses are recorded on a 7-point scale [11]. Occupant satisfaction
surveys are conducted at every potential occupant location simultaneously with IEQ
parameter measurements. On 7-point scale, 1 and 7 represent the most unsatisfactory
and satisfactory conditions, respectively. Each parameter is represented in terms of
percentage satisfaction, where responses 4, 5, 6 and 7 are taken as satisfactory and 1, 2
180 S. Kumar et al.

Fig. 15 Seasonal variations of ratio of illuminance task area to immediate surroundings

and 3 as unsatisfactory responses. Gender, weight, age, height and native place of the
respondents are also recorded in the present investigation as suggested in study given
in [3]. Qualitative aspects of parameters such as room temperature, RH, airflow, stale
air, overall lighting, an external view and daylight availability are recorded in the
questionnaire. The threshold values for occupant responses are 90 and 80 percentage
for Class A and Class B, respectively. The occupant satisfaction for indoor air quality,
thermal and lighting comfort is found to be 80, 81 and 89 percentage, respectively.

7 Conclusions

The present study shows importance of deploying efficient methodology to capture

spatial-temporal variation in IEQ elements and parameters for any given potential
measurement zone. Present study reflects the results for the given location and build-
ings. It is suggested that built environment used for other purposes should also evalu-
ate implementation of this standard as per their requirement. Measurement locations,
frequency and methodology presented in this study allow to gauge IEQ in studied
buildings satisfactorily. For two buildings selected for this study, most of the thermal
comfort parameters are found to be meeting the minimum threshold. The acceptable
range of comfort operative temperature can be increased at elevated air velocity using
fan, which is relatively lower energy-consuming method to achieve thermal comfort.
CO2 concentration is found to be within acceptable range because of natural veg-
etation in vicinity. The concentration of respirable suspended particulate matter is
found to be high from October to January because of surface temperature inversion
Experimental Investigation of ISHRAE IEQ Standard … 181

in winters. Further, because of adequate natural and artificial light, majority of light-
ing comfort parameters are found to be within acceptable range. The collection of
occupant satisfaction survey along with physical parameter measurement is the most
effective way for IEQ assessment. During occupant satisfaction survey, majority of
occupant responses are found to be satisfying more than 80% for all IEQ elements.

Acknowledgements We wish to thank ISHRAE for providing financial support and members of
Centre for Energy and Environment, Malaviya National Institute of Technology, Jaipur, for their
support during this study.

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