Environmental Science and Pollution Research

https://doi.org/10.1007/s11356-024-33496-3

RESEARCH ARTICLE

Influence of building orientation and thermal mass configuration

on the prediction of Natural Ventilation Potential (NVP) of various
climates of India
Dora Nagaraju1 · Siva Subrahmanyam Mendu2 · Neelima Devi Chinta1

Received: 2 August 2023 / Accepted: 24 April 2024

© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024

Abstract
Natural ventilation potential (NVP) of a climate is a theoretical basis, and it gains importance due to the promising need
for building energy conservation while conceding required thermal comfort conditions. A modified NVP analytical model
is proposed by considering parameters involved in the earlier models (Yang et al., Build Environ 40:738–746, 2005;
Luo et al., Build Environ 42:2289–2298, 2007). The effect of the dynamic thermal behavior of the wall/roof and build-
ing orientation on the indoor air temperature has been evaluated. The analytical model is applied to 11 major cities of
India that belong to composite, hot-dry, temperate, and warm-humid climates. Five different envelope configurations are
analyzed to envisage the NVP of concern climate (ED-I to ED-V). The results show that the effect of dynamic thermal
response factors on the NVP is significant, and optimization of thermal response factors in addition to the U-value is
mandatory. The impact of wind frequency on the selection of building orientation is substantial since it influences the
total heat gained by the building envelope. Moreover, it is perceived that the optimum building orientation is independ-
ent of the climate and weather conditions. ED-II and ED-III are energy-efficient envelopes for composite, temperate,
warm-humid, and hot-dry climates. The results revealed that the Mumbai climate has the highest NVP of 66% while the
building is oriented in an E-W direction, and the lowest is observed for Jodhpur, i.e., 44% of the year when the building
is in the NE-SW direction. The model helps the building architectural designers envisage the true NVP and assess the
suitability of the building for natural ventilation.

Keywords Natural Ventilation Potential (NVP) · Envelope thermal mass · Indian climates · Building orientation · Wind
frequency

Introduction

Earth receives continuous climate variations, responsible for

global warming, which refers to the gradual increase of the
Responsible Editor: Philippe Garrigues
earth’s surface and atmospheric air temperatures. The sud-
* Dora Nagaraju den fluctuations in temperature will affect the electricity/
ndora@gitam.edu gas energy consumption in the building sector pertaining to
Siva Subrahmanyam Mendu human thermal comfort. Energy consumption by buildings
m.sivasubrahmanyam@gmail.com has increased in recent years primarily due to population
Neelima Devi Chinta growth, rapid economic development, and rapid growth in
jntukneelima@gmail.com infrastructure. Currently, the rapid growth of urban areas
1
and buildings is being considered one of the primary con-
Department of Mechanical Engineering, JNTU-GV College cerns. It results in excessive energy use from non-renewable
of Engineering Vizianagaram, Vizianagaram 535003,
Andhra Pradesh, India sources, which causes severe impacts on the environment.
2 Climate Change Conference (CCC-2015) in Paris in 2015
Department of Mechanical Engineering, MVGR College
of Engineering (A), Vizianagaram 535003, Andhra Pradesh,
India

Vol.:(0123456789)
 Environmental Science and Pollution Research

addressed and agreed that the mitigation of C ­ O2 emissions using a specific central rating system. In this regard, the
for the reduction of global warming and limiting the global Govt. of India has initiated the implementation of some
temperature rise below 2 °C (Documents, UNFCCC, https://​ benchmarks for buildings. As part of this, the ECO Niwas
newsr​o om.​u nfccc.​i nt/​d ocum​e nts (accessed August 20, Samhita 2018 code’s implementation has the potential for
2021). World Business Council for Sustainable Development energy savings to the tune of 125 billion units of electricity
(WBCSD) has announced that the building sector consumes per year by 2030 (ECO-NIWAS, https://​beein​dia.​gov.​in/​en/​
40% of total electricity production in the world’s energy eco-​niwas-​samhi​ta-​ens). In India, the high energy-intensive
(Energy Efficiency in Buildings Facts and Trends, https://​ sectors are agriculture and buildings. These are part of eco-
www.​wbcsd.​org/​Progr​ams/​Cities-​and-​Mobil​ity (accessed nomic growth and stringent population increase, causing
June 28, 2019)), accounting for one-third of energy con- sudden demand for energy and other patterns in the build-
sumption worldwide. ing sector. NITI Aayog has predicted rapid development in
The focus is shifted to insulating the building and passive the residential building stock, and their electricity consump-
design strategy methods to mitigate energy consumption, tion will increase 6–13 times by 2047 (Omrani et al. 2017).
which can provide controlled and acceptable indoor environ- Also, India has limited energy resources, which may not be
ment conditions. An integrated approach has been imple- sufficient for the country’s long-term growth and develop-
mented for the newly constructed and retrofitted building by ment. In this scenario, the country’s challenge is to ensure an
emphasizing thermal mass insulation and heat recovery tech- adequate energy supply, at least at the possible cost. Another
niques in addition to sustainable practices such as passive crucial one is the inhabitants’ thermal comfort in affordable
building strategies, improved daylighting techniques, and housing to ensure their health. In this scenario, the impera-
natural ventilation. The sustainable methods implemented in tive developments and technology to reduce electricity/gas
a building depend on building usage, pertinent outdoor envi- consumption are typically suitable for various climates of
ronmental factors, location, and design (Tong et al. 2017). India (Patil and Kaushik 2015). As a part of this, analyzing
In this context, the primary concern of building design is climate and relevant building parameters is effectively done
establishing acceptable indoor conditions and utilizing them to ensure acceptable indoor environment conditions.
effectively whenever advantageous while considering the The solution to achieving affordable operating condi-
interaction with the outdoor environment. Moreover, the tions in the building is natural ventilation with stringent
sustainable technique works well under the optimum con- potential to maintain the required indoor comfort condi-
ditions, satisfying the demand for the inhabitant’s thermal tions within an acceptable range (Haase and Amato 2009;
comfort conditions (Tyagi et al. 2011; Wang and Greenberg Chenari et al. 2016). Advanced sensor technologies have
2015). It is imperative to note that sustainable techniques allowed more accurate assessments of interior air quality,
fail to meet the requirements in a harsh environment. Purely temperature, and circulation patterns. Incorporating these
mechanical ventilation or mixed-mode ventilation technique sensors into research on natural ventilation yields valuable
acts as a supplementary system. Progress in computational data for comprehending the efficacy of ventilation sys-
fluid dynamics (CFD) has empowered researchers to pre- tems. The essential advantages of natural ventilation are
dict and simulate airflow in structures precisely. Researchers the exchange of outdoor fresh air with indoor and hence
are increasingly using CFD models to analyze and enhance improved freshness, reduction of the age of air, enhancement
natural ventilation techniques (Jomehzadeh et al. 2017; King of productivity and health, reduction of energy consump-
et al. 2017; Balaji et al. 2019). tion, and controlling greenhouse gas emissions (Germano
In the continuation of the emerging need for a technique and Roulet 2006; Jomehzadeh et al. 2017; L et al. 2017).
to mitigate energy consumption, in the case of climates of It is an energy conservation technique in the building. At
the Indian scenario, it is reported that due to harsh abnor- the early design stage, the primary duty of the designer is
mal outdoor conditions, people are relying on ventilation to envisage its potential through surveys and examine the
systems to achieve thermal comfort, leading to higher elec- suitability of the climate. The anticipation of natural ventila-
tricity consumption (ECBC Residential | Bureau of Energy tion for a particular environment involves experimental and
Efficiency, https://​www.​beein​dia.​gov.​in/​conte​nt/​ecbc-​resid​ computational studies, which are cumbersome and expen-
ential (accessed May 25, 2021)). The updated version of sive. Numerous studies concentrate on natural ventilation
ECBC (Energy Conservation Building Code) for commer- in certain regions, although there is a need for more com-
cial buildings 2017 estimated that energy demand will rise prehensive principles that can be universally applied across
to approximately 1000 billion units by 2030, 3 times more various climatic environments. In the case of computational
than the units required in 2018 (ECBC Residential | Bureau studies, CFD has limitations in predicting the ideal poten-
of Energy Efficiency, https://​www.​beein​dia.​gov.​in/​conte​nt/​ tial since it involves many assumptions. The definition of
ecbc-​resid​ential). It is noticed that various methods/tech- natural ventilation potential is to evaluate the possibility of
nologies are needed to decrease electricity consumption natural driving forces to generate ventilation for a particular
Environmental Science and Pollution Research

climate and ensure inhabitants’ acceptable indoor thermal and NVP was predicted regarding PDPH for three major
comfort conditions. Operating the windows and controlling cities in China (Yang et al. 2005). The analytical model has
the percentage of window opening during mild weather con- considered constant indoor air temperature, assisted wind
ditions is a feasible technique indigenous to all climates in force, and building orientation towards the south. The poten-
the practical scenario. As a part of ventilation cooling, in tial for natural ventilation was estimated regarding PDPH
some environments, the building’s thermal mass is cooled while considering outdoor climate data such as DBT (dry
during night ventilation, reducing anticipated warm weather bulb temperature), wind incident angle, and wind velocity.
conditions the next day. This model is further modified by Luo et al. (2007) by con-
Natural ventilation potential is climate-specific and purely sidering that the indoor air temperature varies with time. A
dependent on wind velocity, wind incident angle, prevail- simple energy balance model predicts indoor temperature
ing wind direction, outdoor DBT (dry bulb temperature), variation by considering weather data such as solar radiation
and solar radiation. NVP evaluation involves three criteria, and DBT, wind incident angle, and wind velocity. Several
namely, outdoor meteorological criteria, urban topology, and studies are expanding their scope beyond individual build-
building criteria. Upon successfully predicting NVP using ings to investigate the influence of natural ventilation on a
these criteria, the designers will conclude “where to build” larger metropolitan scale. It evaluates the impact of adjacent
instead of “how to build.” While short-term studies provide structures, topographical elements, and localized climates on
valuable insights, there is a lack of comprehensive, long- air circulation efficiency.
term assessments of natural ventilation strategies in real- The potential for NV is predicted regarding PDPH and
world settings. Understanding how these systems perform natural ventilation hours (NVH). It is observed that the
over extended periods is crucial for practical implementa- IAQ (indoor air quality) is defined for NVP only based on
tion. In the case of India, five different climates exist: com- ventilation flow rate, and the effect of other pertinent IAQ
posite, warm-humid, hot-dry, temperate, and cold (“National governing parameters is not considered. Finally, their model
Building Code—Bureau of Indian Standards” n.d.). The predicts the number of NV hours in a particular climate out
variation of pertinent outside environment parameters leads of 8760 h. The effect of outdoor humidity on NV hours is
to changes in indoor comfort conditions and thereby influ- studied by Wei Yin et al. (2010). Two openings in a naturally
ences the energy consumption of the building. The direct ventilated building are considered in two different building
application of solar energy in cooler climates can provide orientations: south-north and west–east. In their work, the
buildings with indoor air heating and water heating, which correlation used for thermal comfort temperature limits is
has increased enormously. Simultaneously, it impacts sev- unclear, and solid reasons for the effect of humidity on NV
eral climates by the synergistic interaction between tem- hour are not derived. In these models, the impact of the out-
perature and humidity. The building designers are adopting door heat transfer coefficient is ignored. Building energy
passive techniques to increase energy conservation. There- simulations have been carried out to predict the natural ven-
fore, it is perceived that the survey and weather analysis of tilation potential by considering the feasible assumptions.
major Indian cities and predicting the potential for natural The main objective of these studies is to predict the feasi-
ventilation are paramount. The prediction of climate NVP bility of natural ventilation and, thereby, NV hours. Also,
involves several parameters and constraints that belong the studies explore the energy-saving potential in terms of
to the outdoor environment, building, and indoor thermal NV hours. The NV potential and energy savings were esti-
comfort requirements. The estimation of NVP for a particu- mated for various locations worldwide (Chen et al. 2017).
lar climate through analytical models is limited to a few The climate classification was based on ASHRAE Standard
constraints. In this regard, Axley and Emmerich (Emmer- 90.1–2007 when conducting the building energy simulation
ich et al. n.d.) developed a method to envisage the NVP of (BES). NVP is estimated by predicting the upper threshold
commercial buildings using hourly weather data. NVP can limit for comfort temperature and outdoor wind velocity, and
be estimated using natural ventilation hours and pressure then the NV hour, which falls within these threshold limits,
difference pascal hours (PDPH). It calculates the energy is calculated. The upper threshold comfort temperature is
savings of a particular building in a climate, which will be predicted by considering the mean monthly outdoor temper-
necessary for design engineers to construct buildings as per ature and 80% thermal acceptability range. Also, the upper
standard compliance. The potential for natural driving force threshold outdoor wind velocity is estimated by considering
depends on the outdoor environment, building design, and the maximum allowable indoor air velocity as 0.8 m/s.
site characteristics. Tong et al. (2017) estimated NV hours for high-rise build-
The climatic suitability for buildings predicted based on ings in 35 major cities in China while considering the influ-
NVP differs from the potential for natural driving forces ence of outdoor air pollutants. Ventilation cooling potential
since it depends on the indoor heat source, which causes is evaluated by adopting the thermal resistance ventilation
buoyancy force. A simple analytical model was developed, (TRV) method for office buildings in various climates of
 Environmental Science and Pollution Research

China (Yao et al. 2009). The indoor temperature of three decision-based evaluation must be verified and corrected if
types of strategies, daytime, night-time, day, and night- required. The BES method involves assumptions such as
time ventilation, was estimated while considering comfort constant indoor air temperature and predicting its hourly
temperatures as per ASHRAE 55 2004 standard. Building variation through an iterative procedure. Alone energy simu-
neighboring structures on the potential for NV is predicted lation tools are insufficient to decide the suitability of natu-
using the CFD approach at various wind speeds and angles ral ventilation. It is perceived as a more realistic theoretical
(King et al. 2017). It is observed that buildings in hot-dry basis, and NVP is essential to analyze the climate character-
climates have more potential for energy saving with natural istics. Although short-term studies provide valuable insights,
ventilation when using high heat capacity of building mate- there is a dearth of thorough, long-term evaluations of natu-
rial. In the hot-humid environment, buildings constructed ral ventilation systems in real-world environments. Gaining
with low heat capacity materials while implementing natural insight into the long-term performance of these systems is
ventilation were observed to yield low indoor temperature. It essential for their practical use.
results in a high potential for natural ventilation. Energy-sav- The wind prevailing direction in a particular climate is
ing potential for NV has been investigated in a building that paramount while envisaging the potential for NV; accord-
belongs to a temperate climate using EnergyPlus simulations ingly, building orientation will be specified. Moreover,
(Oropeza-Perez and Østergaard 2014). Moreover, a com- building orientation will influence the direct solar heat gain
prehensive review of NVP research is presented in Table 1. through the envelope. Also, the effect of outdoor weather
Similarly, studies in Bangkok and Thailand have suggested conditions and external thermal mass on the prediction of
that natural ventilation provides acceptable thermal comfort indoor air temperature is imperative. Moreover, thermal
conditions approximately 20% of the year (Tantasavasdi mass dynamic performance is site-specific and independ-
et al. 2001). NV hours are estimated in hot desert climates by ent of envelope configuration and thermophysical proper-
considering the building design criteria while enhancing the ties. Envelope design and dynamic thermal behavior were
natural ventilation effect (Bahadori 1994; Bouchahm et al. not considered while proposing the NVP analytical model.
2011; Calautit et al. 2014). Oropeza-Perez and Ostergaard Notably, the potential for NV in a few Indian cities has been
(Kolokotroni et al. 2006) have assessed the NVP of Denmark predicted by adopting analytical models available in the lit-
and proved that natural ventilation could replace mechanical erature (Patil and Kaushik 2015; Patil et al. 2020). They per-
ventilation during summer. The NVP depends on the capa- ceived that sophisticated NVP models are essential to predict
bility of local climate and urban configurations. Research- the exact potential for NV in various climates of India. Natu-
ers have recently investigated the effect of different climates ral ventilation is in some areas; nevertheless, more universal
and urban designs to predict the feasible NV hours using recommendations are required in different climatic circum-
EnergyPlus simulations (Kolokotroni et al. 2006; Wang and stances. Limited research has been conducted on the interac-
Greenberg 2015). It is observed in the literature that NVP is tion between natural ventilation and other building systems,
significantly less in the climate belonging to winter and tran- such as heating, ventilation, and air conditioning (HVAC).
sition seasons (Su et al. 2009). The highest NVP was marked Holistic studies considering integrating these systems are
with northern Europe than southern Europe (Artmann et al. essential for optimizing overall building performance. Inves-
2007). Inhabitants have expressed more satisfaction in the tigating adaptive techniques that react dynamically to chang-
thermal environment and IAQ when they stay in naturally ing weather conditions and occupant preferences might help
ventilated buildings than in mechanically ventilated build- natural ventilation systems perform better.
ings. Hence, the researchers have claimed that substantially The present work aims to develop and apply a realistic
acceptable indoor conditions are mandatory to lower the sick NVP model to major cities in India, considering different
building syndrome (Mendell et al. 1996; Mendell and Mirer climates and imagining the corresponding NVP. The NVP
2009). A multi-zone airflow network model was employed is estimated while considering the effect of external ther-
to assess the NVP and building simulations results obtained mal mass only. The significance of thermal response fac-
for hybrid mode (N.R.M. Sakiyama et al. 2021). The use tors (time lag (TL) and decrement factor (DF)) and U-value
of different adaptive standards resulted in a more noticeable (thermal transmittance) on the exactness of potential for NV
variation in the assessment of thermal comfort. of concern climate is analyzed. The following objectives are
Moreover, mechanically ventilated buildings ensure set for the current study.
sufficient indoor thermal comfort conditions, with higher
maintenance and energy consumption. The climate-related • To predict feasible building orientations of a concerned
issues can be resolved at the early conceptual design stage; climate with the help of the wind rose diagram and evalu-
the remaining issues can be determined using the iterative ate the thermal response factors of wall/roof for various
procedure at various stages like design, development, and envelope configurations using a developed numerical
performance assessment. These phases are crucial since the model.
Table 1  Summary of natural ventilation potential models and NVP of various climates
NVP evaluation method Assessment criteria Methodology (ana- Parameters analyzed Findings Ref
(outdoor meteorological /urban lytical/BES)
criteria/building criteria)

Outdoor meteorological NVCP of buildings TRV model Indoor temperature for three When designing a strategic plan for natural (Yao et al. 2009)
types of strategies daytime, ventilation, it is important to consider the
nighttime, daytime, and night- building dimensions as well as the kind
time ventilation and profile of ventilation
Building criteria Impact of wind angles on CFD studies against Effect of wind speed, wind This configuration mixes outside and inside (King et al. 2017)
internal mixing and effec- full-scale measure- angle, and neighboring air, improving ventilation. Variable airflow
tive ventilation rate in urban ment structures pathways and microclimate influences may
Environmental Science and Pollution Research

environment affect local temperature and air quality

Outdoor meteorological and Assessment of energy saving EnergyPlus Case study was conducted A good natural ventilation strategy cuts (Oropeza-Perez and
building criteria potential for Temperate while considering window summer mechanical ventilation demand Østergaard 2014)
climate openings and shading devices by 90%. Internal heat sources, external
temperature, temperature set-point, wind
speed, and solar heat gains are the input
factors that affect the model most
Outdoor meteorological and Wind and stack effect Analytical Indoor temperature was kept con- NVP is estimated in terms of PDPH by (Yang et al. 2005)
building criteria stant and weather data (outdoor considering IAQ only, thermal comfort
temperature, wind speed) evaluation is not part of the research
Outdoor meteorological and Wind and stack effect (driving Analytical Variable indoor temperature NVP is estimated in terms of NV hours. (Luo et al. 2007)
building criteria forces), thermal comfort and weather data (outdoor Upper and lower thermal comfort temper-
temperature, wind speed) atures were set based on adaptive comfort
chart for natural ventilation building
Outdoor meteorological and Wind and stack effect (driving Analytical Variable indoor temperature NVP is estimated in terms of NV, non-NV, (Yin et al. 2010)
building criteria forces), thermal comfort and weather data (outdoor heating and cooling, mechanical ventila-
temperature, wind speed, tion hours
humidity) while considering
assisting and opposing wind
Outdoor meteorological and Wind and buoyancy driving Analytical Indoor temperature was kept The wind profiles, temperature profiles, and (Patil and Kaushik
building criteria forces constant, weather data PDPH profiles of a particular site will 2015)
(outdoor temperature, wind determine the kinds of natural ventilation
speed) systems that are used in buildings
Outdoor meteorological and Wind and buoyancy driving Analytical Variable indoor temperature; To maintain a comfortable temperature (Patil et al. 2020)
building criteria forces, thermal comfort weather data (outdoor tem- throughout the year, natural ventilation
perature, wind speed) alone is insufficient. There are a variety
of scenarios that are shown by the PDPH
evaluation when it is analyzed for vari-
ous temperature conditions inside the
building
 Environmental Science and Pollution Research

• To develop the NVP model while considering building • Thermal balance exists in the building (ΔQstored = 0).
orientation and dynamic thermal behavior of the enve- • Window to wall ratio (η) remains the same on both walls.
lope. To evaluate the NV hours of several viable building • Assisting wind direction is considered.
orientations in a particular climate and suggest the best • Windows are placed only in the direction of the prevail-
orientation. ing wind.
• To estimate the indoor air temperature, NV hours of vari- • Single vertical glass without shading devices
ous major cities of India and predict the optimum build- • Air distribution within the building is uniform.
ing orientation which yields maximum NVP.
Simple building model considering thermal mass
The research article is organized as follows: firstly, the effect in the envelope
analytical model for NVP is explained by incorporating the
effect of building orientation and envelope thermal mass The building is assumed to be isolated from the surroundings,
followed by NVP is estimated in terms of PDPH, NV hours, and the impact of neighboring buildings, streets, trees, etc.,
heating, and cooling hours. Later, climate analysis of major is ignored. The building model is treated the same as earlier
Indian cities and criteria evaluation for the selection of enve- research studies, and the goal is to envision the optimal poten-
lope configuration are presented. tial for NV in situations when the structure is not influenced
by its surroundings. The pollutants caused by air pollution and
the effect of noise pollution are not considered in the model.
Analytical model for NVP evaluation The building dimensions are referred from the literature (Yang
et al. 2005), and details are presented in Table 2.
The natural ventilation potential is the ideal value that Here, k and a are constant values at terrain conditions
describes the maximum energy savings achieved. An ana- referred from the literature (Yang et al. 2005) used to calcu-
lytical model is developed using a theoretical basis related late wind velocity at the weather station.
to hourly weather data and natural driving forces. The model assumes the building envelope is exposed to
outdoor solar radiation, temperature, wind incident angle,
Assumptions and wind velocity. The outside envelope surfaces are influ-
enced by fictitious sol–air temperature. Then, heat transfer
The NVP model is proposed based on theoretical knowl- will be propagated through the structure, considering that
edge and the specific attributes at the site level. Therefore, the thermal mass effect will affect the inner surface tem-
the NVP model is usually presented from the macroscopic perature of the envelope. Also, the U-value of the envelope
point of view by considering a single isolated room. In this depends on the configuration. The details of envelope con-
regard, the following assumptions have been set for the figurations considered in the present model are explained in
current model and some of them are the same as literature the “Building envelope configurations and Material proper-
(Yang et al. 2005; Luo et al. 2007). ties” section. The building model is elucidated, and pertinent
information is shown in Fig. 1. The indoor air temperature
• Indoor air temperature is always greater than outdoor is well-mixed and uniform, and wind turbulence effects are
DBT (dry bulb temperature). ignored. Generally, if the flow is buoyancy-dominated, then
• Neglect internal thermal mass the uniform mix of air temperature is not valid, and a non-
• Relative humidity does not affect the indoor air and ther- uniform model has to be presented (Li and Delsante 2001).
mal comfort temperature limits. Building dimensions: 20 m × 10 m × 7 m.
• Internal sources only from people and no other sources Length-to-width ratio: 2:1 (low-rise building).
• Neglect evaporative loss Apply heat balance to the building,

0 0
− + − − =∆ (1)
ℎ
Environmental Science and Pollution Research

Then, it will be simplified as, ∑

5
Qenvelope = Uj Aj (TETD)j (3)
Qi + Qdirect heatgain = Qenvelope + Qventilation (2) j=1

The explanation of each term and relevant calculation Therefore, the heat gained by the envelope is equivalent
procedure is explained below. to the sum of heat gained by four walls and the roof.
Qenvelope (heat transferred through envelope): Where Uj indicates the U-value of each wall and roof
In the building, the envelope’s thermal mass stores heat (W/m2 K), Aj refers to the area of each wall and roof (­ m2),
and acts as inertia against fluctuations in the temperature. and TETDj shows the total equivalent temperature difference
It is distinct from the insulation of the envelope, which (°C) calculated using Eq. (4).
reduces thermal conductivity and stops the flow of heat to ( ) ( )
the next layer of the structure. Thermal mass is also known (TETD)j = Tin − Tas,j + DF j Tas,j − Tsa,j � (4)
as heat capacity. It plays a significant role in stabilizing the
where Tin indicates indoor air temperature (K), and Tas and
indoor temperature throughout the day-to-night tempera-
j are the daily average sol–air temperatures (K). DFj is the
ture fluctuations and thus provides a self-regulating envi-
decrement factor value of each wall and roof. It is differ-
ronment. Moreover, the propagation of heat waves through
ent for various walls and roofs and depends on the diurnal
the envelope depends on pertinent parameters such as ther-
variation of sol–air temperature of the concerned envelope
mal response factors, sol–air, and indoor air temperatures.
component. Similarly, time lag changes with sol–air tem-
Thermal response factors of concern for the envelope wall
perature and differs for walls and roofs. T’sa,j is the sol–air
and roof are estimated by considering the effect of weather
temperature of each wall and roof at TL hours ago (K). Then
data on building orientation.
Eq. (3) will become as,
Considering the thermal mass in the building wall and its
TL and DF heat transfer through the envelope, ∑
5
[( ) ]
Qenvelope = Uj Aj Tin − Tas,j + DF j (Tas,j − Tsa,j �) (5)
j=1

Table 2  Building dimensions Parameter Value Hourly sol–air temperature is calculated using Eq. (6)
and related parameters (Yang
et al. 2005) Window to wall ratio (η) 0.4 𝛼j Ij 𝜀j ΔR
No. of people (Np) 10
Tas,j = Tout + − (6)
ho,j ho,j
Coefficient of discharge 0.61
k 0.68 where Tout is outside DBT (K), αj and εj are the absorptiv-
a 0.17 ity and emissivity of the surface exposed to incident solar

Fig. 1  Simple building model

for energy balance
 Environmental Science and Pollution Research

radiation, as presented in Table 4, and these values are dif- Builder (building energy simulation software) estimates the
ferent for various materials. ho,j is the heat transfer coeffi- incident solar radiation on each wall and roof Ij (W/m2).
cient (W/m2K) of the outer surface exposed to incident solar Upon substituting Tas,j and T’sa,j terms in Eq. (5), then
radiation for wall and roof which are referred from Eco- simplify to get,
Niwas Samhitha 2008 (ECO-NIWAS. https://​beein​dia.​gov.​ [ 5 ]
in/​en/​eco-​niwas-​samhi​ta-​ens). The value of ΔR is referred ∑ ( )
Qenvelope = Uj Aj Tin − Tout − E� (7)
from ASHRAE (Kaşka and Yumrutaş 2009), which is 63 j=1
W/m2 and 0 W/m2 for roof and wall, respectively. Design
where,

{( ) [ ( )]}
∑
5
𝛼j Ij 𝜀j ΔR ( ) 𝛼j Ij 𝛼j Ij �
�
E = (Uj Aj ). − − DF j Tout − Tout �
+ − (8)
j=1
hoj hoj hoj hoj

I′j is the hourly basis incident solar radiation building enve- direct heat gain by assuming one window. Moreover, win-
lope, and T′out is the hourly dry bulb temperature at TL hours ago. dows are considered on walls oriented in the wind prevailing
Qventilation (heat transferred through ventilation): direction only, and other walls do not have windows. Awindow
The model elucidates the analytical solutions for the is the window area calculated using the window-to-wall ratio
ventilation flow rate in the single zone building with two (η). ­SHGCi is the solar heat gain coefficient of the window,
openings in the prevailing wind direction. At the same and it is taken as 0.87 for both windows by considering the
time, they are considering heat interactions between enve- precise single glaze 3 mm glass thickness. It is the incident
lope and solar radiation, buoyancy, and wind forces. More- of solar radiation on the window.
over, the indoor air temperature is assumed to be more Another term of Eq. (2) is Qi, representing the indoor heat
significant than the outside temperature, and then the heat source. It is assumed that 10 people stay inside the build-
transferred through ventilation is calculated using Eq. (9). ing, resulting in the average internal heat source being 1000
( ) W. Then total heat gain by the building is equivalent to the
Qventilation = 𝜌Cp qven Tin − Tout (9) sum of indoor heat source, direct heat gain by windows, and
another term, i.e., E’ which is resulting from heat transfer
The hourly ventilation flow rate (qven) results from the
through the envelope and its value depend entirely on the
combined effect of thermal buoyancy and wind-driven
thermal response factors of concern envelope configuration.
forces. The calculation procedure of qven is explained in
Substitute Eqs. (3) to (10) in Eq. (2) then simplify to get,
the following section, and ρ denotes the density of air (kg/
m3). Cp is the specific heat of air (J/kg K). Etotal
Qdirect heat gain (heat transferred through openings): Tin − Tout = � ∑ � (11)
𝜌Cp qven + Uj Aj
In the previous analytical models of NVP (Yang et al.
2005; Luo et al. 2007; Yin et al. 2010), researchers have where Etotal is represented as Eq. (12),
anticipated the direct heat gain through the window using
hourly direct solar radiation of concern weather data. The Etotal = Qi + Qdirect heat gain + E� (12)
solar radiation flux incident on the envelope is the com-
Therefore, using the fundamental principle of the heat
bined effect of direct and diffuse solar radiation. Also, the
balance method, the difference between indoor and outdoor
incident solar radiation on the building envelope differs
temperatures is represented explicitly as a function of the
from direct solar radiation. Moreover, it is significantly
ventilation flow rate. By solving the ventilation equations,
different for walls and roofs when the building is consid-
the hourly variation of indoor air temperature can be esti-
ered in various orientations. The current model calculates
mated for various climates.
the heat gain through the windows using Eq. (10) by con-
sidering solar radiation incident on the window.
Estimation of natural ventilation flow rate
∑∑
n 4
Qdirect heat gain = nw,i .SHGCi .Awindow,i .Ii (10) From the climatic design point of view, the natural ventila-
w=1 i=1 tion flow rate can be estimated using design elements based
where nw indicates the number of windows, nw,i is the number on the concepts of art and science. The procedure must not
of windows on each wall, and the present model estimates be against the natural driving forces to create comfortable
Environmental Science and Pollution Research

conditions without diminishing the potential requirements. as constant, i.e., 0.6 for both windows. Atot denotes the total
Based on the energy balance method, indoor air temperature, effective opening area is calculated using Eq. (14)
and ventilation flow rate are intercorrelated. In the present ( )
model, the effect of thermal mass is treated as significant Atot = Ab + At .𝜂 (14)
since the building orientation significantly influences it.
Here Ab represents the window area near the floor, which
Therefore, the ventilation flow rate is calculated using natu-
is taken as the inlet. The top window area is located near the
ral driving forces as explained below.
roof and is taken as an outlet for ventilation flow since the
current model is analyzed for assisting wind.
Principles of natural ventilation
Ventilation flow rate due to wind effect is (“TN 44:
Numerical Data for Air Infiltration and Natural Ventilation
The principle of natural ventilation depends on the envi-
Calculations (replaced by Guide GU05) | AIVC” n.d.),
ronmental conditions, the art of building and the surround-
√
ing microclimate, and the dynamic thermal behavior of the
2||ΔPw ||
building itself. At the early design stage, these factors must qwind = Cd 𝜂A∗ (15)
be taken into consideration. Hence, the building orientation 𝜌
is one of the primary concerns in estimating the ventilation
The practical wall area A*,
flow rate. Further, proper design and planning can reduce the
overheat load. Thus, adopting the optimum ventilation strat- (Cdt At ).(Cdb Ab )
A∗ = √(
egy, such as assisting wind, opposing wind with downward, )2 ( )2 (16)
opposing wind with the upward flow, and utilizing natural Cd Cdt At + Cdb Ab
driving force at a particular location, ensures proper air dis-
tribution. Moreover, the location of windows on the wall Here Cdt and Cdb are the coefficients of discharge of top
influences the ventilation flow pattern, creating acceptable and bottom window openings. In the present model, both
indoor comfort requirements. Generally, ventilation flow window openings have the same coefficient of discharge val-
arrangements are single-sided and crossflow. In the present ues and Cd value, either Cdt or Cdb, then Eq. (16) becomes,
analytical model, crossflow ventilation, which is more effec- At .Ab
tive than the former, is considered. A∗ = √
( )2 ( )2 (17)
At + Ab
Concept of natural driving forces and combined effect
on ventilation flow rate The pressure difference (ΔPw) between two openings can
be calculated using,
Natural driving forces are buoyancy-driven or stack due 1 ( )
to temperature difference and wind-driven due to pressure ΔPw = 𝜌 Cpb − Cpt v2 (18)
2
difference.
The ventilation flow rate due to the stack effect or thermal Wind speed (v) at the opening is calculated using Eq. (19),
buoyancy is calculated using Eq. (13) (Awbi 1996). and it is the function of wind speed at the weather station (vo)
√ and terrain conditions (k, a). Values of constant terrain condi-
1 (T − Tout ) tions are referred from literature (Yang et al. 2005).
qstack = Cd Atot gH in (13)
3 Tout v = kv0 H a (19)
Here, the effect of wind speed and wind angle on the Substitute Eqs. (16) to (19) in Eq. (15) to calculate the ven-
coefficient of discharge (Cd) is not considered and treated tilation due to wind pressure force.
�
� �� � �� �2 ��
⎛ ⎞ �
� � � 2�� 1 𝜌 Cpb − Cpt kv0 H a �
�
Awindow ⎜ At .Ab ⎟� � 2 � (20)
qwind = Cd ⎜ �� � � �2 ⎟
Awall ⎜
At + Ab ⎟⎠
2 𝜌
⎝
 Environmental Science and Pollution Research

Cpt and Cpb are the wind pressure coefficients at respective Then, the ventilation flow rate is expressed due to the com-
locations at the bottom and top openings. These values depend bined effect of stack and wind pressure forces (Yang et al.
on the wind incident angle; for low-rise buildings, these values 2005; Luo et al. 2007).
are presented in Table 3. √
q = qven = qstack 2 + qwind 2 (21)

Substitute Eqs. (10) to (12) and Eq. (20), then simplify the
solution yields,

� � � � ��2 � �� 1 � � 1∕2
⎡ � 1 C A �2 gH 2 �
2�� 2 𝜌(Cpb −Cpt )(kv0 H a ) �� ⎤
q=⎢ � � ⎥
d tot E A .A
3 total
. 𝜌C q+∑ U A + Cd 𝜂 √ 2 t b
.
⎢ Tout ( p j j)
(At ) +(Ab )
2 𝜌 ⎥
⎣ ⎦
�� �2 � � � �
� 1 � � �� 1∕2
1 2 � 𝜌(�Cpb −Cpt �)(kv0 H a )2 �
C A gH (Qi + Qdirect heat gain +E� ) A2 ⋅A 2 � 2 �
= 3 d tot
. 𝜌C q+∑ U A + Cd2 (𝜂 2 )( 2t b 2 ) . � �
Tout ( p j j) (At ) +(Ab ) 𝜌

�∑U �
Aj A2t .A2b .𝜂 2 . k2 . H 2a . v2o � �
q3 + q2 j
− q . Cd2 . . (�Cpt − Cpb �)
𝜌 Cp (A2t .A2b ) � �
�∑U �� �
Aj � �
A2t .A2b .𝜂 2 . k2 . H 2a . v2o
− j
Cd2 . . ( �C − C � )
𝜌 Cp A2t .A2b � pt pb �

� � ��
∑
5 �� 𝛼 I 𝜀j △R
� � �𝛼 𝛼j Ij �
���
j Ij
−Cd2 A2tot g.H. (Qi + Qdirect heat gain ) + (Uj Aj ) . h
j j
− ho j
− DF j (Tout − Tout � ) + ho j
− ho j
j=1 oj

=0

q3 + Ao .q2 − Bo .q − Ao .Bo − Co = 0 (22)

∑ A2t .A2b .𝜂 2 .k2 .H 2a .v2o (| |

)
Uj Aj Bo = Cd2 . ( 2 ) . | C − C | (24)
Ao = (23) At + A2b | pt pb |
𝜌Cp

Cd2 A2tot g.H. ∑5 � � 𝛼I 𝜀j ΔR

Co = .{(Qi + Qdirect heat gain ) + ( j=1
Uj Aj .{( hj j − ) − DF j [(Tout −
9Tout 𝜌Cp oj hoj
𝛼I 𝛼j Ij�
(25)
�
Tout ) + ( hj j − hoj
)]})}
oj

The solution of Eq. (22) is obtained using MATLAB, 1 6B + 2Ao 2 1

and the root of the equation is the combination of real and q= Do + o − Ao (26)
6 3Do 3
complex. The real root of Eq. (22) is considered the solu-
tion and presented in Eq. (26). where Do is expressed in terms of Ao, Bo, and Co in Eq. (27).

Table 3  Wind pressure Location Wind incident angle (θ)

coefficient (Yang et al. 2005)
(for low-rise exposed building 0o 45o 90o 135o 180o 225o 270o 315o
of length to width ratio 2:1)
Inlet face 0.5 0.25 − 0.5 − 0.8 − 0.7 − 0.8 − 0.5 0.25
Outlet face − 0.7 − 0.8 − 0.5 0.25 0.5 0.25 − 0.5 − 0.8
Environmental Science and Pollution Research

(√ )
Do = (72Ao .Bo + 108.Co − 8A3o + 12 −12.B3o + 24A2o + B2o − 12.Bo .A4o (27)
1
+108.Ao .Bo .Co + 81.Co2 − 12Co .A3o ) 3

Upon computing Eqs. (23) to (25) and Eq. (27), the sub- Brager and de Dear (Brager et al. 2000) proposed adap-
stitute in Eq. (26) gives the hourly ventilation flow rate. tive comfort standards for the naturally ventilated building
based on the field measurements, as shown in Fig. 2. The
standard provides two thermal comfort zones to anticipate
Thermal comfort standard and required ventilation
the acceptable indoor temperature, namely 80% accept-
flow rate
ability and 90% acceptability. It is applicable for the build-
ing, which has the provision to control window openings
Adaptive comfort standard for NV building
and average activity level < 1.2 met. The standard helps to
anticipate and compare the comfort temperature ranges with
Naturally ventilated buildings have thermal comfort stand-
those predicted from any thermal simulation. Moreover, it
ards comparatively different from the widely accepted pre-
is likely to be helpful to determine whether the predicted
dicted mean vote (PMV) method. Since the inhabitant’s
indoor comfort temperatures are comfortable enough with
thermal comfort temperature is higher than air-conditioned
natural ventilation or whether air conditioning would be
buildings, it is reported that the PMV is invalid for evaluat-
required during the design phase of the building. The selec-
ing thermal comfort conditions of natural ventilation build-
tion of the acceptability range depends on the inhabitants’
ings because it ignores the adaptation of occupants, which
climate characteristics and thermal expectations. In general,
is significantly considerable in naturally ventilated buildings
a 90% acceptability range is chosen if the thermal expecta-
(Busch 1992; Cena and De Dear 2001). Occupants staying in
tion of inhabitants is greater than the normal unevenness. In
naturally ventilated buildings can change the window open-
the present study, 80% acceptability is selected for Indian
ing percentage, and their thermal perception is diverse. An
people, and corresponding upper and lower thermal comfort
adaptive comfort standard (ACS) model was developed by
temperatures are defined using an adaptive standard chart.
Richard and Dear A (De Dear and Brager 2002) (De Dear
It is to be noted that the thermal comfort zone is limited to
and Brager 2002), and comfort temperature is proposed as
0–40 °C, because natural ventilation fails to provide comfort
a function of the mean monthly outdoor temperature given
conditions beyond the limit. Therefore, the monthly aver-
in Eq. (28).
age outdoor temperature hours beyond 0–40 °C limit are
Tc = 0.31Tao + 17.8 (28) ignored.
Upper thermal comfort temperature (Tupper) criteria,
where Tc is comfort temperature (K), and Tao denotes the
monthly average outdoor temperature (oC). ⎧ 22.85 0 ≤ Tao < 5
⎪
Tupper = ⎨ 0.31Tao + 14.30 5 ≤ Tao ≤ 33 (29)
⎪ 31.53 33 < Tao ≤ 40
⎩
32
30 Lower thermal comfort temperature (Tlower) criteria,
Indoor comfort temperature, Top (oC)

28 80% acceptability limit

26 90% acceptability limit

⎧ 15.85 0 ≤ Tao < 5
⎪
Tupper = ⎨ 0.31Tao + 14.30 5 ≤ Tao ≤ 33 (30)
24
⎪ 24.53 33 < Tao ≤ 40
22
⎩
20

18

16 Required ventilation flow rate

14
0 5 10 15 20 25 30 35 40 The variation of actual and required ventilation flow rates and
Mean monthly outdoor Air temperature (oC)
corresponding pressure differences in the climate measures its
potential for natural ventilation. The present work estimates
Fig. 2  Adaptive comfort chart for naturally ventilating building the needed ventilation flow rate according to ASHRAE 2002
(Brager et al. 2000)
 Environmental Science and Pollution Research

∑
Standard 62-2P Standards 62.1 & 62.2. https://​www.​ashrae.​ PDPH = 1hr ΔP+
org/​techn​ical-​resou​rces/​books​tore/​stand​ards-​62-1-​62-2). (35)
hours
According to the model, the ventilation flow ensures accept-
able indoor air quality by diluting the pollution from occupants Here, “ + ” shows only positive pressure difference values.
and background sources. The required ventilation flow rate is PDPH indicates the NVP of climate, which can be pre-
given by Eq. (31), dicted daily, monthly, and yearly. Also, it suggests the
region's capability to maintain indoor air quality while con-
qr = 0.0075Np + 0.0001Af (31) sidering thermal comfort criteria. To be precise, the esti-
mation of PDPH comprises the calculation of the ventila-
Here, qr is the required ventilation flow rate (­ m3/s), and Af tion flow rate due to natural driving forces and the required
is the floor area ­(m2). ventilation flow rate as per standard. That means the hourly
indoor air temperature estimate and further implementation
Estimation of NVP in terms of PDPH, NV hours of thermal comfort limits are appropriate procedures to filter
the hours that are not accountable for evaluating NVP.
The effect of thermal response factors (TL and DF) has been
considered in addition to the U-value of an envelope in the
NVP model. Then, the ventilation flow rate due to the com- Prediction of NV hours
bined effect of wind and stack is estimated, and the potential
for NV is estimated in terms of PDPH and NV hours. The fol- If the predicted indoor air temperature of concern hour falls into
lowing sections present the calculation procedure for PDPH the thermal comfort zone, it is termed natural ventilation hour
and NV hours. (NVH). The sum of NVH in a year indicates the potential for
NV, and the corresponding PDPH ensures indoor air quality.
Calculation of PDPH The workflow chart of NVP for a particular climate is presented
in Fig. 3. One climate is chosen, and its weather data is taken
Upon completion of both the natural ventilation flow rate (q) from the Typical Meteorological Year (TMY) database. Later,
and required ventilation flow rate (qr), the associated pressure the wind rose diagram is drawn in 8 directions (N, NE, E, SE,
difference can be estimated using Eqs. (32) and (33) (Yang S, SW, W, NW) using hourly wind speed and angle, choosing
et al. 2005). possible building orientations based on the wind frequency.
The effective pressure difference (ΔPeff), Further, the building model (dimensions presented in
𝜌 Table 2) is created and oriented in the feasible direction in
ΔPeff = q2 (32)
2Cd Atot 2
2 Design Builder software. Weather data of concern climate is
imported using a standard format, and an annual simulation
The required pressure difference (ΔPreq) for IAQ control, is conducted to calculate the incident solar radiation on the
𝜌 building envelope. The monthly DBT is estimated to choose
2
ΔPreq = 2
q
2 r (33) the design month, and the corresponding average sol–air
2Cd Atot
temperature is calculated using Eq. (6). Further, the building
The difference between Eqs. (32) and (33) gives the meas- envelope is assigned with suitable material configuration, and
ure of the potential for natural ventilation, which can be rep- their thermal response factors, which are predicted using a
resented as, developed numerical model, are incorporated into the NVP
analytical model. The hourly effective natural ventilation flow
( ) ( )
ΔP = ΔPeff − ΔPreq =
𝜌
q2 − qr 2 rate, indoor air temperature, heat gain, PDPH, and NV hours
2 2 (34)
2Cd Atot are estimated using MATLAB code. In addition, the predicted
total NV hours are divided as NV hours of windows fully
It is evident from Eq. (34) that the natural ventilation alone
opened and NV hours partially opened. On the other hand, the
can satisfy the required indoor air quality if ΔP is zero. Further,
remaining hours are classified as heating and cooling hours.
the term PDPH is introduced to evaluate the NVP of climate.
The conditions for segregating 8760 h into various types
According to Yang et al. (2005), the definition of PDPH is
follow the below constraints (Yin et al. 2010).
hourly. Some of the positive values of pressure difference are
given in Eq. (34). Later, it is modified by Luo et al. (2007) by • If Tin ≥ Tupper , cooling hours
incorporating the effect of thermal comfort in the NVP model. • If Tlower < Tin < Tupper , NV hours and windows are
That means the hour that does not satisfy the thermal comfort
assumed to be fully opened
condition and corresponding pressure difference will not be • If Tin ≤ Tlower andTin,max > Tlower , NV hours and windows
considered to estimate the climate’s PDPH.
are assumed to be partially opened
Environmental Science and Pollution Research

Fig. 3  Workflow chart for the

estimation of NV hour estima-
tion

• If Tin ≤ Tlower andTin,max ≤ T lower , heating hours The optimum building orientation is predicted for a particular
climate based on total NV hours, which yields maximum value.
Here Tin, max is the maximum indoor air temperature when
windows are closed completely, which means natural venti-
lation flow rate q = 0 then Eq. (11) will become as follows: Criteria evaluation and analysis of climate
potential
E
Tin,max = Tout + �∑ total � (36)
Uj Aj India is in the northern hemisphere (longitudes 60° E–100°
E and latitude between 5 and 20° N) and a large area in
the tropical region, and it has diversity in tropical climates.
 Environmental Science and Pollution Research

These regions are subjected to highly sunny climates. The Composite

climate of India is diverse, and the difference in tempera-
tures during winter and summer is found. The behavior of Yearly wind direction and wind speed data of various com-
the wind profile in India is it starts from the SE (southeast) posite cities, Raipur, New Delhi, Dehradun, and Jaipur are
direction, then it will be reversed in the northeast (NE) at the obtained from TMY. The wind rose diagram is plotted by
beginning and end of the rainy season (Tyagi et al. 2011). considering the occurrence of wind speed in a particular
The climate in India is classified as per the National Build- direction out of 8760 h, known as wind frequency in 8 eight
ing Code of India, 2016 (NBC), into five types: composite, directions; refer to Appendix 1 for wind rose diagrams. The
hot-dry, temperate, warm-humid, and cold (“National Build- concerned city’s optimum orientation is predicted based on
ing Code—Bureau of Indian Standards” n.d.). It is based on possible orientations noted per the prevailing wind direction.
the mean values of maximum and minimum temperatures From the wind rose of Raipur city, it is apparent that the
during summer and winter, the diurnal temperature range feasible wind prevailing directions are south, southwest, and
variation, and average relative humidity and annual precipi- west; corresponding wind frequencies are 22%, 17%, and
tation. According to NBC, 2016, the diurnal variation of 14%, respectively. The windows are assumed to be placed
temperature is 15–20 °C, 5–8 °C, 8–13 °C, and 35–22 °C only in the direction of the prevailing wind. In general, the
for hot-dry, warm-humid, temperate, and composite climates potential for natural ventilation is treated as high when the
of India. windows are placed in a high wind frequency direction,
The current study chooses 11 significant cities from var- irrespective of incident solar radiation on the envelope. But
ious climates, as presented in Fig. 4. The proposed NVP when the envelope’s thermal response factors are considered,
model is applied to major cities, and their potential for natu- it is anticipated that NVP varies significantly. For instance,
ral ventilation is estimated. Generally, climate suitability for if the building orientation is set in a high wind frequency
natural ventilation is predicted by evaluating energy conser- direction, the window receiving more solar load may lower
vation using local weather data and indicating the acceptable the NV hours than the other feasible directions. That means
outdoor temperature range. At the same time, the NVP of different conceivable building orientations that receive low-
climate explores the availability of natural driving forces and incident solar radiation may show higher potential. Hence,
whether the building benefits from the driving forces. So, in optimizing building orientation along with thermal response
the present work, the NVP of significant cities is estimated factors is paramount for estimating the true NVP of climate.
based on meteorological criteria, and the analysis of each Similarly, New Delhi city has shown a higher wind fre-
climate is illustrated below. quency of 34% in the north and 18% in the west than in other

Fig. 4  Climate classification Major Cities

and major cities of India
1. Raipur
2. NewDelhi
3. Jaipur
4. Dehradun
5. Ahmedabad
6. Jodhpur
7. Bengaluru
8. Chennai
9. Guwahati
10. Mumbai
11. Kolkata

Diurnal variation
Climate
of temperature
Hot-dry 15oC-20oC

Warm-humid 5oC-8oC

Temperate 8oC-13oC

Composite 35oC-22oC
Environmental Science and Pollution Research

directions (refer to Appendix 1 Fig. 11). In the case of Deh- According to Eco-Niwas Samhita (https://​beein​dia.​gov.​
radun, the highest wind frequency was in the northeast direc- in/​en/​eco-​niwas-​samhi​t a-​ens), one temperate climate in
tion, and different directions, namely southeast, west, and Bengaluru city is considered, and its wind rose, variation
south, have shown almost the same wind frequency of 14%. of monthly average incident solar radiation, and DBT have
The wind blew from west to east for Jaipur city, which is been obtained. The building orientation is analyzed using
located on the eastern border of the Thar Desert. Similarly, the result of the windrose diagram, and subsequently, the
south-to-north and northwest-to-southeast directions were effect of pertinent parameters is considered to envisage the
considered possible orientations (refer to Appendix 1 Fig. 11). NVP of Bengaluru’s climate.
The monthly average diurnal variation of incident solar
radiation and outside air temperature for four cities of com-
posite climate is presented in Appendix 2. It is to be noted Warm‑humid
that the interpretation is suggested for optimum building ori-
entation, which is predicted based on NV hours. The detailed The wind rose diagrams of four warm-humid cities, Chen-
explanations will be presented in the following sections. nai, Guwahati, Kolkata, and Mumbai, are obtained. Chen-
From hourly incident solar radiation for composite climate, nai city has the highest wind speed magnitude in the range
it is observed that the highest solar radiation incident on the of 28–30 m/s, and for the entire year, the wind occur-
roof is 1003 W/m2 in Raipur, 1013 W/m2 in New Delhi, and rence is in the direction of N-S. Similarly, Kolkata city
1022 W/m2 in Jaipur and Dehradun shows comparatively has shown the highest wind frequency in the N-S direc-
less value of 910 W/m2 (refer to Appendix 2). It is to be tion, and the maximum wind speed is 20–21 m/s. In the
noted that the analysis of weather data is presented for the case of Guwahati, the prevailing wind trends are noted as
optimum building orientation. Moreover, in the case of Deh- NE-SW, N-S, and SE-NW directions. The wind occur-
radun, if the building is oriented in the NE-SW direction, all rence is widespread most of the year, which means higher
walls receive almost the same magnitude of solar radiation. NVP. Still, the severe effect of thermal mass behavior is
Its highest value is the range of 410–505 W/m2. That means significant and cannot be avoided. Moreover, Mumbai city
the building envelope of different configurations may behave has a wind occurrence of 26% in the W-E direction, com-
differently, further influencing the NVP since their dynamic paratively higher than the other three cities. The maximum
thermal performance differs (refer to Appendix 1 Fig. 15). magnitude of wind speed is low. From the analysis of the
monthly average variation of incident solar radiation and
Hot‑dry and temperate DBT, the maximum DBT value observed for Chennai is
35.5 °C, Kolkata is 34.8 °C, and other cities, Guwahati and
Windrose diagrams of hot-dry climate cities Ahmedabad and Mumbai are 30.4 °C and 32.1 °C, respectively. Further,
Jodhpur are drawn. It is observed that Ahmedabad city has the effect of sol–air temperature, estimated using incident
feasible wind prevailing in the west (21%), southwest (18%), solar radiation, DBT, is analyzed for various envelope con-
and south (11%) (refer to Appendix 1). Also, higher wind figurations on the NVP.
speeds were observed at 24 m/s from the entire year’s data at
the lower frequency occurrence. In the case of Jodhpur, the
wind blew with the highest magnitude of 10–12 m/s wind
speed in the southwest direction. Wind occurrences are 18% Building envelope configurations
southwest, 14% northeast, and following frequent directions, and material properties
with 12% in west and south. The diurnal variation of inci-
dent solar radiation and DBT is presented for Ahmedabad The materials chosen for the wall design are commonly
and Jodhpur when the building is oriented in the optimum used in Indian cities, such as brick, AAC (autoclaved aer-
direction, i.e., northeast to southwest (NE-SW) is plotted ated concrete), EPS (expanded polystyrene), XPS (extruded
(refer Appendix 2). Both cities have similar variations of polystyrene), and cement plaster (CP). The envelope con-
sol–air temperature and DBT. figuration is assumed with insulation materials and air cavity
According to Eco-Niwas Samhita (https://​beein​dia.​gov.​ to analyze the potential for NV and whether the building
in/​en/​eco-​niwas-​samhi​t a-​ens), one temperate climate in benefits from the predicted NVP. Five wall designs are pro-
Bengaluru city is considered, and its wind rose, variation posed, namely W1, W2, W3, W4, and W5, and their thermal
of monthly average incident solar radiation, and DBT have transmittance (U-value) is shown in Table 4. Also, one roof
been obtained. The building orientation is analyzed using design (R1) with a U-value of 3.24 W/m2K is employed to
the result of the windrose diagram, and subsequently, the propose five different envelope configurations. The details
effect of pertinent parameters is considered to envisage the of five envelope configuration designs (ED), namely ED-I,
NVP of Bengaluru’s climate. ED-II, ED-III, ED-IV, and ED-V, are presented in Table 4,
 Environmental Science and Pollution Research

Table 4  List of envelope configurations variable indoor temperature, the potential for NV changes
Name of envelope con- Wall and roof design U-value (W/m K)2 abruptly.
figuration
NVP of significant cities using the present NVP
ED-I W1/R1 2.09 (W1)
model and comparison with the literature (Luo et al.
ED-II W2/R1 0.52 (W2)
2007)
ED-III W3/R1 0.52 (W3)
ED-IV W4/R1 1.4 (W4)
Natural ventilation hours of major cities are estimated by
ED-V W5/R1 0.7 (W5)
considering one major city from each climate when using
the new NVP model developed in this work. Three enve-
lope configurations are chosen to envisage the effect of
and material thermophysical properties referred from the thermal mass on NVP: conventional brick, insulation, and
literature are presented in Table 5. The schematic representa- air cavity. The impact of building orientation and dynamic
tion of envelope configurations and materials used for vari- thermal behavior of the envelope on NVH is compared in
ous designs are shown in Fig. 5. Table 6. Luo et al.’s (2007) model estimates the NVH of
the concerned city by considering the U-value of the build-
ing envelope constructed with different configurations and
Results and discussion located in a concerned city. It is seen that the predicted NVH
using both NVP models is different for various major cit-
NVP validation studies ies. Raipur, Ahmedabad, and Mumbai cities are observed
to overestimate NVP using the present model compared to
The comparison of effective pressure difference and its (Luo et al. 2007) the model, whereas Bangalore has shown
cumulative frequency (%) occurrence for three cities in an underestimation of NVP. In the case of Raipur, when the
China (Yang et al. 2005) has been done with the pre- effect of thermal response factors and building orientation
sent results as shown in Fig. 6. The weather data source is incorporated into the NVP model, NVP is overestimated
used in the literature and the assumptions considered are by an average of 18% compared to the NVP model, which
identical in the present simulation. It is apparent from is developed alone using U-value with fixed building ori-
Fig. 6 that the variation of adequate pressure difference entation. Similarly, both Ahmedabad and Mumbai cities
(ΔPeff) of all cities is matched with the present analyti- observed an overestimation of NVP, an average of 14% and
cal results. The weather data in the literature belongs 8%, respectively. In the case of Bengaluru, the underestima-
to 2005, 15 years ago. Notably, Shanghai has shown a tion of NVP is marked by an average of 7% with the present
mean percentage error (MPE) of 1.51% due to changes NVP model compared to literature.
in weather data. Similarly, Beijing and Guangzhou had Furthermore, the comparison of monthly variation of
0.13% and 0.09% errors, respectively. NVH obtained using both NVP models for composite cli-
Similarly, the results of the modified NVP model mate (Raipur) constructed with ED-I, II, and IV is presented
(Luo et al. 2007) are compared with the present analyti- in Fig. 8. A similar variation of monthly NVH is observed
cal results. They predicted NVP in terms of NV hours, for three different envelope configurations. Moreover, a sig-
and the comparison of monthly NV hours for three cities nificant effect on the prediction of NVH is monitored using
with current results is shown in Fig. 7 due to signifi- the present NVP model, and the developed model affirms
cant changes in this analytical model, i.e., estimation of the true NVP of climate.

Table 5  Material thermo Name of material Density Thermal conduc- Specific heat Absorptivity (α) Emissivity (ε)
physical properties (Kaşka and (ρ) (kg/ tivity (k) (W/m (Cp) (J/kg. K)
Yumrutaş 2009), (“IS 3792: m 3) K)
Guide for heat insulation of
non-industrial buildings; Balaji CP 1762 0.721 840 0.6 0.9
et al. 2019; Barreira et al. 2021)
Brick 1820 0.811 880 0.6 0.88
Expanded polystyrene 24 0.035 1340 0.6 –-
Air 1.125 0.0242 1006.43 –- –-
Reinforced concrete 2288 1.58 880 0.663 0.8
Concrete block (AAC) 700 0.166 1450.5 –- –-
Environmental Science and Pollution Research

Outside Inside Outside Inside

Cement plaster (12.5 mm) Cement plaster (12.5 mm)

Brick (230 mm)

Brick (230 mm)

EPS (50 mm)

Cement plaster (12.5 mm)

Cement plaster (12.5 mm)

W1 W2
Outside Inside Outside Inside

Cement plaster (12.5 mm) Brick (115 mm)

Brick (230 mm)

Air cavity (50 mm)

EPS (50 mm)
Cement plaster (12.5 mm) Brick (115 mm)

W3 W4
Outside Inside

Cement plaster (15 mm)

AAC (200 mm)

Cement plaster (15 mm)

W5
Outside

RCC (100 mm)

Cement plaster (25 mm)

Inside

Roof

Fig. 5  Schematic representation of envelope configurations

Applying the NVP model to major cities of India higher total NV hours. It can be perceived from the results of
and the effect of envelope configuration Raipur city, i.e., Raipur city has three possible building ori-
entations, namely, north–south (N-S), east–west (E-W), and
Optimum building orientation northeast-southwest (NE-SW) based on the wind frequency.
Incident solar radiation on the envelope is calculated for all
The possible building orientations are considered with the three orientations while importing the associated weather
help of the wind rose diagram, and the associated poten- file in a prescribed format into Design-Builder software as
tial for NV is estimated in terms of NV hours. The same per the workflow mentioned in Fig. 3. It is perceived that
is presented for major cities of India in Table 7. First, NV solar radiation on the envelope is the same when the build-
hours of concern for the city are assessed by considering the ing is orientated in N-S and E-W. Whereas in the case of the
building envelope as an ED-I configuration. The optimum NE-SW direction, it is different. Thus, the influence of build-
orientation of the concerned city is predicted, which yields ing orientation on the thermal response of the envelope, heat
 Environmental Science and Pollution Research

Fig. 6  Validation of effective 1 1

Shanghai Beijing

Cumulative Frequency (%)

cumulative ΔPeff of various cit-

Cumulative Frequency (%)

0.9 0.9
ies (Yang et al. 2005). a Shang-
0.8 0.8
hai. b Beijing. c Guangzhou
0.7 0.7
0.6 0.6
0.5 0.5
0.4 0.4
0.3 0.3
0.2 0.2
Present-work Present-work
0.1 Yang et.al., 2005 0.1 Yang et.al., 2005
0 0
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
ΔPeff(Pa) ΔPeff(Pa)
(a) (b)
1

Cumulative Frequency (%)

0.9 Guangzhou
0.8
0.7
0.6
0.5
0.4
0.3
0.2 Present work
0.1 Yang et.al., 2005
0
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5
ΔPeff(Pa)
(c)

Fig. 7  Validation of NV hours 700 700

Luo et.al., 2007 Shanghai Luo et.al., 2007 Beijing
in Chinese cities (Luo et al. Present work Present work
600 600
2007). a Shanghai. b Beijing. c
Guangzhou 500 500
NV hour
NV hour

400 400

300 300

200 200

100 100

0 0

(a) (b)
800
Luo et.al., 2007 Guangzhou
700 Present
600
500
NV hour

400
300
200
100
0

(c)
Environmental Science and Pollution Research

Table 6  Comparison of NVH obtained using the present NVP model with literature (Luo et al. 2007)
City name Luo et al. 2007 NVP model (no. Present NVP model (no. of % of NVH varia- % of NVH varia- % of NVH vari-
of NVH) NVH) tion for ED-I tion for ED-II ation for ED-IV
ED-I ED-II ED-IV ED-I ED-II ED-IV

Raipur 3528 3520 3706 4234 4271 4198 − 20.01 − 21.34 − 13.28
Ahmedabad 2959 3109 3338 3545 3688 3504 − 19.80 − 18.62 − 4.97
Bangalore 3546 3245 3009 3005 3198 2879 15.26 1.45 4.32
Mumbai 5128 5089 5232 5588 5650 5481 − 8.97 − 11.02 − 4.76

Fig. 8  Comparison of monthly 700 700

NVH of the building located in Luo et al [13] ED-I Luo et al [13] ED-II
Raipur, obtained for different 600 Present 600 Present
envelope configurations using
present NVP and Lou et al.’s 500 500
(2007) model. a ED-I. b ED-II.

NV hour
NV hour

400 400
c ED-IV
300 300

200 200

100 100

0 0

(a) (b)
600
Luo et al [13] ED-IV
Present
500

400
NV hour

300

200

100

(c)

gain, and subsequently on the NV hours is found. Although obtained optimum total NV hours as 4251 and 3753,
both N-S and E-W orientations have the same dynamic respectively. Similarly, for Bengaluru, out of 3 possible
thermal response behavior, it is observed that the highest orientations, southeast-northwest (SE-NW) is the opti-
wind frequency is kept for the N-S orientation. Similarly, mum. Warm, humid cities such as Chennai and Guwahati
in the case of New Delhi and Jaipur, the optimum building have obtained N-S orientation to predict optimum NVP.
orientation is observed for the N-S direction. In the case of Similarly, Mumbai is observed with E-W orientation. On
Dehradun, the NE-SW direction is observed as the optimum the other hand, Kolkata city has optimum NVP when the
orientation for the building. It is seen that the significant building is oriented in the NE-SW direction. Further, the
effect of thermal response factors of the envelope on the effect of remaining envelope designs on PDPH, total NV
potential for natural ventilation. hours, heating, and cooling hours have been studied by
In the case of hot-dry climate cities, i.e., Ahmedabad considering the optimum orientation for the building,
and Jodhpur, the northeast-southwest (NE -SW) has which is predicted using ED-I.
 Environmental Science and Pollution Research

Table 7  NVP comparison of various cities of composite climate when the building is oriented in feasible directions (ED-I configuration)
ity Orientation NV hours (win- NV hours (windows Heating hours Cooling hours Total NV hours PDPH (Pa.h)
dows fully open) partially open)

Composite climate
Raipur N-S 4234 233 1541 2752 4467 836
E-W 3708 483 1669 2900 4191 688
NE-SW 3857 480 1611 2812 4337 705
New Delhi N-S 3461 781 1541 2977 4242 545
E-W 3055 793 1703 3209 3848 489
Dehradun NE-SW 3805 635 2610 1710 4440 560
SE-NW 3738 518 2717 1787 4256 503
E-W 3722 715 2622 1701 4437 549
N-S 3657 744 2607 1752 4401 537
Jaipur N-S 3296 985 1496 2983 4281 612
E-W 3578 447 1543 3192 4025 689
SE-NW 3449 452 1569 3290 3901 663
Hot-dry climate
Ahmedabad E-W 3654 512 1612 2982 4166 678
N-S 3299 543 1673 3245 3842 653
NE-SW 3545 706 1612 2897 4251 669
Jodhpur NE-SW 2888 865 1526 3481 3753 725
SE-NW 2678 876 1589 3617 3554 708
E-W 2559 785 1710 3706 3344 702
N-S 2540 789 1720 3711 3329 719

Fig. 9  Hourly variation of 50 55

Raipur NewDelhi
the indoor air temperature of 45 50
buildings constructed with ED-I 40 45
configuration for composite 35 40
climate cities. a Raipur. b New 35
30
Tin (oC)

Tin (oC)

Delhi. c Dehradun. d Jaipur 30

25
25
20
20
15 15
10 10
5 5
0 0
0 1460 2920 4380 5840 7300 8760 0 1460 2920 4380 5840 7300 8760
Time (hr) Time (hr)
(a) (b)
45 50
Dehradun Jaipur
40 45
35 40
35
30
30
Tin (oC)

Tin (oC)

25
25
20
20
15
15
10 10
5 5
0 0
0 1460 2920 4380 5840 7300 8760 0 1460 2920 4380 5840 7300 8760
Time (hr) Time (hr)
(c) (d)
Environmental Science and Pollution Research

Hourly indoor air temperature Natural ventilation hours

The hourly variation of indoor air temperature for com- The effect of building orientation, the envelope’s dynamic
posite climate cities is shown in Fig. 9 when the building thermal response, and its configurations on NVP have been
is oriented in the optimum direction and constructed with obtained according to the workflow in Fig. 3. The monthly
ED-I configuration. The highest indoor air temperature is variation of NVP for Raipur climate when the building is
observed for Raipur, New Delhi, Dehradun, and Jaipur at oriented in the optimum direction and constructed with
45.6 °C, 46.7 °C, 42.5 °C, and 45.9 °C, respectively, and ED-II configuration has been presented in Fig. 10a. These
these values are registered during summer. Similarly, dur- results affirm that in the actual climatic conditions of
ing winter, the lowest indoor air temperature is observed as Raipur, generally during summer, the wind frequency with
8.1 °C, 9.1 °C, 4.1 °C, and 4.5 °C, respectively. It is to be higher wind speed magnitude is possible between March
noted that the hours that fall outside of the 0–40 °C range and August (based on yearly wind data). Figure 10a affirms
are ignored because natural ventilation alone cannot meet that NV hours when windows are opened completely, i.e.,
the required thermal comfort conditions. Indeed, the hour 100% windows opening, are higher during the period, and
that falls above 40 °C will be treated as a cooling hour. In the highest value is observed in August. Moreover, it sug-
the case of Dehradun, the intensity of outside weather data gests that some winter season months can be managed
is significantly different from that of other cities. Most of with natural ventilation. During the summer season, natu-
the hours in the year belong within the prescribed tempera- ral ventilation alone will not be sufficient to maintain the
ture limit. It is anticipated that both Raipur and Dehradun occupant’s thermal comfort as required. However, mixed-
can show enough potential for natural ventilation; moreo- mode ventilation conserves enough energy to overcome
ver, the building benefits from NVP are based on the enve- the cooling load demand instead of entirely depending on
lope configuration and its dynamic thermal performance. artificial ventilation.

Fig. 10  Potential of Raipur cli- 700

NV hours windows fully open
mate. a Monthly segregation of ED-II
8760 h. b Influence of envelope NV hour windows partially open
600
configuration on total NV hours Heating hours
Potential of City (hours)

500 Cooling hours

400

300

200

100

0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

(a)
800
ED-I
700 ED-II
ED-III
600 ED-IV
ED-V
Total NV Hours

500

400

300

200

100

0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

(b)
 Environmental Science and Pollution Research

Table 8  Comparison of NVP for various cities of composite climate when building constructed with different envelope configurations
City Optimum Configuration NV hours (win- NV hours (windows Heating hours Cooling hours Total NV hours
orientation dows fully open) partially open)

Raipur N-S ED-I 4234 233 1541 2752 4467

ED-II 4271 306 1449 2734 4577
ED-III 4269 300 1451 2732 4569
ED-IV 4198 329 1460 2773 4527
ED-V 4179 349 1490 2742 4528
New Delhi N-S ED-I 3461 781 1541 2977 4242
ED-II 3590 786 1560 2824 4376
ED-III 3440 779 1547 2994 4219
ED-IV 3389 792 1565 3014 4181
ED-V 3452 793 1528 2987 4245
Dehradun E-W ED-I 3722 715 2622 1701 4437
ED-II 3789 712 2472 1787 4501
ED-III 3803 675 2601 1681 4478
ED-IV 3805 689 2601 1665 4494
ED-V 3686 793 2616 1665 4479
Jaipur N-S ED-I 3296 985 1496 2983 4281
ED-II 3387 945 1502 2926 4332
ED-III 3187 912 1637 3024 4099
ED-IV 3098 958 1623 3081 4056
ED-V 3101 957 1667 3035 4058

Table 9  Comparison of NVP of hot-dry and temperate climate cities when building constructed with various envelope configurations
City Optimum Configuration NV hours (win- NV hours (windows Heating hours Cooling hours Total NV hours
orientation dows fully open) partially open)

Hot-dry
Ahmedabad NE-SW ED-I 3545 706 1612 2897 4251
ED-II 3688 721 1602 2749 4409
ED-III 3679 786 1654 2641 4465
ED-IV 3504 702 1676 2878 4206
ED-V 3465 723 1703 2869 4188
Jodhpur NE-SW ED-I 2888 865 1526 3481 3753
ED-II 2939 798 1647 3376 3737
ED-III 3001 887 1634 3238 3888
ED-IV 2876 912 1612 3360 3788
ED-V 2789 927 1576 3468 3716
Temperate
Bengaluru SE-NW ED-I 3010 2355 1765 1630 5365
ED-II 3198 2317 1656 1589 5515
ED-III 2989 2344 1707 1720 5333
ED-IV 2879 2267 1812 1802 5146
ED-V 2901 2213 1883 1763 5114

The influence of envelope configuration on NV hours is and low decrement factor. Hence, the associated dynamic
presented in Fig. 10b. It is observed that the monthly vari- thermal performance of the envelope is optimum, and wind
ation of total NV hours is significant. The reason is attrib- frequency is of concern to building orientation. It is found
uted to thermal response factors. It is noted that thermal that the building constructed with ED-II configuration has
mass will be effective when it possesses a high time lag shown optimum total NV hours throughout the year. Thus,
Environmental Science and Pollution Research

Table 10  Comparison of NVP for various cities of warm-humid climate when buildings constructed with different envelope configurations
City Optimum Configuration NV hours (win- NV hours (windows Heating hours Cooling hours Total NV hours
orientation dows fully open) partially open)

Chennai N-S ED-I 5442 101 264 2953 5543

ED-II 5489 134 261 2876 5623
ED-III 5387 157 293 2923 5544
ED-IV 5267 181 325 2987 5448
ED-V 5303 118 342 2997 5421
Guwahati NE-SW ED-I 4836 457 1600 1867 5293
ED-II 4902 464 1657 1737 5366
ED-III 4757 469 1647 1887 5226
ED-IV 4678 489 1704 1889 5167
ED-V 4548 488 1812 1912 5036
Kolkata N-S ED-I 4805 311 1135 2509 5116
ED-II 4944 362 1145 2309 5306
ED-III 4812 278 1249 2421 5090
ED-IV 4768 313 1098 2581 5081
ED-V 4781 296 1125 2558 5077
Mumbai E-W ED-I 5588 142 428 2602 5730
ED-II 5650 139 435 2536 5789
ED-III 5587 148 458 2567 5735
ED-IV 5481 178 497 2604 5659
ED-V 5498 173 476 2613 5671

Table 11  Consolidate NVP results of major cities in India

Climate City Orientation Envelope con- Total NV hours NV hours NV hours (win- Heating hours Cooling hours
figuration (windows fully dows partially
open) open)

Composite Raipur N-S W2, R1 (ED-II) 4577 4271 306 1449 2734
New Delhi N-S W2, R1 (ED-II) 4376 3590 786 1560 2824
Dehradun E-W W2, R1 (ED-II) 4501 3789 712 2472 1787
Jaipur N-S W2, R1 (ED-II) 4332 3387 945 1502 2926
Hot-dry Jodhpur NE-SW W3, R1 (ED-III) 3888 3001 887 1634 3238
Ahmedabad NE-SW W3, R1 (ED-III) 4465 3679 786 1654 2641
Temperate Bengaluru SE-NW W2, R1 (ED-II) 5515 3198 2317 1656 1589
Warm-humid Guwahati NE-SW W2, R1 (ED-II) 5366 4902 464 1657 1737
Mumbai E-W W2, R1 (ED-II) 5789 5650 139 435 2536
Chennai N-S W2, R1 (ED-II) 5623 5489 134 261 2876
Kolkata N-S W2, R1 (ED-II) 5306 4944 362 1145 2309

the proposed building with ED-II envelope configuration building is oriented optimally and constructed with five
in Raipur city will benefit from the natural ventilation. The envelope configurations. The building built with ED-II enve-
results of other major cities are discussed in the following lope configuration yields the highest NVP for all cities of
section. composite climate. At the same time, the building orienta-
tion is observed as independent of the climatic conditions
Optimum envelope configuration of the concerned city. The U-values of ED-II and ED-III
are the same, but it has been found that their dynamic ther-
Composite The optimum envelope configuration and associ- mal performance is different. It is observed that the ED-II
ated building orientation are presented in Table 8 for com- configuration has the highest time lag and lowest decre-
posite cities of India. It shows the climate’s NVP when the ment factor than other configurations, which is one of the
 Environmental Science and Pollution Research

optimum conditions for the best thermal mass performance. partially. The blow of higher wind speeds corroborates with
Therefore, the building constructed with ED-II configuration more wind frequency, and the building can utilize it when it is
shows optimum total NV hours: Raipur – 4577 h, NewD- in optimum orientation. To be precise, composite climate can
elhi – 4376 h, Dehradun – 4501 h, and Jaipur – 4332 h. On be managed with natural ventilation approximately 50% of the
the other hand, the highest cooling and heating hours are year when the building is constructed with ED-II configura-
observed for Jaipur and Dehradun, respectively. tion. The hot-dry climate has 47% of year time as NVP and the
highest NVP is observed for temperate and warm humid cities.
Hot‑dry and temperate The comparison of envelope con-
figurations on NVP for various cities of hot-dry and temper-
ate is presented in Table 9. It is observed that the building
constructed with ED-III configuration located in a hot-dry Conclusions
climate has shown optimum total NV hours. The reason is
corroborated by the influence of insulation location in the The NVP analytical model became more realistic by incor-
envelope configuration. While ED-II and III have the same porating the effect of building orientation, envelope thermal
material design, their thermal response characteristics vary. mass, and configuration. The thermal response factors of
It is anticipated that the location of insulation in the envelope concern envelope configuration are obtained from the previ-
configuration influences the indoor air temperature. In the ous studies of the same authors (Nagaraju et al. 2023). The
case of Ahmedabad city, approximately 50% of the year can model predicts the variation of indoor air temperature in
be managed with natural ventilation. Similarly, Jodhpur city response to the diurnal variation of outside weather condi-
has shown 44% of the time, which is significantly very low tions. 8760 h a year are segregated into NV hours when
potential for NV among all major cities of India. Temperate windows open fully, NV hours when windows open par-
climate city Bengaluru has demonstrated the potential for tially, and heating and cooling hours. The potential for NV
natural ventilation 63% of the time when the building is con- is indicated as the sum of NV hours when windows are
structed with ED-II configuration. Furthermore, a compre- opened fully, and windows opened partially are termed
hensive examination of the envelope’s material composition total NV hours. The developed NVP model is applied to 11
and structural arrangement is necessary to determine if the major cities in India, and the results of NVP are presented
building can utilize natural ventilation. Moreover, the enve- as the optimum building orientation and optimum envelope
lope configuration is climate-dependent, and the optimum configuration, which yields higher total NV hours. The fol-
potential for NV can be estimated with the help of desired lowing points are observed from the present investigation.
thermal response factors and the U-value of the envelope.
• The effect of thermal mass’s dynamic thermal performance
Warm‑humid A comparison of natural ventilation potential (thermal response factors) is paramount, along with the
for warm-humid cities is presented in Table 10. When the U-value, to anticipate the climate potential for NV.
building is constructed with five different envelope configura- • The developed model is more realistic because it assesses
tions, it is perceived that all warm-humid cities have shown whether the building benefits from NV or not in a par-
more than 50% of year time potential for NV. It is found that ticular climate rather than its suitability for NV.
optimum envelope configuration is observed with ED-II con- • A comparison of NVH obtained using the present NVP
figuration for all cities of warm-humid climates. The potential model with Lou et al. (2007) is presented for various major
for natural ventilation is observed as 64%, 62%, 60.5%, and cities of the Indian climate. It is observed that the incorpora-
66% of the time for Chennai, Guwahati, Kolkata, and Mum- tion of thermal mass effect and building orientation signifi-
bai, respectively. Moreover, the highest NVP is observed with cantly influences the true NVP of the concerned environment.
Mumbai when the building is oriented in an E-W direction. • ED-II is suitable for designing energy-efficient envelopes
Furthermore, the consolidated results of major cities of for composite, temperate, and warm-humid environ-
India are presented in Table 11. The details of optimum build- ments, and ED-III is best for hot-dry cities.
ing orientation and corresponding envelope configuration for • From the NVP analysis of 11 major cities, almost all
effective NV hours are illustrated. When the building is ori- warm, humid, and temperate cities have shown higher
ented in the N-S direction, the maximum potential for NV is potential for NV. It is observed that Mumbai has shown
observed as best for most cities, irrespective of climate. Also, 66% of year time for NV. The high to low NVP cities are
the envelope configuration consisting of cement plaster, EPS Mumbai, Chennai, Bengaluru, Guwahati, and Kolkata.
insulation, and conventional brick (i.e., both ED-II and III) • In the case of composite climate, Raipur has shown high
is the best for constructing the building in most Indian cities. potential, followed by Dehradun, New Delhi, and Jaipur.
Interestingly, temperate climate has the capability of natural The least NVP is observed for Jodhpur (hot-dry), i.e.,
ventilation to provide thermal comfort when windows open 44% of the year for NV.
Environmental Science and Pollution Research

• It is perceived from the analysis that although ED-II The model predicts the realistic NVP of climate and
and III possess the same U-value, the effect on NVP is illustrates whether the building benefits from the NVP of
registered significantly due to the variation of thermal climate. Moreover, it helps the designers decide while imple-
response factors. The envelope configuration is site-spe- menting natural ventilation and proposes a suitable passive
cific, and it is observed that most of the climates have design strategy for energy-efficient buildings. To make more
shown high NVP with ED-II except hot-dry. realistic decisions the study will benefit from CFD studies
and on-site measurements.
Appendix 1

N 0-2 N 0-1
25% 2-4 35% 1-2
4-6 2-3
20% 6-8 30% 3-4
NW NE 8-10 NW 25% NE 4-5
15% 10-12 5-6
>12 20% 6-7
10% 15% 7-8
>8
10%
5%
5%
W 0% E W 0% E

SW SE SW SE

S S

(a) (b)
N 0-1 0-1
18% 1-2
N 1-2
20% 2-3
16% 2-3 18% 3-4
NW 14% NE 3-4 16% 4-5
12% 4-5 NW 14% NE 5-6
10% 5-6 12% 6-7
8% 6-7 10% 7-8
6% 7-8 8% 8-9
6% 9-10
4% 9-10 10-11
2% 4%
10-11 2% 11-12
W 0% E >14 W 0% E

SW SE SW SE

S S

(c) (d)

Fig. 11  Wind rose of composite cities for yearly wind direction and wind speed. a Raipur. b New Delhi. c Dehradun. d Jaipur
 Environmental Science and Pollution Research

N 0-2 N 0-2
25% 2-4 20% 2-4
4-6 18% 4-6
20% 16%
NW NE 6-8 NW NE 6-8
14% 8-10
15% 8-10 12%
22-24 10% 10-12
10% 8%
6%
5% 4%
2%
W 0% E W 0% E

SW SE SW SE

S S

(a) (b)

Fig. 12  Wind rose of hot-dry cities for yearly wind direction and wind speed. a Ahmedabad. b Jodhpur

0-1
N 1-2
30% 2-3
3-4
25% 4-5
NW NE 5-6
20%
6-7
15% 7-8
8-9
10% 9-10
10-11
5%
W 0% E

SW SE

Fig. 13  Temperate climate city (Bengaluru) wind rose for yearly wind
directions
Environmental Science and Pollution Research

N 0-2
20% 2-4 0-1
4-6 N 1-2
6-8 18%
NW 15% NE 16% 2-3
8-10 3-4
NW 14% NE
10-12 12%
10% 12-14 4-5
10%
14-16 8% 5-6
5% 18-20 6% 6-7
20-22 4%
24-26 7-8
2%
W 0% E 28-30 W 0% E 8-9
10-11
11-12

SW SE
SW SE

S
S

(a) (b)
0-1 0-1
N 1-2 N 1-2
30% 2-3 30% 2-3
25% 3-4 25% 3-4
NW NE 4-5 NW NE
20% 20% 4-5
5-6
15% 15% 5-6
6-7
10% 7-8 10% 6-7
5% 8-9 5% 7-8
9-10 8-9
W 0% E W 0% E
20-21 9-10

SW SE SW SE

S S

(c) (d)

Fig. 14  Wind rose of warm-humid cities for yearly wind direction and wind speed. a Chennai. b Guwahati. c Kolkata. d Mumbai
 Environmental Science and Pollution Research

Appendix 2

Fig. 15  Monthly average inci- 1200 45 1200 45

dent solar radiation and outside N-S 40 N-S 40

Incident solar radiation (W/m2)

Incident solar radiation (W/m2)

DBT of composite cities for 1000 1000
35 35
design month May. a Raipur.

Temperature (oC)

Temperature (oC)
b New Delhi. c Dehradun. d 800 30 800 30
Jaipur 25 25
600 600
20 20
North North
400 East 15 400 East 15
South South
West West
10 10
Roof Roof
200 Tout
200 Tout
5 5

0 0 0 0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324 1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Time (hr) Time (hr)
(a) (b)
1000 35 1200 45
900 E-W N-S 40
Incident solar radiation (W/m2)

(W/m2)
30 1000
800 35
700 25

Temperature (oC)

Temperature (oC)
800 30

Incident solar radiation

600
20 25
500 600
15 20
400 North North
East 400 East 15
300 South 10 South
West West
200 10
Roof Roof
Tout 5 200 Tout
100 5

0 0 0 0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324 1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Time (hr) Time (hr)
(c) (d)

Fig. 16  Monthly average inci- 1200 45 1200 45

dent solar radiation and outside NE-SW 40 NE-SW 40
Incident solar radiation (W/m2)

(W/m2)

DBT of hot-dry cities for design 1000 1000

35 35
month May. a Ahmedabad. b
Temperature (oC)

Temperature (oC)
Jodhpur 800 30 800 30
Incident solar radiation

25 25
600 600
20 20
NE NE
400 SE 15 400 SE 15
SW SW
NW NW
10 10
Roof Roof
200 Tout
200 Tout
5 5

0 0 0 0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324 1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Time (hr) Time (hr)
(a) (b)
Environmental Science and Pollution Research

1200 35
SE-NW
Incident solar radiation (W/m2) 1000 30

25

Temperature (oC)
800
20
600
15
NE
400 SE
SW 10
NW
Roof
200 Tout 5

0 0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Time (hr)

Fig. 17  Temperate climate city (Bengaluru) monthly average varia-

tion of incident solar radiation and DBT

Fig. 18  Monthly average inci- 1000 40 800 35

dent solar radiation and outside 900 N-S
35 700
NE-SW
Incident solar radiation (W/m2)

Incident solar radiation (W/m2)

30
DBT of warm-humid cities for 800
design month May. a Chen- 30 600
25
700

Temperature (oC)

Temperature (oC)
nai. b Guwahati. c Kolkata. d 25 500
Mumbai 600
20
500 20 400
15
400 North 15 300 NE
East SE
300 South SW 10
West 10 200 NW
200 Roof Roof
Tout 5 100 Tout 5
100
0 0 0 0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324 1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Time (hr) Time (hr)
(a) (b)
1000 40 1200 35
900 N-S E-W
35
Incident solar radiation (W/m2)

(W/m2)

1000 30
800
30
700 25
Temperature (oC)

Temperature (oC)
800
Incident solar radiation

600 25
20
500 20 600
15
400 North 15 North
East 400 East
300 South South 10
West 10 West
200 Roof Roof
Tout
200 Tout 5
100 5

0 0 0 0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324 1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Time (hr) Time (hr)
(c) (d)
 Environmental Science and Pollution Research

Supplementary Information The online version contains supplemen- buildings: a review. Renew Sustain Energy Rev 59:1426–1447.
tary material available at https://d​ oi.o​ rg/1​ 0.1​ 007/s​ 11356-0​ 24-3​ 3496-3. https://​doi.​org/​10.​1016/J.​RSER.​2016.​01.​074
De Dear RJ, Brager GS (2002) Thermal comfort in naturally venti-
Author contribution Dora Nagaraju: conceptualization, methodology, lated buildings: revisions to ASHRAE Standard 55. In: Energy
writing—original draft. Siva Subrahmanyam Mendu: writing—review and Buildings. pp 549–561
and editing, supervision. Neelima Devi Chinta: supervision. Documents | UNFCCC. https://​n ewsr​o om.​u nfccc.​i nt/​d ocum​e nts.
Accessed 20 Aug 2021a
Data availability All the data used in this research is available in the ECBC Residential | Bureau of Energy Efficiency. https://w ​ ww.b​ eeind​ ia.​
manuscript. gov.​in/​conte​nt/​ecbc-​resid​ential. Accessed 25 May 2021c
ECO-NIWAS.https://​beein​dia.​gov.​in/​en/​eco-​niwas-​samhi​ta-​ens
Declarations Emmerich SJ, Dols WS, Axley JW (n.d.) A method to assess the suit-
ability of a climate for natural ventilation of commercial buildings
Ethics approval Not applicable. Energy Efficiency in Buildings Facts and Trends. https://​www.​wbcsd.​
org/​Progr​ams/​Cities-​and-​Mobil​ity/​Energy-​Effic​iency-​in-​Build​
Consent to participate No human subjects or animals are used for the ings/​Resou​rces/​Busin​ess-​reali​ties-​and-​oppor ​tunit​ies-​Summa​r y.
research in the manuscript. Hence, no consent to participate is required. Accessed 28 Jun 2019b
Germano M, Roulet CA (2006) Multicriteria assessment of natural
Consent for publication No human subjects or animals are used for the ventilation potential. Sol Energy 80:393–401. https://​doi.​org/​10.​
research in the manuscript. Hence, no consent to publish is required. 1016/j.​solen​er.​2005.​03.​005
Haase M, Amato A (2009) An investigation of the potential for natural
ventilation and building orientation to achieve thermal comfort
Conflict of interest The authors declare no competing interests. in warm and humid climates. Sol Energy 83:389–399. https://​doi.​
org/​10.​1016/J.​SOLEN​ER.​2008.​08.​015
IS 3792: Guide for heat insulation of non industrial buildings : Bureau
of Indian Standards : Free Download, Borrow, and Streaming :
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