Air pollutant emissions

scenario for India

EDITORS
Sumit Sharma
Atul Kumar

The Energy and Resources Institute

 Air pollutant
emissions scenario for
India
 Air pollutant
emissions scenario for
India

EDITORS
Sumit Sharma
Atul Kumar

The Energy and Resources Institute

© The Energy and Resources Institute 2016

Suggested format for citation

Sharma S., Kumar A. (Eds), 2016, Air pollutant emissions scenario for India,.The Energy and Resources Institute.
New Delhi.

Chapter Citation
Chapter Authors, Chapter name, In : Sharma S., Kumar A. (Eds), 2016, Air pollutant emissions scenario for India,
The Energy and Resources Institute

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 Introduction • v

CONTENTS
Chapter1 Introduction................................................................................... 1

Chapter 2 Energy Outlook for India............................................................... 7

Chapter 3 Residential.................................................................................... 21

Chapter 4 Industries...................................................................................... 49

Chapter 5 Power ........................................................................................... 83

Chapter 6 Transport ..................................................................................... 93

Chapter 7 Diesel Generator Sets ................................................................. 111

Chapter 8 Open Burning of Agricultural Residue ........................................ 121

Chapter 9 Evaporative Emissions................................................................. 133

Chapter 10 Other Sectors............................................................................. 149

Chapter 11 Summary and Conclusions........................................................ 163

CONTRIBUTORS
Editors
Sumit Sharma, Atul Kumar

Reviewers
Dr Prashant Gargava (Central Pollution Control Board, New Delhi), Prof. Mukesh Khare (Indian
Institute of Technology, Delhi), Prof. Mukesh Sharma (Indian Institute of Technology, Kanpur),
Prof. Suresh Jain (TERI University, New Delhi), Prof. B S Gurjar, (Indian Institute of Technology,
Roorkee), Prof. Prateek Sharma (TERI University, New Delhi), and Mr Zbigniew Klimont (IIASA,
Austria).

Chapter contributors
Sumit Sharma, Atul Kumar, Arindam Dutta, Ilika Mohan, Saptrishi Das, Arindam Dutta, Richa
Mahtta, C Sita lakshami, Sarbojit Pal, and Jai Kishan Malik

GIS
Vivek Ratan

TERI Press
Anushree Tiwari Sharma, Rajiv Sharma, Spandana Chatterjee, and R K Joshi
 Introduction • ix

PREFACE
 Introduction • xi

ACKNOWLEDGEMENTS

We gratefully acknowledge the support provided by the UK Aid for carrying out research
to develop air pollutant emission inventories in India and coming up with this publication.
The support was crucial in developing this important database of spatially distributed multi-
sectoral air pollutant emission inventories for India. However, the views expressed do not
necessarily reflect the official policies of the UK government.
The project team thankfully acknowledges the cooperation extended by various government
departments/organizations in providing relevant data and information. We gratefully
acknowledge the reviewers of the book who provided their unconditional and unbiased
comments and suggestions to improve the quality of the estimates. Finally, the project team
thankfully acknowledges the kind support, guidance and cooperation by TERI colleagues
during the entire study duration.
CHAPTER 1
Introduction
Sumit Sharma and Atul Kumar

I
ndia is following a steep trajectory of economic standards for particulate matter (PM) in about 80 per
growth. This makes it essential to plan for cent of the Indian cities conveys a grim picture of
optimal energy use and reduced impact over the prevalent ambient air quality across the country
the environment. Energy consumption in different (CPCB 2014). Air pollutants, such as PM, carbon
sectors is linked to emissions of various air pollutants monoxide (CO), oxide of sulphur (SO2), hydrocarbons
that deteriorate air quality at different scales. (HCs), oxide of nitrogen (NOX), are emitted from
Some of the pollutants are linked to inefficiency variety of sources and have adverse health effects.
in the combustion processes and others are due The impacts of some of the pollutants can be seen
to inadequate tail-pipe controls required for their at the regional scale. Ground level ozone formed
treatment. There are market-driven improvements by reactions of NOx and HC can lead to detrimental
that have happened on energy efficiency fronts in impacts on agricultural productivity of a region. The
the industrial sector, which have led to some control various impacts of air pollution are documented in a
of pollutant emissions. Some efforts have been made number of studies.
to control emission of air pollutants and betterment One of the preliminary step towards forming an air
of air quality at the city and national scale. However, quality management plan is to generate source-wise
rapid growth in different sectors has negated the emission inventories of different pollutants. These
effects of these interventions and led to further inventories are generally compiled for emissions
deterioration of air quality. from energy use in different sectors such as transport,
The health impacts of the deteriorating ambient industries, power, residential, etc., and fugitive
air quality, especially in urban cities of India are of emissions from non-energy sources, such as road
serious concern. Violation of ambient air quality dust, storage and handling of fuels, etc. The emission
2  •  Air Pollutant Emissions Scenario for India
inventories are developed for a base year and Model is linked with the emission estimation models
could be projected for future years under different to develop multi sectoral emission inventories in an
growth scenarios. Emission inventory is one of the integrated manner.
fundamental components of air quality management
plan to assess the progress or changes over time to Goal
achieve the cleaner air goal. Also, emission inventories To develop and document air pollutant emission
are an important input to the atmospheric models for inventories for different sources in India for a base
simulation of atmospheric pollutants. year and future. This study does not include emissions
For India, efforts have been made in past (Chatani of greenhouse gases and only focusses on air
et al. 2014; EDGAR 4.2 ((http://edgar.jrc.ec.europa. pollutant inventories.
eu/); Garg and Shukla 2002; Garg et al. 2006; Klimont
et al. 2009, Kurokawa et al. 2013; Lu et al. 2011; Ohara
et al. 2007; Purohit et al. 2010; Sahu et al. 2012;
Research Objectives
PP To prepare a baseline of emission inventories of air
Sharma et al. 2015; Streets et al. 2003; Zhang et al.
pollutant loads across different energy- and non-
2009) to estimate emissions for different sources
energy-based sources.
and pollutants. However, limited efforts are being
PP To prepare grid-wise high-resolution dataset of air
made to understand the possible future trajectory of
pollutant emissions inventory for India.
emissions for different sectors and pollutants, using
PP To project the future emission inventories using
integrated modelling approach. This study has used
integrated energy and emission modelling
an integrated modelling approach for achieving the
approaches.
above-mentioned goal. The integration of energy
PP To draft specific policy recommendations for
modelling exercise with emission assessment models
emission control in India.
helps to understand the overall energy mix in India
and inventorize the air pollutant loads from different
sectors (from energy-based and non-energy-based Approach and Methodology
sources) at a suitable resolution after taking into The overall framework used in this study is shown
account all the macro-economic changes in future in in Figure 1.1. Energy system modelling is carried out
an integrated manner. In this study, the TERI MARKAL using the MARKet ALlocation (MARKAL) model (Loulu

Figure 1.1: Overall framework for emission estimation

 Introduction • 3
et al. 2004) for India, which is fed into the emission control technology n (%) where ∑X = 1 (Klimont et al.
model to estimate emissions. The estimated emissions 2002).
are spatially allocated at the finest possible resolutions. Energy use information from the MARKAL model
results is fed into the emission modelling equations
The broad approach used in this study is further is to derive emission estimates for India. The main
explained by Equation 1. sectors considered in the analysis are residential,
transport, industries, power, and non-energy under
Ek=ΣiΣmΣnAk,l,m.(1—η l,m,n)Xk,l,m,n (1) the fuel categories of coal, diesel, gasoline, natural
gas, liquefied petroleum gas, and biomass. The
where, emission inventory was prepared for pollutants, such
k, l, m, n are region, sector, fuel, or activity type, as PM, NOx, SO2, CO, and NMVOC. PM emissions are
abatement technology; E denotes emissions of also speciated into different fraction of PM10, PM2.5,
pollutants (kt);  A the activity rate; ef the unabated black carbon (BC), and organic carbon (OC).
emission factor (kt per unit of activity); η the removal The schematic for steps followed for emission
efficiency (%); and X the actual application rate of inventorization is presented in Figure 1.2. This includes

Figure 1.2: Overall framework for emission estimation

4  •  Air Pollutant Emissions Scenario for India
a literature review of the existing inventories in India Garg, A. and Shukla, P. R., Emission Inventory of India,
and identification of key sources. These sources Tata McGraw-Hill, New Delhi, 2002.
include energy and non-energy sources contributing Garg, A., P. R. Shukla, and M. Kapshe. 2006. The sectoral
to atmospheric pool of pollutants. Activity data are trends of multigas emissions inventory of India.
collected at the finest possible resolution for different Atmospheric Environment 40:4608–4620.
sectors, and data quality checks are performed.
Klimont, Z., J. Cofala, J. Xing, W. Wei, C. Zhang, S.
A detailed review of emission factors is carried out for
Wang, J. Kejun, et al. 2009. Projections of SO2, NOx
all the major sources. Emission factors are selected and carbonaceous aerosols emissions in Asia. Tellus B
from the literature (mainly indigenous sources). 61(4):602–617.
Baseline emission inventories are prepared for the
Klimont, Z., D. G. Streets, S. Gupta, J. Cofala, L. Fu, and
year 2011 for different administrative regions and are
Y. Ichikawa. 2002. Anthropogenic emissions of non-
gridded using geographic information system (GIS).
methane volatile organic compounds in China.
Future energy scenarios till 2051 are developed using
Atmospheric Environment 36(8):1309–1322.
the TERI MARKAL model results. Emission projections
are made for the next four decades till 2051. Based Kurokawa, J., T. Ohara, T. Morikawa, S. Hanayama, J.-M.
on assessment of emission inventories, some Greet, T. Fukui. 2013. Emissions of air pollutants and
greenhouse gases over Asian regions during 2000–
recommendations are made for reduction in emissions.
2008: Regional Emission inventory in Asia (REAS)
version 2, Discussion. Atmospheric Chemistry and
Structure Physics 13:11019–11058, 10049–10123.
In this publication, baseline and future trends of
Loulou R., G. Goldstein, K. Noble, 2004. Documentation
emissions are presented for various sectors in for the MARKAL Family of Models, URL: http://www.iea-
India. Chapter 2 focuses on current energy use etsap.org/web/MrklDoc-I_StdMARKAL.pdf
patterns in India and future projections using the
Lu, Z., Q. Zhang, and D. G. Streets. 2011. Sulfur dioxide
TERI-MARKAL models. Thereafter, Chapter 3 to 10
and primary carbonaceous aerosol emissions in China
present the emissions inventories for Residential,
and India, 1996–2010. Atmospheric Chemistry and
Industries, Power, Transport, DG sets, Agricultural
Physics 11:9839–9864, doi:10.5194/acp-11-9839- 2011.
residue burning, Evaporative, and others sectors,
respectively. The final Chapter 11 summarizes Purohit, P., M. Amann, R. Mathur, I. Gupta, S. Marwah, V.
Verma, I. Bertok, et al. 2010. GAINS ASIA scenarios for
the report and presents overall findings including
cost-effective control of air pollution and greenhouse
sectoral contributions to the emission inventories.
gases in India. Laxenburg, Austria: International
Emission intensities are discussed in global context
Institute For Applied Systems Analysis.
and finally recommendations are provided for
control. The chapters also presents spatial distribution Ohara, T., H. Akimoto, J. Kurokawa, N. Horii, K. Yamaji, X.
of emissions at a fine grid resolution of 36 × 36 km2. Yan, and T. Hayasaka. 2007. An Asian emission inventory
of anthropogenic emission sources for the period
1980–2020. Atmospheric Chemistry and Physics
References 7:4419–4444, doi:10.5194/acp-7-4419-2007.
CPCB. 2014. National ambient air quality status & trends
– 2012. New Delhi: Central Pollution Control Board. Sahu, S. K., G. Beig, and N. S. Parkhi. 2012. Emerging
pattern of anthropogenic NOx emission over Indian
Chatani, S., M. Amann, A. Goel, J. Hao, Z. Klimont, A. Kumar, subcontinent during 1990s and 2000s . Atmospheric
A. Mishra, S. Sharma, et al. 2014. Photochemical roles Pollution Research 3(2012):262–269. 
of rapid economic growth and potential abatement
strategies on tropospheric ozone over South and Sharma, S., A. Goel, D. Gupta, A. Kumar, A. Mishra, S.
East Asia in 2030. Atmospheric Chemistry and Physics Kundu, S. Chatani, et al. 2015. Emission inventory
14:9259–9277. of non-methane volatile organic compounds
 Introduction • 5
from anthropogenic sources in India. Atmospheric Zhang, Q., D. G. Streets, G. R. Carmichael, K. B. He, H.
Environment 102:209–219. Huo, A. Kannari, Z. Klimont, et al. 2009. Asian emissions
in 2006 for the NASA INTEX-B mission. Atmospheric
Streets, D. G., T. C. Bond, G. R. Carmichael, S. Fernandes,
Chemistry and Physics 9:5131–5153.
Q. Fu, D. He, et al. 2003. An inventory of gaseous and
primary aerosol emissions in Asia in the year 2000.
Journal of Geophysical Research 108(D21):8809
CHAPTER 2
Energy Outlook for India
Ilika Mohan, Atul Kumar, and Saptarshi Das

Introduction India is highly dependent on fossil fuels. In 2011–12,

97 per cent of our commercial supply was from fossil

I
ndia’s commercial energy consumption has
fuels (coal, oil, and natural gas). Figure 2.1 below
almost doubled in the past decade growing at
provides a break-up of the commercial energy
a rate of 7 per cent per annum from 179 Mtoe
supply by fuel share. With the current consumption
(million tonnes of oil equivalent) in 2001–02 to 354
mix the role of fossil fuels is expected to grow.
Mtoe in 2011–12 (TERI 2006a; 2015a). India is one of
Energy consumption has environmental
the fastest growing economies in the world. Energy
implications as well. Increased usage of fossil fuels
consumption is among the key inputs in attaining
leads to a rise in air pollutants emission load in the
such growth. India’s growth experience is somewhat
country. India’s greenhouse gas emissions grew by 2.9
different from that of the developed countries
per cent per annum between 1994 and 2007, with total
as its energy requirements are growing faster,
emissions, including land use, land-use change, and
leading to energy insecurity and pollution impacts.
forestry, being 1,728 million tonnes of CO2 equivalent
(Ramakrishna & Rena 2013). Being a developing
in 2007 (MOEF 2010). In 2011, the CO2 emissions due to
country, with 27 per cent of its population below
energy usage from the power, residential, commercial,
the poverty line, access to energy is yet another
industry, transport, and agriculture sectors was 1.7
important issue that requires attention (Planning
billion tonnes, which was equivalent to 1.38 tonnes per
Commission 2009). Commercial energy supply in
capita.
8  •  Air Pollutant Emissions Scenario for India
and planners in the public and private sectors with
extensive details on energy producing and consuming
technologies. It also provides an understanding of the
interplay between the various fuel and technology
choices for given sectoral end-use demands. As a
result, this modelling framework has contributed
to national and local energy planning and to the
development of carbon mitigation strategies. The
MARKAL family of models is unique with applications
in a wide variety of settings and global technical
Figure 2.1: Commercial energy supply mix in 2011–12 support from the international research community.
Source: (TERI 2015a) MARKAL interconnects the conversion and
consumption of energy. This user-defined network
Modelling Framework and Scenario includes:
Description1 PP All energy carriers involved in primary supplies
(e.g., mining, petroleum extraction, etc.),
The scenario analysis and energy projections for
PP Conversion and processing (e.g., power plants,
the Indian energy sector have been carried out
refineries, etc.), and
with the aid of the MARKet ALlocation (MARKAL2)
PP End-use demand for energy services (e.g.,
model. This study builds on and integrates work
automobiles, residential space conditioning, etc.).
that has already been undertaken by TERI using
These may be disaggregated by sector (i.e.,
the MARKAL modelling framework for India and
residential, manufacturing, transportation, and
the knowledge base existing within TERI. TERI has
commercial) and by specific functions within a sector
developed a relatively detailed bottom-up MARKAL
(e.g., residential air conditioning, lighting, water
model database for India over the last two decades
heating, etc.).
and has been using it extensively for the analysis of
The optimization routine used in the model’s
energy technology at the national level. The following
solution selects from each of the sources, energy
sections describe the modelling framework, the
carriers, and transformation technologies to
rationale for choosing this model, how the reference
produce the least-cost solution, subject to a variety
energy scenario has been structured, and the
of constraints. The user defines technology costs,
assumptions that define it.
technical characteristics (e.g., conversion efficiencies),
and energy service demands.
Modelling Framework
As a result of this integrated approach, supply-
MARKAL is a bottom-up dynamic linear programming
side technologies are matched to energy service
model. It depicts both the energy supply and demand
demands. Some uses of MARKAL include
sides of the energy system, providing policy makers
1 Identifying least-cost energy systems and
1 It should be noted this exercise builds on the database investment strategies;
set up for the publication ‘Energy Security Outlook - 2 Identifying cost-effective responses to restrictions
defining a secure and sustainable future for India’ (TERI,
on environmental emissions and wastes under the
2015b). Authors would like to acknowledge the support
and input received from several research professionals principles of sustainable development;
and sector experts across TERI. 3 Evaluating new technologies and priorities for
2 MARKAL was developed in a cooperative multinational research and development;
project over a period of almost two decades by the
Energy Technology Systems Analysis Programme (ETSAP) 4 Performing prospective analysis of long-term
of the International Energy Agency. Available at <http:// energy balances under different scenarios;
www.iea-etsap.org/web/Markal.asp>.
 Energy Outlook for India  •  9
5 Examining reference and alternative scenarios in important to understand the assumptions made to
terms of the variations in overall costs, fuel use, construct the scenario.
and associated emissions.
Reference Scenario (RES)
A detailed representation of the modelling
This scenario is structured to provide a baseline
framework is shown in Figure 2.2.
that shows how the nation’s energy trajectory could
The MARKAL database for this exercise has been set
evolve provided current trends in energy demand and
up over a 50-year period extending from 2001 to 2051
supply are not changed. It takes into account existing
at five-yearly intervals coinciding with the duration of
policy commitments and assumes that those recently
the Government of India’s Five-Year plans. The base
announced are implemented. However, wherever
year of the exercise is 2001–02 and the data for 2001–
necessary, a diversion from government projections
02, 2006–07, and 2011–12 has been calibrated and
and forecasts has been assumed. The key assumptions
matched to the existing and published data.
made to construct the RES have been made in
In the model, the Indian energy sector is
consultation and discussion with several organizations,
disaggregated into five major energy consuming
relevant stakeholders, and sector experts across the
sectors, namely agriculture, commercial, industry,
country. These are described in the following sections.
residential, and transport. Each of these sectors is
further disaggregated to reflect the sectoral end-use
demands. The model is driven by the demands from
Macroeconomic parameters
the end-use side. The energy demand of the end-use sectors are an
On the supply side, the model considers the exogenous input in to the model. The calculation of
various energy resources that are available both each of these end-use energy demands is in itself an
domestically and from abroad for meeting various extensive exercise. The demands are primarily derived
end-use demands. This includes both conventional as a function of the gross domestic product (GDP)
energy sources, such as coal; oil; natural gas; hydro and population. For this, both GDP and population
and nuclear; as well as the renewable energy have been projected and the same have been used
sources, such as wind, solar, etc. The level of domestic across all sectors in this publication.
availability of each of these fuels is represented as
constraints in the model. Gross Domestic Product (GDP)
The relative energy prices of various forms and The GDP is assumed to grow at a rate of about 8 per
sources of fuels dictate the choice of fuels, which play cent rising from INR 19.7 trillion in 2001 to INR 741.58
an integral role in capturing inter-fuel and inter-factor trillion in 2051 at 1999–2000 prices. The sectoral GDP
substitution within the model. Furthermore, various has been calculated based on a regression analysis
conversion and process technologies characterized that establishes the relationship between sectoral GDP
by their respective investment costs, operating and the total GDP. The share of agriculture, industry,
and maintenance costs, technical efficiency, life, and services GDP in the total GDP is seen to vary over
etc. to meet the sectoral end-use demands are also the years. The share of agriculture falls from 26 per
incorporated in the model. cent in 2001 to 6 per cent in 2051 while the share of
The model run and analysis that has been industry rises from 23 per cent in 2001 to 34 per cent
carried out provides outcomes in terms of fuel in 2051 and the service sector rises from 51 per cent in
mix, technology deployment, primary energy 2001 to 60 per cent in 2051. Table 2.1 shows the gross
requirement, power generation, and CO2 emission GDP (in trillion, at 1999–2000 prices) and shares of
levels. In order to understand the model results, it is various sectors in the GDP.
 10  •  Air Pollutant Emissions Scenario for India

Figure 2.2: MARKAL modelling framework

Source: (TERI 2006b)
 Energy Outlook for India  •  11

Table 2.1: Gross GDP (in trillion, at 1999–2000 prices) and sector Table 2.2: Population (in billion) of India
shares  Year Total Rural Urban
Sector Shares 2001 1.03 0.74 0.29
Year Gross GDP Agriculture (%) Industry (%) Services (%) 2011 1.20 0.84 0.36
2001 19.7 26 23 51 2021 1.37 0.93 0.44
2011 43.4 19 26 55 2021 1.37 0.93 0.44
2021 97.6 16 28 56 2031 1.52 1.01 0.52
2031 211.7 12 30 58 2041 1.65 1.06 0.59
2041 414.1 9 32 59 2051 1.75 1.09 0.67
2051 741.5 6 34 60 Source: (PFI 2007)
Source: TERI Analysis
End-use demand
Population The end-use demands, as described earlier, are
divided in to five sectors: agriculture, industry,
There are many studies that have projected
residential, commercial, and transport. Future
population of India at national and state level. The
demand for each of these sectors is calculated using
Population Foundation of India (PFI) has carried
different econometric methods and is then fed in to
out projections in two scenarios, viz scenario A and
MARKAL as input.
Scenario B (PFI, 2007). PFI has used a component
The population and GDP projections are used as
method to make the projections. The Component
the main driving force for estimating the end-use
Method is the universally accepted method of
demands in each of the energy-consuming sectors.
carrying out population projection where the
Also, on the demand side, assumptions are
population is broken down into its three major
made on the end-use technological levels. It
components- survived population, number of births
involves inclusion of new technologies, efficiency
taking place and net migration. This method takes
improvements in the existing ones, and their
into account separately future course of fertility,
changing penetration levels.
mortality and migration and is therefore considered
Demand for the industry sector has been
more accurate than any mathematical method
calculated for 10 of its most energy-consuming
based on past trends. The ability to provide age sex
sub-sectors, namely iron and steel, cement, brick,
break-up of the projected population is an added
glass, aluminium, textile, fertilizers, chlor-alkali,
advantage of this method.
petrochemicals, and paper. Other energy-consuming
Among all the projections studied, PFI scenario B
industries that include small-scale industries, such
assumptions have been agreed upon as the most
as food-processing, ceramics, sugar mills, foundry,
likely trajectory for India after expert consultation
leather/tanning, etc., are grouped in a single sub-
and extensive literature review. This study has
sector collectively called ‘other industries’. Production
therefore used PFI scenario B projection.
(as a proxy of demand) in each of these industrial
The Scenario B of the PFI projections, assume that the
sub-sectors is projected using econometric
states of India with total fertility rate (TFR) more than
techniques. Econometric analysis has been carried
that of the replacement level TFR will reach a target
out for each of the major industry sub-sectors, taking
level of 1.85 by 2101, while those states with very low
production as the dependent variable and using
levels of TFR like Kerala and Tamil Nadu are assumed
various macroeconomic indicators, such as GDP
to have a constant TFR at the existing level. Table 2.2
(aggregate), GDP of industrial sector, services, and
shows the decadal population (in billion) of India.
agriculture, etc. as independent variables.
12  •  Air Pollutant Emissions Scenario for India
In the RES, efficiency improvement is considered accordance to the current and expected cropping
as per the past trend and in line with commercially patterns.
available technological options in the industry sector. In the RES, the share of efficient tractors in land
Due to liberalization and opening up of domestic preparation is assumed to be the same as the current
markets, large scale industries, such as cement, iron levels with no improvement. The share of efficient
and steel, petrochemicals, and other chemicals, electric pump sets in irrigation is assumed to rise from
assumed to improve their energy efficiency levels negligible levels in 2011 to about 40 per cent in 2051.
by adoption of state-of-art technologies. Small-scale In the residential sector, the demand is projected for
manufacturing enterprises adopt energy efficient lighting, cooking, space conditioning, and refrigeration
technologies at slower rate. separately for urban and rural households to account
The transportation demand (disaggregated for the differences in lifestyle and choice of fuel and
further into mode-wise passenger kilometre demand technology options. Each of these end-use demands
and freight kilometre demand) is projected using is estimated using a bottom-up methodology wherein
various socioeconomic indicators, such as per-capita they are calculated across different monthly per capita
income (indicator of purchasing power), population, expenditure classes and these are further aggregated
and so on. To project the passenger and freight to give the final demand.
kilometres from each mode, their estimated vehicle Various assumptions have been made on the
population is multiplied with the occupancy rates level of penetration of efficient appliances in the RES.
and utilization levels. The estimation of occupancy The share of efficient air conditioners, fans, coolers,
rates and efficiency for each mode of transport has and refrigerators is taken to rise in both the rural and
been made after extensive stakeholder consultation urban households from about 9 per cent in 2011 to 50
and discussion with sector experts. per cent in 2051. It is also assumed that 100 per cent
Assumptions regarding fuel and technology electrification will be achieved post 2016. By 2031, we
penetration in RES for the transport sector have been assume that 90 per cent of the lighting demand would
made keeping the present situation in mind. We be met by CFLs (Compact Fluorecscent Lamps). The
consider that the share of CNG (Compressed Natural share of improved cook stoves rises to 20 per cent from
Gas) in cars and public transport rises to 4 per cent, negligible levels in 2011 by 2051 in the RES.
from present levels of 1 per cent, by 2051. Share of In the commercial building sector, the demand
railways in passenger movement is taken to drop is projected for cooking, lighting, and space
from 14 per cent in 2011 to 12 per cent in 2051 while conditioning based on built-up area, energy
that in freight is assumed to decrease to 23 per cent performance index (EPI), and the value added by
(2051) from 39 per cent (2011). An increase in electric the services sector as an explanatory variable. Along
traction in freight movement from 65 per cent (2011) with the energy demand arising from commercial
to 70 per cent (2051) and in passenger movement buildings, energy demand for public lighting, public
from 50 per cent (2011) to 52 per cent (2051) has water and sewage pumping is included in the
been built in the model. Role of biofuels is minimal in commercial sector. The commercial buildings sector’s
the RES. energy demand for the study was calculated using
In the agriculture sector, demand is estimated for EPI numbers and the built-up area.
land preparation and irrigation pumping. Demand In the RES, we assume no improvement in the EPI
for land preparation is calculated by estimating the and limited GRIHA3 penetration in the new buildings
number of tractors and tillers that will be required (from 1 per cent in 2011, 3 per cent by 2021, 6 per cent
in future. The demand for irrigation pumping is by 2031, and 10 per cent by 2051).
calculated by estimating the future water demand 3 GRIHA is an acronym for Green Rating for Integrated
of the agriculture sector. This has been done in Habitat Assessment. Available at <http://grihaindia.
org/>. last accessed on July 1, 2015.
 Energy Outlook for India  •  13

Energy supply discoveries coming on-stream, and OIL’s natural gas

output stays constant at 2.8 BCM.
As a result of problems currently constraining the
In the medium to long term (2021–51),
production of coal, it is assumed that the production
assumptions are made on total domestic gas
of non-coking coal will reach a maximum of about 700
production and not on production by individual
MT by 2021 (i.e., representing a compounded annual
companies. If the natural gas scenario continues as
growth rate (CAGR) of 3.7 per cent) and increase by 3
usual, we do not consider a very significant rise in
MT annually up to 2031. It is assumed that the present
domestic gas production. Domestic production is
trend in the production of metallurgical coal will
assumed to reach a maximum of 50 BCM by 2031.
continue, and the production will reach a maximum of
With regards to technology penetration in the
19 MT by 2021–22 and stay at that level thereafter. We
power sector, large scale deployment of supercritical
see that the overall constraints in production of coal
technology for coal-based generation is considered.
will impact the production of non-metallurgical coal
Further, it is also assumed that ultra-supercritical
as well. Therefore, it is assumed that the production
technology would be available at commercial scale
of non-metallurgical coal will peak at nearly 50
MT by 2021–22 and increase by 0.5 MT each year Table 2.3: Tentative programme for capacity additions to grid-
thereafter till 2031. For the production of lignite, we interactive renewable power under the XII Five-Year Plan (2012–17)
take conservative estimates, with projections that the and XIII Five-Year Plan (2017–22)
production will increase at a rate of 4 per cent between Source/system Capacity addition Capacity addition (MW),
2011–12 and 2021–22, reaching approximately 63 MT (MW), XII Plan XIII Plan
by 2021–22. Thereafter, it is assumed to grow by 2 MT Wind power 15,000 15,000
each year. Total domestic coal production reaches a Biomass power 2,100 2,000
maximum of about 880 MT by 2036. Small hydropower 1,600 1,500
In order to estimate constraints on our domestic
Solar power 10,000 16,000
crude oil production for the RES, we assume that in
Waste to energy 500
the short term (up to 2021) ONGC’s offshore crude
output remains constant, and its onshore crude Tidal power 7
output continues to decline steadily. OIL’s onshore Geothermal power 7
crude production stays at around 4.5 MT. Private/joint Total 29,214 34,500
venture (JV) onshore crude output increases steadily
up to 10 MT in 2015–16 and offshore crude output by only by 2031. In view of increasing concern about
private/JV companies continues to decline as has been rehabilitation and relocation issues, the capacity
the case over 2000–01 to 2011–12. realizations of large hydroelectric plants to a
In the medium to long term (2021–51), moderate level of around 94 GW by 2031 and 148 by
assumptions are made on the total domestic crude 2051 is predicted.
oil production and not on production by individual Nuclear energy in the RES is projected to rise
companies. Total production remains relatively from an installed capacity of 5 GW in 2011 to 28
stagnant at a little above 40 MT after 2021. GW in 2031 and 103 GW in 2051. Delays in land
Natural gas assumptions are based on a similar acquisitions, slow expansion, and commercialisation
analysis. In the short term (up to 2021), we assume of Fast Breeder technology and uncertainties (from
Reliance’s KG-D6 gas output continues to fall steadily. the supplier’s perspective) surrounding the nuclear
Private/JV companies’ production of natural gas liability law are the major considerations for such
remains constant at 11 billion cubic metres (BCM) modest projections.
from 2016 to 2017. ONGC’s gas output stays constant Till now, renewable energy capacity addition
and increases moderately after 2015–16 due to new targets have always been achieved in each of the five-
14  •  Air Pollutant Emissions Scenario for India

Figure 2.3: Primary energy supply

Source: TERI Analysis, 2015

year plans. This scenario assumes that this positive five times over from 717 Mtoe in 2011 to 3,851 Mtoe
trend will continue and there will be no shortfall in by 2051 at a CAGR of 4.3 per cent. In the RES scenario,
targets. The targets of the five-year plans taken in to coal continues to remain the dominant fuel in the
consideration are mentioned in Table 2.3. supply mix throughout the modelling period with
its share rising from 39 per cent in 2011 to 50 per
Modelling Results for the RES cent by 2031 and remaining so for the rest of the
The following sections enumerate the results modelling period. Coal supply grows from 280 Mtoe
obtained from the model for the RES. in 2011 to a staggering 1,897 Mtoe in 2051. The share
of oil in the supply mix rises from 22 per cent in 2011
to 26 per cent in 2031 and 31 per cent by 2051. Even
Primary Energy Supply4
though it is projected that the magnitude of natural
Figure 2.3 reflects the primary energy supply by fuel.
gas in the supply mix will increase about five times
The primary energy supply in the RES grows almost
from 58 Mtoe in 2011 to 271 Mtoe by 2051, its share
4 As per the glossary of statistical terms of the in the mix drops from 8 per cent in 2011 to 7 per cent
Organisation for Economic Co-operation and by 2051. Share of nuclear energy is predicted to see a
Development (OECD), primary energy consumption slight increase from 1 per cent in 2011 to 5 per cent
refers to the direct use at the source or supply to users
by 2051. Thus by 2051, 88 per cent of the primary
without transformation, of crude energy, that is, energy
that has not been subjected to any conversion or commercial energy comes from coal, oil, and gas; 4
transformation process.
 Energy Outlook for India  •  15

Figure 2.4: Power generation capacity (centralized and decentralized)

Source: TERI Analysis, 2015

per cent from traditional biomass;5 5 per cent from the XII and XIII five-year plans for the development
nuclear energy; and remaining from renewables and of renewable energy capacity have been achieved,
large hydro. increasing the renewable-based capacity from 22
GW (sum total of solar, wind, biomass, waste, tidal,
Power Generation and geothermal energy-based capacity) in 2011
Figure 2.4 shows the growth of power generation to 142 GW in 2031 and to 265 GW by 2051; hence,
capacity (centralized and decentralized). In the their share rises from 9 per cent (2011) to 14 per
RES, the generation capacity grows thrice from 239 cent (2051).
GW to 821 GW in 2031 and almost eight times over
to 1,884 GW by 2051. In 2051, 54 per cent of this Final Energy Demand6
generation capacity is based on coal and the share Figure 2.5 shows the final energy demand by sectors
of gas-based generation capacity rises from 11 per over the modelling framework. Our energy demand in
cent in 2011 to 19 per cent in 2051. Diesel-based the RES grows from 549 Mtoe in 2011 to 1,460 Mtoe in
generation is seen to slowly disappear. Nuclear 2031 and 2,812 Mtoe in 2051, increasing by five times
capacity grows over 21 times from 5 GW in 2011 to in 40 years. Energy consumption of the commercial
103 GW by 2051. It is also seen that even though the sector grows at the fastest pace, with a CAGR of 8 per
target potentials for hydro power are realized and cent. In terms of magnitude, industry and transport
its capacity grows from 42 GW in 2011 to 142 GW sector are the two main energy-consuming sectors
by 2051. As was the assumption, targets set out in with the energy consumption of the transport sector
increasing by about 10 times by 2051.
5 Traditional biomass includes fuel wood, animal dung, and
crop residue. 6 End use energy demand.
16  •  Air Pollutant Emissions Scenario for India

Figure 2.5: Final energy demand (inclusive of traditional biomass)

Source: TERI Analysis, 2015

Figure 2.6: Final energy demand by fuel—Industry sector

Source: TERI Analysis, 2015
 Energy Outlook for India  •  17
The energy consumption trajectories, by fuel, of while that of natural gas from 12 per cent in 2011 to
each demand sector are discussed in details below. 10 per cent by 2051.

Industry sector Transport sector

Figure 2.6 shows the final energy demand by Figure 2.7 reflects the final energy demand by the
the industry sector by fuel. Industry demand has transport sector by fuel. The energy demand of the
been projected to grow from 221 Mtoe in 2011 transport sector grows from 86 Mtoe in 2011 to 360
to 697 Mtoe in 2031 to 1,215 Mtoe by 2051 at a Mtoe in 2031 and over 10 times to 900 Mtoe by 2051.
CAGR of 4 per cent over 40 years. This rapid growth This sizeable growth in the transport sector can be
in energy consumption in the industrial sector is attributed to a shift towards more energy-intensive
largely on account of the growth in infrastructural modes of transport for both passenger and freight
demands of the country (steel, cement, and brick movement. This 10-fold increase is mainly due to
demands). Coal is used to meet more than half of the rapid growth in the consumption of petroleum
the sector’s energy demand and its consumption products in the transport sector, which has grown at a
increases by seven times over in 40 years. CAGR of 6 per cent. In 2011, petroleum products were
Coal in this sector is also used to generate used to meet over 97 per cent of the sector’s energy
decentralized electricity. Petroleum products and demand and this falls to 95 per cent in 2051, which
natural gas are the next most popular fuels that still is a very significant share. There is a slight increase
are used in the sector. The share of petroleum in the use of CNG and electricity. Role of biofuels in
products, however, is seen to decrease slightly this scenario is minimal.
from 16 per cent in 2011 to 11 per cent by 2051,

Figure 2.7: Final energy demand by fuel—Transport sector

Source: TERI Analysis, 2015
18  •  Air Pollutant Emissions Scenario for India

Figure 2.8: Final energy demand by fuel- Residential sector

Source: TERI Analysis, 2015

Figure 2.9: Final energy demand by fuel—Commercial sector

Source: TERI Analysis, 2015

Residential sector in 2011 to 269 Mtoe in 2031 and about 1.6 times to
325 Mtoe in 2051. About 40 per cent of the energy
Figure 2.8 depicts the final energy demand by the
demand in the sector is met by traditional biomass
residential sector by fuel. The final energy demand
even in 2051. Traditional biomass is an important
of the residential sector increases from 206 Mtoe
 Energy Outlook for India  •  19
fuel primarily used for cooking in the residential Agriculture sector
sector. Also, due to greater appliance penetration and
Figure 2.10 depicts the final energy demand of the
electrification, the electricity consumed by the sector
agriculture sector by fuel. The final energy demand of
rises over 11 times from 15 Mtoe in 2011 to 161 Mtoe
the sector rises almost three times over from 21 Mtoe
in 2051.
in 2011 to 58 Mtoe in 2031 and 76 Mtoe by 2051 in
the RES. Electricity and petroleum products are the
Commercial sector only two fuels used to meet the energy demand of
Figure 2.9 reflects the final energy demand of the the sector, with diesel being used mainly for land
commercial sector by fuel. The final energy demand preparation and electricity for irrigation purposes.
of the sector grows from 16 Mtoe in 2011 to 77 Mtoe Overtime, the share of petroleum products is seen to
in 2031 and grows by 19 times to 295 Mtoe in 2051. fall while that of electricity rises.
Petroleum products and electricity are the two most
popular fuel choices of the sector. Use of petroleum CO2 emissions
products is inclusive of DG sets used in the sector. It
Figure 2.11 shows the level of CO2 emissions
should be noted that in the RES no reduction of EPI
throughout the modelling period. The CO2 emission
of commercial buildings is considered and limited
levels reported by the model are the emissions that
penetration of GRIHA-rated buildings is assumed in
result from fuel use across the economy both for
new buildings. Thus, we see that the use of electricity
energy and non-energy purposes. In the RES, the CO2
grows by about 24 times and its share in the sector’s
emission levels rise from 1.7 billion tonnes (2011) to
fuel mix grows form 61 per cent in 2011 to 79 per
5.5 billion tonnes in 2031 and 11.3 billion tonnes in
cent by 2051. Hence, electricity is the prime fuel used
2051. Thus, the per capita emissions grow from 1.38
to fulfil energy demands of this sector.
tonnes (2011) to 3.64 tonnes (2031) and 6.45 tonnes
(2051). Our per capita emissions in 2051 still are

Figure 2.10: Final energy demand by fuel—Agriculture sector

Source: TERI Analysis, 2015
20  •  Air Pollutant Emissions Scenario for India

Figure 2.11: CO2 emission levels

Source: TERI Analysis, 2015

lower than then the present per capita emissions of and supply sides for the economy to attain the most
many developed nation but whether or not the RES efficient utilization of its resources and moving
is a most sustainable pathway is subject to debate in towards a sustainable growth.
light of the results shown in the preceding sections.
There is no doubt that a lot more needs to be done References
for India to move towards an energy secure future. MOEF. 2010. India: Greenhouse gas emissions 2007.
New Delhi: INNCA: Indian network for Climate Change
Conclusion Assessment, Ministry of Environment and Forests,
The modelling exercise clearly points towards Government of India.
India’s increasing dependence on fossil fuels in a PFI. 2007. The future population of India: A long-range
‘Business-As-Usual’ scenario. It indicates that coal demographic view. New Delhi: Population Foundation
would continue to play a key role in meeting the of India.
country’s energy requirements. This may push India’s Planning Commission. 2009. Report of the expert group
dependence on import of fossil fuels. The growth in to review the methodology for estimation of poverty.
usage of fossil fuels is coupled by a ten-fold increase New Delhi: Planning Commission, Government of India.
in the level of CO2 emissions in 40 years. Ramakrishna, G., & R. Rena. 2013. An empirical analysis
India’s demand energy is also going to grow of energy consumption and economic growth in
tremendously in the future. It is seen that one of India: Are they casually related? Studia Oeconomica,
58(2):22–40.
the major consumers of commercial energy in
India is the transport sector. The sector is also the TERI. 2006a. TERI energy data directory and yearbook
largest consumer of petroleum-based fuels. This (TEDDY). New Delhi: TERI Press.
is a particular cause of concern owing to the large TERI. 2006b. National energy map for India: Technology
dependence of the country’s refining sector on vision 2030. New Delhi: TERI Press.
imported crude oil. The Industry sector is also a TERI. 2015a. TERI energy and environment data
major consumer of coal. Another point to note is directory and yearbook (TEDDY). New Delhi: TERI Press.
the continued reliance of the residential sector on TERI. 2015b. Energy security outlook: Defining a secure
traditional biomass to meet its cooking needs. and sustainable energy future for India. New Delhi: TERI
Thus, it is imperative that efforts are focussed Press.
towards focussing simultaneously on the demand
CHAPTER 3
Residential
Arindam Datta, Ilika Mohan, and Sumit Sharma

Introduction of the largest consumers of energy, especially the

traditional biomass-based energy in the developing
Energy use in the residential sector has drawn
and underdeveloped countries around the world
global concerns in the past decades for its effect on
(ABS 2012; EEA 2012; EIA 2014; Howley et al. 2008;
atmospheric pollution, human health, and climate
TERI 2014). Inefficient combustion process leads to
change due to the emission of particulate matter and
emissions of different air pollutants with varying
other pollutants (Koe et al. 2001). The sector is one
degree of effects on the air quality and health
(Bingemer et al. 1991). While ambient air pollution
is an issue, pollutant concentrations in the indoor
environment sometime go 100 times higher than
the outdoors (EPA 2013). In general, people spend
more than 70% of their daily time in the indoor
environment (elderly and children spend even more
time indoors) (Myers and Maynard 2005), and hence,
are exposed to the prevailing indoor air pollutant
levels. Many studies have linked inefficient cooking,
lighting, and heating activities in the residential
sector with ill health of the residents (Smith et al.
2000a). Countries around the world have developed
their ambient air quality standards based on the WHO
22  •  Air Pollutant Emissions Scenario for India
Air Quality Guidelines (WHO 2000); however, there m3 (Bruce et al. 2000), whereas the ambient PM2.5
are limited efforts to develop standards for indoor standard of USEPA for 24 hours mean concentration
air quality. is 35 mg/m3 (USEPA 2012). Patel and Aryan (1997)
Energy use in the residential sector can broadly have estimated the indoor levels of CO in an Indian
be classified as (i) energy used for the cooking, kitchen during cooking with dung cake, wood, coal,
(ii) energy used for the lighting, and (iii) energy kerosene, LPG, and reported their concentrations as
used for space heating. Variety of fuel (solid, liquid, 3.56, 2.01,0.55, 0.23, and 0.13 mg/m3, respectively. In
and gaseous) is used in the sector on a variety of a similar study, Gautam et al. (2013) have reported
cooking/lighting devices that usually have different the indoor concentrations of PM2.5 and PM10 with
combustion efficiencies. Solid fuels, generally used different types of cooking fuels (Figure 3.1).
in the residential sector include fuel wood, dung Carbonaceous fine fraction of PM is generally
cake, crop residue, and coal. Kerosene is generally partitioned into two major classes, organic carbon
used as liquid fuel and LPG, natural gas, biogas are (OC) and black carbon (BC). About 40–45% of
used as gaseous fuels in the sector. Among different global emission of BC is originated from the
biomass materials, fuel wood remained the main residential sector (Bond et al. 2004; Kulkarni et
solid biomass fuel since the historical time. Fuel al. 2015). Globally, residential sector accounts for
wood is derived from the forest residues (such about 42% of atmospheric non-methane volatile
as dead trees, branches, and tree stumps), yard organic compounds (NMVOC) (Li et al. 2014). Among
clippings, wood chips, and even municipal solid different countries of Asia, the contribution of the
waste. However, dry dung cake and crop residues residential sector to the total atmospheric NMVOC is
are also used in the residential sector as a source of significantly higher in India (Li et al. 2014). Incomplete
solid biomass energy for cooking. Fuel wood use in fuel combustion in the residential sector also emits
India was even higher than that of China and Brazil large amount of carbon monoxide (CO). Generally,
in 2013 (FAOSTAT 2014). TERI (2014) also reported while it caters to the basic necessity of cooking,
similar high figures for fuel wood consumption in lighting, and heating, the residential sector in India is
India. This is mainly because more than 60% of the one of the biggest sources of atmospheric pollutants
rural households rely on fuel wood followed by (Jayalakshmi 2015; Sharma et al. 2015).
crop-residues (12%) and cow dung cakes (11%) There are some studies carried out to estimate
(India Census 2011). Other than this, an estimated emissions from residential sector in India
500 million households rely on kerosene or other (Klimont et al. 2002; Pandey et al. 2014; Reddy and
liquid fuels for lighting around the world, which Venkataraman 2002a,b) and large uncertainties
amounts to ~7.6 billion litre consumption of liquid have been reported in estimation of residential
fuel annually (Mills 2005). In India, 31.4% households sector emissions on account of varying estimates
use kerosene for the lighting and nearly 3% of energy use and emission factors due to variety of
households (mainly in the urban areas) use kerosene fuel-wood usage. In this study, bottom-up estimates
for cooking (India census 2011). for energy consumption have been made for spatial
Combustion of the solid biomass fuels and distribution of national level estimates derived
kerosene is rather incomplete in the type of burning from TERI MARKAL Energy model. The emissions of
system (e.g., cook stove or wick lamp) that are different pollutants from residential sector in India
mainly used in the developing countries. This leads are estimated using indigenous emission factors
to emissions of pollutants in significant quantities. based on literature review. Projections have also
Various studies have reported the mean 24-hour been made for the future emissions from the sector.
concentration of particulate matter (PM) in the The uncertainties in this emission inventory have
indoor environment in the range of 300–3,000 mg/ also been evaluated.
 Residential • 23

Figure 3.1: Fuel-wise estimation of pollutant concentrations in a rural kitchen of Ballabhgarh, India A. PM2.5;
B. PM10
Source: Gautam et al. (2013)

Methodology particular fuel type (f). D is the number of district

in a particular state (S). There are 35 states/union
The national level estimates of energy consumption
territories in India at present.
in residential sector are presented in chapter 2. The
spatial distribution of energy use and emissions in
the residential sector is carried using a bottom-up
Estimation of Activity Data
approach. The basic equation employed for emission As discussed earlier, five different types of fuel (e.g.,
estimation from the residential sector is biomass, coal, kerosene, electricity, and LPG) are
mainly consumed in the residential sector in India.
n n
35
Ep = ∑
∑ ▒∑ Af ×EFp,f The consumption of different types of fuels in India
(S=1)(D=1)(f=1) 3.1 was estimated based on following equations:
where, Ep = Emission of a particular
pollutant (p) with a particular fuel type (f); Ac(f, Y) = P(Y) 3.2
Af = Activity data of the particular fuel type (f); EFp,f = Al(f, Y) = P(Y) × Cl(f,Y) 3.3
Emission factor of the particular pollutant (p) of the
24  •  Air Pollutant Emissions Scenario for India
Af = Ac(f,Y) + Al(f,Y) 3.4 pollutants emitted during burning of these fuels
in other south Asian countries, China, and other
where, Ac(f,y) and Al(f,y) are the activity data of developing countries were included. While kerosene
a particular type of fuel in a district (D) during a has been used as a fuel for both cooking and
particular year (Y) for cooking (c) and lighting (l) lighting in India, there are large differences in the
purposes, respectively. P is the total population emission of PM and BC from the two activities (Lam
distributed in urban or rural regions in a district et al. 2012a, b). Hence, separate estimates of PM and
(D) during the year (Y). Cc(f,y) and Cl(f,y) are the per BC emission from kerosene combustion in cooking
capita consumption of fuel for cooking and lighting and lighting have been made. Detail of the literature
purposes, respectively, for a particular fuel (f) in the review for emission factors of different pollutants
state (s) during the year (Y). We have calculated the from different fuels used in the residential sector
Ac(f,y) and Al(f,y) separately for the rural and urban area is given in Annexure 3.1. The variation of emission
of a district using the Equation 3.2 and 3.3. However, factors as reported in different studies is presented
the sum of Ac(f,y) and Al(f,y) was used to derive the Af of in Figure 3.2.
the particular district (D). Af was derived separately There are wide variations in the reported
for the rural and urban areas of every district to use emission factors of different pollutants. The full
the value in the Equation 3.1. range of collated emission factors along with
The dataset of district wise rural and urban a mean value (EFp,f) was used in the present
population in India was collected from the India study. Few studies earlier have also used the
census data of the year 2001 and 2011 (www. mean of the collated emission factors from
censusindia.gov.in). Per capita consumption of literature to estimate emission from burning of
different types of fuel for residential use in rural and biomass fuel in the residential sector (Saud et
urban areas of different states of India is collected al. 2012; Sen et al. 2014). A Monte Carlo analysis
from different sources (MoHA 2014; NARI 2013; was performed with the activity data (Af) and
NSSO 2007; 2010; 2012). This was used to estimate different emission factors (EFp,f) of a pollutant
energy consumption in the sector during 2001 and from a specific fuel collated from the literature
2011. The energy use estimates were compared with to estimate the range of emissions from the
other existing estimates. residential sector.

Emission Factors Future Projections

Future energy scenarios were developed
Emission factors of different pollutants (e.g., PM10,
considering the current plans and policies of the
PM2.5, OC, BC, SOx, NOx, NMVOC, and CO) emitted
government of India and are used to estimate the
during combustion of different types of fuel in the
emissions. These are based on the results of energy
residential sector were derived from an exhaustive
modelling exercise based on TERI-MARKAL model
literature review. Emissions of different pollutants
results (TERI 2015).
depend on the types of fuel used and the devices
used for domestic cooking and lighting in different
parts of India. A comprehensive literature review is Energy Use and Emissions from
carried out to collate the emission factors reported Residential Sector of India
in recent (after 2000) research studies focussed on This section presents the estimates of fuel
India. However, there is paucity of reported literature consumption and emission of air pollutants from
on emission factors from burning of coal, kerosene, the residential sector. The pollutant emissions
and LPG in the residential sector of India (Pandey from the residential sector are estimated for the
et al. 2014). Reported emission factors of different years 2001–2051 at an interval of 10 years. While,
 Residential • 25

Figure 3.2: Collated emission factors of different pollutants based on literature review
Kerosene (Cook): Kerosene used for cooking; Kerosene (Light): Kerosene used for lighting. The emission factors of the
Kerosene (Light) were not collated from literature for the pollutants in the left hand side and Kerosene indicates Kerosene
(Cook) for them.
‘×’ indicates values from literature survey and the bar indicates standard deviation of the mean.
the years 2001 and 2011 correspond to the actual Energy Used in Residential Sector
population and fuel use information, the future year The main factors influencing emissions from the
projections are based on energy projections using residential sector are population growth, availability
TERI-MARKAL model. of fuels in urban and rural regions, affordability
26  •  Air Pollutant Emissions Scenario for India
and their consumption patterns (Elias and Victor (Saud et al. 2011a, b). The per capita consumption of
2005). Average decadal population growth in India fuel wood in the rural area was higher in the north-
after independence is 35.1% and 18.7% in urban eastern states (e.g., Nagaland, Arunachal Pradesh,
and rural areas, respectively (Figure 3.3). However, Mizoram, and Tripura) ranging from 681 to 774 kg/
there is a decline in the population growth rate in year during 2011. While per capita consumption of
both urban and rural areas during 2001 to 2011 crop residue and dung cake was significantly higher
(India census 2001; 2011). There is a high rate of in the states of Bihar (244.9 kg/year) and Uttar
migration from rural areas to urban cities (Masanad Pradesh (193.8 kg/year), respectively (NSSO 2012).
2008). In India, 13.7% people in the urban areas
live below the poverty line (INR 1,000/month), Kerosene
whereas about 25.7% population in the rural area Since the mid-19th century, kerosene (synonyms:
is below poverty line (INR 816/month) (RBI 2012). paraffin, paraffin oil, fuel oil no. 1, lamp oil) has
According to the 68th round of the Household become a major commercial household fuel with
Consumer Expenditure Survey (NSSO 2012), rural the belief that it is a much cleaner fuel than the
India’s average monthly per capita expenditure conventional solid biomass and fossil fuels (Mills
(MPCE) rose to INR 1,278.94 in 2012, while that of 2005). In India, 31.4% households use kerosene for
urban India stood at INR 2,399.24. However, the lighting and nearly 3% households (mainly in the
rural-urban division is much smaller (35.2%) when urban areas) use kerosene for cooking (India census
the MPCE on energy consumption is considered 2011). Total consumption of kerosene in India
(NSSO 2012). The rural population primarily has decreased by ~68% during last two decades;
use conventional fuels for cooking and lighting whereas, the consumption has decreased by 36.3%
energy due to lack of access to cleaner fuels. Fuel- in the rural areas compared to ~84% decrease in
wise energy use pattern in India is discussed in the urban areas (Figure 3.4). Compared to the urban
following sections. areas, the monthly per capita kerosene consumption
in the rural area has increased nearly four times
Solid biomass fuel during the last two decades (Figure 3.4). During
There is significant variation in the type of solid the first half of the 20th century, the prevalence
biomass fuel used in different parts of the country of kerosene for lighting has greatly reduced, as
based on their availability and cultural practices electrification and availability of gaseous fuels

Figure 3.3: Decadal growth of rural and urban population of India

Source: India census (2011); TERI (2015a)
 Residential • 27

Figure 3.4: Annual changes in the monthly per capita consumption of kerosene in the rural and urban areas
of India. Compiled from NSSO dataset

spread, particularly in developed countries. Towards the period. However, with respect to other fuels,
the beginning of 20th century, liquid petroleum gas the consumption of coal in the residential sector
(LPG) was introduced for cooking, the consumption is small.
of kerosene in the urban areas gradually declined. About 74% households in the rural area and
96% households in urban areas use electricity for
Gaseous and other fuels the lighting purpose (NSSO 2012). There was a rise
LPG is considered as a relatively cleaner and efficient of 36% in the electricity consuming household
cooking option presently available in India (D’Sa and in the rural areas during the period 2004–05 and
Murthy 2004). There is a steady growth of 8% p.a. in 2011–12, (compared to a rise of 6% in urban areas).
LPG consumption during the last decade in India. Electricity at the users end is generally regarded
At present, 28.5% (rural: 11.4% and urban: 65.0%) as the ‘cleanest fuel’ (Brander et al. 2011); however,
of total households in India use LPG for cooking consumption of electricity in the hotplates/burners
purpose (India census 2011). Rural areas showed an for the cooking purpose may produce NOx (EPA
increase of 83% in the proportion of LPG-consuming 2007). In India, such uses of electricity for cooking
households and an increase of 75% in the purpose in the residential sector is minimal (<1%),
consumption of LPG per person during 2004–05 and so the emissions due to the consumption of
2011–12. Urban areas has shown a rise of 20% both electricity were not considered in the present study.
in the proportion of LPG-consuming households Similarly, solar power and wind power was not
and in the quantity of LPG consumption per person considered in the estimation of pollutant emission
during the period (NSSO 2012). from the residential sector. Burning of biogas
Apart from these, about 1.4% households in India although releases some pollutants; its consumption
use coal as a fuel for cooking purpose (India census in India is also negligible.
2011). The use of coal (including coke and charcoal)
in the residential sector has increased in both rural Fuel Consumption in Residential
and urban areas during 2001 to 2011. Increased Sector using bottom-up approach
use of coal in Jharkhand, Odisha, and Bengal may Figure 3.5 shows the use of different kinds of
be attributed to the availability in these states. The fuel in the residential sector in different states of
rate of increase in the coal consumption in urban India during 2001 and 2011. The consumption of
areas of Bengal was significantly higher during different fuels in the residential sector has increased
28  •  Air Pollutant Emissions Scenario for India
significantly during 2001 to 2011. Especially, the Total consumption of fuel wood in the residential
consumption of fuel wood in the rural areas has sector was earlier reported as 307 Mt during 2011
increased by 12.5%. The consumption of dung (FAOSTAT 2014). On the other side, Woodbridge et
cake has significantly increased in Bihar and Uttar al. (2011) have reported the annual consumption of
Pradesh (more than five times) followed by Madhya fuel wood in the residential sector of India as 206 Mt
Pradesh, West Bengal, and Punjab during 2001–11. based on the NSSO (2007). However, Ravindranath
Consumption of crop residue in the rural areas and Hall (1995) have reported 218 Mt of fuel wood
has also significantly increased in the states like consumption in the residential sector of India
Bihar, Assam, Uttar Pradesh, Maharashtra, Madhya during 1990. They have also reported that the total
Pradesh, and Bengal (Figure 3.5). The use of coal in crop residue consumption in the residential sector
the residential sector has increased in the states of as 96 Mt during 1990.
Jharkhand, Odisha, and West Bengal. This may be
attributed to local availability of coal. Emission Inventory for Residential
The present estimation suggests that the Sector
total consumption of biomass (fuel wood, crop
The district-wise annual activity data (Af) of different
residue, and dung cake) in the domestic sector
types of fuel derived through the Equation 3.4 was
during 2011 was 436 Mt (Figure 3.5) (TERI 2015).
fed into Equation 3.1 along with the respective

Figure 3.5: Consumption of different fuels in the residential sector in the rural and urban areas of different
states and in the country during 2001 and 2011 as estimated using the bottom-up approach (following
Equation 3.4).
FW: fuel wood; CR: crop residue; CDC: dung cake; LPG: liquid petroleum gas. ANDA: Andaman & Nicobar Islands; ANPR: Andhra
Pradesh; ARPR: Arunachal Pradesh; ASSA: Assam; BIHR: Bihar; CHAN: Chandigarh; CHHA: Chhattisgarh; DANA: Dadra & Nagar
Haveli; DADU: Daman & Diu; DELH: Delhi; GOA: Goa; GUJA: Gujarat; HARY: Haryana; HIMA: Himachal Pradesh; JAKA: Jammu &
Kashmir; JHAR: Jharkhand; KARN: Karnataka; KERA: Kerala; LAKH: Lakshadweep; MADH: Madhya Pradesh; MAHA: Maharashtra;
MANI: Manipur; MEGH: Meghalaya; MIZO: Mizoram; NAGA: Nagaland; ODIS: Odisha; PUDU: Puducherry; PUNJ: Punjab; RAJA:
Rajasthan; SIKI: Sikkim; TAMI: Tamil Nadu; UTPR: Uttar Pradesh; UTKR: Uttarakhand; BENG: West Bengal.
 Residential • 29
pollutant emission factor to estimate emissions of NOx (37.3%) and CO (38.9%) from the rural areas
different pollutants from the residential sector in compared to that in the urban areas (Figure 3.7).
rural and urban areas. Total emission of different Table 3.1 summarizes the total emission of different
pollutants from residential sector of the rural area pollutants due to combustion of various fuels in the
was more than 10 times higher than that in the residential sector of India during 2011.
urban areas during 2001 and 2011 (Figures 3.6 and The baseline estimates of PM2.5, BC, CO, and
3.7). Emissions of different atmospheric pollutants NMVOC are comparable to those reported by
increased significantly by 2011 as compared Pandey et al. (2014) for the year 2010. They have
to 2001, which can be attributed to increased reported the PM2.5, BC, CO, and NMVOC as 2,656 Kt,
consumption of different fuels in 2011. Emissions of 488 Kt, 30,594 Kt, and 5,100 Kt, respectively. On the
the particulates (e.g., PM10, PM2.5, BC, and OC) were other hand, the estimation of OC, SOx, and NOx were
significantly higher from fuel wood combustion. higher in the present study compared to that of the
Gaseous emissions, such as SO2, from the rural area Pandey et al. (2014). However, Sharma et al. (2015),
were significantly higher with the consumption of Pandey et al (2014) have reported that the NMVOC
kerosene. This is attributed to significant increase emission from the residential sector of India as 5,863
in the consumption of kerosene during 2011 in the Kt and 5100Kt, respectively, during 2010, which are
rural area. On the other side, the NOx emissions were comparatively lesser present estimation (6,637 Kt).
significantly higher from LPG/PNG stoves in the This may be attributed to different emission factors
urban area compared to others (Figure 3.7). of NMVOCs reported in recent studies.
During both years total PM10 and PM2.5 emissions The emissions are spatially distributed using GIS
from the rural areas of different states followed at a resolution of 36×36 km2. The spatial distribution
the order; Uttar Pradesh > Bihar > Karnataka > of different pollutant emissions in the residential
Rajasthan. Saud et al. (2011a, b) have also reported sector of India is presented in Figure 3.8. Among the
significantly higher particulate matter emission 640 districts (India census 2011) of India, higher PM10
from the rural areas of the state of Uttar Pradesh emission (19.41 kt) was estimated from the rural
followed by Bihar; however, they had considered area of 24 paraganas (S), West Bengal during 2011
only the solid biomass fuel in their estimation. This (Figure 3.8).
study also indicates that nearly 95% of total PM10
and PM2.5 emission from the residential sectors Future Projections
due to consumption of solid biomass fuel in rural Future energy consumption estimates from the
areas (Figure 3.6). PM10 and PM2.5 emissions from residential sector are adopted from TERI-MARKAL
residential sector in rural area have increased by model results (vide Chapter 2) to estimate emissions
more than 40% during the period of 2001–2011. This in the future. The residential energy consumption
may be attributed to increase in the consumption data as projected by the TERI-MARKAL indicates
of solid biomass fuel in the rural area. Significant (Figure 3.9) a decrease of traditional biomass energy
increase in OC emission (more than 50%) in rural use in the residential sector after 2021. This is due
areas during the period also points to the increased to enhanced penetration of the fossil fuel in the
consumption of solid biomass fuel. Among the residential sector.
gaseous pollutants, SO2 emission has nearly doubled The same set of emission factors for each pollutant
in the rural areas (Figure 3.7) due to substantial (Figure 3.4) was used to estimate the future emission
increase in the consumption of kerosene during of different pollutants using Equation 3.1. Figures 3.10
2001–2011. Similarly, increased consumption and 3.11 show that the total emission of all pollutants
of kerosene in the rural area also attributed to from the residential sector will decrease after 2021,
significantly higher increase in the emission of as the use of traditional biomass fuel (e.g., fuel wood,
30  •  Air Pollutant Emissions Scenario for India

Figure 3.6: Total emission of PM and its constituents from the rural and urban areas of India during 2001
and 2011using the bottom-up approach
Note: The x-axis scale of the urban area is 10 times lower than that of the rural area.

dung cake, crop residue) decreases. The PM10 and pattern (Figure 3.10). However, NOx emissions due
PM2.5 emissions from residential sector are projected to panetration of LPG in the rural areas is expected
to decrease by 14% over the period 2001–51. The to increase more than 10 times during the 50 years
projected emissions of BC and OC also follow the same period. Significant decrease in the consumption of
 Residential • 31

Figure 3.7: Total emission of NOx, SOx, NMVOC, and CO from the domestic sector in the rural and urban areas
of India during 2001 and 2011 using the bottom-up approach
Note: The x-axis scale of the urban area is 10 times lower than that of the rural area.
32  •  Air Pollutant Emissions Scenario for India

Table 3.1: Emission inventory (Kt/yr) of different pollutants from the residential sector of India during 2011 using TERI-MARKAL energy
consumption estimates
PM10 PM2.5 OC BC NOX SOx NMVOC CO
Fuel wood 1,671 1,152 820 161 424 198 4,671 16,801

Crop Residue 928 1,141 545 86 287 93 1,544 12,511

Dung cake 259 110 121 8 25 18 358 1,579
Kerosene (Light) 252 252 0 266 0 21 0 81
Kerosene (Cook) 5 4 2 1 2 1 0 64
LPG 1 1 0 0 29 0 64 348
TOTAL 3,115 2,660 1488 521 766 330 6,637 31,385

Figure 3.8: Estimated spatial distribution of emission of different pollutants (Kt/yr) from the residential
sector of India during 2011
 Residential • 33
kerosene will lead to 27% decrease in the SO2 emission is significantly higher with OC among the different
from the sector (Figure 3.11). pollutants (Figure 3.12); whereas, the estimation
uncertainty is lower with CO (0.5), NMVOC (0.6), and
Uncertainty of Estimation PM2.5 (0.6).
As mentioned earlier, the mean of collated emission
factors was used to estimate the emission of Conclusion
pollutants from the residential sector using Equation Residential sector in India is one of the largest
3.1. When EFp,f of the equation is constant then Ep is consumers of energy (see Chapter 2). Large amounts
directly proportional to the activity data (Af). This of pollutants are released in the atmosphere due to
indicates that the estimation uncertainty of emission inefficient consumption of fuels in the residential
of pollutants from the residential sector is directly sector. These pollutants lead to adverse effects on
related to the uncertainty in the fuel consumption human health. In this study, a bottom-up approach
data. was used to estimate the fuel consumption in
The uncertainties in fuel consumption in the the residential sector. Emission factor of different
residential sector for a given fuel used for cooking pollutants were derived by collating emission factor
consisted of uncertainties in food consumption, data from the published literature. District-wise and
specific cooking energy, the fraction of households thereafter grid-wise (36 × 36 km²) emission estimates
using that fuel type, stove efficiency, and calorific are prepared for different pollutants from the
value of the fuel. However, the use of bottom-up residential sector. The analysis shows that currently
approach to estimate the fuel consumption in the the emissions are very high from the residential
residential sector, has reduces the uncertainty in sector mainly due to dependence on solid fuels. The
the estimation of fuel consumption in the present analysis clearly highlights the need for strategies
study.Apart from this, there lies uncertainty related to reduce emissions form the sector. Some of the
to emission factor itself. In this analysis, an attempt strategies that can be employed for reduction of
has been made to estimate uncertainties in the emissions from residential sector are :
emission factors. The upper bound and lower bound PP Enhanced and faster penetration of cleaner fuels
along with the mean value of the collated published such as LPG.
emission factors have been used to estimate the PP Increased penetration of improved biomass
estimation uncertainty of different pollutants. based challahs with higher efficiencies and lower
Emission factor-related uncertainty estimation in the emissions.
emission budget of pollutants from the residential PP R&D efforts to develop clean technologies.
sector indicates that the uncertainty in the estimation

Figure 3.9: Future projections of energy consumption in the residential sector

Source: TERI-MARKAL model output.
34  •  Air Pollutant Emissions Scenario for India

Figure 3.10: Future projection of different PM constituents from the domestic sector

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42  •  Air Pollutant Emissions Scenario for India

Annexure: 3.1 consumed, expressed in units of gram per kilogram

(Andrae and Merlet 2001). People from different
countries have worked on the development of
Review of Emission Factors of Different emission factor of different gaseous and particulate
Pollutants from the Combustion in pollutants from the burning of the solid biomass
Residential Sector in India (Andrae and Merlet 2001; Lemieux et al. 2004; Reid et
al. 2005; Smith et al. 2000a; Venkatraman et al. 2006)
In the rural areas of developing countries, solid fuels
in the residential sector. However, very limited studies
are mainly burnt in traditional residential stoves
have been conducted in India (Saud et al. 2011a). The
(chulhas) or cookers with low combustion efficiency.
concentration of PM10 ranges from 500 to 2000 mg/m3
In the developing countries, burning of solid biomass
inside the kitchen during cooking with solid biomass
fuel could lead to significant quantities of emissions
fuel in typical Indian households (Balakrishnan et
at regional and global levels. It is important to develop
al. 2002). The emission factors vary significantly with
emission factors (EF) of different pollutants from
type of fire wood and crop residue (Akagi et al. 2011;
burning of fuels in the residential sector to develop
Saud et al. 2013). Saud et al. (2013) have also reported
a reliable inventory of pollutants emitted due to the
significant spatial variation in the emission from dung
energy consumption in the residential sector. The
cake and same type of fire wood. They have reported
EF is the amount of pollutant released per unit fuel

Table A3.1 : Collated Emission factors of PM10 (g/kg)

Country Fuel wood Crop residue Dung cake Kerosene Source
India 1.74 2.16 5.36 Sen et al. (2014)
India 1.36 1.82 1.6 Sen et al. (2014)
India 1.81 3.09 8.00 Sen et al. (2014)
India 2.05 1.85 5.26 Sen et al. (2014)
India 1.69 2.85 5.37 Sen et al. (2014)
India 4.34 7.54 3.87 Saud et al. (2011b)
India 3.78 12.09 19.98 Saud et al. (2011a)
India 5.99 8.83 16.17 Saud et al. (2011a)
India 4.11 3.09 15.17 Saud et al. (2011a)
India 4.85 10.47 16.14 Saud et al. (2011a)
India 4.66 3.29 Saud et al. (2011a)
India 8.5 5.1 12.6 Parashar et al. (2005)
India 8.6 Garg et al. (2001)
India 6.64 Akagi et al. 2011)
India 11.1 Roden and Bond (2006)
India 16.7 Roden and Bond (2006)
India 8.5 Roden and Bond (2006)
India 6.5 Roden and Bond (2006)
India 5.28 Arora et al. (2013)
India 12.13 Arora et al. (2013)
India 2.05 Arora et al. (2013)
 Residential • 43

Table A3.1 : Collated Emission factors of PM10 (g/kg)

Country Fuel wood Crop residue Dung cake Kerosene Source
India 16.14 Arora et al. (2013)
India 2.89 Arora et al. (2013)
India 12.4 Arora et al. (2013)
India 2.89 Arora et al. (2013)
India 2.77 Arora et al. (2013)
India 10.0 Arora et al. (2014a)
World 0.5 UNDP (2003)
World 9.04 Lam et al. (2012)
World 5.2 Apple et al.(2010)
India 1.0 Smith et al. (2000a–c)
India 2.2 Pandit et al. (2001)
World 1.74 Traynor et al. (1990)
Guatemala 5.7 Schare and Smith (1995)

significant higher emission of PM (15.64 g/kg), organic benzo(a) pyrene benzene, etc., which are hazardous
carbon (4.32 g/kg) and elemental carbon (0.51 g/kg) to human health (Smith et al. 2000a–c). Significantly
from burning of dung cake compared to other two solid higher emission of SO2 (0.74 g/kg) from burning of
biomass fuels used in the residential sector. They have dung cake and higher emission of NOx from burning
also reported significantly higher and lower emission of crop residue (1.41 g/kg) were reported in the
of PM from burning of dung cake in Delhi and West Western India (Sen et al. 2014). Fossil fuel such as Coal
Bengal, respectively. Six different types of crop residues (mainly lignite) is used for cooking purpose in few
and fire woods that are prevalently used for residential households in the rural and urban areas of India, based
cooking in the Indo-Gangetic plain (IGP) of India are on its local availability. CO is emitted from burning of
associated with significantly different emission factors coal in residential cook stoves. Large amount of PM
for different pollutants (Saud et al. 2013). Sen et al. and polyaromatic hydrocarbon are released during
(2014) have also reported significantly higher PM and burning of kerosene for cooking and lighting purposes.
BC due to burning of dung cake in residential sector in LPG is one of the popular residential fuels used for the
western India. The collated emission factors of PM10, cooking purpose in the urban areas of India. LPG is
PM2.5, BC and OC are summarized in Table A3.1 to A3.4. also regarded as a clean fuel, but certain pollutants are
In addition to PM, burning of different types of fuel for released during the combustion of LPG also (USEPA
household purpose generates high level of gaseous 2008). The collated emission factors of NOx, SOx, CO
pollutants such as carbon monoxide (CO), oxides and Non-Methane Volatile Organic Carbon (NMVOC)
of nitrogen (NOx) and sulphur (SO2), formaldehyde, are summarized in Table A3.5 to A3.8.
44  •  Air Pollutant Emissions Scenario for India

Table A3.2 : Collated Emission factors of PM2.5 (g/kg)

Fuel Crop Dung Kerosene Kerosene
Country Source
wood residue cake (Cooking) (Lighting)
World 9.1 6.3 6.6 Akagi et al. (2011)
World 1.6 Bond et al. (2004)
China 2.2 4.4 Li et al. (2009)
China 3.1 8.2 Shen et al. (2010)
South Asia 3.8 9.9 5.4 Stone et al. (2010)
South Asia 2.0 10.9 Stone et al. (2010)
Sweden 10.0 Hedberg et al. (2002)

USA 2.6 Larson and Koenig (1993)

India 7.5 Rajput et al. (2014)
India 3.9 5.0 Reddy and Venkataraman (2002a)
India 2.1 Mukherji et al. (2002)
India 2.1 Mukherji et al. (2002)
India 1.9 Swin et al. (2002)
India 6.1 Saud et al. (2011a, b)
India 6.3 Saud et al. (2011a, b)
China 2.4 Zheng et al. (2010)
India 3.3 Reddy and Venkataraman (2002b)
World 0.3 Veranth et al. (2000)
Chile 1.6 Ruiz et al. (2010)
Chile 2.5 Ruiz et al. (2010)
Guatemala 8.0 Schare and Smith (1995)
World 86.0 Lam et al. (2012)
World 98.0 Lam et al. (2012)
World 92.0 Lam et al. (2012)
World 90.0 Lam et al. (2012)

Table A3.3 : Collated Emission factors of OC (g/kg)

Country Fuel wood Crop residue Dung Kerosene LPG Source
cake
India 1.0 1.5 3.9 Saud et al. (2012)
India 1.2 2.2 5.2 Saud et al. (2012)
India 1.1 1.2 4.3 Saud et al. (2013)
India 0.7 0.6 4.5 Saud et al. (2013)
India 1.4 1.4 4.5 Saud et al. (2013)
India 1.2 1.7 3.8 Saud et al. (2013)
India 0.9 1.0 3.7 Saud et al. (2013)
 Residential • 45

Table A3.3 : Collated Emission factors of OC (g/kg)

Country Fuel wood Crop residue Dung Kerosene LPG Source
cake
India 0.4 0.4 0.7 Sen et al. (2014)
India 0.5 0.8 1.5 Sen et al. (2014)
India 2.1 1.9 5.1 Sen et al. (2014)
India 4.4 3.9 12.6 Parashar et al. (2005)
India 7.4 8.5 Parashar et al. (2005)
India 7.8 0.3 Venkatraman et al. (2005)
India 1.7 1.2 Venkatraman et al. (2005)
India 3.5 Venkatraman et al. (2005)
China 0.7 Lu et al. (2011)
India 0.3 Lu et al. (2011)
India 1.0 Lu et al. (2011)
Uganda 2.0 Lam et al. (2012b)
Uganda 3.0 Lam et al. (2012b)

Table A3.4 : Collated Emission factors of BC (g/kg)

Fuel Crop Dung Kerosene Kerosene
Country Source
wood residue cake (Cooking) (Lighting)
India 0.4 0.6 0.9 Saud et al. (2012)
India 0.4 0.3 0.5 Saud et al. (2012)
India 0.4 0.4 0.6 Saud et al. (2012)
India 0.3 0.4 0.4 Saud et al. (2012)
India 0.3 0.4 0.2 Saud et al. (2012)
India 0.4 0.2 0.5 Saud et al. (2012)
India 0.4 0.4 0.3 Saud et al. (2012)
India 0.1 0.1 0.2 Sen et al. (2014)
India 0.4 0.2 0.1 Sen et al. (2014)
India 0.3 0.3 0.1 Sen et al. (2014)
India 0.3 0.2 0.1 Sen et al. (2014)
India 1.1 0.1 Parashar et al. (2005)
India 0.4 0.1 Venkatraman et al. (2005)
India 0.6 0.2 Venkatraman et al. (2005)
India 1.0 0.3 Venkatraman et al. (2005)
China 0.9 2.4 Shen et al. (2012)
China 0.8 Guofeng et al. (2012)
China 1.2 Guofeng et al. (2012)
China 2.2 0.4 Li et al. (2009)
46  •  Air Pollutant Emissions Scenario for India

Table A3.4 : Collated Emission factors of BC (g/kg)

Fuel Crop Dung Kerosene Kerosene
Country Source
wood residue cake (Cooking) (Lighting)
World 0.83 0.8 0.53 Akagi et al. (2011)
World 1.0 Bond et al. (2004)
India 0.2 Habib et al. (2008)
India 0.3 Habib et al. (2008)
India 0.2 Lu et al. (2011)
India 0.7 Lu et al. (2011)
India 0.6 Lu et al. (2011)
India 0.9 Lu et al. (2011)
South Asia 90.0 Lam et al. (2012b)
South Asia 128.0 Lam et al. (2012b)
South Asia 75.0 Lam et al. (2012b)
South Asia 100.0 Lam et al. (2012b)
Uganda 90.0 Lam et al. (2012a)

Table A3.5: Collated Emission factors of NOx (g/kg)

Fuel
Country Crop residue Dung cake Kerosene LPG Source
wood
India 2.0 1.9 1.6 Sen et al. (2014)
India 4.4 1.5 Sen et al. (2014)
India 0.6 0.5 0.6 Sen et al. (2014)
India 0.9 1.2 0.9 Sen et al. (2014)
India 4.6 4.0 3.3 Sen et al. (2014)
India 0.8 1.1 0.6 Saud et al. (2011a, b)
India 1.6 2.6 1.2 Saud et al. (2011a, b)
India 1.0 1.0 0.8 Saud et al. (2011a, b)
India 0.3 1.3 0.3 Saud et al. (2011a, b)
India 0.6 0.8 0.2 Saud et al. (2011a, b)
India 2.0 0.9 Garg et al. (2001)
India 2.2 1.6 0.8 Gadi et al. (2003)
India 0.8 Smith (1988)
India 0.8 Kumari et al. (2011)
India 1.6 Venkataraman et al. (1999)
World 0.7 Spiro et al. (1992)
World 3.1 0.5 Akagi et al. (2011)
World 2.5 Andrae and Marlet (2001)
India 1.3 Apte et al. (1989)
 Residential • 47

Table A3.5: Collated Emission factors of NOx (g/kg)

Fuel
Country Crop residue Dung cake Kerosene LPG Source
wood
World 0.6 Lam et al. (2012)
World 1.3 Lam et al. (2012)
World 1.4 Girman et al. (1982)
India 2.5 Shankar and Mohanan (2011)
India 2.0 Bisen and Suple (2013)
World 3.6 USEPA (2011)

Table A3.6: Collated Emission factors of SO2 (g/kg)

Country Fuel Crop Dung Kerosene Kerosene Source
wood residue cake (Cooking) (Lighting)
India 0.3 0.3 0.3 Saud et al. (2011a, b)
India 0.4 0.3 0.3 Saud et al. (2011a, b)
India 0.2 0.4 0.4 Saud et al. (2012)
India 0.5 0.2 0.2 Saud et al. (2013)
India 0.7 0.9 0.8 Sen et al. (2014)
India 0.4 0.5 0.3 Sen et al. (2014)
India 0.8 1.3 0.9 Sen et al. (2014)
India 0.9 0.9 1.1 Sen et al. (2014)
India 1.3 0.5 1.4 Gadi et al. (2003)
India 0.8 0.6 0.6 Garg et al. (2001)
India 0.8 Reddy and Venkataraman 2002a
India 0.5 Reddy and Venkataraman
(2002)
India 2.3 1.6 Venkataraman et al. (1999)
World 0.6 Akagi et al. (2011)
World 0.6 Bond et al. (2004)
India 7.4 Kandpal et al. (1995)
India 6.5 Kandpal et al. (1995)
India 4.8 Kandpal et al. (1995)
India 12.1 Raiyani et al. (1993)
China 0.1 Zhang et al. (2000)
China 0.1 Zhang et al. (2000)
World 0.7 Leaderer (1982)
World 0.6 Leaderer et al. (1999)
World 0.4 Leaderer et al. (1999)
48  •  Air Pollutant Emissions Scenario for India

Table A3.7: Collated Emission factors of CO (g/kg)

Fuel Crop Kerosene Kerosene
Country Dung cake LPG Source
wood residue (Cooking) (Lighting)
India 28.0 Arora et al. (2014b)
India 36.0 Arora et al. (2014b)
India 65.2 Arora et al. (2014b)
India 80.0 68.0 60.0 20.0 Smith et al. (2000b)
China 54.0 56.0 61.0 Zhang et al. (2000)
China 89.0 66.0 30.0 Zhang et al. (1999)
China 47.8 Wei et al. (2012)
China 63.0 101.0 Zhang et al. (1999)
World 93.0 102.0 105.0 Akagi et al. (2011)
India 11.0 Apte et al. (1989)
China 18.0 Zhang et al. (1999)
China 60.0 Zhang et al. (1999)
World 28.0 Hobson and Thistlethwaite (2003)
India 30.0 Shankar and Mohanan (2011)
India 40.0 Bisen and Suple (2013)
World 50.0 USEPA (2008)
India 28.0 Smith et al. (2000 a–c)
India 56.0 Smith et al. (2000 a–c)
India 45.0 Smith et al. (2000a–c)

Table A3.8 : Collated Emission factors of NMVOC (g/kg)

Crop
Country Fuel wood Dung cake Kerosene LPG Source
residue
India 15.89 13.26 10.37 0.08 0.14 Sharma et al. (2014)
India 6.9 8.5 24.1 17.0 19 Pandey et al. (2014)
China 3.13 7.3 6.51 Wei et al. (2008)
World 8 9 0.2 0.2 IPCC (2006)
World 19.32 9.73 Andrae and Marlet (2001)
World 57.7 Akagi et al. (2011)
CHAPTER 4
Industries
Richa Mahtta, C Sita Lakshmi, Sumit Sharma, Atul Kumar, and Saptarishi Das

Introduction slowly opened up its markets through economic

liberalization. The perecentage contribution of
Indian economy has grown manifolds since
different sectors to national GDP during 1981–
independence in 1947. The agriculture sector
2013 is presented in Figure 4.1 which shows that
dominated the GDP of India till 1980s, when India

Figure 4.1: Growth rates of different sector contributing to Indian economy in different timeframes.
Source : RBI (2014–15)
50  •  Air Pollutant Emissions Scenario for India
industry and services sectors have broadend Emissions from industries are function of quality of
their shares in last two decades. Over all a healthy fuel, combustion efficiency, and tail-pipe controls.
growth rate of about 7.5% is achieved in post High sulphur fuels result in oxides of sulphur, while
2000 era, which is sufficient to double the average high ash content in fuels leads to particulate matter
income in a decade. There are certain states such (PM) emissions. Inefficient combustion also leads to
as Tamil Nadu (9.9%), Gujarat (9.6%), Haryana (9.1%), PM, while high temperature combustion forms NOx
or Delhi (8.9%) that have shown highest growth in the industrial stacks. In Indian scenario, tail-pipe
rates during 1999–2008, while there are states controls and their efficiencies play a very important
that have lagged behind. Now, India is the  10th role in defining the emission, as the fuels combusted
biggest economy in the world and the third are of high ash content. Other than due to combustion
largest by purchasing power parity adjusted at of fuels, emissions also take place in manufacturing
market exchange rates (World Bank 2015). Over the processes of some products such as cement, lime, etc.
years, the share of primary sector has gone down Other than large industrial units, there are 36
and industrial manufacturing sector has shown million micro, small, and medium enterprises. Their
tremendous growth. While on one hand, it has contribution to GDP is about 8% besides 45% to
led to improved per capita incomes and quality the total manufacturing output and 40% to the
of life, it has also contributed to deterioration of exports from the country (MMSME 2015). Although
air quality. Inefficient combustion of fuels (with big industries are somewhat capable of controlling
high ash content), limited tail-pipe controls, and emissions through installations of air pollutant
fugitive process emissions have led to release control devices, pollution from small scale industries
of huge quantities of air emissions, which lead is an issue. Financial and technical capacities are
to deterioration of air quality. A Comprehensive major constraints for control of pollution in small
Environmental Pollution Index was formulated in scale industries.
2009 that showed that 43 industrial areas/clusters
out of the 88 investigated were critically polluted, Energy Consumption in Industries
with respect to one or more environmental Based on the actual energy consumed in various
component (CPCB 2009). Air quality was one of the industries such as paper and pulp, iron & steel
important criteria that were evaluated. production, chemical production, non-metallic
minerals and non-ferrous minerals, and other
Industrial Pollution industries, TERI-MARKAL model is used to derive
Air pollution in industries in India is an important issue future projections of energy use in the industrial
that if not addressed can lead to severe deterioration sector. Estimated fuel-wise energy consumed in the
of air quality. Seventeen categories of highly polluting sector is shown in Figure 4.2, which clearly shows
industries have been identified in India. CPCB had around 51% of energy demand in industries is met
carried out an inventorization of the post-91 large and by coal, followed by petroleum products (16%), and
medium scale industries under these 17 categories. electricity (13%).
It was considered mandatory for these units to have The sub-sector–wise distribution of energy
been allowed only if they had the requisite pollution consumed in Industries is shown in Figure 4.3. Other
control facilities The state-wise status of 17 categories than cement, iron & steel, brick, aluminium, glass,
of highly polluting industries in India (as on May 19, paper, and fertilizer industry, significant energy
2014) is presented in Table 4.1. consumption takes place in other small and medium
Manufacturing of products require energy, which scale industries. In 2011, iron and steel sector has
is produced in the industries through combustion the maximum share of 26%, followed by the brick,
of fuels such as coal, fuel oil, biomass, and diesel. fertilizers, and cement industries.
 Industries • 51

Table 4.1: State-Wise Status of 17 Categories of Highly Polluting Industrial Units in India (as on May 19, 2014)
Sl No State Complying Non-Complying Closed Total
1 Andhra Pradesh 359 74 39 472
2 Arunachal Pradesh 2 0 0 2
3 Assam 36 12 1 49
4 Bihar 16 4 0 20
5 Chattisgarh 71 6 1 78
6 Chandigarh 0 0 0 0
7 Daman & Diu 1 1 1 3
8 Delhi 2 0 0 2
9 Goa 13 2 0 15
10 Gujarat 302 7 8 317
11 Haryana 119 6 16 141
12 H.P. 14 0 3 17
13 Jharkhand 103 48 22 173
14 Jammu & Kashmir 7 0 3 10
15 Karnataka 175 30 26 231
16 Kerala 21 11 19 51
17 Lakshadeep 0 0 0 0
18 Madhya Pradesh 65 16 2 83
19 Maharashtra 317 145 58 520
20 Meghalaya 4 12 1 17
21 Mizoram 1 0 0 1
22 Nagaland 0 0 0 0
23 Orissa 37 17 11 65
24 Puducherry 5 2 0 7
25 Punjab 57 12 18 87
26 Rajasthan 69 31 18 118
27 Sikkim 3 1 0 4
Total 1799 437 247 2483
Source: CPCB (2014)

Other than combustion of fuels, they are also used Table 4.2: Fuel Used in Non-Energy Sector during Year 2009–10
in non-combustion activities. There are certain fuels
  Natural gas Million m³ Naphtha (000 tonnes)
that are used in industry as feedstock and other non- (MCM)
energy uses. Naphtha (part of GSL) and natural gas Fertilizer 13168 13168
are used as feedstock in fertilizers and petrochemical Petrochemical 1264 1264
industries. This non-combustion fuel usage also leads Source: MoPNG (2010)
to emissions. Data pertains to these uses is presented
in the Table 4.2. during different industrial processes. The calculations
are based on the following Equation 4.1.
Emission Inventorization of Industries
Emissions = Activity level × Abated emission
Energy estimates made in the previous section are
factor × Percentage of capacity controlled .................4.1
used to estimate emissions of various pollutants
52  •  Air Pollutant Emissions Scenario for India

Figure 4.2 Estimated energy consumption in industry sector (PJ) during 2001-2051
Source: TERI (2015), TERI-MARKAL model results

Figure 4.3: Past and projected energy consumption in the industrial sector (2001-2051)

where fertilizers, paper, brick, aluminium, and glass industries

Abated emission factor = Unabated emission factor and rest of the industries are clubbed in ‘others’
× (1 – Percentage removal efficiency of the control categories.
system).
Cement Industry
Other than fuel combustion, there are a number With growing economy, the demands for
of industries for which emissions are estimated construction material has grown multi-folds. The
based on the processes followed rather than the cement production in India has grown from about
fuel consumed in the sector. In this study, emissions 50 MT in 1993–94 to 169 MT in 2011. India is the
are estimated separately for cement, iron and steel, second largest producer of cement in the world after
 Industries • 53
China (Planning Commission 2011). Major clusters of Manufacturing of cement is a process which
cement industry in India are: leads to emissions of PM and gaseous pollutants.
PP 1. Satna in Madhya Pradesh The process flow diagram of cement manufacturing
PP 2. Chandrapur in Maharashtra is shown in Figure 4.6. There are a number of
PP 3. Gulbarga in Karnataka stages which can lead to emissions in a cement
PP 4. Yerranguntla in Andhra Pradesh manufacturing process including
PP 5. Nalgonda in Andhra Pradesh PP handling and storage of raw, intermediate and
PP 6. Bilaspur in Chattisgarh final materials,
PP 7. Chandoria in Rajasthan PP operation of kiln systems, clinker coolers, and mills.
There are 183 large cement plants and more The major release of emissions happens in the
than 360 mini cement plants. The Ordinary Portland kilns during the production through physical and
Cement (OPC) and Portland Pozzolana Cement chemical reactions involving the raw materials and
account for 93% of the total production (Figure 4.4). combustion of fuels. The indigenous emission factors
In India, the housing sector is the biggest driver per unit of cement production for this study are
of cement demand, accounting for about 67 per cent adopted from ILFS, 2010 and CPCB (2007) (Table 4.3)
of the total consumption. The other major consumers In a cement kiln, solid material moves counter
of cement include infrastructure (17%), commercial currently to the hot combusted gases. This counter
construction (13%), and industrial construction (9%) current flow affects the release of pollutants, since
(IBEF 2015). it acts as a built-in circulating fluidized bed. Most
TERI analysis (TERI 2015) on future projections of cement plants have made considerable efforts in
the sector shows bright prospects for growth of the controlling the stack emissions using most efficient
sector. The cement production is expected to grow control systems like bag filter and Electrostatic
about 6.5 times and will reach to about 1300 MT in Precipiators (ESPs) and these plants generally meet
2051 (Figure 4.5). the environmental regulations for stack emissions.

Figure 4.4: Variety-wise cement production in India

Source: Cement Manufacturers’ Association
OPC, Ordinary Portland Cement; PPC, Portland Pozzolana Cement; PBF, Portland Blast Furnace Slag
Cement; SR, Sulphate Resistant; IRS, Indian Railway Standard; Others
54  •  Air Pollutant Emissions Scenario for India

Figure 4.5 Projected growth of cement production in India (TERI, analysis)

Figure 4.6: Process flow diagram for the cement manufacturing process
Source: Adapted from Huntzinger, D.N. and Eatmon, T.D., 2008. A life-cycle assessment of Portland cement
manufacturing: comparing the traditional process with alternative technologies, J Clean Prod, doi:10.1016/j.
jclepro.2008.04.007
 Industries • 55

Table 4.3: Emission Factors for Cement Sector

Emission factors (kg/t)
Dry process
PM NOX SO2 CO
w/o APCD With APCD w/o APCD w/o APCD w/o APCD
Klin 94 0.98
Grinding 257 0.21
Others 7 0.01
Total 358 1.2 2.2 4.9 0.27
Fugitive 0.56*
Wet process
w/o APCD APCD w/o APCD w/o APCD w/o APCD
Klin 174 0.2
Grinding 123 0.02
Others 6 0.03
Total 303 0.25 4 3.75 0.27
Source: ILFS, 2010, CPCB (2007)
APCD: Air pollution control devices
 * Ratios for PM2.5, BC, OC are used from EEA 2009 and EPA 2012.

However, fugitive emissions from various sources in influx of FGDs in the sector, the SO2 emissions can
cement plants still remain an area of concern (CPCB reduce considerably. The use of pet coke has resulted
2007). Based on the emission factors and controls, in substantial reduction in conventional fuel and
the emissions coming out of the cement plant present study has taken this into account for current
are estimated and presented in Figure 4.7. These and future scenarios.
emissions include pollutants emitted during captive
power generation activities. Iron and steel Industry
The PM10 emissions are projected to go up from The iron and steel industry in India caters to the
354 Kt in 2011 to 2446 Kt in 2051. The ratio of PM2.5 demands of key sectors like construction and
emissions to the PM10 emissions is about 0.56. While, automobiles. The sector is mainly divided into
the presence of air pollution control (APC) equipment two types; the first one comprises of a few large
for PM leads to control of emissions, NOx emissions integrated steel providers producing primary
are projected to go up uncontrolled by about 7 times products billets, slabs and hot rolled coils, and
from the current levels of 450 Kt. This highlights the secondary smaller units producing value-added
need for emission control norms for NOx in industries. products such as cold rolled coils, galvanised coils,
The SO2 emissions are expected to increase from angles, columns, beams and other re-rollers, and
about 1044 Kt in 2011 to about 7327 Kt in 2051. It sponge iron units. The sector has seen enormous
is to be noted that in last few years, many cement growth in the recent past with India becoming
industries have started co-processing of hazardous the fourth largest producer of crude steel and the
and other high calorific value material like petcoke. largest producer of soft iron in the world. The per
This leads to higher emissions of SO2 due to high capita consumption is about 58 kg in 2013 which
sulphur content of the fuel (petcoke) used in the is expected to rise with increased industrialization
sector. Present estimates do not assume the influx throughout the country. The report of the Working
of FGD technology in the sector. However, with Group on Steel for the 12th Five Year Plan envisages
56  •  Air Pollutant Emissions Scenario for India

SO2

NOx
PM10

PM2.5

CO

Figure 4.7: Past and projected growth of emissions (Kt) from cement manufacturing in India
increase in the per capita steel consumption in MT by 2016–17 and has the potential to reach 149
the country on the basis of high infrastructure MT. The MARKAL model estimates are close to the
investment, high projected growth of manufacturing projections. The model projected the finished steel
sector, increasing urban population, and emergence production to 388 MT in 2031 and 779 MT in 2051
of the rural markets. The Working Group on Steel for (Figure 4.8).
the 12th Five Year Plan made projections for domestic Various processes involved in iron and steel
crude steel capacity in the county to be about 140 manufacturing are metallurgical coke production,

Figure 4.8: Past and projected finished steel production (MT) in India (2001-2051)
Source: TERI-MARKAL model
 Industries • 57
sinter production, pellet production, iron ore processes followed in the iron and steel sector in
processing, iron making, steel making, steel casting, India (Table 4.4).
and sometimes combustion of blast furnace and Basic oxygen furnaces use pig iron and electric
coke oven gases for other purposes. The raw steel is arc furnace is used for steel produced from scrap.
produced using a basic oxygen furnace from pig iron Based on emission factors, the emissions for different
produced by the blast furnace and then processed pollutants from iron and steel plants are estimated
into finished steel products (Figure 4.9). and presented in Figure 4.10.
Emissions occur at all the stages of the production The iron and steel plants are generally equipped
and emission factors are chosen for different with high efficiency APC equipment and the PM10

Figure 4.9: Processes in iron and steel production industry

Adopted from EEA (2009)

Table 4.4: Emission Factors for Different Pollutants from Various Processes in Steel Making
Emission Factors  Sintering  Pig Iron Basic Oxygen Furnace with ESP Electric Arc Furnace with ESP
  Kg/t Kg/t Kg/t Steel making
PM2.5 0.08 0.025 0.021 0.021
PM10 0.1 0.04 0.024 0.024
BC 0.00017 0.0024 0.00036 0.00036
OC  – – 0.002484 0.003168
NOx 0.5  – 0.01 0.13
SO2  1 –  –  0.06
CO 12 10 7 0.0017
NMVOC 0.138 – – 0.046
Source: EEA, 2.C.1 Iron and steel production , GAINS ASIA model
58  •  Air Pollutant Emissions Scenario for India

Figure 4.10: Emissions (Kt) from iron and steel industry in India (2001–51)

emissions are projected to go up from 24.2 Kt in 2011 activity data to estimate emissions during 2001–51
to 144 Kt in 2051. This is mainly due to the growth for different pollutants (Figure 4.13).
expected in the sector. NOx emissions are projected to The emissions from aluminium industry are
grow from 86 Kt to 707 Kt during 2011- 2051. comparatively less than cement and iron and steel
industries, except for CO. The CO emissions are
Aluminium Industry expected to grow from 194 Kt to 1,096 Kt during
In India, aluminium is mainly produced in large 2011–51.
integrated plants such as Hindalco and National
Aluminium Company, and Bharat Aluminium, etc. Glass Industry
The main energy inputs are in the form of electricity, Glass industry caters to the demands of key sector
coal, and furnace oil and the standard Bayer– such as construction, automotive, consumer
Hall–Heroult technology is used for aluminium goods, and pharmaceuticals. Apart from few big
production. The production process is described
in Figure 4.11. Captive power plants are installed Table 4.5: Emission Factors for Aluminium Production
to provide uninterrupted power. Presently, India Pollutant Unabated Emission factor (kg/t)
accounts for 6% of the total deposits and 2.1 million PM10 2
tons of aluminium production in 2011. Aluminium PM2.5 1
production has grown steadily in India and is
BC 0.023
projected to grow to about 9 MT in 2051 (Figure 4.12).
OC  0.0391
Aluminium production is expected to increase due to
demands from packaging, construction, automobiles, NOx 1
and electrical sectors. SO2 6
The emission factors used for estimating emissions CO 120
form aluminium production in India are shown in NMVOC -
Table 4.5. The emission factors are applied to the
Source: EEA 2009, EPA 2012, GAINS
 Industries • 59

Figure 4.11: Aluminium production process flow chart

Source: Adapted from Halvor and Per Arne (2014)

Figure 4.12: Aluminium production in India (2001-2051)

Source: TERI (2015)

manufacturers there are more than 1,000 small oil and natural gas are mainly used in India as the
and medium scale enterprises involved in glass thermal energy source. The emission factors used to
production in India. The glass consumption in India is estimate emissions from glass manufacturing in India
just 1.2 kg/c/yr in 2010–11 in comparison to 30–35 kg are shown in Table 4.6 and emissions are presented in
in the US (TERI 2015). Figure 4.14. The PM10 emissions are expected to grow
Glass industry is highly energy intensive and the from 1 Kt in 2011 to 5 Kt in 2051. NOx emissions will
melting and refining processes account for 60–70% grow from 34 Kt to 153 Kt during 2011–51.
of the energy consumed in production. Furnace
60  •  Air Pollutant Emissions Scenario for India

CO
SO2

NOx
PM10
PM2.5

OC
BC

Figure 4.13: Emissions (kilotonnes) from aluminium industry in India (2001–51)

Paper and Pulp Industry rates in the country. Presently, the per capita paper
consumption is just 9.3 kg in India as against 42 kg
The Indian paper industry accounts for about 2.6%
in China and 312 kg in US (TERI 2015). However, with
of the world’s paper production. The technologies
growing literacy and middle class, the consumption
used in the paper mills show wide variations
is expected to grow. Production of paper is
ranging from oldest to the most modern. A variety
projected to grown from 7.5 MT in 2011 to about 20
of raw material are used including wood, bamboo,
MT in 2051 (Figure 4.15).
recycled fibre, bagasse, wheat straw, rice husk, etc.
There are about 720 paper mills in India of which
Of the total paper production, 31% is based on
621 are in operation (Ministry of Commerce & Industry
chemical pulp, 47% on recycled fibre, and 22% on
2010–11). Gujarat has the maximum number of paper
agro-residues (IPMA 2015). Paper industry is heavily
mills followed by Uttar Pradesh. Majorly operating
dependent on the industrial growth and literacy
mills in India falls under three categories (CPCB 2011;
Table 4.6: Emissions Factors for Glass Ministry of Commerce & Industry 2010–11):
Manufacturing PP Large Integrated Wood Based: It includes
newsprint, rayon grade pulp, bleached and
Pollutant Unabated emission factor (kg/t)
unbleached varieties. Scale of operation for these
PM10 0.27
mills is 100–700 tpd.
PM2.5 0.24 PP Medium Agricultural Residue Based: It includes
BC 0.0038 bleached varieties with and without recovery
NOx 8.12 system and unbleached varieties without recovery
SO2 1.74 system. Scale of operation for these mills is 50–100
CO 0.1 tpd.
PP Small Recycled Fibre and Market Pulp Based: It
NMVOC – 
includes unbleached craft, writing and printing
Source: EEA 2009, GAINS
 Industries • 61

Figure 4.14: Emissions (kilotonnes) from glass industry in India (2001–51)

Figure 4.15: Past and project growth of paper industry in India

Source: TERI Analysis

varieties with and without deinking, unbleached sodium sulphide and sodium hydroxide) is subjected
crafts, and paper board. Scale of operation for to high temperature and pressure. The lignin that
these mills is 5–50 tpd. binds the cellulose fibres of the wood is chemically
dissolved. Thereafter, the pulp is washed, screened,
Kraft method is broadly used in India for paper and dried or further delignified and bleached, if
production. In this, the white liquor (water solution of required based upon the intended use of the product.
62  •  Air Pollutant Emissions Scenario for India
The rest of the Kraft processes are there for chemicals Table 4.7: Emission Factors for Paper Industry
and heat recovery. The black liquor formed during the
Pollutant Unabated emission factor (kg/t)
process is concentrated through evaporation, which
PM10 0.8
is then combusted for recovery of heat and chemicals.
Broadly, the emissions produced from different PM2.5 0.6
processes in paper and pulp industry are shown in BC 0.012
Figure 4.16. OC 0.0408
The emission factors used to estimate emissions NOx 1
of different pollutants from Kraft pulping process are
SO2 2
presented in Table 4.7. It is evident from the Figure
CO 5.5
4.17 that emissions from the paper and pulp industry
will grow; PM10 will grow from 8 Kt to 17 Kt during NMVOC 2
2011–51, while CO emissions from 42 Kt to 112 Kt in Source: EEA 2009, EPA 2012
the same period.
2010–11 and per hectare consumption, has increased
Fertilizer Industry from less than 1 Kg in 1951–52 to the level of 135 Kg
Chemical fertilizers are important to improve or now. The overall production of fertilizers in India is
sustain agricultural production in the country. expected to grow to 56 MT/a by 2051 (Figure 4.18).
Government of India has consistently persuaded About 78 per cent of Urea production is through
policies conducive to increased availability and natural gas used as feedstock. Fuel oil and naptha are
consumption of fertilizers at affordable prices in the also used in the sector. Thakkar (2013) has found high
country (MoCF 2012). The consumption of fertilizers, levels of pollutant emissions from industrial sector
in nutrient terms (N, P, & K ) has increased from 0.07 in India. The emission factors used in this study for
million MT in 1951–52 to more than 28 million MT in emission estimation are presented in Table 4.8.

Figure 4.16: Emissions produced from paper production process

Source: Reproduced from CPCB (2011)
 Industries • 63

CO
SO2

NMVOC
NOx

PM10
PM2.5

Figure 4.17: Emissions from paper industry in India (2001–51)

Figure 4.18: Past and future projections of fertilizer production in India (2001-2051)
Source: TERI Analysis

The estimated emissions are shown in Figure 4.19 Kt in 2011 to 3,462 Kt in 2051. SO2 emissions that are
for the period 2001–51. The CO emissions from the coming from captive power generation using coal
fertilizer industry are expected to go up from 1,020 will gradually diminish in the future.
64  •  Air Pollutant Emissions Scenario for India

Table 4.8: Emission Factors (kg/t) for Fertilizer Industry pollutants are injurious to human health, animal, and
plant life. At global level, CO2 and BC contribute to
Pollutant Emission factor (kg/t)
global warming and climate change.
PM10 0.33
There are about 300,000 brick kilns across the
PM2.5 0.2145 world that produce around 1,350 billion bricks across
BC – the year (MNRE 2013). Brick production is mainly
OC – focused in four countries across the world. Among
NOX 2 these countries, China holds the maximum share
SO2 0.04 of brick production followed by India, Pakistan, and
Bangladesh (Figure 4.20). In India, total number of
CO 62.25
brick kilns are estimated to be around 1.4 lakh with a
VOC –
production of 280 billion brick annually (Rajarathnam
Source: AP42, Section 6.10 phosphate fertilizers et al. 2014). It is reported that during 2000–01, about
80 billion bricks were produced in India (TERI 2002).
As a result of increasing demand for infrastructure,
Brick Industry commercial, and residential buildings, the demand for
Brick industry is a small scale traditional and bricks is also increasing at a high rate. Brick making in
unorganized industry in India (Maithel 2013; Pandey India is concentrated in Indo-Gangetic plains and in
et al. 2014; Rajarathnam et al. 2014). But over time, it some scattered pockets in other states (Figure 4.21).
has become one of the largest consumers of coal in Maximum number of the brick kilns is located in the
the country. Around 17.14 tonnes of coal is required rural areas lying adjacent to rapidly expanding cities.
to produce one lakh bricks. Incomplete combustion Brick kiln industry in India started with the clamp
of coal results in the release of several air pollutants technology having non-fixed structures. The practice
in atmosphere such as CO, SO2, NOX, and PM. At local was to take clay and mud from fields, moulding
level (in the vicinity of a brick kiln) some of these them, and heating them in inefficient furnaces using

NOx
CO

PM10
PM2.5
SO2

Figure 4.19: Emissions from fertilizer industry in India (2001-2051)

 Industries • 65
Brick production involves moulding, drying, and
firing processes. These bricks are heated between
600°C and 1,100°C to get the desired product (TERI
1999). Different types of kilns are used for firing bricks,
which are broadly divided into intermittent and
continuous categories (Figure 4.22).
Continuous kilns are generally more efficient as fire
is always burning and bricks are being warmed, fired,
and cooled simultaneously in different parts of the
kiln. Heat in the flue gas is utilized for heating green
bricks and the heat in fired bricks is used for heating
Figure 4.20: Worldwide production of bricks in
major producing industries air for combustion. On the other hand, fire is allowed
Source: MNRE (2013) to die out and the bricks to cool after they have been
fired in intermittent kilns. The kiln are emptied, refilled,
any fuel that is easily available. There was no control and a new fire is initiated for each load of bricks. In
technology involved in these temporary structures. intermittent kilns, most of the heat contained in the
The brick manufacturing is known as one of the hot flue gases and the fired bricks is lost.
major polluting sectors. Studies have pointed out Different types of Brick kiln technologies practiced
that around 9% of black carbon emissions in India in India are Clamps (scove, scotch), Moving Chimney
are from brick sector. Many technologies with varied Bull’s Trench kiln (MC-BTK), Fixed Chimney Bull’s
designs have been introduced from time to time Trench kiln (FCBTK), Vertical Shaft Brick kiln (VSBK),
in order to reduce the huge environmental cost Zig-Zag, and Tunnel Kilns (Figure 4.23). Clamp and
associated with the sector. downdraught kilns are examples of intermittent kilns,
while, rest are continuous in nature.

Figure 4.21: Brick production sites in India.

Source: Adapted from http://www.ecobrick.in/ Figure 4.22: Brick production in India
brickmakinginindia.aspx Photo credit: R Suresh
66  •  Air Pollutant Emissions Scenario for India
A transition has been observed in last two Table 4.9: Comparison of SEC for Different Kilns
decade with the introduction of new technologies Type of Kiln SEC (MJ/kg of fired bricks)
in the country, which are shown in Figure 4.24. These Clamp and other batch kilns (Asia) 2.0-4.5
different types of brick kilns differ in terms of specific
MC-BTK (India) 1.2-1.75
energy consumption (SEC). SEC is expressed in terms
FCBTK (India) 1.1-1.5
of energy required for firing per Kg of bricks. A study
VSBK (India, Nepal, Vietnam) 0.7-1.0
conducted by SDC (2008) has come up with SEC
Tunnel Kiln (Vietnam) 1.4-1.6
values for few technologies, shown in Table 4.9.
In this study, bricks production has been estimated
by assuming growth in brick production same as alternate walling materials could decrease the share of
growth of construction sector, which is 6.6% for the fired bricks to some extent in the construction sector.
time period 2005–30 (MNRE 2013) in the country. For For 2010, the share of other walling materials has
further projections, growth rates have been taken been estimated as 7.8%, which is expected to increase
from TERI MARKAL model outputs. However, in the to 14.1% in 2030 (Enzen & Greentech Knowledge
past few decades, it has been observed that other Solutions 2011). The current and expected brick
walling materials such as fly-ash bricks, fly-ash lime production in India is shown in Figure 4.25.
gypsum blocks, autoclaved aerated concrete blocks State-wise allocation is done on the basis of
have entered the Indian market and replaced bricks reported number of brick kilns in the states in TERI
to some extent. In future, it is expected that these (2007). Based on consultation with experts, it is

Figure 4.23: Brick kilns categorization on basis of firing technology

Source: CSE (2015)

Figure 4.24: Technology transition in brick sector in India

Source: Maithel (2013)
 Industries • 67

Figure 4.25: Current and projected brick production in India (2001–51)

assumed that 32% of the bricks in the country are experts, it is assumed that for 2030, 12% of the bricks
manufactured using clamps, 61% are manufactured will be produced from Clamps, 65% from FCBTKs,
using Bull’s trench kiln, 3% with moving chimney 19% from zig-zag kilns, and 3% through tunnel kilns.
BTK (BTK-MC), and 1% for Holfmann kiln for the Considering the field performance of VSBKs in India, it
baseline year (2011). Vertical Shaft Brick Kilns (VSBKs) is being assumed that their number will not increase
contribute very little in the total share of kilns across much with time. Further in 2050, it is assumed that
India (Table 4.10). percentage of brick kilns with Zig-Zag technology
With the advent of advanced technologies such will increase to 45% and FCBTK to be 55%. Clamps
as Zig-Zag firing and tunnel kilns, it is expected that will diminish and tunnel kilns with economical
these cleaner technologies will penetrate into Indian constraints will be negligible in number.
Brick industry and numbers of clamps will gradually Emissions from brick manufacturing facilities
reduce (Figure 4.26). Thus, on consultation with include PM (PM10 , PM 2.5, SO2, nitrogen oxides (NOx),

Table 4.10: Estimated Kiln Technology–Wise Distribution of Brick Production in India in 2011
Kiln Technology Number of Kilns (Approx.) 2010 Capacity Ratio (Thousand bricks/day) Total number of Bricks
produced/day
DDK 300 3 900
MCBTK 2,000 20 40,000
FCBTK 32,000 30 9,60,000
Zig-Zag 2,000 30 60,000
Holfman Kiln 500 30 15,000
VSBK 100 7 700
Clamp 100,000 5 5,00,000
Tunnel Kiln (Coal) 0 45 0
68  •  Air Pollutant Emissions Scenario for India

Figure 4.26: Projected kiln technology–wise distribution of brick production in India till 2051
Source: Expert consultations

carbon monoxide (CO), carbon dioxide (CO2), metals, and plant design. Emissions of each gas depends on
organic compounds (including methane, ethane, different steps involved in the production of bricks in
volatile organic compounds [VOC], hydrochloric acid kilns.
(HCl), and fluoride compounds) (EPA 1997) (Figure In a recent study conducted by Greentech
4.27). Factors that may affect emissions from brick Knowledge solutions, nine brick kilns were monitored
industry include raw material composition, moisture in India and Vietnam in order to understand
content, kiln fuel type, kiln operating parameters, energy consumption and emissions using different

Figure 4.27: Emissions from brick industry

Source: Reproduced from EPA (1997)
 Industries • 69
technologies. Table 4.11 presents emission factors for the kiln’s production capacity. Along with control
different brick manufacturing technologies. of emissions from brick industry, newer options for
Based on the brick production rates and expected alternative walling material should be explored which
influx of technologies, the emissions from Brick are environmentally sustainable.
kiln industry for India are estimated and are shown
in Table 4.12. In 2011, 294 Kt of PM10 and 226 Kt of Other Industries
PM2.5 emissions are estimated. It is observed that Other than cement, iron & steel, brick, aluminium,
PM emissions will increase two folds by 2031 and glass, paper, and fertilizer industry, significant energy
stabilize thereafter with marginal increase till 2051. consumption takes place in small and medium scale
Similarly black carbon and organic carbon emissions industries. The energy consumed in these ‘other
are expected to increase and will double by 2051. industries’ in comparison to the major sectors is
These emission estimates take into account shown in Figure 4.3. The energy consumed in the
the influx of improved technologies; however, in other industry sector is multiplied with emission
absence of these, the emissions from the sector will factors listed in Tables 4.13 and 4.14 to estimate
be much higher. Ministry of Environment, Forest, and emissions. Table 4.13 shows the PM emission factors
Climate Change in India has brought up PM emission for coal combustion in industries based on the ash
standards and stack height specifications based on content and efficiency of tale pipe controls.

Table 4.11: Emission Factor for Different Type of Brick Kilns

Technology Unabated emission Factors (g/kg of fired brick)
PM10 PM2.5 SO2 CO CO2
Greentech energy solutions FCBTK 0.86 0.18 0.66 2.25 115
(2012)a Zig-zag 0.26 0.13 0.32 1.47 103
VSBK 0.11 0.09 0.54 1.84 70
DDK 1.56 0.97 n.d 5.78 282
Tunnel 0.31 0.18 0.72 2.45 166
Rajarathnam et al. (2014)b FCBTK 0.89 0.52 3.63 179
NDZZ 0.22 0.06 0.35 119
FDZZ 0.24 0.24 2.04 96
VSBK 0.09 0.10 4.14 118
DDK 1.56 0 5.01 526
a
Study was conducted on seven brick kilns in India and two (modified VSBK and Tunnel Kiln) in Vietnam in 2011.
b
Study was performed on 15 brick kilns in India.
Ratios of PM2.5, BC, OC and EF of NOX and NMVOC are adopted from GAINS Asia

Table 4.12: Emissions (Kt) from Brick Kiln Industry in India

2001 2011 2021 2031 2041 2051
PM10 164 294 430 588 678 691
PM2.5 126 226 331 453 522 531
BC 38 68 99 136 156 159
OC 44 79 116 158 183 186
NOx 0 0 0 0 0 0
SO2 38 68 99 136 156 159
CO 1263 2261 3307 4526 5216 5312
VOC 19 34 50 68 78 80
70  •  Air Pollutant Emissions Scenario for India

Table 4.13: PM Emission Factor for Coal Combustion in Industrial Sector

PM10 PM2.5
Large Scale (High Medium Small (low Large Scale Medium Small (low
Controls e.g. ESP) (medium controls) (ESP) (medium controls)
controls) controls)
Ash content 35% 35% 35% Ash content 35% 35% 35%
Fly/Bottom ash ratio 80:20 80:20 80:20 Fly/Bottom ash ratio 80:20 80:20 80:20
PM10/PM 0.71 0.48 0.39 PM2.5/PM 0.35 0.29 0.21
Efficiency of control 99.90% 70% 40% Efficiency of control 99.90% 70% 40%
Emission factor (t/PJ)** 11 2314 3753 Emission factor (t/PJ)** 6 1379 2026
*PM10/PM and PM2.5/PM ratios are taken as an average of wet and dry bottom boilers
BC and OC are assumed to be 0.1% and 0.2% of PM10 fractions; adopted from emission factor ratios in GAINS
** Emission Factors = Ash content ×Fly/Bottom ash ratio × PM fraction ratio × (1–efficiency of control)

Table 4.14: Fuel- and Pollutant-Wise Emission Factors (Kt/PJ) for Based on the energy consumption and respective
NOx, SO2, CO, and HC emission factors, the emissions for different years
Fuel NOx SO2 CO HC PM10 are estimated (Figure 4.28). It is expected that
Coal 0.13 0.57 0.01 0.02 with industrial growth the emissions will grow
Natural Gas 0.07 0.02 0.04 - considerably. However, with improved enforcement
Biomass 0.03 0.00 0.3 0.80 0.12 of existing standards for PM, there will be increased
Fuel oil 0.15 1.73 0.01 0.09 0.11 penetration of APC technologies. Presently, only
Diesel 0.08 0.94 0.04 - 0.77 large scale industries are assumed to be equipped
Light Diesel Oil 0.08 0.94 0.04 - 0.77 with high efficiency APC equipment such as ESPs
Naphtha 0.07 0.02 0.04 - 0.10 and Bag-filters. As per the consent to establish and
Source: CPCB 2011, GAINS Asia consent to operate requirements for industries, all

PM10

SO2

PM2.5

NOx

Figure 4.28: Emissions of different pollutants from other industrial fuel consumption (Kt)
 Industries • 71
polluting industries need to install emission control in India, the majority (88%) are comprised of non-
equipments. Although, the efficiency of controls vary coking coal and about 11.5% are coking coal, while
with the requirements and type of APCE installed. a minimal share (0.5%) is of tertiary coal reserves
Based on expert consultations, micro, small, and (Indian Chamber of Commerce & PwC 2012). Indian
medium industries are assumed to be equipped with coal is characterized by its high ash content (as high
APCs with an efficiency of 40%. Based on the growth as 45%), along with low sulphur content (0.2–0.7%),
of the current APCE industry, and growing concerns and low calorific values (between 2,500–5,000 kcal/
over air pollution in Indian cities, penetration of high kg) (IEA 2002). The total production of coal in India
efficiency APC equipments in industries is assumed in the year 2013–14 was 565.64 Million tonnes
to increase to about 50% by 2051. However, there will (MoC 2013). The largest consumer of coal in India
be variation in degree of control with the type of APC is power sector, accounting for almost 70% of coal
technologies installed. consumption in 2011 (MOC 2014). Steel production
PM10 emissions from ‘other’ industries will grow and cement industries are other significant coal
from 3,791 Kt in 2011 to 11,700 Kt in 2051, with an consumers in the country.
increase of 209%. However with influx of control India is ranked third in coal, lignite, and bauxite
technologies, the intensity of emission per unit of production and fourth in iron ore production in
production is expected to go down significantly. In the world in the year 2009–10 (Ministry of Mines,
absence of suitable standards for NOx and SO2, the Government of India). Public sector continues to play
emissions will grow by eight to nine folds by 2051. a dominant role in mineral production, and accounts
for 74.5% of all minerals produced and a sizeable 91%
Mining of the total coal produced. Data of major coal mines
Coal and iron scenario in India along with their production capacities is presented in
Table 4.15 (MoC, 2014). The major coal field locations
Coal along with other fossil fuels continues to be
are shown over the map of India in Figure 4.29.
the primary source of energy in India, despite its
environmental impacts both at local as well as regional
level. Among all the ores and industrial minerals, iron
Past trends and future growth of mining in India
ore (along with bauxite and copper) is of the most Mining and mineral extraction in India can be traced
quantitative importance in terms of its mass flows in back to the days of the ancient civilizations residing
the Indian economy (Singh et al. 2012). Mining of coal in the region. The country is known to be endowed
along with other minerals is an important economic with rich and widely available resources of many
activity though burdened by severe environmental metallic and non-metallic minerals; hence mining
impact particularly on air and water quality, and forest sector plays a key role in the Indian economy. India
resources including biodiversity and green cover. produces as many as 87 minerals, which include
The growing demand for natural resources such as four fuels among others (Ministry of Mines 2011).
coal and iron ore, from developed as well as rapidly Coal mining became an important part of the public
developing countries such as India and China, have led sector in India during the years 1971–73 with the
to increasing shortages of these resources in the global enactment of the Coal Mines (Nationalization) Act,
economy (Planning Commission 2013). In this scenario, 1973. In the same year, the Coal Mines Authority
making a robust supply of domestic resources is all the Ltd. was set up and was made responsible for all the
more necessary. operation and maintenance of the nationalized non-
The geological coal reserves have been estimated coking coal mines in India (Dutt 2007).
to be 301.56 billion tonnes (as on 1st April 2014) Mainly there are two kinds of methods for
in India according to the Ministry of Coal (MOC), coal extraction: opencast (surface) mining and
Government of India. Of the total reserves of coal underground mining. In India, the predominantly
72  •  Air Pollutant Emissions Scenario for India

Table 4.15: Major Coal Mines along with their Production

Capacities in India in 2012–13
Unit Production (in Million Tonnes)
Eastern Coal fields 33.9
Bharat Coking Coal Ltd. 31.2
Central Coalfields Ltd. 48.1
Northern Coalfields Ltd. 70.0
WCL western Coalfields Ltd. 42.3
SECL South Eastern Coalfields Ltd. 118.2
MCL Mahanadi Coalfields Ltd. 107.9
NEC North Eastern Coalfields. 0.6
Total CIL 452.2
SCCL Singareni Collieries Co. Ltd 53.2
Other Public 3.9
Total Public 509.2
Total Private 47.2 Figure 4.29: Major coal fields in India
All India 556.4 Source: CMPDI, Coal India

used method is opencast extraction; and mining in involves construction of a vertical shaft or slope
the country has grown with a 4% annual average mine entry to the coal seam and then extracting the
growth rate over the past decade. Opencast coal using various standard techniques. About 9% of
mining involves mining coal in an earth-moving India’s coal production was from underground mines
operation by excavating the overburden up to in the year 2012–13 (MoC, 2014).
the coal seams and then removing the coal using In 2010, India produced the world’s third largest
draglines, shovels, and dump trucks. This method of volume (532 MT) of coal domestically, which was more
extraction is overall more advantageous due to the than double of the 1990 level of 205 MT; however,
following factors: the production has more or less plateaued in recent
PP greater extraction rate of coal years (Ahn and Graczyk 2012). The 12th Five-Year Plan
PP higher productivity compared to the other aims to further increase coal production to 715 MT
method of extraction in FY 2016/17, a 33% increase from the level of 2010.
PP lower in costs and labour intensity According to the World Energy Council, the demand
PP and better workplace conditions and supply gap of coal was around 85 million tons in
2011–12 and it is expected to gradually increase to as
However, opencast mining is infamous for much as 140 million tons by 2017.
having greater impact on the local environment; On the consumption side, power sector in India
such as large-scale land use, overburden disposal, has been increasingly dependent on coal; in 2009,
disturbance of hydrology and run-off, increased 73% of domestic coal was consumed by the power
erosion, acid mine drainage, noise, and possible sector, while in 1991, the figure was much lower at
damage to the ecosystems. 61% (IEA 2012). Coal Vision 2025 estimates that the
On the other hand, underground mining is power sector alone would require 916 MT of coal
employed for extraction of very deep coal seams, in 2025. The Figure 4.30 illustrates the trend of coal
 Industries • 73
consumption by different sectors in India from 2001 of metallic minerals extracted in India in the year
to 2010 (Qaisar and Ahmad 2014) showing a steady 2010 was 322.74 billion INR, of which iron ore’s
and significant growth in the consumption by power/ contribution was 268.65 billion INR (Ministry of
electricity sector over the years. Mines 2011). Production of iron ore registered a
The Planning Commission in 2006 put together 2.67% increase from the previous year, at 218.64
different projections from various agencies for coal million tonnes in 2010. While in the year 2011 it
and other fossil fuel demands in future years in a again decreased slightly and was recorded as 207
specific scenario, which estimates the coal demand million tonnes by the Ministry of Mines, Government
in 2031–32 to be 1,397 MT (for both power and non- of India. In contrast to the coal scenario, only 27%
power use) in India. On the production side, TERI has of the total iron production was shared by public
estimated the domestic coal production in India in sector companies like SAIL, NMDC, etc. While the
the same year 2031–32 to be in the tune of 868 MT, private sector owned the major share of 63%
again showing that the demand and supply gap including companies like Tata steel (8%) and Jindal
in coal is expected to increase in the future as well. steel, etc. Almost 96% of the iron ore in India is
Under this likelihood of consistently increasing coal produced in Orissa, Karnataka, Chhattisgarh, Goa, and
demand, it becomes even more imperative to curb Jharkhand during the year 2010. Iron ore mining is
the emissions from coal mining and production also predominantly carried out by opencast mining
activities to limit its environmental impact. Figure (both manual and mechanized) in India. The iron ore
4.31 shows the increasing trend in production of coal industry in India is highly fragmented and prior to
in India and future projections (TERI 2015). the ban imposed by the Supreme Court in Karnataka
Among all the principal metallic ores mined in on iron ore mining, there were 336 operating mines
India, iron ore has the major share. The total value reporting production in 2011–12 (Firoz, 2014).

Figure 4.30: Consumption of raw coal (in million-tons) by different sectors from the period 2001–02 to
2009–10
74  •  Air Pollutant Emissions Scenario for India

Figure 4.31: Current and future trends of coal production in India (2001–51)
Source: TERI Analysis, 2015

Sources of emissions from mining Despite such huge emissions of dusts from
opencast mining, there is no well-defined
The major causes of air pollution from mines are
methodology to calculate these emissions from
fugitive emissions of PM and gases including CH4,
mining activities. Many independent studies have
SO2, NOX, and CO, although in lesser concentrations.
been undertaken in different parts of the world
All major activities (overburden removal, drilling,
to calculate dust emissions from different mines
blasting, crushing, hauling, loading, transportation,
and have also developed relevant emission factors;
etc.) carried out in the mines produces a lot of dust.
however, these are highly site-specific owing to the
As stated in the earlier sections of this chapter,
highly variable conditions prevalent in different
opencast mining has a more severe impact on air
mines in different regions and countries. Estimation
quality compared to underground mining, with high
of the amount of dust actually generated in mining
levels of suspended PM associated with opencast
is an important first step towards mitigating and
mines. A number of studies have repeatedly reported
managing the emissions effectively.
that as high as 50–80% of the total dust emitted in
A significant piece of work in this field was
open cast coal mines can be attributed to vehicular
carried out by Chakraborty et al. in 2002 in which
movement on unpaved haul roads, followed by
they developed empirical formulae to calculate the
loading and unloading of dumpers (Ghose and Majee
emission rate of various opencast mining activities. In
2001).
this study, they selected seven coal and three iron ore
The dust not only affects the ambient air quality
mining sites across India to generate emission data
in and around the mines but also pollutes the nearby
for major mining activities by considering various
surface waters and stunts crop growth by shading
factors. We have adopted the empirical formula
and clogging the pores of the plants (Singh 2006).
 Industries • 75
developed by Chakraborty et al. (2002), to quantify In order to validate the results obtained using
the national emissions from opencast mining of coal these formulae, the total emissions from open-
and iron ore in this study. cast coal mining in India was also estimated using
emission factors developed by Ghose (2004). These
Methodology to estimate emissions from emission factors were developed by Ghose for
mining activities various open-cast mining activities (Table 4.16).
The PM emissions for India from open-cast coal
This study employed the empirical formulae derived
mining was also calculated by this method using
by Chakraborthy et al. (2002) to calculate the national
the average emission factor for OB removal and coal
emissions of different pollutants from coal and iron
mining along with emission factors for transportation
ore mining in India. The empirical formulae used for
of OB and coal.
calculating the emission rates of different pollutants
for the overall mines are listed below:
Emissions from mining sector in India
PM The national emissions from coal and iron ore
E=[u0.4 a0.2 {9.7+0.01p+b/(4+0.3b)}] mining are estimated using the methodology
described above for the years 2001 to 2051. The
SO2 national level emissions of different pollutants from
E=a 0.14 {u/(1.83+0.93u)}×[{p/(0.48+0.57p)}+{b/ coal mining sector for India in the year 2011 are
(14.37+1.15b)}] shown in Table 4.17. For validating these emissions,
the overall emissions of PM were also calculated
NOX
Table 4.16: Emission Factors for Mining Operations (Ghose 2004)
E=a0.25 {u/(4.3+32.5u)}[1.5p+{b/(0.06+0.08b)}]
Mining Activity Material Emission Factor for PM

Where, E = Emission rate for overall mine Overburden (topsoil) Overburden 0.029 kg/t
removal
u = wind speed (m/s)
a = area of pit (Km2) Dumper loading of Overburden 0.018 Kt/t
overburden (by power
p = mineral production (MT/year)
shovel)
b = OB handling (Mm3/year)
Unloading Overburden 0.001 kg/t
Total emission factor for OB Overburden 0.048 kg/t
The production and overburden removal and the
removal
number of mines for each coal mining company for
Transportation in haul road Overburden 2.25 kg/vKt*
the year 2011 were acquired from MoC, 2013. Since
the data on the mining area for each mine in India Loading Coal 0.014 kg/t
is not available, the ratio of coal production to area Unloading Coal 0.033 kg/t
of production 0.039 MT/Km2 (calculated for the state Total emission factor for Coal 0.047 kg/t
of Orissa; TERI 2013) is used to calculate area per coal mining
mine for the whole country. Wind speed datasets Transportation in haul road Coal 2.25 kg/vKt**
were obtained from the nearest IMD stations using *For overburden, it is assumed that average length of haul road (h) is
Climatological Tables of India, published by the 0.5 km and the average capacity (c) of each dumper used to transport
IMD. Using this data and the empirical relationship it is 85t
described above, the PM, SO2, and NOX emissions for **For coal, it is assumed that average length of haul road is 0.7 km and
the average capacity of each dumper used to transport it is 58 t
each mine was calculated. Ratios of PM10 and PM2.5
in the total PM were adopted from GAINS database, So, VKT is calculated for both overburden and coal as:
which were 0.5 and 0.1, respectively. VKT= h ×c×total quantity of material transported in tonnes
76  •  Air Pollutant Emissions Scenario for India
using the emission factors developed by Ghose Table 4.17: Emissions of PM from Open-Cast Coal Mining in India
(2004) as mentioned in the methodology section. in 2011
PM10 and PM2.5 emissions calculated from both the Pollutant Total Emissions (kT/year)
methodologies are almost the same hence proving Chakraborty (2002) Ghose (2004)
that the estimations in this study are reliable.
PM10 90.29 90.42
Due to lack of detailed data on mine-wise area
PM2.5 18.06 18.08
and location of each mine for iron ore mining, their
emissions were only calculated using the emission
Table 4.18: Annual emissions from open-cast iron ore mining
factors developed by Ghose (2004). For open-cast iron
in India in 2011
ore mining, the total emissions of different pollutants
Pollutant Total Emissions (kT/year)
across India are presented in Table 4.18.
The emissions from open-cast mining have PM10 49.92
also been estimated for the past and future years. PM2.5 9.98
Considering 2011 as the base year, estimates were SO2 9.54
made for each 10-year interval from 2001 to 2051. NOX 3.08
TERI 2015 has estimated the total coal production
and steel production in India for the future years, steel) was used. This ratio was based on the actual
till 2051. Using this data for total coal and steel 2011 domestic iron ore consumption of 117 MT to
production in India from the recent TERI analysis produce 60.51 MT of finished steel (12th Annual
(TERI 2015) for future years and employing the same Five Year Plan, Iron and Steel). However, for the past
emission factors mentioned in the methodology years (2001, 2006) and the base year 2011, the actual
section, the emissions were estimated for future years production numbers (from Ministry of mines for iron
(Figures 4.32 and 4.33). For estimating the amount of ore and coal directory for coal) were used.
iron ore mined from the projected steel production in As evident from Figures 4.32 and 4.33, the total
future years, the ratio of 1.93 (of iron ore to finished emissions from open-cast mining of coal and iron ore

Figure 4.32: Annual emission trends from 2001 to 2051 in India from open-cast coal mining sector
 Industries • 77

Figure 4.33: Annual emission trends from 2001 to 2051 in India from iron ore open-cast mining

in India have an increasing trend over the years. In data from MoSPI, 2011. However, for some of the key
future also, they are expected to be growing further sectors such as Cement, Iron & Steel, the emission
considering the growing demand for coal and iron are allocated at the grid locations using the actual
ore as raw material for various industrial sectors as coordinates of the manufacturing plants. The
well as for generating power. emissions maps for industrial emissions for PM10 and
SO2 emissions are shown in Figure 4.34.
Total Emissions from Industrial Sector The PM10 emissions from coal and iron ore mining
in India sectors in India where also allocated spatially using
the mining data of coal and iron ore in different
Total emissions (process , combustion, and fugitive)
districts. The amount of coal or iron ore mined from
from the industrial sector are shown in Table 4.19.
While, there is some control of PM emissions envisaged
in the future scenario, the gaseous pollutants in Table 4.19: Total Industrial Sector Emissions (kilotonnes) in India
absence of control standards, are expected to grow Pollutant 2001 2011 2021 2031 2041 2051
multi-folds in future. The majority of emissions are from
PM10 3685 4562 10212 13953 15230 15093
coal consumption in industries. Highest increase of
PM2.5 1923 2351 5507 7816 8706 8546
about six times is expected in NOx and SO2 emissions,
while other pollutants will increase by 2.6–5.4 times BC 44 62 88 113 138 161
during 2011–51. OC 63 90 143 198 248 290
NOx 520 950 1980 3405 4877 6038
Spatial Allocation of Emissions SO2 1901 3160 6070 10118 14478 18147
The estimated emissions are spatially allocated to the CO 3196 5229 9921 16751 23370 28335
district levels using the industrial fuel consumption HC 74 115 194 305 425 532
78  •  Air Pollutant Emissions Scenario for India
these districts was used to distribute emission loads of fuels, high ash content, and limited control of
in these districts. The emission maps from mining pollution are the major causes for high emissions
sector for PM10 emissions are shown in Figure 4.35. from the sector. The emissions are expected to
Since mining is limited to few states in India, most grow in future with rise in manufacturing activities.
of the regions in the map show nil emissions and However, it is also expected that in future there
only in the districts where coal or iron ore mining will be better enforcement of the standards with
was prevalent in 2010–11, the emissions have been enhanced penetration of the APC technologies. For
distributed based on activity level. this, there is an urgent need for capacity building
Emission from brick industry in India are spatially and strengthening of the pollution control boards
distributed based on major regions of brick for better enforcement of standards. There is also
manufacturing as shown in Figure 4.21. The main a need for development of standards for gaseous
regions for brick manufacturing are located in the pollutants such as NOx and SO2, which are increasing
Indo-Gangetic plains, Gujarat, West Bengal, and some gradually with the growing industrial production.
regions of west and south of India (Figure 4.36). Many of these gaseous pollutants such as NOx not
only just have their own health impacts, but they
Conclusions also lead to secondary pollutant formation such as
Industrial emissions are substantial and are of Ozone and secondary particulates.
important concern to India. Inefficient combustion

Figure 4.34: Spatial distribution of PM10 and SO2 emissions from industrial sector in India in 2011
Note: Brick and mining sector emissions not included
 Industries • 79

Figure 4.35: Spatial distribution of PM10 emissions from coal and iron ore mining in India in 2011

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Consumption and Future Challenges of Coal in India. TERI 2015, Energy Security Outlook, The Energy and
Int. J. Curr. Engg. Tech., 4 (5). URL: http://inpressco.com/ Resources Institute, New Delhi
category/ijcet
World Bank 2015, GDP ranking, PPP based, URL: http://
Rajarathnam U., Athalye V., Ragavan S., Maithel S., data.worldbank.org/data-catalog/GDP-PPP-based-
Lalchandani D., Kumar S., Baum E., Weyant C & Bond T., table
2014, Assessment of air pollutant emissions from brick
kilns, Atmos. Environ. 98, 549-553.
CHAPTER 5
Power
Richa Mahtta, Sumit Sharma, and Atul Kumar

Introduction
Power sector in India is undergoing a rapid
change not only in terms of installed capacity and
transmission and distribution, but also with the
introduction of advanced technologies such as
deployment of supercritical technology. The total
power generating capacities of utilities and non-
utilities in India have grown from 1,362 MW in 1947
to 243 GW in 2014. However, demand of power has
crossed the production levels leading to shortages in
the country. At consumer level in utilities, industries
are the largest consumer of electricity with a share of
45 per cent, followed by domestic (22 per cent), and
agriculture (18 per cent) sectors. Efforts are underway
to bridge the gap of demand–supply of electricity
by increasing the share of renewables, private sector
participation, and improved governance.
In India, more than 50 per cent of this electricity
production (utilities) is met through coal-
based thermal power plants (TPP) (Singh and
Siddique 2013; TERI 2015). To meet the electricity Photo Credit: R Suresh
84  •  Air Pollutant Emissions Scenario for India
requirements, huge quantity of coal is burnt Power Generation in India
annually. In 2010-11, around 360 MT of coal was
Indian Power Sector, with an electricity generation
burnt that produced around 100 MT of fly ash and
capacity of 243 GW as on March 2014, is the fourth
25 MT of bottom ash annually (CEA 2012) which is
largest producer in the world. Despite a growth
one of the major reasons for increasing air pollution
of 11.75 per cent in the total installed generating
levels in India (Bhanarkar et al. 2008; Guttikunda and
utilities in power sector during 2012–13 and 15
Jawahar 2014; Ohara et al. 2007). Guttikunda and
per cent in 2011–12, there are still gaps in demand
Jawahar 2014, reported that TPP produced 1,200
and supply (CEA 2013). In 2013–14, there was
kt of PM10 emissions in the year 2010–11. Also, SO2
4.2 per cent shortfall of energy as shown in Table 5.1.
emitted from TPP is a major source of environmental
pollution and has huge impact on health and
Table 5.1: Energy Status in India (2013–14)
agriculture (Burney and Ramanathan 2014). Similarly
NOx emissions from power plants in India have Energy (GWH) Peak (MW)
increased by 70 per cent during 1996–2010 (Lu and Requirement 1,002,257 135,918
Streets 2012), which is a prime precursor for Ozone Availability 959,829 129,815
formation in India. Shortage 42,428 6,103
PM emissions from coal-based TPP are linked
Shortfall 4.2% 4.5%
to high ash content (30–50 per cent) in Indian coal
along with 7–20 per cent moisture content (Shail et
Of the total power produced in India, coal power
al. 1994). Ash, being a non-combustible part of the
plants makes up for 57.42 per cent of the installed
coal, if present in large quantity, increases the coal
capacity in India, followed by hydro (18.62 per cent),
demand to produce the same amount of electricity.
renewable energy sources (12.2 per cent), natural
This leads to increased specific coal consumption
gas (8.92 per cent), nuclear plants (2.25 per cent), and
in power plants in India. Specific coal consumption
oil (0.56 per cent) (CEA 2013; Pryas 2011). Electricity
(SCC) for TPP in India during 2011–12 was 0.72 Kg/
production from different energy sources in India in
KWh and it varied from 0.60 (Ramagundam Thermal
past three decades is shown in Figure 5.1(a).
Power Station in Andhra Pradesh) to 1.28 for
Power generation using coal has grown
Bhusawal plant in Maharashtra (CEA 2012). However,
significantly from 100 TWh in 1980 to around 670
due to high calorific value of imported coal, SEC for
TWh in 2012. The projections of future energy
imported–coal based TPPs is comparatively quite
demands and coal consumption for power
less. For example, Torangallu TPP has a SEC 0.33 Kg/
generation in India are made using the TERI-MARKAL
KWh. High SECs of Indian TPP leads to high emission
model. It is observed that coal consumption in power
levels too. Although Electrostatic precipitators (ESPs)
plants will continue to grow in future (Figure 5.1(b) as
are installed in all the TPP, but the efficiencies and
per the reference scenario (RES) (TERI 2015).
inspection and maintenance system for these units
The share of natural gas and hydroelectric plants
is a major concern. Also, emission standards are
has increased in electricity production in India after
only available for PM in India for TPP. There are no
1990. But as evident from the Figures 5.1(a) and (b),
standards available for NOx, SO2, CO, etc. pollutants
despite growth of other sectors and renewables, coal
from TPP.
will remain to be the major fuel used for electricity
This chapter briefly present review on available
production in India. Thus, emissions from the sector
literature on methods used to compute emissions
are expected to increase in future.
from coal-based TPP, available emission factors from
existing studies, and emissions computed using unit-
based approach.
 Power • 85

Figure 5.1(a): Electricity production from all energy Figure 5.1(b): Present and future projections of coal
sources in India consumption in power sector in India

Sources: The Shift project Data Portal; Baseline: CEA 2012, Future projections: TERI 2015 Markal Model

Methodology for Emission control technology, and geographical location of

Estimation from Power Generation each unit types in China. Chen et al. (2014) calculated
emissions of SO2, NOx, and PM10 and PM2.5 for entire
Sector in India China for the year 2011 to be 7,251 kt, 8,067 kt, 1,433
Different approaches have been used across the kt, and 622 kt, respectively, using unit-based approach.
world to estimate emissions from power sector. Emission factors (kg/ton) for different pollutants
The approaches used for emission estimation are used in all these studies are summarized in Table 5.2a.
conventionally classified as bottom-up and top- Table 5.2b provides emission factors for different
down approaches. In the past two decades, a series pollutants from gas-based power plants (GAINS Asia
of studies have been carried out using top-down database).
method to compute emissions of PM, NOx, and SO2
(Hao et al. 2002; Purohit et al. 2010; Streets et al. 2003; Unit-Based Methodology in this
Tian 2003; Wang 2001; Yi 2006; Zhang et al. 2007 a, b).
Study
However, all of these studies focused on power
In this study, a unit-based approach is adopted to
sector as a single source in the emission inventory
compute emissions from power sector. All the TPP in
framework. Over time, it was felt that different
India are taken into account to calculate emissions
technologies and fuel characters among specific
from the sector. Emissions from power plant are
power units can greatly affect emission levels from
dependent on the quality of fuel (ash and sulphur
power sector (Zhao 2008). Following this, unit-
content), type of boilers, the type of air pollution
based bottom-up approach came into practice.
control equipment, and their efficiencies.
In this approach, annual emission of each unit is
The equations (5.1–5.3) used for emission
calculated based on emission factor and specific
estimation are listed below
fuel consumption of each unit. These emissions are
EPM= ∑Pj × ACj × (1–ar)× f ×(1–Cj) ............................ (5.1)
then aggregated at regional level. Zhao et al. (2008)
ENOx= ∑Pj × EF × (1-Cj) .................................................... (5.2)
calculated SO2, NOx, and PM emissions over 31
ESO2= ∑Pj × EF × (1-Cj)..................................................... (5.3)
provinces of China using this approach for the year
2005. It was based on detailed information on fuel,
86  •  Air Pollutant Emissions Scenario for India

Table 5.2(a): Different Studies Reporting Emission Factors for Coal-Based Power Generation Activity in India
Source Year Units PM10 PM2.5 SO2 NOx
Streets et al. (2003) 2000 kg/ton 4.04–7.69 2.22–5.68
Ohara et al. (2007) 2000 kg/ton 5.09 2.71
Garg et al. (2006) 2000 kg/ton 2.54 3.71 2.07
GAINS (2012) base 2000–05 kg/ton 0.18–3.78 0.54–2.64 0.70–13.94 1.01–2.73
GAINS (2012) controlled 2000–05 kg/ton 0.19–0.43 0.13–0.27 0.27–0.70 0.20–0.55
Lu and Streets (2012) 1996–2006 kg/ton 1.79–4.14
Guttikunda and Jawahar (2014) 2010-11 kg/ton 0.91–1.39 0.49–0.69 1.76–1.94 1.79–1.81
Zhao et al. (2008) 2005 kg/ton 6.17–11.75
Uncontrolled
Control kg/ton 4.07–11.17
Zhao et al. (2010) uncontrolled 2005 kg/ton 0.26–1.54A 0.1–0.45A 13.0S–18.0S 5.30–9.90
A= Ash Content S= sulphur content
Zhao et al. (2010) controlled 2005 kg/ton 0.008A–0.034A 0.9S–15.0S 3.50–6.81
Chen et al. (2014) 2011 kg/ton 0.021A–0.064A 4.08–11.50
Controlled
This study (uncontrolled) 2015 kg/ton 0.12-3.46** 0.38** 4.86* 2.23*
*Emission factor (EF) for NOx and SO2 have been adopted based on various studies.
**For PM10 and PM2.5, EF has been calculated by using unit level approach based on ash content and efficiency of ESPs.

Table 5.2(b): Emission Factors for Gas-Based Power Plants AP-42 as 20 per cent. The size fractions of the PM
emissions are again adopted from USEPA (2015)
   EF (t/PJ
for the pulverized coal-fired, wet-bottom boilers.
PM10 0.10 A ratio of 0.4 is used for PM2.5 to PM10 and 0.75 for
PM2.5 0.10 PM10 to total suspended particulates (TSP). Ratios
NOx (with selective catalytic reduction [SCR]) 10.00 of black carbon (BC) and organic carbon (OC) to
CO 10.00 PM2.5 are adopted from GAINS database as 0.12 and
0.19, respectively.
HC 1.00
After expert consultations, it is concluded that
Source: GAINS Asia Database
all the TPP in India are equipped with ESPs as the
air pollution control equipment. ESP efficiencies for
Where, P= coal consumption, AC = ash content of 40 units have been adopted from Chandra (2008)
fuel, ar = ratio of bottom ash to total ash, C = efficiency and for rest of the plants an average efficiency
of control equipment, f = particulate mass fraction by has been assumed. For future scenario, coal
size, EF = unabated emission factor, j = power plant consumption has been projected using the TERI
units in India. MARKAL model (TERI 2015). In this study, emission
Activity data viz. coal consumption in each power factors for SO2 and NOX are taken as 4.86 kg/ton and
plant (102 in total) for the year 2010–11 has been 2.23 kg/ton, respectively (based on existing studies
taken from CEA (2012) database. Plant-wise ash for India). Emission factors for carbon monoxide (CO)
content data has also been taken from CEA. Expert and hydrocarbons (HC) are adopted from GAINS Asia
consultations were held to understand the type of database.
boilers. Ratio of bottom to fly ash is adopted from
 Power • 87

Control Measures generated from coal handling units and ash ponds
still comprise around 20 per cent of the PM emissions
Sulphur emission–control system ranges from
(UE and CAT 2015). For control of these emissions,
limestone injection through control in furnaces, wet
the government has notified certain guidelines.
scrubbing of flue gas, or high-efficiency regeneration
To control fugitive emissions from coal handling,
process (by capturing SO2 in the flue gas through
MoEF&CC issued a notification in June 2001 that
industrial processes). Limestone injection process
specifies the TPP located beyond 1 km from pit heads
produces huge amount of waste material. On the
and the ones located in urban and sensitive areas are
other hand, high-efficiency regeneration process is
required to use beneficiated coal containing ash not
very expensive. Wet flue gas desulphurization (FGD)
more than 34 per cent. Further, to control fugitive
units are the most commonly used process with
emissions from ash ponds, MoEF mandated through
sulphur removal rate of 90 per cent. There are only
a notification in 2003 that brick kiln units coming up
four TPP in India that have FGD units in operation
within 100-km radius of TPP have to use 25 per cent
(Guttikunda and Jawahar 2014; Prayas 2011). Among
of ash in brick kilns and any construction in the same
those, three are in Maharashtra and one in Karnataka.
radius will use only fly ash bricks (Guttikunda and
PP Tata Power in Trombay (Maharashtra)
Jawahar 2014).
PP BSES/Reliance at Dabanu (Maharashtra)
PP Jindal TPP at Ratnagiri (Maharashtra)
PP Udupi TPP (coastal Karnataka)
Emissions from Thermal Power
Generation in India
Till 2020, seven TPP which are just 3.2 per cent Emissions from TPP are estimated and are presented
of the total thermal power capacity in India have in Table 5.4. PM10 emissions are estimated to be about
been granted clearance for installation of FGD units. 453 kt from coal-based power plants in India for the
However, this is to be noted that the coal used in year 2011. Of which, around 181 kt are PM2.5, 22 kt
India is low in sulphur content (~0.5 per cent). black carbon, and 34 kt organic carbon emissions.
For NOx emissions, there are no existing norms For the same year, SO2 and NOx emissions are 1,842
in India for coal-based power plants for control of kt and 1,015 kt, respectively. Due to lack of stringent
emissions. The formation of NOx emissions depends regulations on SO2 and NOx emission in past, their
on the temperature and residence time of the gases emissions are considerably high. As envisaged, a
in the combustion chamber. Formation of NOx can minor capacity (3.2 per cent) will be installed with
be reduced by providing low nitrogen oxide burners. FGD units for control of SO2 emissions, which is
Only a few newly installed TPP and extensions have accounted in projections of SO2 emissions till 2020.
low NOx burners (Chikkatur et al. 2011; Guttikunda However, MoEF&CC, Government of India has issued
2014). However, as per the new draft notification
Table 5.3: Emission Standards (mg/Nm3) for Coal-Based TPP
issued by Ministry of Environment, Forest and Climate
Capacity of TPP PM NOx SO2
Change (MOEF&CC), Government of India, new norms
for control of SO2 and NOx have been prescribed, Existing
which will force the use of pollution control devices <210 MW 350 No standards No standards
for these pollutants in future years (Table 5.3). >210 MW 150 No standards No standards
Presently, PM is the only pollutant for which Indian Proposed standards in draft notification by MOEF&CC, 2015
emission standards exist for coal-fired TPP in India. Plants before 2003 100 600 600/200
Particulate emissions from a power plant can be Plants between 2003 50 300 200
categorized into flue gas emissions and fugitive dust and 2006
emissions. ESPs are installed in all the TPP to remove Plants after 2017 30 100 100
flue gas emissions. However, fugitive dust emissions Source: Guttikunda & Jawahar, 2014); MoEF & CC, 2015
88  •  Air Pollutant Emissions Scenario for India

Table 5.4: Emissions from Coal-Based Power Plants in India (kt/ power plants. The gas-based power plants are
yr) for 2001–51 required to maintain NOx standards and are generally
2001 2011 2021 2031 2041 2051 equipped with control equipment.

PM10 257 453 869 1016 1216 1353

PM2.5 103 181 348 406 486 541
Spatial Distribution
Emissions from power plants in India are spatially
BC 12 22 42 49 58 65
put on the map of India using actual coordinates of
OC 20 34 66 77 92 103
the power plant facilities (Figure 5.2). The emissions
SO2 1031 1842 3490 3981 4650 5108 are observed to be higher in the states of West
NOx 570 1015 1928 3556 5773 7293 Bengal, Orissa and Chhattisgarh, and Maharashtra.
CO 19 34 65 120 194 246 This can be due to higher coal consumption and
NMVOC 4 7 13 24 39 49 lower efficiencies of control equipments in the power
plants.
draft notification for revised emission standards for
coal-based TPP. Along with PM10, standards for SO2, Comparison with Other Studies
NOx, and Hg have also been introduced. The new
The emission estimated in this study is compared
emission limits are 83 per cent more stringent for
with other studies for validation purpose (Table 5.6).
power plants envisaged after 2017 in comparison
Particulate emissions calculated in this study are
to those established before 2003. Final guidelines
are expected to come in force in near future and
have been taken into account while estimation of
emissions for future years.
It is evident that under the RES scenario (TERI
2015) of future projections, despite an increase of
more than 7 times in the coal consumption, the PM
emissions from power sector will increase by about
three folds during 2011–51. The gaseous pollutants
show even lesser increase due to consideration of
stringent norms for NOx and SO2 controls in future
from the power plants. Other than coal-based power
generation, emissions are also estimated for gas
power stations. Table 5.5 shows the emissions of
different pollutants from gas-based power stations.
This is to be noted that PM emissions are insignificant
in comparison to the emissions from coal-based

Table 5.5: Emissions from Gas-Based Power Plants in India (kt/

yr) for 2001–51
  2001 2011 2021 2031 2041 2051
PM10 0.04 0.10 0.07 0.09 0.13 0.40
PM2.5 0.04 0.10 0.07 0.09 0.13 0.40
NOx (with SCR) 3.72 9.61 6.95 8.69 12.60 40.30
CO 3.72 9.61 6.95 8.69 12.60 40.30
Figure 5.2: Spatial distribution of PM2.5 emissions
HC 0.37 0.96 0.69 0.87 1.26 4.03 from power plants in India (2011)
 Power • 89

Table 5.6: Comparison of Emission Estimates (kt) with Other Studies in TPPs. Along with PM10, standards for SO2, NOx, and
Hg emissions has been introduced. Emission limits
Studies Year PM10 PM2.5 SO2 NOx
set for the TPPs are under major discussion as new
IIASA (2010) 2010 268 3396 1821
standards have taken into consideration the stringent
Guttikunda and Jawahar. 2011 1200 580 2100 2000 standards only for newly constructed units. Standards
(2014)
are still very high for older units. Final guidelines are
Mittal (2009) 2009 3800 2300 expected to come in near future.
This study 2011 453 181 1842 1015 Other than through regulation and introduction
lower compared to other studies. The main reason of standards, there are strategies that could be
could be the different plant-wise ESP efficiencies employed for control of emissions from power plant.
taken into account while estimating the emissions. PP Coal beneficiation—reduction of ash content
On the other hand, NOx emissions are in close range PP Regular monitoring and maintenance of ESPs and
with other studies as no specific air pollution control other control systems
equipments APCE’s are assumed to be installed. PP Introduction of control technologies (such as
Although, the estimates are derived from actual unit FGD units) should be made mandatory in all
level data, the accuracy of the estimated emissions the plants for control of SO2 as FGD not only
could be further enhanced with the use of more helps in reducing SO2 to a higher extent but also
detailed studies on emission factor development for significantly reduce toxic heavy metals such as Hg,
power plants in India. Moreover, regular updating of which are not usually trapped by ESPs and affect
data on efficiencies of control equipments such as the efficiency of boilers.
ESPs can also help to improve the accuracy. PP Introduction of technologies such as SCR for
control of pollutants such as NOx emissions.
Conclusion PP Demand control measures to reduce loads on
power plants.
The demands for power are increasing at a rapid rate.
PP Shift towards renewable or cleaner sources of
Power generation sector in India is heavily dependent
power generation.
on coal, which makes it emission intensive. However,
air pollution control technologies (ESPs) are
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CHAPTER 6
Transport
Sumit Sharma, Atul Kumar, and Sarbojit Pal

Introduction Total registered vehicles in India has grown from

Air pollution is a serious concern especially in the 5.3 million in 1981 to 159 million by 2012 (MoRTH,
urban areas of India. Source apportionment studies 2013). However, not all registered vehicles are fit
have highlighted many sources of air pollution to ply on road. Figure 6.1 shows the estimates of
in urban centres, and emissions from growing on-road vehicles in India that have grown from
number of motor vehicles play an important role 4.4 million in 1981 to about 96 million by 2011.
in the increasing pollutant loads in the cities. This The numbers are projected to grow to 427 million
is particularly important in India, which has one of by 2031 and 933 million by 2051. Private vehicle
the most critically polluted cities in the world. To ownership in particular has grown from 6 per 1,000
add to its woes, India has seen very rapid growth in people in 1981 to 75 in 2011. This is expected to grow
vehicles, especially across its urban centres that has to up to 258 per 1,000 population by 2031, and 461
contributed to increase in particulate emissions by 2051.
from vehicular sources; accounting for up to 50 per The distribution of vehicles in Figure 6.2 shows
cent in the particulate matter less than 2.5 microns that the share of two-wheelers has grown rapidly
(PM2.5) concentrations in a city like Bangalore (CPCB, during the period 1981–2011. However, in future with
2010). These PM2.5 emissions from diesel vehicles growth in economy, the share of cars will grow and
are critically important given that the World Health will increase from 15 per cent in 2011 to about 18 per
Organization (WHO) has recently classified diesel cent by 2031 and 24 per cent by 2051.
engine exhaust as carcinogenic to humans since Presently, the transport sector is the second largest
exposure to these emissions is associated with consumer of commercial energy in the country.
increased risk of lung cancer. Growth of transport sector increases the dependence
94  •  Air Pollutant Emissions Scenario for India

Figure 6.1: Year-wise on-road vehicular stock in India (TERI MARKAL model estimates)

Figure 6.2: Distribution of on-road vehicles by type in past and future years (TERI MARKAL model estimates)

on imported crude. The sector is expected to grow at scenario (RES) in TERI 2015, the energy consumption
a steady rate for the next few decades. With further in the sector is expected to grow from about 3.6
growth projected in future, the energy consumption thousand PJ to more than 15 thousand PJ by 2031,
is expected to increase considerably. In reference and further to about 37 thousand PJ by 2051 (Figure
 Transport • 95
6.3). Currently, about 43 per cent of energy in road categories of vehicles based on their classes under
transport sector is consumed by heavy and light various emission control categories, that is, Euro-I
commercial vehicles (HCV and LCVs), followed by 23 to Euro-VI. ARAI (2008) also carried out a series of
per cent by buses. The share of private vehicles in measurements to ascertain indigenous emission
energy use is expected to increase from 11 per cent factors for different categories of vehicles in Indian
in 2011 to about 19 per cent by 2051. The share of conditions. A vehicle-wise comparison of emission
buses in energy use will reduce from 21 per cent to factors from the three sources is shown in Figure 6.4.
just 5 per cent in the same period of time. Increased It is evident that while the emission factors are more
energy consumption may lead to higher emissions or less in similar ranges, while there are considerable
of air pollutants in comparison to current levels, in a differences in some categories. The most recent
stagnant emission control scenario. measurements in Indian context is reported in ARAI
dataset, which shows higher emissions for heavy-
Methodology for Emissions duty vehicles. However, lower emissions factors are
Estimation derived from ARAI in case of two-wheelers categories.
This is to be noted that ARAI (2008) reports emission
The transport sector emissions are estimated using
factors in gram per kilometre units, which have been
the basic approach of emission factors.
converted to gram per kilojoules based on typical
Emissions = Energy use (PJ) × No control emission
vehicle mileages. Energy consumption estimated for
factor (kt/PJ) × (1 – Percentage of Bharat Stage
the sector is compared and validated with actual fuel
emission control)
consumption estimates reported by MoPNG.
The emission factors for this exercise have been
PM emissions are also estimated for four different
adopted from primarily three sources. CPCB (2000)
fractions namely, PM10, PM2.5, Black Carbon (BC) and
reported emissions factors for various categories of
organic carbon (OC). The shares of BC and OC in PM10/
vehicles with varying vintages. GAINS Asia database
PM2.5 fractions are adopted from EPA (2012).
provides a database of emission factors for different

Figure 6.3: Growth in energy consumption (PJ) in transport sector in India

Source: MARKAL model results, TERI (2015)
96  •  Air Pollutant Emissions Scenario for India

Figure 6.4: Comparison of PM emission factors from GAINS, ARAI (2008), and CPCB (2000)

Important Aspects Affecting importantly, the heavy-duty trucks (which are the

Emissions from the Transport largest contributor to vehicular emissions) (Sharma

et al. 2014) need to move all across the country
Sector and hence, remained on BS-III standards across the
Other than the emission factors, there are number country, despite BS-IV norms introduced in some
of aspects which affect energy consumptions and cities. Another Auto Fuel Vision Committee was set
emissions from the transport sector in India. Each of up in 2013 to recommend the future roadmap on
these are discussed in subsequent sections. advancement of fuel quality and vehicular emission
standards up to 2025. The committee recommended
Fuel Quality and New Vehicle Emission that BS-IV and BS-V norms be introduced across the
Standards country by 2017 and 2020, respectively (AFV 2014).
The road map suggested in Auto Fuel Policy 2002 and
The quality of fuel plays an important role in
the current recommendations of the Auto Fuel Vision
determining the tail-pipe emissions of pollutants
2025 Committee on the future road map of auto fuel
from vehicles. The sulphur and benzene content
emissions are shown in Table 6.1.
in fuels not only affect the emissions of SO2 and
However, it is to be noticed that the roadmap
hydrocarbons but also contribute to secondary
recommended by the Auto Fuel Vision 2025
particulate formation. The Auto Fuel Policy of 2002
Committee would also keep India almost 10 years
of Government of India (MoPNG 2002) laid down a
behind the US and European countries. Although,
roadmap till 2010 for introduction of cleaner fuels
recently the BS-IV fuel quality norms have been
and vehicles in the country. Under this, 13 selected
announced to be introduced in most regions of the
cities were gradually moved to BS-IV norms by 2010,
country by 2016, the automobile manufacturers have
while rest of the country reached BS-III norms. This
shown their reluctance in moving to the BS-IV norms
led to the establishment of one set of ambient air
for heavy-duty vehicles with the immediate effect.
quality standards to determine the quality of air, and
The usefulness of BS-IV fuel can only be realised if the
dual standards for vehicle emissions and fuel quality.
manufacturers start supplying the BS-IV complaint
It was observed that the rate of increase in PM10
heavy-duty trucks and buses in the country. Moreover,
concentrations was much higher in cities where lower
the lowest emission levels can only be achieved with
quality fuel was provided (Sharma et al. 2014). More
 Transport • 97

Table 6.1: Road Map Suggested in Auto Fuel Policy 2002 and the Current Recommendations of the Expert
Committee

Category Bharat Stage II Bharat Stage III Bharat Stage IV Bharat Stage V
Two and Three wheelers Entire country April 2005 Entire country April 2010 Entire country April Entire country April 2020
2016
All other new vehicles Entire country April 2005 Entire country April 2010 Entire country Entire country 2020–2021*
11 cities—April 2003 11 cities—April 2005 2017*
11 cities—April 2010
(20 cities )
No road map beyond
2010
*Suggested by the new Auto Fuel Vision 2025 Committee in 2014.

a move to BS-V quality of fuel (10 ppm sulphur) and Road transport now accounts for nearly 66–68
BS-VI vehicular emissions standards for vehicles. Till per cent of the total freight and 82–84 per cent of
date the Ministry of Road Transport and Highways, the total passenger traffic shares. The share of the
(Government of India) has notified BS-IV and BS-V energy efficient railways in freight movement have
emission norms. Based on the current scenario, the reduced from over 80 per cent in 1950–51 to about
business as usual scenario in this study assumes 35 per cent in 2011–12, while the share of railways in
adoption of BS-IV norms by 2016 and BS-V from 2021. passenger traffic has reduced from over 50 per cent
to barely 14 per cent in the same period. The shares
Growth of Private Vehicles vis-à-vis of traffic on inland water ways and coastal shipping,
Enhancement of Public Transport which are the most efficient forms of transport, have
almost declined to oblivion (Ramanathan et al. 2014).
One of the prime factors for emissions from the
Without a conscious effort to increase the share of
transport sector is the rapid growth of private
efficient transport modes, India is going to witness an
vehicles. Ghate and Sundar (2013) showed that
increase in energy intensity in the transport sector.
the average level of private car ownership in India
could grow from 13 per 1,000 population to 35 by
2025. While, growing number of vehicles has serious
State of Public Transport in India
implications for energy security, road safety, and The public transport scenario in India paints a grim
equitable allocation of road space, it also adds to the picture. Most Indian cities are not equipped with
pool of air pollutants. Increasing private vehicles in effective public transport systems to meet their
India is linked to growing income levels, aspirations, demand for mobility. The share of buses in the overall
and limited public transport. There is a lot to learn fleet of registered vehicles have declined from 11 per
from the experiences of some cities like Singapore, cent in 1951 to just 1 per cent in 2011 (PC 2014). The
Hong Kong, etc. to decouple vehicle ownership decline has been found to be rapid in the last decade
with economic growth. The success of these cities mainly due to enormous growth of private vehicles.
hinged on having efficient public transport systems Government of India launched the National Urban
to cater to the growing demands of mobility. Indian Transport Policy (NUTP) in 2006 to improve the health
cities have however been moving in a different of the urban transport systems across the country.
and unsustainable direction as compared to these NUTP identifies a number of public transport options
international cities. The share of efficient mass such as metro-rail (Delhi, Hyderabad, Mumbai, etc.)
transport modes have continuously gone down and bus rapid transit systems (Ahmedabad, Jaipur, etc.)
across most Indian urban centres. other than the existing suburban rail and bus systems
98  •  Air Pollutant Emissions Scenario for India
for mass transport solutions in cities. The Ministry of could be mainly due to wear and tear, lack of proper
Urban Development also launched the Jawaharlal maintenance, engine faults, or misuse at the hands
Nehru National Urban Renewal Mission (JNNURM) to of the driver, amongst other causes. This also points
provide financial assistance to cities for development to the fact that mere switching to advanced new
of projects for improving urban mobility. The NTDPC vehicle standards will not suffice and in-use vehicle
report recommends a dense integrated system of management should go hand in hand.
transport for Indian cities. While metro rail systems can Presently, the only in-use vehicle testing
be considered for big cities with careful examination, conducted in India is the Pollution-Under-Control
bus-based systems are absolutely essential for (PUC) programme, which is based on idle test
small and medium cities. In addition to these, the emission limits without any loaded mode tests.
Government of India has recently launched the Smart These idle mode tests do not reflect the real-life
Cities Program and the AMRUT Scheme for India under situation of a vehicle running on the road. Moreover,
which urban transport finds special significance. despite a provision of heavy penalties, merely 21 per
cent of vehicles appear for PUC testing in Delhi (Sita
In-use Vehicle Management System Lakshmi et al. 2014). The current situation is not so
While improvements have been made through effective in control of emissions and does not ensure
introduction of emission standards for new vehicles, on-road compliance despite compliance during
there are limited efforts being made in India to manufacturing stage.
control emissions from in-use vehicle fleet. This
requires an effective inspection and maintenance
Congestion and Improving Driving
system to check and tune the vehicles to comply Cycles
with the prescribed standards. Worldwide, it has been Internationally, and now in 10 Indian cities, Sharma
reported that on-road vehicles emit much higher et al. (2016) has observed that there are considerable
levels of pollutants during their lifecycle as compared differences between driving cycles on which vehicles
to the limits set during their certification stage. This are initially tested (for type approvals) and real-

Figure 6.5: Comparison of driving patterns observed in 10 Indian cities with the prescribed driving modified
Indian driving cycle ((MIDC)) for emission testing for cars in India
 Transport • 99
world driving conditions (Figure 6.5). The real world made and presented in subsequent sections . It is to
driving patterns observed in 10 cities highlight be noted that ARAI (2008) emission factors are used
two issues. Firstly, there is a problem in the current to derive emission estimates; however, the variations
testing procedures, which may lead to higher on- using other emission factor datasets is also presented
road emissions despite compliance with testing in subsequent section ‘Comparison of Emission
procedures and limits. This means that the vehicles Estimates with Other Studies’. For future emission
may comply with emission regulations, but may norms, reduction factors are adopted from GAINS
emit much more under real-world conditions, hence Asia Database.
making the policy ineffective. The second issue
highlighted in the TERI study of 10 cities is of very NOx Emissions
high congestion levels, which could lead to loss NOx emissions from vehicles grew by more than
of time, fuel, and enhanced exposure to very high two times during 2001–11 from 1164 kt to 2665 kt,
emission levels (Sharma et al. 2013, 2016). The driving with heavy-duty vehicles having the biggest share.
patterns show very low driving speeds mainly on The emissions are expected to grow further by 1.5
account of congestion. City specific strategies will be times till 2031 and 2.3 times by 2051 (Figure 6.6).
required to address and improve the traffic flows. This Figure 6.7 shows that introduction of BS norms have
will not only reduce exposure to emissions but also arrested the growth of NOx emissions in India. BS-I/
could save fuel and time. II emission norms led to a reduction of 21 per cent
NOx emissions by 2051 in comparison to the no-
Baseline and Future Emission control scenario. Further, introduction of BS-III and IV
Inventory norms in 2011 and 2016 would lead to a reduction of
Based on the energy consumption (Figure 6.3), the 62 per cent NOx emissions by 2051. The RES scenario
emission factors (Figure 6.4) and factors described in assumed in this study takes into account the current
section ‘Important Aspects Affecting Emissions from notification and assumes the introduction of BS-V in
the Transport Sector’ that affect vehicular emissions 2021. This leads to an overall reduction of 78 per cent
in India, pollutant-wise emission estimates are in comparison to the No control scenario.

Figure 6.6: Past and projected growth of NOx emissions (kilotonnes per year) in India (2001–51)
100  •  Air Pollutant Emissions Scenario for India

Figure 6.7: Effect of introduction of vehicle emission norms (BS-I to BS-IV) on NOx emissions in India
NOC refers to a scenario without any emission norms in the sector

PM Emissions to an overall reduction of 97 per cent in comparison to

the no control scenario in 2051.
Emission estimates are prepared for different fractions
The PM2.5 emissions are speciated into BC and OC
of PM emitted from various vehicle categories.
components using factors from EPA (2012). The BC
The emission estimates of PM2.5, BC, and OC are
emissions are dominated by diesel driven vehicles
presented in Figures 6.8, 6.10, and 6.11. PM2.5
with BC to PM2.5 ratios of 0.73–0.77. BC emissions from
emissions grew from 191 in 2001 kt to 276 kt in
the transport sector are first expected to grow till
2011. Heavy-duty vehicles have the biggest share in
2031 and then go down from 197 kt to 111 kt during
the current emissions. The emissions are expected
2011–51 (Figure 6.10 ).
to increase till 2021 and are expected to reduce
Other than major contributions from diesel
thereafter with introduction of BS-V norms (Figure
driven vehicles, the organic carbon fraction receives
6.8). Figure 6.9 shows that introduction of BS norms
contributions from gasoline driven private vehicles.
have arrested the increase of PM emissions in India.
The OC emissions from the transport sector are
BS-I/II emission norms led to a reduction of 49 per
expected to go down from 70 kt to 35 kt during
cent PM emissions by 2051 in comparison to the no-
2011–51, due to introduction of BS-V norms (Figure
control scenario. Further, introduction of BS-III and IV
6.11).
norms in 2011 and 2016 would lead to a reduction of
83 per cent PM emissions by 2051. The BAU scenario
Carbon Monoxide
assumed in this study takes into account the current
recommendations of the expert committee and Carbon monoxide gas is released due to incomplete
assumes the introduction of BS-V in 2021. This leads combustion of fuel. Gasoline engines have higher
emission factors in comparison to diesel vehicles. The
 Transport • 101

Figure 6.8: Past and projected growth of PM2.5 emissions (kilotonne per year) in India (2001–51)

Figure 6.9: Effect of introduction of vehicle emission norms (BS-I to BS-IV) on PM2.5 emissions in India
 Figure 6.10: Past and projected growth of BC emissions in India (2001–51)

Figure 6.11 Past and projected growth of OC emissions in India (2001-2051)

emission estimates from 2001 to 2051 are presented consumption also have a significant share of 33 per
in Figure 6.12. CO emissions grew from 1,983 in 2001 cent in the overall inventory. With growing energy
kt to 2,777 kt in 2011. Private vehicles (two wheelers demands, the emissions from the transport sector are
and cars) have the biggest share in the current CO projected to grow by 2.2 and 5.1 times by 2031 and
emissions (38 per cent). Trucks with high energy 2051, respectively. The emission is expected to grow
 Figure 6.12: Past and projected growth of CO emissions in India (2001–51)

with the energy consumption mainly on account of comparison to diesel vehicles. The emission estimates
no further control of CO emissions in BS-V norms in from 2001 to 2051 are presented in Figure 6.13. HC
trucks. However, the emission could have been much emissions grew from 605 in 2001 kt to 802 kt in 2011.
higher without the introduction of emission control Private gasoline driven vehicles have the biggest
norms (BS-I to BS-IV) in India. share (46 per cent) in the overall inventory. On
account of introduction of BS-V norms, the emissions
Hydrocarbons are expected to grow only marginally till 2031 and
Hydrocarbons are released mostly from gasoline
will increase to 980 kt. Despite introduction of BS-V
engines that have higher emission factors in
norms, the emission will grow to 1,103 kt by 2051,

Figure 6.13: Past and projected growth of HC emissions in India (2001–51)

104  •  Air Pollutant Emissions Scenario for India
mainly due to growth in energy consumption. The Table 6.2: Fuel Quality Improvement Program in India
emission could have been much higher without the
Fuel Date Lead content Area covered
introduction of emission control norms in India.
Gasoline 1994 Low leaded (0.15 NCT, Delhi, Mumbai,
g/l) Kolkata, and Chennai
SO2 Emissions Gasoline 1995 Unleaded (0.013 NCT, Delhi, Mumbai,
Sulphur dioxide emissions are related to the sulphur g/l) + low lead Kolkata, and Chennai
content in the automotive fuels. Fuel quality has Gasoline 1998 Ban on leaded NCT
gradually improved in the country and sulphur gasoline. Only
content has reduced considerably over the years unleaded
(Table 6.2). Gasoline 1999 Unleaded only NCR
With this the sulphur dioxide emissions have Gasoline 2000 Unleaded only Entire country
come down significantly from 120 kt in 2001 to Fuel Date Benzene Content Areas Covered
53 kt in 2011 (Figure 6.14). It is expected to go Gasoline Pre1996 No specification Entire country
down further with introduction of BS-V (10 ppm for Benzene
sulphur) fuels in 2021. However, no changes have Gasoline 2000 3 % Benzene Metro cities
been assumed in high sulphur fuels used in non- Gasoline 2000 1% Benzene NCT and Mumbai
road sector (tractors, railways, and shipping). With Gasoline 2005 1% Benzene Entire country
2,000 ppm sulphur assumed in non-road fuels, the Fuel Date Sulphur Content Areas Covered
emissions are expected to reach 145 kt by 2051. Diesel 1996 0.5% Four metros and Taj
Trapezium
Comparison of Emission Estimates Diesel 1997 0.25% Delhi and Taj
with Other Studies Trapezium

The emission estimates in the previous section are Diesel 1998 0.25% Delhi, Mumbai,
Chennai, Kolkata
based on emission factors from ARAI (2008) datasets.
Diesel 2000 0.05% NCR-Private Vehicles
The differences in emission esitmates using GAINS
and CPCB (2000) emission factors are shown in Table Diesel 2001 0.05% NCT-all diesel
vehicles
6.3. The estimates in this study are also compared
Diesel 2001 0.05% NCR-all diesel
with previous studies.
vehicles
It is to be noted that when GAINS emission factors
Diesel 2001 0.05% Chennai, Mumbai,
are used, the emissions ranges between 115 kt to 147 and Kolkata
kt between 2001 and 2051. However, in the current
Diesel 2003 0.05% Ahmedabad,
study the emissions estimated using ARAI emission Bangalore, and
factor leads to higher PM2.5 emissions of 261 kt in Hyderabad
2011. This is due to higher emission factors reported Diesel 2005 0.05% All over country
in ARAI (2008) while testing of indigenous vehicles on  Diesel 2005  0.035%  11 cities
Indian driving cycles.  Diesel 2010  0.035%  All over country
 Diesel 2010  0.005% 11 cites
Emissions from Road Dust Re- Diesel 2016  0.005%  All over country*
Suspension Diesel 2021/2019  0.001%/  All over country*
When vehicles move on a road, the silt lying on the *Planned as per AFV 2025; ** As per MoRTH notification
road gets re-suspended. The rate of re-suspension
is dependent on the weight of the vehicles and
quantity of silt lying on the road. Road dust
 Transport • 105

Figure 6.14: Past and projected growth of SO2 emissions in India (2001–51)

Table 6.3: Comparison of Different Studies Reporting Emissions (kilotonnes) for Different Pollutants from Transport Sector in India
Source Year PM2.5 NOx CO HC
ICCT, 2013 2011 220 2200
CPCB, 2010 2003–04 153 2298 5692 723
CAIA, 2008 2008 150 2200
Guttikunda and Mohan, 2014 2011 253 5000 5500 1850
Purohit et al., 2010 2010 319 2706 1798
This study (ARAI, 2008 efs) 2011 276 2665 2777 802
This study (GAINS efs) 2011 156 2820
This study (CPCB, 2000 efs) 2011 235 2376

suspension emissions in this study are estimated 2007, 2011, Sharma et al, 2015) a conservative SL
using the USEPA procedure specified in AP-42. of 0.1 g/m² is assumed in this study. Vehicle-wise
Emission loads =VKT × EF where VKT estimates were taken from TERI (2015) (based
EF = k (SL)0.91⋅(W)1.02 on TERI-MARKAL model estimates) for 2001–51. ‘W’
EF = particulate emission factor (having units values were derived based on fleet distributions.
matching the units of k), PM10 and PM2.5 emissions are estimated be
k = particle size multiplier for particle size range 47.8 and 11.6 kt in 2011, respectively (Figure
and units of interest, for PM10 k = 0.62, PM2.5 k = 0.15 6.15). The emission projections are made with an
SL = road surface silt loading (grams per square assumption that road quality and maintenance
meter; g/m2), will improve at the rate of 10 per cent per annum
W = average weight (tons) of the vehicles and silt loading will reduce to 0.043 g/m² by 2051.
travelling the road The emissions will still grow by 12.5 times with the
Based on silt loadings experiments carried out growing mobility demands and weight of the overall
by TERI in the past in various cities of India (TERI vehicular fleet.
106  •  Air Pollutant Emissions Scenario for India

Figure 6.15 : PM10 and PM2.5 emissions (kilotonnes) from road dust re-suspension in India

Spatial Allocation of Emissions in India

Emissions of different pollutants from on-
road vehicles in India are allocated based on
district-wise vehicular population in India. The
district-wise emissions are used to allocate emissions
at the grid resolution of 36 × 36 km2. The national
highways of India carry 40 per cent of total traffic
(http://www.nhai.org/) and hence 40 per cent of the
emissions are allocated at the national highways
digitised using geographical information system
(GIS). The spatial distribution of emissions at 36 × 36
km² resolution is shown in Figure 6.16. This is evident
that high vehicular density in India is limited to urban
regions and national highways. For non-road sector,
the emissions are distributed at the state level. State-
wise allocation of aircraft emissions is done on the
basis of state-wise air craft movement. Shipping
emissions are allocated state wise on the basis of
total traffic handled by major and minor ports in
the country. State-wise allocation of emissions from
railways is done on the basis of state-wise rail route
length. Figure 6.16: Spatial distribution of PM2.5 emissions
from tail-pipe emissions in India
Conclusions in the sector is projected to grow. The emissions
from the sector has grown in the past; however,
The transport sector is expected to grow multi-
introduction of fuel quality and vehicular emissions
folds over the next four decades. Despite some fuel
norms has arrested the growth to some extent. Future
efficiency improvements, the energy consumption
projections show that the emissions from transport
 Transport • 107
sector will stabilize over the years mainly due to fees, road usage fees, etc. However, this can only
introduction of advanced vehicular emission norms be implemented once a public transport system is
(BS-V) by 2021. The inventory of emissions from in place that is attractive enough for the general
transport sector is found to be comparatively lower public. The bus-based public transport systems are
than other sectors such as residential and industries. within reach of larger cities’ budgets as well as state
However, it is to be noted that transport emissions transport funding, but incentives from national
are concentrated more in the urban regions and programs such as the forthcoming successor to the
that is why the sectoral contribution of transport JNNURM or the SMART cities program could motivate
may not be prominent at the National scale but will greater attention to buses as an important part of
be significant at the urban scales. CPCB (2011) has public transport systems. Bus-based systems are
shown higher contributions of the transport sector particularly well suited for most Indian cities since
at the urban scales. Other than tail-pipe emissions, they are inherently more flexible than rail based ones
fugitive emissions due to road dust re-suspensions and can accommodate unforeseen growth.
are also emitted from the sector. While there are
norms in place for control of tail-pipe emissions, the Improved in-use vehicle management system
road dust emissions are dependent on the quality of It could be better to set up adequate numbers of
roads and maintenance. well-equipped centralized inspection centres in
Evidently, there are a number of steps that are every city, in place of the existing decentralized PUC
required to be taken for control of vehicular pollution centres. These limited number of inspection centres
in India. should be closely monitored by the respective state
transport departments for quality assurance. Instead
Improve fuel quality and vehicular standards of quarterly testing, annual testing of vehicles (such
Considering the current state of air quality, the as in US and China) across India can ensure higher
Government of India has notified earlier introduction percentage of the vehicular fleet actually appearing
of BS-V fuels than those recommended in the AFV for inspections. For further improvement, annual I&M
(2014) by asking the Indian refineries to move to checks can be linked with the vehicle insurance. The
BS-V fuels by 2019. The GOI has also announced total investment required for establishing inspection
the possibility of leap frogging to BS-VI emissions centres for catering to all the vehicles is estimated
norms. GOI should also immediately set up an expert to be about INR 7,300 crores. Annual testing charges
group to prescribe BS-VI vehicle emission norms of INR 100 to 400 per vehicle—for different category
by 2017 that can be adopted by the auto industry of vehicles—should recover this cost within the next
by 2020. This would also facilitate the use of after 2.3 years (Sitalakshami et al, 2014). Moreover, there is
treatment devices (e.g., diesel particle filters) as a need of an in-use vehicle compliance programme
retrofits for vehicles already in use. Studies carried to check and ensure that vehicles actually comply
out by TERI and ICCT have shown that the benefits with their original emission standards (type approval
of the adoption of these advanced norms outweigh standards) throughout their useful life. Limited
the costs of implementation and the initial costs testing can be initiated at the central level to assess
of refinery upgradation can be met with a slight the compliance of in-use vehicles of different
increase in the fuel price (less than a rupee per litre) manufacturers with the type approval norms.
(ICCT 2013; Sharma et al. 2014) .
Improving Driving cycles
Reduce private vehicles ownership in urban areas This call for further investigations and change in the
Discouraging ownership of vehicles can be done current procedures and therefore improvement in
through higher taxation policies, high parking the prescribed driving cycles in the vehicle emission
108  •  Air Pollutant Emissions Scenario for India
test procedures. In this respect, a move towards the Ghate, A., and S. Sundar. 2013. Can we reduce the rate of
world harmonized test procedures could be explored, growth of car ownership? Economic and Political Weekly
which cover a variety of driving conditions and are XLVIII(23), June 8.
much more comprehensive than the current ones. Guttikunda S.K. , Mohan D. 2014. Re-fueling road
Other than these, encouraging fleet transport for better air quality in India, Energy Policy, 68,
modernization, promoting non-motorized means 556–561.
of transport (walking and cycling), increasing MoRTH. 2013. Road Transport Year Book (2011–12).
distribution of electric and hybrid vehicles, and Ministry of Road Transport and Highways, New Delhi
integrated land-use and transport planning should
PC. 2014. India Transport Report, Moving India to 2032,
also help. For control of road dust emissions, the
National Transport development Policy Committee,
quality of roads and maintenance levels also need to
Planning Commission, New Delhi.
improve significantly.
Purohit, P., M. Amann, R. Mathur, et al. 2010. GAINS Asia
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Annexure
Table A.6.1: Comparison of ARAI (2008), CPCB (2000) and GAINS Emission Factors (Tonnes/PJ)
Categories     GAINS ARAI* CPCB (2000)*
Fuel Category Vintage CO HC NOx PM CO HC NOx PM CO HC NOx PM
Gasoline 2-W (2s) 1991–96 15000   200 1500 9449 5333 49 119 18022 10813 83 638
Gasoline 2-W (2s) 1996–2000         6719 4704 112 106 10922 9011 164 273
Gasoline 2-W (2s) Post 2000 7500   200 487.5 4069 3412 87 76 5189 5023 165 118
Gasoline 2-W (2s) Post 2005 1500   200 300 454 1470 60 84 2429 2290 139 87
Gasoline 2-W (4s) 1991–96 12000   108 10 7426 1856 547 24 8947 2386 924 209
Gasoline 2-W (4s) 1996–2000       9 3990 1869 758 38 7477 2013 863 173
Gasoline 2-W (4s) Post 2000 7200   108 6 3419 1384 798 60 4564 1452 622 104
Gasoline 2-W (4s) Post 2005 3000   96   1263 746 273 18 1739 870 373 62
Diesel Cars 1991–96 310   350 140 1088 607 743 249 3121 158 1184 359
Diesel Cars 1996–2000         1379 326 301 203 571 176 328 200
Diesel Cars Post 2000 257   350 60.9 450 116 387 95 346 50 192 27
Diesel Cars Post 2005 111   350 34.72 88 55 194 25 224 19 174 19
Gasoline Cars 1991–96 6900   860 2 3185 563 637 5 6850 1188 1258 42
Gasoline Cars 1996–2000         2765 403 458 5 2438 500 688 31
Gasoline Cars Post 2000 2760   249 1.1 1223 108 92 3 1048 132 106 16
Gasoline Cars Post 2005 828   112 1.1 341 49 37 1 537 58 46 8
Diesel LDV 1991–96 310   350 110 663 493 655 216 2991 1773 107 75
Diesel LDV 1996–2000         643 274 532 140 1804 1468 19 31
Diesel LDV Post 2000 257   350 47.8 652 241 378 85 749 357 19 14
Diesel Truck 1991–96 900   1300 70 795 167 857 143 459 149 793 125
Diesel Truck 1996–2000       52.7 577 94 1153 79 376 101 701 67
Diesel Truck Post 2000 855   904 28.3 685 130 1006 111 301 73 526 23
Diesel Truck Post 2005       23.1 327 23 682 33 267 73 459 10
Diesel Bus 1991–96 900   1300 70 1132 208 975 175 470 152 1625 257
Diesel Bus 1996–2000         352 115 1199 95 342 92 1276 121
110  •  Air Pollutant Emissions Scenario for India

Table A.6.1: Comparison of ARAI (2008), CPCB (2000) and GAINS Emission Factors (Tonnes/PJ)
Categories     GAINS ARAI* CPCB (2000)*
Diesel Bus Post 2000 855   904 52.7 371 188 607 52 326 79 1088 51
Diesel Bus Post 2005 756   958 19.6 472 19 787 36 372 101 1278 28
*Values are originally in gram per kilometre, converted using fuel efficiency values computed using CO2, HC, and CO concentrations.
Data source: ARAI (2008), GAINS, CPCB (2000) 

Other than on-road vehicles, the emissions were Table A.6.2:Emission Factors (T/PJ) for Railways, Airways, and
also calculated for non-road transport including Waterways Transport
railways, airways, waterways transport, and tractors. The  Controls Pollutant Air craft Diesel Ship/coastal
emission factors (T/PJ) are provided in below in Table locomotives water
A.6.2. transportation
Euro-II 0 50.8915 55.41825
Table A.6.2:Emission Factors (T/PJ) for Railways, Airways, and
Euro-III 0 15.26745 16.62548
Waterways Transport
Euro-IV 0 3.05349 3.325095
 Controls Pollutant Air craft Diesel Ship/coastal
locomotives water Euro-V 0 6.10698 6.65019
transportation Euro-VI 0 2.239226 2.438403
NOC NOx 0.008 1.16 1.16 Source: GAINS
Euro-I 0.008 0.7656 0.7656
Euro-II 0.008 0.696 0.696 Table A.6.3 Emission Factor for Tractors (g/kwh)
Euro-III 0.008 0.522 0.522 Pollutant Bharat Bharat Bharat Bharat Stage
Euro-IV 0.008 0.348 0.348 Stage I Stage II Stage III III A
Euro-V 0.008 0.2204 0.2204 HC + NOx - 15 9.5 6.2
Euro-VI 0.008 0.0522 0.0522
PM 2.43 1 0.8 0.51
Euro-VII 0.008 0 0
PM2.5 2.06 0.85 0.68 0.44
NOC PM_2_5 0.35604 96.426 105.003
Euro-I 0.35604 64.31614 70.037 BC 1.46 0.6 0.48 0.31
Euro-II 0.35604 48.213 52.5015 OC
Euro-III 0.35604 14.4639 15.75045 NOx 18 12.6 8.0 5.2
Euro-IV 0.35604 2.89278 3.15009 SO2 0.24 0.060 0.060 0.042
Euro-V 0.35604 5.78556 6.30018
CO 14 9 5.5 5
Euro-VI 0.35604 2.121372 2.310066
Euro-VII 0.35604 0 0 HC 3.5 2.44 1.55 1.01
NOC CO — 0.25 0.25 Source: Based on prescribed emission norms
Euro-I — 0.2375 0.2375
Euro-II — 0.21 0.21
Euro-III — 0.1125 0.1125
Euro-IV — 0.09 0.09
Euro-V — 0.09 0.09
Euro-VI — 0.09 0.09
Euro-VII — — —
NOC PM10 0 101.783 110.8365
Euro-I 0.387 67.88926 73.92795
CHAPTER 7
Diesel Generator Sets
C. Sita Lakshmi and Sumit Sharma

Introduction (MU) reported as 3.6 per cent and the peak deficit
(MW) was 4.7 per cent during 2014–15. However, the
Unreliable power situation along with ever-increasing unreliability of supply necessitates the use of DG sets.
gap between demand and supply has been a DG sets are used in number of residential
major challenge in India for many years now. To complexes, factories, and businesses in India, and
counter these issues, diesel generator (DG) sets have the estimated installed capacity in India during
become an imperative across various sectors such as 2014 was about 60–90 GW, which was about 36 per
industries, infrastructure, housing, IT, and telecom. Not cent of India’s total installed generation capacity in
only in India but all around the world diesel-powered 2014 (Pearson 2014; Sasi 2014). Despite the cost of
generator sets are the preferred choice for standby producing electricity from DG sets steadily rising,
and emergency power systems, perhaps owing to owing to increasing prices of diesel fuel to as much
the ease of installation and operation, limited space as INR 24–30 per kilowatt-hour in 2014 (Chatterjee
requirement, and easy availability in the market 2014), its demand is still rising.
(Iverson 2007). The total energy availability in 2010– Of the total diesel sales in India, 82 per cent was
11 in India increased by 5.6 per cent at 788,355 MU sold through retail outlets (petrol pumps) in the year
over the previous year and the peak met increased by 2011–12 while the remaining was directly sold by
6.0 per cent and was reported at 110,256 MW; still the the oil marketing companies to bulk consumers such
energy deficit (MU) was 8.5 per cent and peak deficit as industries, railways, and defence among others.
(MW) was 9.8 per cent during 2010–11 (CEA 2012). The retail sales data shows that maximum diesel
While the latest data indicates shortage situation to consumption is by the transport sector, with highest
have improved in the country with the energy deficit by heavy and light duty vehicles (HCVs, LCVs) and
112  •  Air Pollutant Emissions Scenario for India
buses followed by private cars and utility vehicles. including the source apportionment study
While in the non-transport sector, tractors consume published by CPCB in 2011 has estimated a
the maximum quantities of diesel followed by DG significant share of DG sets in the prevailing air
sets (Petroleum Planning and Analysis Cell 2013). pollution levels in the cities. In Bangalore, the share of
One of the major sectors employing the use of DG sets was about 14 per cent in the ambient PM2.5
DG sets in India is the telecom industry. TRAI 2011 concentrations (CPCB 2011). Other than particulate
shows that there were 400,000 telecom towers across matter (PM), these devices are known to emit
India by end of the year 2010. With as high as 60 per significant NOX emissions. Moreover, the pollutants
cent of the power requirement of telecom towers are emitted at low heights, and hence provide more
being met through the use of DG sets and towers in exposure to the receptors (Figure 7.1).
remote areas being powered 100 per cent by DG sets, Agriculture contributes to as high as 15 per cent
telecom sector has an important contribution in the of the overall GDP in India and employs a major
overall energy use and emissions from DG sets. It is proportion of the county’s workforce (KPMG and
estimated that in 2010, the telecom sector consumed Shakti Foundation 2014). Almost all Indian states
about 2 billion litres of diesel (TRAI 2011). heavily rely on diesel pump-sets for irrigating their
The Indian DG set sector has both organized big croplands. Currently, there are about 7 million
manufacturers, along with the unorganized and small diesel-powered pump-sets in India (excluding
manufacturers, the latter constituting as high as 30– grid connected electric pump-sets) consuming
40 per cent of the whole market size. approximately 4 billion litres of diesel annually
Compared to the transport sector, DG sets (KPMG and Shakti Foundation 2014). The pump-
consume a small amount of diesel; however it is sets manufacturing market is predominantly
a key contributor in the non-transport segment in the unorganized sector providing low cost
and is set to sustain in near future keeping in (less than INR 15,000) and low efficient pump-
mind the power situation in India. DG set is an sets with efficiency between 20 per cent and 35
important source of emissions and many studies per cent (BEE 2011). Owing to poor efficiency,

Figure 7.1: Small diesel generator set

 Diesel Generator Sets  •  113
these pump-sets consume a lot of diesel and
hence are an important source of PM emissions.
This chapter provides the estimates of energy
consumed by DG generator sets in India and the
corresponding emissions.

Past Trends and Future Growth

FaS 2010 showed results of a market research study
and states that the DG set market is estimated to
grow steadily at a compounded annual growth rate Figure 7.2: Capacity wise sales of DG sets in India,
of about 10.1 per cent in revenue terms between (2011)
2010 and 2015. Further, it reports a 7.2 per cent
annual growth in number of DG sets in India.
According to other industry estimates, the power
back-up market in India is growing at an annual
rate of 15–20 per cent (CWO 2010), varying within
the three different segments—generators, UPS, and
inverters. Annually it is estimated that roughly 2 lakh
DG sets are added to the domestic market, including
telecom sector. It is estimated that in the year 2000,
the number of DG sets sold in India was 37,569 units,
which grew to 186,531 units in 2010. Majority of the
DG sets sold in India are of the capacities 15–25 KVA
Figure 7.3: Capacity wise market share of
(56 per cent) and 62–125 (26 per cent) (Figure 7.2).
agricultural pumps (by volume)
The agricultural pump-sets market is reported
Source: KPMG and Shakti Foundation 2014
to be growing at the rate of 6.3 per cent annually
in terms of number of units from 2009 to 2013
with revised norms (CPCB II) in the year 2013; these
(KPMG and Shakti Foundation 2014). Farmers across
new norms are applicable to new DG sets being sold
the country use pump-sets of varying capacities
from 1st July 2014 (Table 7.2).
depending on their specific requirement based on
The efficiency of a DG set is expressed as a
ground water levels and affordability. Almost 50 per
combined efficiency of its two subcomponents,
cent of the market share is occupied by pump-sets in
namely the engine and the alternator or the AC
the range of 5 to 7.5 HP (Figure 7.3).
converter; typically it varies between 30 per cent to
55 per cent depending on its design, size, capacity,
Emission Control for DG Sets in mechanism for fuel control, and operating speed,
India among other factors (Shakti Sustainable Energy
The Ministry of Environment and Forests set Foundation and ICF International 2014). Efficiency
regulations and emission norms (CPCB I) for the of the DG sets is also dependent on external factors
diesel engines used in the DG sets in the year 2002 such as load conditions, ambient conditions, and
(Table 7.1), which also imposed type approval (TA) operation and maintenance (O&M) practices.
testing and conformity of production (CoP) along Small and medium-sized DG sets are designed
with labelling requirements on DG sets. These to meet the existing emission standards at
emission norms were subsequently strengthened manufacturing stage itself, while the larger DG sets
114  •  Air Pollutant Emissions Scenario for India

Table 7.1: Emission Standards for Diesel Engines ≤800 kW for a reduction in PM emissions, but simultaneously
Generator Sets (2004–05) —CPCB I increasing NOX emissions. Lower temperatures lead
Engine Power CO HC NOX PM Smoke to a reduction in NOX emissions but increase in PM
Date emissions.
(P) g/kWh l/m
P ≤ 19 kW 2004.01 5.0 1.3 9.2 0.6 0.7
2005.07 3.5 1.3 9.2 0.3 0.7
Methodology
19 kW < P ≤ 2004.01 5.0 1.3 9.2 0.5 0.7 Emissions from the DG set sector across India were
50 kW calculated using established emission factors (US
2004.07 3.5 1.3 9.2 0.3 0.7
Environmental Protection Agency; USEPA) and
50 kW < P ≤ 2004.01 3.5 1.3 9.2 0.3 0.7
secondary data from various sources. The total daily
176 kW
energy consumption by DG sets was estimated based
176 kW < P ≤ 2004.11 3.5 1.3 9.2 0.3 0.7
800 kW on the following equation.

E(kWh) = C × W (hrs)..........................................................(7.1)
Table 7.2: Emission Standards for Diesel Engines ≤800 kW for Where, E = Energy
Generator Sets (Gazette Notification of 2013, Applicable From C = Installed capacity
2014)—CPCB II W = Working/operating hours, (assumed as 2 hours/
Emission limits day in this study)
Smoke limit
NOX + HC CO PM
Power category The installed capacity (C) for DG sets was
(g/kW-hr) Light absorption
calculated by:
coefficient per m
C(kW) = P(kVA) × PE × Percentage of loading..........(7.2)
Up to 19 KW ≤7.5 ≤3.5 ≤0.3 ≤0.7
Where, P = Apparent power (kVA)
19 kW < P ≤ ≤4.7 ≤3.5 ≤0.3 ≤0.7 PE = Power factor, 0.8 in this case (i.e., 80 per cent of
75 kW
apparent power is converted to working power) and,
75 kW < P ≤ ≤4.0 ≤3.5 ≤0.2 ≤0.7 85 per cent loading (percentage of DG set in use)
800 kW
The energy consumption estimated using the
need different interventions to reduce their emissions Equations 7.1 and 7.2 is used to estimate diesel
(of NOX, PM, CO, and HC) and meet the emission consumption in DG sets during 2011. The fuel
standards (Herzog 2002). Some of the most common consumption of the DG sets varies according to
emission control technologies for DG sets are their capacity (Annexure 7.1). Thus, the average fuel
PP More efficient combustion engines consumption (in Gal/hr) for the range of capacities
PP Catalytic after treatment systems (DOCs/DPFs) commonly used in India was correlated with their
PP Low sulphur fuels respective sales data for the year 2010 (Figure 7.2), and
PP High-pressure direct injection gas technology the weighted average fuel consumption for different
capacity ranges of DG sets was used to calculate the
However, tail pipe controls are currently not total diesel fuel consumption across India (Table 7.3).
employed in India to control emissions from DG sets. Table 7.3: Capacity-Wise Average Fuel Consumption in DG Sets
The PM and NOX emission conundrum, in controlling Range of capacities (in kVA) Average Fuel Consumption (Gal/hr)
diesel emissions, still poses a major challenge in 7.5 and 10 0.6
designing engines, since most engine technologies
15, 20 and 25 (Telecom series) 1.3
increase NOX emissions to reduce PM inversely, and
62–125 5.3
vice versa. Both these pollutants are inherently linked
250–500 19.2
to the in-cylinder temperatures where combustion
750–1500 58.6
takes place: with higher temperatures favouring
 Diesel Generator Sets  •  115
To validate the estimates of fuel consumption, it Table 7.5: Emissions (in KT/year) from DG Sets
is compared with other similar studies that have and Agricultural Pump Sets Sector in 2011
reported the diesel consumption by DG sets in India 2011 Total Emissions (KT/year)
(Section “Comparison with Other Fuel Consumption
PM10 81.9
Estimates”).
SO2 76.6
For calculating the emissions from the DG sets and
NOX 1164.4
agricultural pump-sets, the total energy consumed
by these two sectors is taken from TERI MARKAL TOC 95.1
model results (TERI 2015) and annual emissions are CO 250.8
calculated according to the formula and emission PM2.5 70.0
factors given below: BC 49.0

EM = E(J) × EF (ng/J)......................................................... (7.3)

Spatial Distribution of Emissions
Where, EM = Emissions, in Nano gram Due to lack of data on installed DG set capacity
E = Energy, in Joules across different states or districts in India, the
EF = Emission factor (Table 7.4) state-wise diesel fuel consumption for DG sets
(including domestic, commercial, telecom DG sets,
DG Set Emissions in India and agricultural pump-sets) was used to distribute
the state-wise emissions from this sector. The fuel
Emissions from the DG set usage in India (including
consumption of DG sets in different states was
agricultural pump-sets) are estimated for the years
obtained from secondary sources (namely Petroleum
2001, 2011, 2021, 2031, 2041, and 2051.
Planning and Analysis Cell and Ministry of Petroleum
and Natural Gas, refer to Annexure 7.2). This state-
National Emissions
wise diesel consumption data was used as a proxy to
Emissions for different pollutants from DG sets sector
distribute the overall emissions of PM10 and NOX from
were calculated using the methodology explained
DG sets sector across different states in India (Figures
in the previous section. The national level emissions
7.4 and 7.5).
of different pollutants from DG sets (including
It is evident from the Figures 7.4 and 7.5 that some
agricultural pump-sets) for India in the year 2011 are
states rely more heavily on DG sets, and hence have
shown in Table 7.5.
higher emissions from this sector, such as Punjab,
Haryana, Delhi, and Uttar Pradesh in the north and
Tamil Nadu and Kerala in the south.
Table 7.4: Emission Factors for DG Sets
Pollutant Emission factor (ng/J*)
Comparison with Other Fuel
PM10 133.3
SO2 124.7
Consumption Estimates
There have been no previous estimates of national
NOX 1896.3
emissions of various pollutants from DG sets sector
TOC 154.8
that can be used as comparative numbers to evaluate
CO 408.5
our study. In order to validate the results of our
PM2.5 85% of PM10 study, the total fuel (diesel) consumption by DG
BC 60% of PM10 sets in India was used as a proxy measure. This was
* ng/J: Nano gram/Joule calculated for the baseline (2011) as 7,733 million
Source: AP-42, USEPA litres per year, which is satisfactorily close to the
116  •  Air Pollutant Emissions Scenario for India

Figure 7.4: State-wise distribution of PM10 Figure 7.5: State-wise distribution of NOx
emissions from DG sets sector across India emissions from DG sets sector across India

diesel consumption data reported by MoPNG for

the same year, that is, 7,426 million litres per year.
Industrial and miscellaneous diesel consumption
reported by MoPNG (2011) is assumed to be
consumed in running DG sets. A recent study by PPAC
also estimated the actual diesel fuel consumption
by DG sets (in all sectors) for the year 2012 through
primary surveys of retail outlets across India (Figure
7.6). Lately, another study on improving efficiency
and emission performance in DGs in India, by ICF
and Shakti foundation stated a lower figure of about
4,510 million litres of diesel consumption by the
DG sets in India in 2012–13. The closeness of diesel
consumption estimates with the reported numbers
in MoPNG statistics reflects the reliability of the Figure 7.6: Comparative analysis with other
emission estimates in this study. estimates of diesel consumption by the DG sets
sector
 Diesel Generator Sets  •  117

Past and Future Projections (2001–

51)
The emissions from DG sets sector has also been
estimated for the past and future years. Considering
2011 as the base year, estimates were made for
each five-year interval from 2001 to 2051. TERI has
estimated the total energy consumption by different
sectors in India from 2001 to 2051 using the MARKAL
model. The data for total energy consumed by DG
sets sector in India was derived from this model
for past and future years, and employing the same
emission factors mentioned in the ‘Methodology’
section, the emissions were estimated for different Figure 7.7: Annual PM10 and NOx emission trends
years (Table 7.6). As evident from Figure 7.7, the from 2001 to 2051 in India from DG sets
total emissions from the DG sets sector has been
decreasing over the years (from 2001 to 2011).
In the future also, the emissions are expected to
1164.4 KT of NOX in 2011. Beyond 2031, it is estimated
reduce, since it is expected that the power situation
that DG sets will not be used in residential and
will improve in India. Also, the new emission norms
commercial sectors for power back-up and that there
(applicable from 2014) will further bring down the
will be continuous power supply.
emissions in the future (hence the marked drop
from 2016 to 2021 in the Figure 7.7). The estimated
emissions in 2051 of PM10 are 77.6 KT and that of
Conclusions
NOX are 893 KT as compared to 82 KT of PM10 and It is evident from assessing the past and future
growth trends for DG sets, that power back-up
Table 7.6: Past and Future Annual Emissions of Different sector will gradually diminish over the years, though
Pollutants from DG Sets Sector in India currently it contributes substantially to the PM10 and
PM10 SO2 NOX TOC (BC + OC) CO other emissions. In India, there is still a significant
Past In KT/year disparity between the demand and supply of power
2001 103.66 96.97 1474.66 120.38 317.67 both in the urban centres as well as the developing
rural set-up. Lack of alternative options for power
2006 91.59 85.68 1302.89 106.36 280.67
back-up and convenience of diesel-fired engines
2011 81.85 76.57 1164.44 95.06 250.84
has ensured that DG sets are the first choice for
Future* In KT/year consumers to meet their needs.
2016 102.85 96.21 1463.11 119.44 315.18 The contribution of this sector in overall emissions
2021 72.32 15.34 832.89 67.99 288.48 of air pollutants is quite low compared to other
2026 73.49 15.59 846.33 69.09 293.14 important sectors such as transport, industry, and
2031 76.19 16.16 877.47 71.63 303.92 power, still it is likely to impact a large number of
the population since they are most often placed
2036 76.30 16.19 878.74 71.73 304.36
in crowded and congested commercial areas that
2041 80.63 17.10 928.60 75.80 321.63 already have potent levels of air pollutants in the
2046 84.38 17.90 971.78 79.33 336.59 ambient air.
2051 77.56 16.45 893.14 72.91 309.35 Along with manufacturing improvements,
*in context of the base year taken for this study, which is 2011 inspection and maintenance of DG sets can not only
118  •  Air Pollutant Emissions Scenario for India
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designed to over time but also that they function analysis for solar agricultural water pumps in India.
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Iverson, J. 2007. EPA emissions regulations: What Stationary internal combustion sources. In AP 42, 5h ed.,
they mean for standby, prime and distributed power Vol. I. Available at: <http://www.epa.gov/ttnchie1/ap42/
systems. Available at: <https://www.cumminspower. ch03/>
com/www/literature/technicalpapers/F-1564-
EPAEmissionsRegulations-en.pdf>, last accessed on
February 17, 2015.
 Diesel Generator Sets  •  119

Annexure – 7. 1 Annexure – 7. 2
Capacity-Wise Fuel Consumption for DG Sets States Diesel Percentage Power
consumption by distribution deficit**
Generator Size (kW) 3/4 Load (gal/hr) Full Load (gal/hr) DG sets (litre/
year)*
20 1.3 1.6
Andhra Pradesh 772.23 11% 3.44%
30 2.4 2.9
Arunachal Pradesh 11.79 0% 0.10%
40 3.2 4 Assam 81.59 1% 0.46%
60 3.8 4.8 Bihar 369.95 5% 2.20%
75 4.6 6.1 Chandigarh 9.66 0% 0.00%
Chhattisgarh 148.88 2% 0.24%
100 5.8 7.4
Delhi 180.85 2% 0.09%
125 7.1 9.1 Goa 38.80 1% 0.09%
135 7.6 9.8 Gujarat 281.61 4% 5.62%
150 8.4 10.9 Haryana 628.50 9% 2.63%
Himachal Pradesh 68.23 1% 0.36%
175 9.7 12.7
Jammu & Kashmir 75.52 1% 4.63%
200 11 14.4 Jharkhand 179.30 2% 0.29%
230 12.5 16.6 Karnataka 440.85 6% 5.26%
250 13.6 18 Kerala 312.09 4% 0.35%
Madhya Pradesh 297.48 4% 13.37%
300 16.1 21.5
Maharashtra 471.87 6% 29.05%
350 18.7 25.1 Manipur 9.47 0% 0.09%
400 21.3 28.6 Meghalaya 45.30 1% 0.26%
500 26.4 35.7 Mizoram 6.80 0% 0.07%
Nagaland 7.04 0% 0.09%
600 31.5 42.8
Orissa 231.70 3% 0.08%
750 39.3 53.4 Puducherry 42.77 1% 0.11%
1000 52.1 71.1 Punjab 375.20 5% 3.67%
1250 65 88.8 Rajasthan 222.98 3% 0.58%
Sikkim 6.79 0% 0.00%
1500 77.8 106.5
Tamil Nadu 750.37 10% 7.12%
1750 90.7 124.2 Tripura 10.38 0% 0.11%
2000 103.5 141.9 Uttar Pradesh 969.94 13% 15.63%
2250 116.4 159.6 Uttarakhand 86.91 1% 0.81%
West Bengal 196.71 3% 0.87%
Source: Diesel Service and Supply, available at: http://www.
dieselserviceandsupply.com/Diesel_Fuel_Consumption.aspx ) * PPAC and MoPNG
** From Central Electricity Authority
CHAPTER 8
Open Burning of Agricultural Residue
Arindam Datta and Sumit Sharma

Introduction al. 2008; Yevich and Logan 2003; Zhang et al. 1996).
However, in-situ burning of crop residue has also
Open (in-situ) burning of crop residue in agricultural been identified as an important local and regional
lands is practiced in many part of the world for quick contributor of particulate and trace gas emissions
preparation of the land for seeding of the next crop that affect air quality and public health (Dennis et
and protection from the development of mould and al. 2002; Hays et al. 2005). Researchers all over the
variety of crop diseases (Chen et al. 2005; Korontzi globe have reported the effects of open burning
et al. 2006; Sahai et al. 2007; Yan et al. 2006; Yang et of biomass on local and regional climate (Krishna
Prasad et al. 2000; Seiler and Crutzen 1980; Yevich
and Logan 2003). Studies have also suggested
significant linkage of the crop residue burning event
with the severe asthmatic symptoms in child and
elderly (Boopathy et al. 2002, Mar et al. 2004). The
emissions characteristics are different from shielded
combustion of biofuel in small cook-stoves or
industrial boilers and in-situ burning of crop residue
or forest fires (Bond et al. 2004; Venkataraman et al.
2005).
Biomass burning is a major source of gaseous and
particulate pollution in the troposphere (Crutzen
and Andrae 1990; Venkataraman et al. 2005). Earlier
122  •  Air Pollutant Emissions Scenario for India
studies have found a clear correlation between the fraction of the crop residues of cotton (lint), maize,
ambient concentrations of fine particulate matter soyabean, jute also undergo in-situ burning in different
(PM10 and PM2.5) and open burning of crop residue parts of India (Jain et al. 2014; Sharma et al. 2010). On
(Long et al. 1998; Mar et al. 2004). Satellite observations the other hand, ~350 Mt of sugarcanes are produced
have revealed elevated levels of aerosols over wide in India from ~5.0 Mha of crop land area during 2013–
areas of Central Africa and South America, over the 14 (INDIASTAT 2015). In India, Sugarcane is mainly
tropical Atlantic, and the Indian Ocean due to long- harvested manually (NAIP 2012). Before harvesting,
range transport of pollutants emitted from biomass the dry above ground part of the sugarcane is burnt to
burning (Venkataraman et al. 2006). Global biomass ensure the access of labours to harvest the crop (NAIP
burning dataset from the satellites such as GLOBSCAR 2012). Large amount of sugarcane is harvested in the
(Hoelzemann et al. 2004; Simon et al. 2004), GBA- southern part of India and the IGP during spring and
2000 (Tansey et al. 2004), MODIS-Terra (Sharma et al. summer, respectively.
2010), MODIS/UMD (Venkataraman et al. 2006) have In different studies, researchers all over the globe
identified large scale open biomass burning in the have established release of large amount of emission
Northern America, South America, Central Africa, and of different atmospheric pollutants during the in-
Tropical Asia (especially South Asia and South-East situ burning of crop residues (He et al. 2010; Lai et
Asia). al. 2009; MacCarty et al. 2009; Yamaji et al. 2010). In
Indo-Gangetic Plains (IGP) is a very important India, Mittal et al. (2009) have reported the ground
agro-economic zone in South-Asia, which occupies level study on the contribution of wheat and rice
substantial geographic area of four countries (Pakistan, crop stubble burning on SO2, NO2, and aerosols
India, Nepal, and Bangladesh). Widespread adaptation concentration levels in ambient air at five different
of the green revolution resulted in the inception of the sites such as agricultural, commercial, and residential
high-yielding varieties and increase in both crop and areas of Patiala, Punjab. Singh et al. (2010a) analysed
residues. In the IGP region of India, rice and wheat are the organic tarry matter (OTM) content in ambient air
the major crops that cover approximately 13.5 Mha of of the north-western IGP during crop residue burning
crop land (DoES 2013). Harvesting crops with ‘combine months and non-crop residue burning months for
harvester’ (mechanical harvester) is very popular with the period of 2006–07. OTM are the volatile and
farmers of Punjab, Haryana, and western Uttar Pradesh non-volatile organic matter in the carbonaceous PM
(Badarinath et al. 2009). These harvesters leave behind (Lighty et al. 2000). Singh et al. (2010b) have reported
large quantities of crop residue in the field. The crop increase in the particulate concentration in the
residues are subjected to in-situ burning on account ambient air of Patiala, Punjab, during two rice residue
of high labour wages to collect them from the field burning seasons of 2006–08. Open field burning of
and their transportation to the market. Agricultural rice straw and other crop residues in the IGP emits
crop residues, mainly of kharif (wet season) rice are species such as CO, non-methane hydrocarbons,
burnt during the months of October and November NOx, SO2, PM, and few others species (Gadde et al.
each year in the IGP, which has significant impact on 2009). Recently, Jain et al. (2014) have reported the
pollutants and aerosol loading in the regional scale state-level emissions of different pollutants due to
(Badarinath et al. 2009). The small window between in-situ burning of different crop residues during
harvest of rice crop and plantation of wheat crop 2008–09 using the state-level residue generation data
forces the farmers to burn the residue in field. The and reported emission factors of different pollutants.
wheat crops are harvested during March-April and However, burning pattern of crop residue is not
fraction of the wheat residues are burnt in the field uniform in all districts in a state and crop residue
in the north western area of the IGP (Singh 2003). burning is not practiced in all states of India (Sharma
However, apart from rice and wheat, a significant et al. 2015).
 Open Burning of Agricultural Residue  •  123
There are associated uncertainties in the the particular crop (a); fDa is the fraction of dry matter
estimation of the emission of different pollutants in the residue of the particular crop (a); fBa is the
during burning of crop residues. It is required to fraction of the crop residue that is burnt, and EFpol is
estimate the total residue burnt in each state (even the emission factor of the particular pollutant. Epol of
in districts) to reduce the uncertainty in estimation PM10, PM2.5, BC, OC, SOx, NOx, and NMVOC are reported
of different pollutants emission from burning of in kilotonnes per annum.
crop residue. Estimation of total crop residue burnt District-wise different crop production (Pa) data
with reduced uncertainty can help to develop was collected from MoCIT (2012) for the year 2001 to
future projections of pollutants emission from crop 2011. Ra for different crop was adopted from available
residue burning. It will support to develop mitigation literatures preferably from India (Table 8.1).
opportunities to reduce atmospheric emissions
from crop residue burning. In the present study, we fD value of rice, wheat, maize, and sugarcane was
have used a bottom-up approach using the satellite taken as 0.86, 0.88, 0.88, and 0.88, respectively (Jain
dataset to identify the district level in-situ burning of et al. 2014). For all other crops, the fD value was 0.80
crop residue in different states and union territories (Jain et al. 2014). The burning fraction of different
of India. This district-level dataset was used to crop residues (R) of different states of India is
estimate the emissions of different pollutants from different. We have estimated the burning fraction
the in field burning of crop residue using respective of different crop residues for different states (to
emission factors. An exhaustive literature survey was the extent for the district) based on the available
conducted to generate emission factor of different literature and expert judgement from the local
pollutants during the burning of different crop agriculture institutes. The emission factor (EFpol) of
residues. different pollutants emission from the burning of
crop residues in the field was derived through the
Methodology literature survey of reported field level studies (Table
8.2).
Estimation of base line Emissions of Different
The MODIS-terra platform dataset for the year
Pollutants
2006–10 was used to identify districts of India
Emission inventory of different pollutants from the
where the in-situ burning of crop residues takes
burning of different crop residues in the crop land
place during different cropping seasons of the year
was prepared following the IPCC (2006) inventory
following the method of Sharma et al. (2010). A
preparation guideline. The primary crops considered
mean value of this dataset was used in the present
for inventory preparation were sunflower, ragi,
study to identify the specific districts where in-situ
soyabean, jute, maize, cotton (lint), wheat, rice,
burning of crop residue takes place during different
and sugarcane. Data was collected based on the
cropping seasons. This derived mean dataset was
discussion with agriculture experts from agriculture
compared with values already published in literature
research institutions spread across India. Emission
on open crop residue burning in India (Sharma et
from the in-situ burning of crop residue was
al. 2010; Venkataraman et al. 2006) and opinion of
calculated using eq. (i);
the agricultural expert groups from different states.
35 n n District-wise emission of different pollutants due
Epol = ∑ ∑ ∑ Pa ×Ra ×fDa ×fBa ×EFpol ..........................8.1
(S=1) (D=1) (C=a) to open burning of the crop residue was estimated
following the Equation 8.1 for the year 2001 and 2011.
where, Epol = Emission of a particular pollutant (pol)
(g); Pa is the total production of a particular crop (C Future Projections of Pollutants Emission
) in a particular district (D) of the state (S); Ra is the The contribution of different crops (e.g., sunflower,
fraction of residue generated for the production of ragi, soyabean, jute, maize, cotton, wheat, rice, and
124  •  Air Pollutant Emissions Scenario for India

Table 8.1: Residue to Crop Ratio of Different Crops Included in the Present Study
Residue to crop ratio Source
Rice Wheat Sugarcane Maize Soyabean Cotton (lint) Jute Sunflower Ragi
1.75 Bhattacharya et al. 1993
1.87 Vimal 1979
1.50 1.50 Sidhu et al. 1995
1.25 Njie 2006
1.50 1.50 Singh and Ragnekar 1986
1.75 Koppman and Koppejan 1997
1.50 1.70 0.40 1.50 3.00 2.15 Jain et al. 2014
1.50 Gupta et al. 2004
1.70 Badarinath and Chand Kiran 2006
1.70 Brown 2003
2.30 0.60 1.85 Nelson 2002
0.60 Hemwong et al. 2009
3.00 3.50 2.00 Dubay and Chandra 2010
2.00 3.80 3.00 1.30 Hiloidharia et al. 2014
1.59 1.70 0.53 1.78 3.00 3.43 2.08 3.00 1.30 Mean (Present study)

sugarcane) to the total agricultural GDP during Crop Residue Generation in India
the year 2001 and 2011 was calculated using the
The amount of crop residue generated was estimated
crop production dataset of the year 2001 and 2011,
as the product of crop production (Pa), residue to crop
respectively. These values were used to project the
ratio (Ra) and dry matter fraction of the crop biomass
crop production in different years during 2021 to
(fDa). Total amount of dry residue generated during
2051 based on the agricultural GDP growth depicted
2001 and 2011 was estimated as 489 Mt and 597 Mt,
in Markal results (TERI 2015). The projected emissions
respectively. Sahai et al. (2011) have estimated 253
of different pollutants during the in-situ burning of
Mt of crop residue generation in the year 2010 from
different crop residues were calculated using the
rice and wheat crop. On the other side, Jain et al.
Equation 8.1.
(2014) have estimated 620 Mt of residue production
during 2008. The variation in the estimation with the

Figure 8.1: Projected production of different crops in India during 2021–51

 Open Burning of Agricultural Residue  •  125

Table 8.2: Emission Factor of Different Pollutants

Crop Emission factor (g/kg) Source
PM10 PM2.5 BC OC CO SOx NOx NMVOC
Rice 5.8 5.5 58.9 2.4 0.5 6.3 Jenkins et al. 1996
5.5–10.1 0.8 1.5 0.4 Venkataraman et al. 2006
7.0 5.4 EPA 2005
8.4 10.9 71.72 2.4 8.32 Allen and Denis 2000
Wheat 5.7 5.4 66.7 2.3 0.5 0.5 Jenkins et al. 1996
5.5–10.1 0.8 1.3 0.6 Venkataraman et al. 2006
11.0 64.0 EPA 2005
4.5 4.3 30.6 2.3 Allen and Denis 2000
Maize 6.2 6.0 38.8 1.8 0.2 4.5 Jenkins et al. 1996
7.0 54.0 EPA 2005
Sugarcane 4.1 1 2.7 Venkataraman et al. 2006
6.9 6.7 0.5 1.5 Allen and Denis 2000
Mixed crop residue 0.2 0.3 28.1 1.7 Sahai et al. 2007
5.5 15.7-23.4 Venkataraman et al. 2006
4.0 5.5 88.0 EPA 2005
3.9 0.7 91.9 0.4 2.4 15.7 Jain et al. 2014
Rice 7.1 5.45 0.8 1.5 58.9 2.4 0.45 6.3 Present Study
Wheat 8.0 5.4 0.8 1.3 65.5 1.45 0.5 0.5 Present Study
Sugarcane 6.9 5.4 1.0 2.7 28.1 0.5 1.5 0.5 Present Study
Maize 6.6 6.0 0.2 0.3 46.4 1.8 0.2 4.5 Present Study
Soyabean 10.0 5.5 0.2 0.3 28.1 0.5 1.7 19.1 Present Study
Sunflower 10.0 5.5 0.2 0.3 28.1 0.5 1.7 19.1 Present Study
Ragi 10.0 5.5 0.2 0.3 28.1 0.5 1.7 19.1 Present Study
Cotton(lint) 10.0 5.5 0.2 0.3 28.1 0.5 1.7 19.1 Present Study
Jute 10.0 5.5 0.2 0.3 28.1 0.5 1.7 19.1 Present Study

present study may be attributed to the type of crop Pradesh (115.4 Mt) during 2011. Higher crop residue
residues considered in the present study. The amount generation from the state of Uttar Pradesh was also
of crop residue generation is highly variable based reported earlier (Jain et al. 2014).
on the crop type (Figure 8.2). Among nine different
crops selected in the present study, the contribution Estimation of the Crop Residue Burnt
of rice crop residue was significantly larger to the The total amount of in-situ burning of crop residue
total residue generation (29 per cent and 32 per cent, depends upon several factors such as type of crop,
respectively during 2001 and 2011) (Figure 8.2). Jain residue to grain ratio, fraction of residues subjected
et al. (2014) have also reported higher contribution to burning, and largely area-specific usage pattern
of the rice residue to the total dry residue generation of the respective crop residue. These lead to large
per annum in India. Rice residue generation during uncertainties in the estimates of in-situ burning
2011 in different states followed the order: West of crop residues. The burning of rice crop residue
Bengal (23.9 Mt), Andhra Pradesh (22.6 Mt), Uttar was about 80 per cent in the states of Punjab and
Pradesh (20.8 Mt), Punjab (15.7 Mt). However, the Haryana; on the other hand, in the states of Odisha,
total crop residue generated from the selected nine Andhra Pradesh, and West Bengal, the burning of
crops was significantly higher in the state of Uttar rice residue is less than 0.1 per cent. About 80 to 90
126  •  Air Pollutant Emissions Scenario for India

Figure 8.2: Estimated total dry crop residue generated and amount of dry crop residue burnt in situ during
2001 and 2011 in India

per cent of the sugarcane residues are burnt in the burning during 2008 in India. During the present
states of Bihar; whereas, sugarcane residue burning study, we have identified the specific districts in
in Punjab and Haryana is about 25 per cent. Lesser India with in-situ burning of crop residues using the
amount of sugarcane residue burning in the states of satellite data; however, most of the previous studies
Punjab and Haryana may be attributed to the use of have estimated the amount of crop residue burnt
mechanical harvesters (Gupta et al. 2003). However, based on the state level production data; this might
due to small window between the rice crop harvest have led to higher estimation of total crop residue
season and plantation of wheat, along with large burning in earlier studies.
labour cost in handling the rice crop residues, large
amount of rice crop residues are burnt in situ in the Baseline Emission from Crop Residue
states of Punjab, Haryana, and western Uttar Pradesh
Burning
(Gupta 2014). The IPCC coefficient for the in-situ
burning of crop residue is 25 per cent of total amount Based on the methodology described earlier, it is
of residue produced (IPCC 2006). Following the IPCC estimated that the emission of all pollutants was
(2006) factor, the total amount of crop residue burnt highest from the Muzaffarnagar district of the state
in India during 2011 was about 145 Mt. However of Uttar Pradesh (Figure 8.3). It is estimated that
in the present study, we have estimated that about significantly higher (4.4 Mt) sugarcane residues
56 Mt and 68 Mt of crop residues were burnt during were burnt in the district. Total emission of PM10
2001 and 2011 (Figure 8.2). Sahai et al. (2011) have was significantly higher (216 Kt) from the western
estimated 57 Mt and 63 Mt of crop residue burning, region of the state of Uttar Pradesh followed by the
respectively, during 2000 and 2010 in India. Street state of Punjab (158 Kt). However, PM2.5 emission
et al. (2003) have estimated approximately 132 Mt was significantly higher from the state of Punjab
of crop residue burning in India annually, which was (110 Kt) followed by the western region of Uttar
about 18 per cent of total biomass burning from Pradesh (100 Kt). Burning of rice crop residue (8.8
anthropogenic and natural sources in Asia. However, Mt) was significantly higher in the state of Punjab
earlier studies have estimated 98.5 Mt of crop residue after the harvest of the kharif crop. On the other
burning in a year in India (Jain et al. 2014). Pathak hand, burning of total crop residues was significantly
et al. (2010) have estimated 90 Mt of crop residue higher in Uttar Pradesh (21.5 Mt) with significantly
higher contribution of the sugarcane residue (17.5
 Open Burning of Agricultural Residue  •  127

Figure 8.3: Estimation of the emission of particulate and gaseous pollutants (Kt/year) from the in-situ
burning of crop residues during 2011

Mt). However, the emission factor of PM2.5 was higher burning during 2001 and 2011 were estimated as
with rice crop residue (7.8 g/Kg) compared to that 48 Kt and 57 Kt, respectively. During 2001, burning
of sugarcane (4 g/Kg). Significantly higher burning of sugarcane crop residue (BC: 27 Kt) was the
of the crop residue in the state of Uttar Pradesh largest contributor to total BC emission from the in-
was attributed to higher PM10 emission; however, situ burning of the crop residue. OC emission was
large amount of rice crop residue burning which also significantly increased during 2011 (128 Kt)
has higher PM2.5 emission factor among nine crops compared to 2001 (108 Kt). Similar to BC, emissions
considered in the present study increases the PM2.5 of OC was higher from the burning of the sugarcane
emission from the state of Punjab. The total emissions crop residues. Overall, BC emission from the in-situ
of PM10 and PM2.5 in India during 2001 were 619 burning of crop residue was significantly higher from
Kt and 350 Kt, respectively; whereas during 2011, the state of Uttar Pradesh (21 Kt) followed by Punjab
emissions increased to 818 Kt and 419 Kt, respectively. (10 Kt) and Haryana (6 Kt). OC emission also followed
The emission of different gaseous and particulate the same pattern. Higher BC and OC emission
pollutants due to in-situ burning of crop biomass was from the state of Uttar Pradesh was attributed to
significantly higher in the northwestern region of the significantly higher crop residue burning in the state.
IGP in India (Figure 8.3) during both 2001 and 2011. State-wise emissions of different gaseous
Venkataraman et al. (2006) and Sharma et al. (2010) pollutants from the in-situ burning of crop residues in
have also reported higher emission of pollutants from the field also followed the same pattern. Significantly
the crop residue burning in the northwester IGP. higher emissions of different gaseous pollutants
In-situ burning of crop residues contributes were recorded in the state of Uttar Pradesh during
significantly to the atmospheric BC and OC. Total 2011. Total emissions of CO, SOx, NOx, and NMVOC
atmospheric BC emissions from the crop residue during 2011 were 3244 Kt, 40 Kt, 137 Kt, and 511 Kt,
128  •  Air Pollutant Emissions Scenario for India
respectively. Among different crop residues, the residues or develop crop varieties with lesser
contribution of cotton (lint) crop residue burning amounts of residue generation.
towards gaseous emission of different pollutants
was recorded higher during 2001 and 2011. A Conclusion
comparative view of the reported emission of Large amount of particulate and gaseous pollutants
different pollutants from the in-situ burning of crop are emitted during in-situ burning of crop residues
residue is India is given in Table 8.3. in the crop lands in different parts of the country.
Emissions of all pollutants were significantly higher in
Emission Projections the western part of the IGP of India. However, almost
Emissions of different pollutants were estimated all regions of the country contributed towards the
to increase during 2011–51 (Figure 8.4). By the gaseous emission of the atmospheric pollutants.
year 2051, the increase of emission of particulates The type of crop residue burnt varies across state.
and gaseous pollutants would be significantly However, this study has estimated that the residue
higher from burning of soyabean crop residue of the rice crop is mostly burnt all over the country.
(approximately four times compared to 2011 Future prediction of emission of different pollutants
emissions) (Figure 8.4). During 2051, emissions from from in situ burning of crop residue suggests large
the in-situ burning of rice and wheat crop residues increase in the pollution emission by the year 2050,
would increase by 60 per cent and 82 per cent, if adequate measures to reduce the crop residue or
respectively, compared to their emissions during handling the crop residues are not developed.
2011. The key measures that are required to be taken
Over all, PM10, PM2.5, NOX, SO2, NMVOC, CO for control of emissions from open burning of
will increase by ................................ by percentage, agriculutural residue in India are:
respectively during 2011 to 2051. PP Imposition and strict enforcement of a ban on
However in the present estimates, we have open burning of agriculutural residue.
considered burning fraction of the crop constant till PP Development of biomass gasification technologies
2051. This may increase with increase in productivity for waste to energy generation from agricultural
of an individual crop due to crunch of space to store residue.
the excess crop residues. Oppositely, the burning PP Development of business model for collection
fraction may decrease if improved technology is storage and processing of agriculutral waste for
developed to effectively handle the excess crop waste to energy generation.

Table 8.3 Estimation of emission of different atmospheric pollutants from the in-situ burning of crop
residues in India
Year of Kt annum-1 Reference
estimation PM10 PM2.5 BC OC SOx NOx CO NMVOC
1994 78 2138 Gupta et al., 2004
2000 84 2305 Gupta et al., 2004
2000 3 6 33 541 Sahai et al., 2007
2001 572-2393 86-372 211-970 46-172 289-1290 10000-74000 1818-6767 Venkatraman et al., 2006
2006 8114 472 69 344 8114 633 Gadde et al., 2009
2010 658 Sharma et al., 2014
2011 384 68 246 7 9063 39 Jain et al., 2014
2011 818 462 49 57 40 137 3244 512 Present study
 Open Burning of Agricultural Residue  •  129

Figure 8.4: Emissions of different pollutants from the in-situ burning of crop residue in India

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CHAPTER 9
Evaporative Emissions
Sumit Sharma and Atul Kumar

Introduction cumulative assessment of the quantities of NMVOCs

released from the use of these products leads to
While there are pollutants emitted due to
substantial emissions. Hence, there is a need for an
combustion of fuels, there are activities that lead
accurate emission inventory of these emissions for
to fugitive emissions, mainly due to volatility of
their control.
the compounds used in the process. Mostly these
Limited work has been carried out in past on
are volatile hydrocarbons. These compounds
exhaustive estimation of emissions from these
are grouped as non-methane volatile organic
sources. In this study, NMVOC emissions are estimated
compounds (NMVOCs) as the majority of them
for different years between 2001 and 2051 based on
display similar behaviour in the atmosphere (DEFRA
the future growth trajectories. The ‘emission factor
2003). While considerable attention has been paid
approach’ is used in the current work for estimation
on control of pollutants such as particulate matter
of NMVOCs from different sectors and sources. A list
(PM), non-methane hydrocarbons have steadily
of probable sources of NMVOC was compiled from
grown unnoticed in India. NMVOCs not only have
literature review exercise. These sources includes
direct health impacts over the exposed receptors,
paints, printing inks, dry cleaning, handling of oil and
but they also act as important precursor of ground
solvent use in industries. Activity data for different
level Ozone formation and secondary particulates
sectors was collected and compiled form reliable
known as secondary organic aerosols (SOAs). There
sources. Emission factors are adopted from a recent
are multiple sources of these emissions including
work of Sharma et al. (2015), where detailed review
use of paints, printing inks, personal products,
was carried out to choose appropriate emission
etc. The solvent use in these products is small but
factors for different sources. The source-wise emission
134  •  Air Pollutant Emissions Scenario for India
inventory is presented in subsequent sections using types of solvents used, and mixing temperature.
folllowing equation: Industrial coatings in India are almost exclusively
solvent based. The only applications that are currently
E= Activity data × Emission factor × (1–% controls) employing water-borne technology are certain
automotive primers and high-end automotive
Paints refinishes. The production of industrial paints is found
Paints are used in both residential and industrial to be 0.67 mt in 2009 and about 0.9 mt in 2011(PI
sectors. Due to increased urbanization, it is noticed 2010), of which 44% accounts for paint used in auto
that there is a drastic shift from semi-permanent sector and coil coating, and rest is accounted for
to permanent housing structures, which has been industrial painting category. The distribution of paints
driving growth in decorative paints segment in the in plastic, general industry, continuous, and powders
domestic sector, which constitutes 77% of the 2.9 is adopted from PI (2011).
million tonne paint industry in India (Paint India 2011). During manufacture of automobiles, the
Per capita consumption of paint is about 1.6 Kg. The automobiles are painted and during this process
industry has grown to about 10–15% annually in large amount of NMVOCs are emitted in one or
last 5 years and is consistent with the growth of real the other forms. The activity data in this case was
estate sector in India. There has been a recent shift total number of vehicles manufactured in India,
towards water-based coatings in the recent past, and which were about 10.4 million during 2011. Paints
about 50% of the paints currently used for decorative used and emissions generated in the automobile
purposes are water based. About 65 per cent of manufacturing and vehicle repair were estimated
the demand for decorative paints is contributed to from the size distribution of different vehicles
repainting of houses, etc. Paints most commonly used manufactured in India (IBEF 2008). The weighted
in bigger cities are premium decorative paints (acrylic emission factor per unit vehicle manufactured is
emulsions) while medium range paints consisting of derived as 3.18 kg per vehicle and total emissions
enamels are more popular in smaller cities and towns. from the automobile manufacturing sector is
In India, nearly 11 per cent of all the decorative estimated to be 35 kt/year. The total paint consumed
paints are distempers, which are economical in the sector is 160 kt. A total of 21% of paints used
products, mostly demanded in the suburban and in automobiles come out as NMVOC emissions.
rural area. Considerable growth is observed in Coil coating is another process that requires
the exterior coatings segment, under decorative paints, as it is a continuous and highly automated
paint segment. Many superior quality paints with process for coating metal before fabrication.
high durability have been launched by many paint According to available data, the Indian domestic
manufacturers in India. Import of paints is about 4% market consumes colour-coated sheets in the
and export of paints is negligible. The total quantity thickness range from 0.2 to 1.2 mm and widths
of decorative solvent based paints consumed in between 600 and 1,250 mm. Recently, the imported
India is 1.32 million tonnes (mt). Emission factor galvalume colour-coated products and its plain sheet
(CITEPA 2003c) used for solvent-based paint is 400 (in small quantities) have gained popularity. In recent
kg/kt of paint used and for water-based paints is 102 years, colour-coated coils have gained importance
kg/kt. Total emissions estimated from the sector is in the domestic market and, consequently, their
582 kt/yr. consumption has accelerated during the last two
Industrial paints include powder coatings, high years across the country. The total coil coating
performance coating, and automotive and marine capacity installed in the country is 9,85,000 T/yr
paints. The primary factors affecting emissions from (Nagori and Ajemra 2006). Assuming an average
paint manufacture are care in handling dry pigments, thickness of 0.7 mm, total coated surface area
 Evaporative Emissions • 135

Table 9.1: Emission Inventory of NMVOC Emissions from Paint Usage in Different Sectors in India in 2011
Total Percentage of EF (kt/kt) Emission Factor Paints (mt) Emissions (kt)
Distribution source
Plastic 18% 0.75 CITEPA (2004) 0.09 67.5
General industry 29% 0.69 0.144 99.4
Continuous 29% 0.74 0.144 106.6
Powders 25% 0 0.126 0.0
Total industrial paints 273.4
Coil coating Emission factor used GAINSa Area of coils 5.5
is 0.04320 Kt/million 128 million m²
m².
Automobile paints 3.18 kg/vehicles Based on CITEPA 0.16 35
(weighted avg. for (2003d), IBEF
different vehicles) 2008
Decorative paints 50% solvent based 400 kg/kt GAINSa; CITEPA 1.33 534
(2003c)
50% water based 102 kg/kt 1.33 137
European version available from: http://gains.iiasa.ac.at.
a

amounts to 128 million sq. m in 2011. The coil coating Table 9.2: Surrogate Variable Used for Projections of Different
capacity is projected using industrial GDP growth to Non-Energy Sectors
2,895 million sq. m in 2051. S.No Sector Dependant Variable
The distribution of emissions from paints used in
1 Paints: Decorative Per capita income
industrial and residential sector in 2011 is shown in
2 Paints: Industrial Industrial GDP growth
Table 9.1.
Future projections of NMVOC emissions are made 3 Vehicle manufacturing Vehicular growth, number of
and refinishing road accidents
using regression analysis of various activities with
appropriate variables. The past 15 years data of the 4 Coil coating Industrial GDP growth
activity levels in different sectors were regressed

Figure 9.1: Examples of regression analysis carried out for projection of industrial and decorative paints in
India
136  •  Air Pollutant Emissions Scenario for India
against the selected variables. In the case of paints, emissions are estimated. The future projections of
regression equations were derived for projections NMVOC emissions from paint used are shown in
for future years after satisfactory correlations Figure 9.3. The total emission will grow from 944 kt
are observed between the paint consumption in 2011 to 19301kt in 2051. The automotive paint
and dependant variables (Figure 9.1). The list of emissions will grow from 34.5 kt to 54.6 kt during
dependant variable used for projections of emissions 2011–51 and emission form coil coating will grow
from sectors using paints are shown in Table 9.2. from 5.5 kt to 125 kt in the same period.
Based on the regression equations, the paint Vehicular refinishing is another activity that
consumption in residential and industrial sector generates NMVOC emissions. Vehicles are repainted
is estimated, as shown in Figure 9.2. With rise in or refinished due to different reasons. The NMVOC
industrial GDP and per capita income levels, the emissions from this category are linked to application
overall paint consumption will increase from 3.6 of paint, drying operations, cleaning of equipment,
mt in 2011 to 71.6 mt in 2051. Based on the future and cleaning operations before the coating and
estimates of paint use in different sectors, the between the applications of different layers. In India,

Figure 9.2: Future projections of paint consumption (mt) in India

Figure 9.3: Future projections of NMVOC emissions in India

 Evaporative Emissions • 137

Table 9.3 Total Use of Personal Products (kt) and NMVOC Emissions (kt) in India in 2011
Products Per Capita Consumption (g/yr) Volume (kt) Solvents (EF)* Emissions (kt) 2011
Facewash 7.2 8.0 65% 5.2
Perfumes 6.1 6.8 60% 4.1
Skin care 48.9 54.7 11% 6.0
Shoe polish 1.1 1.2 45% 0.6
Floor cleaning 14.0 15.6 5% 0.8
Glass cleaning 1.0 1.1 10% 0.1
Kitchen (liquid cleaners) 16.0 17.9 35% 6.3
Kitchen (solid cleaners) 304 339.6 3% 10.2
Detergents (liquid + powder) 2700.0 3015.9 3% 90.5
Shampoos 13.0 14.5 10% 1.5
Soap 460.0 513.8 5% 25.7
Hair oil 96.2 107.5 28% 30.1
Hair dyes/colour 9.5 10.6 44% 4.7
Colour cosmetics 0.1 0.1 44% 0.0
Shaving creams/toiletries 8.1 9.1 10% 0.9
Total     186
* Based on Umweltministerium Baden-Württemberg (1993)

the number of vehicles being refinished has been fresheners, furniture polishes are the potential
estimated broadly using the data on accidents that source of NMVOC emissions. Other household
occurred in a year with an assumption of 50% of products including detergents, floor cleaners, etc.
those going for refinishing. Moreover, the paint used are although having lesser solvent content but
per vehicle is also assumed to be half of the overall could be important source in the overall inventory.
paint used in manufacturing. Indian personal care industry is valued at USD 4
On this basis, the total emissions from this activity billion including different types of products. The
are estimated to be 3.3 kt in 2011, which reduces to figures for the consumption of the personal care
almost negligible in future with anticipated reduction products are derived using:
in the rate of accidents. The weighted emission factor PP per capita consumption values
used for all vehicles is 12 kg per vehicle (higher PP by converting the monetary units (market shares
emission factor due to higher percentage of heavy of different products) to volumetric forms using
vehicles going for refinishing). market prices (Rs/mL) of the major products in
each of the categories.
Personal and Home Care Products
The solvent-based products used in houses include In abssence of readily availabel information on
personal care and household care products. The Indian products, the solvent content of the different
personal care products such as hair care, skin care, types of personal and home care products is adopted
oral care, personal wash (soaps), cosmetic and from Umweltministerium Baden-Württemberg (1993).
toiletries, feminine hygiene, disinfectants, room The overall estimates of different personal products
138  •  Air Pollutant Emissions Scenario for India
used in India and the related emissions from the in India during 2011. It was estimated based on
solvent use in baseline year are presented in Table 9.3. percentage of households in rural and urban India
The total emissions from personal and home using laundry services. A total of 50% of it was
care products consumption in India are estimated assumed to be dry cleaned. NSSO (2012) shows that
to be 186 kt in 2011. Based on this an emission 4% of rural households and 11% of urban households
factor of 0.16 kt of NMVOCs per million populations are using dry cleaning facility. As per the per capita
can be derived. Use of personal products is expenditure estimates on dry cleaning, the net
highly dependent on per capita income levels in weight of textile undergone for dry cleaning during
the region and the same is used as a variable to 2011 was estimated to be 7.8 kt. Using average
project the consumption of personal products and emission factor of 0.177 kt/kt weight of textiles, the
corresponding NMVOC emissions in future. With NMVOC emissions are estimated to be 1.2 kt/yr. The
growing economy and income levels, the NMVOC emissions from the activity are projected for future
emissions in future from the personal and home care years using per capita income as the influencing
product use in India is expected to grow from 186 to variable. It is estimated that the emissions will grow
2,173 kt during 2011–51 (Figure 9.4). This is assuming from 1.2 to 13.7 kt during 2011–51.
no interventions for control of solvent use in the
products. Extraction, Processing, and Distribution
of Gaseous Fuels
Dry Cleaning The gaseous fuels are extracted directly from a gas
It is the cleaning process for clothing and textiles field or as part of the mixture from an oil and gas
using a chemical solvent other than water. The field. During extraction by heating systems, lighting,
solvent typically used for this is tetrachloroethylene pumps and compressors, large amount of energy
(perchloroethylene). Other solvents used during (electrical energy supplied by gas turbine generators)
this process are Glycol ethers, hydrocarbons, liquid is being consumed. Other than energy consumed,
silicone, liquid CO2, perchloroethylene, etc. In India, there are fugitive NMVOC emissions from not only
Mineral Turpentine Oil is commonly used while the extracting, but transport, storage, and handling of
use of perchloroethylene has also started. gaseous fuels. After extraction, minimal processing of
The activity used to estimate emissions from this natural gas is carried out at the terminals prior to the
exercise is the total weight of textiles dry cleaned long distance transmission through pipeline network

Figure 9.4 Future projections of emissions from personal and home care products in India
 Evaporative Emissions • 139
(distribution system). During processing, activities such as distribution of gas and the estimation
mainly required are removal of hydrogen sulphide process is depicted in Table 9.4, which shows different
from gas and drying—which results in sulphur emission factors for losses in pipelines, compressors,
dioxide emission as the main ingredient. After and others.
production and on-shore processing, natural gas is The emissions are projected for future years using
fed directly into the distribution system. TERI analysis for energy modelling exercise (TERI
The activity data in this case is total natural gas 2015) for natural gas production and use in India
production in the country, which is ~47,500 mmscm during 2001–51 (Figure 9.5).
in 2010/11, of which 18% is on-shore production.
The emission factors used to estimate the emissions Extraction, Processing, and Distribution
during extraction are 0.968 g/m³ for onshore and of Liquid Fuels
0.1426 g/m³ for off-shore facilities (average of many
The liquid fuels are mainly composed of crude oil (a
countries assumed from CORINAIR, 1990). Total
complex mixture of hydrocarbons with very different
NMVOC emissions are estimated at 6.3 kt/yr for 2011.
chemical and physical properties). The extraction
NMVOC emissions are also estimated for activities

Table 9.4: NMVOC Emissions from Gas Distribution in 2011

Activity Natural Gas Production (MMSCM) Emissions Factor ((g/m3)* Emissions (kt/yr)
Onshore Offshore   Onshore Offshore Total
Production 8684 38826 Onshore :0.0968 0.8 5.5 6.3
Offshore :0.142
Distribution**
General 1.38 16 74 90
Pipelines 0.01 0.1 0.6 0.7
Compressors 0.07 0.8 3.6 4.4
Network 0.78 9.4 41.9 51.3
 Total   146.8
*Source : EEA,1999; ** including imports

Figure 9.5: Projections of NMVOC emissions from gas extraction and handling in India (2001–51)
140  •  Air Pollutant Emissions Scenario for India
of crude is the first step. The route from extraction Table 9.5: Emission Factors for Loading and Transit Losses for
to individual use (refined components) includes Oil Handling
storage, refining, transport, and filling of the fuel. Transit Losses (Loading + Transit) EF (mg/L)
The processing of crude oil, aimed at separating the
Crude 580
mixture into groups of chemicals (identification of
them with similar properties for use in particular Gasoline 1430
applications). Refineries have many different Others 4
combinations of process units such as distillation Naptha 430
column. The last step is distribution of products
(could be through combination of pipeline, road, m³ is assumed with 75% filling to arrive at the
rail, or even tanker) from the refinery to the point of total number of tanks required. TANKS model takes
end use that could be either a single- or multi-stage into account the tank geometry, meteorological
process. conditions (typical conditions given for Indian
Emissions have been estimated for each of these conditions), and the type of fluid stored. The
steps: emissions in this case are estimated for crude
PP Extraction: Total crude extracted in India is 39 mt stored at ports and refineries and the petroleum
in 2011 (MoPNG 2012). The emission factor used products stored at refineries and bulk terminals.
to estimate NMVOC’s from extraction was taken The estimated emissions due to storage of crude
as 475 g/tonne of crude (Lewis 1997), and NMVOC and other petroleum products are estimated to be
emissions from the activity is estimated to be 19 around 9 kt/yr.
kt/yr. PP Transit losses: Transit losses occur when crude/
PP Storage of crude: Crude is stored in big tanks that petroleum products move over road/rail. The
are an important source of NMVOC emissions. emissions factors used for estimation are shown in
These are called working and breathing losses. The Table 9.5. The transit losses are accounted for rail/
emissions from this activity are computed using road travel and not for the pipelines. In India, 30%
the TANKS model (http://www.epa.gov/ttnchie1/ of fuel is transported through pipelines and hence,
software/tanks/). Typical tank capacity of 60,000 emissions are reduced by 30%. The total emissions
from transit of fuel are estimated to be 122 kt.

Figure 9.6: NMVOC emissions from oil extraction, refining and handling
 Evaporative Emissions • 141
PP Refining: A total of 213 mt of crude is refined in systems (tanks, injection systems, and fuel lines)
2011. An emission factor of 0.9 kt/mt of crude of gasoline vehicles and emissions from diesel
is adopted and emissions are estimated.Total vehicles are considered negligible (TRL 2009). In
NMVOC emissions from refining activities are 191 this study, the evaporative emissions from these
kt in 2011 and are projected to grow to 1696 kt in sources are estimated using the energy consumed
2051. in each of the vehicle category and emission
PP Emissions during fuel filling at the pumps: factors listed in Table 9.6.
Emissions at the fuel pumps are accounted using a
no-control emissions factor of 2.6 g/kg of gasoline It is to be noted that there is a Type IV standard
filled. After 2030, stage-II control norms have been for evaporative emissions in BS III and IV four
assumed that lowers the emission factor to 1.6 g/ wheeled vehicles while there is no standard for two
kg. The emissions from this activity are estimated wheelers. However, two wheelers will be subjected
to be about 30 kt in 2011, which is expected to go to evaporative emission test starting from BS IV in
up to 197 in 2051, despite introduction of stage-II 2016 for the first time. Based on these controls, the
controls. Figure 9.6 shows the NMVOC emissions emissions for different years are estimated using the
from fuel extraction, working , transiting, refining energy consumption projected for different category
and filling operations in India. of vehicles using TERI-MARKAL model results (Figure
PP Evaporative emissions from vehicles: There are 9.7). The evaporative emissions from vehicles are
significant evaporative emissions from different projected to increase from 279 kt in 2011 to 257kt in
categories of vehicles. Most volatile organic 2051.
compound (VOC) emissions generate from fuel

Figure 9.7: NMVOC evaporative emissions from vehicles in India during 2001–51

Table 9.6: Evaporative Emission Factors (kt/PJ) for Different Vehicles

No-control Euro-I Euro-II Euro-III Euro-IV Euro-V

2w/3w 0.60696 0.60696 0.60696 0.60696 0.17602 0.0789

Cars 0.60696 0.17602 0.0789 0.04856 0.02428 0.01821
Source: GAINS ASIA, 2015
Printing collected from the Prowess database. The printing
ink produced during the year 2011 is estimated to
Printing can be broadly categorized into four types:
be 155 kt. Exports of ink is subtracted to derive the
offset, flexography and rotogravure in packaging,
consumption volumes in India. Based on ITALIA
rotogravure in publication, and screen printing.
(2010) and further discussion with industrial experts,
Major printing ink components include clear and
colour concentrates (pigments or dyes), a solvent,
Table 9.7: Printing Ink Consumption for Different Uses and
and pigment and, a binder resin. Organic solvents Corresponding NMVOC Emission Factors
are used almost exclusively with pigments. Emissions
Printing Type Ink Usage EF (kt/kt) No Control
from the printing activities depend on the total (Percentage of Total)
amount of solvent used in inks. The sources of these
Packaging 40% 2.2
VOC emissions are the solvent components in the raw
Offset 35% 0.72
inks, related coatings used at the printing presses, and
Publication 20% 2
solvent added for dilution and press cleaning. The
data for printing ink produced in India as a whole was Screen 5% 1

Figure 9.8: NMVOC evaporative emissions (kt) from printing activities in India during 2001-2051

the usage of ink in the four categories is broadly forecast the future production of inks. Based on this,
distributed to 40% in packaging, 35% in offsetting, the NMVOC emissions of 245 kt in 2011 are projected
20% in publications, and 5% in screen printing to grow to 3,842 kt in 2051 (Figure 9.8).
activities. Finally, specific emission factors (CITEPA
2003a, b) for each of the categories of printing were Industrial Process Emissions
used to estimate NMVOC emissions as shown in Table There are number of industrial processes which
9.7. generate NMVOC emissions in different quantities.
The future projections of printing emissions are
made using the growth of per capita incomes as it is Fat, Edible, and Non-Edible Oil Extraction
found to be linked to the growth of printing industry. Vegetable fats, edible oils, and non-edible oils are
The data on consumption of printing inks in India extracted from various natural products. Examples
is regressed with the per capita income levels to
of inedible vegetable fats and oils include processed production in India are projected using the per
linseed oil, tung oil, and castor oil. The estimation of capita income as a surrogate. The emissions will
NMVOC emissions from edible and non-edible oils grow from 3.6 kt in 2011 to 42.5 kt in 2051.
production is made using the annual production of Beer production in India is estimated to be about
these commodities. In India, about 30 mt of oil seeds 700 million litres in 2011. Emission factor is adopted
were produced in 2011 (MoFPI). However, only soya from AP-42 Emission Factor Database (www.epa.
bean oil is recovered through the solvent extraction gov/ttnchie1/ap42/ch09) as 0.035 kg/L. Total
techniques and rest depend on crushing (with only emission from beer production turns out to be 25 kt
10% as crushed cake is processed through the use of in 2011, which is projected to increase with growing
solvents). Hence, 14.4 mt of seeds are processed using income levels to 454 kt in 2051.
solvents. The emission factor used is 0.003 kt/kt (GAINS
Asia, 2015) and total emissions are estimated to be Industrial Application of Adhesives
43.1 kt/yr in 2011,which are projected to 264kt in 2051 An adhesive is a compound that adheres or bonds
based on growth expected in agricultural GDP. two items together to form a single unit. Raw
materials required for adhesives are different
Food and Drink Industry resins, solvents, preservatives. The global market
Food industry undergoes processing of food for adhesives and sealants is growing at about the
and includes methods and techniques used to rate of GDP, with significant variations between the
transform raw ingredients into food for human regions. There are several commercial combinations
consumption. India’s food processing sector covers of multi-component adhesives in use in industry
fruit and vegetables; meat and poultry; milk and such as polyester resin—polyurethane resin,
milk products; alcoholic beverages; plantation; grain polyols—polyurethane resin, Acrylic polymers—
processing; and other consumer product groups polyurethane resins. These solvents involved in
such as confectionery, cocoa products, soya-based adhesives result in NMVOCs generation.
products, mineral water, high protein foods, etc. The The production of adhesives was found to be
processing involves use of many solvents in food about 60 kt/yr in India (IP 2010). Emission factor
and drink industry. NMVOC emissions from this adopted is 0.78 kt/kt for no-control conditions.
sector is mainly expected from bread production Therefore, total emissions were estimated as
and distilleries. The data for the production of food 66 kt in 2011, which is projected to increase with the
and drink was collected from the MoFPI (2012). The industrial GDP growth to 1,481 kt in 2051.
bread production in India is about 2.52 mt in 2010.
The method used to estimate emissions from this Production of Paints, Inks, and Adhesives
sector is adopted from AP-42 (Chapter 9). Other than the usage, the production processes of
VOC E.F. = 0.95Yi + 0.195ti – 0.51S – 0.86ts + 1.90 paints, inks, and adhesives also generate emissions.
Where A general emission factor used here is 0.00715 kt/kt
VOC E.F. = pounds VOC per ton of baked bread of production (GAINS ASIA, 2015). The emissions are
Yi = initial baker’s percentage of yeast (2%) estimated as 27 kt in 2011, which is projected to grow
ti = total yeast action time in hours (12 hrs) to 540 kt in 2051 with growth in production of paint,
S = final (spike) baker’s percentage of yeast (1%) inks, and adhesives (Figure 9.9).
ts = spiking time in hours (1 hr)
Organic Chemical Industry, Storage
Based on this, the emissions factor for bread
The organic chemicals are stored in tanks to avoid
production is estimated to be about 3.4 lb/ton of
hazardous effect on the environment. These tanks
bread produced. The total emissions from bread
then release VOCs emissions because most of the
144  •  Air Pollutant Emissions Scenario for India

Figure 9.9 NMVOC emissions from production of paints, inks, and adhesives

compounds are volatile and evaporate at normal Polystyrene, PVC, and Ethylene
conditions.
Processing
Production of organic chemicals in India was 1,279
Production of Polystyrene (PS), PVC, and ethylene
kt/yr (MoCF 2011). It was assumed that capacity of
also leads to generation of NMVOCs. PS, also called
tank is about 800 m3 and tanks are 75% filled. Based
thermocole, is an aromatic polymer made from
on this, total number of tanks required for storage of
the monomer styrene, a liquid hydrocarbon that
40 days was estimated. TANKS model software is used
is manufactured using petroleum in the chemical
to estimate the emissions during storage of organic
industry. Foamed PS is used for packaging purposes
chemicals. The emissions for 2011 are estimated to be
of chemicals, but it does not come into contact with
10 kt/yr. The organic chemical production is regressed
the actual solvents. The data on total PS, PVC, and
with the industrial GDP for future projections. The
ethylene manufactured for different years is taken
emissions are projected to grow 29 kt in 2031 and 38
from MoCF (2011). The emission factors used are
kt in 2051.
0.06 kt/kt, 0.03 kt/kt, and 0.0034 kt/kt for PS, PVC, and
ethylene production, respectively. The PS, PVC, and

Figure 9.10: NMVOC emissions (kt) from PS, PVC, and ethylene processing in India (2001–51)
 Evaporative Emissions • 145
ethylene production in 2011 is about 296 kt, 1,278 kt, Tire Production
and 3,216 kt, respectively (MoCF 2011). Of the total
There are various activities that emit VOC at certain
PVC production, 80% is through suspension process
stages of the manufacturing process of tyres and also
that leads to NMVOC emissions (CPCB 2008). Seventy
in offset natural drying sector. The tyre production for
per cent of ethylene production is through steam
the year 2010 was taken from the Prowess database,
cracking in India. The future estimates of production of
which is about 1,781 lakh numbers (including cycle
the three compounds were made using the regression
tyres, passenger cars, etc.). Total weight of tyres
with industrial GDP. The emissions for different years
produced estimated based on standard sizes and
are presented in Figure 9.10. The emissions are
weights for different tyre categories. The total weight
expected to grow from 59 kt in 2011 to 454 in 2051,
of tyres produced was estimated to be 1,248.32
mainly due to higher growth in PVC production.
kt. The emission factor used is 0.01 kt/kt and total
NMVOC emissions are estimated to be 14 kt in 2011,
Synthetic Rubber Production
which is projected to increase to 23 kt in 2051. The
Synthetic rubber is produced through butadiene projections are made based on increased number of
(a by-product of petroleum refining) and styrene vehicles and demands for tyres.
(captured either in the coking process or as a
petroleum refining by-product). Two types of Winding Wire Coating
polymerization reaction are used to produce styrene- In India, almost 88% of wires are in plain carbon steel
butadiene copolymers—the emulsion type and the grades, 5% are in stainless steel, and remaining in
solution type. This activity addresses VOC emissions alloy steel wires. In the plain carbon wire category,
from the manufacture of copolymers of styrene about 20–25% is in the Galvanized Wire sector or
and butadiene made by emulsion polymerization copper-coated, bronze-coated, and others in coating
processes. The amount of synthetic rubber produced materials. A total of 75–80% of this is in the form of
in kilotonnes for the different years is estimated black/uncoated wires only. During coating of wires,
based on natural rubber production and its share large amount of solvents are used, thereby releasing
in total rubber production from George and VOCs.
Chandrashekar (2014). The emission factor used is The emissions were calculated on the basis of
0.021 kt/kt and total NMVOC emissions are estimated total quantities of wire coated in year 2011. The
to be 8.1 kt in 2011, which is expected to increase to production of wire was estimated to be around 2.68
20 kt in 2051. million tonnes of which 25% is coated. The emission

Table 9.8: Sector-Wise Inventory of NMVOCs (kt/yr)

Source 2001 2011 2021 2031 2041 2051
Paints* 288 988 2484 5537 10857 19481
Personal & homecare 98 186 366 714 1287 2173
Dry cleaning 1 1 2 4 8 14
Gaseous fuel handling 43 153 181 289 424 695
Oil Handling 198 258 371 539 738 992
Printing 58 245 571 1201 2239 3842
Industrial processes 122 238 486 956 1749 2990
Total 808 2068 4460 9241 17301 30187
*Paints include decorative, industrial, coil coating and automobile paints.
146  •  Air Pollutant Emissions Scenario for India

Figure 9.11: Growth of NMVOC emissions in India (2001–51)

factor used is 0.0168 kt/kt and total VOC emissions will grow and consumption of paints, printing inks,
released amounts to 11.8 kt in 2011. The emissions and personal products will increase significantly.
are projected to grow to 138 kt in 2051. While there are regulations in place for control of
PM and to some extent for gaseous pollutants such
Total Evaporative Emissions as NOx and SO2, there are hardly any regulations
The source-wise inventory of evaporative NMVOC for control of NMVOC emissions. This is the primary
emissions in India is presented in Table 9.8 and reason for steady growth of projected NMVOC
Figure 9.11. The evaporative NMVOC emissions emissions in a business as usual scenario.
are expected to grow by almost 15 times during
2011–51. Sectoral distribution shows that emissions Conclusions
from paints, printing, and personal products will Evaporative emissions of NMVOCs are gradually
grow significantly with rise in per capita income increasing unnoticed. These emissions can have
levels. Paint industry is expected to grow at the serious implications over human health, ozone
fastest rate and corresponding emissions will grow formation, and SOA (Secondry Organic Aerosols)
by 20 times during 2011–51, followed by 16 and 12 formation. There are very limited regulations in place
times growth in NMVOC emissions in printing and for control of solvent use, manufacturing of low
personal products sectors. Most of these sources VOC products, and control of fugitive/evaporative
of evaporative emissions are linked to the growth emissions of VOCs. Some efforts are made by the
of economy and income levels. With projected industry in this direction mainly due to market
economic growth and income levels, these sectors demands for greener products. Projections for
 Evaporative Emissions • 147

Table 9.9: NMVOC Control Strategies

Sector Control strategy
Paints Mandating low VOC paints for decorative and industrial use
Printing Solvent free inks and enclosure
Tyre Process optimization
Wire Low solvent content of enamel, and secondary measures (increased efficiency of the oven)
Dry cleaning Dry cleaning conventional closed circuit machine
Gasoline distribution - service stations Stage II vapour recovery systems at service stations
Fat oil Activated carbon adsorption
Adhesives Activated carbon adsorption
PS Expandable PS beads consumption-incineration
PVC Suspension process stripping and vent gas treatment
Manufacture of vehicles Adsorption, incineration, process modification, and substitution
Coil Incineration
Organic chemical storage Vapour recovery systems
Refinery Leak detection and repair programs

industrial sector show a strong competitive growth forums/egtei/17-Synopsis-sheet-decopaint-29-09-05.

that may lead to higher use of solvents and emissions pdf>, last accessed on September 4, 2015.
of NMVOCs. However, in attempt to keep the costs of CITEPA. 2003d. Final background document on the
production down, the market competition may lead sector - Car coating. Paris: CITEPA.
to increased rate of recovery and reuse of solvents.
CITEPA. 2004. Industrial applications of paints, prepared
Despite this, there is an urgent need to have specific
in the framework of EGTEI. Paris: CITEPA. Available
strategies in place for control of NMVOC emissions
at: <http://citepaax.alias.domicile.fr/forums/egtei/
from various sources. Table 9.9 shows a list of organic_chemical_industry_version2-280405.pdf>>,
strategies that could be employed for their control. last accessed on September 4, 2015.

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emissions, prepared in the framework of EGTEI. Paris:
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ec.europa.eu/environment/archives/air/stationary/ CORINAIR. 1990. Database. Copenhagen, Denmark:
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4, 2015. implications of chlorine and its compounds. New Delhi:
CITEPA. 2003b. Heat set offset, prepared in the Central Pollution Control Board.
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citepaax.alias.domicile.fr/forums/egtei/heat_set_ 2001. Fifteenth Annual Report from the UK National
offset.pdf>, last accessed on September 4, 2015. Atmospheric Emissions Inventory (NAEI). London, UK:
CITEPA. 2003c. Architectural and domestic use of Department for Environment, Food and Rural Affairs.
paints, prepared in the framework of EGTEI. Paris: GAINS ASIA. 2015. Austria: IIASA. Available at: <gains.
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George, J. G., and H. M. Chandrashekar. 2014. Growth MoPNG, 2012. Indian petroleum and natural gas
and trends in production and marketing of natural statistics, 2010-11. New Delhi: Ministry of Petroleum &
rubber in Kerala, India. Indian Journal of Current Natural Gas, Government of India, New Delhi.
Research and Academic Review 2(8):53–61.
Nagori, S. H., and S. Ajmera. 2006. The industry and the
IBEF.2008.Automotive market & opportunities.Gurgaon, coil coating market in India. Steel Grips 4(3)
Haryana: Indian Brand Equity Foundation. Available at:
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<www.ibef.org/download/Automotive_250608.pdf>,
–2010/11. D. Raghavan, ed. Mumbai: Paint India.
last accessed on September 4, 2015.
Available at: <http://www.paintindia.in/PDFs/
IP. 2010. The power of adhesive. Indian purchase, Paintindia_DR_Industry_Summary_2011.pdf>, last
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<www.Indianpurchase.com>, last accessed September
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ITALIA. 2010. Indian printing industry profile 2010. www.paintindia.in/PDFs/Paintindia_DR_Industry_
Available at: <http://italiaindia.com/images/uploads/ Summary_2011.pdf, last accessed September 4, 2015.
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Sharma, S., A. Goel, D. Gupta, et al. 2015. Emission
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CategoryId¼687>. Stuttgart, Germany.
CHAPTER 10
Other Sectors
Jai Malik and Sumit Sharma

Introduction PP Agricultural activities such as soil cultivation,

harvesting, cleaning, and drying;
The emissions from major pollutant sources have
PP Waste gas flaring; and
already been covered in the earlier chapters.
PP Crematorias.
However, there are certain sources of air pollution
that are not covered in these heads and seem too
These activities generate comparatively smaller
insignificant as compared to other sources. This
quantities of emissions at the National scale, but
chapter presents the emission inventory of other
could be significant at the local levels. The activity
unconventional and comparatively smaller sources
data are collected and appropriate emission factors
that also contribute in deterioration of air quality.
(EFs) are applied to estimate the emissions of
These emission are significant when considered
different pollutants from these sources. Emissions
cumulatively. Also, understanding the unconventional
from all these sub-sectors are then cumulatively
sources of pollution can be a cue towards filling the
compared to the emissions from conventionally
knowledge gaps one comes across, especially, while
well-known sources such as transport, industries,
understanding the dynamics air pollution of a region
household cooking, etc. Each of these ‘other sectors’
at a local level.
emissions are presented in subsequent sections.
This chapter focuses on following ‘other sources’ in
terms of their contribution to air pollution:
PP Handling and burning of waste;
Waste Handling and Burning
PP Storage, handling, and transportation of coal and Management of municipal solid waste (MSW) is a
cement; major problem in India. Most of the waste produced
150  •  Air Pollutant Emissions Scenario for India
goes uncollected. And, most of the collected countries 60 per cent of the uncollected waste is
waste ends up in landfills that are not scientifically burnt (IPCC 2006). These numbers were used to
designed for proper management and disposal. calculate the amount of MSW burnt in any given year
Since collection efficiency is low in towns and almost using the following Equation 10.1.
negligible in rural areas, some parts of waste is also W = MSWP × Popl. × (1–Fcoll.) × Bfrac .............................(10.1)
burnt in open for volume reduction and heating W = Waste burnt
purposes during winters. This adds to the emissions MSWP = Per capita waste produced
loads in the regions. Moreover, the waste in landfills Popl. = Population
is another source of pollution. These emissions are Fcoll. = Collection efficiency(0.68)
directly linked with the quantity of waste produced. Bfrac = Fraction of waste burnt (0.6)
Thus, the basic information required to estimate
emissions from the waste sector is the quantity of Out of the total waste generated, Figure 10.2
waste produced and burnt in the country. It was shows the estimates of refuse burnt over the years in
estimated that the per capita waste generation India. The refuse burnt is expected to increase from
rate increases by 1.33 per cent annually (Pappu et 27 MT to 44 MT during 2011–51.
al. 2007). Based on this and population projections, Table 10.1 shows the EFs for different pollutants,
Figure 10.1 shows the total generation of MSW for which have been used to estimate the pollutant load
2001 and 2011 and projections for 2021, 2031, 2041, emitted from refuse burning activity.
and 2051. The waste generation has increased from These EFs were used to estimate the emission load
almost 42 mt in 2011 to 160 mt in 2051. using Equation 10.2.

Refuse Burning Emission from refuse burning = E.F × W..................(10.2)

For assessment of refuse burning in India, the data
on waste generated, collection effieciencies, and Landfills
fraction of waste burnt, were collected. It is found that Since all kinds of waste are dumped in landfills in an
collection efficiency of MSW is about 68 per cent in unplanned manner, they practically become a huge
urban areas. It is assumed that waste is not collected store pile of wastes of various chemical and physical
at all in rural areas. The per capita waste generation compositions. Activities like movement of trucks on
in urban India is adopted as 0.45 kg/day. (Planning unpaved roads, flaring, un-planned fires, etc. make
Commission 2014). (Shah et al. 2012) has estimated a landfills a source of air pollution. The pollutants
corresponding value for rural areas as 0.29 Kg/day. As released from landfills directly depend upon the
per IPCC guidelines, it is assumed that in developing quantity of waste. According to a report on status of

Figure 10.1: Total municipal waste (kt) produced in urban areas in India
 Other Sectors • 151

Figure 10.2 Estimates of refuse burning (mt) in India during 2001–51

Table 10.1: EFs for Burning Waste Table 10.2 EFs for landfills
Pollutant Emission factor Unit Pollutant EF in Kg/MT
PM2.5 9.8 Kg/T
PM10 8
PM10 11.9 Kg/T
PM2.5 5.44
NOx 3.74 Kg/T
SO2 0.5 Kg/T CO 42
VOC 14.5 Kg/T SOx 0.5
CO 38 Kg/T NOx 3
BC 0.65 Kg/T VOC 21.5
OC 5.27 Kg/T Source: USEPA, AP42 EF database
SO2 – Sulphur Dioxide; VOC – Volatile Organic Carbon
BC – Black Carbon ; OC – Organic Carbon
Figure 10.3 shows the combined emissions
Source: Woodall et al. (2012) & Pappu et al. (2007) from the waste sector in India. The most significant
pollutant emitted from the waste sector is CO, and
MSW management by CPCB in 2012, 68 per cent of further increase in CO emissions is expected over
the waste produced in urban areas is collected, out of the years; an increase from almost 2,000 kT in 2001
which, almost 28 per cent is processed (CPCB 2012). to 5,600 kT in 2051. VOCs and particulate matters are
It is assumed that the remaining unprocessed waste some other pollutants emitted from the waste sector
ends up in landfills. Thus, yearly waste in landfills can in relatively higher quantities.
be calculated as per Equation 10.3.
Storage, Handling, and
Waste in landfills = Collected waste
– processed waste.....................(10.3)
Transportation of Coal and Cement
It is well known that pollutants such as particulate
The EFs in Table 10.2 were used to calculate matter are generated in extraction of coal
pollutant emissions from landfills using Equation 10.4: and production of cement. However, dust is
also generated during storage, handling, and
Emissions = EF × Waste in landfills............................(10.4) transportation of these products. These fugitive
emissions are directly dependent on the quantity of
152  •  Air Pollutant Emissions Scenario for India
product produced or consumed. Figure 10.4 shows Equation 10.5 was used to estimate fugitive
TERI’s projections for coal consumption and cement emissions from coal and cement in the future as
production in India. shown in Figure 10.5. It can be seen that substantial
The EFs used for estimation of fugitive emissions increase in the emissions of particulate matter is
are presented in Table 10.3. expected.

Table 10.3 EFs for Fugitive Emissions from Coal Emissions = EF × production.......................................(10.5)
and Cement
Product Pollutant EF Source Waste Gas Flaring
Coal PM10 0.042 kg/T EEA 2013 Oxidation of hydrocarbons in industrial waste gases
Coal PM2.5 0.005 k g/T EEA 2013 at high temperature is called flaring. Flaring is used
Cement PM10 0.46 kg/T CPCB 2007 to dispose waste products from refineries and waste
Cement PM2.5 0.055 kg/T Derived from PM2.5/PM10 gases emerging from:
ratios from AP42 PP Chemical industries
PP Oil wells

CO

VOC
PM10
PM2.5
OC
NOx

Figure 10.3: Emissions from waste (landfills and refuse burning) sector

Figure 10.4 Coal consumption and Cement production in India during 2001-2051
 Other Sectors • 153
PP Blast furnaces Dust from Agricultural Operations
PP Coke ovens Dust is generated during various agricultural
operations. A large portion of the emissions from this
Apart from apparent problem of heat and noise, sector can be on account of agricultural tilling, which
flares also produce pollutants such as un-burnt includes soil cultivation and crop harvesting. These
hydrocarbons, carbon monoxide, particulate matter, activities include movement of agricultural vehicles
oxides of nitrogen, and sulphur dioxide, depending on unpaved roads, wind-blown particles, application
upon the composition of the gas. Estimates of gas of pesticides, etc. The settled particulate matter is also
flaring have been made using the outputs of the re-suspended because of activities on agricultural
TERI-MARKAL model exercise. Figure 10.6 shows the land. According to EEA emission inventory guidelines
quantity of gases (in terms of energy) that is expected 2013, the emissions from this sector primarily
to be flared in future. depends upon the climatic conditions, type of activity
EFs, as shown in Table 10.4, have been used to undertaken, and the type of crop cultivated. To
estimate the emissions using Equation 10.6. calculate PM10 and PM2.5 emissions from this sector,
the EF are selected for different types of activities
Emission = E.F × gas flared (10.6) on the agricultural field—soil cultivation, crop
harvesting, cleaning, and drying. These emissions
The estimated emission loads of various also depend on the types of crops cultivated. The EEA
pollutants from the gas flaring activities are shown guidelines suggest emission factors for various types
in Figure 10.7. Of all the pollutants emitted from of crops—wheat, rye, barley, oat, grass, and others.
waste gas flaring, the highest emissions are of CO, On this basis, the crops grown in India were further
which is about 23 Kt in 2011. It is projected that divided into three broad categories—wheat, rye, and
emissions from this sector will be consistent in the others. Some of the crops such as cotton, sugarcane,
coming years.

Figure 10.5: Fugitive emissions from coal and cement storage and handling during 2001–51
154  •  Air Pollutant Emissions Scenario for India

Figure 10.6 Estimates of gas flaring (PJ) in India during 2001-2051

Source: (TERI, 2015)

Table 10.4 EFs of Flaring Waste Gases corresponding emissions are made. The percentage
of Hindus and Sikhs in India is about 81.3 (GoI 2001).
Pollutant EF in kg/PJ
Even though the electric crematoria have come up
Total HC 0.060 over the years, but because of their unpopularity
CO 0.159 and unavailability at most places, it is assumed that
NOx 0.029 a very insignificant number of bodies are cremated
Source: USEPA, AP42 EF database there. On an average 350 kg of wood is burnt in each
cremation (NEERI 2010). Thus, total wood burnt every
groundnut, maize, etc. are covered in the ‘others’ year all over India was estimated using Equation 10.8,
categories. Table 10.5 shows the EFs for PM10 and based on the population projections in TERI analysis
PM2.5 from this activity in agriculture sector. till 2051 and death rates. Figure 10.10 shows the
The data on district-wise area of cultivation is projections.
collected from MoA (2001). The estimated increase in
the areas of crops cultivated based on TERI’s analysis TW = P × F × DR × 350 kg.............................................(10.8)
for energy sector modelling is shown in Figure 10.8.
PM10 and PM2.5 emissions were calculated using the TW = Total wood burnt
following equation. The results are shown in Figure P = Total population
10.9. F = Fraction of Hindus and Sikhs
DR = Death rate
Emissions = E.F × Cultivated area ..............................(10.7)
The trends of crude death rate for India as reported
The PM10 emissions are estimated to be 181 kT in in WHO (2012) for the years 1950 to 2005 were used
2011 and 214 kT in 2051. to project death rate in future, as shown in Table 10.6.
The fraction of Hindu and Sikh population is assumed
Crematoria to be constant.
The following EFs were used for calculating
Significant quantities of wood is combusted
emissions using Equation 10.9.
during creamation ceremony in the Hindu and
Emissions = EF × Total wood burnt ..........................(10.9)
Sikh religions. The estimates of wood burnt and
 Other Sectors • 155

Figure 10.7: Emissions from waste gas flaring

Table 10.5: EFs for PM10 and PM2.5 (kg/ha of Agricultural Land) from Agriculture Sector
Type of crop Soil cultivation Crop harvesting Cleaning Drying Total EFs
PM10 PM2.5 PM10 PM2.5 PM10 PM2.5 PM10 PM2.5 PM10 PM2.5
Wheat 0.25 0.015 0.49 0.02 0.19 0.009 0.56 0.168 1.49 0.212

Rye 0.25 0.015 0.37 0.015 0.16 0.008 0.37 0.111 1.17 0.221
Others 0.28 0.015 NA NA NA NA NA NA 0.25 0.015
Source: (EEA 2013)

Figure 10.8 : Projected increase in cultivated area in India

Source: TERI Analysis
156  •  Air Pollutant Emissions Scenario for India

Figure 10.9: PM10 and PM2.5 emissions (kT) from agricultural sector

Figure 10.10: Annual projected wood combustion (T/yr) in crematoria in 2001–51

Figure 10.11 shows the emissions from crematoria all Figure 10.12 shows the PM10 emissions in India.
over India. Crematoria contribute to some NMVOC In 2001, the PM10 emissions from others sector
and PM emissions. Due to reduced death rate, the were about 900 kT, with major contribution from
emissions will show a decline of 43 per cent during refuse burning. However, in 2050 the emissions are
2011–51. estimated to increase to about 2,600 kT. In 2050, the
contributions from coal and cement handling will
Total Emissions from all Sources in have higher contributions.
‘Others’ Category Figure 10.13 shows PM2.5 emission over the years.
This section summarizes the overall national Currently, the emissions from the ‘other’ category
scenario of eight major pollutants—PM10, PM2.5, sources are about 600 kT, which is estimated to
BC, CO, VOC, NOx, SO2, and OC for the sources in increase to 1500 kT in 2050. The major contribution
the ‘others’ category. The total estimated emissions is again from refuse burning whereas emissions from
along with the contribution of various sectors, as agriculture sector, crematoria, and waste gas flaring
discussed in previous sections are summarized. are small.
 Other Sectors • 157

Table 10.6: Projected Crude Death Rates (Deaths per Thousand Table 10.7: EFs of Wood Burning
Population) in India
Pollutant EF in kg/T
Year Crude death rate
SO2 0.4
2001 8.7
NOx 2.55
2011 7.9
PM2.5 9.1
2021 5.65
PM10 18.5
2031 4.63
NMVOC 51.9
2041 3.79
BC 0.52
2051 3.1
OC 4.71
Source: Based on data for 1951–2005 from (WHO 2012) Source: Akagi et al. (2011)

Figure 10.11: Current and projected emissions (kt) from crematoriums in India

Figure 10.12: Total PM10 emissions (kt) from other sectors in India
 Figure 10.13: Total PM2.5 emissions (kt) from other sectors in India

The estimates of BC emissions are shown in increase to 570 kT in 2050 (Figure 10.15). Like other
Figure 10.14. The other category sources contribute pollutants, the major source again is refuse burning
in a small manner in case of black carbon emissions. with contribution from crematoria and waste gas
The total emissions were of 37 kT in 2001, which are flaring.
estimated to increase to above 100 kt by 2051. Refuse SO2 emissions show an increase of almost 40 kT
burning and emissions from crematoria are the only in next 5 decades, with refuse burning as the major
two major contributors. Comparatively, the emissions source. (Figure 10.16)
from crematoria are less and also show a decreasing An increase of almost 1200 kT is estimated in VOC
trend over the years, with reduced death rates. emissions, as shown in Figure 10.17, with crematoria
However, refuse burning emissions are projected and refuse burning are the major contributors.
to grow with increasing population and waste Figure 10.18 depicts the increase of almost 175%
generation rates. in the CO emission from the year 2001 to 2051. Refuse
NOx emissions from these unconventional sources burning and crematoria are the major contributors to
were about 210 kT in 2001, which is estimated to CO emissions.

Figure 10.14: Total BC emissions (kt) from other sectors in India

Spatial allocation projections also present an increase in emissions
from refuse burning in a population and waste
Emissions of different pollutants are spatially
generation growth scenario. In case of all the
allocated using various surrogate indicators, as
pollutants except PM10, it is clear that refuse burning
suggested in Table 10.8. Thereafter, the emissions are
is a dominant source among all sources in the ‘others‘
gridded to a resolution of 36 × 36 km2.
category. Over all, emissions from refuse burning,
and crematoria are also significant. However, the
Conclusions emission may show a decline over the future mainly
Other sectors for which emissions are estimated on account of reducing death rates. Though, these
in this chapter are important as they cumulatively sectors have small contributions, these also need to
contribute significantly to the overall inventory of be controlled to reduce impacts over air quality.
emissions in India. The analysis shows that some of Emissions from waste burning can be controlled
the sectors such as refuse burning may contribute by improving the collection of waste at household
significantly to the emission loads. The emission level. Creating awareness amongst the general

Figure 10.15: Total NOx emissions (kt) from other sectors in India

Figure 10.16: Total SO2 emissions (kt) from other sectors in India
160  •  Air Pollutant Emissions Scenario for India

Figure 10.17: Total VOC emissions (kt) from other sectors in India

Figure 10.18: Total CO emissions (kt) from other sectors in India

Table 10.8: Surrogate Variables Used for Spatial Allocation of Emissions from Other Sectors
S.No Sector Surrogate variable
1 Refuse burning and emissions from landfills District-wise urban and rural population
2 Agriculture District-wise agricultural land area
3 Emissions from storage and handling of coal and cement Coal and cement production units
4 Waste gas flaring Gases flaring at different states
5 Crematoria Number of deaths in different states

public to increase the understanding about the need emissions from crematoria are already on decline but
of better waste management could certainly be a promotion of electric crematoria could also help in
mitigating step towards reducing air pollution from reducing air pollution from this sector.
this sector. On account of decreasing death rate, the
 Other Sectors • 161

References National Environmental Engineering Research

Institute (NEERI). 2010. Air quality monitoring, emission
Akagi, S. K., R. J. Yokelson, C. Wiedinmyer, et al. 2011.
inventory & source apportionement studies for Delhi.
Emission factors for open and domestic biomass
New Delhi: Central Pollution Control Board.
burning for use in atmospheric models. Atmospheric
Chemistry and Physics 11(9): 4039–4072. Pappu, A., M. Saxena, and S. R. Asolekar. 2007. Solid
wastes generation in India and their recycling potential
CPCB. 2007. Assessment of fugitive emissions and
in building materials. Building and Environment 42(6):
development of guideline for control of fugitive
2311–2320.
emissions from cement manufacturing industries .
Delhi: CPCB. Planning Commission. 2014. Report of the task force on
waste to energy vol II. New Delhi: Government of India.
CPCB. 2012. Status of municipal solid waste
management. Delhi: CPCB. Shah, R., U. S. Sharma, and A. Tiwari. 2012. Sustainable
solid waste management in rural areas. International
European Environment Agency (EEA). 2013. EMEP/EEA
Journal of Theoretical and Applied Sciences 4(2): 72–75.
air pollution inventory guidebook 2013. Luxembourg:
European Environment Agency TERI. 2015. Energy security outlook. New Delhi: The
Energy and Resources Institute.
Government of India (GoI). 2001. Census of India
2001. URL: http://www.jsk.gov.in/projection_report_ WHO. 2012. World population prospects: The
december2006.pdf 2012 revision. Geneva, Switzerland:World Health
Organization
IPCC. 2006. IPCC guidelines for national greenhouse gas
inventories. Geneva, Switzerland: Intergovernmental Woodall, B. D., D. P. Yamamoto, B. K. Gullett, and A. Touati.
Panel on Climate Change. 2012, Emissions from small-scale burns of simulated
deployed US military waste. Environmental science &
MoA. 2001. Agricultural statistics at a glance, 2000. New
technology 46(20): 10997–11003.
Delhi: Ministry of Agriculture.
CHAPTER 11
Summary and Conclusions
Sumit Sharma and Atul Kumar

Chapters 2 to 10 provided details of emissions of concentrated at the urban centres where their
different pollutants from different sectors in India. contribution to the prevailing air quality levels could
The emissions are estimated for the years 2001 and be much high. On the other hand, emissions from
2011, and also projected for future years till 2051. It is domestic cooking are mainly from biomass burning
important to understand the relative contributions of in rural households using traditional cook stoves.
different sectors to the overall emission inventories. Open burning of agricultural residue in rural areas
This chapter focuses on summarization of results and contributes 8 per cent to the total PM10 emissions.
assessment of sectoral contributions to emissions of Other sectors cumulatively contribute 11 per cent
various pollutants at the National scale. The pollutant- of PM10 emissions. Power plant contribute 4 per cent
wise results of emission inventories are presented in of PM10 emissions, however, these may contribute
subsequent sections. significantly to pollution levels in specific zones of
influence of power plants.
Particulate Matter The future projections of PM10 emissions show
Growth of PM10 emissions during 2001–51 is that the emissions from industrial sector will grow
presented in Figure 11.1. PM10 emissions in India significantly till 2031. It is mainly due to anticipated
are presently (2011) estimated to be 10,641 kt, growth in the manufacturing sector in the next few
dominated by industrial (43 per cent) and residential decades. Present environmental control scenario
combustion (29 per cent) sectors. Transport in industries is limited considering absence of
contributes to just 3 per cent of PM10 emissions at continuous monitoring, limited vigilance capacity,
the National scale. However, these emissions are and limited installations of high efficiency air
164  •  Air Pollutant Emissions Scenario for India

Figure 11.1: Year-wise growth of PM10 emissions (kilotonnes) during 2001–51

pollution control equipments. Enormous growth in technologies and installation of ESPs/flue gas
infrastructure development sector is expected to desulphurisation/selective catalytic reduction for tail-
fuel the demand for cement and brick in next few pipe control. Transport sector emissions are expected
decades. Cement industry despite being assumed to go down further with considerations of advanced
to be controlled with highly efficient electrostatic (BS-V) emissions norms from 2020 onwards in India.
precipitators (ESPs) for control of PM emissions, This could contribute to significant improvements in
is expected to emit 6.5 times more PM10 in 2051 air quality at the urban scales.
than in 2011. In the brick sector, it is assumed that The distribution of energy-based sources have a
penetration of Zig-Zag technologies will increase share of about 80 per cent in PM10 emissions, while
from mere 4 per cent in 2011 to about 44 per cent non-energy sources such as open burning, road
in 2051, despite which, the PM10 emissions will dust suspension, mining, and other fugitive sources
be more than double in 2051 than in 2011. In the account for 20 per cent in 2011. Based on different
medium and small industries, further penetration sectoral projections, the share of energy base sources
of ESPs and other control technologies has been will remain to be about 80 per cent in 2051.
assumed. Despite these considerations, the overall PM2.5 emissions also show similar trends as shown
emissions from industrial sector will be 3.3 times in by PM10 (Figure 11.2). The share of PM2.5 emissions
2051 in comparison to the 2011. However, the GDP in PM10 emissions varies from 0.58 to 0.67 during all
from industrial sector will grow by 17 times in the years in considerations.
same period. This point to tremendous reduction in Black carbon (BC) and organic carbon (OC) are
emission intensity in industrial sector. the two main constituents of PM. BC emissions are
Other than industries, the emissions from mainly a product of incomplete combustions. The
combustion of fuels in residential sector will reduce 2011 inventories are dominated by residential sector
because of higher penetration of cleaner fuels for emissions (54 per cent), followed by 20 per cent
cooking and lighting. On the other hand, emissions from transport sector (Figure 11.3a). It is to be noted
from open agricultural biomass burning are expected that while the share of transport was less in PM10 or
to go up by six times during 2011–51, with growth PM2.5 fractions, BC inventories show a very significant
in agricultural sector, in a no control scenario. Power contribution from the sector mainly form diesel
sector emissions are expected to grow despite engines. Industries (8 per cent), open agricultural
considerations of high-efficiency supercritical burning (6 per cent), and diesel consumed in diesel
 Summary and Conclusions  •  165

Figure 11.2: Year-wise growth of PM2.5 emissions (kilotonnes) during 2001–51

generator (DG) sets (5 per cent) also contribute to However, with decline in biomass usage in future,
the BC inventories in 2011. The future projections the emissions are expected to go down in future.
show that the emissions will stabilize over the years, However, BC emissions could show higher reductions
with decrease in contributions from residential mainly on account of reduced kerosene usage for
and transport sectors. However, emissions from lighting, which is a very big source of BC emissions.
industrial combustion and open burning will increase.
Considering the stabilization of BC emission over the Gaseous Pollutants
years despite growing economy, there will be drastic Figures 11.4 to 11.7 show emission inventories of
reduction in BC emission intensity in India. gaseous pollutants such as NOx, SO2, CO, and non-
OC emissions in India are dominated by residential methane volatile organic compounds (NMVOC).
sector (Figure 11.3b), open burning and combustion While PM emissions are somewhat controlled
in other sector (crematoria and refuse burning).

Figure 11.3a: Year-wise growth of BC emissions (kilotonnes) during 2001–51

166  •  Air Pollutant Emissions Scenario for India

Figure 11.3b: Year-wise growth of OC emissions (kilotonnes) during 2001–51

due to adoption of emission control standards, However, introduction of BS-V emission norms will
gaseous pollutants are expected to grow gradually reduce NOx emissions to some extent from the sector.
mainly on account of high industrial growth, power Overall, the NOx emissions are expected to grow 3.1
consumption, and mobility demands. The current times between 2001 and 2051.
inventories of NOx emissions are dominated by SO2 emissions are linked to sulphur content in
high-temperature combustion in transport sector the fuels used in different sectors. The emissions are
(38 per cent), power utilities (15 per cent), and DG presently and in future also will be dominated by coal
and agricultural pump sets (17 per cent). While it combustion activities in power and industrial sectors.
is expected that with enhanced power generation The sulphur content has already been considerably
capacities, the use of small DG in residential and reduced in the automotive fuels and is planned to
commercial sector set will diminish over the years, reduce it to 10 ppm levels by 2020. In power sector,
the demand for diesel will grow in transport sector. introduction of control norms for SO2 will somewhat

Figure 11.4: Year-wise growth of NOx emissions (kilotonnes) during 2001–51

 Summary and Conclusions  •  167
arrest the growth of emissions. Despite this, with in private vehicle ownership. It is to be noted that CO
limited SO2 controls in industrial sector, the emissions emissions are primarily emitted from gasoline-driven
are projected to increase by 4.3 times during 2011–51 vehicles. CO emissions form iron and steel sector are
(Figure 11.5). expected to grow significantly in future. Increased
Carbon monoxide is also a product of incomplete open crop-residue burning activities will add to CO
combustion and is currently dominated by emissions with higher shares in future (Figure 11.6).
biomass burning in residential sector. However, Currently NMVOC emissions are dominated by
with penetration of cleaner fuels in the sector, the residential biomass burning; however, its contribution
emission contribution will reduce. On the other hand, will reduce drastically in future. Evaporative emissions
the sectoral contribution from transport sector will from increased paints, printing activities, and use
grow substantially with enormous growth expected of personal products will increase dramatically in a

Figure 11.5: Year-wise growth of SO2 emissions (kilotonnes) during 2001–51

Figure 11.6: Year-wise growth of CO emissions (kilotonnes) during 2001–51

168  •  Air Pollutant Emissions Scenario for India
no-control business as usual (RES) scenario (Figure is about 26–33 per cent of the emissions estimated in
11.7). The overall NMVOC emissions are projected to this study for various pollutants.
increase by four folds by 2051. The variations observed are due to a number of
reasons. Firstly, the estimates are for different years
Comparison with Other Studies and this study provides the latest estimates for
A comparison of emissions estimated in this study India-based local information. This study has used
with others is shown in Table 11.1. There is variation Indian emission factors for most of the emission
in emissions reported by different studies for various sources and also accounts for latest information
pollutants. The emissions estimated in this study on controls. For example, introduction of improved
show 34%,-23%, 20%, -10%, and 24% differences with vehicular emission norms, norms for DG sets
the mean of emissions estimated in other studies have been accounted in this study. There are also
for PM10, SO2, NOx, NMVOC, and CO, respectively. The methodological differences in estimation of energy
standard deviation observed among all these studies demand in some of the sectors such as residential,

Figure 11.7: Year-wise growth of NMVOC emissions (kilotonnes) during 2001–51

Table 11.1: Comparison of Emission Inventory (Million Tonnes) in This Study with Others
Study Year PM10 SO2 NOx NMVOC CO
This study 2011 10.6 5.6 7.0 11.4 46.4
Garg et al. (2006) 2005 4.6 4.4 41.7
Streets et al. (2003) 2000 5.5 4.0 8.6 51.1
Ohara et al. (2007) 2003 7.0 5.0 9.7 84.4
Zhang et al. (2009 2006 4.0 5.6 4.9 10.8 61.1
EDGAR 4.2a 2008 10.9 8.5 6.4 10.6 46.3
Kurokawa et al. (2013) 2008 4.7 10.0 9.7 15.9 61.8
Purohit et al (2010) 8.2 6.4 5.0 15.1
Lu et al. (2011) 2008 8.0
Klimont et al. (2009) 2005 6.4 5.0
a
http://edgar.jrc.ec.europa.eu/);
 Summary and Conclusions  •  169
which is primarily dependent on poorly accounted km². Figure 11.8(a–f ) shows the spatial distribution
firewood combustion. Moreover, this study includes of different pollutants in India. PM emissions are
many more sources such as evaporative, DG sets, geographically more in Indo-Gangetic plains (IGP)
agricultural pumpsets, etc., which have not been mainly due to high population density, dependence
properly accounted in previous studies. of biomass for cooking, vehicular density, and
presence of power plants. Other than IGP, PM10
Spatial Distributions intensities are higher in the states of Gujarat, Tamil
Emissions of different pollutants for all the sectors are Nadu, and Maharashtra. NOx emissions are mainly
spatially distributed using GIS into grids of 36 × 36 concentrated at urban centres and highways, mainly

(a) PM10 (b) PM2.5

(c) BC (d) OC
170  •  Air Pollutant Emissions Scenario for India

(e) NOx (f ) SO2

(g) CO (h) NMVOC

Figure 11.8(a–h): Spatial distribution of PM10, PM2.5, BC, OC, NOx, SO2, CO, and NMVOC emissions in 2011

due to vehicular activity. SO2 emissions are found Economic Growth and Emissions
to be higher at locations of power plants, cement
While there is growth in emissions projected in future
plants, iron steel manufacturing units, and other
for most of the pollutants, the emission intensities
industries burning coal. CO emissions are primarily
are expected to reduce significantly with controls in
driven by incomplete combustion in rural households
different sectors. These controls reduce the emissions
and hence show higher intensities in Bihar, West
intensity (kilotonnes of pollutants per unit of GDP
Bengal, and Uttar Pradesh. NMVOC emissions are
produced) considerably over the years (Figure 11.9).
also dominated by biomass burning in IGP, followed
The emission intensities are also compared with
by emissions in urban centres due to vehicles and
other regions in the world (Figure 11.10 and 11.11).
solvent use.
 Summary and Conclusions  •  171

Figure 11.9: Projected emission intensity (kilotonnes/billion USD of GDP) in India over the years

Figure 11.10: Projected NOx emission intensity (kilotonnes/billion USD of GDP) in different regions of the
world over the years
Source: http://www.iiasa.ac.at/web-pps/ggi/GgiDb/dsd?Action=htmlpage&page=series

This shows that although the present emission Conclusions

intensities are higher in India, they are slowly
India is on the path of rapid economic growth. While
reducing to converge with the emission intensities
the focus is on poverty alleviation and development,
projected for other regions by the year 2050. The GDP
emissions have gradually increased over the years.
is at market exchange rates.
There are some interventions taken in past for control
172  •  Air Pollutant Emissions Scenario for India

Figure 11.11: Projected BC emission intensity (kilotonnes/billion USD of GDP) in different regions of the
world over the years
Source: http://www.iiasa.ac.at/web-apps/ggi/GgiDb/dsd?Action=htmlpage&page=series
OECD90 = Includes the OECD 90 countries, therefore encompassing the countries included in the regions Western Europe
(Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Portugal,
Spain, Sweden, Switzerland, Turkey, United Kingdom), Northern America (Canada, United States of America), and Pacific OECD
(Australia, Fiji, French Polynesia, Guam, Japan, New Caledonia, New Zealand, Samoa, Solomon Islands, Vanuatu) .
REF = Countries from the Reforming Economies region (Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria,
Croatia, Cyprus, Czech Republic, Estonia, Georgia, Hungary, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Malta, Poland, Republic
of Moldova, Romania, Russian Federation, Slovakia, Slovenia, Tajikistan, TFYR Macedonia, Turkmenistan, Ukraine, Uzbekistan,
Yugoslavia).
ASIA = The countries included in the regions China + (China, China Hong Kong SAR, China Macao SAR, Mongolia, Taiwan) , India
+ (Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, Sri Lanka) and Rest of Asia (Brunei Darussalam, Cambodia,
Democratic People’s Republic of Korea, East Timor, Indonesia, Lao People’s Democratic Republic, Malaysia, Myanmar, Papua New
Guinea, Philippines, Republic of Korea, Singapore, Thailand, Viet Nam) are aggregated into this region.
MAF = This region includes the Middle East (Bahrain, Iran (Islamic Republic of), Iraq, Israel, Jordan, Kuwait, Lebanon, Oman,
Qatar, Saudi Arabia, Syrian Arab Republic, United Arab Emirates, Yemen) and African (Algeria, Angola, Benin, Botswana, Burkina
Faso, Burundi, Cote d’Ivoire, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Congo, Democratic Republic of
the Congo, Djibouti, Egypt, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho,
Liberia, Libyan Arab Jamahiriya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria,
Reunion, Rwanda, Senegal, Sierra Leone, Somalia, South Africa, Sudan, Swaziland, Togo, Tunisia, Uganda, United Republic of
Tanzania, Western Sahara, Zambia, Zimbabwe) countries.
LAM = This region includes the Latin American countries (Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia,
Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica,
Martinique, Mexico, Netherlands Antilles, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Suriname, Trinidad and Tobago,
Uruguay, Venezuela).
where MAF and LAM are together, the former ALM region of the SRES scenarios

of air pollution mainly at the urban scales in India. inventories to carry out simulation studies for regional
However, the recent studies have suggested that the scale improvement of air quality in India. This study
regional scale improvements are required to effectively presents a multi-scale high-resolution emission
control pollution levels at urban and regional scales. inventory for India for the baseline (2011) and future
This calls for preparation of databases for emissions years till 2051. The estimates are based on TERI’s
 Summary and Conclusions  •  173
earlier work in developing energy use scenarios for Evaporative emissions
the country. Established methodologies have been
PP Development of standards for control of
used to estimate emissions from different sectors and
evaporative/fugitive emissions from different
useful insights have been drawn. It is noted that while
product use
residential sector biomass burning–based emissions
PP Installation of stage-I/II control at oil handling
are significantly high currently, they are projected to
units.
reduce considerably in next few decades. On the other
PP Control of evaporative emissions from vehicles
hand, rapid industrial growth will lead to significant
emissions and in a limited control scenario, the
emission are expected to increase in future. Transport
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trends of multigas emissions inventory of India.
the National scale but are significantly concentrated
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there. Key sectoral recommendations that are made for Klimont, Z., J. Cofala, J. Xing, et al. 2009. Projections of
control of emissions are : SO2, NOx and carbonaceous aerosols emissions in Asia.
Tellus B 61(4):602–17.
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PP Development of standards for NOx and other Greet, and T. Fukui. 2013. Emissions of air pollutants
important gaseous pollutants and greenhouse gases over Asian regions during
PP Installation and maintenance of APC devices 2000–2008: Regional Emission inventory in Asia (REAS)
PP Continuous monitoring and reporting of stacks version 2; Discussion. Atmospheric Chemistry and
PP Development emission trading schemes and Physics 13:11019–58; 10049–123.
other fiscal measures for performance beyond Lu, Z., Q. Zhang, and D. G. Streets. 2011. Sulfur dioxide
compliance levels and primary carbonaceous aerosol emissions in China
PP Ensuring 24×7 power supply to reduce DG Set and India, 1996–2010. Atmospheric Chemistry and
usage. Physics 11:9839–64, doi:10.5194/acp-11-9839- 2011.
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Transport Yan, and T. Hayasaka. 2007. An Asian emission inventory
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emission norms 1980–2020. Atmospheric Chemistry and Physics
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PP On-road vehicle emission management : I&M
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PP Development of fuel efficiency standards and greenhouse gases in India. Laxenburg, Austria:
PP Electric mobility International Institute for Applied Systems Analysis.
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Open burning Atmospheric Chemistry and Physics 9:5131–53.

PP Development of plans for more productive energy

use of the crop-residues currently burnt
174  •  Air Pollutant Emissions Scenario for India

Annexure
Annexure 11.1: Sectoral emission estimates (kt/yr) of different pollutants 2001–51
PM10 Sectors 2001 2011 2021 2031 2041 2051
Residential 2944 3115 2913 2774 2502 2048
Industry 3685 4627 10212 13953 15230 15093
Power 257 453 869 1016 1216 1354
Transport 218 342 478 498 594 761
DG set 104 82 72 76 81 78
Open burning 620 818 1004 1190 1376 1562
Evaporative            
Others 890 1204 1561 1976 2399 2773
Total 8717 10641 17110 21483 23398 23668
PM2.5 Sectors 2001 2011 2021 2031 2041 2051
  Residential 2570 2660 2450 2333 2104 1723
  Industry 1923 2451 5507 7816 8706 8546
  Power 103 181 348 407 487 542
  Transport 194 288 371 293 256 296
  DG set 88 70 61 65 69 66
  Open burning 350 462 567 672 777 882
  Evaporative            
  Others 602 756 942 1149 1363 1574
  Total 5830 6867 10246 12733 13760 13629
 
BC Sectors 2001 2011 2021 2031 2041 2051
Residential 835 521 260 247 223 183
Industry 44 77 88 113 138 161
Power 12 22 42 49 58 65
Transport 138 197 235 158 104 111
DG set 62 49 43 46 48 47
Open burning 48 57 66 75 83 92
Evaporative            
Others 38 48 59 72 84 97
Total 1178 971 794 759 739 755
               
CO Sectors 2001 2011 2021 2031 2041 2051
  Residential 25942 31385 31953 30560 27696 22827
  Industry 3196 5728 9921 16751 23370 28335
  Power 23 43 72 128 207 286
 Summary and Conclusions  •  175

  Transport 1983 2777 4149 6173 9488 14167

  DG set 318 251 288 304 0 0
  Open burning 2549 3244 3905 4565 5225 5885
  Evaporative            
  Others 2389 3006 3621 4328 5059 5799
  Total 36401 46435 53909 62809 71046 77299
NOx Sectors 2001 2011 2021 2031 2041 2051
Residential 633 766 789 762 699 585
Industry 520 950 1980 3405 4877 6038
Power 573 1015 1935 3565 5786 7334
Transport 1164 2665 3826 3904 4530 6162
DG set 1475 1164 833 877 929 893
Open burning 104 137 169 200 232 263
Evaporative            
Others 220 280 344 415 488 562
  Total 4689 6978 9876 13129 17540 21838
SO2 Sectors 2001 2011 2021 2031 2041 2051
  Residential 303 330 314 299 270 221
  Industry 1901 3175 6070 10118 14478 18147
  Power 1031 1842 3490 3981 4650 5108
  Transport 120 53 27 50 87 145
  DG set 97 77 15 16 0 0
  Open burning 30 40 50 59 68 77
  Evaporative 0 0 0 0 0 0
  Others 29 37 46 55 65 75
  Total 3512 5553 10011 14577 19617 23773
NMVOC Sectors 2001 2011 2021 2031 2041 2051
  Residential 5457 6637 6771 6471 5860 4824
  Industry 74 123 194 305 425 532
  Power 4 8 14 25 40 53
  Transport 605 802 1026 980 926 1103
  DG set 120 95 68 72 247 304
  Open burning 274 512 732 952 1173 1393
  Evaporative 797 2050 4431 9194 17233 30089
  Others 952 1191 1418 1684 1960 2238
  Total 8283 11418 14652 19683 27863 40536
OC Sectors 2001 2011 2021 2031 2041 2051
Residential 1222 1488 1513 1441 1300 1064
 Industry 63 107 143 198 248 290
Power 20 34 66 77 92 103
Transport 47 70 96 66 42 35
DG set 19 15 13 14 15 14
Open burning 109 128 145 163 180 198
Evaporative            
Others 309 392 482 581 684 788
Total 1787 2234 2459 2540 2561 2493

Annexure 11.2: State-wise emission estimates (kt/yr) of different pollutants in 2011

States PM10 PM2.5 NOx SO2 CO BC OC NMVOC
Andhra Pradesh 708 415 553 440 2956 54 126 736
Arunachal Pradesh 25 15 19 4 186 4 8 47
Assam 247 170 89 44 1594 30 72 364
Bihar 500 375 311 165 3834 65 224 891
Chhattisgarh 818 541 323 533 1222 36 34 145
Goa 22 10 19 14 42 1 2 16
Gujarat 1129 637 519 542 2509 48 99 804
Haryana 293 189 254 124 1355 30 49 322
Himachal Pradesh 92 51 65 39 392 7 16 98
Jammu & Kashmir 78 52 75 39 526 11 24 118
Jharkhand 238 153 194 210 1856 25 58 320
Karnataka 468 250 376 214 2401 42 105 657
Kerala 179 95 203 80 1250 24 54 350
Madhya Pradesh 568 384 366 246 2620 54 139 659
Maharashtra 748 469 589 528 3456 70 141 925
Manipur 12 10 14 1 93 2 4 23
Meghalaya 32 23 25 11 172 4 7 41
Mizoram 12 7 10 2 73 1 3 20
Nagaland 16 9 13 3 107 2 5 26
Orissa 963 630 307 392 2297 53 85 465
Punjab 461 280 267 149 2011 34 60 370
Rajasthan 617 421 439 354 2700 63 128 674
Sikkim 4 3 3 1 23 0 1 6
Tamil Nadu 414 246 553 418 1924 51 91 549
Tripura 27 16 13 3 218 4 9 50
Uttar Pradesh 1207 916 733 468 6985 159 391 1540
Uttaranchal 167 87 67 45 716 12 23 147
West Bengal 514 364 444 483 2858 62 138 664
Air pollutant emissions
scenario for India
EDITORS
Sumit Sharma
Atul Kumar

The Energy and Resources Institute