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Sub-region (District) and Sector Level SO2 and NOX Emissions for India:

Assessment of Inventories and Mitigation Flexibility

Amit Garg and P.R. Shukla Indian Institute of Management, Ahmedabad,

Sumana Bhattacharya

National Physical Laboratory, New Delhi

V.K. Dadhwal Space Applications Centre, Ahmedabad

Paper Published in Atmospheric Environment, Vol. 35/4, pp. 703-713

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http://www.e2analytics.com

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Sub-region (District) and Sector Level SO2 and NOX Emissions for India:

Assessment of Inventories and Mitigation Flexibility By

Amit Garg*, P.R. Shukla*, Sumana Bhattacharya** and V.K. Dadhwal*** (* Indian Institute of Management, Ahmedabad, ** National Physical Laboratories, New Delhi, ***

Space Applications Centre, Ahmedabad)

Abstract

Sub-regional and sector level distribution of SO2 and NOX emissions inventories for India

have been estimated for all the 466 Indian districts using base data for years 1990 and 1995.

Although, national level emissions provide general guidelines for assessing mitigation

alternatives, but significant regional and sectoral variability exist in Indian emissions.

Districts reasonably capture this variability to a fine grid as 80% of these districts are

smaller than 1ox1o resolution with 60% being smaller than even 1/2ox1/2o. Moreover,

districts in India have well established administrative and institutional mechanisms that

would be useful for implementing and monitoring mitigation measures. District level

emission estimates thus offer a (A.1.1) finer regional scale inventory covering the combined

interests of the scientific community and policy makers. The inventory assessment

methodology adopted is similar to that prescribed by the Intergovernmental Panel on

Climate Change (IPCC) for greenhouse gas (GHG) emissions. The sectoral decomposition

at district level includes emissions from fossil fuel combustion, non-energy emissions from

industrial activities and agriculture. Total SO2 and NOX emissions from India were 3542

and 2636 Gg respectively [1990] and 4638 and 3462 Gg [1995] growing at annual rate of

around 5.5%. The sectoral composition of SO2 emissions indicates a predominance of

electric power generation sector [46%]. Power and transport sector emissions equally

dominate NOX emissions contributing nearly 30% each. However, majority of power plants

are situated in predominantly rural districts while the latter are concentrated in large urban

centers. Mitigation efforts for transport sector NOX emissions would therefore be higher.

The district level analysis indicates diverse spatial distribution with the top 5% emitting

districts contributing 46.5% and 33.3% of total national SO2 and NOX emissions

respectively. This skewed emission pattern, with a few districts, sectors and point sources

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emitting significant SO2 and NOx, offers mitigation flexibility to policy makers for cost-

effective mitigation.

Keywords: Emissions Inventory, SO2 Emissions, NOx Emissions, Emissions Mitigation

1. Introduction

India has large variability in regional population distribution [Census of India, 1992]

and energy consumption patterns [CMIE, 1999; TEDDY, 1999]. Rapid economic growth

and industrialization are enhancing this variability further creating pockets of heavy

pollutant emitting regions like metro-cities which have seen rapid rise in the fleet of

vehicles in the last decade [CMIE, 1998a]. Similarly many thermal power plants have

become operational in this decade, which are consuming coal for electricity generation.

Therefore, a need arises for the policy makers to specially identify these regions of high

pollution and target the sectors for mitigation, which are causing it. In association with the

rising coal use, emissions of SO2 and NOx have increased to levels, which pose serious

threat to public health and sensitive ecosystems [Chameides et. al., 1994].

The emissions inventories are traditionally reported in gridded formats. Bhatti and

Streets [1991] report SO2 emission inventories for most of Asian nations. Kato and Akimoto

[1992] have estimated SO2 and NOx inventories for 25 Asian countries for some selected

years. Akimoto and Narita [1994] estimate the emissions for a 1ox1o [110 km x 110 km]

grid. Aardene et al. [1999] have reported NOx emissions for 1990 to 2020 for entire Asia in

1ox1o resolution using the RAINS Asia model [Foelle et. al., 1995]. Arndt et al. [1997] also

report SO2 inventory for the same region and period using the same model. Gaps in grid

level energy consumption information, and therefore emissions estimates, are mostly filled

in by allocating emissions to grids in proportion to the population assigned to these grids.

In this paper, we are first presenting the all India emission scenario of SO2 and NOX,

their emission trends and the sectoral shares followed by emission estimates for each of the

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466 Indian districts [Census of India, 1992] for 1990 and 1995. The aim of this exercise is

to identify the largest contributing regions and sectors that can be targeted for mitigation.

Although, national level inventory estimates provide general guidelines for assessing

mitigation alternatives, significant regional and sectoral variability exist. Estimates of

emission magnitudes on a sub-regional site-specific scale allow more focused and efficient

mitigation strategies by exploiting this variability. Districts can reasonably capture this

variability to a fine grid since 80% of these districts are smaller than 1ox1o resolution with

60% being smaller than even 1/2ox1/2o. The largest district is about 20x20 size but the larger

districts have much lower population densities and lower emissions as well. Data for fossil

fuel consumption, industrial activities and agriculture are available at district levels. Since

the districts have well-established administrative and institutional mechanisms, this analysis

would be useful for implementing and monitoring local pollutant mitigation measures.

Hence, district level emission estimates offer a (A.1.1) finer regional scale inventory

covering the combined interests of the scientific community and policy makers. The largest

25-emitter districts in each source category have been termed as hotspot districts for that

category for a more focussed analysis of large emitter districts. Such a study offers

mitigation flexibility to policy makers by identifying the specific regions, sectors and

sources, which require mitigation.

2. Data

We have used diverse data sources covering various sectors and fuels. These energy

and non-energy sources have been captured at district level giving a profound richness and

robustness to the base data for national inventory estimates. For example, plant level coal

consumption data has been captured for all the power, steel, cement and fertiliser plants in

India. Similarly, plant level production data of sulfuric acid, smelting of lead, zinc and

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copper ores have been captured. District level consumption of different petroleum oil

products has also been captured. The district level data on livestock population by category

has been used to estimate production of dry dung cakes, used as energy sources. Similarly

production of various crops in each districts has been used to estimate agricultural crop

residue burnt. The depth and richness of these base data also implies that more accurate

future inventory projections can be made. Most of the data sources are published documents

of the government of India. The data used are that of coal [MoC, 93; MoC, 1998], oil

production and natural gas consumption [MoPNG, 1992; CMIE, 1995a; CMIE, 1996; IPD,

1996; MoPNG, 1996; OCC, 1998; SAKET, 1998; TEDDY, 1998], electric power

generation [CEA, 1987; CMIE, 1996; IBC 1996; CEA, 1997; TEDDY, 1997; CMIE,

1998b], biomass [CMIE, 1995b; FAI, 1996a; Ravindranath et al, 1995; FAI, 1997; TERI,

1997], brick [Census of India, 1992; Shukla, 1994; CMIE, 1996], cement [ICRA, 1995;

CIER, 1998], steel [SAIL, 1994; CII, 1996; SAIL, 1996], fertilizer [CMIE, 1995b; CMIE,

1996; FAI, 1991; FAI, 1995; FAI, 1996b, CMIE, 1998c], sulfuric acid production [GoI,

1986; GoI, 1989; CIER, 1994; CIER, 1998; CMIE, 1998c; CMIE, 1998d] and smelting of

zinc, lead and copper [CIER, 1998]. We have tried to cross verify all these data sources as

much as possible.

3. Methodology and Emission Coefficients

The basic methodology to estimate the total emissions of a particular gas from the

country uses the following formula, which is in line with the IPCC methodology [1997]:

Total emissions = ∑ ∑ ∑ [Activity level * Emission coefficient]

Districts Source Sectors Categories

Source categories are in Million metric tons [MT] per year except for natural gas

consumption [Billion cubic meters]. This methodology follows the same approach as used

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by Li et al. [1999], except that one more level of disaggregation [namely district] has been

incorporated in our methodology. The sectors that have been considered are energy,

transport, industry, agriculture and residential. The energy sector captures emissions from

consumption of fossil fuels [source categories] such as coal, petroleum oil products and

natural gas for electric power generation, steel, cement, brick, paper, sugar, chemicals etc.

Transport sector mainly consumes oil products with use of coal being limited to railways

and that too almost negligible due to phasing out of steam traction from Indian Railways.

The industrial sector includes emissions from non-energy activities namely cement

production, zinc, lead, copper smelting, nitric and sulfuric acid production. Agriculture and

residential sectors include emissions arising out of animal manure and consumption of

biomass [agricultural crop residue, dung-cakes and fuelwood]. The district level sectoral

petroleum oil product consumption is assumed to follow the national consumption pattern.

The sectoral SO2 emission coefficients have been Indianised depending upon the

sulfur content of different fuels. The Indian coal has low sulfur content and it has been

taken to be 0.51% sulfur by weight [IPCC, 1997; URBAIR, 1997]. The Indian petroleum oil

products have higher sulfur, as the level of sulfur removal by Indian refineries is not high

presently. The sulfur content is eight times more than the European standards and 250 times

more than the Swiss norms [Down to Earth, 1998; Down to Earth, 1999a; Down to Earth,

1999b; Down to Earth, 1999c]. However, there is sufficient evidence of recent policy

decisions in India that are aimed at controlling local pollution levels and would reduce SO2

emission coefficients from fuel combustion activities in near future. These include

mandatory washing of coal that is used 500 Kms away from the mine mouth. This measure

is aimed at reducing fly ash and also simultaneously reduces sulfur. Since, over a third of

coal is used beyond 500 Kms, this measure is expected to start reducing SO2 from coal use

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in near future. The second decision is about reducing the sulfur contents of diesel oil

coming out of the Indian refineries. Official claim in India is that government has spent

$1.34 billion to reduce the sulfur content in diesel from 1 percent to 0.25 percent by weight

[Down to Earth, 1999a]. Besides these, there has been recent Supreme Court judgement

which has ordered Euro II standards to be followed for cars in India. While this is not very

significant for SO2 control, it shows the mind-set of the judiciary and policymakers to

control local pollution. The SO2 emission coefficients from biomass are based on studies

made by Ravindranath et. al. [1995]. These coefficients may, however, have scope for

further refinements since the type of biomass consumed in India has wide regional and

seasonal variations, which are not captured in these coefficients. NOx emission coefficients

are as per the IPCC guidelines [1997]. For NOx emissions from nitric acid production, we

have used the IPCC default value of 12 Kg NOx per ton of acid production. Table 1 and 2

give the SO2 and NOx emission coefficients used in this paper.

The district level emissions have been linked to the district topology available with

the Space Application Centre, Ahmedabad, India. These data were then converted into per

unit area for each of the 466 districts and plotted [except for the state of Jammu and

Kashmir where state level averages have been plotted].

4.0 Inventory Assessment

4.1 SO2 emissions

All India SO2 emissions are estimated at 3.54 Tg in 1990 and 4.64 Tg in 1995. In

1990, coal consumption contributed 64% of total SO2 emissions in India, oil products 29%,

biomass 4.5% and non-energy consumption 2.5%. Emissions from natural gas are

negligible. It is interesting to note that composition of emissions from different fuels

remained almost the same in 1990 and 1995 with a marginal increase in the share of

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emissions from coal and a corresponding reduction in emission from biomass, which have

almost stagnated. Two thirds of the increase in all India SO2 emissions during 1990-95 has

been due to consumption of coal and the rest from oil products. The increase in coal based

SO2 has been entirely due to increased electric power generation. Oil product SO2 increase

is almost entirely due to a 50% increase in high-speed diesel and fuel oil consumption

indicating expansion of transport and industry sectors.

Sector specific emissions indicate dominance of electric power generation sector

contributing 46% of all India SO2 emissions in 1995 [figure 1]. Industry is the second

largest SO2 emitter at 36% followed by transport [7.8%], biomass consumption [6%] and

other sectors [3.8%]. Almost a quarter of industrial emissions come from steel sector and

10% from cement manufacturing. The non-energy share is 7% including emissions due to

H2SO4 manufacturing and smelting of zinc, lead and copper ores. Other industries including

(B6) petroleum refining, fertilizer, brick, sugar, chemicals, textiles, non-ferrous metal

manufacturing etc. contributed 56% of industrial emissions [figure 2].

(A.1.2; B1) The regional spread of SO2 emissions from various sectors varies. The

present paper includes emission estimates from 94 power plants (81 coal, 12 gas and one

oil based), 11 steel plants, 92 cement plants, 31 fertilizer plants, 12 petroleum refineries and

26 other sources including petrochemicals and smelting units. These cover almost all the

major point sources in India. Mapping them using satellite data will be the next phase of

research activity, which will also include the stack heights to understand the local spread.

Our estimates indicate that the largest 57-point source emissions contribute 50% of all India

SO2 emissions and 10% NOx emissions. About two-thirds of these are power plants.

India’s power sector is mainly growing on coal with its total coal and lignite

consumption increasing by above 60% between 1990-95. However since the Indian coal has

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lower sulfur content, the impact of increased coal usage is not so pronounced in absolute

terms. There has been only a marginal improvement in overall performance of Indian power

sector, which continues to be dominated by sub critical pulverized coal technology with

about 7.0 tons SO2 emissions per GWh during 1990-95. Cement industry is much more

scattered but concentration is more in districts of Madhya Pradesh, Karnataka and Tamil

Nadu provinces. For SO2 emissions from non-energy sectors, sulfuric acid manufacturing is

wide spread over almost 15 provinces in India and Madhya Pradesh is the biggest emitter.

Copper ore smelting is spread over only eight districts, Lead over five districts and Zinc ore

smelting is done mainly in two districts in India. Rajasthan province is the largest SO2

emitter for all these categories, contributing about 35% of the all India SO2 emissions from

non-energy sector, followed by Madhya Pradesh [20%].

The regional spread of overall SO2 emissions per unit area varies widely across the

Indian districts and has a close correspondence with coal consumption pattern [figure 3a

and 3b]. The emissions from a province also indicate a good correlation with its population

and level of economic activity. Higher population implies higher level of economic

activities and correspondingly higher energy consumption as the energy elasticity of the

Indian GDP has been above unity for the last twenty years [ESI, 1999; CMIE, 1999]. Uttar

Pradesh happens to be the most populous province of the country and heads the list of SO2

emissions as well. Net State Domestic Product [NSDP] captures the level of economic

activity of a province and the eight provinces with highest NSDP [CMIE, 1994; CMIE,

1997] are also the top SO2 emitters in the country.

Range analysis of SO2 emissions from Indian districts indicates that the top five-

hotspot districts contributed almost 16% of all India SO2 emissions in 1995 and these have

grown at 11.7% annually between 1990-95 [table 3]. All of these have more than 90%

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emissions due to coal combustion. Similarly 35 of the top 47-hotspot districts also have

predominant coal based SO2 emissions [above 60%]. The emission shares of large emitter

districts have increased between 1990-95. There is a reduction in number of districts in

lower emission ranges while there is an increase in those in higher ranges. 350 districts had

individual emissions less than 6 Gg in 1990. Their number decreased to 336 in 1995.

Districts emitting more than 20 Gg SO2 increased from 46 to 57 in the interim period. Our

analysis indicates an upward shift in SO2 emission from Indian districts and is more

pronounced in higher ranges. The percentage contribution by least 400 emitters has gone

down over 1990-95. This is not due to a reduction in their absolute emissions, which have in

fact marginally grown, but it is due to the high growth rates of the largest 10% emitter

districts.

The total SO2 emissions from seven of the top ten hotspots have grown faster than

the national Compounded Annual Growth Rate (CAGR) of 5.5% per annum. These districts

are not the largest urban centers of India and do not even include any state capital district.

All of these districts are near coal mine mouths and have more than 90% of their SO2

emissions due to coal consumption for power generation. Bilaspur district [MP], the largest

SO2 emitter district in India, had almost 95% of its emissions due to this source. This

picture changes considerably if we analyze hotspot districts for SO2 emissions per unit area

[table 5]. The four Indian metropolis districts appear in this list along with three other state

capital districts. Their average annual ambient SO2 concentration levels, as measured by the

Central Pollution Control Board of India [CPCB], are also indicated. CPCB regularly

monitors these values for (B2) 92 Indian cities using 290 observation points. World Health

Organization has specified that annual average SO2 concentrations should not be more than

100-150 micro gm/mt3, while the CPCB norms for India are stricter and are pegged at 60

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micro gm/mt3 for residential areas and 80 micro gm/mt3 for industrial areas. It is to be noted

that only two cities [Howrah and Surat] crossed the safe residential emission concentration

level CPCB norms in 1995 while only Surat crossed even the industrial area limits. Many

other cities do however cross these limits many times in a year if their eight hourly CPCB

emission data is analyzed for the whole year.

The national average per capita SO2 emission was 4.2 kg/person in 1990, which rose

to 5 kg in 1995, an increase of almost 20% in 5 years. The top 25 hotspots for per capita

SO2 emission do not include the four Indian metropolis districts. The per unit area [table 5]

and per capita hotspot lists do not have much overlap and only eleven out of largest 25

hotspot districts are common to both the categories. However, total SO2 and per capita SO2

hotspot lists have a good overlap since the districts in former list have relatively lower

population densities as compared to those appearing in per area list.

Table 6 lists the largest five-hotspot districts for some important sectors based on

total SO2 emissions. Sonbhadra and Bilaspur are the two largest SO2 emitting districts in

India and this is mainly due to their SO2 emissions from electric power generation. In fact

for 1995, the five largest SO2 emitters for all India happen to be the same as those in the

electric power sector. For 1990, Greater Mumbai comes at all India fourth place since

corresponding electric power generating districts had lower emission levels comparatively.

Delhi was also in the top five emitter's list for 1990 due to its high transport sector SO2

emissions.

4.2 NOx emissions

India emitted 3.46 Tg NOX in 1995 as per our estimates and these grew at about

5.6% per annum between 1990-95. Coal and oil product combustion have almost equal

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shares in total NOx emissions growing around 7.2% per annum. The shares were 36% in

1990 and marginally increased in 1995 [41% for coal and 38% for oil products].

The sectoral composition indicates that transport sector is the predominant source of

NOX emissions in India contributing 32%, out of which road transport contributed around

28% [figure 4]. Electric power generation [28%], industry [19%], biomass consumption

[19%] and other industries [2%] follow. All India NOX emissions have risen by one-third

between 1990-95 at a CAGR of 5.6%, however sectoral emissions have wide variations.

These increased by 63%, 46%, 19% and 10% for electric power generation, transport,

industry and other sectors respectively.

The regional distribution indicates a close relationship with coal and oil products

consumption [figure 5]. Districts with big thermal power plants and large vehicular

population emit more NOx. Dark spots indicate high emission areas with more than 75

thousand-ton emissions per year. These are Bilaspur district of Madhya Pradesh [MP], the

national capital Delhi and Sonbhadra district of Uttar Pradesh [UP]. UP, Maharashtra, MP,

AP and TN were the largest five NOX emitting provinces in 1995. These five states together

accounted for more than half of India’s NOX emissions both in 1990 and 1995. In addition

to human population and the level of economic activity, NOX emissions also have a close

correlation with vehicular population. The top five-emitter provinces account more than half

of all India registered vehicular population [CMIE, 1996]. It should however be noted that

all of the registered vehicles might not be in active use. The composition of total vehicle

population and their shares in passenger-km and ton-km of traffic moved are also important

since heavy duty and/or diesel driven vehicles emit much more NOX per unit passenger-km

(or ton-km) as compared to light duty and/or petrol driven vehicles.

The range analysis indicate that the top 1% emitter districts covered 11% of all India

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NOX emissions and the next 1% districts another 9% emissions. The top 5% districts

covered 33% of total emissions while the least 233-emitter districts together emitted 13% of

India’s total NOX [table 7]. This pattern, even though skewed, is more evenly distributed

than SO2 [table 3] since transport sector plays a dominant role in NOX emissions. Transport

activities are more evenly distributed across the country and are more concentrated in and

around the large urban centres. The top ten-hotspot districts for NOX emissions [table 8]

include Delhi and Mumbai, which were not there in the SO2 list. State capital districts

encompass big urban centres, most of which have large vehicular population while some

have big electric power plants as well [Delhi, Gandhinagar and Mumbai]. These two

sources together result in high NOX emissions from state capital districts. In fact nine of

these capital districts figure in top 25-NOX hotspots in India in 1995.

The NOX emission hotspot districts are different for total emissions, per unit area

emissions [table 9] and per capita emissions for 1995. While Bilaspur and Delhi occupy top

positions for total NOX emissions, Chennai heads the list for per unit area NOX emissions

and Sonbhadra has the highest per capita emissions. The source category based top five

hotspot districts in India are indicated in table 10. Coal and oil consumption drive all India

NOX emission almost equally. The five largest hotspots from coal use correspond to electric

power generation sector and those for oil use correspond to transport and industrial sector.

Biomass consumption is partially accounted for in agriculture sector and partly in

residential sector. Natural gas hotspots correspond to gas based electric power plants while

industrial process is nothing but production of nitric acid.

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5.0 Mitigation flexibility

Although local pollution standards across regions and sectors are often useful as

overall policy targets, the marginal mitigation cost for achieving each target varies. The

present work on regional and sector specific inventories of gases contributes to

effectiveness of emissions mitigation by indicating the hotspot locations and sectors where

controls can lead to maximum benefits. Table 11 gives the shares of various sectors for SO2

and NOX emissions in India in 1995. SO2 hotspots are driven by power sector emissions

while NOX hotspots are equally driven by transport and power sector emissions. (B4)

Transport, being ground level source, has more adverse impact on the ambient environment

as compared to power plants and should be kept in mind while formulating mitigation

policies. Power sector emissions are mainly concentrated from about 40 large power plants,

five steel plants and 15 large cement plants in India; thus mitigation efforts would be quite

focussed. Transport sector sources are extremely dispersed, large in numbers and

concentrated at urban centres thus necessitating different mitigation approach. The extent of

NOX emissions also depends upon traffic patterns, driving habits and condition of vehicles.

Improving fuel quality, mainly diesel and gasoline, will have considerable reductions in

transport sector emissions.

While the impacts of climate change from greenhouse gas emissions are large and

felt over a long duration, local pollution impacts on health and ecology are felt much earlier.

Mitigating local pollutant emissions therefore is a more urgent task. Often, mitigation of

local pollution causes reduction in associated GHG emissions and vice versa, even though

the level of reductions in each direction may vary substantially. Reductions in GHG

emissions by efficiency improvements in fuel combustion processes, switching over to

cleaner fuels and employing cleaner production technologies will reduce local pollutants

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almost in the same proportion as GHG. However, measures aimed at reducing local

pollutants alone, for example employing technologies like flue gas desulfurisation [FGD]

which reduces 90 to 95% SO2 emissions, do not result in equivalent GHG reductions.

Pursuing cleaner local environment policies alone, therefore, may not provide any

substantive reduction in GHG emissions.

There is another dimension to this discussion, which is the relative cost of GHG and

local pollutant mitigation efforts. While SO2 emissions from the power sector may be

mitigated at around US$ 300 per ton of SO2 by employing technologies like FGD, those for

NOX would be around US$ 250 per ton using low-NOX burners etc [WB, 1997; Shukla et

al., 1999]. On the other hand if we reduce SO2 and NOX as ancillary benefits of GHG

mitigation measures like fuel switching from coal to gas and adopting cleaner production

technologies, the per unit costs would be much higher. Cost effectiveness requires equal

marginal mitigation cost across various mitigation options. Therefore in a developing

country perspective, where resources are competing for allocation, controlling local

pollution directly may serve India’s purpose better than taking the GHG route for tackling

local pollution problem.

The third reason to focus on mitigating local pollution problem alone in India is the

historical dependence of India's energy sector on coal, which is not likely to change in near

future [Shukla et al., 1997]. The local pollutant hotspot districts have a major dominance of

coal consumption. Most of these districts are in hinterland and hence there would be

reasonable possibilities of acid rains in the surrounding areas if the generating capacities of

these power plants were increased much. A similar situation would arise if future mega-coal

based thermal power plants were situated near the mine mouths alone, which even presently

have many big plants. However, both these problems can be addressed in a cost-effective

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manner if suitable measures are adopted to control local pollutant emissions alone as

discussed above. Since, India has no GHG reductions commitment at present, GHG

emissions reductions may only remain an ancillary benefit of mitigating local pollutant

emissions and may have to be done for its own sake in India.

6.0 Summary

Our study indicates that per area SO2 emissions have increased from 1.08 tons/km2

in 1990 to 1.41 tons/km2 in 1995. The hotspot SO2 emitting districts in both the years are

the ones where power plants for electric generation are located. Similarly, per area NOX

emissions have increased from 0.8 tons/km2 to 1.05 tons/km2. Power and transport sectors

contribute about 30% each to NOX emissions. However, transport being ground level

source, has more adverse impact on the ambient environment as compared to power plants

and should be kept in mind while formulating mitigation policies. The rapidly rising SO2

and NOX emission trajectories in hotspot districts (CAGR above 7.5%) require early

mitigation measures, even though majority of the Indian districts are relatively clean

(CAGR below 4%). The present paper captures the diversity and variability of Indian

emissions, therefore providing inputs to strengthen scientific and policy-making processes.

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Foelle et al., 1995. Rains Asia: An assessment model for Air pollution in Asia. Report on the World Bank sponsored project " Acid Rain and Emission Reduction in Asia", December 1995. GoI, 1986. Handbook of Indigenous Manufacturers (Chemical & Miscellaneous Stores). Ministry of Industry, Government of India, New Delhi. GoI, 1989. Perspective Plan for Chemical Industry (Upto Year 2000 AD). Ministry of Industry, Department of Chemicals & Petrochemicals, Government of India. New Delhi. ICRA, 1995. The Indian Cement Industry Update: 1995. ICRA Industry Watch Series # 1, ICRA Investment Information Publications , New Delhi. IPCC, 1997. Revised IPCC guidelines for national greenhouse gas inventories: Reference Manual, vol. 3. Inter Governmental Panel on Climate Change, Bracknell, USA. IPD, 1996. Indian Petroleum Directory. Indian Petroleum Publishers, Dehradun, India. Kato N. and Akimoto H., 1992. Anthropogenic emissions of SO2 and NOX in Asia: Emission inventories (plus errata), Atmospheric Environment 26 A (16), 2997-3017. Li Y. F., Zhang Y. J., Cao G. L., Liu J. H. and Barrie L. A., 1999. Distribution of seasonal SO2 emission from fuel combustion and industrial activities in Shanxi province, China, with 1/6ox1/4o longitude/latitude resolution. Atmospheric Environment 33, pp 257-265. MoC, 1993. Coal Directory of India: 1991-92. Ministry of Coal, Government of India, Calcutta. MoC, 1998. Coal Directory of India: 1996-97 ------------------------------------------------------- MoPNG, 1992. Indian Petroleum and Natural Gas Statistics: 1990-91. Ministry of Petroleum and Natural Gas, Government of India, New Delhi. MoPNG, 1996. Indian Petroleum and Natural Gas Statistics: 1994-95 -------------------------- OCC, 1998. Oil Coordination Committee Data (restricted access), Ministry of Petroleum and Natural Gas, Government of India, New Delhi, 1998. Ravindranath N. H. and Hall D. O., 1995. Biomass, Energy & Environment: A Developing Country Perspective from India. Oxford University Press, New York. SAIL, 1994. Statistics for Iron & Steel Industry in India. Steel Authority of India, New Delhi. SAIL, 1996. Statistics for Iron & Steel Industry in India ------------------------------------------ SAKET, 1998. SAKET Petrochemical Handbook, Saket Projects Ltd, Ahmedabad.

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Shukla P. R., 1994. Brick Making in India 1993: A Draft Report. Indian Institute of Management, Ahmedabad. Shukla P.R., Loulou R., and Kanudia A., 1997. Energy and Environment Strategies for a Sustainable Future: Analysis with the Indian MARKAL model. Allied Publishers, New Delhi. Shukla, P. R., Ghosh, Debyani, Chandler, W. and Logan, J., 1999. Developing Countries and Global Climate Change: Electric Power Option in India. PEW Center on Global Climate Change, Arlington, US. TEDDY, 1997. Teri Energy Directory and Data Yearbook 1996-97. Tata Energy Research Institute, New Delhi. TEDDY, 1998. Teri Energy Directory and Data Yearbook 1997-98 ----------------------------- TEDDY, 1999. Teri Energy Directory and Data Yearbook 1998-99 ----------------------------- TERI, 1997. Rural and Renewable Energy: Perspectives from Developing Countries. Tata Energy Research Institute, New Delhi. URBAIR, 1997. Urban Air Quality Management Strategy in Asia: Greater Mumbai Report. Edited by Jitendra J. Shah and Tanvi Nagpal, Wolrld Bank Technical Paper No. 381, Washington D. C. WB, 1997. A Planner’s Guide for Selecting Clean Coal Technologies for Power Plants, World Bank Technical Paper No. 387. The World Bank, Washington D. C. Acknowledgements

The authors are grateful to Dr Jae Edmonds, Dr Murari Lal, Dr A. P. Mitra, Dr Morita T.

Suneyuki and Dr Jayant Sathaye for their suggestions and valuable comments.

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Tables Table 1: Sulfur Dioxide emission coefficients Source categories Emission Coefficient Energy combustion Ton/Ton Ton/PJ Coal 0.0102 549.1 High Speed Diesel 0.02 465.2 Motor Spirit 0.01 108.7 Kerosene 0.005 116.2 Light Diesel Oil 0.04 837.4 Fuel Oil 0.08 1993.6 Naphtha 0.01 111.1 Aviation Turbine Fuel 0.001 23.2 Low Sulfur Heavy Stock 0.04 995.2 Natural gas Negligible 0 Fuel wood 0.0008 53.3 Dung cakes 0.0006 42.9 Agriculture crop residue 0.0006 46.2 Non-energy sources Sulfuric acid production 0.012 - Copper smelting * 0.33 - Lead Smelting * 0.2 - Zinc smelting * 0.2 - Cement production 0.0003 - * Sources: IPCC, 1997; Xiulian et al., 1997. Table 2: NOx Emission coefficients for various fuels in India (Kg/TJ)

Sectors \ Source categories

Coal Natural Gas

Oil Wood/ Wood Waste

Charcoal Other Biomass (b)

Energy Sector (a) 300 150 200 100 100 100 Manufacturing and Construction (a) 300 150 200 100 100 100

Aviation 300 Road 600 600

800 (c)

Railways 300 1200

Transport

Navigation 300 1500 Commercial 100 50 100 100 100 100 Residential 100 50 100 100 100 100 Agriculture Stationary 100 50 100 100 100 100

Other Sectors

Mobile 1000 1200

Note: (a) NOX emission factors for small combustion facilities tend to be much smaller than for large facilities due to lower combustion temperatures. (b) Includes animal dung, agricultural, municipal and industrial waste (c) It assumes that heavy-duty vehicles running on diesel consume the major part.

Source: IPCC, 1997.

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Table 3: Range analysis of SO2 emissions

% of total emissions No. of largest emitter districts 1990 1995

% CAGR (1990-95)

1-5 14.7 15.5 11.7 1-15 31.9 33.4 7.7 1-25 43.1 46.5 7.9 1-47 59.1 63.8 8.1 1-233 92.1 94.3 6.1 All India (1-466) 100 100 5.5 Table 4: Top ten SO2 emitting districts in terms of total emissions

Total SO2 (Gg) District 1990 1995

% CAGR (1990-95)

Bilaspur 156 176 2,4 Sonbhadra 119 174 8,0 South Arcot 10 138 69,1 Karimnagar 84 127 8,4 Chandrapur 49 112 18,0 Mirzapur 83 105 4,7 Giridih 83 96 3,1 Tirunelveli-Kattabomman 49 89 12,6 Krishna 44 86 14,2 Nagpur 62 85 6,4

Table 5: Top ten SO2 emitting districts in terms of emissions per unit area

SO2/area (tons/km2) Average annual concentration (Micro grams/m3) #

District Area (km2)

1990 1995 1990 1995 Chennai 174 206,2 330,3 19 23 Calcutta 185 197,2 177,1 30 36 Greater Mumbai 603 118,4 112,0 37 31 Mahe 9 88,9 75,6 NM NM Gandhinagar 649 16,7 49,6 21* 32* Delhi 1483 47,9 46,7 16 24 Hyderabad 217 33,5 41,0 9 17 Chandigarh 114 23,1 35,7 7 11 Rupnagar 2085 21,8 31,6 NM NM Sonbhadra 6358 18,7 27,4 NM NM # Source: (B5) CPCB (1991 and 1996) NM indicates not monitored. * For Gandhinagar district, we have taken the CPCB measured values for Ahmedabad city.

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Table 6: Top 5 top SO2 emitting districts for different sectors in 1995 Sector Largest Second Third Fourth Fifth

Power generation Sonbhadra Bilaspur South Arcot Karimnagar Chandrapur Transport Delhi Greater

Mumbai Bangalore Chennai Pune

Steel Raipur Giridih Visakhapatnam Barddhaman Purbi Singhbhum

Cement Gulbarga Satna Chandrapur Chittaurgarh Raipur Other industries Dhenkanal Karimnagar Kanpur Puri Calcutta Sulfuric acid Ernakulam Vadodara Visakhapatnam Greater

Mumbai Chidambaranar

Copper Smelting Jhunjhuna Balagat Purbi Singhbhum

Alwar Sundargarh

Lead smelting Udaipur Sundargarh Bilwara Guntur East Sikkim Zinc Smelting Udaipur Bilwara East Sikkim Other sectors Greater

Mumbai Delhi Medinipur North

Twenty Barddhaman

Overall Sonbhadra Bilaspur South Arcot Karimnagar Chandrapur Table 7: Range analysis of NOX emissions

% of total emissions No. of largest emitter districts 1990 1995

% CAGR (1990-95)

1-5 10.73 10.98 8.8 1-15 22.75 24.04 7.64 1-25 31.01 33.26 7.66 1-47 43.74 46.6 7.4 1-233 84.7 86.9 6 All India (1-466) 100 100 5.6 Table 8: Top ten NOX emitting districts in terms of total emissions

Total NOX (Gg) District 1990 1995

% CAGR (1990-95)

Bilaspur 74 85 2.6 Delhi 66 82 4.5 Sonbhadra 56 81 7.8 South Arcot 13 70 40.9 Karimnagar 41 63 8.7 Chandrapur 25 54 16.9 Mirzapur 39 50 4.9 Greater Mumbai 46 49 1.2 Krishna 27 48 12.6 Giridih 40 46 3.1

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Table 9: Top ten NOX emitting districts in terms of emissions per unit area NOX /area (tons/km2) District Area (km2)

1990 1995 Chennai 174 116 170 Mahe 9 143 119 Calcutta 185 112 114 Greater Mumbai 603 76 81 Hyderabad 217 40 58 Delhi 1483 44 55 Chandigarh 114 28 41 Gandhinagar 649 9 25 Rupnagar 2085 9 14 Sonbhadra 6358 9 13

Table 10: Largest NOx emitting Indian districts for different sources in 1995 Source Largest Second Third Fourth Fifth Coal Combustion

Sonbhadra Bilaspur South Arcot Karimnagar Chandrapur

Oil Combustion

Delhi Greater Mumbai Bangalore Thane Raigarh

Biomass Combustion

Cuttak Muzaffarnagar Bijnor Meerut Medinipur

Natural Gas Bulandshahr Etawah Surat Kota Bharuch Industrial Process

Greater Mumbai Sundargarh Bharuch Raigarh Rupnagar

Overall Bilaspur Delhi Sonbhadra South Arcot Karimnagar Table 11: Sectoral contributions to Indian emissions in 1995

% share Sectors NOx SO2

Power generation 27,9 46,1 Transport 32,0 7,8 Industry 19,2 34,4 Biomass burning 18,7 5,2 Other sectors 1,9 3,8 Non-energy sources 0,3 2,7 All India emissions (Tg) 3.46 4.64

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