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Atmospheric Environment 45 (2011) 4922e4929

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Atmospheric Environment

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Methane emissions in India: Sub-regional and sectoral trends

Amit Garg, Bhushan Kankal*, P.R. ShuklaIndian Institute of Management, Ahmedabad, India

a r t i c l e i n f o

Article history:Received 6 February 2011Received in revised form10 May 2011Accepted 1 June 2011

Keywords:MethaneSectoralSub-regionalIndia

* Corresponding author. Tel.: þ91 79 6632 4429.E-mail address: bhushank@iimahd.ernet.in (B. Kan

1352-2310/$ e see front matter � 2011 Elsevier Ltd.doi:10.1016/j.atmosenv.2011.06.004

a b s t r a c t

This paper uses the 2006 IPCC Guidelines and latest country specific emission factors to estimate Indianmethane emissions at sectoral and district level for the years 1990, 1995, 2005 and 2008. The estimatesshow that while methane emissions have increased steadily over past two decades, their share in India’saggregate GHG emissions has declined from 31% in 1985 to 27% in 2008 mainly due to relatively highergrowth CO2 emissions from the fossil fuels. The estimates for the year 2008 show that: i) agriculturesector, which employed two-thirds of India’s population and contributed 17% of GDP, accounted for 23%of India’s GHG emissions ii) 83% of country’s methane emissions are contributed by enteric fermentation,manure use and rice production, and iii) methane emissions from urban solid waste are steadily risingover the past two decades; their share in aggregate methane emissions has reached 8%. Resting on thedisaggregated emissions estimates, the paper argues for using geographical and sectoral flexibilities todevelop a roadmap for mitigation of methane emissions for India.

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1. Introduction

India is an emerging economy and is witnessing multiple tran-sitions, including high value addition by services and industrysectors than traditional agriculture. Still, agriculture currentlyprovides two-thirds of country’s employment and contributes 17%to GDP. It is the main contributor to methane (CH4) and nitrousoxide (N2O) emissions. This paper estimates the national methaneemissions and their sectoral contributions for each of the 594districts of India for 1990, 1995, 2005 and 2008.

We show that the disaggregated emission estimates, by region,sector and source categories, are the key to delineate mitigationactions where they matter most. The 594 districts capture well thegeographical diversity of Indian emission patterns arising fromdiverse resource endowments, human and livestock populationdistributions, and cultivation practices. The 80% of these districts aresmaller than 1�1 degree resolution and 60% are even smaller than½�½ degree. District level emissions thus represent very finelygridded inventory information by international standards, requiredfor climate change modeling and also inverse modeling purposes,including for aerosols and black carbon estimation. Moreover,districts in Indiahavewell establishedgovernance structures that arewell suited for implementing and monitoring mitigation measures.

We identify the top five largest emitter districts, in each sourcecategory, as hot spot districts. These are the key administrative

kal).

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locales to implement portfolio of measures that best suits howmuch, where, and how of methane mitigation flexibility. Livestockare the largest source of India’s methane emissions and contributenearly a half of present national methane emissions. Mitigationmeasures for livestock related methane emissions, such asimprovement of feed by adding digesters and methane inhibitorsand enhancing share of cross-bred cattle that have lower methaneto milk yield ratio, require locale specific implementation. Forinstance, well administered grass-root institutions, e.g. livestockextension centers, are key to effective mitigation and the districtthat house such centers are better equipped to implement miti-gation actions at lower costs.

Similarly mitigating methane emissions from paddy cultivation,the second highest methane emitting source from India, requirestargeting sub-regional administrative set-ups for implementinglocale specific measures that enhance rice productivity whilesimultaneously delivering higher water use efficiency andmethaneemission mitigation. Capturing methane from municipal solidwaste sites, oil and gas exploration wells and coal mines alsorequires facility level assessment at a sub-regional level. Therefore,the district level GHG inventory estimation reported in this paperadds to the depth as well as the value to the national GHG inventoryassessment and mitigation programs.

2. Emission sources, methodology, activity dataand emission factors

The all India methane (CH4) emissions are calculated by aggre-gating emissions from the following source categories e livestock,

Table 1Methodology used for emission estimation with reference to IPCC (2006)Guidelines.

Emission source Methodology Page no. Equation no. Emission factorgiven in thispaper

Enteric fermentation Vol. 4, Ch. 10 10.28 10.19e10.20 Table 2Rice cultivation Vol. 4, Ch. 5 5.45 5.1 Table 3Manure management Vol. 4, Ch. 10 10.37 10.22 Table 2Biomass burning

(off-site)Vol. 2, Ch. 2 2.11 2.1 Table 4

Coal miningand handling

Vol. 2, Ch. 4 4.12 4.1.4 and4.1.8

Table 5

Oil and naturalgas systems

Vol. 2, Ch. 4 4.41 4.2.1e4.2.2 Table 6

Agriculturecrop residueburning (on-site)

Vol. 4, Ch. 2 2.42 2.27 Table 4

Municipalsolid waste

Vol. 5, Ch. 3 3.8 3.1e3.7

Wastewater disposalDomestic

wastewaterVol. 5, Ch. 6 6.11e6.16 6.1e6.3

Industrialwastewater

Vol. 5, Ch. 3 6.20e6.23 6.4e6.6

A. Garg et al. / Atmospheric Environment 45 (2011) 4922e4929 4923

rice cultivation, agriculture residue, biomass burning, coalproduction, oil production, municipal solid waste, industrial solidwaste, wastewater disposal, and biogas for energy.

There are two sources of methane emission from livestock: (1)enteric fermentation, that is from digestive process of ruminantsand (2) from animal waste management (IPCC, 2006;Bandyopadhyay et al., 1996). Livestock population in India is thehighest in the world and is growing at a high rate in certain live-stock sub-categories. Studies by Huarte et al. (2010) have alsoshown a positive correlation between methane emissions andcattle livestock.

Rice paddy cultivation is the next main source of methaneemissions in India. Rice irrigation regime is the driving factor alongwith rice variety and other cultivation practices. The rice varietiesgrown in different parts of India have considerable variability inwater availability, weather, soil, traditional cultivation practices andpurposes (GoI, 2008). Rice fields of India are classified as irrigated,

Table 2The availability of data and methodology used for data estimation.

Activity data Year of data Available data level and main s

Charcoal consumption 2005 State (NSSO, 2007)Coal mining 2008 Seam level (CMIE, 2010)Fuelwood consumption 2005 State (Indiastat, 2008)

Human population 2001 District (CoI, 2001)Livestock population 2003 District (DAHDF, 2008)Municipal Solid waste generation 2005 National

Natural Gas consumption 2005 LPS level for industry and statelevel for vehicles (CEA, 2006; FASAIL, 2004; CMIE, 2010; CPCB, 2TDMS, 2008; AMC, 2006; Malho

Natural Gas Flaring 2008 Gas field (CMIE, 2010)Natural Gas Production 2008 Basin level (MoPNG, 2010)Oil production 2008 Basin level (MoPNG, 2010)Oil Refining 2008 Refinery level (MoPNG, 2010)Rice cultivation 2008 State Level (MoA, 2010)Synthetic fertilizer applied 2005 District (FAI, 2005)Waste water generation 2004 Industry level norms and stand

(CPCB, 2008; CMIE, 2010; IPCC,

rainfed, deepwater or upland. Most of the rice is grown onwetlands(irrigated, rainfed and deepwater), only 15% of the cultivated area isunder uplands (Ananda et al., 2004). Wetland rice fields are themajor sources of methane emission.

Methane is also generated from waste decomposition underanaerobic conditions. These include emission from municipal solidwaste, residential and industrial waste water handling. The currentper capita waste generation and thus consequent methane emis-sions are low in India as compared to developed countries (Kumaret al., 2004). However an increase in waste generation and collec-tion levels, higher segregation of non-degradable waste beforedumping, and more compaction at dump sites are projected toincrease methane generation from this source in India (Singhal andPandey, 2001; Garg et al., 2004).

Coal mining activities also produce considerable methane.Deeper the mine more is the methane generation since moremethane is trapped in coal seams due to higher pressures availableat higher mine depths. However, since 85% coal is surface mined inIndia currently, the methane generation is relatively lower.Banerjee et al. (1994) estimates coal mine methane emissions to be0.60 million ton in 2000, a ten-fold increase during the years1951e2000. There is an increased methane emission from oil andnatural gas production and distribution activities, as newgas basinsare discovered and refinery capacities are added during the pastdecade in India (MoPNG, 2010).

We have used IPCC (2006) Guidelines for present estimation. Itprovides specific methodologies for each of the source categories.The different methodologies used for emissions calculations aregiven in Table 1with specific volume and chapter references to IPCC(2006).

Tier 2 methodology has been adopted for estimating methaneemissions from enteric fermentation which takes into account agedistribution and the weight of the animals. To estimate totalemission, the selected emission factors are multiplied by theassociated animal population and summed. The 17th Indian Live-stock census, population has been used by extrapolating the data to2008 based on 1997e2003 CAGR (DAHDF, 2008).

Emissions ¼ EFðTÞ �

NðTÞ106 kg Gg�1

!

ources Allocation/estimation index

Level required Methodology

District level 2008 urban-rural population ratioDistrict Data aggregatedDistrict level Urbanerural population ratio; Pachauri, 2006;

Ravindranath et al., 20072008 data 1991e2001 growth rates used2008 data 1997-2003 growth rates usedDistrict level Per capita MSW generation (CPCB, 2007);

urban population and UMP (1999)

I, 2005;003, 2006;tra, 2001)

District level Industry data aggregated,per vehicle consumption

District level Data aggregatedDistrict level Data aggregatedDistrict level Data aggregatedDistrict level Data aggregatedDistrict level Rural population ratio (Garg et al., 2006)District level e

ards2006)

District level LPS for each industry in each districts

Table 3Methane emission factor.

(a) Enteric fermentation and manure management

Category IPCC default Enteric fermentation(kg capita�1 yr�1)

Manure management(kg capita�1 yr�1)

Dairy cattle Indigenous 28� 4 3.5Crossbred 49� 4 3.8

Nondairy cattle(cross bred)

0e1 yr 12� 4 1.11e3 yr 31� 4 2.3Adult 38� 4 2.5

Nondairy cattle(indigenous)

0e1 yr 14� 4 1.21e2 1/2 yr 30� 4 2.8Adult 37� 4 2.9

Dairy buffalo 42� 4 4.4Nondairy buffalo 0e1 yr 12� 4 1.8

1e3 yr 29� 4 3.4Adult 49� 4 4

Sheep 4� 4 0.18Goat 3� 4 0.18Horses and ponies 6.08a 1.6b

Donkeys 6.08a 0.96b

Camels 6.08a 1.96b

Pigs 6.08a 4.37b

(b) Rice cultivation

Type of water regime % of total areaharvested

Methaneemissions(Gg km�2)

Upland 15%Low land Rainfed Flood prone 10% 0.019� 0.006

Drought prone 16% 0.007� 0.002Irrigated Continuously

flooded16% 0.0174� 0.004

Intermittentlyflooded

Singleaeration

23% 0.0066� 0.0019

Multipleaeration

14% 0.0021� 0.0015

Deepwater

Water depth50e100 cm

6% 0.019� 0.006

(c) Field burning of agricultural residue

Source category Methane emission(kg kg�1)

Fuel wood consumption 0.006Dung cake consumption 0.008Charcoal consumption 0.001Charcoal production 0.2Biogas burningc 1.00E�09

(d) Coal production

Mine type Methane emissions(Ton ton�1)

Open Cast 0.002Degree I 0.00073Degree II 0.00743Degree III 0.01579

(e) Oil and natural gas

Source categories Emission coefficients(g kg�1)

Oil production Fugitive (onshore) 36.3Fugitive (offshore) 7.10E�04Venting 1Flaring 0.0036

Natural Gasproductiond

Fugitives 12.19Flaring 8.80E�04

Oil refiningd 3.91Gas transmission

and storagedFugitives 0.633Venting 0.392

(f) Agriculture crop residue burning

Parameter Crop Value (fraction)

Frac remove (T) 0.8Cf¼ combustion factor Wheat 0.9

All others 0.8Gef¼ emission factor g CH4/kg DM 2.7

(g) Municipal solid waste disposal (only urban population considered) generates0.019 kg methane per kg waste and methane generated is 2.739 kg head�1 yr�1

for 2005.(h) Municipal wastewater disposal:Generates 0.38 kg methane per urban head per year.

(i) Industrial wastewater disposal:Generates 0.086 kg methane per urban head per year.

Source: Indian’s Initial National Communication to the UNFCCC, 2004.Source: Garg and Shukla (2002) and Swamy et al. (2004).Source: IPCC, 2006.

a Garg and Shukla (2002).b Swamy and Bhattacharya (2006).c Tera gram/Tera Joule, (Tg/TJ).d In g CH4 per m�3 of gas.

A. Garg et al. / Atmospheric Environment 45 (2011) 4922e49294924

where Emissions¼methane emissions from enteric fermentation,Giga gram (Gg) CH4 yr�1; EF(T)¼ emission factor for the definedlivestock population, kg head�1 yr�1; N(T)¼ the number of head oflivestock species/category T in the country; T¼ Species/category oflivestock.

Total CH4 Enteric ¼Xi

Ei

where Total CH4Enteric¼ total methane emissions from entericfermentation, Gg CH4 yr�1; Ei¼ is the emissions for the ith livestockcategories and sub-categories.

Similarly the calculations are done for rest of the methaneemitting sectors.

The different activity data is collected from different govern-ment reports and statistics and also some paid secondary data-bases. Table 2 provides details of data availability and how it isconverted to the required data for the particular year.

Diverse data sources have been used and cross verified as muchas possible. Wherever year-specific data were not available, growthtrends of the previous years were applied. Mainly emission coef-ficients relevant to the Indian conditions have been used andwherever not available, appropriate IPCC default emission factorsapplied. In most of the calculation, the collected data are divided asper the urban and rural population of India for the year 2008. Thepopulation (total, urban and rural) has been estimated by projec-ting the population from 2001 Census of India at a compoundannual growth rate (CAGR) of 1991 and 2001 census population forseven years.

Almost 50% of the dung produced is converted to dung cakes(IPCC, 2006) used as fuel and the rest is assumed to decomposeanaerobically leading to CH4 emission. The paddy area of 0.86 km2

in India (MoA, 2010) is of special concern as it is double and at timestriple cropped in a year to increase production. Sun et al. (2011) hasindicated factors responsible for higher CH4 emissions in wet fieldswhile Dong et al. (2011) has compared the addition rates ofnitrogen fertilizer with methane emissions. The emission factorsfor our estimation are taken from the NATCOM (2004) values(Table 3b).

Tier 1 methodology is used for calculation of methane emissionsfrommanuremanagement. The emission factor used for estimationis given in Table 3a. Fuel wood, charcoal, agricultural residues,agricultural waste and municipal waste combustion are by far themajor contributor to CH4 emissions within the fuel combustiongroup.

The fuel wood production data for state level household fuel-wood consumption was taken from Indiastat (2008) for the year2005, distributed as urban and rural consumption on the basis ofstate level 2008 projected urban and rural population ratio of therespective state. The fuelwood consumption in brick industry istaken as 8 Tera grams (Pachauri, 2006) and distributed in ratio ofcoal consumption in bricks industry.

Table 4CH4 emissions from various source categories.

Source categories 2008 (Tg) % CAGR 1995e2008

All energya 4.7 3.54%Biomass 2.23 2.25%Coal mining 1.07 4.02%Oil and natural gas 0.99 6.28%Agriculture 14.4 �0.27%Field burning of agriculture residue 0.41 �3.68%Enteric fermentation 9.23 �0.16%Manure management 0.88 1.22%Rice cultivation 3.88 �0.39%Waste 1.87 3.68%Solid waste 1.71 4.27%Wastewater 0.17 �0.55%

Total 20.97 0.53%

a Sources such as biogas for energy have also been estimated, but foundminisculeand thus not reported here.

A. Garg et al. / Atmospheric Environment 45 (2011) 4922e4929 4925

On an average 41% of wet dung generated is used for dungcakepreparation (Ravindranath et al., 2007) which is then dried beforeburning for energy. However in Delhi, 31% of dung is used fordungcake preparation, while in states of Himachal Pradesh, Jammuand Kashmir, Kerala, Goa, Sikkim, Arunachal Pradesh, Nagaland,Manipur, Mizoram, Tripura, Meghalaya and Assam only 10% dung isused (Swamy et al., 2004).

The coal production from mining has been multiplied with theCH4 emission factor [the conversion factor of 1.49�109 m3 asequivalent to 1Tg of CH4] to arrive at the total CH4 emission fromthis source. In India monitoring of all coal mines is mandatoryunder the auspices of Directorate General of Mine Safety and all thestates have mines identified and classified under various degrees ofgassiness degree I, II, and III instead of sizes, which has been usedfor disaggregated activity data, employing tier 2 methodology.

Tier 1 methodology was used for estimating methane emissionsfrom municipal solid waste (MSW). The average value of per capitaMSW generated from 59 Indian cities was taken for the calculationof all India solid waste generation (CPCB, 2007), distributed in the2008 urban population ratio. 70% of the total solid waste is land-filled, 20% is treated by composting and 10% of the waste isuntreated (UMP, 1999). The methane generation from industrialsolid waste could only be accounted as sludge removed during thewastewater treatment process in methane generation from indus-trial wastewater section, mainly due to absence of proper wastegeneration data from the industries.

Waste water is divided in two categories for calculation ofmethane generatione domestic and industrial. The activity data fordifferent types of industries and the amount of wastewater valuesand other characteristics of wastewater are taken from CPCB(2008). The list of district level industry of the particular typewas taken from CMIE (2010). The methane emissions are calculatedaccording to 2006 IPCC guidelines using India specific emissionfactors.

Table 5Methane emission hotspot districts in India (2008).

District/State

Totalemissions

Methaneemission

Per capitamethane

Main contributors

3. Methane emissions inventory assessment

3.1. Sectoral emissions

Indian methane emissions contributed 27% to total Indian GHGemissions in 2008. Indian methane emissions have been steadilyincreasing since 1985 (Garg et al., 2006) due to increase in thelivestock population and oil and natural gas related activities(Fig. 1). The total amount of methane emitted from India increasedfrom 19 Tg in 1995 to 21 Tg in 2008. Table 4 provides the sectoralincrease in methane emissions during 1995e2008.

The agriculture sector (enteric fermentation, manure manage-ment, rice cultivation) accounts for 61% of the total methane

Fig. 1. Methane emissions over the years.

emissions in India, with 40% from Enteric Fermentation, 17% fromRice Cultivation and 4% from Manure Management. India had thehighest methane production in 2000 from south-Asian countries,with 11.8 Tg CH4 from livestock, primarily cattle and buffaloes(Yamaji et al., 2003). Thenumberof cattle andbuffalo populationhasavisible impacton themethaneemissions fromlivestock (Fig. 4aec).It is followed by biomass burning (21%), solid waste disposal (7%),coal mining (5%), fugitive emissions from oil and natural gasproduction and handling (4%) and waste water disposal (1%).

The marginal decrease in methane emissions from entericfermentation over 1995e2008 is due to the changing profile oflivestock, wherein total cattle population has declined over1997e2003 census, even though milking cow and buffalo pop-ulation hasmarginally increased as well as a change in age profile ofcattle. Area for rice paddy cultivation has marginally changed overthe years resulting in reduction in methane emissions. Fieldburning of agriculture residue has been declining due to its use asa feed for animals. For the energy sector, increasing coal mining andoil and gas exploration contribute to increased methane emissionsfrom these activities. Government policies for better waste waterhandling in urban areas, including for river cleaning purposes, maybe attributed for reducing methane emissions from waste waterhandling activities. Municipal solid waste collection and disposalhas been increasing resulting in a high growth rate of emissions.

(Tg) per capita(kg)

emissionsin CO2eterms (kg)

Mumbai(Maharashtra)

0.36 97 2045 Oil and naturalgas system, MSW,enteric fermentation

Anugul(Orissa)

0.24 186 3908 Coal mining, ricecultivation, entericfermentation

Jamnagar(Gujarat)

0.18 84 1764 Oil and natural gassystem, entericfermentation, biomass

Surguja(Chhattisgarh)

0.17 75 1586 Coal mining, ricecultivation, entericfermentation

Medinipur(West Bengal)

0.15 14 298 Rice cultivation, oiland natural gassystem, entericfermentation

Fig. 2. Total methane emissions in India for 2008 (Gg) (a) State level (b) District level.

A. Garg et al. / Atmospheric Environment 45 (2011) 4922e49294926

The sectoral analysis has implications for national methanemitigation strategies. The nature of sectors and sources woulddetermine the ease of implementing mitigation options and theirrelative costs. A dozen companies in coal mining and oil and gasexploration sectors contribute around 10% of Indian methaneemissions. These firms could target project level interventions(including clean development mechanism projects), have technicalexpertise and can arrange financing. Methane mitigation frommunicipal solid waste could also follow on similar lines and thereare already CDM projects in the pipeline for the same. They havetheir own set of challenges but proper management inputs andbundling could improve their chances of success. National urbanreconstruction mission (JNNURM) and state governments couldprovide institutional facilitation.

The large point sources of methane are mainly from fossil fuelextraction that is unevenly distributed across India and dependsupon the natural resource endowment of various regions. Higheremission growth rate of CO2 (5.6% per annum presently) vis-à-vismethane (0.53% presently) is likely to increase the share of CO2from present 62% to 76% by 2035 mainly at the expense of meth-ane’s share (Garg et al., 2002). However the increasing emissionsfrom landfills LPS in mega-cities would offer possibilities of

Fig. 3. District level (a) cattle population in thousand (b) buffalo po

methane recovery for domestic use. Similarly as coal consumptionincreases in future, especially from deeper mines, there would behigher methane emissions and therefore good potential for har-vesting coal-bed methane.

Dispersed agriculture sources contribute more than 70% ofnational methane emissions. An evaluation of various methanemitigation options indicate that some of the available technologieslike, diet supplementation with feed additive and molasses ureaproduct are highly cost effective in reducing enteric methaneemissions. The availability of cost-effective technologies suggeststhat the methane mitigation projects under CDM can be planned inthe Indian dairy sector to the mutual benefit of countries withemission targets and India (Sirohi et al., 2007).

3.2. Regional emissions

Sub-regional estimation is useful for exploring focused mitiga-tion opportunities. We provide analysis of hotspot locations formethane emissions that could be targeted for mitigation (Table 5).For instance, the largest emitter Mumbai contributes almost 1.5% ofthe total CH4 emitted from India in 2008 with 95% from oil andnatural gas exploration, 3% from MSW and 2% from biomass

pulation in thousand (c) emissions from livestock in kilo tons.

Table 6Category level largest CH4 emitter hotspot districts in 2008.

Sr. No. Source categories Largest Second Third Fourth Fifth

1 Biomass for energy Belgaum Medinipur North 24 Parganas Gulbarga Barddhaman2 Coal mining Anugul Sidhi Surguja Hazaribag Raigarh3 Oil & Natural Gas Mumbai Jamnagar Vadodara Panipat Dakshina Kannada4 Field burning of agricultural residue Uttar Kannada Viluppuram West Godavari Erode Allahabad5 Enteric Fermentation Barbanki Khammam Jaipur Vishakhapatanam Alwar6 Manure Management Barddhaman Bankura Udaipur Barbanki Jaipur7 Rice cultivation Medinipur South 24 Parganas Murshidabad Barddhaman Surguja8 Solid waste disposal Thane Mumbai (Suburban) Bangalore Pune North 24 Parganas9 Wastewater handling Chennai Hyderabad Thane Pondicherry Aurangabad

All India Mumbai Anugul Jamnagar Surguja Medinipur

The names in the italics indicates the presence of these as hotspot district in 1995 emission inventory for the same category (Garg and Shukla, 2002).

A. Garg et al. / Atmospheric Environment 45 (2011) 4922e4929 4927

burning. Methane mitigation in Mumbai would therefore requiremanagement of oil and gas exploration emissions and efficientmethod for collection and disposal of MSW. There are large oilexploration companies in Mumbai that could be targeted throughappropriate corporate policy for GHG mitigation efforts. On theother hand, the next largest emitter e Anugul district, is a coalmining and industrial hubwith appreciable contributions from ricepaddy cultivation as well. While technology for capturing of thefugitive methane emissions from coal mining activities would beuseful for mining companies, dispersed methane emissions fromrice cultivation would require totally different strategies formitigation.

At a state level, Uttar Pradesh, Andhra Pradesh, Maharashtra,West Bengal andMadhya Pradesh are the five top emitting states inIndia for 2008 (Fig. 2aeb). While methane from enteric fermenta-tion and manure management is the main reason for high emis-sions from states Uttar Pradesh and Andhra Pradesh; methane fromMSW generation and oil and gas exploration is main emitter forMaharashtra.

The methane emissions per districts in 2008 were 0.035Tg ascompared to 0.04 Tg in 1995, mainly due to fragmentation ofdistricts in creating almost 20% more districts. The top 25 hotspotdistricts have an average annual growth rate of 0.74% during1995e2008 as compared to 0.84% of all India methane emissions(Fig. 3; Table 7). The major sources of methane emissions aredifferent in top-emitter districts. Methane as part of total GHGemissions would also be different for different districts. Forinstance, Anugul district has per capita methane emissions almostdouble the national CO2e per capita emissions, with methanecontributing over 8% of district’s GHG emissions, while districts likeSonebhadra (UP), Chandigarh, and Chhindwara (MP) methanecontributes 2%,10% and 55%of district’s GHGemissions respectively.

The sectoral hotspot districts have been listed in Table 6. Almost75% districts have changed in this table during 1995 and 2008.

Fig. 4. Distribution of Indian CH4 emissions.

However this churn may not be too drastic for large emitterdistricts and they have settled within top 15 ranks anyway in boththe years, except for districts where new LPS have come in such asa large oil refinery in Jamnagar district.

The methane emission distribution for all the Indian districtsshow an increasing mean (a shift toward right) as well as anincreasing variability (flattening of the distribution curve) over1990e2008 (Fig. 4). A shift toward right implies that district levelemissions would have a higher probability to move to a highervalue in future than reducing. A flattening of the curve implies thatdifference between districts over annual methane emissions isreducing and more districts are now crowding up the space inhigher emissions per district.

The per capita methane emission distribution for each district inIndia over the years is shown in Fig. 5. The average per capitaemissions for the year 2005 from China and US are also marked inthe same figure (World Bank, 2009). It is evident that not only theaverage Indian emissions are much lower than the Chinese and theUS per capita emissions, the highest Indian per capita methaneemissions are just touching the average US per capita emissions.

3.3. Emission intensity of GDP

We tried to estimate methane emission intensity of district GDP(market exchange rate, current price) in each district for the year2008. The value added data was taken from Indicus Analytics(2007) database. The districts with low methane emissions perGDP are industrial districts with high GDP and also high pop-ulations. Their per capita emissions are also comparatively lower.The districts with high methane emissions per GDP are generallyagrarian districts with low GDP contribution and also rural

Fig. 5. Indian district level per capita annual methane emission distribution.

Table 7Distribution of CH4 emissions from Indian districts.

Largest emitter districts % of total emissions

1995 2008

1 to 5 6.63 5.371 to 15 12.98 11.341 to 25 18.04 15.941 to 47 27.74 24.751 to 233 77.59 68.71 to 297 78.2All India (1e593) 100 100

Fig. 6. District level total methane emissions and total gross value added.

A. Garg et al. / Atmospheric Environment 45 (2011) 4922e49294928

dominance (Table 8). However from agriculture perspective alone,Tuensang of Nagaland state and Idukki of Kerala state come out ashaving low intensity, while Anugul, Sidhi and Surguja have highintensity. The later are high fertilizer consuming agrarian districts.In fact the efficient states are in north-east India and Kerala thathave considerable tea plantations and spice cultivation. These cropsdo not contribute muchmethane emissions but add good economicvalue. On the other hand, we have districts in grain productiondominant areas that have higher methane emissions per thousanddollar value added. Fig. 6 provides the xey scatter for the same.

Fig. 7. Marginal Methane Abatement cost curve for Indian districts (US$ per ton CO2e).

3.4. Marginal abatement cost curve

We have estimated the abatement cost of methane for variousdistricts (Fig. 7). The ‘marginal abatement cost (MAC)’ curves ofmethane emissions show, in an increasing order of cost, thepotential of methane abatement options available in an economy.The MAC for a district is computed as the ratio of gross economic‘value added’ from a district and its total methane emissions. TheMAC for methane abatement actions forms an upper bound on theoverall abatement MAC curve that would include all greenhousegases. Fig. 7 provides analysis and some useful insights from MACcurve of methane emissions. TheMAC range for methane emissionsvaries from nearly negligible to US$ 800 per ton CO2e per ton. Themethane mitigation cost depends on the specific measures adop-ted. The costs are higher for rice paddy and livestock due to thelower scale and dispersed nature of these activities. The emissionsmitigation from coal mining and coal bed methane, oil and gasexploration and municipal solid waste offer scale economy as wellas reasonable potential for methane capture, besides co-benefitfrom use of methane as a cleaner energy source (Garg et al.,2004). In cases where the recovered methane from MSW or thecoal bed deliver substantial net benefits, the net methane mitiga-tion cost could be negative. The MAC for a same source acrossdistricts is often depending on the activity level, level of

Table 8Methane emission intensity of GDP in each district.

District State kgCH4/$1000

Low intensityMumbai (Suburban) Maharashtra 2.6Chandigarh Chandigarh 3.3Kolkata West Bengal 4.3Chennai Tamil Nadu 4.3South West Delhi 4.4

High IntensityRaigarh Chhattisgarh 210.4Debagarh Orissa 226.7Surguja Chhattisgarh 246.1Sidhi Madhya Pradesh 264.7Anugul Orissa 373.1

1 US$ ¼ 45 Indian rupees.

infrastructure and local governance structure to facilitateimplementation.

4. Conclusions

This research has updated methane emission estimates fromIndia by incorporating the contemporary methodologies (IPCC,2006), the latest activity data for 2008 and the most recentIndian emission factors available. Time-series analysis using theseupdated methane emissions over the period 1985e2008 have alsoimproved our previous published estimates (Garg et al., 2006). Asper the findings of this paper, the methane emissions from Indiahave grown from 18.85 Tg in 1985 to 20.56 Tg in 2008. Entericfermentation continues to be the largest contributor to India’smethane emissions, increasing by nearly 5% from 1985 to 2008.

The paper has also identified the hotspot districts of methaneemissions in India. Uttar Pradesh and Andhra Pradesh are the twotop-most hotspot methane emitting states of India, while Mumbai(Maharashtra) and Anugul (Orissa) are the top emitter districts. Thehotspot districts have shifted significantly over the time, dependingon the change in activity level and themix in the districts. The shareof methane emission from municipal solid waste in nationalemissions has steadily increased. This suggests increased solidwaste generation as well as more solid waste getting collected anddispatched to the waste dumping sites.

A. Garg et al. / Atmospheric Environment 45 (2011) 4922e4929 4929

India’s disaggregated methane emissions pattern howeverdiffers from that of developed countries in several facets. Thelivestock in India contributes a significantly higher share ofmethane emissions compared to that in developed countries. Dueto their smaller size and weight and conventional feeds ascompared to those in developed countries, the Indian livestockemit lower methane per head. A sizable fraction of the paddycultivation in India is fragmented, dispersed and rain-fed, It istherefore less methane intensive per ton of rice produced. Sinceopen cast coal mining has a very high share in India, the methaneemissions are lower per ton of coal mined. These characteristics ofIndia’s methane emission sources result into a MAC curve which isrelatively different than elsewhere, especially when compared todeveloped countries. Major methane emissions contributingactivities in India, namely livestock rearing and paddy cultivation,involve millions of small and poor farmers. The transaction cost ofimplementing mitigation measures in these sectors is thereforevery high. Our assessment of methane emissions at sub-regional(district) and sectoral level can be useful to focus the actionsaimed at mitigation by the local administrators and economicagents and thereby reduce the cost of mitigation and simulta-neously enhance the mitigation potential.

Acknowledgements

The authors have benefited from discussions with Dr SubodhSharma, Dr A.P Mitra and other experts working on methaneemissions for India’s National Communication preparation process.Research support from our colleague Ms Jigeesha Upadhyay isacknowledged. We also acknowledge Dr. M. Kainuma and Prof.Y. Matsuoka for our continued research cooperation. However theresponsibility for the contents in this paper lies solely with theauthors.

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