Indian GHG and Local Pollutant Emissions: Present Trends and Future Projections Amit Garg Workshop...

Indian GHG and Local Pollutant Emissions: Present Trends and Future Projections

Amit Garg

Workshop on Global Air Pollution Trends to 2030January 27-28, 2005, IIASA, Austria

Indian Emission Analysis • Greenhouse gases (CO2, Methane, N2O, CFC, HFC, SF6)

• Local pollutants (SO2, NOX, CO, Particulates)• Large point and Area source emissions mapping• Present (1990 to 2000) and future projections (up to 2030)• GHG and local pollutants: Policy links and disjoints• Development pathways and emission scenarios • SO2 emissions trading and technology push comparison • Human health impact assessments due to local pollutant emissions• Bottom-up models used: MARKAL and AIM/Local

MARKAL (Market Allocation)

AIM/Local and AIM/Enduse

Bottom-UP Models Used

Model System for India’s Emissions Policy Analysis

Models

Top-down Models

•AIM/Material•SGM•GEMA•ERB•AIM/Trend

Local Models

•AIM/Local•Inventory Assessment•Health Impact Assessment Model

Bottom-up Models

•ANSWER – MARKAL•Stochastic MARKAL•Demand Projection•AIM/End-use•Power Sector LP

Soft-linked Models Framework

ERB

SGM

AIM/Material

AIM/Trend

Invent o ry Assessment

Health Impact A ssessment Model

GIS I/F

Prod

uctiv

ity Global Energy Prices

Regional projections

Power Sector LP

Demand Projection

AIM/E nd - use

ANSWER MARKAL

Stochastic MARKAL

AIM/Local

Bottom - Up Models

Energy Balances

Sector Demand

End -use Demand

Tech

nolo

gy S

hare Scenarios Emissions

Consolidation

Prices, GDP

Local Models

Top - Down Models

GEMA

Local Emissions Future Projections

Technology Specifi cations

Emissions Inventory of India: Present Trends

Salient features Gridded inventory database for 1990, 1995 and 2000

• CO2, CH4, N2O, SO2 , NOX emissions covered• District level emission data (466 districts in 1991, now 593)• 80% districts smaller than 1o x 1o and 60% smaller than 1/2o x 1/2o

• 382 large point sources (LPS) mapped for the year 2000• Collaboration with Space Application Centre, ISRO• 2004 database being created• IPCC methodology used• Indian emission factors used to the extent possible

Future projections• Up to 2100 for CO2 (national emission nos.)• Up to 2030 for CO2, CH4, N2O, SO2 (finer with LPS and area sources)• Up to 2030 for SPM and CO (coarse estimation)• LPS increased to 457 (2010), 523 (2020) and 587 (2030)

CO2 Emission Distribution (1995)

Power IndustryRoad Other transportOther sectors

SteelCement

Other industries

45%

35%

13%2%5%

35%

10%55%

Power sector has 90% emissions from 50 plants

Industry emissions are relatively dispersed. 10% districts emit 70% (including 5 steel plants)

Coal and power sector dominate Indian CO2 emissions

Methane Emissions (1995)

45%

22%

15%

10%2% 4% 2%

LivestockPaddy cultivationBiomass burningMunicipal solid wasteWaste waterOil & gas production & transportationCoal production

Livestock and rice paddy emissions dominate Indian methane emissions

N2O: Major Contributors (1995)

60%11%

10%

9%7% 3%

Nitrogen fertilizer use Biomass burning Fertilizer production LivestockOthers Industry (non-energy)

SO2: Major Contributors (1995)

Power sector IndustryAgriculture RoadOthers Other transport

Other industries SteelFertilizer CementIndustry (non-energy SO2)

46%

36%

8%6%3%1%

42%

27%

14%

10%7%

Emission sources are mostly similar to CO2 emissions

NOX : Major Contributors (1995) 28%

28%19%

19%4% 2%

Electric power generation Road transportIndustry (energy use) Biomass burningOther transport Other Industries

% 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

Development Pathways and Emission Scenarios for India

Development Pathways

IA1: High Growth

IA2: Fragmented Growth

IB1: Sustainable Development

IB2: Business-As-Usual

High market integration

Fragmented market

Centralized Governance

Decentralized governance

Governance Market Integration

IA1 IA2

IB2IB1

Scenario StorylinesIA1: High Growth

• 7.7% GDP growth for next three decades• Enhanced all-round infrastructure• Accelerated market reforms• High access to global finance & technologies• Technology, information & industry driven

IB2: Business-As-Usual• 5.5% GDP growth for next three decades• Fragmented infrastructure development• Inward looking policies• Low globalization and liberalization• Dematerialization, renewable energy thrust

IB1: Sustainable Development• 6.5% GDP growth for next three decades• Strong environmental integrity of the economy• Sustainable consumption all-round• Dematerialization, renewable energy thrust• Enhanced all-round infrastructure• Lower income disparities• High access to global finance & technologies

IA2: Fragmented Growth• 4.5% GDP growth for next three decades• Fragmented infrastructure development• Slower market reforms• High regional disparities in development levels• Heavy-industry driven•Slower technology improvements

GDP Projections

0

5000

10000

15000

20000

25000

2000

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

US$

, 200

0 pr

ices

IA1

IB1

IB2

IA2

Indexed GDP projections GDP per capita projections

0

1000

2000

3000

4000

5000

6000

7000

8000

2000

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

GD

P In

dexe

d (2

000

= 10

0)

IA1

IB1

IB2

IA2

Population Projections

•“Chain of generations concept” to be dominant for major part of the 21st century for IA2 and IB2 scenarios and also for initial 30 years of IA1 and IB1 scenarios. •“Single generation concept” becomes dominant for IA1 and IB1 after 30 years, and plays a role in IB2 after 2060 and only later for IA2. •These decisions affect the Total Fertility Rates (TFR) and therefore the national population projections.

0

200

400

600

800

1000

1200

1400

1600

1800

2000

1990

2000

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

Mill

ion

IB1, IA1 IB2 IA2

Decadal population growth has declined from 24.8% during 1961–71 to 21.3% during 1991–2001 and is targeted to further decline to 16.2% during 2001–2011

Urbanization

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

1990

2000

2010

2020

2030

2040

2050

2060

2070

2080

2090

2100

Urb

an to

tota

l pop

ulat

ion

ratio

IA1

IB1

IB2

IA2

The drivers of urbanization are different for alternate scenarios

Population Density Distribution

Maps available for 1990 and 2000

0 115

225

335

455

565

675 785

>=900

Population density (persons per km2)

Land use

0

200

400

600

800

1000

1200

1400

1600

1950 1960 1970 1980 1990 2000

Are

a (T

hous

and

km sq

)

Miscellaneous tree crop and grooves Permenent pasture and other grazing land

Culturable wasteland Barren and unculturable land

Non-agriculture use Fallow land

Forests Net sown area

•Parts of barren, fallow and wastelands (19% in 2000) would be brought into active use•Non-agriculture use of land would grow due to rising urbanization and industrial growth•Tree and forest cover would also change under alternate scenarios. Government’s internal target is 33% forest and tree cover•Agricultural yield is expected to increase although net sown area has almost stagnated over the last 30 years to around 1.42 million km2

Livestock population share projections

0

10

20

30

40

50

1980

1985

1990

1995

2000

2005

2010

2015

2020

2025

2030

Year

Shar

e (%

)

Cattle Buffalo SheepGoat Horses & Ponies DonkeysCamels Pigs

There is an increasing trend in buffalo (dairy) population resulting in increased share

Shares of opencast and underground mining, IB2

0

10

20

30

40

50

60

70

80

90

2000 2005 2010 2015 2020 2025 2030

Years

Min

ing

Shar

e (%

)

Opencast mining

Underground mining

Cost: cheapEnv.: overburden removalReserves: limited

Cost: expensiveEnv.: coal bed methaneReserves: higher

Increase coal import

Emission Projections for India

GHG versus Local Emissions in India (IB2 Scenario)

Carbon Emissions SO2 Emissions

0

200

400

600

800

1995 2005 2015 2025 2035Year

Car

bon

(MT

)

Year

Mill

ion

Ton

nes

0

1

2

3

4

5

6

1995 2005 2015 2025 2035

7

Delhi SO2 emissions from Oil

Sulfur Coefficient decrease for Diesel over 1995-2002 has resulted in substantial SO2 emission reduction in Delhi0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

1900 1995 2000

SO2

(Mill

ion

Ton)

High Speed Diesel Gasoline Kerosene

Light Diesel Oil Aviation Turbine Fuel Others

Carbon Emissions ( Million Ton)

200

300

400

500

600

700

800

900

2000 2010 2020 2030

IA1

IB2

IB1

IA2

Carbon Emission Pathways

Energy, Carbon, Electricity and GDP(IB2 Scenario)

0

2

4

6

8

10

12

14

16

18

20

1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030

Energy Carbon Electricity GDP

Past Trends

Future Projections

4

5

6

7

8

9

10

1500 3500 5500 7500 9500 11500

GDP per capita (PPP$)

MT IB2

IB1

IA22035

2025

2020

Kuznets’ Analysis – SO2 Emissions: Development Pathways Vs. Time-frame

Projecting Regional Emission Spreads

LPS Coverage for CO2 and SO2

Sector Sub-sectors LPS covered 2000 2010 2020 2030

Power (coal & Oil) 82 111 131 150 Power (natural gas) 12 17 20 23

Steel 10 16 22 28 Cement * 85 98 110 123 Fertilizer 31 41 52 62 Paper 33 38 43 48 Sugar 28 28 29 30

Energy

Caustic Soda 19 21 23 26 H2SO4 manufacturing 63 64 66 68 Aluminium (Al) 3 4 5 5 Copper ore smelting (Cu) 8 9 10 11 Lead ore smelting (Pb) 5 6 7 8

Industrial processes

Zinc ore smelting (Zn) 3 4 5 5 Total 382 457 523 587

LPS Locations

2000 2030

Million Tons

LPS: CO2 Emissions

1995

CO 2

Sectors

No. ofLPS LPS ( Tg) LPS/Total

Power 94 365 47Steel 11 48 6Cement 85 68 9Fertilizer 31 14 2Sugar 28 0.7 0.09Paper 33 2.9 0.37

LPS: SO2 Emissions

Region Details No. of LPS

LPS/Total SO2 (%)

Main Sources

A Golden

corridor 32 6.1 Power,

H2SO4 B Delhi 20 2.4 Power,

Cement C Northeast

India coal mine 21 7.9 Power,

Cement D East India coal

mine 18 5.5 Power,

Steel, Cement

E Central India coal mine

16 6.1 Power, Steel

F Southern region

13 3.9 Power, Cement

Thousand Tons

A

B

C

D

E

F

1995

Regional distribution of CO2 emissions for IB2 Scenario

Note: Circles show emissions from large point sources

05

1015

30

40

20

Million Tons

< 33 - 66 - 99 - 1212 - 1515 - 1818 - 21> 21

Million Tons

2000 2030

2000 2030

< 0.010.03

0.07

0.15

< 0.20

0.11

Million Tons< 0.01

0.03

0.07

0.15

> 0.20

0.11

Million Tons

< 0.010.01-0.017

0.017-0.0260.026-0.0350.035-0.0440.044-0.0530.053-0.060

> 0.060

Million Tons


Regional distribution of SO2 emissions for IB2 Scenario

CH4 Emissions under BAU Scenario (IB2)

0

5

10

15

20

25

30

2000 2010 2020 2030

CH

4 e

mis

sion

s (T

g)

Coal production

Agriculture residue

Waste water

Paddy cultivationManure management

Oil & natural gasCoal productionBiomass consumption

Enteric fermentation

Municipal solid waste

Increasing urban population, higher waste collection,Increased dumping at land-fills, deeper waste dumps,and their improved management


2000 2030

Thousand Ton CH4

Regional distribution of CH4 emissions for IB2 Scenario

N2O Emissions Under BAU Scenario (IB2)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

2000 2010 2020 2030

N2O

em

issi

ons (

Tg)

Indirect emissionsIndustrial processesLivestockSynthetic fertilizer useNatural gas combustionBiological nitrogen fixationField burning of agricultureresidueOil product combustionCoal combustion

Agriculture sector activities account for more than 90%


Regional distribution of N2O emissions forIB2 Scenario

2000 2030

CO2, CH4, N2O and CO2 Equivalent GHG Emissions (IB2)

0

50

100

150

200

250

300

350

2000 2010 2020 2030

Inde

x 20

00 =

100

CO2

Methane

N2O

CO2 equivalent

0%

20%

40%

60%

80%

100%

2000 2010 2020 2030

CO

2 equ

ival

ent (

% S

hare

)CO2 Methane N2O

Basket of 6-Gases and CO2 Equivalent GHG Emissions (IB2)

Emission 2000 2005 2010 2015 2020 2025 2030CO2 956 1203 1507 1778 2080 2350 2572CH4 391 407 422 435 462 497 529N2O 95 125 156 187 214 235 250PFC 7.13 8.4 10.3 12.4 15.2 19 24HFC 3.7 8.4 15.0 32.0 56.0 85.2 110.0SF6 0.3 2.0 4.4 7.7 11.9 17.4 21.3CO2-Eq 1454 1754 2115 2453 2839 3203 3507

0%

20%

40%

60%

80%

100%

2000 2005 2010 2015 2020 2025 2030

Year

CO

2 E

quiv

alen

t Sha

res

CO2 CH4 N2O fluorochemical GHGs

Contributing Factors Towards BAU Emissions (Gap Filling Policies)

Carbon Emissions, IB2 (Mt)

212

738

0

300

600

900

1200

1995 2000 2005 2010 2015 2020 2025 2030 2035

Technological freezeAutonomous Energy Efficiency Improvementsstructural conversion of economy

1080

212

738

0

300

600

900

1200

1995 2000 2005 2010 2015 2020 2025 2030 2035

Em

issi

ons (

MtC

)

Technological freezeBAU (IB2)Technological freeze

SO2 Emissions, IB2 (Mt)

0

4

8

12

16

20

1995 2000 2005 2010 2015 2020 2025 2030 2035

Em

issi

ons (

Mt)

Reference caseFGD introductionTechnological freeze

Fuel quality improvementsAutonomous Energy Efficiency Improvementsstructural conversion of economy

Reference caseFGD introductionTechnological freeze

Reference case, IB2FGD introductionTechnological freeze

NOX Emissions, IB2 (Mt)

Reference caseTechnological freeze

Autonomous Energy Efficiency ImprovementsStructural conversion of economy

0

5

10

15

20

1995 2000 2005 2010 2015 2020 2025 2030 2035

8.5

17.4

3.46


Autonomous Energy Efficiency ImprovementsStructural conversion of economy


Autonomous Energy Efficiency ImprovementsStructural conversion of economyAutonomous Energy Efficiency ImprovementsStructural conversion of economy

0

5

10

15

20

1995 2000 2005 2010 2015 2020 2025 2030 2035

8.5

17.4

3.46

0

5

10

15

20

1995 2000 2005 2010 2015 2020 2025 2030 2035

Em

issi

ons (

Mt)

8.5

17.4

3.46

(IB2)

CO Emissions, IB2 (Mt)

0

20

40

60

80

1995 2000 2005 2010 2015 2020 2025 2030 2035

Em

issi

ons (

Mt)

Reference case Demand side (Good practices & Synergistic effects) Technological freeze (demand) Structural conversion of economy

(IB2)

Particulate Emissions, IB2 (Mt)

0

7

14

21

28

35

1995 2000 2005 2010 2015 2020 2025 2030 2035

3.1

32

5.9

10.9

0

7

14

21

28

35

1995 2000 2005 2010 2015 2020 2025 2030 2035

Em

issi

ons (

Mt)

Reference caseAsh content reductionTechnological freeze

ESP efficiency improvementsAutonomous Energy Efficiency ImprovementsStructural conversion of economy



MARKAL Model Applications for India

Some Mitigation Results for India

Carbon Mitigation Potential

Mitigation options

Mitigation potential during 2002-2012

(MtC)

Long-term marginal cost

($/tC)

Demand side energy efficiency 45 0-15

Supply side energy efficiency 32 0-12

Electricity transmission and distribution 12 5-30

Renewable electricity technologies 23 3-15

Fuel switching (coal to gas) 8 5-20

Carbon mitigated 120 MtC (up to $30/tC)

Cumulative emissions 4.4 BtC

Marginal Cost of Carbon Mitigation (1995-2035)

6 billion tons of mitigation below $25/ ton of carbon

Carbon mitigation (billion ton)

Cos

t ($/

Ton

of C

arbo

n)

0

10

20

30

40

50

60

1 2 3 4 5 6 7

0

25

50

100

150

-2510 20 30 40 50

Cumulative CH4 mitigation (Million TCE)Mar

gina

l Aba

tem

ent C

ost

($/T

CE

)

Methane Mitigation

• Methane mitigation mostly from coal mining and MSW• Agriculture activities are widely dispersed, unorganized, and for sustenance. Therefore mitigation is more difficult than CO2 emissions.• Yield enhancement has to be the driving factor in agriculture and methane mitigation would be additional benefits.

Marginal costs for SO2 mitigation

0

2000

4000

6000

8000

2005 2015 2030

YearMar

gina

l Cos

ts (R

s/to

n of

SO

2)

Compliance costs over 2010-2030

Technology push US$ 12.7 billion

Emissions Trading US$ 7.1 billion

Annual average cost savings over a 20 year period are US$ 280 million

0

500

1000

1500

2000

1975 1985 1995 2005 2015 2025 2035

Year

Inde

x (1

975

= 10

0)

Carbon Energy GDP

Population Sulfur

Conclusions

• CO2 and SO2 emissions from India, although connected, do not move in synchronization in future and have a disjoint under various scenarios.

• GHG emissions continue to rise while SO2 emissions decline after some years under all scenarios.

• SO2 mitigation has “where” flexibility in a national context, which is not available for GHG mitigation.

• SO2 mitigation under BAU due to sulfur reduction in petroleum oil products (recently) and FGD penetration (later).

• SPM mitigation due to enforcing electro-static precipitator efficiency norms in industrial units, with cleaner fuels and vehicles also contributing substantially.

Conclusions

• High economic growth is better than lower growth to mitigate local pollution as lack of investible resources limits investments in cleaner environmental measures.

• Validates the environmental Kuznets’ curve for India as SO2 emissions peak around per capita GDP of US$ 5000-6000 (year 2000 PPP basis) under alternate scenarios.

• Co-benefits for direct SO2 mitigation policy and direct CO2 mitigation policy are asymmetric. The emission elasticity of SO2 emissions due to C mitigation policy is around 1.2, and C elasticity due to SO2 mitigation policy is around 0.1

Conclusions

• Under simultaneous CO2 and SO2 constraints, mitigation depends upon carbon price assumptions. • Under high carbon price, coal to gas switch for LPS (SO2 declines) but not much

oil substitution in transport sector (urban hotspots still persist). • Under low carbon price, marginal coal substitution (so marginal SO2 mitigation).

• Separate mitigation policies for CO2 and SO2 emissions in India, although joint mitigation policies possible mainly through efficiency improvements and fuel switching for certain sectors

Conclusions

Thanks

Indian GHG and Local Pollutant Emissions: Present Trends and Future Projections Amit Garg Workshop...

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