7. Methodology for Exploring Co-benefits of CO2
and SO2 Mitigation Policies in India using
AIM/Enduse model
Rahul Pandey1 and Priyadarshi R. Shukla2
Summary. This study illustrates a methodology to explore co-benefits of CO2 andSO2 mitigation objectives, along with initial results for India, using AIM/Enduse
model. It is assumed for India that use of low-sulfur fuels in transport sector, rapid
penetration of sulfur removal technologies in power sector and large industry
boilers will enable early decoupling of the two emissions under the business-asusual scenario. Two additional sets of scenarios – one for carbon taxes and theother for corresponding SO2 constraints – were set up to analyze co-benefits.
Initial results suggest that under the application of carbon tax there is a strong
overlap among the economic options for reduction of CO2 and SO2 emissions overthe business-as-usual level. However, under pure SO2 mitigation targets overbusiness-as-usual, the economic options for SO2 mitigation and CO2 mitigation
are likely to get decoupled. AIM/Enduse, being rich in representation oftechnological processes, is an effective vehicle to analyze these effects.

7.1 Introduction
The Indian energy system, dominated by coal, accounted for over 250 million tonsof carbon emissions from the country in 2000. Despite a decade old process of
economic reforms and accompanied introduction of efficient technologies andpractices in certain sectors like process industries, manufacturing, andtransportation, carbon emissions continue to rise at an alarming rate. This ismainly because of three reasons: i) The Indian economy continues to grow at ahigh rate; ii) Cumulative shift away from coal remains insignificant, particularly inthe electricity generation and industrial sectors, and iii) Inefficient technologies
and practices still thrive in significant parts of the economy including several
small and medium industries and services, agriculture, and the traditional sector.
Although India does not have GHG emissions mitigation commitment under
Kyoto Protocol to the United Nations Framework Convention on Climate Change(UNFCCC), it would be interesting to analyze the effect of future carbon
mitigation commitment on Indian economy, energy, and emissions.
An important concern of policy makers in developing countries like India will
be how to achieve a synergy between domestic environmental policy priorities and1

National Institute for Environmental Studies, Tsukuba 305-8506, Japan (on leave from
Indian Institute of Management, Lucknow 226013, India)
2
Indian Institute of Management, Ahmedabad 380015, India

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GHG mitigation objectives to accrue the co-benefits. Concerns of controlling local
pollution deservedly figure high on the list of domestic policy priorities. Since
developing countries have scarce financial resources, it is essential for them todesign policies that are aimed toward domestic priorities and simultaneously
contribute to GHG mitigation objectives.
In this paper we present a methodology for analyzing above-mentioned synergy
using AIM/Enduse model, with initial results for India. We analyze two sets ofpolicies – (i) CO2 emissions mitigation (ii) SO2 emissions mitigation – and theextent to which the latter can contribute to the former and vice versa. Focus of ouranalysis is on technology and energy options available within different sectors ofIndian economy to achieve these objectives. For this purpose we set up the
AIM/Enduse model for India by treating entire country as a single area, in contrast
to chapter 6 of this book which analyzes Indian area and large point source
emission using AIM/Local model with spatial disaggregation.

7.2 Bottom-up Modeling Framework
Depending on the way a model captures interactions between energy andeconomy, it is classified as bottom-up or top-down. Zhang and Folmer (1998)
have discussed different bottom-up and top-down economic modelling approaches
used in the context of carbon dioxide emissions mitigation. Pandey (2002) has
discussed this classification from the viewpoint of energy policy modeling andresearch concerns for developing countries. Bottom-up models contain detailed
representation of the energy resources, technologies, and end-uses. They are better
suited than top-down models to analyze sector and technology level policy
options. Although top-down models have better characterization of impacts on
economic growth, price feedback, and trade (Hourcade 1993), they are weak inrepresentation of technology and energy details.
AIM/Enduse (Morita et al. 1996; Kainuma et al. 1999, 2000), MARKAL(Fishbone and Abilock 1981; Berger et al. 1987), and EFOM (Finon 1974) are
examples of bottom-up models. AIM/Enduse scores over several other bottom-up
models with respect to its representation of technological detail. On one hand, it
permits modeling of technological processes as complex networks of devices
through which energy and materials flow. On the other hand, it enables
representation of SO2 and NOx pollution removal processes as attachments toregular industrial technologies. Refer to ‘A Guide to AIM/Enduse model’ in thisbook for further details.
Setting up country-level AIM/Enduse model for India comprised four steps: (i)Selection of sectors, services, technologies, reference year and discount rate, (ii)
Estimation of data for services and technologies in the reference year, and (iii)
Projection of service demands, technology shares, and technology improvements
over 37 year time horizon, and (iv) Design of business-as-usual (BAU) and otherscenarios for policy analysis. We summarize the salient features of AIM-India in
Table 1.

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Table 1. Salient features of AIM-India
FeatureTime horizon
Demand sectors*

Description
37 year horizon, from 1995 to 2032
18 sectors comprising agriculture, commercial, residential, roadtransport, rail transport, air transport, water transport, iron & steel,aluminium, cement, brick, nitrogenous fertilizer, pulp & paper,
caustic soda, soda ash, cotton textiles, sugar, and other industries
Energy3 energy conversion and supply sectors comprising electricity, oilconversion andrefining, and natural gas (refer to Sec. 4 of ‘A Guide to
supply sectors
AIM/Enduse model’)Services
Over 70 services including 33 final (or external) services
EnergyOver 20 energy kinds including 10 primary (or external) energy
kindsOver 190 devices in demand sectors, and over 25 devices in energy
Technologies*
conversion sectors (refer to Appendices J and K of ‘A Guide to
AIM/Enduse model’)Sulfur removal
Pollution removal processes like coal washing, limestone injection,
processes
conventional and advanced flue gas desulfurization in electricity
generation and process industries
Data estimation
Bottom-up methodology for estimation of data in reference year
for reference year based partly on published sources and partly on standard
assumptions (refer to Sec. 4 of ‘A Guide to AIM/Enduse model’)Projection of
Projection of service demands until 2032 based on a top-down
service demands
methodology comprising projection of drivers using logistic
regression (refer to Sec. 4 of ‘A Guide to AIM/Enduse model’)*Technological processes in small and medium industries have not yet been modeled in
the current version of AIM-India.

7.3 Design of Scenarios
7.3.1 BAU scenario
No GHG policy intervention was assumed in BAU over the 37 year horizon.
Service demands were projected assuming GDP growth with compounded annual
growth rate of 5% in 1995-2032, decreasing from 5.7% in 1995-2010 to 4.0% in
2020-2032. Annual discount rate was fixed at of 6%.
BAU scenario assumes SO2 control measures that are already envisaged (forthe near-term implementation) and others that can be anticipated (in the longterm) for a rapidly growing developing economy with low per capita present
income. Mitigating SO2 pollution in urban India is a domestic concern that has
recently attracted attention of policy makers. Electricity generation, Iron & Steelindustry, Road transport, and Biomass combustion comprised over 65% of India’s
SO2 emissions in 1995 (Garg and Shukla 2002). Recent steps taken by policy
makers include regulation targeted at reducing sulfur content of diesel in large
cities accompanied with an elaborate vehicle inspection and certification system.
Such measures have already led to a reduction of SO2 concentration in traffic

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intersection areas in Delhi by over 50% from 1995 to 2000 (Sengupta 2001).
Additionally, regulations for adoption of pollution removal technologies like coal
washing and flue gas desulfurization in thermal power plants have beenreasonably successful. In BAU, we assumed continuation of these trends.
7.3.2 Policy scenarios
Carbon tax scenarios
Carbon tax is one of the instruments for mitigating global CO2 emissions that is
widely discussed in international forums on climate change. Main economic
advantage of emissions tax is that it limits the cost of reduction programme byallowing emission to rise if costs are unexpectedly high (IPCC 2001). Since wewanted to study the linkage between SO2 mitigation and CO2 mitigation objectives
using AIM/Enduse, we first chose three levels of carbon tax and then set
corresponding SO2 mitigation targets for defining SO2 constraint scenarios.
AIM/Enduse permits application of sectorwise and energywise application of tax
or constraints on each gaseous emission. In each scenario, a constant level ofcarbon tax was applied from 2010 onwards (no tax was applied before 2010).
These levels are based on the likely ranges of tax indicated by results for 550
ppmv carbon mitigation target through 2100 from AIM/CGE global model (seeChapters 4 and 10 of this book). However, it must be noted that at this stage thesetax levels are for illustrating the methodology. Following tax scenarios wereassumed.
• C-Tax (US$50/t-C): Constant tax of US$ 50/t-C from 2010 onwards• C-Tax (US$100/t-C): Constant tax of US$ 100/t-C from 2010 onwards• C-Tax (US$200/t-C): Constant tax of US$ 200/t-C from 2010 onwards
SO2 constraint scenarios
To analyze the co-benefits, we constructed three SO2 constraint scenarios having
SO2 limitation equivalent to the SO2 emissions trajectory for each of the threecarbon tax scenarios. Table 2 shows the SO2 emissions constraints for the three
scenarios. The scenarios, named SO2 Constraint1, SO2 Constraint2, and SO2
Constraint3, correspond to SO2 emissions in C-Tax (US$50/t-C), C-Tax(US$100/t-C), and C-Tax (US$200/t-C) scenarios respectively.
The effect of a SO2 constraint is different from the effect of a carbon tax even if
the level of SO2 emissions is the same in the two scenarios. While a carbon tax
increases the price of an energy-kind in proportion to its carbon content, a SO2
constraint imposes a hard limit on the total quantity of SO2 emissions in a year.
While the former is an example of a market-based intervention, the latter is that ofa command-and-control regulation. Imposing an upper limit on SO2 emission
quantity will induce different players to chose technologies and fuels that are lesse
sulfur intensive, independent of their carbon emission performance.

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Table 2. SO2 constraint scenarios
Scenario
1995
2005
2010
2020
2032
4.93
5.44
5.87
6.06
4.74
SO2 Constraint1
4.93
5.44
5.87
4.61
3.08
SO2 Constraint2
4.93
5.44
5.79
3.98
2.30
SO2 Constraint3
Note: Units are in Million ton SO2; These figures denote the upper bounds on quantity ofSO2 emission; Data between specified years are linearly interpolated.

7.4 Results and Analysis
Discussion of BAU scenario for India has been covered under ‘reference scenario’in Chapter 6 of this book. We will confine our discussion to analysis of policy
scenarios. Since the results are from the initial stage of our study, our discussion inthis section is meant to illustrate the richness of analyses that is possible with
AIM/Enduse model, rather than provide specific numbers for policy
recommendation.
Figures 1 and 2 show the CO2 and SO2 emissions in BAU and carbon tax
scenarios. In comparison to BAU, CO2 emissions in 2032 under carbon tax
scenarios of US$ 50, US$ 100, and US$ 200 decline by 9%, 28%, and 35%
respectively. Marginal reduction in CO2 decreases with increasing carbon tax,
indicating a corresponding increase in the marginal cost of carbon reduction.
Carbon taxes aimed at reducing CO2 also induce significant SO2 reduction.
Explanation for this close association can be found in primary energy substitution
as shown in Fig. 3. Under carbon tax scenario of US$ 200, coal reduces by 286
Million tons oil equivalent (Mtoe), whereas natural gas increases by 91 Mtoe andrenewables and nuclear energy (excluding biomass) increase by 32 Mtoe, in 2032,
as compared to BAU. Most of the energy substitution occurs in electricity
generation (higher penetration of natural gas and renewables), iron & steel
production (higher penetration of electric arc furnace and direct reduction
process), pulp & paper production (higher penetration of waste paper based
process), sugar industry (greater use of cogeneration), and residential sector(greater use of fluorescent lamps). There is little change in supply of crude oil due
to little switch in road transport sector.
Additionally, there is an increase in efficiency of technologies in various
sectors leading to a decline in total primary energy supply during the period 19952032 from 29.0 Btoe in BAU to 27.6 Btoe in carbon tax US$ 200 scenario.
Substitution of coal primarily by natural gas and renewables, and increase inefficiency, result in a close association between reductions in CO2 and SO2. Thisphenomenon is also observed in case of other carbon tax scenarios.

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800
700
600

BAU

M t-C

500

C -Ta x (U S $5 0 /t-C )400

C -Ta x (U S $1 0 0 /t-C )300

C -Ta x (U S $2 0 0 /t-C )

200
100
0
2000

2004

2008

2012

2016

2020

2024

2028

2032

Y ear

Fig. 1. CO2 emissions in BAU and carbon tax scenarios
7
6

M t-S O2
Mt-SO
2

5

BAU

4

C -Ta x (U S $5 0 /t-C )3

C -Ta x (U S $1 0 0 /t-C )C -Ta x (U S $2 0 0 /t-C )210
2 0 002 0 042 0 082 0 122 0 162 0 202 0 242 0 282 0 32Y ear

Fig. 2. SO2 emissions in BAU and carbon tax scenarios
450

M to e
Mtoe

400
350

B A U - Coal

300

C - Ta x ( U S $ 2 0 0 /t-C ) - C o a l

250

B A U - Gas

200

C - Ta x ( U S $ 2 0 0 /t-C ) - G a s

150

B A U - R&N

100

C - Ta x ( U S $ 2 0 0 /t-C ) - R & N

50
0
2000

2004

2008

2012

2016

2020

2024

2028

2032

Y ear

Fig. 3. Primary energy supply in BAU and carbon tax scenarios
Note: Coal includes coal and lignite; Gas includes natural gas; R&N includes renewables
and nuclear energy excluding biomass.

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700

M
illio n To n C a rb o n
Mt-C

600
C -Ta x (U S $5 0 /t-C )500

S O22 -C o ns tra int1
400

C -Ta x (U S $1 0 0 /t-C )300

S O22 -C o ns tra int2

200

C -Ta x (U S $2 0 0 /t-C )S O22 -C o ns tra int3

1000
2 0 002 0 042 0 082 0 122 0 162 0 202 0 242 0 282 0 32Y ear

Fig. 4. Comparison of CO2 emissions in carbon tax and SO2 constraint scenarios
160
140

U S $ / t-C re duc tio n

120
100
80
60
40
20
0
U S $5 0

U S $1 0 0

U S $2 0 0

Ca rbo n ta x s c e na rio

Fig. 5. Average undiscounted system cost over 2000-2032 period of CO2 reduction under
different levels of carbon tax
Note: The cost includes only initial investment cost in plant and machinery and energy
costs; it does not include cost of land and building, wages and overhead costs, cost ofcarbon tax, and cost of implementing regulatory measures.

Figure 4 shows CO2 emissions under carbon tax and corresponding SO2
constraint scenarios. Figure 5 compares the average cost of CO2 reduction over
2000-2032 under carbon tax scenarios. These figures are based on initial results,
and in future they may change as we intend to consider more sulfur removal
options especially in small and medium industries, and effect of on-going reforms
in the power sector. Nevertheless, with the existing results, we can make thefollowing observations.

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• For the same trajectory of SO2 reduction under both policies, carbon emissions
are lower under carbon mitigation policy as compare to sulfur mitigation
policy.
• Overall, a domestic regulation for reducing SO2 emissions beyond the BAU is
likely to result in some reduction in CO2 emissions as well. This is because themajority of options exclusively for SO2 removal available in power sector,
transport sector, and large industries, have been selected in BAU itself.
Marginal cost of SO2 mitigation over BAU through such exclusive options ishigher than the marginal cost of its mitigation through fuel switch options. This
could be because of two reasons: (i) we have not considered SO2 removal
options in small and medium industries, and (ii) further advanced technologies
for SO2 removal in power sector and large industry boilers are expensive. We
would expect more decoupling between CO2 and SO2 emissions if small andmedium industrial processes are modeled and heavy subsidies are given to theadvanced sulfur removal technologies.
• Average undiscounted cost of CO2 reduction increases with the level of carbon
tax (from US$ 99/t-C for US$ 50 tax to US$ 140/t-C for US$ 200 tax). This isdue to increasing marginal cost of mitigation resulting from higher investment
cost of renewable energy technologies and higher cost of supplying natural gas
and other cleaner fuels.

7.5 Concluding Remarks
Using a simple methodology for analyzing co-benefits using AIM/Enduse model,
our initial study demonstrates that under application of carbon tax, there is astrong overlap between most economic options for SO2 mitigation and CO2
mitigation. This is mainly because energy substitution from coal to natural gas andrenewables offers an economic way of sharing costs to achieve both CO2 and SO2
mitigation. Even without any carbon tax some gas based technologies are proving
to be economically viable (compared to coal based technologies) in electricity
generation and a few other industries worldwide (Pandey 2002).
Although under a CO2 mitigation policy regime, extents of SO2 mitigation andCO2 mitigation are strongly correlated, the two trajectories get decoupled under a
SO2 mitigation policy regime. It is difficult to comment on the extent of thisdecoupling because we have not considered several SO2 removal options in small
and medium industries in India.
These results have implication for sequencing of mitigation options over a longterm planning period. Facilitating rapid penetration of conventional sulfur removal
technologies for coal washing, limestone injection, and flue gas desulfurization, is
an immediate domestic policy imperative (as is assumed under BAU),
independent of GHG mitigation objective. However, for GHG mitigation policy,
preparing institutions and infrastructure for facilitating medium-term penetrationof natural gas is a robust GHG mitigation option. Although this strategy is7. Co-benefits of CO2 and SO2 Mitigation Policies in India

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economically desirable under GHG mitigation commitment, it will help inachieving medium-term reduction of both CO2 and SO2 emissions.
While the SO2 limitations do generate co-benefits of carbon mitigation, theresidual reduction of carbon vis-à-vis BAU would be relatively less significant
compared to reduction of SO2 under carbon control policies. The co-benefits arethus likely to be asymmetric, i.e. carbon limitation has much greater residual
impact on SO2 trajectory whereas SO2 limitation has milder residual effect on
carbon trajectory. The GHG mitigation policies for India therefore may have to be
crafted for its own sake, in accordance with the global GHG mitigation dynamics.

Since our analysis in based on initial stage of the study, a few
words of caution deserve mention here. Firstly, potential for exclusive SO2
removal in India is far more than what we have considered in this study, especiallyin small and medium industries. We intend to enrich our technological databasefor these industries in future. This potential may lend economic credibility tostrong decoupling of SO2 and CO2 mitigation objectives for a long period of time.
Secondly, we have not studied the effect of rapid changes going on in thepolicy regime, markets, and technological progress in the electricity industry.
These are global trends and most countries including India have initiated power
sector reforms, guided mainly by the reforms model of some of the more advanced
countries like the UK. Several experts predict that changes in the structure andtechnologies in electricity industry worldwide will tilt the economic balance
decisively in favor of smaller scale generation technologies like those based onnatural gas (Pandey 2002; Patterson 1999). These trends, independent of GHG
mitigation commitments, may lend economic credibility to substitution away fromcoal in the Indian power sector.
Since AIM/Enduse permits exhaustively detailed modeling of technologicalsystems and their emission characteristics, it is an effective vehicle to analyze cobenefit policies. In the next stage, we intend to include small and medium
industrial processes too in our study.
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