Download - 1 - Transitioning to a low carbon transport system in developing

Transitioning to a low carbon transport system in developing nations: Future
Scenarios for India
Prasoon Agarwal, Mr.
Indian Institute of Management Ahmedabad, India
D1506, IIM Campus, Ahmedabad 380015, India
+91-9904203424, [email protected]
Abstract
Economic development and the rapidly increasing demand for mobility in developing countries
are leading to increased demand for transport services. The sector is an important driver for
determining future energy needs and emissions, being responsible for about 10% of total final
energy demand and 8 % of CO2 emissions in India currently (IEA, 2007). However, the current
trends seek caution with regard to environmental implications, so as to avoid locking into a carbon
intensive future transport system. This paper assesses two paradigms for transiting to a low carbon
transport system in India, using Asia-Pacific Integrated Model Energy Snapshot tool (ESS) to
model energy demand for India between 2000 and 2050. Future energy demand and GHG
emissions are estimated under the two scenarios, and the total reduction potential from the
transport sector as compared to the ‘Business as usual’ case has been presented. The model output
presents the energy and environment benefits that can occur from such initiatives, under the Kaya
Identity framework, for a detailed policy analysis. Also, to demonstrate the long term emission
benefits of such low carbon initiatives, a project level case study of the Dedicated Freight Corridor
between Delhi and Mumbai has been taken.
Key Words: Climate Change, Sustainability, Transport
1. Introduction
Economic development and the rapidly increasing demand for mobility in developing countries
are leading to increased demand for transport services, so as to support lifestyles and economic
activities in developing countries like India. The transport sector is responsible for about 10% of
total final energy demand in India, and is projected to increase at a rate of 6.1 % over the outlook
period (2005-2030), to reach 20% in 2030, under the business as usual scenario (IEA, 2007). The
sector is an important driver for determining future energy needs, especially dominating the
growing demand for oil in India, with majority of the vehicles being diesel driven. Also, the
transport sector has serious implications on emissions and energy security, being responsible for 8
% of India’s CO2 emissions currently (IEA, 2007). This is projected to increase to 13 % on 2030
under the business as usual scenario. Thus there is a need to check this trend and address these
issues in the medium to long term, so as to avoid locking into a carbon intensive transport systems
in India. Unlike the developed nations, currently there are no mandatory vehicle fuel efficiency
norms in India. Engines of higher efficiency need to be developed and used for lowering demand
for transportation fuel. Besides, there is a need to shift to vehicles that run on alternate fuels.
Already battery operated two wheelers and cars have started plying on Indian roads. However,
with improvement in battery technology, which has tremendous potential and can drastically
improve the performance of vehicles, the share of battery operated vehicles is bound to grow.
Similarly, solar power operated cars have also forayed in the market. Currently their share is very
low, but with advancement in technology, they can capture a higher share. The government is also
analyzing possibilities for blending ethanol with petrol and bio-diesel with diesel. With increasing
percentage of blend, as envisaged for the future, the emissions from transportation sector would be
increasingly lower. As a characteristic unique to the Indian transport system, in the absence of
well designed public transport facilities, two wheelers form a major portion of the vehicle stock,
so as to facilitate mobility in cities. This trend is supposed to change, with a shift to cars, as the
society becomes more economically affluent. The number of vehicles on road is projected to rise
rapidly, and match the United States by 2025. Thus there is a need to check this trend and address
these issues in the medium to long term. This research conceptualizes transitioning the transport
system in India to a low carbon pathway, by a number of policy actions aimed at passenger and
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freight transport sector. Some of them could be - improvement of vehicle efficiency, and increased
penetration of electric vehicles, hybrid vehicles, bioethanol and biodiesel, investments in alternate
transport modes, shift of transport choice from private to public like trains for long distance travel;
BRTS, City buses, light rail, metro and car-pooling for local and short distance commutation. It is
envisaged that electric and hybrid vehicle will form a significant share of the vehicle stock,
especially for short distance inter and intra city commutation. ICT and Intelligent transport
systems will be used for effective traffic management, so as to reduce congestion and unnecessary
fuel wastage. For freight transport sector, an impetus will be given to development of better
logistical linkages through infrastructure investments in dedicated freight corridors, so as to cause
a shift from lesser efficient road transport to rail freight transportation system.
Low Carbon Society (LCS) scenarios envisage reduction in global greenhouse gas emissions to
50% by 2050 compared to the 2005, while meeting energy service demands through proposing
combinations of technological and social innovations based on favorable socio-economic future
visions (Strachan et. al., 2008). In this paper we use a modeling framework to realize a Low
Carbon Society through two alternative pathways. The first pathway uses a pure carbon policy
instrument in the form of a carbon tax whereas in the second we combine sustainable polices with
a carbon tax. These two alternative development pathways for India were conceptualized by
Shukla et al. (2008) and follow different paradigms – one following the conventional paradigm to
reduce emissions through a carbon price regime and the other focusing on emission stabilization
with sustainable development by aligning climate actions with development responses to
numerous development challenges typical in a developing economy. The current paper presents a
detailed analysis of major environment benefits arising out of such a transition under the two
scenarios. Besides, to demonstrate the long term emission benefits of such low carbon transitions
in the transport sector, a project level case study of the Dedicated Freight Corridor between Delhi
and Mumbai has been taken.
2. Methodology and model framework
The current paper uses the integrated framework proposed by Shukla et. al. (2008). The
framework falls under the earlier AIM family of models (Kainuma et. al., 2003; Shukla et. al.,
2004), with the inclusion of a new model AIM SNAPSHOT, which has a simple graphic interface.
The framework (Figure 1) proposed by Shukla et. al. (2008) uses the modelling resources
developed over the last few years by the AIM team with a widely used energy system model
ANSWER-MARKAL (Fishbone & Abilock, 1981) and finally combining it with the SNAPSHOT
Model.
Figure 1.
Integrated Soft-linked Model Framework
DATABASES:
Socio-Economic, Technologies, Energy Resources, Environmental Constraints
ANSWER-MARKAL
Model
AIM SNAPSHOT Model
AIM Strategic
Database
End Use Demand
Model
AIM CGE Model
(Shukla et. al., 2008)
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Shukla et. al. (2008) have used the top down model, AIM CGE for estimating the GDP under
different scenarios and these are used as an exogenous input to the bottom up ANSWER
MARKAL model. The ANSWER MARKAL model provides detailed technology and sector level
energy and emission projections, which along with other drivers, are in turn inputted to the AIM
SNAPSHOT model for a detailed sectoral energy, emission and factor analysis. The Energy
SnapShot is a spreadsheet tool designed to calculate the energy balance table and CO2 emission
table with inputs such as service demands, share of energy and energy improvements by
classifications of service and energy in the base and target year (NIES, 2006). The tool can be
used for i) developing and designing preliminary scenarios ii) doing “what if” analysis iii)
checking the consistency among the sectors iv) analyzing the impacts of countermeasures and v)
communicating with stakeholders. Models require diverse databases such as economic growth,
global and regional energy resource availability, sectoral and temporal end use production
processes and technologies, emission types and much more. AIM database plays a critical role to
ensure data consistency across the models (Hibino et. al., 2003; Shukla et. al., 2004, Chapter 7).
3. Scenario Description
Three scenarios have been articulated to describe the future strategies relating to the development
of India’s road transport sector. The first scenario is the ‘Business as Usual’ scenario, used as a
baseline reference scenario, in which the impacts of current policy initiatives on the long-term
trends of road transport energy demand are assessed. Thus, this scenario assumes the future
development of transport sector in India along the conventional path, which essentially means a
carbon intensive transport system for India similar to the pathway followed by the present
developed countries. The assumptions about the key drivers are similar to the base case in Shukla
et. al. (2008).
Besides, two alternative scenarios for ‘Low Carbon Transport’ are considered as more optimal
cases, and are modeled for the period until 2050. The scenarios use the articulation by Shukla et.
al. (2008), with a carbon tax (CT) scenario of a pure carbon policy instrument in the form of a
carbon tax, and a sustainability society (SS) scenario which combines sustainable polices with a
carbon tax. The CT scenario assumes greater improvements in the energy intensity and higher
target for the share of commercial renewable energy compared to the Base Case scenario. Also, a
stringent carbon permit price trajectory is presumed in this scenario, as compared to milder carbon
regime assumed under the base case. Besides this, the underlying structure of this scenario is
identical to the Base Case (Shukla et. al., 2008). However, a series of best available reduction
technologies and practices, measures such as increased focus on public transport, fuel economy
regulation, promoting gas and electric vehicles, biofuel promotion, technological interventions and
modifications in urban architecture are assumed to be implemented. On the other hand, the SS
scenario follows a distinct ‘sustainability’ rationale, like that of the IPCC SRES B1 global
scenario (IPCC, 2000). The scenario represents a very different approach to development as
compared to the Base Case, with a long-term perspective aiming to decouple the economic growth
from highly resource intensive and environmentally unsustainable path. The ‘sustainability’
scenario cannot be constructed by incremental changes in the Base Case, because it requires many
upfront decisions to be taken. The scenario rationale rests on aligning the economic development
policies, measures and actions to gain multiple co-benefits, especially in developing countries
where major decisions are yet to be taken. The scenario assumes the society to pro-actively
transition the transport system in India to a low carbon pathway, many behavioral changes like
shifting transport choice from private to public like trains for long distance travel; BRTS, City
buses, light rail, metro and car-pooling for local and short distance commutation.
4. Model Results
As against the energy accounting framework used by different international agencies like IEA, the
results presented in this paper use a different approach. This approach avoids many fallouts
because in the other approach, contribution of renewable like hydro, wind and solar to primary
energy is only equivalent to the electricity generated, whereas the contributions of others like
fossil fuels and biomass it is in terms of the calorific value of the fuel. This depresses the share of
hydro, wind and solar in primary energy mix and thus creates a distorted picture of the final
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energy system. Besides, the alternative approach used by IEA also provides undue advantage to
biomass over other renewable in case of renewable energy targets (Larsen et. al., 2007).
4.1 Overall energy and emission projections (Base and LCS Scenarios)
As per Shukla et. al. (2008), the demand for energy in India increases 5.8 times to 3016 Mtoe in
2050, whereas it was only 520 Mtoe in 2005. In the same duration, GDP increases by 23.6 times,
and thus as a result of changes in the structure of economy and efficiency improvements, a
decoupling of GDP and Energy takes place (Figure 2). The base case emissions for India are
projected to be 6.6 Billion
Figure 2.
Energy and Carbon Intensities for Base Scenario
Energy & Carbon Intensity (2000 = 100)
110
100
8000
90
6000
80
4000
70
2000
60
0
CO2 Emissions (Mt CO2)
2000 2010 2020 2030 2040 2050
50
40
30
Energy Intensity
20
CO2 Intensity
10
0
2000
2050
Source: Shukla et al. (2008)
tCO2 in 2050 (Shukla et. al., 2008), thus the carbon intensities are also reduced substantially
(Figure 2) due to an increase in the share of nuclear and gas in the overall energy mix. The fuel
mix in the base case remains highly dominant on coal, but the share of natural gas, other
renewable, nuclear and commercial biomass increases significantly by 2050(Figure 3).
Figure 3.
2010
2020
2030
2040
Fuel Mix in Base Case Scenario
3,500
Other Renewables
Nuclear
Hydro
Gas
Oil
Coal
Commercial Biomass
Non Com Biomass
3,000
Mtoe
2,500
2,000
1,500
1,000
500
0
2005
2015
2025
2035
2045
Source: Shukla et al. (2008)
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While conceptualizing a Carbon Tax (CT) Scenario, Shukla et. al. (2008) assume a carbon tax
trajectory which increases to US $ 100 per tCO2. The base case scenario is corresponding to 650
ppmv CO2e stabilization whereas the CT scenario is corresponding to 550 ppmv CO2e
stabilization. The carbon tax assumed lead to subsequent GDP losses, which were used to
recalculate the end use demands for the carbon tax scenario. The cumulative CO2 mitigation for
the period 2005-2050 comes out to be substantial, with major reduction in emissions from the
electricity sector, due to fuel switching initially, and CCS along with Coal fired electricity
generation, CCS in steel and cement making later. The remaining mitigation happens due to
higher adoption of renewable especially biomass, and improvements in device efficiencies like
better vehicle efficiency norms.
While conceptualizing a Sustainable Society (SS) scenario, based on the precautionary principle
(Rao, 2000) paradigm, we assume that anthropogenic influences as the root cause of GHG
emissions, and hence the policy actions are based on reducing these influences in in all walks of
life (Shukla et. al., 2008). However the reduction of anthropogenic influences is not at the expense
of economic and social development, but it believes in expanding the economic and climate
frontier (Shukla, 2005), by innovations in technology, institutions, targeted technology, focusing
on inputs (& not only outputs) and long-term perspective to avoid lock-ins. The sustainable
society can come up through a number of policies, which eventually bring down the intermediate
demand for products, while assuming a GDP equivalent to the base case. The demand projections
are done using sector specific drivers, which are changed keeping in mind the sustainable society
storylines. For example improvements in transport sector planning will lead to an overall
reduction in the demand for steel, as can be understood in Table 1.
Table 1.
Sector
Transport
Impact of Sustainable transport on steel and cement demand
Driver
Impact on steel demand
• Better Urban Planning
Less automobile per unit of transport service
• Public Transport
delivered
• Substitution
Thus the demand for steel would reduce as a result of such sustainable transport policies, and this
would lower the final demand of energy from steel sector.
The approach for analysis introduces different set of actions under different scenarios, for
lowering the use of energy across sectors in the economy. As can be seen from Figure 4, there is a
substantial reduction in primary energy consumption, as compared to the CT scenario.
Figure 4.
Primary Energy Consumption
-
500
1,000
1,500
2,000
2,500
3,000
2000
2050 CT Case (CM)
2050 SS Case (CM)
COL
OIL
GAS
BMS
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NUC
HYD
REN
However, this reduction in overall energy consumption is achieved through a set of measures
across sectors. There is a reduction in demand from industrial sector as demand for steel, cement
and other energy intensives commodities goes down due to recycling, reuse, material substitutions,
improvement of device efficiencies and fuel substitutions. The demand of energy from agriculture
is lower due to reduced consumption on account of improved agricultural practices related to
irrigation and cropping patterns. Electricity demand which is a derived demand is also lower.
Similarly, the transport sector also demonstrates a reduction in demand, due to the use of energy
efficient vehicles and a greater modal shift in favor of public The impact of these different set of
policy actions can be better understood in Figure 5 and 6 below, which demonstrate how the share
of different energy carries changes in the overall numbers of primary energy demand and related
emissions in the economy.
Figure 5.
Primary Energy Consumption ( % shares)
0%
20%
40%
60%
80%
100%
BMS
NUC
HYD
REN
60%
80%
100%
2000
2050 CT Case (CM)
2050 SS Case (CM)
COL
Figure 6.
OIL
GAS
CO2 emissions by fuel ( % shares)
0%
20%
40%
2000
2050 CT Case (CM)
2050 SS Case (CM)
COL
OIL
GAS
For example, there is an increasing reliance on renewable sources like hydro, wind and solar.
Besides, cleaner fuels like natural gas and nuclear also find an increased use. In spite of an
increase in the share of coal in overall energy mix , there is a reduction in overall emissions under
the SS scenario, because technological options like CCS have been assumed to take up a greater
role.
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4.2 Projections for transport sector (Base and LCS Scenarios)
The approach for analysis introduces different set of actions under different scenarios, for
lowering the use of energy across sectors in the economy. Thus, although transport sector accounts
for a large share of mitigation in both the scenarios, there are different set of policy actions that are
causing this mitigation. For the carbon tax scenario, the mitigation is achieved through climate
centric actions like increased vehicle efficiency, penetration of electric and hybrid vehicles, and
impetus on biofuels, like biodiesel and bioethanol. Whereas, under the sustainability scenario, the
mitigation is achieved through sustainable policies, such as adaptation for non-motorized transport
( bicycles, pedestrian pathways), better public transport to substitute private vehicles, investments
in alternate transport modes like BRTS, City buses, local train, metro, monorail, etc, and use of
ICT/Intelligent systems for effective traffic management. It can be seen clearly from Figure 7 and
8 below that SS scenario accounts for a larger reduction in overall energy consumption and
corresponding emissions, in passenger transport sector.
Figure 7.
CO2 emission in passenger transportation sector (MtC)
-50
-
50
100
150
200
2000
2050 CT Case (CM)
2050 SS Case (CM)
COL
Figure 8.
OIL
GAS
BMS
REN
Heat
H2
ELE
Energy consumption in passenger transportation sector ( Mtoe)
-
100
200
300
400
500
2000
2050 CT Case (CM)
2050 SS Case (CM)
COL
OIL
GAS
BMS
REN
Heat
H2
ELE
As far as the freight transport sector is concerned, although there is a slight reduction in the CO2
emissions from freight transportation in the SS scenario (Figure 9), there is a notable increase in
the overall energy consumption (Figure 10). This increase can be explained on account of a higher
overall good movement, for better recycling and reuse in the economy. This increase in the energy
consumption is more than compensated by the reduced energy demand from the industrial sector
on account of reduced demand for new production.
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Figure 9.
CO2 emission in freight transportation sector ( MtC)
-10
-
10
20
30
40
50
2000
2050 CT Case (CM)
2050 SS Case (CM)
COL
Figure 10.
OIL
GAS
BMS
REN
Heat
H2
ELE
Energy consumption in freight transportation sector (Mtoe)
-
20
40
60
80
100
2000
2050 CT Case (CM)
2050 SS Case (CM)
COL
OIL
GAS
BMS
REN
Heat
H2
ELE
4.3 Analysis of De-carbonization
To analyze the decoupling between energy and emissions, the two pathways for achieving low
carbon society are represented in terms of consumptions of final and intermediate goods and
services. This we do using the “Extended Kaya Identity” (NIES, 2006). The change in CO2
emissions from a base year can be understood using the following identity
D
E
C’
C
Change in CO2 = Demand effect (D)
+ Energy intensity effect (E/D)
+ Carbon intensity effect (C/E)
+Measures effect (C’/C)
: Driving forces (service demand of final and intermediate consumption)
: Energy Consumption
: CO2 emission without measures in energy transformation sector
: CO2 emission with measures in transformation sector
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Thus, it can be seen from Figure 11 below that there is a substantial reduction on account of
reduction in overall service demand under the SS scenario, which is achieved through lower
demand in intermediate sectors like transport. The energy intensities (Figure 11) with respect to
demand are fairly similar in the two scenarios and contrary to expectations a sustainable society is
more carbon intensive. The overall level of emissions in SS scenario (Figure 12) is also higher,
since the key priority of the scenario is on development with the co-benefits of climate change.
Total
C'/C
C/E
E/D
Kaya Analysis of LCS Scenarios: Total Demand
D
Figure 11.
800%
628%
600%
468%
vs 2000's
400%
200%
71%
137%
107%
15%
0%
-200%
-152%
-162%
-400%
-346%
-523%
-600%
2050 CT Case
Figure 12.
2050 SS Case
CO2 emissions by fuel : Total Demand
-
100
200
300
400
500
600
700
800
2000
2050 CT Case
(CM)
2050 SS Case
(CM)
COL
OIL
GAS
Specifically for the passenger transport sector (Figure 13), it can be seen that there is a substantial
reduction in overall demand of transport services under the SS scenario (the transport service
demand growth is 1527% in the CT scenario, as against only 890%in the SS scenario). Thus,
although the SS scenario is more carbon and energy intensive (E/D, C/C, and C’/C ratios are better
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for CT scenario), this reduction in overall energy demand (D) compensates for this, leading to an
overall reduction in the emissions from transport sector under the sustainable society scenario.
Total
C'/C
C/E
E/D
Kaya Analysis of LCS Scenarios: Passenger Transport Sector
D
Figure 13.
2000%
vs 2000's
1500%
1527%
890%
1000%
545%
381%
500%
0%
-19%
-171%
-306%
-500%
2050 CT Case
-304%
-319%
-373%
2050 SS Case
As far as the freight transport sector is concerned, although there is a slight reduction in the CO2
emissions (viz-a-viz BAU) from freight transportation in the SS scenario as against CT scenario
(Figure 14), there is a slight increase in overall emissions. As discussed earlier, this increase can
be explained on account of an increased demand for freight transport (D) in SS Scenario, due to
higher overall good movement for better recycling and reuse in the economy. This increase in the
energy consumption and emissions is supposed to be more than compensated by the reduced
energy demand and emissions from the industrial sector on account of reduced demand for new
production.
600%
500%
Total
C'/C
C/E
E/D
Kaya Analysis of LCS Scenarios: Freight Transport Sector
D
Figure 14.
536%
492%
400%
304%
280%
vs 2000's
300%
200%
100%
10%
4%
0%
-100%
-34%
-22%
-156%
-200%
-246%
-300%
2050 CT Case
2050 SS Case
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5. Low carbon transitions: A case study on freight transport
To demonstrate the long term emission benefits of such low carbon transitions in particular
transport sector, a project level case study of the Dedicated Freight Corridor between Delhi and
Mumbai has been taken. The freight transport in India is shared between rail and road, with only a
minor movement by air. In the last few decades, the share of rail in total freight has declined
considerably viz a viz road, from above 80% in 1960s to around 35% currently. Although the
absolute numbers have increased for both, but rail freight suffered a setback as against road. It was
only in last few years that rail freight has seen a reversal in decrease due to innumerous initiatives
by The Ministry of Railways, thereby resulting in the improvement of market share and
operational margins. The Indian Railways’ quadrilateral linking the four metropolitan cities of
Delhi, Mumbai, Chennai and Howrah, commonly known as the Golden Quadrilateral; and its two
diagonals (Delhi-Chennai and Mumbai-Howrah), adding up to a total route length of 10,122 km
carries more than 55% of revenue earning freight traffic of IR. The existing trunk routes of
Howrah-Delhi on the Eastern Corridor and Mumbai-Delhi on the Western Corridor are highly
saturated, line capacity utilization varying between 115% to 150%, with projections for a further
increase in next few decades. It was for this reason that the idea of a Dedicated Freight Corridor
was conceptualized, which is a multi-modal high axle load corridor between Delhi and Mumbai,
planned to cover an overall length of 1483km.
Railways, especially such dedicated corridors, have always been an economical option of freight
movement as compared to road. However, apart from the obvious economical benefits of freight
transport through rail, there are implicit co-benefits of reduced emissions. Railways can carry a
higher tonnage of freight load for the same amount of fuel used, causing a decoupling of green
house gas emissions per unit of transport services rendered. This decoupling between emissions
and freight movement will be even stronger for such corridors, since they are designed for higher
speed, higher capacity and axle load , and longer trains . Thus, whereas a typical truck used for
freight transportation in India can carry a payload capacity of 10 tonnes, a train moving on the
DFC will have a payload capacity of 12000 tonnes. Hence, every train on the DFC will be
replacing 1200 such tracks for the movement. As per our analysis, this will cause a significant
reduction in the emissions since for a tonne of freight movement by road, the CO2 equivalent
emissions are 16 times more than that of freight train on DFC. Under the current CDM
architecture, a journey of the freight train between Mumbai and Delhi will lead to a saving of
around US$ 75,000 per trip from emission reduction alone, as compared to the same movement by
road1.
As per DMIC2 concept note, the rail share of container traffic on this corridor is slated to increase
from 0.69 million TEUs in 2005-06 to 6.2 million TEUs in 2021-22. The other commodities are
projected to increase from 23 million tonnes in 2005-06 to 40 million tonnes in 2021-22. Using
these projections from DMIC and the business as usual growth rates for rail and road freight, the
freight movement on rail and road can be summarized that for the period 2005-2006 to 2021-2022,
2005-06
Total Rail Freight in India
Rail freight on the Mumbai-Delhi corridor
Road freight
667
37
106
2021-22
BAU
50-50
2565
163
407
2565
285
285
(all figures in million tonnes)
BAU: Business as usual modal share
50-50: 50% movement by road and rail each in future
1
2
assuming CER price of € 10/CER, and an exchange rate of 1 USD = Rs. 52.50
Downloaded from http://dipp.nic.in/japan/japan_cell/Concept_Paper_Summary_020807.pdf
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Thus, this incremental shift over and above the business as usual baseline, if eligible for carbon
credits under the CDM architecture, will lead to earning of CERs, which can be sold in the global
carbon markets.
6. Conclusion
Infrastructure is the backbone of any economy, more so for developing economies aspiring to
attain higher rates of growth. Since infrastructure like transport is a long life asset, the
development pathway taken by a country might create an irreversible lock-in into certain style of
sectoral architecture, with associated path dependencies. Sectoral infrastructure choices made by
an economy have a long term bearing on the energy and emission profile of the nation. Hence, it
becomes crucial to make upfront policy choices for different infrastructural sectors like energy
supply, transport, urban, etc, to avoid locking in a carbon intensive future like many developed
nations. Thus, we need to alter the development pathway, so as to achieve the co benefits for
addressing climate change issue along with the developmental concerns (GoI, 2008d). The paper
analyzed two such pathways for transition to a ‘low carbon transport’ in India. The first, which
follows conventional development paradigm, treats the carbon mitigation as an issue to be treated
at the margin of development decisions through carbon centric market efficient instruments like
carbon tax or permits to decouple the carbon emissions from the economy (Shukla et. al. 2008).
The alternate paradigm considers low carbon transition as an issue embedded within the larger
development issue of transition to a ‘sustainable society’. It is clear from the results that both
pathways focus on set of policy actions having individual advantages, in terms of achieving our
development priorities and also mitigating against long term climate change. These scenarios
articulate two different futures, thus providing a conceptual basis of discussion for policy makers
to act upon.
7. Future Scope
Infrastructure like rail are long life assets, and hence vulnerable to long term climate change
impacts. Traditionally impact assessment is carried out within the framework of the impact of
economic activities on the environment, such as demonstrated in this research paper. Another
issue which should be of concern for the project planners is the potential threats posed by climate
change to large infrastructure projects like railway lines and roads. The vulnerability of many such
infrastructure projects against climate change is a issue of concern, and demands extensive
research, both for planning in advance in case of upcoming infrastructure investments and for a
better adaptation plan in case of existing infrastructure, especially in the case of developing
countries like India.
Apart from this, another interesting research issue to explore, from a pure policy perspective, is the
way in which the government of India plans to improve the modal split of freight movement in
favor of railways. Although the principal collaborator for the DMIC project is Japan, but the
country itself has a poor share of railways in overall freight. Rail freight in Japan owns or controls
virtually no tracks, and is excluded from much of the network. And the scenario is similar for most
of the developed nations, with UK also having a substantially lower share of rail in freight
transport. Amongst the EU-25 nations, the modal share of rail transport has steadily been
decreasing viz a viz road. Amongst the developing nations also the share of rail is relatively low,
for example in South Africa, 85% of freight movement is through road. Thus, it can be seen that
rail has lost to road in freight movement across the world, and how India should address this issue
so as to increase the share of rail, will be a crucial policy question to explore.
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8.
References
ABARE (1999), "User Manual: ANSWER MARKAL an Energy Policy Optimisation Tool,
version 3.3.4." Canberra: The Australian Bureau of Agricultural and Resource Economics.
AIM Japan Team (2005), "AIM/CGE [Country] : Data and Program Manual." Tsukuba: National
Institute for Environmental Studies.
Arrow Kenneth, Dasgupta Partha, Goulder, Lawrence, Daily Gretchen, Ehlrich Paul, Heal
Geoffery, Levin Simon, Maler Karl-Goran, Schneider Stephen, Starret David and Walker Brain
(2004), “Are We Consuming Too Much?”, The Journal of Economic Perspectives, 18(3), 147-172
Bates, B.C., Z.W. Kundzewicz, S. Wu and J.P. Palutikof, Eds., 2008: Climate Change and Water.
Technical Paper of the Intergovernmental Panel on Climate Change, IPCC Secretariat, Geneva,
210 pp
Bhattacharya, Sumana, N. H. Ravindranath, P. R. Shukla, N Kalra, A K Gosain, and K K Kumar
(2003), "Tools for Vulnerability Assesment and Adaptation," in Climate Change and India:
Vulnerability Assessment and Adaptation, P. R. Shukla and S. K. Sharma and N. H. Ravindranath
and Amit Garg and Sumana Bhattacharya, Eds. Hyderabad: Universities Press.
Clarke, L E, J A Edmonds, H D Jacoby, H M Pitcher, J M Reilly, and R G Richels (2007),
"Scenario of Greenhouse Gas Emissions and Atmospheric Concentrations," in Synthesis and
Assessment Product 2.1a: United States Climate Change Science Program and Subcommittee on
Global Change Research.
CoI, Census of India (2001), "Census Data 2001: H – Series: Tables on Houses, Household
Amenities
and
Assets,"
Vol.
2007:
http://www.censusindia.gov.in/Census_Data_2001/Census_data_finder/Census_Data_Finder.aspx.
CoI, Census of India (2006), "Population Projections for India and States 2001-2026 : Report of
the Technical Group on Population Projections constituted by the National Commission on
Population." New Delhi: Office of the Registrar General & Census Commissioner, India.
Correlje´, A and van der Linde, C. (2006). “Energy supply security and geopolitics: A European
perspective” Energy Policy, Vol. 34, pp. 532–543.
Co-operative Program for Water and Development (2006). Water and Climate risks: A plea for
climate proofing of water development strategies and measures. World Water Forum
Edmonds, J. and J. Reilly (1983), "A long-term energy-economic model of carbon dioxide release
from fossil fuel use," Energy Economics, April, 74-88.
Edmonds, J A, M A Wise, J J Dooley, S H Kim, S J Smith, P J Runci, L E Clarke, E L Malone,
and G M Stokes (2007), "Global Energy Technology Strategy: Addressing Climate Change," in
Phase 2 Findings from an international public-private sponsored research program: Joint Global
Change Research Institute; Pacific Northwest National Laboratory & Battelle.
European Environment Agency (2007). Climate change and water adaptation issues. EEA
technical report, Netherlands
Fishbone, L G and H Abilock (1981), "MARKAL, A Linear Programming Model for Energy
System Analysis: Technical Description of the BNL Version," International Journal of Energy
Research, 5, 353-75.
Garg, Amit, P.R. Shukla, and Manmohan Kapshe (2006), "The sectoral trends of multigas
emissions inventory of India," Atmospheric Environment, 40 (24), 4608-20.
- 13 -
Garg, Amit (2000), "Technologies, Policies and Measures for Energy and Environment Future,"
Unpublished doctoral dissertation, Indian Institute of Management, Ahmedabad.
GoI, Government of India (2006), "Integrated Energy Policy: Report of the Expert Committee."
New Delhi: Planning Commission, New Delhi.
GoI (2007). Report of the Steering committee on water resources for 11th five year plan (2007-12).
Planning commission, New Delhi
GoI (2008a). Eleventh Five Year Plan 2007-2012. Vol I. Planning Commission, New Delhi
GoI (2008b). Eleventh Five Year Plan 2007-2012. Vol II. Planning Commission, New Delhi
GoI (2008c). Eleventh Five Year Plan 2007-2012. Vol III. Planning Commission, New Delhi
GoI (2008d). National Action Plan on Climate Change. Prime Ministers Council on Climate
Change. New Delhi
Grubler, A, N Nakicenovic, and A Schafer (1993), "Dynamics of Transport and Energy Systems History of Development and a scenario for Future." Laxenburg: International Institute for Applied
Systems, Austria.
Halsnæs, K and Garg, A (2006), "Sustainable Development, Energy and Climate: Exploring
Synergies and Tradeoffs."
Hibino, Go, Yuzuru Matsuoka, and Mikiko Kainuma (2003), "AIM/Common Database: A Tool
for AIM family Linkage," in Climate Policy Assesment: Asia- Pacific Integrated Modeling,
Mikiko Kainuma and Yuzuru Matsuoka and T Morita, Eds. Tokyo: Springer
IEA.(2007). World Energy Outlook 2007. International Energy Agency, Paris.
IIM (2005). Implications of Selected Carbon Stabilization Regimes for the Indian Energy System
(till 2100). A report written for the Environment Ministry project “Long-term Climate Change
Mitigation Policies: Implications of Future UNFCCC Regimes for National Energy and
Environment Policies”
IPCC. (2000). Special Report on Emissions Scenarios (SRES): Inter-governmental Panel on
Climate Change (IPCC), Nebojsa Nakicenovic and Rob Swart (Eds.), Cambridge University
Press, UK
IPCC, 2007: Summary for Policymakers. In: Climate Change 2007: Impacts, Adaptation and
Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change, M.L Parry, O.F. Canziani, J.P. Palutikof, P.J. van
der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 7-22
Kainuma, Mikiko, Yuzuru Matsuoka, and Tsunehuki Morita (2003), "AIM Modeling: Overview
and Major Findings," in Climate Policy Assesment: Asia Pacific Integrated Modeling, Mikiko
Kainuma and Yuzuru Matsuoka and Tsunehuki Morita, Eds. Tokyo: Springer.
Kainuma, Mikiko, Toshihiko Masui, Junichi Fujino, Shuichi Ashina, Yuzuru Matsuoka, Reina
Kwase, Osamu Akashi, Go Hibino, Maho Miyashita, Tomoki Ehara, Rahul Pandey, Manmohan
Kapshe, and Pedro Piris-Cabezas (2006), "Development of Japan Low Carbon Scenarios,"
Ministry of the Environment, Japan.
- 14 -
Kanudia, Amit (1996), "Energy-Environment Policy and Technology Selection: Modelling and
Analysis for India," Unpublished Doctoral Dissertation, Indian Institute of Management,
Ahmedabad.
Larsen, Hans and Leif Sønderberg Petersen (2007), "Future options for energy technologies," in
Risø Energy Report 6. Rosklide: Risø Energy Centre.
Levina, E. (2006). Domestic Policy Frameworks for Adaptation to Climate Change in the Water
sector. IEA
MoWR (2008). Preliminary consolidated report on effect of climate change on water resources.
Government of India, New Delhi
NIES (2006), "Energy Snapshot tool (ESS): Manual." Tsukuba: National Institute of
Environmental Studies.
Sathaye, Jayant, P. R. Shukla, and N. H. Ravindranath (2006), "Climate change, sustainable
development and India: Global and national concerns," Current Science, Vol. 90 (No. 3).
Shukla, P.R., Dhar, S., and Mahapatra, D. 2008. Low Carbon Society Scenarios for India. Climate
Policy, Vol. 8, Supplement 2008
Shukla, P.R., Garg, Amit, Dhar, S., Halsnaes, K. (2007). Balancing Energy, Development and
Climate Priorities in India: Current Trends and Future Projections. UNEP Risoe Centre on Energy,
Climate and Sustainable Development, Roskilde, Denmark. ISBN: 978-87-550-3627-7.
Shukla, P R (2006) India's GHG emission scenarios: Aligning development and stabilization
paths, Current Science, 90, 3.
Shukla, P R (2005), "Aligning Justice and Efficiency in the Global Climate Regime: A
Developing Country Perspective," in Advances in the Economics of Environmental Resources,
Volume 5: Perspectives on Climate Change: Science, Economics, Politics, Ethics, Walter
Sinnott0Armstrong and Richard B. Howarth, Eds. Oxford, UK: Elsevier.
Shukla, P. R., Ashish Rana, Amit Garg, Manmohan Kapshe, and Rajesh Nair (2004), Climate
Policy Assessment for India: Applications of Asia Pacific Integrated Model (AIM). New Delhi:
Universities Press.
Shukla, P. R., Subodh K. Sharma, Amit Garg, Sumana Bhattacharya and N. H. Ravindranath
(2003) Climate Change Vulnerability Assessment and Adaptation: The Context. In P. R. Shukla,
Subodh K. Sharma, N. H. Ravindranath, Amit Garg and Sumana Bhattacharya (eds.), Climate
Change and India: Vulnerability Assessment and Adaptation. Hyderabad: Universities Press.
Strachan, N., Foxon, T., and Fujino, J. Policy Implications from the Low-Carbon Society
Modelling Project. Climate Policy, Vol. 8, Supplement 2008
UNDP (2007). Human development report: Fighting climate change : Human solidarity in a
divided world.
- 15 -