Low carbon economy: Modelling and more
CSEAt the South Asia Media Briefing Workshop
Delhi, August 27-28
Low carbon economy
An economy model with a minimal output of GHG emissions, specifically carbon dioxide
Energy efficiency, low carbon energy supply & terrestrial carbon (forestry and agriculture) –reducing consumption or lifestyle changes not considered
Abatement cost: (cost of new tech – old tech)/(GHG emissions from old – new) -- US$ 100/ Euro 60 per tonne of CO2e avoided
WGIII, AR4, IPCC, 2007
How much emission reductions can be done by 2030, by using technologies that will cost less than 100 US$/ CO2e abatement cost?
Potential: 16-30 billion tonne CO2e – 30-50% below business-as-usual in 2030
Building, agriculture and forestry sector – cheapest + maximum potential
65% of the total potential in the developing countries
McKinsey global GHG abatement cost curve
Potential of technologies with abatement cost below Euro 60/ CO2e.
Potential: 38 billion tonnes in 2030 – 70% below BAU or 35% below 1990 levels
Worldwide cost: Euro 200-350 billion/ yr by 2030 – 1% of Global GDP
Capital cost: 500-800 billion/yr above BAU investment
70% of total abatement potential in the developing countries
McKinsey GHG abatement cost curve
10 billion tonnes of CO2e by 2030 at negative cost + 20 billion tonnes between Euro 0-20 + 8 billion tonnes Euro 20-60
14 billion tonnes in energy efficiency in buildings, transport and industrial sectors + 12 billion tonnes in low carbon energy (nuclear+renewable+CCS) + 12 billion tonnes forestry and agriculture
World in 2030: 330 million ha. new forests + 70 percent renewable electricity + 40% hybrid cars ……………
Low carbon models for India
McKinsey’s India GHG abatement cost curve
India’s energy consumption would quadruple and GHG emissions would increase from about 1.5 billion tonnes CO2e in 2005 to 5-6.4 billion tonnes by 2030
Potential to restrict total emissions to 3.0 billion tonnes CO2e in 2030
But it will cost more than a trillion US$ -- 2-3% of GDP
McKinsey’s India GHG abatement cost curve
Cost of solar technologies and nuclear lower in India – highly debatable.
Some proposals ludicrous – afforest pasture land, anti-methanation vaccines to 140 million heads of livestocks
National Climate Change Policy Modelling Forum
India Computable General Equilibrium (CGE) Model: GDP growth, level of energy use and GHG emissions
India MARKAL Model: “optimal” choice of energy-technology combination and least cost options to satisfy end-use energy demands.
India Activity Analysis Model: GDP, poverty and impact of GHG mitigation policy on poverty
India SWAT Hydrology Model: impact on water resources
India ASWP Cropping Model: impact on agriculture
Preliminary results – CGE, MARKAL, AA Model
Reference scenario (Business as usual) India can achieve around 8 per cent GDP growth
rate till 2030 which will virtually eliminate poverty India’s commercial energy consumption increases
by 5.1 times – coal consumption increases by 4 times and petroleum by 5 times.
CO2 intensity of the economy (kg CO2e per US$ GDP) will decline by 3.7% per annum
India’s per capita CO2 emissions will be around 2.7 tonnes in 2030, much below the current global per capita emissions of 4.5 tonnes
Preliminary results – CGE, MARKAL, AA Model
Scenario studies:
1. Imposition of revenue positive carbon tax on the production sectors (US$ 10, 20, 40, 80 per tonne CO2e)
2. Imposition of revenue neutral carbon tax on the production sectors (US$ 10, 20, 40, 80 per tonne CO2e)
3. Binding emission reduction target of 20% from the reference scenario (deviation of 20% from business as usual)
Preliminary results – Impact of carbon tax
Preliminary results – Impact of carbon tax
Preliminary results – Impact of tax and binding targets
Carbon tax will reduce India’s GDP growth rate, reduce per capita consumption level and hence welfare and will therefore increase poverty
Carbon tax will have no significant impact on energy consumption, CO2 emissions or the commercial energy mix in the country
Binding emission reduction targets will reduce per capita consumption level and hence welfare much more than carbon tax and therefore will have larger impact on poverty levels
Modelling and more
Model outcomes highly depend on assumptions made, algorithm used and quality of data fed
The outcome of Indian models primarily hinges on two key assumptions they have made for the BAU scenario – Total factor productivity (TFG) growth rate of 3% per annum and Autonomous Energy Efficiency Index (AEEI) of 1.5% per annum.
We believe these are optimistic assumptions. lower these two and GDP decreases, emissions and per capita emissions increases
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