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Mobilising new partnerships to address global societal challenges: Role of EU research & innovation programmes for sustainable development. Dr Ritu Mathur TERI, India. India’s development challenges. 27.5% of India’s population below official poverty line - PowerPoint PPT Presentation
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Mobilising new partnerships to address global societal challenges: Role of EU research & innovation
programmes for sustainable development
Dr Ritu Mathur
TERI, India
2
India’s development challenges 27.5% of India’s population below official poverty line
Over 400 million people without access to electricity
People consuming less than the minimum calorific intake has increased from 64% in 1987-88 to 76% in 2004/05 (MoSPI, 2009)
90% of rural India dependent on traditional fuels for cooking
Energy shortages (2008/09)
~ 11% in energy terms
~ 12% in peak energy
Developmental goals and energy access to all High targets for economic growth
Indicators of human development such as life expectancy, mean years of schooling and mortality suggest that deprivation levels in India remain stubbornly high as compared to other countries
Multiple challenges across sectors MSMEs in the Indian context
Small units lacking capacity for investment/knowledge
National Solar Mission, National Mission on Energy Efficiency 20 GW by 2020/ energy & peak shortages continue
Food security/Agricultural productivity Huge gap in yields (India & other countries)
Sustainable transport Access to mobility /Air pollution & Congestion
Energy access More than 400 million without access to electricity & around 850 million
lack access to clean cooking fuels – energy security/ indoor air pollution
4
Higher vulnerability of developing countries
Reliance on climate-sensitive activities Weak technical, institutional, and financial
capacities to cope Those with the least resources have the least
capacity to adapt and are the most vulnerable Aggregate monetary damage for 2 x CO2
(annual damages as % of GDP) World 1.5-2 % OECD countries 1-2 % Developing countries 2-9 %
Source: IPCC WG II, 2001
EU Funded Research project – 7th Framework Programme on:
Economic costs of climate change
Costs and benefits of mitigation (including co-benefits)
Costs and benefits of adaptation
Completed End of 2011
Multi-disciplinary study, involving top-down and bottom up modelling, with teams from
across Europe [India & China as separate country scenarios]
European detailed analysis, within Global assessment
ClimateCost
Climate Cost used Classical Impact Assessment Method - series of steps
• Climate model output (future climate change signal)
Combine with stock at risk (e.g. population)
Use response functions that link climate parameters to assess physical impacts
Value physical impacts in economic terms, for both market and non-market sectors
Assess costs and benefits of adaptation
Innovation
1) Explicitly consider climate uncertainty- rather than central projections only
2) Separate out socio-economic and climate change
3) Feed analysis into macro-economic assessment with CGE and IA models
Methods and Innovation
30 yr time slices ENSEMBLES data
(2010-2040; 2040-2070; 270-2100) for 2 scenarios
A1B (medium-high)
E1 Mitigation (equivalent to 2 degrees)
So can consider benefits of mitigation action
BUT looking at uncertainty
Very large differences across the models - even in the sign (+/-) of change
Climate model information written up in short policy summary
Climate model analysis and data
Projected change in global mean temperature (°C) with respect to 1961-1990 for the A1B (red) and E1 (green) emissions scenarios. Results from ENSEMBLES GCMs. Thin lines: individual models. Thick lines: ensemble mean.
Source Christensen, Goodess, Harris, Climatic and Watkiss, 2011
Medium high baseline
(A1B)
Mitigation = 2 degrees (E1) B
enef
it o
f m
itig
atio
n
ClimateCost uses a ‘impact assessment’ approach using sector models
coastal zones (DIVA). Population affected, flood damage, beach erosion, loss wetlands, etc
floods (LISFLOOD) – flood damage for 5 sectors.
energy (POLES). Heating and cooling, hydro potential, thermal cooling, water abstraction
health (LSHTM). Heat and cold related mortality, food borne disease, labour productivity, floods
agriculture (UPM - PESETA). Crop based models and land productivity - linked to economic
ecosystems (LPJ) – terrestrial carbon and biomes
While comprehensive – still only a subset of impacts – and subset of sectors
Models and Sector Analysis
There are large economic costs from climate change in Europe
Also strong distributional patterns across Europe – economic impacts are not equal across
Member States
Economic costs significantly lower under mitigation scenarios, but only post 2040, thus need
for adaptation and mitigation
Mitigation also avoids major tipping elements
Mitigation leads to high co-benefits, health benefits and large economic benefits from
improving air quality
Adaptation effective in reducing impacts at low cost (high benefit to cost ratios)
However, uncertainty requires decision making under uncertainty – and a move to
robustness and resilience
Results of the study
India component: detailsWP1: Scenarios
WP2: C/B of CC/A
WP3: Catastrophic Event
WP4: Mitigation
WP5: Ancillary Benefits
WP6: Model Development
WP7: Policy Integration
WP8: Dissemination
WP9: PM
Assess the mitigation costs of different future policy scenarios
Ancillary air quality benefits of mitigation in terms of physical and monetary impacts for those
scenarios
TERI to develop /align scenarios that could be incorporated into other world models & assessment frameworks
WP4: Mitigation
Using the MARKAL model three scenarios were developed. BAU A2B1 Low Growth Scenario ~E1 (from targets given by the GEM-E3 Model)
Emissions, System Cost, Technological mix, Fuel mix etc. for each of these scenarios assessed
WP4: Comparison across Scenarios Total Emissions CO2
0.00
2.00
4.00
6.00
8.00
10.00
12.00
2001/02 2006/07 2011/12 2016/17 2021/22 2026/27 2031/32 2036/37
Mill
ion
s
A2B1 E1 BAU
GAINS ModelAimed at reduction in Air Pollution & GHG Emissions
Greenhouse Gases
Study of implications for India Emission tonnage taken from two scenarios
BAU E1
Emissions converted using an atmospheric chemistry model and allocated into multiple grids across India
Grid level concentration reduction along with projected population (broken by age) and concentration response functions employed to calculate lives saved due to reduction
Indication of benefits across scenarios
Age Group Lives Saved ('000) BAU vis-à-vis E1
0 to 4 506
5 to 14 81
15 to 44 757
45 to 64 779
65+ 517
Total 2641
Differential vulnerabilitySome influencing factors for human health
Location Regions with low financial, institutional and
technological capacity Communities in proximity to ‘sensitive ecosystems’-
coastal areas, mountains etc. Age Gender Lack of preparedness: Existing status of population
health and access to health care facilities; lack of awareness and planning
Addressing differential vulnerabilityFrom global to local scale
Source: McMichael et al 2008
From research to action: Informing policies to protect health from climate change
Source: McMichael et al 2008
Challenges of bringing science to general public & policy makers
Moving towards prioritization Planning for Implementation Regional & local Scales Adapting knowledge solutions & technologies to
local needs Co-operation
Research (RDD&D) Knowledge management & dicussion platforms
Collation & replication of success stories Evaluation tools, techniques & methodologies
Way forward Large opportunities to help scale up research &
action EU can play a key role in facilitating joint
research to bridge knowledge gaps Supporting research through appropriate tools &
techniques Use at appropriate scales
Nature of involvement important Capacity building Involvement of local partners at each stage
Thank You