Dr Ritu Mathur TERI, India

1. 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

3. 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

5. ClimateCost • 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

6. Methods and Innovation • 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

7. Climate model analysis and data • 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

8. Medium high baseline (A1B) Benefit of mitigation Mitigation = 2 degrees (E1) 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

9. Models and Sector Analysis • 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

10. Results of the study • 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

11. India component: details WP1: Scenarios Assess the mitigation costs of different future policy scenarios WP2: C/B of CC/A WP3: Catastrophic Event WP4: Mitigation WP5: Ancillary Benefits Ancillary air quality benefits of mitigation in terms of physical and monetary impacts for those scenarios WP6: Model Development WP7: Policy Integration WP8: Dissemination WP9: PM TERI to develop /align scenarios that could be incorporated into other world models & assessment frameworks

12. 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

13. WP4: Comparison across Scenarios

14. GAINS ModelAimed at reduction in Air Pollution & GHG Emissions Greenhouse Gases

15. 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

16. Indication of benefits across scenarios

17. 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

18. Addressing differential vulnerabilityFrom global to local scale Source: McMichael et al 2008

19. From research to action: Informing policies to protect health from climate change Source: McMichael et al 2008

20. 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

21. 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

22. Thank You