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