Presentation on theme: "Towards Local Costing of Climate Change Impacts for Decision Making in Adaptation Alistair Hunt Department of Economics, University of Bath I-SEE Seminar."— Presentation transcript:
Towards Local Costing of Climate Change Impacts for Decision Making in Adaptation Alistair Hunt Department of Economics, University of Bath I-SEE Seminar December 15 th 2009
Contents of Presentation Motivation for research Estimating economic welfare costs of CC impacts at local scale, within UK. Some aspects of the economics of adaptation to climate change
Motivation for Research Information needed to prepare against possible risks –Provide quantitative estimates of economic welfare costs of CC impacts at local scale, within UK benefits gained from taking adaptive action. How to make decisions in face of substantial uncertainty –Test use of cost information in adaptation decision-making
Projected Baseline Impacts without Climate Change (no adaptation) Impacts (e.g. average annual total market and non-market damages of flood) Time 2002 203020502080 Influence of Socio-economic change - e.g. increase in number of properties, change in occupancy rates, change in value of property / contents Stylised Analytical Framework: No CC Impacts/Adaptation Historical analogue (1-250 yr flood) (NB only linear to simplify presentation) e.g. River Flooding in UK
Physical Impact Assessment Use of Socio-Economic scenarios to: –Quantify magnitude of physical impacts under CC scenarios relative to climate baseline on consistent SE scenarios –Inform unit values ( e.g. changing with GDP growth per capita) Use scenarios developed for UK Climate Impacts Programme –Governance & capacity of institutions at different levels to manage change. –Orientation of social and political values –Up to 2050s, linear extrapolation to 2080s
Use of SES : River flooding example Quantitative: population and household size Qualitative:
Future Impacts with Climate Change & no Adaptation (predicted change in return period) Projected Baseline without Climate Change & no Adaptation Time 2002 203020502080 Gross annual average cost of climate change Impact of climate change on return period Stylised Analytical Framework Impacts (e.g. average annual total market and non-market damages of flood)
Generic methods for linking climate variables with physical impacts Using historical analogues of weather extremes to identify impacts. –E.g. flooding events. –Sectors: Building, Transport Simulation modeling of behavioural change –E.g. carbon enrichment –Sectors: Tourism, Health, Agriculture and Biodiversity Stakeholder-led and Ad-hoc projections –E.g. retailing responses to warmer summers –Sectors: Retail & Manufacturing, Water, Energy
Physical Impact Assessment Climate data Basis: UKCIP02 Climate scenarios Data presented for: precipitation & temperature 5 X 5 km areas individual months in three time-slices of 30 years covering 2010 – 2100 Assume climate change manifests itself either by: - changes in means of climate variable or; - climate variability (extremes)
UK projected changes in average temperature Low emissions High emissions
Results for UK – 2080s time-slice Annual Average Welfare Costs (£ million, 2004 prices) (-ve denotes benefit)
Results for UK – 2080s time-slice Changes in Consumer Expenditure (£ million, 2004 prices) -ve denotes reduction in consumer spend; +ve denotes increase in consumer spend
Local costing: Impacts and primary stakeholder Impact consideredPrimary Stakeholder Road maintenance in summer (subsidence) and winter (salting - ice) Cambridgeshire County Council Domestic property subsidenceAssociation of British Insurers Historic garden maintenance in Cornwall (lawn mowing and pest control) National Trust Health impacts of hot summers in Hampshire Hampshire County Council
Annual Impact multipliers over baseline (2011–2040 time period, undiscounted) Impact consideredCost multipliers Road maintenance in summer (subsidence) and; winter (salting - ice) 13 – 15 (-) 1.3 – 1.6 Domestic property subsidence12 - 15 Historic garden maintenance in Cornwall (lawn mowing and pest control) 1.2 – 1.5 Health impacts of hot summers in Hampshire 16 - 18
Future Impacts with Climate Change & no Adaptation Projected Baseline without Climate Change & no Adaptation Time 2002 203020502080 Gross benefit of adaptation for comparison with costs of adaptation Future Impacts (with Climate Change) after Adaptation (e.g. reduction in predicted return period) Residual Impacts of Climate Change Stylised Analytical Framework Impacts (e.g. average annual total market and non-market cost of flood)
Application to Flood Management Riverine flood risks in Shrewsbury, Shropshire –Impacts Direct physical damage to residential and non- residential property Forgone output from short-term disruption to non- residential properties. Direct impacts on human health (mortality, injuries and stress).
Total damage costs associated with different flood frequencies in Shrewsbury (£'000s) Average waiting time (yrs) between events/frequency per year Average waiting time (yrs) between events 3510152550100150Infinity Frequency per year 10.330.20.10.0670.040.020.010.0070 Damage category Residential property512788498188326352 Ind/commercial (direct)7146376440570121715141558 Car damage76128256 290306 Infrastructure damage 1225293136487779 Health 8152955108115122133 Total damage (000)1073257678661068182423292427 Area (damage X frequency)35.6228.7854.6255.07 36.4820.737.9316.18
Application to Flood Management Riverine flood risks in Shrewsbury, Shropshire –Adaptation Key problem: uncertainty in impacts may result in inappropriate level or type of adaptation May be better to adopt a portfolio of options that reflect the decision-makers preferences relating to (economic?) optimisation versus reducing the chances of getting it wrong (variance from the optimal)
Flood management decision-making: portfolio analysis Instead of appraisal of single flood response options using the economic efficiency criterion, a group of options are collectively appraised. Economic efficiency criterion (Net Present Value) is the measure of portfolio return. Also measure NPV variance as indicator of uncertainty May be better able to capture variations in effectiveness of responses across a wider range of possible (climatic and socio-economic) futures.
Potential Flood Management Options Option TypeSpecific Options Managing the Rural Landscape to reduce runoff Rural infiltration Rural catchment storage Rural conveyance Managing the Urban Landscape Urban storage Urban infiltration Urban conveyance Managing Flood Events Pre-event measures Forecasting and warning systems Flood fighting actions Collective damage avoidance Individual damage avoidance e.g. property resistance Managing Flood Losses Land use management Flood-proofing Land use planning Building codes Insurance, shared risk and compensation Health and social measures River Engineering River conveyance Engineered flood storage Flood water transfer Hard defences
Economic returns to flood management options 3 options: hard defence; property resistance; warning system CBA for each option –Three degrees of implementation (20%, 50%, 100%) –Constant-scale economies in costs assumed –Four (consistent) CC/SE scenario combinations –Portfolios created from combinations of two options and three options, each option disaggregated according to degree of implementation
Results Economic efficiency – variance trade-off exists for both 2 and 3 option portfolios Sub-optimal portfolios can be identified Hard defences generally contribute most to higher NPV and higher variance; property resistance option has opposite effect.
Conclusions Seems possible to scope out identified climate change impacts against specified climate scenarios, though socio-economic scenarios add significant (even more!) complexity Adaptation assessment may be enriched by use of portfolio analysis – incorporates uncertainty more explicitly into decision-making. But reliant on reliable, quantitative data relating to both the costs and benefits of identified adaptation options.
Conclusions Future research priorities may, inter alia, include: –Applying portfolio analysis within a portfolio of alternative decision rules –Improving representation of non-market values within decision rules –Application of non-market valuation techniques to evaluation of softer, behavioural-based, adaptation options