Impacts of a global 2 degrees C climate change upon European air quality
Résumé
Several policy statements, including the 2009 Copenhagen Accord, stated that global temperature rise should be held below 2 degrees C above pre-industrial levels in order to limit the impacts of climate change. In this context, the impacts of 2-degree increase in temperature have been analyzed in the European project IMPACT2C. The objective of the present study is to evaluate how these changes will have an impact on European air quality and will potentially affect human health, using four offline atmospheric chemistry transport models. The first step was to perform air quality simulations for the current climate, using two sets of meteorological forcings for each model: reanalysis of past observation data and global climate model output. The differences between the simulations allow to evaluate how global climate models modify climate hindcast by boundary conditions inputs. Among others, we analyze whether the chemical composition of PM is affected by the use of climate models. We then investigate the contributions of the changes in meteorological parameters (precipitation, temperature, boundary layer height, etc) on surface primary and secondary compounds of PM (Lacressonnière et al., under review). For the future scenarios, the time period that corresponds to a 2-degree C global warming, such as predicted from climate simulations using RCP4.5 scenario, was run; this time period varies depending on which global climate model is used. We separately calculate the effects of climate change and emission reduction scenarios, and show that the fate of European air pollution is primarily controlled by emission reductions. A 2-degree C global warming will not hinder beneficial effects of air quality legislation, albeit inducing small changes in ozone and particulate matter changes. We then evaluate the uncertainty associated to the air quality projection under regional climate change, with a focus on annual PM2.5 and SOMO35, two indicators commonly used for health assessments (Lacressonnière et al., under preparation). We assess the robustness/ uncertainty of model predictions, by comparing the intermodel spread to the climate change signals. Our results highlight that the inter-model variability is mainly due to differences in regional climate projections, affecting several meteorological parameters, which are crucial for air quality. Beyond the model uncertainty, climate penalty or benefit have been made evident over different European areas. The use of four different models, and additional uncertainty evaluations, make our study one of the most comprehensive ones up to date to assess the impact of regional climate change on air quality and health.