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              <p>People exposure to particulate matter can have various health effects as described in scientific publications in the area of observational epidemiology. This study estimates the Loss of Life Expectancy (LLE) related to PM2.5 concentrations corresponding to a selected baseline energy scenario derived from the GAINS model. Most often energy scenarios are defined as consistent pathways towards a long-term target defined by a set of criteria that describe a sustainable energy supply. This study accounts for the temporal evolution of PM2.5 concentrations along the time frame from 2005 till 2050. The analysis was carried out for 43 European countries with a spatial resolution of 50 x 50 km. LLE was considered over the whole life time of the population older than 30 years in year 2005. We propose an algorithm for the computation of LLE for population exposed to PM2.5 based on the approach recommended by the Task Force on Health described in IIASA's Report and accounting for the Pope exposure-risk parameter. The LLE computation is based on the difference between the life expectancy with no exposure to particulates and life expectancy with exposure to observed particulates. We considered in our algorithm the temporal evolutions of PM2.5 concentrations along the scenario, as well as population densities. LLE results were derived using different PM2.5 concentration profiles from 2005 to 2050. The first PM2.5 concentration profile corresponds to a constant PM2.5 concentration with values fixed to the 2005 situation. The second PM2.5 concentration profile corresponds to the temporal evolution of the selected energy scenario. LLE is then derived for both situations: the fixed PM2.5 concentrations case and the variable PM2.5 case as defined for the baseline scenario. LLE results are significantly different between the two cases with a decrease by half for most European countries. The Netherlands and Eastern Europe are the only regions where LLE exceed 300 days/person of life lost. Applying this new feature of temporal evolution of PM2.5 is of interest for assessing the potential impacts of scenarios accounting for the possible technical evolution of energy pathways. Results are provided on line in numerical form as well as in form of LLE maps.</p>
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