Publication Date:
2014-02-26
Description:
[1] A statistical algorithm was developed to estimate PM 2.5 concentrations over Europe based on a weather-type representation of the meteorology. We used modeled PM 2.5 concentrations as pseudo-observations, because of a lack of PM 2.5 speciated measurements over Europe, and included four meteorological variables. This algorithm was evaluated on the learning period (2000-2008) to test its ability to reproduce the pseudo-observed data set and then applied for two climatological scenarios (RCP4.5 and RCP8.5), one historical (1975-2004) and two future periods (2020-2049 and 2070-2099). In Italy, Poland, northern, eastern, and southeastern Europe, all future scenarios lead to decreases in PM 2.5 , whereas, in the Balkans, Benelux, the U.K., and northern France, they lead to increases in PM 2.5 . Considering each season separately shows stronger responses, which may vary for a given region and scenario. Decomposing the changes in PM 2.5 concentrations as the sum of inter-type and intra-type changes, and a residual term shows that: (1) the residual term is negligible, (2) inter-type changes affect more the regions along the Atlantic Ocean, (3) in most other regions, inter-type and intra-type changes are often on the same order of magnitude. The relationship between the atmospheric circulation and weather-types evolves, and therefore modifies the mean of meteorological variables and PM 2.5 concentrations. This algorithm offers a novel approach to investigate the effect of climate change on air quality, and can be applied to other pollutants, regions, and meteorological models. Furthermore, this approach can be applied using actual speciated PM 2.5 observations, if a sufficiently dense monitoring network were available.
Print ISSN:
0148-0227
Topics:
Geosciences
,
Physics
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