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| Titel |
A Statistical Method to Estimate PM2.5 Concentrations over Europe from Meteorology and Its Application to the Effect of Climate Change |
| VerfasserIn |
Ève Lecoeur, Christian Seigneur, Christian Pagé, Laurent Terray |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250079608
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| Zusammenfassung |
| Atmospheric particulate matter (PM) pollution has become a field of great interest because of
its impacts on human health, climate change, and atmospheric visibility. In particular, fine
particles with an aerodynamical diameter less than or equal to 2.5 μm (PM2.5) are regulated
in North America and Europe. It is well-known that PM concentrations depend on
meteorology via its effects on the emissions, the kinetics of chemical reactions, the
gas/particle partitionning, and the removal of PM from the atmosphere. Therefore, climate
change is expected to affect PM concentrations.
First studies of the effect of climate change on air quality have originally been conducted
on ozone, whereas the study of its effect on PM concentrations is more recent. However, most
of the work pertaining PM has focused so far on the United States. Furthermore, there is
currently no strong consensus on the effects of the present and future climate on PM2.5
concentrations. Therefore, we propose here a statistical method which estimates PM2.5
concentrations over Europe from the meteorology and which can be applied to present and
future climates.
In more detail, we apply a multiple linear regression model to understand the
relationships between PM2.5 concentrations and meteorological variables in Europe. Multiple
linear regression predictors include temperature, precipitation, wind speed, and weather
types, which are representative of the large-scale atmospheric circulation. We use the results
of a 9-year (2000-2008) model simulation as PM2.5 pseudo-observations. By assuming that
the weather types will remain the same in the future (stationarity), we use different model
predictions provided by the IPCC to study how the frequency of the weather types will
change in the future. The statistical model is used to estimate future PM2.5 concentrations
that would result from this climate change. |
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