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| Titel |
Influence of Climate on PM2.5 Concentrations over Europe : a Meteorological Analysis using a 9-year Model Simulation |
| VerfasserIn |
È. Lecoeur, C. Seigneur, L. Terray, C. Pagé |
| Konferenz |
EGU General Assembly 2012
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 14 (2012) |
| Datensatznummer |
250059491
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| Zusammenfassung |
| In the early 1970s, it has been demonstrated that a large number of deaths and health
problems are associated with particulate pollution. As a consequence, several governments
have set health-based air quality standards to protect public health. Particulate matter with an
aerodynamical diameter of 2.5 μg.m-3 or less (PM2.5) is particularly concerned by these
measures. As PM2.5 concentrations are strongly dependent on meteorological conditions, it is
important to investigate the relationships between PM2.5 and meteorological parameters. This
will help to understand the processes at play and anticipate the effects of climate change on
PM2.5 air quality.
Most of the previous work agree that temperature, wind speed, humidity, rain rate and
mixing height are the meteorological variables that impact PM2.5 concentrations the most. A
large number of those studies used Global Circulation Models (GCM) and Chemical
Transport Models (CTM) and focus on the USA. They typically predict a diminution of
PM2.5 concentrations in the future, with some geographical and/or temporal discrepancies,
when only the climate evolution is considered. When considering changes in emissions along
with climate, no consensus has yet been found. Furthermore, the correlations between PM2.5
concentrations and meteorological variables are often low, which prevents a straightforward
analysis of their relationships.
In this work, we consider that PM2.5 concentrations depend on both large-scale
atmospheric circulation and local meteorological variables. We thus investigate the influence
of present climate on PM2.5 concentrations over Europe by representing it using a weather
regimes/types approach. We start by exploring the relationships between classical weather
regimes, meteorological variables and PM2.5 concentrations over five stations in Europe,
using the EMEP air quality database. The pressure at sea level is used in the classification as
it effectively describes the atmospheric circulation. We experimentally verify some
intuitive results: weather regimes associated with weak (resp. high) precipitation,
wind and low (resp. high) temperatures correspond to higher (resp. lower) PM2.5
concentrations. We also observe that rain rate is the variable that impacts PM2.5
concentrations the most. Next, we search for better relationships by adding this second
variable to the classification: we therefore build new weather regimes, called weather
types. Because of the low number of the EMEP observations, we compute PM2.5
concentrations with the Polyphemus/Polair3D CTM for years between 2000 and 2008 in
order to obtain a spatially and temporally complete dataset of PM2.5 concentrations
and chemical components, which can be used to relate PM2.5 concentrations to
meteorological regimes and specific variables. By classifying both a large-scale
variable and a local variable that influence the PM2.5 concentrations and using
gridded data of the modeled concentrations of PM2.5, we obtain a more robust
analysis.
The results of this work will provide the basis to predict the effects of climate change (via
the evolution of weather regimes/types frequencies) on PM2.5 chemical composition and
concentrations. |
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