Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 365238
Title Statistical mapping of PM10 concentrations over Western Europe using secondary information from dispersion modeling and MODIS satellite observations
Author(s) Kassteele, J. van de; Koelemeijer, R.B.A.; Dekkers, A.L.M.; Schaap, M.; Homan, C.D.; Stein, A.
Source Stochastic environmental research and risk assessment 21 (2006)2. - ISSN 1436-3240 - p. 183 - 194.
DOI https://doi.org/10.1007/s00477-006-0055-4
Department(s) Biometris (WU MAT)
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2006
Keyword(s) air-quality prediction - aerosol - pollution - products - association - mortality - health - texas
Abstract This paper illustrates the use of statistical techniques to standardize ground based measurements of particulate matter (PM10). Concentrations are interpolated over Western Europe using uncertain secondary information from a chemical transport model and of aerosol optical thickness from MODIS satellite observations. A consistent overview of PM10 concentrations over Europe based solely on ground based measurements is complicated by differences between countries. Different monitoring methods are used and calibrations are applied. There also is an inherent limitation to the spatial representativeness of ground based measurements. Validation showed that adding secondary information from either the chemical transport model or the satellite observations improved the PM10 mapping. The URMSE decreased from 5.14 to 4.26 and 4.58, respectively. A combination of both sources of secondary information gave the most accurate and precise predictions, with an URMSE of 3.62. This means that both external sources contain additional information on the spatial distribution of PM10 concentrations and should therefore be preferred.
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