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Statistical mapping of PM10 concentrations over Western Europe using secondary information from dispersion modeling and MODIS satellite observations.

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Title: Statistical mapping of PM10 concentrations over Western Europe using secondary information from dispersion modeling and MODIS satellite observations.
Authors: van de Kassteele, J.1,2 Jan.van.de.Kassteele@rivm.nl, Koelemeijer, R. B. A.3, Dekkers, A. L. M.1, Schaap, M.4, Homan, C. D.5, Stein, A.2,6
Source: Stochastic Environmental Research & Risk Assessment. Dec2006, Vol. 21 Issue 2, p183-194. 12p. 3 Charts, 3 Graphs, 3 Maps.
Subjects: Statistical maps, Radioactive aerosols, Dispersion (Chemistry), Standardization, Calibration, Aerosols, Statistics, Mathematical mappings
Geographic Terms: Western Europe
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. [ABSTRACT FROM AUTHOR]
Copyright of Stochastic Environmental Research & Risk Assessment is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Stochastic Environmental Research & Risk Assessment is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Western Europe
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              Text: Dec2006
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