Statistical mapping of PM10 concentrations over Western Europe using secondary information from dispersion modeling and MODIS satellite observations
Statistical mapping of PM10 concentrations over Western Europe using secondary information from dispersion modeling and MODIS satellite observations
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DOI：
10.1007/s00477-006-0055-4
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发表时间：
2006-12-01
影响因子：
4.2
通讯作者：
Stein, A.
中科院分区：
文献类型：
--
作者：
van de Kassteele, J.;Koelemeijer, R. B. A.;Stein, A.
本文阐述了使用统计技术对颗粒物(PM10)的地面测量进行标准化。使用来自化学输送模式的不确定的二次信息和来自MODIS卫星观测的气溶胶光学厚度，对西欧上空的浓度进行了内插。仅仅基于地面测量的对欧洲PM10浓度的一致概述因国家之间的差异而变得复杂。使用了不同的监测方法并进行了校准。地面测量的空间代表性也有固有的局限性。验证表明，添加来自化学输送模型或卫星观测的次要信息改善了PM10测绘。URMSE分别从5.14降至4.26和4.58。这两个二次信息来源的组合给出了最准确和精确的预测，URMSE为3.62。这意味着这两个外部来源都包含关于PM10浓度空间分布的额外信息，因此应首选。
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.