Spatial interpolation of air pollution measurements using CORINE land cover data
Spatial interpolation of air pollution measurements using CORINE land cover data
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DOI：
10.1016/j.atmosenv.2008.02.043
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发表时间：
2008-06-01
影响因子：
5
通讯作者：
Mensink, Clemens
中科院分区：
文献类型：
--
作者：
Janssen, Stijn;Dumont, Gerwin;Mensink, Clemens
近年来，环境空气质量的实时评估得到了越来越多的关注。为了支持这一演变，统计空气污染插值模型RIO的发展。由于计算成本非常低，该插值模型是环境机构进行实时空气质量评估时的有效工具。除此之外，还可以使用可靠的插值模型来生成历史数据记录的分析图。这些地图对于正确检查是否符合新的欧盟空气质量指令所预见的人口接触限值至关重要。RIO是一种插值模型，可以归类为去趋势克里格模型。在第一步骤中，在去趋势过程中去除空气污染采样值的局部特征。随后，站点独立的数据内插的普通克里格方案。最后，在重新趋势化步骤中，将局部偏差添加到克里格插值结果中。作为去趋势过程中的空间分辨驱动力，土地利用指标的基础上CORINE土地覆盖数据集的开发。该指标针对O-3、NO2和PM10三种污染物进行了独立优化。因此，RIO模型能够在没有监测站的地方解释空气污染现象的局部特征。通过交叉验证程序的RIO模型优于标准插值技术，如普通克里格证明。针对上述三种污染物提供了空气质量地图，并与基于标准插值技术的地图进行了比较。(c)2008爱思唯尔有限公司保留所有权利。
Real-time assessment of the ambient air quality has gained an increased interest in recent years. To give support to this evolution, the statistical air pollution interpolation model RIO is developed. Due to the very low computational cost, this interpolation model is an efficient tool for an environment agency when performing real-time air quality assessment. Beside this, a reliable interpolation model can be used to produce analysed maps of historical data records as well. Such maps are essential for correctly checking compliance with population exposure limit values as foreseen by the new EU Air Quality Directive. RIO is an interpolation model that can be classified as a detrended Kriging model. In a first step, the local character of the air pollution sampling values is removed in a detrending procedure. Subsequently, the site-independent data is interpolated by an Ordinary Kriging scheme. Finally, in a re-trending step, a local bias is added to the Kriging interpolation results. As spatially resolved driving force in the detrending process, a land use indicator is developed based on the CORINE land cover data set. The indicator is optimized independently for the three pollutants O-3, NO2 and PM10. As a result, the RIO model is able to account for the local character of the air pollution phenomenon at locations where no monitoring stations are available. Through a cross-validation procedure the superiority of the RIO model over standard interpolation techniques, such as the Ordinary Kriging is demonstrated. Air quality maps are presented for the three pollutants mentioned and compared to maps based on standard interpolation techniques. (c) 2008 Elsevier Ltd. All rights reserved.