Mapping urban air pollution using GIS: a regression-based approach
Mapping urban air pollution using GIS: a regression-based approach
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DOI：
10.1080/136588197242158
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发表时间：
1997-10-01
影响因子：
5.7
通讯作者：
VanderVeen, A
中科院分区：
文献类型：
--
作者：
Briggs, DJ;Collins, S;VanderVeen, A
作为欧盟资助的SAVIAH项目的一部分，在GIS环境中开发了一种基于回归的方法来绘制与交通有关的空气污染。对阿姆斯特丹、哈德斯菲尔德和布拉格的NO2进行了测绘。在每个中心，调查NO2，作为交通相关污染的标志，进行被动扩散管，暴露了4个2周的时间。还建立了一个地理信息系统，其中载有关于监测到的空气污染程度、公路网、交通量、土地覆盖、海拔和其他当地确定的特征的数据。从80个监测点的数据，然后被用来构建一个回归方程，预测环境变量的基础上，和由此产生的方程用于映射整个研究区域的空气污染。然后通过将预测的污染水平与一系列独立参考地点的监测水平进行比较，评估地图的准确性。结果表明，该地图对监测到的污染水平进行了非常好的预测，无论是对个别调查还是对年平均浓度，在8-10个参考点上，r（2）近似于0.79-0.87，尽管个别调查期间的预测准确性差异较大。在哈德斯菲尔德和阿姆斯特丹，进一步的监测也表明，污染地图提供了可靠的估计NO2浓度在第二年（r（2）类似于0.59-0.86，n=20）。
As part of the EU-funded SAVIAH project, a regression-based methodology for mapping traffic-related air pollution was developed within a GIS environment. Mapping was carried out for NO2 in Amsterdam, Huddersfield and Prague. In each centre, surveys of NO2, as a marker for traffic-related pollution, were conducted using passive diffusion tubes, exposed for four 2-week periods. A GIS was also established, containing data on monitored air pollution levels, road network, traffic volume, land cover, altitude and other, locally determined, features. Data from 80 of the monitoring sites were then used to construct a regression equation, on the basis of predictor environmental variables, and the resulting equation used to map air pollution across the study area. The accuracy of the map was then assessed by comparing predicted pollution levels with monitored levels at a range of independent reference sites. Results showed that the map produced extremely good predictions of monitored pollution levels, both for individual surveys and for the mean annual concentration, with r(2) similar to 0.79-0.87 across 8-10 reference points, though the accuracy of predictions for individual survey periods was more variable. In Huddersfield and Amsterdam, further monitoring also showed that the pollution map provided reliable estimates of NO2 concentrations in the following year (r(2) similar to 0.59-0.86 for n=20).