Equipe géostatistique, Centre de Géosciences, Mines ParisTech 35, rue Saint Honoré, 77305, Fontainebleau, France.
Institut National de l'Environnement Industriel et des Risques (INERIS) Direction des risques chroniques, Parc Technologique Alata, 60550, Verneuil-en-Halatte, France.
Environ Monit Assess. 2018 Jun 29;190(7):441. doi: 10.1007/s10661-018-6788-y.
The European legislation on ambient air quality introduces the concepts of spatial representativeness of a monitoring station and spatial extent of an exceedance zone. Spatial representativeness is an essential macro-scale siting criterion which should be evaluated before the setting-up and during the life of a monitoring point. As for the exceedance area, it has to be defined each time an environmental objective is exceeded in an assessment zone. No specific approach is prescribed to delimit such areas. A probabilistic methodology is presented, based on a preliminary kriging estimation of atmospheric concentrations at each point of the domain. It is applied to NO pollution on the urban scale. In the proposed approach, a point belongs to the area of representativeness of a station if its concentration differs from the station measurement by less than a given threshold. To take the estimation uncertainty into account, the standard deviation of the kriging error is used in a probabilistic framework. The choice of the criteria used to deal with overlapping areas is first tested on NO annual mean concentration maps of France, built by combining surface monitoring observations and outputs from the CHIMERE chemistry transport model. At the local scale, data from passive sampling surveys and high -resolution auxiliary variables are used to provide a more precise estimation of the background pollution in different French cities. The traffic-related pollution can also be accounted for in the map by additional predictors such as distance to the road, and traffic-related NO emissions. Similarly, the proposed approach is implemented to identify the points, at a given statistical risk, where the NO concentration is above the annual limit value.
欧洲环境空气质量法规引入了监测站空间代表性和超标区域空间范围的概念。空间代表性是一个基本的宏观选址标准，应在监测点建立和运行期间进行评估。对于超标区域，在评估区域内超过环境目标时必须定义。没有规定具体的方法来划定这些区域。提出了一种基于大气浓度初步克里金估计的概率方法，该方法适用于城市尺度的 NO 污染。在所提出的方法中，如果点的浓度与站测量值相差小于给定阈值，则该点属于站代表性区域。为了考虑估计不确定性，在概率框架中使用克里金误差的标准差。首先在法国的 NO 年平均浓度图上测试了用于处理重叠区域的标准的选择，这些图是通过结合表面监测观测和 CHIMERE 化学传输模型的输出构建的。在局部尺度上，使用被动采样调查和高分辨率辅助变量的数据来更准确地估计不同法国城市的背景污染。还可以通过其他预测因子（例如距道路的距离和与交通相关的 NO 排放）来考虑与交通相关的污染。同样，实施了所提出的方法来识别处于给定统计风险下 NO 浓度超过年限值的点。
