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Retrieval of PM10 Concentration from an AOT Passive Remote-Sensing Station between 2003 and 2007 over Northern France

机译:在2003年至2007年期间从法国北部的AOT被动遥感站获取PM10浓度

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摘要

A method of retrieving PM10 particles concentrations at the ground level from AOT (Aerosol Optical Thickness) measurements is presented. It uses data obtained among five years during 2003 to 2007 summers in the Lille region (northern France). As PM10 concentration strongly depends on meteorological variables, we clustered the meteorological situations provided by the MM5 meteorological model forced at the lateral boundaries by the operational NCEP model in eight classes (local weather types) for which a robust statistical relationship between AOT and PM10 was found. The meteorological situations were defined by the hourly vertical profiles of temperature and (zonal and meridian) wind components. The clustering of the weather types were obtained by a self-organizing map (SOM) followed by a hierarchical ascending classification (HAC). We were then able to retrieve the PM10 at the surface from the AERONET AOT measurements for each weather type by doing non linear regressions with dedicated SOMs. The method is general and could be extended to other regions. We analyzed the strong pollution event that occurred during August 2003 heat wave. Comparison of the results from our method with the output of the CHIMERE chemical-transport model showed the interest to tentatively combine these two pieces of information to improve particle pollution alert. ?
机译:提出了一种从AOT(气溶胶光学厚度)测量值中检索地面PM10颗粒浓度的方法。它使用里尔地区(法国北部)2003年至2007年夏季的5年间获得的数据。由于PM10浓度强烈依赖于气象变量,因此我们将由操作NCEP模型强迫在横向边界处MM5气象模型提供的气象情况分为八类(局部天气类型),针对这些气象情况,发现了AOT和PM10之间的稳健统计关系。气象情况由温度和(纬向和子午线)风分量的每小时垂直剖面定义。天气类型的聚类是通过自组织图(SOM),然后是层次升序分类(HAC)获得的。然后,我们可以通过使用专用SOM进行非线性回归,从每种天气类型的AERONET AOT测量值中检索地面的PM10。该方法是通用的,可以扩展到其他区域。我们分析了2003年8月热浪期间发生的强烈污染事件。将我们的方法的结果与CHIMERE化学传输模型的输出进行比较表明,有兴趣将这两种信息初步结合起来,以改善颗粒物污染预警。 ?

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