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Mapping particulate matter in alpine regions with satellite and ground-based measurements: An exploratory study for data assimilation

机译：利用卫星和地面测量在高寒地区绘制颗粒物的图：数据同化的探索性研究

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摘要

The objective of this study is the integration of satellite and in-situ measurements of particulate matter (PMio) to provide PM10 maps in Switzerland and South Tyrol (Italy) on an operational daily basis. Satellite retrieval of PM has been widely investigated in the past years, showing moderate potential (uncertainty of ~30%) but also a number of severe limitations (e.g., due to cloud and snow cover or unknown aerosol extinction profiles). Its actual effectiveness can only be tested by a comparison with the mapping capability of ground-based measurements from existing air-quality networks. Moreover, the integration of both observational systems (assimilation) can improve PM mapping. Herein, we apply a linear model including aerosol optical depth (AOD) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and meteorological boundary layer height (BLH) to estimate spatially homogeneous maps of PM10 over the study region in 2008—2009. AOD from MODIS is used to compare the results with those of similar studies. The validation of the satellite maps reveals higher accuracy in flat areas (r ~ 0.6, RMSE ~ 10 μg m~-3) than in alpine valleys and elevated sites. In contrast, the inverse distance interpolation of in-situ measurements is able to produce more accurate (r > 0.8, RMSE < 6 μg m~(-3)) PM10 maps. An assimilation schema was developed considering the interpolation of ground measurements as a background field, updating it with satellite observations wherever they are available. The accuracy of the assimilated maps is assessed and compared to the background fields. It is found that satellite data is of limited benefit in the considered region due to the good spatial coverage of the ground networks and the difficulties inherent to the satellite PM retrieval over rugged topography. The results of the assimilation are positive (~ 1 μg m~(-3) improvement in RMSE) when a number of ground sites (80%) are excluded. It is concluded that satellite data are of higher interest for regions with a sparser distribution of measurement sites (e.g., distance > 100 km between sites).
机译：这项研究的目的是对卫星和颗粒物原位测量（PMio）进行整合，以提供每日运行中瑞士和南蒂罗尔（意大利）的PM10地图。过去几年中，对PM的卫星检索进行了广泛研究，显示出中等潜力（不确定性约为30％），但也存在许多严重局限性（例如，由于云层和积雪或未知的气溶胶灭绝特征）。它的实际有效性只能通过与现有空气质量网络的地面测量的制图能力进行比较来进行测试。此外，两个观测系统（同化）的集成可以改善PM测绘。在本文中，我们应用线性模型，其中包括自旋增强型可见光和红外成像仪（SEVIRI）的气溶胶光学深度（AOD）和气象边界层高度（BLH），以估算2008-2009年研究区域内PM10的空间均匀图。来自MODIS的AOD用于将结果与类似研究的结果进行比较。卫星地图的验证表明，在平坦区域（r〜0.6，RMSE〜10μgm〜-3）比高山山谷和高架地区的精度更高。相反，原位测量的反距离插值能够生成更准确的（r> 0.8，RMSE <6μgm〜（-3））PM10图。考虑到地面测量值的插值作为背景场，因此开发了一种同化方案，并在可能的地方通过卫星观测进行更新。评估同化图的准确性并将其与背景字段进行比较。已经发现，由于地面网络的良好空间覆盖以及在崎top地形上检索卫星PM所固有的困难，在所考虑的区域中，卫星数据的收益有限。当排除许多地面站点（80％）时，同化的结果为正（RMSE约〜1μgm〜（-3）改善）。结论是，对于测量地点稀疏分布的区域（例如，地点之间的距离> 100 km），卫星数据具有更高的关注度。

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  • 来源
    《Atmospheric environment》 |2011年第26期|p.4344-4353|共10页
  • 作者

    E. Emili; C. Popp; S. Wunderle; M. Zebisch; M. Petitta;

  • 作者单位

    University of Bern, Institute of Geography, Remote Sensing Croup, Hallerstrasse 12, 3012 Bern, Switzerland,European Academy, Institute for Applied Remote Sensing, Viale Druso 1, 39100 Bolzano, Italy;

    Empa, Swiss Federal Laboratories for Materials Science and Technology, Dubendorf, Switzerland;

    University of Bern, Institute of Geography, Remote Sensing Croup, Hallerstrasse 12, 3012 Bern, Switzerland;

    European Academy, Institute for Applied Remote Sensing, Viale Druso 1, 39100 Bolzano, Italy;

    European Academy, Institute for Applied Remote Sensing, Viale Druso 1, 39100 Bolzano, Italy;

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  • 正文语种 eng
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  • 关键词

    aerosols; pm10; air-quality maps; satellite pm retrieval; data assimilation; interpolation; seviri; modis; mountain region; aod; boundary layer;

    机译：气溶胶;pm10;空气质量图;卫星pm检索;数据同化;内插;seviri;modis;山地地区;od;边界层;

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