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GIS based assessment of the spatial representativeness of air quality monitoring stations using pollutant emissions data

机译:使用污染物排放数据的基于GIS的空气质量监测站空间代表性评估

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摘要

Spatial representativeness of air quality monitoring stations is a critical parameter when choosing location of sites and assessing effects on population to long term exposure to air pollution. According to literature, the spatial representativeness of a monitoring site is related to the variability of pollutants concentrations around the site. As the spatial distribution of primary pollutants concentration is strongly correlated to the allocation of corresponding emissions, in this work a methodology is presented to preliminarily assess spatial representativeness of a monitoring site by analysing the spatial variation of emissions around it. An analysis of horizontal variability of several pollutants emissions was carried out by means of Geographic Information System using a neighbourhood statistic function; the rationale is that if the variability of emissions around a site is low, the spatial representativeness of this site is high consequently. The methodology was applied to detect spatial representativeness of selected Italian monitoring stations, located in Northern and Central Italy and classified as urban background or rural background. Spatialized emission data produced by the national air quality model MINNI, covering entire Italian territory at spatial resolution of 4 × 4 km~2, were processed and analysed. The methodology has shown significant capability for quick detection of areas with highest emission variability. This approach could be useful to plan new monitoring networks and to approximately estimate horizontal spatial representativeness of existing monitoring sites. Major constraints arise from the limited spatial resolution of the analysis, controlled by the resolution of the emission input data, cell size of 4 × 4 km~2, and from the applicability to primary pollutants only.
机译:在选择场所的位置并评估长期暴露于空气污染对人口的影响时,空气质量监测站的空间代表性是一个关键参数。根据文献,监测站点的空间代表性与站点周围污染物浓度的变化有关。由于主要污染物浓度的空间分布与相应排放的分配密切相关,因此在本工作中,提出了一种方法,通过分析其周围排放的空间变化来初步评估监测站点的空间代表性。利用邻域统计函数的地理信息系统对几种污染物排放的水平变化进行了分析;其理由是,如果站点周围的排放变化率较低,则该站点的空间代表性较高。该方法用于检测位于意大利北部和中部并分类为城市背景或农村背景的选定意大利监测站的空间代表性。处理并分析了由国家空气质量模型MINNI产生的空间排放数据,其空间分辨率为4×4 km〜2,覆盖了整个意大利领土。该方法已显示出快速检测具有最高发射变化率的区域的强大能力。这种方法对于计划新的监视网络和大约估算现有监视站点的水平空间代表性很有用。主要的限制来自于有限的分析空间分辨率,受排放输入数据分辨率,4×4 km〜2的像元大小控制以及仅适用于主要污染物。

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  • 来源
    《Atmospheric environment》 |2014年第11期|121-129|共9页
  • 作者单位

    ENEA - National Agency for New Technologies, Energy and Sustainable Economic Development, Via Martiri di Monte Sole 4, 40129 Bologna, Italy;

    ENEA - National Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy;

    ENEA - National Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy;

    ENEA - National Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy;

    ENEA - National Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy;

    ENEA - National Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy;

    ENEA - National Agency for New Technologies, Energy and Sustainable Economic Development, Bologna, Italy;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Air pollution; Emissions; Monitoring networks; Spatial representativeness; GIS;

    机译:空气污染;排放物;监测网络;空间代表性;地理信息系统;

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