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首页> 外文期刊>International Journal of Environmental Research and Public Health >Geospatial Interpolation and Mapping of Tropospheric Ozone Pollution Using Geostatistics
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Geospatial Interpolation and Mapping of Tropospheric Ozone Pollution Using Geostatistics

机译：利用地统计法对流层臭氧污染进行地理空间内插和制图

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Tropospheric ozone (O3) pollution is a major problem worldwide, including in the United States of America (USA), particularly during the summer months. Ozone oxidative capacity and its impact on human health have attracted the attention of the scientific community. In the USA, sparse spatial observations for O3 may not provide a reliable source of data over a geo-environmental region. Geostatistical Analyst in ArcGIS has the capability to interpolate values in unmonitored geo-spaces of interest. In this study of eastern Texas O3 pollution, hourly episodes for spring and summer 2012 were selectively identified. To visualize the O3 distribution, geostatistical techniques were employed in ArcMap. Using ordinary Kriging, geostatistical layers of O3 for all the studied hours were predicted and mapped at a spatial resolution of 1 kilometer. A decent level of prediction accuracy was achieved and was confirmed from cross-validation results. The mean prediction error was close to 0, the root mean-standardized-prediction error was close to 1, and the root mean square and average standard errors were small. O3 pollution map data can be further used in analysis and modeling studies. Kriging results and O3 decadal trends indicate that the populace in Houston-Sugar Land-Baytown, Dallas-Fort Worth-Arlington, Beaumont-Port Arthur, San Antonio, and Longview are repeatedly exposed to high levels of O3-related pollution, and are prone to the corresponding respiratory and cardiovascular health effects. Optimization of the monitoring network proves to be an added advantage for the accurate prediction of exposure levels.
机译：对流层臭氧（O3）污染是全世界的主要问题，包括在美国（USA），尤其是在夏季。臭氧的氧化能力及其对人体健康的影响引起了科学界的关注。在美国，对O3的稀疏空间观测可能无法提供地理环境区域上可靠的数据来源。 ArcGIS中的Geostatistical Analyst能够对感兴趣的不受监视的地理空间中的值进行插值。在这项对德克萨斯州东部O3污染的研究中，有选择地确定了2012年春季和夏季的每小时事件。为了可视化O3的分布，ArcMap中采用了地统计技术。使用普通克里格法，可以预测并预测所有研究小时内O3的地统计层，并将其映射为1公里的空间分辨率。达到了不错的预测准确性，并从交叉验证结果中得到了证实。平均预测误差接近0，均方根标准化预测误差接近1，均方根误差和平均标准误差均较小。 O3污染图数据可进一步用于分析和建模研究。克里金法结果和O3年代际趋势表明，休斯顿-糖土地-贝敦，达拉斯-沃思堡-阿灵顿，博蒙特-亚瑟港，圣安东尼奥和朗维尤的居民反复遭受高水平的O3相关污染，并且容易发生对相应的呼吸和心血管健康有影响。事实证明，监控网络的优化是准确预测暴露水平的另一个优势。

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