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利用机器学习和遥感技术估算 2001 年至 2018 年伊拉克和科威特的环境 PM。

Estimation of ambient PM in Iraq and Kuwait from 2001 to 2018 using machine learning and remote sensing.

机构信息

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston 02115, USA.

Pulmonary, Allergy, Sleep, and Critical Care Medicine Section, Medical Service, VA Boston Healthcare System, Boston, MA 02132, USA; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.

出版信息

Environ Int. 2021 Jun;151:106445. doi: 10.1016/j.envint.2021.106445. Epub 2021 Feb 19.

DOI:10.1016/j.envint.2021.106445
PMID:33618328
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8023768/
Abstract

Iraq and Kuwait are in a region of the world known to be impacted by high levels of fine particulate matter (PM) attributable to sources that include desert dust and ambient pollution, but historically have had limited pollution monitoring networks. The inability to assess PM concentrations have limited the assessment of the health impact of these exposures, both in the native populations and previously deployed military personnel. As part of a Department of Veterans Affairs Cooperative Studies Program health study of land-based U.S. military personnel who were previously deployed to these countries, we developed a novel approach to estimate spatially and temporarily resolved daily PM exposures 2001-2018. Since visibility is proportional to ground-level particulate matter concentrations, we were able to take advantage of extensive airport visibility data that became available as a result of regional military operations over this time period. First, we combined a random forest machine learning and a generalized additive mixed model to estimate daily high resolution (1 km × 1 km) visibility over the region using satellite-based aerosol optical depth (AOD) and airport visibility data. The spatially and temporarily resolved visibility data were then used to estimate PM concentrations from 2001 to 2018 by converting visibility to PM using empirical relationships derived from available regional PM monitoring stations. We adjusted for spatially resolved meteorological parameters, land use variables, including the Normalized Difference Vegetation Index, and satellite-derived estimates of surface dust as a measure of sandstorm activity. Cross validation indicated good model predictive ability (R = 0.71), and there were considerable spatial and temporal differences in PM across the region. Annual average PM predictions for Iraq and Kuwait were 37 and 41 μg/m, respectively, which are greater than current U.S. and WHO standards. PM concentrations in many U.S. bases and large cities (e.g. Bagdad, Balad, Kuwait city, Karbala, Najaf, and Diwaniya) had annual average PM concentrations above 45 μg/m with weekly averages as high as 150 μg/m depending on calendar year. The highest annual PM concentration for both Kuwait and Iraq were observed in 2008, followed by 2009, which was associated with extreme drought in these years. The lowest PM values were observed in 2014. On average, July had the highest concentrations, and November had the lowest values, consistent with seasonal patterns of air pollution in this region. This is the first study that estimates long-term PM exposures in Iraq and Kuwait at a high resolution based on measurements data that will allow the study of health effects and contribute to the development of regional environmental policies. The novel approach demonstrated may be used in other parts of the world with limited monitoring networks.

摘要

伊拉克和科威特位于世界上已知的细颗粒物(PM)水平较高的地区,这些颗粒物可归因于包括沙漠尘埃和环境污染物在内的多种来源,但历史上其污染监测网络十分有限。无法评估 PM 浓度限制了对这些暴露对当地居民和先前部署的军事人员健康影响的评估。作为退伍军人事务部合作研究计划健康研究的一部分,该研究针对曾部署到这些国家的陆基美国军事人员,我们开发了一种新方法来估算 2001 年至 2018 年期间的每日 PM 暴露情况,该方法具有空间和时间分辨率。由于能见度与地面颗粒物浓度成正比,因此我们能够利用该地区在此期间进行的区域军事行动产生的大量机场能见度数据。首先,我们结合随机森林机器学习和广义加性混合模型,利用基于卫星的气溶胶光学深度(AOD)和机场能见度数据来估算该地区的每日高分辨率(1km×1km)能见度。然后,通过将能见度转换为 PM,使用来自现有区域 PM 监测站的经验关系,将空间和时间分辨率的能见度数据估算为 2001 年至 2018 年的 PM 浓度。我们对空间分辨率气象参数、土地利用变量(包括归一化差异植被指数)和卫星衍生的地表尘埃估计值进行了调整,以此来衡量沙尘暴活动。交叉验证表明模型具有良好的预测能力(R=0.71),并且整个地区的 PM 存在很大的空间和时间差异。伊拉克和科威特的年平均 PM 预测值分别为 37 和 41μg/m,均高于当前的美国和世界卫生组织标准。许多美国基地和大城市(如巴格达、巴拉德、科威特市、卡尔巴拉、纳杰夫和迪瓦尼亚)的 PM 浓度年平均值高于 45μg/m,周平均值高达 150μg/m,具体取决于历年。科威特和伊拉克的最高年 PM 浓度均出现在 2008 年,其次是 2009 年,这与这些年份的极端干旱有关。PM 值最低的是在 2014 年。平均而言,7 月的浓度最高,11 月的浓度最低,这与该地区的空气污染季节性模式一致。这是第一项基于测量数据估算伊拉克和科威特长期 PM 暴露情况的研究,该研究将有助于研究健康影响,并为制定区域环境政策做出贡献。所展示的新方法可用于其他监测网络有限的世界其他地区。

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