No one knows which city has the highest concentration of fine particulate matter
No one knows which city has the highest concentration of fine particulate matter
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DOI：
10.1016/j.aeaoa.2019.100040
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发表时间：
2019-07-01
影响因子：
4.6
通讯作者：
Dey, Sagnik
中科院分区：
文献类型：
--
作者：
Martin, Randall, V;Brauer, Michael;Dey, Sagnik
暴露在环境中的细颗粒物(PM2.5)是导致死亡和疾病负担的主要全球环境风险因素，每年全球相关福利成本高达数万亿美元。考察的是当前数据回答有关PM2.5的一个基本问题的能力，即PM2.5浓度最高的城市的位置。回答这一基本问题的能力是评估全球人类暴露于空气污染的科学进步的一个指标，也是减少其影响的努力的一个重要组成部分。尽管PM2.5很重要，但我们发现没有足够的监测数据来回答这个关于全球范围内PM2.5空间格局的基本问题。在234个国家中，只有24个国家的每百万居民拥有3个以上的监测仪，而世界上绝大多数国家的密度要低一个数量级，141个国家根本没有定期监测PM2.5。全球人口到最近的PM2.5监测仪的平均距离为220公里，太大了，无法进行暴露评估。用卫星遥感、化学品运输模型和统计模型的估计来填补监测空白的努力，在个别监测地点存在偏差，可超过50微克米(-3)。在推进有关PM2.5全球分布的知识方面取得进展，将需要一个统一的网络，将不同类型的监测设备(监管网络、低成本监测仪、卫星遥感和研究级仪器)与大气和统计模型结合起来。实现这一综合框架将有助于准确识别PM2.5浓度最高的城市的位置，并在跟踪减少全球空气污染影响的工作进展方面发挥关键作用。
Exposure to ambient fine particulate matter (PM2.5) is the leading global environmental risk factor for mortality and disease burden, with associated annual global welfare costs of trillions of dollars. Examined within is the ability of current data to answer a basic question about PM2.5, namely the location of the city with the highest PM2.5 concentration. The ability to answer this basic question serves as an indicator of scientific progress to assess global human exposure to air pollution and as an important component of efforts to reduce its impacts. Despite the importance of PM2.5, we find that insufficient monitoring data exist to answer this basic question about the spatial pattern of PM2.5 at the global scale. Only 24 of 234 countries have more than 3 monitors per million inhabitants, while density is an order of magnitude lower in the vast majority of the world's countries, with 141 having no regular PM2.5 monitoring at all. The global mean population distance to nearest PM2.5 monitor is 220 km, too large for exposure assessment. Efforts to fill in monitoring gaps with estimates from satellite remote sensing, chemical transport modeling, and statistical models have biases at individual monitor locations that can exceed 50 mu g m(-3). Progress in advancing knowledge about the global distribution of PM2.5 will require a harmonized network that integrates different types of monitoring equipment (regulatory networks, low-cost monitors, satellite remote sensing, and research-grade instrumentation) with atmospheric and statistical models. Realization of such an integrated framework will facilitate accurate identification of the location of the city with the highest PM2.5 concentration and play a key role in tracking the progress of efforts to reduce the global impacts of air pollution.