Mobile Monitoring of Air Pollution Reveals Spatial and Temporal Variation in an Urban Landscape
Mobile Monitoring of Air Pollution Reveals Spatial and Temporal Variation in an Urban Landscape
复制标题
DOI：
10.3389/fbuil.2021.648620
复制
发表时间：
2021-05-04
影响因子：
3
通讯作者：
Kremer, Peleg
中科院分区：
文献类型：
--
作者：
Cummings, Lucas E.;Stewart, Justin D.;Kremer, Peleg
城市空气污染对人类健康构成重大威胁。了解城市空气污染物浓度在何时何地达到峰值，对于有效的空气质量管理和可持续城市发展至关重要。为此，我们实施了一种移动的监测方法来确定宾夕法尼亚州费城各地颗粒物（PM）和黑碳（BC）的时空分布，并使用热点分析和热图来确定污染物浓度最高的时间和位置。在2019年6月27日至7月29日的12天内，我们连续测量了两条150英里（241.4公里）长的路线上的空气污染浓度。日平均浓度分别为11.55 +/- 5.34 μ g/m3（PM 1）、13.48 +/- 5.59 μ g/m3（PM2.5）、16.13 +/- 5.80 μ g/m3（PM10）和1.56 +/- 0.39 μ g/m3（BC）。我们发现，细颗粒物的大小部分（PM2.5）构成约84%的PM10和BC包括11.6%的观察到的PM2.5。空气污染热点在三个大小部分的PM（PM 1，PM2.5和PM10）和BC有类似的分布在整个费城，但最普遍的是在北特拉华州，河病房，和北部规划区。在整个数据收集期间发现的多个检测到的热点（30.19%）发生在上午8：00-上午9：00之间。
Urban air pollution poses a major threat to human health. Understanding where and when urban air pollutant concentrations peak is essential for effective air quality management and sustainable urban development. To this end, we implement a mobile monitoring methodology to determine the spatiotemporal distribution of particulate matter (PM) and black carbon (BC) throughout Philadelphia, Pennsylvania and use hot spot analysis and heatmaps to determine times and locations where pollutant concentrations are highest. Over the course of 12 days between June 27 and July 29, 2019, we measured air pollution concentrations continuously across two 150 mile (241.4 km) long routes. Average daily mean concentrations were 11.55 +/- 5.34 mu g/m(3) (PM1), 13.48 +/- 5.59 mu g/m(3) (PM2.5), 16.13 +/- 5.80 mu g/m(3) (PM10), and 1.56 +/- 0.39 mu g/m(3) (BC). We find that fine PM size fractions (PM2.5) constitute approximately 84% of PM10 and that BC comprises 11.6% of observed PM2.5. Air pollution hotspots across three size fractions of PM (PM1, PM2.5, and PM10) and BC had similar distributions throughout Philadelphia, but were most prevalent in the North Delaware, River Wards, and North planning districts. A plurality of detected hotspots found throughout the data collection period (30.19%) occurred between the hours of 8:00 AM-9:00 AM.