Pollution hot spots and the impact of drive-through COVID-19 testing sites on urban air quality

D. Mendoza, T. Benney, Casey S. Olson, E. Crosman, Shawn A Gonzales, Mamta Chaudhari, Corbin Anderson
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Abstract

To be successful, commitments to climate change and environmental policy will require critical changes in human behavior and one important example is driving and idling. Idling is defined as running a vehicle’s motor while not in motion. Idling studies have repeatedly demonstrated that this behavior is costly, harmful to human health, and highly polluting. However, with the onset of COVID-19, the use of drive-through services to provide food, pharmaceuticals, and medical testing has increased. To understand this phenomenon further, we worked cooperatively with our government partners to compare the concentrations of PM2.5 at three regulatory sensor locations with nearby drive-through COVID-19 testing sites during average to elevated pollution days. Salt Lake City, UT (USA), where this study was undertaken, has seen a dramatic rise in drive-through services since the onset of the pandemic and community concern is also high due to poor local air quality. More importantly, the Salt Lake Valley is home to one of the largest research grade air quality networks in the world. Fine particulate matter sensors were installed or already in place at or adjacent to COVID-19 testing sites in the area, and we used data from nearby Utah Division of Air Quality monitors to provide comparative PM2.5 concentrations. Due to their placement (e.g., further distance from large roads and other emitting sources), we found that testing sites showed lower PM2.5 concentrations during average air quality days despite increased idling rates. However, when urban pollution rates were elevated due to atmospheric inversions, extensive idling around testing sites led to hyper local PM2.5 concentrations or pollution hot spots. This suggests that idling has serious compounding effects in highly polluted urban areas and policies minimizing vehicle emissions from idling and congestion could conceivably curtail pollutant exposure in a range of settings.
污染热点及驾车穿越新冠肺炎检测点对城市空气质量的影响
要想取得成功,对气候变化和环境政策的承诺将需要人类行为的重大改变,一个重要的例子就是开车和空转。空转是指在不运动的情况下运行车辆的电机。空转研究一再表明,这种行为代价高昂,对人类健康有害,污染严重。然而,随着新冠肺炎的爆发,提供食品、药品和医学检测的驾车服务的使用有所增加。为了进一步了解这一现象,我们与政府合作伙伴合作,在平均污染日至高污染日期间,将三个监管传感器位置的PM2.5浓度与附近的驾车穿越新冠肺炎检测点进行了比较。进行这项研究的犹他州盐湖城(美国)自疫情爆发以来,免下车服务急剧增加,由于当地空气质量差,社区也高度关注。更重要的是,盐湖谷拥有世界上最大的研究级空气质量网络之一。在该地区的新冠肺炎检测点或附近安装或已经安装了细颗粒物传感器,我们使用附近犹他州空气质量监测部门的数据来提供PM2.5的比较浓度。由于它们的位置(例如,距离大型道路和其他排放源更远),我们发现,尽管怠速率增加,但在平均空气质量天数内,测试点的PM2.5浓度较低。然而,当城市污染率因大气逆温而上升时,测试点周围的大量闲置会导致PM2.5浓度或污染热点过高。这表明,在污染严重的城市地区,怠速具有严重的复合效应,而将怠速和拥堵造成的车辆排放降至最低的政策可以在一系列环境中减少污染物暴露。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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