[论文解读] Changes in air quality and human mobility in the U.S. during the COVID-19 pandemic

Cristina L. Archer, Guido Cervone+3 more|arXiv (Cornell University)|Jun 27, 2020

COVID-19 impact on air quality参考文献 22被引用 5

一句话总结

本研究利用地面监测与卫星数据，分析了新冠疫情爆发期间美国空气质量与人类活动模式的变化，结果显示NO₂浓度显著下降（最高下降8 ppb，平均下降2 ppb），与活动减少密切相关；而PM₂.₅水平则基本保持不变。关键发现为：乘用车数量减少导致NO₂下降，但柴油动力的货运车辆与发电厂持续排放PM₂.₅。

ABSTRACT

The first goal of this study is to quantify the magnitude and spatial variability of air quality changes in the US during the COVID-19 pandemic. We focus on two federally regulated pollutants, nitrogen dioxide (NO2), and fine particulate matter (PM2.5). Observed concentrations at all available ground monitoring sites (240 and 480 for NO2 and PM2.5, respectively) were compared between April 2020 and April of the prior five years, 2015-2019, as the baseline. Large statistically significant decreases in NO2 concentrations were found at more than 65% of the monitoring sites, with an average drop of 2 ppb when compared to the mean of the previous five years. The same patterns are confirmed by satellite-derived NO2 column totals from NASA OMI. PM2.5 concentrations from the ground monitoring sites, however, were more likely to be higher. The second goal of this study is to explain the different responses of the two pollutants during the COVID-19 pandemic. The hypothesis put forward is that the shelter-in-place measures affected peoples' driving patterns most dramatically, thus passenger vehicle NO2 emissions were reduced. Commercial vehicles and electricity demand for all purposes remained relatively unchanged, thus PM2.5 concentrations did not drop significantly. To establish a correlation between the observed NO2 changes and the extent to which people were sheltering in place, we use a mobility index, which was produced and made public by Descartes Labs. This mobility index aggregates cell phone usage at the county level to capture changes in human movement over time. We found a strong correlation between the observed decreases in NO2 concentrations and decreases in human mobility. By contrast, no discernible pattern was detected between mobility and PM2.5 concentrations changes, suggesting that decreases in personal-vehicle traffic alone may not be effective at reducing PM2.5 pollution.

研究动机与目标

• 量化2020年4月与2015–2019年同期相比，美国NO₂与PM₂.₅浓度在空间与时间上的变化。
• 探究尽管广泛实施活动限制，为何NO₂显著下降而PM₂.₅未发生明显变化。
• 分析观测到的空气污染变化与疫情期间实际人类活动模式之间的相关性。
• 评估将活动数据用作排放变化与污染响应代理指标的局限性。

提出的方法

• 将2020年4月的地面监测站数据（NO₂为240个站点，PM₂.₅为480个站点）与2015–2019年4月的平均值进行比较，以量化污染变化。
• 利用NASA OMI提供的卫星反演NO₂柱浓度数据，验证地面测量结果并评估全国趋势。
• 采用Descartes Labs提供的基于匿名手机定位数据的县级活动指数，代表人类活动的变化。
• 在县一级层面，将NO₂与PM₂.₅浓度的变化与活动减少情况进行相关性分析，以评估因果关系。
• 分析污染与活动变化的空间模式，识别热点区域与区域差异。
• 提出假设：柴油车排放与发电厂活动是尽管乘用车流量减少但PM₂.₅水平仍持续存在的主要原因。

实验结果

研究问题

• RQ1 与2015–2019年同期相比，2020年4月美国NO₂与PM₂.₅浓度变化程度如何？
• RQ2 疫情爆发期间NO₂浓度变化与人类活动减少之间的相关性有多强？
• RQ3 尽管乘用车流量显著减少，为何PM₂.₅浓度基本保持不变？
• RQ4 活动模式在多大程度上能够解释美国不同县NO₂与PM₂.₅污染的差异？
• RQ5 尽管活动减少，疫情期间维持PM₂.₅水平的主要排放源是什么？

主要发现

• 2020年4月，美国监测站点NO₂浓度显著下降，与2015–2019年平均值相比，平均降幅达2 ppb。
• 卫星数据显示，2020年4月全国对流层NO₂柱浓度平均较前五年下降13%。
• 在活动减少至接近零的县，NO₂降幅最大（最高达8 ppb），且活动减少与污染下降之间存在直接的非线性相关性。
• 超过65%的NO₂监测站点显示显著下降，尤其在东北部与加利福尼亚等活动减少程度高的区域。
• 2020年4月PM₂.₅浓度未出现显著下降，且在约20%的监测站点中甚至高于往年。
• 未发现人类活动变化与PM₂.₅浓度变化之间存在明显相关性，表明仅减少乘用车流量不足以降低PM₂.₅水平。