Kant Rahul, Trivedi Avani, Ghadai Bibhutimaya, Kumar Vinod, Mallik Chinmay
Department of Atmospheric Science, Central University of Rajasthan, Ajmer, 305801, India.
Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128, Mainz, Germany.
Environ Monit Assess. 2022 Mar 14;194(4):274. doi: 10.1007/s10661-022-09932-7.
Most of the published articles which document changes in atmospheric compositions during the various lockdown and unlock phases of COVID-19 pandemic have made a direct comparison to a reference point (which may be 1 year apart) for attribution of the COVID-mediated lockdown impact on atmospheric composition. In the present study, we offer a better attribution of the lockdown impacts by also considering the effect of meteorology and seasonality. We decrease the temporal distance between the impacted and reference points by considering the difference of adjacent periods first and then comparing the impacted point to the mean of several reference points in the previous years. Additionally, we conduct a multi-station analysis to get a holistic effect of the different climatic and emission regimes. In several places in eastern and coastal India, the seasonally induced changes already pointed to a decrease in PM concentrations based on the previous year data; hence, the actual decrease due to lockdown would be much less than that observed just on the basis of difference of concentrations between subsequent periods. In contrast, northern Indian stations would normally show an increase in PM concentration at the time of the year when lockdown was effected; hence, actual lockdown-induced change would be in surplus of the observed change. The impact of wind-borne transport of pollutants to the study sites dominates over the dilution effects. Box model simulations point to a VOC-sensitive composition.
大多数已发表的文章记录了新冠疫情不同封锁和解封阶段大气成分的变化,并将其与一个参考点(可能相隔1年)进行直接比较,以确定新冠疫情介导的封锁对大气成分的影响。在本研究中,我们还考虑了气象学和季节性的影响,从而对封锁的影响进行了更好的归因。我们首先考虑相邻时期的差异,然后将受影响点与前几年几个参考点的平均值进行比较,从而缩短受影响点与参考点之间的时间间隔。此外,我们进行了多站点分析,以全面了解不同气候和排放状况的影响。在印度东部和沿海的几个地方,根据上一年的数据,季节性变化已经表明PM浓度有所下降;因此,封锁导致的实际下降幅度将远小于仅根据后续时期浓度差异所观察到的降幅。相比之下,印度北部的监测站通常会在实施封锁的一年中的那个时候出现PM浓度上升的情况;因此,封锁实际导致的变化将超过所观察到的变化。污染物通过风力传输到研究地点的影响超过了稀释作用。箱式模型模拟表明存在对挥发性有机化合物敏感的成分。