The coronavirus pandemic (COVID-19) has impacted the usual global movement patterns, atmospheric pollutants, and climatic parameters. The current study sought to assess the impact of the COVID-19 lockdown on urban mobility, atmospheric pollutants, and Pakistan’s climate. For the air pollution assessment, total column ozone (O₃), sulphur dioxide (SO₂), and tropospheric column nitrogen dioxide (NO₂) data from the Ozone Monitoring Instrument (OMI), aerosol optical depth (AOD) data from the Multi-angle Imaging Spectroradiometer (MISR), and dust column mass density (PM_2.5) data from the MERRA-2 satellite were used. Furthermore, these datasets are linked to climatic parameters (temperature, precipitation, wind speed). The Kruskal–Wallis H test (KWt) is used to compare medians among k groups (k > 2), and the Wilcoxon signed-rank sum test (WRST) is for analyzing the differences between the medians of two datasets. To make the analysis more effective, and to justify that the variations in air quality parameters are due to the COVID-19 pandemic, a Generalized Linear Model (GLM) was used. The findings revealed that the limitations on human mobility have lowered emissions, which has improved the air quality in Pakistan. The results of the study showed that the climatic parameters (precipitation, T_max, T_min, and T_mean) have a positive correlation and wind speed has a negative correlation with NO₂ and AOD. This study found a significant decrease in air pollutants (NO₂, SO₂, O₃, AOD) of 30–40% in Pakistan during the strict lockdown period. In this duration, the highest drop of about 28% in NO₂ concentrations has been found in Karachi. Total column O₃ did not show any reduction during the strict lockdown, but a minor decline was depicted as 0.38% in Lahore and 0.55% in Islamabad during the loosening lockdown. During strict lockdown, AOD was reduced up to 23% in Islamabad and 14.46% in Lahore. The results of KWt and WRST evident that all the mobility indices are significant (p < 0.05) in nature. The GLM justified that restraining human activities during the lockdown has decreased anthropogenic emissions and, as a result, improved air quality, particularly in metropolitan areas.

中文翻译：

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巴基斯坦城市交通状况：具有气候风险认知的 COVID-19 封锁之前、期间和之后

冠状病毒大流行 (COVID-19) 影响了通常的全球运动模式、大气污染物和气候参数。目前的研究旨在评估 COVID-19 封锁对城市交通、大气污染物和巴基斯坦气候的影响。对于空气污染评估，来自臭氧监测仪器 (OMI) 的总柱状臭氧 (O ₃ )、二氧化硫 (SO ₂ ) 和对流层柱状二氧化氮 (NO ₂ ) 数据，以及来自 Multi -角成像光谱仪 (MISR) 和尘柱质量密度 (PM _2.5) 来自 MERRA-2 卫星的数据被使用。此外，这些数据集与气候参数（温度、降水、风速）相关联。Kruskal–Wallis H 检验 (KWt) 用于比较 k 组 (k > 2) 之间的中位数，Wilcoxon 符号秩和检验 (WRST) 用于分析两个数据集的中位数之间的差异。为了使分析更有效，并证明空气质量参数的变化是由 COVID-19 大流行引起的，我们使用了广义线性模型 (GLM)。调查结果显示，人类流动的限制降低了排放，从而改善了巴基斯坦的空气质量。研究结果表明，气候参数（降水量、T _max、T _min和 T _mean) 呈正相关，风速与 NO ₂和 AOD呈负相关。这项研究发现，在严格的封锁期间，巴基斯坦的空气污染物（NO ₂、SO ₂、O ₃、AOD）显着减少了 30-40%。在此期间，卡拉奇的NO ₂浓度下降幅度最大，约为 28% 。在严格封锁期间，总 O ₃列没有显示任何减少，但在放松封锁期间，拉合尔和伊斯兰堡分别出现了 0.38% 和 0.55% 的小幅下降。在严格的封锁期间，伊斯兰堡的 AOD 减少了 23%，拉合尔的 AOD 减少了 14.46%。KWt 和 WRST 的结果表明所有的流动性指标都是显着的（p< 0.05) 本质上。GLM 认为，在封锁期间限制人类活动减少了人为排放，从而改善了空气质量，尤其是在大都市地区。