Situation of Urban Mobility in Pakistan: Before, during, and after the COVID-19 Lockdown with Climatic Risk Perceptions

被引:8
作者
Syed, Alishbah [1 ,2 ,3 ]
Zhang, Jiquan [1 ,2 ,3 ]
Moniruzzaman, Md [4 ]
Rousta, Iman [5 ,6 ,7 ]
Omer, Talha [8 ]
Ying, Guo [1 ,2 ,3 ]
Olafsson, Haraldur [7 ,9 ]
机构
[1] Northeast Normal Univ, Inst Nat Disaster Res, Sch Environm Sci, Changchun 130024, Peoples R China
[2] Northeast Normal Univ, State Environm Protect Key Lab Wetland Ecol & Veg, Changchun 130024, Peoples R China
[3] Minist Educ, Key Lab Vegetat Ecol, Changchun 130024, Peoples R China
[4] Spatial Business Integrat GmbH SBI, Dept Agr, Marienburgstr 27, D-64297 Darmstadt, Germany
[5] Yazd Univ, Dept Geog, Yazd 8915818411, Iran
[6] Univ Iceland, Inst Atmospher Sci & Climate, Bustadavegur 7, IS-108 Reykjavik, Iceland
[7] Iceland Meteorol Off IMO, Bustadavegur 7, IS-108 Reykjavik, Iceland
[8] Jonkoping Univ, Jonkoping Int Business Sch, Dept Econ Finance & Stat, Gjuterigatan 5, S-55318 Jonkoping, Sweden
[9] Univ Iceland, Inst Atmospher Sci Weather & Climate, Dept Phys, Bustadavegur 7, IS-108 Reykjavik, Iceland
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
urban mobility; COVID-19; lockdown; O-3; NO2; PM2.5; SO2; AOD; climate parameters; air pollution; GLM; AIR-POLLUTION; METEOROLOGICAL CONDITIONS; PARTICULATE MATTER; TRENDS; IMPACT; PM2.5; PARIS; REDUCTION; QUALITY; PUNJAB;
D O I
10.3390/atmos12091190
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 (O-3), 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 (PM2.5) 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, O-3, 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 O-3 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.
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页数:19
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