Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan

被引:40
作者
Mehmood, Khalid [1 ]
Bao, Yansong [2 ,3 ]
Abrar, Muhammad Mohsin [4 ]
Petropoulos, George P. [5 ]
Saifullah [6 ]
Soban, Ahmad [7 ]
Saud, Shah [8 ]
Khan, Zalan Alam [9 ]
Khan, Shah Masud [10 ]
Fahad, Shah [11 ,12 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Sch Environm Sci & Engn, Nanjing 210044, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, CMA Key Lab Aerosol Cloud Precipitat, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing 210044, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Sch Atmospher Phys, Nanjing 210044, Peoples R China
[4] Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Natl Engn Lab Improving Qual Arable Land, Beijing 100081, Peoples R China
[5] Harokopio Univ Athens, Dept Geog, El Venizelou 70, Athens 17671, Greece
[6] Imam Abdulrahman Bin Faisal Univ, Coll Publ Hlth, Dept Environm Hlth, Dammam, Saudi Arabia
[7] Balochistan Univ Informat Technol Engn & Manageme, Software Engn Dept, Quetta, Pakistan
[8] Northeast Agr Univ, Dept Hort, Harbin, Peoples R China
[9] COMSATS Univ, Dept Civil Engn, Abbotabad 22010, Pakistan
[10] Univ Haripur, Dept Hort, Haripur 22620, Pakistan
[11] Hainan Univ, Coll Trop Crops, Hainan Key Lab Sustainable Utilizat Trop Bioresou, Haikou 570228, Hainan, Peoples R China
[12] Univ Haripur, Dept Agron, Khyber Pakhtunkhwa 21120, Pakistan
基金
中国国家自然科学基金;
关键词
COVID-19; PM2.5; Climate factors; GLM model; Correlation; GRA; Geoinformation; PARTICULATE MATTER;
D O I
10.1016/j.chemosphere.2021.129584
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Information on the spatiotemporal variability of respirable suspended particulate pollutant matter concentrations, especially of particles having size of 2.5 mu m and climate are the important factors in relation to emerging COVID-19 cases around the world. This study aims at examining the association between COVID-19 cases, air pollution, climatic and socioeconomic factors using geospatial techniques in three provincial capital cities and the federal capital city of Pakistan. A series of relevant data was acquired from 3 out of 4 provinces of Pakistan (Punjab, Sindh, Khyber Pakhtunkhwa (KPK) including the daily numbers of COVID-19 cases, PM2.5 concentration (mu gm(-3)), a climatic factors including temperature (degrees F), wind speed (m/s), humidity (%), dew point (%), and pressure (Hg) from June 1 2020, to July 31 2020. Further, the possible relationships between population density and COVID-19 cases was determined. The generalized linear model (GLM) was employed to quantify the effect of PM2.5, temperature, dew point, humidity, wind speed, and pressure range on the daily COVID-19 cases. The grey relational analysis (GRA) was also implemented to examine the changes in COVID-19 cases with PM2.5 concentrations for the provincial city Lahore. About 1,92, 819 COVID-19 cases were reported in Punjab, Sindh, KPK, and Islamabad during the study period. Results indicated a significant relationship between COVID-19 cases and PM2.5 and climatic factors at p < 0.05 except for Lahore in case of humidity (r = 0.175). However, mixed correlations existed across Lahore, Karachi, Peshawar, and Islamabad. The R-2 value indicates a moderate relationship between COVID-19 and population density. Findings of this study, although are preliminary, offers the first line of evidence for epidemiologists and may assist the local community to expedient for the growth of effective COVID-19 infection and health risk management guidelines. This remains to be seen. (C) 2021 Elsevier Ltd. All rights reserved.
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页数:11
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