Literature DB >> 35582473

The Environmental Story During the COVID-19 Lockdown: How Human Activities Affect PM2.5 Concentration in China?

Zhenyu Tan1, Xinghua Li2, Meiling Gao3, Liangcun Jiang2.   

Abstract

At the end of 2019, the very first COVID-19 coronavirus infection was reported and then it spread across the world just like wildfires. From late January to March 2020, most cities and villages in China were locked down, and consequently, human activities decreased dramatically. This letter presents an "offline learning and online inference" approach to explore the variation of PM2.5 pollution during this period. In the experiments, a deep regression model was trained to establish the complex relationship between remote sensing data and in situ PM2.5 observations, and then the spatially continuous monthly PM2.5 distribution map was simulated using the Google Earth Engine platform. The results reveal that the COVID-19 lockdown truly decreased the PM2.5 pollution with certain hysteresis and the fine particle pollution begins to increase when advancing resumption of work and production gradually.

Entities:  

Keywords:  Absorbing Aerosol Index (AAI); Aerosol Optical Depth (AOD); COVID-19; Google Earth Engine (GEE); PM25; deep learning; remote sensing

Year:  2020        PMID: 35582473      PMCID: PMC8843045          DOI: 10.1109/LGRS.2020.3040435

Source DB:  PubMed          Journal:  IEEE Geosci Remote Sens Lett        ISSN: 1545-598X            Impact factor:   3.966


  16 in total

1.  Impact of urbanization level on urban air quality: a case of fine particles (PM(2.5)) in Chinese cities.

Authors:  Lijian Han; Weiqi Zhou; Weifeng Li; Li Li
Journal:  Environ Pollut       Date:  2014-08-09       Impact factor: 8.071

2.  Spatiotemporal characteristics of aerosols and their trends over mainland China with the recent Collection 6 MODIS and OMI satellite datasets.

Authors:  Kang Hu; Kanike Raghavendra Kumar; Na Kang; Richard Boiyo; Jinwen Wu
Journal:  Environ Sci Pollut Res Int       Date:  2017-12-22       Impact factor: 4.223

3.  Health burden attributable to ambient PM2.5 in China.

Authors:  Congbo Song; Jianjun He; Lin Wu; Taosheng Jin; Xi Chen; Ruipeng Li; Peipei Ren; Li Zhang; Hongjun Mao
Journal:  Environ Pollut       Date:  2017-02-03       Impact factor: 8.071

4.  Comparative PM10-PM2.5 source contribution study at rural, urban and industrial sites during PM episodes in Eastern Spain.

Authors:  Sergio Rodríguez; Xavier Querol; Andrés Alastuey; María-Mar Viana; Marta Alarcón; Enrique Mantilla; C R Ruiz
Journal:  Sci Total Environ       Date:  2004-07-26       Impact factor: 7.963

5.  Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study.

Authors:  Nanshan Chen; Min Zhou; Xuan Dong; Jieming Qu; Fengyun Gong; Yang Han; Yang Qiu; Jingli Wang; Ying Liu; Yuan Wei; Jia'an Xia; Ting Yu; Xinxin Zhang; Li Zhang
Journal:  Lancet       Date:  2020-01-30       Impact factor: 79.321

6.  Improving satellite-based PM2.5 estimates in China using Gaussian processes modeling in a Bayesian hierarchical setting.

Authors:  Wenxi Yu; Yang Liu; Zongwei Ma; Jun Bi
Journal:  Sci Rep       Date:  2017-08-01       Impact factor: 4.379

7.  A Deep CNN-LSTM Model for Particulate Matter (PM2.5) Forecasting in Smart Cities.

Authors:  Chiou-Jye Huang; Ping-Huan Kuo
Journal:  Sensors (Basel)       Date:  2018-07-10       Impact factor: 3.576

8.  Real estimates of mortality following COVID-19 infection.

Authors:  David Baud; Xiaolong Qi; Karin Nielsen-Saines; Didier Musso; Léo Pomar; Guillaume Favre
Journal:  Lancet Infect Dis       Date:  2020-03-12       Impact factor: 25.071

9.  Decline in PM2.5 concentrations over major cities around the world associated with COVID-19.

Authors:  Akshansha Chauhan; Ramesh P Singh
Journal:  Environ Res       Date:  2020-05-05       Impact factor: 6.498

Review 10.  COVID-19 and Italy: what next?

Authors:  Andrea Remuzzi; Giuseppe Remuzzi
Journal:  Lancet       Date:  2020-03-13       Impact factor: 79.321

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  2 in total

Review 1.  A review of GIS methodologies to analyze the dynamics of COVID-19 in the second half of 2020.

Authors:  Ivan Franch-Pardo; Michael R Desjardins; Isabel Barea-Navarro; Artemi Cerdà
Journal:  Trans GIS       Date:  2021-07-11

2.  Classifier Fusion for Detection of COVID-19 from CT Scans.

Authors:  Taranjit Kaur; Tapan Kumar Gandhi
Journal:  Circuits Syst Signal Process       Date:  2022-01-03       Impact factor: 2.311

  2 in total

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