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      Assessing the change of ambient air quality patterns in Jiangsu Province of China pre-to post-COVID-19

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          Abstract

          Following the outbreak of the novel coronavirus in early 2020, to effectively prevent the spread of the disease, major cities across China suspended work and production. While the rest of the world struggles to control COVID-19, China has managed to control the pandemic rapidly and effectively with strong lockdown policies. This study investigates the change in air pollution (focusing on the air quality index (AQI), six ambient air pollutants nitrogen dioxide (NO 2), ozone (O 3), sulphur dioxide (SO 2), carbon monoxide (CO), particulate matter with aerodynamic diameters ≤10 μm (PM 10) and ≤2.5 μm (PM 2.5)) patterns for three periods: pre-COVID (from 1 January to May 30, 2019), active COVID (from 1 January to May 30, 2020) and post-COVID (from 1 January to May 30, 2021) in the Jiangsu province of China. Our findings reveal that the change in air pollution from pre-COVID to active COVID was greater than in previous years due to the government's lockdown policies. Post-COVID, air pollutant concentration is increasing. Mean change PM 2.5 from pre-COVID to active COVID decreased by 18%; post-COVID it has only decreased by 2%. PM 10 decreased by 19% from pre-COVID to active COVID, but post-COVID pollutant concentration has seen a 23% increase. Air pollutants show a positive correlation with COVID-19 cases among which PM 2.5, PM 10 and NO 2 show a strong correlation during active COVID-19 cases. Metrological factors such as minimum temperature, average temperature and humidity show a positive correlation with COVID-19 cases while maximum temperature, wind speed and air pressure show no strong positive correlation. Although the COVID-19 pandemic had numerous negative effects on human health and the global economy, the reduction in air pollution and significant improvement in ambient air quality likely had substantial short-term health benefits; the government must implement policies to control post-COVID environmental issues.

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          An interactive web-based dashboard to track COVID-19 in real time

          Ensheng Dong, Hongru Du, Lauren Gardner (2020)
          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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            The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak

            Matteo Chinazzi, Jessica Davis, Marco Ajelli … (2020)
            Motivated by the rapid spread of COVID-19 in Mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated based on internationally reported cases, and shows that at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in Mainland China, but has a more marked effect at the international scale, where case importations were reduced by nearly 80% until mid February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.
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              A review on the human health impact of airborne particulate matter.

              Ki-Hyun Kim, Ehsanul Kabir, Shamin Kabir (2015)
              Particulate matter (PM) is a key indicator of air pollution brought into the air by a variety of natural and human activities. As it can be suspended over long time and travel over long distances in the atmosphere, it can cause a wide range of diseases that lead to a significant reduction of human life. The size of particles has been directly linked to their potential for causing health problems. Small particles of concern include "inhalable coarse particles" with a diameter of 2.5 to 10μm and "fine particles" smaller than 2.5μm in diameter. As the source-effect relationship of PM remains unclear, it is not easy to define such effects from individual sources such as long-range transport of pollution. Because of the potent role of PM and its associated pollutants, detailed knowledge of their human health impacts is of primary importance. This paper summarizes the basic evidence on the health effects of particulate matter. An in-depth analysis is provided to address the implications for policy-makers so that more stringent strategies can be implemented to reduce air pollution and its health effects. Copyright © 2014 Elsevier Ltd. All rights reserved.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Chemosphere
                Journal ID (iso-abbrev): Chemosphere
                Title: Chemosphere
                Publisher: Published by Elsevier Ltd.
                ISSN (Print): 0045-6535
                ISSN (Electronic): 1879-1298
                Publication date PMC-release: 14 October 2021
                Publication date (Electronic): 14 October 2021
                Electronic Location Identifier: 132569
                Affiliations
                [a ]School of Geography, Nanjing Normal University, Nanjing, 210023, China
                [b ]Key Laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, No. 1 Wenyuan Road, Nanjing, China
                [c ]Key Laboratory of Tropical Biological Resources of Ministry of Education, School of Life and Pharmaceutical Sciences, Hainan University, Haikou, 570228, China
                [d ]Kymeta Corporation, Redmond, WA, USA
                [e ]School of Natural and Computational Sciences, Massey University, Auckland, 0632, New Zealand
                Author notes
                [∗ ]Corresponding author. School of Geography, Nanjing Normal University, Nanjing, 210023, China.
                Article
                Publisher Item ID: S0045-6535(21)03041-1 Publisher ID: 132569
                DOI: 10.1016/j.chemosphere.2021.132569
                PMC ID: 8514250
                PubMed ID: 34655644
                SO-VID: db0e0be6-d7cb-4708-bab2-d3048338127a
                Copyright © © 2021 Published by Elsevier Ltd.
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Date received : 4 August 2021
                Date revision received : 1 October 2021
                Date accepted : 12 October 2021
                Categories
                Subject: Article

                ScienceOpen disciplines: General environmental science
                Keywords: air pollution,covid-19,particulate matter,china
                Data availability:
                ScienceOpen disciplines: General environmental science
                Keywords: air pollution, covid-19, particulate matter, china

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