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      Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns

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          Abstract

          True air quality improvements during the COVID-19 lockdowns in global cities are more limited than we thought.

          Abstract

          The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO 2, O 3, and PM 2.5 concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO 2 concentrations and increases in O 3 were observed in almost all cities. However, the decline in NO 2 concentrations attributable to the lockdowns was not as large as expected, at reductions of 10 to 50%. Accordingly, O 3 increased by 2 to 30% (except for London), the total gaseous oxidant (O x = NO 2 + O 3) showed limited change, and PM 2.5 concentrations decreased in most cities studied but increased in London and Paris. Our results demonstrate the need for a sophisticated analysis to quantify air quality impacts of interventions and indicate that true air quality improvements were notably more limited than some earlier reports or observational data suggested.

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          Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement

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            Effect of restricted emissions during COVID-19 on air quality in India

            The effectiveness and cost are always top factors for policy-makers to decide control measures and most measures had no pre-test before implementation. Due to the COVID-19 pandemic, human activities are largely restricted in many regions in India since mid-March of 2020, and it is a progressing experiment to testify effectiveness of restricted emissions. In this study, concentrations of six criteria pollutants, PM10, PM2.5, CO, NO2, ozone and SO2 during March 16th to April 14th from 2017 to 2020 in 22 cities covering different regions of India were analysed. Overall, around 43, 31, 10, and 18% decreases in PM2.5, PM10, CO, and NO2 in India were observed during lockdown period compared to previous years. While, there were 17% increase in O3 and negligible changes in SO2. The air quality index (AQI) reduced by 44, 33, 29, 15 and 32% in north, south, east, central and western India, respectively. Correlation between cities especially in northern and eastern regions improved in 2020 compared to previous years, indicating more significant regional transport than previous years. The mean excessive risks of PM reduced by ~52% nationwide due to restricted activities in lockdown period. To eliminate the effects of possible favourable meteorology, the WRF-AERMOD model system was also applied in Delhi-NCR with actual meteorology during the lockdown period and an un-favourable event in early November of 2019 and results show that predicted PM2.5 could increase by only 33% in unfavourable meteorology. This study gives confidence to the regulatory bodies that even during unfavourable meteorology, a significant improvement in air quality could be expected if strict execution of air quality control plans is implemented.
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              High secondary aerosol contribution to particulate pollution during haze events in China.

              Rapid industrialization and urbanization in developing countries has led to an increase in air pollution, along a similar trajectory to that previously experienced by the developed nations. In China, particulate pollution is a serious environmental problem that is influencing air quality, regional and global climates, and human health. In response to the extremely severe and persistent haze pollution experienced by about 800 million people during the first quarter of 2013 (refs 4, 5), the Chinese State Council announced its aim to reduce concentrations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 micrometres) by up to 25 per cent relative to 2012 levels by 2017 (ref. 6). Such efforts however require elucidation of the factors governing the abundance and composition of PM2.5, which remain poorly constrained in China. Here we combine a comprehensive set of novel and state-of-the-art offline analytical approaches and statistical techniques to investigate the chemical nature and sources of particulate matter at urban locations in Beijing, Shanghai, Guangzhou and Xi'an during January 2013. We find that the severe haze pollution event was driven to a large extent by secondary aerosol formation, which contributed 30-77 per cent and 44-71 per cent (average for all four cities) of PM2.5 and of organic aerosol, respectively. On average, the contribution of secondary organic aerosol (SOA) and secondary inorganic aerosol (SIA) are found to be of similar importance (SOA/SIA ratios range from 0.6 to 1.4). Our results suggest that, in addition to mitigating primary particulate emissions, reducing the emissions of secondary aerosol precursors from, for example, fossil fuel combustion and biomass burning is likely to be important for controlling China's PM2.5 levels and for reducing the environmental, economic and health impacts resulting from particulate pollution.
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                Author and article information

                Journal
                Sci Adv
                Sci Adv
                SciAdv
                advances
                Science Advances
                American Association for the Advancement of Science
                2375-2548
                January 2021
                13 January 2021
                : 7
                : 3
                : eabd6696
                Affiliations
                [1 ]School of Geography Earth and Environment Sciences, University of Birmingham, Birmingham B15 2TT, UK.
                [2 ]Department of Economics, University of Birmingham, Birmingham B15 2TT, UK.
                [3 ]School of Public Health, Imperial College London, London W2 1PG, UK.
                [4 ]Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou 310027, China.
                Author notes
                [*]

                These authors contributed equally to this work.

                []Corresponding author. Email: z.shi@ 123456bham.ac.uk (Z.S.); c.song.1@ 123456bham.ac.uk (C.S.)
                [‡]

                Also at: Department of Environmental Sciences and Center of Excellence in Environmental Studies, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi Arabia.

                Author information
                http://orcid.org/0000-0002-7157-543X
                http://orcid.org/0000-0001-7948-4834
                http://orcid.org/0000-0002-2237-1289
                http://orcid.org/0000-0002-9022-1004
                http://orcid.org/0000-0002-7100-096X
                http://orcid.org/0000-0002-3966-2082
                http://orcid.org/0000-0003-4887-4260
                http://orcid.org/0000-0002-3017-4461
                http://orcid.org/0000-0002-2684-5226
                Article
                abd6696
                10.1126/sciadv.abd6696
                7806219
                33523881
                38fa33ea-d71d-4e26-8d46-bb44ee52b106
                Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

                This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 July 2020
                : 18 November 2020
                Funding
                Funded by: doi http://dx.doi.org/10.13039/501100000270, Natural Environment Research Council;
                Award ID: NE/S00579X/1; NE/N007190/1; NE/R005281/1
                Funded by: UoB Institute of Global Innovation;
                Award ID: Clean Air
                Categories
                Research Article
                Research Articles
                SciAdv r-articles
                Atmospheric Science
                Environmental Studies
                Coronavirus
                Custom metadata
                Adrienne Del Mundo

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