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A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions
- Publication Year :
- 2021
-
Abstract
- This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015–2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015–2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples’ mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared<br />Peer Reviewed<br />Article signat per 97 autors: Ranjeet S. Sokhi, Vikas Singh, Xavier Querol, Sandro Finardi, Admir Créso Targino, Maria de Fatima Andrade, Radenko Pavlovic, Rebecca M. Garland, Jordi Massagué, Shaofei Kong, Alexander Baklanov, Lu Ren, Oksana Tarasova, Greg Carmichael, Vincent-Henri Peuch, Vrinda Anand, Graciela Arbilla, Kaitlin Badali, Gufran Beig, Luis Carlos Belalcazart, Andrea Bolignano, Peter Brimblecombe, Patricia Camacho, Alejandro Casallas, Jean-Pierre Charland, Jason Choi, Eleftherios Chourdakis, Isabelle Coll, Marty Collins, Josef Cyrys, Cleyton Martins da Silva, Alessandro Domenico Di Giosa, Anna Di Leo, Camilo Ferro, Mario Gavidia-Calderon, Amiya Gayen, Alexander Ginzburg, Fabrice Godefroy, Yuri Alexandra Gonzalez, Marco Guevara-Luna, Sk. Mafizul Haque, Henno Havenga, Dennis Herod, Urmas Horrak, Tareq Hussein, Sergio Ibarra, Monica Jaimes, Marko Kaasik, Ravindra Khaiwal, Jhoon Kim, Anu Kousa, Jaakko Kukkonen, Markku Kulmala, Joel Kuular, Nathalie La Violette, Guido Lanzani, Xi Liu, Stephanie MacDougall, Patrick M. Manseau, Giada Marchegiani, Brian McDonald, Swasti Vardhan Mishra, Luisa T. Molina, Dennis Mooibroek, Suman Mor, Nicolas Moussiopoulos, Fabio Murena, Jarkko V. Niemi, Steffen Noe, Thiago Nogueira, Michael Norman, Juan Luis Pérez-Camano, Tuukka Petaj, Stuart Piketh, Aditi Rathod, Ken Reid, Armando Retama, Olivia Rivera, Néstor Y. Rojast, Jhojan P. Rojas-Quincho, Roberto San José, Odon Sanchez, Rodrigo J. Seguel, Salla Sillanpaa, Yushan Su, Nigel Tapper, Antonio Terrazas, Hilkka Timonen, Domenico Toscano, George Tsegas, Guus J.M. Velders, Christos Vlachokostas, Erika von Schneidemesseri, Rajasree VPM, Ravi Yadav, Rasa Zalakeviciute, Miguel Zavala<br />Postprint (published version)
Details
- Database :
- OAIster
- Notes :
- application/pdf, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1298728004
- Document Type :
- Electronic Resource