Impact of COVID-19 lockdown on particulate matter oxidative potential at urban background<i>versus</i>traffic sites-Reference-Cited by-同舟云学术

Impact of COVID-19 lockdown on particulate matter oxidative potential at urban backgroundversustraffic sites

Published:2023 Issue:5 Volume:3 Page:942-953
ISSN:2634-3606
Container-title:Environmental Science: Atmospheres
language:en
Short-container-title:Environ. Sci.: Atmos.

Author:

Borlaza Lucille Joanna S.¹^ORCID,Ngoc Thuy Vy Dinh¹,Grange Stuart²,Socquet Stéphane³,Moussu Emmanuel³,Mary Gladys³,Favez Olivier⁴,Hueglin Christoph²,Jaffrezo Jean-Luc¹,Uzu Gaëlle¹

Affiliation:

1. University of Grenoble Alpes, CNRS, IRD, INP-G, IGE (UMR 5001), Grenoble F-38000, France

2. Empa, Swiss Federal Laboratories for Materials Science and Technology, 8600 Dübendorf, Switzerland

3. Atmo AuRA, Grenoble 38400, France

4. INERIS, Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte, France

Abstract

During the lockdown period, the oxidative potential of PM decreased in a traffic site but not in an urban site due to sustained contributions from residential heating emissions. Random forest modelling is useful in predicting business-as-usual levels for air quality studies.

Funder

Agence Nationale de la Recherche

Agence de l'Environnement et de la Maîtrise de l'Energie

Horizon 2020 Framework Programme

Publisher

Royal Society of Chemistry (RSC)

Subject

Pollution,Environmental Chemistry,Chemistry (miscellaneous),Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/EA/D3EA00013C

Reference69 articles.

1. COVID-19 pandemic and environmental pollution: A blessing in disguise?

2. COVID-19 lockdowns cause global air pollution declines

3. Impact of COVID-19 lockdown on the fine particulate matter concentration levels: Results from Bengaluru megacity, India

4. Effects of COVID-19 lockdowns on fine particulate matter concentrations

5. Response of atmospheric composition to COVID-19 lockdown measures during spring in the Paris region (France)

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