Modelling the Effect of COVID-19 Lockdown on Air Pollution in Makkah Saudi Arabia with a Supervised Machine Learning Approach

Habeebullah, TM, Munir, S, Zeb, J et al. (1 more author) (2022) Modelling the Effect of COVID-19 Lockdown on Air Pollution in Makkah Saudi Arabia with a Supervised Machine Learning Approach. Toxics, 10 (5). 225. ISSN 2305-6304

Abstract

Metadata

Authors/Creators:
  • Habeebullah, TM
  • Munir, S
  • Zeb, J
  • Morsy, EA
Copyright, Publisher and Additional Information: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Keywords: COVID-19 lockdown; air quality; Makkah; NO2; O3; PM10; intervention; machine learning
Dates:
  • Accepted: 27 April 2022
  • Published (online): 29 April 2022
  • Published: May 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 02 Aug 2022 12:02
Last Modified: 25 Jun 2023 23:04
Status: Published
Publisher: MDPI
Identification Number: https://doi.org/10.3390/toxics10050225
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