Footprint of the 2020 COVID-19 Lockdown on Column-Integrated Aerosol Parameters in Spain

The lockdown adopted in Spain to combat the global pandemic due to the coronavirus disease (COVID-19) led to a significant reduction in the emission of aerosols produced by road traffic and industry. This study aims to detect changes in column aerosols in Spain due to the COVID-19 lockdown. High-qua...

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Bibliographic Details
Published in:Remote Sensing
Main Authors: María Ángeles Obregón, Blanca Martín, Antonio Serrano
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2023
Subjects:
COVID-19
lockdown
column aerosol
AERONET
Spain
Science
Q
Aerosol Robotic Network
Online Access:https://doi.org/10.3390/rs15123167
https://doaj.org/article/20133e1a40ff47afa5f20bf9e60d1d4d
Description
Summary:The lockdown adopted in Spain to combat the global pandemic due to the coronavirus disease (COVID-19) led to a significant reduction in the emission of aerosols produced by road traffic and industry. This study aims to detect changes in column aerosols in Spain due to the COVID-19 lockdown. High-quality AErosol RObotic NETwork (AERONET) measurements of AOD (aerosol optical depth), AE (Ångström exponent) and SSA (single scattering albedo) over the period 2012–2020 are used for this purpose. Ten AERONET stations with available measurements during the lockdown and post-lockdown periods with a long previous data record are selected. The stations are well distributed throughout Spain, covering different areas and population densities. A comprehensive set of three statistical tests are applied to assess general changes in the dataset, the central tendency and low and high values for each parameter. The analyses are conducted for the 2020 lockdown and post-lockdown periods by comparing daily aerosol data with the measurements recorded for the same calendar days during the period 2012–2019. The results indicate a general increase in AOD during the lockdown and a decrease during the post-lockdown. While AE shows no overall behaviour, SSA is the parameter most sensitive to changes in anthropogenic contribution, with an overall significant increase in almost all the stations during both lockdown and post-lockdown periods. The study contributes to addressing the impact of the COVID-19 lockdown and provides methodologies to detect its footprint.

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