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Title

Effects of the covid-19 lockdown on urban light emissions: Ground and satellite comparison

AuthorsBustamante-Calabria, Máximo; Sánchez de Miguel, A.; Martín-Ruiz, Susana ; Ortiz, José Luis ; Vílchez Medina, José Manuel ; Pelegrina López, Alicia; García, Antonio; Zamorano, Jaime; Bennie, Jonathan; Gaston, Kevin J.
KeywordsArtificial lighting
Light pollution
Night
Remote sensing
Urban
Aerosols
Particulate matter
Issue Date13-Jan-2021
PublisherMultidisciplinary Digital Publishing Institute
CitationRemote Sensing 13(2): 258 (2021)
Abstract’Lockdown’ periods in response to COVID-19 have provided a unique opportunity to study the impacts of economic activity on environmental pollution (e.g., NO2, aerosols, noise, light). The effects on NO2 and aerosols have been very noticeable and readily demonstrated, but that on light pollution has proven challenging to determine. The main reason for this difficulty is that the primary source of nighttime satellite imagery of the earth is the SNPP-VIIRS/DNB instrument, which acquires data late at night after most human nocturnal activity has already occurred and much associated lighting has been turned off. Here, to analyze the effect of lockdown on urban light emissions, we use ground and satellite data for Granada, Spain, during the COVID-19 induced confinement of the city’s population from 14 March until 31 May 2020. We find a clear decrease in light pollution due both to a decrease in light emissions from the city and to a decrease in anthropogenic aerosol content in the atmosphere which resulted in less light being scattered. A clear correlation between the abundance of PM10 particles and sky brightness is observed, such that the more polluted the atmosphere the brighter the urban night sky. An empirical expression is determined that relates PM10 particle abundance and sky brightness at three different wavelength bands. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
DescriptionThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license http://creativecommons.org/licenses/by/4.0/.--This article belongs to the Special Issue Light Pollution Monitoring Using Remote Sensing Data.
Publisher version (URL)http://dx.doi.org/10.3390/rs13020258
URIhttp://hdl.handle.net/10261/240269
DOI10.3390/rs13020258
E-ISSN2072-4292
Appears in Collections:(IAA) Artículos
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