Implications of COVID-19 Restriction Measures in Urban Air Quality of Thessaloniki, Greece: A Machine Learning Approach

Implications of COVID-19 Restriction Measures in Urban Air Quality of Thessaloniki, Greece: A Machine Learning Approach

Following the rapid spread of COVID-19, a lockdown was imposed in Thessaloniki, Greece, resulting in an abrupt reduction of human activities. To unravel the impact of restrictions on the urban air quality of Thessaloniki, NO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathM...

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Autores principales: Dimitris Akritidis, Prodromos Zanis, Aristeidis K. Georgoulias, Eleni Papakosta, Paraskevi Tzoumaka, Apostolos Kelessis
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
COVID-19
air quality
machine learning
NO<sub>2</sub>
O<sub>3</sub>
Thessaloniki
Meteorology. Climatology
QC851-999
Acceso en línea:https://doaj.org/article/f130ecf2e988474a92a1ecdfb5e5c89f
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spelling oai:doaj.org-article:f130ecf2e988474a92a1ecdfb5e5c89f2021-11-25T16:45:36ZImplications of COVID-19 Restriction Measures in Urban Air Quality of Thessaloniki, Greece: A Machine Learning Approach10.3390/atmos121115002073-4433https://doaj.org/article/f130ecf2e988474a92a1ecdfb5e5c89f2021-11-01T00:00:00Zhttps://www.mdpi.com/2073-4433/12/11/1500https://doaj.org/toc/2073-4433Following the rapid spread of COVID-19, a lockdown was imposed in Thessaloniki, Greece, resulting in an abrupt reduction of human activities. To unravel the impact of restrictions on the urban air quality of Thessaloniki, NO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula> and O<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>3</mn></msub></semantics></math></inline-formula> observations are compared against the business-as-usual (BAU) concentrations for the lockdown period. BAU conditions are modeled, applying the XGBoost (eXtreme Gradient Boosting) machine learning algorithm on air quality and meteorological surface measurements, and reanalysis data. A reduction in NO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula> concentrations is found during the lockdown period due to the restriction policies at both AGSOFIA and EGNATIA stations of −24.9 [−26.6, −23.2]% and −18.4 [−19.6, −17.1]%, respectively. A reverse effect is revealed for O<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>3</mn></msub></semantics></math></inline-formula> concentrations at AGSOFIA with an increase of 12.7 [10.8, 14.8]%, reflecting the reduced O<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>3</mn></msub></semantics></math></inline-formula> titration by NO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mi>x</mi></msub></semantics></math></inline-formula>. The implications of COVID-19 lockdowns in the urban air quality of Thessaloniki are in line with the results of several recent studies for other urban areas around the world, highlighting the necessity of more sophisticated emission control strategies for urban air quality management.Dimitris AkritidisProdromos ZanisAristeidis K. GeorgouliasEleni PapakostaParaskevi TzoumakaApostolos KelessisMDPI AGarticleCOVID-19air qualitymachine learningNO<sub>2</sub>O<sub>3</sub>ThessalonikiMeteorology. ClimatologyQC851-999ENAtmosphere, Vol 12, Iss 1500, p 1500 (2021)
institution DOAJ
collection DOAJ
language EN
topic COVID-19
air quality
machine learning
NO<sub>2</sub>
O<sub>3</sub>
Thessaloniki
Meteorology. Climatology
QC851-999
spellingShingle COVID-19
air quality
machine learning
NO<sub>2</sub>
O<sub>3</sub>
Thessaloniki
Meteorology. Climatology
QC851-999
Dimitris Akritidis
Prodromos Zanis
Aristeidis K. Georgoulias
Eleni Papakosta
Paraskevi Tzoumaka
Apostolos Kelessis
Implications of COVID-19 Restriction Measures in Urban Air Quality of Thessaloniki, Greece: A Machine Learning Approach
description Following the rapid spread of COVID-19, a lockdown was imposed in Thessaloniki, Greece, resulting in an abrupt reduction of human activities. To unravel the impact of restrictions on the urban air quality of Thessaloniki, NO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula> and O<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>3</mn></msub></semantics></math></inline-formula> observations are compared against the business-as-usual (BAU) concentrations for the lockdown period. BAU conditions are modeled, applying the XGBoost (eXtreme Gradient Boosting) machine learning algorithm on air quality and meteorological surface measurements, and reanalysis data. A reduction in NO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula> concentrations is found during the lockdown period due to the restriction policies at both AGSOFIA and EGNATIA stations of −24.9 [−26.6, −23.2]% and −18.4 [−19.6, −17.1]%, respectively. A reverse effect is revealed for O<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>3</mn></msub></semantics></math></inline-formula> concentrations at AGSOFIA with an increase of 12.7 [10.8, 14.8]%, reflecting the reduced O<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>3</mn></msub></semantics></math></inline-formula> titration by NO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mi>x</mi></msub></semantics></math></inline-formula>. The implications of COVID-19 lockdowns in the urban air quality of Thessaloniki are in line with the results of several recent studies for other urban areas around the world, highlighting the necessity of more sophisticated emission control strategies for urban air quality management.
format article
author Dimitris Akritidis
Prodromos Zanis
Aristeidis K. Georgoulias
Eleni Papakosta
Paraskevi Tzoumaka
Apostolos Kelessis
author_facet Dimitris Akritidis
Prodromos Zanis
Aristeidis K. Georgoulias
Eleni Papakosta
Paraskevi Tzoumaka
Apostolos Kelessis
author_sort Dimitris Akritidis
title Implications of COVID-19 Restriction Measures in Urban Air Quality of Thessaloniki, Greece: A Machine Learning Approach
title_short Implications of COVID-19 Restriction Measures in Urban Air Quality of Thessaloniki, Greece: A Machine Learning Approach
title_full Implications of COVID-19 Restriction Measures in Urban Air Quality of Thessaloniki, Greece: A Machine Learning Approach
title_fullStr Implications of COVID-19 Restriction Measures in Urban Air Quality of Thessaloniki, Greece: A Machine Learning Approach
title_full_unstemmed Implications of COVID-19 Restriction Measures in Urban Air Quality of Thessaloniki, Greece: A Machine Learning Approach
title_sort implications of covid-19 restriction measures in urban air quality of thessaloniki, greece: a machine learning approach
publisher MDPI AG
publishDate 2021
url https://doaj.org/article/f130ecf2e988474a92a1ecdfb5e5c89f
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