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Título : Spatio-temporal evaluation of air pollution using ground-based and satellite data during COVID-19 in Ecuador
Autor: Mejia Coronel, Julio Danilo
Faican Cabrera, Gina Maricela
Correspondencia: Mejia Coronel, Julio Danilo, danilo.mejia@ucuenca.edu.ec
Palabras clave : COVID-19
NO2
Sentinel-5P
O3
Linear regression model
Atmospheric pollution
Área de conocimiento FRASCATI amplio: 2. Ingeniería y Tecnología
Área de conocimiento FRASCATI detallado: 2.7.1 Ingeniería Ambiental y Geológica
Área de conocimiento FRASCATI específico: 2.7 Ingeniería del Medio Ambiente
Área de conocimiento UNESCO amplio: 07 - Ingeniería, Industria y Construcción
ÁArea de conocimiento UNESCO detallado: 0712 - Tecnología de Protección del Medio Ambiente
Área de conocimiento UNESCO específico: 071 - Ingeniería y Profesiones Afines
Fecha de publicación : 2024
Volumen: Volumen 10
Fuente: Heliyon
metadata.dc.identifier.doi: 10.1016/j.heliyon.2024.e28152
Tipo: ARTÍCULO
Abstract: 
The concentration of gases in the atmosphere is a topic of growing concern due to its effects on health, ecosystems etc. Its monitoring is commonly carried out through ground stations which offer high precision and temporal resolution. However, in countries with few stations, such as Ecuador, these data fail to adequately describe the spatial variability of pollutant concentrations. Remote sensing data have great potential to solve this complication. This study evaluates the spatiotemporal distribution of nitrogen dioxide (NO2) and ozone (O3) concentrations in Quito and Cuenca, using data obtained from ground-based and Sentinel-5 Precursor mission sources during the years 2019 and 2020. Moreover, a Linear Regression Model (LRM) was employed to analyze the correlation between ground-based and satellite datasets, revealing positive associations for O3 (R2 = 0.83, RMSE = 0.18) and NO2 (R2 = 0.83, RMSE = 0.25) in Quito; and O3 (R2 = 0.74, RMSE = 0.23) and NO2, (R2 = 0.73, RMSE = 0.23) for Cuenca. The agreement between ground-based and satellite datasets was analyzed by employing the intra-class correlation coefficient (ICC), reflecting good agreement between them (ICC ≥0.57); and using Bland and Altman coefficients, which showed low bias and that more than 95% of the differences are within the limits of agreement. Furthermore, the study investigated the impact of COVID-19 pandemic-related restrictions, such as social distancing and isolation, on atmospheric conditions. This was categorized into three periods for 2019 and 2020: before (from January 1st to March 15th), during (from March 16th to May 17th), and after (from March 18th to December 31st). A 51% decrease in NO2 concentrations was recorded for Cuenca, while Quito experienced a 14.7% decrease. The tropospheric column decreased by 27.3% in Cuenca and 15.1% in Quito. O3 showed an increasing trend, with tropospheric concentrations rising by 0.42% and 0.11% for Cuenca and Quito respectively, while the concentration in Cuenca decreased by 14.4%. Quito experienced an increase of 10.5%. Finally, the reduction of chemical species in the atmosphere as a consequence of mobility restrictions is highlighted. This study compared satellite and ground station data for NO2 and O3 concentrations. Despite differing units preventing data validation, it verified the Sentinel-5P satellite's effectiveness in anomaly detection. Our research's value lies in its applicability to developing countries, which may lack extensive monitoring networks, demonstrating the potential use of satellite technology in urban planning.
URI : https://dspace.ucuenca.edu.ec/handle/123456789/45777
https://www.scopus.com/record/display.uri?eid=2-s2.0-85188427540&origin=resultslist&sort=plf-f&src=s&sot=b&sdt=b&s=TITLE-ABS-KEY%28Spatio-temporal+evaluation+of+air+pollution+using+ground-based+and+satellite+data+during+COVID-19+in+Ecuador%29&relpos=0
URI Fuente: https://www.sciencedirect.com/journal/heliyon
ISSN : 2405-8440
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