Spatio-temporal evaluation of air pollution using ground-based and satellite data during COVID-19 in Ecuador

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.

Eficiencia de la Imputación de Datos Faltantes de Precipitaciones Utilizando Herramientas Computacionales en la Cuenca Hidrográfica, Jubones - Ecuador

Para un correcto análisis de los recursos hídricos es necesario conocer de una manera precisa las precipitaciones de una zona, esto permitirá realizar aplicaciones con altos niveles de confiabilidad en cuanto a la cantidad de agua que se tenga en una cuenca hidrográfica. Las series suelen ser de varios años por lo que es muy probable que por fallas de los equipos, fallas humanas o pérdida de registros de almacenamiento se encuentren datos faltantes. Previo a cualquier análisis hidrológico, una tarea fundamental es tener series de datos completas y debido a la variabilidad de ciertas cuencas hidrográficas muchos de los métodos convencionales no resultan efectivos. Por tal motivo se utiliza la paquetería Climatol de R y la metodología estadística recomendada desde la normalización de los datos para evaluar su funcionamiento. Para esto se imputan los datos de la cuenca del río Jubones que se caracteriza por ser vertiente de Pacífico y por tener una gran variabilidad de precipitaciones. Se han utilizado varias métricas estadísticas de comparación para comprobar el funcionamiento de la metodología encontrando muy buenos ajustes en diversas comparaciones entre series de datos de diferentes estaciones meteorológicas.