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Title: | Sentinel satellite data monitoring of air pollutants with interpolation methods in Guayaquil, Ecuador |
Authors: | Mejía, Danilo Álvarez, Hermel Zalakeviciute, Rasa Macancela, Diana Sánchez, Carlos Bonilla-Bedoya, Santiago |
Issue Date: | 2023 |
Publisher: | Remote Sensing Applications: Society and Environment. Open Access. Volume 31 |
Abstract: | In Ecuador, there is a limitation on air quality monitoring due to the cost of monitoring networks. Although air quality monitoring stations are instruments for air measurement, they do not cover an entire city due to their scope. Satellite remote sensing is now an effective tool to study atmospheric pollutants and has been applied to continuously assess a region and overcome the limitations of fixed stations. Despite the application of satellite data for air quality monitoring, there are some limitations, such as measurement frequency, cloud cover and wide spatial resolution, which do not allow the assessment of air pollution in cities. Therefore, downscaling, applying interpolation methods, is essential for continuous air quality monitoring at smaller scales. For this research, Nitrogen Dioxide (NO2) data from the Sentinel-5 satellite percussor was used in the city of Guayaquil for January–December 2020, which is considered before, during and after the COVID-19 quarantine. This mid-size port city does not have a permanent monitoring network, which prevents us from knowing the air quality. Due to the limitation of pixel size, this study used satellite data to apply interpolation techniques and reduce pixels to assess air quality. Two categories of interpolation were selected: deterministic and stochastic. The empirical Bayesian kriging (EBK) interpolation obtained a R2 of 0.9546, which was superior to the other methods applied. Therefore, the EBK method had the best accuracy for tropospheric NO2 concentration. Finally, the method used in this research can help monitor air quality in cities lacking continuous monitoring networks, as the reduction of the pixel size gives us a better pattern of pollutants. |
URI: | https://doi.org/10.1016/j.rsase.2023.100990 https://repositorio.uti.edu.ec//handle/123456789/5725 |
Appears in Collections: | Artículos Científicos Indexados |
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