The system for near-real time air pollution monitoring over cities based on the Sentinel-5P satellite data
Abstract
Introduction. Air pollution heterogeneity and rapid urbanization impose numerous constraints on available near-surface air quality monitoring. The solution for effective warning comes with the integration of different data, including remote sensing. Satellite data cannot answer whether dangerous pollution levels are observed; however, it provides a complete picture and may detect air pollution transportation towards or away from cities. The possibilities for effective near-real time (NRTI) monitoring have significantly improved with the launch of the Sentinel-5P satellite. The study aimed to describe the developed system for NRTI air pollution monitoring over Kharkiv, Kryvyi Rig, Kyiv, and Odesa based on NO2 and CO data derived from the Sentinel-5P satellite.
Data and methodology. The NRTI System was developed for tropospheric NO2 and total CO column number densities based on the Sentinel-5P NRTI products. After satellite scanning of Ukrainian territory, the NRTI System goes live in 2-3 hours. It is fully automatic, and modules were written using Python, VB.NET, and batch-scripting.
Results. The NRTI System includes four main phases: preparatory, source data downloading, processing and post-processing with visualization, archiving, and result distribution among users. Source data filtering with a quality assurance index and downscaling with linear kriging interpolation were developed. The output of the NRTI System is data in regular grids with a spatial resolution of 0.02o×0.02o. Based on the NRTI System work during October – December 2021, we conducted preliminary analyses to understand the possibilities of data usage. Higher NO2 content was observed in Kyiv and Kharkiv, where traffic emissions play a crucial role in air quality worsening. The use of daily time series allowed the detection of an increase in NO2 variance during the heating season, as well as plume distribution from cities to rural areas due to the prevailing wind. CO content is more homogeneous; however, higher values were observed in industrial Kryvyi Rig and Odesa. It is emphasized the huge impact of shipping CO emissions on air quality in Odesa. The temporal averaging of the NRTI System output allowed us to define the most polluted districts within the cities of interest. We intend to continue developing the presented NRTI System and develop the same algorithms for all cities with populations greater than 500 000 people in order to provide operational air pollution monitoring based on satellite data.
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References
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