Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Ratios of chemical compounds in the atmosphere are becoming more widely used for assessment of changes in fuel consumption by cities or specific industrial objects, as well as for correction of emission factors, which are crucial for emission inventories. The methodology for using the NO2/CO ratio for analysis of burning efficiency based on remote sensing data was first implemented for Ukrainian territory. We selected seven case studies for analyses, including three days for Kyiv with a variety of emission sources, two days for Mariupol with prevailing coal-fired industrial facilities, and two days for wildfires as reference cases for comparison. We use NO2 and CO column number densities derived from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor, supported by the boundary layer height and wind parameters from the ERA-5 reanalysis. The overall methodology for NO2/CO estimation includes data quality analysis using cloudiness and a quality assurance index; meteorological data processing for obtaining the prevailing wind field at the top of the boundary layer; retrieving NO2 and CO content from emission sources and background values; and the NO2/CO ratio computation itself. For selected cases, the NO2/CO ratio equals 2.6 to 6.5 for wildfires, 3.1 to 4.6 for Mariupol, and 10.8 to 31.7 for Kyiv. Because of the available uncertainties, the necessity of estimating the NO2/CO ratio using longer time series is emphasized. The prospects for using the NO2/CO ratio are possibilities for the computation of emission factors and detecting the mass of pollutants emitted in Ukrainian cities. The NO2/CO ratio can be used as an additional parameter for assessing the changes in fuel consumption, considering the war consequences in Ukraine.
Ratios of chemical compounds in the atmosphere are becoming more widely used for assessment of changes in fuel consumption by cities or specific industrial objects, as well as for correction of emission factors, which are crucial for emission inventories. The methodology for using the NO2/CO ratio for analysis of burning efficiency based on remote sensing data was first implemented for Ukrainian territory. We selected seven case studies for analyses, including three days for Kyiv with a variety of emission sources, two days for Mariupol with prevailing coal-fired industrial facilities, and two days for wildfires as reference cases for comparison. We use NO2 and CO column number densities derived from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor, supported by the boundary layer height and wind parameters from the ERA-5 reanalysis. The overall methodology for NO2/CO estimation includes data quality analysis using cloudiness and a quality assurance index; meteorological data processing for obtaining the prevailing wind field at the top of the boundary layer; retrieving NO2 and CO content from emission sources and background values; and the NO2/CO ratio computation itself. For selected cases, the NO2/CO ratio equals 2.6 to 6.5 for wildfires, 3.1 to 4.6 for Mariupol, and 10.8 to 31.7 for Kyiv. Because of the available uncertainties, the necessity of estimating the NO2/CO ratio using longer time series is emphasized. The prospects for using the NO2/CO ratio are possibilities for the computation of emission factors and detecting the mass of pollutants emitted in Ukrainian cities. The NO2/CO ratio can be used as an additional parameter for assessing the changes in fuel consumption, considering the war consequences in Ukraine.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.