An Estimation Model of Emissions from Burning Areas Based on the Tier Method
The emissions of particulates from burning agricultural fields threaten the environment and human health, contributing to air pollution and increasing the risk of respiratory and cardiovascular diseases. An analysis of total suspended particulate (TSP), PM2.5, and PM10 emissions from crop residue bu...
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MDPI AG
2025-04-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/7/1264 |
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| author | Barbara Dobosz Kamil Roman Emilia Grzegorzewska |
| author_facet | Barbara Dobosz Kamil Roman Emilia Grzegorzewska |
| author_sort | Barbara Dobosz |
| collection | DOAJ |
| description | The emissions of particulates from burning agricultural fields threaten the environment and human health, contributing to air pollution and increasing the risk of respiratory and cardiovascular diseases. An analysis of total suspended particulate (TSP), PM2.5, and PM10 emissions from crop residue burning is presented in this study. A primary goal is to improve emission estimation accuracy by integrating satellite imagery from modes of Moderate Resolution Imaging Spectroradiometers (MODIS) and Visible Infrared Imaging Radiometers (VIIRS) with traditional data. Particulate emissions were estimated using Tier 1 and Tier 2 methodologies outlined in the EEA/EMEP Emission Inventory Guidebook based on thermal anomaly data from satellite observations. According to the findings, burning wheat, maize, barley, and rice residue accounts for most emissions, with significant variations identified in India, China, and the United States. The variations highlight the need for a location-specific approach to emission management. Particulate emissions cause adverse environmental and health impacts, which can be minimized by targeting mitigation strategies at key emission hotspots. The research provides important insights to inform policymakers and support developing strategies to reduce fine particulate agricultural emissions. |
| format | Article |
| id | doaj-art-751e9073c42e462e9524a738d09aa4ca |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-751e9073c42e462e9524a738d09aa4ca2025-08-20T02:09:17ZengMDPI AGRemote Sensing2072-42922025-04-01177126410.3390/rs17071264An Estimation Model of Emissions from Burning Areas Based on the Tier MethodBarbara Dobosz0Kamil Roman1Emilia Grzegorzewska2Department of Biometry, Institute of Agriculture, Warsaw University of Life Sciences, Nowoursynowska 159, 02-776 Warsaw, PolandDepartment of Technology and Entrepreneurship in the Wood Industry, Institute of Wood Sciences and Furniture, Warsaw University of Life Sciences, 159 Nowoursynowska Str., 02-776 Warsaw, PolandDepartment of Technology and Entrepreneurship in the Wood Industry, Institute of Wood Sciences and Furniture, Warsaw University of Life Sciences, 159 Nowoursynowska Str., 02-776 Warsaw, PolandThe emissions of particulates from burning agricultural fields threaten the environment and human health, contributing to air pollution and increasing the risk of respiratory and cardiovascular diseases. An analysis of total suspended particulate (TSP), PM2.5, and PM10 emissions from crop residue burning is presented in this study. A primary goal is to improve emission estimation accuracy by integrating satellite imagery from modes of Moderate Resolution Imaging Spectroradiometers (MODIS) and Visible Infrared Imaging Radiometers (VIIRS) with traditional data. Particulate emissions were estimated using Tier 1 and Tier 2 methodologies outlined in the EEA/EMEP Emission Inventory Guidebook based on thermal anomaly data from satellite observations. According to the findings, burning wheat, maize, barley, and rice residue accounts for most emissions, with significant variations identified in India, China, and the United States. The variations highlight the need for a location-specific approach to emission management. Particulate emissions cause adverse environmental and health impacts, which can be minimized by targeting mitigation strategies at key emission hotspots. The research provides important insights to inform policymakers and support developing strategies to reduce fine particulate agricultural emissions.https://www.mdpi.com/2072-4292/17/7/1264air pollutionparticulate matterbiomass burningemission estimationremote sensingagriculture |
| spellingShingle | Barbara Dobosz Kamil Roman Emilia Grzegorzewska An Estimation Model of Emissions from Burning Areas Based on the Tier Method Remote Sensing air pollution particulate matter biomass burning emission estimation remote sensing agriculture |
| title | An Estimation Model of Emissions from Burning Areas Based on the Tier Method |
| title_full | An Estimation Model of Emissions from Burning Areas Based on the Tier Method |
| title_fullStr | An Estimation Model of Emissions from Burning Areas Based on the Tier Method |
| title_full_unstemmed | An Estimation Model of Emissions from Burning Areas Based on the Tier Method |
| title_short | An Estimation Model of Emissions from Burning Areas Based on the Tier Method |
| title_sort | estimation model of emissions from burning areas based on the tier method |
| topic | air pollution particulate matter biomass burning emission estimation remote sensing agriculture |
| url | https://www.mdpi.com/2072-4292/17/7/1264 |
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