Xincen Ning , Jianwei Li , Pengkun Zhuang , Shifu Lai , Xiaogan Zheng
{"title":"基于 MODIS 火灾辐射能数据的中国西南地区野火燃烧排放清单(2001-2020 年","authors":"Xincen Ning , Jianwei Li , Pengkun Zhuang , Shifu Lai , Xiaogan Zheng","doi":"10.1016/j.apr.2024.102279","DOIUrl":null,"url":null,"abstract":"<div><p>Wildfires, a persistent environmental menace, are a significant source of harmful gases and particulate emissions. This study leverages the fire radiative power (FRP) method to delineate a comprehensive wildfire emission inventory for Southwest China from 2001 to 2020. Daily fire radiative power data derived from 1 km MODIS Thermal Anomalies/Fire products (MOD14/MYD14) were used to calculate the FRE and combusted biomass. Available emission factors were assigned to three biomass burn types: forest, grass, and shrub fires. Over the span of two decades, we have compiled data and estimated the annual emissions of carbon dioxide (CO<sub>2</sub>), carbon monoxide (CO), methane (CH<sub>4</sub>), sulfur dioxide (SO<sub>2</sub>), ammonia (NH<sub>3</sub>), nitrogen oxides (NO<sub>x</sub>), total particulate matter (TPM), black carbon (BC), organic carbon (OC), and non-methane volatile organic compounds (NMVOC<sub>s</sub>) to be 9809.13, 566.82, 25.79, 5.37, 12.25, 16.67, 133.53, 4.16, 41.81, and 97.23 Gg per year (Gg yr<sup>−1</sup>), respectively. In terms of fire type, forest fires accounted for the largest portion of total CO<sub>2</sub> emissions (59.23%), with grass fires and shrub fires coming in second and third, accounting for 20.41% and 20.36%, respectively. Geographically, Yunnan Province were identified as the major contributor in Southwest China, accounting for 69.67% of the total emissions. Temporally, the maximum emission occurred in 2010 (24263.33 Gg), and the minimum emission occurred in 2017 (2917.66 Gg). And the emissions were mainly concentrated in February (23.33%), March (25.52%), and April (22.61%), which accounted for nearly three-fourths of the total emissions. The results of this study are much higher than those obtained by the burned area method, almost three times as high. In contrast, the results of this study are close to the fire emission data from the GFED4s and GFASv1.2 and QFEDv2.5r1 databases.</p></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 11","pages":"Article 102279"},"PeriodicalIF":3.9000,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wildfire combustion emission inventory in Southwest China (2001–2020) based on MODIS fire radiative energy data\",\"authors\":\"Xincen Ning , Jianwei Li , Pengkun Zhuang , Shifu Lai , Xiaogan Zheng\",\"doi\":\"10.1016/j.apr.2024.102279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Wildfires, a persistent environmental menace, are a significant source of harmful gases and particulate emissions. This study leverages the fire radiative power (FRP) method to delineate a comprehensive wildfire emission inventory for Southwest China from 2001 to 2020. Daily fire radiative power data derived from 1 km MODIS Thermal Anomalies/Fire products (MOD14/MYD14) were used to calculate the FRE and combusted biomass. Available emission factors were assigned to three biomass burn types: forest, grass, and shrub fires. Over the span of two decades, we have compiled data and estimated the annual emissions of carbon dioxide (CO<sub>2</sub>), carbon monoxide (CO), methane (CH<sub>4</sub>), sulfur dioxide (SO<sub>2</sub>), ammonia (NH<sub>3</sub>), nitrogen oxides (NO<sub>x</sub>), total particulate matter (TPM), black carbon (BC), organic carbon (OC), and non-methane volatile organic compounds (NMVOC<sub>s</sub>) to be 9809.13, 566.82, 25.79, 5.37, 12.25, 16.67, 133.53, 4.16, 41.81, and 97.23 Gg per year (Gg yr<sup>−1</sup>), respectively. In terms of fire type, forest fires accounted for the largest portion of total CO<sub>2</sub> emissions (59.23%), with grass fires and shrub fires coming in second and third, accounting for 20.41% and 20.36%, respectively. Geographically, Yunnan Province were identified as the major contributor in Southwest China, accounting for 69.67% of the total emissions. Temporally, the maximum emission occurred in 2010 (24263.33 Gg), and the minimum emission occurred in 2017 (2917.66 Gg). And the emissions were mainly concentrated in February (23.33%), March (25.52%), and April (22.61%), which accounted for nearly three-fourths of the total emissions. The results of this study are much higher than those obtained by the burned area method, almost three times as high. In contrast, the results of this study are close to the fire emission data from the GFED4s and GFASv1.2 and QFEDv2.5r1 databases.</p></div>\",\"PeriodicalId\":8604,\"journal\":{\"name\":\"Atmospheric Pollution Research\",\"volume\":\"15 11\",\"pages\":\"Article 102279\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Pollution Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1309104224002447\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Pollution Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1309104224002447","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Wildfire combustion emission inventory in Southwest China (2001–2020) based on MODIS fire radiative energy data
Wildfires, a persistent environmental menace, are a significant source of harmful gases and particulate emissions. This study leverages the fire radiative power (FRP) method to delineate a comprehensive wildfire emission inventory for Southwest China from 2001 to 2020. Daily fire radiative power data derived from 1 km MODIS Thermal Anomalies/Fire products (MOD14/MYD14) were used to calculate the FRE and combusted biomass. Available emission factors were assigned to three biomass burn types: forest, grass, and shrub fires. Over the span of two decades, we have compiled data and estimated the annual emissions of carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), sulfur dioxide (SO2), ammonia (NH3), nitrogen oxides (NOx), total particulate matter (TPM), black carbon (BC), organic carbon (OC), and non-methane volatile organic compounds (NMVOCs) to be 9809.13, 566.82, 25.79, 5.37, 12.25, 16.67, 133.53, 4.16, 41.81, and 97.23 Gg per year (Gg yr−1), respectively. In terms of fire type, forest fires accounted for the largest portion of total CO2 emissions (59.23%), with grass fires and shrub fires coming in second and third, accounting for 20.41% and 20.36%, respectively. Geographically, Yunnan Province were identified as the major contributor in Southwest China, accounting for 69.67% of the total emissions. Temporally, the maximum emission occurred in 2010 (24263.33 Gg), and the minimum emission occurred in 2017 (2917.66 Gg). And the emissions were mainly concentrated in February (23.33%), March (25.52%), and April (22.61%), which accounted for nearly three-fourths of the total emissions. The results of this study are much higher than those obtained by the burned area method, almost three times as high. In contrast, the results of this study are close to the fire emission data from the GFED4s and GFASv1.2 and QFEDv2.5r1 databases.
期刊介绍:
Atmospheric Pollution Research (APR) is an international journal designed for the publication of articles on air pollution. Papers should present novel experimental results, theory and modeling of air pollution on local, regional, or global scales. Areas covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.