Global Emissions Inventory from Open Biomass Burning (GEIOBB): utilizing Fengyun-3D global fire spot monitoring data

被引:3
|
作者
Liu, Yang [1 ,2 ]
Chen, Jie [3 ,4 ]
Shi, Yusheng [1 ]
Zheng, Wei [3 ,4 ]
Shan, Tianchan [3 ,4 ]
Wang, Gang [5 ]
机构
[1] Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[2] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 101408, Peoples R China
[3] China Meteorol Adm, Innovat Ctr FengYun Meteorol Satellite, Natl Satellite Meteorol Ctr, Natl Ctr Space Weather, Beijing 100081, Peoples R China
[4] China Meteorol Adm, Natl Satellite Meteorol Ctr, Natl Ctr Space Weather, Key Lab Radiometr Calibrat & Validat Environm Sate, Beijing 100081, Peoples R China
[5] China Meteorol Adm, Natl Satellite Meteorol Ctr, Natl Ctr Space Weather, Guangzhou Meteorol Satellite Ground Stn, Guangzhou 510640, Peoples R China
基金
中国国家自然科学基金;
关键词
LONG-TERM TRENDS; INTERANNUAL VARIABILITY; AGRICULTURAL FIRES; RADIATIVE POWER; SOUTHEAST-ASIA; AIR-QUALITY; CLIMATE; RESOLUTION; SAVANNA; FOREST;
D O I
10.5194/essd-16-3495-2024
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Open biomass burning (OBB) significantly affects regional and global air quality, the climate, and human health. The burning of forests, shrublands, grasslands, peatlands, and croplands influences OBB. A global emissions inventory based on satellite fire detection enables an accurate estimation of OBB emissions. In this study, we developed a global high-resolution (1 kmx1 km) daily OBB emission inventory using the Chinese Fengyun-3D satellite's global fire spot monitoring data, satellite-derived biomass data, vegetation-index-derived spatiotemporally variable combustion efficiencies, and land-type-based emission factors. The average annual estimated OBB emissions for 2020-2022 were 2586.88 Tg C, 8841.45 Tg CO2, 382.96 Tg CO, 15.83 Tg CH4, 18.42 Tg NOx, 4.07 Tg SO2, 18.68 Tg particulate organic carbon (OC), 3.77 Tg particulate black carbon (BC), 5.24 Tg NH3, 15.85 Tg NO2, 42.46 Tg PM2.5 and 56.03 Tg PM10. Specifically, taking carbon emissions as an example, the average annual estimated OBBs for 2020-2022 were 72.71 (Boreal North America, BONA), 165.73 (Temperate North America, TENA), 34.11 (Central America, CEAM), 42.93 (Northern Hemisphere South America, NHSA), 520.55 (Southern Hemisphere South America, SHSA), 13.02 (Europe, EURO), 8.37 (Middle East, MIDE), 394.25 (Northern Hemisphere Africa, NHAF), 847.03 (Southern Hemisphere Africa, SHAF), 167.35 (Boreal Asia, BOAS), 27.93 (Central Asia, CEAS), 197.29 (Southeast Asia, SEAS), 13.20 (Equatorial Asia; EQAS), and 82.38 (Australia and New Zealand; AUST) Tg C yr(-1). Overall, savanna grassland burning contributed the largest proportion of the annual total carbon emissions (1209.12 Tg C yr(-1); 46.74 %), followed by woody savanna/shrubs (33.04 %) and tropical forests (12.11 %). SHAF was found to produce the most carbon emissions globally (847.04 Tg C yr(-1)), followed by SHSA (525.56 Tg C yr(-1)), NHAF (394.26 Tg C yr(-1)), and SEAS (197.30 Tg C yr(-1)). More specifically, savanna grassland burning was predominant in SHAF (55.00 %, 465.86 Tg C yr(-1)), SHSA (43.39 %, 225.86 Tg C yr(-1)), and NHAF (76.14 %, 300.21 Tg C yr(-1)), while woody savanna/shrub fires were dominant in SEAS (51.48 %, 101.57 Tg C yr(-1)). Furthermore, carbon emissions exhibited significant seasonal variability, peaking in September 2020 and August of 2021 and 2022, with an average of 441.32 Tg C month(-1), which is substantially higher than the monthly average of 215.57 Tg C month(-1). Our comprehensive high-resolution inventory of OBB emissions provides valuable insights for enhancing the accuracy of air quality modeling, atmospheric transport, and biogeochemical cycle studies. The GEIOBB dataset can be downloaded at http://figshare.com (last access: 30 July 2024) with the following DOI: https://doi.org/10.6084/m9.figshare.24793623.v2 (Liu et al., 2023).
引用
收藏
页码:3495 / 3515
页数:21
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