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Dataset of top-down nitrogen oxides fire emission estimation in northeastern Asia.
Fu, Yuyun; Li, Rui; Hu, Jiheng; Wang, Yipu; Duan, Jiawei.
Afiliação
  • Fu Y; State Key Laboratory of Fire Science, MEM Key Laboratory of Forest Fire Monitoring and Warning, School of Earth and Space Sciences, Comparative Planetary Excellence Innovation Center, University of Science and Technology of China, Hefei 230026, China.
  • Li R; Institut de recherche sur les forêts, Université du Québec en Abitibi-Témiscamingue (UQAT), Rouyn-Noranda J9 × 5E4, Canada.
  • Hu J; State Key Laboratory of Fire Science, MEM Key Laboratory of Forest Fire Monitoring and Warning, School of Earth and Space Sciences, Comparative Planetary Excellence Innovation Center, University of Science and Technology of China, Hefei 230026, China.
  • Wang Y; Institut de recherche sur les forêts, Université du Québec en Abitibi-Témiscamingue (UQAT), Rouyn-Noranda J9 × 5E4, Canada.
  • Duan J; State Key Laboratory of Fire Science, MEM Key Laboratory of Forest Fire Monitoring and Warning, School of Earth and Space Sciences, Comparative Planetary Excellence Innovation Center, University of Science and Technology of China, Hefei 230026, China.
Data Brief ; 45: 108734, 2022 Dec.
Article em En | MEDLINE | ID: mdl-36426019
Fire emission is a major source of atmospheric nitrogen oxides (NOx = NO2 + NO), accounting for a large part of global NOx emission, which profoundly changes atmosphere physicochemical property and impacts human society. An effective evaluation of these impacts relies on accurate NOx fire emission estimation. In this article, we developed a full top-down NOx fire emission dataset for northeastern Asia based on the satellite-derived emission coefficient (EC) and fire radiative power (FRP) density. In the dataset, daily NOx fire emissions during 2012-2019 were estimated at 1°x1° resolution across northeastern Asia, which can be used as fundamental input data in driving climate and weather models, and can be applied to investigate the characteristic of fire emission, fire-climate interaction, air pollution and human health effect. As a full top-down emission dataset, it can also serve as a reference for other existing emission inventories that are mostly based on bottom-up approaches.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Data Brief Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Data Brief Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China