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A critical assessment of provincial-level variation in agricultural GHG emissions in China.
Han, Jinyu; Qu, Jiansheng; Maraseni, Tek Narayan; Xu, Li; Zeng, Jingjing; Li, Hengji.
Afiliación
  • Han J; College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China. Electronic address: hanjy18@lzu.edu.cn.
  • Qu J; College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China; Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China. Electronic address: jsqu@lzb.ac.cn.
  • Maraseni TN; Institute for Agriculture and the Environment, University of Southern Queensland, Toowoomba, QLD, 4350, Australia.
  • Xu L; College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China.
  • Zeng J; Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China.
  • Li H; College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China; Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, 730000, China.
J Environ Manage ; 296: 113190, 2021 Oct 15.
Article en En | MEDLINE | ID: mdl-34271354
ABSTRACT
China is a world leader on agriculture production; with only 8% of global cropland it feeds 20% of the world's population. However, the increasing production capacity comes with the cost of greenhouse gas (GHG) emissions. As a populous country with the highest GHG emissions in the world, determining how to achieve the dual goals of mitigating climate change and ensuring food security is of great significance for the agricultural sector. This requires assessing the spatial variation in agricultural greenhouse gases (GHGs) and their drivers. In this study, we conduct a spatial assessment of agricultural GHGs at the provincial level in China for the years 1997-2017, and then explore the effects of related factors on GHG emissions using a geographically weighted regression (GWR) model. The results suggest the following. 1) There have always been significant interprovincial variations, whether in the total amount, structure, intensity, or per capita level of agricultural GHG emissions. 2) The directions of the effects of selected factors on GHG intensity fall broadly into three categories negative effects (urbanization, intensity of agricultural practices, and agricultural structure), positive effects (agricultural investment and cropland endowments), and mixed effects, with factors leading to reductions in some provinces and increases in others (economic level, frequency and intensity of disasters, and the level of mechanization). 3) The magnitude of the effects varies by factor and also by province. The results suggest synergetic province- or state-specific reduction policies in agricultural GHG for China, as well as for other developing and emerging economies.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Efecto Invernadero / Gases de Efecto Invernadero Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: J Environ Manage Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Efecto Invernadero / Gases de Efecto Invernadero Tipo de estudio: Prognostic_studies Límite: Humans País/Región como asunto: Asia Idioma: En Revista: J Environ Manage Año: 2021 Tipo del documento: Article