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Zhang M, Dong S, Li F, Xu S, Guo K, Liu Q. Spatial-Temporal Evolution and Improvement Measures of Embodied Carbon Emissions in Interprovincial Trade for Coal Energy Supply Bases: Case Study of Anhui, China. Int J Environ Res Public Health 2022; 19:ijerph192417033. [PMID: 36554913 PMCID: PMC9779169 DOI: 10.3390/ijerph192417033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Revised: 12/14/2022] [Accepted: 12/16/2022] [Indexed: 05/04/2023]
Abstract
On account of the long-term dependence on energy trade and the phenomenon of embodied carbon emissions in interprovincial trade (ECEs-IPT), energy supply bases (ESBs) in the economic integration regions (EIRs) are under unprecedented dual pressure of achieving carbon emissions (CEs) reduction targets and ensuring security and stability of the energy supply. This problem has attracted more and more attention and research by experts and scholars. This paper took Anhui, the coal ESB of the Yangtze River Economic Belt (YREB), as an example and took the key stage of rapid development of regional economic integration (REI) and accelerated the realization of CEs reduction targets in YREB from 2007 to 2017 as the study period. From the perspectives of regions and industry sectors, we calculated the transfer amount of ECEs-IPT in Anhui among the YREB, analyzed the spatial-temporal evolution pattern of ECEs-IPT, and revealed the industrial characteristics of ECEs-IPT. Then, we classified the industry sectors and proposed the direction of industrial improvement measures. The results showed that, during the decade, the amount of provinces undertaking the net ECEs-IPT outflow from Anhui increased significantly and spatially expanded from only Jiangxi Province to almost all of the YREB. In addition, 39.77% of the net ECEs-IPT outflow of Anhui was concentrated in petroleum processing, coking, and nuclear fuel processing (RefPetraol), metal smelting and rolling processing (MetalSmelt), and electricity and heat production and supply (ElectpowerProd) that trade with Shanghai, Jiangsu, Zhejiang, and Jiangxi. The analytical model and results will provide a useful reference for the global similar coal ESBs, especially the coal ESBs within the EIRs, to formulate improvement measures for regions or even the world to ensure stability of the energy supply and achieve regional CEs reduction targets.
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Affiliation(s)
- Menghan Zhang
- Research Office of Resource Economics and Energy and Mineral Resources, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Suocheng Dong
- Research Office of Resource Economics and Energy and Mineral Resources, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fujia Li
- Research Office of Resource Economics and Energy and Mineral Resources, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
- Innovation Academy for Green Manufacture, Chinese Academy of Sciences, Beijing 100190, China
- Correspondence:
| | - Shuangjie Xu
- Research Office of Resource Economics and Energy and Mineral Resources, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
- College of Geographical Sciences, Liaoning Normal University, Dalian 116029, China
| | - Kexin Guo
- Research Office of Resource Economics and Energy and Mineral Resources, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qian Liu
- Research Office of Resource Economics and Energy and Mineral Resources, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
- College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
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Ran D, Zhang Z, Jing Y. A Study on the Spatial-Temporal Evolution and Driving Factors of Non-Grain Production in China's Major Grain-Producing Provinces. Int J Environ Res Public Health 2022; 19:16630. [PMID: 36554509 PMCID: PMC9778755 DOI: 10.3390/ijerph192416630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 12/03/2022] [Accepted: 12/09/2022] [Indexed: 06/17/2023]
Abstract
Food self-sufficiency in a large country with 1.4 billion people is very important for the Chinese government, especially in the context of COVID-19 and the Russian-Ukrainian conflict. The objective of this paper is to explore the spatial-temporal evolution and driving factors of non-grain production in thirteen major grain-producing provinces in China, which account for more than 75% of China's grain production, using 2011-2020 prefecture-level statistics. In the present study, the research methodology included GIS spatial analysis, hot spot analysis, and spatial Durbin model (SDM). The findings of this study are as follows: (1) The regions with a higher level of non-grain production were mainly concentrated in the central and western regions of Inner Mongolia, the middle and lower reaches of Yangtze River and Sichuan, while the regions with a low level of non-grain production were mainly distributed in the Northeast Plain. The regions with a higher proportion of grain production to the national total grain production were concentrated in the Northeast Plain, the North China Plain, and the Middle and Lower Yangtze River Plain of China. The hot spot regions with changes in non-grain production levels were mainly distributed in the Sichuan region and Alashan League City in Inner Mongolia, and the cold spot regions were mainly distributed in Hebei, Shandong, Henan, and other regions. (2) An analysis of the SDM indicated that the average air temperature among the natural environment factors, the ratio of the sum of gross secondary and tertiary industries to GDP, the ratio of gross primary industry to the GDP of economic development level, the urbanization rate of social development, and the difference in disposable income per capita between urban and rural residents of the urban-rural gap showed positive spatial spillover effects. The grain yield per unit of grain crop sown area of grain production resource endowment, the total population of social development, and the area sown to grain crops per capita of grain production resource endowment all showed negative spatial spillover effects. The research results of this paper can provide a reference for the country to carry out the governance of non-grain production and provide a reference for China's food security guarantee.
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Affiliation(s)
- Duan Ran
- School of Public Administration and Policy, Renmin University of China, Beijing 100872, China
| | - Zhanlu Zhang
- School of Public Administration and Policy, Renmin University of China, Beijing 100872, China
| | - Yuhan Jing
- School of Marxism Studies, Chongqing University, Chongqing 400044, China
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