Spatial-temporal variation and nonlinear prediction of environmental footprints and comprehensive environmental pressure in urban agglomerations
文献类型:期刊论文
作者 | Chen, Yizhong2; Qiao, Youfeng2; Yan, Pengdong1; Lu, Hongwei3; Yang, Lingzhi2; Xia, Jun3,4 |
刊名 | JOURNAL OF CLEANER PRODUCTION
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出版日期 | 2022-06-01 |
卷号 | 351页码:15 |
关键词 | Water-carbon-ecological footprints Comprehensive environmental pressure Nonlinear grey Bernoulli projection model Urban agglomerations Coupling coordination degree |
ISSN号 | 0959-6526 |
DOI | 10.1016/j.jclepro.2022.131556 |
英文摘要 | It is necessary to evaluate the comprehensive environmental pressure (CEP) for achieving the Sustainable Development Goals. Water-carbon-ecological footprints (named as WF, CF, and EF3D) and Nonlinear Grey Bernoulli projection model are integrated for identifying the CEP in the urban agglomerations of Cheng-Yu district (UAC), middle reaches of the Yangtze River (UAM), and Yangtze River Delta (UAD). Results reveal that the general water resources system is quite satisfactory. The annual growth rate of CF is approximately 4.93%, mostly contributed by raw coal consumption. Natural resources consumption exceeds the ecosystem carrying capacity due to the increased ecological deficit (above 3.0 hm(2)/cap). The average ecological footprint depth reaches 24.61, 17.59, and 30.89 in the UAC, UAM, and UAD, respectively, implying higher than 17 times its own land area required for supporting regional resource consumption. The growth rates of CEP are 3.53%, 2.86%, and 6.85% in the UAC, UAM, and UAD, respectively, above 80% of which is from carbon and ecological pressure. In terms of the coupling coordination degree of environmental footprints, results disclose that the resources consumption structure is improved in the UAM and UAD, but it is in an unfavorable direction for the UAC. Moreover, the future environmental footprints and CEP will continuously increase. Some measures, such as energy-saving and emission-reduction technologies, thus should be further strengthened. |
WOS关键词 | GREY BERNOULLI MODEL ; ECOLOGICAL FOOTPRINT ; WATER FOOTPRINT ; CHINA ; OPTIMIZATION ; INDICATORS |
资助项目 | National Natural Science Foundation of China[42107479,41890824] ; Natural Science Foundation of Hebei Province[E2020202117] ; Second Tibetan Plateau Scientific Expedition and Research Program (STEP)[2019QZKK1003] ; Science and Technology Project of Hebei Edu-cation Department[BJ2020019] |
WOS研究方向 | Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology |
语种 | 英语 |
WOS记录号 | WOS:000791198600003 |
出版者 | ELSEVIER SCI LTD |
资助机构 | National Natural Science Foundation of China ; Natural Science Foundation of Hebei Province ; Second Tibetan Plateau Scientific Expedition and Research Program (STEP) ; Science and Technology Project of Hebei Edu-cation Department |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/176121] ![]() |
专题 | 陆地水循环及地表过程院重点实验室_外文论文 |
作者单位 | 1.Tianjin Univ, State Key Lab Hydraul Engn Simulat & Safety, Tianjin 300072, Peoples R China 2.Hebei Univ Technol, Sch Econ & Management, Tianjin 300401, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 4.Wuhan Univ, State Key Lab Water Resources & Hydropower Engn Sc, Wuhan 430000, Peoples R China |
推荐引用方式 GB/T 7714 | Chen, Yizhong,Qiao, Youfeng,Yan, Pengdong,et al. Spatial-temporal variation and nonlinear prediction of environmental footprints and comprehensive environmental pressure in urban agglomerations[J]. JOURNAL OF CLEANER PRODUCTION,2022,351:15. |
APA | Chen, Yizhong,Qiao, Youfeng,Yan, Pengdong,Lu, Hongwei,Yang, Lingzhi,&Xia, Jun.(2022).Spatial-temporal variation and nonlinear prediction of environmental footprints and comprehensive environmental pressure in urban agglomerations.JOURNAL OF CLEANER PRODUCTION,351,15. |
MLA | Chen, Yizhong,et al."Spatial-temporal variation and nonlinear prediction of environmental footprints and comprehensive environmental pressure in urban agglomerations".JOURNAL OF CLEANER PRODUCTION 351(2022):15. |
入库方式: OAI收割
来源:地理科学与资源研究所
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