Journal of Guangdong University of Technology ›› 2021, Vol. 38 ›› Issue (05): 90-96.doi: 10.12052/gdutxb.200145
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Lu Xiao-qing1, Fang Yuan1, Liang Ze-qi2
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[1] PAN W, TU H T, HU C, et al. Driving forces of China's multisector CO2 emissions: a Log-Mean Divisia Index decomposition[J]. Environmental Science and Pollution Research, 2020, 27: 23550-23564. [2] WU Y, CHAU K W, LU W S, et al. Decoupling relationship between economic output and carbon emission in the Chinese construction industry[J]. Environmental Impact Assessment Review, 2018, 71: 60-69. [3] MA X J, WANG C X, DONG B Y, et al. Carbon emissions from energy consumption in China: Its measurement and driving factors[J]. The science of the Total Environment, 2018, 648: 1411-1420. [4] WANG P, WU W S, ZHU B Z, et al. Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China[J]. Applied Energy, 2013, 106: 65-71. [5] WANG C J, WANG F, ZHANG X L, et al. Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang[J]. Renewable and Sustainable Energy Reviews, 2017, 67: 51-61. [6] XU B, LIN B Q. Factors affecting CO2 emissions in China's agriculture sector: Evidence from geographically weighted regression model [J]. Energy Policy, 2017, 104: 404-414. [7] CHEN Y, LI M, SU K, et al. Spatial-Temporal Characteristics of the Driving Factors of Agricultural Carbon Emissions: Empirical Evidence from Fujian, China[J]. Energies, 2019, 12. [8] LIU Y, TANG H, MUHAMMAD A, et al. Emission mechanism and reduction countermeasures of agricultural greenhouse gases —— a review [J]. Greenhouse Gases-Science and Technology, 2019, 9(2): 160-174. [9] XIONG C H, YANG D G, XIA F Q, et al. Changes in agricultural carbon emissions and factors that influence agricultural carbon emissions based on different stages in Xinjiang, China [J]. Scientific Reports, 2016, 6(1). [10] HAN H B, ZHONG Z Q, GUO Y, et al. Coupling and decoupling effects of agricultural carbon emissions in china and their driving factors [J]. Environmental Science and Pollution Research, 2018, 25(9): 1-14. [11] LI N, WEI C D, ZHANG H, et al. Drivers of the national and regional crop production-derived greenhouse gas emissions in China[J]. Journal of Cleaner Production, 2020, 257. [12] ZHEN W, QIN Q D, KUANG Y Q, et al. Investigating low-carbon crop production in Guangdong province, China (1993–2013): a decoupling and decomposition analysis[J]. Journal of Cleaner Production, 2017, 146: 63-70. [13] XIONG C H, CHEN S, XU L T. Driving factors analysis of agricultural carbon emissions based on extended STIRPAT model of Jiangsu Province, China [J]. Growth and Change, 2020, 51(3): 1401-1416. [14] YANG Y, JIA J S, CHEN C D. Residential Energy-Related CO2 Emissions in China’s Less Developed Regions: A Case Study of Jiangxi [J]. Sustainability, 2020, 12(5). [15] WANG Z H, YANG L. Indirect carbon emissions in household consumption: evidence from the urban and rural area in China[J]. Journal of Cleaner Production, 2014, 78: 94-103. [16] CHEN Q, YANG H R, WANG W G, et al. Beyond the City: Effects of Urbanization on Rural Residential Energy Intensity and CO2 Emissions [J]. Sustainability, 2019, 11(8). [17] ZHA D L, ZHOU D Q, ZHOU P. Driving forces of residential CO2 emissions in urban and rural China: An index decomposition analysis [J]. Energy Policy, 2010, 38(7): 3377-3383. [18] FAN J B, RAN A, LI X M. A study on the factors affecting china's direct household carbon emission and comparison of regional differences [J]. Sustainability, 2019, 11(18). [19] WANG W X, ZHAO D Q, KUANG Y Q. Decomposition analysis on influence factors of direct household energy-related carbon emission in Guangdong province —— Based on extended Kaya identity [J]. Sustainable Energy, 2016, 35(1): 298-307. [20] DONG Y M, ZHAO T. Difference analysis of the relationship between household per capita income, per capita expenditure and per capita CO2 emissions in China: 1997—2014 [J]. Atmospheric Pollution Research, 2017, 8(2): 310-319. [21] QIU H G, YAN J B, LEI Z, et al. Rising wages and energy consumption transition in rural China[J]. Energy Policy, 2018, 119: 545-553. [22] SALAHUDDIN M, GOW J, OZTURK I. Is the long-run relationship between economic growth, electricity consumption, carbon dioxide emissions and financial development in Gulf Cooperation Council Countries robust?[J]. Renewable & Sustainable Energy Reviews, 2015, 51: 317-326. [23] ANG B W. Decomposition analysis for policy making in energy: which is the preferred method? [J]. Energy Policy, 2004, 32(9): 1131-1139. [24] YORK R, ROSA E A, DIETZ T. STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts [J]. Ecological Economics, 2003, 46(3): 351-365. [25] ANG B W, LIU F L, CHUNG H S. A generalized Fisher index approach to energy decomposition analysis [J]. Energy Economics, 2004, 26(5): 757-763. [26] LI W, SHEN Y B, ZHANG H X. A Factor Decomposition on China's Carbon Emission from 1997 to 2012 Based on IPAT-LMDI Model[J]. Mathematical Problems in Engineering, 2015, 2015: 1-14. [27] TAPIO P. Towards a theory of decoupling: degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001 [J]. Transport Policy, 2005, 12(2): 137-151. [28] LI X, HE X, LUO X, et al. Exploring the characteristics and drivers of indirect energy consumption of urban and rural households from a sectoral perspective [J]. Greenhouse Gases-Science and Technology, 2020, 10(5): 907-924. [29] MIAO L, GU H, ZHANG X, et al. Factors causing regional differences in China's residential CO2 emissions — Evidence from provincial data[J]. Journal of Cleaner Production, 2019, 224: 852-863. |
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