Features and drivers for energy-related carbon emissions in mega city: The case of Guangzhou, China based on an extended LMDI model

被引:29
作者
Wang, Changjian [1 ]
Wu, Kangmin [1 ]
Zhang, Xinlin [2 ]
Wang, Fei [3 ]
Zhang, Hongou [1 ]
Ye, Yuyao [1 ]
Wu, Qitao [1 ]
Huang, Gengzhi [1 ]
Wang, Yang [1 ]
Wen, Bin [4 ]
机构
[1] Guangzhou Inst Geog, Guangdong Open Lab Geospatial Informat Technol &, Key Lab Guangdong Utilizat Remote Sensing & Geog, Guangzhou, Guangdong, Peoples R China
[2] Jiangsu Normal Univ, Sch Geog Geomat & Planning, Xuzhou, Jiangsu, Peoples R China
[3] Xinjiang Normal Univ, Coll Geog Sci & Tourism, Urumqi, Peoples R China
[4] Huanghuai Univ, Coll Econ & Management, Zhumadian, Peoples R China
来源
PLOS ONE | 2019年 / 14卷 / 02期
基金
中国国家自然科学基金;
关键词
GREENHOUSE-GAS EMISSIONS; COMMERCIAL BUILDING SECTOR; STRUCTURAL DECOMPOSITION ANALYSIS; CO2; EMISSIONS; GHG EMISSIONS; INPUT-OUTPUT; POLICY IMPLICATIONS; DIOXIDE EMISSION; ECONOMIC-GROWTH; CONSUMPTION;
D O I
10.1371/journal.pone.0210430
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Based on the apparent energy consumption data, a systematic and comprehensive city-level total carbon accounting approach was established and applied in Guangzhou, China. A newly extended LMDI method based on the Kaya identity was adopted to examine the main drivers for the carbon emissions increments both at the industrial sector and the residential sector. Research results are listed as follow: (1) Carbon emissions embodied in the imported electricity played a significant important role in emissions mitigation in Guangzhou. (2) The influences and impacts of various driving factors on industrial and residential carbon emissions are different in the three different development periods, namely, the 10th five-year plan period (2003-2005), the 11th five-year plan period (2005-2010), and the 12th five-year plan period (2010-2013). The main reasons underlying these influencing mechanisms were different policy measures announced by the central and local government during the different five-year plan periods. (3) The affluence effect (g-effect) was the dominant positive effect in driving emissions increase, while the energy intensity effect of production (e-effect-Production), the economic structure effect (s-effect) and the carbon intensity effect of production (f-effect-Production) were the main contributing factors suppressing emissions growth at the industrial sector. (4) The affluence effect of urban (g-effect-AUI) was the most dominant positive driving factor on emissions increment, while the energy intensity effect of urban (e-effect-Urban) played the most important role in curbing emissions growth at the residential sector.
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页数:22
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