城市能源消费碳排放特征及其机理分析——以广州市为例
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摘要
采用表观能源消费数据进行分能源品种和分行业类型的碳排放总量核算,利用基于IDA理论和Kaya恒等式的LMDI模型对碳排放总量变化进行多要素的分解分析,在解析人口规模效应、经济产出效应、能源强度效应对碳排放影响机理的同时,进一步纳入人口结构性因素、产业结构性因素和能源结构性因素对碳排放的影响。以广州市为例,对其2003—2013年产业活动和居民消费2个部门碳排放的主要驱动因素进行时间序列分析,并定量研究各个影响因子在2003—2005、2005—2010和2010—2013年3个不同发展阶段的作用机理,主要研究结论如下:1)广州市能源消费及其碳排放前期以煤炭为主,近年来以石油为主,同时外购电力对广州市的能源消费结构优化影响显著。2)各影响因子对广州市碳排放总量变化的作用机理与影响机制在3个发展阶段各不相同,不同发展阶段的发展措施和政策背景对于各个影响因子的碳排放效应影响显著。3)总体分析,经济产出效应和人口规模效应是产业部门碳排放增长的最主要贡献因子;工业能源消费强度效应、工业能源消费结构效应和经济结构效应是遏制产业部门碳排放增长的最主要贡献因子。城镇居民收入效应是居民消费碳排放增长的最主要贡献因子,城镇居民能源消费强度效应是遏制居民消费碳排放增长的最主要贡献因子。
Cities are the main sources of carbon emissions throughout the world, which are also the major components in the implementation of carbon mitigation measures. Examining and understanding the features and drivers of carbon emissions in cities is considered a fundamental step for implementing "low carbon city" strategies and actions. Based on the apparent energy consumption data, a systematic and comprehensive city-level total carbon accounting approach was established and applied in Guangzhou City. A newly extended LMDI method based on the Kaya identity was adopted to examine the main drivers for carbon emissions increments both at the industrial sectors and the residential sectors. Economic, population and energy data were collected from the Guangdong Province Statistical Yearbook(2004-2014) and Guangzhou City Statistical Yearbook(2004-2014). The main contribution of our paper is providing an in depth analysis of energy-related carbon emissions at city level considering multiple factors in regional China. This paper also provides temporal variations in the influence factors of carbon emission over a period between 2003 and 2013. Research results show that coal consumption was still the main contributor to energy-related carbon emissions during the whole research period, while oil consumption played relatively important and positive effect on energy consumption structure optimization and carbon emissions mitigation. In addition, imported electricity played an important role in the energy consumption system in Guangzhou. Manufacturing industries and service industries were the main carbon emitting sectors in Guangzhou during the period from 2003 to 2014. Contributions of manufacturing industries for carbon emissions decreased gradually, while contributions of service industries for carbon emissions performed an increasing trend in recent years. The influences and impacts of various driving factors on industrial and residential carbon emissions are different in the three different development periods, namely, the 10 th five-year plan period(2003-2005), the 11 th five-year plan period(2005-2010), and the 12 th five-year plan period(2010-2013). Affluence effect was the dominant positive effect in driving emissions increase, while energy intensity effect of production, economic structure effect and carbon intensity effect of production were the main contributing factors suppressing emissions growth at the industrial sector. Affluence effect of urban areas was the most dominant positive driving factor on emissions increment, while energy intensity effect of urban areas played the most important role in curbing emissions growth at the residential sector. Solving these issues effectively will be of great help for Guangzhou's sustainable development.
Cities are the main sources of carbon emissions throughout the world, which are also the major components in the implementation of carbon mitigation measures. Examining and understanding the features and drivers of carbon emissions in cities is considered a fundamental step for implementing "low carbon city" strategies and actions. Based on the apparent energy consumption data, a systematic and comprehensive city-level total carbon accounting approach was established and applied in Guangzhou City. A newly extended LMDI method based on the Kaya identity was adopted to examine the main drivers for carbon emissions increments both at the industrial sectors and the residential sectors. Economic, population and energy data were collected from the Guangdong Province Statistical Yearbook(2004-2014) and Guangzhou City Statistical Yearbook(2004-2014). The main contribution of our paper is providing an in depth analysis of energy-related carbon emissions at city level considering multiple factors in regional China. This paper also provides temporal variations in the influence factors of carbon emission over a period between 2003 and 2013. Research results show that coal consumption was still the main contributor to energy-related carbon emissions during the whole research period, while oil consumption played relatively important and positive effect on energy consumption structure optimization and carbon emissions mitigation. In addition, imported electricity played an important role in the energy consumption system in Guangzhou. Manufacturing industries and service industries were the main carbon emitting sectors in Guangzhou during the period from 2003 to 2014. Contributions of manufacturing industries for carbon emissions decreased gradually, while contributions of service industries for carbon emissions performed an increasing trend in recent years. The influences and impacts of various driving factors on industrial and residential carbon emissions are different in the three different development periods, namely, the 10 th five-year plan period(2003-2005), the 11 th five-year plan period(2005-2010), and the 12 th five-year plan period(2010-2013). Affluence effect was the dominant positive effect in driving emissions increase, while energy intensity effect of production, economic structure effect and carbon intensity effect of production were the main contributing factors suppressing emissions growth at the industrial sector. Affluence effect of urban areas was the most dominant positive driving factor on emissions increment, while energy intensity effect of urban areas played the most important role in curbing emissions growth at the residential sector. Solving these issues effectively will be of great help for Guangzhou's sustainable development.
引文
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苟少梅,王长建,张利,乔梦梦,王璀蓉,王强.2012.1990―2010年广东省能源消费的碳排放驱动因素分析.热带地理,32(4):389-394,401.[Gou Shaomei,Wang Changjian,Zhang Li,Qiao Mengmeng,Wang Cuirong and Wang Qiang.2012.Variations and influence factors of carbon emission of primary energy consumption from 1990 to 2010in Guangdong Province.Tropical Geography,32(4):389-394,401.]
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Liang S,Zhang T,Wang Y and Jia X.2012.Sustainable urban materials management for air pollutants mitigation based on urban physical input-output model.Energy,42:387-392.
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Liu Z,Liang S,Geng Y,Xue B,Xi F,Pan Y,Zhang T and Fujita T.2012.Features,trajectories and driving forces for energy-related GHGemissions from Chinese mega cites:The case of Beijing,Tianjin,Shanghai and Chongqing.Energy,37:245-254.
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Lu Y,Chen B,Feng K and Hubacek K.2015.Ecological Network Analysis for Carbon Metabolism of Eco-industrial Parks:A Case Study of a Typical Eco-industrial Park in Beijing.Environ.Sci.Technol.,49:7254-7264.
李媛芳,张晓平.2015.中国城市居民生活用电碳排放差异及时空演变.热带地理,35(2):250-257.[Li Yuanfang and Zhang Xiaoping.2015.Regional Disparities and Spatial-Temporal Evolution of Carbon Emissions of Domestic Electricity Consumption in Urban China.Tropical Geography,35(2):250-257.]
刘英,赵荣钦,张战平,丁明磊,焦士兴.2018.城市开发区工业企业的碳排放效率比较--以南京江宁经济技术开发区为例.热带地理,38(1):103-111.[Liu Ying,Zhao Rongqin,Zhang Zhanping,Ding Minglei and Jiao Shixing.2018.Carbon Emission Efficiency of Different Industrial Companies of Urban Industrial Zone:A Case Study of Jiangning Economic and Technological Development Zone,Nanjing.Tropical Geography,38(1):103-111.]
Meng L,Graus W,Worrell E and Huang B.2014.Estimating CO2(carbon dioxide)emissions at urban scales by DMSP/OLS(Defense Meteorological Satellite Program’s Operational Linescan System)nighttime light imagery:Methodological challenges and a case study for China.Energy,71:468-478.
Meng J,Mi Z,Yang H,Shan Y,Guan D and Liu J.2017.The consumption-based black carbon emissions of China’s megacities.Journal of Cleaner Production,161:1275-1282.
Mi Z,Zhang Y,Guan D,Shan Y,Liu Z,Cong R,Yuan X C and Wei YM.2016.Consumption-based emission accounting for Chinese cities.Applied Energy,184:1073-1081.
Ming Z,Honglin L,Mingjuan M,Na L,Song X,Liang W and Lilin P.2013.Review on transaction status and relevant policies of southern route in China’s West-East Power Transmission.Renewable Energy,60:454-461.
Shao S,Yang L,Yu M and Yu M.2011.Estimation,characteristics,and determinants of energy-related industrial CO2 emissions in Shanghai(China),1994-2009.Energy Policy,39:6476-6494.
Shao S,Yang L,Gan C,Cao J,Geng Y and Guan D.2016.Using an extended LMDI model to explore techno-economic drivers of energyrelated industrial CO2 emission changes:A case study for Shanghai(China).Renewable and Sustainable Energy Reviews,55:516-536.
Su Y,Chen X,Li Y,Liao J,Ye Y,Zhang H,Huang N and Kuang Y.2014.China’s 19-year city-level carbon emissions of energy consumptions,driving forces and regionalized mitigation guidelines.Renewable and Sustainable Energy Reviews,35:231-243.
Sugar L,Kennedy C and Leman E.2012.Greenhouse gas emissions from Chinese cities.Journal of Industrial Ecology,16:552-563.
TAN X,Dong L,Chen D,Gu B and Zeng Y.2016.China’s regional CO2emissions reduction potential:A study of Chongqing city.Applied Energy,162:1345-1354.
Tian X,Chang M,Tanikawa H,Shi F and Imura H.2013.Structural decomposition analysis of the carbonization process in Beijing:Aregional explanation of rapid increasing carbon dioxide emission in China.Energy Policy,53:279-286.
Vause J,Gao L,Shi L and Zhao J.2013.Production and consumption accounting of CO2 emissions for Xiamen,China.Energy Policy,60:697-704.
Wang M,Che Y,Yang K,Wang M,Xiong L and Huang Y.2011.Alocal-scale low-carbon plan based on the STIRPAT model and the scenario method:The case of Minhang District,Shanghai,China.Energy Policy,39:6981-6990.
Wang Z,Yin F,Zhang Y and Zhang X.2012.An empirical research on the influencing factors of regional CO2 emissions:Evidence from Beijing city,China.Applied Energy,100:277-284.
Wang Y,Ma W,Tu W,Zhao Q and Yu Q.2013a.A study on carbon emissions in Shanghai 2000-2008,China.Environ.Sci.Policy,27:151-161.
Wang Y,Zhao H,Li L,Liu Z and Liang S.2013b.Carbon dioxide emission drivers for a typical metropolis using input-output structural decomposition analysis.Energy Policy,58:312-318.
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