海岛城市碳排放测度及其影响因素分析——以浙江省舟山市为例
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摘要
海岛城市具有独特的社会经济发展轨迹以及碳排放特征。定量剖析海岛城市碳排放的演变趋势及其关键驱动因子,对于指导"低碳海岛城市"和"生态海岛城市"建设意义重大。以中国典型海岛城市舟山市为案例区,采用IPCC参考方法,测算2001-2015年间舟山市各部门的碳排放量,并运用STIRPAT扩展模型,定量分析能源强度、人均GDP以及城市化率等关键驱动因子对海岛城市碳排放的影响;在此基础上,结合情景分析技术对舟山市未来的碳排放量进行情景预测。结果表明:(1)2001-2015年间,舟山市碳排放量增加迅速,年均增长率达到32%,碳排放强度遵从先降后增的"U型"变化规律,年均值略高于厦门市。(2)岭回归分析表明城市化率对碳排放量的增加影响最大,其次为能源强度,人均GDP对碳排放的影响最弱。(3)舟山市经济增长与碳排放之间存在Kuznets曲线假说,且理论拐点将出现在人均GDP为10.46万元附近(2000年可比价)。(4)舟山市在2020年和2030年的碳排放总量将分别达到2142万t和4333万t。总体而言,产业结构低碳化和能源效率提升是缓解舟山市未来碳减排压力的有力抓手。
Island cities have unique economic development paths and characteristics of carbon emissions. Quantitatively examining the evolution trends and influencing factors of carbon emissions in island cities will play an important role in guiding the constructions of "lowcarbon city" and "eco-city". In this study, we chose Zhoushan Islands as a case study and used the IPCC guidelines methods to estimate its multi-sectoral carbon emissions during 2001-2015.Meanwhile, the STIRPAT model was applied to analyze the effects of energy intensity, GDP per capita and urbanization rate on carbon emissions. Based on the carbon emission effects, the future carbon emissions of Zhoushan Islands were then predicted by setting various socioeconomic scenarios. The results indicated that the carbon emissions in Zhoushan have a dramatical increase, with an annual growth rate of 32% since 2001, while carbon emissions intensity followed the U-shaped changing trend, and its annual mean value was higher than that of Xiamen city. In addition, the disaggregated analysis revealed urbanization rate was the most robust driving factor of increasing carbon emissions, and energy intensity was the secondary,and GDP per capita was the weakest factor. We also found evidences in support of inverted Ushaped curve relationship between economic growth and carbon emissions, and the theory inflection point of CO_2 emissions was found at 10.46×10~4 yuan of GDP per capita(calculated at2000 comparable prices). According to our prediction, the total amount of carbon emissions in Zhoushan Islands by 2020 and 2030 may reach 2142 × 10~4 t CO_2 e, and 4333 × 10~4 t CO_2 e,respectively. Overall, we suggested that low-carbonization of industrial structure and the improvement of energy efficiency would be the effective measures for future carbon emissions reduction of Zhoushan Islands.
Island cities have unique economic development paths and characteristics of carbon emissions. Quantitatively examining the evolution trends and influencing factors of carbon emissions in island cities will play an important role in guiding the constructions of "lowcarbon city" and "eco-city". In this study, we chose Zhoushan Islands as a case study and used the IPCC guidelines methods to estimate its multi-sectoral carbon emissions during 2001-2015.Meanwhile, the STIRPAT model was applied to analyze the effects of energy intensity, GDP per capita and urbanization rate on carbon emissions. Based on the carbon emission effects, the future carbon emissions of Zhoushan Islands were then predicted by setting various socioeconomic scenarios. The results indicated that the carbon emissions in Zhoushan have a dramatical increase, with an annual growth rate of 32% since 2001, while carbon emissions intensity followed the U-shaped changing trend, and its annual mean value was higher than that of Xiamen city. In addition, the disaggregated analysis revealed urbanization rate was the most robust driving factor of increasing carbon emissions, and energy intensity was the secondary,and GDP per capita was the weakest factor. We also found evidences in support of inverted Ushaped curve relationship between economic growth and carbon emissions, and the theory inflection point of CO_2 emissions was found at 10.46×10~4 yuan of GDP per capita(calculated at2000 comparable prices). According to our prediction, the total amount of carbon emissions in Zhoushan Islands by 2020 and 2030 may reach 2142 × 10~4 t CO_2 e, and 4333 × 10~4 t CO_2 e,respectively. Overall, we suggested that low-carbonization of industrial structure and the improvement of energy efficiency would be the effective measures for future carbon emissions reduction of Zhoushan Islands.
引文
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[14]黄蕊,王铮,丁冠群,等.基于STIRPAT模型的江苏省能源消费碳排放影响因素分析及趋势预测.地理研究,2016,35(4):781-789.[Huang Rui,Wang Zheng,Ding Guanqun,et al.Trend prediction and analysis of influencing factors of carbon emissions from energy consumption in Jiangsu province based on STIRPAT model.Geographical Research,2016,35(4):781-789.]
[15]Wang P,Wu W S,Zhu B Z,et al.Examining the impact factors of energy-related CO2emissions using the STIRPAT model in Guangdong Province,China.Applied Energy,2013,106:65-71.
[16]卢娜,曲福田,冯淑怡,等.基于STIRPAT模型的能源消费碳足迹变化及影响因素:以江苏省苏锡常地区为例.自然资源学报,2011,26(5):814-824.[Lu Na,Qu Futian,Feng Shuyi,et al.Trends and determining factors of energy consumption carbon footprint:Analysis for Suzhou-Wuxi-Changzhou region based on STIRPAT model.Journal of Natural Resources,2011,26(5):814-824.]
[17]陆大道.中速增长:中国经济的可持续发展.地理科学,2015,35(10):1207-1219.[Lu Dadao.Moderate-speed growth:Sustainable development of China's economy.Scientia Geographica Sinica,2015,35(10):1207-1219.]
[18]黄蕊,王铮.基于STIRPAT模型的重庆市能源消费碳排放影响因素研究.环境科学学报,2013,33(2):602-608.[Huang Rui,Wang Zheng.Influencing factors of carbon emissions from energy consumptions in Chongqing based on STIRPAT model.Acta Scientiae Circumstantiae,2013,33(2):602-608.]
[19]燕华,郭运功,林逢春.基于STIRPAT模型分析CO2控制下上海城市发展模式.地理学报,2010,65(8):983-990.[Yan Hua,Guo Yungong,Lin Fengchun.Analyzing the developing model of Chinese cities under the control of CO2emissions using the STIRPAT model:A case study of Shanghai.Acta Geographica Sinica,2010,65(8):983-990.]
[20]朱远程,张士杰.基于STIRPAT模型的北京地区经济碳排放驱动因素分析.特区经济,2012,(1):77-79.[Zhu Yuancheng,Zhang Shijie.Analyzing the driving factors of carbon emissions in Beijing based on STIRPAT model.Special Zone Economy,2012,(1):77-79.]
[21]Wang M W,Che Y,Yang K,et al.A local-scale low-carbon plan based on the STIRPAT model and the scenario method:The case of Minhang District,Shanghai,China.Energy Policy,2011,39(11):6981-6990.
[22]孙昌龙,靳诺,张小雷,等.城市化不同演化阶段对碳排放的影响差异.地理科学,2013,33(3):266-272.[Sun Changlong,Jin Nuo,Zhang Xiaolei,et al.The impact of urbanization on the CO2emission in the various development stages.Scientia Geographica Sinica,2013,33(3):266-272.]
[23]林伯强,蒋竺均.中国二氧化碳的环境库兹涅茨曲线预测及影响因素分析.管理世界,2009,(4):27-36.[Lin Boqiang,Jiang Zhujun.Analyzing the influencing factors and Kuznets curves prediction of Chinese CO2.Management World,2009,(4):27-36.]
[24]刘源,李向阳,林剑艺,等.基于LMDI分解的厦门市碳排放强度影响因素分析.生态学报,2014,34(9):2378-2387.[Liu Yuan,Li Xiangyang,Lin Jianyi,et al.Factor decomposition of carbon intensity in Xiamen City based on LMDI method.Acta Ecologica Sinica,2014,34(9):2378-2387.]
[2]卢俊宇,黄贤金,陈逸,等.基于能源消费的中国省级区域碳足迹时空演变分析.地理研究,2013,32(2):326-336.[Lu Junyu,Huang Xianjin,Chen Yi,et al.Spatiotemporal changes of carbon footprint based on energy consumption in China.Geographical Research,2013,32(2):326-336.]
[3]IPCC(Intergovernmental Panel on Climate Change).Climate Change 2007:the physical science basis.Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.Cambridge,UK:Cambridge University Press,2007:44-45.
[4]Quah A K L,Roth M.Diurnal and weekly variation of anthropogenic heat emission in a tropical city,Singapore.Atmospheric Environment,2012,46(1):92-103.
[5]方创琳,王少剑,王洋.中国低碳生态新城新区:现状、问题及对策.地理研究,2015,35(9):1601-1614.[Fang Chuanglin,Wang Shaojian,Wang Yang.Current situation and countermeasures of Chinese low-carbon eco-metro area development.Geographical Research,2015,35(9):1601-1614.]
[6]秦伟山,张义丰.国内外海岛经济研究进展.地理科学进展,2013,32(9):1401-1412.[Qin Weishan,Zhang Yifeng.Research progress on island economy.Progress in Geography,2013,32(9):1401-1412.]
[7]周晟吕,胡静,李立峰.崇明岛中长期碳排放预测及其影响因素分析.长江流域资源与环境,2015,24(4):632-639.[Zhou Sehnglv,Hu Jing,Li Lifeng.Prediction of Chongming Island's medium and long-term carbon emissions and its influencing factors analysis.Resources and Environment in Yangtze Basin,2015,24(4):632-639.]
[8]林剑艺,孟凡鑫,崔胜辉,等.城市能源利用碳足迹分析:以厦门市为例.生态学报,2012,32(12):3782-3794.[Lin Jianyi,Meng Fanxin,Cui Shenghui,et al.Carbon footprint analysis on urban energy use:A case study of Xiamen,China.Acta Ecologica Sinica,2012,32(12):3782-3794.]
[9]Kuo N W,Chen P H.Quantifying energy use,carbon dioxide emission,and other environmental loads from island tourism based on a life cycle assessment approach.Journal of Cleaner Production,2009,17:1324-1330.
[10]Shirley R,Jones C,Kammen D.A household carbon footprint calculator for islands:Case study of the United States Virgin Islands.Ecological Economics,2012,80(2):8-14.
[11]肖建红,于爱芬,王敏.旅游过程碳足迹评估:以舟山群岛为例.旅游科学,2011,25(4):58-66.[Xiao Jianhong,Yu Aifen,Wang Min.Carbon footprint evaluation in tours:A case study of Zhoushan Islands.Tourism Science,2011,25(4):58-66.]
[12]王海鲲,张荣荣,毕军.中国城市碳排放核算研究:以无锡市为例.中国环境科学,2011,31(6):1029-1038.[Wang Haikun,Zhang Rongrong,Bi Jun.Carbon accounting for chinese cities:A case of Wuxi City.China Environmental Science,2011,31(6):1029-1038.]
[13]Lin J Y,Liu Y,Meng F X,et al.Using hybrid method to evaluate carbon footprint of Xiamen City,China.Energy Policy,2013,58(5):220-227.
[14]黄蕊,王铮,丁冠群,等.基于STIRPAT模型的江苏省能源消费碳排放影响因素分析及趋势预测.地理研究,2016,35(4):781-789.[Huang Rui,Wang Zheng,Ding Guanqun,et al.Trend prediction and analysis of influencing factors of carbon emissions from energy consumption in Jiangsu province based on STIRPAT model.Geographical Research,2016,35(4):781-789.]
[15]Wang P,Wu W S,Zhu B Z,et al.Examining the impact factors of energy-related CO2emissions using the STIRPAT model in Guangdong Province,China.Applied Energy,2013,106:65-71.
[16]卢娜,曲福田,冯淑怡,等.基于STIRPAT模型的能源消费碳足迹变化及影响因素:以江苏省苏锡常地区为例.自然资源学报,2011,26(5):814-824.[Lu Na,Qu Futian,Feng Shuyi,et al.Trends and determining factors of energy consumption carbon footprint:Analysis for Suzhou-Wuxi-Changzhou region based on STIRPAT model.Journal of Natural Resources,2011,26(5):814-824.]
[17]陆大道.中速增长:中国经济的可持续发展.地理科学,2015,35(10):1207-1219.[Lu Dadao.Moderate-speed growth:Sustainable development of China's economy.Scientia Geographica Sinica,2015,35(10):1207-1219.]
[18]黄蕊,王铮.基于STIRPAT模型的重庆市能源消费碳排放影响因素研究.环境科学学报,2013,33(2):602-608.[Huang Rui,Wang Zheng.Influencing factors of carbon emissions from energy consumptions in Chongqing based on STIRPAT model.Acta Scientiae Circumstantiae,2013,33(2):602-608.]
[19]燕华,郭运功,林逢春.基于STIRPAT模型分析CO2控制下上海城市发展模式.地理学报,2010,65(8):983-990.[Yan Hua,Guo Yungong,Lin Fengchun.Analyzing the developing model of Chinese cities under the control of CO2emissions using the STIRPAT model:A case study of Shanghai.Acta Geographica Sinica,2010,65(8):983-990.]
[20]朱远程,张士杰.基于STIRPAT模型的北京地区经济碳排放驱动因素分析.特区经济,2012,(1):77-79.[Zhu Yuancheng,Zhang Shijie.Analyzing the driving factors of carbon emissions in Beijing based on STIRPAT model.Special Zone Economy,2012,(1):77-79.]
[21]Wang M W,Che Y,Yang K,et al.A local-scale low-carbon plan based on the STIRPAT model and the scenario method:The case of Minhang District,Shanghai,China.Energy Policy,2011,39(11):6981-6990.
[22]孙昌龙,靳诺,张小雷,等.城市化不同演化阶段对碳排放的影响差异.地理科学,2013,33(3):266-272.[Sun Changlong,Jin Nuo,Zhang Xiaolei,et al.The impact of urbanization on the CO2emission in the various development stages.Scientia Geographica Sinica,2013,33(3):266-272.]
[23]林伯强,蒋竺均.中国二氧化碳的环境库兹涅茨曲线预测及影响因素分析.管理世界,2009,(4):27-36.[Lin Boqiang,Jiang Zhujun.Analyzing the influencing factors and Kuznets curves prediction of Chinese CO2.Management World,2009,(4):27-36.]
[24]刘源,李向阳,林剑艺,等.基于LMDI分解的厦门市碳排放强度影响因素分析.生态学报,2014,34(9):2378-2387.[Liu Yuan,Li Xiangyang,Lin Jianyi,et al.Factor decomposition of carbon intensity in Xiamen City based on LMDI method.Acta Ecologica Sinica,2014,34(9):2378-2387.]