基于理论碳赤字的东北三省碳补偿费用预测
|
摘要
碳补偿是全球气候变暖和低碳发展背景下产生的生态补偿研究新领域。本文基于足迹理论,提出理论碳赤字的概念,对地区间碳补偿费用的核算方法进行了改进,并采用灰色预测模型GM (1,1)预测了2017—2026年东北三省地区间碳补偿费用。研究结果表明:2003—2016年,东北三省的碳排放量总体呈上升趋势,但增速有所放缓,减排工作初见成效;东北三省各省份的碳吸收量呈稳步上升状态,环境保护工作持续推进。2017—2026年东北三省各省份的实际碳赤字均为正值,但实际碳赤字增长速度均呈下降趋势,整个生态环境朝着良性状态发展;东北三省中,辽宁省为绝对碳补偿主体,吉林省和黑龙江省为绝对碳受偿主体,大体上为经济发展水平较高地区补偿经济发展水平较低地区,符合区域协调发展的理念。本文的研究结果能够为东北三省建立和完善地区间碳补偿机制,测算碳补偿费用提供合理参考。
Carbon compensation is a new field of ecological compensation research under the background of global warming and low carbon development. Based on the footprint theory,this paper puts forward the concept of theoretical carbon deficit,improves the accounting method of carbon compensation cost among regions,and forecasts the carbon compensation cost of northeast three provinces from 2017 to 2026 using the grey prediction model GM(1,1). The results show that: first,from 2003 to 2016,the carbon emissions of the three provinces in northeast China showed an upward trend on the whole,but the rate of increase slowed down. Second,from 2003 to 2016,the carbon absorption of the three provinces in northeast China showed a steady increase,and the environmental protection work continued to advance. Thirdly,from 2017 to 2016,the actual carbon deficit of the three provinces in northeast China was positive,but the growth rate of the actual carbon deficit of the provinces was decreasing,and the whole ecological environment was developing towards a benign state. Fourth,among the three northeastern provinces,Liaoning is the subject of carbon compensation,Jilin and Heilongjiang is the recipient of carbon compensation,and it is generally the region with higher level of economic development to compensate the region with lower level of economic development,which is consistent with the concept of regional coordinated development. The research results in this paper can provide a reasonable reference for the establishment and improvement of interregional carbon compensation mechanism and the calculation of carbon compensation cost in the three northeastern provinces.
Carbon compensation is a new field of ecological compensation research under the background of global warming and low carbon development. Based on the footprint theory,this paper puts forward the concept of theoretical carbon deficit,improves the accounting method of carbon compensation cost among regions,and forecasts the carbon compensation cost of northeast three provinces from 2017 to 2026 using the grey prediction model GM(1,1). The results show that: first,from 2003 to 2016,the carbon emissions of the three provinces in northeast China showed an upward trend on the whole,but the rate of increase slowed down. Second,from 2003 to 2016,the carbon absorption of the three provinces in northeast China showed a steady increase,and the environmental protection work continued to advance. Thirdly,from 2017 to 2016,the actual carbon deficit of the three provinces in northeast China was positive,but the growth rate of the actual carbon deficit of the provinces was decreasing,and the whole ecological environment was developing towards a benign state. Fourth,among the three northeastern provinces,Liaoning is the subject of carbon compensation,Jilin and Heilongjiang is the recipient of carbon compensation,and it is generally the region with higher level of economic development to compensate the region with lower level of economic development,which is consistent with the concept of regional coordinated development. The research results in this paper can provide a reasonable reference for the establishment and improvement of interregional carbon compensation mechanism and the calculation of carbon compensation cost in the three northeastern provinces.
引文
[1] Fu,B.,et al. Value of Ecosystem Hydropower Service and Its Impact on the Payment for Ecosystem Services[J]. Science of the Total Environment,2014,472(2):338-346.
[2]段福梅.中国二氧化碳排放峰值的情景预测及达峰特征——基于粒子群优化算法的BP神经网络分析[J].东北财经大学学报,2018,(5):19-27.
[3]毕莹,杨方白.辽宁省碳排放影响因素分析及达峰情景预测[J].东北财经大学学报,2017,(4):91-97.
[4] Ambastha,K.,Hussain,S. A.,Badola,R. Social and Economic Considerations in Conserving Wetlands of Indo-Gangetic Plains:A Case Study of Kabartal Wetland,India[J]. Environmentalist,2007,27(6):261-273.
[5] Wünscher, T., Engel, S., Wunder, S. Spatial Targeting of Payments for Environmental Services:A Tool for Boosting Conservation Benefits[J]. Ecological Economics,2008,65(4):822-833.
[6]代明,刘燕妮,江思莹.主体功能区划下的生态补偿标准——基于机会成本和佛冈样域的研究[J].中国人口·资源与环境,2013,(2):18-22.
[7] Sheng,W., Zhen,L. Xie,G.,et al. Determining Eco-Compensation Standards Based on the Ecosystem Services Value of the Mountain Ecological Forests in Beijing,China[J]. Ecosystem Services,2017,26(6):422-430.
[8] Shen,N.,Pang,A.,Li,C.,et al. Study on Ecological Compensation Mechanism of Xin'an Spring Water Source Protection Zone in Shanxi Province,China[J].Procedia Environmental Sciences,2010,2(3):1063-1073.
[9] Wei,X. Y., Xia,J. X. Ecological Compensation for Large Water Projects Based on Ecological Footprint Theory:A Case Study in China[J]. Procedia Environmental Sciences,2012,13(1):1338-1345.
[10]耿涌,戚瑞,张攀.基于水足迹的流域生态补偿标准模型研究[J].中国人口·资源与环境,2009,(6):11-16.
[11] Galik,C. S.,Jackson,R. B. A Virtual“Field Test”of Forest Management Carbon Offset Protocols:the Influence of Accounting.[J]. Mitigation&Adaptation Strategies for Global Change,2009,14(7):677-690.
[12] Lovell,H.,Liverman,D. Understanding Carbon Offset Technologies[J]. New Political Economy,2010,15(2):255-273.
[13] Fankhauser,S., Hepburn, C. Designing Carbon Markets. Part I:Carbon Markets in Time[J]. Energy Policy,2010,38(8):4381-4387.
[14] Yu,B.,Xu,L.,Yang,Z. Ecological Compensation for Inundated Habitats in Hydropower Developments Based on Carbon Stock Balance[J]. Journal of Cleaner Production,2016,114(7):334-342.
[15]中国环境文化促进会.中国碳平衡交易框架研究[DB/OL]. http://www. zhb. gov. cn/zhxx/hjyw/200811/t20 081106_130915. htm,2008-11-06.
[16]公衍照,吴宗杰.论温室气体减排中的碳补偿[J].山东理工大学学报(社会科学版),2012,(1):5-10.
[17]李青青,龚梦祎,顾庆平.总量控制与交易机制中的碳补偿制度研究[J].环境科学与管理,2013,(8):51-55.
[18]于谨凯,杨志坤,邵桂兰.基于影子价格法的碳汇渔业碳补偿额度分析——以山东海水贝类养殖业为例[J].农业经济与管理,2011,(6):83-90.
[19]陈儒,姜志德.中国省域低碳农业横向空间生态补偿研究[J].中国人口·资源与环境,2018,(4):87-97.
[20]胡小飞,邹妍,傅春.基于碳足迹的江西生态补偿标准时空格局[J].应用生态学报,2017,(2):493-499.
[21]赵荣钦,刘英,马林,等.基于碳收支核算的河南省县域空间横向碳补偿研究[J].自然资源学报,2016,(10):1675-1687.
[22]闫丰,王洋,杜哲,等.基于IPCC排放因子法估算碳足迹的京津冀生态补偿量化[J].农业工程学报,2018,(4):15-20.
[23]彭文英,马思瀛,张丽亚,等.基于碳平衡的城乡生态补偿长效机制研究——以北京市为例[J].生态经济,2016,(9):162-166.
[24] Schimel,D. CO2and the Carbon Cycle[J]. Climate Change,1996,18(3):1533-1545.
[25]李少林.城镇化进程中碳锁定的诱发机制与解锁路径研究[J].财经问题研究,2017,(3):28-35.
[26]政府间气候变化专门委员会. 2006年IPCC国家温室气体清单指南[DB/OL]. http://www. ipccnggip. iges. or. jp/public/2006gl/chinese/,2006.
[27]汪澜.水泥生产企业CO2排放量的计算[J].中国水泥,2009,(11):21-22.
[28]李克让.土地利用变化和温室气体净排放与陆地生态系统碳循环[M].北京:气象出版社,2002. 33-35.
[29]谢鸿宇,陈贤生,林凯荣,等.基于碳循环的化石能源及电力生态足迹[J].生态学报,2008,(4):1729-1735.
[30]杨立,唐柳.曲周县碳平衡分析与预测[J].中国人口·资源与环境,2013,(S2):10-13.
[31] Intergovernmental Panel on Climate Change[R].Climate Change:The Physical Ccience Basis,2007-10-18.
[32]张颖,吴丽莉,苏帆,等.我国森林碳汇核算的计量模型研究[J].北京林业大学学报,2010,(2):194-200.
[33]邓聚龙.灰色预测与决策[M].武汉:华中理工大学出版社,1988. 99-101.
[2]段福梅.中国二氧化碳排放峰值的情景预测及达峰特征——基于粒子群优化算法的BP神经网络分析[J].东北财经大学学报,2018,(5):19-27.
[3]毕莹,杨方白.辽宁省碳排放影响因素分析及达峰情景预测[J].东北财经大学学报,2017,(4):91-97.
[4] Ambastha,K.,Hussain,S. A.,Badola,R. Social and Economic Considerations in Conserving Wetlands of Indo-Gangetic Plains:A Case Study of Kabartal Wetland,India[J]. Environmentalist,2007,27(6):261-273.
[5] Wünscher, T., Engel, S., Wunder, S. Spatial Targeting of Payments for Environmental Services:A Tool for Boosting Conservation Benefits[J]. Ecological Economics,2008,65(4):822-833.
[6]代明,刘燕妮,江思莹.主体功能区划下的生态补偿标准——基于机会成本和佛冈样域的研究[J].中国人口·资源与环境,2013,(2):18-22.
[7] Sheng,W., Zhen,L. Xie,G.,et al. Determining Eco-Compensation Standards Based on the Ecosystem Services Value of the Mountain Ecological Forests in Beijing,China[J]. Ecosystem Services,2017,26(6):422-430.
[8] Shen,N.,Pang,A.,Li,C.,et al. Study on Ecological Compensation Mechanism of Xin'an Spring Water Source Protection Zone in Shanxi Province,China[J].Procedia Environmental Sciences,2010,2(3):1063-1073.
[9] Wei,X. Y., Xia,J. X. Ecological Compensation for Large Water Projects Based on Ecological Footprint Theory:A Case Study in China[J]. Procedia Environmental Sciences,2012,13(1):1338-1345.
[10]耿涌,戚瑞,张攀.基于水足迹的流域生态补偿标准模型研究[J].中国人口·资源与环境,2009,(6):11-16.
[11] Galik,C. S.,Jackson,R. B. A Virtual“Field Test”of Forest Management Carbon Offset Protocols:the Influence of Accounting.[J]. Mitigation&Adaptation Strategies for Global Change,2009,14(7):677-690.
[12] Lovell,H.,Liverman,D. Understanding Carbon Offset Technologies[J]. New Political Economy,2010,15(2):255-273.
[13] Fankhauser,S., Hepburn, C. Designing Carbon Markets. Part I:Carbon Markets in Time[J]. Energy Policy,2010,38(8):4381-4387.
[14] Yu,B.,Xu,L.,Yang,Z. Ecological Compensation for Inundated Habitats in Hydropower Developments Based on Carbon Stock Balance[J]. Journal of Cleaner Production,2016,114(7):334-342.
[15]中国环境文化促进会.中国碳平衡交易框架研究[DB/OL]. http://www. zhb. gov. cn/zhxx/hjyw/200811/t20 081106_130915. htm,2008-11-06.
[16]公衍照,吴宗杰.论温室气体减排中的碳补偿[J].山东理工大学学报(社会科学版),2012,(1):5-10.
[17]李青青,龚梦祎,顾庆平.总量控制与交易机制中的碳补偿制度研究[J].环境科学与管理,2013,(8):51-55.
[18]于谨凯,杨志坤,邵桂兰.基于影子价格法的碳汇渔业碳补偿额度分析——以山东海水贝类养殖业为例[J].农业经济与管理,2011,(6):83-90.
[19]陈儒,姜志德.中国省域低碳农业横向空间生态补偿研究[J].中国人口·资源与环境,2018,(4):87-97.
[20]胡小飞,邹妍,傅春.基于碳足迹的江西生态补偿标准时空格局[J].应用生态学报,2017,(2):493-499.
[21]赵荣钦,刘英,马林,等.基于碳收支核算的河南省县域空间横向碳补偿研究[J].自然资源学报,2016,(10):1675-1687.
[22]闫丰,王洋,杜哲,等.基于IPCC排放因子法估算碳足迹的京津冀生态补偿量化[J].农业工程学报,2018,(4):15-20.
[23]彭文英,马思瀛,张丽亚,等.基于碳平衡的城乡生态补偿长效机制研究——以北京市为例[J].生态经济,2016,(9):162-166.
[24] Schimel,D. CO2and the Carbon Cycle[J]. Climate Change,1996,18(3):1533-1545.
[25]李少林.城镇化进程中碳锁定的诱发机制与解锁路径研究[J].财经问题研究,2017,(3):28-35.
[26]政府间气候变化专门委员会. 2006年IPCC国家温室气体清单指南[DB/OL]. http://www. ipccnggip. iges. or. jp/public/2006gl/chinese/,2006.
[27]汪澜.水泥生产企业CO2排放量的计算[J].中国水泥,2009,(11):21-22.
[28]李克让.土地利用变化和温室气体净排放与陆地生态系统碳循环[M].北京:气象出版社,2002. 33-35.
[29]谢鸿宇,陈贤生,林凯荣,等.基于碳循环的化石能源及电力生态足迹[J].生态学报,2008,(4):1729-1735.
[30]杨立,唐柳.曲周县碳平衡分析与预测[J].中国人口·资源与环境,2013,(S2):10-13.
[31] Intergovernmental Panel on Climate Change[R].Climate Change:The Physical Ccience Basis,2007-10-18.
[32]张颖,吴丽莉,苏帆,等.我国森林碳汇核算的计量模型研究[J].北京林业大学学报,2010,(2):194-200.
[33]邓聚龙.灰色预测与决策[M].武汉:华中理工大学出版社,1988. 99-101.