中国畜牧业温室气体排放的脱钩与预测分析
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摘要
面对日益严峻的温室气体排放形势,中国做出到2030年左右二氧化碳排放达到峰值的承诺,其中畜牧业成为重要减排领域,因此,研究中国畜牧业温室气体排放现状及趋势尤为必要。基于2000—2014年省级面板数据,在参考《省级温室气体排放清单指南》测算畜牧业温室气体排放量基础上,借助Tapio脱钩模型分析畜牧业温室气体排放与经济发展之间的关系,采用LMDI模型分解其影响因素,并构建不同情景对2020年畜牧业温室气体排放目标进行分析。研究结果表明:畜牧业温室气体排放量总体呈下降趋势,非奶牛减排明显,是下降主因,但其仍处于50%水平之上,排放量达18 180.54万t;羊、生猪、奶牛排放量增加,分别为7 072.56万t、6 202.69万t、4 359.97万t。畜牧业温室气体排放脱钩效应比较理想,全国以弱脱钩状态为主,但经历波动变化、相对平稳、持续上升3个发展阶段,脱钩状态不稳定。综合效应在国家层面呈倒"U"型特征,但在省份间差异明显;生产效率效应是国家和省份减排的最大贡献者,经济发展效应则是增排的最主要推动因素;综合效应差异主要来自产业结构效应和劳动力效应的不同。2020年畜牧业温室气体排放远超管控目标,预测区间端点值分别超过目标12.84%和34.71%,减排压力大。因此,应调整产业结构,适当进口畜产品;针对不同地区脱钩状态差别化治理,提高养殖效率;明确畜牧业减排目标,分解管控任务。
With increasing greenhouse gas emission, China has committed to cap carbon dioxide emissions by 2030. As animal husbandry has become an important part of the emission reduction effort, it is necessary to analyze the current situation and trend in greenhouse gas emission due to animal husbandry in the country. Based on the 2000-2014 provincial panel data and the Guidelines on Provincial Greenhouse Gas Emission Inventories, we estimated greenhouse gas emission due to animal husbandry and then used the Tapio decoupling model to analyze the relationship between greenhouse gas emission and the economic development due to animal husbandry. Furthermore, LMDI model was used to decompose the driving factors, and the greenhouse gas emissions target of animal husbandry in 2020 under different scenarios were also analyzed. The results suggested that greenhouse gas emission from animal husbandry decreased from 377.852 4 million tons in 2000 to 358.157 6 million tons in 2014, representing a drop of 5.21%.Emission reduction from non-dairy cattle was significant. However, it was still above the 50% threshold — 181.805 4 million tons.Emissions from sheep, pigs and cattle were respectively 70.725 6 million tons, 62.026 9 million tons and 43.599 7 million tons, all of which still increased. The decoupling effect of greenhouse gas emission from animal husbandry was ideal. The whole country was under weak decoupling that underwent three stages of fluctuation — relative stability — increase. The decoupling condition for each province was good, among which 15 provinces had strong decoupling, 15 provinces had weak decoupling and 1 province had receding decoupling. The comprehensive effect tracked an inverted U-curve at the national level, which was quite different for the provinces. The efficiency of production was the main contributor to the national and provincial emission reductions, while the effect of economic development was the most important driving factor of emission. The difference in comprehensive effect mainly came from the difference in industrial structure and labor. In 2020, greenhouse gas emission from animal husbandry far exceeded planned target. The predicted range of greenhouse gas emission from animal husbandry was from 335.630 8 to 400.677 1 million tons. Then the predicted endpoint values were respectively 12.84% and 34.71% more than the target, which great increased the pressure of emission reduction. In this case, only the lowest decoupling elasticity and the fastest economic growth rate had the least greenhouse gas emission gap. Greenhouse gas emission reduction was an inevitable requirement for sustainable development in the world. Although the decoupling effect of greenhouse gas emission from animal husbandry in China was obvious under the effect of several factors,emission reduction was still an arduous task, requiring the formulation of practical measures to promote it. Therefore, this work suggested that China needed to adjust its industrial structure and import livestock products instead of promoting domestic production.There was the need to implement differential governance of decoupling in different regions and improving farming efficiency. Also,clear animal husbandry emission reduction objectives and task assignments to provinces were required.
With increasing greenhouse gas emission, China has committed to cap carbon dioxide emissions by 2030. As animal husbandry has become an important part of the emission reduction effort, it is necessary to analyze the current situation and trend in greenhouse gas emission due to animal husbandry in the country. Based on the 2000-2014 provincial panel data and the Guidelines on Provincial Greenhouse Gas Emission Inventories, we estimated greenhouse gas emission due to animal husbandry and then used the Tapio decoupling model to analyze the relationship between greenhouse gas emission and the economic development due to animal husbandry. Furthermore, LMDI model was used to decompose the driving factors, and the greenhouse gas emissions target of animal husbandry in 2020 under different scenarios were also analyzed. The results suggested that greenhouse gas emission from animal husbandry decreased from 377.852 4 million tons in 2000 to 358.157 6 million tons in 2014, representing a drop of 5.21%.Emission reduction from non-dairy cattle was significant. However, it was still above the 50% threshold — 181.805 4 million tons.Emissions from sheep, pigs and cattle were respectively 70.725 6 million tons, 62.026 9 million tons and 43.599 7 million tons, all of which still increased. The decoupling effect of greenhouse gas emission from animal husbandry was ideal. The whole country was under weak decoupling that underwent three stages of fluctuation — relative stability — increase. The decoupling condition for each province was good, among which 15 provinces had strong decoupling, 15 provinces had weak decoupling and 1 province had receding decoupling. The comprehensive effect tracked an inverted U-curve at the national level, which was quite different for the provinces. The efficiency of production was the main contributor to the national and provincial emission reductions, while the effect of economic development was the most important driving factor of emission. The difference in comprehensive effect mainly came from the difference in industrial structure and labor. In 2020, greenhouse gas emission from animal husbandry far exceeded planned target. The predicted range of greenhouse gas emission from animal husbandry was from 335.630 8 to 400.677 1 million tons. Then the predicted endpoint values were respectively 12.84% and 34.71% more than the target, which great increased the pressure of emission reduction. In this case, only the lowest decoupling elasticity and the fastest economic growth rate had the least greenhouse gas emission gap. Greenhouse gas emission reduction was an inevitable requirement for sustainable development in the world. Although the decoupling effect of greenhouse gas emission from animal husbandry in China was obvious under the effect of several factors,emission reduction was still an arduous task, requiring the formulation of practical measures to promote it. Therefore, this work suggested that China needed to adjust its industrial structure and import livestock products instead of promoting domestic production.There was the need to implement differential governance of decoupling in different regions and improving farming efficiency. Also,clear animal husbandry emission reduction objectives and task assignments to provinces were required.
引文
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[15]李忠民,陈向涛,姚宇.基于弹性脱钩的中国减排目标缺口分析[J].中国人口·资源与环境,2011,21(1):57-63LI Z M,CHEN X T,YAO Y.Gap of emission reduction targets:Analysis based on elastic decoupling of China[J].China Population,Resources and Environment,2011,21(1):57-63
[16]肖丽群,吴群.基于脱钩指数的2020年江苏省耕地保有量目标分析[J].资源科学,2012,34(3):442-448XIAO L Q,WU Q.Target analysis of cultivated land protection area in Jiangsu Province in 2020 based on decoupling index[J].Resources Science,2012,34(3):442-448
[17]刘琼,佴伶俐,欧名豪,等.基于脱钩情景的中国建设用地总量管控目标分析[J].南京农业大学学报:社会科学版,2014,14(2):80-85LIU Q,NAI L L,OU M H,et al.Analysis on control objective of construction land in China based on decoupling scene[J].Journal of Nanjing Agricultural University:Social Science Edition,2014,14(2):80-85
[18]TAPIO P.Towards a theory of decoupling:Degrees of decoupling in the EU and the case of road traffic in Finland between 1970and 2001[J].Transport Policy,2005,12(2):137-151
[19]ANG B W.Decomposition analysis for policymaking in energy:Which is the preferred method?[J].Energy Policy,2004,32(9):1131-1139
[2]CARO D,DAVIS S J,BASTIANONI S,et al.Global and regional trends in greenhouse gas emissions from livestock[J].Climatic Change,2014,126(1/2):203-216
[3]FAO.FAO Statistical Yearbook 2013 World Food and Agriculture[M].Rome:Food and Agriculture Organization of the United Nations,2013
[4]GERBER P J,STEINFELD H,HENDERSON B,et al.Tackling climate change through livestock:A global assessment of emissions and mitigation opportunities[R].Rome:Food and Agriculture Organization of the United Nations,2013
[5]陈瑶,尚杰.中国畜牧业脱钩分析及影响因素研究[J].中国人口·资源与环境,2014,24(3):101-107CHEN Y,SHANG J.Disconnect analysis and influence factors of animal husbandry in China[J].China Population,Resources and Environment,2014,24(3):101-107
[6]董红敏,林而达,杨其长.中国反刍动物甲烷排放量的初步估算及减缓技术[J].农村生态环境,1995,11(3):4-7DONG H M,LIN E D,YANG Q C.Methane emitted from ruminants in China and the mitigation technologies[J].Rural Eco-Environment,1995,11(3):4-7
[7]ZHOU J B,JIANG M M,CHEN G Q.Estimation of methane and nitrous oxide emission from livestock and poultry in China during 1949-2003[J].Energy Policy,2007,35(7):3759-3767
[8]胡向东,王济民.中国畜禽温室气体排放量估算[J].农业工程学报,2010,26(10):247-252HU X D,WANG J M.Estimation of livestock greenhouse gases discharge in China[J].Transactions of the CSAE,2010,26(10):247-252
[9]闵继胜,胡浩.中国农业生产温室气体排放量的测算[J].中国人口·资源与环境,2012,22(7):21-27MIN J S,HU H.Calculation of greenhouse gases emission from agricultural production in China[J].China Population,Resources and Environment,2012,22(7):21-27
[10]陈苏,胡浩.中国畜禽温室气体排放时空变化及影响因素研究[J].中国人口·资源与环境,2016,26(7):93-100CHEN S,HU H.Study on the spatial-temporal changes and influence factors of greenhouse gases emission from livestock and poultry in China[J].China Population,Resources and Environment,2016,26(7):93-100
[11]易平,方世明,马春艳.地质公园旅游经济增长与生态环境压力脱钩评价--以嵩山世界地质公园为例[J].自然资源学报,2014,29(8):1282-1296YI P,FANG S M,MA C Y.Decoupling evaluation between tourism economic growth and eco-environmental pressure of Songshan Global Geopark[J].Journal of Natural Resources,2014,29(8):1282-1296
[12]舒畅,乔娟.我国养殖业生态足迹时空特征及脱钩效应研究--以生猪产业为例[J].生态经济,2016,32(1):148-151SHU C.QIAO J.Research on spatial-temporal characteristics and decoupling effect of the breeding ecological footprint in China:Taking pig breeding as an example[J].Ecological Economy,2016,32(1):148-151
[13]潘丹,孔凡斌.鄱阳湖生态经济区畜禽养殖污染与产业发展的关系--基于脱钩和LMDI模型的实证分析[J].江西社会科学,2015,35(6):49-55PAN D,KONG F B.The relationship between livestock pollution and industrial development in Poyang Lake ecological economic zone:An empirical analysis based on decoupling and LMDI model[J].Jiangxi Social Sciences,2015,35(6):49-55
[14]TIAN J X,YANG H L,XIANG P A,et al.Drivers of agricultural carbon emissions in Hunan Province,China[J].Environmental Earth Sciences,2016,75(2):121
[15]李忠民,陈向涛,姚宇.基于弹性脱钩的中国减排目标缺口分析[J].中国人口·资源与环境,2011,21(1):57-63LI Z M,CHEN X T,YAO Y.Gap of emission reduction targets:Analysis based on elastic decoupling of China[J].China Population,Resources and Environment,2011,21(1):57-63
[16]肖丽群,吴群.基于脱钩指数的2020年江苏省耕地保有量目标分析[J].资源科学,2012,34(3):442-448XIAO L Q,WU Q.Target analysis of cultivated land protection area in Jiangsu Province in 2020 based on decoupling index[J].Resources Science,2012,34(3):442-448
[17]刘琼,佴伶俐,欧名豪,等.基于脱钩情景的中国建设用地总量管控目标分析[J].南京农业大学学报:社会科学版,2014,14(2):80-85LIU Q,NAI L L,OU M H,et al.Analysis on control objective of construction land in China based on decoupling scene[J].Journal of Nanjing Agricultural University:Social Science Edition,2014,14(2):80-85
[18]TAPIO P.Towards a theory of decoupling:Degrees of decoupling in the EU and the case of road traffic in Finland between 1970and 2001[J].Transport Policy,2005,12(2):137-151
[19]ANG B W.Decomposition analysis for policymaking in energy:Which is the preferred method?[J].Energy Policy,2004,32(9):1131-1139
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