碳税政策对农业土地利用变化及其碳排放的影响
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摘要
农业生态系统具有碳源和碳汇的双重特征,其在减缓气候变化中的重要性已得到国际社会的广泛认可。相较于技术手段的创新,碳税、补贴等经济手段被认为是较为简单、可行、易出台的碳排放减缓政策。采用气候变化综合评估模型-GOPer-GC模型,构建国际碳税情景,模拟分析了2008年至2050年碳税政策的实施对全球各区域农业土地覆被及土地利用变化碳排放的影响。模拟结果表明,情景2和情景3中全球农业土地利用变化累计碳排放分别达到49.6 GtC和23.1 GtC,明显低于基准情景的累计排放量51.9 GtC。这说明,实施碳税政策后,相较于将碳税收入用作一般性财政收入,将碳税收入补贴至农业部门在一定程度上减缓农业碳排放。此外,林业部门获取更多的碳税补贴时,多数区域农业土地利用变化碳排放规模大幅减少,主因是耕地变为林地、草地变为林地面积的增加。情景3中,中国的碳汇量较其他情景显著增加,主要来自耕地变为林地、草地变为林地,累计碳汇量分别达到1.7和3.7 GtC。因此,对于中国、美国、印度等大部分区域来说,碳税收入更多地补贴至林业部门有利于在整体上减缓农业碳排放,而欧盟、日本、东亚、马来西亚、印度尼西亚、俄罗斯、东欧地区,碳税收入平均补贴至种植业、畜牧业和林业反而具有相对更好的减排效果。
Agricultural ecosystems can act not only as a carbon source, but also as a carbon sink. Its importance in mitigating carbon emission has been widely recognized by the international community.Compared with advanced technologies, carbon tax, subsidies, and other economic measures are considered to be relatively simple and feasible to govern climate change. Based on integrated assessment model GOPer-GC(Governance and development policy simulator on global climate model), we constructed international carbon tax scenarios and simulated their effects on agricultural land cover and its carbon emissions from 2008 to 2050. The simulation results showed that cumulative carbon emission due to global agricultural land use change in scenarios 2 and 3 was 49.6 and 23.1 GtC, respectively, which were significantly lower than that in the baseline scenario. This indicated that instead of carbon tax income as a general revenue, carbon tax income as a subsidy for the agricultural sector can reduce carbon emissions of the agricultural land use change. Additionally, the subsidy policy, considering that the forestry sector gets more carbon tax income than farming and animal husbandry sector, significantly reduces carbon emission due to land use change, mainly due to the increase in the conversion of crop land and grassland to woodland. China′s carbon sinks, contributed from the conversion of crop land and grassland to woodland, increased obviously in scenario 3. In this scenario, converting cropland and grassland to woodland in China contributed 1.7 GtC and 3.7 GtC of carbon sink respectively. Therefore, for most regions, such as China, the United States and India, increasing the subsidy of the forestry sector will be an effective way to mitigate agricultural carbon emission due to land use change. In the EU, Japan, East Asia, Malaysia, Indonesia, Russia, and Eastern Europe, the same subsidy in crops, livestock, and forestry resulted in a relatively obvious reduction in emission.
Agricultural ecosystems can act not only as a carbon source, but also as a carbon sink. Its importance in mitigating carbon emission has been widely recognized by the international community.Compared with advanced technologies, carbon tax, subsidies, and other economic measures are considered to be relatively simple and feasible to govern climate change. Based on integrated assessment model GOPer-GC(Governance and development policy simulator on global climate model), we constructed international carbon tax scenarios and simulated their effects on agricultural land cover and its carbon emissions from 2008 to 2050. The simulation results showed that cumulative carbon emission due to global agricultural land use change in scenarios 2 and 3 was 49.6 and 23.1 GtC, respectively, which were significantly lower than that in the baseline scenario. This indicated that instead of carbon tax income as a general revenue, carbon tax income as a subsidy for the agricultural sector can reduce carbon emissions of the agricultural land use change. Additionally, the subsidy policy, considering that the forestry sector gets more carbon tax income than farming and animal husbandry sector, significantly reduces carbon emission due to land use change, mainly due to the increase in the conversion of crop land and grassland to woodland. China′s carbon sinks, contributed from the conversion of crop land and grassland to woodland, increased obviously in scenario 3. In this scenario, converting cropland and grassland to woodland in China contributed 1.7 GtC and 3.7 GtC of carbon sink respectively. Therefore, for most regions, such as China, the United States and India, increasing the subsidy of the forestry sector will be an effective way to mitigate agricultural carbon emission due to land use change. In the EU, Japan, East Asia, Malaysia, Indonesia, Russia, and Eastern Europe, the same subsidy in crops, livestock, and forestry resulted in a relatively obvious reduction in emission.
引文
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[10] 黄蕊, 刘昌新, 王铮. 碳税和硫税治理下中国未来的碳排放趋势. 生态学报, 2017, 37(9): 2869- 2879.
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[18] 高颖, 李善同. 征收能源消费税对社会经济与能源环境的影响分析. 中国人口·资源与环境, 2009, 19(2): 30- 35.
[19] 顾高翔, 王铮. 国际资本流动模式及其国际经济影响模拟研究. 财经研究, 2015, 41(11): 58- 70.
[20] 刘宇, 肖宏伟, 吕郢康. 多种税收返还模式下碳税对中国的经济影响——基于动态CGE模型. 财经研究, 2015, 41(1): 35- 48.
[21] 王遥, 刘倩. 气候融资: 全球形势及中国问题研究. 国际金融研究, 2012, (9): 34- 42.
[22] 周义, 覃志豪, 包刚. 气候变化对农业的影响及应对. 中国农学通报, 2011, 27(32): 299- 303.
[23] FAO. The State of Food and Agriculture 2016: Climate Change, Agriculture and Food Security. Rome: FAO, 2016.
[24] 马晓哲. 碳税驱动下的全球气候治理及其对世界宏观经济的影响研究[D]. 北京: 中国科学院大学, 2016.
[25] Plevin R, Gibbs H, Duffy J, Yui S, Yeh S. Agro-ecological Zone Emission Factor (AEZ-EF) Model (v47). West Lafayette: Purdue University, 2014.
[26] 曹静. 走低碳发展之路: 中国碳税政策的设计及CGE模型分析. 金融研究, 2009, (12): 19- 29.
[27] 马晓哲, 王铮. 土地利用变化对区域碳源汇的影响研究进展. 生态学报, 2015, 35(17): 5898- 5907.
[28] 罗上华, 毛齐正, 马克明, 邬建国. 城市土壤碳循环与碳固持研究综述. 生态学报, 2012, 32(22): 7177- 7189.
[29] 姜群鸥, 邓祥征, 战金艳, 刘兴权. 黄淮海平原耕地转移对植被碳储量的影响. 地理研究, 2008, 27(4): 839- 846.
[30] 王克强. 土地利用变化的碳排放效应研究——兼沂水县实证分析[D]. 雅安: 四川农业大学, 2012.
[2] 苏明, 傅志华, 许文, 王志刚, 李欣, 梁强. 碳税的国际经验与借鉴. 经济研究参考, 2009, (9): 17- 23.
[3] Elliott J, Foster I, Kortum S, Munson T, Pérez-Cervantes F, Weisbach D. Trade and carbon taxes. The American Economic Review, 2010, 100(2): 465- 469.
[4] Speck S. Carbon taxation: two decades of experience and future prospects. Carbon Management, 2014, 4(2): 171- 183.
[5] 娄峰. 碳税征收对我国宏观经济及碳减排影响的模拟研究. 数量经济技术经济研究, 2014, 31(10): 84- 96, 109- 109.
[6] Schneider U A, McCarl B A. Implications of a carbon-based energy tax for U.S. agriculture. Agricultural and Resource Economics Review, 2005, 34(2): 265- 279.
[7] Wise M, Calvin K, Thomson A, Clarke L, Bond-Lamberty B, Sands R, Smith S J, Janetos A, Edmonds J. Implications of limiting CO2 concentrations for land use and energy. Science, 2009, 324(5931): 1183- 1186.
[8] 刘亦文, 胡宗义. 农业温室气体减排对中国农村经济影响研究——基于CGE模型的农业部门生产环节征收碳税的分析. 中国软科学, 2015, (9): 41- 54.
[9] 张兴平, 朱锦晨, 徐岸柳, 郭正权, 刘珊珊. 基于CGE碳税政策对北京社会经济系统的影响分析. 生态学报, 2015, 35(20): 6798- 6805.
[10] 黄蕊, 刘昌新, 王铮. 碳税和硫税治理下中国未来的碳排放趋势. 生态学报, 2017, 37(9): 2869- 2879.
[11] Rautiainen A, Lintunen J, Uusivuori J. Carbon taxation of the land use sector—the economics of soil carbon. Natural Resource Modeling, 2017, 30(2): e12126.
[12] 施正屏, 徐逢桂. 台湾碳税财政支付移转至农业部门之最适策略——基于可计算一般均衡模型(CGE)的运用. 台湾农业探索, 2012, (4): 1- 10.
[13] Liu L C, Wu G. The effects of carbon dioxide, methane and nitrous oxide emission taxes: an empirical study in China. Journal of Cleaner Production, 2017, 142: 1044- 1054.
[14] Tang K, Hailu A, Kragt M E, Ma C B. The response of broadacre mixed crop-livestock farmers to agricultural greenhouse gas abatement incentives. Agricultural Systems, 2018, 160: 11- 20.
[15] Frank S, Havlík P, Valin H, Wollenberg E, Hasegawa T, Obersteiner M. Carbon Prices, Climate Change Mitigation & Food Security: How to Avoid Trade-Offs? Wageningen: CCAFS, 2017.
[16] 贾敬敦, 魏珣, 金书秦. 澳大利亚发展碳汇农业对中国的启示. 中国农业科技导报, 2012, 14(2): 7- 11.
[17] Climate Action Tracker. The ten most important short-term steps to limit warming to 1.5℃. (2016- 11- 16) [2017-04- 20] https://climateactiontracker.org/publications/the-ten-most-important-short-term-steps-to-limit-warming-to- 15c/
[18] 高颖, 李善同. 征收能源消费税对社会经济与能源环境的影响分析. 中国人口·资源与环境, 2009, 19(2): 30- 35.
[19] 顾高翔, 王铮. 国际资本流动模式及其国际经济影响模拟研究. 财经研究, 2015, 41(11): 58- 70.
[20] 刘宇, 肖宏伟, 吕郢康. 多种税收返还模式下碳税对中国的经济影响——基于动态CGE模型. 财经研究, 2015, 41(1): 35- 48.
[21] 王遥, 刘倩. 气候融资: 全球形势及中国问题研究. 国际金融研究, 2012, (9): 34- 42.
[22] 周义, 覃志豪, 包刚. 气候变化对农业的影响及应对. 中国农学通报, 2011, 27(32): 299- 303.
[23] FAO. The State of Food and Agriculture 2016: Climate Change, Agriculture and Food Security. Rome: FAO, 2016.
[24] 马晓哲. 碳税驱动下的全球气候治理及其对世界宏观经济的影响研究[D]. 北京: 中国科学院大学, 2016.
[25] Plevin R, Gibbs H, Duffy J, Yui S, Yeh S. Agro-ecological Zone Emission Factor (AEZ-EF) Model (v47). West Lafayette: Purdue University, 2014.
[26] 曹静. 走低碳发展之路: 中国碳税政策的设计及CGE模型分析. 金融研究, 2009, (12): 19- 29.
[27] 马晓哲, 王铮. 土地利用变化对区域碳源汇的影响研究进展. 生态学报, 2015, 35(17): 5898- 5907.
[28] 罗上华, 毛齐正, 马克明, 邬建国. 城市土壤碳循环与碳固持研究综述. 生态学报, 2012, 32(22): 7177- 7189.
[29] 姜群鸥, 邓祥征, 战金艳, 刘兴权. 黄淮海平原耕地转移对植被碳储量的影响. 地理研究, 2008, 27(4): 839- 846.
[30] 王克强. 土地利用变化的碳排放效应研究——兼沂水县实证分析[D]. 雅安: 四川农业大学, 2012.