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Journal of Geo-information Science >

2018 , Vol. 20 >Issue 4: 405 - 413

DOI: https://doi.org/10.12082/dqxxkx.2018.170590

Methodological Framework and Research Progress on the Social and Economic Costs of Carbon Emission and Reduction

  • DENG Xiangzheng , 1, 2, 3, * ,
  • DAN Li 4 ,
  • YE Qian 5 ,
  • WANG Zhaohua 6 ,
  • LIU Yu 7 ,
  • ZHANG Xueyan 1, 2 ,
  • ZHANG Fan 5 ,
  • QI Wei 1, 2 ,
  • WANG Guofeng 8 ,
  • WANG Pei 1, 2, 3 ,
  • BAI Yuping 1, 2, 3
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  • 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 2. Center for Chinese Agricultural Policy, Chinese Academy of Sciences, Beijing 100101, China
  • 3. University of Chinese Academy of Sciences, Beijing 100149, China
  • 4. Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
  • 5. Beijing Normal University, Beijing 100875, China
  • 6. Beijing Institute of Technology, Beijing 100081, China
  • 7. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China
  • 8. Beijing Forestry University, Beijing 100083, China
*Corresponding author: DENG Xiangzheng, E-mail:

Received date: 2017-12-06

  Request revised date: 2018-02-11

  Online published: 2018-04-20

Supported by

National Key Research and Development Program of China, No.2016YFA0602500.

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《地球信息科学学报》编辑部 所有
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Abstract

Social and economic costs of carbon emission and reduction have increasingly been one of the hot research topics and are concerns by the policy makers of academic communities. We have conducted a comprehensive analysis on the key scientific issues and research progress on global carbon emission and carbon mitigation at both domestic and abroad. The latest observations from carbon satellites have proved that the global carbon dioxide has been spatially unevenly distributed. Given the 1.5 °C and 2.0 °C temperature increase limits of the Paris Agreement, we propose a technical framework to explore the temporal and spatial relationship between CO2 non-uniform dynamic distribution and global surface temperature, and to evaluate the carbon emission of selected major countries on the conditions of CO2 non-uniform dynamic distribution, and to estimate the social and economic costs of carbon emission and carbon reduction under the scenario of the 1.5°C and 2.0°C temperature limits. We finally propose an in-depth applied research on the complex relationships between climate change, economic growth and technology development. The technical framework and research methodologies in this paper will provide supports for the government on the aspects of formulating strategies and countermeasures for carbon emission and carbon reduction, by providing decision-making advices on mitigating climate change and achieving sustainable transformation and enhancing China′s dominant voice in the carbon diplomacy as well.

Key words： global change; carbon emission; carbon reduction; climate change economics; social and economic cost

Cite this article

DENG Xiangzheng , DAN Li , YE Qian , WANG Zhaohua , LIU Yu , ZHANG Xueyan , ZHANG Fan , QI Wei , WANG Guofeng , WANG Pei , BAI Yuping . Methodological Framework and Research Progress on the Social and Economic Costs of Carbon Emission and Reduction[J]. Journal of Geo-information Science, 2018 , 20(4) : 405 -413 . DOI: 10.12082/dqxxkx.2018.170590

1 引言

当前,以全球变暖为主要特征的气候变化给自然生态系统和人类社会的可持续发展带来了严峻的挑战[1,2]。人类活动排放大量CO2是引起全球变暖的主要原因[3]。碳排放引发全球、局部性气候变化的影响机理,碳排放及减碳对社会经济系统的 影响和适应机制日益受到学术界和决策部门的关注[4,5,6]。近年来,我国积极应对气候变化和碳减排问题,实行能源、碳排放总量和强度双控行动,提出到2030年碳排放达峰并尽早达峰的战略目标,使得经济增长和社会代价面临的内外部环境发生了深刻变化。在研究碳排放对社会经济代价影响时不难发现,主流经济模型中并没有考虑CO2非均匀分布、地表升温过程与经济系统间的互馈机制,传统分析也普遍认为其他条件不变的条件下,短期内碳排放约束将对潜在经济增速和社会代价变迁产生不利影响。然而,随着全球对碳减排问题的关注持续升温,理论和实践层面都开始从不同方面考虑长时期内碳排放与地表升温的内在机理及其对社会经济代价的影响传导机制。
本文通过分析碳排放与减碳的社会经济代价研究的重要科学问题和国内外研究现状,考虑各学科的相互交叉、渗透和耦合等特点,提出大气CO2浓度非均匀动态分布的事实。通过揭示全球CO2浓度、地表升温与社会经济系统之间的互馈关系,将表征全球CO2非均匀动态分布参数引入到新气候变化经济学理论体系模块,以土地利用结构变化和产业结构为驱动参数,以福利最大化和成本最小化为优化目标,提出和探讨了全球CO2非均匀动态分布如何影响全球地表升温过程;如何基于全球CO2与地表温度的非线性关系构建新气候变化经济学的理论方法与技术体系;温控1.5 ℃和2 ℃阈值情景下中国及世界主要国家碳排放空间多大;兼顾正义、公平、效率与历史责任,中国及世界主要国家碳排放与减碳的社会经济代价及其国别差异如何 4个关键科学问题。该理论框架不仅具有科学前瞻性,更是气候变化背景下社会经济代价评估领域的一个重大挑战,对未来国际气候变化协议的制订与实施有着重要意义。

2 碳排放和减碳的社会经济代价背景研究

碳排放和减碳的社会经济代价影响机制极其复杂,需要多学科交叉的研究及相关模型研发。国际上经济学家已开始利用经济学理论和观测数据量化气候变化对社会经济系统的影响[7,8,9],而国内由经济学家介入的多学科交叉的气候变化社会经济系统影响与适应机制多集中在区域实证分析[10,11,12],系统综合评估亟待破题[13,14,15]。针对大气CO2浓度非均匀动态分布的客观事实,构建新气候变化经济学模型评估碳排放和减碳的社会经济代价,制订适应气候变化的减排策略,无疑能为中国减缓气候变化影响并实现可持续转型提供科学依据和方法支持。
全球范围看,气候变化既是环境问题,也是发展问题[16]。2015年12月12日,巴黎气候变化大会通过了全球气候变化的新协议《巴黎协议》,要求把全球平均气温升幅控制在2 ℃之内,并努力将气温升幅限制在工业化前水平以上1.5 ℃之内。基于温控1.5 ℃和2 ℃阈值情景,探索碳排放影响社会经济系统的关键理论和方法,将对建立碳排放社会经济系统影响和减排措施评价的方法体系起关键作用。厘定不同温控情景下碳排放与减碳对社会经济影响的适应机制和减排措施的优先序,有助于决策者制定应对气候变化的有效措施,也是国际学术界在碳排放经济学领域最前沿的重大学术问题之一[17]。从经济学视角看,碳排放社会经济影响的长期性和复杂性挑战了传统经济学的理论范式与方法体系[18,19,20],新的经济学理论亟待研究以解决碳排放的社会经济代价这一全局性难题。目前结合温控阈值情景,探索碳排放对社会经济系统的影响机理仍是传统经济学领域的关键难题之一[21,22],国际上主要借助于敏感性分析、贴现率大小等指标开展对社会经济系统的成本效益分析[23,24];国内研究主要围绕碳减排的外部性、贴现率与代际公平、国际合作与博弈等理论问题[25,26]对碳减排经济学理论进行了一些总结归纳,但多集中在碳减排政策和技术的经济评估和应对方面,缺乏统领性和原创性的研究成果,结合气候模式和温控情景的碳排放社会经济影响与适应机理也鲜有探究。中国亟需在碳排放经济学理论方面进行创新,在不同温控情景下开展碳排放对社会经济系统响应的多学科理论探索,为科学评价碳排放和减碳对中国社会经济代价影响提供理论支撑。

3 碳排放与减碳的社会经济代价的研究进展与方法探究

碳排放和减碳的社会经济代价影响和适应机制极其复杂,已经超出了传统经济学的研究范围,碳排放和减碳的社会经济影响与气候变化间的互馈关系也亟待破题和深入考究。气候变化对经济系统不同尺度的影响存在不均匀分布性,这表现为气候变化影响依据时间、区域和行业的不同而产生差异。刘允芬[27]探究了气候变化对渔业的影响,得出中国四大海区主要经济鱼种的产量在气候变化之后降低了5%~15%,渔获量降低幅度降低1%~8%的研究结论;宁金花等[28]通过研究气候变化对农业的影响,发现CO2浓度倍增情景下,中国作物全年生长季延长8~32 d;郑景云等[29]发现,温度上升1 ℃,平均物候提前3.5 d;陈小勇等[30]报道了中国红树林退缩严重,CO2浓度倍增时,林业生产力上升12%~35%,温度上升2 ℃,红树林北移2.5个纬度,未来直接经济损失不小;丑洁明等[31]为中国气候变化经济评估提供了一种新的思路,利用改进的C-D-C模型分析了气候变化对我国农业粮食产量的经济影响,并从理论上确认了该模型对其他领域和部门的适用性;张永勤等[32]利用投入产出（IO）模型分析了气候变化对江苏省各经济行业部门的影响。另有学者研究发现,气候变暖对制造业负面影响较大,气候变化所带来的气候灾害严重影响交通运输业的发展;同时气候变化会增加风险评估中保险精算的不确定性,导致保险行业成本增加;受气候变化影响风险增高,东中西部地区旅游业的风险也将增大。综上所述,目前学者对碳排放和减碳社会经济代价方面的研究,主要集中在分析温度变化对某一行业或特定区域的经济影响[33],很少有学者全面探究温度对不同行业和区域经济影响的机理,以及温度变化对所有行业或区域经济影响的差异性分析。
国内外学者对碳减排政策效果方面的研究颇多,但大多集中于研究某一项政策所带来的影响,对于不同政策的叠加性影响分析,以及与无政策的效果对比寥寥无几。Loisel[34]利用动态CGE模型模拟了罗马尼亚的排放许可市场,发现由于环境管制促进了经济结构的转变,在严峻的排放配额下,排放权的自由分配也能保证经济增长;王灿等[35]应用综合描述中国经济、能源、环境系统的递推动态可计算一般均衡（CGE）模型,分析在中国实施碳减排政策的经济影响,以2010年实施碳税政策为模拟情景,定量描述了碳减排政策下国内生产总值、能源价格、资本价格等宏观经济变量的变化;牛玉静等[36]应用完全自主开发的全球多区域CGE模型（GAGE模型）,对中国、印度、美国和欧盟4个区域的减排成本以及经济影响进行了系统研究,从边际减排成本、GDP损失率、边际社会减排成本以及减排对部门总产出和出口的影响多个方面进行了比较分析;Matsumoto和Fukuda[37]认为尽管全球性的统一碳税税率可以经济有效地降低CO2排放,但它给发展中国家带来沉重的经济负担。除此之外,国内外学者还就碳排放交易体系、能效标准、国际技术合作和转让、能源效率提升、能源结构改革等减排政策效果进行了广泛研究。
目前气候变化综合评估模型按其模型方法可分为综合评估模型（IAM）、可计算一般均衡（CGE）模型和模拟模型。IAM模型包含DICE （Dynamic Integrated model of Climate and the Economy）、ENTICE （Endogenous technological change in the DICE model of global warming）、DEMETER （Development of a European Multi-model Ensemble Forecast System for Seasonal to Inter-annual Climate Prediction）、MIND （Model of Investment and Technological Development）、GET （Global Energy Transition） 等为主的全球模型,和以 RICE （Regional Integrated model of Climate and the Economy）、FUND （Framework for Uncertainty, Negotiation and Distribution）、CETA （Carbon Emission Trajectory Assessment） 等为代表性的区域化模型。可计算一般均衡 （CGE） 模型主要包括IGEM （Inter-temporal General Equilibrium Model） 全球模型和 GTAP-E （Global Trade Analysis Project-energy）、SGM （Second Generation Model）、AIM （Asia-Pacific Integrated Model）为代表性的区域化模型,模拟模型主要集中在区域化分析方面,有 PAGE （Policy Analysis of the Greenhouse Effect）、ICAM-1 （Integrated Climate Assessment Model-1）、IMAGE （Integrated Model to Assess the Greenhouse Effect） 模型等。IAM 模型能够计算不同外部假设条件下以及多个因子同时相互作用时的结果,但不能体现出经济系统作为一个整体,各个子系统之间的相互作用情况,也没有反映经济系统的运行机理。目前CGE模型用于气候变化分析时关注最多的问题,如气候变化的经济成本、延缓气候变化的政策措施选择、不同的政策措施对气候和社会经济结构等方面的影响。但是CGE模型也存在不足,首先,大部分模型是静态的,对于长期动态地经济系统的模拟并不完整;其次,模型中参数“校准法”值得商榷,很多计量经济学家对这种以基准年数据进行参数较正的方法进行了批评,表现在基准年随机现象在模型中不恰当传递、校准参数没有可信度度量、模型初始条件敏感等方面。模拟模型可用于研究一系列自适应政策和预防措施减少气候变化损害的程度,但由于科学认识与模拟技术的不确定性,以及模拟模型用简化的公式表示复杂的科学和经济关系,使得模拟结果不能很好的反映实际情况。除了模型固有缺陷外,各国研究机构所采用的分析模型虽然一定程度上能够分析出气候变化对经济的影响,但与大气环流模式（GCM）结合的工作尚不成熟,没有模 型能够揭示碳排放对各区域温度变化幅度的影响（表1）。
Tab. 1 Advantages and disadvantages of comprehensive assessment models of climate change

表1 气候变化综合评估模型优劣势对比

IAM模型 CGE模型 模拟模型
概况 包括以DICE、ENTICE、DEMETER-ICCS、MIND、GET-LFL 为主的全球模型,和以 RICE、FUND、CETA 为代表性的区域化模型 包括 JAM、IGEM 全球模型和 GTAP-E、MIT-EPPA、SGM、AIM 为代表性的区域化模型 主要集中在区域化分析方面,有 PAGE、ICAM-1、IMAGE、E3MG 模型等
优点 可反映不同外部假设条件下多因子间相互作用 可反映气候政策对社会经济结构等 影响 可模拟、评估自适应政策和预防措施缓解气候变化损害程度
缺点 无法反映子系统间相互作用与经济系统运行机理 无法模拟长期动态变化,模型参数缺乏可信度度量,初始条件敏感 社会经济关系过于简化,不符合实际
此外,国际上大多学者采用全球平均的CO2浓度开展研究,构建了大气CO2浓度与地表温度间的耦合关系[38,39]。科学、准确的数据对于提高全球变化研究的准确性至关重要[40]。2014年12月,美国航空航天局（NASA）发布了全球CO2空间分布图,证实大气CO2浓度非均匀动态分布的空间特征。国际学者也相继揭示了大气CO2浓度分布不仅在时间上有季节性的差异[41],在空间上也存在显著的地域性差别[42,43,44]。目前,全球范围内应用气候变化和传统经济模型评估气候变化对水资源、实物生产、人类健康和环境的影响均是基于全球CO2平均分布假设[45],IPCC第五次评估报告[46]发布的耦合模式的结果也都采用全球平均的CO2浓度来驱动模式进行模拟的,对于全球CO2非均匀动态分布、地表温度及社会经济系统的耦合机制却鲜有探究。
因此,基于已有气候变化对经济影响的研究、减排政策效果研究、气候经济学的模型工具创新和全球CO2非均匀动态分布的现状,我们提出大气CO2浓度与地表增温的关系、气候变化经济学模型、主要国家碳排放空间和碳排放与减碳社会经济代价等国际学术热点。围绕这些热点,提出探究全球CO2非均匀动态分布与地表升温过程的关系,构建新气候变化经济学理论模型与技术体系,提炼温控情景与国家战略背景下碳排放与减碳的社会经济代价的理论思想和技术方法。总体思路和技术途径如图1所示。
Fig. 1 Technical flowchart of studies on costs of carbon emission and reduction

图1 碳排放和减碳的社会经济代价研究技术路线

4 碳排放与减碳的社会经济代价研究的技术路线

碳排放与减碳社会经济代价研究的基础环节是揭示全球CO2非均匀动态分布与地表温度的时空关系,主要解决集成多源遥感数据的全球碳卫星CO2浓度观测资料整理与时空演变分析[47]、全球海陆气-碳循环耦合模式系统中非均匀动态分布的CO2对地表升温过程的影响[48]、全球主要国家及典型区域地表升温对CO2非均匀动态分布的敏感度分析及历史和未来碳通量的时空变化特征与基础数据集整理等科学问题。

4.1 全球CO2非均匀动态分布于地表温度时空关系辨析方法

理清全球CO2非均匀动态分布与地表温度的时空关系的关键环节是大气CO2时空分布数据平台的建立和完善,需要以海量的碳卫星数据和CO2数据产品为支持。研究在整理全球碳卫星资料,集成具有空间分布结构的CO2数据集并将其转换为气候耦合模式所需的数据格式和分辨率的基础上,在气候模式的驱动模块引入全球海陆气-碳循环的耦合模式FGOALS-AVIM作为强迫场[49],使用非均匀动态分布的大气CO2浓度驱动耦合模式达到平衡态,以求保证海陆气界面上碳通量计算的稳定性;同时设计数值模拟方案进行历史演变和未来气候变化的碳-气相互作用试验,计算出非均匀动态分布状况下的大气CO2浓度和地表温度在季节到年际尺度上的时空对应关系;根据二者时空变化遴选典型区域,模拟大气CO2浓度和温度在基本态、周期性变化方面的对应关系,模拟碳通量和碳库的时空演变与数量级变化、碳源和碳汇的变化;厘定温控1.5 ℃和2 ℃阈值情景下碳通量和碳库的时空分异特征[50],测算全球CO2和地表升温的敏感度曲线。

4.2 气候变化经济学技术体系构建及综合研究方法

碳排放与减碳社会经济代价研究的关键环节是构建新气候变化经济学理论体系和综合应用方法,基于空间计量模型揭示全球非均匀分布的CO2浓度与地表升温非线性关系对社会经济系统的影响机制,集成全球CO2非均匀动态分布、地表温度与社会经济系统关键指标;利用空间计量经济学方法揭示全球CO2浓度、地表升温过程与关键社会经济系统指标参数之间的非线性关系;利用随机前沿生产函数模型评估水、土资源与劳动力生产要素效率,并借助计量经济学模型分析候变化对生产效率的影响;在此基础上,基于可计算一般均衡理论,链接气候变化影响社会经济系统机制研究成果,构建新气候变化经济学模型。具体来说,新气候变化经济学模型主要包括生产与消费函数改进模块,影响方程和参数读写模块,气候变量、贫困、环境等关键社会指标嵌入模块,敏感性分析及模型校准模块,通过整理社会经济系统不同行业主体的生产投入、消费方式、行为决策、碳排放等参数,集成社会经济系统行业主体对气候变化适应的行为规则集,基于多主体建模环境构建气候变化社会经济系统主体适应分析计量经济学模型,探究自上而下方式构建全球尺度多区域动态递归的新气候变化经济学模型与社会经济系统适应的ABM模型耦合的时空尺度、链接机制与参数互馈路径[51],开展全球CO2浓度、地表升温过程与关键社会经济系统指标参数之间的互馈机制模拟。

4.3 碳排放空间核算方法

全球CO2非均匀动态分布状况下主要国家碳排放空间评价是碳排放与减碳社会经济代价研究的重要手段,主要包括基于复杂网络技术的大气CO2浓度与地表升温耦合关系研究、典型区域辨识与综合风险防范框架下的风险评估、基于系统科学理论方法的碳排放空间研究3部分内容。鉴于全球CO2非均匀动态分布事实及其对全球升温过程可能影响,应用复杂网络技术分析全球CO2与地表升温的耦合关联影响,在此基础上,建立温度网络和CO2网络,分析不同时间、不同区域的碳排放敏感度曲线,构建综合风险防范理论框架,从排放和影响两个维度对全球主要国家及典型区域开展应对气候变化的风险评估,并厘定温控1.5 ℃和2 ℃阈值情景下碳排放空间阈值范围。同时,现有的系统动力学模型UrbanCLIM已经难以满足跨学科和综合性的需求,研究将现有模型进行扩展,建立将气候变化数据集、气候系统动力学模型模拟结果、碳排放数据集、碳排放空间分配方案和减排途径等自然气候系统与社会经济系统信息融为一体的气候变化影响评估决策支持系统和平台,开展碳排放空间信度及减排途径研究。

4.4 碳排放和减碳社会经济代价评估方法

温控情景下世界主要国家碳排放和减碳的社会经济代价评估是本文构建技术路线中的核心内容和应用出口,本文拟从碳排放和减碳的情景设计与分析,碳排放和减碳对我国经济系统（GDP总量、结构、增长率等）的影响机理和途径识别,碳排放和减碳的宜居性变迁代价评估及脱贫代价评估等方面破题,在有自主知识产权的中国能源与环境政策模型（China Energy & Environmental Policy Analysis Model, CEEPA）基础上[52],综合集成RICE、DICE等主流气候经济模型[53],建立碳排放和减碳的动态均衡经济模型系统,以评估碳排放和减碳的成本以及对GDP、工业增加值等的经济影响。此外,设计中国与“一带一路”主要国家、气候变化南南合作参与国家的碳排放和减碳情景,为模拟分析碳排放和减碳对社会经济系统的影响提供情景方案和关键参数;识别碳排放和减碳对经济系统（GDP总量、结构、增长等）的影响机理、途径和模式,定量分析影响减碳的技术、管理和政策措施采纳的主要制约因素,定量分析这些措施对居民消费、企业生产等的影响和代价;综合运用能值理论（Emergy）和条件价值法（CVM）等方法[54,55],通过模拟和实证方法分析碳排放和减碳的宜居性变迁代价,以中国典型生态脆弱区为评估范围,将气候变化风险分析和评估作为脱贫代价的一项重要内容,量化自主适应策略发挥作用所需的政策支持。

5 结语

本文基于对碳排放与减碳的社会经济代价研究的重要科学问题和国内外研究现状的综合分析,提出并初步设计了基于大气CO2浓度非均匀动态分布事实构建的碳排放与减碳的社会经济代价评估技术路线。
本文旨在通过碳排放与减碳社会经济代价技术路线的设计与构建,有力支持以下主要科学目标的实现：① 揭示碳排放与减碳对中国社会经济代价影响的机理、途径和适应机制,探究全球CO2非均匀动态分布与地表升温过程的非线性关系,基于全球CO2非均匀动态分布与地表升温过程的非线性关系构建新气候变化经济学的理论方法、模型与技术体系。② 基于全球海陆气-碳循环耦合模式,模拟全球CO2非均匀动态分布的气候效应及机理,利用系统科学方法,探究大气CO2浓度、地表温度与社会经济影响的互馈机制,鉴于全球CO2非均匀动态分布与地表升温过程的非线性关系,以一般均衡分析理论为建模框架,以多源异构海量数据为驱动参数,探究并设计了新气候变化经济学的理论方法、模型和技术体系。③ 测度碳排放和减碳的社会经济代价动态互动的数量关系,开展碳排放和减碳适应性措施的成本效益分析,厘定碳减排成本曲线和减碳技术的优先序,模拟碳排放和减碳对典型区域社会经济代价的综合影响。
综上所述,碳排放和减碳社会经济代价技术路线的设计也将为国家需求提供参考,如评估碳排放和减碳对社会经济代价的影响将为国家可持续转型与应对气候变化提供决策方案;基于全球CO2非均匀动态分布事实,测算中国与全球主要国家碳排放空间也将为减缓气候变化可持续发展提供科学依据。为了实现上述研究目标,必须在开展全球CO2与地表升温的非线性关系等基础理论研究的同时,重视新气候变化经济学的理论方法、模型与技术体系的构建,发展基于全球CO2非均匀动态分布的气候变化经济学的方法论,推动地球科学与气候变化经济科学的发展。

The authors have declared that no competing interests exist.

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Funk C, Peterson P, Landsfeld M, et al.The climate hazards infrared precipitation with stations: A new environmental record for monitoring extremes[J]. Scientific data, 2015,2:150066.The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset builds on previous approaches to ‘smart’ interpolation techniques and high resolution, long period of record precipitation estimates based on infrared Cold Cloud Duration (CCD) observations. The algorithm i) is built around a 0.05° climatology that incorporates satellite information to represent sparsely gauged locations, ii) incorporates daily, pentadal, and monthly 1981-present 0.05° CCD-based precipitation estimates, iii) blends station data to produce a preliminary information product with a latency of about 2 days and a final product with an average latency of about 3 weeks, and iv) uses a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights. We present the CHIRPS algorithm, global and regional validation results, and show how CHIRPS can be used to quantify the hydrologic impacts of decreasing precipitation and rising air temperatures in the Greater Horn of Africa. Using the Variable Infiltration Capacity model, we show that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.

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[21]
Greenstone M, Kopits E, Wolverton A.Developing a social cost of carbon for US regulatory analysis: A methodology and interpretation[J]. Review of Environmental Economics and Policy, 2013,7:23-46.The US government recently developed a range of values representing the monetized global damages associated with an incremental increase in carbon dioxide (CO2) emissions, commonly referred to as the social cost of carbon (SCC). These values are currently used in benefit09“cost analyses to assess potential federal regulations. For 2010, the central value of the SCC is $21 per ton of CO2 emissions, with sensitivity analyses to be conducted at $5, $35, and $65 per ton of CO2 (2007 dollars). This article summarizes the methodology and interagency process used to develop these SCC values, offers our own commentary on how the SCC can be used to inform regulatory decisions, and identifies priorities for further research. (JEL: Q54, Q51, and Q58)

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[22]
Friedlingstein P, Andrew R M, Rogelj J, et al.Persistent growth of CO2 emissions and implications for reaching climate targets[J]. Nature Geoscience, 2014,7:709-715.Efforts to limit climate change below a given temperature level require that global emissions of CO2 cumulated over time remain below a limited quota. This quota varies depending on the temperature level, the desired probability of staying below this level and the contributions of other gases. In spite of this restriction, global emissions of CO2 from fossil fuel combustion and cement production have continued to grow by 2.5% per year on average over the past decade. Two thirds of the CO2 emission quota consistent with a 2 C temperature limit has already been used, and the total quota will likely be exhausted in a further 30 years at the 2014 emissions rates. We show that CO2 emissions track the high end of the latest generation of emissions scenarios, due to lower than anticipated carbon intensity improvements of emerging economies and higher global gross domestic product growth. In the absence of more stringent mitigation, these trends are set to continue and further reduce the remaining quota until the onset of a potential new climate agreement in 2020. Breaking current emission trends in the short term is key to retaining credible climate targets within a rapidly diminishing emission quota.

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[23]
Sierzchula W, Bakker S, Maat K, et al.The influence of financial incentives and other socio-economic factors on electric vehicle adoption[J]. Energy Policy, 2014,68:183-194.Electric vehicles represent an innovation with the potential to lower greenhouse gas emissions and help mitigate the causes of climate change. However, externalities including the appropriability of knowledge and pollution abatement result in societal/economic benefits that are not incorporated in electric vehicle prices. In order to address resulting market failures, governments have employed a number of policies. We seek to determine the relationship of one such policy instrument (consumer financial incentives) to electric vehicle adoption. Based on existing literature, we identified several additional socio-economic factors that are expected to be influential in determining electric vehicle adoption rates. Using multiple linear regression analysis, we examined the relationship between those variables and 30 national electric vehicle market shares for the year 2012. The model found financial incentives, charging infrastructure, and local presence of production facilities to be significant and positively correlated to a country s electric vehicle market share. Results suggest that of those factors, charging infrastructure was most strongly related to electric vehicle adoption. However, descriptive analysis suggests that neither financial incentives nor charging infrastructure ensure high electric vehicle adoption rates.

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[24]
Stern P C.Individual and household interactions with energy systems: Toward integrated understanding[J]. Energy Research & Social Science, 2014,1:41-48.This paper argues for the value of developing an integrated, trans-disciplinary science of human nergy interactions and suggests that Energy Research & Social Science can provide a space for further development of this science. It sketches this intellectual domain and then focuses on that part of it that encompasses interactions of individuals and households with energy systems. It considers the roles of these actors as energy consumers, as citizens who may influence the development and regulation of energy systems, as energy producers, as participants in organizations and institutions, and as parties affected by energy systems. The paper shows, in each case, that single disciplines rarely provide the depth of knowledge that is desirable for understanding or influencing individual and household interactions with energy systems and that integration of knowledge and insights from multiple disciplines is required. It also suggests some promising research directions.

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[25]
杨礼琼,李伟娜.集聚外部性、环境技术效率与节能减排[J].软科学,2011,25(9):14-19.

[ Yang L Q, Li W N.Agglomeration externality, environmental technology efficiency and ESER[J]. Soft Science, 2011,25(9):14-19. ]

[26]
刘昌义.气候变化经济学中贴现率问题的最新研究进展[J]. 经济学动态,2012(3):123-129.

[ Liu C Y.Recent advances in the discount rate in climate change economics[J]. Economics Information, 2012(3):123-129. ]

[27]
刘允芬. 气候变化对我国沿海渔业生产影响的评价[J].中国农业气象,2000,21(4):1-5.

[ Liu Y F.Study of the impact of climatic change on fishery production at coastal areas in China[J]. Chinese Journal of Agrometeorology, 2000,21(4):1-5. ]

[28]
宁金花,申双和.气候变化对中国农业的影响[J].现代农业科技,2009(12):251-254.从种植制度、作物生产潜力、作物产量、气象灾害以及病虫害等方面阐述了气候变化对中国农业的影响．分析了应对气候变化的对策，并对未来研究作出展望。

DOI

[ Ning J H, Shen S H.Effects of climate change on agriculture in China[J]. Modern Agricultural Science and Technology, 2009(12):251-254. ]

[29]
郑景云,葛全胜,郝志新.气候增暖对我国近40年植物物候变化的影响[J].科学通报,2002,47(20):1582-1587.lt;p>根据现代气象观测资料及中国科学院物候观测网络26个观测站点的物候资料, 分析了近40年温度变化对我国木本植物物候变化的影响, 并建立了不同年代物候期与地理位置之间的关系模式, 分析了当前气候增暖背景下物候期地理分布模式对温度变化的响应. 结果表明: (1) 物候期的提前与推迟对温度的上升与下降的响应是非线性的. 20世纪80年代以后, 在同等升降温幅度情况下, 因降温而导致的物候期推迟幅度较因升温而导致的物候期提前幅度大; 因升温而导致的物候期提前日数的变化率随着升温幅度的增大而减小, 因降温而导致物候期推迟日数的变化率随着降温幅度的增大而加大. (2)物候期与地理位置的关系模式因气候变化而呈现不稳定特点. 随着20世纪80年代以后我国大部分地区的春季增温及秦岭以南广大地区的降温, 东北、华北及长江下游等地区的物候期提前, 西南东部、长江中游等地区的物候期推迟; 同时物候期随纬度变化的幅度减小.</p>

DOI

[ Zhen J Y, Ge Q S, Hao Z X.et al.Effect of climate warming on plant phenology in recent 40 years in China[J]. Chinese Science Bulletin, 2002,47(20):1582-1587. ]

[30]
陈小勇,林鹏.我国红树林对全球气候变化的响应及其作用[J].海洋湖沼通报,1999(2):11-17.

[ Chen X Y, Lin P.Responses and roles of mangroves in China to global climate changes[J]. Transactions of Oceanology and Limnology, 1999(2):11-17. ]

[31]
丑洁明,叶笃正.构建一个经济—气候新模型评价气候变化对粮食产量的影响[J].气候与环境研究,2006,11(3):347-353.

[ Chou J M, Ye D Z.Assessing the effect of climate change on grains yields with a new economy-climate model[J]. Climatic and Environmental Research, 2006,11(3):347-353. ]

[32]
张永勤,缪启龙.气候变化对江苏省经济的影响研究[J].长江流域资源与环境,2001(10):8-14.利用经济学上的“投入—产出” 分析方法 ,结合气候变化对农业产量影响的计算机模拟系统 ,研究了当气候变化影响农业生产和产量时 ,江苏省农业产值的变化及与农业部门相联系的国民经济各个部门产出量的变化。考虑江苏省的经济发展速度和产业结构 ,预测了未来不同气候变化情景下 ,为使经济发展达到预期目标 ,社会需对各经济部门追加的资金投入量及各经济部门之间相互投入量的变化 ,提出了适应气候变化的相应对策。研究结果反映了国民经济各部门之间及部门与整体的相互联系 ,从而对制定区域经济平衡发展规划提供了理论依据和建议。

DOI

[ Zhang Y Q, Miao Q L.Research of climate change on the economy of Jiangsu Povince[J]. Resources and Environment in the Yangtza Basin, 2001(10):8-14. ]

[33]
Deng X, Shi Q, Zhang Q, et al.Impacts of land use and land cover changes on surface energy and water balance in the Heihe River Basin of China, 2000-2010[J]. Physics & Chemistry of the Earth Parts A/b/c, 2015,79:2-10.It is well known that there are huge land use and land cover changes (LUCC) all over the world in recent decades, and plenty of ensuing effect appeared on the energy and water balance. This study aims to analyze the impacts of land use and land cover changes on the energy and water balance in the Heihe River Basin of China during 2000–2010, and four key study sites with representative hydrological stations and dramatic LUCC in the past decades were selected to illustrate the responses of the energy and water balance to LUCC. First, LUCC of the Heihe River Basin from 2000 to 2010 was analyzed based on the interpretation of remote sensing images. Then a series of indicators of the energy and water balances were simulated with the Weather Research and Forecasting (WRF) model and corresponding land use and land cover data. Thereafter the impacts of LUCC on the surface energy and water balance were detected and analyzed. The spatial–temporal variance of the impacts of LUCC on energy and water balance in a typical arid inland river basin was specifically presented in following analysis. The results show that different land use/cover conversions result in various energy balances. During this process, the most significant impacts on surface energy balance occurred when grassland was converted to barren or sparsely vegetated land. As for water balance, the impact is measured with variations of precipitation, runoff and evapotranspiration induced by LUCC, which were also remarkable, although seasonal trends of the effects are similar among various land use/cover conversions during 2000–2010. At last, policy suggestions, e.g., shifting the water balance by LUCC to improve the water management, are given to conclude this study.

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[34]
Loisel R.Environmental climate instruments in Romania: A comparative approach using dynamic CGE modelling[J]. Energy Policy, 2009,37:2190-2204.This study simulates a CO permit market in Romania using a dynamic general equilibrium model. The carbon constraint is set at 20.7% below the reference emissions level for sectors eligible according to the European Union Emission Trading Scheme (EU-ETS). Free permit distribution enhances growth despite a severe emissions cap, because environmental regulation stimulates structural changes [Porter, M., 1991. American's green strategy. Scientific American 264, 168]. That is, grandfathering allows sectors additional resources to invest in developing technologies, but it also raises the CO abatement costs because of energy rebound effects from enhanced growth. Results under endogenous growth [Romer, P.M., 1990. Endogenous technological change. Journal of Political Economy 98 (5), 71 102] are very similar to those obtained under an exogenous growth scenario [Ramsey, Y.F., 1928. A mathematical theory of saving. Economic Journal 38, 543 559], as the substitution effects are responsible for the majority of variations; in addition, Romanian research activities are too modest to significantly impact this system. The abatement cost per unit of GDP is higher under endogenous growth, as spillover effects reduce incentives to invest. Technological diffusion continues to have a positive impact on economic growth, which counterbalances the free-riding attitude adopted by some energy-intensive sectors, such as glass and cement.

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[35]
王灿,陈吉宁,邹骥.基于CGE模型的CO2减排对中国经济的影响[J].清华大学学报:自然科学版,2005,45(12):1621-1624.为有助于中国在气候谈判过程中科学有效地维护国家利益,应用一个综合描述中国经济、能源、环境系统的递推动态“可计算一般均衡”(com pu tab le genera l equ ilibrium,CGE)模型,分析在中国实施碳减排政策的经济影响。以2010年实施碳税政策为模拟情景,定量描述了减排政策下国内生产总值(GDP)、能源价格、资本价格等宏观经济变量的变化。结果表明:当减排率为0~40%时,GDP损失率在0~3.9%之间,减排边际社会成本是边际技术成本的2倍左右。在中国实施CO2减排政策将有助于能源效率的提高,但同时也将对中国经济增长和就业带来负面影响。

DOI

[ Wang C, Chen J N, Zou J.Impact assessment of CO2 mitigation on China economy based on a CGE model[J]. Journal of Tsinghua University (Science and Technology), 2005,45(12):1621-1624. ]

[36]
牛玉静,陈文颖,吴宗鑫.全球多区域CGE模型的构建及碳泄漏问题模拟分析[J].数量经济技术经济研究,2012,29(11):34-50.

[ Niu Y J, Chen W Y, Wu Z X.Construction of global multi-regional CGE model and simulation analysis of carbon leakage[J]. The Journal of Quantitative & Technical Economics, 2012,29(11):34-50. ]

[37]
Matsumoto K, Fukuda T.Environmental and economic analyses of the carbon tax based on the imputed price using applied general equilibrium model: Taxation on the upper industrial sectors[J]. Environmental Economics and Policy Studies, 2006,8(1):89-102.Considering the latest arguments on global warming, CO 2 emissions reduction by not only developed countries but also by developing countries is becoming a pivotal issue. Although the worldwide uniform-rate carbon tax (UCT) is thought to be a cost-effective method to reduce CO 2 emissions, it places heavy economic burdens on developing countries. Because such a policy is likely to be opposed by developing countries and is against ommon but differentiated responsibilities of the UNFCCC, it is unlikely to be successfully implemented. This article discusses the effects of the worldwide differentiated-rate carbon tax from the policy viewpoint regarding environmental (CO 2 ) and economic (gross domestic product) aspects. The tax, based on the imputed price of carbon (ICT), was compared with UCT by simulation analysis using the applied general equilibrium model. The world economy was classified into 15 industries and 14 regions in the model. Each tax was imposed on the upper industrial sectors. As ICT reduced CO 2 emissions slightly less than UCT, it was found to generate positive GDP effects on developing countries, unlike UCT. With regard to the importance of worldwide introduction of CO 2 abating policies and avoidance of excessive economic burdens on developing countries, ICT has higher economic equity and policy effectiveness than UCT.

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[38]
Cherubini F, Gasser T, Bright R M, et al.Linearity between temperature peak and bioenergy CO2 emission rates[J]. Nature Climate Change, 2014,4:983-987.Many future energy and emission scenarios envisage an increase of bioenergy in the global primary energy mix(1-4). In most climate impact assessment models and policies, bioenergy systems are assumed to be carbon neutral, thus ignoring the time lag between CO2 emissions from biomass combustion and CO2 uptake by vegetation(5). Here, we show that the temperature peak caused by CO2 emissions from bioenergy is proportional to the maximum rate at which emissions occur and is almost insensitive to cumulative emissions. Whereas the carbon-climate response (CCR; ref. 6) to fossil fuel emissions is approximately constant, the CCR to bioenergy emissions depends on time, biomass turnover times, and emission scenarios. The linearity between temperature peak and bioenergy CO2 emission rates resembles the characteristic of the temperature response to short-lived climate forcers. As for the latter(7-9), the timing of CO2 emissions from bioenergy matters. Under the international agreement to limit global warming to 2 degrees C by 2100(3), early emissions from bioenergy thus have smaller contributions on the targeted temperature than emissions postponed later into the future, especially when bioenergy is sourced from biomass with medium(50-60 years) or long turnover times (100 years).

DOI

[39]
Leduc M, Matthews H D, de Elía R. Regional estimates of the transient climate response to cumulative CO2 emissions[J]. Nature Climate Change, 2016,6(5):474.

[40]
吴国雄,林海,邹晓蕾,等.全球气候变化研究与科学数据[J].地球科学进展, 2014,29(1):15-22.lt;p>当今,全球变化与地球系统研究已成为一门涉及多时空尺度、多学科交叉融合的复杂科学。不仅包括观测、模拟与预测的科学研究,还包括海量科学数据存储、信息分析和决策服务等多种信息技术要求。因此,全球变化研究与科学数据之间的关系非常密切、互为依存。全球变化研究对科学数据有广泛的需求,反之,大量多参数、准确、高质量的科学数据也对全球变化研究具有不可低估的促进作用。所以,建设全球变化与地球系统研究的数据和信息系统,推动区域和全球数据共享是国际科技界的一项重要任务。国家地球系统科学数据共享中心经历了10年的发展,取得了举世瞩目的成绩,获得了我国地学界的一致好评。第一屆地球系统科学数据论坛的召开,也标志着我国为地球系统研究服务的科学数据共享事业已进入到一个新的阶段。</p>

DOI

[ Wu G X, Lin H, Zou X L.et al.2014. Research on global climate change and scientific data[J]. Advance in Earth Sciences, 2014,29(1):15-22. ]

[41]
Zeng N., Zhao F, Collatz G J, et al.Agricultural Green Revolution as a driver of increasing atmospheric CO2 seasonal amplitude[J]. Nature, 2014,515:394-397.Abstract The atmospheric carbon dioxide (CO2) record displays a prominent seasonal cycle that arises mainly from changes in vegetation growth and the corresponding CO2 uptake during the boreal spring and summer growing seasons and CO2 release during the autumn and winter seasons. The CO2 seasonal amplitude has increased over the past five decades, suggesting an increase in Northern Hemisphere biospheric activity. It has been proposed that vegetation growth may have been stimulated by higher concentrations of CO2 as well as by warming in recent decades, but such mechanisms have been unable to explain the full range and magnitude of the observed increase in CO2 seasonal amplitude. Here we suggest that the intensification of agriculture (the Green Revolution, in which much greater crop yield per unit area was achieved by hybridization, irrigation and fertilization) during the past five decades is a driver of changes in the seasonal characteristics of the global carbon cycle. Our analysis of CO2 data and atmospheric inversions shows a robust 15 per cent long-term increase in CO2 seasonal amplitude from 1961 to 2010, punctuated by large decadal and interannual variations. Using a terrestrial carbon cycle model that takes into account high-yield cultivars, fertilizer use and irrigation, we find that the long-term increase in CO2 seasonal amplitude arises from two major regions: the mid-latitude cropland between 25°02N and 60°02N and the high-latitude natural vegetation between 50°02N and 70°02N. The long-term trend of seasonal amplitude increase is 0.31102±020.027 per cent per year, of which sensitivity experiments attribute 45, 29 and 26 per cent to land-use change, climate variability and change, and increased productivity due to CO2 fertilization, respectively. Vegetation growth was earlier by one to two weeks, as measured by the mid-point of vegetation carbon uptake, and took up 0.5 petagrams more carbon in July, the height of the growing season, during 2001-2010 than in 1961-1970, suggesting that human land use and management contribute to seasonal changes in the CO2 exchange between the biosphere and the atmosphere.

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[42]
Deng X, Liu J, Lin Y, et al.A framework for theland use change dynamics model compatible with RCMs[J]. Adv Meteorol, 2013,65:187-190.A framework of land use change dynamics (LUCD) model compatible with regional climate models (RCMs) is introduced in this paper. The LUCD model can be subdivided into three modules, namely, economic module, vegetation change module, and agent-based module. The economic module is capable of estimating the demand of land use changes in economic activities maximizing economic utility. A computable general equilibrium (CGE) modeling framework is introduced and an approach to introduce land as a production factor into the economic module is proposed. The vegetation change module provides the probability of vegetation change driven by climate change. The agroecological zone (AEZ) model is supposed to be the optimal option for constructing the vegetation change module. The agent-based module identifies whether the land use change demand and vegetation change can be realized and provides the land use change simulation results which are the underlying surfaces needed by RCM. By importing the RCMs' simulation results of climate change and providing the simulation results of land use change for RCMs, the LUCD model would be compatible with RCMs. The coupled simulation system composed of LUCD and RCMs can be very effective in simulating the land surface processes and their changing patterns.

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[43]
陈卓奇,陈镜明,郑小谷,等.基于大气反演陆地碳通量季节变化信息的模型参数优化研究[J].科学通报,2015,60:3397-3397.生态系统碳通量是光合作用和呼吸作用之和.在没有附加信息的情况下,区分光合作用和呼吸作用对碳通量的贡献是目前参数优化研究的难点.本研究探讨了利用陆地生态系统碳通量的季节变化信息,优化生态系统模型中光合作用和呼吸作用参数的可行性,并利用大气反演系统估算的净生态系统生产力（NEP）,在北美北部地区（BNA）开展了陆地生态系统模型参数（25maxV和Q10）优化研究.通过模型敏感性分析,

DOI

[ Chen Z, Chen J, Zheng X.et al.Optimizing photosynthetic and respiratory parameters based on the seasonal variation pattern in regional net ecosystem productivity obtained from atmospheric inversion[J]. Chinese Science Bulletin, 2015,60:1943-1950. ]

[44]
刘羽,虢建宏,岳天祥,等.地表CO2浓度分布模拟试验及分析[J].地球信息科学报,2017,19(2):197-204.如何获取CO2浓度时空分布特征,是气候变化研究中的一个关键问题。本文基于中国碳卫星在吉林航飞试验区的地面观测数据,分析地表CO2浓度与环境变量的相关关系,运用多元线性回归与HASM高精度曲面建模相结合的方法,模拟航飞区地表CO2浓度分布格局。结果表明：CO2浓度空间分布受气象条件的影响较大,短波辐射是影响CO2浓度的重要因素;第1时段整体浓度最高,特别是在西部区域;第2时段CO2浓度高值区东移,呈现西低东高的分布特点;第3时段浓度空间分布与第2时段有类似的特征,但细节存在差异,且高值区缩小;精度对比显示在采样点较少及采样密度不大的情况下,HASM方法的模拟误差小于Kriging方法。因此,这种使用多元线性回归模型通过引入环境变量获得高分辨率趋势面,结合HASM模型进行修正残差提高模拟结果精度的手段,可作为模拟地表CO2浓度时空分布的有效方法。

DOI

[ Liu Y, Guo J H, Yue T X, et al.Simulation and analysis of Carbon Dioxide concentration in the surface layer[J]. Journal of Geo-information Science, 2017,19(2):197-204. ]

[45]
Deng X, Zhao C, Lin Y, et al.Downscaling the impacts of large-scale LUCC on surface temperature along with IPCC RCPs: A global perspective[J]. Energies, 2014,7:2720-2739.This study focuses on the potential impacts of large-scale land use and land cover changes (LUCC) on surface temperature from a global perspective. As important types of LUCC, urbanization, deforestation, cultivated land reclamation, and grassland degradation have effects on the climate, the potential changes of the surface temperature caused by these four types of large-scale LUCC from 2010 to 2050 are downscaled, and this issue analyzed worldwide along with Representative Concentration Pathways (RCPs) of the Intergovernmental Panel on Climate Change (IPCC). The first case study presents some evidence of the effects of future urbanization on surface temperature in the Northeast megalopolis of the United States of America (USA). In order to understand the potential climatological variability caused by future forest deforestation and vulnerability, we chose Brazilian Amazon region as the second case study. The third selected region in India as a typical region of cultivated land reclamation where the possible climatic impacts are explored. In the fourth case study, we simulate the surface temperature changes caused by future grassland degradation in Mongolia. Results show that the temperature in built-up area would increase obviously throughout the four land types. In addition, the effects of all four large-scale LUCC on monthly average temperature change would vary from month to month with obviously spatial heterogeneity.

DOI

[46]
IPCC. Climate change: Work group I contribution to the IPCC fifth assessment report(AR5)[R]. Switzerland: IPCC, 2014.

[47]
蒲强,邹滨,翟亮,等.集成多源遥感数据的PM2.5浓度空间分布制图[J].地球信息科学学报,2016,18(12):1717-1724.

[ Pu Q, Zou B, Zhai L, et al.Mapping of PM2.5 fine particulates using multi-source remote sensing data[J]. Journal of Geo-information Science, 2016,18(12):1717-1724. ]

[48]
时洪涛,宋冬梅,单新建,等. MODIS_LST与AMSR-E_BT的相关性及地表温度反演[J].地球信息科学学报,2016,18(4):564-574.lt;p>本文以2007年和2008年MODIS每日地表温度（LST）数据及AMSR-E地表亮温（BT）数据为研究对象,结合土地覆盖类型数据,统计分析MODIS_LST与AMSR-E_BT在不同土地覆盖类型、频率和极化方式条件下的相关性。结果表明,频率在18.7、23.8和36.5 GHz的AMSR-E-BT与MODIS_LST的相关性较大,且在垂直极化通道上的相关性较在水平极化上大;不同土地覆盖类型,与MODIS_LST相关性较大所对应的AMSR-E微波通道不同。同时,考虑混合像元问题对相关性的影响,对25种不同地物类型组合下MODIS_LST与AMSR-E-BT的相关性进行统计分析,发现混合像元中地物类型越多,则二者相关性越小。最后,采用多元线性回归分析法,根据不同土地覆盖类型建立反演回归模型,对部分研究区域MODIS-LST进行反演,误差平均在&plusmn;3.15 K以内,与不考虑下垫面覆盖的模型比较,反演MODIS_LST精度平均提高了1.5 K。</p>

DOI

[ Shi H T, Song D M, Shan X J.et al.The correlation analysis between MODIS_LST and AMSR-E_BT and study of LST retrieval method[J]. Journal of Geo-information Science, 2016,18(4):564-574. ]

[49]
Kim, Seong-joong, Kim, Ji-Won, Kim, Baek-Min. Last Glacial Maximum climate over Kerean Peninsula in PMIP3 simulations[J]. Quaternary International, 2015,384:52-81.The Last Glacial Maximum (LGM) at 21,000 years before present is a marked climate event with thick ice sheets over North America and Europe and associated sea level drop of about 120m. We used the most updated coupled climate model results to analyze the climate change over Korea for the LGM. Eight coupled models (CCSM, CNRM, COSMOS, FGOALS, IPSL, MIROC, MPI, and MRI) were used to analyze the LGM climate. With LGM boundary conditions, surface air temperature decreases almost everywhere in all seasons with the largest cooling in winter and least cooling in summer. Overall, in the LGM, the multi-model annual-mean cooling over Korea is 5.85 C掳, which is consistent with proxy evidence using pollen reconstructions. Associated with the surface cooling, precipitation decreases in general, with the largest reduction in winter by 56%, but in summer precipitation increases by 12% in the LGM over Korea. Overall, precipitation decreases by about 14% in the LGM over Korea. The surface cooling tends to increase surface pressure almost everywhere over Asia. The sea level pressure increase is especially larger in high latitudes and this leads to the easterly wind anomaly in northern part of Korea. On the other hand, in South Korea, the increase in surface pressure leads to the westerly wind anomaly. The increase in surface pressure associated with surface cooling leads to the anticlockwise wind anomalies in the LGM over Korea.

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[50]
龚元,赵敏,姚鑫,等.基于Hsieh和Kljun模型的城市生态系统碳通量贡献区分析与对比[J].环境工程技术学报,2017,7(2):225-231.利用上海市奉贤大学城内的涡动相关通量观测站点,基于Hsieh和Kljun模型对研究区内的碳通量贡献区进行了分析。结果表明：1）随着大气稳定度的增加,各风向上的碳通量贡献区范围有增加的趋势;2）当大气处于稳定条件下时,非主风向上的碳通量贡献区范围要大于主风向;3）当大气处于不稳定状态时,主风向和非主风向上的碳通量贡献区范围相差不大;4）在各风向和各大气稳定度上Hsieh和Kljun模型所输出的碳通量贡献区范围数值不同,但无显著差异,碳通量贡献区范围形态近似椭圆;5）Hsieh和Kljun模型输出的垂直于主风向和非主风向上的碳通量贡献区的长度无显著差异;6）在迎风向上Hsieh和Kljun模型的碳通量贡献峰值所处的位置有显著差异。

DOI

[ Gong Y, Zhao M, Yao X.et al.Analysis and comparison of carbon flux contribution zones in urban ecological system based on Hsieh and Kljun Models[J]. Journal of Environmental Engineering Technology, 2017,7(2):225-231. ]

[51]
Bell, Andrew Reid.Informing decisions in agent-based modelsnology, on zones[J]. Environmental modelling & Software, 2017,93:310-321.

[52]
Fan J L, Liang Q M, Wang, et al. Will export rebate policy be effective for CO2 emissions reduction in China? A CEEPA-based analysis[J]. Journal of Cleaner Production, 2015,103:120-129.China has adopted cancellation of export tax rebate policies on many occasions to push ahead energy conservation and emission reduction since 2007. By applying a CEEPA (China Energy & Environmental Policy Analysis system) model, this paper simulates the impacts of the cancellation of export rebates on CO 2 emissions and socio-economic consequences in different scenarios so as to figure out whether it works. This paper covers three export rebate scenarios and makes comparisons between the impacts of export rebates on emission reduction effects and that of carbon tax policies. The conclusions are: 1) the current policy which cancels export rebates for key sectors can cut emissions at huge economic cost, yet it is unsustainable; 2) the policy which cancels export rebates for key sectors and meanwhile subsidizes sectoral outputs yields double dividends in the short term, thus can facilitate emission reduction yet the boost is limited; 3) the policy which cancels export rebates and boosts domestic demand helps improving residents' welfare in the short term while it may inflict pronounced social and economic impacts in the long run. So policy of this kind should be adopted with great caution; 4) export rebates generate far more economic costs than carbon tax policies in the long term, and don't contribute to optimizing the energy mix as well as the latter. In summary, canceling export rebates should not be regarded as a priority to encourage emission reduction.

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[53]
吴静,朱潜挺,刘昌新,等. DICE/ RICE模型中碳循环模块的比较[J].生态学报,2014,34(22):6734-6744. [ Wu J, Zhu Q T, Liu C X, et al. Comparison of the carbon cycle models in DICE/ RICE[J]. Acta Ecologica Sinica, 2014,34(22):6734-6744. ]碳循环模型的正确构建是影响综合集成评估模型IAM(Integrated Assessment Model)模拟结果的重要因素之一.DICE/RICE模型中的碳循环模型主要有两个,即Nordhaus单层碳库模型和Nordhaus三层碳库模型,但这两个模型的主要缺陷是不考虑陆地生态系统在碳循环中的贡献,因此,引入了包含陆地生态系统的Svirezhev碳循环模型,并将其与Nordhaus单层碳库模型、Nordhaus三层碳库模型展开比较研究.结果表明,在基于历史数据的模型检验中,Svirezhev碳循环模型对全球二氧化碳浓度模拟的准确度优于其他两个模型.对于未来全球气候变化的模拟,3个模型模拟得到了至2100年的温度预测值分别为2.98,3.54,2.91℃,二氧化碳浓度值分别为608.04,733.04,594.70μL/L.其中,Svirezhev碳循环模型的模拟值在3个模型中最低,表明了陆地生态系统和海洋对二氧化碳的吸收作用对抑制全球升温的贡献;而分析也发现Nordhaus三层碳库模型对陆地生态系统和海洋碳库的模拟与实际观测值偏离较大.最后,通过敏感性分析,研究发现DICE/RICE模型中使用的气候响应模块在短期温度模拟中对地表温度的初值较为敏感,在长期温度模拟中敏感度显著下降.总之,从碳循环机制的模拟性能而言,Svirezhev碳循环模型优于其他两个模型,而Nordhaus单层碳库模型虽然机制较为简单却保证了模拟的准确性,但Nordhaus三层碳库模型虽然丰富了碳库的表征,实际上各碳库的模拟准确性差,降低了模型的可靠性.

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[54]
Qi W, Deng X, Chu X, et al.Emergy anlysis on urban metabolism by counties in Beijing[J]. Physics and Chemistry of the Earth, 2017,101:157-165.Beijing is an international metropolis, with rapid urbanization during the last 30 years. However, it faces the challenge of sustainability with limited natural resources. This paper attempts to incorporate emergy analysis on urban metabolism to investigate the sustainability of the entire Beijing at the county level. Based on the time-series climate data and socioeconomic data, we calculated the structure, intensities, environment pressures and output efficiency of the urban metabolic emergy system by counties between 2005 and 2014. The result shows that the metabolic emergy stores of Beijing, especially in Capital Function Core (CFC) area, had been increasing significantly during the study period, especially for the increasing imported and exported emergy accounting. The 16 districts of Beijing can be grouped into four types of functional areas in terms of the function in urban metabolism. The five parts of urban metabolic emergy system had obviously spatial difference by counties, and the renewable emergy in CFC area and Urban Function Development (UFD) zone was obviously lower than in City Development (CD) zone and Ecological Conservation Development (ECD) area. The non-renewable emergy and waste emergy in CFC area, UFD zone and CD zone were obviously higher than that in ECD area. The imported emergy and exported emergy were significantly higher in Dongcheng, Xicheng and Chaoyang district. Emergy use intensities of CFC area had been increasing with the rapid rise in imported emergy and exported emergy, resulting in the increasing environmental pressure. However, the district governments of CFC area are trying to enhance output efficiency and sustainability to reduce waste emergy. The indices of EYR and ESI had been gradually decreasing and the region with the highest value of ESI and EYR, in decreasing order, are: ECD area, CD zone, UFD zone, and CFC area. The result indicates that CFC area is more fragile and dependent on external resources. Therefore, the Beijing government, especially the district governments of CFC area should encourage the exploitation and utilization of renewable resources and energy, increase the consumption efficiency of non-renewable resources and energy, and establish the mechanism to re-use wastes of resources and energy in order to promote the urban metabolism.

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[55]
Chaudhry P, Singh B, Tewari V.Non-market economic valuation in developing countries: Role of participant observation method in CVM analysis[J]. Journal of Forest Economics, 2007,13(4):259-275.Developing countries have high proportion of black money and related corruption in the society in comparison to the developed ones. This aspect has to be kept in mind while conducting contingent valuation method (CVM) questionnaire survey (in-person) at the site whose economic valuation is being done. Participant observation method (POM) and unstructured interview schedule (UIS) are the two means, which must be used in addition to structured interview schedule during CVM studies in developing countries to arrive at a reasonable non-market economic valuation figure of an environmental amenity. It has been observed that researchers generally ignore this fact during survey for primary data collection among respondents who are quite well off, educated and belong to countries of huge parallel economy. However in the present study, we have utilized these two means during primary data collection for a CVM study and reached the conclusion that CVM has to be used with caution even among educated masses in the developing countries.

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