社会经济因素对大气污染物与二氧化碳区域协同减排的影响机理研究：基于变系数模型的分析

More attentions have been paid to a special co-benefit studies: certain options for greenhouse gas (GHG) emission reduction will simultaneously reduce local air pollution, and air quality management also affects GHG abatement.Integrating this co-benefit into the regional sustainable development decision-making process is urgently required in China. Methods recently used to evaluate this benefit are the sectoral technology based studies, also called bottom-up approach, which contributes to the selection of more effective pollution control technologies for certain sectors. However, it is difficult for this method to deal with the social-economic influence on the regional co-benefit. This research will explore the social-economic role in the regional co-benefit of air pollution control and carbon emission reduction, focusing on three questions, including 'Which factors play roles in the regional co-benefit?','What is the influence rule?' and 'How to optimize this co-benefit?'. To solve these question, 1)the regional historic data including both air pollutant and carbon emission will be calculated and pretreated on the basis of desk review and expert consultation, the inherent laws between the two data series will be depicted and illustated using certain parametric regressive models. Then the key driving forces affecting the regional co-benefit law would be identified with the help of statistical models and spatial analysis models and two aspects are focused: spatial differentiation and index decompostion.2) Based on the studies above, varying coefficient model would be employed to resolve the regional co-benefit's dynamic evolution mechanism and explore the key elements' contribution to the co-benefit.3) Finally, scenario analysis will be improved to deal with the integration of co-benefit and regional decision-making process. The outcome is anticipated to contribute to implement better regional sustaionable development and climate-friendly strategies.

利用协同效应同时减排多种污染物，要求尽快建立区域发展决策过程的协同效应融入机制。目前基于行业技术核查的研究难以分析社会经济因素对区域层面协同效应的影响。本课题以社会经济因素对大气污染物和二氧化碳区域协同减排的影响机理为研究目标，基于数理模型重点解决"哪些因素对区域协同效应产生影响？""这些影响有什么规律及其动力学原理？"以及"如何优化这些因素组合？"等三个问题。因此本课题①利用回归系数模型刻画区域层面上的协同减排规律，从空间差异和因素分解两个角度遴选影响这种协同效应的主要社会经济因素；②突破以往回归模型的静态参数假设，从动态的角度综合运用变系数模型解析典型因素对这种协同效应贡献的时间变化规律，建立社会经济因素对区域协同减排的影响机理模型；③基于减排规律和机理模型，提出协同减排机制优化的情景分析方法和区域发展决策过程的协同效应融入路径，为我国不同区域的协同减排优化发展决策提供技术支持。

在区域可持续发展决策过程融入大气污染物和二氧化碳的协同减排因素，环境质量改善和温室气体减排的双重目标可以更好的共同实现。本课题（1）深入开展了我国主要行业协同减排和总量关联管理的实地调研工作，基于排放源的性质总结了污染物排放与碳排放的内在相关关系；（2）通过对当前的区域碳排放计量模型进行讨论，本课题对IPCC计量模型进行了改进，通过探讨碳责任分担原理，基于中国大量排放数据的挖掘，识别出火电行业的特殊性，创新性的提出了一种简单易行的基于公平发展的碳排放混合估算方法，对全球气候谈判、碳责任划分和国家碳减排政策制定提供了新的视角；（3）系统开展了碳排放和污染排放空间差异性分析和因素分解研究，完成基于协同控制目标的我国大气污染物排放影响因素研究工作，识别了区域协同效应的社会经济影响因素，并选取全国30个省市1991年到2013年碳排放和二氧化硫排放的官方数据，采用面板数据回归中的变系数模型和固定效应模型，引入人口、经济增长、城市化水平、能源结构、产业结构以及政策因素共七个指标作为解释变量，以碳排放量与二氧化硫排放量之比作为被解释变量进行量化回归分析；（4）课题利用混合碳排放估算模型、采用多指标联合表征，探讨了中国省域间的碳排放强度的差异性及其根源。运用逐步回归方法和系统聚类分析工具，将中国30个省市划分为经济发达型低碳区域、产业优化型低碳区域、资源丰富型高碳区域和经济发展型高碳区域四种类型。针对不同类型的区域，提出了差异化的低碳发展政策建议并构建了不同类型区域低碳发展过程应关注的共性指标和特征指标。本课题共发表高水平学术论文8篇，其中SCI收录4篇，国际和国内学术会议专题报告3人次，指导研究生3名并成功晋升副教授1人，圆满完成了既定研究目标。

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