基于环境生产技术的区域大气污染物减排目标、逐步标杆路径及技术预测研究

Following the rapid and diversified developments of economy and society, environmental pollution has been transformed from point-source to area-source, single to complex forms. At present, the regional and complex air pollutions, such as the haze, have been severely affecting people's health and life safety. As the basic unit of protecting ecological environment, district is the liability subject to control air pollution with multi-target and multi-stage. The relationship between regional economic activities and the emissions of air pollutants can be studied in the framework of environmental production technology, which can describe the joint production of desirable and undesirable outputs (pollutants generated), provide the behavioral objective, burden share and emissions path for improving production activity, and even short and medium term predictions for production activity and environmental production technology. Considering the constraints from environmental production technology, this research combines environmental performance measure, benchmarking management, self-organizing feature map neural network and technometrics to study the natural, managerial, costly and multi-criteria abatement activities and targets, stratifies the environmental DEA technology, establishes stepwise benchmarking path, and explores the impact factors, mechanisms and rules for spanning technology levels. In practice, this research will explore and classify the benchmarks for each region to realize technology leapfrogging step by step, and make plans for pursuing benchmarks in each technology level. At last, this research will provide decision-making reference for the promotion of regional emission reduction capability.

伴随我国经济社会的高速、多元化发展，环境污染呈现出由单一向复合、由点源向面源蔓延与加重的趋势，当前以“雾霾”为特征的区域性大气污染复合问题严重影响了人民群众的身体健康与生命安全。区域作为生态环境保护的基本单元，是多目标、分阶段统筹大气污染防治的责任主体。从环境生产技术视角分析区域经济活动与大气污染物排放的关系，可以从源头上把握内化到生产过程中的大气污染物排放，为生产行为的改善提供目标、责任、路径，乃至中短期生产行为与生产技术预测。本课题采用环境绩效测度、标杆管理、自组织特征映射神经网络、技术计量学等方法，重点研究环境生产技术约束下，自然减排、管理减排、成本最优与多准则减排目标与减排行为，对环境DEA技术进行分层，构建标杆路径，挖掘影响标杆路径选择的深层诱因及技术递阶规律。从实践上分区域、分类别在现实中搜寻“逐步对标对象”，制定可行“逐步对标方案”，为区域减排能力提升提供决策参考。

中国正处于破解生态环境约束、实现经济转型升级、构建可持续发展新模式的关键时期，全面推进生态文明建设，践行绿水青山就是金山银山的发展理念成为时代主题。在此背景下，如何以提升能源效率和环境绩效为抓手，实现高产出、低消耗、低污染的目标，成为亟待解决的科学问题。本项目提出非径向双期Luenberger能源环境绩效指数来评估城市能源环境绩效动态变化及驱动因素，并将能源环境绩效变化分解为能源环境技术效率变化和能源环境技术进步。然后运用空间探索性分析方法和地理加权回归模型分别识别能源环境绩效的空间集聚特征和减排潜力影响因子。考虑城市在资源禀赋、产业结构、经济发展水平、技术条件等方面存在较高异质性，本项目为不同类型城市量身设计独特的大气污染物减排逐步标杆路径，并对跨区合作减排模式及减排收益分配做了进一步研究。结论如下：（1）城市能源环境绩效提升主要归功于城市能源环境技术进步，但是城市能源环境技术进步速度在逐步放缓。（2）绩效最佳城市一般拥有发达的服务业或先天具有较高质量的生态环境，而绩效最差城市一般是以煤炭、非金属矿产等自然资源的开采、加工为主导产业的资源型城市。（3）绩效最佳城市开始从东部沿海地区移向内陆自然生态禀赋较好且能源消耗较少的地区。（4）烟尘绩效在样本期间出现减排绩效恶化现象，这与该期间中国雾霾天气频发事实相符。（5）通过减排因素回归分析，本项目发现环渤海湾区域的污染物排放强度对减排潜力释放起决定作用。（6）本项目依据城市特点为典型城市量身设计合适的大气污染物减排绩效标杆路径，并总结不同类型城市大气污染物减排逐步标杆规律。（7）单独减排成本及减排损失的大小与地区产业结构和经济发展程度相关，对能源依赖度高的地区单独减排成本高，经济发展水平低的地区减排带来的潜在产出损失比重较大。合作减排确实在一定程度上节约了减排成本。