绿色发展背景下区域旅游生态效率影响因素——以西部地区为例

旅游生态效率是评估区域绿色全要素生产率和可持续发展水平的绩效依据。基于西部各省（市、自治区）2000-2017年的面板数据，用"自下而上"法测算西部地区旅游业碳排放量并运用比值法计算旅游生态效率，分析旅游生态效率的时空演变特征及影响因素。首先构建由旅游生态效率、规模效应、结构效应、技术效应共同组成的PVAR模型，探究3种效应对旅游生态效率的影响。然后在考虑各地区能源消费结构差异的基础上构建面板门槛模型，对旅游业发展水平与旅游生态效率的非线性关系进行实证检验。研究结果表明：（1）西部地区旅游生态效率自2000年西部大开发战略实施以来呈逐步提高的趋势，绿色发展水平持续提高。（2）旅游生态效率受自身滞后因素以及技术效应因素的影响较大，游客规模的扩大、产业结构优化以及技术水平的提高均有利于旅游生态效率的提高。（3）旅游业发展水平对旅游生态效率的影响存在门槛效应，经济发展水平、规模效应、结构效应对旅游生态效率有显著的正向作用，城镇化对旅游生态效率有显著的负向作用。最后根据实证分析的结果，提出西部地区实现旅游业绿色、低碳发展的相关对策。     

黄河流域旅游生态效率时空演变及空间溢出效应——基于73个城市数据的分析

黄河流域旅游生态效率时空演变及空间溢出效应研究，有利于优化旅游资源要素投入，推动黄河流域生态保护及高质量发展。基于超效率SBM模型测算2010-2019年黄河流域73个城市旅游生态效率，借助ArcGIS软件描绘时空演化轨迹，并构建空间杜宾模型揭示空间溢出效应。结果表明：（1）黄河流域旅游生态效率时序上呈现先上升后下降的阶段性特征，空间上呈现"下游-中游-上游"阶梯式递减的异质性特征；（2）旅游生态效率分布具有明显的空间集聚与依赖特征，低水平同质化现象显著；（3）空间溢出效应显著，政府干预、市场规模对邻近城市旅游生态效率具有正向溢出效应，经济发展、产业结构、交通可达性对邻近城市旅游生态效率具有负向溢出效应。基于实证分析结果，提出制定差异化、互补性旅游发展策略，加强区域旅游战略合作，发挥邻近区域辐射带动作用，优化城市空间溢出效应的建议。     

中国生态效率时空动态分布与区域差异

生态效率的积极发展对生态环境和经济协同发展具有重要意义。为研究中国生态效率的发展情况,使用超效率SBM模型对中国2005—2020年省域生态效率进测算,并通过核密度函数、基尼系数、σ收敛和Markov转移矩阵进行时空动态分布和区域差异性分析。研究结果表明：(1)中国生态效率呈现先下降后增长的趋势,北京、青海、广东、海南、上海、江苏、福建、河南、云南生态效率发展较好。(2)六大地理区域生态效率总体差异较大,区域间差异和超变密度是总体差异的主要来源。华北地区生态效率发展较好,东北地区生态效率最低。西北地区区域内部差异最大,东北地区区域内差异最小。中国省域及区域生态效率发展均不具有收敛特征。(3)全国及区域生态效率从t年向t+1年向同水平生态效率转移概率最大,2021—2025年省域生态效率差距仍旧较大,整体水平下降。     

安徽省铜陵市生态效率变化及其驱动因素

首次应用物质流分析(material flow analysis,MFA)方法构建了三层面区域生态效率评价指标体系,其指标分别为:区域直接生态效率(regional direct eco-efficiency,RDE)、区域总体生态效率(regional total eco-efficiency,RTE)、整体生态效率(holistic eco-efficiency,HE),采用数据包络分析(data envelopment analysis,DEA)方法评价了铜陵市1990—2008年间的区域生态效率.本文同时引入莫氏生产力指数(Malmquist productivity index,MPI)研究了相邻年份区域生态效率变化,并找出其生态效率变化的驱动因素.结果表明:1)铜陵市区域直接生态效率虽得到了不断提升,但相对区域总体生态效率和区域整体生态效率而言,其相对生态效率均值不高,80%左右年份的相对生态效率在0.8以下;2)铜陵市直接生态效率的持续增长与铜陵市多年来不断加大资源利用和环境保护技术投入密切相关.为进一步提高直接生态效率,铜陵市既可以通过扩大原材料进口、减少本地采掘实现,又可以通过提高资源生产率...     

新疆城镇化进程中生态效率变化与影响因素

识别城镇化进程中经济社会发展与资源环境的动态关系，能够丰富生态效率影响机制和地域性分异研究，为区域可持续发展提供理论借鉴。本文以新疆干旱区为研究对象，结合超效率SBM模型、熵值法、OLS回归模型，对2002—2019年城镇化进程中生态效率变化，以及不同城镇化水平生态效率的影响因素进行研究，提出优化生态效率的政策建议。结果表明：新疆生态效率较低，具有“中部高、东西低”的空间分异特征；低、中等水平城镇化区域生态效率符合“U”形曲线变化规律，高水平城镇化区域生态效率呈倒“U”形；生态效率受到产业结构和经济发展水平的显著正向影响，低水平城镇化区域的生态效率受到能源结构的显著影响，中等水平城镇化生态效率受到对外联系、科研投入、发展水平影响显著，高水平城镇化生态效率受产业结构、能源结构和对外联系影响显著；推动能源产业升级、增强科研实力、制定差异化生态策略是优化生态效率的主要路径。     

我国农业生态效率的时空差异

农业生态效率是按照定量化的方式反映区域农业发展可持续发展水平,可以作为决策者制定政策的一个抓手。利用基于机会成本的经济核算方法对我国2003—2010年的农业生态效率进行总体分析与评价,并利用回归模型分析农业生态效率的影响因素。结果表明:我国农业生态效率总体水平比较低,但呈逐年好转的趋势,其中劳动力资源和COD环境要素在不同时期对生态价值增长起到关键性作用;农业生态效率空间分布特征显著,秦岭-淮河以北的省市区和传统粮食主产区的农业生态效率相对较低;区域资源环境禀赋条件有助于农业生态效率的提高,但是农资投入和农业政策支持与农业生态效率呈显著负相关,未来进一步提升农业生产资源与环境要素合理配置是保障农业生产可持续的必然选择。     

基于生态效率的辽宁省循环经济分析

生态效率与循环经济相辅相成。基于区域生态效率评价是考量区域循环经济的重要内容,又基于目前对于循环经济与生态效率结合的实证研究相对较少,因此,以生态效率理论为基础,对我国最早开展循环经济的试点省份——辽宁省的循环经济发展作以综合衡量。通过生态效率度量模型与循环经济度量模型,以辽宁省1990～2008年数据为基础,运用基于熵权的TOPSIS方法,分别计算了19a间辽宁省各年的资源效率、环境效率、生态效率,进而综合评价了辽宁省循环经济发展轨迹。研究表明：在19a间,辽宁省生态效率总体呈现波动上升态势,经历了传统经济发展模式——末端治理模式——循环经济模式的转变;19a间,辽宁省循环经济发展状态总体上处于循环性不断增强的状态,即经济发展的同时,环境压力不断减小。研究证明了辽宁省2002年实行循环经济以来取得了明显成效,对全国尤其是东北地区发展循环经济,走新型工业化道路具有重要的示范意义。     

区域生态效率研究进展

作为指示可持续发展水平的重要指标,区域生态效率定量表征了区域发展过程中社会经济和生态环境的协调水平,能够为生态文明建设提供重要科学依据。在对生态效率概念内涵进行系统梳理的基础上,重点探讨了区域生态效率研究的近今进展：研究方法从单一比值到模型模拟、研究对象从静态评估到时空动态、研究内容从效率测度到机理认知。最后,提出区域生态效率研究的重点方向,即地理大数据的时空分析、多要素集成的模型研发、区域城市化的重点关注、面向可持续的区域管治等4个方面。     

多维发展导向视角下江苏省县域生态效率差异化评价

提高生态效率是实现县域经济绿色发展的重要方式，在充分考虑江苏省县域经济发展合作共赢以及发展导向差异的前提下，遴选一产、二产、三产的增加值为关键指标并设置了3种不同的县域经济发展导向，采用权重约束的仁慈型交叉效率模型和Malmquist生产率指数测算了2015-2017年间江苏省32个县域在3种发展导向下的生态效率和生态全要素生产率，剖析各县域生态效率的差异性及其全要素生产率变动的驱动力，探寻各县域的差异化绿色发展模式。研究结果显示：（1）整体上看，江苏省县域总体生态效率水平较高，但同一地级市下辖的县域生态效率排名差距较大，且生态效率高的县域辐射效应不足。（2）从不同发展导向来看，县域平均生态效率值在绿色经济导向下最高，乡村振兴导向下次之，新型工业导向下最低；同时，同一县域在不同导向下的生态效率排名差异较大，隶属于乡村振兴类的县域最多，绿色经济类次之，新型工业类最少。（3）从动态分析来看，江苏省县域生态效率逐步提升，技术进步指数的增长是促进江苏省县域生态全要素生产率指数增长的主导因素，而绝大多数县域的技术效率变化指数保持不变或呈现衰退现象，表明分析期内江苏省县域生态技术效率未有所提升。     

国内外生态效率核算方法及其应用研究述评

生态效率由于具有突出的定量化分析优势,在可持续发展的评价与量化分析中起着重要作用,且在全世界范围内得到广泛推广和应用。参阅近十年国内外相关文献的基础上,系统总结了生态效率的核算方法及其在不同尺度的应用,侧重于国内外对比分析,研究表明:(1)国外已从简单评价转向生态效率驱动机制的探究。(2)对于生态效率测算,国外开始借助会计、金融以及管理学中的理论和模型对现有的经济/环境比值法以及模型法进行改良和修正;我国则侧重于生态效率评价指标体系构建以及生产率模型的应用。(3)在应用层次上,国外侧重于企业及其产品系统的生态效率分析,并且开始将生态效率同产品的生态设计、关键问题辨识、系统开发等融合起来,而区域等大尺度的研究则处于尝试阶段;我国在企业尺度的研究甚少,主要集中在行业、生态园区、城市及区域等大尺度的生态效率评价。(4)国外开始将生态效率同全球生态问题(全球变暖、生物多样性、食物安全)等结合起来;而我国生态效率研究侧重于污染物分析。(5)由于社会维度定量分析难度较大,目前绝大部分研究都很少涉及。最后,文章提出:我国应加大生态效率的宣传与推广,推动生态效率在微观(企业)以及宏观(全球生态问题)上的研究和应用;借助经济、管理、会计等学科的理论和方法完善生态效率核算方法体系;综合利用全排列多边形图示法,反映社会-经济-自然复合生态系统的各个方面。     

国外旅游生态效率优化与管理

旅游生态效率概念采用定量化方法对旅游业经济、环境影响进行分析,成为旅游业可持续发展评价的重要工具。基于可持续理论的旅游生态效率优化管理方案不断涌现,相关利益主体应用较多的有环境管理系统、旅游生态标签、清洁生产理念、旅游生态效率中心、21世纪地方议程等。在旅游企业日常运营中积极推动生态效率优化管理,是贯彻绿色发展理念,提高目的地旅游经济、环境绩效的一种新思路。从可持续背景下旅游生态效率优化模型入手,系统化分析了国外旅游生态效率优化管理方案的内容与特征。其中,环境管理系统在目的地层面为旅游生态效率优化设计了一套评估管理流程,旅游生态标签为目的地生态效率水平提供了可视化标志符号,21世纪地方议程为旅游可持续发展提供一致性整合方案,清洁生产理念是一种基于生态效率优化的长期战略,旅游生态效率中心作为非营利性机构有利于中小企业获得较好的环境绩效表现。国外旅游生态效率优化管理方案特征明显、设计合理、管理科学,对我国目的地旅游生态效率优化提升具有重要的借鉴作用。     

Eco-efficiency and Its xsTerminology

Eco-efficiency has been defined as a general goal of creating value while decreasing environmental impact. Leaving out the normative part of this concept, the empirical part refers to a ratio between environmental impact and economic cost or value. Two basic choices must be made in defining practical eco-efficiency: which variable is in the denominator and which is in the numerator; and whether to specify environmental impact or improvement and value created or cost. Distinguishing between two situations, the general one of value creation and the specific one of environmental improvement efforts, and leaving the numerator-denominator choice to the user, as diverging practices have developed, four basic types of ecoefficiency result: environmental intensity and environmental productivity in the realm of value creation; and environmental improvement cost and environmental cost-effectiveness in the realm of environmental improvement measures.     

How Can the Eco‐efficiency of a Region be Measured and Monitored?

The concept of eco-efficiency is commonly referred to as a business link to sustainable development. In this article, ecoefficiency is examined at a regional level as an approach to promoting the competitiveness of economic activities in the Finnish Kymenlaakso region and mitigating their harmful impacts on the environment. The aim is to develop appropriate indicators for monitoring changes in the eco-efficiency of the region. A starting point is to produce indicators for the environmental and economic dimensions of regional development and use them for measuring regional eco-efficiency. The environmental impact indicators are based on a life-cycle assessment method, producing different types of environmental impact indicators: pressure indicators (e.g., emissions of CO₂), impact category indicators (e.g., CO₂ equivalents in the case of climate change), and a total impact indicator (aggregating different impact category indicator results into a single value). Environmental impact indicators based on direct material input, total material input, and total material requirement of the Kymenlaakso region are also assessed. The economic indicators used are the gross domestic product, the value added, and the output of the main economic sectors of Kymenlaakso. In the eco-efficiency assessment, the economic and environmental impact indicators are monitored in the same graph. In a few cases eco-efficiency ratios can also be calculated (the economic indicators are divided by the environmental indicators). Output (= value added + intermediate consumption) is used as an economic indicator related to the environmental impact indicators, which also cover the upstream processes of the region's activities. In the article, we also discuss the strengths and weaknesses of using the different environmental impact indicators.     

A Framework for Quantified Eco-efficiency Analysis

Eco-efficiency is an instrument for sustainability analysis, indicating an empirical relation in economic activities between environmental cost or value and environmental impact. This empirical relation can be matched against normative considerations as to how much environmental quality or improvement society would like to offer in exchange for economic welfare, or what the trade-off between the economy and the environment should be if society is to realize a certain level of environmental quality. Its relevance lies in the fact that relations between economy and environment are not self-evident, not at a micro level and not at the macro level resulting from micro-level decisions for society as a whole. Clarifying the why and what of eco-efficiency is a first step toward decision support on these two aspects of sustainability. With the main analytic framework established, filling in the actual economic and environmental relations requires further choices in modeling. Also, the integration of different environmental effects into a single score requires a clear definition of approach, because several partly overlapping methods exist. Some scaling problems accompany the specification of numerator and denominator, which need a solution and some standardization before eco-efficiency analysis can become more widely used. With a method established, the final decision is how to embed it in practical decision making. In getting the details of eco-efficiency better specified, its strengths, but also its weaknesses and limitations, need to be indicated more clearly.     

Operational Eco-efficiency: Comparing Firms' Environmental Investments in Different Domains of Operation

Eco-efficiency has been established as a crucial concept for corporate environmental management. Most approaches deal with eco-efficiency on the level of the company or the product. However, given that companies have special budgets earmarked for environmental operations or investments, the question arises as to which operation within which domain is the most eco-efficient. This article presents an approach to supporting these decisions by calculating eco-efficiency on the operational level. The procedure is demonstrated using a case study of the Swiss National Railway Company. Investments and operations in the domains of energy production, landscape and nature conservation, noise protection, and contaminated soil remediation are assessed and compared. Decision-makers seeking an eco-efficient corporate investment policy will find, in this concept, a guideline for prioritizing various domains of operation as well as the operations within a domain.     

The Ecological Footprint Intensity of National Economies

At least three perspectives—industrial ecology (IE), ecological modernization theory (EMT), and the “environmental Kuznets curve” (EKC)—emphasize the potential for sustainability via refinements in production systems that dramatically reduce the environmental impacts of economic development. Can improvements in efficiency counterbalance environmental impacts stemming from the scale of production? To address this question we analyze cross‐national variation in the ecological footprint (EF) per unit of gross domestic product (GDP). The EF is a widely recognized indicator of human pressure on the environment. The EF of a nation is the amount of land area that would be required to produce the resources it consumes and to absorb the wastes it generates. The most striking finding of our analyses is that there is limited variation across nations in EF per unit of GDP. This indicates limited plasticity in the levels of EF intensity or eco‐efficiency among nations, particularly among affluent nations. EF intensity is lowest (ecoefficiency is highest) in affluent nations, but the level of efficiency in these nations does not appear to be of sufficient magnitude to compensate for their large productive capacities. These results suggest that modernization and economic development will be insufficient, in themselves, to bring about the ecological sustainability of societies.     

基于物质流分析和数据包络分析的区域生态效率评价——以江苏省为例

区域生态效率(eco-efficiency)评价是考量区域可持发展的重要内容.基于物质流分析(material flow analysis, MFA)构建区域生态效率评价指标体系,并将污染物排放作为一种非期望输入引入到数据包络分析(data envelopment analysis, DEA)模型中,以江苏省(1990～2005年)为例进行生态效率分析评价.结果表明,江苏省的区域生态效率在1990～2005年期间呈现逐步上升的趋势.但是,同期的总物质投入(total material input, TMI)、物质需求总量(total material requirement, TMR)和污染物排放量也呈上升趋势.因此,江苏省社会经济发展和环境影响总体上呈现"弱脱钩(weak de-link)".     

A Practical Method for Quantifying Eco-efficiency Using Eco-design Support Tools

Eco-efficiency at the product level is defined as product value per unit of environmental impact. In this paper we present a method for quantifying the eco-efficiency using quality function deployment (QFD) and life-cycle impact assessment (LCIA). These well-known tools are widely used in the manufacturing industry.
QFD, which is one of the methods used in product development based on consumer preferences, is introduced to calculate the product value. An index of the product value is calculated as the weighted average of improvement rates of quality characteristics. The importance of customer requirements, derived from the QFD matrix, is applied.
Environmental impacts throughout a product life cycle are calculated based on an LCIA method widely used in Japan. By applying the LCIA method of endpoint type, the endpoint damage caused by various life-cycle inventories is calculated. Willingness to pay is applied to integrate it into a single index.
Eco-design support tools, namely, the life-cycle planning (LCP) tool and the life-cycle assessment (LCA) tool, have already been developed. Using these tools, data required for calculation of the eco-efficiency of products can be collected. The product value is calculated based on QFD data stored in the LCP tool and the environmental impact is calculated using the LCA tool.
Case studies of eco-efficiency are adopted and the adequacy of this method is clarified. Several advantages of this method are characterized.     

The environmental effectiveness of the beverage sector in Norway in a Factor 10 perspective

Scope and Background

The environmental effectiveness of the Norwegian beverage sector has been studied in a Factor 10 perspective. The objective of the study was to identify strategies that could make the beverage sector radically more effective from an environmental and resource perspective, leading to a Factor 10 improvement. Another main purpose of the work was to test the potential for using Life Cycle Assessment (LCA) methodology on an economic sector with a network of product chains, rather than for a single product.

Methods

Life Cycle Assessment data from STØ’s own studies and literature studies have been used as a basis for analysis of the environmental status of the beverage sector in Norway. The functional unit was defined as the amount of beverage products consumed per capita in Norway in the year 2000. The study includes raw material production, production of the beverage product, packaging manufacture, distribution, use and waste management of the products. The study has, for practical reasons, been limited to the environmental impact indicators total energy consumption and global warming potential. This was done as other types of data have been difficult to obtain for all of the products that were studied (tap water, coffee, milk, soft drinks, beer, squash, juice and bottled water).

Results and Discussion

The study shows differences between the drinking products with respect to energy consumption and emissions that can contribute to global warming. Due to large uncertainties in the data, general conclusions regarding the differentiation of products based on environmental performance should be made with care. Production and distribution of tap water is, however, significantly less energy intensive than the other products. For the impact categories studied, production of raw materials was the most important part of the life cycle for most drinking products.

Conclusions and Perspective

The most significant contributions to achieving a Factor 10 development can be made by consuming more water, especially tap water, and through improving raw material production in the agricultural sector. Packaging and distribution is responsible for only a small part of the energy consumption and emissions leading to global warming. Optimal packaging sizes might however reduce loss of products in the user phase, which is important in order to improve the system. A Factor 10 level seems achievable only if the consumption of tap water is increased to a high level.