基于改进的投影寻踪的森林生态系统生态价位分级模型

针对投影寻踪技术计算过程复杂、编程实现困难等缺陷,提出采用改进单纯形法直接优化投影寻踪技术的投影函数和投影方向,从而简化了投影寻踪技术的实现过程,克服了目前投影寻踪技术编程实现困难、搜索时间长及投影方向难以最优化等缺点.提出了基于改进单纯形法的投影寻踪技术的森林生态系统生态价位分级模型.利用该模型可把各森林生态系统多维分类指标综合成一维投影值.投影值越大表示该森林类型生态服务价值越大.根据投影值大小可对森林生态系统样本集进行合理分级.实例分级结果表明,直接由样本数据驱动的改进的投影寻踪森林生态系统生态价位分级模型用于生态价位分级,简单可行,具有较强的适用性和应用性;可操作性强,其优化时间及投影函数值分别为传统投影寻踪技术的34%和143%;投影寻踪效果很理想,可广泛应用于生态学、生物学及区域可持续发展研究中各类非线性、高维数据分级与评价.     

社会-经济-自然复合生态系统生态位评价模型——以四川省为例

在深入分析区域资源、环境、社会、经济综合系统基础上,建立了四川省2001—2010年社会-经济-自然复合生态系统生态位评价指标体系,复合生态系统综合生态位包括资源、环境、经济和社会4个子系统生态位。将耦合投影寻踪模型应用于复合生态系统生态位评价,其中,采用并行模拟退火算法对评价模型参数进行优化。研究结果表明:2001年—2010年四川省复合生态位呈现先降后升的趋势,复合生态位评价值从2001年3.1325下降到2005年的2.8499,从2005年开始,复合生态位逐渐增加,到2010年增加到3.3304。表明环境重视程度的提高,环保意识的加强,促进了复合生态位的提高,区域自然生态和环境得以改善。最佳投影方向各分量的大小反映了各评价指标对生态位评价等级的影响程度,值越大则对应的评价指标对生态位评价等级的影响程度越大。区域生态位评价等级指标的影响程度最大的10项中有4项是环境生态位子系统指标,表明环境生态位子系统对综合生态位影响最大。发展过程中经济生态位子系统和社会生态位子系统指标值相关系数为0.9957,表明两子系统基本上是保持同步发展。而经济生态位和环境生态位子系统指标值相关系数为-0.9346,呈现明显的负相关关系。资源子系统呈现上升趋势。模拟退火优化的投影寻踪耦合模型应用于复合生态位评价,具有实用性和可行性,为区域生态管理科学决策提供重要依据。     

效率视角下的省域生态文明建设评价研究

在界定生态文明概念的基础上,从省域层面入手,选取25个具有可操作性的评价指标,构建以国土空间优化、资源节约集约利用和生态环境保护为一级指标的生态文明建设评价指标体系,综合运用网络层次分析和集对分析等研究方法,定量研究我国省域生态文明建设绩效;在此基础上,将国土空间优化绩效、资源节约集约利用绩效和生态环境保护绩效作为产出指标,将就业人数、科学技术财政支出、节能环保财政支出作为投入指标,运用数据包络分析法测度各省(市)生态文明建设效率,分析指标投入冗余和产出不足情况,并修正评价绩效。研究表明:(1)规模效率低于0.6的省份共24个,占80%,规模效率不高是制约生态文明建设水平提升的重要障碍;(2)在生态文明建设投入冗余和产出不足方面,数值较高的省(市)在地理分布上具有明显的区域聚集性;(3)领先地区资源节约集约利用绩效平均分高达3.92,落后地区平均分仅为0.84,生态文明建设绩效的差异性在资源节约集约利用方面表现的尤为明显;(4)人口规模偏大、绿色生态空间建设滞后于经济发展、水资源利用效率不高是多数生态强省(市)的薄弱环节。     

生态土地分类研究进展

土地分类是土地评价、规划和管理的基础,对林业资源可持续利用具有重要的意义.生态土地分类是目前土地分类的主要方向和趋势,国际上早已开展此项研究.随着景观生态学和3S技术的发展,生态分类系统的研制已成为生态土地分类的重点.本文对生态土地分类的定义、特点、发展历史、生态分类系统理论,以及国际生态分类系统的发展趋势进行了系统的综述,并指出以资源(森林、土地、水域等)多目标管理为基础,定量与定性相结合的多因子多层次综合是未来生态土地研究发展的总趋势,有必要在我国大力开展相关研究.     

生态土地分类研究进展

土地分类是土地评价,替代和管理的基础,对林业资源可持续利用具有重要的意义。生态土地分类是目前土地分类的主要方向和趋势。国际上早已开展此项研究。随着景观生态学和3S技术的发展,生态分类系统的研制已成为生态土地分类的重点。本文对生态土地分类的定义,特点,发展历史,生态分类系统理论,以及国际生态分类系统的发展趋势进行了系统的综述,并指出以资源（森林,土地,水域等）多目标管理为基础,定量与定性相结合的多因子多层次综合是未来生态土地研究发展的总趋势,有必要在我国大力开展相关研究。     

生态创新系统功能、过程和可持续评估

不同国家生态创新水平有高低,生态创新系统有差异。生态创新系统是由一系列参与者通过相互作用形成的网络,目的是推动有助于生态环境和社会经济协调发展的知识和技术的生产、传播和应用。为比较不同国家生态创新系统的发展状况和可持续性,分析不同国家生态创新系统的优势和不足,提出生态创新系统两步评估法和整体分析框架。把生态创新系统的功能和过程结合起来,对生态创新系统的发展水平进行评价。重点关注系统的长期发展,即系统可持续性。基于资本的角度,包括知识、经济、人力和社会资本,建立生态创新系统可持续评估模型,考察相关资本存量、流量和风险因素。根据创新系统理论、文献回顾和国际研究比较,遴选出30个关键指标,构建涵盖2个指标矩阵的综合评价指标体系。采用主成分分析和综合评价方法,对不同国家生态创新系统的功能-过程和可持续性分别进行评价。研究表明,法国、德国、韩国、西班牙和挪威生态创新系统的功能-过程表现最强,韩国、德国、奥地利、挪威、捷克生态创新系统的可持续性表现最强。根据生态创新系统的现状和可持续性,主要生态创新国家可以分为四种类型,据此采用不同发展策略。如韩国系统现状水平和可持续性都较高,属于生态创新先进国。...     

浙江省沿海县域生态效率评价

基于浙江省沿海27个县域2005—2018年投入-产出面板数据,结合超效率SBM模型、投影寻踪模型对浙江沿海生态效率时空演化特征、投入-产出要素与生态效率的叠加特征进行研究,并提出优化浙江沿海县域生态效率的措施。结果表明：(1)沿海县域生态效率可划分为较平稳增长期、颠簸下降期两个阶段。(2)浙北沿海县域生态效率大于浙南沿海县域生态效率,浙北与浙南沿海县域生态效率具有不对等性与空间差异性。(3)沿海县域各等级生态效率具有相互转化的特征。高生态效率由“大聚集”向“小分散”演化;较低、低生态效率由“大分散”向“小聚集”演化,具有“弱者恒弱”的特征。(4)沿海县域资源投入与经济效益的高低变化具有同高同低的特征,环境污染状况与资源投入和经济效益具有反向性特征。(5)投入-产出要素与生态效率等级叠加类型具有多样性、复杂性,高投入、高经济效益的县域基本稳定,中投入县域近似圈层性分布于高投入外围,低投入县域主要集中于浙南沿海。     

特大型城市生态文明建设评价指标体系及应用——以武汉市为例

特大型城市是我国社会、经济、文化和人口的中心,也是我国资源环境问题最为突出的地方之一。由于特大型城市与中小城市资源环境问题存在差异,特大型城市之间生态环境问题和生态文明建设的状态也存在相似之处,建立反映特大型城市资源环境问题特征的生态文明评价指标体系,依据评价结论,指导特大型生态文明建设十分必要。以服务于特大型城市生态文明建设为目标,在对特大型城市发展状态和特大型城市资源环境问题与社会经济发展突出矛盾分析的基础上,建立了包括有生态环境健康度、资源环境消耗强度、面源污染治理效率和居民生活宜居度等4个方面,共20个指标的特大型城市生态文明评价指标体系,并以各个指标对应的国家标准、政策和规划要求,以及相关研究确立的指标发展目标为依据,对武汉市2006—2011年生态文明建设完成情况进行了评价。依据评价结果,指出武汉市要从以下方面加强生态文明建设:一要控制空气中可吸入颗粒物含量,降低大气中硫化物含量,控制污水排放规模和噪音污染,循环利用废水资源;二要实施总量和强度"双控"政策,显著降低单位GDP的能耗、废气排放量和工业固体排放量;三要提高城市生活污水和生活垃圾的治理能力,循环利用可再生的城市生活"矿产";四要提高森林覆盖率和建城区绿化率,降低人口密度,解决城市住房和交通拥挤问题。     

生态治理技术评价指标体系

为了对生态治理技术进行更加科学合理的评价,在确定了指标体系构建思路的基础上,根据评价指标的筛选原则,通过对评价指标的理论初选和专家筛选,构建了能够揭示生态治理技术本身属性、相宜性、应用效果、推广潜力等的综合评价指标体系。该指标体系包含目标层和指标层两个层次,目标层为生态治理技术适应效果,指标层分为控制性指标和分类评价指标。控制性指标包含5个一级指标和14个二级指标,适用于所有类型的生态治理技术;分类评价指标为三级指标,共有水土保持技术、荒漠化治理技术、石漠化治理技术和生态恢复技术四个类型的三级指标各29个,针对不同的生态治理技术可以选用合适的三级指标对其进行评价。这样的评价指标体系既可体现区域差异,又可建立公共评价平台,为生态治理技术的评估提供了科学依据和关键技术支撑。     

我国茶叶产业生态效率与生产效率评价研究——基于DEA 方法的实证分析

生态效率是经济与环境协调发展的有效测度, 是可持续发展的重要评价指标。基于DEA 模型的实证研究, 分析了我国18 个产茶省份2004-2013 年的生产效率与2009-2013 年的生态效率。研究结果表明: 我国茶叶产业有较高的生产效率, 但茶叶产业的生态效率较低, 存在从事茶业劳动力冗余较多, 水资源和土地资源资源消耗过大, 利用效率不高, 经济效益不佳的问题。因此强化茶业劳动人员的技术知识, 减少农村剩余劳动力, 提高资源能源的利用效率, 提升茶叶产业的经济效益是改善我国茶叶产业生态效率, 使我国茶叶产业健康可持续发展的重要途径。     

基于投入产出表的北京市产业生态效率

提高生态效率对协调经济发展与环境保护的关系至关重要。为了了解北京市产业转型过程中各产业部门生态效率的变化趋势,识别提高影响北京市产业生态效率的关键部门,基于北京市投入产出表,运用指标体系法,选取水资源效率,以及废水、二氧化硫、工业固体废弃物的环境效率作为生态效率的衡量指标,核算了北京市2007、2010和2012年各部门的水资源效率以及2005、2007和2010年各部门的环境效率,并比较分析了各部门的水资源的完全用水系数以及污染物的完全排放系数,计算各部门之间完全排放量的相互贡献比例,识别了提高生态效率的关键部门。研究结果:(1)2007—2012年,北京市各部门水资源效率和2005—2010年废水、二氧化硫(SO_2)、工业固体废弃物的环境效率整体呈波动上升趋势。(2)农林牧渔业和废品废料部门是提高水资源效率的关键部门。(3)水的生产和供应业、化学工业、食品制造及烟草加工业、纺织业和造纸印刷及文教体育用品制造业是提高废水环境效率的关键部门。(4)石油加工、炼焦及核燃料加工业、非金属矿物制品业、金属冶炼及压延加工业、电力及热力的生产和供应业是提高SO_2环境效率的关键部门。(5)煤炭开采和洗选业、金属矿采选业、木材加工及家具制造业、非金属矿物制品业、金属冶炼及压延加工业、电力及热力的生产和供应业、水的生产和供应业是提高工业固体废弃物环境效率的关键部门。     

基于LMDI分解的厦门市碳排放强度影响因素分析

研究碳排放强度的变化趋势及其影响因素对于指导低碳城市建设具有重要意义。应用对数平均权重分解法(LMDI),基于厦门市2005—2010年各部门终端消费数据对碳排放强度指标进行因素分解,并将传统分析仅注重产业部门的能源碳排放,拓展到全面考虑产业部门和家庭消费的能源活动和非能源活动影响。研究结果表明:2005—2010年厦门市碳排放强度下降17.29%,其中产业部门能源强度对总碳排放强度变化影响最大(贡献63.07%),家庭消费能源强度是碳排放强度下降的主要抑制因素(-45.46%)。从影响效应角度看,经济效率对碳排放强度下降贡献最大,碳排系数减排贡献最小;从部门减排贡献角度看,第二产业贡献最大,家庭消费贡献最小。总体而言,厦门市未来碳减排重点部门在第二产业,优化产业结构和能源结构有较大减排潜力。     

福建省行业碳排放驱动因素分解及其与经济增长脱钩关系

主要部门和重点行业的二氧化碳排放是区域碳排放的主要来源。厘清行业碳排放影响因素,分析其与区域经济增长相互关系及程度,从而推动部门和行业碳减排对于落实区域碳排放总量控制具有重要意义。本研究运用对数平均迪式指数分解法(LMDI)和Tapio脱钩模型对福建省1997—2017年13个主要碳排放行业进行碳排放驱动因素分解和脱钩分析。结果表明: 电力、热力的生产和供应业是福建省主要的碳排放行业,1997—2017年,其碳排放总量由18.89 Mt上升到120.63 Mt,增长量为101.74 Mt。有色金属冶炼及压延加工业、纺织业、黑色金属冶炼及压延加工业的碳排放增长速度最快,其年均增长率分别为18.1%、12.1%、12.1%。13个主要行业碳排放变动的驱动因素中,经济增长效应和人口规模效应是主要的正向驱动因素,能源结构效应、能源强度效应和产业结构效应的抑制作用在不断增强。从脱钩关系来看,13个主要碳排放行业的脱钩指数整体呈下降趋势。从“十一五”时期开始,部分行业开始出现不同程度的强脱钩。而在“十三五”时期,农、林、牧、渔、水利业表现为扩张负脱钩,电力、热力的生产和供应业表现为弱负脱钩。能源结构效应和能源强度效应对各行业实现脱钩的影响较大,产业结构效应的脱钩努力较小,人口规模效应未做出脱钩努力。     

The forest resources input–output model: An application in China

Understanding the state of forest resource utilization in China and correctly evaluating the role and function of forest resources in national economic development are essential for realizing balanced development of forests, the environment, and the economy. This is especially true given the present situation of increasingly scarce forest resources. Using data from Chinese forest industry statistical yearbooks, forestry development reports, and other documents, this paper examines the current state of forest resource utilization in China from the angle of combining quantities and values based on input–output tables. We show that demand for and input use of forest resources varies greatly across industrial sectors; the paper products and furniture manufacturing industries have the greatest direct consumption coefficient for timber use. When considering direct and indirect demand, it is clear that forest resources restrict different industrial sectors in diverse ways. These results provide an important set of reference values regarding the utilization of forest resources and coordinated industrial development in China.     

基于数据包络分析方法的辽宁省工业节能减碳效率

以辽宁省2003—2012年39个行业作为独立的决策单元,综合考虑经济、能源和环境效益,结合方向距离函数和径向数据包络分析(DEA)方法对各工业行业节能减碳效率进行测算和分解,核算了各工业行业的CO₂排放,并将CO₂作为一种非期望产出引入到节能减碳效率模型中.结果表明: 研究期间,辽宁省工业行业节能减碳效率具有明显的行业异质性;辽宁省工业节能减碳效率总体不高,但呈现上升趋势;提高纯技术效率和规模效率是提高工业节能减碳效率的主要措施,尤其是提高规模效率.为了提高辽宁省各行业节能减碳效率,辽宁省应加快调整产业结构,鼓励发展低碳排放高效益的产业;提高科技水平,合理调整产业规模;优化能源结构,推进可再生能源和清洁能源的开发.     

Towards a Circular Economy in Australian Agri‐food Industry: An Application of Input‐Output Oriented Approaches for Analyzing Resource Efficiency and Competitiveness Potential

The food industry in Australia (agriculture and manufacturing) plays a fundamental role in contributing to socioeconomic sectors nationally. However, alongside the benefits, the industry also produces environmental burdens associated with the production of food. Sectorally, agriculture is the largest consumer of water. Additionally, land degradation, greenhouse gas emissions, energy consumption, and waste generation are considered the main environmental impacts caused by the industry. The research project aims to evaluate the eco‐efficiency performance of various subsectors in the Australian agri‐food systems through the use of input‐output–oriented approaches of data envelopment analysis and material flow analysis. This helps in establishing environmental and economic indicators for the industry. The results have shown inefficiencies during the life cycle of food production in Australia. Following the principles of industrial ecology, the study recommends the implementation of sustainable processes to increase efficiency, diminish undesirable outputs, and decrease the use of nonrenewable inputs within the production cycle. Broadly, the research outcomes are useful to inform decision makers about the advantages of moving from a traditional linear system to a circular production system, where a sustainable and efficient circular economy could be created in the Australian food industry.     

Economy‐wide Material Flow Indicators on a Sectoral Level and Strategies for Decreasing Material Inputs of Sectors

The article presents a method for the calculation of selected economy‐wide material flow indicators (namely, direct material input [DMI] and raw material input [RMI]) for economic sectors. Whereas sectoral DMI was calculated using direct data from statistics, we applied a concept of total flows and a hybrid input‐output life cycle assessment method to calculate sectoral RMI. We calculated the indicators for the Czech Republic for 2000–2011. We argue that DMI of economic sectors can be used for policies aiming at decreasing the direct input of extracted raw materials, and imported raw materials and products, whereas sectoral RMI can be better used for justifying support for or weakening the role of individual sectors within the economy. High‐input material flows are associated in the Czech Republic with the extractive industries (agriculture and forestry, the mining of fossil fuels [FFs], other types of mining, and quarrying), with several manufacturing industries (manufacturing of beverages, basic metals, motor vehicles or electricity, and gas and steam supply) and with construction. Viable options for reducing inputs of agricultural biomass include changes in people's diet toward a lower amount of animal‐based food and a decrease in the wasting of food. For FFs, one should think of changing the structure of total primary energy supply toward cleaner gaseous and renewable energy sources, innovations in transportation systems, and improvements in overall energy efficiency. For metal ores, viable options include technological changes leading to smaller and lighter products, as well as consistent recycling and use of secondary metals.     

Energy simulation and LCA for macro-scale analysis of eco-innovations in the housing stock

Purpose

Energy consumption of buildings is one of the major drivers of environmental impacts. Life cycle assessment (LCA) may support the assessment of burdens and benefits associated to eco-innovations aiming at reducing these environmental impacts. Energy efficiency policies however typically focus on the meso- or macro-scale, while interventions are typically taken at the micro-scale. This paper presents an approach that bridges this gap by using the results of energy simulations and LCA studies at the building level to estimate the effect of micro-scale eco-innovations on the macro-scale, i.e. the housing stock in Europe.

Methods

LCA and dynamic energy simulations are integrated to accurately assess the life cycle environmental burdens and benefits of eco-innovation measures at the building level. This allows quantitatively assessing the effectiveness of these measures to lower the energy use and environmental impact of buildings. The analysis at this micro-scale focuses on 24 representative residential buildings within the EU. For the upscaling to the EU housing stock, a hybrid approach is used. The results of the micro-scale analysis are upscaled to the EU housing stock scale by adopting the eco-innovation measures to (part of) the EU building stock (bottom–up approach) and extrapolating the relative impact reduction obtained for the reference buildings to the baseline stock model. The reference buildings in the baseline stock model have been developed by European Commission-Joint Research Centre based on a statistical analysis (top–down approach) of the European housing stock. The method is used to evaluate five scenarios covering various aspects: building components (building envelope insulation), technical installations (renewable energy), user behaviour (night setback of the setpoint temperature), and a combined scenario.

Results and discussion

Results show that the proposed combination of bottom–up and top–down approaches allow accurately assessing the impact of eco-innovation measures at the macro-scale. The results indicate that a combination of policy measures is necessary to lower the environmental impacts of the building stock to a significative extent.

Conclusions

Interventions addressing energy efficiency at building level may lead to the need of a trade-off between resource efficiency and environmental impacts. LCA integrated with dynamic energy simulation may help unveiling the potential improvements and burdens associated to eco-innovations.

     

On the suitability of input–output analysis for calculating product-specific biodiversity footprints

Recently it has been estimated that one third of biodiversity threats are driven by consumer demand from outside the country in which the threat occurs. This occurs when the production of export goods exerts pressure on vulnerable populations. While population biologists have in cases been able to establish links between species threats and the causative industry(s), little has been done to trace this biodiversity footprint from the directly implicated industry out to final consumers, a step that would open a wider variety of policy responses. Here we investigate the suitability of multi-region input–output (MRIO) analysis for tracing out links between particular species threats, directly implicated industries, and the countries and consumer goods sectors ultimately driving these industries. Environmentally extended MRIO models are understood to provide reliable results at a macroeconomic level but uncertainty increases as the models are used to investigate individual sectors, companies, and products. In this study we examine several case studies (nickel mining in New Caledonia, coltan from the Democratic Republic of Congo, cut flowers from Kenya, and forestry in Papua New Guinea) in order to understand how and when MRIO techniques can be useful for studying biodiversity implicated supply chains. The study was conducted using the Eora global input–output database that documents >5 billion global supply chains. Calculating the biodiversity footprint at this level of detail, between specific threats, supply chains, and consumer goods, has not been done before. These case studies provide interesting insights in their own right and also serve to highlight the strengths and weaknesses of using input–output analysis techniques to calculate detailed biodiversity footprints. We conclude that MRIO analysis, while no panacea, can be useful for outlining supply chains and identifying which consumption sectors and trade and transformation steps can be subjected to closer analysis in order to enable remedial action.