线虫区系分析指示土壤食物网结构和功能研究进展

土壤食物网结构复杂,功能众多,直接测定土壤食物网各功能群生物量并结合数学模型来推断土壤食物网结构和功能,工作量大且分析过程繁琐。线虫生态学的发展为土壤食物网的研究开辟了一条新的思路,即利用线虫区系分析来定性推断食物网的结构和功能。线虫作为土壤中数量最丰富的后生动物,占据着土壤食物网的中心位置,其物种多样性、食性多样性、生活史策略多样性、功能团多样性奠定了其作为土壤食物网结构和功能指示生物的生态学基础。线虫区系分析根据发展历史可以分为个体分类、生活史策略分类、功能团分类和代谢足迹分类四个时期,其中后两个时期主要用于推断土壤食物网结构和功能。基于功能团的线虫区系分析将线虫的食性和生活史策略结合起来,发展出一系列指数来判断土壤食物网的连通性、食物网链长度、外界养分投入情况、分解途径及对外界干扰的响应等。基于代谢足迹的线虫区系分析在功能团分析基础上,加入线虫能流分析,从而定性反映了土壤食物网功能的大小。两者在指示土壤食物网自下而上调节及对植物线虫控制等方面起着重要的作用。     

A Carbon Footprint of High‐Speed Railways in China: A Case Study of the Beijing‐Shanghai Line

A carbon footprint (CF) assessment of Chinese high‐speed railways (HSRs) can help guide further development of the world's longest HSR network. In this research, a hybrid economic input‐output and life cycle assessment (EIO‐LCA) method was applied to estimate the CF of the Beijing‐Shanghai HSR line. Specific CFs were analyzed of different subsystems of the line, different stages of production, and three calculation scopes. Results showed that the annual CF of the Beijing‐Shanghai HSR is increasing, whereas the per‐passenger CF constantly declined between 2011 and 2014. Scope 1 emissions account for an average of 4% of the total annual CF, Scope 2 contribute 71%, and Scope 3 comprise 25%. Among the different stages, operation contributes the largest (71%), followed by construction (20%) and maintenance (9%). In the construction stage, the bridges have the largest CF, followed by trains, and then rails. A trade‐off exists between the increase in carbon emissions due to construction of bridges and the reduction in operation emissions affected by leveling changes in terrain. The Beijing‐Shanghai HSR line has a relatively higher per‐passenger CF than eight other HSR lines, which is largely due to China's coal‐based carbon‐intensive energy mix of electricity generation, high proportion of bridges, higher operating speed, and heavier train body. In the future, cleaner electricity supply options, more efficient raw material production, and improvement of trains are keys to reducing the CF of Chinese HSRs.     

基于水足迹的山东省农业水土资源匹配特征及短缺压力分析

高强度农业开发引起的农业水土资源生态问题日益增多,探究粮食及蔬菜（粮蔬）生产中水土资源空间配置及短缺压力对农业资源的可持续利用具有重要意义。从水足迹视角出发,分析了山东省3种主要粮食作物（冬小麦、玉米及大豆）和两种不同种植模式蔬菜（设施蔬菜和露地蔬菜）的生产水足迹空间特征;同时将资源数量及资源质量的概念纳入研究框架,分析了农业水土资源数量及质量匹配格局差异,并进一步探究了农业水土资源短缺压力及其影响因素。研究结果表明：（1）2019年,山东省粮食和蔬菜的生产总水足迹为811亿m³,其中粮食生产总水足迹占比78.50%,蔬菜生产总水足迹占比21.50%;粮蔬生产水足迹受地势影响明显,鲁西北及鲁西南平原地区的粮蔬生产水足迹占比较大。（2）考虑资源数量的水土资源匹配系数均值为0.622×10⁴ m³/hm²,考虑资源质量的匹配系数均值为0.416×10⁴ m³/hm²;水土资源数量及质量匹配系数在空间上呈现出一致性,表明山东省农业生产水土资源空间配置水平高的地区同时面临着较大的农业面源污染压力。（3）整体上,土地资源短缺压力略高于水资源短缺压力;基于生产视角的水土资源短缺压力受生产环境因素制约显著,受经济发展因素的影响具有差异性,社会因素对水土资源短缺压力无显著影响。研究可为农业资源可持续管理提供数据基础,为全面理解粮蔬生产所产生的水土资源短缺提供案例参考。     

Implications of corn prices on water footprints of bioethanol

Previously reported water footprints (WFPs) of corn ethanol have been estimated based on the assumption that corn ethanol feedstock could be supplied by the same states where the corn is grown. However, ethanol conversion facilities may choose out-of-state feedstock suppliers depending on the total price of feedstock they have to pay including both the corn price and transportation costs. The purpose of this study is to evaluate the WFPs and total water use (TWU) of corn ethanol considering an optimal allocation of corn with heterogeneous corn feedstock prices across states. The results show that the WFPs of corn ethanol are less than 100 l of water per liter of ethanol (Lw/Le) for all ethanol-producing states based on both the 2008 corn price and transportation costs for rail and truck. Results also reveal that WFPs are very sensitive to the market price of corn and that additional greenhouse gas emissions due to corn trade between states are not significant.     

陕北农田作物生产碳源/汇及碳足迹空间特征

农作物生产过程既是碳源,也是碳汇。研究作物生产过程中碳吸收、碳排放特征对区域农业碳减排具有重要意义。以陕北区域为例,采用高分辨率遥感数据,结合GEE遥感云平台和随机森林算法,获取了作物种植分布信息,并建立碳吸收排放测算模型,分析了陕北地区2021年农田作物的碳源/汇效应、碳足迹及其空间分布格局。结果表明:①陕北种植的粮食作物主要为玉米、稻谷、薯类、豆类,经济作物主要为蔬菜、苹果、枣树,这七类作物集中分布在延安南部河谷区域和榆林西北部区域。②除枣类外,陕北地区其余作物的碳吸收量均高于碳排放量,以碳汇功能为主,其中,玉米和苹果分别对该地区碳吸收、碳排放的贡献率最高,碳吸收、排放量分别达到了189.74×10⁴ t和11.41×10⁴ t,苹果、薯类和枣类碳足迹较高,分别达到了9.92×10⁴ hm²、8.77×10⁴ hm²和21.65×10⁴ hm²,其余作物碳足迹处于0.26-1.49×10⁴ hm²之间。③从空间上看,研究区单位面积农田碳吸收量呈现西北高、南部低的分布格局,而碳排放量、碳足迹分布正好相反,南部高、西北低。④研究区可通过培育高产品种、优化施肥量、控制农膜农药用量、调整作物种植结构等措施,提高作物固碳效应,促进农业生产碳减排。     

Supply versus use designs of environmental extensions in input–output analysis: Conceptual and empirical implications for the case of energy

Input–output analysis is one of the central methodological pillars of industrial ecology. However, the literature that discusses different structures of environmental extensions (EEs), that is, the scope of physical flows and their attribution to sectors in the monetary input–output table (MIOT), remains fragmented. This article investigates the conceptual and empirical implications of applying two different but frequently used designs of EEs, using the case of energy accounting, where one represents energy supply while the other energy use in the economy. We derive both extensions from an official energy supply–use dataset and apply them to the same single‐region input–output (SRIO) model of Austria, thereby isolating the effect that stems from the decision for the extension design. We also crosscheck the SRIO results with energy footprints from the global multi‐regional input–output (GMRIO) dataset EXIOBASE. Our results show that the ranking of footprints of final demand categories (e.g., household and export) is sensitive to the extension design and that product‐level results can vary by several orders of magnitude. The GMRIO‐based comparison further reveals that for a few countries the supply‐extension result can be twice the size of the use‐extension footprint (e.g., Australia and Norway). We propose a graph approach to provide a generalized framework to disclosing the design of EEs. We discuss the conceptual differences between the two extension designs by applying analogies to hybrid life‐cycle assessment and conclude that our findings are relevant for monitoring of energy efficiency and emission reduction targets and corporate footprint accounting.     

Environmental Load from Dutch Private Consumption: How Much Damage Takes Place Abroad?

This article describes a method for determining the environmental load of Dutch private consumption. The method generates detailed information about consumption-related environmental impacts. The environmental load of households (direct) and production (indirect) was determined for 360 expenditure categories reported in the Dutch Expenditure Survey. The indirect environmental load was calculated with linked input-output tables covering worldwide production and trade. The environmental load per Euro turnover of industries was linked to consumer expenditures. With this method we can quantify several types of environmental load per expenditure category and per economic production region.
It was found that food production, room heating, and car use are the most important elements in the environmental load of Dutch private consumption. The impacts taking place abroad were—with the exception of emission of greenhouse gases and road traffic noise—found to be larger than domestic impacts. Most land use was found to take place in developing (non-OECD) countries, whereas most emissions occur in industrialized (OECD) countries.     

城市水资源生态足迹核算模型及应用——以沈阳市为例

水资源生态足迹可以直接反映区域人类社会经济活动对水资源的压力.本研究在现有的生态足迹模型基础上,充分考虑城市自然生态系统对水资源的需求,建立了包括居民日常生活用水、生产运营用水、公共服务用水和生态需水4类帐户的城市水资源生态足迹核算模型,并结合沈阳市实际情况,确定了模型中的相关参数,对沈阳市水资源生态足迹和生态承载力进行分析.结果表明:2000-2009年,沈阳市人均水资源生态足迹总体呈下降态势,但各年度均为水生态赤字;2005年较2000年水资源生态足迹人均下降0.31 hm2,2006、2007年有小幅回升,2008、2009年趋于平稳,说明沈阳市水资源可持续利用状况有一定改善,但仍处于不可持续状态.     

基于国家生态足迹账户计算方法的福建省生态足迹研究

运用国家生态足迹账户计算方法(2010版),计算并分析2000-2009年福建省的生态足迹和生态承载力,旨在展示国外生态足迹计算方法研究的最新进展,更准确地揭示近年来福建省的生态足迹和生态承载力状况。结果表明:2000-2009年福建省人均生态足迹由1.2902 gha^**快速增长至2.4925 gha;人均生态承载力由0.9772 gha轻微下降为0.9363 gha;生态赤字持续快速扩大,支撑经济发展由需要1.32倍的福建生态承载力变为需要2.66倍;碳吸收地在生态足迹结构中始终占据首位且呈快速扩大趋势,是福建生态赤字的主导因素;生态效率年均增长率大大低于地区生产总值年均增长率,目前福建生态效率还远低于主要发达国家。