足迹家族:概念、类型、理论框架与整合模式

足迹研究是当前生态经济学和可持续发展领域的热点与前沿课题。探讨了足迹类指标的内涵,将其定义为一类评估人类资源消费和废弃物排放等活动环境影响的指标;介绍了生态足迹、碳足迹、水足迹、能源足迹、化学足迹、氮足迹和生物多样性足迹7类典型足迹指标的概念与研究进展;在此基础上提出了普适性的足迹家族概念,总结了足迹家族的选择性、开放性、系统性和不确定性特征,并根据足迹类指标的一般运算流程构建了足迹家族的理论框架;基于大量文献成果系统比较了生态足迹、碳足迹和水足迹3类关键足迹的特征差异,提出了在足迹家族层面增强指标兼容性的措施;通过逐一测试各关键足迹与27项环境问题的相关程度,从决策相关性的角度初步探索了该足迹家族的整合模式;展望了未来足迹(家族)研究的重点方向。     

基于投入产出的中国省际农业水-土-碳足迹流动分析

水-土-碳多要素耦合研究是近年来资源环境领域的热点之一。开展农业水-土-碳足迹流动分析有助于揭示农业生产和贸易带来的跨区域环境影响,对不同区域资源可持续管理和协同减排具有重要意义。以中国30个省级行政区为研究对象,基于投入产出方法科学识别不同省区农业水、土、碳足迹的空间格局、流动特征及关联状况。主要结论如下：（1）省域尺度农业水、土、碳足迹具有较大的空间差异,这归因于自然条件、社会经济、产业结构、耕作方式及种植结构等的区域差异;（2）农业水、土、碳足迹流动主要从西部和北部流向东部和东南部地区,这与农产品市场供需关系密切相关,表明东部和东南部地区农产品消费导致了西部和北部地区资源的虚拟占用和隐含碳排放;（3）农业水、土、碳足迹及其强度之间存在一定程度的关联关系,经济发展状况、地区产业结构、自然条件状况等因素均会影响某一要素或几种要素的消耗强度,进而影响其关联作用;农业水、土、碳足迹流动表现出明显的关联性特征,空间关联网络存在不均衡性,关联渠道有待丰富;（4）建议未来加强农业技术革新,提高机械化、智能化生产水平;通过土地规模化经营实现水土资源的节约集约利用;开展基于水-土-碳跨区域影响的横向农业生态补偿,实现中国省际协同减排和资源优化。     

环境足迹的核算与整合框架——基于生命周期评价的视角

环境足迹及其与生命周期评价(LCA)的关系是工业生态学关注的新热点。从探讨环境足迹与LCA的关系入手,以碳足迹、水足迹、土地足迹和材料足迹为例,分别对每一项足迹指标两个版本的核算方法进行了比较。根据清单加和过程的特点,将所有足迹指标划分为基于权重因子和基于特征因子两类,总结了两者的适用性和局限性。在此基础上提出了一个环境足迹核算与整合的统一框架。该框架基于LCA视角建立,但对系统边界和清单数据的要求相对灵活,因而也适用于生命周期不甚明确的情形。研究在一定程度上揭示了足迹指标的方法学实质,同时也为环境影响综合评估提供了一条规范化的途径。     

足迹家族研究综述

综合测度人类社会的可持续发展状态是生态经济学者追求的重要目标。足迹家族由生态足迹、碳足迹和水足迹等一系列足迹类指标整合而成,旨在为决策者系统评估与权衡人类活动的环境影响提供理论和技术支持。从理论探索、整合实践和分类比较等三方面对足迹家族的研究现状进行了综述;在此基础上围绕极具争议的足迹定义、计算方法和加权方式等问题,深入分析了阻碍当前研究进一步推进的关键性因素;指出未来应从建立足迹类型学、完善跨区域投入产出模型、细化产品和机构环境足迹标准等方面入手,推动实现足迹家族的量化整合;并首次提出了足迹家族与行星边界耦合的构想,以期为监测和预警人类活动的生态阈值、促进环境影响评价向可持续性评价转变提供科学依据。     

基于碳足迹的传统农业系统环境影响评价——以青田稻鱼共生系统为例

现代农业在带来粮食高产的同时也产生许多生态环境问题,这促使人们再次把目光转向传统农业系统。一些传统农业系统不仅具有突出的经济、社会和文化价值,还具有多种重要的生态功能,如温室气体减排。然而,已有研究缺乏对传统农业系统整个生命周期的固碳减排能力的测算及其环境影响的评价。为此,基于农户调研数据,运用生命周期评价法对青田稻鱼共生系统的碳足迹进行了测算,并与当地水稻单作系统进行比较。研究发现:(1)青田稻鱼共生系统和水稻单作系统碳足迹分别为6266.7 kgCO_2-eq/hm~2和7520.0 kgCO_2-eq/hm~2,单位产值碳足迹分别为0.12 kgCO_2-eq/元和0.21 kgCO_2-eq/元。与水稻单作系统相比,稻鱼共生系统排放的温室气体更少,环境影响更小,生态和经济效益更高。(2)农业生产过程中积累的CH_4是碳足迹的最主要来源,农业生产资料投入中的化肥是碳足迹的的第二大来源。农业生产资料投入中的饲料则是稻鱼共生系统碳足迹的另一重要来源。通过碳足迹的方法对青田稻鱼共生系统的环境影响进行量化,不仅丰富了碳足迹在实际应用中的适用类型,对于其他传统农业系统的环境影响评价也具有借鉴意义。     

Water,land and carbon footprints of sheep and chicken meat produced in Tunisia under different farming systems

Meat production puts larger demands on water and land and results in larger greenhouse gas emissions than alternative forms of food. This study uses footprint indicators, the water, land and carbon footprint, to assess natural resources use and greenhouse gas emissions for sheep and chicken meat produced in Tunisia in different farming systems in the period 1996–2005. Tunisia is a water-scarce country with large areas of pasture for sheep production. Poultry production is relatively large and based on imported feed. The farming systems considered are: the industrial system for chicken, and the agro-pastoral system using cereal crop-residues, the agro-pastoral system using barley and the pastoral system using barley for sheep. Chicken meat has a smaller water footprint (6030 litre/kg), land footprint (9 m²/kg) and carbon footprint (3 CO₂-eq/kg) than sheep meat (with an average water footprint of 18900 litre/kg, land footprint of 57 m²/kg, and carbon footprint of 28 CO₂-eq/kg). For sheep meat, the agro-pastoral system using cereal crop-residues is the production system with smallest water and land footprints, but the highest carbon footprint. The pastoral system using barley has larger water and land footprints than the agro-pastoral system using barley, but comparable carbon footprint.     

典型移民城市食物氮足迹估算分析——以深圳市为例

城市食物源氮消费产生的环境排放是全国氮污染的重要源头,城市食物氮足迹评估可反映维持城市人口基本食物需求的活性氮排放以及对周边环境的潜在影响。以典型移民城市深圳市为例,基于改进N-Calculator模型的基础上,估算了2010-2015年间因城市人口流动导致的城市食物氮足迹变化,并分析其时空异质性及其与城市化间的关系。结果表明：深圳市不同类型城市居民食物氮足迹不一致,其中常住户籍居民人均食物氮足迹从14.63 kg N a^-1增加至15.17 kg N a^-1,高于非户籍居民食物氮足迹13.09 kg N a^-1,其主要体现在瓜果、肉类、水产品等食物消费上。总体上,深圳城市食物氮足迹呈增长趋势,5年增幅11.50%,增幅最大为常住户籍居民食物氮足迹,但目前深圳非户籍居民的食物消费主导着城市食物氮足迹。深圳城市内部区域食物氮足迹呈高度空间异质性与聚集性,各区域增长量差异明显,街道尺度城市食物氮足迹增长热点主要分布在城市的西部沿海区域,部分热点区域单位增长量数量级比肩区级尺度单位的增长量,城市区域食物氮足迹与人口城市化的关联性不明显,但与经济城市化存在一定的关联性。当前城市移民落户趋势及居民高氮饮食倾向不利于城市氮足迹的削减,减少食物生产上游活性氮流失为深圳市贯彻粤港澳大湾区协同可持续发展的关键。     

污染足迹及其在区域水污染压力评估中的应用——以太湖流域上游湖州市为例

传统生态足迹理论虽然在可持续发展评价等方面得到了广泛的应用,但却仍然无法全面衡量人类活动对生态系统造成的各种影响。其无法全面评估人类活动的根源在于,土地功能排他性假设限制了其对利用生态系统非生物生产性产品和服务的人类活动的衡量。为了摆脱传统生态足迹理论的局限性,建议承认土地功能多样性的客观事实,将生态足迹构建于多种生态系统服务功能之上。针对传统生态足迹对定义中废弃物吸纳的考虑不足,提出了基于污染物吸纳功能的生态足迹,即污染足迹。污染足迹不是对传统生态足迹中能源足迹的简单置换,而是能够囊括人类活动产生的大部分污染物,并可以根据不同的污染物类别或类型进一步细化的足迹类型。构建了太湖流域有机物、氮和磷污染足迹模型,并利用该模型对流域上游湖州市的水污染压力进行了综合评估。结果表明:(1)2007年湖州市污染足迹为39948.73 hm²,东部平原地区污染足迹较大,西部丘陵地区污染足迹相对较小;(2)湖州市人类活动排放的氮磷污染物对水域空间的生态占用已经远远超过了有机污染物;(3)2007年湖州市污染承载力为20896.00 hm²,污染赤字为19052.73 hm²,人类排污活动俨然超出了当地水域的承载能力;(4)2007年湖州市污染压力指数为1.91,当地水环境总体上处于轻度接近中度污染压力;(5)湖州市水污染压力较大的地区,区域内人类活动的维持建立在区域水环境质量恶化或污染物向下游输移的基础之上。     

土地流转背景下不同经营规模青田稻鱼共生系统的环境影响差异——基于碳足迹的实证研究

在快速工业化和城镇化的影响下,农业文化遗产的保护与管理正面临着适龄劳动力大量外流、土地抛荒、传统知识体系难以维持等诸多威胁与挑战。推动土地流转、进行适度规模经营,可在农业文化遗产的保护中产生积极作用。土地流转在给遗产地带来经济效益的同时,对当地生态环境产生的影响变化同样值得关注,但现有研究却少有涉及。本研究以全球重要农业文化遗产——浙江青田稻鱼共生系统为例,将不同经营规模的稻鱼共生系统分为小农户经营模式和规模化经营模式,运用生命周期法对两种模式的碳足迹进行核算。结果表明: 小农户经营模式和规模化经营模式的碳足迹分别为6510.80和5917.00 kg CO₂-eq·hm^-2,单位产值碳足迹分别为0.13和0.10 kg CO₂-eq·yuan^-1。与小农户经营模式相比,规模化经营模式温室气体排放更少,单位产值的环境影响更小。农户扩大经营规模后,当地温室气体排放减少了4097.20 kg CO₂-eq。农业生产过程中积累的CH₄在碳足迹中占比最大,农业生产资料中复合肥是仅次于CH₄的第二大温室气体排放来源。对于小农户经营模式,饲料中使用的玉米和小麦也对温室气体排放有重要的影响。因此,推动土地适度规模经营,有利于传统农业系统实现经济效益和环境效益的双赢,对于农业文化遗产保护具有重要作用。     

生态足迹理论方法的改进及应用

针对生态足迹理论关于耕地一年只耕种一次的假设,对生态足迹方法中的耕地类足迹用复种指数进行调整,使计算得到的耕地类足迹是人们所需要的耕地面积而不是复种面积.用改进的方法,对江苏省滨海县和阜宁县两个区域生态经济系统1995—2003年的情况进行了分析.结果表明:在1995—2003年,采用Wackernagel方法,滨海和阜宁的人均生态足迹分别由1.79hm2、1.38hm2增加为2.22hm2、2.81hm2,生态足迹中耕地足迹的比重分别由42.65%、45.73%下降为38.81%、38.85%;采用改进后的方法,滨海和阜宁的人均生态足迹则分别由1.43hm2、1.12hm2增加为1.88hm2、2.43hm2,生态足迹中耕地足迹的比重分别由28.45%、32.94%下降为22.89%、29.42%.表明采用改进后的方法所计算得到的生态足迹为土地面积,增强了生态足迹与生态承载力的可比性;使得生态足迹的大小及构成发生变化,更能准确表征人类对自然资源的利用程度.     

基于GTWR模型的浙江省海岸带三维生态足迹动态变化及其影响因素

厘清海岸带自然资本存量消耗和自然资本流量占用情况及其影响因素,能有效缓解海岸带社会经济发展与自然资源、生态环境之间的矛盾,促进区域协调可持续发展。本研究基于二维和三维生态足迹评价模型,分析浙江省海岸带2006—2016年生态足迹时空变化特征,基于足迹深度和足迹广度探究了区域自然资本存量和资本流量占用情况,并利用时空地理加权模型分析其影响因素的时空异质性。结果表明: 研究期间,浙江省海岸带生态危机加深,人均生态赤字平均值为3.5 hm²·cap^-1,人均生态赤字上升了15.5%,其中,能源消耗账户对人均生态足迹的贡献率大于生物资源账户;各县区人均生态足迹呈增长趋势,且空间分异显著。浙江省海岸带以消耗自然资本存量为主,且对自然资本流量更新起到较大的抑制作用;2016年,自然资本存量的消耗量是资本流量占有量的14.87倍。城市规模和经济发展水平、人民收入水平对浙江省海岸带各县区生态足迹以正向促进作用为主,渔业生产对生态足迹为负向影响,并有向正向影响作用转换的趋势,3个影响因子的影响机制时空分异性显著。     

Sensitivity of the carbon footprint of New Zealand milk to greenhouse gas metrics

Milk production is responsible for emitting a range of greenhouse gases (GHGs), mainly carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄). In Life Cycle Assessments (LCA), the Global Warming Potential with a time horizon of 100 years (GWP100) is used almost universally to aggregate emissions of individual gases into so-called CO₂-equivalent emissions that are used to calculate the overall carbon footprint of milk production. However, there is growing awareness that, depending on the purpose of the LCA, metrics other than GWP100 could be justified and some would give a very different weighting for the short-lived gas CH₄ relative to the long-lived gases CO₂ and N₂O when calculating the carbon footprint. Pastoral dairy production systems at different levels of intensification differ in the balance of short- and long-lived GHGs associated with on- and off-farm emissions. Differences in the carbon footprint of different production systems could therefore be highly sensitive to the choice of GHG metric. Here we explore the extent to which alternative GHG metric choices would alter the carbon footprint of New Zealand milk production at different levels of intensification at national, regional and individual farm scales and compared to the carbon footprint of milk of selected European countries. We find that the ranking of different production systems and individual farms in terms of their carbon footprint is relatively robust against the choice of GHG metric, despite significant differences in their utilisation of pastures versus supplementary off-farm feed, fertiliser use and energy consumption at various stages of farm operations. However, there are instances where alternative GHG metric choices would fundamentally change the conclusions of LCA of different production systems, including whether a move towards higher or lower input systems would increase or decrease the average carbon footprint of milk production in New Zealand. Greater transparency about the implications of alternative GHG metrics for LCA, and the often inadvertent and implicit value judgements embedded in these metrics, would help ensure that policy decisions and consumer choices based on LCA indeed deliver the climate outcomes intended by end-users.     

Theoretical exploration for the combination of the ecological,energy, carbon,and water footprints: Overview of a footprint family

Over the past two decades, a continuously expanding list of footprint-style indicators has been introduced to the scientific community with the aim of raising public awareness of how humanity exerts pressures on the environment. A deeper understanding of the connections and interactions between different footprints is required in an attempt to support policy makers in the measurement and choice of environmental impact mitigation strategies. Combining a selection of footprints that address different aspects of environmental issues into an integrated system is, therefore, a natural step. This paper starts with the idea of developing a footprint family from which most important footprints can be compared and integrated. On the basis of literature review in related fields, the ecological, energy, carbon, and water footprints are employed as selected indicators to define a footprint family. A brief survey is presented to provide background information on each of the footprints with an emphasis on their main characteristics in a comparative sense; that is, the footprints differ in many aspects more than just the impacts they are addressed. This allows the four footprints to be complementarily used in assessing environmental impacts associated with natural resource use and waste discharge. We evaluate the performance of the footprint family in terms of data availability, coverage complementarity, methodological consistency, and policy relevance and propose solutions and suggestions for further improvement. The key conclusions are that the footprint family, which captures a broad spectrum of sustainability issues, is able to offer a more complete picture of environmental complexity for policy makers and, in particular, in national-level studies. The research provides new insights into the distinction between environmental impact assessment and sustainability evaluation, properly serving as a reference for multidisciplinary efforts in estimating planetary boundaries for global sustainability.     

LIFE BEEF CARBON: a common framework for quantifying grass and corn based beef farms’ carbon footprints

Europe’s roadmap to a low-carbon economy aims to cut greenhouse gas (GHG) emissions 80% below 1990 levels by 2050. Beef production is an important source of GHG emissions and is expected to increase as the world population grows. LIFE BEEF CARBON is a voluntary European initiative that aims to reduce GHG emissions per unit of beef (carbon footprint) by 15% over a 10-year period on 2172 farms in four large beef-producing countries. Changes in farms beef carbon footprint are normally estimated via simulation modelling, but the methods current models apply differ. Thus, our initial goal was to develop a common modelling framework to estimate beef farms carbon footprint. The framework was developed for a diverse set of Western Europe farms located in Ireland, Spain, Italy and France. Whole farm and life cycle assessment (LCA) models were selected to quantify emissions for the different production contexts and harmonized. Carbon Audit was chosen for Ireland, Bovid-CO₂ for Spain and CAP’2ER for France and Italy. All models were tested using 20 case study farms, that is, 5 per country and quantified GHG emissions associated with on-farm live weight gain. The comparison showed the ranking of beef systems gross carbon footprint was consistent across the three models. Suckler to weaning or store systems generally had the highest carbon footprint followed by suckler to beef systems and fattening beef systems. When applied to the same farm, Carbon Audit’s footprint estimates were slightly lower than CAP’2ER, but marginally higher than Bovid-CO₂. These differences occurred because the models were adapted to a specific region’s production circumstances, which meant their emission factors for key sources; that is, methane from enteric fermentation and GHG emissions from concentrates were less accurate when used outside their target region. Thus, for the common modelling framework, region-specific LCA models were chosen to estimate beef carbon footprints instead of a single generic model. Additionally, the Carbon Audit and Bovid-CO₂ models were updated to include carbon removal by soil and other environmental metrics included in CAP’2ER, for example, acidification. This allows all models to assess the effect carbon mitigation strategies have on other potential pollutants. Several options were identified to reduce beef farms carbon footprint, for example, improving genetic merit. These options were assessed for beef systems, and a mitigation plan was created by each nation. The cumulative mitigation effect of the LIFE BEEF CARBON plan was estimated to exceed the projects reduction target (−15%).     

减氮施肥对春玉米-晚稻生产系统碳足迹的影响

随着对气候变化和粮食安全的的日益认识,低碳农业引起了人们的广泛关注.低碳农业的研究需要综合考虑作物产量和温室气体排放,改进氮肥管理可能有助于减缓作物生产系统的温室气体排放,同时实现对作物稳产甚至高产的需求.本试验利用生命周期法研究了不同施氮量(150、225、300 kg N·hm^-2)对春玉米-晚稻轮作系统碳足迹的影响.结果表明: 随着氮肥用量增加,两季作物生产过程中温室气体和碳足迹增加.在春玉米生产过程中,氮肥生产和施用引起的温室气体排放对碳足迹贡献最大,占36.2%～50.2%;而在晚稻生产中,甲烷的排放贡献最大,占42.8%～48.0%,并且随氮肥用量增加甲烷排放增加.当氮肥施用量减少25%(225 kg N·hm^-2)和50%(150 kg N·hm^-2)时,春玉米生产的温室气体排放分别下降了21.9%和44.3%,碳足迹分别下降了20.3%和39.1%;晚稻生产的温室气体排放分别下降了12.3%和20.4%,碳足迹分别降低了13.7%和16.7%.氮肥减量对春玉米产量无显著影响,而晚稻产量在225 kg N·hm^-2施肥量下最高.因此,春玉米氮肥用量降低至150 kg N·hm^-2和晚稻氮肥用量降低至225 kg N·hm^-2不仅能够保持作物高产,而且还能大幅度降低作物系统的碳足迹.     

中国省际碳足迹广度、深度评价及时空格局

借鉴三维生态足迹方法构建了碳足迹广度、深度测算模型,对吸纳碳排放所占用的自然资本流量、存量进行区分,核算了2000—2016年中国30个省(市、自治区)碳足迹广度和碳足迹深度,并对其进行空间关联性分析。结果显示:①中国碳足迹广度受碳足迹和碳生态承载力的综合影响,由0.173 hm~2/人升至0.329 hm~2/人又降至0.301 hm~2/人;碳足迹广度高值区集中于东北、西北和西南地区,其自然资本流量尚未完全占用,低值区集中于东部沿海和中部,其自然资本流量已不足以补偿碳排放。②2008年起中国碳足迹深度突破自然原长1,数值由1.04升至1.42又降至1.31;研究期内碳足迹深度始终处于自然原长1的有10个地区,高值区集中于东部沿海和中部,尤其是上海可达298.83,以存量资本耗竭为主且生态持续性弱。吸纳碳排放所占用的流量资本和存量资本存在地域互补性。③中国碳足迹广度、深度呈显著的空间正相关。碳足迹广度H-H集聚区分布于东北和西北,该类集聚有减弱趋势;碳足迹深度H-H集聚区主要分布于东部沿海且向中部扩散,该类集聚有增强趋势。通过引入碳足迹广度、深度两项指标对碳足迹的研究方法进行了深化和完善,在碳排放对生态环境影响规模的刻画和表达上取得了较优于传统碳足迹的评价结果。     

长江中游城市群水-碳-生态足迹变化特征及其平衡性分析

长江中游城市群是长江经济带三大跨区域城市群支撑之一,实现该区域高效协同发展对于打造全国重要增长极具有重要意义。基于水-碳-生态足迹评估长江中游城市群资源环境压力,引入基尼系数分析城市群水-碳-生态足迹与经济、人口、水资源的平衡性,并构建深度神经网络模型预测水-碳-生态足迹的未来变化趋势。结果表明：长江中游城市群2000—2015年的人均生态足迹由1.98hm~2增至4.06hm~2,人均碳足迹由0.27hm~2增至0.56hm~2,年平均增幅分别为6.56%和6.5%;人均水资源生态足迹整体呈先下降后上升,最后趋于平衡的变化趋势;大部分城市的水资源超载指数为正值,总体水资源状况良好,湖南和江西水资源状况优于湖北。长江中游城市群面临巨大资源环境压力,且大部分来自于碳排放压力。研究期内,江西省资源环境压力由中上等级升至较高等级;湖南省资源环境压力基本处于高等级;湖北省资源环境压力均处于很高等级。城市群人口分布、经济发展、水资源分布与水-碳-生态足迹的匹配关系较差。从生态足迹角度来看,综合基尼系数均值为0.456,处于“一般不匹配”范围,研究期内呈现缓慢下降趋势,表明区域间整体协调性增强;从...     

The Nexus of Carbon,Nitrogen, and Biodiversity Impacts from Urban Metabolism

Methodology is developed for linking the urban metabolism (UM) to global environmental stresses on the carbon (C) cycle, nitrogen (N) cycle, and biodiversity loss. UM variables are systematically mapped to the drivers of carbon, nitrogen, and biodiversity impacts. Change in mean species abundance is used as metric of biodiversity loss, by adopting the dose‐response relationships from the GLOBIO model. The main biodiversity drivers related to UM included here are land‐use change (LUC) and atmospheric N deposition. The methodology is demonstrated by studying the nexus for Shanghai in 2006, based on energy and soybean consumption. Results for Shanghai show a strong nexus between C, N, and biodiversity impact due to electricity consumption and energy used in manufacturing industries and construction. Prioritization of the shift away from coal energy will therefore lead to lowering the urban growth impact on all three dimensions. Road transportation, domestic aviation, and the metal industry impact only the C footprint highly, whereas district energy impacts only biodiversity loss highly, showing a weak nexus. Among the global impacts of soybean consumption in Shanghai on biodiversity loss (due to LUC only), the highest impact occurs in Uruguay (0.52%) followed by Brazil (0.05%) and Argentina (0.02%). The local impact on biodiversity loss (i.e., within China) of soybean consumption in Shanghai is 1.03%. However, the methodology and results are limited due to the partial inclusion of drivers, a carbon footprint based on carbon dioxide emissions only, and limitations of biodiversity loss models. Potential to overcome methodological limitations is discussed.     

A methodology for separating uncertainty and variability in the life cycle greenhouse gas emissions of coal-fueled power generation in the USA

Purpose

Results of life cycle assessments (LCAs) of power generation technologies are increasingly reported in terms of typical values and possible ranges. Extents of these ranges result from both variability and uncertainty. Uncertainty may be reduced via additional research. However, variability is a characteristic of supply chains as they exist; as such, it cannot be reduced without modifying existing systems. The goal of this study is to separately quantify uncertainty and variability in LCA.

Methods

In this paper, we present a novel method for differentiating uncertainty from variability in life cycle assessments of coal-fueled power generation, with a specific focus on greenhouse gas emissions. Individual coal supply chains were analyzed for 364 US coal power plants. Uncertainty in CO₂ and CH₄ emissions throughout these supply chains was quantified via Monte Carlo simulation. The method may be used to identify key factors that drive the range of life cycle emissions as well as the limits of precision of an LCA.

Results and discussion

Using this method, we statistically characterized the carbon footprint of coal power in the USA in 2009. Our method reveals that the average carbon footprint of coal power (100 year time horizon) ranges from 0.97 to 1.69 kg CO₂eq/kWh of generated electricity (95 % confidence interval), primarily due to variability in plant efficiency. Uncertainty in the carbon footprints of individual plants spans a factor of 1.04 for the least uncertain plant footprint to a factor of 1.2 for the most uncertain plant footprint (95 % uncertainty intervals). The uncertainty in the total carbon footprint of all US coal power plants spans a factor of 1.05.

Conclusions

We have developed and successfully implemented a framework for separating uncertainty and variability in the carbon footprint of coal-fired power plants. Reduction of uncertainty will not substantially reduce the range of predicted emissions. The range can only be reduced via substantial changes to the US coal power infrastructure. The finding that variability is larger than uncertainty can obviously not be generalized to other product systems and impact categories. Our framework can, however, be used to assess the relative influence of uncertainty and variability for a whole range of product systems and environmental impacts.     

水足迹研究进展

水为生命之源,水资源的合理分配与科学管理是区域可持续发展与流域综合管理的核心环节;水足迹作为一种全面核算人类活动对水资源真实占用的综合指标,将人类消费终端与水资源利用密切关联,为维护流域水资源安全、提高区域水资源利用效率提供了重要的科学依据,已成为当前国际水资源管理的前沿研究领域。在明确水足迹及水资源生态足迹相关概念的基础上,对比分析了水足迹与生态足迹、水资源生态足迹模型的异同,明晰了过程、产品及区域等不同研究对象的水足迹核算方法,系统梳理了产品和区域水足迹评价、基于水足迹的区域水资源安全研究、区域水足迹可持续性分析等水足迹主要研究内容的近今进展,并展望了进一步的重点研究方向,即水足迹综合研究、水足迹评价不确定性分析、水足迹与物质流核算的关联研究,以及基于足迹整合的可持续发展多维测度等。