Life cycle assessment of industrial symbiosis: A critical review of relevant reference scenarios

This paper highlights the methods and parameters used to define and design a reference scenario to be compared with an industrial symbiosis (IS) scenario using the life cycle assessment (LCA) methodology. To this end, a critical review was conducted of 26 peer‐reviewed papers using LCA in the field of IS. The analysis focuses on the definition and design of reference scenarios through five cross‐analyses to determine correlations between the type and the number of reference scenarios and the type of IS scenarios studied and also some LCA characteristics such as the functional unit, the type of data used, and the use of sensitivity analysis. Results show that the definition of reference scenarios depends mainly on the type of IS scenario considered. For a current IS developed at an industrial scale, the suitable reference scenario is mainly a hypothetical nonsymbiotic reference scenario. For a prospective IS, the suitable reference scenario is mainly a current nonsymbiotic reference scenario. Due to this critical review, the problem of variability of reference scenarios emerges. To resolve it, the authors analyze different reference scenarios or use sensitivity analysis. What is more, territorial aspects are rarely taken into account in the design of reference scenarios. It is clearly a gap for LCA of IS because of the influence of territorial factors. The new research challenge is to include the consideration of territorial aspects to define and design the worst‐ and best‐case reference scenarios to assess strict environmental performances of IS.     

A Stochastic Approach to Model Dynamic Systems in Life Cycle Assessment

This article presents a framework to evaluate emerging systems in life cycle assessment (LCA). Current LCA methods are effective for established systems; however, lack of data often inhibits robust analysis of future products or processes that may benefit the most from life cycle information. In many cases the life cycle inventory (LCI) of a system can change depending on its development pathway. Modeling emerging systems allows insights into probable trends and a greater understanding of the effect of future scenarios on LCA results. The proposed framework uses Bayesian probabilities to model technology adoption. The method presents a unique approach to modeling system evolution and can be used independently or within the context of an agent‐based model (ABM). LCA can be made more robust and dynamic by using this framework to couple scenario modeling with life cycle data, analyzing the effect of decision‐making patterns over time. Potential uses include examining the changing urban metabolism of growing cities, understanding the development of renewable energy technologies, identifying transformations in material flows over space and time, and forecasting industrial networks for developing products. A switchgrass‐to‐energy case demonstrates the approach.     

Scenario Modelling in Prospective LCA of Transport Systems. Application of Formative Scenario Analysis (11 pp)

Background Tools and methods able to cope with uncertainties are essential for improving the credibility of Life Cycle Assessment (LCA) as a decision support tool. Previous approaches have focussed predominately upon data quality. Objective and Scope. An epistemological approach is presented conceptualising uncertainties in a comparative, prospective, attributional LCA. This is achieved by considering a set of cornerstone scenarios representing future developments of an entire Life Cycle Inventory (LCI) product system. We illustrate the method using a comparison of future transport systems. Method Scenario modelling is organized by means of Formative Scenario Analysis (FSA), which provides a set of possible and consistent scenarios of those unit processes of an LCI product system which are time dependent and of environmental importance. Scenarios are combinations of levels of socio-economic or technological impact variables. Two core elements of FSA are applied in LCI scenario modelling. So-called impact matrix analysis is applied to determine the relationship between unit process specific socio-economic variables and technology variables. Consistency Analysis is employed to integrate unit process scenarios, based on pair-wise ratings of the consistency of the levels of socio-economic impact variables of all unit processes. Two software applications are employed which are available from the authors. Results and Discussion The study reveals that each possible level or development of a technology variable is best conceived of as the impact of a specific socio-economic (sub-) scenario. This allows for linking possible future technology options within the socio-economic context of the future development of various background processes. In an illustrative case study, the climate change scores and nitrogen dioxide scores per seat kilometre for six technology options of regional rail transport are compared. Similar scores are calculated for a future bus alternative and an average Swiss car. The scenarios are deliberately chosen to maximise diversity. That is, they represent the entire range of future possible developments. Reference data and the unit process structure are taken from the Swiss LCA database 'ecoinvent 2000'. The results reveal that rail transport remains the best option for future regional transport in Switzerland. In all four assessed scenarios, four technology options of future rail transport perform considerably better than regional bus transport and car transport. Conclusions and Recommendations. The case study demonstrates the general feasibility of the developed approach for attributional prospective LCA. It allows for a focussed and in-depth analysis of the future development of each single unit process, while still accounting for the requirements of the final scenario integration. Due to its high transparency, the procedure supports the validation of LCI results. Furthermore, it is well-suited for incorporation into participatory methods so as to increase their credibility. Outlook and Future Work. Thus far, the proposed approach is only applied on a vehicle level not taking into account alterations in demand and use of different transport modes. Future projects will enhance the approach by tackling uncertainties in technology assessment of future transport systems. For instance, environmental interventions involving future maglev technology will be assessed so as to account for induced traffic generated by the introduction of a new transport system.     

Integrating life cycle cost analysis and LCA

The private sector decision making situations which LCA addresses mustalso eventually take theeconomic consequences of alternative products or product designs into account. However, neither the internal nor external economic aspects of the decisions are within the scope of developed LCA methodology, nor are they properly addressed by existing LCA tools. This traditional separation of life cycle environmental assessment from economic analysis has limited the influence and relevance of LCA for decision-making, and left uncharacterized the important relationships and trade-offs between the economic and life cycle environmental performance of alternative product design decision scenarios. Still standard methods of LCA can and have been tightly, logically, and practically integrated with standard methods for cost accounting, life cycle cost analysis, and scenario-based economic risk modeling. The result is an ability to take both economic and environmental performance — and their tradeoff relationships — into account in product/process design decision making.     

中国西南地区土地覆盖情景的时空模拟

气候植被类型的空间分布与土地覆盖类型的空间分布在时空层次上具有很好的相关性和一致性。在运用HLZ生态系统模型获得CMIP5的3种气候情景RCP26、RCP45、RCP85情景下西南地区未来90a(2011—2100年)HLZ生态系统时空分布情景数据的基础上,结合2010年土地覆盖现状数据,构建了土地覆盖情景的空间分析模型,并在此基础上,实现了西南地区未来90a土地覆盖情景的时空模拟分析。模拟结果表明:3种气候情景下,西南地区未来90a的落叶针叶林、落叶阔叶林、草地、耕地、冰雪、荒漠及裸岩石砾地等土地覆盖类型面积将呈逐渐减少趋势;常绿针叶林、常绿阔叶林、混交林、灌丛、湿地、建设用地、水体等土地覆盖类型面积则呈逐渐增加趋势。其中,湿地增加速度最快(平均每10a增加5.28%),荒漠及裸岩石砾地减少速度最快(平均每10a减少2.34%)。     

The fate of European breeding birds under climate,land‐use and dispersal scenarios

Many species have already shifted their distributions in response to recent climate change. Here, we aimed at predicting the future breeding distributions of European birds under climate, land‐use, and dispersal scenarios. We predicted current and future distributions of 409 species within an ensemble forecast framework using seven species distribution models (SDMs), five climate scenarios and three emission and land‐use scenarios. We then compared results from SDMs using climate‐only variables, habitat‐only variables or both climate and habitat variables. In order to account for a species’ dispersal abilities, we used natal dispersal estimates and developed a probabilistic method that produced a dispersal scenario intermediate between the null and full dispersal scenarios generally considered in such studies. We then compared results from all scenarios in terms of future predicted range changes, range shifts, and variations in species richness. Modeling accuracy was better with climate‐only variables than with habitat‐only variables, and better with both climate and habitat variables. Habitat models predicted smaller range shifts and smaller variations in range size and species richness than climate models. Using both climate and habitat variables, it was predicted that the range of 71% of the species would decrease by 2050, with a 335 km median shift. Predicted variations in species richness showed large decreases in the southern regions of Europe, as well as increases, mainly in Scandinavia and northern Russia. The partial dispersal scenario was significantly different from the full dispersal scenario for 25% of the species, resulting in the local reduction of the future predicted species richness of up to 10%. We concluded that the breeding range of most European birds will decrease in spite of dispersal abilities close to a full dispersal hypothesis, and that given the contrasted predictions obtained when modeling climate change only and land‐use change only, both scenarios must be taken into consideration.     

森林-农业景观格局变化的社会-生态系统模拟模型方法进展

社会-生态系统（SES）模拟模型是景观格局分析和决策的有效工具,能表征景观格局变化的社会-生态效应及景观决策的复杂反馈机制。文献综述了森林-农业景观格局的SES模型方法进展发现：（1）多数模型对景观过程与社会经济决策的反馈关系分析不足;（2）应集成多种情景模拟和景观效应分析方法,完善现有SES模型的理论方法基础;（3）通过集成格局优化模型和自主体模型会有效改进SES模型功能,具体途径包括：集成情景-生态效应的景观格局模拟方法、完善景观决策的理论基础、加强集成模型的不确定性分析、降低模型复杂性和综合定性-定量数据等。研究结果有助于理解多尺度森林-农业景观格局在社会-生态系统中的重要作用,能更好地支持跨学科集成模型开发与应用。     

Scenario-Based Economic Risk Assessment of Paddy Damage Caused by Floods in the Huai River Sub-Basin of China

ABSTRACT

A new method, namely, the scenario-based method, is developed and further applied in assessing economic risk of paddy damage caused by floods in the Huai River sub-basin of China following these four steps: (1) generation of scenarios, (2) simulation of scenarios, (3) consequence of scenarios, and (4) comprehension of scenarios. In the first step, a rainfall Intensity-Duration-Frequency (IDF) model is established to generate a set of storm scenarios in the sub-basin by selecting seven return periods. In the second step, the flooding simulation for each scenario is carried out based on the distributed Rainfall-Runoff-Inundation (RRI) model to obtain inundation depth (meter) and time (day) over the sub-basin. In the third step, a grid-based Flood Economic Loss Estimation (FELE) model of paddies is employed to estimate economic losses of paddies in Chinese Yuan (CNY), where inundation depth and duration are treated as parameters for each scenario. In the last step, the Conditioned Expected Losses (CELs) in CNY for each county is derived as a measurement of risk by fitting the risk curve with scenario samples. Based on CELs, an economic risk zoning map of paddy damage caused by floods in the Huai River sub-basin was created as a final result.     

Incorporating the impacts of climate change into infrastructure life cycle assessments: A case study of pavement service life performance

Climate change is expected to impact both the operational and structural performance of infrastructures such as roads, bridges, and buildings. However, most past life cycle assessment (LCA) studies do not consider how the operational/structural performance of infrastructure will be affected by a changing climate. The goal of this research was to develop a framework for integrating climate change impacts into LCA of infrastructure systems. To illustrate this framework, a flexible pavement case study was considered where life‐cycle environmental impacts were compared across a climate change scenario and several time horizons. The Mechanistic‐Empirical Pavement Design Guide (MEPDG) was utilized to capture the structural performance of each pavement performance scenario and performance distresses were used as inputs into a pavement LCA model that considered construction and maintenance/rehabilitation materials and activities, change in relative surface albedo, and impacts due to traffic. The results from the case study suggest that climate change will likely call for adaptive design requirements in the latter half of this century but in the near‐to‐mid term, the international roughness index (IRI) and total rutting degradation profile was very close to the historical climate run. While the inclusion of mechanistic performance models with climate change data as input introduces new uncertainties to infrastructure‐based LCA, sensitivity analyses runs were performed to better understand a comprehensive range of result outcomes. Through further infrastructure cases the framework could be streamlined to better suit specific infrastructures where only the infrastructure components with the greatest sensitivity to climate change are explicitly modeled using mechanistic‐empirical modeling routines.     

Exploitation scenarios in industrial system LCA

Purpose

This paper considers the variabilities that exist in the exploitation of a complex industrial system. Our scenario-based LCA model ensures the reliability of results in situations where the system life cycle is very uncertain, where there is substantial lack of data, and/or where time and resources available are limited. It is also an effective tool to generate exploitation recommendations for clients.

Methods

Existing quantitative uncertainty methods in LCA require a huge amount of accurate data. These data are rarely available in simplified and upstream LCA for complex industrial systems. A scenario-based approach is the best compromise between acceptable quality of results and resources required. However, such methods have not yet been proposed to improve the environmental knowledge of the system in the case of exploitation scenarios. The method proposed here considers a limited number of scenarios (three or four) that are defined using the Stanford Research Institute matrix. Using results from past projects, relevant parts of the system are listed, and expert knowledge and parameters are associated with these parts and quantified. A classical LCA process then provides the results for the different scenarios.

Results and discussion

The method was applied to an Alstom Grid AC/DC conversion substation for the primary aluminum industry. A previous study had limited scope, as the life cycle was poorly understood. Relevant parts were, thus, clearly identified as follows: spare parts program, transport failures, preventive and corrective maintenance, updates and revampings, lifetime modulation, and end-of-life. Four scenarios were considered as follows: best case, worst case, baseline (expected future), and a highly different alternative. Results show the pertinence of considering several exploitation scenarios when the life cycle is not predictable, as the environmental impacts may vary widely from one case to another. A sensitivity analysis also shows that some relevant parts such as updates and revampings will need to be carefully considered in futures studies.

Conclusions

The consideration of three exploitation scenarios (best case, baseline, and worst case) appears to be extremely pertinent when considering simplified LCA of industrial systems with high uncertainties and limited time and resources. This model is also very useful to generate good practice and recommendations towards clients, thus initiating a dialog centered on eco-design and continuous improvement.     

基于生命周期方法的生活垃圾资源化利用系统生态效率分析

我国生活垃圾产量大但处理能力不足,产生多种环境危害,对其资源化利用能够缓解环境压力并回收资源。为探讨生活垃圾资源化利用策略,综合生命周期评价与生命周期成本分析方法,建立生态效率模型。以天津市为例,分析和比较焚烧发电、卫生填埋-填埋气发电、与堆肥+卫生填埋3种典型生活垃圾资源化利用情景的生态效率。结果表明,堆肥+卫生填埋情景具有潜在最优生态效率;全球变暖对总环境影响贡献最大,而投资成本对经济影响贡献最大。考虑天津市生活垃圾管理现状,建议鼓励发展生活垃圾干湿组分分离及厨余垃圾堆肥的资源化利用策略。     

Modeling process and material alternatives in life cycle assessments

Background, Aims and Scope  Although LCA is frequently used in product comparison, many practitioners are interested in identifying and assessing improvements within a life cycle. Thus, the goals of this work are to provide guidelines for scenario formulation for process and material alternatives within a life cycle inventory and to evaluate the usefulness of decision tree and matrix computational structures in the assessment of material and process alternatives. We assume that if the analysis goal is to guide the selection among alternatives towards reduced life cycle environmental impacts, then the analysis should estimate the inventory results in a manner that: (1) reveals the optimal set of processes with respect to minimization of each impact of interest, and (2) minimizes and organizes computational and data collection needs. Methods  A sample industrial system is used to reveal the complexities of scenario formulation for process and material alternatives in an LCI. The system includes 4 processes, each executable in 2 different ways, as well as 1 process able to use 2 different materials interchangeably. We formulate and evaluate scenarios for this system using three different methods and find advantages and disadvantages with each. First, the single branch decision tree method stays true to the typical construction of decision trees such that each branch of the tree represents a single scenario. Next, the process flow decision tree method strays from the typical construction of decision trees by following the process flow of the product system, such that multiple branches are needed to represent a single scenario. In the final method, disaggregating the demand vector, each scenario is represented by separate vectors which are combined into a matrix to allow the simultaneous solution of the inventory problem for all scenarios. Results  For both decision tree and matrix methods, scenario formulation, data collection, and scenario analysis are facilitated in two ways. First, process alternatives that cannot actually be chosen should be modeled as sub-inventories (or as a complete LCI within an LCI). Second, material alternatives (e.g., a choice between structural materials) must be maintained within the analysis to avoid the creation of artificial multi-functional processes. Further, in the same manner that decision trees can be used to estimate ‘expected value’ (the sum of the probability of each scenario multiplied by its ‘value’), we find that expected inventory and impact results can be defined for both decision tree and matrix methods. Discussion  For scenario formulation, naming scenarios in a way that differentiate them from other scenarios is complex and important in the continuing development of LCI data for use in databases or LCA software. In the formulation and assessment of scenarios, decision tree methods offer some level of visual appeal and the potential for using commercially available software/ traditional decision tree solution constructs for estimating expected values (for relatively small or highly aggregated product systems). However, solving decision tree systems requires the use of sequential process scaling which is difficult to formalize with mathematical notation. In contrast, preparation of a demand matrix does not require use of the sequential method to solve the inventory problem but requires careful scenario tracking efforts. Conclusions  Here, we recognize that improvements can be made within a product system. This recognition supports the greater use of LCA in supply chain formation and product research, development, and design. We further conclude that although both decision tree and matrix methods are formulated herein to reveal optimal life cycle scenarios, the use of demand matrices is preferred in the preparation of a formal mathematical construct. Further, for both methods, data collection and assessment are facilitated by the use of sub-inventories (or as a complete LCI within an LCI) for process alternatives and the full consideration of material alternatives to avoid the creation of artificial multi-functional processes. Recommendations and Perspectives  The methods described here are used in the assessment of forest management alternatives and are being further developed to form national commodity models considering technology alternatives, national production mixes and imports, and point-to-point transportation models. ESS-Submission Editor: Thomas Gloria, PhD (t.gloria@fivewinds.com)     

基于能值及系统动力学的中新天津生态城可持续发展模式情景分析

可持续发展动态评价是确保我国第一个国际合作建设的中新天津生态城项目成功的关键基础之一.在对中新天津生态城自然经济状况、功能结构和规划建设指标体系等分析基础上,将能值分析和系统动力学方法相结合,基于功能流视角将生态城系统划分为能物流、货币流及人口流子系统,构建了中新天津生态城可持续发展的能值评价指标体系及系统动力学模型,设计了惯性情景、科技情景、经济情景、环保情景及协调发展情景等5种生态城发展情景,并对各情景下的可持续发展状况进行了仿真和动态评价分析.结果表明：在经济与环境协调发展情景下,中新天津生态城的GDP、能值积累量、货币积累量均呈稳步增长趋势,能值废弃率、废弃物能值比、环境负载率等较小,能值可持续指标(ESI)和生态效率指数(UEI)均处于较低水平,但比其他几种方案更具活力,是中新天津生态城的最佳发展模式.     

A proposal for accounting for biodiversity in life cycle assessment

Life cycle assessment (LCA) is a methodology for assessing the environmental impacts associated with products throughout their lifecycle. Many impacts are accounted for within the LCA framework, but to date biodiversity impacts have received little attention. There are a number of existing direct and indirect measures of biodiversity within the ecological field, some of which have the potential to be developed into a useable method for LCA. However, our assessment is that considerable development would be required and their implementation for LCA is not likely in the foreseeable future. Here an alternative approach is proposed for rapidly incorporating biodiversity impacts into LCA. The approach relies on expert opinions through a series of questions which aim to encapsulate the main issues relating to biodiversity within a disturbance impact framework. While the technique is in its infancy we outline a foundation for the approach and identify the steps required to develop this method for implementation into LCA.     

Inferring functional linkages between proteins from evolutionary scenarios

Identifying potential protein interactions is of great importance in understanding the topologies of cellular networks, which is much needed and valued in current systematic biological studies. The development of our computational methods to predict protein-protein interactions have been spurred on by the massive sequencing efforts of the genomic revolution. Among these methods is phylogenetic profiling, which assumes that proteins under similar evolutionary pressures with similar phylogenetic profiles might be functionally related. Here, we introduce a method for inferring functional linkages between proteins from their evolutionary scenarios. The term evolutionary scenario refers to a series of events that occurred in speciation over time, which can be reconstructed given a phylogenetic profile and a species tree. Common evolutionary pressures on two proteins can then be inferred by comparing their evolutionary scenarios, which is a direct indication of their functional linkage. This scenario method has proven to have better performance compared with the classical phylogenetic profile method, when applied to the same test set. In addition, predicted results of the two methods are found to be fairly different, suggesting the possibility of merging them in order to achieve a better performance. We analyzed the influence of the topology of the phylogenetic tree on the performance of this method, and found it to be robust to perturbations in the topology of the tree. However, if a completely random tree is incorporated, performance will decline significantly. The evolutionary scenario method was used for inferring functional linkages in 67 species, and 40,006 linkages were predicted. We examine our prediction for budding yeast and find that almost all predicted linkages are supported by further evidence.     

LCA impact assessment categories

A technical framework is presented to evaluate the strengths and the limitations of LCA impact assessment categories to yield accurate, useful results. The framework integrates the inherent characteristics of life-cycle inventory (LCI) data sets, characteristics of individual impact categories, how impact categories are defined, and the models used to characterize different categories. The sources for uncertainty in impact assessment are derived from the basic LCI procedures and the complexity of environmental processes and mechanisms. The noteworthy LCI procedures are: (1) the collection and aggregation of data across a comprehensive product system, (2) co-product and recycling allocation for releases and resources, and (3) the conversion of these data by functional unit calculations. These operations largely remove spatial and temporal considerations, resulting in analytical and interpretive limitations that vary in magnitude for different impact assessment categories. The framework shows two groups of categories where LCA results may be insufficient for making comparisons: (1) categories that involve local and/or transient processes and (2) categories that involve non-mass loading, biological parameters, such as biodiversity, habitat alteration, and toxicity. The framework also shows that how impact categories are defined complicates their use. Some categories are based on objective stressor-effect networks using known environmental mechanisms. In contrast, other categories are defined using various levels of subjective judgment to address either highly complex or unknown mechanisms. Finally, the framework shows that differences in the quality and detail of information provided by various models used during characterization also influence the accuracy and usefulness of the results. In summary, the framework indicates that (1) the various uncertainties in each individual category have a a number of different technical origins and that (2) the degree of uncertainty varies significantly between categories. As a result, interpretation and valuation cannot presume an equivalency of processes or merit behind numerical values for different categories. The framework can be used to initially identify and track these uncertainties to improve LCA impact assessment interpretation and application.     

Combining industrial ecology tools to assess potential greenhouse gas reductions of a circular economy: Method development and application to Switzerland

Industrial ecology (IE) methodologies, such as input/output or material flow analysis and life cycle assessment (LCA), are often used for the environmental evaluation of circular economy strategies. Up to now, an approach that utilizes these methods in a systematic, integrated framework for a holistic assessment of a geographic region's sustainable circular economy potential has been lacking. The approach developed in this study (IE4CE approach) combines IE methodologies to determine the environmental impact mitigation potential of circular economy strategies for a defined geographic region. The approach foresees five steps. First, input/output analysis helps identify sectors with high environmental impacts. Second, a refined analysis is conducted using material flow and LCA. In step 3, circular strategies are used for scenario design and evaluated in step 4. In step 5, the assessment results are compiled and compared across sectors. The approach was applied to a case study of Switzerland, analyzing 8 sectors and more than 30 scenarios in depth. Carbon capture and storage (CCS) from waste incineration, biogas and cement production, food waste prevention in households, hospitality and production, and the increased recycling of plastics had the highest mitigation potential. Most of the scenarios do not influence each other. One exception is the CCS scenarios: waste avoidance scenarios decrease the reduction potential of CCS. A combination of scenarios from different sectors, including their impact on the CCS scenario potential, led to an environmental impact mitigation potential of 11.9 Mt CO₂-eq for 2050, which equals 14% of Switzerland's current consumption-based impacts.     

Combining Multiregional Input‐Output Analysis with a World Trade Model for Evaluating Scenarios for Sustainable Use of Global Resources,Part I: Conceptual Framework

Consumption in a particular country often entails resource extraction, production, and environmental degradation in remote locations. This fact has stimulated a growing body of empirical analysis using input‐output (I‐O) databases and techniques to reveal and quantify the underlying linkages. Two lines of research rooted in I‐O economics, multiregional input‐output (MRIO) analysis and I‐O modeling of the world economy, describe and analyze these relationships, the first for the past, increasingly in the form of footprints and the underlying pathways, and the latter under alternative scenarios about possible courses of action in the future. The article shows how organizing such scenario outcomes into an MRIO database can extend the reach of MRIO analysis to the future while simultaneously supplementing the capabilities of the world trade modeling framework. We describe the compilation of an MRIO database from the results of scenario analysis using the world trade model (WTM) in a companion article (Part II, Implementation); the subsequent application of MRIO techniques to this database permits the evaluation of prospects for the future. We also address several overlooked challenges, namely, the need to include factor endowments and distances between potential trade partners in an MRIO database, the representation of sectors providing transport of internationally traded goods, and the manipulation of mixed physical and money units when both quantities and prices are endogenous.