生命周期评估为电子标准制定制定决策分析方法外文文献

A decision analysis approach to electronics standard development informed by life cycle assessment using infl uence diagrams Therese Garvey David E Meyer Michael A Gonzalez Brian Dyson John F Carriger United States Environmental Protection Agency National Risk Management Research Laboratory 26 W Martin Luther King Dr Cincinnati OH 45268 USA a r t i c l e i n f o Article history Received 12 July 2019 Received in revised form 11 December 2019 Accepted 6 January 2020 Available online 9 January 2020 Handling Editor Cecilia Maria Villas B oas de Almeida Keywords Life cycle assessment Decision analysis Infl uence diagram Product standards Sustainable electronics a b s t r a c t Life cycle assessment LCA provides holistic information on systems including the trade offs between environmental impacts and the drivers of such impacts Coupling life cycle assessment with a decision analysis DA method can help ensure that a life cycle assessment is focused on pertinent decision performance measures In this paper a framework integrating life cycle assessment with a decision analysis method to enhance the application of life cycle assessment is presented with a real world case study of developing a material inclusion criterion for sustainable electronics standards The proposed DA LCA framework is a fi ve step process that tracks the fl ow of information between the steps of de cision analysis and life cycle assessment The case study considered the level of post consumer recycled or biobased content in laptop enclosures Elicitation with a mock stakeholder panel was used to structure a means ends network and create a utility based infl uence diagram to link changes in material inclusion to environmental objectives using life cycle impact scores Unlike typical life cycle assessment the de cision analysis approach allows for explicit incorporation of non environmental factors and better constrains product options Using this approach the optimum decision for a possible range of 0e30 material content is 5 or 10 depending on weighting The DA LCA framework can provide a blueprint for placing life cycle assessment results in context for decision makers Published by Elsevier Ltd 1 Introduction Life cycle assessment LCA provides a systems based frame work that is applicable to environmental management decision making Dahlbo et al 2013 Nissinen et al 2007 by calculating a comprehensive range of environmental impacts occurring across a product s life cycle The LCA methodology is defi ned by the inter national standard ISO 14040 2006 ISO 2006 To ensure the LCA is relevant for decision making the practitioner should directly engage the decision makers and their stakeholders to capture the context constraints and economic and social issues that also shape the decision and affect the environment in which the product system lives However such contextual factors are typically not integratedwiththeactualenvironmentalassessmentand developing methods to incorporate their implications contempo raneously with environmental results could benefi t LCA The effectiveness of implementing LCA within decisions is often challenged by the fact that impact measures and results can be diffi cult to interpret by those not well versed in the process itself or in the underlying assumptions and uncertainty of the scenarios used Furthermore the connection between the values beliefs and goals of the decision makers are not readily identifi able in LCA results and the proper evaluation of values based and technical tradeoffs can be daunting These challenges highlight an opportu nity to enhance LCA through integration with decision analysis Decision analysis DA is the formal process of making choices when considering risk and uncertainty In general DA is comprised of fi ve steps 1 problem formulation 2 identifying objectives 3 identifying options 4 evaluating alternatives 5 decision making followed by implementation Decision analysis can help clarify the relevant range of measures for assessment and provide infor mation regarding how external factors contribute to outcomes uncertainties and potential scenario results Dyson 2017 Numerous other researchers have considered the integration of LCA results with DA as summarized in Table 1 primarily by Corresponding author U S Environmental Protection Agency National Risk Management Research Laboratory Land and Materials Management Division 26 West Martin Luther King Drive MS 483 Cincinnati OH 45268 USA E mail addresses garvey therese epa gov T Garvey meyer david epa gov D E Meyer gonzalez michael epa gov M A Gonzalez dyson brian epa gov B Dyson carriger john epa gov J F Carriger Contents lists available at ScienceDirect Journal of Cleaner Production journal homepage https doi org 10 1016 j jclepro 2020 120036 0959 6526 Published by Elsevier Ltd Journal of Cleaner Production 254 2020 120036 developing preference and aggregation models through multiple criteria decision analysis MCDA which may include comparing impacts with rule based procedures Thus far the use of DA tech niques for LCA has been confi ned to identifying an optimal solution or scenario after the life cycle inventory LCI development and impact assessment LCIA have been performed Full integration of LCA with DA should consider more fundamental questions for decision making from the outset such as whether or not an LCA is the appropriate assessment tool for a given decision how best to structure an LCA how to select representative impacts measures that meet stakeholder needs and how to communicate results to a non LCA audience Furthermore the methods often employed in LCA to evaluate alternatives have relied solely on expert input without recognizing that those experts may not be the actual de cision makers Dong et al 2018 recently reviewed environmental decision making for sustainability with a stated emphasis on the need for and obstacles to integrating LCA with DA However their efforts focused more on the integration of LCA with specifi c decision tools including risk assessment and cost benefi t analysis Such an anal ysis is different than the work presented here because it seeks to align LCA with other environmental tools and focuses more on understanding the differences in scope and application of the various tools instead of maximizing the benefi ts of LCA within the decision process in general Thus Dong and co workers focused on methodological challenges includingaligningdecisiongoals temporalandgeographicscopesandproperlyinterpreting comparative LCA results within a risk based context As a takeaway for future work they called for the development of methods to integrate LCA with other decision tools to improve decision making for sustainability While this is a worthwhile pursuit it doesn t address all issues related to the use of LCA results in decision making Visualization of LCA results for executives policy makers and consumers has been identifi ed as a need in the LCA community with recognition that some simplifi cation may be required in order todo so Laurin et al 2016 Different types of communication tools are possible including consequence tables decision trees and in fl uence diagrams Gregory et al 2012 To meet the need of visu alizing LCA for decision makers the present work explores the use of a probabilistic decision model expressed asan infl uence diagram Infl uence diagrams IDs are benefi cial because theycan graphically relate decision options dependencies and consequences in a probabilistic construct Howard and Matheson 2005 Pearl 2005 while providing a visualization of the problem structure and the relationship of decisions to impact trade offs Infl uence diagrams model the relationships between random variables with nodes and arcs They include utility and decision nodes to evaluate the infl u ence of specifi c decisions on the system and calculate the expected utilities of different scenarios If desired uncertainties regarding the relationship between nodes can be represented using the best available evidence which might include mathematical equations or elicited judgments from experts This is an important feature for LCA where understanding the infl uence of uncertainty in life cycle models is a key challenge for decision makers Utility functions one form of a quantitative value model are used in IDs when uncertainty is involved in alternatives and translate a performance measures scale into a utility scale normalized from 0 to 1 across the range of outcomes for the vari able The utility function can refl ect the strength of preference for different levels of a variable along with the degree of aversion to uncertainties Keeney and von Winterfeldt 2009 The utility of each of the outcomes is multiplied by the probabilities of that outcome where the probabilities are calculated by the ID to generate expected utility EU refl ecting a preference for alterna tives with a higher EU over ones with a lower EU The present method uses linear utility functions indicating no risk aversion as a baseline If risk aversion is important the utility functions can be further tailored with the risk preferences of stakeholders using decision analysis procedures such as ones described in Clemen and Reilly 2013 and Keeney and Raiffa 1976 The LCA needs highlighted here will best be resolved through development of a more immersive framework for implementing LCA within DA Support from decision makers and stakeholders as well as their ability to interpret the results is key to effective environmental decision making and the value of LCA for environ mental decision making can be enhanced by better engaging decision makers and stakeholders in the process The step wise nature progression of DA provides a complementary approach to achieve this The desired outcome of the present research is to demonstrate the proposed connections and potential for informa tion sharing between LCA and DA The objectives of the work include 1 developing a framework that merges the LCA process with objectives for decision making in an interactive and visual manner and 2 demonstrating the application of the framework using a case study of a standards development process 2 Methods The integration of LCA with DA is fl exible and can incorporate 1 more aspects of decision making not modeled in a typical LCA 2 external factors not controlled by the decision making body but infl uential on the success of decisions 3 behavioral aspects of those affected by the decision and 4 the inherent randomness and uncertainty associated with knowledge of the system A framework to this end is proposed described and demonstrated using a case study The key contribution of this framework is the use of an ID as demonstrated in the case study because such visual tools have not yet been explored in literature for LCA 2 1 DA LCA framework While ISO requires LCA practitioners to perform many of the practices laid out in DA the process of engaging stakeholders and Table 1 Examples of previous DA LCA integration DA TechniqueUse in LCA CompensatoryMulti Attribute Utility Value Theory MAUT MAVT weighting and aggregating impact scores to achieve a single score that can be directly compared across alternatives Tsang et al 2014 and Stoycheva et al 2018 Analytical Hierarchy Process AHP developing weights between alternatives and measures using pairwise comparison Pineda Henson Culaba 2004 Non CompensatoryELECTRE and PROMETHEEcomparing and eliminating nonoptimal alternatives based on perceived goodness or preference Domingues et al 2015 and Lolli et al 2016 Dominance based rough set approach DRSA classifying alternatives Cinelli et al 2015 T Garvey et al Journal of Cleaner Production 254 2020 1200362 analyzing values is often underexplored The DA LCA framework shown in Fig 1 relies on elicitation techniques to clearly defi ne the problem system and develop a probabilistic graphical model to visualize the problem structure and properly link the associated LCA In this way the proposed framework enables decision makers to interactively explore LCA models by choosing different condi tions and options to understand how potential decisions may affect the intended objectives Thus this integration can improve communication of LCA results during decision making The indi vidual steps of the framework are discussed in the subsections that follow 2 1 1 Step A establish context The fi rst step of the framework establishes the context for the decision to be made by assembling various aspects of the decision to see the bigger picture This is analogous to problem formulation in DA and begins by identifying who is making the decision the decision makers and who will be impacted the stakeholders because these entities will drive the expert elicitation process The decision makers should fi rst clearly defi ne the overarching issue being addressed As part of establishing the context the decision makers working with the stakeholders should specify any geographic information or regionalization that affects any part of the issue or system as well as external concerns such as regulation or required product attributes that constrain the decision This information can then be used to properly set the goal and scope of an LCA including how the results will be used interpreted by the decision makers and those impacted The context will also be important for understanding the acceptable level of uncertainty in the life cycle models and the appropriate impact methods to employ for the assessment 2 1 2 Step B map objectives During Step B expertelicitation is used to developthe objectives and structure them in an ends means network that maps them to the impact assessment indicators of the LCA Constructing objec tives consists of identifying the things that matter i e benefi ts and costs in a decision and attaching a direction of preference e g increase and decrease The key challenge for this step is dis tinguishing between means and fundamental objectives Funda mental objectives refl ect values or what people care about whereas means objectives refl ect how to achieve those desired values Keeney 1992 The goal and scope of the LCA should align with the fundamental objectiveswhile the meansobjectives are the coupling points for the impact indicators Ultimately LCA indicator selection should be governed by what is and is not included in the objectives More importantly practitioners should revisit and communicate this relationship between the LCIA indicators and the objectives and measures when informing the fi nal decision Con structing a means ends network that explicitly highlights the relationship between LCIA and objectives helps ensure that stake holder values are placed at the forefront of the decisionprocess and any options that are subsequently developed are constructed to achieve those values 2 1 3 Step C defi ne options Step C continues the use of expert elicitation with the emphasis in this step on brainstorming options Options can mean different things for DA and LCA The options in DA are the actions defi ned to realize the stakeholder values and objectives The alternatives are what is evaluated when a decision is made or as stated by Gregory et al 2012 Alternatives are complete solutions to a given prob lem that can be directly compared by decision makers Only one alternative can be decided upon and each alternative consists of multiple options so that multiple alternatives containing multiple options are evaluated Parnell et al 2013 The options in LCA are the alternatives created to satisfy the functional unit or need For example the options for a decision to minimize a chemical emis sion may be a range of emission reduction values The options in a corresponding LCA would include scenarios of various abatement technologies or product alternatives to achieve each of the target reduction values Thus a decision with only a single option could require a number of LCA scenarios to account for the possibilities which means a more complex decision with numerous options could require a large number of LCA options and scenarios Although these can be different the LCA options should be devel oped byfi rst understanding the decision options and alternatives to ensure the LCA adequately informs the understanding of these options It is critical to perform this step after the objectives have been agreed upon in order to ensure decision options meet values and do not arise merely out of convention Once the options have been defi ned the LCA practitioner can develop suitable life cycle Fig 1 A DA LCA framework blue boxes integrating information fl ows blue arrows between a decision analysis process and life cycle assessment For interpretation of the references to colour in this fi gure legend the reader is referred to the Web version of this article T Garvey et al Journal of Cleaner Production 254 2020 1200363 inventory models within goal scope and especially the decision context 2 1 4 Step D evaluate consequences Step D includes the development of a visual tool to connect the LCA results with the decision model and the subsequent evaluation of consequences For the fi rst iteration of this framework the proposed visual tool is an ID integrating the decision objectives and LCI LCIA indicators with utility functions A combination of expert elicitation literature and other relevant sources can be used to construct the ID Input from decision makers and stakeholders is necessary to determine the acceptable level of risk for the decision and to specify any necessary weighting preferences Expert input can be useful for defi ning utility functions describing any non LCA decision factors The utility functions for the measures associated with LCA impacts can be constructed using literature on LCIA normalization factors The actual evaluation involves fi rst gener ating life cycle impact scores for all specifi ed LCA options and scenarios These scores are then used to evaluate the utility of de cision scenarios where