Survey Insights into Weighting Environmental Damages: Influence of Context and Group

When one models impact pathways due to stressors that are caused by the provision of product systems, it results in indicators for environmental damages. These indicators are incommensurable and cannot be compared per se. For example, the statistical life years lost for a human population cannot necessarily be compared with the potentially affected fraction of species within an ecosystem. However, some decision makers who use life-cycle assessment (LCA) prefer a single index, because it facilitates interpretation better than a multi-indicator system. This requires a method for aggregating environmental damages of differing types, thereby confronting LCA with a valuation problem.
The article describes a nonmonetary approach to valuation in LCA that incorporates the findings of a survey among LCA practitioners and users. The survey focuses on the weighting of three safeguard subjects for Eco-indicator 99, a damage-oriented impact-assessment method: human health, ecosystem quality, and resources. Of particular interest here is what influence the context provided in the survey (framing) and an individual's characteristics have on his or her weighting of environmental damages. The results indicate that damages on the European level are easier to compare than damages on a micro level. Additionally, although only half of the survey participants could be classified unequivocally into one of three cultural perspectives, each perspective rated the damage categories presented to them significantly differently from the others. Our conclusions were that framing effects need to be more carefully considered in weighting procedures and that weighting preferences vary significantly according to a group's archetypical attitudes.     

Multi-criteria Analysis for Technique Assessment:Case Study from Industrial Coating

Environmental policy is oriented toward integrated pollution prevention, taking into consideration all environmental media (air, water, land) and energy consumption. Therefore, methods for assessing environmentally relevant installations are needed which take economic, technical, and especially ecological criteria into account simultaneously. Mass and energy flow models are used for the representation of production processes and form the basis for the inventory phase in life-cycle assessment (LCA). For the interpretation of LCA results and the weighting of the aggregated impact assessment indicators, approaches of multicriterion analysis (MCA) have been proposed. These can analyze ecological aspects as well as economic and technical criteria. Recent developments in LCA focus on decision support for policy makers or decision boards. Appropriate support for investment decisions on environmentally relevant installations, however, is rare.
Based on a case study of the sector called surface coating, an MCA of environmentally relevant installations is described. With the help of a mass and energy flow management system, alternative scenarios, depicting the use of solvent-reduced materials and environmentally friendly techniques, are modeled for the job coater processes in case studies of coating of mobile phones and coating of polyvinyl chloride (PVC) parts destined for the automobile industry. The modeled scenarios are further analyzed by using a multicriterion decision support module. The application of the outranking approach PROMETHEE is illustrated. A further investigation of the derived ranking can be obtained through sensitivity analyses. Moreover, the results derived by PROMETHEE are compared with the outcomes of the multicriterion approaches multiattribute utility theory and analytical hierarchy process.     

Stochastic multi-attribute analysis (SMAA) as an interpretation method for comparative life-cycle assessment (LCA)

Purpose

Comparative life-cycle assessments (LCAs) today lack robust methods of interpretation that help decision makers understand and identify tradeoffs in the selection process. Truncating the analysis at characterization is misleading and existing practices for normalization and weighting may unwittingly oversimplify important aspects of a comparison. This paper introduces a novel approach based on a multi-criteria decision analytic method known as stochastic multi-attribute analysis for life-cycle impact assessment (SMAA-LCIA) that uses internal normalization by means of outranking and exploration of feasible weight spaces.

Methods

To contrast different valuation methods, this study performs a comparative LCA of liquid and powder laundry detergents using three approaches to normalization and weighting: (1) characterization with internal normalization and equal weighting, (2) typical valuation consisting of external normalization and weights, and (3) SMAA-LCIA using outranking normalization and stochastic weighting. Characterized results are often represented by LCA software with respect to their relative impacts normalized to 100 %. Typical valuation approaches rely on normalization references, single value weights, and utilizes discrete numbers throughout the calculation process to generate single scores. Alternatively, SMAA-LCIA is capable of exploring high uncertainty in the input parameters, normalizes internally by pair-wise comparisons (outranking) and allows for the stochastic exploration of weights. SMAA-LCIA yields probabilistic, rather than discrete comparisons that reflect uncertainty in the relative performance of alternatives.

Results and discussion

All methods favored liquid over powder detergent. However, each method results in different conclusions regarding the environmental tradeoffs. Graphical outputs at characterization of comparative assessments portray results in a way that is insensitive to magnitude and thus can be easily misinterpreted. Typical valuation generates results that are oversimplified and unintentionally biased towards a few impact categories due to the use of normalization references. Alternatively, SMAA-LCIA avoids the bias introduced by external normalization references, includes uncertainty in the performance of alternatives and weights, and focuses the analysis on identifying the mutual differences most important to the eventual rank ordering.

Conclusions

SMAA-LCIA is particularly appropriate for comparative LCAs because it evaluates mutual differences and weights stochastically. This allows for tradeoff identification and the ability to sample multiple perspectives simultaneously. SMAA-LCIA is a robust tool that can improve understanding of comparative LCA by decision or policy makers.     

Institutionalization of Life-Cycle Thinking in the Everyday Discourse of Market Actors

The widespread popularity of life-cycle assessment (LCA) is difficult to understand from the point of view of instrumental decision making by economic agents. Ehrenfeld has argued, in a 1997 issue of this journal, that it is the world-shaping potential of LCA that is more important than its use as a decision-making tool. The present study attempts to explore the institutionalization of this "LCA world view" among ordinary market actors. This is important because environmental policy relies increasingly on market-based initiatives. Cognitive and normative assumptions in authoritative LCA documents are examined as empirical data and compared with data from focus group interviews concerning products and the environment with "ordinary" manufacturers, retailers, and consumers in Finland. These assumptions are (1) the "cradle-to-grave" approach, (2) the view that all products have an environmental impact and can be improved, (3) the relativity of environmental merit, and (4) the way responsibility for environmental burdens is attributed. Relevant affinities, but also differences, are identified. It is argued that life-cycle thinking is not primarily instrumental, but rather is gaining a degree of intrinsic value. The study attempts to establish a broader institutional context in which the popularity of LCA can be understood. From the point of view of this broader context, some future challenges for the development of LCA and life-cycle thinking are suggested.     

A Theoretical Foundation for Life-Cycle Assessment

The presence of value judgments in life-cycle impact assessment (LCIA) has been a constant source of controversy. According to a common interpretation, the international standard on LCIA requires that the assessment methods used in published comparisons be "value free." Epistemologists argue that even natural science rests on "constitutive" and "contextual" value judgments. The example of the equivalency potential for climate change, the global warming potential (GWP), demonstrates that any impact assessment method inevitably contains not only constitutive and contextual values, but also preference values. Hence, neither life-cycle assessment (LCA) as a whole nor any of its steps can be "value free." As a result, we suggest a more comprehensive definition of objectivity in LCA that allows arguments about values and their relationship to facts. We distinguish three types of truth claims: factual claims, which are based on natural science; normative claims, which refer to preference values; and relational claims, which address the proper relation between factual knowledge and values. Every assessment method, even the GWP, requires each type of claim. Rational arguments can be made about each type of claim. Factual truth claims can be assessed using the scientific method. Normative claims can be based on ethical arguments. The values of individuals or groups can be elicited using various social science methods. Relational claims must follow the rules of logic. Relational claims are most important for the development of impact assessment methods. Because LCAs are conducted to satisfy the need of decision makers to consider environmental impacts, relational claims about impact assessment methods should refer to this goal. This article introduces conditions that affect environmental decision making and discusses how LCA—values and all—can be defended as a rational response to the challenge of moving uncertain scientific information into the policy arena.     

Evaluating Environmental Performance of Pulp and Paper Manufacturing Using the Analytic Hierarchy Process and Life-Cycle Assessment

This article addresses the need for a structured and compre-hensive methodology for assessing the environmental perfor-mance of manufacturing processes. The analytic hierarchy pro-cess (AHP) is used as the basic framework for analyzing environmental impacts and improvement options following a streamlined life-cycle assessment (LCA) approach that is fo-cused on the manufacturing operation. The multicriteria de-cision analysis approach of the AHP is consistent with the LCA concept because the environmental factors can be hierarchi-cally structured into impacts and improvement options. Its po-tential as a valuation tool for impact and improvement assess-ment addresses both qualitative and quantitative issues in environmental decision making.
Through application to a pulp and paper manufacturing case study, the viability of the AHP for evaluating environmen-tal impacts and prioritizing process improvement options rela-tive to these impacts is demonstrated. AHP was used to pro-vide a quantitative tool for the design of a set of weighting factors for impact and improvement analyses.     

Excluding site-specific data from the lca inventory: how this affects life cycle impact assessment

The exclusion of site-specific data from the inventory phase of an LCA continues to be a point of controversy. Though the current simplified data collection strategy is widely supported by the LCA community, there are still many who are concerned about the implications this limitation has for the utility and reliability of LCA results. This is particularly relevant to practitioners who are attempting to draw conclusions about the environmental performance of different systems for the development of environmental policy. The current site-generic methodology introduces uncertainties into LCA results that have the potential to misdirect decisions on improvement measures. Therefore, in this paper we assess the practicality of collecting site-specific data and examine its value for study interpretation and decision-making. In our case study, we compare the contribution of a number of plastics-based packaging systems to photochemical oxidant formation. Our results demonstrate that the aggregation of photochemical oxidant precursor emissions into a single global parameter is an unreliable indicator of environmental burden and that the real significance of each packaging’ contribution to the formation of photochemical smog in the atmosphere can only be understood after the addition of spatial and temporal information. We conclude that for non-global cumulative impact categories, additional spatial and temporal data should be collected, and that the benefits to decision makers far outweigh the additional effort needed to acquire this data for the LCA inventory.     

Impact of normalisation,elicitation technique and background information on panel weighting results in life cycle assessment

Purpose

Weighting in Life Cycle Assessment (LCA) is a much-debated topic. Various tools have been used for weighting in LCA, Multi-Criteria Decision Analysis (MCDA) being one of the most common. However, it has not been thoroughly assessed how weight elicitation techniques of MCDA with different scales (interval and ratio) along with external and internal normalisation affect weighting and subsequent results. The aim of this survey is to compare different techniques in an illustrative example in the building sector.

Methods

A panel of Nordic LCA experts accomplished six weighting exercises. The different weight elicitation techniques are SWING which is based on the interval scale; Simple Multi-Attribute Rating Technique (SMART) and Analytic Hierarchy Process (AHP) which is based on the ratio scale. Information on the case study was provided for the panellists, along with characterised or normalised impact assessment scores. However, in the first weighting exercise, the panellists were not provided with any scores or background information, but they had to complete the weighting at a more general level. With the weights provided by the panel, the environmental impacts of three alternative house types were aggregated. The calculations were based on three well-grounded aggregation rules, which are commonly used in the field of LCA or decision analysis.

Results and discussion

In the illustrative construction example, the different aggregation rules had the biggest impact on the results. The results were different in the six calculation methods: when externally normalised scores were applied, house type A was superior in most of the calculations, but when internal normalisation was accomplished, house type C was superior. By using equal weights, similar results were obtained. None of the panellists intuitively considered A as the superior house type, but in some of the calculations, this was indeed the case. Furthermore, the results refer to the fact that the panellists completed the weighting on the basis of their general knowledge, without taking the features of different weight elicitation techniques into account.

Conclusions

External normalisation provides information on a magnitude of impacts, and in some cases, external normalisation may be a more influential factor than weighting. Based on the results, it cannot be stated which different weight elicitation technique is the most suitable for LCA. However, the method should be selected based on the aims and purpose of the study. Moreover, the elicitation questions should be explained with care to experts so that they interpret the questions as intended.     

On the use of weighting in LCA: translating decision makers’ preferences into weights via linear programming

Purpose

The main goal of any life cycle assessment (LCA) study is to identify solutions leading to environmental savings. In conventional LCA studies, practitioners select from some alternatives the one which better matches their preferences. This task is sometimes simplified by ranking these alternatives using an aggregated indicator defined by attaching weights to impacts. We address here the inverse problem. That is, given an alternative, we aim to determine the weights for which that solution becomes optimal.

Methods

We propose a method based on linear programming (LP) that determines, for a given alternative, the ranges within which the weights attached to a set of impact metrics must lie so that when a weighting combination of these impacts is optimized, the alternative can be optimal, while if the weights fall outside this range, it is guaranteed that the solution will be suboptimal. A large weight value implies that the corresponding LCA impact is given more importance, while a low value implies the converse. Furthermore, we provide a rigorous mathematical analysis on the implications of using weighting schemes in LCA, showing that this practice guides decision-making towards the adoption of some specific alternatives (those lying on the convex envelope of the resulting trade-off curve).

Results and discussion

A case study based on the design of hydrogen infrastructures is taken as a test bed to illustrate the capabilities of the approach presented. Given are a set of production and storage technologies available to produce and deliver hydrogen, a final demand, and cost and environmental data. A set of designs, each achieving a unique combination of cost and LCA impact, is considered. For each of them, we calculate the minimum and maximum weight to be given to every LCA impact so that the alternative can be optimal among all the candidate designs. Numerical results show that solutions with lower impact are selected when decision makers are willing to pay larger monetary penalties for the environmental damage caused.

Conclusions

LP can be used in LCA to translate the decision makers’ preferences into weights. This information is rather valuable, particularly when these weights represent economic penalties, as it allows screening and ranking alternatives on the basis of a common economic basis. Our framework is aimed at facilitating decision making in LCA studies and defines a general framework for comparing alternatives that show different performance in a wide variety of impact metrics.     

A decision-analytic framework for impact assessment part I: LCA and decision analysis

Life-cycle assessments (LCAs) are conducted to satisfy the aspiration of decision makers to consider the environment in their decision making. This paper reviews decision analysis and discusses how it can be used to structure the assessment and to integrate characterization and valuation. The decision analytic concepts of objectives (goals) and attributes (indicators of the degree to which an objective is achieved) are used to describe steps of the assessment of the entire impact chain. Decision analysis distinguishes among different types of objectives and attributes; it describes how these relate to each other. Impact indicators such as the Human Toxicity Potential are constructed attributes. A means-ends objectives network can show how the different constructed attributes relate to the objective of protecting the environment. As LCA takes disparate environmental impacts into account, it needs to assess their relative importance. Trade-off methods in decision analysis are grouped into utility theory and multicriteria decision aids; they have different advantages and disadvantages, but are all more sophisticated than simple weighting. The performance of the different trade-off methods has not yet been tested in an LCA context. In the second part of the paper, we present criteria for the development of characterization methods.     

Applying Life Cycle Tools and Process Engineering to Determine the Most Adequate Treatment Process Conditions. A Tool in Environmental Policy (12 pp)

Background The analysis of a wastewater treatment technology, under a expanded boundaries system which includes both the technology and the inputs required for its operation, quantifies the overall environmental impact that may result from the treatment of a wastewater stream. This is particularly useful for environmental policy makers being that a expanded boundaries system tends to provide a holistic view. The former view can be highly enriched with the use of process engineering tools, such as mathematical process modelling, process design, performance assessment and cost optimised models. Main Features The traditional approach used to assess waste treatment technologies is contrasted with a life cycle analysis (LCA) approach. The optimal design of a granular activated carbon adsorption (GAC) process is used as a model system to demonstrate the advantages of LCA approaches over traditional approaches. Further sections of the paper describe a mathematical framework for the assessment of technologies, design considerations applied in the cost optimised carbon adsorption model, the use of LCA techniques to perform an inventory of all emissions associated to the process system and, some of its environmental impacts. Results Economic and environmental considerations regarding the optimum process design are introduced as a basis for decision towards the selection and operating conditions of wastewater treatment technologies. Moreover, the use of LCA has revealed that the environmental burden associated with the wastewater treatment may produce a higher environmental impact than one that can be caused by untreated discharges. Conclusion The paper highlights the string advantages that environmental policy makers may have by combining LCA and process engineering tools. Furthermore, this approach can be incorporated into other existing treatment processes or for process designers.     

Hierarchical Activity Model for Risk‐Based Decision Making

For the practical implementation of the assessment of environmental impact, actual procedures and data requirements should be clarified so that industrial decision makers understand them. Researchers should consider local risks related to processes and environmental impact throughout the life cycle of products simultaneously to supervise these adverse effects appropriately. Life cycle assessment (LCA) is a useful tool for quantifying the potential impact associated with a product life cycle. Risk assessment (RA) is a widely used tool for identifying chemical risks in a specific situation. In this study, we integrate LCA and RA for risk‐based decision making by devising a hierarchical activity model using the type‐zero method of integrated definition language (IDEF0). The IDEF0 activity modeling language has been applied to connect activities with information flows. Process generation, evaluation, and decision making are logically defined and visualized in the activity model with the required information. The activities, information flows, and their acquisitions are revealed, with a focus on which data should be collected by on‐site engineers. A case study is conducted on designing a metal cleaning process reducing chemical risks due to the use of a cleansing agent. LCA and RA are executed and applied effectively on the basis of integrated objective settings and interpretation. The proposed activity model can be used as a foundation to incorporate such assessments into actual business models.     

Entity Normalization in Life Cycle Assessment: Hybrid Schemes Applied to a Transportation Agency Case Study

Government agencies, companies, and other entities are using environmental assessments, like life cycle assessment (LCA), as an input to decision‐making processes. Communicating the esoteric results of an LCA to these decision makers can present challenges, and interpretation aids are commonly provided to increase understanding. One such method is normalizing results as a means of providing context for interpreting magnitudes of environmental impacts. Normalization is mostly carried out by relating the environmental impacts of a product (or process) under study to those of another product or a spatial reference area (e.g., the United States). This research is based on the idea that decision makers might also benefit from normalization that considers comparisons to their entity's (agency, company, organization, etc.) total impacts to provide additional meaning and aid in comprehension. Two hybrid normalization schemes have been developed, which include aspects of normalization to both spatially based and entity‐based impacts. These have been named entity‐overlaid and entity‐accentuated normalization, and the schemes allow for performance‐based planning or emphasizing environmental impact types that are most relevant to an entity's operational profile, respectively. A hypothetical case study is presented to demonstrate these schemes, which uses environmental data from a U.S. transportation agency as the basis for entity normalization factors. Results of this case study illustrate how entity‐related references may be developed, and how this additional information may enhance the presentation of LCA results using the hybrid normalization schemes.     

Modelling the Valuesphere and the Ecosphere:

Methods for Life Cycle Impact Assessment have to cope with two critical aspects, the uncertainty in values and the (unknown) system behaviour. LCA methodology should cope explicitly with these subjective elements. A structured aggregation procedure is proposed that differentiates between the technosphere and the ecosphere and embeds them in the valuesphere. LCA thus becomes a decision support system that models and combines these three spheres. We introduce three structurally identical types of LCA, each based on one coherent but different set of values. These sets of values can be derived from the Cultural Theory and are labeled as ‘egalitarian’, ‘individualistic’, and ‘hierarchic’. Within Life Cycle Impact Assessment, a damage oriented assessment model is complemented with both a newly developed precautionary indicator designed to address unknown damage and an indicator for the manageability of environmental damages. The indicators for unknown damage and for manageability complete the set of indicators judged to be relevant by decision makers. The weights given to these indicators are also value-dependent. The framework proposed here answers the criticisms that present LCA methodology does not strictly enough separate subjective from objective elements and that it fails to accurately model environmental impacts.     

Weighting across safeguard subjects for LCIA through the application of conjoint analysis

Background  

Many types of weighting methods, which have integrated the various environmental impacts that are used for life-cycle impact assessment (LCIA), were proposed with the aim of developing the methodology as a useful information resource for decision making, such as in the selection of products. Economic valuation indexes, in particular, have attracted attention, as their assessment results are easy to understand and can be applied in conjunction with other assessment tools, including life-cycle costing (LCC) and environmental accounting. Conjoint analysis has been widely used in market research, and has recently been applied to research in environmental economics. The method enables us to provide two types of assessment results; an economic valuation and a dimensionless index. This method is therefore expected to contribute greatly to increasing the level of research into weighting methodology, in which an international consensus has yet to be established. Conjoint analysis, however, has not previously been applied to LCIA.     

Modelling the valuesphere and the ecosphere: Integrating the decision makers’ perspectives into LCA

Methods for Life Cycle Impact Assessment have to cope with two critical aspects, the uncertainty in values and the (unknown) system behaviour. LCA methodology should cope explicitly with these subjective elements. A structured aggregation procedure is proposed that differentiates between the technosphere and the ecosphere and embeds them in the valuesphere. LCA thus becomes a decision support system that models and combines these three spheres. We introduce three structurally identical types of LCA, each based on one coherent but different set of values. These sets of values can be derived from the Cultural Theory and are labeled as ‘egalitarian’, ‘individualistic’, and ‘hierarchic’. Within Life Cycle Impact Assessment, a damage oriented assessment model is complemented with both a newly developed precautionary indicator designed to address unknown damage and an indicator for the manageability of environmental damages. The indicators for unknown damage and for manageability complete the set of indicators judged to be relevant by decision makers. The weights given to these indicators are also value-dependent. The framework proposed here answers the criticisms that present LCA methodology does not strictly enough separate subjective from objective elements and that it fails to accurately model environmental impacts.     

A survey of life cycle approaches in waste management

Background, aim, and scope  

Life-cycle thinking and life-cycle approaches are concepts that are getting increased attention worldwide and in particular in EU Policies related to sustainability. The European Commission is launching a number of activities to strengthen life-cycle thinking in policy and business. EU policies aim to decrease waste generation through new waste prevention initiatives, better use of resources and shift to more sustainable consumption patterns. The approach to waste management is based on three principles: waste prevention, recycling and reuse and improving the final disposal and monitoring. In particular, concerning the prevention and recycling of waste, the definition of a waste hierarchy should be the basis for the prioritisation of waste management options. The benefit of using Life Cycle Assessment (LCA) in analysing waste management systems is the provision of a comprehensive view of the processes and impacts involved. However, it is also clear that the studies will always be open for criticism as they are simplifications of reality. Moreover, in order to become the LCA, a leading tool within businesses and government to understand and manage risks or opportunities related to waste management and treatment technologies, there are methodological choices required and a number of aspects that still need to be worked out. It is therefore important to review open and grey literatures, EU guidelines, relevant environmental indicators and databases for the waste sector and data easily usable in waste policy decision-making, with an agreed approach and methodology based on life-cycle thinking. The following survey gathers and describes the existing guidelines and methodologies based on life-cycle thinking and applicable in waste policy decision-making.     

Decision Analysis Utilizing Data from Multiple Life-Cycle Impact Assessment Methods Part I: A Theoretical Basis

Numerous methodologies for the life-cycle impact assessment (LCIA) step of life-cycle assessment (LCA) are currently in popular use. These methods, which are based on a single method or level of analysis, are limited to the environmental fates, impact categories, damage functions, and stressors included in the method or model. Because of this, it has been suggested within the LCA community that LCIA data from multiple methods and/or levels of analysis, that is, end-point and midpoint indicators, be used in LCA-based decision analysis to facilitate better or, at least more informed, decision making. In this (two-part) series of articles, we develop and present a series of LCA-based decision analysis models, based on multiattribute value theory (MAVT), which utilize data from multiple LCIA methods and/or levels of analysis. The key to accomplishing this is the recognition of what LCIA damage indicators represent with respect to decision analysis, namely, decision attributes and, in most cases, proxy attributes. The use of proxy attributes in a decision model, however, poses certain challenges, such as the assessment of decision-maker preferences for actual consequences that are only known imprecisely because of inherent limits of both LCA and scientific knowledge. In this article (part I), we provide a brief overview of MAVT and examine some of the decision-theoretic issues and implications of current LCIA methods. We illustrate the application of MAVT to develop a decision model utilizing damage indicators from a single LCIA methodology; and, we identify the decision-theoretic issues that arise when attempting to combine LCIA indicators from multiple methods and/or levels of analysis in a single decision model. Finally, we introduce the use in our methodology of constructed attributes to combine related end-point damage indicators into single decision attributes and the concept and evaluation of proxy attributes.     

Modelling the Valuesphere and the Ecosphere: Integrating the Decision Makers' Perspectives into LCA

Methods for Life Cycle Impact Assessment have to cope with two critical aspects, the uncertainty in values and the (unknown) system behaviour. LCA methodology should cope explicitly with these subjective elements. A structured aggregation procedure is proposed that differentiates between the technosphere and the ecosphere and embeds them in the valuesphere. LCA thus becomes a decision support system that models and combines these three spheres. We introduce three structurally identical types of LCA, each based on one coherent but different set of values. These sets of values can be derived from the Cultural Theory and are labeled as ‘egalitarian’, ‘individualistic’, and ‘hierarchic’. Within Life Cycle Impact Assessment, a damage oriented assessment model is complemented with both a newly developed precautionary indicator designed to address unknown damage and an indicator for the manageability of environmental damages. The indicators for unknown damage and for manageability complete the set of indicators judged to be relevant by decision makers. The weights given to these indicators are also value-dependent. The framework proposed here answers the criticisms that present LCA methodology does not strictly enough separate subjective from objective elements and that it fails to accurately model environmental impacts.     

A Decision Support Framework for Sustainable Waste Management

This article describes a decision support framework for the evaluation of scenarios for the integrated management of municipal solid waste within a local government area (LGA).
The work is initially focused on local government (i.e., municipal councils) in the state of Queensland, Australia; however, it is broadly applicable to LGAs anywhere. The goal is to achieve sustainable waste management practices by balancing global and regional environmental impacts, social impacts at the local community level, and economic impacts. The framework integrates life-cycle assessment (LCA) with other environmental, social, and economic tools. For this study, social and economic impacts are assumed to be similar across developed countries of the world. LCA was streamlined at both the life-cycle inventory and life-cycle impact assessment stages.
For this process, spatial resolution is introduced into the LCA process to account for impacts occurring at the local and regional levels. This has been done by considering social impacts on the local community and by use of a regional procedure for LCA data for emissions to the environment that may have impacts at the regional level.
The integration follows the structured approach of the pressure-state-response (PSR) model suggested by the Organisation for Economic Cooperation and Development (OECD). This PSR model has been extended to encompass nonenvironmental issues and to guide the process of applying multiple tools.
The framework primarily focuses on decision analysis and interpretation processes. Multiattribute utility theory (MAUT) is used to assist with the integration of qualitative and quantitative information. MAUT provides a well-structured approach to information assessment and facilitates objective, transparent decisions. A commercially available decision analysis software package based on MAUT has been used as the platform for the framework developed in this study.