Comparing the midpoint and endpoint approaches based on ReCiPe—a study of commercial buildings in Hong Kong

Purpose

Life cycle assessment (LCA) has been increasingly implemented in analyzing the environmental performance of buildings and construction projects. To assess the life cycle environmental performance, decision-makers may adopt the two life cycle impact assessment (LCIA) approaches, namely the midpoint and endpoint models. Any imprudent usage of the two approaches may affect the assessment results and thus lead to misleading findings. ReCiPe, a well-known work, includes a package of LCIA methods to provide assessments on both midpoint and endpoint levels. This study compares different potential LCIA results using the midpoint and endpoint approaches of ReCiPe based on the assessment of a commercial building in Hong Kong.

Methods

This paper examines 23 materials accounting for over 99 % of the environmental impacts of all the materials consumed in commercial buildings in Hong Kong. The midpoint and endpoint results are compared at the normalization level. A commercial building in Hong Kong is further studied to provide insights as a real case study. The ranking of impact categories and the contributions from various construction materials are examined for the commercial building. Influence due to the weighting factors is discussed.

Results and discussion

Normalization results of individual impact categories of the midpoint and endpoint approaches are consistent for the selected construction materials. The difference in the two approaches can be detected when several impact categories are considered. The ranking of materials is slightly different under the two approaches. The ranking of impact categories demonstrates completely different features. In the case study of a commercial building in Hong Kong, the contributions from subprocesses are different at the midpoint and endpoint. The weighting factors can determine not only the contributions of the damage categories to the total environment, but also the value of a single score.

Conclusions

In this research, the midpoint and endpoint approaches are compared using ReCiPe. Information is whittled down from the inventories to a single score. Midpoint results are comprehensive while endpoint results are concise. The endpoint approach which provides additional information of damage should be used as a supplementary to the midpoint model. When endpoint results are asked for, a LCIA method like ReCiPe that provides both the midpoint and endpoint analysis is recommended. This study can assist LCA designers to interpret the midpoint and endpoint results, in particular, for the assessment of commercial buildings in Hong Kong.     

Accounting for overfishing in life cycle assessment: new impact categories for biotic resource use

Purpose

Overfishing is a relevant issue to include in all life cycle assessments (LCAs) involving wild caught fish, as overfishing of fish stocks clearly targets the LCA safeguard objects of natural resources and natural ecosystems. Yet no robust method for assessing overfishing has been available. We propose lost potential yield (LPY) as a midpoint impact category to quantify overfishing, comparing the outcome of current with target fisheries management. This category primarily reflects the impact on biotic resource availability, but also serves as a proxy for ecosystem impacts within each stock.

Methods

LPY represents average lost catches owing to ongoing overfishing, assessed by simplified biomass projections covering different fishing mortality scenarios. It is based on the maximum sustainable yield concept and complemented by two alternative methods, overfishing though fishing mortality (OF) and overfishedness of biomass (OB), that are less data-demanding.

Results and discussion

Characterization factors are provided for 31 European commercial fish stocks in 2010, representing 74 % of European and 7 % of global landings. However, large spatial and temporal variations were observed, requiring novel approaches for the LCA practitioner. The methodology is considered compliant with the International Reference Life Cycle Data System (ILCD) standard in most relevant aspects, although harmonization through normalization and endpoint characterization is only briefly discussed.

Conclusions

Seafood LCAs including any of the three approaches can be a powerful communicative tool for the food industry, seafood certification programmes, and for fisheries management.     

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.     

Improving odour assessment in LCA—the odour footprint

Purpose

Odour is an important aspect of systems for human and agricultural waste management and many technologies are developed with the sole purpose of reducing odour. Compared with greenhouse gas assessment and the assessment of toxicity, odour assessment has received little attention in the life cycle assessment (LCA) community. This article aims to redress this.

Methods

Firstly, a framework for the assessment of odour impacts in LCA was developed considering the classical LCA framework of emissions, midpoint and endpoint indicators. This suggested that an odour footprint midpoint indicator was worth striving for. An approach to calculating an areal indicator we call “odour footprint”, which considers the odour detection threshold, the diffusion rate and the kinetics of degradation of odourants, was implemented in MATLAB. We demonstrated the use of the characterisation factors we calculated in a case study based on odour removal technology applied to a pig barn.

Results and discussion

We produced a list of 33 linear characterisation factors based on hydrogen sulphide equivalents, analogous to the linear carbon dioxide equivalency factors in use in carbon footprinting, or the dichlorobenzene equivalency factors developed for assessment of toxic impacts in LCA. Like the latter, this odour footprint method does not take local populations and exposure pathway analysis into account—its intent is not to assess regulatory compliance or detailed design. The case study showed that despite the need for materials and energy, large factor reductions in odour footprint and eutrophication potential were achieved at the cost of a smaller factor increase in greenhouse emissions.

Conclusions

The odour footprint method is proposed as an improvement on the established midpoint method for odour assessment in LCA. Unlike it, the method presented here considers the persistence of odourants. Over time, we hope to increase the number of characterised odourants, enabling analysts to perform simple site-generic LCA on systems with odourant emissions.     

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.     

Interpretation of comparative LCAs: external normalization and a method of mutual differences

Purpose

Identification of environmentally preferable alternatives in a comparative life cycle assessment (LCA) can be challenging in the presence of multiple incommensurate indicators. To make the problem more manageable, some LCA practitioners apply external normalization to find those indicators that contribute the most to their respective environmental impact categories. However, in some cases, these results can be entirely driven by the normalization reference, rather than the comparative performance of the alternatives. This study evaluates the influence of normalization methods on interpretation of comparative LCA to facilitate the use of LCA in decision-driven applications and inform LCA practitioners of latent systematic biases. An alternative method based on significance of mutual differences is proposed instead.

Methods

This paper performs a systematic evaluation of external normalization and describes an alternative called the overlap area approach for the purpose of identifying relevant issues in a comparative LCA. The overlap area approach utilizes the probability distributions of characterized results to assess significant differences. This study evaluates the effects in three LCIA methods, through application of four comparative studies. For each application, we call attention to the category indicators highlighted by each interpretation approach.

Results and discussion

External normalization in the three LCIA methods suffers from a systematic bias that emphasizes the same impact categories regardless of the application. Consequently, comparative LCA studies that employ external normalization to guide a selection may result in recommendations dominated entirely by the normalization reference and insensitive to data uncertainty. Conversely, evaluation of mutual differences via the overlap area calls attention to the impact categories with the most significant differences between alternatives. The overlap area approach does not show a systematic bias across LCA applications because it does not depend on external references and it is sensitive to changes in uncertainty. Thus, decisions based on the overlap area approach will draw attention to tradeoffs between alternatives, highlight the role of stakeholder weights, and generate assessments that are responsive to uncertainty.

Conclusions

The solution to the issues of external normalization in comparative LCAs proposed in this study call for an entirely different algorithm capable of evaluating mutual differences and integrating uncertainty in the results.

     

Life cycle assessment as a decision support tool for bridge procurement: environmental impact comparison among five bridge designs

Purpose

The conventional decision-making for bridges is mostly focusing on technical, economical, and safety perspectives. Nowadays, the society devotes an ever-increased effort to the construction sector regarding their environmental performance. However, considering the complexity of the environmental problems and the diverse character of bridges, the related research for bridge as a whole system is very rare. Most existing studies were only conducted for a single indicator, part of the structure components, or a specific life stage.

Methods

Life Cycle Assessment (LCA) is an internationally standardized method for quantifying the environmental impact of a product, asset, or service throughout its whole life cycle. However, in the construction sector, LCA is usually applied in the procurement of buildings, but not bridges as yet. This paper presents a comprehensive LCA framework for road bridges, complied with LCA ReCiPe (H) methodology. The framework enables identification of the key structural components and life cycle stages of bridges, followed by aggregation of the environmental impacts into monetary values. The utility of the framework is illustrated by a practical case study comparing five designs for the Karlsnäs Bridge in Sweden, which is currently under construction.

Results and discussion

This paper comprehensively analyzed 20 types of environmental indicators among five proposed bridge designs, which remedies the absence of full spectrum of environmental indicators in the current state of the art. The results show that the monetary weighting system and uncertainties in key variables such as the steel recycling rate and cement content may highly affect the LCA outcome. The materials, structural elements, and overall designs also have varying influences in different impact categories. The result can be largely affected by the system boundaries, surrounding environment, input uncertainties, considered impact indicators, and the weighting systems applied; thus, no general conclusions can be drawn without specifying such issues.

Conclusions

Robustly evaluating and ranking the environmental impact of various bridge designs is far from straightforward. This paper is an important attempt to evaluate various designs from full dimensions. The results show that the indicators and weighting systems must be clearly specified to be applicable in a transparent procurement. This paper provides vital knowledge guiding the decision maker to select the most LCA-feasible proposal and mitigate the environmental burden in the early stage.     

Weighting environmental effects: Analytic survey with operational evaluation methods and a meta-method

Purpose

The purpose of this paper is to supply an open method for weighting different environmental impacts, open to basically different evaluation approaches and open to easy revisions. From the partial, diverse and conflicting weighing methods available, a most consistent and flexible meta-method is constructed, allowing for a transparent discussion on weighting.

Methods

The methods incorporated are as general as possible, each single one being as pure as possible. We surveyed encompassing operational methods for evaluation, applicable in LCA and in larger systems like countries. They differ in terms of modelling, as to midpoint or as to endpoint; as to evaluation set-up, in terms of collective preferences or individual preferences; and as to being either revealed or stated. The first is midpoint modelling with collectively stated preferences, with operational weighting schemes from Dutch and US government applications. Second is the LCA-type endpoint approach using individual stated preferences, with public examples from Japan and the Netherlands. The third is the integrated modelling approach by economists.

Results

All methods are internally inconsistent, as in terms of treatment of place and time, and they are incomplete, lacking environmental interventions and effect routes. We repaired only incompleteness, by methods transfer. Finally, we combined the three groups of methods into a meta-weighting method, aligned to the ILCD Handbook requirements for impact assessment. Application to time series data on EU-27 consumption shows how the EU developed in terms of overall environmental decoupling.

Conclusions

The disparate methods available all can be improved substantially. For now, a user adjustable meta-method is the best option, allowing for public discussion. A flexible regularly updated spreadsheet is supplied with the article.     

Uncertainty in environmentally conscious decision making: beer or wine?

Purpose

Life cycle assessment (LCA) is being used increasingly in decision support situations. In actual cases, the sources of uncertainty are easily hidden in the complexity. Methods for taking uncertainty into account are recommended by LCA guidelines, but actual application remains rare. The aim of this study is to demonstrate the sources of uncertainty in a practical simple selection case wherein a customer makes a decision between beer and wine in a restaurant, considering the selected criteria and the given information. The uncertainty in LCA results is connected to the broader scope of decision analysis.

Methods

Life cycle inventories were collected for beer and wine production from existing literature. The functional unit was chosen to be one serving of alcohol: beer or wine. For illustrative purposes, only the global warming potential indicator was included in the LCA through carbon footprint (CF). Probabilistic uncertainty analysis was applied to the CF system using Monte Carlo simulation. Water footprint was also roughly considered. In addition, three non-environmental indicators were included in the decision: weight control, price, and taste. The comparison between the two products was constructed as a multiple-criteria decision analytical problem.

Results and discussion

The results indicated that beer had, on average, a higher CF value than wine did. However, the difference was not significant, and within the uncertainty range, also the opposite conclusion was possible. The ratio of wine to beer CF was dominated by the uncertainty in the N₂O emissions of wine production. When all of the decision criteria were included, the level of uncertainty prevented robust overall conclusions about preference for beer or wine. However, depending on the utility differences assigned to subjective indicators, there existed also cases wherein decisions could be made at a 10?% risk level regardless of high overall uncertainty.

Conclusions

In many cases, the uncertainties of LCA are dwarfed by the overall uncertainty of the decision situation. However, as shown by our example, in many cases, reasonable decisions can be made in spite of high uncertainties. The uncertainties of single LCA indicators should be considered in relation to the decision-making problem, which depends on the uncertainty of LCA indicators but also significantly on the weighting of the indicators and the related uncertainty. Successful decision making depends on both the magnitude of uncertainty and the differences in expected utility value between alternatives. More attention should be paid to uncertainty analysis considering the weighting factors.     

Development of a dynamic LCA approach for the freshwater ecotoxicity impact of metals and application to a case study regarding zinc fertilization

Purpose

Temporal variability is a major source of uncertainty in current life cycle assessment (LCA) practice. In this paper, the recently developed dynamic LCA approach is adapted to assess freshwater ecotoxicity impacts of metals. The objective is to provide relevant information regarding the distribution and magnitude of metal impacts over time and to show whether the dynamic approach significantly influences the conclusions of an LCA. An LCA of zinc fertilization in agriculture was therefore carried out.

Methods

Dynamic LCA is based on the temporal disaggregation of the inventory, which is then assessed using time-horizon-dependent characterization factors. The USEtox multimedia fate model is used to develop time-horizon-dependent characterization factors for the freshwater ecotoxicity impact of 18 metals. Mass balance equations are solved dynamically to obtain fate factors as a function of time, providing both instantaneous (impact at time t following a pulse emission) and cumulative (total time-integrated impact following a pulse emission) characterization factors (CFs).

Results and discussion

Time-horizon-dependent CFs for freshwater ecotoxicity depend on the emission compartment and the metal itself. The two variables clearly influence metal fate aspects such as the maximum mass loading reaching freshwater and the persistence time of metals into this compartment. The time needed to reach the total impact for each metal may exceed thousands of years, so the time horizon used in the analysis constitutes a determining factor. The case study reveals that the results of a classical LCA are always higher than those obtained from a dynamic LCA, especially for short time horizons. For instance, at the end of a 100-year fertilization treatment, only 25 % of the impacts obtained through traditional LCA occurred.

Conclusions

Results show that dynamic LCA enables assessing freshwater ecotoxicity impacts of metals over time, allowing decision makers to test the sensitivity of their results to the choice of a time horizon. For the particular case study of zinc fertilization over a period of 20 years, the use of time-horizon-dependent CFs is more important in determining the dynamics of impacts than the timing of emission.     

Is land use impact assessment in LCA applicable for forest biomass value chains? Findings from comparison of use of Scandinavian wood,agro-biomass and peat for energy

Purpose

A framework for the inclusion of land use impact assessment and a set of land use impact indicators has been recently proposed for life cycle assessment (LCA) and no case studies are available for forest biomass. The proposed methodology is tested for Scandinavian managed forestry; a comparative case study is made for energy from wood, agro-biomass and peat; and sensitivity to forest management options is analysed.

Methods

The functional unit of this comparative case study is 1 GJ of energy in solid fuels. The land use impact assessment framework of the United Nations Environment Programme and the Society of Environmental Toxicology and Chemistry (UNEP-SETAC) is followed and its application for wood biomass is critically analysed. Applied midpoint indicators include ecological footprint and human appropriation of net primary production, global warming potential indicator for biomass (GWP_bio-100) and impact indicators proposed by UNEP-SETAC on ecosystem services and biodiversity. Options for forest biomass land inventory modelling are discussed. The system boundary covers only the biomass acquisition phase. Management scenarios are formulated for forest and barley biomass, and a sensitivity analysis focuses on impacts of land transformations for agro-biomass.

Results and discussion

Meaningful differences were found in between solid biofuels from distinct land use classes. The impact indicator results were sensitive to land occupation and transformation and differed significantly from inventory results. Current impact assessment method is not sensitive to land management scenarios because the published characterisation factors are still too coarse and indicate differences only between land use types. All indicators on ecosystem services and biodiversity were sensitive to the assumptions related with land transformation. The land occupation (m²a) approach in inventory was found challenging for Scandinavian wood, due to long rotation periods and variable intensities of harvests. Some suggestions of UNEP-SETAC were challenged for the sake of practicality and relevance for decision support.

Conclusions

Land use impact assessment framework for LCA and life cycle impact assessment (LCIA) indicators could be applied in a comparison of solid bioenergy sources. Although forest bioenergy has higher land occupation than agro-bioenergy, LCIA indicator results are of similar magnitude or even lower for forest bioenergy. Previous literature indicates that environmental impacts of land use are significant, but it remains questionable if these are captured with satisfactory reliability with the applied LCA methodology, especially for forest biomass. Short and long time perspectives of land use impacts should be studied in LCA with characterisation factors for all relevant timeframes, not only 500 years, with a forward-looking perspective. Characterisation factors need to be modelled further for different (forest) land management intensities and for peat excavation.     

Comparative LCA of ethanol versus gasoline in Brazil using different LCIA methods

Purpose

The main objective of this study is to expand the discussion about how, and to what extent, the environmental performance is affected by the use of different life cycle impact assessment (LCIA) illustrated by the case study of the comparison between environmental impacts of gasoline and ethanol form sugarcane in Brazil.

Methods

The following LCIA methods have been considered in the evaluation: CML 2001, Impact 2002+, EDIP 2003, Eco-indicator 99, TRACI 2, ReCiPe, and Ecological Scarcity 2006. Energy allocation was used to split the environmental burdens between ethanol and surplus electricity generated at the sugarcane mill. The phases of feedstock and (bio)fuel production, distribution, and use are included in system boundaries.

Results and discussion

At the midpoint level, comparison of different LCIA methods showed that ethanol presents lower impacts than gasoline in important categories such as global warming, fossil depletion, and ozone layer depletion. However, ethanol presents higher impacts in acidification, eutrophication, photochemical oxidation, and agricultural land use categories. Regarding to single-score indicators, ethanol presented better performance than gasoline using ReCiPe Endpoint LCIA method. Using IMPACT 2002+, Eco-indicator 99, and Ecological Scarcity 2006, higher scores are verified for ethanol, mainly due to the impacts related to particulate emissions and land use impacts.

Conclusions

Although there is a relative agreement on the results regarding equivalent environmental impact categories using different LCIA methods at midpoint level, when single-score indicators are considered, use of different LCIA methods lead to different conclusions. Single-score results also limit the interpretability at endpoint level, as a consequence of small contributions of relevant environmental impact categories weighted in a single-score indicator.     

Assessing freshwater use impacts in LCA: Part I—inventory modelling and characterisation factors for the main impact pathways

Background, aim and scope

Freshwater is a basic resource for humans; however, its link to human health is seldom related to lack of physical access to sufficient freshwater, but rather to poor distribution and access to safe water supplies. On the other hand, freshwater availability for aquatic ecosystems is often reduced due to competition with human uses, potentially leading to impacts on ecosystem quality. This paper summarises how this specific resource use can be dealt with in life cycle analysis (LCA).

Main features

The main quantifiable impact pathways linking freshwater use to the available supply are identified, leading to definition of the flows requiring quantification in the life cycle inventory (LCI).

Results

The LCI needs to distinguish between and quantify evaporative and non-evaporative uses of ‘blue’ and ‘green’ water, along with land use changes leading to changes in the availability of freshwater. Suitable indicators are suggested for the two main impact pathways [namely freshwater ecosystem impact (FEI) and freshwater depletion (FD)], and operational characterisation factors are provided for a range of countries and situations. For FEI, indicators relating current freshwater use to the available freshwater resources (with and without specific consideration of water ecosystem requirements) are suggested. For FD, the parameters required for evaluation of the commonly used abiotic depletion potentials are explored.

Discussion

An important value judgement when dealing with water use impacts is the omission or consideration of non-evaporative uses of water as impacting ecosystems. We suggest considering only evaporative uses as a default procedure, although more precautionary approaches (e.g. an ‘Egalitarian’ approach) may also include non-evaporative uses. Variation in seasonal river flows is not captured in the approach suggested for FEI, even though abstractions during droughts may have dramatic consequences for ecosystems; this has been considered beyond the scope of LCA.

Conclusions

The approach suggested here improves the representation of impacts associated with freshwater use in LCA. The information required by the approach is generally available to LCA practitioners

Recommendations and perspectives

The widespread use of the approach suggested here will require some development (and consensus) by LCI database developers. Linking the suggested midpoint indicators for FEI to a damage approach will require further analysis of the relationship between FEI indicators and ecosystem health.     

Identifying best existing practice for characterization modeling in life cycle impact assessment

Purpose

Life cycle impact assessment (LCIA) is a field of active development. The last decade has seen prolific publication of new impact assessment methods covering many different impact categories and providing characterization factors that often deviate from each other for the same substance and impact. The LCA standard ISO 14044 is rather general and unspecific in its requirements and offers little help to the LCA practitioner who needs to make a choice. With the aim to identify the best among existing characterization models and provide recommendations to the LCA practitioner, a study was performed for the Joint Research Centre of the European Commission (JRC).

Methods

Existing LCIA methods were collected and their individual characterization models identified at both midpoint and endpoint levels and supplemented with other environmental models of potential use for LCIA. No new developments of characterization models or factors were done in the project. From a total of 156 models, 91 were short listed as possible candidates for a recommendation within their impact category. Criteria were developed for analyzing the models within each impact category. The criteria addressed both scientific qualities and stakeholder acceptance. The criteria were reviewed by external experts and stakeholders and applied in a comprehensive analysis of the short-listed characterization models (the total number of criteria varied between 35 and 50 per impact category). For each impact category, the analysis concluded with identification of the best among the existing characterization models. If the identified model was of sufficient quality, it was recommended by the JRC. Analysis and recommendation process involved hearing of both scientific experts and stakeholders.

Results and recommendations

Recommendations were developed for 14 impact categories at midpoint level, and among these recommendations, three were classified as “satisfactory” while ten were “in need of some improvements” and one was so weak that it has “to be applied with caution.” For some of the impact categories, the classification of the recommended model varied with the type of substance. At endpoint level, recommendations were only found relevant for three impact categories. For the rest, the quality of the existing methods was too weak, and the methods that came out best in the analysis were classified as “interim,” i.e., not recommended by the JRC but suitable to provide an initial basis for further development.

Discussion, conclusions, and outlook

The level of characterization modeling at midpoint level has improved considerably over the last decade and now also considers important aspects like geographical differentiation and combination of midpoint and endpoint characterization, although the latter is in clear need for further development. With the realization of the potential importance of geographical differentiation comes the need for characterization models that are able to produce characterization factors that are representative for different continents and still support aggregation of impact scores over the whole life cycle. For the impact categories human toxicity and ecotoxicity, we are now able to recommend a model, but the number of chemical substances in common use is so high that there is a need to address the substance data shortage and calculate characterization factors for many new substances. Another unresolved issue is the need for quantitative information about the uncertainties that accompany the characterization factors. This is still only adequately addressed for one or two impact categories at midpoint, and this should be a focus point in future research. The dynamic character of LCIA research means that what is best practice will change quickly in time. The characterization methods presented in this paper represent what was best practice in 2008–2009.     

Enabling optimization in LCA: from “ad hoc” to “structural” LCA approach—based on a biodiesel well-to-wheel case study

Purpose

Applied life cycle assessment (LCA) studies often lead to a comparison of rather few alternatives; we call this the “ad hoc LCA approach.” This can seem surprising since applied LCAs normally cover countless options for variations and derived potentials for improvements in a product life cycle. In this paper, we will suggest an alternative approach to the ad hoc approach, which more systematically addresses the many possible variations to identify the most promising. We call it the “structural LCA approach.” The goals of this paper are (1) to provide basic guidelines for the structural approach, including an easy expansion of the LCA space; (2) to show that the structural LCA approach can be used for different types of optimization in LCA; and (3) to improve the transparency of the LCA work.

Methods

The structural approach is based on the methodology “design of experiments” (Montgomery 2005). Through a biodiesel well-to-wheel study, we demonstrate a generic approach of applying explanatory variables and corresponding impact categories within the LCA methodology. Explanatory variables are product system variables that can influence the environmental impacts from the system. Furthermore, using the structural approach enables two different possibilities for optimization: (1) single-objective optimization (SO) based on response surface methodology (Montgomery 2005) and (2) multiobjective optimization (MO) by the hypervolume estimation taboo search (HETS) method. HETS enables MO for more than two or three objectives.

Results and discussion

Using SO, the explanatory variable “use of residual straw from fields” is, by far, the explanatory variable that can contribute with the highest decrease of climate change potential. For the respiratory inorganics impact category, the most influencing explanatory variable is found to be the use of different alcohol types (bioethanol or petrochemical methanol) in biodiesel production. Using MO, we found the Pareto front based on 5 different life cycle pathways which are nondominated solutions out of 66 different analyzed solutions. Given that there is a fixed amount of resources available for the LCA practitioner, it becomes a prioritizing problem whether to apply the structural LCA approach or not. If the decision maker only has power to change a single explanatory variable, it might not be beneficial to apply the structural LCA approach. However, if the decision maker (such as decision makers at the societal level) has power to change more explanatory variables, then the structural LCA approach seems beneficial for quantifying and comparing the potentials for environmental improvement between the different explanatory variables in an LCA system and identifying the overall most promising product system configurations among the chosen PWs.

Conclusions

The implementation of the structural LCA approach and the derived use of SO and MO have been successfully achieved and demonstrated in the present paper. In addition, it is demonstrated that the structural LCA approach can lead to more transparent LCAs since the potentially most important explanatory variables which are used to model the LCAs are explicitly presented through the structural LCA approach. The suggested structural approach is a new approach to LCA and it seems to be a promising approach for searching or screening product systems for environmental optimization potentials. In the presented case, the design has been a rather simple full factorial design. More complicated problems or designs, such as fractional designs, nested designs, split plot designs, and/or unbalanced data, in the context of LCA could be investigated further using the structural approach.     

The Water Impact Index: a simplified single-indicator approach for water footprinting

Purpose

Along with climate change-related issues, improved water management is recognized as one of the major challenges to sustainability. However, there are still no commonly accepted methods for measuring sustainability of water uses, resulting in a recent proliferation of water footprint methodologies. The Water Impact Index presented in this paper aims to integrate the issues of volume, scarcity and quality into a single indicator to assess the reduction of available water for the environment induced by freshwater uses for human activities.

Methods

The Water Impact Index follows life cycle thinking principles. For each unit process, a volumetric water balance is performed; water flows crossing the boundaries between the techno-sphere and environment are multiplied by a water quality index and a water scarcity index. The methodology is illustrated on the current municipal wastewater management system of Milan (Italy). The Water Impact Index is combined with carbon footprint to introduce multi-impact thinking to decision makers. The Water Impact Index is further compared to results obtained using a set of three life cycle impact indicators related to water, from the ReCiPe life cycle impact assessment (LCIA) methodology.

Results and discussion

Onsite water use is the main contribution to the Water Impact Index for both wastewater management schemes. The release of better quality water is the main driver in favour of the scenario including a wastewater treatment plant, while the energy and chemicals consumed for the treatment increase the indirect water footprint and carbon footprint. Results obtained with the three midpoint indicators depict similar tendencies to the Water Impact Index.

Conclusions

This paper presents a simplified single-indicator approach for water footprinting, integrating volume, scarcity and quality issues, representing an initial step toward a better understanding and assessment of the environmental impacts of human activities on water resources. The wastewater treatment plant reduces the Water Impact Index of the wastewater management system. These results are consistent with the profile of the three midpoint indicators related to water from ReCiPe.     

Adapting the LCA framework to environmental assessment in land planning

Purpose

Since the implementation of the European directive (EC/2001/42) on strategic environmental assessment, an ex ante evaluation has become mandatory for plans and programs. This requirement could have significant consequences for the environment. Local authorities, who are in charge of land planning issues, must therefore conduct such assessments. However, they are faced with lack of uniform methodology. The aim of this paper is thus to propose a methodological framework for the required environmental assessment stages in land planning.

Methods

Life cycle assessment (LCA) has been identified as a promising tool to perform environmental assessment at a meso-level (i.e., territories). Yet, the standardized LCA framework has never been used for assessing the environmental impacts of a territory as such, which can be explained by the complexity that its application would involve. Four major methodological bottlenecks have been identified in this paper, i.e., (1) functional unit definition, (2) boundary selection, (3) data collecting, and (4) the refinement of the life cycle impact assessment phase in order to provide useful indicators for land planning. For each of these challenges, recommendations have been made to adapt the analytical framework of LCA.

Results and discussion

A revised framework is proposed to perform LCA of a territory. One of the major adaptations needed concerns the goal and scope definition phase. Henceforth, the association of a territory and the studied land planning scenario, defined by its geographical boundaries and its interactions with other territories, will be designated as the reference flow in LCA. Consequently, two kinds of indicators will be determined using this approach, i.e., (1) a vector of environmental impacts generated (conventional LCA) and (2) a vector of land use functions provided by the territory for different stakeholders (e.g., provision of work, recreation, culture, etc.). This revised framework has been applied to a theoretical case study in order to highlight its utility in land planning.

Conclusions

This work is a first step in the adaptation of the LCA framework to environmental assessment in land planning. We believe that this revised framework has the potential to provide relevant information in decision-making processes. Nonetheless, further work is still needed to broaden and deepen this approach (i.e., normalization of impacts and functions, coupled application with GIS, uncertainties, etc.).     

System delimitation in agricultural consequential LCA

Background, aim, and scope

When dealing with system delimitation in environmental life cycle assessment (LCA), two methodologies are typically referred to: consequential LCA and attributional LCA. The consequential approach uses marginal data and avoids co-product allocation by system expansion. The attributional approach uses average or supplier-specific data and treats co-product allocation by applying allocation factors. Agricultural LCAs typically regard local production as affected and they only include the interventions related to the harvested area. However, as changes in demand and production may affect foreign production, yields and the displacement of other crops in regions where the agricultural area is constrained, there is a need for incorporating the actual affected processes in agricultural consequential LCA. This paper presents a framework for defining system boundaries in consequential agricultural LCA. The framework is applied to an illustrative case study; LCA of increased demand for wheat in Denmark. The aim of the LCA screening is to facilitate the application of the proposed methodology. A secondary aim of the LCA screening is to illustrate that there are different ways to meet increased demand for agricultural products and that the environmental impact from these different ways vary significantly.

Materials and methods

The proposed framework mainly builds on the work of Ekvall T, Weidema BP (Int J Life Cycle Assess 9(3):pp. 161–171, 2004), agricultural statistics (FAOSTAT, FAOSTAT Agriculture Data, Food and Agriculture Organisation of the United Nations (2006), http://apps.fao.org/ (accessed June)), and agricultural outlook (FAPRI, US and world agricultural outlook, Food and Agriculture Research Institute, Iowa, 2006a). The framework and accompanying guidelines concern the suppliers affected, the achievement of increased production (area or yield), and the substitutions between crops. The framework, which is presented as a decision tree, proposes four possible systems that may be affected as a result of the increased demand of a certain crop in a certain area.

Results

The core of the proposed methodology is a decision tree, which guides the identification of affected processes in consequential agricultural LCA. The application of the methodology is illustrated with a case study presenting an LCA screening of wheat in Denmark. Different scenarios of how increased demand for wheat can be met show significant differences in emission levels as well as land use.

Discussion

The great differences in potential environmental impacts of the analysed results underpin the importance of system delimitation. The consequential approach is appointed as providing a more complete and accurate but also less precise result, while the attributional approach provides a more precise result but with inherent blind spots, i.e. a less accurate result.

Conclusions

The main features of the proposed framework and case study are: (1) an identification of significant sensitivity on results of system delimitation, and (2) a formalised way of identifying blind spots in attributional agricultural LCAs.

Recommendations and perspectives

It is recommended to include considerations on the basis of the framework presented in agricultural LCAs if relevant. This may be done either by full quantification or as qualitative identification of the most likely ways the agricultural product system will respond on changed demand. Hereby, it will be possible to make reservations to the conclusions drawn on the basis of an attributional LCA.