Land use and biodiversity indicators for life cycle impact assessment

Background  The primary purpose of environmental assessment is to protect biological systems. Data collected over the last several decades indicates that the greatest impacts on biological resources derive from physical changes in land use. However, to date there is no consensus on indicators of land use that could be applicable worldwide at all scales. This has hampered the assessment of land use in the context of LCA. Objectives  The Institute for Environmental Research and Education and its partner Defenders of Wildlife have begun an effort to develop the necessary consensus. Methods  In July 2000, they held a workshop attended by a diverse group of interested parties and experts to develop a preliminary list of life cycle indicators for land use impacts. Results  Their preliminary list of impact indicators includes: protection of priority habitats/species; soil characteristics: soil health; proximity to & protection of high priority vegetative communities; interface between water and terrestrial habitats/buffer zones; assimilative capacity of water and land; hydrological function; percent coverage of invasive species within protected areas; road density; percent native-dominated vegetation; restoration of native vegetation; adoption of Best Management Practices linked to biodiversity objectives; distribution (patchiness; evenness, etc.); and connectivity of native habitat. Conclusion  The list of indicators conforms well to other efforts in developing indicators. There appears to be convergence among experts in the field and in related fields on the appropriate things to measure. Future Prospects  These indicators are currently being tested in the United States. Further workshops and testing is planned towards developing internationally recognized indicators for land use.     

Comparison of two equivalency factor approaches with simplified risk assessment for lcia of toxicity impact potential

Three approaches recommended for characterization of toxicity impact potential in a life cycle impact assessment (LCIA) are tested on a case study and compared. The two equivalency factor methods are the Persistence, Bioaccumulation, and Toxicity (PBT) method and the Multimedia Fate Modeling (MFM) method using a Mackay Level III model with state-specific environmental data. The simplified risk assessment (SRA) method involved dispersion modeling using site-specific environmental data. The life cycle inventory information evaluated by all three methods was limited to manufacturing of the RDX-based explosive in Kingsport, Tennessee. The effort to collect site-specific environmental data and conduct air dispersion modeling for the SRA method required about 24 times more effort than the PBT method and about 4 times more effort than the MFM method. Direct comparison of impact potential scores for the three approaches were limited to inhalation toxicity scores for nine air pollutants modeled by SRA. Correlations were made on the rank order of the impact potential scores for the nine air emissions evaluated for all three LCIA methods. Although the number of chemicals compared is very limited, the best correlation coefficient (0.96) was between the rank orders for the MFM and the SRA methods. The minimal effort and reduced accuracy of the PBT approach make it best suited for screening large numbers of chemicals for further evaluation of the highest ranked chemicals. The intermediate effort and reasonable accuracy (includes transfers to other media) of the MFM approach make it well suited for LCIAs involving comparative assertions or governmental policy decisions. The maximum effort and assumption of highest accuracy make the SRA approach suitable only after limiting the locations of interest to a few sites by screening with the other two approaches.     

Generic spatial classes for human health impacts, Part I:

A new method for the spatially differentiated assessment of impacts of airborne pollutants on human health is presented. It is applicable to primary pollutants with linear exposure response functions. This includes the most important primary air pollutants from transportation and energy generation. The article looks at the spatial differentiation of impacts due to emission height and the local population density distribution around the emission site, as has been predicted using a Gaussian plume model. The differentiation due to population density is captured by way of five generic spatial classes: large cities in agglomerations, highly densified districts in agglomerations, cities in urbanized regions, country average districts, and low density rural districts in rural regions. Average impacts are calculated for each class. The method is simple enough to be applied to a large number of emissions within Life Cycle Assessments. It was used to calculate site-dependent exposure efficiencies for a variety of primary pollutants emitted at different heights. For traffic emissions of pollutants with short atmospheric residence times, the exposure efficiencies vary by a factor of 5 across Germany and by a factor of 75 across Europe. This differentiation due to population density decreases significantly with an increasing atmospheric residence time of the pollutants and with an increasing emission height.     

Uncertainty calculation in life cycle assessments

Goal and Background  Uncertainty is commonly not taken into account in LCA studies, which downgrades their usability for decision support. One often stated reason is a lack of method. The aim of this paper is to develop a method for calculating the uncertainty propagation in LCAs in a fast and reliable manner. Approach  The method is developed in a model that reflects the calculation of an LCA. For calculating the uncertainty, the model combines approximation formulas and Monte Carlo Simulation. It is based on virtual data that distinguishes true values and random errors or uncertainty, and that hence allows one to compare the performance of error propagation formulas and simulation results. The model is developed for a linear chain of processes, but extensions for covering also branched and looped product systems are made and described. Results  The paper proposes a combined use of approximation formulas and Monte Carlo simulation for calculating uncertainty in LCAs, developed primarily for the sequential approach. During the calculation, a parameter observation controls the performance of the approximation formulas. Quantitative threshold values are given in the paper. The combination thus transcends drawbacks of simulation and approximation. Conclusions and Outlook  The uncertainty question is a true jigsaw puzzle for LCAs and the method presented in this paper may serve as one piece in solving it. It may thus foster a sound use of uncertainty assessment in LCAs. Analysing a proper management of the input uncertainty, taking into account suitable sampling and estimation techniques; using the approach for real case studies, implementing it in LCA software for automatically applying the proposed combined uncertainty model and, on the other hand, investigating about how people do decide, and should decide, when their decision relies on explicitly uncertain LCA outcomes-these all are neighbouring puzzle pieces inviting to further work.     

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.     

Implementing a Dynamic Life Cycle Assessment Methodology with a Case Study on Domestic Hot Water Production

This work contributes to the development of a dynamic life cycle assessment (DLCA) methodology by providing a methodological framework to link a dynamic system modeling method with a time‐dependent impact assessment method. This three‐step methodology starts by modeling systems where flows are described by temporal distributions. Then, a temporally differentiated life cycle inventory (TDLCI) is calculated to present the environmental exchanges through time. Finally, time‐dependent characterization factors are applied to the TDLCI to evaluate climate‐change impacts through time. The implementation of this new framework is illustrated by comparing systems producing domestic hot water (DHW) over an 80‐year period. Electricity is used to heat water in the first system, whereas the second system uses a combination of solar energy and gas to heat an equivalent amount of DHW at the same temperature. This comparison shows that using a different temporal precision (i.e., monthly vs. annual) to describe process flows can reverse conclusions regarding which case has the best environmental performance. Results also show that considering the timing of greenhouse gas (GHG) emissions reduces the absolute values of carbon footprint in the short‐term when compared with results from the static life cycle assessment. This pragmatic framework for the implementation of time in DLCA studies is proposed to help in the development of the methodology. It is not yet a fully operational scheme, and efforts are still required before DLCA can become state of practice.     

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.     

A survey of unresolved problems in life cycle assessment

Background, aims, and scope  Life cycle assessment (LCA) stands as the pre-eminent tool for estimating environmental effects caused by products and processes from ‘cradle to grave’ or ‘cradle to cradle.’ It exists in multiple forms, claims a growing list of practitioners and remains a focus of continuing research. Despite its popularity and codification by organizations such as the International Organization for Standardization and the Society of Environmental Toxicology and Chemistry, life cycle assessment is a tool in need of improvement. Multiple authors have written about its individual problems, but a unified treatment of the subject is lacking. The following literature survey gathers and explains issues, problems and problematic decisions currently limiting LCA’s impact assessment and interpretation phases. Main features  The review identifies 15 major problem areas and organizes them by the LCA phases in which each appears. This part of the review focuses on the latter eight problems. It is meant as a concise summary for practitioners interested in methodological limitations which might degrade the accuracy of their assessments. For new researchers, it provides an overview of pertinent problem areas toward which they might wish to direct their research efforts. Having identified and discussed LCA’s major problems, closing sections highlight the most critical problems and briefly propose research agendas meant to improve them. Results and discussion  Multiple problems occur in each of LCA’s four phases and reduce the accuracy of this tool. Considering problem severity and the adequacy of current solutions, six of the 15 discussed problems are of paramount importance. In LCA’s latter two phases, spatial variation and local environmental uniqueness are critical problems requiring particular attention. Data availability and quality are identified as critical problems affecting all four phases. Conclusions and recommendations  Observing that significant efforts by multiple researchers have not resulted in a single, agreed upon approach for the first three critical problems, development of LCA archetypes for functional unit definition, boundary selection and allocation is proposed. Further development of spatially explicit, dynamic modeling is recommended to ameliorate the problems of spatial variation and local environmental uniqueness. Finally, this paper echoes calls for peer-reviewed, standardized LCA inventory and impact databases, and it suggests the development of model bases. Both of these efforts would help alleviate persistent problems with data availability and quality.

Gone…but not away—addressing the problem of long-term impacts from landfills in LCA

Background, aim and scope  Land filling of materials with content of toxic metals or highly persistent organic compounds has posed a problem for life cycle assessment (LCA) practitioners for many years. The slow release from the landfill entails a dilution in time, which is dramatic compared to other emissions occurring in the life cycle, and with its focus on the emitted mass, LCA is poorly equipped to handle this difference. As a consequence, the long-term emissions from landfills occurring over thousands of years are often disregarded, which is unacceptable to many stakeholders considering the quantities of toxic substances that can be present. On the other hand, inclusion of all future emissions (over thousands of years) in the inventories potentially dominates all other impacts from the product system. The paper aims to present a pragmatic approach to address this dilemma. Materials and methods  Two new impact categories are introduced representing the stored ecotoxicity and stored human toxicity of the contaminants remaining in the landfill after a ‘foreseeable’ time period of 100 years. The impact scores are calculated using the normal characterisation factors for the ecotoxicity and human toxicity impact categories, and they represent the toxicity potentials of what remains in the landfill after 100 years (hence the term ‘stored’ (eco)toxicity). Normalisation references are developed for the stored toxicity categories based on Danish figures to support comparison with indicator scores for the conventional environmental impact categories. In contrast to the scores for the conventional impact categories, it is uncertain to what extent the stored toxicity scores represent emissions, which will occur at all. Guidance is given on how to reflect this uncertainty in the weighting and interpretation of the scores. Results and discussion  In landfills and road constructions used to deposit residuals from incinerators, less than 1% of the content of metals is leached within the first 100 years. The stored toxicity scores are therefore much higher than the conventional impact scores that represent the actual emissions. Several examples are given illustrating the use and potential significance of the stored toxicity categories. Conclusions and perspectives  The methodology to calculate stored human and ecotoxicity is a simple and pragmatic approach to address LCA’s problem of treating the slow long-term emissions at very low concentrations appropriately. The problem resides in the inventory analysis and the impact assessment, and the methodology circumvents the problem by converting it into a weighting and interpretation issue accommodating the value-based discussion of how to weight potential effects in the far future. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.

Comparison of Three Different LCIA Methods: EDIP97, CML2001 and Eco-indicator 99

Goal, Scope and Background

A number of impact assessment methodologies are available to the LCA practitioner. They differ, and often there is not one obvious choice among them. The question therefore naturally arises: ‘Does it make any difference to my conclusions which method I choose?’ To investigate this issue, a comparison is performed of three frequently applied life cycle impact assessment methods.

Methods

The three life cycle impact assessment methods EDIP97 [1], CML2001 [2] and Eco-indicator 99 [3] are compared on their performance through application to the same life cycle inventory from a study of a water-based UV-lacquer. EDIP97 and CML2001 are both midpoint approaches and hence quite similar in their scope and structure, and this allows a comparison during both characterisation and normalisation. The third impact assessment method Eco-indicator 99 is an endpoint method and different in scope and structure from the other two. A detailed comparison can not be done but a comparative analysis of the main contributors to the Eco-indicator 99 results and the weighted and aggregated EDIP97 results is performed.

Results and Discussion

Following a translation into common units of the EDIP97 and CML2001 output, differences up to two orders of magnitude are found for some of the indicator results for the impact categories describing toxicity to humans and ecosystems, and there is little similarity in the patterns of major contributors among the two methods. For human toxicity the CML2001 score is dominated by contribution from metals while the EDIP97 score is caused by a solvent and nitrogen oxides. For aquatic ecotoxicity, metals are the main contributors for both methods but while it is vanadium for CML2001, it is strontium for EDIP97. After normalisation, the differences are reduced but still considerable. For the other impact categories, the two methods show only minor differences. The comparison of the main contributors to the Eco-indicator 99 results and the weighted and aggregated EDIP97 results identifies nitrogen oxides as the main contributor for both methods. It is, however, much more dominant for Eco-indicator 99 while the EDIP97 score represents important contributions from a number of different substances, and furthermore, the analysis reveals that the aggregated scores for the two methods come from different impacts. It is thus difficult to extend the findings for these two methods to other inventories.

Conclusion

For EDIP97 and CML2001, it mainly matters which method is used if the chemical impacts on human health and ecosystem health are important for the study. For the other impact categories, the differences are minor for these two methodologies. For EDIP97 and Eco-indicator 99, the patterns of most important contributors to the weighted and aggregated impact scores are rather different, and considering the known differences in the underlying framework and models, the results of the two methods may well go in opposite directions for some inventories even if the conclusion is the same for the inventory studied in this paper.

Recommendations and Oudook

Particularly for the impact categories representing toxic impacts from chemicals, the study demonstrates the need for more a detailed analysis of the causes underlying the big differences revealed between the methods.