Ralph K. Rosenbaum

Land use impacts on biodiversity in LCA: proposal of characterization factors based on functional diversity

PurposeThe focus of land use modeling in life cycle impact assessment has been mainly on taxonomic measures of biodiversity, namely species richness (SR). However, increasing availability of trait data for species has led to the use of functional diversity (FD) as a promising metric to reflect the distinctiveness of species; this paper proposes the use of an FD index to calculate characterization factors (CFs) for land use impacts. Furthermore, we compare the results of the CFs to current practice and assess the increase in complexity introduced by the use of the new indicator.MethodsThe model proposed is based on data compiled by previous regional meta-analysis on SR and FD, in different land use types in the Americas. The taxonomic groups included were mammals, birds, and plants. Within each study, calculated values for FD for different land use types were compared with the natural or close-to-natural state, taken as the reference situation. FD values among different land uses were standardized, and CFs were calculated. The final results were then analyzed and compared by analysis of variance and post hoc tests. A sensitivity analysis was also applied to verify the influence on the choice of the reference state.Results and discussionThe results show that significant differences exist between CFs for SR and FD metrics. Across all taxa, CFs differ significantly between land use types. The results support the use of CF for FD, as a complement to current practice. Distinct CFs should be applied for at least six groups of land use categories. The choice of reference land use type did not significantly alter the results but can be a source of variability. A sensitivity analysis evaluating the impact of alternate land use types as reference types found only few significant changes on the results.Conclusions and recommendationsGiven the results, we believe the use of CFs based on FD can help on the establishment of possible links between species loss and key ecosystem functions, i.e., on the association between the midpoint indicator (e.g., biodiversity loss) and the damage caused to ecosystem quality, in terms of functions lost. Basing CFs on FD is not without challenges. Such indices are data hungry (requiring species composition and traits) require more complex calculations than current common practice, including decisions on the choice of a method to calculate FD and the selection of traits.

Updated US and Canadian normalization factors for TRACI 2.1

When LCA practitioners perform LCAs, the interpretation of the results can be difficult without a reference point to benchmark the results. Hence, normalization factors are important for relating results to a common reference. The main purpose of this paper was to update the normalization factors for the US and US-Canadian regions. The normalization factors were used for highlighting the most contributing substances, thereby enabling practitioners to put more focus on important substances, when compiling the inventory, as well as providing them with normalization factors reflecting the actual situation. Normalization factors were calculated using characterization factors from the TRACI 2.1 LCIA model. The inventory was based on US databases on emissions of substances. The Canadian inventory was based on a previous inventory with 2005 as reference, in this inventory the most significant substances were updated to 2008 data. The results showed that impact categories were generally dominated by a small number of substances. The contribution analysis showed that the reporting of substance classes was highly significant for the environmental impacts, although in reality, these substances are nonspecific in composition, so the characterization factors which were selected to represent these categories may be significantly different from the actual identity of these aggregates. Furthermore the contribution highlighted the issue of carefully examining the effects of metals, even though the toxicity based categories have only interim characterization factors calculated with USEtox. A need for improved understanding of the wide range of uncertainties incorporated into studies with reported substance classes was indentified. This was especially important since aggregated substance classes are often used in LCA modeling when information on the particular substance is missing. Given the dominance of metals to the human and ecotoxicity categories, it is imperative to refine the CFs within USEtox. Some of the results within this paper indicate that soil emissions of metals are significantly higher than we expect in actuality.

Development of normalization factors for Canada and the United States and comparison with European factors

In Life Cycle Assessment (LCA), normalization calculates the magnitude of an impact (midpoint or endpoint) relative to the total effect of a given reference. The goal of this work is to calculate normalization factors for Canada and the US and to compare them with existing European normalization factors. The differences between geographical areas were highlighted by identifying and comparing the main contributors to a given impact category in Canada, the US and Europe. This comparison verified that the main contributors in Europe and in the US are also present in the Canadian inventory. It also showed that normalized profiles are highly dependent on the selected reference due to differences in the industrial and economic activities. To meet practitioners needs, Canadian normalization factors have been calculated using the characterization factors from LUCAS (Canadian), IMPACT 2002+ (European), and TRACI (US) respectively. The main sources of uncertainty related to Canadian NFs are data gaps (pesticides, metals) and aggregated data (metals, VOC), but the uncertainty related to CFs generally remains unknown. A final discussion is proposed based on the comparison of resource extraction and resource consumption and raises the question of the legitimacy of defining a country by its geographical borders.

The Glasgow consensus on the delineation between pesticide emission inventory and impact assessment for LCA

PurposePesticides are applied to agricultural fields to optimise crop yield and their global use is substantial. Their consideration in life cycle assessment (LCA) is affected by important inconsistencies between the emission inventory and impact assessment phases of LCA. A clear definition of the delineation between the product system model (life cycle inventory—LCI, technosphere) and the natural environment (life cycle impact assessment—LCIA, ecosphere) is missing and could be established via consensus building.MethodsA workshop held in 2013 in Glasgow, UK, had the goal of establishing consensus and creating clear guidelines in the following topics: (1) boundary between emission inventory and impact characterisation model, (2) spatial dimensions and the time periods assumed for the application of substances to open agricultural fields or in greenhouses and (3) emissions to the natural environment and their potential impacts. More than 30 specialists in agrifood LCI, LCIA, risk assessment and ecotoxicology, representing industry, government and academia from 15 countries and four continents, met to discuss and reach consensus. The resulting guidelines target LCA practitioners, data (base) and characterisation method developers, and decision makers.Results and discussionThe focus was on defining a clear interface between LCI and LCIA, capable of supporting any goal and scope requirements while avoiding double counting or exclusion of important emission flows/impacts. Consensus was reached accordingly on distinct sets of recommendations for LCI and LCIA, respectively, recommending, for example, that buffer zones should be considered as part of the crop production system and the change in yield be considered. While the spatial dimensions of the field were not fixed, the temporal boundary between dynamic LCI fate modelling and steady-state LCIA fate modelling needs to be defined.Conclusions and recommendationsFor pesticide application, the inventory should report pesticide identification, crop, mass applied per active ingredient, application method or formulation type, presence of buffer zones, location/country, application time before harvest and crop growth stage during application, adherence with Good Agricultural Practice, and whether the field is considered part of the technosphere or the ecosphere. Additionally, emission fractions to environmental media on-field and off-field should be reported. For LCIA, the directly concerned impact categories and a list of relevant fate and exposure processes were identified. Next steps were identified: (1) establishing default emission fractions to environmental media for integration into LCI databases and (2) interaction among impact model developers to extend current methods with new elements/processes mentioned in the recommendations.

Analytical Propagation of Uncertainty in Life Cycle Assessment Using Matrix Formulation

Inventory data and characterization factors in life cycle assessment (LCA) contain considerable uncertainty. The most common method of parameter uncertainty propagation to the impact scores is Monte Carlo simulation, which remains a resource‐intensive option - probably one of the reasons why uncertainty assessment is not a regular step in LCA. An analytical approach based on Taylor series expansion constitutes an effective means to overcome the drawbacks of the Monte Carlo method. This project aimed to test the approach on a real case study, and the resulting analytical uncertainty was compared with Monte Carlo results. The sensitivity and contribution of input parameters to output uncertainty were also analytically calculated. This article outlines an uncertainty analysis of the comparison between two case study scenarios. We conclude that the analytical method provides a good approximation of the output uncertainty. Moreover, the sensitivity analysis reveals that the uncertainty of the most sensitive input parameters was not initially considered in the case study. The uncertainty analysis of the comparison of two scenarios is a useful means of highlighting the effects of correlation on uncertainty calculation. This article shows the importance of the analytical method in uncertainty calculation, which could lead to a more complete uncertainty analysis in LCA practice.

Using the Lashof Accounting Methodology to Assess Carbon Mitigation Projects with Life Cycle Assessment: Ethanol Biofuel as a Case Study

As governments elaborate strategies to counter climate change, there is a need to compare the different options available on an environmental basis. This study proposes a life cycle assessment framework integrating the Lashof accounting methodology, which enables the assessment and comparison of different carbon mitigation projects (e.g., biofuel use, a sequestering plant, an afforestation project). The Lashof accounting methodology is chosen amid other methods of greenhouse gas (GHG) emission characterization for its relative simplicity and capability to characterize all types of carbon mitigation projects. Using the unit of megagram-year (Mg-year), which accounts for the mass of GHGs in the atmosphere multiplied by the time it stays there, the methodology calculates the cumulative radiative forcing caused by GHG emission within a predetermined time frame. Basically, the developed framework uses the Mg-year as a functional unit and isolates impacts related to the climate mitigation function with system expansion. The proposed framework is demonstrated with a case study of tree ethanol pathways (maize, sugarcane, and willow). The study shows that carbon mitigation assessment through life cycle assessment is possible and that it could be a useful tool for decision makers, as it can compare different projects regardless of their original context. The case study reveals that system expansion, as well as each carbon mitigation projects efficiency at reducing carbon emissions, are critical factors that have a significant impact on the results. Also, the framework proves to be useful for treating land-use change emissions, as they are considered through the functional unit.

Addressing bystander exposure to agricultural pesticides in life cycle impact assessment.

Residents living near agricultural fields may be exposed to pesticides drifting from the fields after application to different field crops. To address this currently missing exposure pathway in life cycle assessment (LCA), we developed a modeling framework for quantifying exposure of bystanders to pesticide spray drift from agricultural fields. Our framework consists of three parts addressing: (1) loss of pesticides from an agricultural field via spray drift; (2) environmental fate of pesticide in air outside of the treated field; and (3) exposure of bystanders to pesticides via inhalation. A comparison with measured data in a case study on pesticides applied to potato fields shows that our model gives good predictions of pesticide air concentrations. We compared our bystander exposure estimates with pathways currently included in LCA, namely aggregated inhalation and ingestion exposure mediated via the environment for the general population, and general population exposure via ingestion of pesticide residues in consumed food crops. The results show that exposure of bystanders is limited relative to total population exposure from ingestion of pesticide residues in crops, but that the exposure magnitude of individual bystanders can be substantially larger than the exposure of populations not living in the proximity to agricultural fields. Our framework for assessing bystander exposure to pesticide applications closes a relevant gap in the exposure assessment included in LCA for agricultural pesticides. This inclusion aids decision-making based on LCA as previously restricted knowledge about exposure of bystanders can now be taken into account.

Addressing water needs of freshwater ecosystems in life cycle impact assessment of water consumption: state of the art and applicability of ecohydrological approaches to ecosystem quality characterization

PurposeIn recent history, human development overbalanced towards economic growth has often been accompanied by the degradation and reduction of freshwater resources at the expense of freshwater dependent ecosystems. For their subsistence and correct functioning, understanding environmental water requirements (EWR) represents an area of great interest for life cycle impact assessment (LCIA) and it has been only marginally explored. The aim of this paper is to investigate how this concept has evolved in ecological and hydrological literature and how it can be better integrated in LCIA, to identify potential options for improvement of LCIA indicators in the short, mid and long term.MethodsTo address the limitations of existing LCIA approaches in modelling EWR, four families of EWR methods have been reviewed, namely hydrological, hydraulic, habitat simulation and holistic methods. Based on existing scientific literature and their broad application, 24 methods have been selected and their suitability to be adopted in LCIA has been evaluated against nine criteria, with regard to data management issues, accuracy, scientific robustness, and potential for future development. A semi-quantitative performance score has been subsequently assigned for each criterion, showing the main strengths and weaknesses of selected methods.Results and discussionThe underlying rationale of the chosen approaches is markedly different, likewise the input information needed and results applicability. Hydrological methods are well suited for the development of global models and they are the only ones currently considered in LCIA, although their applicability remains limited to water stress indicators. Habitat modelling is identified as an essential step for the development of mechanistic LCIA models and endpoint indicators. In this respect, hydraulic, habitat simulation and holistic methods are fit for the purpose. However, habitat simulation methods represent the best compromise between scientific robustness and applicability in LCIA. For this reason, a conceptual framework for the development of habitat-based characterization factors has been proposed. Among the evaluated habitat simulation methods, ESTIMHAB showed the best performance and was the method retained for the development of an LCIA model that will assess the consequences of water consumption on stream ecosystems.ConclusionsThis study identifies the advantages of specific modelling approaches for the assessment of water requirements for ecosystems. Selected methods could support the development of LCIA models at different levels. In the short-term for improving environmental relevance of water stress indicators, and in the mid/long-term to build up midpoint habitat indicators relating water needs of ecosystems with new endpoint metrics.

Developing characterisation factors for land fragmentation impacts on biodiversity in LCA: key learnings from a sugarcane case study

PurposeHabitat change was identified by the Millennium Ecosystem Assessment as the main direct driver of biodiversity loss. However, while habitat loss is already implemented in Life Cycle Impact Assessment (LCIA) methods, the additional impact on biodiversity due to habitat fragmentation is not assessed yet. Thus, the goal of this study was to include fragmentation effects from land occupation and transformation at both midpoint and endpoint levels in LCIA.MethodsOne promising metric, combining the landscape spatial configuration with species characteristics, is the metapopulation capacity λ, which can be used to rank landscapes in terms of their capacity to support viable populations spatially structured. A methodology to derive worldwide regionalised fragmentation indexes based on λ was used and combined with the Species Fragmented-Area Relationship (SFAR), which relies on λ to assess a species loss due to fragmentation. We adapted both developments to assess fragmentation impacts due to land occupation and transformation at both midpoint and endpoint levels in LCIA. An application to sugarcane production occurring in different geographical areas, more or less sensitive to land fragmentation, was performed.Results and discussionThe comparison to other existing LCIA indicators highlighted its great potential for complementing current assessments through fragmentation effect inclusion. Last, both models were discussed through the evaluation grid used by the UNEP-SETAC land use LCIA working group for biodiversity impact assessment models.ConclusionsMidpoint and endpoint characterisation factors were successfully developed to include the impacts of habitat fragmentation on species in LCIA. For now, they are provided for bird species in all forest ecoregions belonging to the biodiversity hotspots. Further work is required to develop characterisation factors for all taxa and all terrestrial ecoregions.

The issue of considering water quality in life cycle assessment of water use

PurposeAvailable water-use impact assessment methods provide insight into the potential impacts of water use. As water-use impact assessment models develop, the amount of inventory information required increases. Among the parameters needed, water quality is identified as essential since water quality can also influence availability to meet specific water users’ needs. It was argued that these users could be deprived and suffer consequences. However, data on water quality may be difficult to gather and the related impact pathways may entail risks of double counting with emission characterization models. This paper answers to which extent water quality must be considered in water-use impact assessment.MethodsThe role and the necessity of water quality information are discussed along the cause-effect chain of three water-use interventions: water consumption (WU1), water degradation (WU2), and water quality improvement (WU3). Each intervention is individually explored and put in perspective with the human health, ecosystem quality, and natural resources areas of protection (AoPs).Results and discussionOur findings suggest that, for WU1, the quality of input water elementary flow might be useful to know the pressure on the resource and the affected users, but alternative methods that avoid the need for this scarce information can be built. WU1 (including quality information) and WU2 are currently assessed by linking water users to water functionality via water quality, which may be misleading in areas unable to compensate for lacking water of a certain quality. In these areas, low-quality water may still be consumed even if it does not fulfill a quality standard. Thus, WU2 would rather lead to toxic impacts instead of to water deprivation impacts since this latter pathway assumes that polluted water below the quality standard will no longer be used. Hence, water deprivation impacts should only focus on WU1 to avoid double counting with emission characterization models. For WU3, no LCA approach exists to meaningfully quantify its environmental benefits, but an indicator for water as a natural resource may be a solution.ConclusionsThis study improves the understanding of the role of water quality information in water-use impact assessment and brings more consistency between existing (and future) models. Further research is required to better understand the positive effects induced by water quality improvement and the effects on freshwater resources themselves. More generally, a framework is required to identify how freshwater resources can be defined as an entity to protect within the AoP natural resource.