Rosalie van Zelm

Review of methods addressing freshwater use in life cycle inventory and impact assessment

PurposeIn recent years, several methods have been developed which propose different freshwater use inventory schemes and impact assessment characterization models considering various cause–effect chain relationships. This work reviewed a multitude of methods and indicators for freshwater use potentially applicable in life cycle assessment (LCA). This review is used as a basis to identify the key elements to build a scientific consensus for operational characterization methods for LCA.MethodsThis evaluation builds on the criteria and procedure developed within the International Reference Life Cycle Data System Handbook and has been adapted for the purpose of this project. It therefore includes (1) description of relevant cause–effect chains, (2) definition of criteria to evaluate the existing methods, (3) development of sub-criteria specific to freshwater use, and (4) description and review of existing methods addressing freshwater in LCA.Results and discussionNo single method is available which comprehensively describes all potential impacts derived from freshwater use. However, this review highlights several key findings to design a characterization method encompassing all the impact pathways of the assessment of freshwater use and consumption in life cycle assessment framework as the following: (1) in most of databases and methods, consistent freshwater balances are not reported either because output is not considered or because polluted freshwater is recalculated based on a critical dilution approach; (2) at the midpoint level, most methods are related to water scarcity index and correspond to the methodological choice of an indicator simplified in terms of the number of parameters (scarcity) and freshwater uses (freshwater consumption or freshwater withdrawal) considered. More comprehensive scarcity indices distinguish different freshwater types and functionalities. (3) At the endpoint level, several methods already exist which report results in units compatible with traditional human health and ecosystem quality damage and cover various cause–effect chains, e.g., the decrease of terrestrial biodiversity due to freshwater consumption. (4) Midpoint and endpoint indicators have various levels of spatial differentiation, i.e., generic factors with no differentiation at all, or country, watershed, and grid cell differentiation.ConclusionsExisting databases should be (1) completed with input and output freshwater flow differentiated according to water types based on its origin (surface water, groundwater, and precipitation water stored as soil moisture), (2) regionalized, and (3) if possible, characterized with a set of quality parameters. The assessment of impacts related to freshwater use is possible by assembling methods in a comprehensive methodology to characterize each use adequately.

Toward Meaningful End Points of Biodiversity in Life Cycle Assessment

Halting current rates of biodiversity loss will be a defining challenge of the 21st century. To assess the effectiveness of strategies to achieve this goal, indicators and tools are required that monitor the driving forces of biodiversity loss, the changing state of biodiversity, and evaluate the effectiveness of policy responses. Here, we review the use of indicators and approaches to model biodiversity loss in Life Cycle Assessment (LCA), a methodology used to evaluate the cradle-to-grave environmental impacts of products. We find serious conceptual shortcomings in the way models are constructed, with scale considerations largely absent. Further, there is a disproportionate focus on indicators that reflect changes in compositional aspects of biodiversity, mainly changes in species richness. Functional and structural attributes of biodiversity are largely neglected. Taxonomic and geographic coverage remains problematic, with the majority of models restricted to one or a few taxonomic groups and geographic regions. On a more general level, three of the five drivers of biodiversity loss as identified by the Millennium Ecosystem Assessment are represented in current impact categories (habitat change, climate change and pollution), while two are missing (invasive species and overexploitation). However, methods across all drivers can be greatly improved. We discuss these issues and make recommendations for future research to better reflect biodiversity loss in LCA.

Global guidance on environmental life cycle impact assessment indicators: findings of the scoping phase

Olivier Jolliet & Rolf Frischknecht & Jane Bare & Anne-Marie Boulay & Cecile Bulle & Peter Fantke & Shabbir Gheewala & Michael Hauschild & Norihiro Itsubo & Manuele Margni & Thomas E. McKone & Llorenc Mila y Canals & Leo Postuma & Valentina Prado-Lopez & Brad Ridoutt & Guido Sonnemann & Ralph K. Rosenbaum & Tom Seager & Jaap Struijs & Rosalie van Zelm & Bruce Vigon & Annie Weisbrod & with contributions of the other workshop participants

Assessing the importance of spatial variability versus model choices in life cycle impact assessment: The case of freshwater eutrophication in europe

In Life Cycle Impact Assessment (LCIA) both spatial variability and model choices may be influential. In the case of the effect model, the effect factors differ with respect to their assumption of linear/nonlinear responses to increases in environmental stressor levels, and whether or not they account for the current stressor levels in the environment. Here, we derived spatially explicit characterization factors of phosphorus emissions causing eutrophication based on three different effect models (depicted by marginal, linear, and average effect factors) and two freshwater types (lakes and streams) and we performed an analysis of variance (ANOVA) to investigate how the selection of the effect models and the freshwater types influence the impacts of phosphorus emissions to freshwater on heterotrophic species. We found that 56% of the variability of ecological impacts per unit of phosphorus emission was explained, primarily, by the difference between freshwater types and, to a lesser extent, by the difference between effect models. The remaining variability was attributed to the spatial variation between river basins, mainly due to the variability in fate factors. Our study demonstrates the particular importance of accounting for spatial variability and model choices in LCIA.

Value Choices in Life Cycle Impact Assessment of Stressors Causing Human Health Damage

This article investigates how value choices in life cycle impact assessment can influence characterization factors (CFs) for human health (expressed as disability‐adjusted life years [DALYs]). The Cultural Theory is used to define sets of value choices in the calculation of CFs, reflecting the individualist, hierarchist, and egalitarian perspectives. CFs were calculated for interventions related to the following impact categories: water scarcity, tropospheric ozone formation, particulate matter formation, human toxicity, ionizing radiation, stratospheric ozone depletion, and climate change. With the Cultural Theory as a framework, we show that individualist, hierarchist, and egalitarian perspectives can lead to CFs that vary up to six orders of magnitude. For persistent substances, the choice in time horizon explains the differences among perspectives, whereas for nonpersistent substances, the choice in age weighting and discount rate of DALY and the type of effects or exposure routes account for differences in CFs. The calculated global impact varies by two orders of magnitude, depending on the perspective selected, and derives mainly from particulate matter formation and water scarcity for the individualist perspective and from climate change for the egalitarian perspective. Our results stress the importance of dealing with value choices in life cycle impact assessment and suggest further research for analyzing the practical consequences for life cycle assessment results.

Uncertainty in msPAF‐based ecotoxicological effect factors for freshwater ecosystems in life cycle impact assessment

Abstract Ecotoxicological effect factors are part of the analysis of relative impacts by chemical contaminants on ecosystems. Uncertainty distributions, represented by the 90% confidence interval, belonging to ecotoxicological effect factors for freshwater ecosystems were determined. This study includes 869 high production volume chemicals, related to 7 nonspecific toxic modes of action (TMoAs). The ecotoxicological effect factors are divided into a TMoA-specific part and a chemical-specific part. The 90% confidence interval of the TMoA-specific part of the effect factor ranges from 23 orders of magnitude for acrylate toxicity to 2 orders of magnitude for nonpolar narcosis. The range in the TMoA-specific part of the effect factor is mainly caused by uncertainty in the spread in toxic sensitivity between species (σj). Average uncertainty in the chemical-specific part of the effect factors depends on the number of species tested and ranges on average from a factor of 5 for more than 3 species tested to a factor of about 1,000 for 2 species tested. Average uncertainty in the ecotoxicological effect factors ranges from a factor of 100 for more than 3 species tested to a factor of nearly 10,000 for 2 species tested. It is recommended that the ecotoxicological effect factor of a chemical is based on toxicity data of at least 4 species.

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.

Transformation products in the life cycle impact assessment of chemicals

The current life cycle impact assessment (LCIA) of chemicals focuses only on the fate and effects of the parent compound, neglecting the potential impact of transformation products. Here, we assess the importance of including the potential impact of transformation products in the calculation of characterization factors (CF). The developed method is applied to freshwater ecotoxicity for 15 pesticides and perchloroethylene, which are all known to have potentially persistent transformation products. The inclusion of transformation products resulted in a median increase in CF that varied from negligible to more than 5 orders of magnitude. This increase, however, can be highly uncertain, particularly due to a lack of toxicity data for transformation products and a lack of mode of action-specific data. We show in a case study that replacement of atrazine with other pesticides for application on corn results in a median impact score of 2 orders of magnitude lower when the fate and effects of only the parent compounds are included. When transformation products are included, the reduction in median impact score would likely be lower (less than 1 order of magnitude). An uncertainty analysis showed that the difference in impact scores of atrazine and the atrazine replacements was not statistically significant when only the parent chemical was considered. When transformation products were included, the uncertainty in impact scores was even greater.

Species richness–phosphorus relationships for lakes and streams worldwide

Aim We investigated the patterns of autotrophic and heterotrophic relative species richness along a total phosphorus (TP) concentration gradient. The relative species richness–TP relationships were calculated separately for four different regions [(sub)tropical, xeric, temperate and cold] and two types of water bodies (lakes and streams). Location Global Methods Using data from peer-reviewed articles reporting the occurrence of freshwater species at specific TP concentrations, we determined the species richness along a TP gradient. Using log-logistic regressions, we then estimated the TP concentration at which the potential decrease of relative species richness (RSR) equals 0.5 and the slope at which the decrease occurs (β). The RSR is given as the ratio of species richness to maximized species richness along a TP gradient. Results The RSR of streams generally decreased more rapidly than that of lakes with increasing P, as illustrated by the steeper slope of the log-logistic functions for streams (βlakes < βstreams). Although there was no consistent trend between autotrophs and heterotrophs in the different regions, we found that the TP concentration at which the RSR equals 0.5 was lower in cold regions (0.04–0.22 mg P/L) than in warmer regions (0.28–1.29 mg P/L). Main Conclusions The log-logistic relationships between RSR and TP concentration vary considerably among regions of the world, between freshwater types (lakes and streams) and between species groups (autotrophs and heterotrophs). This variability may be attributed to differences between the two freshwater types in respect to their species groups and evolutionary patterns, nutrient demand, biogeochemical and hydrological processes. We were not able to derive log-logistic regressions for all combinations of freshwater type or species type and region [e.g. (sub)tropical lakes]. For other areas, our results can be used to assess the potential impact of phosphorus eutrophication on freshwater biota.

Quantifying the Trade-off between Parameter and Model Structure Uncertainty in Life Cycle Impact Assessment

To enhance the use of quantitative uncertainty assessments in life cycle impact assessment practice, we suggest to quantify the trade-off between parameter uncertainty, i.e. any uncertainty associated with data and methods used to quantify the model parameters, and model structure uncertainty, i.e. the uncertainty about the relations and mechanisms being studied. In this paper we show the trade-off between the two types of uncertainty in a case of maize production with a focus on freshwater ecotoxicity due to pesticide application in The Netherlands. Parameter uncertainty in pesticide emissions, chemical-specific data, effect and damage data, and fractions of metabolite formation of degradation products was statistically quantified via probabilistic simulation, i.e. Monte Carlo simulation. Model structure uncertainties regarding the concentration-response model to be included, the selection of the damage model, and the inclusion of pesticide transformation products were assessed via discrete choice analysis. We conclude that to arrive at a minimum level of overall uncertainty the linear concentration-response model is preferable, while the transformation products may be excluded. Selecting the damage model has a relatively low influence on the overall uncertainty. Our study shows that quantifying the trade-off between different types of uncertainty can help to identify optimal model complexity from an uncertainty point of view.