Toward harmonizing ecotoxicity characterization in life cycle impact assessment.

Ecosystem quality is an important area of protection in life cycle impact assessment (LCIA). Chemical pollution has adverse impacts on ecosystems on a global scale. To improve methods for assessing ecosystem impacts, the Life Cycle Initiative hosted by the United Nations Environment Programme established a task force to evaluate the state-of-the-science in modeling chemical exposure of organisms and the resulting ecotoxicological effects for use in LCIA. The outcome of the task force work will be global guidance and harmonization by recommending changes to the existing practice of exposure and effect modeling in ecotoxicity characterization. These changes will reflect the current science and ensure the stability of recommended practice. Recommendations must work within the needs of LCIA in terms of 1) operating on information from any inventory reporting chemical emissions with limited spatiotemporal information, 2) applying best estimates rather than conservative assumptions to ensure unbiased comparison with results for other impact categories, and 3) yielding results that are additive across substances and life cycle stages and that will allow a quantitative expression of damage to the exposed ecosystem. We describe the current framework and discuss research questions identified in a roadmap. Primary research questions relate to the approach toward ecotoxicological effect assessment, the need to clarify the method's scope and interpretation of its results, the need to consider additional environmental compartments and impact pathways, and the relevance of effect metrics other than the currently applied geometric mean of toxicity effect data across species. Because they often dominate ecotoxicity results in LCIA, we give metals a special focus, including consideration of their possible essentiality and changes in environmental bioavailability. We conclude with a summary of key questions along with preliminary recommendations to address them as well as open questions that require additional research efforts. Environ Toxicol Chem 2018;37:2955-2971. © 2018 SETAC.

Developing Product Environmental Footprint Category Rules (PEFCR) for shampoos: The basis for comparable life cycle assessment.

In 2013, the European Commission launched the Environmental Footprint Rules pilot phase. This initiative aims at setting specific rules for life cycle assessment (LCA: raw material sourcing, production, logistics, use, and disposal phase) studies within 1 product category, called product environmental footprint category rules (PEFCR), and for organizations, called organizational environmental footprint sector rules (OEFSR). Such specific rules for measuring environmental performance throughout the life cycle should facilitate the comparability between LCA studies and provide principles for communicating environmental performance, such as transparency, reliability, completeness, and clarity. Cosmetics Europe, the association representing the cosmetics industry in the European Union, completed a voluntary study into the development of PEFCR for shampoo, generally following the guidelines and methodology developed by the European Commission for its own pilot projects. The study assessed the feasibility and relevance of establishing PEFCR for shampoo. Specifically, the study defines a large number of modeling assumptions and default values relevant for shampoo (e.g., for the functional unit, the system boundaries, default transport distances, rinsing water volumes, temperature differences, life cycle inventory data sources) that can be modified as appropriate, according to the specificities of individual products, manufacturing companies, and countries. The results of the study may be used to support internal decision making (e.g., to identify "hotspots" with high environmental impact and opportunities for improvement) or to meet information requests from commercial partners, consumers, media, or authorities on product environmental characteristics. In addition, the shampoo study also highlighted many of the challenges and limitations of the current product environmental footprint (PEF) methodology, namely its complexity and resource intensiveness. It highlighted 2 areas where improvements are much needed: (1) data quality and availability, and (2) impact assessment methodologies and robustness. Many of the findings are applicable to other rinse-off cosmetic products, such as shower gels, liquid soaps, bath products, and hair conditioners. Integr Environ Assess Manag 2018;14:649-659. © 2018 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Review of the partitioning of chemicals into different plastics: Consequences for the risk assessment of marine plastic debris.

Marine plastic debris are found worldwide in oceans and coastal areas. They degrade only slowly and contain chemicals added during manufacture or absorbed from the seawater. Therefore, they can pose a long-lasting contaminant source and potentially transfer chemicals to marine organisms when ingested. In order to assess their risk, the contaminant concentration in the plastics needs to be estimated and differences understood. We collected from literature plastic water partition coefficients of various organic chemicals for seven plastic types: polydimethylsiloxane (PDMS), high-density, low-density and ultra-high molecular weight polyethylene (LDPE, HDPE, UHMWPE), polystyrene (PS), polypropylene (PP), and polyvinyl chloride (PVC). Most data was available for PDMS (1060) and LDPE (220), but much less for the remaining plastics (73). Where possible, regression models were developed and the partitioning was compared between the different plastic types. The partitioning of chemicals follows the order of LDPE≈HDPE≥PP>PVC≈PS. Data describing the impact of weathering are urgently needed.

Spatial variability versus parameter uncertainty in freshwater fate and exposure factors of chemicals.

We compared the influence of spatial variability in environmental characteristics and the uncertainty in measured substance properties of seven chemicals on freshwater fate factors (FFs), representing the residence time in the freshwater environment, and on exposure factors (XFs), representing the dissolved fraction of a chemical. The influence of spatial variability was quantified using the SimpleBox model in which Europe was divided in 100 × 100 km regions, nested in a regional (300 × 300 km) and supra-regional (500 × 500 km) scale. Uncertainty in substance properties was quantified by means of probabilistic modelling. Spatial variability and parameter uncertainty were expressed by the ratio k of the 95%ile and 5%ile of the FF and XF. Our analysis shows that spatial variability ranges in FFs of persistent chemicals that partition predominantly into one environmental compartment was up to 2 orders of magnitude larger compared to uncertainty. For the other (less persistent) chemicals, uncertainty in the FF was up to 1 order of magnitude larger than spatial variability. Variability and uncertainty in freshwater XFs of the seven chemicals was negligible (k < 1.5). We found that, depending on the chemical and emission scenario, accounting for region-specific environmental characteristics in multimedia fate modelling, as well as accounting for parameter uncertainty, can have a significant influence on freshwater fate factor predictions. Therefore, we conclude that it is important that fate factors should not only account for parameter uncertainty, but for spatial variability as well, as this further increases the reliability of ecotoxicological impacts in LCA.

A compilation of life cycle studies for six household detergent product categories in Europe: the basis for product-specific A.I.S.E. Charter Advanced Sustainability Profiles.

BACKGROUND: A.I.S.E., the International Association for Soaps, Detergents and Maintenance Products, launched the 'A.I.S.E. Charter for Sustainable Cleaning' in Europe in 2005 to promote sustainability in the cleaning and maintenance products industry. This Charter is a proactive programme for translating the concept of sustainable innovation into reality and actions. Per product category, life cycle assessments (LCA) are used to set sustainability criteria that are ambitious, but also achievable by all market players. RESULTS: This paper presents and discusses LCAs of six household detergent product categories conducted for the Charter, i.e.: manual dishwashing detergents, powder and tablet laundry detergents, window glass trigger spray cleaners, bathroom trigger spray cleaners, acid toilet cleaners, and bleach toilet cleaners. Relevant impact categories are identified, as well as the life cycle stages with the largest contribution to the environmental impact. CONCLUSIONS: It was concluded that the variables that mainly drive the results (i.e. the environmental hotspots) for manual dishwashing detergents and laundry detergents were the water temperature, water consumption (for manual dishwashing detergents), product dosage (for laundry detergents), and the choice and amount of surfactant. By contrast, for bathroom trigger sprays, acid and bleach toilet cleaners, the driving factors were plastic packaging, transportation to retailer, and specific ingredients. Additionally, the type of surfactant was important for bleach toilet cleaners. For window glass trigger sprays, the driving factors were the plastic packaging and the type of surfactant, and the other ingredients were of less importance. A.I.S.E. used the results of the studies to establish sustainability criteria, the so-called 'Charter Advanced Sustainability Profiles', which led to improvements in the marketplace.

Including exposure variability in the life cycle impact assessment of indoor chemical emissions: the case of metal degreasing.

The present paper describes a method that accounts for variation in indoor chemical exposure settings and accompanying human toxicity in life cycle assessment (LCA). Metal degreasing with dichloromethane was used as a case study to show method in practice. We compared the human toxicity related to the degreasing of 1m(2) of metal surface in different exposure scenarios for industrial workers, professional users outside industrial settings, and home consumers. The fraction of the chemical emission that is taken in by exposed individuals (i.e. the intake fraction) was estimated on the basis of operational conditions (e.g. exposure duration), and protective measures (e.g. local exhaust ventilation). The introduction of a time-dependency and a correction for protective measures resulted in reductions in the intake fraction of up to 1.5 orders of magnitude, compared to application of existing, less advanced models. In every exposure scenario, the life cycle impacts for human toxicity were mainly caused by indoor exposure to metal degreaser (>60%). Emissions released outdoors contributed up to 22% of the life cycle impacts for human toxicity, and the production of metal degreaser contributed up to 19%. These findings illustrate that human toxicity from indoor chemical exposure should not be disregarded in LCA case studies. Particularly when protective measures are taken or in the case of a short duration (1h or less), we recommend the use of our exposure scenario-specific approach.

The QSPR-THESAURUS: the online platform of the CADASTER project.

The aim of the CADASTER project (CAse Studies on the Development and Application of in Silico Techniques for Environmental Hazard and Risk Assessment) was to exemplify REACH-related hazard assessments for four classes of chemical compound, namely, polybrominated diphenylethers, per and polyfluorinated compounds, (benzo)triazoles, and musks and fragrances. The QSPR-THESAURUS website (http: / /qspr-thesaurus.eu) was established as the project's online platform to upload, store, apply, and also create, models within the project. We overview the main features of the website, such as model upload, experimental design and hazard assessment to support risk assessment, and integration with other web tools, all of which are essential parts of the QSPR-THESAURUS.

Assessing predictive uncertainty in comparative toxicity potentials of triazoles.

Comparative toxicity potentials (CTPs) quantify the potential ecotoxicological impacts of chemicals per unit of emission. They are the product of a substance's environmental fate, exposure, and hazardous concentration. When empirical data are lacking, substance properties can be predicted. The goal of the present study was to assess the influence of predictive uncertainty in substance property predictions on the CTPs of triazoles. Physicochemical and toxic properties were predicted with quantitative structure-activity relationships (QSARs), and uncertainty in the predictions was quantified with use of the data underlying the QSARs. Degradation half-lives were based on a probability distribution representing experimental half-lives of triazoles. Uncertainty related to the species' sample size that was present in the prediction of the hazardous aquatic concentration was also included. All parameter uncertainties were treated as probability distributions, and propagated by Monte Carlo simulations. The 90% confidence interval of the CTPs typically spanned nearly 4 orders of magnitude. The CTP uncertainty was mainly determined by uncertainty in soil sorption and soil degradation rates, together with the small number of species sampled. In contrast, uncertainty in species-specific toxicity predictions contributed relatively little. The findings imply that the reliability of CTP predictions for the chemicals studied can be improved particularly by including experimental data for soil sorption and soil degradation, and by developing toxicity QSARs for more species.

Statistical uncertainty in hazardous terrestrial concentrations estimated with aquatic ecotoxicity data.

Since chemicals' ecotoxic effects depend for most soil species on the dissolved concentration in pore water, the equilibrium partitioning (EP) method is generally used to estimate hazardous concentrations (HC50) in the soil from aquatic toxicity tests. The present study analyzes the statistical uncertainty in terrestrial HC50s derived by the EP-method. For 47 organic chemicals, we compared freshwater HC50s derived from standard aquatic ecotoxicity tests with porewater HC50s derived from terrestrial ecotoxicity tests. Statistical uncertainty in the HC50s due to limited species sample size and in organic carbon-water partitioning coefficients due to predictive error was treated with probability distributions propagated by Monte Carlo simulations. Particularly for specifically acting chemicals, it is very important to base the HC50 on a representative sample of species, composed of both target and non-target species. For most chemical groups, porewater HC50 values were approximately a factor of 3 higher than freshwater HC50 values. The ratio of the porewater HC50/freshwater HC50 was typically 3.0 for narcotic chemicals (2.8 for nonpolar and 3.4 for polar narcotics), 0.8 for reactive chemicals, 2.9 for neurotoxic chemicals (4.3 for AChE agents and 0.1 for the cyclodiene type), and 2.5 for herbicides-fungicides. However, the statistical uncertainty associated with this ratio was large (typically 2.3 orders of magnitude). For 81% of the organic chemicals studied, there was no statistical difference between the hazardous concentration of aquatic and terrestrial species. We conclude that possible systematic deviations between the HC50s of aquatic and terrestrial species appear to be less prominent than the overall statistical uncertainty.

Arguments for considering uncertainty in QSAR predictions in hazard and risk assessments.

Chemical regulation allows non-in vivo testing (i.e. in silico-derived and in vitro-derived) information to replace experimental values from in vivo studies in hazard and risk assessments. Although non-in vitro testing information on chemical activities or properties is subject to added uncertainty as compared to in vivo testing information, this uncertainty is commonly not (fully) taken into account. Considering uncertainty in predictions from quantitative structure-activity relationships (QSARs), which are a form of non-in vivo testing information, may improve the way that QSARs support chemical safety assessment under the EU Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) system. We argue that it is useful to consider uncertainty in QSAR predictions, as it: a) supports rational decision-making; b) facilitates cautious risk management; c) informs uncertainty analysis in probabilistic risk assessment; d) may aid the evaluation of QSAR predictions in weight-of-evidence approaches; and e) provides a probabilistic model to verify the experimental data used in risk assessment. The discussion is illustrated by using case studies of QSAR integrated hazard and risk assessment from the EU-financed CADASTER project.

Understanding quantitative structure-property relationships uncertainty in environmental fate modeling.

In cases in which experimental data on chemical-specific input parameters are lacking, chemical regulations allow the use of alternatives to testing, such as in silico predictions based on quantitative structure-property relationships (QSPRs). Such predictions are often given as point estimates; however, little is known about the extent to which uncertainties associated with QSPR predictions contribute to uncertainty in fate assessments. In the present study, QSPR-induced uncertainty in overall persistence (POV ) and long-range transport potential (LRTP) was studied by integrating QSPRs into probabilistic assessments of five polybrominated diphenyl ethers (PBDEs), using the multimedia fate model Simplebox. The uncertainty analysis considered QSPR predictions of the fate input parameters' melting point, water solubility, vapor pressure, organic carbon-water partition coefficient, hydroxyl radical degradation, biodegradation, and photolytic degradation. Uncertainty in POV and LRTP was dominated by the uncertainty in direct photolysis and the biodegradation half-life in water. However, the QSPRs developed specifically for PBDEs had a relatively low contribution to uncertainty. These findings suggest that the reliability of the ranking of PBDEs on the basis of POV and LRTP can be substantially improved by developing better QSPRs to estimate degradation properties. The present study demonstrates the use of uncertainty and sensitivity analyses in nontesting strategies and highlights the need for guidance when compounds fall outside the applicability domain of a QSPR.

Do interspecies correlation estimations increase the reliability of toxicity estimates for wildlife?

For warm-blooded species, the hazardous dose of a chemical (HD50) is an upcoming and important characteristic in the assessment of toxic chemicals. Generally, experimental information is available for a limited number of warm-blooded species only, which causes statistical uncertainty. Furthermore, when small datasets contain an unrepresentative sample of species, they can cause systematic uncertainty in chemicals' hazardous doses. The number of species can be enlarged with interspecies correlation estimation (ICE) models, but these are uncertain themselves. The goal of this study is to quantify the possible gain in reliability of the HD50 values for warm-blooded wildlife species after enlargement of the sample size with ICE predictions. For 1137 chemicals, we compared systematic uncertainty and statistical uncertainty between HD50 values based on experimental data (HD50(Ex)) and on datasets combining experimental data and ICE predictions (HD50(Co)). HD50(Ex) values ranged between 1.0×10(-1) and 9.5×10(3)mgkg(wwt)(-1), and HD50(Co) values between 1.1×10(0) and 6.1×10(3)mgkg(wwt)(-1). For over 97 percent of the chemicals, HD50(Ex) values exceeded HD50(Co) values, with a systematic uncertainty (i.e. the ratio of HD50(Ex)/HD50(Co)) of typically 3.5. The limited availability of experimental toxicity data, predominantly for mammals, resulted in a systematic underestimation of the wildlife toxicity of a chemical. Statistical uncertainty factors (i.e. the ratio of the 95th/5th percentile) quantified the statistical uncertainty in the HD50 values. The statistical uncertainty factors ranged between 1.0×10(0) and 2.5×10(22) for the experimental dataset, and between 4.8×10(0) and 1.1×10(2) for the combined dataset. For all sample sizes, median statistical uncertainty factors were the largest for combined datasets. However, combining experimental toxicity data with ICE predictions makes it possible to reduce the upper limit of the range for statistical uncertainty factors. We conclude that, by combining experimental data with ICE model predictions, the validity of the HD50 value can be improved and high statistical uncertainty can be reduced, particularly in cases of limited toxicity data, i.e. data for mammals only or a sample size of n≤4.

Including ecotoxic impacts on warm-blooded predators in life cycle impact assessment.

In current life cycle impact assessment, the focus of ecotoxicity is on cold-blooded species. We developed a method to calculate characterization factors (CFs) for the impact assessment of chemical emissions on warm-blooded predators in freshwater food chains. The method was applied to 329 organic chemicals. The CF for these predators was defined as a multiplication of the fate factor (FF), exposure factor (XF), bioaccumulation factor (BF), and effect factor (EF). Fate factors and XFs were calculated with the model USES-LCA 2.0. Bioaccumulation factors were calculated with the model OMEGA, for chemical uptake via freshwater, food, and air. Effect factors were calculated based on experimental, median lethal doses (LD50). The concentration buildup (CB) of the chemicals (i.e., FF, XF, and BF over the 3 routes of exposure) showed a range of 7 to 9 orders of magnitude, depending on the emission compartment. Effect factors displayed a range of 7 orders of magnitude. Characterization factors ranged 9 orders of magnitude. After emissions to freshwater, the relative contribution of the uptake routes to CB were 1% (90% confidence interval [CI]: 0%-2%) for uptake from air, 43% (11%-50%) for uptake from water, and 56% (50%-87%) for uptake from food. After an emission to agricultural soil, the contribution was 11% (0%-80%) for uptake from air, 39% (5%-50%) for uptake from water, and 50% (11%-83%) for uptake from food. Uptake from air was mainly relevant for emissions to air (on average 42%, 90% CI: 5%-98%). Characterization factors for cold-blooded species were typically 4 orders of magnitude higher than CFs for warm-blooded predators. The correlation between both types of CFs was low, which means that a high relative impact on cold-blooded species does not necessarily indicate a high relative impact on warm-blooded predators. Depending on the weighing method to be considered, the inclusion of impacts on warm-blooded predators can change the relative ranking of toxic chemicals in a life cycle assessment.