Mark A. J. Huijbregts

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

PurposeLife 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).MethodsExisting 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 recommendationsRecommendations 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 outlookThe 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.

Application of uncertainty and variability in LCA

As yet, the application of an uncertainty and variability analysis is not common practice in LCAs. A proper analysis will be facilitated when it is clear which types of uncertainties and variabilities exist in LCAs and which tools are available to deal with them. Therefore, a framework is developed to classify types of uncertainty and variability in LCAs. Uncertainty is divided in (1) parameter uncertainty, (2) model uncertainty, and (3) uncertainty due to choices, while variability covers (4) spatial variability, (5) temporal variability, and (6) variability between objects and sources. A tool to deal with parameter uncertainty and variability between objects and sources in both the inventory and the impact assessment is probabilistic simulation. Uncertainty due to choices can be dealt with in a scenario analysis or reduced by standardisation and peer review. The feasibility of dealing with temporal and spatial variability is limited, implying model uncertainty in LCAs. Other model uncertainties can be reduced partly by more sophisticated modelling, such as the use of non-linear inventory models in the inventory and multi media models in the characterisation phase.

Priority assessment of toxic substances in life cycle assessment. Part I: Calculation of toxicity potentials for 181 substances with the nested multi-media fate, exposure and effects model USES-LCA

Toxicity potentials are standard values used in life cycle assessment (LCA) to enable a comparison of toxic impacts between substances. In most cases, toxicity potentials are calculated with multi-media fate models. Until now, unrealistic system settings were used for these calculations. The present paper outlines an improved model to calculate toxicity potentials: the global nested multi-media fate, exposure and effects model USES-LCA. It is based on the Uniform System for the Evaluation of Substances 2.0 (USES 2.0). USES-LCA was used to calculate for 181 substances toxicity potentials for the six impact categories freshwater aquatic ecotoxicity, marine aquatic ecotoxicity, freshwater sediment ecotoxicity, marine sediment ecotoxicity, terrestrial ecotoxicity and human toxicity, after initial emission to the compartments air, freshwater, seawater, industrial soil and agricultural soil, respectively. Differences of several orders of magnitude were found between the new toxicity potentials and those calculated previously.

Cumulative energy demand as predictor for the environmental burden of commodity production.

Cumulative energy demand has been used as a methodology to assess life cycle environmental impacts of commodity production since the early seventies, but has also been criticized because it focuses on energy only. During the past 30 years there has been much research into the development of more complex single-score life cycle impact assessment methodologies. However, a comprehensive analysis of potential similarities and differences between these methodologies and cumulative energy demand has not been carried out so far. Here we compare the cumulative energy demand of 498 commodities with the results of six frequently applied environmental life cycle impact assessment methodologies. Commodity groups included are metals, glass, paper and cardboard, organic and inorganic chemicals, agricultural products, construction materials, and plastics. We show that all impact assessment methods investigated often provide converging results, in spite of the different philosophies behind these methodologies. Fossil energy use is identified by all methodologies as the most important driver of environmental burden of the majority of the commodities included,with the main exception of agricultural products. We conclude that a wide range of life cycle environmental assessment methodologies point into the same environmental direction for the production of many commodities.

Framework for modelling data uncertainty in life cycle inventories

Modelling data uncertainty is not common practice in life cycle inventories (LCI), although different techniques are available for estimating and expressing uncertainties, and for propagating the uncertainties to the final model results. To clarify and stimulate the use of data uncertainty assessments in common LCI practice, the SETAC working group ‘Data Availability and Quality’ presents a framework for data uncertainty assessment in LCI. Data uncertainty is divided in two categories: (1) lack of data, further specified as complete lack of data (data gaps) and a lack of representative data, and (2) data inaccuracy. Filling data gaps can be done by input-output modelling, using information for similar products or the main ingredients of a product, and applying the law of mass conservation. Lack of temporal, geographical and further technological correlation between the data used and needed may be accounted for by applying uncertainty factors to the non-representative data. Stochastic modelling, which can be performed by Monte Carlo simulation, is a promising technique to deal with data inaccuracy in LCIs.

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.

Human-Toxicological Effect and Damage Factors of Carcinogenic and Noncarcinogenic Chemicals for Life Cycle Impact Assessment

Abstract Chemical fate, effect, and damage should be accounted for in the analysis of human health impacts by toxic chemicals in life-cycle assessment (LCA). The goal of this article is to present a new method to derive human damage and effect factors of toxic pollutants, starting from a lognormal dose–response function. Human damage factors are expressed as disability-adjusted life years (DALYs). Human effect factors contain a disease-specific and a substance-specific component. The disease-specific component depends on the probability of disease occurrence and the distribution of sensitivities in the human population. The substance-specific component, equal to the inverse of the ED50, represents the toxic potency of a substance. The new method has been applied to calculate combined human damage and effect factors for 1,192 substances. The total range of 7 to 9 orders of magnitude between the substances is dominated by the range in toxic potencies. For the combined factors, the typical uncertainty, represented by the square root of the ratio of the 97.5th and 2.5th percentile, is a factor of 25 for carcinogenic effects and a factor of 125 for noncarcinogenic effects. The interspecies conversion factor, the (non)cancer effect conversion factor, and the average noncancer damage factor dominate the overall uncertainty.

Ranking potential impacts of priority and emerging pollutants in urban wastewater through life cycle impact assessment

Life cycle impact assessment (LCIA), a feature of the Life cycle assessment (LCA) methodology, is used in this work outside the LCA framework, as a means to quantify the potential environmental impacts on ecotoxicity and human toxicity of wastewater containing priority and emerging pollutants. In order to do this, so-called characterisation factors are obtained for 98 frequently detected pollutants, using two characterisation models, EDIP97 and USES-LCA. The applicability of this methodology is shown in a case study in which wastewater influent and effluent samples from a Spanish wastewater treatment plant located in the Mediterranean coast were analysed. Characterisation factors were applied to the average concentration of each pollutant, obtaining impact scores for different scenarios: discharging wastewater to aquatic recipient, and using it for crop irrigation. The results show that treated wastewater involves a substantially lower environmental impact when compared to the influent, and pharmaceuticals and personal care products (PPCPs) are very important contributors to toxicity in this wastewater. Ciprofloxacin, fluoxetine, and nicotine constitute the main PPCPs of concern in this case study, while 2,3,7,8-TCDD, Nickel, and hexachlorobenzene are the priority pollutants with highest contribution. Nevertheless, it must be stressed that the new characterisation factors are based on very limited data, especially with regard to toxicology, and therefore they must be seen as a first screening to be improved in the future when more and higher quality data is available.

Integrating Human Indoor Air Pollutant Exposure within Life Cycle Impact Assessment

Neglecting health effects from indoor pollutant emissions and exposure, as currently done in Life Cycle Assessment (LCA), may result in product or process optimizations at the expense of workers’ or consumers’ health. To close this gap, methods for considering indoor exposure to chemicals are needed to complement the methods for outdoor human exposure assessment already in use. This paper summarizes the work of an international expert group on the integration of human indoor and outdoor exposure in LCA, within the UNEP/SETAC Life Cycle Initiative. A new methodological framework is proposed for a general procedure to include human-health effects from indoor exposure in LCA. Exposure models from occupational hygiene and household indoor air quality studies and practices are critically reviewed and recommendations are provided on the appropriateness of various model alternatives in the context of LCA. A single-compartment box model is recommended for use as a default in LCA, enabling one to screen occupational and household exposures consistent with the existing models to assess outdoor emission in a multimedia environment. An initial set of model parameter values was collected. The comparison between indoor and outdoor human exposure per unit of emission shows that for many pollutants, intake per unit of indoor emission may be several orders of magnitude higher than for outdoor emissions. It is concluded that indoor exposure should be routinely addressed within LCA.

Spatially Explicit Characterization of Acidifying and Eutrophying Air Pollution in Life‐Cycle Assessment

Simple models are often used to assess the potential impact of acidifying and eutrophying substances released during the life cycle of products. As fate, background depositions, and ecosystem sensitivity are not included in these models, environmental life-cycle assessment of products (LCA) may produce incorrect results for these impact categories. This paper outlines the spatially explicit regional air pollution information and simulation model (RAINSLCA), which was developed for the calculation of acidification and terrestrial eutrophication potentials of ammonia (NH3) and nitrogen oxide (NOx) air emissions and acidification potentials for sulfur dioxide (SO2) air emissions for Europe and a number of European regions, taking fate, background depositions and effects into account. Two impact definitions are explored in the calculations: (1) the marginal change in the hazard index of all ecosystems in Europe and (2) the marginal change in the hazard index of ecosystems in Europe where the critical load is actually exceeded. The inclusion of fate, background depositions, and ecosystem sensitivity results in a different ranking of substances compared to simpler model outcomes.