Current Life Cycle Impact Assessment Research Articles

An LCIA-based model proposal for the selection of building interior finishing materials

The increasing environmental impacts of buildings highlight conscious material selection as a pivotal aspect of sustainable building design. Most current life cycle impact assessment (LCIA) models on material selection focus on the main construction or insulation materials while often neglecting the environmental effects of finishing materials. Hence, this study seeks to present an LCIA-based model for selecting finishing materials based on their environmental impacts. Environmental Product Declaration (EPD) as a data source for the mandatory steps of LCIA is recommended for the model since it provides fast, reliable, and equivalent data on the environmental impacts of the materials. The model is validated by assessing three wall finishing materials in hotel bedrooms- gypsum board, paint, and wood panel. Findings revealed that the model has the potential to mitigate the environmental effects by guiding decisions made during the finishing material selection phase.

Relevance of attributional and consequential life cycle assessment for society and decision support

Life cycle assessment (LCA) is an essential tool for assessing the environmental impact of product systems. There are two main types: attributional LCA (ALCA), which assesses the global impact share of a product's life cycle, and consequential LCA (CLCA), which evaluates the consequential impact of a decision. In our analysis, we explored the relevance of these types for society and their ability to aid decision-making. This analysis builds upon existing literature and incorporates two ideological and three pragmatic criteria. First, when it comes to realistic modeling as desired in the context of sustainable development, in theory, CLCA attempts to model realistically, whereas ALCA falls short to a certain degree because of conceptual rules, e.g., artificial splitting of co-product processes. Concerning the second criterion of alignment with ethics, CLCA completely aligns with consequential ethics, where an action is judged based on its consequences. This alignment of CLCA makes it undoubtedly relevant in a world where we aim to obtain favorable consequences in the future, e.g., meeting sustainability goals. ALCA is only partially consequential, as it is restricted by conceptual rules relating to deontological ethics and, for example, covers the relative past of the product. Since deontological ethics, i.e. judging an action based on its alignment with rules, is generally relevant for our modern human society, there is room for complementarity in ethical relevance between ALCA and CLCA. However, the conceptual rules of ALCA (e.g., additivity) and their relevance have not been accepted by society. As a result, ethical acceptance of ALCA is still required. In the context of decision support, CLCA evaluates the consequences of decisions, while ALCA encompasses the approval and sharing of potential responsibility for the environmental impact throughout the life cycle of the product associated with the decision. We also highlight the unique valorization of Organizational ALCA, which entails the aforementioned aspects for the organizations responsible for the product. Concerning the three practical criteria, the following conclusions were drawn. Although ALCA has received the most attention in terms of standards, only CLCA can currently be consistently conducted in a reliable manner. This is because the current life cycle impact assessment methods applied in ALCA do not yet partition environmental multi-input processes. CLCA should be given greater prominence in standards. Furthermore, the complexity and uncertainty associated with modeling may often be only slightly higher for CLCA than for ALCA, mainly due to the consideration of change resulting from a decision. However, both ALCA and CLCA modeling may be similarly complex and have equally high levels of uncertainty as both methods encompass past and/or future projections (e.g., prediction of future background processes). Finally, ALCA modeling may be viewed as a practical approximation of CLCA, but the current CLCA models are more suitable for studying consequential effects. As CLCA modeling and databases continue to improve, this distinction will become even more pronounced.

The impacts of plastic products on air pollution - A simulation study for advanced life cycle inventories of plastics covering secondary microplastic production

A framework, SecµPlast, to include secondary microplastic (MP) formation due to photooxidation into current Life Cycle Assessments (LCA) from cradle-to-grave of products. The framework details how to incorporate secondary MP formation into the plastic's life cycle as related to the plastic's use phase, and location specific waste treatment and how to connect the impacts with current life cycle impact assessment methodologies (LCIA). Plastics, now ubiquitous in the environment are a potential source of emerging pollution and have been shown to have negative effects of various species. Thus, the framework consist of 1) a degradation module, which accounts for micro- and nano- plastic formation with dynamic degradation of microparticles, 2) an emissions module accounts for the potential of the plastic particles to be emitted to air, and 3) an impacts module which connects the various emissions to existing LCIA methods. The framework allows for quantification of secondary microplastic in an LCA context and for further characterization of the impacts at endpoints in terms of human health, and allows for a high level of regionalization, both in terms of input data and characterization of impact damages. SecµPlast was tested on a case study of mulch film which showed that the per kg contribution to particulate matter (PM) and other impacts is low. The impacts vary largely depending on the degradation rate and ranged from 9.24×10 −6 to 0.00043 kg PM equivalents per kg of mulch film, depending on either a slow or fast degradation rate, respectively. The impact came mostly from the littered fraction, which was estimated to be 10% of the products weight after the use phase, in Europe. The degradation rates due to UV degradation were low, 0.034 µg/year for a slow degradation rate, compared to values derived from the literature, 0.345 µg/year for a fast degradation rate during littering, that included other sources of degradation, such as abrasion. However, when these impacts are scaled up to the European consumption of plastics and monetized, it is evident that even small increases of PM are costly for society and could potentially amount to millions of dollars per year in human health damages. Further research efforts should focus on filling data gaps, such as microplastic losses during production, recycling and potentially incineration, as well as degradation kinetics including other degradation factors such as freeze/thawing, wet/drying in combination with UV degradation.

Inter-Individual Variability and Non-linear Dose-Response Relationship in Assessing Human Health Impact From Chemicals in LCA: Addressing Uncertainties in Exposure and Toxicological Susceptibility

Current life cycle impact assessment (LCIA) practices use a characterization factor to linearly scale chemical emission to human health impact assuming a homogeneous exposure and toxicological susceptibility for the entire population. However, both exposure and toxicological susceptibility may vary within the population, making the same emission elicit disproportionate impacts. Here we explore how inter-individual variabilities in human exposure and toxicological susceptibility interact to affect the estimated overall health impacts on the population level. For exemplification, we use the PROTEX model to simulate the exposure of the general American population to dieldrin and heptachlor, two organochlorine pesticides that tend to accumulate in food items. Using a Monte-Carlo analysis, we characterize inter-individual variabilities in exposure by considering variations in anthropometrics and dietary patterns between ages, sexes, and racial groups. We assess the overall health impact on the population level in five scenarios with different combinations of assumptions in exposure (homogeneous/heterogeneous) and the dose-response relationship (linear/non-linear, homogeneous/heterogeneous susceptibility). Our results indicate human exposure can vary by a factor of six among the different demographic groups. Combined with a non-linear dose-response relationship with heterogeneous susceptibility, the estimated overall health impact is substantially higher than the results using homogeneous susceptibility. However, the current LCIA practice of using a linear dose-response relationship produces even higher results that may overestimate the health impacts.

Globally differentiated effect factors for characterising terrestrial acidification in life cycle impact assessment

To assess terrestrial ecosystems damages from acidification, life cycle impact assessment (LCIA) can be applied using characterisation factors, which integrate the quantification of adverse effects via effect factors (EFs), linking decreasing soil pH to declines in species richness. With a species coverage of 0.6%, the currently-existing EFs defined for 14 biomes carry important uncertainties and lack the appropriate spatial resolution to capture the effects of terrestrial acidification. In our study, we thus used georeferenced observational data with 113 million data points to develop a comprehensive, global inventory covering 189,185 vascular plant species, which is nearly 100 times more species than existing inventories used in LCIA (raising the species coverage to 49%). EFs were then calculated for 825 ecoregions. Great spatial variability is observed between ecoregions within a same biome spanning up to 3 orders of magnitude, and EFs developed at biome level tend to underestimate acidification effects. We find up to 2 orders of magnitude differences between our EFs and the ones currently recommended for use in LCIA. These results call for updating current LCIA practice to assess acidification impacts with our more differentiated and environmentally representative EFs and to implement our approach to other site-dependent environmental impacts where large georeferenced datasets exist.

Regionalization of characterization factor in Brazil: freshwater eutrophication category

Brazil is privileged to have the most important natural resource in its territory, the water. But currently, the increased concentration of phosphorus (P) affects the water quality. It has two main routes to get into aquatic environmental: through the dump of untreated sewage and fertilizers runoff. The P excess may promote eutrophication, a process characterized by microalgae uncontrolled growth, affecting several parameters of freshwater. Due to the great differences at the Brazilian regions, the current Life Cycle Impact Assessment methodologies are not capable to evaluate properly the eutrophication impact in Brazil. The most viable method to obtain a more suitable model is regionalizing it by estimating the characterization factor (CF). Therefore this is the first study that presents a regionalized model to estimate Brazilian CF for freshwater eutrophication. The regionalization was based on the models proposed by Helmes et al. (2012) and Azevedo et al. (2013), which are considered the most complete and suitable models. Due to the lack of data it was possible to calculate the CF for Alto Iguaçu micro watershed and four more subwatersheds: Paraíba do Sul, Parnaíba, Litorânea do Ceará and Litorânea Pernambuco Alagoas. The processes assessment of advection, retention and water use provides valuable information of each region and also results in more realistic Fate Facto (FF), since Brazilian sanitation is completely uneven, and the sewage treatment must be modelled to not overestimated or sub estimated the FF. At Alto Iguaçu is the advection rate is the most relevant and its CF is 7.43 103. m3 .KgP-1 day. For that reason, the same amount of emitted phosphorus promotes a bigger eutrophication potential at Paraíba do Sul and Parnaíba than other basins. Phosphorus income rates estimate is possible to know the origin of its most significant input. Based on this information, financial resources can be better used. This was the first attempt to develop a Brazilian CF and some improvements need to be done. Firstly, new studies ought to concentrate to promote good quality of data, because the unavailability of data was one of the greatest difficulties of this study. Then the regionalized model should be improved modeling treatment of industrial sewage and, finally, CF needs to be calculated for all subwatershed.
 Keywords: Eutrophication. Characterization factor. Freshwater. Brazil. Life Cycle Impact Assessment.

Environmental impacts of an advanced oxidation process as tertiary treatment in a wastewater treatment plant

Due to global water scarcity, the use of reclaimed wastewater for crop irrigation is required; however, if the wastewater treatment is inadequate, it can be a source of environmental pollution. In order to improve wastewater reclamation, advanced oxidation processes (AOPs) have been tested. At full scale, ozonation is one such process that effectively removes micropollutants, despite its high-energy consumption. At pilot scale, other technologies such as the solar photo-Fenton process are being developed. This process is under consideration as a sustainable technology because it uses sunlight as a source of radiation. However, there is little information available on its environmental performance. In this work, we perform a comparative analysis between the ozonation and the photo-Fenton process as tertiary wastewater treatment processes used to reclaim wastewater for agricultural irrigation. We apply the Life Cycle Assessment (LCA) methodology for quantifying environmental impacts with ReCiPe and USEtox as life cycle impact assessment (LCIA) methods. The results show that both tertiary treatment options reduce water stress locally. Ozonation has a better overall environmental performance compared to the photo-Fenton process because the environmental impact of the required ozone is smaller than of the reactants involved in the solar photo-Fenton. Moreover, the first can be operated both day and night, and therefore needs no additional storage for collecting the nightly secondary effluent, and thus has lower infrastructure related impacts. Additionally, when the solar photo-Fenton process operates at an acidic pH, there are environmental drawbacks related to the pH adjustment, which consumes a large amount of acid thus liberating CO2. Finally, the environmental impacts associated with the discharge of micropollutants to soil through the use of reclaimed water are very small compared to the other impacts generated by the treatment. However, due to the current LCIA method limitations of micropollutant impact assessment, these are subject to major uncertainty.

Reviewing the potential for including habitat fragmentation to improve life cycle impact assessments for land use impacts on biodiversity

The biosphere is progressively subjected to a variety of pressures resulting from anthropogenic activities. Habitat conversion, resulting from anthropogenic land use, is considered the dominant factor driving terrestrial biodiversity loss. Hence, adequate modelling of land use impacts on biodiversity in decision-support tools, like life cycle assessment (LCA), is a priority. State-of-the-art life cycle impact assessment (LCIA) characterisation models for land use impacts on biodiversity translate natural habitat transformation and occupation into biodiversity impacts. However, the currently available models predominantly focus on total habitat loss and ignore the spatial configuration of the landscape. That is, habitat fragmentation effects are ignored in current LCIAs with the exception of one recently developed method. Here, we review how habitat fragmentation may affect biodiversity. In addition, we investigate how land use impacts on biodiversity are currently modelled in LCIA and how missing fragmentation impacts can influence the LCIA model results. Finally, we discuss fragmentation literature to evaluate possible methods to include habitat fragmentation into advanced characterisation models. We found support in available ecological literature for the notion that habitat fragmentation is a relevant factor when assessing biodiversity loss. Moreover, there are models that capture fragmentation effects on biodiversity that have the potential to be incorporated into current LCIA characterisation models. To enhance the credibility of LCA biodiversity assessments, we suggest that available fragmentation models are adapted, expanded and subsequently incorporated into advanced LCIA characterisation models and promote further efforts to capture the remaining fragmentation effects in LCIA characterisation models.

Towards the determination of metal criticality in home-based battery systems using a Life Cycle Assessment approach

The operation and production of batteries is associated with environmental impacts that can be quantified with Life Cycle Assessment methodologies. Current life cycle impact assessment methodologies do not assess metal criticality: they are based on geological availability or resource depletion only and do not consider socio-economic factors. Such factors are included by the concept of metal criticality. This paper determines the metal criticality of six home-based battery systems (Li-Ion: LFP-C, NMC-C, NCA-C, NCA-LTO; VRLA battery and the VRFB) for a photovoltaics self-consumption application based on a Life Cycle Assessment approach. Cumulative life cycle inventory results on extraction of metal resources are coupled with characterization factors of 13 metals derived from three state-of-the-art criticality methodologies. The results are presented for two functional units: (1) the installed battery system per kWh of energy delivered (per cycle); (2) additionally including necessary replacements of battery packs during the system lifetime. Due to substantial differences in terms of battery lifetimes between battery technologies, the latter functional unit turns out to be more meaningful. In general, there is a correlation between lower metal criticality scores (i.e. better performance) and batteries with a higher specific energy, longer battery lifetime and lower mass of metal consumption. LFP-C battery shows both low metal criticality scores and comparatively robust results, while VRFB exhibits low metal criticality but associated with relatively high uncertainties. In contrast, the VRLA battery performs the worst due to low discharge efficiency and relatively short battery lifetime. We argue that metal criticality could be reduced by improving the specific energy of the battery, by selecting low metal-intensive and low-critical metal containing components, by increasing the use of secondary metals and by selecting batteries with longer battery lifetimes.

Evaluating the monetary values of greenhouse gases emissions in life cycle impact assessment

It is commonly acknowledged that greenhouse gas (GHG) emissions from anthropogenic sources accelerate climate change impacts. Efforts are made by governments and companies to reduce GHG emissions via policies and actions. In order to determine which actions to prioritize among many options, benefits of emission reductions are often monetized, to compare with the costs of action or with benefits that can be obtained from other actions. Life cycle assessment (LCA) is a commonly used tool to assess the amount of GHGs emitted over the life cycle of a service, policy or product system. However, the damage modelling of GHGs in life cycle impact assessment (LCIA) and its monetary values have not been separately evaluated. This hinders the application of LCA in relevant decision contexts. This study evaluates the cause-effect chains and associated monetary values of GHG in three LCIA methods LIME2, EPS2015 and ReCiPe2016. Among these three, EPS2015 covers most damage categories, including the ones on human health, ecosystem and social assets. ReCiPe2016 does not include social assets damages and LIME2 does not consider ecosystem damages in climate change impact. Human health damages are well estimated in all three methods, contributing to 70–97% of the GHG monetary values. The lack of data is a clear obstacle across methods. Further research is needed to develop comprehensive and robust modelling approach for ecosystem damages, which are not well covered in current LCIA methods. Moreover, due to the scope of environmental LCA, there is a lack of consideration on socio-economic consequences, which may not be negligible for climate change. The resulting monetary value of GHG, expressed in per tonne CO2-eq are 16, 160 and 140 US$2017 respectively in LIME2, EPS2015 and ReCiPe 2016. These monetary values are reasonable for use in decision contexts where LCA is applied. Further research is, however, needed to reduce the current uncertainty of at least 1–2 orders of magnitude.

Global Resource Indicator for life cycle impact assessment: Applied in wind turbine case study

Different methodological approaches under Life Cycle Assessment framework are used so far to address the impact of resource depletion. However, they provide partial visions, based on limited available data, and do not reflect resource related aspects. The aim of this article is to go beyond the current Life Cycle Impact Assessment methodologies to complete the existing indicators, by adding important parameters (e.g. recycling), not yet covered by Life Cycle Assessment resource impact assessment indicators.New Characterization Factors are developed, considering different criteria which affect the availability of resources through different life cycles. Global Resource Indicator integrates resource assessment aspects to better characterize the Resource. Both recyclability and criticality of resources are part of the multi-criteria indicator complementing scarcity.Results illustrate that the importance of different resources are influenced by introduction of recyclability and criticality. The new indicator assesses all types of resources including renewables and non-renewables using regeneration rates. The sensitivity of the Characterization Factors with regard to different input parameters is tested and discussed. The results are compared with Abiotic Depletion Potentials indicator and assessment is made on the differences.The newly developed factors provide a more exhaustive vision of the availability of resources and may be used in Life Cycle Assessment or circular economy approaches. Characterization Factors, derived from the new method are tested in a wind turbine case study and their applicability is validated.

Spatially explicit fate factors of waterborne nitrogen emissions at the global scale

Marine eutrophication impacts due to waterborne nitrogen (N) emissions may vary significantly with their type and location. The environmental fate of dissolved inorganic nitrogen (DIN) forms is essential to understand the impacts they may trigger in receiving coastal waters. Current life cycle impact assessment (LCIA) methods apply fate factors (FFs) with limited specificity of DIN emission routes, and often lack spatial differentiation and global applicability. This paper describes a newly developed method to estimate spatially explicit FFs for marine eutrophication at a global scale and river basin resolution. The FF modelling work includes DIN removal processes in both inland (soil and river) and marine compartments. Model input parameters are the removal coefficients extracted from the Global NEWS 2-DIN model and residence time of receiving coastal waters. The resulting FFs express the persistence of the fraction of the original DIN emission in the receiving coastal large marine ecosystems (LMEs). The method further discriminates three DIN emission routes, i.e., diffuse emission from soils, and direct point emissions to freshwater or marine water. Based on modelling of individual river basins, regionally aggregated FFs are calculated as emission-weighted averages. Among 5772 river basins of the world, the calculated FFs show 5 orders of magnitude variation for the soil-related emission route, 3 for the river-related, and 2 for emissions to marine water. Spatial aggregation of the FFs at the continental level decreases this variation to 1 order of magnitude or less for all routes. Coastal water residence time was found to show inconsistency and scarcity of literature sources. Improvement of data quality for this parameter is suggested. With the proposed method and factors, spatial information of DIN emissions can be used to improve the environmental relevance and the discriminatory power of the assessment of marine eutrophication impacts in a geographically differentiated characterization model at a global scale.

Characterization of waterborne nitrogen emissions for marine eutrophication modelling in life cycle impact assessment at the damage level and global scale

Current life cycle impact assessment (LCIA) methods lack a consistent and globally applicable characterization model relating nitrogen (N, as dissolved inorganic nitrogen, DIN) enrichment of coastal waters to the marine eutrophication impacts at the endpoint level. This paper introduces a method to calculate spatially explicit characterization factors (CFs) at endpoint and damage to ecosystems levels, for waterborne nitrogen emissions, reflecting their hypoxia-related marine eutrophication impacts, modelled for 5772 river basins of the world. The proposed method combines environmental fate factors (FFs) integrating (i) DIN removal processes in soils and rivers, based on the NEWS 2-DIN model, and in coastal waters, based on water residence time; (ii) coastal ecosystem exposure (XF) to N enrichment, based on biological cycling processes; and (ii) effect factors (EFs) based on species sensitivity to hypoxia. Three emission routes are discriminated as N from soil and N in emissions to river and to coastal waters. Damage factors (DFs) are also estimated, based on endpoint metric conversion from potentially affected to potentially disappeared fractions of species (i.e. potentially affected fraction (PAF) to PDF m3 year kg N−1) and harmonization across coastal ecosystems based on spatially explicit density of demersal species, to further express CFs as species year per kilogram N−1. Endpoint CFs show 6 orders of magnitude (o.m.) spatial differentiation amongst the river basins for the soil emission route, 4 for the river and 2 for emissions to coastal waters. Damage CFs vary 7, 5 and 3 o.m. for the same routes. After aggregation at the level of continents, maximum CFs and DFs are consistently found in Europe, but the aggregation reduces spatial differentiation to 1 o.m. for each route in both factors. The FFNsoil and species density terms are responsible for most of the spatial differentiation of the damage model. Uncertainty is higher for the residence time term used in the FF model, due to scarcity and inconsistency of data sources, the assumptions of representativeness of DIN persistence and removal rates. Major contributions to the current state-of-the-art of marine eutrophication characterization modelling are (i) full pathway coverage, thus reaching damage level; (ii) significant increase in geographic coverage; (iii) mechanistic modelling of exposure and effect factors; and (iv) application of spatially explicit damage to ecosystems factors based on species densities. Application of the developed CFs in life cycle impact assessment is recommended at a river basin scale, provided that emission location is known.

Boosting the use of spectral heterogeneity in the impact assessment of agricultural land use on biodiversity

No consensus has been yet achieved among Life Cycle Assessment (LCA) practitioners on how to assess the impact on biodiversity due to land uses and land use changes, in particular with regard to agricultural areas. In the domain of nature conservation and landscape ecology, spectral heterogeneity (SH) derived from remotely sensed imagery is considered a viable proxy for species diversity detection. The assessment rationale is based on the ‘spectral variation hypothesis’: the higher the spectral variability, the higher the ecological heterogeneity and species community diversity, occupying different niches. Our hypothesis is that SH can be effective to improve or complement current Life Cycle Impact Assessment−LCIA practice on biodiversity loss evaluation driven by land use. Hence, we aim here to explore this assumption by computing SH at a local scale of crops cultivation in Southern Alps (Trentino province, Italy), and then combining this information with land use over 30 years. We observe and analyse the relationships between land cover maps and habitat heterogeneity at different time and spatial resolutions. This allows us to argue about the robustness of SH to be a potential surrogate of environmental nuances for species variability detection in LCIA.

Hotspots analysis and critical interpretation of food life cycle assessment studies for selecting eco-innovation options and for policy support

Food production and consumption have been identified among the human interventions generating huge pressures and impacts on the environment. Policies aiming at sustainable production and consumption need to identify hotspots in order to decide where and how to act to steer eco-innovation and to reduce impacts. This could be achieved by applying a life cycle perspective and having a thorough and systematic interpretation of the results of the assessment within and beyond LCA (life cycle assessment) results. The present study aims at presenting a life cycle based method for hotspots analysis focussing on the life cycle impact assessment steps (characterization, normalization and weighting). These steps, which support a correct interpretation of the results, are often performed superficially and not in a systematic way. Hence, in this study, we propose a procedure for supporting the interpretation of LCA results, complementing the assessment with an analysis of hotspots of impact beyond those identified by LCA, to avoid excluding potential hotspots only because they are not fully captured by the current LCIA (life cycle impact assessment) methods. A case study on hotspot analysis and interpretation of results is presented, building on the results of a previous study, which assessed the impact of EU (European Union) food consumption based on the LCA of 17 representative food products. The present study includes: i) a hotspots analysis on characterized and normalized results, ii) the check of un-characterized elementary flows, iii) a sensitivity analysis of the results applying several LCIA methods, normalization references and weighting factors. For all the analyses, product group contribution and impact category relevance are assessed. The results of the hotspot analyses are generally convergent in identifying the most impacting product groups (meat and dairy), whereas they are sometimes diverging in identifying the most relevant impact categories. In this case study, the identification of the most relevant impact categories is mainly influenced by the selection of the set of normalization references compared to that of the weighting sets.

Correlations in Life Cycle Impact Assessment methods (LCIA) and indicators for construction materials: What matters?

Different Life Cycle Impact Assessment (LCIA) methods have been developed over the past twenty years. While the use of a single score indicator may, on the one hand, ease the decision making it may also induce a loss of information. On the other hand, the use of a large set of environmental indicators may increase the difficulty of decision making due to the high number of parameters. In this paper, a statistical methodology is used to identify a simplified set of environmental indicators. This methodology applies Principal Component Analysis (PCA) to five LCIA methods (CML’01, Eco-indicator99, IMPACT 2002+, ecological scarcity, EPD) using a building products database. For each method, the results show that only 4–6 dimensions are sufficient to explain at least 90–95% of the variance for each set of indicators. They refer to the following environmental themes: fossil-fuel consumption, ecotoxicity, ionising radiation, land use and mineral resources. The use of a selected set of five LCI flows is found to be as relevant as current LCIA methods from a statistical point of view. Furthermore, PCA applied to a building LCA case study shows similar trends as for the database results. Further studies are now needed to confirm these findings for going towards simplified structural relationships among LCIA indicators for building materials.

Assessment of Life Cycle Impacts on Ecosystem Services: Promise, Problems, and Prospects.

The analysis of ecosystem services (ES) is becoming a key-factor to implement policies on sustainable technologies. Accordingly, life cycle impact assessment (LCIA) methods are more and more oriented toward the development of harmonized characterization models to address impacts on ES. However, such efforts are relatively recent and have not reached full consensus yet. We investigate here on the transdisciplinary pillars related to the modeling of LCIA on ES by conducting a critical review and comparison of the state-of-the-art in both LCIA and ES domains. We observe that current LCIA practices to assess impacts on "ES provision" suffer from incompleteness in modeling the cause-effect chains; the multifunctionality of ecosystems is omitted; and the "flow" nature of ES is not considered. Furthermore, ES modeling in LCIA is limited by its static calculation framework, and the valuation of ES also experiences some limitations. The conceptualization of land use (changes) as the main impact driver on ES, and the corresponding approaches to retrieve characterization factors, eventually embody several methodological shortcomings, such as the lack of time-dependency and interrelationships between elements in the cause-effect chains. We conclude that future LCIA modeling of ES could benefit from the harmonization with existing integrated multiscale dynamic integrated approaches.

Limitations of toxicity characterization in life cycle assessment: Can adverse outcome pathways provide a new foundation?

Life cycle assessment (LCA) has considerable merit for holistic evaluation of product planning, development, production, and disposal, with the inherent benefit of providing a forecast of potential health and environmental impacts. However, a technical review of current life cycle impact assessment (LCIA) methods revealed limitations within the biological effects assessment protocols, including: simplistic assessment approaches and models; an inability to integrate emerging types of toxicity data; a reliance on linear impact assessment models; a lack of methods to mitigate uncertainty; and no explicit consideration of effects in species of concern. The purpose of the current study is to demonstrate that a new concept in toxicological and regulatory assessment, the adverse outcome pathway (AOP), has many useful attributes of potential use to ameliorate many of these problems, to expand data utility and model robustness, and to enable more accurate and defensible biological effects assessments within LCIA. Background, context, and examples have been provided to demonstrate these potential benefits. We additionally propose that these benefits can be most effectively realized through development of quantitative AOPs (qAOPs) crafted to meet the needs of the LCIA framework. As a means to stimulate qAOP research and development in support of LCIA, we propose 3 conceptual classes of qAOP, each with unique inherent attributes for supporting LCIA: 1) mechanistic, including computational toxicology models; 2) probabilistic, including Bayesian networks and supervised machine learning models; and 3) weight of evidence, including models built using decision-analytic methods. Overall, we have highlighted a number of potential applications of qAOPs that can refine and add value to LCIA. As the AOP concept and support framework matures, we see the potential for qAOPs to serve a foundational role for next-generation effects characterization within LCIA. Integr Environ Assess Manag 2016;12:580-590. Published 2015. This article is a US Government work and is in the public domain in the USA.

Life cycle human health impacts of 875 pesticides

Residues in field crops grown and harvested for human consumption are the main contributor to overall human exposure toward agricultural pesticides for the general population. However, exposure from crop residues is currently not considered in life cycle assessment practice. We therefore present a consistent framework for characterizing human toxicological impacts associated with pesticides applied to agricultural crops in the frame of life cycle impact assessment based on state-of-the-art data and methods. We combine a dynamic multicrop plant uptake model designed for evaluating human exposure to residues for a wide range of pesticide-crop combinations with latest findings of pesticide dissipation kinetics in crops and post-harvest food processing. Outcome is a set of intake fractions and characterization factors for 875 organic pesticides and six major food crops along with specific confidence intervals for each factor. Intake fractions aggregating exposure via crop residues and exposure via fractions lost to air and soil for pesticides applied to agricultural crops vary between 10−8 and 10−1 kg intake per kilogram applied as a function of pesticide and crop. Intake fractions are typically highest for lettuce and tomato and lowest for potato due to differences in application times before crop harvest and soil as additional barrier for uptake into potato tubers. Uncertainty in intake fractions is mainly associated with dissipation dynamics in crops, where results demonstrate that using pesticide- and crop-specific data is crucial. Combined with the uncertainty in effect modeling, characterization factors per pesticide and crop show squared geometric mean standard deviations ranging from 38 to 15,560 over a variability range across pesticide-crop combinations of 10 orders of magnitude. Our framework is operational for use in current life cycle impact assessment models, is made available for USEtox, and closes an important gap in the assessment of human exposure to pesticides. For ready use in life cycle assessment studies, we present pesticide-crop combination-specific characterization factors normalized to pesticide mass applied and provide default data for application times and loss due to post-harvest food processing. When using our data, we emphasize the need to consult current pesticide regulation, since each pesticide is registered for use on certain crops only, which varies between countries.

Aggregated indicator to assess land use impacts in life cycle assessment (LCA) based on the economic value of ecosystem services

Soils are one of earth's essential natural resources, supporting nearly all terrestrial life. By and large, current life cycle impact assessment (LCIA) methodologies are limited in their assessment of potential land use impacts in terms of terrestrial biodiversity loss. The land use life cycle impact assessment (LULCIA) project spearheaded by the United Nations Environment Programme/Society of Environmental Toxicology and Chemistry (UNEP/SETAC) Life Cycle Initiative recently broadened the scope of land use evaluation in life cycle assessment (LCA) by encompassing six additional indicators that represent ecosystem provision and regulation services, as defined in the Millennium Ecosystem Assessment (2005). Although LCIA methodology is more comprehensive with regards to relevant impact pathways linked to land use, the development could potentially decrease the capacity of LCA as a decision support system by increasing the number of indicators from one to seven for the assessment of the land use impact category alone. To overcome this limitation, the project proposes a new LCIA method to estimate the decrease in value of the ecosystem services provided to society due to land use. The six midpoint land use indicators proposed by the LULCIA project are further modeled into a new area of protection, resources and ecosystem services, based on a functional approach. To do so, indicators expressed in biophysical units are converted into monetary units based on the economic valuation of the reduction of a given ecosystem service. The loss of provision services biotic production and fresh water recharge are estimated through productivity loss and water supply cost, respectively. The regulation services erosion resistance and mechanical and physicochemical water filtration are estimated through the cost of erosion mitigation measures and water purification process costs, respectively. The climate regulation potential is estimated through the social carbon cost: a decrease in carbon sequestration by soils is considered equivalent to an amount of carbon emitted in the atmosphere. We also propose to consider the local socioeconomic context by evaluating the economic adaptation capacity of countries: impacts on the resources and ecosystem services area of protection are only accounted for when the country has the capacity to adapt (while indirect impacts would be calculated by assessing the burdens of the adaptation scenario by performing a full LCA of these adaptation measures). The application of the method is illustrated through a case study evaluating the cradle-to-gate land use impacts of three bio-based polymers (biopolyethylene, polylactic acid and thermoplastic starch) produced in Brazil, Italy, Thailand and the United States. Impact scores are not only influenced by the biophysical specificity of the studied systems (e.g. crop yield affecting the inventory flow, type of biome affecting impact characterisation) but also by the local socioeconomic capacity to compensate for an ecosystem service loss and available compensation measures and technologies. In this case study, thermoplastic starch appears to have fewer impacts on land use and ecosystem services than biopolyethylene or polylactic acid. Overall, the research demonstrates the feasibility of further modeling the biophysical indicators of land use into an economic metric. This additional and complementary modeling step is meant to facilitate the interpretation of LCA results, enabling discussions on the relevance of the biophysical indicators affecting the loss of ecosystem services from land use. It may also be used as an explicit weighting scheme to aggregate the midpoint results into a single value expressing the social cost to compensate for the loss of the ecosystem services.