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Purpose: Although a wide number of industrial processes routinely release radionuclides into the environment, the resulting potential impacts on human health have been largely overlooked in life cycle assessment (LCA). As part of the Life Cycle Initiative project on Global Guidance for Life Cycle Impact Assessment Indicators and Methods (GLAM), we aim to develop a consensus-based source-to-damage framework and factors for characterizing human health damage from ionizing radiation in LCA. Methods: Our framework comprises four modules. The fate and exposure modules are based on UCrad, an earlier developed compartment-based environmental model for radionuclides. The focus of the present work is on the dose response and severity modules, which are based on most recent data from the International Committee on Radiological Protection and the Global Burden of Disease project series. The characterization factors are expressed in terms of DALY per kBq released. Results and discussions: We obtain characterization factors for 115 radionuclides and 8 environmental compartments. To evaluate our approach, we compare both effect factors (combining dose response and severity) and characterization factors with those proposed in earlier studies. Our analysis demonstrates that differences are explicable by the different approaches used in the fate and exposure modelling. We also test the sensitivity of our factors to different approaches for filling data gaps, suggesting that our factors are robust. Finally, we apply our factors in an illustrative case study on rice production and consumption under various scenarios to identify dominant radionuclides and how these differ when other approaches are used. Conclusions: Our framework is aligned with widely adopted methodologies for human health impact assessment, thus enabling robust comparisons, and covers nearly all radionuclides released by anthropogenic activities, including those

Decisions about the development of new marketed technologies or products invariably come with consequences for economy, society and the environment. Environmental and health risk assessment on the one hand and sustainability assessment on the other hand are tools that offer different but complementary information about such consequences. Conflicts or synergies between the two tools may arise when there are trade-offs between considerations of specific risks and safety versus long-term sustainability. There is a compelling case for a combined assessment of both sustainability and risks, also in support of a successful safe and sustainable-by-design (SSbD) approach, but this is not straightforward. We offer a roadmap showing when the two assessment tools should be applied together and how to combine them in a consistent way, to support more robust decision-making. Four alternative approaches are evaluated against six performance criteria to recommend an approach that makes use of the broader and more generic sustainability assessment as a baseline and includes iterative applications of risk and sustainability assessment elements to increase specificity, reliability and relevance of the assessment results. The recommended approach provides a basis for better-informed decisions about technology choices for policy and societal stakeholders.

We evaluate fine particulate matter (PM2.5) exposure-response models to propose a consistent set of global effect factors for product and policy assessments across spatial scales and across urban and rural environments. Relationships among exposure concentrations and PM2.5-attributable health effects largely depend on location, population density, and mortality rates. Existing effect factors build mostly on an essentially linear exposure-response function with coefficients from the American Cancer Society study. In contrast, the Global Burden of Disease analysis offers a nonlinear integrated exposure-response (IER) model with coefficients derived from numerous epidemiological studies covering a wide range of exposure concentrations. We explore the IER, additionally provide a simplified regression as a function of PM2.5 level, mortality rates, and severity, and compare results with effect factors derived from the recently published global exposure mortality model (GEMM). Uncertainty in effect factors is dominated by the exposure-response shape, background mortality, and geographic variability. Our central IER-based effect factor estimates for different regions do not differ substantially from previous estimates. However, IER estimates exhibit significant variability between locations as well as between urban and rural environments, driven primarily by variability in PM2.5 concentrations and mortality rates. Using the IER as the basis for effect factors presents a consistent picture of global PM2.5-related effects for use in product and policy assessment frameworks.

We evaluate fine particulate matter (PM2.5) exposure-response models to propose a consistent set of global effect factors for product and policy assessments across spatial scales and across urban and rural environments. Relationships among exposure concentrations and PM2.5-attributable health effects largely depend on location, population density, and mortality rates. Existing effect factors build mostly on an essentially linear exposure-response function with coefficients from the American Cancer Society study. In contrast, the Global Burden of Disease analysis offers a nonlinear integrated exposure-response (IER) model with coefficients derived from numerous epidemiological studies covering a wide range of exposure concentrations. We explore the IER, additionally provide a simplified regression as a function of PM2.5 level, mortality rates, and severity, and compare results with effect factors derived from the recently published global exposure mortality model (GEMM). Uncertainty in effect factors is dominated by the exposure-response shape, background mortality, and geographic variability. Our central IER-based effect factor estimates for different regions do not differ substantially from previous estimates. However, IER estimates exhibit significant variability between locations as well as between urban and rural environments, driven primarily by variability in PM2.5 concentrations and mortality rates. Using the IER as the basis for effect factors presents a consistent picture of global PM2.5-related effects for use in product and policy assessment frameworks.

Semivolatile organic compounds (SVOCs) are ubiquitous in the indoor environment and a priority for exposure assessment because of the environmental health concerns that they pose. Direct air-to-skin dermal uptake has been shown to be comparable to the inhalation intake for compounds with certain chemical properties. In this study, we aim to further understand the transport of these types of chemicals through the skin, specifically through the stratum corneum (SC). Our assessment is based on collecting three sequential forehead skin wipes, each hypothesized to remove pollutants from successively deeper skin layers, and using these wipe analyses to determine the skin concentration profiles. The removal of SVOCs with repeated wipes reveals the concentration profiles with depth and provides a way to characterize penetration efficiency and potential transfer to blood circulation. We used a diffusion model applied to surface skin to simulate concentration profiles of SVOCs and compared them with the measured values. We found that two phthalates, dimethyl and diethyl phthalates, penetrate deeper into skin with similar exposure compared to other phthalates and targeted SVOCs, an observation supported by the model results as well. We also report the presence of statistically significant declining patterns with skin depth for most SVOCs, indicating that their diffusion through the SC is relevant and eventually can reach the blood vessels in the vascularized dermis. Finally, using a nontarget approach, we identified skin oxidation products, linked to respiratory irritation symptoms, formed from the reaction between ozone and squalene.

We evaluate fine particulate matter (PM2.5) exposure–response models to propose a consistent set of global effect factors for product and policy assessments across spatial scales and across urban and rural environments. Relationships among exposure concentrations and PM2.5-attributable health effects largely depend on location, population density, and mortality rates. Existing effect factors build mostly on an essentially linear exposure–response function with coefficients from the American Cancer Society study. In contrast, the Global Burden of Disease analysis offers a nonlinear integrated exposure–response (IER) model with coefficients derived from numerous epidemiological studies covering a wide range of exposure concentrations. We explore the IER, additionally provide a simplified regression as a function of PM2.5 level, mortality rates, and severity, and compare results with effect factors derived from the recently published global exposure mortality model (GEMM). Uncertainty in effect factors is dominated by the exposure–response shape, background mortality, and geographic variability. Our central IER-based effect factor estimates for different regions do not differ substantially from previous estimates. However, IER estimates exhibit significant variability between locations as well as between urban and rural environments, driven primarily by variability in PM2.5 concentrations and mortality rates. Using the IER as the basis for effect factors presents a consistent picture of global PM2.5-related effects for use in product and policy assessment frameworks.

A practical challenge in LCA for comparing pesticide application in different agricultural practices is the agreement on how to quantify the amount emitted, while only the amount applied to the field is known. Main goal of this paper is to present an international effort carried out to reach agreement on recommended default agricultural pesticide emission fractions to environmental media. Consensual decisions on the assessment framework are (a) primary distributions are used as inputs for LCIA, while further investigating how to assess secondary emissions, (b) framework and LCA application guidelines and documentation will be compiled, (c) the emission framework will be based on modifying PestLCI 2.0, (d) drift values will be provided by German, Dutch and other drift modelers, (e) pesticide application methods will be complemented to develop scenarios for tropical regions, (f) climate, soil and application method scenarios will be based on sensitivity analysis, (g) default emission estimates for LCA will be derived from production-weighted averages, and (h) emission fractions will be reported spatially disaggregated. Recommendations for LCA practitioners and database developers are (a) LCA studies should state whether the agricultural field belongs to technosphere or ecosphere, (b) additional information needs to be reported in LCI (e.g. pesticide mass applied), (c) emissions after primary distribution and secondary fate processes should be reported, (d) LCIA methods should allow for treating the field as part of technosphere and ecosphere, (e) fate and exposure processes should be included in LCIA (e.g. crop uptake), (f) default emission estimates should be used in absence of detailed scenario data, (g) and all assumptions should be reported. The recommended pesticide emission fractions results and recommendations are presented and disseminated to strive for broad acceptance at a dedicated stakeholder workshop back-to-back with the current LCA Food 2016 conference

A practical challenge in LCA for comparing pesticide application in different agricultural practices is the agreement on how to quantify the amount emitted, while only the amount applied to the field is known. Main goal of this paper is to present an international effort carried out to reach agreement on recommended default agricultural pesticide emission fractions to environmental media. Consensual decisions on the assessment framework are (a) primary distributions are used as inputs for LCIA, while further investigating how to assess secondary emissions, (b) framework and LCA application guidelines and documentation will be compiled, (c) the emission framework will be based on modifying PestLCI 2.0, (d) drift values will be provided by German, Dutch and other drift modelers, (e) pesticide application methods will be complemented to develop scenarios for tropical regions, (f) climate, soil and application method scenarios will be based on sensitivity analysis, (g) default emission estimates for LCA will be derived from production-weighted averages, and (h) emission fractions will be reported spatially disaggregated. Recommendations for LCA practitioners and database developers are (a) LCA studies should state whether the agricultural field belongs to technosphere or ecosphere, (b) additional information needs to be reported in LCI (e.g. pesticide mass applied), (c) emissions after primary distribution and secondary fate processes should be reported, (d) LCIA methods should allow for treating the field as part of technosphere and ecosphere, (e) fate and exposure processes should be included in LCIA (e.g. crop uptake), (f) default emission estimates should be used in absence of detailed scenario data, (g) and all assumptions should be reported. The recommended pesticide emission fractions results and recommendations are presented and disseminated to strive for broad acceptance at a dedicated stakeholder workshop back-to-back with the current LCA Food 2016 conference

Purpose The life cycle impact assessment (LCIA) guidance flagship project of the United Nations Environment Programme (UNEP)/Society of Environmental Toxicology and Chemistry (SETAC) Life Cycle Initiative aims at providing global guidance and building scientific consensus on environmental LCIA indicators. This paper presents the progress made since 2013, preliminary results obtained for each impact category and the description of a rice life cycle assessment (LCA) case study designed to test and compare LCIA indicators. Methods The effort has been focused in a first stage on impacts of global warming, fine particulate matter emissions, water use and land use, plus cross-cutting issues and LCAbased footprints. The paper reports the process and progress and specific results obtained in the different task forces (TFs). Additionally, a rice LCA case study common to all TF has been developed. Three distinctly different scenarios of producing and cooking rice have been defined and underlined with life cycle inventory data. These LCAs help testing impact category indicators which are being developed and/or selected in the harmonisation process. The rice LCA case study further helps to ensure the practicality of the finally recommended impact category indicators. Results and discussion The global warming TF concludes that analysts should explore the sensitivity of LCA results to metrics other than GWP. The particulate matter TF attained initial guidance of how to include health effects from PM2.5 exposures consistently into LCIA. The biodiversity impacts of land use TF suggests to consider complementary metrics besides species richness for assessing biodiversity loss. The water use TF is evaluating two stress-based metrics, AWaRe and an alternative indicator by a stakeholder consultation. The cross-cutting issues TF agreed upon maintaining disabilityadjusted life years (DALY) as endpoint unit for the safeguard subject "human health"

A practical challenge in LCA for comparing pesticide application in different agricultural practices is the agreement on how to quantify the amount emitted, while only the amount applied to the field is known. Main goal of this paper is to present an international effort carried out to reach agreement on recommended default agricultural pesticide emission fractions to environmental media. Consensual decisions on the assessment framework are (a) primary distributions are used as inputs for LCIA, while further investigating how to assess secondary emissions, (b) framework and LCA application guidelines and documentation will be compiled, (c) the emission framework will be based on modifying PestLCI 2.0, (d) drift values will be provided by German, Dutch and other drift modelers, (e) pesticide application methods will be complemented to develop scenarios for ropical regions, (f) climate, soil and application method scenarios will be based on sensitiv ity analysis, (g) default emission estimates for LCA will be derived from production-weighted averages, and (h) emission fractions will be reported spatially disaggregated. Recommendations for LCA practitioners and database developers are (a) LCA studies should state whether the agricultural field belongs to technosphere or ecosphere, (b) additional information needs to be reported in LCI (e.g. pesticide mass applied), (c) emissions after primary distribution and secondary fate processes should be reported, (d) LCIA methods should allow for treating the field as part of technosphere and ecosphere, (e) fate and exposure processes should be included in LCIA (e.g. crop uptake), (f) default emission estimates should be used in absence of detailed scenario data, (g) and all assumptions should be reported. The recommended pesticide emission fractions results and recommendations are presented and disseminated to strive for broad acceptance at a dedicated stakeholder workshop back-to-back with the current LCA F

The 2010 Global Burden of Disease report demonstrates that fine particulate matter (PM2.5) pollution is the major environmental contributor to mortality. Exposures outdoors (ambient) and indoors (household) contribute almost qually to this burden. Unfortunately, the health impacts from exposure to PM2.5 are often excluded from life cycle impact assessment (LCIA) used for characterizing environmental performance of products and services. This is in large part because of the lack of well-vetted harmonized guidance about how to consistently assess the exposures and impacts of indoor and outdoor emissions of PM2.5 and its precursors. We present a modeling framework for calculating exposure factors for indoor and outdoor emissions of primary PM2.5 and secondary PM2.5 precursors, and a roadmap for further refining this modelling framework for operational use in LCIA. The framework was developed over the last three years by a task force convened under auspices of the Society of Environmental Toxicology and Chemistry (SETAC)/United Nations Environment Program (UNEP) Life-Cycle Initiative to provide guidance and methods for estimating the health impacts associated with PM2.5 exposure and to re commend PM2.5 characterization factors for application in life cycle assessment. The framework involves three stages--analyzing PM2.5 fate and exposure (including indoor and outdoor urban/rural environments), modeling exposure-response, and the integration of exposure-response and PM2.5 exposure reflecting population and location characteristics. We introduce the overall framework and present key components of the exposure assessment underlying the health impact characterization factors. The exposure metric at the center of this analysis is the population intake fraction (iF). Our exposure model is organized as a mass balance matrix that tracks the global fate of primary PM2.5 and secondary PM2.5 precursor emissions (both indoors and outdoors) as an embedded system of comp

Exposure to fine particulate matter (PM2.5) pollution is a major contributor to human disease burden as continuously shown in the Global Burden of Disease study series. Exposures to PM2.5 concentration outdoors and indoors contribute almost equally to this burden. Despite the importance, health impacts from exposure to PM2.5 are often excluded from life cycle impact assessment (LCIA) characterization profiles. This is in large part because of the lack of well-vetted harmonized guidance about how to consistently assess the exposures and impacts of indoor and outdoor emissions of PM2.5 and its precursors. We present a framework for calculating characterization factors for indoor and outdoor emissions of primary PM2.5 and secondary PM2.5 precursors, and a roadmap for further refining this modelling framework for operational use in LCIA. The framework was developed over the last three years by a task force convened under SETAC/UNEP auspices. A recent SETAC Pellston Workshop® was convened to formalize guidance and methods for estimating the health impacts associated with PM2.5 exposure and to recommend PM2.5 characterization factors for application in life cycle assessment. The framework involves three stages–analyzing PM2.5 fate and exposure (including indoor and outdoor urban/rural nvironments), modeling exposure-response, and the integration of exposure-response and PM2.5 exposure reflecting population and location characteristics. Our exposure model is organized as a mass balance matrix that tracks the global fate of primary PM2.5 and secondary PM2.5 precursor emissions (both indoors and outdoors) as an embedded system of ompartments including urban environments, rural environments, and indoor environments within urban and rural areas. After presenting the model structure, we will review initial results and will present geographic variability, discuss key uncertainties, and evaluate our model using results from o

Exposure to fine particulate matter (PM2.5) is a major contributor to the global human disease burden. The indoor environment is of particular importance when considering the health effects associated with PM2.5 exposures because people spend the majority of their time indoors and PM2.5 exposures per unit mass emitted indoors are two to three orders of magnitude larger than exposures to outdoor emissions. Variability in indoor PM2.5 intake fraction (iFin,total), which is defined as the integrated cumulative intake of PM2.5 per unit of emission, is driven by a combination of building-specific, human-specific, and pollutant-specific factors. Due to a limited availability of data characterizing these factors, however, indoor emissions and intake of PM2.5 are not commonly considered when evaluating the environmental performance of product life cycles. With the aim of addressing this barrier, a literature review was conducted and data characterizing factors influencing iFin,total were compiled. In addition to providing data for the calculation of iFin,total in various indoor environments and for a range geographic regions, this paper discusses remaining limitations to the incorporation of PM2.5-derived health impacts into life cycle assessments and makes recommendations regarding future research. This article is protected by copyright. All rights reserved.

This study assesses for California how increasing end-use electrical energy efficiency from installing residential insulation impacts exposures and disease burden from power-plant pollutant emissions. Installation of fiberglass attic insulation in the nearly 3 million electricity-heated homes throughout California is used as a case study. The pollutants nitrous oxides (NOx), sulfur dioxide (SO2), fine particulate matter (PM2.5), benzo(a)pyrene, benzene, and naphthalene are selected for the assessment. Exposure is characterized separately for rural and urban environments using the CalTOX model, which is a key input to the US Environmental Protection Agency (EPA) Tool for the Reduction and Assessment of Chemicals and other environmental Impacts (TRACI). The output of CalTOX provides for urban and rural populations emissions-to-intake factors, which are expressed as an individual intake fraction (iFi). The typical iFi from power plant emissions are on the order of 10-13 (g intake per g emitted) in urban and rural regions. The cumulative (rural and urban) product of emissions, population, and iFi is combined with toxic effects factors to determine human damage factors (HDFs). HDF are expressed as disability adjusted life years (DALYs) per kilogram pollutant emitted. The HDF approach is applied to the insulation case study. Upgrading existing residential insulation to US Department of Energy (DOE) recommended levels eliminates over the assumed 50-year lifetime of the insulation an estimated 1000 DALYs from power-plant emissions per million tonne (Mt) of insulation installed, mostly from the elimination of PM2.5 emissions. In comparison, the estimated burden from the manufacture of this insulation in DALYs per Mt is roughly four orders of magnitude lower than that avoided.

This study assesses for California how increasing end-use electrical energy efficiency from installing residential insulation impacts exposures and disease burden from power-plant pollutant emissions. Installation of fiberglass attic insulation in the nearly 3 million electricity-heated homes throughout California is used as a case study. The pollutants nitrous oxides (NOx), sulfur dioxide (SO2), fine particulate matter (PM2.5), benzo(a)pyrene, benzene, and naphthalene are selected for the assessment. Exposure is characterized separately for rural and urban environments using the CalTOX model, which is a key input to the US Environmental Protection Agency (EPA) Tool for the Reduction and Assessment of Chemicals and other environmental Impacts (TRACI). The output of CalTOX provides for urban and rural populations emissions-to-intake factors, which are expressed as an individual intake fraction (iFi). The typical iFi from power plant emissions are on the order of 10-13 (g intake per g emitted) in urban and rural regions. The cumulative (rural and urban) product of emissions, population, and iFi is combined with toxic effects factors to determine human damage factors (HDFs). HDF are expressed as disability adjusted life years (DALYs) per kilogram pollutant emitted. The HDF approach is applied to the insulation case study. Upgrading existing residential insulation to US Department of Energy (DOE) recommended levels eliminates over the assumed 50-year lifetime of the insulation an estimated 1000 DALYs from power-plant emissions per million tonne (Mt) of insulation installed, mostly from the elimination of PM2.5 emissions. In comparison, the estimated burden from the manufacture of this insulation in DALYs per Mt is roughly four orders of magnitude lower than that avoided.

Purpose Fine particulate matter (PM2.5) is considered to be one of the most important environmental factors contributing to the global human disease burden. However, due to the lack of broad consensus and harmonization in the life cycle assessment (LCA) community, there is no clear guidance on how to consistently include health effects from PM2.5 exposure in LCA practice. As a consequence, different models are currently used to assess life cycle impacts for PM2.5, sometimes leading to inconsistent results. In a global effort initiated by the United Nations Environment Programme (UNEP)/Society for Environmental Toxicology and Chemistry(SETAC) Life Cycle Initiative, respiratory inorganics’ impacts expressed as health effects from PM2.5 exposure were selected as one of the initial impact categories to undergo review with the goal of providing global guidance for implementation in life cycle impact assessment (LCIA). The goal of this paper is to summarize the current knowledge and practice for assessing health effects from PM2.5 exposure and to provide recommendations for their consistent integration into LCIA. Methods A task force on human health impacts was convened to build the framework for consistently quantifying health effects from PM2.5 exposure and for recommending PM2.5 characterization factors. In an initial Guidance Workshop,existing literature was reviewed and input from a broad range of internationally recognized experts was obtained and discussed. Workshop objectives were to identify the main scientific questions and challenges for quantifying health effects from PM2.5 exposure and to provide initial guidance to the impact quantification process.Results and discussion A set of 10 recommendations was developed addressing (a) the general framework for assessingPM2.5-related health effects, (b) approaches and data to estimate human exposure to PM2.5

We present a risk-based high-throughput screening (HTS) method to identify chemicals for potential health concerns or for which additional information is needed. The method is applied to 180 organic chemicals as a case study. We first obtain information on how the chemical is used and identify relevant use scenarios (e.g., dermal application, indoor emissions). For each chemical and use scenario, exposure models are then used to calculate a chemical intake fraction, or a product intake fraction, accounting for chemical properties and the exposed population. We then combine these intake fractions with use scenario-specific estimates of chemical quantity to calculate daily intake rates (iR; mg/kg/day). These intake rates are compared to oral equivalent doses (OED; mg/kg/day), calculated from a suite of ToxCast in vitro bioactivity assays using in vitro-to-in vivo extrapolation and reverse dosimetry. Bioactivity quotients (BQs) are calculated as iR/OED to obtain estimates of potential impact associated with each relevant use scenario. Of the 180 chemicals considered, 38 had maximum iRs exceeding minimum OEDs (i.e., BQs > 1). For most of these compounds, exposures are associated with direct intake, food/oral contact, or dermal exposure. The method provides high-throughput estimates of exposure and important input for decision makers to identify chemicals of concern for further evaluation with additional information or more refined models.

Human exposure to indoor pollutant concentrations is receiving increasing interest in Life Cycle Assessment (LCA). We address this issue by incorporating an indoor compartment into the USEtox model, as well as by providing recommended parameter values for households in four different regions of the world differing geographically, economically, and socially. With these parameter values, intake fractions and comparative toxicity potentials for indoor emissions of dwellings for different air tightness levels were calculated. The resulting intake fractions for indoor exposure vary by 2 orders of magnitude, due to the variability of ventilation rate, building occupation, and volume. To compare health impacts as a result of indoor exposure with those from outdoor exposure, the indoor exposure characterization factors determined with the modified USEtox model were applied in a case study on cooking in non-OECD countries. This study demonstrates the appropriateness and significance of integrating indoor environments into LCA, which ensures a more holistic account of all exposure environments and allows for a better accountability of health impacts. The model, intake fractions, and characterization factors are made available for use in standard LCA studies via www.usetox.org and in standard LCA software.