Abstract:The world faces an increasing need to phase out harmful chemicals and design sustainable alternatives across various consumer products and industrial applications. Alternatives assessment is an emerging field focusing on...
“…Such improvements are mainly related to increasing the spatiotemporal and population-level resolution of impact estimates and extending the coverage and quality of substance, exposure, and dose-response information (Fantke et al 2018a,b;Kirchhübel & Fantke 2019;Crenna et al 2020;Gentil et al 2020;Holmquist et al 2020). Furthermore, a series of recent studies has demonstrated that environmentally mediated exposure from chemical emissions is less important for overall exposure than consumer exposure to chemical constituents in products (Shin et al 2015;Ernstoff et al 2016;Csiszar et al 2017;Ring et al 2019;Fantke et al 2020b;Jolliet et al 2021). Hence, including pathways related to chemicals in consumer products into toxicity characterization frameworks is crucial for considering all relevant pathways.…”
Purpose
Reducing chemical pressure on human and environmental health is an integral part of the global sustainability agenda. Guidelines for deriving globally applicable, life cycle–based indicators are required to consistently quantify toxicity impacts from chemical emissions as well as from chemicals in consumer products. In response, we elaborate the methodological framework and present recommendations for advancing near-field/far-field exposure and toxicity characterization, and for implementing these recommendations into the scientific consensus model USEtox.
Methods
An expert taskforce was convened by the Life Cycle Initiative hosted by UN Environment to expand existing guidance for evaluating human toxicity impacts from exposure to chemical substances. This taskforce evaluated scientific advances since the original release of USEtox and identified two major aspects that required refinement, namely integrating near-field and far-field exposure, and improving human dose-response modeling. Dedicated efforts have led to a set of recommendations to address these aspects in an update of USEtox, while ensuring consistency with the boundary conditions for characterizing life cycle toxicity impacts and being aligned with recommendations from agencies that regulate chemical exposure. The proposed updated USEtox framework was tested in an illustrative rice production and consumption case study.
Results and discussion
On the exposure side, a matrix system is proposed and recommended to integrate far-field exposure from environmental emissions with near-field exposure from chemicals in various consumer product types. Consumer exposure is addressed via sub-models for each product type to account for product type-specific characteristics and exposure settings. Case study results illustrate that product use–related exposure dominates overall life cycle exposure. On the effect side, a probabilistic dose-response approach combined with a decision tree for identifying reliable points of departure is proposed for non-cancer effects, following recent guidance from the World Health Organization. This approach allows for explicitly considering both uncertainty and human variability in toxicity effect factors. Factors reflecting disease severity are proposed to distinguish cancer from non-cancer effects and within the latter to discriminate reproductive/developmental and other non-cancer effects. All proposed aspects have been consistently implemented into the original USEtox framework.
Conclusions
The recommended methodological advancements address several key limitations in earlier approaches. Next steps are to test the new characterization framework in additional case studies and to close remaining research gaps. Our framework is applicable for evaluating chemical emissions and product-related exposure in life cycle assessment, chemical alternatives assessment and chemical substitution, consumer exposure and risk screening, and high-throughput chemical prioritization.
“…Such improvements are mainly related to increasing the spatiotemporal and population-level resolution of impact estimates and extending the coverage and quality of substance, exposure, and dose-response information (Fantke et al 2018a,b;Kirchhübel & Fantke 2019;Crenna et al 2020;Gentil et al 2020;Holmquist et al 2020). Furthermore, a series of recent studies has demonstrated that environmentally mediated exposure from chemical emissions is less important for overall exposure than consumer exposure to chemical constituents in products (Shin et al 2015;Ernstoff et al 2016;Csiszar et al 2017;Ring et al 2019;Fantke et al 2020b;Jolliet et al 2021). Hence, including pathways related to chemicals in consumer products into toxicity characterization frameworks is crucial for considering all relevant pathways.…”
Purpose
Reducing chemical pressure on human and environmental health is an integral part of the global sustainability agenda. Guidelines for deriving globally applicable, life cycle–based indicators are required to consistently quantify toxicity impacts from chemical emissions as well as from chemicals in consumer products. In response, we elaborate the methodological framework and present recommendations for advancing near-field/far-field exposure and toxicity characterization, and for implementing these recommendations into the scientific consensus model USEtox.
Methods
An expert taskforce was convened by the Life Cycle Initiative hosted by UN Environment to expand existing guidance for evaluating human toxicity impacts from exposure to chemical substances. This taskforce evaluated scientific advances since the original release of USEtox and identified two major aspects that required refinement, namely integrating near-field and far-field exposure, and improving human dose-response modeling. Dedicated efforts have led to a set of recommendations to address these aspects in an update of USEtox, while ensuring consistency with the boundary conditions for characterizing life cycle toxicity impacts and being aligned with recommendations from agencies that regulate chemical exposure. The proposed updated USEtox framework was tested in an illustrative rice production and consumption case study.
Results and discussion
On the exposure side, a matrix system is proposed and recommended to integrate far-field exposure from environmental emissions with near-field exposure from chemicals in various consumer product types. Consumer exposure is addressed via sub-models for each product type to account for product type-specific characteristics and exposure settings. Case study results illustrate that product use–related exposure dominates overall life cycle exposure. On the effect side, a probabilistic dose-response approach combined with a decision tree for identifying reliable points of departure is proposed for non-cancer effects, following recent guidance from the World Health Organization. This approach allows for explicitly considering both uncertainty and human variability in toxicity effect factors. Factors reflecting disease severity are proposed to distinguish cancer from non-cancer effects and within the latter to discriminate reproductive/developmental and other non-cancer effects. All proposed aspects have been consistently implemented into the original USEtox framework.
Conclusions
The recommended methodological advancements address several key limitations in earlier approaches. Next steps are to test the new characterization framework in additional case studies and to close remaining research gaps. Our framework is applicable for evaluating chemical emissions and product-related exposure in life cycle assessment, chemical alternatives assessment and chemical substitution, consumer exposure and risk screening, and high-throughput chemical prioritization.
“…High throughput quantitative exposure assessment is performed according to the product intake fraction (PiF) framework (Fantke et al., 2016; Fantke, Huang et al. 2020; Jolliet et al., 2015) and its implementation within the USEtox model, successively determining the amount of chemical applied in product per user and per day, the corresponding exposure in mg/kg/d and the associated risks, hazard quotients, or health impacts (Fig. 1).…”
Section: Methodsmentioning
confidence: 99%
“…These data and product usage methods have been used within a screening‐level exposure model to inform chemical prioritization (Isaacs et al., 2014), which had some limitations on the exposure side, including lower‐tier conservative assumptions that do not account for the mass balance nature of competing processes, such as volatilization and dermal uptake on skin surface. On the other hand, more elaborate, higher tier mass balance‐based models have been developed to estimate transport, fate, exposure associated with multiple chemical emissions, and usage along the life cycles of products and services (Csiszar, Ernstoff, Fantke, Meyer, & Jolliet, 2016; Fantke, Ernstoff, Huang, Csiszar, & Jolliet, 2016; Fantke, Huang, Overcash, Griffing, & Jolliet, 2020) for high‐throughput screening of cosmetics, and have been consolidated within an extended USEtox near‐field and far‐field model, but to date have incorporated relatively limited data on chemical and product usage.…”
The ubiquitous presence of more than 80,000 chemicals in thousands of consumer products used on a daily basis stresses the need for screening a broader set of chemicals than the traditional well‐studied suspect chemicals. This high‐throughput screening combines stochastic chemical‐product usage with mass balance‐based exposure models and toxicity data to prioritize risks associated with household products. We first characterize product usage using the stochastic SHEDS‐HT model and chemical content in common household products from the CPDat database, the chemical amounts applied daily varying over more than six orders of magnitude, from mg to kg. We then estimate multi‐pathways near‐ and far‐field exposures for 5,500 chemical‐product combinations, applying an extended USEtox model to calculate product intake fractions ranging from 0.001 to ∼1, and exposure doses varying over more than nine orders of magnitude. Combining exposure doses with chemical‐specific dose–responses and reference doses shows that risks can be substantial for multiple home maintenance products, such as paints or paint strippers, for some home‐applied pesticides, leave‐on personal care products, and cleaning products. Sixty percent of the chemical‐product combinations have hazard quotients exceeding 1, and 9% of the combinations have lifetime cancer risks exceeding 10−4. Population‐level impacts of household products ingredients can be substantial, representing 5 to 100 minutes of healthy life lost per day, with users’ exposures up to 103 minutes per day. To address this issue, present mass balance‐based models are already able to provide exposure estimates for both users and populations. This screening study shows large variations of up to 10 orders of magnitude in impact across both chemicals and product combinations, demonstrating that prioritization based on hazard only is not acceptable, since it would neglect orders of magnitude variations in both product usage and exposure that need to be quantified. To address this, the USEtox suite of mass balance‐based models is already able to provide exposure estimates for thousands of product‐chemical combinations for both users and populations. The present study calls for more scrutiny of most impacting chemical‐product combinations, fully ensuring from a regulatory perspective consumer product safety for high‐end users and using protective measures for users.
“…A recent multiphase project to identify a resin for additive manufacturing safer than those currently used in stereolithography provides an example of applying a life cycle‐based approach to understanding the exposure potential for various stakeholders at different stages as well as a methodology for comparing impacts across all life cycle stages of the resin (Overcash ). Presenters noted the potential that life cycle‐based methods, paired with high throughput exposure and toxicity approaches, can play in addressing data gaps in alternatives assessment (Fantke et al ; Overcash et al ).…”
Section: Advancing the Science Of Alternatives Assessmentmentioning
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