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Background Existing models for estimating children’s exposure to chemicals through mouthing currently depends on the availability of chemical- and material-specific experimental migration rates, only covering a few dozen chemicals. Objective This study objective is hence to develop a mouthing exposure model to predict migration into saliva, mouthing exposure, and related health risk from a wide range of chemical-material combinations in children’s products. Methods We collected experimental data on chemical migration from different products into saliva for multiple substance groups and materials, identifying chemical concentration and diffusion coefficient as main properties of influence. To predict migration rates into saliva, we adapted a previously developed migration model for chemicals in food packaging materials. We also developed a regression model based on identified chemical and material properties. Results Our migration predictions correlate well with experimental data (R 2 = 0.85) and vary widely from 8 × 10−7 to 32.7 µg/10 cm2/min, with plasticizers in PVC showing the highest values. Related mouthing exposure doses vary across chemicals and materials from a median of 0.005 to 253 µg/kgBW/d. Finally, we combined exposure estimates with toxicity information to yield hazard quotients and identify chemicals of concern for average and upper bound mouthing behavior scenarios. Significance The proposed model can be applied for predicting migration rates for hundreds of chemical-material combinations to support high-throughput screening.
Nicolò Aurisano; Peter Fantke; Lei Huang; Olivier Jolliet. Estimating mouthing exposure to chemicals in children’s products. Journal of Exposure Science & Environmental Epidemiology 2021, 1 -9.
AMA StyleNicolò Aurisano, Peter Fantke, Lei Huang, Olivier Jolliet. Estimating mouthing exposure to chemicals in children’s products. Journal of Exposure Science & Environmental Epidemiology. 2021; ():1-9.
Chicago/Turabian StyleNicolò Aurisano; Peter Fantke; Lei Huang; Olivier Jolliet. 2021. "Estimating mouthing exposure to chemicals in children’s products." Journal of Exposure Science & Environmental Epidemiology , no. : 1-9.
To meet the nutritional and environmental needs of a growing population, dairy producers must increase milk production while minimizing the farm-gate environmental impact and adapting to the effects of climate change. Here we comprehensively assess the effects of climate change on the environmental performance and productivity of three typical US dairy farms, and evaluate the potential benefits of adaptation strategies and implementation of Beneficial Management Practices (BMPs) for mitigating these effects and the potential increases in environmental impact. Using the Integrated Farm System Model (IFSM), we predicted the productivity and environmental impact of these baseline farms under current emission scenarios and climate projections of 6 general circulation models (GCM), for high and low emission scenarios. We simulated farm-specific BMPs for current and future climate conditions for both unadapted and ‘adapted’ field cultivation plans, based on experiences from other climate locations. Finally, the IFSM predictions were compared to those of two other process-based models to test result robustness. We find that the environmental impact of the three northern US dairy farms (New York, Pennsylvania, and Wisconsin) generally increases by mid-century, if no mitigation measures are taken. Overall, feed production is maintained, as decreased corn grain yields are compensated by increased forage yields. Adoption of farm-specific Beneficial Management Practices can substantially reduce the GHG emissions and nutrient losses from dairy farms under current climate conditions and stabilize the environmental impact in future climate conditions, while maintaining farm productivity (milk and feed production). A comparison of three models corroborates the estimated reductions in methane and ammonia emissions associated with BMPs, as well as the relative trend in P-loss reduction. This study provides a holistic assessment of the impacts of climate change on dairy production systems focusing on both feed production and environmental impacts. It demonstrates the interest of BMPs to both reduce GHG emissions and contribute to more resilient farming systems in a changing climate.
Karin Veltman; C. Alan Rotz; Larry Chase; Joyce Cooper; Chris E. Forest; Peter A. Ingraham; R. César Izaurralde; Curtis D. Jones; Robert E. Nicholas; Matthew D. Ruark; William Salas; Greg Thoma; Olivier Jolliet. Assessing and reducing the environmental impact of dairy production systems in the northern US in a changing climate. Agricultural Systems 2021, 192, 103170 .
AMA StyleKarin Veltman, C. Alan Rotz, Larry Chase, Joyce Cooper, Chris E. Forest, Peter A. Ingraham, R. César Izaurralde, Curtis D. Jones, Robert E. Nicholas, Matthew D. Ruark, William Salas, Greg Thoma, Olivier Jolliet. Assessing and reducing the environmental impact of dairy production systems in the northern US in a changing climate. Agricultural Systems. 2021; 192 ():103170.
Chicago/Turabian StyleKarin Veltman; C. Alan Rotz; Larry Chase; Joyce Cooper; Chris E. Forest; Peter A. Ingraham; R. César Izaurralde; Curtis D. Jones; Robert E. Nicholas; Matthew D. Ruark; William Salas; Greg Thoma; Olivier Jolliet. 2021. "Assessing and reducing the environmental impact of dairy production systems in the northern US in a changing climate." Agricultural Systems 192, no. : 103170.
A critical review of the current state of knowledge of chemical emissions from indoor sources, partitioning among indoor compartments, and the ensuing indoor exposure leads to a proposal for a modular mechanistic framework for predicting human exposure to semivolatile organic compounds (SVOCs). Mechanistically consistent source emission categories include solid, soft, frequent contact, applied, sprayed, and high temperature sources. Environmental compartments are the gas phase, airborne particles, settled dust, indoor surfaces, and clothing. Identified research needs are the development of dynamic emission models for several of the source emission categories and of estimation strategies for critical model parameters. The modular structure of the framework facilitates subsequent inclusion of new knowledge, other chemical classes of indoor pollutants, and additional mechanistic processes relevant to human exposure indoors. The framework may serve as the foundation for developing an open-source community model to better support collaborative research and improve access for application by stakeholders. Combining exposure estimates derived using this framework with toxicity data for different end points and toxicokinetic mechanisms will accelerate chemical risk prioritization, advance effective chemical management decisions, and protect public health.
Clara M. A. Eichler; Elaine A. Cohen Hubal; Ying Xu; Jianping Cao; Chenyang Bi; Charles J. Weschler; Tunga Salthammer; Glenn C. Morrison; Antti Joonas Koivisto; Yinping Zhang; Corinne Mandin; Wenjuan Wei; Patrice Blondeau; Dustin Poppendieck; Xiaoyu Liu; Christiaan J. E. Delmaar; Peter Fantke; Olivier Jolliet; Hyeong-Moo Shin; Miriam L. Diamond; Manabu Shiraiwa; Andreas Zuend; Philip K. Hopke; Natalie Von Goetz; Markku Kulmala; John C. Little. Assessing Human Exposure to SVOCs in Materials, Products, and Articles: A Modular Mechanistic Framework. Environmental Science & Technology 2020, 55, 25 -43.
AMA StyleClara M. A. Eichler, Elaine A. Cohen Hubal, Ying Xu, Jianping Cao, Chenyang Bi, Charles J. Weschler, Tunga Salthammer, Glenn C. Morrison, Antti Joonas Koivisto, Yinping Zhang, Corinne Mandin, Wenjuan Wei, Patrice Blondeau, Dustin Poppendieck, Xiaoyu Liu, Christiaan J. E. Delmaar, Peter Fantke, Olivier Jolliet, Hyeong-Moo Shin, Miriam L. Diamond, Manabu Shiraiwa, Andreas Zuend, Philip K. Hopke, Natalie Von Goetz, Markku Kulmala, John C. Little. Assessing Human Exposure to SVOCs in Materials, Products, and Articles: A Modular Mechanistic Framework. Environmental Science & Technology. 2020; 55 (1):25-43.
Chicago/Turabian StyleClara M. A. Eichler; Elaine A. Cohen Hubal; Ying Xu; Jianping Cao; Chenyang Bi; Charles J. Weschler; Tunga Salthammer; Glenn C. Morrison; Antti Joonas Koivisto; Yinping Zhang; Corinne Mandin; Wenjuan Wei; Patrice Blondeau; Dustin Poppendieck; Xiaoyu Liu; Christiaan J. E. Delmaar; Peter Fantke; Olivier Jolliet; Hyeong-Moo Shin; Miriam L. Diamond; Manabu Shiraiwa; Andreas Zuend; Philip K. Hopke; Natalie Von Goetz; Markku Kulmala; John C. Little. 2020. "Assessing Human Exposure to SVOCs in Materials, Products, and Articles: A Modular Mechanistic Framework." Environmental Science & Technology 55, no. 1: 25-43.
Food and diet life cycle assessment (LCA) studies offer insights on the environmental performance and improvement potential of food systems and dietary patterns. However, the influence of ingredient resolution in food-LCAs is often overlooked. To address this, four distinct decomposition methods were used to determine ingredients for mixed dishes and characterize their environmental impacts, using the carbon footprint of the U.S. daily pizza intake as a case study. Pizza-specific and daily pizza intake carbon footprints varied substantially between decomposition methods. The carbon footprint for vegetarian pizza was 0.18–0.45 kg CO2eq/serving, for meat pizza was 0.56–0.73 kg CO2eq/serving, and for currently consumed pizzas in the U.S. (26.3 g/person/day; 75 pizzas types) was 0.072–0.098 kg CO2eq/person/day. These ranges could be explained by differences in pizza coverage, ingredient resolution, availability of ingredient environmental information, and ingredient adjustability for losses between decomposition methods. From the approaches considered, the USDA National Nutrient Database for Standard Reference, which reports standardized food recipes in relative weights, appears to offer the most appropriate and useful food decompositions for food-LCAs. The influence and limitations of sources of reference flows should be better evaluated and acknowledged in food and diet LCAs.
Katerina Stylianou; Emily McDonald; Victor Fulgoni Iii; Olivier Jolliet. Standardized Recipes and Their Influence on the Environmental Impact Assessment of Mixed Dishes: A Case Study on Pizza. Sustainability 2020, 12, 9466 .
AMA StyleKaterina Stylianou, Emily McDonald, Victor Fulgoni Iii, Olivier Jolliet. Standardized Recipes and Their Influence on the Environmental Impact Assessment of Mixed Dishes: A Case Study on Pizza. Sustainability. 2020; 12 (22):9466.
Chicago/Turabian StyleKaterina Stylianou; Emily McDonald; Victor Fulgoni Iii; Olivier Jolliet. 2020. "Standardized Recipes and Their Influence on the Environmental Impact Assessment of Mixed Dishes: A Case Study on Pizza." Sustainability 12, no. 22: 9466.
We present a list of Chemicals of Concern (CoCs) in plastic toys. We started from available studies reporting chemical composition of toys to group plastic materials, as well as to gather mass fractions and function of chemicals in these materials. Chemical emissions from plastic toys and subsequent human exposures were then estimated using a series of models and a coupled near-field and far-field exposure assessment framework. Comparing human doses with reference doses shows high Hazard Quotients of up to 387 and cancer risk calculated using cancer slope factors of up to 0.0005. Plasticizers in soft plastic materials show the highest risk, with 31 out of the 126 chemicals identified as CoCs, with sum of Hazard Quotients >1 or child cancer risk >10−6. Our results indicate that a relevant amount of chemicals used in plastic toy materials may pose a non-negligible health risk to children, calling for more refined investigations and more human- and eco-friendly alternatives. The 126 chemicals identified as CoCs were compared with other existing regulatory prioritization lists. While some of our chemicals appear in other lists, we also identified additional priority chemicals that are not yet covered elsewhere and thus require further attention. We finally derive for all considered chemicals the maximum Acceptable Chemical Content (ACC) in the grouped toy plastic materials as powerful green chemistry tool to check whether chemical alternatives could create substantial risks.
Nicolò Aurisano; Lei Huang; Llorenç Milà i Canals; Olivier Jolliet; Peter Fantke. Chemicals of concern in plastic toys. Environment International 2020, 146, 106194 .
AMA StyleNicolò Aurisano, Lei Huang, Llorenç Milà i Canals, Olivier Jolliet, Peter Fantke. Chemicals of concern in plastic toys. Environment International. 2020; 146 ():106194.
Chicago/Turabian StyleNicolò Aurisano; Lei Huang; Llorenç Milà i Canals; Olivier Jolliet; Peter Fantke. 2020. "Chemicals of concern in plastic toys." Environment International 146, no. : 106194.
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.
Olivier Jolliet; Lei Huang; Ping Hou; Peter Fantke. High Throughput Risk and Impact Screening of Chemicals in Consumer Products. Risk Analysis 2020, 41, 627 -644.
AMA StyleOlivier Jolliet, Lei Huang, Ping Hou, Peter Fantke. High Throughput Risk and Impact Screening of Chemicals in Consumer Products. Risk Analysis. 2020; 41 (4):627-644.
Chicago/Turabian StyleOlivier Jolliet; Lei Huang; Ping Hou; Peter Fantke. 2020. "High Throughput Risk and Impact Screening of Chemicals in Consumer Products." Risk Analysis 41, no. 4: 627-644.
The first Swiss national dietary survey (MenuCH) was used to screen disease burdens and greenhouse gas emissions (GHG) of Swiss diets (vegan, vegetarian, gluten-free, slimming), with a focus on gender and education level. The Health Nutritional Index (HENI), a novel disease burden-based nutritional index built on the Global Burden of Disease studies, was used to indicate healthiness using comparable, relative disease burden scores. Low whole grain consumption and high processed meat consumption are priority risk factors. Non-processed red meat and dairy make a nearly negligible contribution to disease burden scores, yet are key drivers of diet-related GHGs. Swiss diets, including vegetarian, ranged between 1.1–2.6 tons of CO2e/person/year, above the Swiss federal recommendation 0.6 ton CO2e/person/year for all consumption categories. This suggests that only changing food consumption practices will not suffice towards achieving carbon reduction targets: Systemic changes to food provisioning processes are also necessary. Finally, men with higher education had the highest dietary GHG emissions per gram of food, and the highest disease burden scores. Win–win policies to improve health and sustainability of Swiss diets would increase whole grain consumption for all, and decrease alcohol and processed meat consumption especially for men of higher education levels.
Alexi Ernstoff; Katerina S. Stylianou; Marlyne Sahakian; Laurence Godin; Arnaud Dauriat; Sebastien Humbert; Suren Erkman; Olivier Jolliet. Towards Win–Win Policies for Healthy and Sustainable Diets in Switzerland. Nutrients 2020, 12, 2745 .
AMA StyleAlexi Ernstoff, Katerina S. Stylianou, Marlyne Sahakian, Laurence Godin, Arnaud Dauriat, Sebastien Humbert, Suren Erkman, Olivier Jolliet. Towards Win–Win Policies for Healthy and Sustainable Diets in Switzerland. Nutrients. 2020; 12 (9):2745.
Chicago/Turabian StyleAlexi Ernstoff; Katerina S. Stylianou; Marlyne Sahakian; Laurence Godin; Arnaud Dauriat; Sebastien Humbert; Suren Erkman; Olivier Jolliet. 2020. "Towards Win–Win Policies for Healthy and Sustainable Diets in Switzerland." Nutrients 12, no. 9: 2745.
Evaluating potential hazardous effects of chemicals on ecosystems has always been an important research topic which traditionally done by laboratory or field experiments. Experiment-based ecotoxicity test results are only available for a limited number of chemicals due to the extensive experimental effort and cost. Given the ever-increasing number of chemicals involved in the modern production process and products, rapidly characterizing chemical ecotoxicity at lower costs has become critical for guiding technology and policy development for chemical risk management. In this study, artificial neural network models are developed to predict chemical ecotoxicity (HC50) based on experimental data to fill data gaps in a widely used database (USEtox). To reduce the manual tuning effort on optimal network architecture, a genetic algorithm is investigated to automatically search and configure the network architecture. The resulted neural network model reached an average test R2 of 0.632 and had a trivial difference with the global optimal regarding validation MSE. The findings of this study can rapidly predict the ecotoxicity of chemicals and further help to understand the potential risk of chemicals and develop strategies for risk management.
Ping Hou; Bu Zhao; Olivier Jolliet; Ji Zhu; Peng Wang; Ming Xu. Rapid Prediction of Chemical Ecotoxicity Through Genetic Algorithm Optimized Neural Network Models. ACS Sustainable Chemistry & Engineering 2020, 8, 12168 -12176.
AMA StylePing Hou, Bu Zhao, Olivier Jolliet, Ji Zhu, Peng Wang, Ming Xu. Rapid Prediction of Chemical Ecotoxicity Through Genetic Algorithm Optimized Neural Network Models. ACS Sustainable Chemistry & Engineering. 2020; 8 (32):12168-12176.
Chicago/Turabian StylePing Hou; Bu Zhao; Olivier Jolliet; Ji Zhu; Peng Wang; Ming Xu. 2020. "Rapid Prediction of Chemical Ecotoxicity Through Genetic Algorithm Optimized Neural Network Models." ACS Sustainable Chemistry & Engineering 8, no. 32: 12168-12176.
We developed a Life Cycle based Alternatives Assessment (LCAA) framework for efficiently including quantitative exposure and life cycle impacts in chemical substitution studies.
Peter Fantke; Lei Huang; Michael R. Overcash; Evan Griffing; Olivier Jolliet. Life cycle based alternatives assessment (LCAA) for chemical substitution. Green Chemistry 2020, 22, 1 .
AMA StylePeter Fantke, Lei Huang, Michael R. Overcash, Evan Griffing, Olivier Jolliet. Life cycle based alternatives assessment (LCAA) for chemical substitution. Green Chemistry. 2020; 22 (18):1.
Chicago/Turabian StylePeter Fantke; Lei Huang; Michael R. Overcash; Evan Griffing; Olivier Jolliet. 2020. "Life cycle based alternatives assessment (LCAA) for chemical substitution." Green Chemistry 22, no. 18: 1.
It is well recognized that there are currently limitations in the spatial and temporal resolution of environmental exposure models due to significant variabilities and uncertainties in model inputs and parameters. Here we present the updated Pangea multi-scale multimedia model based on the more spatially resolved, catchment-based hydrological HydroBASINS dataset covering the entire globe. We apply it to predict spatially-explicit exposure concentrations of linear alkylbenzene sulphonate (LAS) and triclosan (TCS) as two chemicals found in homecare (HC) and personal care (PC) products in river catchments across Asia, and test its potential for identifying/prioritizing catchments with higher exposure concentrations. In addition, we also identify the key parameters in the model framework driving higher concentrations and perform uncertainty analyses by applying Monte Carlo simulations on emissions and other non-spatial model inputs. The updated combination of Pangea with the HydroBASINS hydrological data represents a substantial improvement from the previous model with the gridded hydrological dataset (WWDRII) for modelling substance fate, with higher resolution and improved coverage in regions with lower flows, with the results demonstrating good agreement with monitored concentrations for TCS in both the freshwater (R2 = 0.55) and sediment (R2 = 0.81) compartments. The ranking of water basins by Predicted Environmental Concentrations (PECs) was similar for both TCS and LAS, with highest concentrations (Indus, Huang He, Cauvery, Huai He and Ganges) being one to two orders of magnitude greater than the water basins with lowest predicted PECs (Mekong and Brahmaputra). Emissions per unit volume of each catchment, chemical persistence, and river discharge were deemed to be the most influential factors on the variation of predicted PECs. Focusing on the Huang He (Yellow River) water basin, uncertainty confidence intervals (factor 31 for LAS and 6 for TCS) are much lower than the variability of predicted PECs across the Huang He catchments (factors 90,700 for LAS and 13,500 for TCS).
Olivier Jolliet; Cedric Wannaz; John Kilgallon; Lucy Speirs; Antonio Franco; Bernhard Lehner; Karin Veltman; Juliet Hodges. Spatial variability of ecosystem exposure to home and personal care chemicals in Asia. Environment International 2019, 134, 105260 .
AMA StyleOlivier Jolliet, Cedric Wannaz, John Kilgallon, Lucy Speirs, Antonio Franco, Bernhard Lehner, Karin Veltman, Juliet Hodges. Spatial variability of ecosystem exposure to home and personal care chemicals in Asia. Environment International. 2019; 134 ():105260.
Chicago/Turabian StyleOlivier Jolliet; Cedric Wannaz; John Kilgallon; Lucy Speirs; Antonio Franco; Bernhard Lehner; Karin Veltman; Juliet Hodges. 2019. "Spatial variability of ecosystem exposure to home and personal care chemicals in Asia." Environment International 134, no. : 105260.
BackgroundStark racial disparities in disease incidence among American women remains a persistent public health challenge. These disparities likely result from complex interactions between genetic, social, lifestyle, and environmental risk factors. The influence of environmental risk factors, such as chemical exposure, however, may be substantial and is poorly understood.ObjectivesWe quantitatively evaluated chemical-exposure disparities by race/ethnicity and age in United States (US) women by using biomarker data for 143 chemicals from the National Health and Nutrition Examination Survey (NHANES) 1999-2014.MethodsWe applied a series of survey-weighted, generalized linear models using data from the entire NHANES women population and age-group stratified subpopulations. The outcome was chemical biomarker concentration and the main predictor was race/ethnicity with adjustment for age, socioeconomic status, smoking habits, and NHANES cycle.ResultsThe highest disparities across non-Hispanic Black, Mexican American, Other Hispanic, and other race/multiracial women were observed for pesticides and their metabolites, including 2,5-dichlorophenol, o,p’-DDE, beta-hexachlorocyclohexane, and 2,4-dichlorophenol, along with personal care and consumer product compounds. The latter included parabens, monoethyl phthalate, and several metals, such as mercury and arsenic. Moreover, for Mexican American, Other Hispanic, and non-Hispanic black women, there were several exposure disparities that persisted across age groups, such as higher 2,4- and 2,5-dichlorophenol concentrations. Exposure differences for methyl and propyl parabens, however, were the starkest between non-Hispanic black and non-Hispanic white children with average differences exceeding 4 folds.DiscussionsWe systematically evaluated differences in chemical exposures across women of various race/ethnic groups and across age groups. Our findings could help inform chemical prioritization in designing epidemiological and toxicological studies. In addition, they could help guide public health interventions to reduce environmental and health disparities across populations.
Vy Kim Nguyen; Adam Kahana; Julien Heidt; Katelyn Polemi; Jacob Kvasnicka; Olivier J. Jolliet; Justin A. Colacino; Juilen Heidt. A comprehensive analysis of racial disparities in chemical biomarker concentrations in United States women, 1999-2014. 2019, 746867 .
AMA StyleVy Kim Nguyen, Adam Kahana, Julien Heidt, Katelyn Polemi, Jacob Kvasnicka, Olivier J. Jolliet, Justin A. Colacino, Juilen Heidt. A comprehensive analysis of racial disparities in chemical biomarker concentrations in United States women, 1999-2014. . 2019; ():746867.
Chicago/Turabian StyleVy Kim Nguyen; Adam Kahana; Julien Heidt; Katelyn Polemi; Jacob Kvasnicka; Olivier J. Jolliet; Justin A. Colacino; Juilen Heidt. 2019. "A comprehensive analysis of racial disparities in chemical biomarker concentrations in United States women, 1999-2014." , no. : 746867.
Peter Fantke; Thomas E. McKone; Marko Tainio; Olivier Jolliet; Joshua S. Apte; Katerina S. Stylianou; Nicole Illner; Julian D. Marshall; Ernani F. Choma; John S. Evans. Correction to “Global Effect Factors for Exposure to Fine Particulate Matter”. Environmental Science & Technology 2019, 53, 10534 -10534.
AMA StylePeter Fantke, Thomas E. McKone, Marko Tainio, Olivier Jolliet, Joshua S. Apte, Katerina S. Stylianou, Nicole Illner, Julian D. Marshall, Ernani F. Choma, John S. Evans. Correction to “Global Effect Factors for Exposure to Fine Particulate Matter”. Environmental Science & Technology. 2019; 53 (17):10534-10534.
Chicago/Turabian StylePeter Fantke; Thomas E. McKone; Marko Tainio; Olivier Jolliet; Joshua S. Apte; Katerina S. Stylianou; Nicole Illner; Julian D. Marshall; Ernani F. Choma; John S. Evans. 2019. "Correction to “Global Effect Factors for Exposure to Fine Particulate Matter”." Environmental Science & Technology 53, no. 17: 10534-10534.
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 regions and spatial scales. 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 non-linear 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 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 by location, driven primarily by PM2.5 concentrations and mortality rates variations. Using the IER as basis for effect factors presents a consistent picture of global PM2.5-related effects for use in product and policy assessment frameworks.
Peter Fantke; Thomas E. McKone; Marko Tainio; Olivier Jolliet; Joshua Schulz Apte; Katerina S. Stylianou; Nicole Illner; Julian D. Marshall; Ernani F. Choma; John S. Evans. Global Effect Factors for Exposure to Fine Particulate Matter. Environmental Science & Technology 2019, 53, 6855 -6868.
AMA StylePeter Fantke, Thomas E. McKone, Marko Tainio, Olivier Jolliet, Joshua Schulz Apte, Katerina S. Stylianou, Nicole Illner, Julian D. Marshall, Ernani F. Choma, John S. Evans. Global Effect Factors for Exposure to Fine Particulate Matter. Environmental Science & Technology. 2019; 53 (12):6855-6868.
Chicago/Turabian StylePeter Fantke; Thomas E. McKone; Marko Tainio; Olivier Jolliet; Joshua Schulz Apte; Katerina S. Stylianou; Nicole Illner; Julian D. Marshall; Ernani F. Choma; John S. Evans. 2019. "Global Effect Factors for Exposure to Fine Particulate Matter." Environmental Science & Technology 53, no. 12: 6855-6868.
Prioritizing the potential risk posed to human health by chemicals requires tools that can estimate exposure from limited information. In this study chemical structure and physicochemical properties were used to predict the probability that a chemical might be associated with any of four exposure pathways leading from sources – consumer (near-field), dietary, far-field industrial, and far-field pesticide – to the general population. The balanced accuracies of these source-based exposure pathway models range from 73-81%, with the error rate for identifying positive chemicals ranging from 17-36%. We then used exposure pathways to organize predictions from thirteen different exposure models as well as other predictors of human intake rates. We created a consensus, meta-model using the Systematic Empirical Evaluation of Models (SEEM) framework in which the predictors of exposure were combined by pathway and weighted according to predictive ability for chemical intake rates inferred from human biomonitoring data for 114 chemicals. The consensus model yields an R2 of ~0.8. We extrapolate to predict relevant pathway(s), median intake rate, and credible interval for 479,926 chemicals, mostly with minimal exposure information. This approach identifies 1,880 chemicals for which the median population intake rates may exceed 0.1 mg/kg bodyweight/day, while there is 95% confidence that the median intake rate is below 1 µg/kg BW/day for 478,046 compounds.
Caroline L. Ring; Jon A. Arnot; Deborah H. Bennett; Peter P. Egeghy; Peter Fantke; Lei Huang; Kristin K. Isaacs; Olivier Jolliet; Katherine A. Phillips; Paul S. Price; Hyeong-Moo Shin; John N. Westgate; R. Woodrow Setzer; John F. Wambaugh. Consensus Modeling of Median Chemical Intake for the U.S. Population Based on Predictions of Exposure Pathways. Environmental Science & Technology 2018, 53, 719 -732.
AMA StyleCaroline L. Ring, Jon A. Arnot, Deborah H. Bennett, Peter P. Egeghy, Peter Fantke, Lei Huang, Kristin K. Isaacs, Olivier Jolliet, Katherine A. Phillips, Paul S. Price, Hyeong-Moo Shin, John N. Westgate, R. Woodrow Setzer, John F. Wambaugh. Consensus Modeling of Median Chemical Intake for the U.S. Population Based on Predictions of Exposure Pathways. Environmental Science & Technology. 2018; 53 (2):719-732.
Chicago/Turabian StyleCaroline L. Ring; Jon A. Arnot; Deborah H. Bennett; Peter P. Egeghy; Peter Fantke; Lei Huang; Kristin K. Isaacs; Olivier Jolliet; Katherine A. Phillips; Paul S. Price; Hyeong-Moo Shin; John N. Westgate; R. Woodrow Setzer; John F. Wambaugh. 2018. "Consensus Modeling of Median Chemical Intake for the U.S. Population Based on Predictions of Exposure Pathways." Environmental Science & Technology 53, no. 2: 719-732.
Regionalized life cycle impact assessment (LCIA) has rapidly developed in the past decade, though its widespread application, robustness, and validity still face multiple challenges. Under the umbrella of UNEP/SETAC Life Cycle Initiative, a dedicated cross-cutting working group on regionalized LCIA aims to provide an overview of the status of regionalization in LCIA methods. We give guidance and recommendations to harmonize and support regionalization in LCIA for developers of LCIA methods, LCI databases, and LCA software. A survey of current practice among regionalized LCIA method developers was conducted. The survey included questions on chosen method’s spatial resolution and scale, the spatial resolution of input parameters, the choice of native spatial resolution and limitations, operationalization and alignment with life cycle inventory data, methods for spatial aggregation, the assessment of uncertainty from input parameters and model structure, and the variability due to spatial aggregation. Recommendations are formulated based on the survey results and extensive discussion by the authors. Survey results indicate that majority of regionalized LCIA models have global coverage. Native spatial resolutions are generally chosen based on the availability of global input data. Annual modeled or measured elementary flow quantities are mostly used for aggregating characterization factors (CFs) to larger spatial scales, although some use proxies, such as population counts. Aggregated CFs are mostly available at the country level. Although uncertainty due to input parameter, model structure, and spatial aggregation are available for some LCIA methods, they are rarely implemented for LCA studies. So far, there is no agreement if a finer native spatial resolution is the best way to reduce overall uncertainty. When spatially differentiated model CFs are not easily available, archetype models are sometimes developed. Regionalized LCIA methods should be provided as a transparent and consistent set of data and metadata using standardized data formats. Regionalized CFs should include both uncertainty and variability. In addition to the native-scale CFs, aggregated CFs should always be provided and should be calculated as the weighted averages of constituent CFs using annual flow quantities as weights whenever available. This paper is an important step forward for increasing transparency, consistency, and robustness in the development and application of regionalized LCIA methods.
Chris Mutel; Xun Liao; Laure Patouillard; Jane Bare; Peter Fantke; Rolf Frischknecht; Michael Zwicky Hauschild; Olivier Jolliet; Danielle Maia De Souza; Alexis Laurent; Stephan Pfister; Francesca Verones. Overview and recommendations for regionalized life cycle impact assessment. The International Journal of Life Cycle Assessment 2018, 24, 856 -865.
AMA StyleChris Mutel, Xun Liao, Laure Patouillard, Jane Bare, Peter Fantke, Rolf Frischknecht, Michael Zwicky Hauschild, Olivier Jolliet, Danielle Maia De Souza, Alexis Laurent, Stephan Pfister, Francesca Verones. Overview and recommendations for regionalized life cycle impact assessment. The International Journal of Life Cycle Assessment. 2018; 24 (5):856-865.
Chicago/Turabian StyleChris Mutel; Xun Liao; Laure Patouillard; Jane Bare; Peter Fantke; Rolf Frischknecht; Michael Zwicky Hauschild; Olivier Jolliet; Danielle Maia De Souza; Alexis Laurent; Stephan Pfister; Francesca Verones. 2018. "Overview and recommendations for regionalized life cycle impact assessment." The International Journal of Life Cycle Assessment 24, no. 5: 856-865.
The material‐air partition coefficient (Kma) is a key parameter to estimate the release of chemicals incorporated in solid materials and resulting human exposures. Existing correlations to estimate Kma are applicable for a limited number of chemical‐material combinations without considering the effect of temperature. The present study develops a quantitative property‐property relationship (QSPR) to predict Kma for a large number of chemical‐material combinations. We compiled a dataset of 991 measured Kma for 179 chemicals in 22 consolidated material types. A multiple linear regression model predicts Kma as a function of chemical's Koa, enthalpy of vaporization (∆Hv), temperature and material type. The model shows good fitting of the experimental dataset with adjusted R2 of 0.93 and has been verified by internal and external validations to be robust, stable and has good predicting ability (R2ext > 0.78). A generic QSPR is also developed to predict Kma from chemical properties and temperature only (adjusted R2 = 0.84), without the need to assign a specific material type. These QSPRs provide correlation methods to estimate Kma for a wide range of organic chemicals and materials, which will facilitate high‐throughput estimates of human exposures for chemicals in solid materials, particularly building materials and furniture. This article is protected by copyright. All rights reserved.
Lei Huang; Olivier Jolliet. A quantitative structure‐property relationship ( QSPR ) for estimating solid material‐air partition coefficients of organic compounds. Indoor Air 2018, 29, 79 -88.
AMA StyleLei Huang, Olivier Jolliet. A quantitative structure‐property relationship ( QSPR ) for estimating solid material‐air partition coefficients of organic compounds. Indoor Air. 2018; 29 (1):79-88.
Chicago/Turabian StyleLei Huang; Olivier Jolliet. 2018. "A quantitative structure‐property relationship ( QSPR ) for estimating solid material‐air partition coefficients of organic compounds." Indoor Air 29, no. 1: 79-88.
Disability adjusted life years (DALYs) is a health burden metric that combines years of life lost due to disease disability and premature mortality. The Global Burden of Disease (GBD) has been using DALYs to determine the health burden associated with numerous health risks, including risks associated with dietary intakes, at the global and national level. To translate such information at the food level in the U.S., variables in What We Eat in America (WWEIA) need to be aligned with those in the GBD. In this paper, we develop the necessary new variables needed to account for differences in definitions and units between WWEIA and the GBD. We use the Food Patterns Equivalents Database, Food Patterns Equivalents Ingredient Database, Food and Nutrient Database for Dietary Studies, and Standard Reference databases that provide data for WWEIA to develop food group and nutrient variables that align with definitions and units used in the GBD. Considerable effort was needed to disaggregate mixed dishes to GBD components. We also developed a new “non-starchy” vegetable variable, since the GBD vegetables do not include potatoes and corn, and we report fruits and vegetables in grams instead of household measures. New fiber variables were created to avoid double counting of fiber from legumes, whole grains, fruits, and vegetables. Regression analyses were used to predict trans-fat content for foods in WWEIA with missing or incomplete information. The majority of foods in various U.S. Department of Agriculture (USDA) categories contain multiple GBD food groups (e.g., vegetables, whole grains, and processed meat). For most nutrients considered in the GBD, composition is more evenly distributed across the main food categories; however, seafood omega-3 fats were predominantly from either protein foods or mixed dishes and sugar sweetened beverages were from a single category. Dietary intakes in the U.S. fall short of recommendations for all food groups/nutrients with established theoretical minimum-risk targets in GBD. To our knowledge, this is the first approach that aligns WWEIA intake variables with those used in the health burden-based GBD reports. These methods will facilitate researchers to begin comparing data from the U.S. with that from other countries, as well as assess food sustainability performances by concomitantly evaluating DALYs for environmental and nutritional impacts.
Victor L. Fulgoni; Taylor C. Wallace; Katerina S. Stylianou; Olivier Jolliet. Calculating Intake of Dietary Risk Components Used in the Global Burden of Disease Studies from the What We Eat in America/National Health and Nutrition Examination Surveys. Nutrients 2018, 10, 1441 .
AMA StyleVictor L. Fulgoni, Taylor C. Wallace, Katerina S. Stylianou, Olivier Jolliet. Calculating Intake of Dietary Risk Components Used in the Global Burden of Disease Studies from the What We Eat in America/National Health and Nutrition Examination Surveys. Nutrients. 2018; 10 (10):1441.
Chicago/Turabian StyleVictor L. Fulgoni; Taylor C. Wallace; Katerina S. Stylianou; Olivier Jolliet. 2018. "Calculating Intake of Dietary Risk Components Used in the Global Burden of Disease Studies from the What We Eat in America/National Health and Nutrition Examination Surveys." Nutrients 10, no. 10: 1441.
Most alternatives assessments (AAs) published to date are largely hazard‐based rankings, thereby ignoring potential differences in human and/or ecosystem exposures; as such, they may not represent a fully informed consideration of the advantages and disadvantages of possible alternatives. Building on the 2014 US National Academy of Sciences recommendations to improve AA decisions by including comparative exposure assessment into AAs, the ILSI Health and Environmental Sciences Institute's Sustainable Chemical Alternatives Technical Committee, which comprises scientists from academia, industry, government, and nonprofit organizations, developed a qualitative comparative exposure approach. Conducting such a comparison can screen for alternatives that are expected to have a higher or different route of human or environmental exposure potential, which, together with consideration of the hazard assessment, could trigger a higher‐tiered, more quantitative exposure assessment on the alternatives being considered, minimizing the likelihood of regrettable substitution. This article outlines an approach for including chemical ingredient‐ and product‐related exposure information in a qualitative comparison, including ingredient parameters and product‐related parameters. A classification approach was developed for ingredient and product parameters to support comparisons between alternatives as well as a methodology to address exposure parameter relevance and data quality. The ingredient parameters include a range of physicochemical properties that can impact routes and magnitude of exposure, whereas the product parameters include aspects such as product specific exposure pathways, use information, accessibility, and disposal. Two case studies are used to demonstrate the application of the methodology. Key learnings and future research needs are summarized. This article is protected by copyright. All rights reserved
William Greggs; Thomas Burns; Peter Egeghy; Michelle R. Embry; Peter Fantke; Bonnie Gaborek; Lauren Heine; Olivier Jolliet; Carolyn Lee; Derek Muir; Kathy Plotzke; Joseph Rinkevich; Neha Sunger; Jennifer Y. Tanir; Margaret Whittaker. Qualitative Approach to Comparative Exposure in Alternatives Assessment. Integrated Environmental Assessment and Management 2018, 15, 880 -894.
AMA StyleWilliam Greggs, Thomas Burns, Peter Egeghy, Michelle R. Embry, Peter Fantke, Bonnie Gaborek, Lauren Heine, Olivier Jolliet, Carolyn Lee, Derek Muir, Kathy Plotzke, Joseph Rinkevich, Neha Sunger, Jennifer Y. Tanir, Margaret Whittaker. Qualitative Approach to Comparative Exposure in Alternatives Assessment. Integrated Environmental Assessment and Management. 2018; 15 (6):880-894.
Chicago/Turabian StyleWilliam Greggs; Thomas Burns; Peter Egeghy; Michelle R. Embry; Peter Fantke; Bonnie Gaborek; Lauren Heine; Olivier Jolliet; Carolyn Lee; Derek Muir; Kathy Plotzke; Joseph Rinkevich; Neha Sunger; Jennifer Y. Tanir; Margaret Whittaker. 2018. "Qualitative Approach to Comparative Exposure in Alternatives Assessment." Integrated Environmental Assessment and Management 15, no. 6: 880-894.
There is increasing interest in using fate and exposure models to spatially differentiate the impacts of chemical emissions. This work aims at exploring the operationalization in life cycle assessment (LCA) of spatially differentiated models for toxic emissions into freshwater. We analyse and compare the variability of fate and exposure factors at high resolution with aggregated factors at different levels of lower resolution. We developed a spatially resolved fate and exposure characterization model and factors for toxic emissions into freshwater with global coverage at 0.5° × 0.5° resolution, extending a global hydrological model to account for removal processes, namely chemical and biological degradation, sedimentation, and volatilization. We analysed the variation in fate and exposure factors for water ingestion, identifying the main factors of influence. We then developed archetypes for ecosystems and human fate and exposure. Using a case study of emissions of arsenic from red mud disposal as a waste from alumina production, we tested practical solutions to apply spatial characterization factors aggregated at different resolution in LCA, comparing archetype-based with region-based approaches. World maps show up to 5 orders of magnitude variation for chemical fate in fresh water across all 0.5° × 0.5° grid cells and up to 15 orders of magnitude for human intake fractions. The freshwater residence time to the sea and the equivalent depth—over all downstream cells—were the most influential landscape parameters. They were used to define four freshwater landscape archetypes. These archetypes capture variation in fate well, better than country or continent-aggregated values, but are not able to reflect variation in intake fraction. The case study on arsenic from alumina production shows that the determination of industry-specific weighted average represents a pragmatic way to account for sector-specific location of emissions. The population-weighted approach is primarily applicable for emissions that are related to population density, such as household emissions. The developed global freshwater model demonstrates large spatial variations in fate and exposure. Archetypes for fate in fresh water provide substantial reductions in variability compared to country or continental averages, but are more difficult to apply to LCA than rural or urban archetypes for air emissions. The 0.5° × 0.5° grid model and the fate archetypes may also be used in the context of ecological scenarios to identify hotspots. In practice, population-weighted and sector-specific average characterization factors may represent the most operational way to account for specific distribution patterns of toxic emissions in LCA.
Anna Kounina; Manuele Margni; Andrew Henderson; Olivier Jolliet. Global spatial analysis of toxic emissions to freshwater: operationalization for LCA. The International Journal of Life Cycle Assessment 2018, 24, 501 -517.
AMA StyleAnna Kounina, Manuele Margni, Andrew Henderson, Olivier Jolliet. Global spatial analysis of toxic emissions to freshwater: operationalization for LCA. The International Journal of Life Cycle Assessment. 2018; 24 (3):501-517.
Chicago/Turabian StyleAnna Kounina; Manuele Margni; Andrew Henderson; Olivier Jolliet. 2018. "Global spatial analysis of toxic emissions to freshwater: operationalization for LCA." The International Journal of Life Cycle Assessment 24, no. 3: 501-517.
This paper analyzes spatially ecosystem exposure to home and personal care (HPC) chemicals, accounting for market data and environmental processes in hydrological water networks, including multi-media fate and transport. We present a global modeling framework built on ScenAT (spatial scenarios of emission), SimpleTreat (sludge treatment plants), and Pangea (spatial multi-scale multimedia fate and transport of chemicals), that we apply across Asia to four chemicals selected to cover a variety of applications, volumes of production and emission, and physico-chemical and environmental fate properties: the anionic surfactant linear alkylbenzene sulphonate (LAS), the antimicrobial triclosan (TCS), the personal care preservative methyl paraben (MeP), and the emollient decamethylcyclopentasiloxane (D5). We present maps of predicted environmental concentrations (PECs) and compare them with monitored values. LAS emission levels and PECs are two to three orders of magnitude greater than for other substances, yet the literature about monitored levels of LAS in Asia is very limited. We observe a good agreement for TCS in freshwater (Pearson r=0.82, for 253 monitored values covering 12 streams), a moderate agreement in general, and a significant model underestimation for MeP in sediments. While most differences could be explained by uncertainty in both chemical/hydrological parameters (DT50water, DT50sediments, Koc, foc, TSS) and monitoring sites (e.g. spatial/temporal design), the underestimation of MeP concentrations in sediments may involve potential natural sources. We illustrate the relevance of local evaluations for short-lived substances in fresh water (LAS, MeP), and their inadequacy for substances with longer half-lives (TCS, D5). This framework constitutes a milestone towards higher tier exposure modeling approaches for identifying areas of higher chemical concentration, and linking large-scale fate modeling with (sub) catchment-scale ecological scenarios; a major limitation in model accuracy comes from the discrepancy between streams routed on a gridded, 0.5°×0.5° global hydrological network and actual locations of streams and monitoring sites.
Cedric Wannaz; Antonio Franco; John Kilgallon; Juliet Hodges; Olivier Jolliet. A global framework to model spatial ecosystems exposure to home and personal care chemicals in Asia. Science of The Total Environment 2018, 622-623, 410 -420.
AMA StyleCedric Wannaz, Antonio Franco, John Kilgallon, Juliet Hodges, Olivier Jolliet. A global framework to model spatial ecosystems exposure to home and personal care chemicals in Asia. Science of The Total Environment. 2018; 622-623 ():410-420.
Chicago/Turabian StyleCedric Wannaz; Antonio Franco; John Kilgallon; Juliet Hodges; Olivier Jolliet. 2018. "A global framework to model spatial ecosystems exposure to home and personal care chemicals in Asia." Science of The Total Environment 622-623, no. : 410-420.