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Article Commentary
17 February 2022

Filling in the Blanks: A New Tool to Predict Chemical Pathways from Production to Exposure

Publication: Environmental Health Perspectives
Volume 130, Issue 2
CID: 024002
Detailed exposure and risk estimation studies for the many thousands of chemicals in our environment are not feasible. Thus, early mathematical models were developed to predict the environmental fate of understudied chemicals,1 giving rise to the field of computational exposure science.2 Most computational models, however, rely on multiple input parameters that are unknown for the vast majority of commercial chemicals.3 In a study recently published in Environmental Health Perspectives,4 researchers presented a new tool called PROduction-To-EXposure High Throughput (PROTEX-HT) that calculates model input parameters on the basis of two chemical-specific pieces of information: production tonnage and molecular structure.
Chemicals travel a long road, from initial production, to uses in processes and products, and ultimately to disposal. PROTEX-HT aims to identify the emission sources, environmental media, and exposure routes of greatest concern along that road. Image: © Mark A. Leman/Getty Images.
The authors compared median human exposure rates predicted by the new model with inferred exposure estimates of 95 chemicals measured in participants in the National Health and Nutrition Examination Survey (NHANES).5 The list of chemicals included insecticides, intermediate and raw chemicals, solvents, plasticizers, and ingredients used in personal care products. The authors reported that 79% and 97% of the predictions deviated from U.S. general population exposure estimates by a factor of 10 and 100, respectively. First author Li Li, an assistant professor of environmental chemistry at the University of Nevada, Reno, notes that chemicals measured in humans at different times typically vary by a factor up to 100, according to NHANES data.
PROTEX-HT, whose expected users include researchers, chemical manufacturers, and regulatory agencies, combines three existing models. The first is a substance flow analysis that simulates how chemicals move through the human socioeconomic system from production to end-of-lifetime disposal and converts chemical tonnage into emissions.6 The second and third components describe how these emitted chemicals move and degrade within indoor7 or outdoor8 environments. Indoor media include air, carpet, flooring, and hard surfaces; outdoor media include air, soil, water, and sediment. Together, the three model components calculate expected chemical concentrations for each medium.
Next, PROTEX-HT predicts biological concentrations within humans and other organisms from the media-specific concentrations. For broad risk estimation purposes, users of the tool can compare these predictions with existing in vitro or in vivo health reference levels from toxicological studies. This may help prioritize chemicals for more detailed analyses that require a larger number of input parameters and deliver more accurate estimates.9,10
The model assumes that chemicals mix well enough to reach the same concentration throughout each environmental medium. This assumption may not hold for quickly degrading chemicals released by a single-point source, the authors noted.4 The model also assumes that no residues of raw industrial chemicals are present in final consumer products. But for some chemicals in plastic production processes, such as bisphenol A, this assumption may result in underestimated concentrations of the chemical in indoor environments.4
For Zhanyun Wang, a scientist at Empa, the Swiss Federal Laboratories for Materials Science and Technology, who was not involved in the study, PROTEX-HT is useful for ranking the relative importance of different emission sources, provided that accurate production tonnage information is available from chemical manufacturers.
“I think more detailed models are necessary to estimate human exposure to chemicals, which is often of greatest concern for vulnerable subpopulations,” Wang says. Pesticide exposure, for example, may greatly exceed general population estimates for farmers and their neighbors and for people living in poor housing conditions that require regular applications of indoor pest control chemicals.
PROTEX-HT estimates a “maximum allowable tonnage” for chemicals—the point beyond which a chemical’s production and use would cause unacceptable health risks. However, the authors acknowledge several points of uncertainty in these estimates, including physicochemical properties of chemicals that may complicate the simulation of emission rates, unclear toxicity thresholds, and potentially inaccurate chemical tonnage information.
Miriam Diamond, a professor at the University of Toronto’s Department of Earth Sciences and School of the Environment, has published work11 indicating that the computational models that form the basis of PROTEX-HT were not always reliable for certain types of molecules. Diamond, who was not involved in the current study, says the uncertainties surrounding PROTEX-HT preclude acting upon its maximum allowable tonnage estimates for the time being. Still, she says, “This study has assembled a rich body of knowledge into a single framework that advances our understanding of the fate of chemicals from use to exposure.”
Although the current version provides exposure estimates for the general U.S. population, Li says the PROTEX framework may be adjusted to a variety of exposure simulations, including those involving vulnerable subpopulations. Going forward, the authors plan to examine in more detail potential sources of uncertainty in model predictions. Li adds, “There is always a need to further evaluate exposure models with more chemicals as more monitoring and biomonitoring data become available.”

References

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Egeghy PP, Sheldon LS, Isaacs KK, Özkaynak H, Goldsmith MR, Wambaugh JF, et al. 2016. Computational exposure science: an emerging discipline to support 21st-century risk assessment. Environ Health Perspect 124(6):697–702. https://www.ncbi.nlm.nih.gov/pubmed/26545029, https://doi.org/10.1289/ehp.1509748.
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Wetmore BA, Wambaugh JF, Allen B, Ferguson SS, Sochaski MA, Setzer RW, et al. 2015. Incorporating high-throughput exposure predictions with dosimetry-adjusted in vitro bioactivity to inform chemical toxicity testing. Toxicol Sci 148(1):121–136. https://www.ncbi.nlm.nih.gov/pubmed/26251325, https://doi.org/10.1093/toxsci/kfv171.
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Li L, Wania F. 2016. Tracking chemicals in products around the world: introduction of a dynamic substance flow analysis model and application to PCBs. Environ Int 94:674–686. https://www.ncbi.nlm.nih.gov/pubmed/27431909, https://doi.org/10.1016/j.envint.2016.07.005.
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Li L, Westgate JN, Hughes L, Zhang X, Givehchi B, Toose L, et al. 2018. A model for risk-based screening and prioritization of human exposure to chemicals from near-field sources. Environ Sci Technol 52(24):14235–14244. https://www.ncbi.nlm.nih.gov/pubmed/30407800, https://doi.org/10.1021/acs.est.8b04059.
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Arnot JA, Mackay D. 2008. Policies for chemical hazard and risk priority setting: can persistence, bioaccumulation, toxicity, and quantity information be combined? Environ Sci Technol 42(13):4648–4654. https://www.ncbi.nlm.nih.gov/pubmed/18677986, https://doi.org/10.1021/es800106g.
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Ring CL, Arnot JA, Bennett DH, Egeghy PP, Fantke P, Huang L, et al. 2019. Consensus modeling of median chemical intake for the U.S. population based on predictions of exposure pathways. Environ Sci Technol 53(2):719–732. https://www.ncbi.nlm.nih.gov/pubmed/30516957, https://doi.org/10.1021/acs.est.8b04056.
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Li L, Arnot JA, Wania F. 2018. Towards a systematic understanding of the dynamic fate of polychlorinated biphenyls in indoor, urban and rural environments. Environ Int 117:57–68. https://www.ncbi.nlm.nih.gov/pubmed/29727753, https://doi.org/10.1016/j.envint.2018.04.038.
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Rodgers TFM, Okeme JO, Parnis JM, Girdhari K, Bidleman TF, Wan Y, et al. 2021. Novel Bayesian method to derive final adjusted values of physicochemical properties: application to 74 compounds. Environ Sci Technol 55(18):12302–12316. https://www.ncbi.nlm.nih.gov/pubmed/34459590, https://doi.org/10.1021/acs.est.1c01418.

Biographies

Silke Schmidt, PhD, writes about science, health, and the environment from Madison, Wisconsin.

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Published In

Environmental Health Perspectives
Volume 130Issue 2February 2022
PubMed: 35175097

History

Received: 8 December 2021
Accepted: 19 January 2022
Published online: 17 February 2022

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