Viewpoint pubs.acs.org/est
Viewpoint: Closing the Exposure Gap Daniel A. Vallero* Duke University, Pratt School of Engineering, Room 121 Hudson Hall, Box 90287, Durham, North Carolina 27708-0287, United States relevant quantitative structural activity (QSAR) and molecular data are available for some, but only a handful have internal biomarkers of exposure. Wambaugh et al.2 found that only 82 chemicals from the National Health and Nutrition Examination Survey could be used to represent household products. Indeed, large-scale observation exposure studies are becoming rare, in spite of the dire need for data, even as state-of-the-science of exposure modeling and computational exposure science are advancing. This is ironic since the lack of measurement data is a key motivation to design and adapt better exposure models, yet evaluating and ground-proofing these new models will need high quality exposure data. Paul Lioy and Cliff Weisel3 have provided some good news with their important new book, Exposure Science: Basic Principles and Applications. The book is dedicated to “the young scientists who may be selecting the study of exposure” or other disciplines within the environmental health sciences as a career path. The dedication could also include those in the engineering and design communities who apply the sciences to mitigate problems and realize effective solutions.
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THE FACE OF THE EXPOSURE SCIENTIST IS CHANGING The exposure community is mainly comprised of scientists, but also a growing number of professionals, especially in engineering and medicine. If asked, the engineer or physician may say they do not employ exposure science. Most engineers and physicians are likely unfamiliar with specific terms used by Lioy and Weisel, but do indeed continuously apply exposure science under other names. Engineers design barriers and remediation technologies; apply pharmacokinetic models; adapt reactors to reduce occupational exposures, and develop safer chemical substitutes. Likewise, medical doctors recommend measures to reduce exposures to bacteria and viruses in a manner that makes use of Lioy and Weisel’s equations. Indeed, most recent medical and lay concerns, uncertainties, and misconceptions about Ebola have been with activities that may increase exposure to the virus. This harkens the exposome; that is, exposure consists of the person’s biology, location and activities.4 As risk managers who advise clientele, engineers and physicians need better tools and information to determine how human behavior affects exposure and, ultimately, risk. The medical, environmental, and design disciplines have a common and compelling need for reliable exposure information to estimate risks. Unfortunately, exposure data are sparse in the era of systems medicine and engineering, and especially silent on how people’s behavior and activity alter contact with agents, so will increasingly have to rely on OPD.
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ince the 1980s, great progress has been made in environmental risk characterization. The National Academy of Sciences’ “red book” introduced the sequence from hazard identification to exposure to effects that has ably served as a guidepost for structuring research and providing credible information for environmental decisions in both the public and private sectors. Arguably, of the Academy’s recommendations, exposure assessment has been the most eclectic and elusive component. Understanding how humans and ecosystems are exposed to chemicals is fraught with complexities and uncertainties. The uncertainties propagate through the risk assessment process. Indeed, exposure assessment is often the rate limiting step in risk assessment. The physical and natural sciences have incrementally added to the knowledge base for risk characterization, recorded in ES&T articles for decades. This knowledge is certainly necessary, but insufficient. Besides the properties of the harmful agent, exposure must account for the activities. Thus, exposure science must derive information squarely from the domain of the social sciences. This has been known for some time, as evidenced by the U.S. Environmental Protection Agency exposure factor handbook’s1 population percentiles of exposure for numerous activities; but informatics and “big data” are enhancing this information, albeit with new ethical and quality challenges. Exposure science will increasingly depend on “other people’s data” (OPD), as even physicochemical property data important for exposure are sparse compared to those of hazard. Of the tens of thousands of chemicals in the marketplace, exposure© 2014 American Chemical Society
Received: November 20, 2014 Published: December 1, 2014 14075
dx.doi.org/10.1021/es505678p | Environ. Sci. Technol. 2014, 48, 14075−14076
Environmental Science & Technology
Viewpoint
Exposure both informs and is informed by other advances, so must be viewed systematically. Life cycle assessment (LCA), green chemistry, green engineering, and computational methods must be adapted. For example, life cycle inventories often lack reliable exposure information in both downstream and upstream components of the life cycle of the product. This gap is closing, with improved and more risk-relevant QSARs, high throughput chemical exposure models, and integration of exposure metrics in LCAs to differentiate routes (e.g., air, water, or soil) and pathways (e.g., inhalation, dermal absorption, or ingestion) of chemical agents.5 The timely book by Lioy and Weisel marks the next phase of the coalescence of engineering, biomedical and environmental sciences. As such, the physical, biological and social sciences are merging. This brings cautious optimism that the rate of closing the exposure science gap will soon accelerate.
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AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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REFERENCES
(1) Moya, J.; Phillips, L.; Schuda, L.; Wood, P.; Diaz, A.; Lee, R.; Clickner, R.; Birch, R.; Adjei, N.; Blood, P. Exposure Factors Handbook, 2011 ed.; US Environmental Protection Agency, 2011. (2) Wambaugh, J. F.; Setzer, R. W.; Reif, D. M.; Gangwal, S.; Mitchell-Blackwood, J.; Arnot, J. A.; Joliet, O.; Frame, A.; Rabinowitz, J.; Knudsen, T. B.; Judson, R. S.; Egeghy, P.; Vallero, D.; Cohen Hubal, E. A. High-throughput models for exposure-based chemical prioritization in the ExpoCast project. Environ. Sci. Technol. 2013, 47 (15), 8479−88. (3) Lioy, P.; Weisel, C. Exposure Science: Basic Principles and Applications; Academic Press, 2014. (4) Rappaport, S. M.; Smith, M. T. Environment and disease risks. Science 2010, 330 (6003), 460−461. (5) Rosenbaum, R.; Huijbregts, M. J.; Henderson, A.; Margni, M.; McKone, T.; van de Meent, D.; Hauschild, M.; Shaked, S.; Li, D.; Gold, L.; Jolliet, O. USEtox human exposure and toxicity factors for comparative assessment of toxic emissions in life cycle analysis: Sensitivity to key chemical properties. Int. J. Life Cycle Assess. 2011, 16 (8), 710−727.
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dx.doi.org/10.1021/es505678p | Environ. Sci. Technol. 2014, 48, 14075−14076
