Journal of Nanoparticle Research

, 16:2724

Modeling population exposures to silver nanoparticles present in consumer products

  • Steven G. Royce
  • Dwaipayan Mukherjee
  • Ting Cai
  • Shu S. Xu
  • Jocelyn A. Alexander
  • Zhongyuan Mi
  • Leonardo Calderon
  • Gediminas Mainelis
  • KiBum Lee
  • Paul J. Lioy
  • Teresa D. Tetley
  • Kian Fan Chung
  • Junfeng Zhang
  • Panos G. Georgopoulos
Research Paper

Abstract

Exposures of the general population to manufactured nanoparticles (MNPs) are expected to keep rising due to increasing use of MNPs in common consumer products (PEN 2014). The present study focuses on characterizing ambient and indoor population exposures to silver MNPs (nAg). For situations where detailed, case-specific exposure-related data are not available, as in the present study, a novel tiered modeling system, Prioritization/Ranking of Toxic Exposures with GIS (geographic information system) Extension (PRoTEGE), has been developed: it employs a product life cycle analysis (LCA) approach coupled with basic human life stage analysis (LSA) to characterize potential exposures to chemicals of current and emerging concern. The PRoTEGE system has been implemented for ambient and indoor environments, utilizing available MNP production, usage, and properties databases, along with laboratory measurements of potential personal exposures from consumer spray products containing nAg. Modeling of environmental and microenvironmental levels of MNPs employs probabilistic material flow analysis combined with product LCA to account for releases during manufacturing, transport, usage, disposal, etc. Human exposure and dose characterization further employ screening microenvironmental modeling and intake fraction methods combined with LSA for potentially exposed populations, to assess differences associated with gender, age, and demographics. Population distributions of intakes, estimated using the PRoTEGE framework, are consistent with published individual-based intake estimates, demonstrating that PRoTEGE is capable of capturing realistic exposure scenarios for the US population. Distributions of intakes are also used to calculate biologically relevant population distributions of uptakes and target tissue doses through human airway dosimetry modeling that takes into account product MNP size distributions and age-relevant physiological parameters.

Keywords

Manufactured nanoparticles Engineered nanomaterials Silver nanoparticles Consumer products Life cycle analysis Life stage analysis PRoTEGE 

References

  1. ARA (2014) Multiple-path particle dosimetry model (MPPD v 2.11). A model for human and rat airway particle dosimetry. Applied research associates. http://www.ara.com/products/mppd.htm. Accessed April 21 2014
  2. Aschberger K, Micheletti C, Sokull-Klüttgen B, Christensen FM (2011) Analysis of currently available data for characterising the risk of engineered nanomaterials to the environment and human health—lessons learned from four case studies. Environ Int 37:1143–1156. doi:10.1016/j.envint.2011.02.005 CrossRefGoogle Scholar
  3. Bureau of Labor Statistics (2014) Data from 2006 and 2007 consumer expenditure surveys (CEX), accessed using Esri business analyst. http://stats.bls.gov/cex/. Accessed July 1 2014  
  4. CBECS (2003) 2003 CBECS survey data. Table B15. Employment size category, number of buildings for non-mall buildings, 2003. US energy information administration. http://www.eia.gov/consumption/commercial/data/2003/pdf/b15.pdf. Accessed April 21 2014
  5. Chen BT et al (2010) Nanoparticles-containing spray can aerosol: characterization, exposure assessment, and generator design. Inhal Toxicol 22:1072–1082. doi:10.3109/08958378.2010.518323 CrossRefGoogle Scholar
  6. Delmaar JE, Bremmer HJ (2009) The ConsExpo spray model: modelling and experimental validation of the inhalation exposure of consumers to aerosols from spray cans and trigger sprays National Institute for Public Health and the Environment. RIVM, BilthovenGoogle Scholar
  7. Delmaar JE, Park MVDZ, van Engelen JGM (2005) ConsExpo 4.0 consumer exposure and uptake models program manual. RIVM, BilthovenGoogle Scholar
  8. Esri (2014) ESRI Business Analyst Desktop. http://www.esri.com/software/arcgis/extensions/businessanalyst. Accessed March 28 2014
  9. Gangwal S, Brown J, Wang A, Houck K, Dix D, Kavlock R, Cohen Hubal E (2011) Informing selection of nanomaterial concentrations for ToxCast in vitro testing based on occupational exposure potential. Environ Health Perspect. doi:10.1289/ehp.1103750 Google Scholar
  10. Georgopoulos P (2008) A multiscale approach for assessing the interactions of environmental and biological systems in a holistic health risk assessment framework. Water Air Soil Pollut 8:3–21. doi:10.1007/s11267-007-9137-7 CrossRefGoogle Scholar
  11. Georgopoulos PG, Lioy PJ (2006) From theoretical aspects of human exposure and dose assessment to computational model implementation: the MOdeling ENvironment for TOtal Risk studies (MENTOR). J Toxicol Environ Health 9:457–483CrossRefGoogle Scholar
  12. Georgopoulos PG et al (2005) A source-to-dose assessment of population exposures to fine PM and ozone in Philadelphia, PA, during a summer 1999 episode. J Expo Anal Environ Epidemiol 15:439–457. doi:10.1038/sj.jea.7500422 CrossRefGoogle Scholar
  13. Georgopoulos PG, Wang S-W, Yang Y-C, Xue J, Zartarian VG, McCurdy T, Ozkaynak H (2008) Biologically based modeling of multimedia, multipathway, multiroute population exposures to arsenic. J Eposure Sci Environ Epidemiol 18:462–476CrossRefGoogle Scholar
  14. Georgopoulos PG, Sasso AF, Isukapalli SS, Lioy PJ, Vallero DA, Okino M, Reiter L (2009) Reconstructing population exposures to environmental chemicals from biomarkers: challenges and opportunities. J Eposure Sci Environ Epidemiol 19:149–171. doi:10.1038/jes.2008.9 CrossRefGoogle Scholar
  15. Georgopoulos PG, Brinkerhoff CJ, Isukapalli S, Dellarco M, Landrigan PJ, Lioy PJ (2014) A tiered framework for risk-relevant characterization and ranking of chemical exposures: applications to the National Children’s Study (NCS). Risk Anal. doi:10.1111/risa.12165 Google Scholar
  16. Goldsmith MR et al (2014) Development of a consumer product ingredient database for chemical exposure screening and prioritization. Food Chem Toxicol 65:269–279. doi:10.1016/j.fct.2013.12.029 CrossRefGoogle Scholar
  17. Gottschalk F, Sonderer T, Scholz RW, Nowack B (2009) Modeled environmental concentrations of engineered nanomaterials (TiO2, ZnO, Ag, CNT, Fullerenes) for different regions. Environ Sci Technol 43:9216–9222. doi:10.1021/es9015553 CrossRefGoogle Scholar
  18. Gottschalk F, Scholz RW, Nowack B (2010) Probabilistic material flow modeling for assessing the environmental exposure to compounds: methodology and an application to engineered nano-TiO2 particles. Environ Model Softw 25:320–332. doi:10.1016/j.envsoft.2009.08.011 CrossRefGoogle Scholar
  19. Hansen SF, Jensen KA, Baun A (2013) NanoRiskCat: a conceptual tool for categorization and communication of exposure potentials and hazards of nanomaterials in consumer products. J Nanopart Res 16:1–25. doi:10.1007/S11051-013-2195-Z Google Scholar
  20. Hendren CO, Mesnard X, Droge J, Wiesner MR (2011) Estimating production data for five engineered nanomaterials as a basis for exposure assessment. Environ Sci Technol 45:2562–2569. doi:10.1021/es103300g CrossRefGoogle Scholar
  21. Hischier R, Walser T (2012) Life cycle assessment of engineered nanomaterials: state of the art and strategies to overcome existing gaps. Sci Total Environ 425:271–282CrossRefGoogle Scholar
  22. ISO (2006a) Environmental Management—Life Cycle Assessment—Principles and Framework. International Standardisation Organisation (ISO), GenevaGoogle Scholar
  23. ISO (2006b) Environmental Management—Life Cycle Assessment—Requirements and Guidelines. International Standardization Organisation (ISO), GenevaGoogle Scholar
  24. Keil CB, Simmons CE, Anthony TR (2009) Mathematical models for estimating occupational exposure to chemicals, 2nd edn. American Industrial Hygiene Association (AIHA), FairfaxGoogle Scholar
  25. Money C, Schnoeder F, Noij D, Chang H-Y, Urbanus J (2014) ECETOC TRA version 3: capturing and consolidating the experiences of REACH. Environ Sci 16:970–977. doi:10.1039/C3EM00699A Google Scholar
  26. Mueller NC, Nowack B (2008) Exposure modeling of engineered nanoparticles in the environment. Environ Sci Technol 42:4447–4453CrossRefGoogle Scholar
  27. Mukherjee D, Botelho D, Gow AJ, Zhang J, Georgopoulos PG (2013) Computational multiscale toxicodynamic modeling of silver and carbon nanoparticle effects on mouse lung function. PLoS One 8:e80917. doi:10.1371/journal.pone.0080917 CrossRefGoogle Scholar
  28. Nazarenko Y, Han TW, Lioy PJ, Mainelis G (2011) Potential for exposure to engineered nanoparticles from nanotechnology-based consumer spray products. J Eposure Sci Environ Epidemiol 21:515–528. doi:10.1038/jes.2011.10 CrossRefGoogle Scholar
  29. Nazaroff WW (2008) Inhalation intake fraction of pollutants from episodic indoor emissions. Build Environ 43:269–277. doi:10.1016/j.buildenv.2006.03.021 CrossRefGoogle Scholar
  30. NNI (2011) Environmental, health, and safety research strategy environmental, health, and safety research strategy. National Nanotechnology Initiative, Washington DC. http://www.nano.gov/node/681
  31. Oberdorster G (2010) Safety assessment for nanotechnology and nanomedicine: concepts of nanotoxicology. J Intern Med 267:89–105. doi:10.1111/j.1365-2796.2009.02187.x CrossRefGoogle Scholar
  32. Panneerselvam S, Choi S (2014) Nanoinformatics: emerging databases and available tools. Int J Mol Sci 15:7158–7182. doi:10.3390/ijms15057158 CrossRefGoogle Scholar
  33. PEN (2014) The Project on Emerging Nanotechnologies. http://www.nanotechproject.org/. Accessed May 23 2014
  34. Piccinno F, Gottschalk F, Seeger S, Nowack B (2012) Industrial production quantities and uses of ten engineered nanomaterials in Europe and the world. J Nanopart Res 14:1–11. doi:10.1007/s11051-012-1109-9 Google Scholar
  35. Pronk MEJ et al (2009) Nanomaterials under REACH: nanosilver as a case study. RIVM, BilthovenGoogle Scholar
  36. Quadros ME, Pierson R, Tulve NS, Willis R, Rogers K, Thomas TA, Marr LC (2013) Release of silver from nanotechnology-based consumer products for children. Environ Sci Technol 47:8894–8901. doi:10.1021/es4015844 Google Scholar
  37. Reed RB, Faust JJ, Yang Y, Doudrick K, Capco DG, Hristovski K, Westerhoff P (2014) Characterization of nanomaterials in metal colloid-containing dietary supplement drinks and assessment of their potential interactions after ingestion. ACS Sustain Chem Eng 2:1616–1624. doi:10.1021/sc500108m
  38. RIVM (2014) National Institute for Public Health and the Environment. http://www.rivm.nl/English. Accessed July 10 2014
  39. Roberts JR et al (2013) Pulmonary and cardiovascular responses of rats to inhalation of silver nanoparticles. J Toxicol Environ Health A 76:651–668. doi:10.1080/15287394.2013.792024 CrossRefGoogle Scholar
  40. Schafer B et al (2013) State of the art in human risk assessment of silver compounds in consumer products: a conference report on silver and nanosilver held at the BfR in 2012. Arch Toxicol 87:2249–2262. doi:10.1007/s00204-013-1083-8 CrossRefGoogle Scholar
  41. Sparks LE (2001) Indoor air quality modeling. In: Spengler JD, Samet JM, McCarthy JF (eds) Indoor Air Quality Handbook. McGraw-Hill, New YorkGoogle Scholar
  42. Stallings C, Tippett JA, Glen G, Smith L (2002) CHAD user’s guide: extracting human activity information from CHAD on the PC. Prepared for USEPA National Exposure Research Laboratory by ManTech Environmental Technologies, Research Triangle Park, NCGoogle Scholar
  43. Stark WJ (2011) Nanoparticles in biological systems. Angew Chem Int Ed 50:1242–1258. doi:10.1002/anie.200906684 CrossRefGoogle Scholar
  44. Sung JH et al (2008) Lung function changes in Sprague-Dawley rats after prolonged inhalation exposure to silver nanoparticles. Inhal Toxicol 20:567–574. doi:10.1080/08958370701874671 CrossRefGoogle Scholar
  45. Thomas T, Bahadori T, Savage N, Thomas K (2009) Moving toward exposure and risk evaluation of nanomaterials: challenges and future directions. Wiley Interdisc Rev 1:426–433. doi:10.1002/wnan.34 Google Scholar
  46. USCB (2012) United States Census 2010. http://www.census.gov/. Accessed March 28 2014
  47. USEPA (2007) Nanotechnology White Paper. USEPA, Office of the Science Advisor, Washington D.C.Google Scholar
  48. USEPA (2011) Exposure factors handbook, 2011th edn. U.S. Environmental Protection Agency, Washington, DCGoogle Scholar
  49. USEPA (2012) Nanomaterial case study: nanoscale silver in disinfectant spray (Roport number EPA/600/R-10/081F). US Environmental Protection Agency, National Center for Environmental Assessment, WashingtonGoogle Scholar
  50. Yang Y, Westerhoff P (2014) Presence in, and release of, nanomaterials from consumer products. Adv Exp Med Biol 811:1–17. doi:10.1007/978-94-017-8739-0_1 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Steven G. Royce
    • 1
    • 2
  • Dwaipayan Mukherjee
    • 1
    • 2
    • 3
  • Ting Cai
    • 1
    • 2
    • 4
  • Shu S. Xu
    • 1
    • 2
  • Jocelyn A. Alexander
    • 1
    • 2
  • Zhongyuan Mi
    • 1
    • 2
  • Leonardo Calderon
    • 4
  • Gediminas Mainelis
    • 1
    • 4
  • KiBum Lee
    • 5
  • Paul J. Lioy
    • 1
    • 2
    • 4
  • Teresa D. Tetley
    • 6
  • Kian Fan Chung
    • 6
  • Junfeng Zhang
    • 7
  • Panos G. Georgopoulos
    • 1
    • 2
    • 3
    • 4
  1. 1.Environmental and Occupational Health Sciences Institute (EOHSI)Rutgers UniversityPiscatawayUSA
  2. 2.Department of Environmental and Occupational MedicineRutgers University-Robert Wood Johnson Medical SchoolPiscatawayUSA
  3. 3.Department of Chemical & Biochemical EngineeringRutgers UniversityPiscatawayUSA
  4. 4.Department of Environmental SciencesRutgers UniversityNew BrunswickUSA
  5. 5.Department of Chemistry and Chemical BiologyRutgers UniversityPiscatawayUSA
  6. 6.National Heart and Lung Institute, Imperial College LondonLondonUK
  7. 7.Nicholas School of the Environment and Duke Global Health Institute, Duke UniversityDurhamUSA

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