Acknowledgement
This work was supported by the research grant of the Kongju National University in 2019 (Award number: 2019-0233-01).
References
- Fryer M, Collins C, Ferrier H, Colvile R, Nieuwenhuijsen M. Human exposure modelling for chemical risk assessment: a review of current approaches and research and policy implications. Environ Sci Policy. 2006; 9(3): 261-274. https://doi.org/10.1016/j.envsci.2005.11.011
- Maddalena R, Mckone T, Layton D, Hsieh D. Comparison of multi-media transport and transformation models: regional fugacity model vs. CalTOX. Chemosphere. 1995; 30(5): 869-889. https://doi.org/10.1016/0045-6535(94)00447-3
- Fischhoff B. Understanding long-term environmental risks. J Risk Uncertain. 1990; 3(4): 315-330. https://doi.org/10.1007/BF00353344
- Yang JY. Estimation of human exposure to dioxins in Korean urban residents by mulitimedia/multiroute model [dissertation]. [Seoul]: Yonsei University; 2001.
- Hoang H, Chiang CF, Lin C, Wu CY, Lee CW, Cheruiyot NK, et al. Human health risk simulation and assessment of heavy metal contamination in a river affected by industrial activities. Environ Pollut. 2021; 285: 117414. https://doi.org/10.1016/j.envpol.2021.117414
- David G. Ergonomic methods for assessing exposure to risk factors for work-related musculoskeletal disorders. Occup Med (Lond). 2005; 55(3): 190-199. https://doi.org/10.1093/occmed/kqi082
- Mckone T, Macleod M. Tracking multiple pathways of human exposure to persistent multimedia pollutants: regional, continental, and global-scale models. Annu Rev Environ Resour. 2003; 28: 463-492. https://doi.org/10.1146/annurev.energy.28.050302.105623
- Liu C, Bennett DH, Kastenberg WE, Mckone TE, Browne D. A multimedia, multiple pathway exposure assessment of atrazine: fate, transport and uncertainty analysis. Reliab Eng Syst Saf. 1999; 63(2): 169-184. https://doi.org/10.1016/S0951-8320(98)00045-3
- National Research Council. Models in Environmental Regulatory Decision Making. Washington, D.C.: National Academies Press; 2007.
- U.S. Environmental Protection Agency. Guidance on the Development, Evaluation, and Application of Environmental Models. Washington, D.C.: U.S. Environmental Protection Agency; 2009.
- Schlesinger S. Terminology for model credibility. Simulation. 1979; 32(3): 103-104. https://doi.org/10.1177/003754977903200304
- World Health Organization. Human Exposure Assessment. Available: https://apps.who.int/iris/handle/10665/42181 [accessed 25 May 2022].
- National Research Council. Human Exposure Assessment for Airborne Pollutants: Advances and Opportunities. Washington, D.C.: National Academy of Sciences; 1991.
- U.S. Environmental Protection Agency. IRIS Assessments of Benzene. Available: https://cfpub.epa.gov/ncea/iris2/chemicallanding.cfm?substance_nmbr=276 [accessed 13 June 2022].
- International Agency for Research on Cancer. Benzene. Available: https://pubmed.ncbi.nlm.nih.gov/31769947/ [accessed 13 June 2022].
- Sekar A, Varghese GK, Ravi Varma MK. Analysis of benzene air quality standards, monitoring methods and concentrations in indoor and outdoor environment. Heliyon. 2019; 5(11): e02918. https://doi.org/10.1016/j.heliyon.2019.e02918
- Teras LR, Diver WR, Deubler EL, Krewski D, Flowers CR, Switchenko JM, et al. Residential ambient benzene exposure in the United States and subsequent risk of hematologic malignancies. Int J Cancer. 2019; 145(10): 2647-2660. https://doi.org/10.1002/ijc.32202
- Myung H, Baek S. Mid-to Long-term Research on Health Impact Surveys for Residents in Areas Vulnerable to Environmental Pollution in Chungnam Province. Gongju: ChungNam Institute; 2017.
- Kim H, Im J, Yun J, Lee J, Jeon J, Lee C. A study on the characteristics of chemicals in major industrial complexes. J Environ Health Sci. 2018; 44(6): 515-523.
- Moon J, Yang J, Lim Y, Park S, Shin D. Estimating human exposure to Benzo(a)pyrene through multimedia/multiroute exposure scenario. J Environ Toxicol. 2003; 18(4): 255-269.
- Luo Y, Zhang M. Multimedia transport and risk assessment of organophosphate pesticides and a case study in the northern San Joaquin Valley of California. Chemosphere. 2009; 75(7): 969-978. https://doi.org/10.1016/j.chemosphere.2009.01.005
- Tuncel G, Alpan G. Risk assessment and management for supply chain networks: a case study. Comput Ind. 2010; 61(3): 250-259. https://doi.org/10.1016/j.compind.2009.09.008
- National Institute of Chemical Safety. Pollutant Release and Transfer Registers. Available: https://icis.me.go.kr/prtr/main.do [accessed 25 May 2022].
- Korea Meteorological Administration. Wether Information. Available: https://www.weather.go.kr/ [accessed 25 May 2022].
- Statistics Korea. Population Statistics Based on Resident Registration. Available: http://www.index.go.kr/potal/main/EachDtlPageDetail.do?idx_cd=1007 [accessed 25 May 2022].
- U.S. Environmental Protection Agency. Guidelines for Exposure Assessment (1992). Available: https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=15263 [accessed 25 May 2022].
- National Institute of Environmental Research. Korean Exposure Factors Handbook. Incheon: National Institute of Environmental Research; 2019.
- McKone TE. CalTOX: A Multimedia Total-exposure Model for Hazardous-wastes Sites. Part 3, The Multiple-pathway Exposure Model. Sacramento: California State Government; 1992.
- Kuss D, Laurain V, Garnier H, Zug M, Vazquez J. Data-based mechanistic rainfall-runoff continuous-time modelling in urban context. IFAC Proceed Vol. 2009; 42(10): 1780-1785. https://doi.org/10.3182/20090706-3-fr-2004.00296
- Nash J, Sutcliffe J. River flow forecasting through conceptual models part I - a discussion of principles. J Hydrol. 1970; 10(3): 282-290. https://doi.org/10.1016/0022-1694(70)90255-6
- Yu S, Bae H. Trends in toxic chemical releases in Korea: comparison between total releases and human health risk levels in the period 2004 to 2012. J Environ Policy Adm. 2015; 23(1): 21-41.
- Beck MB, Mulkey LA, Barnwell TO. Model Validation for Predictive Exposure Assessments. Washington, D.C.: U.S. Environmental Protection Agency; 1994.
- United States. Agency for Toxic Substances and Disease Registry. Toxicological Profile for Benzene. Atlanta: U.S. Department of Health and Human Services; 2007.
- Bruine de Bruin W, Saw HW, Goldman DP. Political polarization in US residents' COVID-19 risk perceptions, policy preferences, and protective behaviors. J Risk Uncertain. 2020; 61(2): 177-194. https://doi.org/10.1007/s11166-020-09336-3
- Haas C. Importance of distributional form in characterizing inputs to Monte Carlo risk assessments. Risk Anal. 1997; 17(1): 107-113. https://doi.org/10.1111/j.1539-6924.1997.tb00849.x
- Nam BH, Yoon MJ, Lee JH, Choi JS, Baek SO. Goodness-of-fit test of distribution of airborne concentration for probabilistic risk assessment. Proceed Korea Air Pollut Res Assoc Conf. 1998; 2: 134-135.
- Jo AR, Kim TS, Seo JK, Yoon HJ, Kim PJ, Choi KH. Uncertainty analysis and application to risk assessment. J Environ Health Sci. 2015; 41(6): 425-437. https://doi.org/10.5668/JEHS.2015.41.6.425
- Korea Environment Institute. Analysis System for Regional Environmental Status to Support Environmental Assessment: The Status and Potential of i) Onshore Wind Power Generation and ii) Floating Photovoltaic Power Generation. Sejong: Korea Environment Institute; 2017.
- National Institute of Environmental Research. Korean Exposure Factors Handbook for Children. Incheon: National Institute of Environmental Research; 2019.