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A Systematic Development of Uncertainty Modeling in the Assessment of Health Risk to Environmental Contaminants

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Environmental Contaminants

Part of the book series: Energy, Environment, and Sustainability ((ENENSU))

Abstract

The objective of science-based risk assessment is to protect public health by providing profound decisions. Health risk analysis involves various uncertainties and highly variable parameters like multiple routes (ingestion, dermal, and inhalation), complex environmental contaminants, various pathways, and different exposure to population; which makes the risk estimation procedure extremely challenging and rigorous. The uncertainties in risk assessment majorly result from two reasons, firstly, the lack of knowledge of input variable (mostly random), and secondly, data obtained from an expert judgment or subjective interpretation of available information (non-random). The NRC (1994) states that to ignore the uncertainty in any step of risk assessment process is almost as likely as to leave critical parts of the process has been left incompletely examined and therefore increase the probability of generating a risk estimate that is incorrect, incomplete, or misleading. Each step of the risk assessment process involves various assumptions, both quantitative and qualitative, must be evaluated through uncertainty analysis. However, it is necessary that risk process of evaluation must treats uncertainty and variability scientifically and robustly. Moreover, addressing uncertainties in health risk assessment is a critical issue while evaluating the effects of environmental contaminants on public health. The uncertainty propagation in health risk can be assessed and quantified using probability theory, possibility theory, or a combination of both. This chapter will systematically report the development of various methodologies and frameworks to address the uncertainties that are intrinsic to health risk estimation.

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References

  • Acosta H, Wu D, Forrest BM (2010) Fuzzy experts on recreational vessels, a risk modelling approach for marine invasions. Ecol Model 221(5):850–863

    Article  Google Scholar 

  • Arhonditsis GB, Qian SS, Stow CA, Lamon EC, Reckhow KH (2007) Eutrophication risk assessment using Bayesian calibration of process-based models: application to a mesotrophic lake. Ecol Model 208(2):215–229

    Google Scholar 

  • Ascough JC, Maier HR, Ravalico JK, Strudley MW (2008) Future research challenges for incorporation of uncertainty in environmental and ecological decision-making. Ecol Model 219(3):383–399

    Article  Google Scholar 

  • Bedford T, Cooke RM (2001) Probabilistic risk analysis: foundations and methods. Cambridge University Press, Cambridge, UK

    Google Scholar 

  • Buteau S, Valcke M (2010) Probabilistic human health risk assessment for quarterly exposure to high chloroform concentrations in drinking-water distribution network of the province of Quebec, Canada. J Toxicol Environ Health Part A 73(23):1626–1644

    Article  CAS  Google Scholar 

  • Butt TE, Lockley E, Oduyemi KO (2008) Risk assessment of landfill disposal sites–state of the art. Waste Manag 28(6):952–964

    Article  CAS  Google Scholar 

  • Chen CF, Ma HW, Reckhow KH (2007) Assessment of water quality management with a systematic qualitative uncertainty analysis. Sci Total Environ 374(1):13–25

    Article  CAS  Google Scholar 

  • Croke BFW, Ticehurst JL, Letcher RA, Norton JP, Newham LTH, Jakeman AJ (2006) Integrated assessment of water resources: Australian experiences. In: Integrated assessment of water resources and global change, pp 351–373. Springer, Netherlands

    Google Scholar 

  • Dong Z, Liu Y, Duan L, Bekele D, Naidu R (2015) Uncertainties in human health risk assessment of environmental contaminants: a review and perspective. Environ Int 85:120–132

    Article  CAS  Google Scholar 

  • Dubois D, Prade H, Sessa S (2001) Recent Literature. Fuzzy Sets Syst 355–363

    Google Scholar 

  • Ducey MJ, Larson BC (1999) A fuzzy set approach to the problem of sustainability. For Ecol Manage 115(1):29–40

    Article  Google Scholar 

  • Finley B, Paustenbach D (1994) The benefits of probabilistic exposure assessment: three case studies involving contaminated air, water, and soil. Risk Anal 14(1):53–73

    Article  CAS  Google Scholar 

  • Gottschalk F, Sonderer T, Scholz RW, Nowack B (2010) Possibilities and limitations of modeling environmental exposure to engineered nanomaterials by probabilistic material flow analysis. Environ Toxicol Chem 29(5):1036–1048

    CAS  Google Scholar 

  • Guyonnet D, Bourgine B, Dubois D, Fargier H, Coλme B, Chilès JP (2003) Hybrid approach for addressing uncertainty in risk assessments. J Environ Eng 129(1):68–78

    Google Scholar 

  • Hromkovic JI (2005) Zámecniková. Design and analysis of randomized algorithms: introduction to design paradigms. Springer, New York

    Google Scholar 

  • Janssen P, Petersen A, van der Sluijs J, et al (2003) RIVM/MNP guidance for uncertainty assessment and communication: quickscan hints & actions list. RIVM/MNP Guidance for Uncertainty Assessment and Communication Series 2. Copernicus Institute for Sustainable Development, Universitat Utrecht und RIVM-MNP, Utrecht, The Netherlands

    Google Scholar 

  • Jørgensen RB, Hauser T, D’Hertefeldt T, Andersen NS, Hooftman D (2009) The variability of processes involved in transgene dispersal—case studies from Brassica and related genera. Environ Sci Pollut Res 16(4):389–395

    Article  Google Scholar 

  • Kalberlah F, Schneider K, Schuhmacher-Wolz U (2003) Uncertainty in toxicological risk assessment for non-carcinogenic health effects. Regul Toxicol Pharmacol 37(1):92–104

    Article  CAS  Google Scholar 

  • Kentel E, Aral MM (2004) Probabilistic-fuzzy health risk modeling. Stoch Env Res Risk Assess 18(5):324–338

    Article  Google Scholar 

  • Khan FI, Sadiq R, Husain T (2002) GreenPro-I: a risk-based life cycle assessment and decision-making methodology for process plant design. Environ Model Softw 17(8):669–692

    Article  Google Scholar 

  • Knol AB, Petersen AC, Van der Sluijs JP, Lebret E (2009) Dealing with uncertainties in environmental burden of disease assessment. Environmental Health 8(1):21

    Article  Google Scholar 

  • Li H, Yen VC (1995) Fuzzy sets and fuzzy decision-making. CRC press

    Google Scholar 

  • Luttik R, Mineau P, Roelofs W (2005) A review of interspecies toxicity extrapolation in birds and mammals and a proposal for long-term toxicity data. Ecotoxicology 14(8):817–832

    Article  CAS  Google Scholar 

  • Masters GM, Ela W (2008) Introduction to environmental engineering and science, vol 3. Prentice Hall, Englewood Cliffs, NJ

    Google Scholar 

  • Maxwell RM, Kastenberg WE (1999) Stochastic environmental risk analysis: an integrated methodology for predicting cancer risk from contaminated groundwater. Stoch Env Res Risk Assess 13(1):27–47

    Article  Google Scholar 

  • Mishra H, Rathod M, Karmakar S, Kumar R (2016) A framework for assessment and characterisation of municipal solid waste landfill leachate: an application to the Turbhe landfill, Navi Mumbai, India. Environ Monit Assess 188(6):357(1–26)

    Google Scholar 

  • Mishra H, Karmakar S, Kumar R, Singh J (2017) A framework for assessing uncertainty associated with human health risks from MSW landfill leachate contamination. Risk Anal 37:1237–1255

    Google Scholar 

  • Mofarrah A, Husain T (2011) Fuzzy based health risk assessment of heavy metals introduced into the marine environment. Water Qual Exposure Health 3(1):25–36

    Article  CAS  Google Scholar 

  • Morgan MG, Henrion M, Small M (1990). Uncertainty: a guide to dealing with uncertainty in quantitative risk and policy analysis. Cambridge university press

    Google Scholar 

  • National research Council (1983) Risk assessment in the federal government: managing the process. National Academies Press

    Google Scholar 

  • National Research Council (1994) Science and judgment in risk assessment. National Academies Press

    Google Scholar 

  • Penningroth S (2010) Essentials of toxic chemical risk: science and society. CRC Press

    Google Scholar 

  • Petersen AC (2006) Simulating nature: a philosophical study of computer-simulation uncertainties and their role in climate science and policy advice. CRC Press

    Google Scholar 

  • Refsgaard JC, van der Sluijs JP, Højberg AL, Vanrolleghem PA (2007) Uncertainty in the environmental modelling process–a framework and guidance. Environ Model Softw 22(11):1543–1556

    Article  Google Scholar 

  • Regan HM, Colyvan M, Burgman MA (2002) A taxonomy and treatment of uncertainty for ecology and conservation biology. Ecol Appl 12(2):618–628

    Article  Google Scholar 

  • Reis S, Voigt K, Oxley T (2017) Thematic issue on modelling human and ecological health risks

    Google Scholar 

  • Schuhmacher M, Meneses M, Xifró A, Domingo JL (2001) The use of Monte-Carlo simulation techniques for risk assessment: study of a municipal waste incinerator. Chemosphere 43(4):787–799

    Article  CAS  Google Scholar 

  • Shakhawat C, Tahir H, Neil B (2006) Fuzzy rule-based modelling for human health risk from naturally occurring radioactive materials in produced water. J Environ Radioact 89(1):1–17

    Article  CAS  Google Scholar 

  • Singpurwalla ND, Booker JM (2004) Membership functions and probability measures of fuzzy sets. J Am Stat Assoc 99(467):867–877

    Article  Google Scholar 

  • Stackelberg KV, Burmaster DE (1994) A discussion on the use of probabilistic risk assessment in human health impact assessment. Environ Impact Assess Rev 14(5–6):385–401

    Article  Google Scholar 

  • Stirling A (1999) Risk at a turning point? J Risk Res 1(2):97–109

    Article  Google Scholar 

  • U.S. EPA (1989) Risk assessment guidance for superfund, volume I, human health evaluation manual (part A). EPA/540/1-89/002. Office of emergency and remedial response, Washington, DC

    Google Scholar 

  • U.S. EPA (2004) An examination of EPA risk assessment principles and practices. Staff paper prepared for U.S. Environmental Protection Agency by members of the risk assessment task force office of the science advisor. EPA/100/B- 04/001

    Google Scholar 

  • U.S. EPA (2005) Guidelines for carcinogen risk. U.S. EPA, Washington, DC. EPA/630/P-03/0018

    Google Scholar 

  • Van der Keur P, Henriksen HJ, Refsgaard JC, Brugnach M, Pahl-Wostl C, Dewulf A, Buiteveld H (2008) Identification of major sources of uncertainty in current IWRM practice. Illustrated for the Rhine Basin. Water Resour Manage 22(11):1677–1708

    Article  Google Scholar 

  • Van der Sluijs JP, Janssen PHM, Petersen AC, Kloprogge P, Risbey JS, Tuinstra W, Ravetz JR (2004) RIVM/MNP guidance for uncertainty assessment and communication: tool catalogue for uncertainty assessment. Utrecht University (Downloadable from http://www.nusap.net/sections.php

  • Walker WE, Harremoës P, Rotmans J, van der Sluijs JP, van Asselt MB, Janssen P, Krayer von Krauss MP (2003) Defining uncertainty: a conceptual basis for uncertainty management in model-based decision support. Integrated assessment 4(1):5–17

    Article  Google Scholar 

  • Wang LX (1997) A Course in fuzzy systems and control. Prentice-Hall PTR, Englewood Cliffs, NJ

    Google Scholar 

  • Wynne B (1992) Uncertainty and environmental learning: reconceiving science and policy in the preventive paradigm. Glob Environ Change 2(2):111–127

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inform Control 8(3):338–353

    Article  Google Scholar 

  • Zalk DM, Paik SY, Swuste P (2009) Evaluating the control banding nanotool: a qualitative risk assessment method for controlling nanoparticle exposures. J Nanopart Res 11(7):1685

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Centre for Environmental Science and Engineering, Indian Institute of Technology Bombay, Mumbai, 400076, India

    Harshit Mishra & Subhankar Karmakar

  2. Interdisciplinary Program in Climate Studies, Indian Institute of Technology Bombay (IITB-CECS), Mumbai, 400076, India

    Subhankar Karmakar

  3. Centre for Urban Science and Engineering, Indian Institute of Technology Bombay, Mumbai, 400076, India

    Subhankar Karmakar

  4. National Environmental Engineering Research Institute (NEERI), Nagpur, 440020, India

    Rakesh Kumar

Authors
  1. Harshit Mishra
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  2. Subhankar Karmakar
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  3. Rakesh Kumar
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Corresponding author

Correspondence to Harshit Mishra .

Editor information

Editors and Affiliations

  1. Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India

    Tarun Gupta

  2. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India

    Avinash Kumar Agarwal

  3. Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India

    Rashmi Avinash Agarwal

  4. Energy and Resource Management Division, CSIR-National Environmental Engineering Research Institute (NEERI), Nagpur, Maharashtra, India

    Nitin K. Labhsetwar

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Mishra, H., Karmakar, S., Kumar, R. (2018). A Systematic Development of Uncertainty Modeling in the Assessment of Health Risk to Environmental Contaminants. In: Gupta, T., Agarwal, A., Agarwal, R., Labhsetwar, N. (eds) Environmental Contaminants. Energy, Environment, and Sustainability. Springer, Singapore. https://doi.org/10.1007/978-981-10-7332-8_9

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