Advertisement

Water Quality, Exposure and Health

, Volume 3, Issue 1, pp 25–36 | Cite as

Fuzzy Based Health Risk Assessment of Heavy Metals Introduced into the Marine Environment

  • Abdullah MofarrahEmail author
  • Tahir Husain
Article

Abstract

There are concerns among scientists about the significant amount of heavy metals introduced into the marine environment by the petroleum industry during exploration and production phases. The toxicity of heavy metals such as arsenic (As), cadmium (Cd), chromium (Cr), and mercury (Hg) are of particular concern, because they may pose major human health risks through consumption of contaminated food. This study conducts a conservative human health risk assessment study for the selected heavy metals discharged into the marine environment through petroleum operations. Probabilistic risk assessment technique, together with fuzzy set theory, is used to incorporate uncertainties into the risk assessment model. Random and fuzzy variables were integrated to develop the membership functions to individuals’ risk at different fractiles, and corresponding cumulative distribution functions (CDF) of risks were developed. The α-cut concept was used to handle fuzzy arithmetic and Monte Carlo simulation (MCS) was used to carry out the statistical calculations. Using human ingestion pathway, the 90th percentile membership function of cumulative cancer risk due to various heavy metals was calculated, and the support of this fuzzy cancer risk is from 1.0E–08 to 2.50E–05. Non-cancer risk was evaluated as well and found to be within the acceptable limits.

Keywords

Heavy metals Produced water Human health risk Probabilistic risk assessment Fuzzy set 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Andre JM, Rebeyre F, Bouduo A (1990) Mercury contamination levels and distribution in tissues and organs of Delphinids (Stenella attenuata) from the eastern tropical pacific in relation to biological and ecological factors. Mar Environ 30:43–45 CrossRefGoogle Scholar
  2. Atchison GJ, Murphy BR, Bishop WE, McIntosh AW, Mayes RA (1977) Trace metal contamination of bluegill (Lepomis macrochirus) from two Indiana lakes. Trans Am Fish Soc 106:637–640 CrossRefGoogle Scholar
  3. Benekos ID, Shoemaker CA, Stedinger JR (2007) Probabilistic risk and uncertainty analysis for bioremediation of four chlorinated ethenes in groundwater. Stoch Environ Res Risk Assess 21:375–390 CrossRefGoogle Scholar
  4. Brandsma MG, Smith JP (1996) Dispersion modeling perspectives on the environmental fate of produced water discharges. In: Reed M, Johnsen S (eds) Produced water 2: Environmental issues and mitigations. Plenum Press, New York, pp 215–224 Google Scholar
  5. Canli M, Furness RW (1995) Mercury and cadmium uptake from seawater and from food by the Norway lobster Nephrops norvegicus. Environ Toxicol Chem 14(5):819–828 Google Scholar
  6. Chowdhury SH (2004) Decision support system for produced water discharges in offshore operations. MSc thesis, Faculty of Engineering and Applied Science, Memorial University of Newfoundland Google Scholar
  7. Clement Associates (1988) Comparative potency approach for estimating the cancer risk associated with exposure to mixture of polycyclic aromatic hydrocarbons (Interim final report). Prepared for EPA under contract 68-02-4403. ICF-Clement Associates, Fairfax, VA, USA Google Scholar
  8. Cohrssen JJ, Covello VT (1989) Risk analysis: a guide to principles and methods for analyzing health and environmental risks. The National Technical Information Service Google Scholar
  9. Dellenbarger L, Schupp A, Kanjilal B (1993) Seafood consumption in coastal Louisiana. Louisiana Department of Environmental Quality, Office of Water Resources, Baton Rouge, LA, USA Google Scholar
  10. Deng H (1999) Multicriteria analysis with fuzzy pair-wise comparison. Int J Approx Reason 21:215–231 CrossRefGoogle Scholar
  11. DFO (Department of Fisheries and Oceans) (2001) Scientific considerations and research results relevant to the review of the offshore waste treatment guidelines; scientific advice from DFO Atlantic zone to DFO senior management, March 2001. Dartmouth, Nova Scotia, Canada Google Scholar
  12. Doneker RL, Jirka GH (1990) Expert system for hydrodynamic mixing zone analysis of conventional and toxic submerged single port discharges (CORMIX1). Rep. No. EPA/600/3-90/012, Washington, DC, USA Google Scholar
  13. Dubois D, Parade H (1988) Possibility theory: an approach to computerized to uncertainty, 1st edn. Plenum, New York Google Scholar
  14. Frodello JP, Roméo M, Viale D (2000) Distribution of mercury in the organs and tissues of five toothed-whale species of the Mediterranean. Environ Pollut 108:447–452 CrossRefGoogle Scholar
  15. Graham J (1993) The legacy of one in a million in risk in perspective. Harvard Center for Risk Analysis. Risk Perspect 1:1–2 Google Scholar
  16. Guyonnet D, Come B, Perrochet P, Parriaux A (1999) Comparing two methods for addressing uncertainty in risk assessments. J Environ Eng 125(7):660–667 CrossRefGoogle Scholar
  17. Huang H, Fergen RE, Proni JR, Tsaij JJ (1998) Initial dilution equations for buoyancy dominated jets. J Hydraul Eng 24(1):105–108 CrossRefGoogle Scholar
  18. Huang H, Proni JR, Tsai JJ (1996) Probabilistic analysis of ocean outfall mixing zones. J Environ Eng 122(5):359–367 CrossRefGoogle Scholar
  19. IRIS (Integrated Risk Information System), http://www.epa.gov/ngispgm3/iris
  20. Jianbing L, Huang GH, Zeng G, Maqsood I, Huang Y (2007) An integrated fuzzy-stochastic modeling approach for risk assessment of groundwater contamination. J Environ Manag 82:173–188 CrossRefGoogle Scholar
  21. John J, Gjessing ET, Grande M, Salbu B (1987) Influence of aquatic humus and pH on the uptake and depurination of cadmium by the Atlantic salmon (Salmo salar L.). Sci Total Environ 62:253–265 CrossRefGoogle Scholar
  22. Kaufmann A, Gupta MM (1988) Fuzzy mathematical models in engineering and management science. North-Holland, Amsterdam Google Scholar
  23. Kelly KE (1991) The myth of 10-6 as a definition of “acceptable risk”. Presented at the 84th annual meeting and exhibition of the air and waste management association, Vancouver, BC, June 16–21 Google Scholar
  24. Kentel E, Aral MM (2004) Probabilistic-fuzzy health risk modeling. Stoch Environ Res Risk Assess 18:324–338 CrossRefGoogle Scholar
  25. King CK, Riddle MJ (2001) Effects of metal contaminants on the development of the common Antarctic sea urchin Sterechinus neumayeri and comparisons of sensitivity with tropical and temperate echinoids. Mar Ecol Prog Ser 215:143–154 CrossRefGoogle Scholar
  26. Klir G, Yuan B (1995) Fuzzy sets and fuzzy logic: theory and applications. Prentice-Hall, Englewood Cliffs Google Scholar
  27. Lee HM (1996) Applying fuzzy set theory to evaluate the rate of aggregative risk in software development. Fuzzy Sets Syst 79:323–336 CrossRefGoogle Scholar
  28. Lee JHW, Cheung V (1991) Mixing of buoyancy dominated jets in a weak current. Proc Inst Civ Eng. Part 2, Paper No 9697, pp 113–129 Google Scholar
  29. Lohner TW (1997) Is 10-6 an appropriate de minimus cancer risk goal? Risk Policy Report, 18 April 1997, pp 31–33 Google Scholar
  30. Maxwell RM, Kastenberg WE (1999) Stochastic environmental risk analysis: an integrated methodology for predicting cancer risk from contaminated groundwater. Stoch Environ Res Risk Assess 13:27–47 CrossRefGoogle Scholar
  31. Meinhold AF, Holtzman S, DePhillips M (1996) Risk assessment for produced water discharges to open bays in Louisiana. In: Reed M, Johnsen S (eds) Produced water 2: environmental issues and mitigation technologies. Plenum Press, New York, pp 395–409 Google Scholar
  32. Middaugh DP, Davis WR, Yoakum RL (1975) The response of larval fish, Leiostomus zanthurus, to environmental stress following sublethal cadmium exposure. Mar Sci 19:13–19 (as cited in AQUIRE, file 6) Google Scholar
  33. Miller DS, Tyler GM Jr. (1998) Sustaining the Earth: an integrated approach. Thomson, Washington, p 37 Google Scholar
  34. Mukhtasor (2001) Hydrodynamic modeling and ecological risk based design of produced water discharge from an offshore platform. A thesis for PhD at Memorial University of Newfoundland Google Scholar
  35. Nasseri H (2008) Fuzzy numbers: positive and nonnegative. Int Math Forum 3(36):1777–1780 Google Scholar
  36. Neff JM (1997) Metals and organic chemicals associated with oil and gas produced water: bioaccumulation, fates and effects in the marine environment. Continental Shelf Association, Inc., report prepared for the Offshore Operation Committee, 14 April 1997 Google Scholar
  37. Neff JM (2002) Bioaccumulation in marine organisms: effects of contaminants from oil well produced water, pp 191–202. Elsevier, Amsterdam Google Scholar
  38. NSCRF (National Study of Chemical Residue in Fish) (2007) US Environmental Protection Agency. EPA 823-R-92-008. Office of Science and Technology, Standards and Applied Science Division, Washington, DC, USA Google Scholar
  39. Ober AG, González M, Santa Maria I (1987) Heavy metals in molluscan crustacean and other commercially important Chilean marine coastal water species. Bull Environ Contam Toxicol 38:534–539 CrossRefGoogle Scholar
  40. OGP (The International Association of Oil & Gas Producers) (2005) Fate and effects of naturally occurring substances in produced waters on the marine environment. Report 364. Available at http://www.ogp.org.uk/pubs/364.pdf
  41. Proni JR, Huang H, Tsai JJ (1996) Probabilistic analysis of ocean outfall mixing zones. J Environ Eng 122(5):359–367 CrossRefGoogle Scholar
  42. Robinson J, Avenant-Oldewage A (1997) Chromium, copper, iron, and manganese bioaccumulation in some organs and tissues of Oreochromis mossambicus from the lower Olifants River inside the Kruger National Park. Water SA 23(4):387–403 Google Scholar
  43. Schultz E, Stephen E, Steimle M (1996) Distribution of finfish caught near oilfield structures along coastal Louisiana and Texas. In: Reed M, Johnsen S (eds) Produced water; environmental issues and mitigations. Plenum Press, New York, pp 381–394 Google Scholar
  44. Smith JP, Tyler AO, Rymell MC, Shidhart H (1996) Environmental impact of produced water in the Java Sea, Indonesia. In: Proceedings of the SPE Asia Pacific oil and gas conference, Australia, 28–31 October Google Scholar
  45. Stephenson MT (1992) A survey of produced water studies. In: Ray JP, Engelhardt FR (eds) Produced water technological/environmental issues and solutions. Plenum Press, New York, pp 1–10 Google Scholar
  46. Stephenson MT, Ayers RC, Bickford LJ, Caudle DD, Cline JT, Cranmer G, Duff E, Garland TA, Herenius RP, Jacobs WM, Inglesfield C, Norris G, Petersen JD, Read AD (1994) North Sea produced water: fate and effects in the marine environment. Report No. 2, 62/204, E&P Forum, London, England, p 48 Google Scholar
  47. STORET (STOrage and RETrieval) database (2007) US Environmental Protection Agency, Washington, DC, USA. Available at http://www.epa.gov/storet
  48. Taylor D (1983) The significance of the accumulation of cadmium by aquatic organisms. Ecotoxicol Environ Saf 7:33–42 CrossRefGoogle Scholar
  49. Travis CC, et al. (1987) Cancer risk management: a review of 132 federal regulatory agencies. Environ Sci Technol 21:415–420 CrossRefGoogle Scholar
  50. USEPA (US Environmental Protection Agency) (1986) Superfund public health evaluation manual. Office of Emergency and Remedial response US Environmental Protection Agency, Washington, DC. EPA/540/1-86/060 Google Scholar
  51. USEPA (1989) Risk Assessment guidance for superfund: vol 1—Human health evaluation manual (part A, baseline risk assessment). Interim final. Office of Health and Environmental Assessment. EPA/540/1-89/022. United States Environmental Protection Agency, Washington, DC Google Scholar
  52. USEPA (1991) Risk assessment guidance for superfund: vol 1—Human health evaluation manual (part B, development of risk-based preliminary remediation goals). Publication 9285.7-01B. Office of Emergency and Remedial Response, US EPA, Washington, DC Google Scholar
  53. USEPA (1993) Development document for effluent limitations guidelines and new source performance standards for the offshore subcategory of the oil and gas extraction point source category: final. EPA-821-R-93-003. Office of Water, Washington, DC Google Scholar
  54. USEPA (1995) Water quality benefits analysis for the proposed effluent guidelines for the coastal subcategory of the oil and gas extraction industry. EPA 821-R-95-001. Office of Water, Washington, DC Google Scholar
  55. USEPA (1996a) Exposure factor handbook; vol II; Food ingestion factors. EPA l600-p-95/002Bp, US Environmental Protection Agency, Washington, DC Google Scholar
  56. USEPA (1996b) Summary report for the workshop on Monte Carlo analysis, risk assessment forum. USEPA, Washington, DC. EPA-630-R-96-010 Google Scholar
  57. USEPA (1997) Exposure factors handbook. National center for environmental assessment. Office of Research and Development. August 1997. Available at: http://www.epa.gov/ncea/efh/
  58. USEPA (1999) Cancer risk coefficients for environmental exposure to radionuclides. EPA/402/R-99/001. Office of Air and Radiation. Washington, DC Google Scholar
  59. USEPA (2001) Risk assessment guidance for superfund (RAGS), vol III—Part A, process for conducting probabilistic risk assessment. EPA 540-R-02–002. Office of Emergency and Remedial Response, Washington, DC Google Scholar
  60. USEPA (2005a) Human health risk assessment GE/Housatonic River site, rest of river, vol IV, Appendix C, consumption fish and waterfowl risk assessment, February 2005, pp 4–42. Tables 4–9, pp 4–31. USEPA Region I, Boston Google Scholar
  61. USEPA (2005b) Human health risk assessment protocol for hazardous waste combustion facilities—final Google Scholar
  62. Wideman A (1996) Regulation of produced water by the US Environmental Protection Agency. In: Reed M, Johnsen S (eds) Produced water 2; environmental issues and mitigations. Plenum Press, New York Google Scholar
  63. Yong WL, Mohammed F, Bogardi I (1995) Nitrate risk assessment using fuzzy set approach. Environ Eng (ASCE), vol 120, No 3 Google Scholar
  64. Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353 CrossRefGoogle Scholar
  65. Zimmermann HJ (2001) Fuzzy set theory and its applications, 4th edn. Kluwer Academic, Norwell CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Faculty of Engineering and Applied ScienceMemorial UniversitySt. John’sCanada

Personalised recommendations