Probabilistic health risk assessment for exposures to estuary sediments and biota contaminated with polychlorinated biphenyls, polychlorinated terphenyls and other toxic substances.
A Latin Hypercube probabilistic risk assessment methodology was employed in the assessment of health risks associated with exposures to contaminated sediment and biota in an estuary in the Tidewater region of Virginia. The primary contaminants were polychlorinated biphenyls (PCBs), polychlorinated terphenyls (PCTs), polynuclear aromatic hydrocarbons (PAHs), and metals released into the estuary from a storm sewer system. The exposure pathways associated with the highest contaminant intake and risks were dermal contact with contaminated sediment and ingestion of contaminated aquatic and terrestrial biota from the contaminated area. As expected, all of the output probability distributions of risk were highly skewed, and the ratios of the expected value (mean) to median risk estimates ranged from 1.4 to 14.8 for the various exposed populations. The 99th percentile risk estimates were as much as two orders of magnitude above the mean risk estimates. For the sediment exposure pathways, the stability of the median risk estimates was found to be much greater than the stability of the expected value risk estimates. The interrun variability in the median risk estimate was found to be +/- 1.9% at 3000 iterations. The interrun stability of the mean risk estimates was found to be approximately equal to that of the 95th percentile estimates at any number of iterations. The variation in neither contaminant concentrations nor any other single input variable contributed disproportionately to the overall simulation variance. The inclusion or exclusion of spatial correlations among contaminant concentrations in the simulation model did not significantly effect either the magnitude or the variance of the simulation risk estimates for sediment exposures.
Ebasco Environmental, Arlington, Virginia 22201.
M R
MR
Adams
C A
CA
Hanna
J A
JA
Mayernik
W M
WM
Mendez
D000328:Adult; D002273:Carcinogens / Q000032:analysis; D002648:Child; D003198:Computer Simulation; D004781:Environmental Exposure; D006262:Health; D006801:Humans; D008670:Metals / Q000009:adverse effects / Q000032:analysis; D009010:Monte Carlo Method; D009369:Neoplasms / Q000209:etiology; D011078:Polychlorinated Biphenyls / Q000009:adverse effects* / Q000032:analysis; D011080:Polychloroterphenyl Compounds / Q000009:adverse effects* / Q000032:analysis; D011083:Polycyclic Compounds / Q000009:adverse effects / Q000032:analysis; D011336:Probability; D012306:Risk; D018570:Risk Assessment; D012722:Sewage / Q000009:adverse effects / Q000032:analysis; D012989:Soil Pollutants / Q000009:adverse effects / Q000032:analysis; D013997:Time Factors; D014768:Virginia; D014874:Water Pollutants, Chemical / Q000009:adverse effects* / Q000032:analysis; D014877:Water Pollution, Chemical / Q000009:adverse effects* / Q000032:analysis
D002273:Carcinogens; D008670:Metals; D011080:Polychloroterphenyl Compounds; D011083:Polycyclic Compounds; D012722:Sewage; D012989:Soil Pollutants; D014874:Water Pollutants, Chemical; D011078:Polychlorinated Biphenyls