Measured concentrations of 1,2,4-trichlorobenzene (1,2,4-TCB) in soil and groundwater detected in an industrial contaminated site were used to test several probabilistic options for refining site-specific ecological risks assessment, ranging from comparison of single effects and exposure values through comparison of probabilistic distributions for exposure and effects to the use of distribution based quotients (DBQs) obtained through Monte Carlo simulations. The results of the deterministic approach, which suggest that risk exceeds a level of concern for soil organisms, were influenced mainly by the presence of hot spots reaching concentrations able to affect acutely a large proportion of species, while the large majority of the area presents 1,2,4-TCB concentrations below those reported as toxic. Ground-(pore)water concentrations were compared with aquatic ecotoxicity data in orderto obtain an estimation of the potential risk for aquifers and streams in the adjacent area as well as for soil-dwelling organisms exposed via pore water. In this case, the risk is distributed over a large proportion of the site, while the local risk of hot spots was low, showing that risk characterization based exclusively on soil concentrations might be insufficient.
"The probabilistic ecological risk assessment (PERA) was performed by using the Probabilistic Risk Assessment Tool (PRAT) (Solomon et al., 2000, 1996). In PERA, estimation of risk is described as being proportional to the degree of overlap of the distributions, and one method of displaying risk is through the use of joint probability curves (JPCs), which describes the probability of a particular set of exposure conditions occurring relative to the number of taxa that would be affected (Jin et al., 2012; Zolezzi et al., 2005). The x-axis of the JPC represents the intensity of effects, while the y-axis represents their probability. "
"To quantify this uncertainty and its impact on the estimation of expected risk, a Monte Carlo simulation (Oracle Crystal Ball software, Version 7.3.1) was used to conduct the uncertainty analysis, which has been used successfully in many risk assessments (Traas et al., 1996; Kooistra et al., 2005; Zolezzi et al., 2005; Masago et al., 2006; Schenker et al., 2008; Choi et al., 2009; Ritter et al., 2010; Teunis et al., 2010; Viau et al., 2011). DP concentrations were assumed to be uniformly distributed within the minimum and maximum ranges determined in the present study. "
[Show abstract][Hide abstract] ABSTRACT: A screening level human health risk assessment based on the worst-case scenario was conducted on the occupational and residential exposures to Dechlorane Plus (DP) in the manufacturing facility region and an electronic-waste (e-waste) recycling site in China, which are two of the most polluted areas of DP in the world. Total estimated exposure dose (EED) via dietary, dermal, and inhalation was approximately 0.01 mg kg-1 d-1 for people living in the manufacturing facility region. In comparison, total EEDs (approximate 0.03 μg kg-1, d-1) were 300-fold lower in people living near an e-waste recycling site in China. Chronic oral, dermal, and inhalation reference doses (RfDs) were estimated to be 5.0, 2.0, and 0.01 mg kg-1 d-1, respectively. The oral RfD was markedly greater than Mirex (2×10-4 mg kg-1 d-1) and Decabromodiphenyl ether (BDE-209; 7×10-3 mg kg-1 d-1), which have been or might be replaced by DP as a flame retardant with less toxicity. Monte Carlo simulation was used to generate the probability densities and functions for the hazard index which was calculated from the EEDs and RfDs to assess the human health risk. The hazard index was three orders of magnitude lower than 1, suggesting occupational and residential exposures were relatively safe in the manufacturing facility region and e-waste recycling site.
Science of The Total Environment 05/2013; 445. DOI:10.1016/j.scitotenv.2012.12.059 · 4.10 Impact Factor
"The European Union, which frequently establishes regulatory-binding quotients, distinguishes between the two methods in regulatory matters. This is due to the fact that Monte Carlo simulation can be used to assess a variety of types of data distributions and data sets even when data do not fit specific distributions, such as the normal probability function (Zolezzi et al. 2005). "
[Show abstract][Hide abstract] ABSTRACT: The ecological risks posed by three chlorophenols (CPs), 2,4-dichlorophenol (2,4-DCP), 2,4,6-trichlorophenol (2,4,6-TCP), and pentachlorophenol (PCP) in Chinese surface waters were assessed.
This was achieved by applying a tiered ecological risk assessment (ERA) approach ranging from deterministic methods to probabilistic options to measured concentrations of CPs in surface water of seven major watersheds and three drainage regions in China and the chronic toxicity data for indigenous Chinese species.
The results show that the risks of three chlorophenols are ranked PCP>2,4-DCP≈2,4,6-TCP. PCP posed little ecological risk while 2,4-DCP and 2,4,6-TCP posed negligible or de minimis risk in Chinese surface water. However, the risks varied with different river basins, for example, PCP posed some ecological risk in the Yangtze, Huaihe, and Pearl Rivers. The magnitude of 2,4-DCP and 2,4,6-TCP pollution in North China was more serious than that in South China.
The probabilistic risk assessment approach, which can provide more information for risk managers and decision makers, was favored over the screening-level single-value estimate method. However, the results from all tiers of the ERA methods in the framework were consistent with each other.
Environmental Science and Pollution Research 11/2011; 19(5):1544-54. DOI:10.1007/s11356-011-0660-8 · 2.83 Impact Factor
Getnet D. Betrie, Rehan Sadiq, Kevin A. Morin, Solomon Tesfamariam
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