Probabilistic Ecological Risk Assessment of 1,2,4-Trichlorobenzene at a Former Industrial Contaminated Site

Abstract

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 order to 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.

A tiered ecological risk assessment of three chlorophenols in Chinese surface waters

“…The risk assessment process used in this study was a tiered approach following published methods (ECOFRAM 1999;Zolezzi et al 2005;Wang et al 2009) and consisting on four levels-deterministic, etc.…”

“…Margins of safety greater than 1.0 indicated that the distributions did not overlap and thus minimal risk to aquatic organisms. In addition, the exceedance probability function (EXF, calculated as 100-cumulative distribution function) and the SSD were used to generate a joint probability curve (JPC), which describes the probability of a particular set of exposure conditions occurring relative to the number of taxa that would be affected (Solomon et al 2000;Zolezzi et al 2005;Wang et al 2009). …”

“…The level 4 method involved distribution-based quotients (DBQs), which expressed the risk as the probability of exceeding preselected HQs (Zolezzi et al 2005). The Monte Carlo technique (Crystal Ball 2000 v.5.2.)…”

“…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).…”

“…Probabilistic ecological risk assessments (PERAs), which qualify and quantify ecological risks through exposure and effect probability distributions, are regarded as an improvement on the HQ approach and, thus, recommended for later tiers in the ecological risk assessment (ERA) process (Solomon 1996). Because PERAs can better describe the likelihood of exceeding the effect thresholds and the risk of adverse effects (Solomon and Sibley 2002), this approach has been adopted by a number of researchers (Giesy et al 1999;Hall et al 2000;Zolezzi et al 2005;Brain et al 2006;Hunt et al 2010). To obtain more reliable results for decision-making processes on site-specific contamination, some researchers and scientific institutions have suggested the use of a tiered approach, ranging from simple deterministic methods to probabilistic methods, for risk characterization, (Solomon et al 2000;Zolezzi et al 2005;Wang et al 2009).…”