Unsaturated Zone Leaching Model-driven Probabilistic Human Health Risk
Assessment of Groundwater System in the vicinity of Chandigarh Dumping
Site, India
Abstract
The human health risk assessment (HHRA) of groundwater system in the
vicinity of Chandigarh dumping site was conducted, assuming oral
ingestion and dermal contact exposure scenarios. Observed data of lead
(Pb) concentration in the leachate was used to compute cancer risk (CR)
by integrating unsaturated 1-D leaching model with probabilistic HHRA
framework. The 99 percentile and maximum value of lead (Pb)
concentration at the water table was estimated as 0.089 mg/L and 0.506
mg/L, respectively, for pre-monsoon season, higher than the safe limit
of 0.050 mg/L. In contrast, for the post-monsoon season, only the
maximum value of Pb concentration exceeded the safe limit. Results from
10,000 Monte Carlo simulations showed that the 99 percentile and maximum
value of CR for all the sub-populations during pre-monsoon exceeded the
safe limit (>10 ) via oral ingestion exposure to
Pb-contaminated groundwater. The 95 percentile value of CR for adult
sub-population was estimated as 1.05 x 10 for premonsoon; however, for
the post-monsoon season, only maximum values of CR exceeded the safe
limit. The cancer risk estimates for the pre-monsoon and post-monsoon
seasons via skin dermal contact exposure were found to be lower than the
safe level, posing no danger to human health. Among sub-populations, the
order of posing CR was found to be in the order as adults
(>18 years) > child I (1-5 years)
> teen (11-18 years) > child II (6-10 years).
Uncertainty analysis showed that the lead concentration
(>95% variance contribution), as a major contributor
towards uncertainty in the risk estimates, while event duration (t ),
exposure duration (ED), and ingestion rate (IR) were observed as minor
contributors. The approach presented in this study considered the
uncertainty in the unsaturated leaching model parameters along with
uncertainty in the exposure model parameters, thus can help
decision-makers in estimating risk from open dumping sites with minimal
data availability.