Mads Troldborg

Risk assessment and prioritisation of contaminated sites on the catchment scale.

Contaminated sites pose a significant threat to groundwater resources worldwide. Due to limited available resources a risk-based prioritisation of the remediation efforts is essential. Existing risk assessment tools are unsuitable for this purpose, because they consider each contaminated site separately and on a local scale, which makes it difficult to compare the impact from different sites. Hence a modelling tool for risk assessment of contaminated sites on the catchment scale has been developed. The CatchRisk screening tool evaluates the risk associated with each site in terms of its ability to contaminate abstracted groundwater in the catchment. The tool considers both the local scale and the catchment scale. At the local scale, a flexible, site specific leaching model that can be adjusted to the actual data availability is used to estimate the mass flux over time from identified sites. At the catchment scale, a transport model that utilises the source flux and a groundwater model covering the catchment is used to estimate the transient impact on the supply well. The CatchRisk model was tested on a groundwater catchment for a waterworks north of Copenhagen, Denmark. Even though data scarcity limited the application of the model, the sites that most likely caused the observed contamination at the waterworks were identified. The method was found to be valuable as a basis for prioritising point sources according to their impact on groundwater quality. The tool can also be used as a framework for testing hypotheses on the origin of contamination in the catchment and for identification of unknown contaminant sources.

Unsaturated zone leaching models for assessing risk to groundwater of contaminated sites

Risk assessments of sites contaminated with organic contaminants are typically conducted using models that ignore gas phase transport in the unsaturated zone. Here a general approach to developing analytical solutions to multiphase transport is presented. The approach is based on a combined gas and aqueous phase contaminant transport equation. The equation has the same general form as the standard advection-diffusion equation for which many analytical solutions have been derived. Four new analytical solutions are developed using this approach: a three-dimensional solution accounting for infiltration, lateral gas diffusion, sorption and degradation; a simple one-dimensional screening model, and two one-dimensional radial gas diffusion models for use in simulating volatile organic contaminant diffusion in unsaturated soils with an impermeable cover. The models show that both degradation and diffusion are important mechanisms for attenuation of contaminant concentrations at the water table. Finally, model results are compared with field data to illustrate the applicability of the solutions in risk assessment.

Evaluation of spot and passive sampling for monitoring, flux estimation and risk assessment of pesticides within the constraints of a typical regulatory monitoring scheme

In many agricultural catchments of Europe and North America, pesticides occur at generally low concentrations with significant temporal variation. This poses several challenges for both monitoring and understanding ecological risks/impacts of these chemicals. This study aimed to compare the performance of passive and spot sampling strategies given the constraints of typical regulatory monitoring. Nine pesticides were investigated in a river currently undergoing regulatory monitoring (River Ugie, Scotland). Within this regulatory framework, spot and passive sampling were undertaken to understand spatiotemporal occurrence, mass loads and ecological risks. All the target pesticides were detected in water by both sampling strategies. Chlorotoluron was observed to be the dominant pesticide by both spot (maximum: 111.8ng/l, mean: 9.35ng/l) and passive sampling (maximum: 39.24ng/l, mean: 4.76ng/l). The annual pesticide loads were estimated to be 2735g and 1837g based on the spot and passive sampling data, respectively. The spatiotemporal trend suggested that agricultural activities were the primary source of the compounds with variability in loads explained in large by timing of pesticide applications and rainfall. The risk assessment showed chlorotoluron and chlorpyrifos posed the highest ecological risks with 23% of the chlorotoluron spot samples and 36% of the chlorpyrifos passive samples resulting in a Risk Quotient greater than 0.1. This suggests that mitigation measures might need to be taken to reduce the input of pesticides into the river. The overall comparison of the two sampling strategies supported the hypothesis that passive sampling tends to integrate the contaminants over a period of exposure and allows quantification of contamination at low concentration. The results suggested that within a regulatory monitoring context passive sampling was more suitable for flux estimation and risk assessment of trace contaminants which cannot be diagnosed by spot sampling and for determining if long-term average concentrations comply with specified standards.

A Bayesian belief network approach for assessing uncertainty in conceptual site models at contaminated sites.

A key component in risk assessment of contaminated sites is in the formulation of a conceptual site model (CSM). A CSM is a simplified representation of reality and forms the basis for the mathematical modeling of contaminant fate and transport at the site. The CSM should therefore identify the most important site-specific features and processes that may affect the contaminant transport behavior at the site. However, the development of a CSM will always be associated with uncertainties due to limited data and lack of understanding of the site conditions. CSM uncertainty is often found to be a major source of model error and it should therefore be accounted for when evaluating uncertainties in risk assessments. We present a Bayesian belief network (BBN) approach for constructing CSMs and assessing their uncertainty at contaminated sites. BBNs are graphical probabilistic models that are effective for integrating quantitative and qualitative information, and thus can strengthen decisions when empirical data are lacking. The proposed BBN approach facilitates a systematic construction of multiple CSMs, and then determines the belief in each CSM using a variety of data types and/or expert opinion at different knowledge levels. The developed BBNs combine data from desktop studies and initial site investigations with expert opinion to assess which of the CSMs are more likely to reflect the actual site conditions. The method is demonstrated on a Danish field site, contaminated with chlorinated ethenes. Four different CSMs are developed by combining two contaminant source zone interpretations (presence or absence of a separate phase contamination) and two geological interpretations (fractured or unfractured clay till). The beliefs in each of the CSMs are assessed sequentially based on data from three investigation stages (a screening investigation, a more detailed investigation, and an expert consultation) to demonstrate that the belief can be updated as more information becomes available.

A risk-based approach for developing standards for irrigation with reclaimed water

A generalised quantitative risk assessment (QRA) is developed to assess the potential harm to human health resulting from irrigation with reclaimed water. The QRA is conducted as a backward calculation starting from a pre-defined acceptable risk level at the receptor point (defined as an annual infection risk of 10-4 for pathogens and by reference doses (RfD) for chemical hazards) and results in an estimate of the corresponding acceptable concentration levels of the given hazards in the effluent. In this way the QRA is designed to inform the level of water treatment required to achieve an acceptable risk level and help establish reclaimed water quality standards. The QRA considers the exposure of human receptors to microbial and chemical hazards in the effluent through various exposure pathways and routes depending on the specific irrigation scenario. By considering multiple pathways and routes, a number of key aspects relevant to estimating human exposure to recycled water can be accounted for, including irrigation and crop handling practices (e.g., non-edible vs edible, spray vs. drip, withholding time) and volumes consumed (directly vs indirectly). The QRA relies on a large number of inputs, many of which were found to be highly uncertain. A possibilistic approach, based on fuzzy set theory, was used to propagate the uncertain input values through the QRA model to estimate the possible range of hazard concentrations that are deemed acceptable/safe for reclaimed water irrigation. Two scenarios were considered: amenity irrigation and irrigation of ready-to-eat food crops, and calculations were carried out for six example hazards (norovirus, Cryptosporidium, cadmium, lead, PCB118 and naphthalene) and using UK-specific input values. The human health risks associated with using reclaimed water for amenity irrigation were overall deemed low, i.e. the calculated acceptable concentration levels for most of the selected hazards were generally far greater than levels typically measured in effluent from wastewater treatment plants; however the predicted acceptable concentration levels for norovirus and Cryptosporidium suggested that disinfection by UV may be required before use. It was found that stricter concentration standards were required for hazards that are more strongly bound to soil and/or are more toxic/infectious. It was also found that measures that reduce the amount of effluent directly ingested by the receptor would significantly reduce the risks (by up to 2 orders of magnitude for the two pathogens). The results for the food crop irrigation scenario showed that stricter concentration standards are required to ensure the effluent is safe to use. For pathogens, the dominant exposure route was found to be ingestion of effluent captured on the surface of the crops indicating that risks could be significantly reduced by restricting irrigation to the non-edible parts of the crop. The results also showed that the exposure to some organic compounds and heavy metals through plant uptake and attached soil particles could be high and possibly pose unacceptable risk to human health. For both scenarios, we show that the predicted acceptable concentration levels are associated with large uncertainty and discuss the implications this has for defining quality standards and how the uncertainty can be reduced.