Development of a quantitative chemical risk assessment (QCRA) procedure for contaminants of emerging concern in drinking water supply
| Autor: | Manuela Antonelli, Milou M.L. Dingemans, Bas G.H. Bokkers, Andrea Turolla, Luca Penserini, P.W.M.H. Smeets, Beatrice Cantoni, D. Vries |
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| Rok vydání: | 2020 |
| Předmět: |
Environmental Engineering
0208 environmental biotechnology Water supply 02 engineering and technology 010501 environmental sciences Stochastic modeling 01 natural sciences Risk Assessment Activated carbon adsorption Water Supply Environmental monitoring Waste Management and Disposal Chemical risk 0105 earth and related environmental sciences Water Science and Technology Civil and Structural Engineering Drinking water treatment business.industry Ecological Modeling Quantitative Chemical Risk Assessment Drinking Water Probabilistic logic Contaminants of Emerging Concern Contamination Pollution Hazard 020801 environmental engineering Risk analysis (engineering) Charcoal Environmental science Water treatment Risk assessment business Water Pollutants Chemical Environmental Monitoring |
| Zdroj: | Water research. 194 |
| ISSN: | 1879-2448 |
| Popis: | The uncertainties on the occurrence, fate and hazard of Contaminants of Emerging Concern (CECs) increasingly challenge drinking water (DW) utilities whether additional measures should be taken to reduce the health risk. This has led to the development and evaluation of risk-based approaches by the scientific community. DW guideline values are commonly derived based on deterministic chemical risk assessment (CRA). Here, we propose a new probabilistic procedure, that is a quantitative chemical risk assessment (QCRA), to assess potential health risk related to the occurrence of CECs in DW. The QCRA includes uncertainties in risk calculation in both exposure and hazard assessments. To quantify the health risk in terms of the benchmark quotient probabilistic distribution, the QCRA estimates the probabilistic distribution of CECs concentration in DW based on their concentration in source water and simulating the breakthrough curves of a granular activated carbon (GAC) treatment process. The model inputs and output uncertainties were evaluated by sensitivity and uncertainty analyses for each step of the risk assessment to identify the most relevant factors affecting risk estimation. Dominant factors resulted to be the concentration of CECs in water sources, GAC isotherm parameters and toxicological data. To stress the potential of this new QCRA approach, several case studies are considered with focus on bisphenol A as an example CEC and various GAC management options. QCRA quantifies the probabilistic risk, providing more insight compared to CRA. QCRA proved to be more effective in supporting the intervention prioritization for treatment optimization to pursue health risk minimization. |
| Databáze: | OpenAIRE |
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