In recent years, the increasing global population and changing climate patterns have intensified the demand for sustainable water management solutions. Agriculture, which accounts for a significant portion of water usage, underscores the importance of wastewater reuse as a viable option to alleviate pressure on freshwater resources. However, the multiple environmental compartments inherently involved in this practice, raise concerns about cross-contamination, especially regarding Contaminants of Emerging Concern (CECs) and their potential risks posed to both the environment and human health. The vast number of these contaminants, coupled with uncertainties such as data scarcity and occurrences of values below the limits of quantification (LOQ), complicates their classification and analysis. Therefore, it is crucial to adopt approaches capable of managing these uncertainties while prioritizing CECs for systematic monitoring and effective reduction strategies based on both environmental and human health risks. This work aims to assess and compare two distinct risk assessment methodologies for prioritizing CECs based on both environmental and human health risks in the context of agricultural wastewater reuse: Quantitative Chemical Risk Assessment (QCRA) and the Typology of Pollutants (TyPol) approach. QCRA generates probabilistic risk distributions based on toxicological parameters and compound concentrations, while TyPol employs clustering techniques to categorize CECs based on molecular properties and environmental behavior. While QCRA requires comprehensive parameter knowledge, TyPol uses statistical methods to group CECs with similar characteristics, enabling risk estimations even with incomplete data. Both methodologies produce comprehensive CEC rankings, facilitating the prioritization of monitoring efforts and regulatory actions. The study explores and compares the outcomes of both methods, identifying similarities and differences, and evaluates the potential for integrating these approaches to address data gaps.
Negli ultimi anni, l'incremento della popolazione mondiale e i cambiamenti climatici hanno accentuato la necessità di soluzioni sostenibili per la gestione delle risorse idriche. In particolare, l'agricoltura, che consuma una quota significativa dell'acqua disponibile, evidenzia l'importanza del riutilizzo delle acque reflue per mitigare la pressione sulle riserve di acque di approvvigionamento. Tuttavia, dato il numero di comparti ambientali inevitabilmente coinvolti dal riuso agricolo, questa pratica solleva preoccupazioni riguardo alla loro contaminazione incrociata, specialmente in relazione ai Contaminanti Emergenti (CE) ed ai potenziali rischi associati per l'ambiente e la salute umana. La vasta gamma di CE, unita alle incertezze derivanti dalla scarsità di dati e alla presenza di valori inferiori ai limiti di quantificazione (LOQ), rende complessa la loro classificazione e analisi. È dunque essenziale adottare approcci in grado di gestire tali incertezze, prioritizzando i CE per un monitoraggio sistematico e sviluppando strategie di riduzione basate sui rischi per l'ambiente e la salute umana. Questo studio mira a valutare e confrontare due metodologie di valutazione del rischio per prioritizzare i CE nel contesto del riutilizzo delle acque reflue in agricoltura: la Valutazione Probabilistica del Rischio Chimico (QCRA) e l'approccio TyPol (Tipologia di Inquinanti). La QCRA genera distribuzioni probabilistiche di rischio basate sui parametri tossicologici e le concentrazioni dei CE, mentre TyPol utilizza tecniche di clustering per categorizzare i CE in base alle loro proprietà molecolari e al comportamento in ambiente. Mentre la QCRA richieda una conoscenza approfondita dei parametri tossicologici, TyPol si avvale di metodi statistici per raggruppare i CE con caratteristiche simili, consentendo stime del rischio anche in caso di dati incompleti. Entrambe le metodologie permettono di classificare i CE, facilitando la definizione delle priorità sia per il loro monitoraggio che per la loro regolamentazione normativa. Questo studio esplora e confronta i risultati dei due metodi, identificando somiglianze e differenze, e valuta il potenziale per l’integrazione di questi approcci con lo scopo di colmare le lacune nei dati.
Comparing risk-based approaches to jointly assess environmental and human health risks and prioritize emerging contaminants in agricultural wastewater reuse
Desca, Alberto
2023/2024
Abstract
In recent years, the increasing global population and changing climate patterns have intensified the demand for sustainable water management solutions. Agriculture, which accounts for a significant portion of water usage, underscores the importance of wastewater reuse as a viable option to alleviate pressure on freshwater resources. However, the multiple environmental compartments inherently involved in this practice, raise concerns about cross-contamination, especially regarding Contaminants of Emerging Concern (CECs) and their potential risks posed to both the environment and human health. The vast number of these contaminants, coupled with uncertainties such as data scarcity and occurrences of values below the limits of quantification (LOQ), complicates their classification and analysis. Therefore, it is crucial to adopt approaches capable of managing these uncertainties while prioritizing CECs for systematic monitoring and effective reduction strategies based on both environmental and human health risks. This work aims to assess and compare two distinct risk assessment methodologies for prioritizing CECs based on both environmental and human health risks in the context of agricultural wastewater reuse: Quantitative Chemical Risk Assessment (QCRA) and the Typology of Pollutants (TyPol) approach. QCRA generates probabilistic risk distributions based on toxicological parameters and compound concentrations, while TyPol employs clustering techniques to categorize CECs based on molecular properties and environmental behavior. While QCRA requires comprehensive parameter knowledge, TyPol uses statistical methods to group CECs with similar characteristics, enabling risk estimations even with incomplete data. Both methodologies produce comprehensive CEC rankings, facilitating the prioritization of monitoring efforts and regulatory actions. The study explores and compares the outcomes of both methods, identifying similarities and differences, and evaluates the potential for integrating these approaches to address data gaps.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/223136