205 research outputs found
Experimental measurement and modeling of radiation fields in TiO2 nanoparticle photocatalysis
Tecniche di modellazione di reattori di disinfezione con agenti chimici: dall’IDDF alla CFD
Il processo di disinfezione ricopre un ruolo fondamentale negli impianti di potabilizzazione e depurazione. Un importante strumento di supporto alla progettazione e all’ottimizzazione di questa fase è la modellazione del processo, basata su un approccio convenzionale, come l’Integrated Disinfection Design Framework (IDDF), o su un approccio avanzato, come la fluidodinamica computazionale (Computational Fluid Dynamics, CFD). Nel presente lavoro, le due tecniche modellistiche, IDDF e CFD, sono state applicate per la modellazione a scala pilota di un reattore di contatto aperto a setti, confrontando le loro prestazioni nella descrizione del processo di disinfezione e svolgendo un’analisi di sensitività sui principali parametri operativi e cinetici. Una prima parte del lavoro si è concentrata sulla corretta applicazione delle due tecniche modellistiche, utilizzando i dati sperimentali disponibili per scopi di calibrazione, mentre nella seconda parte le due tecniche modellistiche sono state confrontate. Entrambi gli approcci sono risultati strumenti efficaci nel caso si disponga di dati sperimentali affidabili, indispensabili per la messa a punto e la corretta applicazione dei modelli. La scelta dell’approccio più idoneo non è univoca, ma dipende fondamentalmente dell’obiettivo del lavoro e dalle risorse computazionali disponibili. Per quanto un approccio semplificato come l’IDDF abbia dimostrato di essere uno strumento efficace per la stima dei fenomeni coinvolti nei processi di decadimento dell’ipoclorito di sodio, inattivazione batterica e formazione di sottoprodotti, questo tralascia qualsiasi informazione circa gli effetti locali, a differenza della CFD che ha invece evidenziato come la loro identificazione sia indispensabile per determinare e quantificare possibili fonti di non idealitÃ
Editorial: Ecotechnologies for Wastewater Treatment - Impacting the environment with innovation in wastewater treatment
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An integrated human health risk assessment framework for alkylphenols due to drinking water and edible crop consumption
INTRODUCTION
The scarcity of clean freshwater is becoming a major issue for present and future
generations, especially in densely urbanised areas. This situation promotes the potential
cross-contamination of different environmental compartments by contaminants of emerging
concern (CECs) which, in fact, have already been detected worldwide in surface water,
groundwater and soils. In particular, the CECs released by wastewater treatment plants
(WWTPs) can end up both in the recipient surface water and groundwater, both of which are
used as drinking water (DW) sources. Furthermore, if those water sources and reclaimed
wastewater are used for irrigation, CECs can be directly absorbed by crops intended for
human consumption or accumulate in soil and translocate to crops over time. Hence, both
DW and edible crops are critical CEC exposure pathways for humans, the combined effect of
which requires further investigation. This work is aimed at developing an integrated
framework for a quantitative chemical risk assessment due to CECs in complex multiple-use
scenarios, combining DW and edible crop consumption, as a decision-making support tool
for optimising solutions to minimise risks and social costs.
METHODOLOGY
The developed procedure includes several steps. Firstly, the analysed system boundaries are
defined, to evaluate all the phenomena affecting the fate of CECs from source to end user.
Then, CEC migration (e.g. diffusion in surface water, infiltration in soil, uptake by food crops)
and human exposure (via water and edible crop consumption) are modelled in an integrated
framework as a function of boundary conditions, CECs and by-products characteristics, and
proposed interventions. Exposure models are calibrated through literature data, field
monitoring and lab tests where, for instance, the CECs’ fate and uptake by vegetables from
contaminated soils have been investigated. In the hazard assessment step, a toxicological
characterisation was performed to obtain single CEC adverse effect potencies, aimed at
applying the Relative Potency Factors methodology for combining CECs that affect the
same endpoint. Lastly, exposure and hazard assessment steps are combined to
quantitatively estimate the risk to human health from a mixture of CECs, which includes
uncertainty analyses to account for knowledge gaps and to provide decision-makers with
the confidence level of the risk estimation.
RESULTS
The developed quantitative risk assessment procedure has been applied to a case study on
the mixture of two alkylphenols, i.e. bisphenol-A (BPA) and nonylphenol (NP), used as
reference CECs. Literature and field-monitoring data were used to feed the model, with an
estimate of BPA and NP concentration in DW up to 0.1 and 0.35 μg/L, respectively, as a
function of different system boundary conditions. As for their uptake in edible crops, lab
tests with contaminated soil (BPA=75 μg/kg and NP=10 mg/kg, according to the range
reported in literature for soil irrigated with reclaimed wastewater or amended with biosolids)
demonstrated a significant transfer of NP from soil to vegetables, with concentrations of up
to 230 μg/kg fresh weight (f.w.) in the edible parts. No BPA (<8 μg/kg f.w.) was found in
vegetables, unlike its metabolite para-hydroxybenzoic acid (up to 56 μg/kg f.w). Those
results highlight that both DW and edible crop consumption exposure pathways are critical
for the risk to human health due to BPA, NP and their by-products. Several interventions in
WWTPs or in DW treatment plants and distribution networks were simulated, demonstrating
promising cumulative risk reduction.
DISCUSSION
Integrated modelling of the fate of CEC mixtures in complex multiple-use water systems,
combined with quantitative risk assessment, has proven to be an effective tool to identify
the main causes of risk for humans and to assign the various CEC source contributions. Lab
tests proved to be useful to investigate the fate of CECs, including metabolites, in the soil
system and potential transfer to food crops, corroborating the information from literature
and monitoring data for model calibration. Integrated modelling also made it possible to
explore several intervention strategies to be adopted at different points of the water system,
identifying those that achieve the minimum overall mixture risk. Moreover, in addition to CEC
toxicological characterisation, this procedure allows decision-makers to prioritise CECs to
be regulated not only based on their exposure levels but looking at their contribution to the
overall mixture risk. Lastly, uncertainty analysis made it possible to properly consider the
availability and quality of CEC data, especially as regards their physical-chemical behaviour
and toxicity, thereby providing the degree of confidence for the estimated risk, which is a key
factor for taking informed decisions concerning CEC
Alkylphenols from drinking water and food consumption: an integrated human health risk assessment
SafeCREW: a holistic project to reduce NOM and DBPs in drinking water and minimize the human health risk under climate change scenarios
A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems
A smart, safe, and efficient management of water is fundamental for both developed and developing countries. Several wireless sensor networks have been proposed for real-time monitoring of drinking water quantity and quality, both in the environment and in pipelines. However, surface fouling significantly affects the long-term reliability of pipes and sensors installed in-line. To address this relevant issue, we presented a multi-parameter sensing node embedding a miniaturized slime monitor able to estimate the micrometric thickness and type of slime. The measurement of thin deposits in pipes is descriptive of water biological and chemical stability and enables early warning functions, predictive maintenance, and more efficient management processes. After the description of the sensing node, the related electronics, and the data processing strategies, we presented the results of a two-month validation in the field of a three-node pilot network. Furthermore, self-powering by means of direct energy harvesting from the water flowing through the sensing node was also demonstrated. The robustness and low cost of this solution enable its upscaling to larger monitoring networks, paving the way to water monitoring with unprecedented spatio-temporal resolution.
Document type: Articl
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