Emerging micro-pollutants represent a danger to human health and ecosystems, as wastewater treatment plants are currently not designed specifically for their removal. Once released downstream of the plants, the treated water transports the micropollutants into the environment, causing their diffusion and consequent accumulation, entailing risks for both agriculture and aquatic flora. Through some statistical methodologies, 155 micro-pollutants were examined, selected starting from some experimental data resulting of sampling carried out by the Mario Negri Institute at the three waste water treatment plants present in the city of Milan, with the aim of developing statistical models, able to predict the percentages of micro pollutant removal, starting from their chemical-physical parameters. By factor analysis, some prediction models have been developed, with a linear regression procedure, considering both removals derived from the literature, and observed removals, deriving from the Mario Negri Institute's samplings. Using the discriminant analysis, a model was obtained, able to predict the classes of micro pollutant removal in relation to their chemical properties. Finally, the dependence of micro-pollutant removal capacity was assessed with respect to the removal efficiency of macro-pollutants, such as COD, of the three Milan plants. The results showed considerable differences between the removals detected experimentally in the three Milan plants and what was reported in the literature, for many of the substances evaluated. In an attempt to explain the nature of these discrepancies, further analyzes were carried out to assess whether specific plant data (e.g. Equivalent Inhabitants, HRT and SRT) could affect the removal of emerging micro-pollutants.
I microinquinanti emergenti rappresentano un pericolo per la salute umana e gli ecosistemi, in quanto gli impianti di trattamento delle acque reflue attuali non sono progettati specificamente per la loro rimozione. Una volta rilasciate a valle degli impianti, le acque trattate trasportano i microinquinanti nell’ambiente, causandone la diffusione e il conseguente accumulo, comportando rischi sia per l’agricoltura che per la flora acquatica. Attraverso alcune metodologie statistiche, sono stati esaminati 155 microinquinanti, selezionati a partire da alcuni dati sperimentali, frutto di campionamenti svolti dall’Istituto Mario Negri presso i tre impianti di depurazione delle acque reflue presenti nella città di Milano, con il fine di elaborare dei modelli statistici in grado di prevedere le percentuali di rimozione dei microinquinanti, partendo dai loro parametri chimico-fisici. Mediante delle analisi fattoriali, si sono sviluppati alcuni modelli di previsione, con una procedura di regressione lineare, considerando sia rimozioni ricavate dalla letteratura che rimozioni osservate, derivanti dai campionamenti dell’Istituto Mario Negri. Utilizzando l’analisi del discriminante, è stato ottenuto un modello in grado di prevedere le classi di rimozione dei microinquinanti in relazione alle loro proprietà chimiche. È stata infine valutata la dipendenza delle capacità di rimozione dei microinquinanti rispetto all’efficienza di rimozione di macroinquinanti, come il COD, dei medesimi impianti. I risultati hanno mostrato notevoli differenze tra le rimozioni rilevate sperimentalmente nei tre impianti Milanesi e quanto riportato in letteratura per molte delle sostanze valutate. Nel tentativo di spiegare la natura di tali discrepanze, sono state effettuate ulteriori analisi per valutare se dati specifici degli impianti (es. Abitanti Equivalenti, HRT e SRT), potessero incidere sulle rimozioni dei microinquinanti emergenti.
Analisi e modellazione statistica della trattabilità di microinquinanti emergenti nei tre impianti di depurazione di Milano
GIGLIOLI, SARA
2018/2019
Abstract
Emerging micro-pollutants represent a danger to human health and ecosystems, as wastewater treatment plants are currently not designed specifically for their removal. Once released downstream of the plants, the treated water transports the micropollutants into the environment, causing their diffusion and consequent accumulation, entailing risks for both agriculture and aquatic flora. Through some statistical methodologies, 155 micro-pollutants were examined, selected starting from some experimental data resulting of sampling carried out by the Mario Negri Institute at the three waste water treatment plants present in the city of Milan, with the aim of developing statistical models, able to predict the percentages of micro pollutant removal, starting from their chemical-physical parameters. By factor analysis, some prediction models have been developed, with a linear regression procedure, considering both removals derived from the literature, and observed removals, deriving from the Mario Negri Institute's samplings. Using the discriminant analysis, a model was obtained, able to predict the classes of micro pollutant removal in relation to their chemical properties. Finally, the dependence of micro-pollutant removal capacity was assessed with respect to the removal efficiency of macro-pollutants, such as COD, of the three Milan plants. The results showed considerable differences between the removals detected experimentally in the three Milan plants and what was reported in the literature, for many of the substances evaluated. In an attempt to explain the nature of these discrepancies, further analyzes were carried out to assess whether specific plant data (e.g. Equivalent Inhabitants, HRT and SRT) could affect the removal of emerging micro-pollutants.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/147925