Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/91576

TítuloQuantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure
Autor(es)Melo, Antonio
Costa, Joana Sofia Gomes
Quintelas, Cristina Maria Catalão
Amaral, António Luís
Ferreira, Eugénio C.
Mesquita, Daniela P.
Palavras-chaveAtrazine
Sequencing batch reactor
Aggregates
Image analysis
Partial least squares
Data3-Dez-2024
EditoraElsevier 1
RevistaSeparation and Purification Technology
CitaçãoMelo, A. R. B.; Costa, Joana Sofia Gomes; Quintelas, Cristina; Amaral, A. Luís; Ferreira, Eugénio C.; Mesquita, Daniela P., Quantitative image analysis for assessing extracellular polymeric substances in activated sludge under atrazine exposure. Separation and Purification Technology, 349(127831), 2024
Resumo(s)Extracellular polymeric substances (EPS) play a vital role in biological wastewater treatment systems. This study investigates the impact of herbicide atrazine (ATZ) on the overall performance, EPS yield, composition, and sludge morphology in an activated sludge (AS) system operated in a sequencing batch reactor (SBR). Since conventional methods for analyzing EPS are time-consuming and releases residues, a new approach was developed in this work to evaluate the EPS fractions and components, based on the morphological characterization of the biomass using quantitative image analysis (QIA) technique coupled with multivariate statistics. Results showed that exposure to ATZ inhibit biomass activity in terms of organic matter (COD) and nitrogen removal. Moreover, both tightly bound EPS (TB-EPS) and loosely bound EPS (LB-EPS) increased under ATZ, indicating that microorganisms release EPS as a defense mechanism against environmental changes. The PN/PS ratio also increases, indicating likely increased hydrophobicity in ATZ phases. Furthermore, ATZ phases exhibit a predominance of large aggregates compared to intermediate and small ones, indicating a change in aggregate morphological structure associated with EPS production. The new approach using QIA coupled with partial least squares (PLS) modeling provides accurate predictions of EPS content. The increase in TB-EPS is closely related to the rise of large aggregates in phases exposed to higher ATZ concentrations. The PLS models demonstrate high accuracy for EPS prediction (coefficients of determination, R2 above 0.86), showcasing the feasibility of using QIA for EPS assessment in AS systems. This approach offers significant potential for regular process monitoring and management, providing a more environmentally friendly methodology by eliminating the need for chemical usage.
TipoArtigo
URIhttps://hdl.handle.net/1822/91576
DOI10.1016/j.seppur.2024.127831
ISSN1383-5866
Versão da editorahttps://www.journals.elsevier.com/separation-and-purification-technology
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

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