Characterisation of activated sludge by automated image analysis : validation on full-scale plants

Automated methods based on the analysis of macro- and meso-scale images has been developed to characterise activated sludge in terms of size and shape (fractal dimension) of flocs and abundance of filamentous bacteria. After tests on pilot-scale reactors, the method has been validated on full-scale samples from twelve different wastewater treatment plants in France and Portugal

Morphological characterisation of biomass in wastewater treatment using partial least squares

A wastewater treatment plant was followed in order to determine the biomass morphological properties and relate them with other measures as the Total Suspended Solids (TSS) or Sludge Volume Index (SVI). Image analysis was used to provide morphological data, which was subsequently treated by Partial Least Squares (PLS). The results showed very good correlations between observed and model predicted TSS but, considerably lower for SVI

Quantitative image analysis for the characterization of microbial aggregates in biological wastewater treatment : a review

Quantitative image analysis techniques have gained an undeniable role in several fields of research during the last decade. In the field of biological wastewater treatment (WWT) processes, several computer applications have been developed for monitoring microbial entities, either as individual cells or in different types of aggregates. New descriptors have been defined that are more reliable, objective, and useful than the subjective and time-consuming parameters classically used to monitor biological WWT processes. Examples of this application include the objective prediction of filamentous bulking, known to be one of the most problematic phenomena occurring in activated sludge technology. It also demonstrated its usefulness in classifying protozoa and metazoa populations. In high-rate anaerobic processes, based on granular sludge, aggregation times and fragmentation phenomena could be detected during critical events, e.g., toxic and organic overloads. Currently, the major efforts and needs are in the development of quantitative image analysis techniques focusing on its application coupled with stained samples, either by classical or fluorescent-based techniques. The use of quantitative morphological parameters in process control and online applications is also being investigated. This work reviews the major advances of quantitative image analysis applied to biological WWT processes.The authors acknowledge the financial support to the project PTDC/EBB-EBI/103147/2008 and the grant SFRH/BPD/48962/2008 provided by Fundacao para a Ciencia e Tecnologia (Portugal)

Monitoring morphological changes from activated sludge to aerobic granular sludge under distinct organic loading rates and increasing minimal imposed sludge settling velocities through quantitative image analysis

Quantitative image analysis (QIA) was used for monitoring the morphology of activated sludge (AS) during a granulation process and, thus, to define and quantify, unequivocally, structural changes in microbial aggregates correlated with the sludge properties and granulation rates. Two sequencing batch reactors fed with acetate at organic loading rates of 1.1±0.6 kgCOD m3 d1 (R1) and 2.0±0.2 kgCOD m3 d1 (R2) and three minimal imposed sludge settling velocities (0.27mh1, 0.53mh1, and 5.3mh1) induced distinct granulation processes and rates. QIA results evidenced the turning point from flocculation to granulation processes by revealing the differences in the aggregates stratification patterns and quantifying the morphology of aggregates with equivalent diameter (Deq) of 200mDeq650m. Multivariate statistical analysis of the QIA data allowed to distinguish the granulation status in both systems, by clustering the observations according to the sludge aggregation and granules maturation status, and successfully predicting the sludge volume index measured at 5min (SVI5) and 30min (SVI30). These results evidence the possibility of defining unequivocally the granulation rate and anticipating the sludge settling properties at early stages of the process using QIA data. Hence, QIA could be used to predict episodes of granules disruption and hindered settling ability in aerobic granulation sludge processes.The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/ 04469/2020 unit and the project AGeNT PTDC/BTA-BTA/31264/2017 (POCI-01-0145-FEDER-031264). The authors also acknowledge the financial support to S´ergio Alves da Silva through the grant SFRH/BD/ 122623/2016 provided by FCT. A. Val del Rio is supported by Xunta de Galicia (ED418B 2017/075) and program Iacobus (2018/2019).info:eu-repo/semantics/publishedVersio

Activated sludge monitoring of a wastewater treatment plant using image analysis and partial least squares regression

The biomass present in awastewater treatment plantwas surveyed and their morphological properties related with operating parameters such as the total suspended solids (TSS) and sludge volume index (SVI). For that purpose image analysis was used to provide the morphological data subsequently treated by partial least squares regression (PLS) multivariable statistical technique. The results denoted the existence of a severe bulking problem of non-zoogleal nature and the PLS analysis revealed a strong relationship between the TSS and the total aggregates area as well as a close correlation between the filamentous bacteria per suspended solids ratio and the SVI.Fundação para a Ciência e a Tecnologia (FCT) – PRAXIS XXI/BD/20325/99

Evaluation of activated sludge systems by image analysis procedures

Biomass inspection under optical microscopy coupled to automated image analysis methodologies is, nowadays, increasingly used. Image analysis is presently considered a powerful tool to identify and quantify biomass morphological and physiological changes. In this work, an image analysis program was developed in Matlab environment, allowing the identification and characterization of microbial aggregates and protruding filaments in six different wastewater treatment plants. The results showed that the developed image analysis methodology proved to be a feasible method for a continuous monitoring of the activated sludge contents both in terms of aggregated biomass and filamentous bacteria, comparing the results with operating parameters. Furthermore, the results obtained during the monitoring period indicate that automated image analysis can help clarifying the nature of the events within the aeration tanks when the system is submitted to disturbances.Fundação para a Ciência e Tecnologia (FCT) - bolsa doutoramento SFRH/BD/32329/2006, projecto POCI/AMB/57069/2004Empresa de Águas, Efluentes e Resíduos de Braga (AGER

Application of image analysis techniques in environmental biotechnology

IV Curso Internacional de Biotecnologia Industrial Tópicos de Biotecnologia Ambientalinfo:eu-repo/semantics/publishedVersio

Relationship between sludge volume index and biomass structure within activated sludge systems

In activated sludge systems, the sludge settling ability is considered a critical step where filamentous bulking and biomass deflocculation are the most common problems, causing the reduction of the effluent quality. Furthermore, in recent years image processing techniques have been successfully used to elucidate the activated sludge morphology. Keeping that in mind, a program was developed for the characterization of activated sludge collected from eight wastewater treatment plants comprising both good and poor settling sludge. The results showed a strong correlation between the sludge volume index, and image analysis based parameters emerging from filamentous and aggregated biomass contents, explaining the state of biological systems.Fundação para a Ciência e a Tecnologia (FCT)AGERE (Empresa de Águas, Efluentes e Resíduos de Braga, Portuga

Assessment of an aerobic granular sludge system in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric techniques

In this study, a sequencing batch reactor (SBR) with aerobic granular sludge (AGS) was operated with synthetic wastewater containing environmental relevant concentrations of 17-estradiol (E2), 17-ethinylestradiol (EE2) and sulfamethoxazole (SMX). Despite the presence of the studied PhAC, the granular fraction clearly predominated (TSSgran/TSS ranging from 0.82 to 0.98) throughout the monitoring period, presenting aggregates with high organic fraction (VSS/TSS above 0.83) and good settling characteristics (SVI5 ranging from 15 to 39 mL/gTSS). A principal component analysis (PCA) with quantitative image analysis (QIA) based data allowed to distinguish the different operational periods, namely with mature granules (CONT), and the E2, EE2, and SMX feeding periods. It further revealed a positive relationship between the biomass density, sludge settling ability, overall and granular biomass contents, granulation properties, granular biomass fraction and large granules fraction and size. Moreover, a discriminant analysis (DA) allowed to successfully discriminate not only the different operational periods, mainly by using the floccular apparent density, granular stratification and contents data, but also the PhAC presence in samples. The filamentous bacteria contents, sludge settling properties, settling properties stability and granular stratification, structure and contents parameters were found to be crucial for that purpose.The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit and the project AGeNT - PTDC/BTA-BTA/31264/2017 (POCI-01-0145-FEDER-031264). We would also like to thank the scientific collaboration under the FCT project UIDB/50016/2020. The authors wish to thank the company Águas do Tejo Atlântico, S.A. for supplying the granules. Cristiano Leal is recipient of a fellowship supported by a doctoral advanced training (call NORTE-69-2015-15) funded by the European Social Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. A. Val del Rio is supported by Xunta de Galicia (ED418B 2017/075) and program Iacobus (2018/2019). Daniela P. Mesquita and Cristina Quintelas thanks FCT for funding through program DL 57/2016 – Norma transitória. Cristiano Leal also thank to Renê Benevides for all the support during the experimental activities.info:eu-repo/semantics/publishedVersio