Efficiency benchmarking of wastewater service providers: An analysis based on the Portuguese case.

Sustainability is increasingly important in the wastewater treatment sector, and benchmarking studies are needed to identify the best practices in using resources efficiently. This work addresses this need by characterizing and benchmarking this sector in Portugal. Data from around 120 service providers, from 2015 to 2019, regarding inputs consumption, desirable and undesirable outputs, are used in a data envelopment analysis to benchmark these operators and to determine improvement potentials. A productivity change analysis revealed an increase from 2015 to 2019, essentially due to an increased technical efficiency. On the other hand, no real technological change seems to have occurred. A positive effect of the service providers dimension and certifications (quality, environmental and energy) on efficiency was found. Service providers with concessionary governance models and urban typology presented the highest efficiencies, whereas treatment plants underuse contributed negatively to efficiency. These results can inform the definition of strategic policies for the water sector, namely concerning the aggregation of small providers. The proposed methodology, based on the use of a comprehensive new set of studied variables and explanatory factors, allowed to determine the best characteristics regarding the techno-economic efficiency of Portuguese service providers, and can potentially be applied to identify role models in other countries.

Quantitative image analysis as a robust tool to assess effluent quality from an aerobic granular sludge system treating industrial wastewater.

Quantitative image analysis (QIA) is a simple and automated method for process monitoring, complementary to chemical analysis, that when coupled to mathematical modelling allows associating changes in the biomass to several operational parameters. The majority of the research regarding the use of QIA has been carried out using synthetic wastewater and applied to activated sludge systems, while there is still a lack of knowledge regarding the application of QIA in the monitoring of aerobic granular sludge (AGS) systems. In this work, chemical oxygen demand (COD), ammonium (N-NH4+), nitrite (N-NO2-), nitrate (N-NO3-), salinity (Cl-), and total suspended solids (TSS) levels present in the effluent of an AGS system treating fish canning wastewater were successfully associated to QIA data, from both suspended and granular biomass fractions by partial least squares models. The correlation between physical-chemical parameters and QIA data allowed obtaining good assessment results for COD (R2 of 0.94), N-NH4+ (R2 of 0.98), N-NO2- (R2 of 0.96), N-NO3- (R2 of 0.95), Cl- (R2 of 0.98), and TSS (R2 of 0.94). While the COD and N-NO2- assessment models were mostly correlated to the granular fraction QIA data, the suspended fraction was highly relevant for N-NH4+ assessment. The N-NO3-, Cl- and TSS assessment benefited from the use of both biomass fractions (suspended and granular) QIA data, indicating the importance of the balance between the suspended and granular fractions in AGS systems and its analysis. This study provides a complementary approach to assess effluent quality parameters which can improve wastewater treatment plants monitoring and control, with a more cost-effective and environmentally friendly procedure, while avoiding daily physical-chemical analysis.

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 17ß-estradiol (E2), 17α-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.

Use of chemometric analyses to assess biological wastewater treatment plants by protozoa and metazoa monitoring.

Protozoa and metazoa biota communities in biological wastewater treatment plants (WWTP) are known to be dependent of both the plant type (oxidation ditch, trickling filter, conventional activated sludge, among others) and the working operational conditions (incoming effluent characteristics, toxics presence, organic load, aeration, hydraulic and sludge retention times, nitrification occurrence, etc.). Thus, for analogous WWTP operating in equivalent operating conditions, similar protozoa and metazoa communities can be found. Indeed, the protozoa and metazoa biota monitoring can be considered a quite useful tool for assessing the functioning of biological WWTP. Furthermore, the use of chemometric techniques in WWTP monitoring is becoming widespread to enlighten interrelationships within the plant, especially when a large collection of data can be obtained. In the current study, the protozoa and metazoa communities of three different types of WWTP, comprising one oxidation ditch, four trickling filters, and three conventional activated sludge plants, were monitored. For that purpose, metazoa, as well as the main protozoa groups (flagellates, free-swimming, crawling and sessile ciliates, and testate amoeba) were determined in terms of contents and relative abundance. The collected data was further processed by chemometric techniques, such as cross-correlation, principal components, multivariate ANOVA, and decision trees analyses, allowing to successfully identify, and characterize, the different studied WWTP, and thus, being able to help monitoring and diagnosing operational problems.

Polyhydroxyalkanoate granules quantification in mixed microbial cultures using image analysis: Sudan Black B versus Nile Blue A staining.

Polyhydroxyalkanoates (PHA) can be produced and intracellularly accumulated as inclusions by mixed microbial cultures (MMC) for bioplastic production and in enhanced biological phosphorus removal (EBPR) systems. Classical methods for PHA quantification use a digestion step prior to chromatography analysis, rendering them labor intensive and time-consuming. The present work investigates the use of two quantitative image analysis (QIA) procedures specifically developed for PHA inclusions identification and quantification. MMC obtained from an EBPR system were visualized by bright-field and fluorescence microscopy for PHA inclusions detection, upon Sudan Black B (SBB) and Nile Blue A (NBA) staining, respectively. The captured color images were processed by QIA techniques and the image analysis data were further treated using multivariate statistical analysis. Partial least squares (PLS) regression coefficients of 0.90 and 0.86 were obtained between QIA parameters and PHA concentrations using SBB and NBA, respectively. It was found that both staining procedures might be seen as alternative methodologies to classical PHA determination.

Monitoring intracellular polyphosphate accumulation in enhanced biological phosphorus removal systems by quantitative image analysis.

A rapid methodology for intracellular storage polyphosphate (poly-P) identification and monitoring in enhanced biological phosphorus removal (EBPR) systems is proposed based on quantitative image analysis (QIA). In EBPR systems, 4',6-diamidino-2-phenylindole (DAPI) is usually combined with fluorescence in situ hybridization to evaluate the microbial community. The proposed monitoring technique is based on a QIA procedure specifically developed for determining poly-P inclusions within a biomass suspension using solely DAPI by epifluorescence microscopy. Due to contradictory literature regarding DAPI concentrations used for poly-P detection, the present work assessed the optimal DAPI concentration for samples acquired at the end of the EBPR aerobic stage when the accumulation occurred. Digital images were then acquired and processed by means of image processing and analysis. A correlation was found between average poly-P intensity values and the analytical determination. The proposed methodology can be seen as a promising alternative procedure for quantifying intracellular poly-P accumulation in a faster and less labour-intensive way.

Activated sludge characterization through microscopy: a review on quantitative image analysis and chemometric techniques.

In wastewater treatment processes, and particularly in activated sludge systems, efficiency is quite dependent on the operating conditions, and a number of problems may arise due to sludge structure and proliferation of specific microorganisms. In fact, bacterial communities and protozoa identification by microscopy inspection is already routinely employed in a considerable number of cases. Furthermore, quantitative image analysis techniques have been increasingly used throughout the years for the assessment of aggregates and filamentous bacteria properties. These procedures are able to provide an ever growing amount of data for wastewater treatment processes in which chemometric techniques can be a valuable tool. However, the determination of microbial communities' properties remains a current challenge in spite of the great diversity of microscopy techniques applied. In this review, activated sludge characterization is discussed highlighting the aggregates structure and filamentous bacteria determination by image analysis on bright-field, phase-contrast, and fluorescence microscopy. An in-depth analysis is performed to summarize the many new findings that have been obtained, and future developments for these biological processes are further discussed.

Prediction of intracellular storage polymers using quantitative image analysis in enhanced biological phosphorus removal systems.

The present study focuses on predicting the concentration of intracellular storage polymers in enhanced biological phosphorus removal (EBPR) systems. For that purpose, quantitative image analysis techniques were developed for determining the intracellular concentrations of PHA (PHB and PHV) with Nile blue and glycogen with aniline blue staining. Partial least squares (PLS) were used to predict the standard analytical values of these polymers by the proposed methodology. Identification of the aerobic and anaerobic stages proved to be crucial for improving the assessment of PHA, PHB and PHV intracellular concentrations. Current Nile blue based methodology can be seen as a feasible starting point for further enhancement. Glycogen detection based on the developed aniline blue staining methodology combined with the image analysis data proved to be a promising technique, toward the elimination of the need for analytical off-line measurements.