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This study aims to identify barriers and needs for the application of data analytics in municipal wastewater treatment. The study was conducted through a series of interviews with stakeholders involved in instrumentation, control, and automation of wastewater treatment plants. Opportunities and limitations observed by different stakeholders were assessed with a thematic analysis. Thematic analysis enabled a broader consideration of social and organizational aspects related to process control, operation, and maintenance. Identified key barriers for applying data analytics included laborious instrumentation maintenance, unstable control loops, and deficient customization of digital tools for users at wastewater treatment plants. Development needs include easier data processing tools, quality assurance of instrumentation, and controller tuning. Results indicate that the perceived potential of data analytics is highly dependent on the performance of underlying physical and digital systems, as well as the control strategies and operating environment of the plant. Despite the barriers, users and developers see many potential applications for data analytics and expect them to have a central role in the control and operation of wastewater treatment plants in the future.

Reducing water loss from water supply systems is often regarded as one of the most important ways to improve the resource efficiency of water supply services. However, the costs and impacts of water loss reduction efforts need to be weighed against the benefits to define the optimal water loss target level. To this end, we conducted a cost–benefit analysis of three investment-based leakage reduction methods: district metering, pressure reduction, and pipe renovations. Furthermore, we conducted uncertainty and sensitivity analysis to determine the most relevant data for leakage analysis and policymaking on a national level. The results indicate that water loss management might not be directly cost-beneficial to utilities operating with moderate leakage levels. Neither leakage percentage nor the Infrastructure Leakage Index (ILI) were suitable for leakage target setting for the Finnish utilities. The costs of investing in district metering or renovations were the most influential factors in the sensitivity analysis, but the results showed that the estimated values were sufficiently accurate for assessing leakage policies.

Sewer condition is commonly assessed using closed-circuit television (CCTV) inspections. In this paper, we combine inspection results, pipe attributes, network data, and data on pipe environment to predict pipe condition and to discover which factors affect it. We apply the random forest algorithm to model pipe condition and assess the variable importance using the Boruta algorithm. We analyse the impact of predictor variables on poor condition using partial dependence plots, which are a valuable technique for this purpose. The results can be used in screening pipes for future inspections and provide insight into the dynamics between predictor variables and poor condition.

In this work we present and discuss the design of an array of soft-sensors to estimate the nitrate concentration in the denitrifying post-filtration unit at the Viikinmäki wastewater treatment plant in Helsinki (Finland). The developed sensors aim at supporting the existing hardware analyzers by providing a reliable back-up system in case of malfunction of the instruments. In the attempt to design easy to implement and interpretable sensors, computationally light linear models have been considered. However, due to the intrinsic nonlinearity of the process, also nonlinear but still computationally affordable models have been considered for comparison. The experimental results demonstrate the potential of the developed soft-sensors and the possibility for an on-line implementation in the plant's control system as alternative monitoring devices.

This article presents the findings on the effects of flow equalization and prefermentation on nitrification in a full-scale municipal plant. Existing primary clarifiers in one process train were modified for diurnal flow equalization and for a low-rate volatile fatty acid production. The performance of the biological process was compared with the parallel reference process train operated with conventional primary clarification. Only a few reports on the effects of equalization on nitrification have been published, but based on this limited knowledge, diurnal flow equalization was presumed to improve the nitrification performance. However, more constant flow conditions could not fully explain the improvements of autotrophic activity. The authors suggest that increased readily biodegradable organic matter played indirectly a role in nitrification performance. Moreover, stable flow conditions were reflected in improved sludge characteristics and offered, in addition to a levelling out of diurnal variations, a long-term buffer capacity against high hydraulic loadings.

The nitrogen cycle has been expanded with the recent discovery of Nitrospira strains that can conduct complete ammonium oxidation (commamox). Their importance in the nitrogen cycle within engineered ecosystems has not yet been analyzed. In this research, the community structure of the Bacteria domain of six full-scale activated sludge systems and three autotrophic nitrogen removal systems in the Netherlands and China has been investigated through tag -454-pyrosequencing. The phylogenetic analyses conducted in the present study showed that just a few of the Nitrospira sequences found in the bioreactors were comammox. Multivariate redundancy analysis of nitrifying genera showed an outcompetition of Nitrosomonas and non-comammox Nitrospira . Operational data from the bioreactors suggested that comammox could be favored at low temperature, low nitrogen substrate, and high dissolved oxygen. The non-ubiquity and low relative abundance of comammox in full-scale bioreactors suggested that this phylotype is not very relevant in the nitrogen cycle in wastewater treatment plants.

A sequential bed granular bioreactor was adapted to treat nitrate-polluted synthetic groundwater under anaerobic conditions and agitation with denitrification gas, achieving very efficient performance in total nitrogen removal at influent organic carbon concentrations of 1 g L -1 (80–90%) and 0.5 g L -1 (70–80%) sodium acetate, but concentrations below 0.5 g L -1 caused accumulation of nitrite and nitrate and led to system failure (30–40% removal). Biomass size and settling velocity were higher above 0.5 g L -1 sodium acetate. Trichosporonaceae dominated the fungal populations at all times, while a dominance of terrestrial group Thaumarchaeota and Acidovorax at 1 and 0.5 g L -1 passed to a domination of Methanobrevibacter and an unclassified Comamonadaceae clone for NaAc lower than 0.5 g L -1 . The results obtained pointed out that the denitrifying granular sludge technology is a feasible solution for the treatment of nitrogen-contaminated groundwater, and that influent organic matter plays an important role on the conformation of microbial communities within it and, therefore, on the overall efficiency of the system.

Low-pressure membranes (including microfiltration and ultrafiltration) for natural organic matter removal in drinking water treatment have gained increasing interest in the Nordic countries. Microfiltration can produce stable water quality and requires less space than conventional treatment. Hollow fibre microfiltration coupled with chemical coagulation was tested at a Finnish surface water treatment plant to study its feasibility and environmental impact compared to clarification, rapid sand filtration and ozonation. Microfiltration improved both physical and chemical water quality, while natural organic matter removal was similar to that of conventional treatment. Membrane treatment would increase operational costs by 2.5–3.5 euro cents per m3. Most of the costs derive from chemicals used in membrane cleaning. Membrane treatment is an energy-intensive process, but energy production in the Nordic countries has a low emission factor. Greenhouse gas emissions from operating microfiltration are estimated at 16 g CO2-eq./m3 of permeate. Lowering chemical consumption and using renewable energy in production could decrease total emissions.

In this study, the microbial community of nitrifying activated sludge adapted to Finnish climate conditions was studied to clarify the microbial populations involved in low-temperature nitrification. Microbial community analysis of five full-scale wastewater treatment plants (WWTPs) showed several differences compared to WWTPs from other countries with a similar climate. In particular, very low abundance of ammonium oxidizing bacteria (AOBs) (altogether ˂ 0.25% of total community) as well as typical NOBs (˂0.35%) and a high abundance of orders Cytophagales and Micrococcales was observed in all Finnish WWTPs. To shed light on the importance of autotrophic and heterotrophic nitrifying processes, laboratory studies of activated sludge were carried out with a presence of and a lack of organic carbon in wastewater at 10 ± 1 °C. Two different sludge retention times (SRTs) were compared to determine the effect of this operational parameter on low-temperature nitrogen removal. The important role of previously reported Candidatus Nitrotogaarctica for nitrite oxidizing in cold climate conditions was confirmed in both full-scale and laboratory scale results. Additionally, potential participation of Dokdonella sp. and Flexibacter sp. in nitrogen removal at low-temperatures is proposed. Operation at SRT of 100 days demonstrated more stable and efficient nitrogen removal after a sharp temperature decrease compared to 14 days SRT.

A bench-scale granular autotrophic nitrogen removal bioreactor (completely autotrophic nitrogen removal over nitrite (CANON) system) used for the treatment of synthetic wastewater was analyzed for the identification of microbiota with potential capacity for carbonate and phosphate biomineral formation. 16S ribosomal RNA (rRNA) gene-based studies revealed that different bacterial species found in the granular biomass could trigger the formation of phosphate and calcite minerals in the CANON bioreactor. iTag analysis of the microbial community in the granular biomass with potential ability to precipitate calcium carbonate and hydroxyapatite constituted around 0.79–1.32 % of total bacteria. Specifically, the possible hydroxyapatite-producing Candidatus Accumulibacter had a relative abundance of 0.36–0.38 % and was the highest phosphate-precipitating bacteria in the granular CANON system. With respect to calcite precipitation, the major potential producer was thought to be Stenotrophomonas with a 0.38–0.50 % relative abundance. In conclusion, our study showed evidences that the formation of hydroxyapatite and calcite crystals inside of the granular biomass of a CANON system for the treatment wastewater with high ammonium concentration was a biological process. Therefore, it could be suggested that microorganisms play an important role as a precipitation core and also modified the environment due to their metabolic activities.