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| Measured influent and effluent temperature for the treatment plant along with simulated effluent temperature for the whole validation period (a) and selected periods for summer (b) and winter (c). In Figure 3(a), the blue shaded area marks the selected periods and the red shaded area marks the period of partly corrupt data for the measured effluent temperature. In Figure 3(b) and 3(c) the red shaded area between dashed grey lines mark the measurement uncertainty for the measured effluent temperature.
Source publication
Wastewater heat recovery upstream of wastewater treatment plants (WWTPs) poses a risk to treatment performance, i.e. the biological processes. In order to perform a sustainability analysis, a detailed prediction of the temperature dynamics over the WWTP is needed. A comprehensive set of heat balance equations was included in a plant-wide process mo...
Contexts in source publication
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... overall prediction of the temperature change over the WWTP for the full-year simulation is plotted in Figure 3(a). Comparing the simulated effluent temperature with the measured values showed a good fit. ...
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... RMSE equals 0.41 °C and the overall coefficient of determination R 2 0.98. Minor deviations can be observed in Figure 3. There was a slight over prediction during the summer (Figure 3(b)), while the fit is generally better for the winter period (Figure 3(c)). ...
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... deviations can be observed in Figure 3. There was a slight over prediction during the summer (Figure 3(b)), while the fit is generally better for the winter period (Figure 3(c)). At the end of the simulated period, as the temperature rises, model over prediction can be seen again. ...
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... deviations can be observed in Figure 3. There was a slight over prediction during the summer (Figure 3(b)), while the fit is generally better for the winter period (Figure 3(c)). At the end of the simulated period, as the temperature rises, model over prediction can be seen again. ...
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... net average temperature increase over the plant (from influent to effluent) for the full year was 0.78 °C ( Figure 5(a)). However, seasonal variations occur (Figure 3). During the warmer period of the year, the change was larger -due to solar radiation -with a net increase in temperature ( Figure 5(b)). ...
Citations
... Plant-wide models, on the other hand, provide simulation capabilities of more advanced-such as granular and biofilm-based-treatment processes, feature more biological processes such as anaerobic digestion, enable pH, precipitation and gas transfer calculations and allow for more complex plant configurations that may include mechanical pretreatment, sidestream treatment or even effluent wastewater recycling. They can further provide oversight of different aspects of facilities such as energy management and operational costs, and additionally, they take into account equipment operational limitations regarding industrial safety [27]. ...
Benzene, toluene, ethylbenzene and xylenes, collectively known as BTEX compounds, are significant emerging contaminants in municipal wastewater. Stricter effluent quality regulations necessitate their removal, especially with concerns about organic micropollutant concentrations. Water scarcity further underscores the need for wastewater treatment to ensure safe agricultural or drinking water supplies. Although biological treatment partially reduces BTEX levels through processes like biodegradation and sorption, additional purification using physico-chemical methods is crucial for substantial reduction. This paper aims to outline plant-wide simulation methods for treating BTEX-contaminated sewage and facilitating reuse, adhering to IWA Good Modelling Practice Guidelines. The model, built upon the MiniSumo process model, incorporates equations detailing BTEX metabolism and removal kinetics, informed by an extensive literature review. Using a variant of the Benchmark Simulation Model with granular activated carbon for water reuse, the study examines strategies for improving effluent quality and minimizing operational costs. These strategies include adjusting the sludge retention time and airflow to enhance BTEX degradation and stripping, respectively, and comparing maintenance approaches for the GAC tower.
... The reject water is sent back to the influent while the remaining sludge from the dewatering unit is sent for disposal or reuse. Models for the specific sub-processes are also included in Arnell et al. (2021). ...
... The calibrated and validated WWTP model from Arnell et al. (2021) is used in this study. The IWA good modelling practices guideline is followed for model development, calibration and validation (Rieger et al., 2012). ...
Around 90% of the energy requirement for urban water systems management is for heating domestic tap water. In addition, the energy content of wastewater is mainly in the form of heat (85%). Hence, there is an obvious interest in recovering a large portion of this heat. However, city-wide scenario analyses that evaluate heat recovery at various locations while considering impacts on wastewater treatment plant (WWTP) performance are currently very limited. This study presents a comprehensive model-based city-wide evaluation considering four different heat recovery locations (appliance, household, precinct and WWTP effluent) for a Swedish city with varying degrees of implementation using an uncertainty-based approach. Results show that heat recovery at the appliance level, with heat exchangers installed at 77% of the showers at domestic households, leads to a mean energy recovery of 127 MWh/day with a 0.25 °C reduction in mean WWTP inlet temperature compared to the default case without heat recovery. The highest mean temperature reduction compared to the default case is 1.5 °C when heat is recovered at the precinct level for 77% of the domestic wastewater flow rate. Finally, the impact on WWTP nitrification capacity is negligible in this case due to its large existing capacity and design.
... Simplifications are always necessary, and for instance, due to added complexity we have refrained from making a full-scale modelling of the WWTP behaviour (c.f. Arnell et al., 2021;Bergstrand, 2020), and instead focussed on the temperature of WWTP influent, based on literature and in dialogue with our key actors. We have accounted for the range of assumptions made (Appendix B) which we argue stand out as reasonable 3 Currently there is a major re-construction of the sewage network and the Henriksdal WWTP in Stockholm where water currently leading to another WWTP (Bromma) will be transferred to Henriksdal before 2030. ...
... Moreover, it points to the need for increased field measurement and data collection in areas where WWHR has been installed, in order to validate effects downstream and improve temperature prediction at system level. We have treated the entire drainage area to Henriksdal as one unit but recent studies indicate that WWHR in more remote areas within a system may have negligible effect on the WWTP downstream (Walllin and Dalgren, 2021;Arnell et al., 2021). Again, field measurement will be needed to map these urban energy geographies of wastewater more in detail, and render a better understanding of heat loss and transport. ...
This article deals with ongoing attempts to recover heat and greywater at property level, using a case from Stockholm, Sweden. We explore different socio-technical development paths from now up until 2050 using a novel combination of on-property technology case-studies, actor studies and system-level scenario evaluation, based on Artificial Neural Networks modelling. Our results show that the more conservative scenarios work in favour of large-scale actors while the more radical scenarios benefit the property owners. However, in the radical scenarios we identify disruptive effects on a system level due to disturbance on wastewater treatment plants, where incoming wastewater can be critically low for up to 120 days per year. At the same time, net energy savings are relatively modest (7.5% of head demand) and economic gains for property owners small or uncertain. Current policies at EU and national level around energy-efficient buildings risk being counter-productive in cases when they push property owners to install wastewater heat recovery technology which, in places like Stockholm, can create suboptimal outcomes at the system level.
... In such cases, the availability of the entire model toolbox in the same simulation software is advantageous. In this study, a wastewater generation model (Wärff et al. 2020), WWTP model (Arnell et al. 2021) and heat transfer equipment models (Arnell & Saagi 2020) are developed using the same simulation platform (Matlab/Simulink) and can be easily integrated with both the mechanistic and conceptual sewer heat transfer models. This can significantly improve the possibilities for city-wide heat recovery studies with a wider scope. ...
... Two one-dimensional models (mechanistic and conceptual) describing wastewater temperature and flow rate dynamics in sewer systems are developed. The model toolbox offers the choice of either using a conceptual or mechanistic approach to describe both flow rate and wastewater temperature in the same simulation software and can be easily integrated with other upstream and downstream models (Wärff et al. 2020;Arnell et al. 2021) in the urban wastewater system for analysing heat recovery potential and other aspects where the temperature dynamics of the wastewater is of specific importance. The models are applied to describe wastewater flow rate and temperature dynamics for two sewer stretches from different cities in Sweden (Linköping & Malmö). ...
The vast majority of the energy consumed for urban water services is used to heat tap water. Heat recovery from wastewater is consequently an area of rapidly growing concern, both in research and by commercial interest, promoting the path towards a circular economy. To facilitate a system-wide evaluation of heat recovery from wastewater, this paper compares two one-dimensional models (mechanistic and conceptual) that can describe wastewater temperature dynamics in sewer pipe systems. The models are applied to successfully predict downstream wastewater temperature for sewer stretches in two Swedish cities (Linköping and Malmö). The root mean squared errors for the mechanistic model (Linköping Dataset1 – 0.33 °C; Linköping Dataset2 – 0.28 °C; Malmö – 0.40 °C) and the conceptual model (Linköping Dataset1 – 0.32 °C; Linköping Dataset2 – 0.20 °C; Malmö – 0.44 °C) indicate that both models have similar predictive capabilities, encouraging the use of conceptual models to reduce data requirements and model calibration efforts. Both models are freely distributed and can be easily integrated with wastewater generation and treatment models to facilitate system-wide wastewater temperature dynamics analysis. HIGHLIGHTS
Modelling tools to study energy recovery possibilities from wastewater are needed.;
Mechanistic and conceptual models for temperature dynamics in sewer system are developed.;
The models are applied for sewer pipes in two Swedish cities – Linköping and Malmö.;
Both models offer similar prediction capabilities.;
Further studies should include case studies outside Sweden and longer time periods.;
The integration of wastewater heat recovery (WWHR) and wastewater reuse offers a numerous advantage, making its application possible in various sectors. Nevertheless, this concept faced challenges to the identification of appropriate location. Existing research lacks comprehensive evaluation methods that encompass a various factor for effective decision-making. This study introduces a new evaluation framework that involves different aspects, including thermal energy potential and spatial distribution analysis. The novelty of this research lies in its unique focus on the combination of WWHR and wastewater reuse. Moreover, it introduces a structured evaluation framework that considers multiple criteria and expert opinions, enhancing decision-making precision. Multi-criteria decision analysis (MCDA) was applied to select assessment criteria, which were categorized into three aspects: water–energy supplier, water–energy consumers, and water–energy station. The relative importance of criteria was determined using the analytical hierarchical process (AHP). The results of the AHP highlight significance of factors: treated wastewater flow rate; treated wastewater temperature; water–energy supply distance, and type of water–energy consumer. These factors were assigned weight values of 0.297, 0.186, 0.123, and 0.096, respectively. It is emphasizing their influence in the decision-making process that potential locations depend on the water–energy supplier and water–energy consumer as supply and demand sources.
Rain-induced surface runoff and seasons lead to short- to medium-term anomalies in combined storm- and wastewater flows and temperatures, and influence treatment processes in wastewater resource recovery facilities (WRRF). Additionally, the implementation of decentralized heat recovery (HR) technologies for energy reuse in buildings affect energy-related processes across the urban water cycle and WRRFs heat inflows. However, quantitative insights on thermal-hydraulic dynamics in sewers at network scale and across different scales are very rare.
To enhance the understanding of thermal-hydraulic dynamics and the water-energy nexus across the urban water cycle we present a modular framework that couples thermal-hydraulic processes: i) on the surface, ii) in the public sewer network, iii) in households (including in-building HR systems), and iv) in lateral connections. We validate the proposed framework using field measurements at full network scale, present modelling results of extended time periods to illustrate the effect of seasons and precipitation events simultaneously, and quantify the impact of decentralized HR devices on thermal-hydraulics.
Simulation results suggest that the presented framework can predict temperature dynamics consistently all year long including short- to long-term variability of in-sewer temperature. The study provides quantitative evidence that the impact of household HR technologies on WRRF inflow heat budgets is reduced by approximately 20% during wet-weather periods in comparison to dry-weather conditions. The presented framework has potential to support multiple research initiatives that will improve the understanding of the water-energy nexus, pollutant dispersion and degradation, and support maintenance campaigns at network scale.
Most of the existing mathematical models for outdoor biotechnological processes require the measurement of medium temperature, and therefore, they cannot forecast the dynamics of the process in the future or perform scenario analysis under different climatology. Fully predictive models are thus required for advanced predictions, and optimization, of environmental bioprocesses affected by weather fluctuations. This is of major importance for supporting bioprocess design, decision making and process management industries. Here, we introduce the FLAME modelling framework to forecast the future of outdoor bioprocesses. It integrates, on top of a core biological model conserving carbon, nitrogen and phosphorus, a heat transfer model and a chemical sub-model for computing the speciation of all the dissociated chemical molecules. The versatile FLAME modelling platform includes different modules with balanced complexities. Alternative biological models can easily be interchanged, in order to promote a dialog for bioremediation model comparisons and improvements. This approach is illustrated with an algae-bacteria wastewater treatment pond, subjected to solar flux and meteorological events (wind, rain, …). The fully predictive model was validated during more than a year, therefore representing every season. Temperature prediction appeared to be crucial, especially for appropriately simulating nitrification. The model estimates the dynamics of the different biomasses in the system, providing a diagnosis tool to follow the hidden part of the process dynamics. The proposed framework is a powerful tool for advanced control and optimization of environmental processes, which can guide the scaling up and management of the most innovative bioprocesses.
