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"Resource recovery"
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Electro-Microbiology as a Promising Approach Towards Renewable Energy and Environmental Sustainability
Microbial electrochemical technologies provide sustainable wastewater treatment and energy production. Despite significant improvements in the power output of microbial fuel cells (MFCs), this technology is still far from practical applications. Extracting electrical energy and harvesting valuable products by electroactive bacteria (EAB) in bioelectrochemical systems (BESs) has emerged as an innovative approach to address energy and environmental challenges. Thus, maximizing power output and resource recovery is highly desirable for sustainable systems. Insights into the electrode-microbe interactions may help to optimize the performance of BESs for envisioned applications, and further validation by bioelectrochemical techniques is a prerequisite to completely understand the electro-microbiology. This review summarizes various extracellular electron transfer mechanisms involved in BESs. The significant role of characterization techniques in the advancement of the electro-microbiology field is discussed. Finally, diverse applications of BESs, such as resource recovery, and contributions to the pursuit of a more sustainable society are also highlighted.
Journal Article
A critical review of the data pipeline: how wastewater system operation flows from data to intelligence
Faced with an unprecedented amount of data coming from evermore ubiquitous sensors, the wastewater treatment community has been hard at work to develop new monitoring systems, models and controllers to bridge the gap between current practice and data-driven, smart water systems. For additional sensor data and models to have an appreciable impact, however, they must be relevant enough to be looked at by busy water professionals; be clear enough to be understood; be reliable enough to be believed and be convincing enough to be acted upon. Failure to attain any one of those aspects can be a fatal blow to the adoption of even the most promising new measurement technology. This review paper examines the state-of-the-art in the transformation of raw data into actionable insight, specifically for water resource recovery facility (WRRF) operation. Sources of difficulties found along the way are pinpointed, while also exploring possible paths towards improving the value of collected data for all stakeholders, i.e., all personnel that have a stake in the good and efficient operation of a WRRF.
Journal Article
Waste or Gold? Bioelectrochemical Resource Recovery in Source-Separated Urine
In recent years, source-separated human urine has been highlighted as an effective resource for energy and nutrient recovery. However, even though several technologies exist for resource recovery, they have not been widely implemented. Among these technologies, bioelectrochemical systems (BESs) hold promise as technically and economically interesting alternatives for sustainable resource recovery from source-separated urine. Here, we review the resource recovery performance of BESs, including microbial fuel cells (MFCs) and microbial electrolysis cells (MECs), fed with source-separated urine over the past decade, and suggest an effective path forward toward their widespread implementation.
Resource recovery is a key strategy to keep up with a consumption-driven society.Providing an abundant source of energy and nutrients, source-separated urine has proven its potential for sustainable recovery.The performance of urine-fed BES-based resource recovery is showing increasing promise.
Journal Article
Thermochemical conversion of sewage sludge for energy and resource recovery: technical challenges and prospects
Thermochemical processes are considered as a promising technology for sewage sludge management, which could achieve volume reduction, energy and resource recovery, and effective destruction of pathogens. However, there are still many technology limitations and challenges of the thermochemical processes toward industrialization and commercialization. This review first briefly discusses the impact of sewage sludge on environmental sustainability and its current treatment and disposal methods. Typical thermochemical conversion technologies i.e., incineration/combustion, pyrolysis, gasification, and hydrothermal liquefaction for energy and resource recovery from sewage sludge are then comprehensively summarized. Subsequently, the technical challenges of thermochemical conversion of sewage sludge and the solutions that have been and/or are being developed to address the challenges are in-depth analyzed. Meanwhile, the prospects and future directions of the thermochemical technologies are outlined. In addition, the economic analysis and life cycle assessment of thermochemical conversion technologies are evaluated. Finally, the conclusions are put forward.
Journal Article
Estimation and Control of WRRF Biogas Production
The development of resource-efficient digital technologies is a critical challenge in the wastewater sector. This industrial case study, conducted in collaboration with the Veas Water Resource Recovery Facility in Norway, focused on creating data pre-processing methods and resource-efficient control strategies. Using data from the Veas biogas plant, dynamic models were developed to compare control outcomes. The primary objective was to maximize biogas production and hot water usage while maintaining optimal temperature and hydraulic retention time by adjusting inlet sludge and hot water flow rates. Sequential operations were approximated as continuous operations using a 30-min moving minimum/maximum for bimodal data and a 2-h moving average for noisy data. The data-driven dynamic models achieved an accuracy of up to R2 of 0.85. The control strategy, which included one feedback controller, one ratio controller, and flow rate restrictions, was compared to real production data (baseline) and tested across six scenarios. The best improvement over the baseline scenario resulted in a 3% increase in total biogas production, a 6% increase in total organic loading, a 13% increase in hot water use, and a one-day reduction in hydraulic retention time. Future work should focus on control studies using extended datasets and nonlinear models.
Journal Article
Pathways to a net-zero-carbon water sector through energy-extracting wastewater technologies
The energy-consuming and carbon-intensive wastewater treatment plants could become significant energy producers and recycled organic and metallic material generators, thereby contributing to broad sustainable development goals, the circular economy, and the water-energy-sanitation-food-carbon nexus. This review provides an overview of the waste(water)-based energy-extracting technologies, their engineering performance, techno-economic feasibility, and environmental benefits. Here, we propose four crucial strategies to achieve net-zero carbon along with energy sufficiency in the water sector, including (1) improvement in process energy efficiency; (2) maximizing on-site renewable capacities and biogas upgrading; (3) harvesting energy from treated effluent; (4) a new paradigm for decentralized water-energy supply units.
Journal Article
Assessment of Effluent Wastewater Quality and the Application of an Integrated Wastewater Resource Recovery Model: The Burgersfort Wastewater Resource Recovery Case Study
Rivers in Africa have experienced dire pollution as a result of the poor management of wastewater effluent emanating from water resource recovery facilities (WRRFs). An integrated wastewater resource recovery model was developed and applied to identify ideal wastewater resource recovery technologies that can be used to recover valuable resources from a mixture of wastewater effluents in a case study in the Burgersfort WRRF in the Limpopo province, South Africa. This novel model incorporates the process of biological nutrient removal (BNR) with an extension of conventional methods of resource recovery applicable to wastewater. The assessment of results of effluent quality from 2016 to 2022 revealed that ammonia, chemical oxygen demand, total coliform, fecal coliform, and Escherichia coli levels were critically non-compliant with the permissible effluent guidelines, indicating a stable upward trend in terms of concentrations, and scored a very bad wastewater quality index rating. All variables assessed showed a significant loading, except for orthophosphates, and significant correlations were observed among the variables. The results of the integrated wastewater resource recovery model revealed a high probability of reclaiming recoverable resources such as nutrients, sludge, bioplastics, biofuel, metals, and water from wastewater, which have economic, environmental, and social benefits, thereby improving the effluent quality of a WRRF.
Journal Article
A calibration framework toward model generalization for bacteria concentration estimation in water resource recovery facilities
Reduced bacteria concentrations in wastewater is a key indicator of the efficacy of water resource recovery facilities (WRRFs). However, monitoring the presence of bacterial concentrations in real time at each stage of the WRRF is challenging as it requires taking and processing water samples offline. Although few studies have been proposed to predict bacterial concentrations using data-driven models, generalizing these models to unseen data from different WRRFs remains challenging. This paper proposes a calibration approach based on neural networks to adapt the optimal models across various WRRFs in Saudi Arabia for bacterial estimation at the influent and effluent stages. The calibration relies on the out-of-distribution (OOD) framework of the physiochemical water parameters (e.g., pH, COD, TDS, turbidity, conductivity) with a design threshold chosen based on the data distribution of the received unseen samples. We propose a calibration framework that continues updating the trained neural network model for accurate bacterial concentration estimation upon receiving new samples. We tested the effectiveness of the proposed calibration scheme on four WRRF datasets in Saudi Arabia, comparing the results with before and after calibration without the OOD.
Before calibration
model was based on a traditional and optimal neural network approach, typically considered the conventional method for building neural networks.
After calibration without OOD
, the model continued retraining without explicitly checking for OOD condition. The results showed that the proposed calibration framework of the selected baseline WRRF with the OOD scheme improved
and
of the worst-case influent bacteria concentration before calibration and after calibration without OOD, respectively. Similarly, the worst-case effluent bacteria concentration estimation was enhanced by
before calibration and
after calibration without the OOD. Our findings highlight the importance of integrating the calibration framework with neural network approaches to achieve model generalization.
Journal Article