Integrating the selection of PHA storing biomass and nitrogen removal via nitrite for the treatment of the sludge reject water

Integrating the selection of PHA storing biomass and nitrogen removal via-nitrite for the treatment of the sludge reject wate

Indicator based multi-criteria decision support systems for wastewater treatment plants

Data availability: Data will be made available on request.Wastewater treatment plant decision makers face stricter regulations regarding human health protection, environmental preservation, and emissions reduction, meaning they must improve process sustainability and circularity, whilst maintaining economic performance. This creates complex multi-objective problems when operating and selecting technologies to meet these demands, resulting in the development of many decision support systems for the water sector. European Commission publications highlight their ambition for greater levels of sustainability, circularity, and environmental and human health protection, which decision support system implementation should align with to be successful in this region. Following the review of 57 wastewater treatment plant decision support systems, the main function of multi-criteria decision-making tools are technology selection and the optimisation of process operation. A large contrast regarding their aims is found, as process optimisation tools clearly define their goals and indicators used, whilst technology selection procedures often use vague language making it difficult for decision makers to connect selected indicators and resultant outcomes. Several recommendations are made to improve decision support system usage, such as more rigorous indicator selection protocols including participatory selection approaches and expansion of indicators sets, as well as more structured investigation of results including the use of sensitivity or uncertainty analysis, and error quantification.Horizon 2020 research and innovation programme DEEP PURPLE. The H2020 DEEP PURPLE project has received funding from the Bio-based Industries Joint Undertaking (JU) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 837998. The JU receives support from the European Union's Horizon 2020 research and innovation programme and the Bio-based Industries Consortium

Tracing wastewater resources: unravelling the circularity of waste using source, destination, and quality analysis

Data availability: Data will be made available on request.Supplementary materials are available online at: https://www.sciencedirect.com/science/article/pii/S0043135423013416#sec0037 .Copyright © 2023 The Authors. Current circularity assessment terminology restricts application to wastewater processes due to the focus on technical systems. Waste stream and wastewater discharge circularity definitions lead to paradoxical assessments that generate results of little value for evidence-based decision making. Therefore, a classification approach was developed to measure inflow and outflow circularity of the main wastewater resource flows using the principle of traceability, adopting the attitude that not all waste is created equally. Applying it to a wastewater treatment plant (12,000 m3/d load) showed how upstream agricultural, industrial, and human practices impact downstream treatment, and the effectiveness of resource cycling within the natural environment. Industrial actions increasing fossil carbon concentration (400 m3/d effluent at 1000 mgC/l) reduced inflow and outflow circularity by 16 % and 10.6 % respectively, as secondary and sludge treatment fossil emissions increase significantly. Alternatively, changes to human and agricultural practices (50 % reduction of detergent and synthetic fertiliser usage) improved phosphorus inflow and nitrogen outflow circularity by 5.2 % and 20.1 % respectively. This approach can educate and assign responsibility to water users for developing robust circular economy policy, shifting the pattern from promoting circularity to discouraging linear actions, overcoming the shared economic and environmental burden of linear water use.This research was supported by the Horizon 2020 research and innovation programme DEEP PURPLE. The H2020 DEEP PURPLE project has received funding from the Bio-based Industries Joint Undertaking (JU) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 837998. The JU receives support from the European Union's Horizon 2020 research and innovation programme and the Bio-based Industries Consortium

Membrane bioreactors – A review on recent developments in energy reduction, fouling control, novel configurations, LCA and market prospects

COST Action ES1202: Conceiving Wastewater Treatment in 2020 - Energetic, environmental and economic challenges (Water_2020), supported by COST (European Cooperation in Science and Technology)

Economic assessment of nature-based solutions as enablers of circularity in water systems

The transition from the current linear model of abstraction, use and discharge of water into recycle-reuse under the circular economy (CE) principles is momentous. An analysis of recent literature about the economic impact of linear to circular (L2C) transition is made. The review investigates the economic implications (i.e. cost-benefit) of deployment of enabling technologies, tools and methodologies within the circular water systems. The study is enhanced by presenting the results of our investigation into the policy impact (push-barriers) of L2C transition. As the vehicle for the L2C transition, nature-based solutions (NBS) and its economic and policy implications is discussed. A framework is proposed for the monetary assessment of the costs of investment in NBS technologies, infrastructure and education against the environmental and socio-economic benefits within the policy frameworks. This framework may build the early foundation for bridging the gap that exists for a systematic and objective economic impact (cost-benefit) analysis of L2C transition in the Water sector. This framework will lead to a generic multi-parametric cost model of NBS for Circularity Water Systems.Engineering and Physical Sciences Research Council (EPSRC); Horizon 2020 research and innovation program HYDROUS

Water Cycle and Circular Economy: Developing a Circularity Assessment Framework for Complex Water Systems

© 2020 The Authors. Water – the most vital resource, negatively affected by the linear pattern of growth – still tries to find its positioning within the emerging concept of circular economy. Fragmented, sectorial circularity approaches hide the risk of underestimating both the preservation of and impacts to water resources and natural capital. In this study, a game changing circularity assessment framework is developed (i.e. MSWCA). The MSWCA follows a multi-sectoral systems approach, symbiotically managing key water-related socio-economic (i.e. urban water, agro-food, energy, industry and waste handling) and non-economic (i.e. natural environment) sectors. The MSWCA modelling framework enables the investigation of the feedback loops between the nature-managed and human-managed systems to assess water and water-related resources circularity. The three CE principles lie at the core of the developed framework, enabling the consideration of physical, technical, environmental and economic aspects. An indicators database is further developed, including all the relevant data requirements, as well as existing and newly developed indicators assessing multi-sectoral systems’ circularity. The MSWCA framework is conceptually applied to a fictional city, facilitating its understanding and practical use.Horizon 2020 research and innovation program HYDROUSA (grant agreement No 776643)

Energy-aware flowshop scheduling: a case for AI-driven sustainable manufacturing

© Copyright 2021 The Author(s). A fully verifiable and deployable framework for optimizing schedules in a batch-based production system is proposed. The scheduler is designed to control and optimize the flow of batches of material into a network of identical and non-identical parallel and series machines that produce a high variation of complex hard metal products. The proposed multi-objective batch-based flowshop scheduling optimization (MOBS-NET) deploys a fully connected deep neural network (FCDNN) with respect to three performance criteria of energy, cost and makespan. The problem is NP-hard and considers minimizing the energy consumed per unit of product, operations cost, and the makespan. The output of the method has been validated and verified as optimal operational planning and scheduling meeting the business operational objectives. Real-time and look ahead discrete event simulation of the production process provides the feedback and assurance of the robustness and practicality of the optimum schedules prior to implementation.Z-FACTOR Project framework, which received funding from the European Union’s Horizon 2020 Research and Innovation Program (Grant Number: 723906)

Polylactic Acid (PLA) Reinforced with Date Palm Sheath Fiber Bio-Composites: Evaluation of Fiber Density, Geometry, and Content on the Physical and Mechanical Properties

Copyright © 2022 The Author(s). Significant interest for utilizing and processing natural fibers (NF) to develop sustainable and fully biodegradable composites evolved as the global environmental concerns upsurge. Date palm tree (DPT) accounts for more than 2.8 million tons of waste annually, making it the most abundant agricultural biomass waste in the MENA region. This study investigates the effect of date palm fiber (DPF) density, diameter size and content on both the mechanical and physical properties of polylactic acid (PLA) reinforced DPF bio-composite. The bio-composites are developed using melt-mixing technique which is followed by compression molding. The influence of the mechanical properties is investigated by evaluating the tensile, flexural and impact strengths. Meanwhile bio-composite thickness swelling (TS), moisture content (MC) and water absorption (WA) characteristics are evaluated. Bio-composite microstructures are examined using SEM to investigate the interfacial bonding between PLA matrix and DPF. Results showed that at 40 wt.% DPF, the TS, MC, and WA were the highest demonstrating an increase of 4.10%, 4.95%, and 8.22%, respectively. Although the results demonstrated a decrease in mechanical properties as DPF content increased (depending on DPF geometry), the results indicate that the developed technologies could be commercialized under the waste management scheme for non-structural applications. 摘要 随着全球环境问题的加剧，人们对利用和加工天然纤维（NF）开发可持续和完全生物降解的复合材料产生了极大的兴趣. 椰枣树（DPT）每年产生280多万吨废弃物，是中东和北非地区最丰富的农业生物质废弃物. 本研究研究了椰枣纤维（DPF）密度、直径大小和含量对聚乳酸（PLA）增强DPF生物复合材料力学和物理性能的影响. 生物复合材料是使用熔融混合技术开发的，然后是压缩成型. 通过评估拉伸、弯曲和冲击强度来研究力学性能的影响. 同时，评估了生物复合材料的厚度膨胀（TS）、水分含量（MC）和吸水率（WA）特性. 使用SEM检查生物复合材料微观结构，以研究PLA基质和DPF之间的界面结合. 结果表明，在40重量%的DPF下，TS、MC和WA最高，分别增加了4.10%、4.95%和8.22%. 尽管结果表明，随着DPF含量的增加（取决于DPF的几何形状），机械性能有所下降，但结果表明，开发的技术可以在非结构应用的废物管理计划下商业化.This research did not receive any public or private grants and funds

Development of a Novel Process Integrating the Treatment of Sludge Reject Water and the Production of Polyhydroxyalkanoates (PHAs)

The Supporting Information is available free of charge on the ACS Publications website at DOI: https://doi.org/10.1021/acs.est.5b01776This study was carried out within the framework of the European projects LIVE WASTE (LIFE 12 ENV/CY/000544)

Systematic assessment of wastewater resource circularity and sustainable value creation

Data availability: Data will be made available on request.Supplementary materials are avalable online at: https://www.sciencedirect.com/science/article/pii/S0043135424000411#sec0032 .Copyright © 2024 The Authors. The circular use of wastewater has attracted significant attention in recent years. However, there is a lack of universal definitions and measurement tools that are required to achieve the circular economy's full potential. Therefore, a methodology was developed using three indicator typologies, namely resource flow, circular action, and sustainability indicators, to facilitate a robust and holistic circularity assessment. The method uses value propositions to integrate the assessment of intrinsic circularity performance with consequential circularity impacts, by quantifying sustainable value creation (using techniques such as life cycle assessment or cost-benefit analysis). Assessment method capabilities were exhibited by applying the defined steps to a wastewater treatment plant, comparing conventional and novel photobioreactor technologies. The resource flow indicator taxonomy results highlight improved outflow circularity, renewable energy usage, and economic efficiency of the novel system. Action indicators revealed that the photobioreactor technology was successful at achieving its defined circular goals. Lastly, sustainability indicators quantified a reduction of carbon footprint by two thirds and eutrophication by 41%, a M€ 0.5 per year increase of economic value, and that disability adjusted life year impacts are 58% lower. This supports that improving wastewater system circularity using photobioreactor technology results in environmental, economic, and social value for stakeholders.Horizon 2020 research and innovation programme DEEP PURPLE. The H2020 DEEP PURPLE project has received funding from the Bio-based Industries Joint Undertaking (JU) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 837998. The JU receives support from the European Union's Horizon 2020 research and innovation programme and the Bio-based Industries Consortium