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In this paper, a novel methodology and extended hybrid model for the real time control, prediction and reduction of direct emissions of greenhouse gases (GHGs) from wastewater treatment plants (WWTPs) is proposed to overcome the lack of long-term data availability in several full-scale case studies. A mechanistic model (MCM) and a machine learning (ML) model are combined to real time control, predict the emissions of nitrous oxide (N 2 O) and carbon dioxide (CO 2 ) as well as effluent quality (COD - chemical oxygen demand, NH 4 -N - ammonia, NO 3 -N - nitrate) in activated sludge method. For methane (CH 4 ), using the MCM model, predictions are performed on the input data (VFA, CODs for aerobic and anaerobic compartments) to the MLM model. Additionally, scenarios were analyzed to assess and reduce the GHGs emissions related to the biological processes. A real WWTP, with a population equivalent (PE) of 125,000, was studied for the validation of the hybrid model. A global sensitivity analysis (GSA) of the MCM and a ML model were implemented to assess GHGs emission mechanisms the biological reactor. Finally, an early warning tool for the prediction of GHGs errors was implemented to assess the accuracy and the reliability of the proposed algorithm. The results could support the wastewater treatment plant operators to evaluate possible mitigation scenarios (MS) that can reduce direct GHG emissions from WWTPs by up to 21%, while maintaining the final quality standard of the treated effluent., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The impact of climate change on water availability and quality has affected agricultural irrigation. The use of treated wastewater can alleviate water in agriculture. Nevertheless, it is imperative to ensure proper treatment of wastewater before reuse, in compliance with current regulations of this practice. In decentralized agricultural scenarios, the lack of adequate treatment facilities poses a challenge in providing treated wastewater for irrigation. Hence, there is a critical need to develop and implement innovative, feasible, and sustainable treatment solutions to secure the use of this alternative water source. This study proposes the integration of intensive treatment solutions and natural treatment systems, specifically, the combination of up-flow anaerobic sludge blanket reactor (UASB), anaerobic membrane bioreactor (AnMBR), constructed wetlands (CWs), and ultraviolet (UV) disinfection. For this purpose, a novel demo-scale plant was designed, constructed and implemented to test wastewater treatment and evaluate the capability of the proposed system to provide an effluent with a quality in compliance with the current European wastewater reuse regulatory framework. In addition, carbon-sequestration and energy analyses were conducted to assess the sustainability of the proposed treatment approach. This research confirmed that UASB rector can be employed for biogas production (2.5 L h -1 ) and energy recovery from organic matter degradation, but its effluent requires further treatment steps to be reused in agricultural irrigation. The AnMBR effluent complied with class A standards for E. coli, boasting a concentration of 0 CFU 100 mL -1 , and nearly negligible TSS levels. However, further reduction of BOD 5 (35 mg L -1 ) is required to reach water quality class A. CWs efficiently produced effluent with BOD 5 below 10 mg L -1 and TSS close to 0 mg L -1 , making it suitable for water reuse and meeting class A standards. Furthermore, CWs demonstrated significantly higher energy efficiency compared to intensive treatment systems. Nonetheless, the inclusion of a UV disinfection unit after CWs was required to attain water class B standards., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Specific flood volume is an important criterion for evaluating the performance of sewer networks. Currently, mechanistic models - MCMs (e.g., SWMM) are usually used for its prediction, but they require the collection of detailed information about the characteristics of the catchment and sewer network, which can be difficult to obtain, and the process of model calibration is a complex task. This paper presents a methodology for developing simulators to predict specific flood volume using machine learning methods (DNN - Deep Neural Network, GAM - Generalized Additive Model). The results of Sobol index calculations using the GSA method were used to select the ML model as an alternative to the MCM model. It was shown that the DNN model can be used for flood prediction, for which high agreement was obtained between the results of GSA calculations for rainfall data, catchment and sewer network characteristics, and calibrated SWMM parameters describing land use and sewer retention. Regression relationships (polynomials and exponential functions) were determined between Sobol indices (retention depth of impervious area, correction factor of impervious area, Manning's roughness coefficient of sewers) and sewer network characteristics (unit density of sewers, retention factor - the downstream and upstream of retention ratio) obtaining R 2  = 0. 55-0.78. The feasibility of predicting sewer network flooding and modernization with the DNN model using a limited range of input data compared to the SWMM was shown. The developed model can be applied to the management of urban catchments with limited access to data and at the stage of urban planning., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Developing an accurate tourism forecasting decision support system can help the tourism department achieve optimal resource allocation, which is crucial for achieving sustainable tourism operation management and a circular economy. Recent decades have witnessed the frequent strikes of crisis events and mega-events, which profoundly influence tourist arrival volume and bring a great challenge to forecasting tourist arrival volume. To solve this issue, we develop a deep learning framework to forecast the tourist arrival volume utilizing search engine data containing the trends of tourism intention and different event information. Our proposed model is novel for the following reasons: (1) The disturbance value can predict tourist arrival volume in coordination with the trend of travel plans. (2) Compared with the traditional models, our model can reduce the complexity of the model while maintaining accuracy. (3) Our proposed framework introducing event-related search volumes can capture the concerns of tourists and the potential loss of tourist arrivals, enhancing the model's predictive power. Experimental results show that our model can accurately forecast the tourist arrival volume by employing the monthly data in Beijing and Sanya, China. Moreover, our findings provide policymakers with more understanding of the relationship between various predictive factors and tourist arrivals. Based on the forecasting results, allocating an appropriate amount of clean energy transportation capacity, garbage treatment capacity, and fresh food supply capacity to the city can effectively promote the circular economy. [ABSTRACT FROM AUTHOR]

The concepts of sustainability and circular economy (CE) have attracted enormous attention in the academic, business and political spheres. However, a systematic review of case studies concerning CE in the tourism industry remains lacking. The present study collected good environmental management practices and circular solutions related to energy, water and waste from tourist accommodations in Italy/Europe and China. Moreover, sustainable procedures were critically discussed within the strategic water-energy-waste-food-transport (WEWFT) nexus. When comprehensive data were available, good practices were also measured by Circular Indicators (CIs) and compared to benchmark values set by existing certification or labelling. CIs support the innovative, resilient and sustainable development and assessment of the tourism industry. Most of the strategies were focused on energy optimization and a lack of tangible data was depicted for food and waste management. [ABSTRACT FROM AUTHOR]

Millions of cubic meters of water are polluted every day as a result of industrialization and other human activities. The contribution of the Wastewater Treatment Plant, which was built to prevent this pollution, to the water cycle was examined through water footprint indicators in this study. In the study, the wastewater treatment plant was evaluated for treated and non-treated cases, and the contribution of the plant to the grey water footprint was determined from the difference between the two cases. Wastewater Treatment Plants not only save the volume of water in the receiving environment but also protect the water quality. This study revealed that as a result of the treatment of industrial and domestic mixed wastewater with a pollution load of 396.297 mg biochemical oxygen demand L-1, 924.245 mg chemical oxygen demand L-1, 26.139 mg total nitrogen L-1 2.76 mg total phosphorus L-1, and 426.861 mg total suspended solids L-1, in the Wastewater Treatment Plant, it recovered an average of 14,375,243 m3 of freshwater per month in the water cycle by protecting the Class III (medium) water quality of receiving environment. The calculations made in the study are based on the Water Footprint Assessment Manual. The volume of recovered water is 19 ± 14 times larger than the inlet flow of wastewater treatment. On the other hand, the total amount of freshwater consumed directly and indirectly in the wastewater treatment is 3696 m3 month-1. ⁓97.093% of the indirect blue water footprint is used for the generation of electrical energy. This study reveals all aspects of the Wastewater Treatment Plants contribution to the sustainable environment with the natural water cycle and the protection of the receiving water quality. [ABSTRACT FROM AUTHOR]

Worldwide, there has been an increase in the presence of potentially toxic cyanobacterial blooms in drinking water sources and within drinking water treatment plants (DWTPs). The objective of this study is to validate the use of in situ probes for the detection and management of cyanobacterial breakthrough in high and low-risk DWTPs. In situ phycocyanin YSI EXO2 probes were devised for remote control and data logging to monitor the cyanobacteria in raw, clarified, filtered, and treated water in three full-scale DWTPs. An additional probe was installed inside the sludge holding tank to measure the water quality of the surface of the sludge storage tank in a high-risk DWTP. Simultaneous grab samplings were carried out for taxonomic cell counts and toxin analysis. A total of 23, 9, and 4 field visits were conducted at the three DWTPs. Phycocyanin readings showed a 93-fold fluctuation within 24 h in the raw water of the high cyanobacterial risk plant, with higher phycocyanin levels during the afternoon period. These data provide new information on the limitations of weekly or daily grab sampling. Also, different moving averages for the phycocyanin probe readings can be used to improve the interpretation of phycocyanin signal trends. The in situ probe successfully detected high cyanobacterial biovolumes entering the clarification process in the high-risk plant. Grab sampling results revealed high cyanobacterial biovolumes in the sludge for both high and low-risk plants. [ABSTRACT FROM AUTHOR]

This study entails the synthesis of molecularly imprinted polymers (MIPs) with good selectivity coefficients for azo dye as a potential sorbent material to extract azo dye from polluted aqueous media. A series of MIPs for methyl red (MR) as a template, were synthesized by changing the molar ratio of functional monomers, via precipitation polymerization format of non-covalent approach. Water-soluble functional monomer; acrylic acid (AA) was used to weave the frame work of polymers while ethylene glycol dimethacrylate (EGDMA) was utilized as crosslinking monomer. The impact of different experimental parameters, such as mole ratio of monomer (functional) to crosslinking monomer on the molecular recognition was investigated. The highly efficient and selective MR-MIP was used for the removal of spiked MR dye from different water samples. The selected imprinted polymer, MR1-MIP was able to selectively remove the MR molecules from aqueous media. A significant amount of dye was removed by MR1-MIP from the river water samples with a high degree of removal efficiency i.e. 92.25%. The imprinting factor of 3.75 for MR1-MIP indicated that the high selectivity in terms of adsorption for MR. A minimum loss of only ~ 3.35% in the removal efficiency within ten sequential cycles of adsorption–desorption study evidenced that MR-MIPs could be used as the most cost effective and best sorbent for the removal of MR from polluted water. Furthermore, the structural properties of MR-MIPs were characterized by FTIR and EDX, whereas TGA, SEM and BET were used to describe the thermal, morphological and surface structures of the particles, respectively. [ABSTRACT FROM AUTHOR]

Activated sludge processes contain various groups of microorganisms with different metabolic properties, which are responsible for contaminants removal. Therefore, it is important to elucidate the general structure and functional properties of biomass in activated sludge processes. For this purpose, a full-scale domestic biological wastewater treatment plant in Tunceli (Turkey), Tunceli WWTP (wastewater treatment plant), was monitored to observe seasonal variations in process performance and biomass properties for a year. It was observed that nitrifying bacteria developed abundantly in the rainy and cool spring season as they were suppressed in summer because their large losses took place due to an environment containing high alkalinity values. In September, aerobic heterotrophic, nitrify, denitrify, and anaerobic activities increased. It can be said that the biomass contained young and mature microorganism in this environment in which the sludge volume index (SVI) value increased to 196 mL/g. As a result of the improvement in the structural and functional properties of biomass, the nitrogen removal efficiency reached 99%. Throughout the whole study, the structural improvement observed in biomass was reflected in its removal activity. The amount of biomass and removal activity decreased with the abundance of organic matter in the influent at the period in which biomass was closer to being categorized in the aged sludge class. The results showed that as the lowest mixed liquid suspended solids (MLSS) and mixed liquid volatile suspended solids (MLVSS) values of the year were 530 and 400 mg/L, respectively, in November 2017, MLSS and MLVSS values reached the highest amount (1700 and 1400 mg/L, respectively) in December 2017 when aerobic heterotrophic activity accelerated with a decrease in organic matter level. [ABSTRACT FROM AUTHOR]

Water, an essential commodity available to mankind, is constantly under pollution threat. Industries are one of the major causative factors for its poor quality and therefore all organisms depending upon it, directly or indirectly are affected by various life-threatening problems. Thus, the treatment of discharge waste into the freshwater ecosystem is the dire need of the hour. The objective of the study is valorization of discarded snail shells for treatment of industrial wastewater. In the present study, industrial wastewater was treated using snail shell dust obtained from Bellamya bengalensis to assess change in water quality parameters. Various physico-chemical parameters like pH, total dissolved solids, electric conductivity, dissolved oxygen, biological oxygen demand, chemical oxygen demand, calcium, magnesium, total hardness, chlorides, bicarbonates, orthophosphates, sulfates, nitrates, and ammonia-N were assessed after its treatment with snail shell dust. Based on the present observation, it was concluded that all studied parameters except dissolved oxygen showed a remarkable decline in concentration after treatment with snail shell dust at the rate of 15 g per liter at the end of 4 days. Moreover, increased dissolved oxygen concentration also endorsed an enhancement in water quality. Statistical analysis through Pearson correlation and indices, viz., WQI (Water quality index) as well as Nemerow's Pollution index when applied to the present data, also supported an improvement in the water quality. The findings thus endorsed the utilization of snail shell dust as an eco-friendly technique and can be substituted as a sustainable method for the treatment of industrial wastewater. [ABSTRACT FROM AUTHOR]

Interfacial solar energy evaporation is an effective measure to alleviate the current global shortage of clean water resources. However, many solar evaporators are two-dimensional (2D) structured devices developed by coating light-absorbing materials on the surface of host materials, and the efficiency of solar steam generation is limited. For this reason, the present study reports a facile and environment-friendly method to construct a conical three-dimensional (3D) wooden evaporator, which uses flexible wood as the substrate and tannic acid complex as the light-absorbing material and is formed by further convolution. Reasonable structural design and material combination enable the evaporator to show excellent mildew resistance and highly efficient evaporation performance. The black decoration considerably improves the wood light absorption, resulting in high absorbance (>90%) of DW-TA-Fe3+ in the wavelength range of 200–800 nm. The water evaporation rate of the wooden cone evaporator can reach up to 1.79 kg m−2 h−1, about 1.6 times higher than that of the 2D evaporator. Moreover, the evaporator exhibits outstanding biological stability and effective desalination performance. This work is expected to offer a new direction in designing a 3D wooden evaporator for effective solar water desalination. [ABSTRACT FROM AUTHOR]

Circular development creates more resource efficient, adaptive, and ecologically healthy cities. Circular food and construction systems; the ecological regeneration of contaminated brownfield sites and circular tactical urbanism are just some of the processes and systems adopted by those implementing a circular development pathway. These produce benefits, however, there are many challenges to implementing circular development, demonstrated by two London cases. The research reveals the difficulties low-value, circular activities encounter when competing for space in London. It shows how the imbalance between local supply and demand for circular products prevents scaling-up. It suggest a lack of data monitoring the benefits of adopting circular development, undermines political support. It reveals the conflict between the reliance on civil society to engage with circular actions versus public resistance. It highlights the need for accountability and transparency in the process of implementation and for a regulatory framework to encourage circular development. [ABSTRACT FROM AUTHOR]

Home and community composting are key strategies for local organic waste management. The quality and safety of industrial composts are controlled, but those of home and community composts are not, and this could make them unsafe for use in kitchen gardens. Home (n = 20) and community (n = 41) composts, from urban and suburban areas including mildly Pb-contaminated allotment gardens, were analyzed for quality and safety regarding trace metals and metalloids (TMM) using mid-infrared Fourier transform spectrometry (FT-MIR) and portable X-ray fluorescence spectrometry, respectively. Home composts had a significantly higher Pb content (98 mg.kg−1 ± 10 mg.kg−1) than community composts (21 mg.kg−1 ± 2 mg.kg−1). Numerous home composts (85%) and a few community composts (17%) exceeded the organic farming thresholds for Pb (45 mg.kg−1) and Zn (100 mg.kg−1). The high mineral matter content and the relative abundance of chemical functions attributable to silicates (up to 35%) highly paralleled with TMM contents, mostly concentrated in the fine fraction. Co-inertia analysis highlighted strong and significant links between TMM contents and the whole chemical signature delivered by FT-MIR spectrometry. Pb-contaminated soil could be carried into home compost by green waste or by voluntary addition. Covariance analyses indicated that mineral matter and chemical functions only partly explained the variability in Pb content, suggesting a more complex combination of drivers. Community composting appears as a suitable local solution resulting in high-quality compost that complies with European organic farming regulations, while home composting from allotment gardens should be seriously evaluated to comply with such safety requirements. [ABSTRACT FROM AUTHOR]

Recent advances in wastewater treatment processes have resulted in high removal efficiencies for various hazardous pollutants. Nevertheless, some technologies are more suitable for targeting specific contaminants than others. We comprehensively reviewed the recent advances in removing hazardous pollutants from industrial wastewater through membrane technologies, adsorption, Fenton-based processes, advanced oxidation processes (AOP), and hybrid systems such as electrically-enhanced membrane bioreactors (eMBRs), and integrated eMBR-adsorption system. Each technology's key features are compared, and recent modifications to the conventional treatment approaches and limitations of advanced treatment systems are highlighted. The removal of emerging contaminants such as pharmaceuticals from wastewater is also discussed. [ABSTRACT FROM AUTHOR]