Sewage Treatment Research Articles

Review on Odour Assessment Ant Odour Abatement Techniques

Abstract: Odour can be defined as a perception of smell or in scientific terms it can be defined as a sensation resulting from the reception of stimulus by the olfactory sensory system. Odours may cause pleasant or unpleasant sensation and is induced by inhaling volatile organic and inorganic odorants. The sources of odour may be air-borne or water-borne. Foul odour may cause ill health or respiratory symptoms, insomnia, asthama, nausea and discomfort and other environmental nuisance. Odours can be assessed either by sensory measurements or analytical measurements. There are various physical, chemical and biological treatments for odour abatement. The release of unpleasant odours from sewage carrier system as well as sewage treatment system has become a great public concern especially among densely populated countries. These odours cause environmental nuisance and severe damage to locals. Odour is an important physical characteristic of both water and wastewater. Thus, it requires significant attention in terms of measurement as well as abatement. This study reviews the various odour measurement and abatement techniques.

Optimized Antibiotic Resistance Genes Monitoring Scenarios Promote Sustainability of Urban Water Cycle.

Dissemination of antibiotic resistance genes (ARGs) in urban water bodies has become a significant environmental and health concern. Many approaches based on real-time quantitative PCR (qPCR) have been developed to offer rapid and highly specific detection of ARGs in water environments, but the complicated and time-consuming procedures have hindered their widespread use. Herein, we developed a facile one-step approach for rapid detection of ARGs by leveraging the trans-cleavage activity of Cas12a and recombinase polymerase amplification (RPA). This efficient method matches the sensitivity and specificity of qPCR and requires no complex equipment. The results show a strong correlation between the prevalence of four ARG markers (ARGs: sul1, qnrA-1, mcr-1, and class 1 integrons: intl1) in tap water, human urine, farm wastewater, hospital wastewater, municipal wastewater treatment plants (WWTPs), and proximate natural aquatic ecosystems, indicating the circulation of ARGs within the urban water cycle. Through monitoring the ARG markers in 18 WWTPs in 9 cities across China during both peak and declining stages of the COVID epidemic, we found an increased detection frequency of mcr-1 and qnrA-1 in wastewater during peak periods. The ARG detection method developed in this work may offer a useful tool for promoting a sustainable urban water cycle.

Analyzing greenhouse gas emissions and influencing factors of 247 actual wastewater treatment plants in China using emission factor and operational data integrated methods (ODIM).

In response to China's policies on pollution control and carbon emission (CE) reductions, more stringent regulations have been implemented to evaluate CE in wastewater treatment facilities. In this study, we have analyzed CE from China's wastewater treatment plants (WWTPs) and influencing factor. Emission factor (EF) and operational data integrated methods (ODIM) were utilized to measure emissions, using data collected from 247 WWTPs over a 1-year period across seven regions in China. The average CE intensity was 0.45 kgCO2-eq/m3, affected by region, season, influent water quality, treatment processes, effluent discharge standards, and facilities. The scale effect was obvious only in the range of 2 × 105 m3/day. Underground WWTPs exhibited significantly higher CE compared to aboveground WWTPs. In summary, the assessment of CE in 247 actual WWTPs not only identifies emission reduction potential but also provides a scientific basis for formulating targeted emission reduction measures.

Development of a probabilistic risk model for pharmaceuticals in the environment under population and wastewater treatment scenarios.

Preparing for future environmental pressures requires projections of how relevant risks will change over time. Current regulatory models of environmental risk assessment (ERA) of pollutants such as pharmaceuticals could be improved by considering the influence of global change factors (e.g., population growth) and by presenting uncertainty more transparently. In this article, we present the development of a prototype object-oriented Bayesian network (BN) for the prediction of environmental risk for six high-priority pharmaceuticals across 36 scenarios: current and three future population scenarios, combined with infrastructure scenarios, in three Norwegian counties. We compare the risk, characterized by probability distributions of risk quotients (RQs), across scenarios and pharmaceuticals. Our results suggest that RQs would be greatest in rural counties, due to the lower development of current wastewater treatment facilities, but that these areas consequently have the most potential for risk mitigation. This pattern intensifies under higher population growth scenarios. With this prototype, we developed a hierarchical probabilistic model and demonstrated its potential in forecasting the environmental risk of chemical stressors under plausible demographic and management scenarios, contributing to the further development of BNs for ERA. Integr Environ Assess Manag 2024;00:1-21. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Conjoint analysis of nitrogen and phosphorus metabolism in urban system: A case study of Dar es Salaam, Tanzania

AbstractNitrogen (N) and phosphorus (P) metabolism is becoming an increasingly complex process during urbanization due to increasing rates of consumption and emission worldwide. Understanding the urban N and P metabolism helps identifying production capacity, consumption demand, and the impact of N and P emissions on the environment, providing a scientific basis for decision‐making in sustainable utilization of N and P resources. Quantifying and mapping the source, path, and sinks of N and P in an urban system is the premise of controlling emissions. In this paper, we used the substance flow analysis (SFA) method to describe the N and P metabolism processes in the urban system of Dar es Salaam (Tanzania) in 2017, and used the scenario‐based analysis method to understand the impact of different N and P metabolisms on potentially recoverable N and P sources by 2030. The results showed that the urban system of Dar es Salaam receives a total input flow of 28,101.8 tN/year and 3,379 tP/year, with a total output flow of 18,859.6 tN/year and 1,849.3 tP/year with net stock changes of 9,242.2 t/year for N and 1,529.7 t/year for P, respectively. We noticed that increased human activities largely represented the city's waste released after the household consumption, and would become the main causes of N and P emissions. In addition to this, 59.38%, 31.25%, and 9.38% of N flow quantification quality were at high, medium, and low levels, respectively, while 74.07%, 11.11%, and 14.81% of P flow quantification quality were at high, medium, and low levels, respectively. Our results suggest that implementing integrated nutrient management measures, such as changes in people's diets and the use of washing products, and improved management and technologies of manure, sewage, and landfill leachate treatment, would be the most effective approach to resolve the urban nutrient emissions in Dar es Salaam.

Assessment of groundwater quality for human consumption and its health risks in the Middle Magdalena Valley, Colombia

Groundwater is the primary source of water for people living in rural areas, especially during seasons when surface water is contaminated or unavailable. In Colombia, people use groundwater as drinking water without additional treatment. In addition, there is no infrastructure for wastewater collection and sewage treatment in the region of the Middle Magdalena Valley. The current study aims to evaluate the quality of groundwater in this region to determine any potential health hazards associated with its consumption. To reach the objective, three (3) physicochemical and microbiological sampling campaigns were carried out during different hydrological periods. A total of 428 groundwater samples were analyzed for over 28 parameters. The results were compared with the water quality standards proposed by the US EPA and Colombian regulations for human consumption. The analysis revealed the presence of total and fecal coliforms in 89% and 58% of the analyzed samples, respectively, identifying them as the main contaminants in groundwater. Furthermore, the pH levels did not meet the standards set by the US EPA in 33.8% of the cases and by Colombian regulations in 31.02%. Additionally, 32.8%, 17.6%, 14.3%, and 10.9% of the samples failed to meet the established thresholds for apparent color, magnesium, iron, and nitrates, respectively, under both standards. Moreover, only the analyses of selenium, mercury, and zinc complied with the quality standards under both regulatory frameworks. Based on the Colombian Drinking-Water Quality Risk Index (CDWQRI-IRCA), the risk associated with water quality meant for human consumption was assessed. The results showed that over 84% of the samples analyzed posed a high risk to human health, 4.6% posed a medium risk, 5.5% posed a low risk, and only 5.7% posed no risk at all. Additionally, official mortality statistics for children under four years old were reviewed, which revealed two deaths in 2019 due to Acute Diarrheal Disease (ADD) caused by consumption of contaminated water. Therefore, it is crucial to implement water treatment systems, establish aqueducts in rural areas, and conduct rigorous and systematic monitoring of drinking water to ensure it is safe for human consumption. It is also important to track morbidity and mortality rates associated with water consumption.

A short bibliographic review concerning biomethane production from wastewater sludge.

Biomethane production by anaerobic digestion (AD) of sludge from municipal wastewater treatment is a viable practice to valorise the residues of these plants. However, although the relevant literature is abundant, no comprehensive reviews have been recently published on this topic. Detailed information concerning the factors influencing the AD process and values of biomethane production from the sludge from municipal wastewater treatment plants (MWWTPs) on the global scale may support technicians and researchers in both the planning and the design steps of an AD process. This study proposes a systematic review and a meta-analysis of the factors that noticeably influence biomethane yield deriving from AD of sludge from MWWTP. The reported values were systematically analysed compared to the main factors driving AD, including publication year, geographical area of each study, type of digested sludge, treatment in the water line of the MWWTP, possible sludge pre-treatments, type of digestion process, hydraulic retention time (HRT) and temperature regime of the AD process. A higher biomethane production was registered in North American plants compared to countries in other continents. Older studies published between 2001 and 2005 reported lower mean values compared to the more recent experiments. A gradient of 'primary sludge' > 'mixed sludge' > 'wastewater activated sludge' was found for the mean biomethane yield in relation to the digested sludge type. The mean biomethane yields for different types of sludge on a global scale are 0.425, 0.296 and 0.176 Nm3 kg VS-1 for primary sludge, mixed sludge and waste activated sludge, respectively. Overall, the study demonstrates: (i) the very large variability of biomethane yields from AD of the residues from MWWTPs (mainly due to the different characteristics of sludge) and (ii) the non-significance of some factors (i.e. treatment in the water line, pre-treatments, type of process, HRT and temperature regime) on energy yields from the AD process.

Feasibility of using in situ UV/Vis spectrometer probe for measuring COD in WWTP based on UASB reactor

The aim of this work is to report the use of a UV/Vis spectrometer for real time, in situ monitoring of the chemical oxygen demand (COD) in a municipal wastewater treatment plant (WWTP) operating with upflow anaerobic sludge blanket (UASB) reactor, installed in south of Brazil. The spectrometer was used according to the factory calibration procedures: global, local offset and local linear. COD probe measurements were compared to laboratory analyses for the calibration procedures. Continuous operation led to increasing errors, which was related to grime deposition on the probe window and avoided with periodic cleaning. Performance of the probe measurements versus laboratory analyses was evaluated with coefficient of determination, root mean squared error (RMSE), relative RMSE, RMSE to standard deviation ratio (RSR) and Student’s t-test. It is concluded that the best calibration procedures is the local linear, for the influent and the effluent of UASB reactor. The probe consists of an improvement to real time and in situ monitoring of South America WWTPs.

Comparative study for the performance of pure artificial intelligence software sensor and self-organizing map assisted software sensor in predicting 5-day biochemical oxygen demand for Kauma Sewage Treatment Plant effluent in Malawi

Introduction: Modeling plays a crucial role in understanding wastewater treatment processes, yet conventional deterministic models face challenges due to complexity and uncertainty. Artificial intelligence offers an alternative, requiring no prior system knowledge. This study tested the reliability of the Adaptive Fuzzy Inference System (ANFIS), an artificial intelligence algorithm that integrates both neural networks and fuzzy logic principles, to predict effluent Biochemical Oxygen Demand. An important indicator of organic pollution in wastewater.Materials and Methods: The ANFIS models were developed and validated with historical wastewater quality data for the Kauma Sewage Treatment Plant located in Lilongwe City, Malawi. A Self Organizing Map (SOM) was applied to extract features of the raw data to enhance the performance of ANFIS. Cost-effective, quicker, and easier-to-measure variables were selected as possible predictors while using their respective correlations with effluent. Influents’ temperature, pH, dissolved oxygen, and effluent chemical oxygen demand were among the model predictors.Results and Discussions: The comparative results demonstrated that for the same model structure, the ANFIS model achieved correlation coefficients (R) of 0.92, 0.90, and 0.81 during training, testing, and validation respectively, whereas the SOM-assisted ANFIS Model achieved R Values of 0.99, 0.87 and 0.94. Overall, despite the slight decrease in R-value during the testing stage, the SOM- assisted ANFIS model outperformed the traditional ANFIS model in terms of predictive capability. A graphic user interface was developed to improve user interaction and friendliness of the developed model. Integration of the developed model with supervisory control and data acquisition system is recommended. The study also recommends widening the application of the developed model, by retraining it with data from other wastewater treatment facilities and rivers in Malawi.

Water quality assessment of Bheemasandra Lake, South India: A blend of water quality indices, multivariate data mining techniques, and GIS.

An integrated approach combining water quality indices (WQIs), multivariate data mining, and geographic information system (GIS) was employed to examine the water quality of Bheemasandra Lake, located adjacent to a sewage treatment plant (STP) in Tumakuru city, India. The analysis of 22 lake water samples, examined before and after the monsoons, revealed that the physicochemical parameters namely - electrical conductivity, biochemical oxygen demand, turbidity, total dissolved solids, ammoniacal nitrogen, nitrates, phosphates, magnesium, total hardness, total alkalinity, and calcium - exceeded the acceptable limits stipulated by national and international standards. The Canadian Council of Ministers of the Environment WQI (pre-monsoon: 25.3; post-monsoon: 33.9) and weighted arithmetic WQI (pre-monsoon: 3398; post-monsoon: 2093) designated the water as unsafe for drinking. Irrigation WQIs (sodium adsorption ratio, sodium percentage, residual sodium carbonate, magnesium hazard, permeability index, and potential salinity) implied water's suitability for irrigation. However, electrical conductivity indicated otherwise. Industrial WQIs (Larson-Skold Index, Langelier Index, Aggressive Index, and Puckorius Scaling Index) illustrated scaling propensity and the chloride sulfate mass ratio alluded galvanic corrosion potential. Hierarchical cluster analysis gathered 22 sampling points into two clusters (cluster 1: relatively lower polluted regions; cluster 2: highly polluted regions) for each season based on similarities in water features. Principal component analysis extracted four (79.07% cumulative variance) and six (87.14% cumulative variance) principal components before and after the monsoons, respectively. These components identified the primary pollution sources as urban sewage and natural lithological processes. WQI maps, created using the inverse distance weighted interpolation technique, enhanced the visualization of spatial-temporal variations. This study highlights the dire consequences of urbanization, STP pollution, and sewage management failures, necessitating that concerned authorities should implement policies and measures to curb the negative impacts on the environment and public health.

The DPSIR Model-Based Sustainability Assessment of Urban Water Resources: A Comparative Study of Zhuhai and Macao

Based on the driving force-pressure-state-impact-response (DPSIR) model, 19 indicators were selected to construct a comparison between Zhuhai and Macao, two adjacent cities at the estuary of the Pearl River in China, which have different development models and water resource sustainable development strategies. Factors that may affect the sustainability of water resources were screened and placed according to the relationships of the five subsystems in the DPSIR model, establishing a sustainable evaluation model for water resources in the two cities. The results analyzed by Principal Component Analysis and Entropy methods showed that (1) Zhuhai City was greatly affected by the driving force, while Macao was greatly affected by the state system from 2012 to 2021. (2) From the trend changes, it can be seen that, in recent years, the water resources of the two cities have been moving towards sustainable development, and the management and protection of water resources have achieved remarkable results. From the evaluation results, it can be seen that implementing urban water-saving activities, strengthening the proportion of environmental water conservancy, public measures in public investment, upgrading sewage treatment machinery to improve sewage treatment rates, and other measures can effectively improve the current situation of water resources in both regions. In the future, the Zhuhai and Macao cities may continue to face a series of water resource pressures brought on by socio-economic developments. Therefore, an active adjustment of the development of the measurement of controlling wastewater discharge and saving water resources was proposed, adhering to the direction of sustainable development, and ensuring the benign development of socio-economic conditions and the ecological environment. This study can provide data to support regional water resource security and policy formulation with different political systems.

Fabrication of Monodisperse Magnetic Polystyrene Mesoporous Composite Microspheres for High-Efficiency Selective Adsorption and Rapid Separation of Cationic Dyes in Textile Industry Wastewater.

Sustainable development has become an inevitable trend in the world's green chemical industry for a generation or more. In this study, a monodisperse magnetic polystyrene mesoporous composite microsphere (MPPS) composed of Fe3O4 nanoparticles loaded on polystyrene mesoporous microspheres is introduced. These microspheres serve as effective adsorbents for the swift removal of cationic dyes. The fabrication of the wastewater adsorbent, with its simple operation and economic practicality, involved a combination of dispersion polymerization, a sulfonation reaction, two-step swelling polymerization, and in situ alkaline oxidation technology. Notably, the adsorption capacity within 3 min reaches 184.0 mg/g, with an impressive adsorption efficiency of 92%. This is primarily attributed to the high specific surface area (Smax) of the MPPS providing more reaction sites for π-π interaction. Simultaneously, the attractive force between negatively charged sulfonic acid groups and cationic dyes is enhanced through surface modification of the MPPS. Furthermore, the MPPS, boasting a maximum saturation magnetization of 38.19 emu/g, ensures rapid separation from the solution for recycling within 3 s. Even after 5 cycles, the adsorption efficiency remains over 90%. The rapid separation of dyes is facilitated by the magnetic attraction of Fe3O4 nanoparticles from the MPPS under the application of a magnetic field. These composite mesoporous materials exhibit outstanding performance in both efficient selective adsorption and recyclability, presenting a novel green adsorbent with promising prospects for sustainable development. This innovation is poised to excel in fields such as sewage treatment, separation, and purification.

Enhancing Sewage Sludge Treatment with Hydrothermal Processing: A Case Study of Adana City

As a byproduct of municipal wastewater treatment systems, sewage sludge has traditionally been treated in low-value applications such as landfilling, posing significant environmental risks due to its pollutant content. However, there is a growing interest in utilizing the energy potential of sewage sludge through thermochemical conversion methods. Among these methods, hydrothermal liquefaction (HTL) has come to the fore as a promising green approach, offering an environmentally friendly means of extracting bio-oils and biochemicals from sewage sludge. In this study, the HTL method, regarded as an innovative approach among sewage sludge treatment methods apart from incineration, pyrolysis, and landfilling, is comparatively investigated in terms of greenhouse gas (GHG) emissions alongside other methods. In particular, this study analyzes the projected amount and various characteristics of sewage sludge that could potentially be generated by 2030 for the city of Adana, which currently produces approximately 185 tons of sewage sludge per day. The findings indicate that without intervention, sludge production is projected to reach 68,897 tons per year by 2030. Moreover, this research demonstrates that the utilization of HTL for sludge treatment results in a reduction of emissions by approximately 7-fold compared with incineration of sewage sludge.

Degradation of pharmaceuticals and other emerging pollutants employing bi-metal catalysts/magnesium and/or (green) hydrogen in aqueous solution.

Contaminations by pharmaceuticals, personal care products, and other emerging pollutants in water resources have become a seriously burgeoning issue of global concern in the first third of the twenty-first century. As societal reliance on pharmaceuticals continues to escalate, the inadvertent introduction of these substances into water reservoirs poses a consequential environmental threat. Therefore, the aim of this study was to investigate reductive degradation, particularly, catalytic hydrogenation regarding model pollutants such as diclofenac (DCF), ibuprofen (IBP), 17α-ethinylestradiol (EE2), or bisphenol-A (BPA), respectively, in aqueous solutions at lab scale. Iron bimetals (zero valent iron, ZVI, and copper, Cu, or nickel, Ni) as well as zero valent magnesium (Mg, ZVM) in combination with rhodium, Rh, or palladium, Pd, as hydrogenation catalysts (HK), were investigated. Studies were executed through various short-term batch experiments, with multiple sample collections, over a total range of 120min. The results indicated that DCF was attenuated at over 90 % when exposed to Fe-Cu or a Fe-Ni bimetal (applied as a single model pollutant). However, when DCF was part of a mixture alongside with IBP, EE2, and BPA, the attenuation efficacy decreased to 79 % with Fe-Cu and 23 % with Fe-Ni. Conversely, both IBP and BPA exhibit notably low attenuation levels with both bimetals, less than 50 %, both deployed as single substances or in mixtures. No reaction (degradation) products could be identified employing LC-MS, but sometimes a release of the parent pollutant when applying an acetic acid buffer could be noted to a certain extent, suggesting adsorption processes on corrosion products such as iron hydroxide and/or oxides. Surprisingly, Mg in combination with Rh (Rh-HK) or Pd (Pd-HK) showed a significantly rapid decrease in the concentrations of DCF, EE2, and BPA, in part up to approximately 100 %, that is, within a few minutes only in part due to hydrogenation degradation reactions (related reaction products could actually be identified by LC-MS; adsorption processes were not observed here). Moreover, kinetic modeling of the DCF degradation with Mg-Rh-HK was conducted at different temperatures (15 °C, 20 °C, 25 °C, 35 °C) and varied initial concentrations (2.5mg/L, 5.0mg/L, 7.5mg/L, 10.0mg/L). The outcomes prove that the degradation of DCF at the Rh-HK's surface followed a modified first-order kinetics, most probably by catalytic hydrodehalogenation and subsequent hydrogenation of the aromatic moieties (molecular hydrogen was provided by the corrosion of Mg). From the determined reaction rate constants at four different temperatures, the activation energy was estimated to be 59.6kJ/mol by means of the Arrhenius equation what is in good agreement with similar results reported in the literature. This coupled hydrodehalogenation and hydrogenation approach may be upscaled into a new promising technical process for comprehensively removing such pharmaceuticals and similar pollutants in sewage plants in a single step, furthermore, even in combination with adsorption by activated carbon and/or ozonation which have already been established at some sewage plants in Switzerland and Germany recently.

Assessing the spatiotemporal variability of dissolved organic matter fluorescence composition in the Lake George, NY watershed

AbstractLake George (LG) is a temperate, oligotrophic, medium-sized lake (114 km2) located in northeastern New York State (U.S.). Lakes are highly understudied environments where extensive dissolved organic matter (DOM) processing occurs. With this study we establish the foundation for researching the organic biogeochemistry of the LG watershed, in particular, the numerous tributaries flowing into the lake. Collected were 213 samples from 64 tributaries and 12 lake locations. Some of the tributaries had unique wastewater, agricultural, or wetland influences. We employed fluorescence spectroscopy, a common biogeochemical technique, to characterize the fluorescent DOM (FDOM) component. We developed a parallel factor analysis (PARAFAC) model for the deconvolution of FDOM data allowing to depict six underlying FDOM constituents, which varied in source and biogeochemical reactivity on spatiotemporal scales. Tributary DOM, in comparison to lake DOM, was much more aromatic, of larger molecular weight, more humic, and contained less protein-like material. The distribution of humic and protein-like PARAFAC components was impacted by land-use and wastewater influences. Supporting characterization of the chromophoric DOM (CDOM) and total DOM (on dissolved organic carbon basis) allowed differentiating the influence of wetlands, which could not be depicted by spatiotemporally assessing the variability of PARAFAC components. Temporal assessment revealed minor variabilities in tributary DOM quantity and quality except in cases of point sources such as wastewater treatment facilities. Overall, this primer study establishes baseline understanding of the baseflow levels of DOM constituents in the LG watershed, and more broadly, presents a PARAFAC model for the deconvolution of fluorescence spectra of DOM from temperate and oligotrophic lake watersheds such as LG.

Simulation and Experimental Study of Circulatory Flash Evaporation System for High-Salt Wastewater Treatment

Treatment methods for high-salt wastewater mainly consist of physical methods, chemical methods and biological methods. However, there are some problems, such as slow treatment speed, high investment costs and low treatment efficiency. To address NaCl solutions, in this study, a circulatory flash system was designed based on gas–liquid equilibrium, mass conservation equation and energy conservation equation. A circulatory flash evaporation simulation and a static flash evaporation experiment were conducted on NaCl solutions under various operating conditions to investigate the effects of heating temperature, flash pressure and initial NaCl concentration on the circulatory flash evaporation system. The significance of each factor’s influence on the evaporation fraction and energy consumption was examined through static flash experiments. The simulation results demonstrated that increasing the heating temperature, decreasing the flash pressure and having a higher initial NaCl concentration could enhance the treatment capacity of high-salt wastewater. The flow rate of vapor outlets increased with higher heating temperature but decreased as the flash pressure rose. The experimental results demonstrated that flash evaporation pressure was the primary factor influencing both the evaporation fraction and the energy consumption per unit mass of vapor produced. It was observed that with an increase in heating temperature, the flash pressure decreased and there was a corresponding decrease in energy consumption per unit mass of vapor produced. The optimal experimental conditions were achieved at a heating temperature of 99 °C, a flash pressure of 15 kPa, and an initial NaCl concentration of 20%.

A simulation-based DEA approach for multiple criterion decision-making problems with uncertain mixed-criteria values

In ex-ante decision scenarios, predicting criterion values accurately is difficult for decision makers (DMs). Inconsiderable work is normally required for measuring criteria by uncertain random values or ordinal values. However, in the classical data envelopment analysis (DEA) model, criterion values are the constants that limit the application of the classical DEA model in ex-ante decision scenarios. This paper presents a simulation-based DEA approach, which captures random and ordinal criterion values by a simple and direct simulation-based approach. The approach includes three steps. In the first step, Monte Carlo simulation methods are used to convert uncertain random values or ordinal values into cardinal data. In the second step, we use traditional DEA methods to compute the efficiency score of decision-making units (DMUs). In the third step, we ranked all DMUs by calculating the DEA-efficient acceptability of each DMU in multiple simulations and then selected the optimal DMU. The proposed approach is illustrated by experimental examples and a case study of a municipal wastewater treatment system.

Sludge deep dewatering by liquefied dimethyl ether: selection of operating conditions based on response surface methodology

ABSTRACT Sludge is an inevitable by-product of the sewage treatment process and its high moisture content poses significant challenges for its treatment and disposal. This study focuses on the technology of sludge deep dewatering using liquefied dimethyl ether (DME) and explores the relationship between operating parameters (DME/sludge ratio, extraction time and stirring speed) and the water content of the sludge after deep dewatering. After deep dewatering, the sludge's lower heating value (LHV) was significantly increased. The dehydrated filtrate is highly biodegradable and could be treated together with sewage. Based on the response surface method of central composite design, a second-order regression model of the above three variables and sludge water content as the response was established. Finally, the operating conditions diagram was drawn by target water content (36.96 wt.%) which meets the requirement of self-sustained incineration and model equation. This study provides a valuable perspective on sludge drying and fuelisation.

Phytoremediation of Grey Water

Greywater, generated from domestic activities excluding toilet waste, presents a significant challenge for water management due to its diverse contaminants and potential environmental impact. Conventional treatment methods often fall short in addressing the complex composition of greywater while maintaining sustainability. Phytoremediation, a green technology that utilizes plants and their associated microorganisms, offers a promising and ecofriendly alternative for greywater treatment. This paper reviews the principles, mechanisms, and applications of phytoremediation in the context of greywater treatment. Various phytoremediation techniques such as rhizofiltration, phytoextraction, and phytodegradation are discussed, highlighting their efficacy in removing pollutants such as organic matter, nutrients, pathogens, and heavy metals from greywater. The role of specific plant species with remediation potential and their physiological mechanisms in contaminant uptake and transformation are examined. Case studies and experimental findings from greywater phytoremediation projects around the world are presented to demonstrate the practicality and effectiveness of this approach. Factors influencing phytoremediation performance, including plant selection, hydraulic conditions, nutrient availability, and system design, are analysed to optimize greywater treatment efficiency.

Re-assessment of monoclonal antibodies against diclofenac for their application in the analysis of environmental waters.

The non-steroidal anti-inflammatory drug (NSAID) diclofenac (DCF) is an important environmental contaminant occurring in surface waters all over the world, because, after excretion, it is not adequately removed from wastewater in sewage treatment plants. To be able to monitor this pollutant, highly efficient analytical methods are needed, including immunoassays. In a medical research project, monoclonal antibodies against diclofenac and its metabolites had been produced. Based on this monoclonal anti-DCF antibody, a new indirect competitive enzyme-linked immunosorbent assay (ELISA) was developed and applied for environmental samples. The introduction of a spacer between diclofenac and the carrier protein in the coating conjugate led to higher sensitivity. With a test midpoint of 3 μg L-1 and a measurement range of 1-30 μg L-1, the system is not sensitive enough for direct analysis of surface water. However, this assay is quite robust against matrix influences and can be used for wastewater. Without adjustment of the calibration, organic solvents up to 5%, natural organic matter (NOM) up to 10 mg L-1, humic acids up to 2.5 mg L-1, and salt concentrations up to 6 g L-1 NaCl and 75 mg L-1 CaCl2 are tolerated. The antibody is also stable in a pH range from 3 to 12. Cross-reactivity (CR) of 1% or less was determined for the metabolites 4'-hydroxydiclofenac (4'-OH-DCF), 5-hydroxydiclofenac (5-OH-DCF), DCF lactam, and other NSAIDs. Relevant cross-reactivity occurred only with an amide derivative of DCF, 6-aminohexanoic acid (DCF-Ahx), aceclofenac (ACF) and DCF methyl ester (DCF-Me) with 150%, 61% and 44%, respectively. These substances, however, have not been found in samples. Only DCF-acyl glucuronide with a cross-reactivity of 57% is of some relevance. For the first time, photodegradation products were tested for cross-reactivity. With the ELISA based on this antibody, water samples were analysed. In sewage treatment plant effluents, concentrations in the range of 1.9-5.2 μg L-1 were determined directly, with recoveries compared to HPLC-MS/MS averaging 136%. Concentrations in lakes ranged from 3 to 4.4 ng L-1 and were, after pre-concentration, determined with an average recovery of 100%.