Effective sludge management: Reuse of biowaste and sewer sediments for fired bricks.

This study partially replaced the clay with sewer sludge (SS) and rice husk (RH-SS) to make fired bricks. The brick samples were examed in terms of shrinkage, water absorption, and compressive strength. Besides, they were analyzed via XRD and metal extraction to determine the heavy metal residuals in the products. The results showed that it was possible to fabricate fired bricks using sewer sludge or rice husk-blended sludge with up to 30% by weight. These brick samples complied with the technical standard for clay brick production, in which the compressive strength was more than 7.5 MPa, water absorption was from 11-16%, and the linear shrinkage was all less than 5%. The rice husk addition helped mitigate the heavy metal residuals in the bricks and leaching liquid, in which all the values were lower than the US-EPA maximum concentration of contaminants for toxicity characteristics.Implications: Previous studies have proved the possibility of mixing sewage sludge from different origins (sewage sludge, river sediment, canal sediment, sewer sediment, etc.) with clay and some wastes to make bricks. In which, mostof the studies used sewage sludge from wastewater treatment plants, very fewdealt with lake/river or sewer sediment. This study shall be the first to study the possibility of employing sewer sediments with the addition of rice husk powder to achieve two targets, including (1) the reuse of biowaste and sludge for brick fabrication and (2) the reduction of heavy metals in final calcined bricks. Different ratios of the rice-husk blended sewer sludge (RH-SS) - clay mixture shall be tested to find the optimized compositions. The results showed that it was possible to fabricate fired bricks using sewer sludge or rice husk-blended sludge with up to 30% by weight, which meant reduce 30% of clay in the brick production. The final products were proved to meet the quality standard in terms of compressive strength (more than 10 MPa), water absorption(from 11-16%), and the linear shrinkage (less than 5%). Larger scale of this study can be an evident to recommend for policy change in the waste reuse in construction field.

Online soft measurement method for chemical oxygen demand based on CNN-BiLSTM-Attention algorithm.

The measurement of chemical oxygen demand (COD) is very important in the process of sewage treatment. The value of COD reflects the effectiveness and trend of sewage treatment to a certain extent, but obtaining accurate data requires high cost and labor intensity. To1 solve this problem, this paper proposes an online soft measurement method for COD based on Convolutional Neural Network-Bidirectional Long Short-Term Memory Network-Attention Mechanism (CNN-BiLSTM-Attention) algorithm. Firstly, by analyzing the mechanism of the aerobic tank stage in the Anaerobic-Anoxic-Oxic (A2O) wastewater treatment process, the selection range of input variables was preliminarily determined, and the collected sample dataset was subjected to correlation analysis. Finally, pH, dissolved oxygen (DO), electrical conductivity (EC), and water temperature (T) were determined as input variables for soft measurement prediction of COD.Then, based on the feature extraction ability of CNN and the advantage that BiLSTM is able to capture the backward and forward dependencies in time series data, combined with the attention mechanism that can assign higher weights to the key data, a CNN-BiLSTM-Attention algorithm model was established to soft measure COD in the effluent from the aerobic zone of the A2O wastewater treatment process. At the same time, root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and coefficient of determination (R2) were utilized Three indicators were used to evaluate the model, and the results showed that the model can accurately predict the value of COD and has a high accuracy. At the same time, compared with models such as CNN-LSTM-Attention, CNN-BiLSTM, CNN-LSTM, LSTM, RNN, BP, SVM, XGBoost, and RF etc., the results showed that the CNN-BiLSTM Attention model performed the best, proving the superiority of the algorithm model.The Wilcoxon signed-rank test indicates significant differences between the CNN-BiLSTM-Attention model and other models.

Application of Magnetic Materials Combined with Echo® Mass Spectrometry System in Analysis of Illegal Drugs in Sewage.

The aim of this study is to solve the problems of the complicated pretreatment and high analytical cost in the detection technology of trace drugs and their metabolites in municipal wastewater. A high-performance magnetic sorbent was fsynthesized for the enrichment of trace drugs and their metabolites in wastewater to develop a magnetic solid-phase extraction pretreatment combined with the acoustic ejection mass spectrometry (AEMS) analytical method. The magnetic nanospheres were successfully prepared by magnetic nanoparticles modified with divinylbenzene and vinylpyrrolidone. The results showed that the linear dynamic range of 17 drugs was 1-500 ng/mL, the recovery was 44-100%, the matrix effect was more than 51%, the quantification limit was 1-2 ng/mL, and the MS measurement was fast. It can be seen that the developed magnetic solid-phase extraction (MSPE) method is a good solution to the problems of the complicated pretreatment and analytical cost in the analysis of drugs in wastewater. The developed magnetic material and acoustic excitation pretreatment coupled with mass spectrometry analysis method can realize the low-cost, efficient enrichment, and fast analysis of different kinds of drug molecules in urban sewage.

Higher heating value estimation of wastes and fuels from ultimate and proximate analysis by using artificial neural networks.

Higher heating value (HHV) is one of the most important parameters in determining the quality of the fuels. In this study, comparatively large datasets of ultimate and proximate analysis are constructed to be used in HHV estimation of several classes of fuels, including char & fossil fuels, agricultural wastes, manure (chicken, cow, horse, sheep, llama, and pig), sludge (like paper, paper-mil, sewage, and pulp), micro/macro-algae's, wastes (RDF and MSW), treated woods, untreated woods, and others (non-fossil pyrolysis oils) between the HHV range of 4.22-55.55 MJ/kg. The relationships of carbon, hydrogen, and oxygen atomic ratios for fuel classes are illustrated by using ternary plots, and the effects of elemental composition on HHV was analyzed with the extensive dataset. Then, the ultimate (U) and ultimate & proximate (UP) datasets were utilized separately to estimate the HHV by using artificial neural networks (ANN). Hyperparameter optimization was carried out and the best performing ANNs were determined for each dataset, which yielded R2 values of 0.9719 and 0.9715, respectively. The results indicated that while ANNs trained by both datasets perform remarkably well, utilization of U dataset is sufficient for HHV estimation. Finally, the best performing ANN models for both U and UP datasets are given in a directly utilizable format enabling the accurate estimation of HHV of any fuel for optimization of fuel processing and waste management operations.

N2O emission factors in bubbling fluidized bed incineration of municipal sewage sludge: The China case.

The N2O emissions resulting from sludge incineration are estimated using the default values published by the Intergovernmental Panel on Climate Change (IPCC), which may differ significantly from the actual emissions. In this investigation, N2O emissions from four sludge incineration lines in two plants were monitored for varying durations. The variation in N2O emission factors (EFs) between incineration lines of the same plant was much smaller than the difference between different plants. Data on N2O EFs obtained from brief monitoring may contain variabilities of up to 30%. N2O EFs were more sensitive to temperature changes at low temperatures, necessitating extended monitoring periods to improve the reliability of N2O monitoring outcomes in cases of low furnace temperatures. Excessive use of the SNCR system to reduce NOx emissions resulted in concentrations of N2O and NH3 in the exhaust gases exceeding NOx levels. In the case of furnace temperature control and advanced reburning technology, it is advisable to utilize actual monitoring data or the smaller default values provided by the IPCC in China. Otherwise, the estimated N2O emissions may exceed the actual emissions.

Analysis of the effect of intrinsic sludge properties on sludge drying characteristics from both sludge composition and type scales.

Convective drying is an effective method for reducing the moisture content of the sludge. Fewer studies have discussed the effect of sludge physicochemical properties on drying compared to air parameters. Eleven types of sludge were collected, and ultimate analysis, proximate analysis, and heat value analysis were performed. Meanwhile, the maximum drying rate (umax) of sludge convection drying at 70 °C was determined. The results showed that the cumulative variance contribution of the two extracted principal components (PCs) was 92.5 %. Then, a regression model of umax was developed based on the extracted PCs. The coefficient of determination of this model was 0.788, and the difference was statistically significant, with a negative correlation between umax and PC2. Further, the principal component score plot enabled the traceability of the integrated sludge, and based on this classification results, the drying characteristics of various types of sludge were discussed, and a high correlation (R2 = 0.9590) between the initial moisture content of sludge and umax was found. Mathematical models between sludge physicochemical properties and drying characteristics can be effectively developed from both sludge composition and type scales. This exploration deepened the knowledge of sludge drying and facilitates the prediction of drying rate.

Microplastics removal efficiency and risk analysis of wastewater treatment plants in Oman.

Microplastics (MPs) have recently been documented as an emerging pollutant that poses a critical threat to environment. Wastewater treatment plants (WWTPs) are commonly regarded as significant contributors to the presence of MPs. This study aimed to assess the MPs load of three wastewater treatment facilities in Oman using various treatments, including MBR, SBR, and CAS. Wastewater samples from influent, effluent, and sludge were collected and analyzed to determine the concentration, morphology, size, color, and polymer type of the MPs. A set of sieves with a mesh size range of 1 mm-45 µm was used to for filtration. Oxidation treatment was applied for all samples using Fenton's reagent, followed by density separation by sodium chloride solution. The Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR- FTIR) method was utilized to test 10% from each sampling point to confirm the polymer types of the MPs. The pollution load index (PLI) and hazard index (HI) have been employed to assess the risk associated with the chemical toxicity and concentration of detected particles. The PROMETHEE method was used to rank the risk of sampling sites based on different criteria that posed potential ecological and human health risks. The results indicate that the average concentrations of 0.99 MP/L, 1.38 MP/L, and 0.93 MP/L were detected in the final treated effluent of WWTP A, WWTP B, and WWTP C, respectively. These concentrations correspond to overall removal efficiencies of 82.5%, 77.4%, and 79.2% for WWTP A, WWTP B, and WWTP C, respectively Most MPs found in tertiary effluent were smaller particles (425 µm) and fiber-shaped. The major types of MPs were polypropylene (PP), low-density polyethylene (LDPE), polyurethane (PU), polyethylene terephthalate (PET), and Polyvinyl chloride (PVC). This study showed that treated effluent and sludge release significant MPs into the environment.

The Impact of Combined Sewer Overflows on Pharmaceutical and Illicit Drug Levels in New York/New Jersey Waterways.

Pharmaceuticals and drugs of abuse are organic micropollutants of emerging concern in both surface and groundwater worldwide. These compounds are considered to be pseudo-persistent because of their continuous release into water systems. The presence of these compounds in the environment at any concentration poses a potential risk to nontarget organisms. The main sources of these contaminants are wastewater treatment plants (WWTPs) and combined sewer overflows (CSOs). The primary goal of our study was to identify and quantify a panel of 28 commonly prescribed pharmaceuticals (mood-altering drugs, cardiovascular drugs, antacids, antibiotics) and high-prevalence drugs of abuse (cocaine, amphetamines, opioids, cannabis) in river water samples collected from 19 locations in the Hudson and East rivers in New York City. The second goal was to investigate the possible source (WWTP or CSOs) of these micropollutants. Samples were collected weekly from May to August 2021 (n = 224) and May to August 2022 (n = 232), and placed at -20 °C until analysis by liquid chromatography-tandem mass spectrometry. The most frequently detected analytes in 2021 were metoprolol (n = 206, 92%), benzoylecgonine (n = 151, 67%), atenolol (n = 142, 63%), and methamphetamine (n = 118, 53%), and in 2022 the most frequently detected were methamphetamine (n = 194, 84%), atenolol (n = 177, 76%), metoprolol (n = 177, 76%), and 2-ethylene-1,5-dimethyl-3,3-diphenylpyrrolidine (n = 159, 69%). Measured concentrations ranged from the limit of detection (0.50-5.00 ng/L) to 103 ng/L. More drugs and higher concentrations were detected in water contaminated by Enterococci (>60 most probably number) and after rainfall, indicating the influence of CSOs. The presence of drugs in samples with little to no Enterococci and after dry weather events indicates that WWTPs contribute to the presence of these substances in the river, probably due to a low removal rate. Environ Toxicol Chem 2024;43:1592-1603. © 2024 SETAC.

Microfiber emission from a municipal wastewater treatment plant in Hungary.

Since the ingestion of both natural and anthropogenic microfibers produces a deleterious effect on aquatic organisms, it is crucial to explore the emission of these pollutants by WWTPs into the receiving water bodies, such as rivers. Cellulose- and petroleum-based microfibers, as well as microplastic particles, were collected from the effluent of a municipal WWTP operating with activated sludge technology in Budapest, Hungary. During two sampling campaigns organized in February and April of 2023 on different working days and at different times of the day, 123-145 L of effluent was sieved and filtered. The organic matter was removed by hydrogen-peroxide treatment. All fibers and particles larger than 10 µm were counted, and using a fluorescence microscope, the fibers were geometrically characterized in terms of length and diameter. Each fiber was individually identified by transflection-FT-IR method. The fiber concentration varied in the range of 1.88-2.84 and 4.25-6.79 items/L during the 7th and the 16th week of 2023, respectively. In February and April, the proportion of microfibers in the solid particles was 78.3 and 94.7%, respectively. In the effluent the cellulose-based microfibers were dominant (53-91%), while among the petroleum-based microfibers, polyester occurred most often. The median length of cellulose-based fibers was considerably higher in April than in February (650 vs. 1250 µm), and simultaneously the median diameter also increased from 21 to 29 µm. This behaviour was also seen, albeit to a lesser extent, in connection to microfibers derived from petroleum. The treated wastewater's daily microfiber transport to the Danube River varied between 0.44 - 0.69 and 0.94-1.53 billion in February and April 2023, respectively.

On-site monitoring of nandrolone in cattle farming samples by portable atmospheric pressure chemical ionization mass spectrometry with ambient sampling.

Nandrolone (NT) is a type of androgen anabolic steroid that is often illegally used in cattle farming, leading to unpredictable harm to human health via the food chain. In this study, a rapid detection method for NT in the samples of cattle farming was established using a portable mass spectrometer. The instrument parameters were optimized, including a thermal desorption temperature of 220 °C, a pump speed of 30 %, an APCI ionization voltage of 3900 v, and an injection volume of 6 µL. The samples of bovine urine, feed, sewage, and tissue were selected, and extracted using a solution of methanol:acetonitrile (1:1, v/v), followed by spiking a NT standard solution (1000 ng·mL-1) and ionization through the APCI ion source for detection. The results showed that NT could not be detected in beef and feed due to the complexity of the matrix, while clear signals of NT ions were observed in bovine urine and sewage samples, with LODs of 1000 and 100 ng·mL-1, respectively. Furthermore, quantitative analysis was attempted, and a good linear relationship (R2 = 0.9952) was observed for NT in sewage within the range of 100 to 1000 ng·mL-1. At spiked levels of 100, 500, 1000 and 2000 ng mL-1, the recovery rates ranged from 74.3 % to 92.8 %, with a relative standard deviation (n = 6) of less than 15 %. In conclusion, this detection method offers the advantages of simplicity, rapidity, strong timeliness, and specificity, making it suitable for on-site detection. It can be used for qualitative screening of nandrolone in bovine urine and quantitative analysis of nandrolone in sewage.

A simple aptamer-dye fluorescence sensor for detecting Δ9-tetrahydrocannabinol and its metabolite in urban sewage.

This work developed an aptamer-dye complex as a label-free ratiometric fluorescence sensor for rapid analysis of THC and its metabolite in sewage samples. Integrated with a portable fluorescence capture device, this sensor exhibited excellent sensitivity with visualization of as low as 0.6 µM THC via naked-eye observation, and THC analysis can be accomplished within 4 min, which would be a complementary tool for quantifying THC in sewage samples to estimate cannabis consumption.

A new in situ magnetic method to indicate the source and seasonal diffusion of heavy metal contamination at Qingdao Beach, China.

The accumulation of heavy metals from sewage and garbage dumping can seriously impact beach tourism and thus the local economy, but it is difficult to quickly and accurately determine the pollution location and source of heavy metals and clarify their diffusion range. This study investigates a new in situ magnetic testing method to address this issue. (1) The in situ method can be used to effectively and quickly evaluate heavy metal sources and diffusion ranges based on the distribution of κ values. (2) According to chemical experiments, the specific elements polluting a beach can be determined, such as the Cr, Ni, Zn, and Fe pollution of Beach No. 3. (3) Although κ values for assessing heavy metal pollution on different beaches vary, metal pollution occurs when the higher κ value is more than 50 times the lower κ value on the same beach. (4) The κ values vary in different seasons due to the influence of natural factors and urban seasonal sewage policies.

Profiling wastewater characteristics in intra-urban catchments using online monitoring stations.

This study aims to investigate the differences in intra-urban catchments with different characteristics through real-time wastewater monitoring. Monitoring stations were installed in three neighbourhoods of Barcelona to measure flow, total chemical oxygen demand (COD), pH, conductivity, temperature, and bisulfide (HS-) for 1 year. Typical wastewater profiles were obtained for weekdays, weekends, and holidays in the summer and winter seasons. The results reveal differences in waking up times and evening routines, commuting behaviour during weekends and holidays, and water consumption. The pollutant profiles contribute to a better understanding of pollution generation in households and catchment activities. Flows and COD correlate well at all stations, but there are differences in conductivity and HS- at the station level. The article concludes by discussing the operational experience of the monitoring stations.

Seasonal patterns, fate and ecological risk assessment of pharmaceutical compounds in a wastewater treatment plant with Bacillus bio-reactor treatment.

Pharmaceutical compounds (PhCs) pose a growing concern with potential environmental impacts, commonly introduced into the environment via wastewater treatment plants (WWTPs). The occurrence, removal, and season variations of 60 different classes of PhCs were investigated in the baffled bioreactor (BBR) wastewater treatment process during summer and winter. The concentrations of 60 PhCs were 3400 ± 1600 ng/L in the influent, 2700 ± 930 ng/L in the effluent, and 2400 ± 120 ng/g dw in sludge. Valsartan (Val, 1800 ng/L) was the main contaminant found in the influent, declining to 520 ng/L in the effluent. The grit chamber and BBR tank were substantially conducive to the removal of VAL. Nonetheless, the BBR process showcased variable removal efficiencies across different PhC classes. Sulfadimidine had the highest removal efficiency of 87 ± 17% in the final effluent (water plus solid phase). Contrasting seasonal patterns were observed among PhC classes within BBR process units. The concentrations of many PhCs were higher in summer than in winter, while some macrolide antibiotics exhibited opposing seasonal fluctuations. A thorough mass balance analysis revealed quinolone and sulfonamide antibiotics were primarily eliminated through degradation and transformation in the BBR process. Conversely, 40.2 g/d of macrolide antibiotics was released to the natural aquatic environment via effluent discharge. Gastric acid and anticoagulants, as well as cardiovascular PhCs, primarily experienced removal through sludge adsorption. This study provides valuable insights into the intricate dynamics of PhCs in wastewater treatment, emphasizing the need for tailored strategies to effectively mitigate their release and potential environmental risks.

Nationwide occurrence and discharge mass load of per- and polyfluoroalkyl substances in effluent and biosolids: A snapshot from 75 wastewater treatment plants across Australia.

Wastewater treatment plants (WWTPs) have been recognized as secondary sources of per- and polyfluoroalkyl substances (PFAS) released into the environment. In this study, PFAS concentrations were measured in effluent and biosolids samples collected from 75 WWTPs across Australia during the 2016 Census period, which covers more than half of the Australian population. Twelve PFAS compounds, including six C5-C10 perfluoroalkyl carboxylic acids (PFCAs), four perfluoro sulfonic acids (PFSAs) such as perfluorobutane sulfonate (PFBS), perfuorohexane sulfonic (PFHxS), perfluorooctane sulfonic acid (PFOS), and perfluorodecane sulfonic acid (PFDS), and one fluorotelomer sulfonic acid (6:2 FTS), were detected in the effluent, with concentrations up to 504 ng/L (PFHxS). Among these, perfluorooctanoic acid (PFOA), perfluorohexanoic acid (PFHxA), and perfluoropentanic acid (PFPeA) exhibited the highest median concentrations. In the biosolids, a total of 21 PFAS compounds were detected, encompassing ten C4-C14 PFCAs, four PFSAs, two FTS (6:2 and 8:2 FTS), perfluorooctane sulfonamide (PFOSA), two perfluorooctane sulfonamido acetic acid (NMethyl FOSAA and NEthyl FOSAA), and two perfluorooctane sulfonamido ethanol (FOSE), with dry weight (dw) concentrations approaching 235 ng/g (PFOS). The highest median and mean concentrations were observed for perfluorodecanoic acid (PFDA) and PFOS. An annual discharge of approximately 250 kg of the total 21 PFAS compounds was estimated through the effluent and biosolids of the participating WWTPs. Notably, PFOS and 6:2 FTS constituted the largest proportion of total PFAS in the WWTPs' output. While PFCAs were higher in effluent concentrations compared to influent levels across most WWTPs (92% of WWTPs for ∑8PFCAs), the concentrations of PFSAs either decreased or remained relatively stable (in 80% of WWTPs for ∑4PFSAs) throughout the wastewater treatment process.

Investigating the characteristics of biomass wastes via particle feeder in downdraft gasifier.

Particle feeding plays a crucial role in the gasifier due to its effects on the efficiency and performance metrics of the thermochemical process. Investigating particle size distribution's impact on downdraft gasification reactor performance, this study delves into the significance of feedstock characteristics (moisture, volatile matter, fixed carbon, and ash contents) during the particle feeding stage. Various biomass wastes (date palm waste, olive pomace and sewage sludge) at diverse compositions and sizes are subjected to empirical determination of mass flow rates (MFR), power ratings, and storage times for each feedstock. The preheating process in the gasifier is considered, employing both an approximation and analytical solution. In addition, the influence of the equivalence ratio (ER) on the syngas yield is analyzed. The collected data reveals that for average particle size of 200 µm, the highest MFR (in g/min) are 0.518 ± 0.033, 7.691 ± 0.415, and 16.111 ± 1.050, for palm wood biomass, olive pomace and sewage sludge, respectively. Smaller particles (80 µm) led to extended storage times. Moreover, the lumped capacitance approximation method consistently underestimates preheating time, with a percentage error of 6.26%-17.08%. Response surface methodology (RSM) optimization analysis provides optimal gasification conditions for palm wood biomass, olive pomace, and sewage sludge with maximum cold gas efficiencies (CGEs) of 58.01%, 63.29%, and 52.27%. The peak conversion was attained at gasification temperatures of 1089.83 °C, 1151.93 °C, and 1102.91 °C for palm wood biomass, olive pomace, and sewage sludge, respectively. In addition, gasification equilibrium model determined optimal gasification temperatures as 1150 °C for palm biomass, 1200 °C for olive pomace, and 1150 °C for sewage sludge with respective syngas efficiencies of 59.62%, 64.13%, and 53.66%. Consequently, the examination of the dosing procedure, preheating dynamics, particle dimensions, ER, storage time, and their combined impacts offer practical insights to effectively control downdraft gasifiers in handling a variety of feedstocks.

Intelligent management of carbon emissions of urban domestic sewage based on the Internet of Things.

Domestic wastewater is one of the major carbon sources that cannot be ignored by human society. Against the background of carbon peaking & carbon neutrality (Double Carbon) goals, the continuous urbanization has put heavy pressure on urban drainage systems. Nevertheless, the complex subjective and objective conditions of drainage systems restrict the field monitoring, measurement, and analysis of drainage systems, which has become a great obstacle to the study of carbon emissions from drainage system. In this paper, 3389 sensor terminals of Internet of Things (IoT) are used to build a field monitoring IoT for urban domestic wastewater methane (CH4) carbon emission, with 21 main districts of Chongqing Municipality in China as the study area. Incorporating Fick's law of diffusion, this field monitoring IoT derives a measurement model for methane carbon emissions based on measured concentrations, and solves the problems of long-term and stable monitoring and measurement of methane gas in complex underground environment. With GIS spatio-temporal analysis used to analyze the spatial and temporal evolution patterns of carbon emissions from septic tanks in drainage systems, it successfully reveals the spatial and temporal distribution of methane carbon emissions from drainage systems in different seasons, as well as the relationship between methane carbon emissions from drainage systems and the latitude of direct sunlight. Applying the DTW method, it quantifies the stability of methane monitoring in drainage systems and evaluates the effects of Sampling Frequency (SF) and Number of Devices Terminal (NDT) on the stability of methane monitoring. Consequently, an intelligent management system for carbon emissions from urban domestic wastewater is constructed on the base of IoT, which integrates methane monitoring, measurement and analysis in septic tanks of drainage systems.

New multi-source waste co-incineration and clustering park operating model for small- and medium-sized city: A case study in China.

With improvements in urban waste management to promote sustainable development, an increasing number of waste types need to be sorted and treated separately. Due to the relatively low amount of waste generated in small- and medium-sized cities, separate treatment facilities for each waste type lack scale, waste is treated at a high cost and low efficiency. Therefore, industrial symbiosis principles are suggested to be used to guide collaborative waste treatment system of multi-source solid wastes, and co-incineration is the most commonly used technology. Most existing studies have focused on co-incineration of one certain waste type (such as sludge or medical waste) with municipal solid waste (MSW), but the systematic design and the comprehensive benefits on a whole city and park level have not been widely studied. Taking the actual operation of a multi-source waste co-incineration park in south-central China as an example, this study conducted a detailed analysis of the waste-energy-water metabolism process of MSW, sludge, food waste, and medical waste co-incineration. The environmental and economic benefits were evaluated and compared with the single decentralized waste treatment mode. The results showed that the multi-source waste co-incineration and clustering park operating model was comprehensively superior to the single treatment mode, greenhouse gases and human toxicity indicators were decreased by 11.87% and 295.74%, respectively, and the internal rate of return of the project was increased by 29.35%. This mainly benefits from the synergy of technical system and the economies of scale. Finally, this research proposed policy suggestions from systematic planning and design, technical route selection, and an innovative management mode in view of the potential challenges.

Biochemical responses in Pacific oysters Magallana gigas (Thunberg, 1793): Tools to evaluate the environmental quality of aquaculture areas.

The discharge of sanitary sewage into the bays of the Florianópolis Metropolitan Area (Southern Brazil), has led to the contamination of oyster farms. Consequently, linear alkylbenzenes (LABs) were quantified in the sediment, and the biochemical responses in gills and digestive gland of oysters from six farms were assessed. Our findings revealed elevated levels of LABs in the sediment of the Imaruim and Serraria farms. Additionally, alterations were observed in the antioxidant enzymes: catalase, glutathione peroxidase and superoxide dismutase in both oyster tissue from the Serraria, Santo Antonio de Lisboa and Sambaqui farms. Furthermore, correlation analyses indicated strong and moderate associations between biochemical responses, organic contaminants, and certain physicochemical parameters. Consequently, our results demonstrated the activation of the antioxidant system in oysters, representing a protective response to the presence of sanitary sewage and other contaminants. Therefore, we propose the utilization of biochemical biomarkers for monitoring the environmental quality of farms.

Evaluating the environmental and economic performance of biological and advanced biological wastewater treatment plants by life cycle assessment and life cycle costing.

The primary objective of this study is to assess and establish benchmarks for environmental and economic sustainability of biological and advanced biological wastewater treatment plants (WWTPs) with different treatment technologies and characteristics. Furthermore, the study aims to determine the beneficial role of WWTPs to reduction of eutrophication potential. Environmental and economic sustainability of ten municipal WWTPs was assessed using life cycle assessment (LCA) and life cycle costing (LCC). In the first section of the study, LCA was performed to determine the environmental performance of the WWTPs. Furthermore, net environmental benefit (NEB) approach was implemented to reveal the beneficial role of WWTPs to eutrophication potential. In the subsequent section, LCA-based LCC was conducted by integrating the results of LCA. The most significant environmental impact was determined as marine aquatic ecotoxicity, which is highly affected from the generation and transmission of electricity consumed in the WWTPs. Wastewater recovery and co-incineration of sewage sludge in cement kiln ensure significant environmental savings on ozone layer depletion, human toxicity, acidification, photochemical oxidation, and abiotic depletion (fossil fuel) potential. Considering NEB approach, the highest NEB values were found for the WWTPs with the higher organic load and nutrient concentration in the influent. The results of LCC in WWTPs varied between 0.21 and 0.53 €/m3. External (environmental) costs were evaluated higher than internal (operational) costs for all selected WWTPs. While eutrophication was the highest among environmental costs, electricity cost was the highest among operational costs for almost all WWTPs.