Ultrafiltration fractionation of potentially inhibitory substances of hydrothermal liquefaction aqueous phase derived from municipal sludge.

Hydrothermal liquefaction (HTL) is a promising thermo-chemical technology for municipal sludge treatment due to its potential for biocrude oil recovery and minimizing biosolids management costs. However, the process generates a high volume of an aqueous byproduct that needs to be treated due to its high chemical oxygen demand (COD) and various organic and inorganic compounds. Although the aqueous phase is known to contain recalcitrant and potentially inhibitory substances that may affect its biological treatment, their molecular weight distribution (MwD) and its impact on anaerobic biodegradability are poorly understood. Ultrafiltration (UF) was conducted to fractionate HTL aqueous into different molecular weight (Mw) fractions using 300, 100, 10, and 1 kDa membranes. Mesophilic biochemical methane potential (BMP) assays were conducted to assess the anaerobic biodegradability of each fraction, and the first-order model was used to calculate the degradation kinetics of potential inhibitory compounds. The highest percentage of organics (65 %) was found in the Mw<1 kDa range, whereas the 10>Mw>1 kDa had the lowest percentage (8 %). There was no significant difference in the cumulative specific methane produced from various Mw fractions (p>0.05). The Mw<1 kDa fraction had the highest first-order specific methane production rate (0.53 day-1), whereas the unfiltered HTL had the lowest (0.38 day-1). Although UF fractionation increased the rate of anaerobic degradation of HTL aqueous for the Mw<1 kDa fraction, the observed methane potential was only 55 % of the theoretical value. This implies that 45 % of COD remains undegraded even after permeation through the lowest Mw cut-off membrane. Therefore, further characterization of HTL aqueous is needed for compounds with molecular weights below 1 kDa to fully understand the nature of inhibitory organics and their impact on anaerobic digestion. Furthermore, pretreatments utilizing techniques such as adsorption and advanced oxidation may be necessary to enhance the specific methane yields from various HTL aqueous fractions, thereby bringing them closer to the theoretical yield.

Post-treatment of high-rate activated sludge effluent via zeolite adsorption and recovery of ammonium-nitrogen as alternative fertilising products.

This study investigates the potential to connect nutrient flows between wastewater treatment and agriculture through a two-stage nitrogen (N) recovery system composed of high-rate activated sludge treatment in contact stabilisation mode (HRAS/CS) and column adsorption with zeolite. The HRAS/CS process removes organic matter and suspended solids in wastewater, leaving N behind in the effluent. The N was then successfully recovered with the zeolite column under different scenarios, generating N and K-rich by-products. The regeneration effluent from the zeolite column with KCl contained 60-845 mg NH4+-N/L and 1.6-14.3 g K/L, having potential for use as fertigation water. The N-saturated zeolite contained 1.5-8.4 mg N/g and 14.3-19.3 mg K/g of the product fresh weight and low contaminant content, making them potentially eligible as various fertilising products. Adsorption can thus concentrate N from HRAS/CS effluent and produce by-products with potential agricultural value while meeting chemical oxygen demand and total nitrogen discharge standards.

Effects of carbonization temperature and time on the characteristics of carbonized sludge.

To investigate the influence of carbonization process parameters on the characteristics of municipal sludge carbonization products, this study selected carbonization temperatures of 300-700 °C and carbonization times of 0.5-1.5 h to carbonize municipal sludge. The results showed that with an increase in temperature and carbonization time, the sludge was carbonized more completely, and the structure and performance characteristics of the sludge changed significantly. Organic matter was continuously cracked, the amorphous nature of the material was reduced, its morphology was transformed into an increasing number of regular crystalline structures, and the content of carbon continued to decrease, from the initial 52.85 to 38.77%, while the content of inorganic species consisting continued to increase. The conductivity was reduced by 87.8%, and the degree of conversion of salt ions into their residual and insoluble states was significant. Natural water absorption in the sludge decreased from 8.13 to 1.29%, and hydrophobicity increased. The dry-basis higher calorific value decreased from 8,703 to 3,574 kJ/kg. Heavy metals were concentrated by a factor of 2-3, but the content of the available state was very low. The results of this study provide important technological support for the selection of suitable carbonization process conditions and for resource utilization.

Metal-phenolic network as precursor complex coating for forward osmosis membrane with enhanced antifouling property.

In this study, a multi-functional layer was developed based on the commercially available cellulose triacetate (CTA) forward osmosis (FO) membrane to improve its antifouling property. Tannic acid/ferric ion (TA/Fe3+) complexes were firstly coated as a precursor layer on the membrane surface via self-assembly. Afterwards, the tannic acid/diethylenetriamine (TA/DETA) hydrophilic functional layer was further coated, following Ag/polyvinylpyrrolidone (PVP) anti-bacterial layer was formed in situ through the reducibility of TA to obtain TA/Fe3+-TA/DETA-Ag/PVP-modified membrane. The optimized precursor layer was acquired by adjusting the buffer solution pH to 8, TA/Fe3+ ratio to 4 and the number of self-assembled layers to 5. The permeability testing results illustrated that the functional layer had an insignificant effect on the membrane transport parameters. The TA/Fe3+-TA/DETA-Ag/PVP-modified membrane simultaneously exhibited excellent physical and chemical stability. The coated membrane also demonstrated enhanced anti-bacterial properties, achieving 98.63 and 97.30% inhibition against Staphylococcus aureus and Escherichia coli, respectively. Furthermore, the dynamic fouling experiment showed a 12% higher water flux decrease for the TA/Fe3+-TA/DETA-Ag/PVP CTA membrane compared to the nascent CTA membrane, which proved its excellent antifouling performance. This work provides a feasible strategy to heighten the antifouling property of the CTA FO membrane.

Integrating Advanced Techniques and Machine Learning for Landfill Leachate Treatment: Addressing Limitations and Environmental Concerns.

This review article explores the challenges associated with landfill leachate resulting from the increasing disposal of municipal solid waste in landfills and open areas. The composition of landfill leachate includes antibiotics (0.001 to 100 µg), heavy metals (0.001 to 1.4 g/L), dissolved organic and inorganic components, and xenobiotics including polyaromatic hydrocarbons (10-25 µg/L). Conventional treatment methods, such as biological (microbial and phytoremediation) and physicochemical (electrochemical and membrane-based) techniques, are available but face limitations in terms of cost, accuracy, and environmental risks. To surmount these challenges, this study advocates for the integration of artificial intelligence (AI) and machine learning (ML) to strengthen treatment efficacy through predictive analytics and optimized operational parameters. It critically evaluates the risks posed by recalcitrant leachate components and appraises the performance of various treatment modalities, both independently and in tandem with biological and physicochemical processes. Notably, physicochemical treatments have demonstrated pollutant removal rates of up to 90% for various contaminants, while integrated biological approaches have achieved over 95% removal efficiency. However, the heterogeneous nature of solid waste composition further complicates treatment methodologies. Consequently, the integration of advanced ML algorithms such as Support Vector Regression, Artificial Neural Networks, and Genetic Algorithms is proposed to refine leachate treatment processes. This review provides valuable insights for different stakeholders specifically researchers, policymakers and practitioners, seeking to fortify waste disposal infrastructure and foster sustainable landfill leachate management practices. By leveraging AI and ML tools in conjunction with a nuanced understanding of leachate complexities, a promising pathway emerges towards effectively addressing this environmental challenge while mitigating potential adverse impacts.

Forecasting municipal solid plastic waste generation and management policy using system dynamics: a case study of Khulna City in Bangladesh.

A comprehensive analysis of municipal solid plastic waste (MSPW) management while emphasizing plastic pollution severity in coastal cities around the world is mandatory to alleviate the augmenting plastic waste footprint in nature. Thus, decision-makers' persuasion for numerous management solutions of MSPW flow-control can be met through meditative systematic strategies at the regional level. To forecast solutions focused on systematic policies, an agent-based system dynamics (ASD) model has been developed and simulated from 2023 to 2040 while considering significant knit parameters for MSPW management of Khulna City in Bangladesh. Baseline simulation results show that per-capita plastic waste generation will increase to 11.6 kg by 2040 from 8.92 kg in 2023. Eventually, the landfilled quantity of plastic waste has accumulated to 70,000 tons within 18 years. Moreover, the riverine discharge has increased to 834 tons in 2040 from a baseline quantity of 512 tons in 2023. So the plastic waste footprint index (PWFI) value rises to 24 by 2040. Furthermore, the absence of technological initiatives is responsible for the logarithmic rise of non-recyclable plastic waste to 1.35*1000=1350 tons. Finally, two consecutive policy scenarios with baseline factors such as controlled riverine discharge, increased collection and separation of plastic waste, expansion of recycle business, and locally achievable plastic conversion technologies have been simulated. Therefore, policy 2, with 69% conversion, 80% source separation, and 50% riverine discharge reduction of MSPW, has been found adequate from a sustainability perspective with the lowest PWFI ranges of 3.97 to 1.07 alongside a per-capita MSPW generation of 7.63 to 10 kg from 2023 till 2040.

Municipal pipeline networks as preferential vapor intrusion pathways: A review.

Recent reports show a rise in instances where municipal networks, such as sewer lines, serve as pathways for vapor intrusion (VI), enabling volatile organic compounds (VOCs) vapors to travel along these networks. These VOCs pose potential health risks to occupants of buildings connected to these networks. Currently, there's a lack of specific technical or regulatory guidance on identifying and assessing the VI risk associated with sewer as preferential VI pathways. This critical review summarizes key findings from studies and site investigations related to sewer VI pathways. These findings cover background VOCs concentration levels in sewers, updates to site conceptual models, advances in sewer sampling techniques, innovative tools for identifying and characterizing sewer VI, and practices for assessing and mitigating sewer VI risk. While significant improvements have been made towards understanding how municipal pipeline networks act as VI pathways, more research is still needed to develop strategies for investigating sites and assessing risks associated with "pipeline VI pathways". Future research could focus on the development of "pipeline VI pathways" data set, the improvement and validation of investigation tools, and improving the understanding of VOCs transportation mechanisms within these "pipeline VI pathways".

Artificial Intelligence in enhancing sustainable practices for infectious municipal waste classification.

This research paper focuses on effective infectious municipal waste management in urban settings, highlighting a dearth of dedicated research in this domain. Unlike general or specific waste types, infectious waste poses distinct health and environmental risks. Leveraging advanced artificial intelligence techniques, we prioritize infectious waste categorization and optimization, integrating metaheuristics into optimization methods to create a robust dual-ensemble framework. Our model, the "Enhanced Artificial Intelligence for Infectious Municipal Waste Classification System," combines ensemble image segmentation methods and diverse convolutional neural network models. Innovative geometric image augmentation enhances model robustness, diversifies training data, and improves accuracy across waste types. A pivotal aspect is the integration of a reinforcement learning-differential evolution algorithm as a decision fusion strategy, optimizing classification by harmonizing outputs from ensemble methods and convolutional neural network models. Computational results, using a newly collected dataset, demonstrate our model's accuracy exceeding 96.54% while using the existing solid waste dataset we achieve the accuracy of 97.81%, outperforming advanced approaches by margins ranging from 2.02% to 8.80%. This research significantly advances sustainable waste management, showcasing artificial intelligence's transformative potential in addressing intricate waste challenges. It establishes a foundational framework prioritizing efficiency, effectiveness, and sustainability for future waste management solutions. Acknowledging the importance of diverse datasets, customization for urban contexts, and practical integration into existing infrastructures, our work contributes to the broader discourse on the role of artificial intelligence in evolving waste management practices.

Laboratory investigation and prediction of permeability of fresh to five-year-old municipal solid wastes of low and high food contents.

The permeability of municipal solid wastes (MSWs) is important for the design and operation of landfills. This study presented the experimental investigation of the permeability of low food content- (LF-) and high food content- (HF-) MSWs prepared in laboratory-scale bioreactors for up to 5 years. The permeability of MSWs with diverse degrees of decomposition (DOBs), void ratios, and permeation liquids was measured (288 tests). The measured permeability was compared to that predicted from the (modified) Kozeny-Carman (K-C) equations in four different forms. The results indicated that the permeability of both LF- and HF-MSWs decreased significantly (p < 0.05) with decomposition under a given void ratio. The predicted permeability using the original K-C equation fitted well with that of fresh MSWs. The permeability of decomposed MSWs was closer to the predicted results using the modified K-C equation with the effective void ratio. This can be attributed to the increase in the fine fractions due to degradation. The reduction in the effective voids was more significant with HF-MSWs. The parameters required in the (modified) K-C equations showed a good correlation with DOB and effective particle size (d10). The predicted permeability based on the relationship between DOB (or d10) and equation parameters was within 3 times the difference compared to the measured values. The above results indicated that the modified K-C equation can be adopted to predict the permeability of fresh and degraded MSWs while more field-scale experiments should be conducted to further evaluate its feasibility.

Investigation of heavy metals uptake in root-shoot of native plant species adjoining wastewater channels.

Metal pollution in water, soil, and vegetation is an emerging environmental issue. Therefore, this study investigated the abundance of heavy metals (HMs) within roots and shoots of native plant species i.e., Bromus pectinatus, Cynodon dactylon, Poa annua, Euphorbia heliscopa, Anagallis arvensis, and Stellaria media grown in the adjoining area of municipal wastewater channels of a Pakistani city of Abbottabad. HMs concentrations (mg L-1) in municipal wastewater were: chromium (Cr) (0.55) > nickel (Ni) (0.09) > lead (Pb) (0.07) > cadmium (Cd) (0.03). Accumulation of HMs in both roots and shoots of plant species varied as B. pectinatus > C. dactylon > P. annua > E. heliscopa > A. arvensis > S. media. Irrespective of the plant species, roots exhibited higher concentrations of HMs than shoots. Higher amount of Cr (131.70 mg kg-1) was detected in the roots of B. pectinatus and the lowest amount (81 mg kg-1) in A. arvensis, Highest Cd concentration was found in the shoot of B. pectinatus and the lowest in the E. heliscopa. The highest concentration of Ni was found in the roots of S. media (37.40 mg kg-1) and the shoot of C. dactylon (15.70 mg kg-1) whereas the lowest Ni concentration was achieved in the roots of A. arvensis (12.10 mg kg-1) and the shoot of E. heliscopa (5.90 mg kg-1). The concentration of HMs in individual plant species was less than 1000 mg kg-1. Considering the higher values (> 1) of biological concentration factor (BCF), biological accumulation co-efficient (BAC), and translocation factor (TF), B. pectinatus and S. media species showed greater potential for HMs accumulation than other species. Therefore, these plants might be helpful for the remediation of HM-contaminated soil.

Dissemination of antimicrobial resistance in agricultural ecosystems following irrigation with treated municipal wastewater.

The spread of antimicrobial resistance (AMR) in agricultural systems via irrigation water is a serious public health issue as it can be transmitted to humans through the food chain. Therefore, understanding the dissemination routes of antibiotic resistance genes (ARGs) in agricultural systems is crucial for the assessment of health risks associated with eating fresh vegetables such as spinach and radish irrigated with treated municipal wastewater (TMW). In this study, we investigated the bacterial community structure and resistome in the soil-plant-earthworm continuum after irrigation of spinach and radish with TMW containing the antibiotics trimethoprim (TMP), sulfamethoxazole (SMZ), and sulfapyridine (SPD) using 16S rRNA gene sequencing and high throughput quantitative PCR (HT-qPCR). The study was conducted in two phases: Phase I involved eight weeks of spinach and radish production using TMW for irrigation, whereas Phase II entailed three weeks of earthworm exposure to contaminated plant material obtained in Phase I. The 16S data indicated that the rhizosphere bacterial community composition and structure were more resilient to antibiotic residuals in the irrigated water, with radish showing less susceptibility than spinach than those of bulk soils. The HT-qPCR analysis revealed that a total of 271 ARGs (out of 285) and 9 mobile genetic elements (MGEs) (out of 10) were detected in all samples. Higher diversity and abundance of ARGs were observed for samples irrigated with higher concentrations of antibiotics in both spinach and radish treatments. However, compared to spinach, radish ARG dynamics in the soil biome were more stable due to the change of antibiotic introduction to the soil. At the class level, multi-drug resistance (MDR) class was altered significantly by the presence of antibiotics in irrigation water. Compared to earthworm fecal samples, their corresponding soil environments showed a higher number of detected ARGs, suggesting that earthworms could play a role in reducing ARG dissemination in the soil environments. These findings will not only provide insight into the dissemination of ARGs in agricultural environments due to antibiotic residuals in irrigated water but could help understand the potential human health risks associated with ARGs.

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.

Characteristics and management of municipal solid waste in Uyo, Akwa Ibom state, Nigeria.

Increased urbanization and population lead to increased consumption of manufactured goods. This ultimately results in increased production of waste. Identifying its composition is crucial for planning an effective solid waste management strategy. This study assesses the characteristics and composition of the waste generated within the Uyo Capital City Development Area of Akwa Ibom State, Nigeria. This is to aid in developing a scientifically supported waste management pilot system for the state. Direct waste sorting and characterization were conducted on the municipal solid waste arriving at the landfill during the study period. Over 50% of the generated wastes are recyclables and composed of plastics, metals, and paper, while the fraction of organic waste is over 30%. Similarly, the waste generation per capita is 1.34 kg/person/day, while the generation forecast over the next ten years is estimated to increase by approximately 40%. Furthermore, over 9,000 surveys were completed by residents to establish a problem statement about the existing waste collection and disposal system, and possible solutions. Importantly, a majority of survey respondents were willing to source-separate their wastes and supported paying a fee for adequate waste collection. This strongly indicates that an integrated waste management system could be established to generate value from the collected waste. Supplementary revenue can be generated through composting, recycling, and land reclamation.

Utilizing anaerobic substrate distribution for growth of aerobic granular sludge in continuous-flow reactors.

The development of continuous flow reactors (CFRs) employing aerobic granular sludge (AGS) for the retrofit of existing wastewater treatment plants (WWTPs) using a continuous-flow activated sludge (CFAS) system has garnered increasing interest. This follows the worldwide adoption of AGS technology in sequencing batch reactors (SBRs). The better settleability of AGS compared to AS allows for process intensification of existing wastewater treatment plants without the difficult conversion of often relatively shallow CFRs to deeper AGS-SBRs. To retrofit existing CFAS systems with AGS, achieving both increased hydraulic capacity and enhanced biological nutrient removal necessitates the formation of granular sludge based on the same selective pressures applied in AGS-SBRs. Previous efforts have focussed mainly on the selective wasting of flocculent sludge and retaining granular sludge to drive aerobic granulation. In this study a pilot-scale CFR was developed to best mimic the implementation of the granulation mechanisms of full-scale AGS-SBRs. The pilot-scale reactor was fed with pre-settled municipal wastewater. We established metrics to assess the degree to which the proposed mechanisms were implemented in the pilot-scale CFR and compared them to data from full-scale AGS-SBRs, specifically with respect to the anaerobic distribution of granule forming substrates (GFS). The selective pressures for granular sludge formation were implemented through inclusion of anaerobic upflow selectors with a water depth of 2.5 meters, which yielded a sludge with properties similar to AGS from full-scale SBRs. In comparison to the CFAS system at Harnaschpolder WWTP treating the same pre-settled wastewater, a more than twofold increase in volumetric removal capacity for both phosphorus and nitrogen was achieved. The use of a completely mixed anaerobic selector, as opposed to an anaerobic upflow selector, caused a shift in EBPR activity from the largest towards the smallest size class, while nitrification was majorly unaffected. Anaerobic selective feeding via bottom-feeding is, therefore, favorable for the long-term stability of AGS, especially for less acidified wastewater. The research underlines the potential of AGS for enhancing the hydraulic and biological treatment capacity of existing CFAS systems.

Reduction of heavy metals in municipal solid waste incineration fly ash followed by making transparent glass.

Municipal solid waste incineration (MSWI) fly ash is a hazardous waste containing heavy metals. Secondary aluminum dross (SAD) is a hazardous waste discharged from aluminum smelting, containing active aluminum nitride (AlN). In this work, heavy metals from MSWI fly ash were reduced into alloy by AlN from SAD, and the slag was manufactured into transparent glass for building. Reduction of iron and zinc was 67 and 100 %, respectively. Reduction mechanism was explored after applying XRD, XRF and thermodynamics analysis. It was found that the reduction reaction was an ion reaction. The AlN and heavy metal oxide transformed into anionic group containing nitrogen and heavy metal cation, after entering slag. The heavy metals were reduced into alloy after electron was transferred from anionic group to cation. In addition, the reduced iron and zinc could merge into alloy, which inhibited evaporation of zinc. Yellow transparent glass was obtained after the reduction process. Yellow was come from titanium oxide, which could not be reduced by AlN. Microhardness, density and water absorption of the transparent glass were 741 HV, 2.86 g·cm-3 and 0.04 %, respectively. Leaching content of Ni, Cu, Zn and Pb of the glass were 0.1, <0.1, 0.6 and < 0.1 mg/L, respectively, all below the TCLP limit. About 115 âˆ¼ 213 dollars were earned after manufacturing 500 kg of MSWI fly ash into transparent glass. This work provided a novel idea of recycling solid waste into alloy and transparent glass for building.

Microbiologically induced calcite precipitation (MICP) in situ remediated heavy metal contamination in sludge nutrient soil.

Microbiologically induced calcite precipitation (MICP), as a newly developing bioremediation technology, could redeem heavy metal contamination in diverse scenarios. In this study, MICP bacterium Sporosarcina ureilytica ML-2 was employed to suppress the pollution of Pb, Cd and Zn in municipal sludge nutrient soil. After MICP remediation, the exchangeable Cd and Zn in sludge nutrient soil were correspondingly reduced by 31.02 % and 6.09 %, while the carbonate-bound Pb, Cd and Zn as well as the residual fractions were increased by 16.12 %, 6.63 %, 13.09 % and 6.10 %, 45.70 %, 3.86 %, respectively. In addition, the extractable Pb, Cd and Zn either by diethylenetriaminepentaacetic acid (DTPA) or toxicity characteristic leaching procedure (TCLP) in sludge nutrient soil were significantly reduced. These results demonstrated that the bio-calcite generated via MICP helped to immobilize heavy metals. Furthermore, MICP treatment improved the abundance of functional microorganisms related to urea cycle, while reduced the overall abundance of metal resistance genes (MRGs) and antibiotic resistance genes (ARGs). This work confirmed the feasibility of MICP in remediation of heavy metal in sludge nutrient soil, which expanded the application field of MICP and provided a promising way for heavy metal pollution management.

Efficient nitrogen removal from municipal wastewater using an integrated fixed-film activated sludge process in a novel air-lifting loop reactor: A pilot-scale demonstration.

A novel air-lifting loop reactor combines anoxic, oxic, and settling zones to achieve organic and nutrient removal, as well as solid-liquid separation. To address sludge settling ability and operation stability issues caused by low dissolved oxygen in aerobic zones, this study proposes using modified polypropylene carriers to establish a fixed-film activated sludge (IFAS) system. A pilot-scale demonstration of the IFAS-based air-lifting loop reactor is conducted, and the results show successful operation for approximately 300 days. The pilot-scale reactor achieves a maximum aerobic granulation ratio of 16% in the bulk liquid. The IFAS system contributes to efficient removal of organic matter (96%) and nitrogen (94%) by facilitating simultaneous nitrification and denitrification, as well as fast solid-liquid separation with a low sludge volume index of 34 mL/g. Microbial analysis reveals enrichment of functional bacteria involved in nitrification, denitrification, and flocculation throughout the operation process.

Characteristics of humification, functional enzymes and bacterial community metabolism during manganese dioxide-added composting of municipal sludge.

The aim of this study was to assess effects of MnO2 addition (CK-0%, T1-2% and T2-5%) on humification and bacterial community during municipal sludge (MS) composting. The results suggested that MnO2 addition inhibited the growth of Nitrospira but stimulated Nonomuraea, Actinomadura, Streptomyces and Thermopolyspora, facilitating the lignocellulose degradation and humification with the increase in organic matter degradation by 13.8%-19.2% and humic acid content by 10.9%-20.6%. Compared to CK, the abundances of exoglucanase (EC:3.2.1.91), endo-1,4-beta-xylanase (EC:3.2.1.136) and endomannanase (EC:3.2.1.78) increased by 88-99, 52-66 and 4-15 folds, respectively. However, 5%-MnO2 induced the enrichment of Mizugakiibacter that harms the environment of agricultural production. The addition of 2%-MnO2 was recommended for MS composting. Furthermore, metabolic function analysis indicated that MnO2 addition altered amino acid and carbohydrate metabolism, especially enhancing propanoate metabolism and butanoate metabolism but inhibiting citrate cycle. Structural equation modeling revealed that Nonomuraea and Actinomadura were the main drivers for lignocellulose degradation. This study provided theoretical guidance in regulating humification via MnO2 for MS composting.

Intelligent technologies powering clean incineration of municipal solid waste: A system review.

Cleanliness has been paramount for municipal solid waste incineration (MSWI) systems. In recent years, the rapid advancement of intelligent technologies has fostered unprecedented opportunities for enhancing the cleanliness of MSWI systems. This paper offers a review and analysis of cutting-edge intelligent technologies in MSWI, which include process monitoring, intelligent algorithms, combustion control, flue gas treatment, and particulate control. The objective is to summarize current applications of these techniques and to forecast future directions. Regarding process monitoring, intelligent image analysis has facilitated real-time tracking of combustion conditions. For intelligent algorithms, machine learning models have shown advantages in accurately forecasting key process parameters and pollutant concentrations. In terms of combustion control, intelligent systems have achieved consistent prediction and regulation of temperature, oxygen content, and other parameters. Intelligent monitoring and forecasting of carbon monoxide and dioxins for flue gas treatment have exhibited satisfactory performance. Concerning particulate control, multi-objective optimization facilitates the sustainable utilization of fly ash. Despite remarkable progress, challenges remain in improving process stability and monitoring instrumentation of intelligent MSWI technologies. By systematically summarizing current applications, this timely review offers valuable insights into the future upgrade of intelligent MSWI systems.

Solving the waste bin location problem with uncertain waste generation rate: A bi-objective robust optimization approach.

An efficient municipal solid waste (MSW) system is critical to modern cities in order to enhance sustainability and liveability of urban life. With this aim, the planning phase of the MSW system should be carefully addressed by decision makers. However, planning success is dependent on many sources of uncertainty that can affect key parameters of the system, for example, the waste generation rate in an urban area. With this in mind, this article contributes with a robust optimization model to design the network of collection points (i.e. location and storage capacity), which are the first points of contact with the MSW system. A central feature of the model is a bi-objective function that aims at simultaneously minimizing the network costs of collection points and the required collection frequency to gather the accumulated waste (as a proxy of the collection cost). The value of the model is demonstrated by comparing its solutions with those obtained from its deterministic counterpart over a set of realistic instances considering different scenarios defined by different waste generation rates. The results show that the robust model finds competitive solutions in almost all cases investigated. An additional benefit of the model is that it allows the user to explore trade-offs between the two objectives.