For wastewater treatment, the integrated process of anammox-based nitrogen removal and Fe addition-based phosphorus (P) removal is a promising option, and it results in the discharge of iron-containing surplus sludge (ICS), which has the potential for conducting P recovery or inoculating a new anammox-based process. Given that Fe in biological reactors can mediate the microbial community, it is inferred that the startup of the novel anammox-based process using ICS as inoculum will experience complex microbial succession and shifts of nitrogen metabolic pathways. Therefore, this study systematically investigated the transformation of nitrogen metabolic pathways and microbial community dynamics during the eight-month startup of a one-stage partial nitritation/anammox (PNA) reactor inoculated with ICS under the Fe-free influent condition. The results suggested that PNA co-occurred with putative Fe(III) reduction coupled with anammox (Feammox) and potential nitrate-dependent ferrous oxidation (NDFO) during the early-to-mid phases, coinciding with the natural loss of iron from ICS. The system finally stabilized under the PNA-dominated nitrogen removal pathway with the nitrogen removal efficiency and nitrogen removal rate of 82.9 +/- 2.1% and 0.87 +/- 0.02 kg/m3/d, respectively. Ammonia-oxidizing bacteria (Nitrosomonas), anammox bacteria (Candidatus_ Kuenenia), iron-reducing bacteria (Ferruginibacter), and iron-oxidizing bacteria (Denitratisoma) were the main functional bacteria in dynamic microbial community. In all, this study gives a theoretical reference for the utilization of ICS as inoculum for the startup of anammox-based process in application.

The structural failure, blockage, corrosion and harmful gas risks faced by sewer systems affect the safety of the water environment and the health of residents.

Rural wastewater management stands at the nexus of public health, environmental stewardship, and climate resilience. Addressing the growing demand for sustainable sanitation in decentralized contexts, this study presents a multi-objective optimization framework that integrates classical process modeling with machine learning to enhance the performance of bio-ecological treatment systems. By coupling the Activated Sludge Model with a fully connected neural network, our integrated approach provides near real-time decision support for meeting stringent discharge standards and agricultural reuse requirements. The framework demonstrates strong predictive capability, achieving coefficients of determination (R2) of 0.860, 0.854, 0.879, and 0.871 for CODCr, NH4+-N, TN, and TP, respectively, on an independent validation dataset. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is incorporated to guide adaptive aeration strategies. Results indicate an energy reduction of 1.19 kWh/day under high-standard discharge mode and a nutrient retention benefit of 22.5 g/day of ammonia nitrogen under irrigation reuse mode, thereby supporting circular nutrient flows. This work offers a scalable and resilient pathway toward low-carbon, resource-recovering sanitation in rural areas by combining data-driven control with ecological design, contributing to sustainable development and climate adaptation goals.

Decentralized sewage treatment systems (DSTSs) are essential for ensuring rural areas with weak infrastructure, but concerns about their sustainability have been raised due to indirect carbon emissions from electricity consumption. Hybrid renewable energy systems (HRESs) present an attractive alternative to grid electricity by integrating intermittent renewable energy sources, such as solar and wind power, with energy storage devices to provide a stable and reliable power supply. Nevertheless, the practical implementation of HRESs in DSTSs has yet to be validated, particularly in extreme climatic conditions. This study offers a comprehensive evaluation of the one-year technical performance, environmental impact, and economic feasibility of a DSTSs powered by HRES in a cold rural area of Inner Mongolia. The results indicate that the HRES-driven DSTS can effectively remove pollutants, consistently meeting local discharge standards throughout the year, with an energy utilization efficiency of 91.17%. Life cycle analysis reveals that the carbon emission intensity of the HRES is 248.91 g CO2-eq/ kWh, which is only 6.68 years longer than that of the traditional grid-driven system. Economically, although the initial investment is 97.75% higher than that of the grid mode, the 25-year life cycle cost is reduced by 17.65%, with an energy cost of 0.9058 CNY/kWh. These findings underscore the significant potential of HRES in enhancing the sustainability of DSTSs and its compatibility with carbon neutrality goals, providing viable solutions for sewage treatment in regions worldwide with limited or no grid access.

The management of rural sewage faces significant challenges due to the dispersed settlements and inadequate infrastructure characteristics of rural areas. One sustainable management solution is to use constructed wetlands (CWs); however, traditional systems that rely on specific functional plants incur large maintenance costs. This study investigates an innovative approach that integrates native plants (Aster subulatus and Pterodactylus sp.) with functional plants (Arundo donax) in a horizontal subsurface CW (HSCW) to establish a self-sustaining symbiotic system that does not require human intervention. Over 365 days, the HSCW met stringent discharge standards by achieving mean removal efficiencies of 35.05% for chemical oxygen demand (CODCr), 48.92% for ammonium nitrogen (NH4+-N), 40.57% for total nitrogen (TN), and 27.61% for total phosphorus (TP). Microbial analysis identified Proteobacteria (34%), Actinobacteria (26%), and Bacteroidota (12%) as the dominant phyla, with rhizosphere communities influenced by plant-specific exudates and seasonal variations. Key nitrogen metabolism genes (nirB, nirD, nrfH) and genes coding for phosphorus-related enzymes (ppk, phoD) demonstrated seasonal adaptability driven by temperature fluctuations and plant–microbe interactions. Metagenomic sequencing revealed synergistic pathways, including nitrification-denitrification, dissimilatory nitrate reduction to ammonium (DNRA), and polyphosphate synthesis, which contributed to pollutant removal. Native plant polyculture enhanced microbial diversity and stability and reduced reliance on artificial maintenance. These findings demonstrate that leveraging natural plant symbiosis in CWs enhances ecological and economic sustainability by promoting microbial resilience and self-regulating nutrient cycling. Overall, CWs offer a viable strategy for decentralized sewage treatment in rural locations or any areas characterized by scattered settlements and poor infrastructure.

Activated sludge models (ASMs), the most widely used mathematical models for biological wastewater treatment, offer a simplified matrix-based representation of pollutant biochemical degradation. As understanding of wastewater treatment mechanisms has advanced, the simplifying assumptions of general ASMs have proven unreasonable under certain conditions, prompting their improvement. Existing reviews often focus on the specific application of ASMs, with limited comprehensive analyses of their multi-dimensional extensions and cross-model integrations. This review provides the first systematic overview of the latest developments in ASMs, focusing on model mechanism extension and multi-scale model integration. In terms of mechanism extension, the incorporation of new theories and secondary reaction has enhanced the accuracy of models in simulating membrane bioreactor systems, phosphorus removal, and industrial wastewater treatment. It has also quantified the generation and dissipation pathways of N2O and provided a basis for sludge reduction and sedimentation control. Regarding model integration, this review focuses on the coupling interfaces between ASMs and other models, such as anaerobic reaction models, convection-diffusion theory, hydrodynamic models, and machine learning. These coupled models enable full-scale simulation from micro-level biochemical reactions to macro-level environmental dynamics. Finally, the review emphasizes that future ASMs developments should focus on improving mechanisms and addressing emerging contaminants. It highlights that integrating artificial intelligence can serve as a key tool to balance model accuracy and parameter identifiability. The present review aims to establish a systematic research framework for ASMs, analyze the limitations of existing models, and ultimately provide insights for enhancing the precision and application of ASMs in wastewater treatment.

Airborne seed hairs released by poplar (Populus spp.) and willow (Salix spp.) during the fruiting period serve as unique carriers of biological particles, transporting substantial quantities of pollen-related plant materials and bacteria. However, its quantitative contribution to human allergenic and toxic risks relative to atmospheric particulate matter during the same period remains unclear. This study collected airborne seed hairs and PM2.5 simultaneously from urban and suburban areas in Hohhot, China, during May 2-8, 2025. We conducted the first quantitative comparison of the allergenic risks induced by pollen and bacteria based on specific immunoglobulin E (sIgE), and evaluated the toxic equivalent quantity of full-volatile organic compounds (FVOCs) and non-carcinogenic risks of heavy metals in seed hairs and PM2.5. The pollen and bacterial loads per unit mass of airborne seed hairs are 13.1 ± 12.1 and 92.9 ± 55.2 times higher than concurrent PM2.5, resulting in corresponding sIgE levels in airborne seed hairs that are 14.9 ± 13.5 and 124.0 ± 39.0 times higher than those in PM2.5. Pollen dominates the total allergenic risk in both carriers, accounting for 99.08% in airborne seed hairs and 99.89% in PM2.5, while the Salicaceae and Fabaceae as key pollen, respectively. However, the toxicity of FVOCs (dominated by semi-volatile organic compounds) and heavy metals in PM2.5 exceed 43754.2 ± 41130.6 and 41.8 ± 19.6 times greater than airborne seed hairs. We emphasize that airborne seed hairs should be incorporated as an independent seasonal high-risk factor into air quality exposure assessment and public health management.

The collection, treatment, and recycling of rural greywater are of significant importance. However, research on pollutant removal and clogging in filter media remains insufficient. This gap hinders the development of related technologies and the effective management of greywater. To solve the above problems, this study established a single-household rural greywater collection and treatment integrated device loaded with different fillers (corn straw, red brick, and sand filler). The pollutant removal capacity and clogging process were investigated, and their mechanism was discussed. The results indicated that the device had obvious removal effects on chemical oxygen demand (43.91 +/- 15.71%) and suspended solids (32.56 +/- 19.85%). The clogging process of the device was characterized by permeability coefficient, whose decrease rate was 0.18-0.31 cm/s/d. The clogging material was mainly inorganic and relatively large in the upstream filler. Bacteria secreting extracellular substances, such as Acidovorax, was also observed and may have further contributed to pore reduction and clogging development. Flipping effectively restored the permeability coefficient of the filler, thereby contributing to the temporary alleviation of system clogging. In general, this study provided an effective method for the collection and treatment of rural greywater and expounded on the development process and occurrence mechanism of clogging.

Rural domestic sewage management is a crucial pathway for achieving Sustainable Development Goal (SDG) 6 targets. Addressing the crucial challenge of prioritizing administrative villages for rural domestic sewage treatment at the county scale requires dedicated planning. However, county-level comprehensive evaluation models designed specifically for this purpose are currently limited. To address this gap, we developed a model based on 13 evaluation indicators encompassing village distribution characteristics, villager demographics, rural economic levels, and sanitation facility conditions. To gauge the varying emphasis on these factors by different groups, a questionnaire survey was conducted among experts, enterprises, and government departments involved in the rural sewage sector in China. Two counties from distinct regions were then chosen to validate these models. The Analytic Hierarchy Process (AHP) coupled with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was employed to rank the importance of the factors and determine the prioritization of rural domestic sewage management in each area. The model results indicated that priority should be given to the county government, township government, ecologically sensitive areas, and administrative villages near tourist attractions in the two selected empirical counties for governance. A sensitivity analysis showed that altitude consistently exhibited high sensitivity in influencing the ranking results across all scenarios (0.4–0.6). In addition, the empirical results obtained were largely consistent with the priorities of local governments. The proposed framework offers a practical application for decision-making systems in rural domestic sewage management at the county level, providing theoretical support and scientific strategies. This holds great significance for achieving SDG 6.

Rural sewage collection systems are important parts of rural sewage engineering and the conditions in underdeveloped mountainous areas are not conducive to the construction and operation of conventional rural sewage collection systems. This study investigated and analyzed the practical rural sewage collection system in an underdeveloped mountainous area, and found that the diameters of the public rural sewers in the region were mostly DN300 and DN500, the relative depth was generally <0.3, and the frequency of siltation was 6 %. The concentration of chemical oxygen demand (COD), suspended solids (SS) and ammonia nitrogen in the rural sewage collection system was relatively high, and the pollution degree of the sewage could be reflected through the conductivity, turbidity, dissolved oxygen and oxidation reduction potential, so as to realize the rapid monitoring of the rural sewage characteristics and ensure the normal operation of the terminal treatment facilities. The removal capacity of COD and SS in sewers and ditches was different. It is suggested to strengthen the operation and maintenance of the collection system, optimize the design parameters of the collection system and evaluate the concentration of influent pollutants in the treatment facilities to improve the effectiveness of rural sewage treatment.

Anthropogenic greenhouse gases (GHGs) emission, an important role for chemical industrial sources, contributes to the global warming. Coal chemical industry (CCI), one of the mainstays of the chemical industry, is one of major sources of GHGs emission. However, GHGs emission pathways and reduction strategies from CCI remains uncertain, owing to the complexity of their production process. This review comprehensively investigated the generation processes and control measures for GHGs emission in CCI process. According to the different ways of primary conversion processes, CCI divided into three major processes, i.e., coal coking, coal gasification, and coal liquefaction. The coking industry accounts for 60 %–70 % of carbon dioxide (CO2) emissions in the CCI, with fuel combustion accounting for 80 %–90 % of its largest contribution. In the coal gasification (i.e., coal to methanol) and liquefaction (i.e., coal to oil) sectors, the water gas shift, air separation, and coal gasification units represent the main contribution pathways for CO2, accounting for 53 %, 25 %, and 22 % in the whole process, respectively. In addition, the adjustment of the H/C in the syngas produced CO2 in water gas shift unit, and the incomplete combustion of fuel leads to CO2 emissions from air separation and coal gasification units. Furthermore, investigation of various reduction technologies shows that capture or sequestration alone could not provide economic benefits. Therefore, future reduction strategies of CCI CO2 need to focus on resource utilization in the production process. This review provides references for addressing the abatement of GHGs, contributing to mitigate its contribution to global warming.

Dewatered-sludge-based flocculants (DSBF) from wastewater treatment plants has emerged as a promising solution for simultaneous in situ phosphorus removal and waste reuse. Studying kinetics of phosphorus removal processes can help predict reaction rates, however, current kinetic studies primarily emphasize model fitting, neglecting the influence of initial total phosphorus concentration (TPw). To address this issue, a parsimonious kinetic model framework was developed based on the pseudo-second-order (PSO) model, including an adsorption phosphorus removal reaction rate function and a kinetic coefficient (k(2))-TPw function. Laboratory flocculation parameter optimization experiments showed that the effluent phosphorus concentration was reduced to below 0.5 mg/L with optimal conditions of flocculant pH of 4, dosing ratio of 6 %, Al/P of 4.5-5.0, Fe/P of 0.42-0.8, and Al/Fe of 9.0-12.0. The effect of TPw on the reaction kinetics was investigated using the PSO-based kinetic model within a wide TPw range of 1.5 to 40.0 mg/L. The simulation results demonstrated that the kinetic model effectively characterized the slow phosphorus adsorption onto DSBF, with an ultimate prediction error of less than 8 %. Significantly, a robust negative correlation between k2 and TPw was identified and quantified (k(2) = 0.04437 x TPw-(0.4059), R-2>0.95). The applicability of the reaction rate model and the k2-TPw function was validated using municipal wastewater with errors of less than 10 % and 4.5 %, respectively. These findings provide broad insights into phosphorus adsorption kinetics and practical, mathematically efficient framework for real-time, precise wastewater treatment process regulation.

Biological treatment is highly regarded as an effective, cost-efficient, and sustainable method for sewage management, particularly given the challenges posed by cold climates and "double carbon" initiatives that prioritize energy savings and low carbon emissions. In this study, the adaptability of multi-family rural sewage treatment systems (MRST) in these harsh conditions was assessed through continuous monitoring over a 365-day period. The removal efficiencies for CODCr, NH4+-N, TN, and TP during the normal temperature period were recorded at 82.78 +/- 5.38 %, 85.89 +/- 2.38 %, 77.17 +/- 4.36 %, and 78.67 +/- 4.52 %, respectively, with only minor fluctuations between - 4.92 % and + 4.15 % observed during the low temperature (8.32 +/- 4.74 degrees C) and freezing periods (-5.79 +/- 6.25 degrees C). Using 16S rRNA high-throughput sequencing, this study identified key microorganisms in various functional units, uncovering a decrease in species diversity during winter with a stable overall microbial community structure even with pronounced seasonal variations. Notably, the microbial communities among each of the functional units exhibited significant seasonal differences, with greater diversity observed in summer than in winter. Environmental factors, such as temperature, pH, electrical conductivity, dissolved oxygen, and hydraulic retention time showed significant correlations with the presence of crucial functional bacteria including Nitrospira and Denitratisoma. Redundancy analysis (RDA) revealed that these environmental factors accounted for >70 % of the variations in microbial structures caused by seasons, with values of 73.33 % in winter and 70.27 % in summer. This research underscores the robustness and efficiency of biological sewage treatment with low-temperature, providing crucial data and insights for optimizing treatment processes in light of seasonal variations and environmental sustainability goals.

With the rapid pace of global urbanization, health risks faced by rural communities are often overlooked. Deaths Attributable to Unsafe Sanitation in Rural areas (DAUSRs) are influenced by demographic factors, disease mortality rates, and environmental sanitation conditions. However, most studies have been limited in scope and scale and lack a comprehensive evaluation framework for global DAUSRs. Therefore, this study estimated the global DAUSRs from 2000 to 2030, using data from the Global Burden of Disease (GBD) and the World Health Organization (WHO). We employed methods such as comparable risk assessment, Bayesian age (period) models, and AutoRegressive Integrated Moving Average (ARIMA) models. Changes in the DAUSRs and their influencing factors were evaluated by applying a decomposition method to assess the impact of population dynamics, sanitation conditions, age structure, and disease mortality rates. The results indicated that despite improvements in rural sanitation, 12.2% of rural populations will still lack access to sanitary toilets in 2030, with an estimated 243,000 deaths (CI: 147,000-441,000) due to unsafe rural sanitation environments. This outcome highlights the need for better rural sanitation governance to provide for demographic shifts, such as aging and declining fertility rates, which are key drivers of DAUSRs. Regions such as Africa and Southeast Asia are at a higher risk with higher diarrhea-related mortality rates in rural areas. We suggest comprehensive measures, including enhancing rural medical facilities, improving sanitation infrastructure, and focusing on vulnerable groups, such as the elderly and children. These measures could inform global rural environmental and public health policies.

Rural domestic sewage treatment is critical for environmental protection. This study defines the spatial pattern of villages from the perspective of rural sewage treatment and develops an integrated decision-making system to propose a sewage treatment mode and scheme suitable for local conditions. By considering the village spatial layout and terrain factors, a decision tree model of residential density and terrain type was constructed with accuracies of 76.47 % and 96.00 %, respectively. Combined with binary classification probability unit regression, an appropriate sewage treatment mode for the village was determined with 87.00 % accuracy. The Analytic Hierarchy Process (AHP), combined with the Technique for Order Preference (TOPSIS) by Similarity to an Ideal Solution model, formed the basis for optimal treatment process selection under different emission standards. Verification was conducted in 542 villages across three counties of the Inner Mongolia Autonomous Region, focusing on the standard effluent effect (0.3773), low investment cost (0.3196), and high standard effluent effect (0.5115) to determine the best treatment process for the same emission standard under different needs. The annual environmental and carbon emission benefits of sewage treatment in these villages were estimated. This model matches village density, geographic feature, and social development level, and provides scientific support and a theoretical basis for rural sewage treatment decision-making.

Rural sewers are key facilities to collect and transport rural sewage whose microbial characteristics need to be revealed to better understand and improve the biochemical process. In this study, metagenomic method was used to analyze the microbial characteristics of rural sewer biofilms and the effect on pollutant removal was further discussed. Results indicated that rural sewer biofilms contained bacteria (e.g. Pseudomonas), fungi (e.g. Spizellomyces), viruses (e.g. Pbunavirus), and archaea (e.g Methanothrix), including pathogens (e.g. Pseudomonas aeruginosa and Aeromonas hydrophila) and antibiotic resistance genes (target for Aminoglycoside and Tetracycline etc.), while the Ammonia monooxygenase genes (i.e. amoA, amoB, and amoC) was basically absent. Rural sewer biofilms contained abundant Desulfobulbus (similar to 2.40 %) whose relative abundance was nearly 40 times higher than Methanothrix (the predominant archaea). Rural sewer biofilms had the ability to decrease chemical oxygen demand in sewage and generate sulfide and methane but the nitrogen and phosphorus removal ability was limited. This study can provide scientific support for better understanding of biochemical reaction process in rural sewer systems.

Volatile organic compounds (VOCs) emitted from landfills are significant contributors to air pollution, attracting considerable attention. In this study, we investigated VOCs emission from a landfill located in a dry, cold region of Northwest China, where residual sludge from a sewage plant was utilized as a cover material for waste. A total of 43 VOCs were detected, with concentrations ranging from 0.58 to 412.15 mg/m3 for each single VOC, predominantly comprising aromatic and oxygenated compounds. Elevated VOCs concentration was observed in both the covered area and work area, with aromatic (71 %) and chlorinated compounds (76 %) at the downwind site boundary primarily originating from the landfill. Seven priority control pollutants were identified using the fuzzy composite evaluation method. Their diffusion behavior was simulated using the Gaussian plume model, and their chronic toxicity and carcinogenic risks were assessed utilizing Environmental Protection Agency recommended techniques. Styrene, 1,2,3-trimethylbenzene, and toluene exhibited principal ozone generation potential, whereas toluene and benzene contributed most to secondary aerosol generation. VOCs pollution was more severe within 500 m in the downwind direction, posing chronic toxicity and carcinogenic risks within 430 m. It is recommended to cover the area that is not temporarily landfilled with air tightness materials, such as HDPE film, to prevent the dispersion of VOCs. This investigation provides insights for developing effective measures to mitigate health risks and secondary pollution.

Lactic acid (LA) synthesis through fermentation of food waste (FW) is an emerging techniques for utilizing perishable organic wastes with high value. Using food waste collected from a cafeteria as the substrate for fermentation, the current study was conducted by applying a micro electric field to the conventional LA fermentation process and performing open-ended electro-fermentation (EF) without sterilization and lactobacilli inoculation. Furthermore, the effects of pH adjustment on LA production were examined. The findings demonstrated that electrical stimulation enhances the electron transfer rate within the system, accelerates REDOX reactions, and thereby intensifies the lactic acid production process. The pH-regulated group produced LA and dissolved organic materials at considerably higher rates than the control group, which did not receive any pH modification. The maximum LA concentration and organic matter dissolution in the experimental group, where the pH was set to 7 every 12 h of fermentation, were 33.9 and 38.4 g/L, respectively. These values were 208 and 203% higher than those in the control group, indicating that the pH adjustment greatly aided the solubilization and hydrolysis of macromolecules. Among the several hydrolyzing bacteria (Actinobacteriota) that were enriched, Lactobacillus predominated, but Bifidobacterium also became a major genus in the neutral-acidic environment, and its abundance grew dramatically. This study provides a scientific basis for optimizing the LA process of FW.

Small diameter gravity sewers (SDGSs) have a wide range of applications in rural wastewater collection due to their low construction costs, fast implementation, and simple operation and maintenance. However, the mechanism of sediment accumulation urgently needs to be solved. This study investigated the sedimentation mechanisms in different components of SDGS through pilot-scale experiments and computational fluid dynamics (CFD) simulations. The results indicate that the sedimentation rate of SDGSs decreased as the flow velocity increased, with sediment primarily accumulating at the end section of upstream pipes and within manholes, accounting for 90.37 +/- 5.15% of the total accumulation. Areas with relatively high sedimentation rates exhibited lower turbulent kinetic energy (TKE), and this trend became more pronounced as the flow velocity decreased. TKE and flow velocity were identified as the key factors influencing the sedimentation process in the SDGSs. This study provides important theoretical foundations and technical support for the design and maintenance of SDGSs.

To enhance anaerobic digestion (AD) of swine manure (SW) and decrease the hydrogen sulfide (H2S) concentration in biogas, microbial electrolysis cell (MEC) and microaeration (MA) were applied, and semi-continuous experiments were conducted to compare their enhancements. The results showed that both MEC and enhanced the production of methane (24.74-68.24 %) and the removal of organic matter (8.54-23.80 increased the reaction rates of the four main AD steps (hydrolysis, acidogenesis, acetogenesis, and methanogenesis), and boosted the activities of key enzymes, with MEC showing the greater increase. A slight synergistic effect was observed between MEC and MA. MA and MA combined with MEC (MM) decreased the H2S concentration in biogas (67.93 +/- 14.20 % and 12.94 +/- 17.81 %) by enriching sulfur oxidizing bacteria, boosting oxidase activity, and restricting sulfite reductase activity. However, MEC increased the H2S concentration biogas (175.26 +/- 96.80 %) by enriching sulfate reducing bacteria and boosting the sulfite reductase activity. three methods (MEC, MA, and MM) all enriched the hydrolytic and acidogenic bacteria and altered the dominant methanogenesis pathway. MEC and MM strengthened direct interspecies electron transfer by enriching Methanosaeta, Clostridium_sensu_stricto_1, and Romboutsia. Results from this study may offer some promising ternatives for the energy issues faced by villages and small towns in China.