Hydrothermal liquefaction (HTL) is a thermochemical conversion process that converts wet biomass into biocrude oil, a gas phase, a solid phase, and an aqueous phase (HTL-AP). An obstacle to the development and scaling of HTL is the volume of HTL-AP produced during the [...] Read more.

Hydrothermal liquefaction (HTL) is a thermochemical conversion process that converts wet biomass into biocrude oil, a gas phase, a solid phase, and an aqueous phase (HTL-AP). An obstacle to the development and scaling of HTL is the volume of HTL-AP produced during the process, which has high concentrations of nitrogen and carbon and cannot be disposed of in the environment without treatment. The HTL-AP is enriched with organic compounds, particularly light polar organics and nitrogenous compounds, which are inhibitory to microbial treatment in wastewater treatment plants. For this reason, the valorization of the HTL-AP is significant for the circular economy of HTL. This review synthesizes published findings on different types of treatment of the HTL-AP for the recovery of valuable nutrients and the removal of toxic compounds. This work outlines the trade-offs of the treatments to serve as a guide for future research to address these weaknesses and improve the valorization of the HTL-AP. Furthermore, this work uniquely focuses on HTL-AP treatment for recovering plant-available nitrogen, targeting its potential use as a fertilizer. The literature highlights the importance of increasing nitrogen bioavailability in HTL-AP through two-step treatments and by selecting HTL-AP derived from protein-rich feedstocks, which offer higher initial nitrogen content. According to the current state of research, further work is needed to optimize chemical and biological treatments for nutrient recovery from HTL-AP, particularly regarding treatment scale and duration. Additionally, economic analyses across different treatment types are currently lacking, but are essential to evaluate their feasibility and practicality.Full article

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Decentralized sanitation in rural areas urgently requires accessible and nature-based solutions to achieve Sustainable Development Goal 6 (clean water and sanitation for all). However, monitoring studies of such ecotechnologies in disperse communities remain limited. This study evaluated the performance of an evapotranspiration tank [...] Read more.

Decentralized sanitation in rural areas urgently requires accessible and nature-based solutions to achieve Sustainable Development Goal 6 (clean water and sanitation for all). However, monitoring studies of such ecotechnologies in disperse communities remain limited. This study evaluated the performance of an evapotranspiration tank (TEvap), designed with community participation, for the treatment of domestic sewage in a rural Quilombola household in the Brazilian Cerrado. The system (total area of 8.1 m², with about 1.0 m² per inhabitant) was monitored for 218 days, covering the rainy season and the plants’ establishment phase. After 51 days, the TEvap reached operational equilibrium, maintaining a zero-discharge regime, and after 218 days, 92.3% of the total system inlet volumes (i.e., 37.47 in 40.58 m³) were removed through evapotranspiration and uptake by cultivated plants (Musa spp.). Statistical analyses revealed correlations that were moderate to strong, and weak between the blackwater level and relative humidity (Pearson correlation coefficient, r = 0.75), temperature (r = −0.66), and per capita blackwater contribution (r = 0.28), highlighting the influence of climatic conditions on system efficiency. These results confirm the TEvap as a promising, low-maintenance, and climate-resilient technology for decentralized domestic sewage treatment in vulnerable rural communities, with the potential to support sanitation policy goals and promote public health.Full article

Accurate estimation of long-term average (LTA) discharge is fundamental for water resource assessment, infrastructure planning, and hydrological modeling, yet it remains a significant challenge, particularly in data-scarce or ungauged basins. This study introduces an advanced machine learning framework to estimate long-term average discharge [...] Read more.

Accurate estimation of long-term average (LTA) discharge is fundamental for water resource assessment, infrastructure planning, and hydrological modeling, yet it remains a significant challenge, particularly in data-scarce or ungauged basins. This study introduces an advanced machine learning framework to estimate long-term average discharge using globally available hydrological station metadata from the Global Runoff Data Centre (GRDC). The methodology involved comprehensive data preprocessing, extensive feature engineering, log-transformation of the target variable, and the development of multiple predictive models, including a custom deep neural network with specialized pathways and gradient boosting machines (XGBoost, LightGBM, CatBoost). Hyperparameters were optimized using Bayesian techniques, and a weighted Meta Ensemble model, which combines predictions from the best individual models, was implemented. Performance was rigorously evaluated using R², RMSE, and MAE on an independent test set. The Meta Ensemble model demonstrated superior performance, achieving a Coefficient of Determination (R²) of 0.954 on the test data, significantly surpassing baseline and individual advanced models. Model interpretability analysis using SHAP (Shapley Additive explanations) confirmed that catchment area and geographical attributes are the most dominant predictors. The resulting model provides a robust, accurate, and scalable data-driven solution for estimating long-term average discharge, enhancing water resource assessment capabilities and offering a powerful tool for large-scale hydrological analysis.Full article

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Validating the potential of multi-frequency synthetic aperture radar (SAR) data for multi-layer and profile soil moisture (SM) estimation modeling, we conducted an airborne multi-frequency SAR joint observation experiment (AMFSEX) over the Liao River Basin in China. The experiment simultaneously acquired airborne high spatial [...] Read more.

Validating the potential of multi-frequency synthetic aperture radar (SAR) data for multi-layer and profile soil moisture (SM) estimation modeling, we conducted an airborne multi-frequency SAR joint observation experiment (AMFSEX) over the Liao River Basin in China. The experiment simultaneously acquired airborne high spatial resolution quad-polarization (quad-pol) SAR data at five frequencies, including the Ka-, X-, C-, S-, and L-band. A preliminary “vegetation–soil” parameter estimation model based on the multi-frequency SAR data was established. Theoretical penetration depths of the multi-frequency SAR data were analyzed using the Dobson empirical model and the Hallikainen modified model. On this basis, a water cloud model (WCM) constrained by multi-polarization weighted and penetration depth weighted parameters was used to analyze the estimation accuracy of the multi-layer and profile SM (0–50 cm depth) under different vegetation types (grassland, farmland, and woodland). Overall, the estimation error (root mean square error, RMSE) of the surface SM (0–5 cm depth) ranged from 0.058 cm³/cm³to 0.079 cm³/cm³, and increased with radar frequency. For multi-layer and profile SM (3 cm, 5 cm, 10 cm, 20 cm, 30 cm, 40 cm, 50 cm depth), the RMSE ranged from 0.040 cm³/cm³ to 0.069 cm³/cm³. Finally, a multi-input multi-output regression model (Gaussian process regression) was used to simultaneously estimate the multi-layer and profile SM. For surface SM, the overall RMSE was approximately 0.040 cm³/cm³. For multi-layer and profile SM, the overall RMSE ranged from 0.031 cm³/cm³to 0.064 cm³/cm³. The estimation accuracy achieved by coupling the multi-source data (multi-frequency SAR data, multispectral data, and soil parameters) was superior to that obtained using the SAR data alone. The optimal SM penetration depth varied across different vegetation cover types, generally falling within the range of 10–30 cm, which holds true for both the scattering model and the regression model. This study provides methodological guidance for the development of multi-layer and profile SM estimation models based on the multi-frequency SAR data.Full article

This paper focuses on the analysis of variability of density fluxes and water mass transformation in the North Atlantic, the quantities reflecting the intensity of intermediate and deep water formation. The authors assess the influence of atmospheric processes on the intensity of formation [...] Read more.

This paper focuses on the analysis of variability of density fluxes and water mass transformation in the North Atlantic, the quantities reflecting the intensity of intermediate and deep water formation. The authors assess the influence of atmospheric processes on the intensity of formation of subpolar modal waters, subtropical modal waters and Labrador Sea waters using the density fluxes and water mass transformation. This analysis is carried out on a seasonal and climatic time scale. The main result of the study is the seasonal and climatic dynamics of water mass transformation in the Labrador Sea, subtropical and subpolar modal waters based on CFSR reanalysis data. The results obtained help to understand the main factors influencing vertical circulation in the region, which can be used in further model experiments.Full article

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The ecological environment of urban lakes affected by human activities is deteriorating rapidly. As a source and sink of pollutants in the lake environment, sediments have become the focus of environmental assessments. At present, most of the studies only conduct pollution assessments on [...] Read more.

The ecological environment of urban lakes affected by human activities is deteriorating rapidly. As a source and sink of pollutants in the lake environment, sediments have become the focus of environmental assessments. At present, most of the studies only conduct pollution assessments on surface sediments. In this study, taking the typical urban lakes GanTang Lake and NanMen Lake (G&N Lake) as the background, not only is the planar spatial distribution of their nutrient elements, seven kinds of heavy metals, and As analyzed in detail, but risk assessments are also carried out on the pollution conditions at different depths. The causes of pollution at different depths are analyzed. It is found that in this lake, with the increase in depth, the pollution situation decreases slightly, but the pollution of nutrient elements is severe. There is severe pollution of nutrient elements at a depth of up to 1 m in the whole lake sediment. In the sediments with a depth of up to 1 m, more than 90% of the areas in the whole lake are at or above the moderate pollution level of Hg, and more than 70% of the areas are under slight pollution of Cd, resulting in the ecological risk level of the whole lake being at or above the high-risk level. Urban lake sediment management is inherently complex, driven by multifaceted factors where intensive anthropogenic activities constitute the primary pollution source. This research provides insights to guide restoration strategies and sustainable development policies for lacustrine ecosystems.Full article

Water resources are strategic resources that support regional economic social development and maintain the health and stability of ecosystems. This study revealed the evolution of the coordinated development of China’s water resources–economic society–ecological environment system based on the coordination degree mode. The research [...] Read more.

Water resources are strategic resources that support regional economic social development and maintain the health and stability of ecosystems. This study revealed the evolution of the coordinated development of China’s water resources–economic society–ecological environment system based on the coordination degree mode. The research was conducted by integrating machine learning with traditional mathematical methods; by setting up the status quo development scenario, water resources priority scenario, economic society priority scenario, ecological environment priority scenario and balanced development scenario; and by using the Holt exponential smoothing–feedforward neural network prediction model, the coordinated development trends under different scenarios were predicted. The results showed that, analyzed from the perspective of the coordinated evolution type of the dual systems, the dominant development system during the study period gradually transformed from water resources–economic society to water resources–ecological environment. For the coordinated development of the complex system, the coordination degree showed “stepped leap—resilient fluctuation (from 0.7242 to 0.8238)”, and “better in the southeast than in the northwest, with significant advantages in the coast”. The most significant increase in the coordination degrees were observed in the balanced development scenario and economic society priority scenarios, where it increased by an average of around 5%, confirming the effective contribution of stable economic and social development to the level of coordination. This study provides theoretical support and practical guidance for regional water resources management.Full article

The marine habitats of the world’s oceans are being driven beyond their resilience. The ongoing biodiversity crisis is happening fast, within the lifespan of researchers trying to produce the information necessary for the conservation of habitats and marine ecosystems. Here, we report on [...] Read more.

The marine habitats of the world’s oceans are being driven beyond their resilience. The ongoing biodiversity crisis is happening fast, within the lifespan of researchers trying to produce the information necessary for the conservation of habitats and marine ecosystems. Here, we report on the destruction of sciaphilic sessile communities and coralligenous concretions produced by the anchoring of a high-tonnage vessel inside a Marine Protected Area in Cyprus. The damage from the anchors and the chains consisted of the dislodgement of large boulders that were dragged or rolled over the seafloor, increasing the breakage and further dislodgement of more boulders; many were left upside-down. The biological communities that thrived in the dark environments below the boulders were directly exposed to high irradiance levels and went through a slow mortality and decaying process, most probably due to a combination of several deterioration agents, such as exposure to direct sunlight, predation, mucilage aggregates, and cyanobacterial blooms. The enforcement of regulatory measures for anchoring and transit in the MPA is necessary to prevent similar destruction. Given the extent of the irreversible damage to these sciaphilic communities, our study is, unfortunately, another environmental post-mortem contribution.Full article

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Selective water withdrawals (SWWs) are frequently used to minimize the downstream effects of dams by blending water from different depths to achieve a desired temperature regime in the river. In 2010, an SWW was installed on the outlet structure of the primary hydropower [...] Read more.

Selective water withdrawals (SWWs) are frequently used to minimize the downstream effects of dams by blending water from different depths to achieve a desired temperature regime in the river. In 2010, an SWW was installed on the outlet structure of the primary hydropower reservoir on the Deschutes River (Oregon, USA) to increase spring temperatures by releasing a combination of surface water and bottom waters from a dam that formerly only had a hypolimnetic outlet. The objective of increasing spring river temperatures was to recreate pre-dam river temperatures and optimize conditions for the spawning and rearing of anadromous fish. The operation of the SWW achieved the target temperature regime, but the release of surface water from a hypereutrophic impoundment resulted in a number of unintended consequences. These changes included significant increases in river pH and dissolved oxygen saturation. Inorganic nitrogen releases decreased in spring but increased in summer. The release of surface water from the reservoir increased levels of plankton in the river resulting in changes to the macroinvertebrates such as increases in filter feeders and a greater percentage of taxa tolerant to reduced water quality. No significant increase in anadromous fish was observed. The presence of large irrigation diversions upstream of the reservoir was not accounted for in the temperature analysis that led to the construction of the SWW. This complicating factor would have reduced flow in the river leading to increased river temperatures at the hydropower site during the measurement period used to develop representations of historical temperature. The analysis supports the use of numerical models to assist in forecast changes associated with SWWs, but the results from this project illustrate the need for greater consideration of complex responses of aquatic communities caused by structural modifications to dams.Full article

More than half of the world’s rivers are intermittent, and climate change is increasing their intermittency, affecting water resources and ecosystems. In Taiwan, steep topography and uneven rainfall have led to increased intermittency in some areas, reflecting changes in hydrological conditions. Using streamflow [...] Read more.

More than half of the world’s rivers are intermittent, and climate change is increasing their intermittency, affecting water resources and ecosystems. In Taiwan, steep topography and uneven rainfall have led to increased intermittency in some areas, reflecting changes in hydrological conditions. Using streamflow data, this study applied intermittency ratio (IR), modified 6-month dry period seasonality (SD6), and trend analysis, as well as watershed properties and climate indices. Results showed that 92% of stations had low flows for less than 20% of the time. The dry season was mainly from November to April, and intermittency was spatially affected mainly by upstream soil moisture, moderately by potential evapotranspiration and infiltration, and less by actual evapotranspiration and catchment area. Intermittency increased in the east and decreased in the west. It was negatively correlated with upstream soil moisture and strongly associated with rainfall frequency, especially the proportion of days with precipitation less than 1 mm. These patterns highlight regional differences in river responses to climate.Full article

Microplastics (MPs) are becoming an increasingly common pollutant in the aquatic environment, including stormwater. This is a serious problem, as stormwater is becoming an essential transport route for MPs from urban areas to surface waters. Rainwater flowing from roofs, roads, and other impermeable [...] Read more.

Microplastics (MPs) are becoming an increasingly common pollutant in the aquatic environment, including stormwater. This is a serious problem, as stormwater is becoming an essential transport route for MPs from urban areas to surface waters. Rainwater flowing from roofs, roads, and other impermeable surfaces contains a variety of plastic particles originating from tire abrasion or waste disposal. This article presents an overview of current research on the occurrence of MPs in stormwater. The potential of selected green infrastructure solutions—particularly bioretention systems, constructed wetlands, and permeable pavements—for their reduction is assessed. Individual solutions present how the change in filter material, selection of vegetation, or the method of conducting the process (e.g., direction of stormwater flow in constructed wetlands) affects their effectiveness. The potential of green infrastructure is also compared with the traditional gray solution of sewage management in cities. This article emphasizes the importance of integrating such solutions in spatial planning as an effective tool to combat climate change and limit the spread of microplastics in the environment.Full article

The overtopping-induced lateral erosion breaching of tailings dams represents a critical disaster mechanism threatening structural safety, particularly in reinforced fine-grained tailings dams where erosion behaviors demonstrate pronounced water–soil coupling characteristics and material anisotropy. Through physical model tests and numerical simulations, this study systematically [...] Read more.

The overtopping-induced lateral erosion breaching of tailings dams represents a critical disaster mechanism threatening structural safety, particularly in reinforced fine-grained tailings dams where erosion behaviors demonstrate pronounced water–soil coupling characteristics and material anisotropy. Through physical model tests and numerical simulations, this study systematically investigates lateral erosion failure patterns of reinforced fine-grained tailings under overtopping flow conditions. Utilizing a self-developed hydraulic initiation test apparatus, with aperture sizes of reinforced geogrids (2–3 mm) and flow rates (4–16 cm/s) as key control variables, the research elucidates the interaction mechanisms of “hydraulic scouring-particle migration-geogrid anti-sliding” during lateral erosion processes. The study revealed that compared to unreinforced specimens, reinforced specimens with varying aperture sizes (2–3 mm) demonstrated systematic reductions in final lateral erosion depths across flow rates (4–16 cm/s): 3.3–5.8 mm (15.6−27.4% reduction), 3.1–7.2 mm (12.8–29.6% reduction), 2.3–11 mm (6.9–32.8% reduction), and 2.5–11.4 mm (6.2–28.2% reduction). Smaller-aperture geogrids (2 mm × 2 mm) significantly enhanced anti-erosion performance through superior particle migration inhibition. Concurrently, a pronounced positive correlation between flow rate and lateral erosion depth was confirmed, where increased flow rates weakened particle erosion resistance and exacerbated lateral erosion severity. The numerical simulation results are in basic agreement with the lateral erosion failure process observed in model tests, revealing the dynamic process of lateral erosion in the overtopping breach of a reinforced tailings dam. These findings provide critical theoretical foundations for optimizing reinforced tailings dam design, construction quality control, and operational maintenance, while offering substantial engineering applications for advancing green mine construction.Full article

This study explores the application of a Long Short-Term Memory (LSTM) model for river water level forecasting, emphasizing the critical role of hyper-parameters optimization. Similar to physical and numerical rainfall-runoff models, LSTM relies on parameters to drive its data-driven modeling process. The performance [...] Read more.

This study explores the application of a Long Short-Term Memory (LSTM) model for river water level forecasting, emphasizing the critical role of hyper-parameters optimization. Similar to physical and numerical rainfall-runoff models, LSTM relies on parameters to drive its data-driven modeling process. The performance of such models is highly sensitive to the chosen hyper-parameters, making their optimization essential. To address this, three algorithms—Grid Search, Random Search, and Bayesian Search—were applied to identify the most effective hyper-parameter combinations. Cross-correlation analysis revealed that average rainfall had a stronger influence on river water levels than upstream point rainfall, leading to its selection as the model input. The optimization focused on five key hyper-parameters: neuron units, learning rate, dropout rate, number of epochs, and batch size. Results showed that, while Grid Search required the most computational time, both Random and Bayesian Search were more efficient. Notably, Bayesian Search yielded the best predictive performance with minimal time cost, making it the preferred optimization method. Additionally, reproducible LSTM simulations were conducted to ensure the consistency and practical applicability of the forecasting in real-world scenarios. Overall, Bayesian Search is recommended for optimizing LSTM models due to its balance of accuracy and computational efficiency in hydrological forecasting.Full article

Rainfall–runoff processes and flood propagation were quantified to clarify floodwater dynamics in the upper Tenryu River basin. The basin is characterized by contrasting runoff behaviors between its left- and right-bank subbasins and large upstream river storage created by gorge topography. Radar rainfall and [...] Read more.

Rainfall–runoff processes and flood propagation were quantified to clarify floodwater dynamics in the upper Tenryu River basin. The basin is characterized by contrasting runoff behaviors between its left- and right-bank subbasins and large upstream river storage created by gorge topography. Radar rainfall and dam inflow data were analyzed to determine the runoff characteristics, on which the rainfall–runoff simulation was based. A higher storage capacity was observed in the left-bank subbasins, while an exceptionally large specific discharge was observed in one of the right-bank subbasins after several hours of intense rainfall. Based on these findings, the basin-scale storage was quantitatively evaluated. Water level peaks in the main channel appeared earlier at downstream locations, indicating that tributary inflows strongly affect the flood peak timing. A two-dimensional unsteady model successfully reproduced this behavior and captured the delay in the flood wave speed due to the complex morphology of the Tenryu River. The averageα value, representing the ratio of flood wave speed to flow velocity, was 1.38 over the 70 km study reach. This analysis enabled quantification of river channel storage and clarified its relative relationship to basin storage, showing that river channel storage is approximately 12% of basin storage.Full article

The Angat Reservoir serves as a major water source for Metro Manila, providing most of the region’s domestic, agricultural, and hydropower needs. However, its dependence on rainfall makes it sensitive to climate variability and future climate change. This study assesses potential long-term impacts [...] Read more.

The Angat Reservoir serves as a major water source for Metro Manila, providing most of the region’s domestic, agricultural, and hydropower needs. However, its dependence on rainfall makes it sensitive to climate variability and future climate change. This study assesses potential long-term impacts of climate change on water availability in the Angat watershed using the Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS). Historical rainfall data from 1994 to 2023 and projections under both RCP4.5 (moderate emissions) and RCP8.5 (high emissions) scenarios were analyzed to simulate future hydrologic responses. Results indicate projected reductions in wet-season rainfall and corresponding outflows, with declines of up to 18% under the high-emission scenario. Increased variability during dry-season flows suggests heightened risks of water scarcity. While these projections highlight possible changes in the watershed’s hydrologic regime, the study acknowledges limitations, including assumptions in rainfall downscaling and the absence of direct streamflow observations for model calibration. Overall, the findings underscore the need for further investigation and planning to manage potential climate-related impacts on water resources in Metro Manila.Full article

This study combines machine vision technology and deep learning models to rapidly assess the activity of anaerobic ammonium oxidation (Anammox) granular sludge. As a highly efficient nitrogen removal technology for wastewater treatment, the Anammox process has been widely applied globally due to its [...] Read more.

This study combines machine vision technology and deep learning models to rapidly assess the activity of anaerobic ammonium oxidation (Anammox) granular sludge. As a highly efficient nitrogen removal technology for wastewater treatment, the Anammox process has been widely applied globally due to its energy-saving and environmentally friendly features. However, existing sludge activity monitoring methods are inefficient, costly, and difficult to implement in real-time. In this study, we collected and enhanced 1000 images of Anammox granular sludge, extracted color features, and used machine learning and deep learning training methods such as XGBoost and the ResNet50d neural network to construct multiple models of sludge image color and sludge denitrification efficiency. The experimental results show that the ResNet50d-based neural network model performed the best, with a coefficient of determination (R²) of 0.984 and a mean squared error (MSE) of 523.38, significantly better than traditional machine learning models (with R² up to 0.952). Additionally, the experiment demonstrated that under a nitrogen load of 2.22 kg-N/(m³·d), the specific activity of Anammox granular sludge reached its highest value of 470.1 mg-N/(g-VSS·d), with further increases in nitrogen load inhibiting sludge activity. This research provides an efficient and cost-effective solution for online monitoring of the Anammox process and has the potential to drive the digital transformation of the wastewater treatment industry.Full article

Reusing and recycling treated wastewater is a sustainable approach to meet the growing demand for clean water, ensuring its availability for both current and future generations. Wastewater can be treated in such advanced ways that it can be used for industrial operations, recharging [...] Read more.

Reusing and recycling treated wastewater is a sustainable approach to meet the growing demand for clean water, ensuring its availability for both current and future generations. Wastewater can be treated in such advanced ways that it can be used for industrial operations, recharging groundwater, irrigation of fields, or even manufacturing drinkable water. This strategy meets growing water demand in water-scarce areas while protecting natural ecosystems. Treated wastewater is both a resource and a challenge. Though it may be nutrient-rich and can increase agricultural output while showing resource reuse and environmental conservation, high treatment costs, public acceptance, and contamination hazards limit its use. Proper treatment can reduce these hazards, safeguarding human health and the environment while enhancing its benefits, including a stable water supply, nutrient-rich irrigation, higher crop yields, economic development, and community resilience. On the one hand, inadequate treatment may lead to soil salinization, environmental degradation, and hazardous foods. Examining the dual benefits and risks of using treated wastewater for agricultural irrigation, this paper investigates the complexities of its use as a valuable resource and as a potential hazard. Modern treatment technologies are needed to address these difficulties and to ensure safe and sustainable use. If properly handled, treated wastewater reuse has enormous potential for reducing water scarcity and expanding sustainable agriculture as well as global food security.Full article

This study evaluated the efficacy of acclimated cow manure as a seed microbiome to enhance food waste hydrolysis. Anaerobic hydrolysis was performed on simulated food waste in a hydrolytic–acidogenic leach bed reactor (LBR) operated in batch mode under mesophilic conditions (35 °C) for [...] Read more.

This study evaluated the efficacy of acclimated cow manure as a seed microbiome to enhance food waste hydrolysis. Anaerobic hydrolysis was performed on simulated food waste in a hydrolytic–acidogenic leach bed reactor (LBR) operated in batch mode under mesophilic conditions (35 °C) for 16 days. The acclimation process involved three sequential runs: Run-1 utilized 20% (w/w) cow manure as seed, Run-2 employed the digestate from Run-1 (day 5), and Run-3 used the digestate from Run-1 (day 10). Run-3 achieved 70.4% removal of volatile solids (VSs), surpassing Run-1 (47.1%) and Run-2 (57.1%). Compared with the first run, the production of chemical oxygen demand (COD) and total soluble products (TSPs) increased by 48.7% and 75.9%, respectively, in Run-3. The hydrolysis rate of proteins was 48.4% in Run-1, while an increase of 16.9% was achieved in Run-3 with the acclimatized consortium. A molecular analysis of the microbial community existing in the reactors of Run-2 and Run-3 indicated that the improvement in process performance was closely related to the selection and enrichment of specific hydrolytic–acidogenic bacteria in the reactor. A functional analysis showed that the gene copy numbers for pyruvate synthesis and fatty acid synthesis and metabolism pathways were higher in all bacterial species in Run-3 compared to in those of the other two runs, indicating improved capacity through acclimation in Run-3. The experimental results demonstrate that the hydrolysis of food waste can be enhanced through the acclimation of seed microbes from cow manure.Full article

Under the frequent occurrence of urban waterlogging disasters globally, underground spaces, due to their unique environmental conditions and structural vulnerabilities, are facing growing flood pressure, resulting in substantial economic losses that hinder sustainable urban development. This study focused on a high-density urban area [...] Read more.

Under the frequent occurrence of urban waterlogging disasters globally, underground spaces, due to their unique environmental conditions and structural vulnerabilities, are facing growing flood pressure, resulting in substantial economic losses that hinder sustainable urban development. This study focused on a high-density urban area in China, investigating surface waterlogging conditions under rainfall characteristics as the primary driver of flooding. Focusing on the main nodes—entrances and exits—within the waterlogging disaster chain of underground garages, a risk assessment framework was constructed that encompasses three key dimensions: the attributes of extreme rainfall, the structural characteristics of entrances/exits, and emergency response capacities. Subsequently, a waterlogging risk assessment was conducted for selected underground garages in the study area under a 100-year return period extreme rainfall scenario. The results revealed that the flood depth at entrances/exits and the structural height of entrances/exits are the primary factors influencing flood risk in urban underground garages. Under this simulation scenario, 37.5% of the entrances and exits exhibited varying degrees of flood risk. The assessment framework and indicator system developed in this study provide valuable insights for flood risk evaluation in underground garage systems and offer decision-makers a more scientific and robust foundation for formulating improvement measures.Full article