Hydrothermal conversion of lignocellulosic biomass has emerged as a viable thermochemical pathway for the sustainable production of bio-based platform chemicals or intermediates and then finally upgraded into biofuels. This approach evaluates the efficiency of hydrothermal hydrolysis in depolymerizing plant biomass that results in fermentable sugars and also value-added intermediates. It pushes to transform into transport grade biofuels via aligning with circular-economy principles and carbon-neutrality targets. This review analyzes key process parameters from a few selected experimental investigations, demonstrating favorable hydrothermal performance. The referenced studies were conducted at temperatures (ranging from 180 to 280 °C) and residence times (of 30-120 min) with optimal pressure range during thermochemical reaction. The study of these parameters enables the determination of optimal operating conditions for the fractionation of diverse biomasses. At 250 °C for 90 min, hydrolysis of waste lignocellulosic biomass achieved high cellulose conversion (67.5%) and hemicellulose degradation (54.2%) that demonstrates the production of significant quantities of furfural (3.8 wt%) and levulinic acid (4.5 wt%) as important platform chemicals. In parallel, hydrothermal liquefaction was conducted at temperature (300 °C) and pressure (10 MPa) that produced biocrude oils with an energy density (nearly 32 MJ kg-1). This highlighted its further potential as a renewable alternative to fossil-derived fuels with results of biochar (containing 68% fixed carbon) via exhibiting high adsorption capacity and surface area. These properties of biochar made it suitable for bioremediation, soil enhancement, and long-term carbon sequestration applications. Life-cycle assessment (LCA) study of advanced or sustainable biofuel showed its results with an indication of a 47% reduction in greenhouse-gas emissions compared with conventional petroleum-based fuel systems. Further, climate-mitigation potential of hydrothermal technologies findings is validated as a robust pathway via efficient hydrothermal hydrolysis for biomass valorization and resource recovery within sustainable production frameworks. These analyses further underscore the need to transition from energy-intensive thermal conversion methods toward more efficient hydrothermal systems. Future research needs to focus on improving product selectivity via optimizing reactor design, and integrating hydrothermal processes within biorefinery. These research concepts can improve architecture to enhance overall environmental and economic sustainability.
Mercury addition to dissolved organic matter (DOM) can induce changes in its optical properties that may be detected using differential absorbance spectra (DAS). This study evaluated the influence of DOM aromaticity on mercury-induced DAS responses using acetic acid, l-tyrosine, and tannic acid as model compounds representing different molecular and chromophoric characteristics, together with peat water and upland river water as contrasting natural-water matrices. Ultraviolet-visible (UV-Vis) spectra were recorded from 200 to 800 nm, with characteristic DAS responses observed at Δ229, Δ222, and Δ216 for acetic acid, tyrosine, and tannic acid, respectively. The three model compounds showed strong concentration-dependent relationships with mercury concentration, with coefficients of determination (R2) of 0.8905, 0.9026, and 0.9094, respectively. Natural-water samples also exhibited concentration-dependent DAS responses, with logarithmic relationships over 0.01-10 mg/L. Independent blind-spike recovery experiments using peat water and upland river water yielded recoveries of 88-101%. The results demonstrate measurable changes in DOM optical properties following mercury addition, with response magnitude varying among DOM matrices. DAS therefore shows potential as a rapid, non-destructive screening approach under the investigated conditions, while further validation using independent environmental samples and environmentally relevant mercury concentrations is required.
Nitrate contamination of shallow groundwater is a concern for drinking water safety and ecosystem health globally, yet national-scale prediction techniques remain limited. Here, we describe the development and evaluation of an ensemble machine learning framework to estimate median nitrate (NO3-N) concentrations in shallow groundwater across New Zealand. From 957 state of the environment monitoring bores, 589 shallow (<50 m), oxic bores with complete model data were retained. These were combined with 99 predictor variables describing land use, hydrogeology, climate, topography, and soils. Candidate tree-based machine learning models (RF, XRT, XGBoost, LightGBM) were trained and stacked into an ensemble, evaluated with 10-fold cross-validation repeated 10 times within the training set. On the held-out 20% test set, the ensemble model achieved an RMSE of 3.13 mg/L NO3-N and R2 of 0.56, indicating moderate performance. Soil age, dairy cattle density, land use, and bore depth were amongst the strongest predictors of median groundwater nitrate. Gridded estimates indicated a pattern of increased concentrations in intensively farmed areas, with hotspots exceeding the drinking water standard of 11.3 mg/L, though high concentrations were systematically underestimated. This approach demonstrates the first spatially continuous, data-driven estimates of median nitrate in shallow groundwater across New Zealand, offering a tool to inform water quality management and resource management. The machine learning framework can be applied in other regions where monitoring data are sparse but environmental predictors exist.
Epidemiological evidence suggests that the chemical composition of coal dust influences its toxicity, although the underlying mechanisms remain unclear. We previously identified potassium content as a strong predictor of lung cell responses, likely reflecting the presence of potassium alumino-silicate minerals. In this study, we investigated the role of potassium and potassium alumino-silicates in coal dust-induced cellular responses and explored the mechanisms driving these effects. Forty-four coal samples and four potassium alumino-silicate minerals were assessed for their effects on cytotoxicity, cell proliferation, and inflammatory responses in epithelial cells and macrophages. Surface-associated iron was quantified, and intracellular reactive oxygen species (ROS) generation was measured to assess oxidative stress mechanisms. Our data showed that potassium oxide alone induced only minor cytotoxic effects, whereas specific potassium alumino-silicate minerals, particularly illite, elicited strong cytotoxic and pro-inflammatory responses. Higher potassium content in coal dust was associated with reduced epithelial cell proliferation. Illite exhibited elevated surface-associated iron and induced greater ROS production compared with muscovite and orthoclase. Increasing surface iron on these less reactive minerals enhanced inflammatory responses but did not replicate the cytotoxic effects of illite. These findings demonstrate that potassium alone does not directly drive coal dust toxicity, but instead reflects the presence of reactive mineral phases. Mineral-specific surface properties, particularly those related to iron-mediated oxidative stress, play a central role in determining biological responses to coal dust.
Understanding phosphate (PO43-) transport during anaerobic treatment is essential for improving nutrient removal from municipal landfill leachate. This study tested the hypothesis that the Generalized Fulazzaky (GF) equations can quantitatively distinguish external, internal, and global mass-transfer processes and identify the dominant rate-controlling resistance governing PO43- removal in anaerobic systems. A laboratory-scale up-flow anaerobic sludge blanket (UASB) reactor equipped with a gas-liquid-solid separator was operated under mesophilic conditions (38 °C) for 197 d to treat municipal landfill leachate. During the initial operating stage, PO43- removal was limited because the anaerobic sludge (ANS) was still acclimating and granule development was incomplete. As the biomass matured and the influent PO43- concentration increased from 5.02 to 10.93 mg L-1, the removal efficiency improved from 25.25% to 57.79%. Linear GF analysis showed an excellent fit (R2 = 0.9929), enabling determination of the β and B parameters for kinetic simulation. The global mass-transfer factor closely followed the internal mass-transfer factor, whereas the external mass-transfer factor remained consistently lower, indicating that external mass-transfer resistance governed overall PO43- removal under the investigated conditions. Analysis of the C/N/P ratio further demonstrated the coupling between nutrient availability, ANS development, and phosphate transport. These findings provide new mechanistic insight into PO43- biosorption in anaerobic systems and demonstrate that the GF framework is a useful mechanistic tool for interpreting nutrient mass-transfer behavior in laboratory-scale UASB reactors, providing a basis for future pilot-scale validation.
