Environmental Science and Pollution Research最新文献

The study evaluated four household food waste composting systems using replicated trials (n = 3 per device) with standardized feedstock loads to compare temperature dynamics, physicochemical parameters, compost maturity, and microbiological safety. Although electric units automated mixing and heating, they did not achieve faster overall stabilization, and all devices produced semistabilized material requiring extended curing. Economic and environmental assessments indicated trade‑offs between operational costs, energy use, and waste diversion potential. Screening of culturable isolates did not reveal antibiotic‑resistant strains, though this does not exclude their presence in uncultured microbial fractions. The results highlight the need for additional maturation steps and context‑specific adoption strategies for decentralized circular waste management.

Plastic waste is a non-biodegradable material which is extensively used in many applications, creating a critical environmental challenge of its disposal. Therefore, its utilization in large quantities as a recycled product in road infrastructure will mitigate ill effects occurring because of its dumping. The aim of this study was to analyze the impacts of adding recycled plastic waste aggregate (RPWA) in hot mix asphalt (HMA) mixes using a wide range of variables by employing the Marshall mix design procedure in the context of Pakistan. A data-driven framework is employed with a novel multivariate performance score function. Incorporation of RPWA, sourced from LDPE polyethylene bags, at the content of 2.5% by weight (~ 6% by volume) was found to provide the best strength while fulfilling criteria of other key parameters. The mix performance degrades steeply and significantly beyond 2.5% but remains under acceptable design ranges till 10%. Based on these results, RPWA can be used to enhance pavement performance with strict quality control on batching. The findings of this study pave the way towards a sustainable pathway for high-volume disposal of low-value plastic film waste with applications in low to medium-traffic roads. Investigations with smaller increments in RPWA content, field testing, and lifecycle cost analysis (LCCA) are recommended for future research directions. The findings of this study highlight the impacts of using RPWA in road infrastructure providing ways to reduce plastic pollution through optimum design of pavements. However, they are based on Marshall laboratory testing and require validation through durability, moisture, rutting, fatigue, and field studies before implementation.

The Matanza-Riachuelo river basin (MRB) is considered one of the most polluted sites in the world, with very high levels of heavy metal(loid)s (HMs). However, as in almost all urban basins, studies on biological indicators of soil health are limited. In this work, we sampled soil and roots of mycorrhizal plants in three regions of the MRB (upper, middle, and lower basins) with the aim of exploring the potential of arbuscular mycorrhizal fungi (AMF) richness, based on spore morphology, plant mycorrhizal status, and glomalin-related soil proteins (GRSP) concentration as bioindicators of soil health. The highest concentrations of HMs were detected in the lower basin (degree of contamination mean value: 44.55), because it is exposed to a high input of pollutants and anthropogenic impact. AMF community composition was compared across the different soil samples. The Glomeraceae family was the most represented in the MRB (54.55% of species), and Rhizoglomus intraradices was the only AMF species detected at every sampled site. This work constitutes the first report of 8 of the 16 AMF species described so far in the MRB. GRSP differences were related to the lower basin of the MRB and to HMs concentrations, particularly Cu and Cr. Regarding the potential use of the studied AMF-related variables as bioindicators of soil health, GRSP concentrations increased with soil toxicity while AMF richness decreased with soil disturbance. These results suggest that these variables could serve as reliable biological indicators of soil health in future studies.

The transition toward sustainable road construction has led to increased research on replacing conventional asphalt binders with bio-based and waste-derived alternatives. Bio-bitumen derived from lignocellulosic biomass and binders modified using domestic and industrial waste have shown significant potential in reducing greenhouse gas (GHG) emissions by up to 80%. Life cycle assessments have reported net-negative emissions for certain biomass-based binders. However, these alternative binders may alter the chemical and molecular compositions of the base bitumen, thereby affecting its physical characteristics and overall performance. Pyrolysis of biomass and non-recyclable waste is emerging as a promising alternative due to its chemical similarity to fossil fuel–based oils. Despite its potential, the performance of pyrolyzed oils is highly dependent on feedstock type and process parameters. This study investigates the chemical, thermal, and rheological properties of binders produced from lignocellulosic sources (pine needles, sawdust, and rice straw) and a waste source (municipal solid waste). Five percent pyrolyzed oil from each source was added to the base bitumen (VG 40 in this study) for laboratory investigation. Results show that pyrolysis oils are chemically compatible with bitumen, but the variations in molecular composition and their quantitative presence affect the binder characteristics. Among all the samples, pine needle (PN) feedstock and PN bio-oil exhibited a balanced chemical profile with lower polarity, contributing to improved compatibility with petroleum binders. PN bio-bitumen demonstrated the closest similarity to the base bitumen in terms of molecular structure, thermal stability, rheological and aging response. The study concludes that the performance of bio-bitumen is strongly influenced by the source of pyrolysis oil, with PN bio-bitumen showing comparatively promising results for further development.

This study evaluated hyperspectral imaging (HSI)-based prediction of nickel (Ni) and cadmium (Cd) contamination in three agricultural soils from Lebanon, classified as clayey, silty, and sandy, and developed machine learning (partial least squares regression (PLSR) and support vector regression (SVR)) and deep learning (neural networks (NN) and convolutional neural networks (CNN)) models to predict soil contamination levels. The tested soil groups exhibited distinct absorption features, reflectance intensities, and spectral shapes. Among the developed prediction models, SVR and CNN achieved the highest performance. Using SVR, the prediction performances (({R}^{2})) for Ni contamination were 0.850, 0.830, and 0.790 for clayey, silty, and sandy soils, respectively, while the corresponding ({R}^{2}) for Cd were 0.930, 0.931, and 0.945. For the CNN models, ({R}^{2}) values in silty soil reached 0.899 for Ni and 0.944 for Cd, whereas in sandy soils, they were 0.872 and 0.938, respectively. Clayey soils exhibited the highest prediction performance with the NN-based model, achieving ({R}^{2}) of 0.930 for Ni and 0.950 for Cd. SVR and CNN models were validated with newly contaminated soil samples and demonstrated a good fit (({R}^{2})> 0.790) across all tested soils. Both SVR and CNN showed poor transferability across the different tested soil types (({R}^{2}) ranged from 0.107 to 0.242 for SVR models and from 0.110 to 0.260 for CNN models), demonstrating limited model transferability among the tested soil groups and emphasizing the need for soil-specific or matrix-informed calibration models. However, because only three soils with multiple differing physicochemical properties were investigated and detailed mineralogical characterization was not performed, the specific contribution of individual soil characteristics to model transferability could not be isolated.

Graphical Abstract

Environmental contamination by dye containing waste water poses significant water treatment challenges. Removal of the dye necessitates the development of nanomaterial for water remediation. In the current study, a magnetic iron oxide–activated carbon nanocomposite was synthesized using aqueous Mucuna bracteata extracts, and its Methylene Blue dye removal mechanism was investigated along with phytotoxicity of the treated dye. SEM analysis exhibited the formation of nanosized magnetic iron oxide particles deposited with activated carbon, size ranging from 94.18 to 152.0 nm. The UV–Vis spectrophotometric analysis of Mucuna bracteata leaf extracts indicated the presence of phytochemicals. XRD analysis endorses the crystalline magnetic iron oxide in the nanocomposite, with diffraction peak at 2θ = 35.5°. FTIR analysis revealed the adsorption mechanism of dye removal. The effect of temperature, pH, dosage, concentration, and contact time on the adsorption of Methylene Blue dye on the surface of the magnetic iron oxide–activated carbon nanocomposite was studied. The column studies were also carried out in a packed bed column. The maximum capacity of Methylene Blue adsorption was 109.89 mg/g. The isotherm and kinetic studies of Methylene Blue adsorption exhibited good agreement with the Freundlich (R² = 0.9591) and pseudo-second-order models (R² = 0.9749), respectively. The germination results using Trigonella foenum graecum demonstrated 90% of seed germination and improved seedling development due to the reduced phytotoxicity in the eluate. These findings demonstrated that the nanocomposite is an efficient and sustainable adsorbent for the dye contaminated waste water treatment.