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In the quest for effective solutions to address Environ. Pollut. and meet the escalating energy demands, heterojunction photocatalysts have emerged as a captivating and versatile technology. These photocatalysts have garnered significant interest due to their wide-ranging applications, including wastewater treatment, air purification, CO2 capture, and hydrogen generation via water splitting. This technique harnesses the power of semiconductors, which are activated under light illumination, providing the necessary energy for catalytic reactions. With visible light constituting a substantial portion (46%) of the solar spectrum, the development of visible-light-driven semiconductors has become imperative. Heterojunction photocatalysts offer a promising strategy to overcome the limitations associated with activating semiconductors under visible light. In this comprehensive review, we present the recent advancements in the field of photocatalytic degradation of contaminants across diverse media, as well as the remarkable progress made in renewable energy production. Moreover, we delve into the crucial role played by various operating parameters in influencing the photocatalytic performance of heterojunction systems. Finally, we address emerging challenges and propose novel perspectives to provide valuable insights for future advancements in this dynamic research domain. By unraveling the potential of heterojunction photocatalysts, this review contributes to the broader understanding of their applications and paves the way for exciting avenues of exploration and innovation.

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Tuojiang River Basin is a first-class tributary of the upper reaches of the Yangtze River-which is the longest river in China. As phytoplankton are sensitive indicators of trophic changes in water bodies, characterizing phytoplankton communities and their growth influencing factors in polluted urban rivers can provide new ideas for pollution control. Here, we used direct microscopic count and environmental DNA (eDNA) metabarcoding methods to investigate phytoplankton community structure in Tuojiang River Basin (Chengdu, Sichuan Province, China). The association between phytoplankton community structure and water environmental factors was evaluated by Mantel analysis. Additional environmental monitoring data were used to pinpoint major factors that influenced phytoplankton growth based on structural equation modeling. At the phylum level, the dominant phytoplankton taxa identified by the conventional microscopic method mainly belonged to Bacillariophyta, Chlorophyta, and Cyanophyta, in contrast with Chlorophyta, Dinophyceae, and Bacillariophyta identified by eDNA metabarcoding. In α-diversity analysis, eDNA metabarcoding detected greater species diversity and achieved higher precision than the microscopic method. Phytoplankton growth was largely limited by phosphorus based on the nitrogen-to-phosphorus ratios > 16:1 in all water samples. Redundancy analysis and structural equation modeling also confirmed that the nitrogen-to-phosphorus ratio was the principal factor influencing phytoplankton growth. The results could be useful for implementing comprehensive management of the river basin environment. It is recommended to control the discharge of point- and surface-source pollutants and the concentration of dissolved oxygen in areas with excessive nutrients (e.g., Jianyang-Ziyang). Algae monitoring techniques and removal strategies should be improved in 201 Hospital, Hongrihe Bridge and Colmar Town areas.

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Monolithic aerogels are promising candidates for use in atmospheric environmental purification due to their structural advantages, such as fine building block size together with high specific surface area, abundant pore structure, etc. Additionally, monolithic aerogels possess a unique monolithic macrostructure that sets them apart from aerogel powders and nanoparticles in practical environmental clean-up applications. This review delves into the available synthesis strategies and atmospheric environmental applications of monolithic aerogels, covering types of monolithic aerogels including SiO2, graphene, metal oxides and their combinations, along with their preparation methods. In particular, recent developments for VOC adsorption, CO2 capture, catalytic oxidation of VOCs and catalytic reduction of CO2 are highlighted. Finally, challenges and future opportunities for monolithic aerogels in the atmospheric environmental purification field are proposed. This review provides valuable insights for designing and utilizing monolithic aerogel-based functional materials.

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Dibromoethane is a widespread, persistent organic pollutant. Biochars are known mediators of reductive dehalogenation by layered FeII-FeIII hydroxides (green rust), which can reduce 1,2-dibromoethane to innocuous bromide and ethylene. However, the critical characteristics that determine mediator functionality are lesser known. Fifteen biochar substrates were pyrolyzed at 600 °C and 800 °C, characterized by elemental analysis, X-ray photo spectrometry C and N surface speciation, X-ray powder diffraction, specific surface area analysis, and tested for mediation of reductive debromination of 1,2-dibromoethane by a green rust reductant under anoxic conditions. A statistical analysis was performed to determine the biochar properties, critical for debromination kinetics and total debromination extent. It was shown that selected plant based biochars can mediate debromination of 1,2-dibromoethane, that the highest first order rate constant was 0.082/hr, and the highest debromination extent was 27% in reactivity experiments with 0.1 µmol (20 µmol/L) 1,2-dibromoethane, ≈ 22 mmol/L FeIIGR, and 0.12 g/L soybean meal biochar (7 days). Contents of Ni, Zn, N, and P, and the relative contribution of quinone surface functional groups were significantly (p < 0.05) positively correlated with 1,2-dibromoethane debromination, while adsorption, specific surface area, and the relative contribution of pyridinic N oxide surface groups were significantly negatively correlated with debromination.

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Abstract Introduction: Leptodactylus latinasus and Physalaemus cuqui are sympatric anuran species with similar environmental requirements and contrasting reproductive modes. Climatic configuration determines distribution patterns and promotes sympatry of environmental niches, but specificity/selectivity determines the success of reproductive modes. Species distribution models (SDM) are a valuable tool to predict spatio-temporal distributions based on the extrapolation of environmental predictors. Objectives: To determine the spatio-temporal distribution of environmental niches and assess whether the protected areas of the World Database of Protected Areas (WDPA) allow the conservation of these species in the current scenario and future. Methods: We applied different algorithms to predict the distribution and spatio-temporal overlap of environmental niches of L. latinasus and P. cuqui within South America in the last glacial maximum (LGM), middle-Holocene, current and future scenarios. We assess the conservation status of both species with the WDPA conservation units. Results: All applied algorithms showed high performance for both species (TSS = 0.87, AUC = 0.95). The L. latinasus predictions showed wide environmental niches from LGM to the current scenario (49 % stable niches, 37 % gained niches, and 13 % lost niches), suggesting historical fidelity to stable climatic-environmental regions. In the current-future transition, L. latinasus would increase the number of stable (70 %) and lost (20 %) niches, suggesting fidelity to lowland regions and a possible trend toward microendemism. P. cuqui loses environmental niches from the LGM to the current scenario (25 %) and in the current-future transition (63 %), increasing the environmental sympathy between both species; 31 % spatial overlap in the current scenario and 70 % in the future. Conclusion: Extreme drought events and rainfall variations, derived from climate change, suggest the loss of environmental niches for these species that are not currently threatened but are not adequately protected by conservation units. The loss of environmental niches increases spatial sympatry which represents a new challenge for anurans and the conservation of their populations.

Resumen Introducción: Leptodactylus latinasus y Physalaemus cuqui son especies de anuros simpátricos con requerimientos ambientales similares y modos reproductivos contrastantes. La configuración climática determina los patrones de distribución y promueve la simpatría de los nichos ambientales, pero la especificidad/selectividad determina el éxito de los modos reproductivos. Los modelos de distribución de especies (MDE) son una herramienta valiosa para predecir distribuciones espacio-temporales basadas en la extrapolación de predictores ambientales. Objetivos: Determinar la distribución espacio-temporal de los nichos ambientales y evaluar si las áreas protegidas de la base de Datos Mundial de Áreas Protegidas (DMAP) permiten la conservación de estas especies en el escenario actual y futuro. Métodos: Aplicamos diferentes algoritmos para predecir la distribución y superposición espacio-temporal de nichos ambientales de L. latinasus y P. cuqui dentro de América del Sur en el último máximo glacial (UGM), Holoceno medio, actual y futuro. Evaluamos el estado de conservación de ambas especies con las unidades de conservación de la DMAP. Resultados: Todos los algoritmos aplicados mostraron un alto rendimiento para ambas especies (TSS = 0.87, AUC = 0.95). Las predicciones de L. latinasus mostraron amplios nichos ambientales desde LGM hasta el escenario actual (49 % de nichos estables, 37 % de nichos ganados y 13 % de nichos perdidos), sugiriendo fidelidad histórica por regiones climático-ambientales estables. En la transición actual-futura L. latinasus incrementaría la cantidad de nichos estables (70 %) y perdidos (20 %), sugiriendo fidelidad por regiones de tierras bajas y la posible tendencia hacia el microendemismo. P. cuqui pierde nichos ambientales desde el LGM al escenario actual (25 %) y en la transición actual-futura (63 %), incrementando la simpatría ambiental entre ambas especies; 31 % de superposición espacial en el escenario actual y 70 % en el futuro. Conclusión: Los eventos de sequía extrema y las variaciones de precipitaciones, derivados del cambio climático, sugieren la pérdida de nichos ambientales para estas especies, actualmente no se encuentran amenazadas, pero no están adecuadamente protegidas por las unidades de conservación. La pérdida de nichos ambientales aumenta la simpatría espacial que representa un nuevo desafío para estos anuros y la conservación de sus poblaciones.

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Coastal dunes are characterised by strong gradients of abiotic stress, typically increasing in severity from inland areas towards the shoreline. Thus, dune gradients represent unique opportunities to study intraspecific responses to environmental changes and to investigate which factors drive community change. This study aims to examine functional trait variation in two coexisting species in response to environmental changes along a dune gradient in NW Spain. Trait convergence was also investigated and compared between both ends of the gradient. We measured functional leaf traits related to plant efficiency in the use of light, water and nutrients, also possible stressors (salt content and pH) and availability of limiting resources (water and nutrients) in the soil. Most soil variables showed changes following a non-directional gradient. Differences in soil variables were site specific and depended on growth of the study species. Structural and functional traits depended on species and/or plant position on the gradient, except for effective quantum yield of PSII and leaf δ15N. The pattern of variation was mostly directional for reflectance indices related to leaf physiology. Multivariate analyses showed significant interspecific differences in the set of traits they exhibited along positions in the gradient. Species also differed in the combination of traits selected under given environmental conditions. Coexisting species display a specific set of traits that reflects different strategies to environmental stress. Our study highlights the overly simplistic nature of some previous studies that assume dune gradients are monotonically directional, without considering that these gradients may be differentially modified by species activity.

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The presence of metalloids and heavy metals in the environment is of critical concern due to their toxicological impacts. However, not all metallic species have the same risk level. Specifically, the physical, chemical, and isotopic speciation of the metal(loids) dictate their metabolism, toxicity, and environmental fate. As such, speciation analysis is critical for environmental monitoring and risk assessment. In the past two decades, surface-enhanced Raman spectroscopy (SERS) has seen significant developments regarding trace metal(loid) sensing due to its ultrahigh sensitivity, readiness for in situ real-time applications, and cost-effectiveness. However, the speciation of metal(loid)s has not been accounted for in the design and application of SERS sensors. In this Perspective, we examine the potential of SERS for metal(loid) speciation analysis and highlight the advantages, progress, opportunities, and challenges of this application.

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The integrated economic reforms in recent years have transformed human life, however, the subsequent rise in environmental challenges necessitates sustainable development goals to ensure net-zero transformation. Within the context of modern energy, economic, and environmental transformation, we deliberate how environmental taxes, energy transition, and sustainable environmental innovation impact climate change in 38 OECD economies. Our robust empirical investigation allows us to report that environmental taxation, sustainable environmental technology, and energy transition lower but GDP and trade openness exacerbate ecological challenges. We also divide the dataset in G7 and the rest of the OECD groups to document the varying impact of environmental policies within OECD economies. Our econometric analysis helps us report novel policy frameworks to solve climate challenges under the UN SDG agenda.

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The Resource Conservation and Recovery Act of 1976 (RCRA) is a cornerstone of environmental policy in the United States. The law regulates the generation, transportation, storage, and disposal of hazardous chemicals. Although regulated, hazardous releases can still occur at RCRA sites due to flawed equipment, human error, and dated historical practices. Releases are investigated and remediated through what is known as a Corrective Action (CA). Using Census data and a novel dataset of RCRA facilities across the contiguous U.S., we examine the possibility of systematic inequities with regards to the (i) siting of RCRA facilities, (ii) occurrence of releases and CAs, (iii) duration of CAs, and (iv) permanence of remediation methods. We find evidence of disproportionate impacts across racial, ethnic, and income dimensions. The results vary, however, depending on the different aspects of the siting and cleanup process, thus highlighting the need for multi-layered analyses to identify and fully understand potential inequities associated with environmental programs.

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For public interest advocates engaged on issues of worker health and safety and environmental protections, regulatory cost-benefit analysis has long been seen as an obstacle to meaningful progress. In November 2023, the Biden administration overhauled Circular A-4, which provides guidance to agencies on how to perform cost-benefit analyses for their rules. The reforms seek to make cost-benefit analysis less biased against worker safety, public health, environmental, and other protective safeguards. As such, the new version of Circular A-4 offers important new levers to agencies to justify more stringent protections. By extension, those in the public interest community can use agency implementation of the new Circular A-4 as part of their advocacy efforts for specific rules they are tracking. This article seeks to support this tactic by providing a roadmap for advocates on how to incorporate into their comments critiques of agencies' cost-benefit analyses based on the Circular A-4 revisions.

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Darwin's two opposing hypotheses, proposing that non-native species closely or distantly related to native species are more likely to succeed, are known as 'Darwin's Naturalization Conundrum'. Recently, invasion ecologists have sought to unravel these hypotheses. Studies that incorporate rich observational data in disturbed ecosystems that integrate phylogenetic and functional perspectives have potential to shed light on the conundrum. Using 313 invaded plant communities including 46 invasive plant species and 531 native plant species across the Three Gorges Reservoir Area in China, we aim to evaluate the coexistence mechanisms of invasive and native plants by integrating phylogenetic and functional dimensions at spatial and temporal scales. Our findings revealed that invasive plants tended to co-occur more frequently with native plant species that were phylogenetically distant but functionally similar in the reservoir riparian zone. Furthermore, our study demonstrated that the filtering of flood-dry-flood cycles played a significant role in deepening functional similarities of native communities and invasive-native species over time. Our study highlights the contrasting effects of phylogenetic relatedness and functional similarity between invasive and native species in highly flood-disturbed habitats, providing new sights into Darwin's Naturalization Conundrum.

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Remote sensing of forests is a powerful tool for monitoring the biodiversity of ecosystems, maintaining general planning, and accounting for resources. Various sensors bring together heterogeneous data, and advanced machine learning methods enable their automatic handling in wide territories. Key forest properties usually under consideration in environmental studies include dominant species, tree age, height, basal area and timber stock. Being proxies of stand productivity, they can be utilized for forest carbon stock estimation to analyze forests' status and proper climate change mitigation measures on a global scale. In this study, we aim to develop an effective machine learning-based pipeline for automatic carbon stock estimation using solely freely available and regularly updated satellite observations. We employed multispectral Sentinel-2 remote sensing data to predict forest structure characteristics and produce their detailed spatial maps. Using the Extreme Gradient Boosting (XGBoost) algorithm in classification and regression settings and management-level inventory data as reference measurements, we achieved quality of predictions of species equal to 0.75 according to the F1-score, and for stand age, height, and basal area, we achieved an accuracy of 0.75, 0.58 and 0.56, respectively, according to the R2. We focused on the growing stock volume as the main proxy to estimate forest carbon stocks on the example of the stem pool. We explored two approaches: a direct approach and a hierarchical approach. The direct approach leverages the remote sensing data to create the target maps, and the hierarchical approach calculates the target forest properties using predicted inventory characteristics and conversion equations. We estimated stem carbon stock based on the same approach: from Earth observation imagery directly and using biomass and conversion factors developed for the northern regions. Thus, our study proposes an end-to-end solution for carbon stock estimations based on the complexation of inventory data at the forest stand level, Earth observation imagery, machine learning predictions and conversion equations for the region. The presented approach enables more robust and accurate large-scale assessments using limited annotated datasets.

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Global sewage sludge production is rapidly increasing, and its safe disposal is becoming an increasingly serious issue. One of the main methods of municipal sewage sludge management is based on its agricultural use. The wastewater and sewage sludge contain numerous antibiotic resistance genes (ARGs), and its microbiome differs significantly from the soil microbial community. The aim of the study was to assess the changes occurring in the soil microbial community and resistome after the addition of sewage sludge from municipal wastewater treatment plant (WWTP) in central Poland, from which the sludge is used for fertilizing agricultural soils on a regular basis. This study used a high-throughput shotgun metagenomics approach to compare the microbial communities and ARGs present in two soils fertilized with sewage sludge. The two soils represented different land uses and different physicochemical and granulometric properties. Both soils were characterized by a similar taxonomic composition of the bacterial community, despite dissimilarities between soils properties. Five phyla predominated, viz. Planctomycetes, Actinobacteria, Proteobacteria, Chloroflexi and Firmicutes, and they were present in comparable proportions in both soils. Network analysis revealed that the application of sewage sludge resulted in substantial qualitative and quantitative changes in bacterial taxonomic profile, with most abundant phyla being considerably depleted and replaced by Proteobacteria and Spirochaetes. In addition, the ratio of oligotrophic to copiotrophic bacteria substantially decreased in both amended soils. Furthermore, fertilized soils demonstrated greater diversity and richness of ARGs compared to control soils. The increased abundance concerned mainly genes of resistance to antibiotics most commonly used in human and animal medicine. The level of heavy metals in sewage sludge was low and did not exceed the standards permitted in Poland for sludge used in agriculture, and their level in fertilized soils was still inconsiderable.

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Soybean is an economically important crop for animal and human nutrition. Currently, there is a lack of information on the effects of Trichoderma harzianum and Purpureocillum lilacinum on INTACTA RR PRO transgenic soybean plants. The present study evaluated the application of T. harzianum and P. lilacinum under field conditions. The results revealed a significant increase in soybean yield at 423 kg ha-1 in response to the application of P. lilacinum compared with the control treatment. In addition, the application of P. lilacinum promoted a significant increase in phosphorus levels in the plant leaves, and there were significant correlations between the increase in taxon abundance for the genus Erwinia and productivity and the average phosphorus and nitrogen content for the plant leaves, for the taxon Bacillus and nitrogen content and productivity, and for the taxon Sphingomonas and nitrogen content. The Bradyrhizobium taxon was identified in the P. lilacinum treatment as a taxon linking two different networks of taxa and is an important taxon in the microbiota. The results show that the application of the fungus P. lilacinum can increase the productivity of soybean INTACTA RR PRO and that this increase in productivity may be a function of the modulation of the microbiota composition of the plant leaves by the P. lilacinum effect.

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Microeukaryotic plankton are essential to marine food webs and biogeochemical cycles, with coastal seas playing a critical role in aquatic ecosystems. Understanding the diversity of microeukaryotic plankton, deciphering their community structure and succession patterns, and identifying the key factors influencing these dynamics remain central challenges in coastal ecology. In this study, we examine patterns of biodiversity, community structure, and co-occurrence using environmental DNA (eDNA)-based methods. Our results show a linear correlation between α-diversity and distance from the shore, with nutrient-related factors, especially inorganic nitrogen, being the primary determinants of the spatial distribution of plankton communities. Alternation of coastal habitat have shifted the succession patterns of coastal eukaryotic plankton communities from stochastic to deterministic processes. Additionally, our observations indicate that the topology and structure of eukaryotic plankton symbiotic patterns and networks are significantly influenced by environmental heterogeneity such as nutrients, which increase the vulnerability and decrease the stability of offshore ecological networks. Overall, our study demonstrates that the distribution of microeukaryotic plankton communities is influenced by factors related to environmental heterogeneity.

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Excessive environmental vibrations generated by urban traffic pose adverse effects on nearby structures and residents. These vibrations are predominantly carried by surface waves, which are localized within the surface layer of soil. The isolation of surface waves through the embedding of periodic wave barriers in soils between the source and the receiver has gained significant attention in recent years. In this paper, a novel approach is proposed for isolating surface waves induced by urban traffic through the use of variable depth infilled trenches. This innovative design not only achieves efficient surface wave isolation but also minimizes the consumption of structural materials. Based on the measured dominant frequency range of rail transit and the available soil parameters, variable depth infilled trenches are designed with suitable dimensions. The eigenvalue equation is solved using the finite element method to derive the dispersion relations and bandgap of identical regularly spaced trenches. To study the efficacy of the proposed structure, a finite element model of the soil-infilled trench system is developed using COMSOL. The mechanism underlying the isolation of surface wave is elucidated, and the effect of variable angle α on the isolation efficiency within 40-50 Hz η40-50Hz of surface waves is studied. The results of this study reveal that for variable angle α of 15°, the surface wave isolation efficiency within 40-50 Hz η40-50Hz is 90.9 % and 92.5 % for uniformly increasing depth infilled trenches and uniformly decreasing depth infilled trenches, respectively. Although the surface wave isolation efficiencies predicted for the variable depth infilled trench arrangements are only 93.8 % and 95.5 % of those predicted for the regularly spaced identical infilled trenches, the variable depth arrangements result in a remarkable 34 % reduction in material usage. These findings highlight the potential of the proposed variable depth infilled trenches as a cost-effective and efficient solution for surface wave isolation.

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Short-chain carboxylic acids (SCCAs) that are naturally produced by microbial fermentation play an essential role in delaying microbial spoilage. SCCAs are structurally diverse, but only a few of them are routinely used in food biopreservation. This study investigated the effects of environmental pH and intrinsic properties of 21 structurally different SCCAs on the antimicrobial and antibiofilm activity against Salmonella enterica. Inhibition of SCCA toward planktonic and biofilm growth of S. enterica was higher in an acidic environment (pH 4.5) that is common in fermented products, and for SCCA that possessed both a high acid dissociation strength (pKa) (>4.0) and a positive hydrophobicity [octanol/water partition coefficient (log Kow)]. Crotonic and caproic acids were identified as SCCAs with potential as biopreservatives even at near-neutral pH. SCCA with hydrophilic groups such as lactic acid did not inhibit S. enterica at concentrations up to 50 mM, while SCCA with benzene or methyl groups or a double bond prevented S. enterica growth and biofilm formation. Stimulation of biofilm formation was observed for formic, acetic, and propionic acid close to the minimum inhibitory concentration to reduce 50% of cell density (MIC50) of planktonic cells, and for citric and isocitric acid with an MIC50 of ≥50 mM. The presence of low concentrations of formic and propionic acids during biofilm formation conferred protection during eradication possibly due to a pre-adaptation effect, yet two consecutive acid treatments were successful in eradicating biofilms if the first acid treatment was two- to threefold of the MIC50.IMPORTANCEThis study provides a systematic comparison on the antimicrobial and antibiofilm activity of more than 20 structurally different SCCAs against a common food pathogen. We tested the antimicrobial activity at controlled pH and identified the structure-dependent antimicrobial effects of SCCA without the confounding influence of acidification. The combined effect of pKa and log Kow was identified as an important feature that should be considered when deciding for a specific SCCA in the application as antimicrobial. Our results imply that additional phenomena such as the use of SCCA as substrate and cellular pre-adaption effects have to be taken into consideration. We finally present a two-step treatment as an efficient approach to eradicate biofilms, which can be applied for the disinfection of contact surfaces and manufacturing equipment. Results obtained here can serve as guidelines for application of SCCA to avoid the growth of food pathogens and/or to develop biopreserved food systems.

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Nanocomposite materials are emerging as key players in addressing critical challenges in healthcare, energy storage, and environmental remediation. These innovative systems hold great promise in engineering effective solutions for complex problems. Nanocomposites have demonstrated various advantages such as simplicity, versatility, lightweight, and potential cost-effectiveness. By reinforcing synthetic and natural polymers with nanomaterials, a range of nanocomposites have exhibited unique physicochemical properties, biocompatibility, and biodegradability. Current research on nanocomposites has demonstrated promising clinical and translational applications. Over the past decade, the production of nanocomposites has emerged as a critical nano-structuring methodology due to their adaptability and controllable surface structure. This comprehensive review article systematically addresses two principal domains. A comprehensive survey of metallic and nonmetallic nanomaterials (nanofillers), elucidating their efficacy as reinforcing agents in polymeric matrices. Emphasis is placed on the methodical design and engineering principles governing the development of functional nanocomposites. Additionally, the review provides an exhaustive examination of recent noteworthy advancements in industrial, environmental, biomedical, and clinical applications within the realms of nanocomposite materials. Finally, the review concludes by highlighting the ongoing challenges facing nanocomposites in a wide range of applications.

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Triplet-state dissolved organic matter (3DOM⁎) plays a critical role in the photodegradation of organic pollutants in aquatic environments. This review offers a comprehensive overview of 3DOM⁎, focusing on monitoring methods using various probes, formation mechanisms, and photoreactivity. Traditional probes, such as 2,4,6-trimethylphenol (TMP) and sorbic acid, are widely used, while novel probes promise improved accuracy and sensitivity. The E2:E3 ratio emerges as a promising indicator for 3DOM⁎ due to its simplicity and correlation with photoreactivity, though further validation is needed to confirm its broader applicability. This review highlights the higher photoreactivity of DOM with low molecular weight, low aromaticity, and autochthonous sources, although DOM with contrasting features can also show significant photoreactivity. The presence of inorganic ions and nanomaterials significantly influences 3DOM⁎'s degradation capacity, demonstrating complex interactions with surrounding species. Additionally, the review underscores the importance of various environmental factors, including light source and DOM concentration, in affecting the photodegradation rates of contaminants. Recent literature suggests that future research should focus on developing new probes to capture different aspects of 3DOM⁎, exploring the synergistic effects of plastic leachate, and investigating the role of co-existing ions and nanomaterials on 3DOM⁎ activity. Employing machine learning (ML) techniques to predict 3DOM⁎-related parameters from easily measurable DOM descriptors presents an exciting research avenue. Enhanced understanding of 3DOM⁎ can lead to more effective strategies in wastewater treatment and environmental remediation.

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Identification of Cd sources and quantification of their contribution to rice grain Cd is crucial for controlling accumulation of this toxic metal in rice grains. However, accurate assessment of the contribution of different Cd sources to grain Cd concentration in rice under actual field conditions is a challenge. In this study, we determined Cd concentration and their isotopic compositions in rice grains with respect to three potential Cd sources around an e-waste dismantling area in Taizhou City, Zhejiang Province, China. Results demonstrated that average Cd concentrations in grains, surface soils, atmospheric deposition and surface water were 0.32, 0.91, 1.99 mg kg-1 and 2.02 µg L-1, respectively. The δ114/110Cd values of grains, surface soils, surface water and atmospheric deposition ranged from 0.00 ‰ to 0.31 ‰, -0.21 ‰ to 0.14 ‰, -0.04 ‰ to 0.47 ‰, and - 0.25 ‰ to -0.18 ‰, respectively. The MixSIAR model indicated that contribution of soils, irrigation water and atmospheric deposition to grain Cd was 56.8 %, 24.8 % and 18.4 %, respectively, demonstrating soils as the major source of grain Cd in the study area. This study also highlighted significant contribution of irrigation water and atmospheric deposition to Cd concentration in rice grains. The Cd isotopic analysis provides a practical approach for source apportionment of grain Cd and data support for controlling Cd accumulation in rice around the e-waste dismantling area.