The heavy-metal adsorbent ε-MnO₂ was produced through a simple, one-step oxidation-reduction reaction at three different synthesis temperatures (25 °C, 50 °C and 75 °C) and their morphology and chemical-physical properties were compared. Of the three materials, MnO₂-25 had the largest specific surface area and the highest surface hydroxyl concentration. Its optimal performance was demonstrated by batch adsorption experiments with Pb²⁺, Cd²⁺ and Cu²⁺. Of the three metals, Pb²⁺ was adsorbed best (339.15 mg/g), followed by Cd²⁺ (107.50 mg/g) and Cu²⁺ (86.30 mg/g). When all three metals were present, Pb²⁺ was still absorbed best but now more Cu²⁺ was adsorbed than Cd²⁺. In order to explore the mechanism for the inconsistent adsorption order of Cd²⁺ and Cu²⁺ in single and competitive adsorption, we combined experimental data with density functional theory (DFT) calculations to elucidate the distinct adsorption nature of MnO₂-25 towards these three metals. This revealed that the adsorption affinity of the (100) facet was superior to (001), and since the surface complexes were also more stable on (100), this facet was most likely determining the adsorption order for the single metals. When the metals were present in combination, Pb²⁺ preferentially occupied the active adsorption sites of (100), forcing Cu²⁺ to be adsorbed on the (001) facet where Cd²⁺ was only poorly bound. Thus, the adsorption behavior was affected by MnO₂-25 surface chemistry at a molecular scale. This study provides an in-depth understanding of the adsorption mechanisms of the heavy metals on this adsorbent and offers theoretical guidance for production of adsorbent with improved removal efficiency.

The massive generation of medical waste (MW) results in a series of environmental, social, and ecological problems. Pyrolysis is one such approach that has attracted more attention because of the production of value-added products with lesser environmental risk. In this study, the activated biochar (ABC600) was obtained from MW pyrolysis and activated with KOH. The adsorption mechanism of activated biochar on cationic (methylene blue) and anionic (reactive yellow) dyes were studied. The physicochemical characterization of biochar showed that increasing pyrolysis temperature and KOH activation resulted in increased surface area, a rough surface with a clear porous structure, and sufficient functional groups. MB and RYD-145 adsorption on ABC600 was more consistent with Langmuir isotherm (R² ≥ 0.996) and pseudo-second-order kinetics (R² ≥ 0.998), indicating chemisorption with monolayer characteristics. The Langmuir model fitting demonstrated that MB and RYD-145 had maximum uptake capacities of 922.2 and 343.4 mg⋅g⁻¹. The thermodynamics study of both dyes showed a positive change in enthalpy (ΔH°) and entropy (ΔS°), revealing the endothermic adsorption behavior and randomness in dye molecule arrangement on activated-biochar/solution surface. The activated biochar has excellent adsorption potential for cationic and anionic dyes; hence, it can be considered an economical and efficient adsorbent.

Rapid economic growth, industrialization, and urbanization have caused frequent air pollution events in East Asia over the last few decades. Recently, aerosol data from geostationary satellite sensors have been used to monitor ground-level particulate matter (PM) concentrations hourly. However, many studies have focused on using historical datasets to develop PM estimation models, often decreasing their predictability for unseen data in new days. To mitigate this problem, this study proposes a novel real-time learning (RTL) approach to estimate PM with aerodynamic diameters of <10 μm (PM₁₀) and <2.5 μm (PM₂.₅) using hourly aerosol data from the Geostationary Ocean Color Imager (GOCI) and numerical model outputs for daytime conditions over Northeast Asia. Three schemes with different weighting strategies were evaluated using 10-fold cross-validation (CV). The RTL models, which considered both concentration and time as weighting factors (i.e., Scheme 3) yielded consistent improvement for 10-fold CV performance on both hourly and monthly scales. The real-time calibration results for PM₁₀ and PM₂.₅ were R² = 0.97 and 0.96, and relative root mean square error (rRMSE) = 12.1% and 12.0%, respectively, and the 10-fold CV results for PM₁₀ and PM₂.₅ were R² = 0.73 and 0.69 and rRMSE = 41.8% and 39.6%, respectively. These results were superior to results from the offline models in previous studies, which were based on historical data on an hourly scale. Moreover, we estimated PM concentrations in the ocean without using land-based variables, and clearly demonstrated the PM transport over time. Because the proposed models are based on the RTL approach, the density of in-situ monitoring sites could be a major uncertainty factor. This study identified that a high error occurred in low-density areas, whereas a low error occurred in high-density areas. The proposed approach can be operated to monitor ground-level PM concentrations in real-time with uncertainty analysis to ensure optimal results.

Phytoplankton contribute approximately 50% to the global photosynthetic carbon (C) fixation. However, our understanding of the corresponding C sequestration capacity and driving mechanisms associated with each individual phytoplankton taxonomic group is limited. Particularly in the hydrologically dynamic system with highly complex surface hydrological processes (floodplain lake systems). Through investigating seasonal monitoring data in a typical floodplain lake system and estimation of primary productivity of each phytoplankton taxonomic group individually using novel equations, this study proposed a phytoplankton C fixation model. Results showed that dominant phytoplankton communities had a higher gross carbon sequestration potential (CSP) (9.50 ± 5.06 Gg C each stage) and gross primary productivity (GPP) (65.46 ± 25.32 mg C m⁻² d⁻¹), but a lower net CSP (−1.04 ± 0.79 Gg C each stage) and net primary productivity (NPP) (−5.62 ± 4.93 mg C m⁻³ d⁻¹) than rare phytoplankton communities in a floodplain lake system. Phytoplanktonic GPP was high (317.94 ± 73.28 mg C m⁻² d⁻¹) during the rainy season and low (63.02 ± 9.65 mg C m⁻² d⁻¹) during the dry season. However, their NPP reached the highest during the rising-water stage and the lowest during the receding-water stage. Findings also revealed that during the rainy season, high water levels (p = 0.56**) and temperatures (p = 0.37*) as well as strong solar radiation (p = 0.36*) will increase photosynthesis and accelerate metabolism and respiration of dominant phytoplankton communities, then affect primary productivity and CSP. Additionally, water level fluctuations drive changes in nutrients (p = −0.57*) and metals (p = −0.68*) concentrations, resulting in excessive nutrients and metals slowing down phytoplankton growth and reducing GPP. Compared with the static water lake system, the floodplain lake system with a lower net CSP became a heterotrophic C source.

Microplastics (MPs), plastic particles <5 mm in diameter, have become an emerging ubiquitous concern for the environment. Rivers are the primary pathways that transport MPs from the land to the ocean; however, standardized methodologies for in-situ sampling in freshwater environments remain undefined. Notably, uncertainties in MP sampling methods lead to errors in estimating MP discharge through rivers. In the present study, the inter-sample variance of plankton net-obtained MP concentrations for two urban rivers in Japan was investigated. Numerical concentrations, expressed in particles·m⁻³, revealed that variance s2 was proportional to the mean m of replicated estimates of numerical concentrations. A derived statistical model suggested that river MPs disperse according to purely random processes; that is, Poisson point processes. Accordingly, a method was established to project the “precision,” the ratio of the standard error to m, of numerical concentrations based on the number of net sampling repetitions. It was found that the mean of two replicates maintained sufficient precision of <30% for conditions with high concentrations of ≥3 particles·m⁻³. Projected precisions under different levels of MP concentrations are also presented to help design future field campaigns.

Indoor dust has been postulated as an important matrix for residential pesticide exposure. However, there is a lack of information on presence, concentrations and determinants of multiple pesticides in dust in residential homes close to treated fields. Our objective was to characterize the spatial and temporal variance of pesticides in house dust, study the use of doormats and floors as proxies for pesticides in indoor dust and identify determinants of occurrence and concentrations. Homes within 250 m from selected bulb fields were invited to participate. Homes within 20 km from these fields but not having agricultural fields within 500 m were selected as controls. House dust was vacuumed in all homes from floors (VFD) and from newly placed clean doormats (DDM). Sampling was done during two periods, when pesticides are used and not-used. For determination of 46 prioritized pesticides, a multi-residue extraction method was used. Most statistical analyses are focused on the 12 and 14 pesticides that were detected in >40% of DDM and VFD samples, respectively. Mixed models were used to evaluate relationships between possible determinants and pesticides occurrence and concentrations in DDM and VFD. 17 pesticides were detected in more than 50% of the homes in both matrixes. Concentrations differed by about a factor five between use and non-use periods among homes within 250 m of fields and between these homes and controls. For 7 pesticides there was a moderate to strong correlation (Spearman rho 0.30–0.75) between concentrations in DDM and VFD. Distance to agricultural fields and air concentrations were among the most relevant predictors for occurrence and levels of a given pesticide in DDM. Concentrations in dust are overall higher during application periods and closer to fields (<250 m) than further away. The omnipresence of pesticides in dust lead to residents being exposed all year round.

Volatile organic compounds (VOCs) represent a considerable threat to humans and ecosystems. Strategic remediation techniques for the abatement of VOCs are immensely important and immediately needed. Given a unique set of optical, mechanical, electrical, and thermal characteristics, inimitable surface functionalities, porous structure, and substantial specific surface area, graphene and derived nanohybrid composites have emerged as exciting candidates for abating environmental pollutants through photocatalytic degradation and adsorptive removal. Graphene oxide (GO) and reduced graphene oxide (rGO) containing oxygenated function entities, i.e., carbonyl, hydroxyl, and carboxylic groups, provide anchor and dispersibility of their surface photocatalytic nanoscale particles and adsorptive sites for VOCs. Therefore, it is meaningful to recapitulate current state-of-the-art research advancements in graphene-derived nanostructures as prospective platforms for VOCs degradation. Considering this necessity, this work provides a comprehensive and valuable insight into research progress on applying graphene-based nanohybrid composites for adsorptive and photocatalytic abatement of VOCs in the aqueous media. First, we present a portrayal of graphene-based nanohybrid based on their structural attributes (i.e., pore size, specific surface area, and other surface features to adsorb VOCs) and structure-assisted performance for VOCs abatement by graphene-based nanocomposites. The adsorptive and photocatalytic potentialities of graphene-based nanohybrids for VOCs are discussed with suitable examples. In addition to regeneration, reusability, and environmental toxicity aspects, the challenges and possible future directions of graphene-based nanostructures are also outlined towards the end of the review to promote large-scale applications of this fascinating technology.

Systemic studies on the bioremediation of co-contaminated PAHs and heavy metals are lacking, and this paper provides an in-depth review on the topic. The released sources and transport of co-contaminated PAHs and heavy metals, including their co-occurrence through formation of cation-π interactions and their adsorption in soil are examined. Moreover, it is investigated that co-contamination of PAHs and heavy metals can drive a synergistic positive influence on bioremediation through enhanced secretion of extracellular polymeric substances (EPSs), production of biosynthetic genes, organic acid and enzymatic proliferation. However, PAHs molecular structure, PAHs-heavy metals bioavailability and their interactive cytotoxic effects on microorganisms can exert a challenging influence on the bioremediation under co-contaminated conditions. The fluctuations in bioavailability for microorganisms are associated with soil properties, chemical coordinative interactions, and biological activities under the co-contaminated PAHs-heavy metals conditions. The interactive cytotoxicity caused by the emergence of co-contaminants includes microbial cell disruption, denaturation of DNA and protein structure, and deregulation of antioxidant biological molecules. Finally, this paper presents the emerging strategies to overcome the bioavailability problems and recommends the use of biostimulation and bioaugmentation along with the microbial immobilization for enhanced bioremediation of PAHs-heavy metals co-contaminated sites. Better knowledge of the bioremediation potential is imperative to improve the use of these approaches for the sustainable and cost-effective remediation of PAHs and heavy metals co-contamination in the near future.

Headwater streams are a hotspot of freshwater biodiversity, carrying indispensable resource pools of aquatic species. However, up to now, there remain many challenges to accurately and efficiently characterize the responses of this vulnerable ecosystem to human-induced changes. Here, we collected macroinvertebrate data from 12 different headwater streams in the Liao River of northeast China by DNA metabarcoding approach, to reveal biodiversity changes and ecological thresholds affected by human beings. Our data showed that the community composition and structure of headwater streams had unique and significant differences under human impacts, and 5-day biological oxygen demand (BOD₅) and ammonia nitrogen (NH₃–N) were the key variables explaining the variation in community structure. Although α diversity had a unimodal relationship with nutrients and organic loads, β diversity and its turnover component (species replacement) increased significantly. In addition, 22 and 33 indicative taxa were identified to have significant negative responses to BOD₅ and NH₃–N, respectively, and the change points derived from Threshold Indicator Taxa Analysis (TITAN) for the negative response of their frequency and abundance were BOD₅ >3.42 mg/L and NH₃–N >0.14 mg/L. Overall, this study reveals the biodiversity changes in headwater streams from the aspects of α and β diversity, and also determines the thresholds of BOD₅ and NH₃–N pollutants for one reach at one date from 12 headwater streams, suggesting the potential of DNA metabarcoding approach for threshold analyses in headwater streams.

Climate changes and metal contamination are pervasive stressors for soil ecosystems. Mercury (Hg), one of the most toxic metals, has been reported to interact with temperature. However, compared to aquatic biota, little is known about how temperature affects Hg toxicity and bioaccumulation to soil organisms. Here, toxicity and bioaccumulation experiments were replicated at 15 °C, 20 °C, and 25 °C to understand how sub-optimal temperatures affect the toxicokinetics and toxicodynamics of Hg via soil. Genotoxicity and energy reserves were also assessed to disclose potential trade-offs in life-history traits. Results underpin the complexity of temperature-Hg interactions. Survival was determined mainly by toxicokinetics, but toxicodynamics also played a significant role in defining survival probability during early stages. The processes determining survival probability were faster at 25 °C: General Unified Threshold of Survival (GUTS) model identified an earlier/steeper decline in survival, compared to 20 °C or 15 °C, but it also approached the threshold faster. Despite potentiation of Hg genotoxicity, temperature promoted faster detoxification, either increasing toxicokinetics rates or damage repair mechanisms. This metabolism-driven increase in detoxification led to higher depletion of energy reserves and likely triggered stress response pathways. This work emphasized the need for comprehensive experimental approaches that can integrate the multiple processes involved in temperature-metal interactions.