This study aims to better understand the aging characteristics of microplastics in the environment and the influence of aging microplastics on the migration and transformation of organic pollutants. In this study, polyvinyl chloride (PVC) and polyethylene (PE) were chosen as research objects, and the effects of two aging methods (freeze-thaw cycle aging and high-temperature oxidation aging) on their surface properties and atrazine (ATZ) sorption were investigated. The crystallinity of PE increased after freeze-thaw cycling and decreased after high-temperature oxidation. The freeze-thaw cycle destroys the amorphous region of PE, reducing the micropores on the PE surface and decreasing the ATZ adsorbed by PE. Although aging had no significant effect on the surface structure of PVC, it caused new oxygen-containing functional groups to be produced on the PVC surface, which reduced the ATZ adsorption capacity. These results show that the two aging modes change the surface properties of PVC and PE, thus affecting the sorption mechanism of ATZ, and provide a theoretical premise for the natural behavior and ecological chance assessment of ATZ in the presence of microplastics.

The widespread use of decabromodiphenyl ether (BDE-209) resulted in its deposition in environmental media and biological matrices. However, to date, few studies focused on the effect of BDE-209 on microorganisms, and those available were investigated via an enclosed system completely cutting off the communication between testing system and its native environment. Herein, 4.0 mg/g BDE-209 acute exposure induced a 20% decline of NOX-N (the sum of NO₃⁻–N and NO₂⁻–N) removal efficiency and a significant accumulation of NO₂⁻–N and N₂O. These inhibitory effects presented in a BDE-209 concentration-dependent manner. Using a semi-continuous microcosm, the inhibitory effects of BDE-209 on denitrification were observed to be significantly enhanced with the extending of exposure duration. Denitrifying genes assay illustrated that BDE-209 has an insignificant effect on the global abundance of denitrifying bacteria because of microbial exchange with its overlying water. But the utilization of electron donor (carbon substrate), the activity of electron transport system and denitrifying enzymes were significantly inhibited by BDE-209 exposure in a exposure-duration-dependent manner. Finally, insufficient electron donor and lower efficiency of electron transport and utilization on denitrifying enzymes deteriorated the denitrification performance. These results provided a new insight into BDE-209 influence on denitrification in the natural environment.

Biodegradation of microplastics (MPs) in contaminated biowastes has received big scientific attention during the past few years. The aim here is to study the impacts of livestock manure biochar (LMBC) on the biodegradation of polyhydroxyalkanoate microplastics (PHA-MPs) during composting, which have not yet been verified. LMBC (10% wt/wt) and PHA-MPs (0.5% wt/wt) were added to a mixture of pristine cow manure and sawdust for composting, whereas a mixture without LMBC served as the control (CK). The maximum degradation rate of PHA-MPs (22–31%) was observed in the thermophilic composting stage in both mixtures. LMBC addition significantly (P < 0.05) promoted PHA-MPs degradation and increased the carbon loss and oxygen loading of PHA-MPs compared to CK. Adding LMBC accelerated the cleavage of C–H bonds and oxidation of PHA-MPs, and increased the O–H, CO and C–O functional groups on MPs. Also, LMBC addition increased the relative abundance of dominant microorganisms (Firmicutes, Proteobacteria, Deinococcus-Thermus, Bacteroidetes, Ascomycota and Basidiomycota) and promoted the enrichment of MP-degrading microbial biomarkers (e.g., Bacillus, Thermobacillus, Luteimonas, Chryseolinea, Aspergillus and Mycothermus). LMBC addition further increased the complexity and connectivity between dominant microbial biomarkers and PHA-MPs degradation characteristics, strengthened their positive relationship, thereby accelerated PHA-MPs biodegradation, and mitigated the potential environmental and human health risk. These findings provide a reference point for reducing PHA-MPs in compost and safe recycling of MPs contaminated organic wastes. However, these results should be validated with other composting matrices and conditions.

Carbonaceous aerosols pose significant climatic impact, however, their sources and respective contribution to light absorption vary and remain poorly understood. In this work, filter-based PM₂.₅ samples were collected in winter of 2021 at three urban sites in Yibin, a fast-growing city in the south of Sichuan Basin, China. The composition characteristics of PM₂.₅, light absorption and source of carbonaceous aerosol were analyzed. The city-wide average concentration of PM₂.₅ was 87.4 ± 31.0 μg/m³ in winter. Carbonaceous aerosol was the most abundant species, accounting for 42.5% of the total PM₂.₅. Source apportionment results showed that vehicular emission was the main source of PM₂.₅ during winter, contributing 34.6% to PM₂.₅. The light absorption of black carbon (BC) and brown carbon (BrC) were derived from a simplified two-component model. We apportioned the light absorption of carbonaceous aerosols to BC and BrC using the Least Squares Linear Regression with optimal angstrom absorption exponent of BC (AAEBC). The average absorption of BC and BrC at 405 nm were 51.6 ± 21.5 Mm⁻¹ and 17.7 ± 8.0 Mm⁻¹, respectively, with mean AAEBC = 0.82 ± 0.02. The contribution of BrC to the absorption of carbonaceous reached 26.1% at 405 nm. Based on the PM₂.₅ source apportionment and the mass absorption cross-section (MAC) value of BrC at 405 nm, vehicle emission was found to be the dominant source of BrC in winter, contributing up to 56.4%. Therefore, vehicle emissions mitigation should be the primary and an effective way to improve atmospheric visibility in this fast-developing city.

Plastic film mulch (PFM) is a double-edged-sword agricultural technology, which greatly improves global agricultural production but can also cause severe plastic pollution of the environment. Here, we characterized and quantified the amount of macro- and micro-plastics accumulated after 32 years of continuous plastic mulch film use in an agricultural field. An interactive field trial was established in 1987, where the effect of plastic mulching and N fertilization on maize yield was investigated. We assessed the abundance and type of macroplastics (>5 mm) at 0–20 cm soil depth and microplastic (<5 mm) at 0–100 cm depth. In the PFM plot, we found about 10 times more macroplastic particles in the fertilized plots than in the non-fertilized plots (6796 vs 653 pieces/m²), and the amount of film microplastics was about twice as abundant in the fertilized plots than in the non-fertilized plots (3.7 × 10⁶ vs 2.2 × 10⁶ particles/kg soil). These differences can be explained by entanglement of plastics with plant roots and stems, which made it more difficult to remove plastic film after harvest. Macroplastics consisted mainly of films, while microplastics consisted of films, fibers, and granules, with the films being identified as polyethylene originating from the plastic mulch films. Plastic mulch films contributed 33%–56% to the total microplastics in 0–100 cm depth. The total number of microplastics in the topsoil (0–10 cm) ranged as 7183–10,586 particles/kg, with an average of 8885 particles/kg. In the deep subsoil (80–100 cm) the plastic concentration ranged as 2268–3529 particles/kg, with an average of 2899 particles/kg. Long-term use of plastic mulch films caused considerable pollution of not only surface, but also subsurface soil. Migration of plastic to deeper soil layers makes removal and remediation more difficult, implying that the plastic pollution legacy will remain in soil for centuries.

Proteinaceous matter is an important component of PM₂.₅, which can cause adverse health effects and also influence the air quality and climate change. However, there is little attention to high time-resolved variations and potential role of aerosol proteins during haze pollution periods. In this study, PM₂.₅ samples were first collected by a medium flow sampler in autumn and winter in Xi'an, China. Then three high time-resolved monitoring campaigns during haze pollution periods were conducted to determine the evolving characteristics of total protein concentration and explore the interactive relationship between protein and other chemical compositions. The results showed that the average protein concentration in PM₂.₅ in Xi'an (5.46 ± 3.32 μg m⁻³) was higher than those in most cities of China, and varied by seasons and air pollution conditions. In particular, the protein concentration in PM₂.₅ increased with the increase of air quality index (AQI). The continuous variations of aerosol proteins during the haze pollution periods further showed that PM₂.₅, atmospheric humidity and long-distance air mass transport exerted the significant impacts on the protein components in aerosols. Based on the present observation, it is suggested that aerosol proteins might affect the generation of secondary aerosols under haze weather conditions. The present results may provide a new possible insight into the variations and the role of aerosol proteinaceous matter during the formation and development of haze pollution.

Heavy metals (HMs) in soil and water bodies greatly threaten human health. The wide separation of HMs urges the necessity to develop an expert system for HMs prediction and detection. In the current perspective, several propositions are discussed to design an innovative intelligence system for HMs prediction and detection in soil and water bodies. The intelligence system incorporates the Edge Cloud Server (ECS) data center, an innovative deep learning predictive model and the Federated Learning (FL) technology. The ECS data center is based on satellite sensing sources under human expertise ruling and HMs in-situ measurement. The FL system comprises a machine learning (ML) technique that trains an algorithm across multiple decentralized edge servers holding local data samples without exchanging them or breaching data privacy. The expected outcomes of the intelligence system are to quantify the soil and water bodies' HMs, develop new modified HMs pollution contamination indices and provide decision-makers and environmental experts with an appropriate vision of soil, surface water, and crop health.

Land use regression (LUR) models have been widely used in epidemiological studies and risk assessments related to air pollution. Although efforts have been made to improve the performance of LUR models so that they capture the spatial heterogeneity of fine particulate matter (PM₂.₅) in high-density cities, few studies have revealed the vertical differences in PM₂.₅ exposure. This study proposes a three-dimensional LUR (3-D LUR) assessment framework for PM₂.₅ exposure that combines a high-resolution LUR model with a vertical PM₂.₅ variation model to investigate the results of horizontal and vertical mobile PM₂.₅ monitoring campaigns. High-resolution LUR models that were developed independently for daytime and nighttime were found to explain 51% and 60% of the PM₂.₅ variation, respectively. Vertical measurements of PM₂.₅ from three regions were first parameterized to produce a coefficient of variation for the concentration (CVC) to define the rate at which PM₂.₅ changes at a certain height relative to the ground. The vertical variation model for PM₂.₅ was developed based on a spline smoothing function in a generalized additive model (GAM) framework with an adjusted R² of 0.91 and explained 92.8% of the variance. PM₂.₅ exposure levels for the population in the study area were estimated based on both the LUR models and the 3-D LUR framework. The 3-D LUR framework was found to improve the accuracy of exposure estimation in the vertical direction by avoiding exposure estimation errors of up to 5%. Although the 3-D LUR-based assessment did not indicate significant variation in estimates of premature mortality that could be attributed to PM₂.₅, exposure to this pollutant was found to differ in the vertical direction. The 3-D LUR framework has the potential to provide accurate exposure estimates for use in future epidemiological studies and health risk assessments.

The contamination status of heavy metals in urban environment changes frequently with the industrial structure adjustment, energy conservation and emission reduction and thus requires timely investigation. Based on enrichment factor, multivariate statistical analysis and isotope fingerprinting, we assessed comprehensively the inputs and sources of heavy metals in different samples from an urban area that was less impacted by leaded gasoline exhaust. The road dust contained relatively high levels of Cr, Pb and Zn (with enrichment factor >2) that originated from both exhaust and non-exhaust traffic emissions, while the moss plants could accumulate high levels of Pb and Zn from the deposition of traffic exhaust emission. This suggest that the traffic emission is still an important source of metals in the urban area although gasoline is currently lead free. On the contrary, the occurrences of metals in the urban soils were controlled by natural sources and non-traffic anthropogenic emission. These findings revealed that different samples would receive different inputs of metals from different sources in the urban area, and the responsiveness and sensitiveness of these urban samples to metal inputs can be ranked as moss ≥ dust > soil. Taken together, our results suggested that in order to avoid generalizing and get detail source information, multi-samples and multi-measures must be adopted in the assessment of integrated urban environmental quality.