Journal of Environmental Sciences-china最新文献

Methane (CH₄) is the second greenhouse gas and has a profound impact on global climate change due to its high global warming potential and concentration. By 2022, the CH₄ concentration was approximately 1.9 ppm, which was 264% of the pre-industrial level. The spatiotemporal distribution of CH₄ was investigated by a portable CH₄ detector on an unmanned aerial vehicle and electric bicycles in Shaoxing, a city situated in the Yangtze River Delta, China. The vertical distribution revealed CH₄ concentration generally decreased slowly with height. However, the inversion condition and low atmospheric boundary layer height (ABLH) leaded to the enhancement of CH₄ with height. The highest CH₄ concentration (2.2 ± 0.1 ppm, n = 1428) was observed in winter and the lowest (2.0 ± 0.2 ppm, n = 1530) in spring. Regarding the daily variation, CH₄ concentration peaked at 5:00 local time (LT) and reached its lowest level at 14:00 LT, which was attributed to the daily variation of ABLH, lowest in the early morning and highest in the noon. In urban areas, CH₄ concentrations showed higher levels near restaurants, natural gas stations and sewerage well, with a maximum value of 13.1 ppm, which was caused by CH₄ emission and natural gas leakage from these places. The annual CH₄ emission in Shaoxing were estimated to be approximately 69 ton/(km²·year) by the mass balance approach. Compared with other cities in the world, the CH₄ emission is in higher level which imply some control measures should be conducted to reduce CH₄ emission in Shaoxing.

The floodplain of the Yellow River is a typical area characterized by redox fluctuations and heavy metal pollution. However, the mobilization behavior of heavy metals in floodplain sediments during redox fluctuations remains poorly understood. In this study, reductive mobilization of Fe and Mn was observed under reducing environments through reduction and dissolution, leading to the subsequent release of adsorbed As. In contrast, the mobilization of U occurred under oxic conditions, as the oxidative state of U(VI) has higher solubility. Furthermore, insignificant effects on the mobilization of Cd, Cu, Pb, and Hg were noticed during redox fluctuations, indicating higher stability of these heavy metals. Additionally, we demonstrated that carbon sources can play a key role in the mobilization of heavy metals in floodplain sediments, amplifying the reductive mobilization of Fe, Mn, As and the oxidative mobilization of U. Our findings contribute to the understanding of the biogeochemical cycling of heavy metal in floodplain sediments of the Yellow River and the factors that control this cycling.

In recent years, the biodegradable plastics has extensively used in industry, agriculture, and daily life. Herein, the effects of two biodegradable microplastics (BMPs), poly(butyleneadipate-co-terephthalate) (PBAT) and polyhydroxyalkanoate (PHA), on soil sulfamethoxazole (SMX) degradation and sul genes development were comparatively studied based on the type, dosage, and state. The addition of virgin BMPs significantly increased soil DOC following a sequential order PBAT > PHA and high dose > low dose. Meanwhile virgin PBAT significantly reduced soil pH. In general, the addition of BMPs not only promoted soil SMX degradation but also increased the abundance of sul genes, with an exception that pH reduction in virgin PBAT inhibited the proliferation of sul genes. The driving effects of BMPs on soil microbial diversity following the same order as that on DOC. Specific bacteria stimulated by BMPs, such as Arthrobacter and two genera affiliated with phylum TM7, accounted for the accelerated degradation of SMX. Intriguingly, UV-aging hindered the release of DOC from BMPs and the reduction in pH, mitigated the stimulation of microbial communities, and ultimately reduced the promotion effect of BMPs on SMX degradation and sul genes proliferation. Our results suggest that more attention should be paid to the proliferation risk of ARGs in the environment affected by BMPs and UV-aging can be employed sometimes to reduce this risk.

Microalgae are one of the promising feedstocks for biorefinery, contributing significantly to net-zero emissions through carbon capture and utilization. However, the disposal of microalgal byproducts from the manufacturing process causes additional environmental pollution, thus, a new application strategy is required. In this study, the Tetraselmis suecica byproduct from the carotenoid extraction process was carbonized and converted into biochar. The converted biochar was proved to be nitrogen-doped biochar (NDB), up to 4.69%, with a specific surface area of 206.59 m²/g and was used as an electrode for a supercapacitor. The NDB electrode (NDB-E) in half-cell showed a maximum specific capacitance of 191 F/g. In a full-cell test, the NDB-E exhibited a high energy density of 7.396 Wh/kg and a high-power density of 18,100 W/kg, and maintained specific capacity of 95.5% after charge and discharge of 10,000 cycles. In conclusion, our study demonstrated that the carotenoid-extracted microalgal byproducts are a useful resource for the supercapacitor production. This approach is the first to convert T. suecica into active materials for supercapacitors.

PM_2.5 constitutes a complex and diverse mixture that significantly impacts the environment, human health, and climate change. However, existing observation and numerical simulation techniques have limitations, such as a lack of data, high acquisition costs, and multiple uncertainties. These limitations hinder the acquisition of comprehensive information on PM_2.5 chemical composition and effectively implement refined air pollution protection and control strategies. In this study, we developed an optimal deep learning model to acquire hourly mass concentrations of key PM_2.5 chemical components without complex chemical analysis. The model was trained using a randomly partitioned multivariate dataset arranged in chronological order, including atmospheric state indicators, which previous studies did not consider. Our results showed that the correlation coefficients of key chemical components were no less than 0.96, and the root mean square errors ranged from 0.20 to 2.11 µg/m³ for the entire process (training and testing combined). The model accurately captured the temporal characteristics of key chemical components, outperforming typical machine-learning models, previous studies, and global reanalysis datasets (such as Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and Copernicus Atmosphere Monitoring Service ReAnalysis (CAMSRA)). We also quantified the feature importance using the random forest model, which showed that PM_2.5, PM₁, visibility, and temperature were the most influential variables for key chemical components. In conclusion, this study presents a practical approach to accurately obtain chemical composition information that can contribute to filling missing data, improved air pollution monitoring and source identification. This approach has the potential to enhance air pollution control strategies and promote public health and environmental sustainability.

Black carbon (BC) aerosol can lead to adverse health effects and drive climate change; therefore, the characteristic research and identification of BC sources are essential for lowering emissions. In this study, equivalent black carbon (eBC) measurement was performed using a seven-wavelength Aethalometer (AE33) at an urban site in a typical industrial city (Zibo) of Northern China for the first time. The monitoring was performed from February 2021 to January 2022. The mass absorption cross-section (MAC) of AE33 was optimised using the online elemental carbon (EC) data, and eBC was corrected using the MAC. The corrected annual BC concentration was 1.72 ± 1.18 µg/m³. The diurnal variation of BC depicted a bimodal distribution. Furthermore, the BC concentration on weekends was 18 % lower than on weekdays. The diurnal variation and weekend effect reflect the critical contributions of traffic emission to BC concentration. The source apportionment of BC was calculated by a constraining Aethalometer model, which restricted the Ångström exponent using the online potassium ions. The results revealed that BC was not significantly affected by biomass burning (BC_bb) in Zibo. The relative contribution of BC_bb was higher in winter than in other seasons. The daily morning peak of BC was primarily influenced by traffic sources, whereas the contribution of biomass burning increased after 17:00 in the evening peak. Our findings suggest that it is more important to control fossil fuel sources for BC emission reduction in Zibo, while it is necessary to strengthen the control of biomass combustion sources in winter.

Aerosol hygroscopicity and liquid water content (ALWC) have important influences on the environmental and climate effect of aerosols. In this study, we measured the hygroscopic growth factors (GF) of particles with dry diameters of 40, 80, 150, and 200 nm during the wintertime in Nanjing. Both the GF-derived hygroscopicity parameter (κ_gf) and ALWC increased with particle size, but displayed differing diurnal variations, with κ_gf peaking around the midday, while ALWC peaking in the early morning. Nitrate, ammonium and oxygenated organic aerosols (OOA) were found as the chemical components mostly strongly correlated with ALWC. A closure study suggests that during midday photo-oxidation and nighttime high ALWC periods, the κ of organic aerosols (κ_org) was underestimated when using previous parameterizations. Accordingly, we re-constructed parameterizations for κ_org and the oxidation level of organics for these periods, which indicates a higher hygroscopicity of photochemically formed OOA than the aqueous OOA, yet both being much higher than the generally assumed OOA hygroscopicity. Additionally, in a typical high ALWC episode, concurrently increased ALWC, nitrate, OOA as well as aerosol surface area and mass concentrations were observed under elevated ambient RH. This strongly indicates a coupled effect that the hygroscopic secondary aerosols, in particular nitrate with strong hygroscopicity, led to large increase in ALWC, which in turn synergistically boosted nitrate and OOA formation by heterogeneous/aqueous reactions. Such interaction may represent an important mechanism contributing to enhanced formation of secondary aerosols and rapid growth of fine particulate matter under relatively high RH conditions.

Per- and polyfluoroalkyl substances (PFASs) can induce a range of adverse health effects, with the precise molecular mechanisms remaining elusive. Extracellular vesicles (EVs) have demonstrated their potential to elucidate unknown molecular mechanisms. Building upon the close alignment of their biological functions with the observed health effects of PFASs, this study innovatively focuses on proteomic insights from EVs into the molecular mechanisms underlying the systemic health effects of PFASs. Through rat exposure experiments and proteomics technology, it not only demonstrated the occurrence of PFASs in EVs but also revealed the alterations in the serum EVs and the expression of their protein cargos following mixed exposure to PFASs, leading to changes in related pathways. These changes encompass various biological processes, including proteasome activity, immune response, cytoskeletal organization, oxidative stress, cell signaling, and nervous system function. Particularly noteworthy is the uncovering of the activation of the proteasome pathway, highlighting significant key contributing proteins. These novel findings provide a new perspective for exploring the molecular mechanism underlying the systemic health effects of PFASs and offer reliable screening for potential biomarkers. Additionally, comparisons with serum confirmed the potential of serum EVs as biological responders and measurable endpoints for evaluating PFASs-induced toxicity.

N-participated lignin depolymerization is of great importance for the transformation of waste lignin into value-added chemicals. The vast majority of developed strategies employ organic amines as nitrogen source, and considerable methods rely on excessive use of strong base, which suffers severe environmental issues. Herein, benzonitrile derivatives are synthesized from oxidized lignin β-O-4 model compounds in the presence of solid nitrogen source (NH₄)₂CO₃ under mild, base-free conditions over commercially available copper catalyst. Mechanism studies suggest the transformation undergoes a one-pot, highly coupled cascade reaction path involving oxidative C-C bond cleavage and in-situ formation of CN bond. Of which, Cu(OAc)₂ catalyzes the transfer of hydrogen from C_β (C_β-H) to C_α, leading to the cleavage of C_α-C_β bonds to offer benzaldehyde derivative, this intermediate then reacts in-situ with (NH₄)₂CO₃ to afford the targeted aromatic nitrile product. Tetrabutylammonium iodide (TBAI), acting as a promoter, plays a key role in breaking the C_α-C_β bonds to form the intermediate benzaldehyde derivative. With this protocol, the feasibility of the production of value-added syringonitrile from birchwood lignin has been demonstrated. This transformation provides a sustainable approach to benzonitrile chemicals from renewable source of lignin.

There is growing concern about the concept that exposure to environmental chemicals may be contributing to the obesity epidemic. However, there is no consensus on the obesogenic effects of emerging contaminants from a toxicological and environmental perspective. The potential human exposure and experimental evidence for obesogenic effects of emerging contaminants need to be systematically discussed. The main objective of this review is to provide recommendations for further subsequent policy development following a critical analysis of the literature for humans and experimental animals exposed to emerging contaminants. This article reviews human exposure to emerging contaminants (with a focus on antimicrobials, preservatives, water and oil repellents, flame retardants, antibiotics and bisphenols) and the impact of emerging contaminants on obesity. These emerging contaminants have been widely detected in human biological samples. Epidemiological studies provide evidence linking exposure to emerging contaminants to the risks of obesity in humans. Studies based on animal models and adipose cells show the obesogenic effects of emerging contaminants and identify modes of action by which contaminants may induce changes in body fat accumulation and lipid metabolic homeostasis. Some knowledge gaps in this area and future directions for further investigation are discussed.