The study investigates the spatio-temporal dynamics of anthropogenic emissions in China under a carbon-neutral scenario, with a focus on synergistic reductions in carbon dioxide (CO₂), volatile organic compounds (VOCs), and nitrogen oxides (NO_x). Using the Dynamic Projection model for Emissions in China (DPEC), emissions trends were analyzed and compared with two Shared Socio-economic Pathway (SSP) scenarios (SSP1-1.9 and SSP1-2.6). The findings reveal that under the DPEC carbon-neutral scenario, CO₂ emissions will peak by 2030 and decrease by 91% by 2060 relative to 2020 levels. Emissions of VOCs and NO_x show continuous reductions since 2020, with declines of 65% and 88%, respectively, by 2060. Compared to the two SSP scenarios, the DPEC scenario shows a weaker reduction in VOCs but a stronger reduction in NO_x. Sectoral analysis highlights that CO₂ reductions primarily stem from the energy and industrial sectors, whereas the transportation sector drives notable decreases in VOCs and NO_x. By 2060, the industrial sector will remain the dominant source of emissions for CO₂, VOCs, and NO_x. The results suggest that the DPEC carbon-neutral scenario aligns closely with China's future emission reduction trends, demonstrating significant potential for synergistic emission reductions. Achieving these targets on schedule will require robust policy implementation and sectoral commitment, offering substantial improvements in air quality and environmental outcomes.

Earthworm (Pheretima guillelmi) was selected as the model animal. Combination of in situ determination, high-throughput sequencing and biochemical analysis, the results indicated that the production of Fe(Ⅱ) was highest in the glucose treatment group and lowest in the amino acid setup. During the iron(Ⅲ) reduction process, the content of surface-adsorbed Fe(Ⅱ) was the highest, ranging from 0.6 to 24.38mmol/L;whereas the content of ionic Fe(Ⅱ) was the lowest, ranging from 0.02 to 2.21mmol/L. The community structure of iron(Ⅲ)-reducing bacteria was significantly influenced by the type of organic matter, and the dominant iron(Ⅲ)-reducing bacteria in different treatment groups were diverse. Additionally, the iron(Ⅲ) reduction process was accompanied by the generation of reactive oxygen species (ROS). The content of hydrogen peroxide (H₂O₂) was the highest, ranging from 0.32 to 0.73mmol/L, and be show a significant positive correlation with the contents of ionic Fe²⁺, surface-adsorbed Fe(Ⅱ), and high-crystalline iron, while exhibiting a significant negative correlation with the content of iron in organic complex state. Hydroxyl radical (^•OH) has a significant positive correlation with ionic Fe²⁺, adsorbed Fe(Ⅱ), and high-crystalline iron. Superoxide anion (O₂^•−)has a significant positive correlation with low-crystalline iron and a significant negative correlation with adsorbed Fe(Ⅱ) and high-crystalline iron. The research results provide a new perspective for understanding the role of earthworms gut microbiota in soil iron cycling and ROS formation, which can be applied for pollutant control and degradation.

This paper reviewed the occurrence characteristics and abundance of microplastics (MPs) in disinfection processes of water treatment plants both inside and outside China, and analyzed the MPs removal effectiveness of chlorine, ozone and ultraviolet disinfection, followed by an in-depth discussion of the effects of MPs presence on disinfection and its secondary pollution. The results showed significant differences in the abundance of MPs across different water treatment plants, primarily existing in the forms of fibers and fragments, predominantly composed of polyethylene terephthalate (PET), polyethylene (PE), and polypropylene (PP), with most sizes less than 1.0mm and colors mostly black, white, or transparent. The removal rate of the chlorine disinfection unit ranged from 0% to 71.38%; but part of the water treatment plants had seen a rise in MPs abundance after the ozone and ultraviolet disinfection. The removal mechanisms of MPs by disinfection processes remained required further research. Additionally, the trihalomethane formation potential (THMFP) of microplastic-derived dissolved organic matter (MP-DOM) in the chlorine disinfection process could reach as high as 453.3µg/mg, higher than the formation potential of typical aquatic natural organic matter and algae organic matter, pointing to greater health risks.

In this study, the components of dissolved organic matter (DOM) during the anaerobic-anoxic-aerobic (A²O) biological wastewater treatment process was analyzed by using fluorescence emission excitation matrix combined with parallel factor analysis(3D EEMs-PARAFAC), and the generation of nitrous oxide (N₂O) in each unit was also quantified. Additionally, machine learning model was employed to further predict the response relationship between DOM components and N₂O generation. Results showed that DOM in the influent of the wastewater treatment plants (WWTP) was primarily composed of four components, including tryptophan (C1), fulvic acid (C2), humic acid (C3), and tyrosine (C4), while C1 and C4 being the dominant components. The concentration of DOM decreased progressively throughout the treatment process, while the removal efficiency of readily biodegradable DOM (such as C1and C4) were significantly higher than that of C2 and C3. N₂O emission was the major component of direct carbon emissions and showed significant spatial heterogeneity. The N₂O emission amount of each unit ranked from high to low were observed in the following order: oxic tank, secondary sedimentation tank, anoxic tank, anaerobic tank, grille, and primary sedimentation tank. Shapley Additive exPlanation (SHAP) analysis revealed that C1 and C2 would significantly affect the N₂O generation process, while the effects of C3 and C4 were negligible. Specifically, C1would enhance N₂O generation, while C2 had an adverse effect. High-throughput sequencing results indicated that Methylotenera and Terrimonas, which could utilize readily biodegradable organic matter for denitrification, were the dominant bacterial genera in the sludge of WWTP. Overall, this study revealed disparate response between N₂O generation and different DOM components during the A²O process, which would help to improve the current carbon emission accounting method of WWTPs and provide theoretical support for optimizing their low-carbon operation processes.

Microplastics (MPs) pollution has become a hot research topic in the environmental field, while few studies have reported the MPs pollution in the gastrointestinal tract of river fish in Hainan Island. In the present study, 222 freshwater fish specimens belonging to 35 species with different feeding habits were collected from 11 sampling sites located in the upper, middle, and lower reaches of the Nandu River. The pollution characteristics of MPs in the gastrointestinal tract of fish samples were analyzed. The results showed that MPs were detected in 94.5% of the fish gastrointestinal tracts, with an average abundance of (4.85±3.51)MPs per fish. The MPs in fish gastrointestinal tract were dominated by <1.0mm (73.3%) transparent (38.9%) fibers (60.6%), and were mainly composed of polypropylene (53.3%) and polyethylene (34.2%). The highest abundance of MPs was recorded in the gastrointestinal tract of filter-feeding planktivorous fish (7.00 per fish) and the lowest abundance was recorded in the gastrointestinal tract of insectivorous fish (2.57 per fish). From the upper to the lower reaches, the percentage of blue fragment MPs with size <1.0mm in the fish gastrointestinal tract was increasing, while the percentage of yellow/red fiber/film MPs with size >1.0mm was decreasing. This could be attributed to the increase of aquacultural activities, the usage of agricultural films, and a large amount of sewage and industrial wastewater in the lower reaches.

The solid-phase extraction method and the thermal-optical method were combined to obtain different polar HULIS and the carbon content of HULIS (HULIS-C) in PM_2.5 with high temporal resolution during the heavy pollution event in Xi'an. The light absorption characteristics of HULIS were analyzed using a UV-Vis spectrophotometer equipped with a liquid waveguide capillary cell (LWCC), and the positive matrix factorization model (PMF) was used to analyze the sources of HULIS. At the same time, the source of HULIS is combined with the positive matrix factorization model (PMF). The results showed that the average mass concentration of neutral HULIS (HULIS-n) (6.6±2.6)µg/m³ was higher than that of acidic HULIS (HULIS-a) (3.7±3.5)µg/m³, accounting for approximately 30% and 18% of OC, respectively, indicating severe HULIS pollution during heavy pollution periods. The absorption coefficients (AAE, E₂/E₃, and MAE₃₆₅) of HULIS-n were all greater than those of HULIS-a, suggesting that HULIS-n contains more conjugated and aromatic structures and has stronger light-absorbing properties, with a more significant impact on atmospheric visibility. The source analysis revealed clear differences in the contributions of HULIS-n and HULIS-a. The primary sources of HULIS-n included secondary sources, coal combustion, motor vehicle emissions., while the contributions of secondary sources and coal combustion were higher for HULIS-a.

Accurately assessing the degradation status of seagrass bed ecosystems was essential for formulating effective protection and restoration decisions However, existing assessments of seagrass bed ecological degradation were primarily conducted from the health perspective, neglecting the endpoint of degradation and its critical levels during the degradation process. This study took ecosystem collapse as the endpoint of degradation and, from an ecological risk perspective, the assessment framework of the Red List of Ecosystems was drawn upon. Three main criteria—habitat range degradation, abiotic environmental degradation, and biological process degradation—were integrated to establish an assessment framework for seagrass bed ecosystem degradation. Fourteen seagrass bed distribution areas along the South China coast were selected for empirical study. The assessment results showed that the seagrass bed in Tangjiawan had reached an extremely degraded level. Eight seagrass beds, such as Zhelin Bay, were severely degraded (57%); the seagrass bed in Li'an Port was moderately degraded; and four seagrass beds, such as Liusha Bay, were slightly degraded (29%). Among the three major assessment criteria, biological processes were identified as the main manifestation of seagrass bed degradation along the South China coast. From the perspective of ecosystem collapse risk, a framework for assessing seagrass bed ecosystem degradation was constructed, providing a new perspective for evaluating the degradation status of seagrass beds and other ecosystems, and offering important decision-making support for ecosystem conservation and restoration.

This study conducted sampling and testing on the waste gases generated from different processes in typical automobile manufacturing plant coating workshops located in northern and southern China. It meticulously analyzed the emission characteristics of volatile organic compounds (VOCs) and odor characteristics, and extensively explored odor characteristic prediction methods from multiple dimensions. The results revealed that OVOCs, alkanes, and aromatic hydrocarbons are the predominant components in the exhaust gases, with OVOCs constituting 73.80% to 99.03% of the odor activity value (OAV), thereby classifying them the most significant odor-contributing substance category. Acetaldehyde, n-butyl acetate, isobutyl acetate, and n-butyraldehyde all significantly contributed to the odor at both the inlet and outlet of the treatment equipment. Furthermore, electronic noses were used to classify waste gas samples, achieving 100% and 98.1% accuracy rates for inlet and outlet, respectively. Quantification of odour was achieved through regression analysis, which revealed a strong linear correlation between OVOCs substance concentration and OAV_max and OAV_sum. The electronic nose technology combined with BP neural networks was found to be an effective predictor of OAV_max and OAV_sum. Additionally, a logarithmic relationship was observed between OVOCs substance concentration, OAV_max, OAV_sum, and odor concentration.

This study used the urban sprawl index and InVEST model to analyze the spatiotemporal changes of urban sprawl and its impact on ecosystem services in 19 provincial capital cities along the main and tributary streams of the Yangtze River Basin from 2000 to 2020. It also explored the factors influencing ecosystem services in the urban sprawl areas. This study found that: (1) 47.37%and 73.63% of cities experienced urban sprawl during 2000~2010 and 2010~2020, respectively. (2) From 2000 to 2020, the average habitat quality, total food and meat production services, and total carbon storage of provincial capital cities in the Yangtze River Basin (central urban area) decreased by 4.25%, 7.03%, and 4.53%, respectively, while the total water production increased by 12.10%. (3) The loss of ecosystem services due to urban sprawl was the most significant in terms of habitat quality, with a loss of 71.56% from 2010 to 2020 compared to 2000. (4) A correlation analysis was conducted on the impact of land-use conversion, socio-economic factors, and climate on ecosystem services, and it was determined that land-use and use conversion and socio-economic factors were the most influencing factors.

To explore the patterns of forest carbon storage evolution influenced by the implementation of dual-carbon policies, This study selects Jiangmen City, a key ecological barrier in the Guangdong-Hong Kong-Macao Greater Bay Area, as a case study. Using land cover and carbon density data from five periods between 2000 and 2020, the study employs the InVEST model to quantitatively assess the area's carbon storage, in conjunction with the Policy Modeling Consistency (PMC) index model and the Least Absolute Shrinkage and Selection Operator (Lasso) regression model to analyze the quality of forestry policies and their impact on carbon storage. The results indicate that forest and agricultural lands were the principal contributors to carbon storage changes in Jiangmen City. From 2000 to 2015, these lands was significantly converted to built-up areas, causing carbon storage to decrease from 34.22×10⁶t to 33.59×10⁶t, accounting for 72.8% of the decrease in the Greater Bay Area's carbon storage during the same period, which represented a 14.35% reduction. After 2015, the implementation of subsidy policies related to forest city development resulted in an increase in the area of carbon storage exceeding areas of loss from 2015 to 2020, with a net increase of 0.5% in carbon storage. The “incentive safeguard” variable was identified as a principal factor in this increase. Spatially, the areas of increased and decreased carbon storage in Jiangmen City exhibited clustered distributions, reflecting the “forest surrounding cities and trees entering cities”policy. Based on the joint spatial distribution characteristics of carbon storage density and building density, the study proposes carbon sequestration enhancement strategies for different functional zones, including forest protection in ecological conservation areas, carbon planning in wilderness areas, spatial transformation in central old urban areas, and garden construction in newly developed urban areas. These recommendations provide theoretical support and practical examples for formulating sustainable urban development policies.