A carbon intensity accounting method was developed to account for the distinct data characteristics of inland river ship based on carrying capacity and transport distance. The correlation between ship carbon intensity indicator (CII) and factors including vessel age, ship type, port of registry and average speed was analyzed based on operational data collected from ships of 5,000GT and above registered in Chongqing after static parameter filling and dynamic trajectory repair. The results indicated that the carbon intensity values of the study sample in October 2021 were all on the order of 10^-6, ranging between 2.47×10^-6 and 10.53×10^-6t/(t·km). As vessel age increases, the CII demonstrates an upward trend, whereas carbon emissions exhibit a negative correlation with carrying capacity. The overall energy efficiency levels of different ship types were quantified and ranked based on the median and mean values of their CIIs. The resulting order from highest to lowest energy efficiency was Ro-Ro vessels, general cargo ships, container ships, dry bulk carriers, and passenger ships. Vessels registered in main urban area of Chongqing generally demonstrate superior energy efficiency compared to those from its outer districts and counties. Thus establishing a standardized carbon emission monitoring system was crucial to enhance the overall energy efficiency of the ship fleet registered in Chongqing. The CII demonstrated a strong correlation with ship average speed. Furthermore, different ship types exhibit distinct variation characteristics, each reaching its minimum carbon intensity at different specific speed points.

Based on China's construction industry low-carbon technology patents and carbon emission data from 2003 to 2022, the subject collaboration networks and knowledge fusion networks were constructed using social network analysis, and a coupling coordination degree model was designed based on their topological structures. Further, an autoregressive distributed lag (ARDL) model and generalized impulse response function (GIRF) were applied to empirically examine the impact mechanism of the coordinated development of dual-network coupling on the construction industry's carbon emission intensity. The results indicated that: ① The subject collaboration networks and knowledge fusion networks continued to optimize, with the coupling coordination level increasing from 0.4043 to 0.9591, showing an evolution from disorder to high coordination; ② During the sample period, the coupling coordination development index lagged by one period was found to exert a significant negative impact on carbon emission intensity, reflecting its delayed promoting effect on emission reduction; ③ The coupling coordination development index was identified as a one-way Granger cause of carbon emission intensity. Its negative shock peaked at -1.865 in the second lag and then gradually stabilized, demonstrating a significant stage-based adjustment effect. Relying on a framework integrating structural measurement and dynamic analysis, the results provided quantitative tools and empirical support for systematic low-carbon innovation policies.

Direct air carbon capture (DAC) technology reached the stage of commercial deployment, yet its large-scale application still faced challenges of high energy consumption and resource-environmental impacts. An exergy-based life cycle assessment (ExLCA) framework for DAC systems was established, with their performance being evaluated across energy, resource, and environmental dimensions. It was shown that under grid-electricity and natural gas energy supply scenarios, the system's life cycle energy consumption was 10.22GJ/tCO₂, with thermal energy demand for capture, CO₂ compression, and oxygen production through air separation being identifiedas the dominant energy-intensive processes, which accounted for 62.72%, 13.41%, and 8.98%, respectively. The cumulative exergy consumption over the life cycle was 9.19GJ/t CO₂, with electricity and thermal energy contributing 39.98% and 58.93% to total exergy consumption, while material-related exergy was accounted for only 1.09%, which was negligible. In terms of environmental benefits, a life cycle carbon removal efficiency of 47.50% was achieved by the system, with thermal energy and electricity consumption contributing 53.18% and 33.43% to total carbon emissions. Carbon removal efficiency could be increased to 88.60% by transitioning to biomass and wind power as energy sources. Furthermore, 80kg of water and 1465(m²·a) per ton of CO₂ removed were required by the system, highlighting the need for careful resource management in large-scale deployment.

HEK293-α-syn cells and primary cortical neurons of wild-type mice were used as experimental models to deeply explore the environmental neurotoxicity and mechanism of Maneb exposure at different concentrations (0, 0.1, 1.0, 5.0mg/L). The results showed that Maneb exposure inhibited the activity of HEK293-α-syn cells in a dose-dependent manner and induced primary neuronal damage. The higher the Maneb exposure concentration, the more significant its toxic effect. In the 0.1mg/L experimental group, the apoptosis rate of neurons was close to 60%. In addition, Maneb exposure induced the aggregation ofα-syn in HEK293-α-syn cells and primary neurons, stimulated its abnormal phosphorylation at the S129 site, and upregulated the level of insoluble phosphorylated α-syn, further forming Lewy body (LB)-like aggregates, indicating that Maneb induces Parkinson's (PD)-like neurotoxicity.

Meteorology is a known driver of pollen concentrations, using Yulin City in Shaanxi Province—a hotspot for pollen allergies in China—as a case study, this research integrates 2019~2021 pollen concentration data and meteorological observations. Through statistical analysis and synoptic diagnosis, we investigate the meteorological drivers of an explosive pollen surge from August 4~7, 2021. Key findings reveal:Pollen concentrations in Yulin show a clear bimodal seasonality with spring and autumn peaks. Anther dehiscence in Artemisia ordosica is triggered by rising temperature and low huidity, with winds of 1.5~3.0m/s being optimal for dispersal. Enhanced near-surface winds during the event facilitated local dispersion, but shifting wind directions impeded stable transport pathways, promoting localized accumulation. Synoptic diagnosis shows that a transition from upper-level through to a ridge, combined with mid-low-level anticyclonic activity, was critical. This pattern promoted subsidence, which suppresses atmospheric diffusion by reducing boundary-layer height and forming temperature inversions. Total cloud cover modulates surface radiation budgets and vertical motions, thereby influencing boundary-layer thermal structure. The key driver of the diurnal peaks was the synergy between periods of low cloud cover (<2oktas) and boundary-layer compression.

The growth and death processes of microorganisms result in the release of pathogen-associated molecular patterns (PAMPs). Chronic exposure to PAMPs through the gastrointestinal, respiratory, and dermal routes poses a risk of inflammatory effects. The presence of large numbers of microorganisms in the air, water, and soil provides extremely favorable conditions for the release of PAMPs. This study summarizes the characteristics of endotoxins, peptidoglycan, teichoic acids, lipoproteins, and CpG DNA, which are pivotal substances in PAMPs. The occurrence and health risks of PAMPs in different environmental media, such as air, water, and soil, are introduced. The recognition mechanism of PAMPs and their ability to trigger disease are also discussed. The synergistic enhancement of inflammatory responses induced by combined exposure to PAMPs and environmental pollutants is analyzed. Based on current research of PAMPs in the environmental field, this study highlights the urgent need to accelerate research into standardized detection systems, exposure risk thresholds, and epidemiological studies of PAMPs, given the existing limitations. The aim of these efforts is to advance research progress on PAMPs in environmental science and to provide a reference for a comprehensive understanding and assessment of the health risks posed by PAMPs.

Water, energy, and carbon are critical resource and environmental elements that underpin socio-economic development. Exploring the coupling coordination among water-energy-carbon (WEC) and promoting their synergistic development are essential for advancing regional green and high-quality growth. Taking 95 cities in the Yangtze River Economic Belt (YREB) as the study area, WEC evaluation indicators were constructed from the dual-control perspective of total amount and intensity. The coupling coordination degree (CCD) model was applied to measure the CCD of WEC from 2006 to 2019, and the spatial durbin model was employed to identify the key influencing factors. The results showed that the CCD of WEC, water-energy, water-carbon, and energy-carbon in the YREB ranged from 0.6724 to 0.9987, and were classified into four levels: primary, intermediate, good, and quality coordination, with the median and mean showing an overall upward trend and notable improvement. Since 2014, more than 75% of the cities had reached the quality coordination level each year. All four categories of CCD exhibited positive spatial clustering, with cities achieving quality coordination in the other three categories evolving from scattered to contiguous distribution patterns, while energy-carbon remained widely distributed. Significant positive spatial spillover effects were detected for all four categories, indicating that improvements in local coupling coordination positively impacted that of spatially connected cities. Economic development level, environmental regulation, technological innovation, and NDVI significantly promoted local CCD, whereas fixed asset investment exerted a suppressing effect. Furthermore, economic development level and industrial structure upgrading showed positive and negative spatial spillover effects on spatially connected cities, respectively, while the negative spillovers of environmental regulation and technological innovation were more pronounced among geographically adjacent cities compared to economically linked cities.

The National Key Ecological Function Zone Policy is an important part of China's ecological governance system, but whether it promoted county-level green economic growth remained unclear. Using county panel data for 2005~2020, the policy's impact on green economic growth was analyzed with a difference-in-differences design and machine-learning methods. The results show that the policysignificantly increased county green economic growth by 2.77%. Mechanism analyses indicated that the policy raised the value of ecosystem services by 6.59%, increased transfer payments by 11.71%, enhanced green technological innovation by 1.63%, and reduced the number of moderately polluting firms by 11.72%. The economic structure was further modernized. The heterogeneity analysis showed that the overall policy effect was stronger in western regions. Machine learning results show that the promotion effect was weaker where the welfare base was stronger, the fiscal burden was heavier, and the functional zone covered a larger area. These findings help us better understand how the policy promotes green economic growth and its shortcomings. The results provide useful reference for improving the policy according to local conditions and further promoting regional green economic growth.

The establishment of National Agricultural Green Development Pilot Zones (NAGDPZ) was regarded as a major policy initiative aimed at facilitating the green transformation of agriculture and was expected to significantly influence agricultural carbon emissions. However, limited research had been conducted in this area. Based on panel data from 284 cities spanning the period from 2013 to 2023, a quasi-natural experiment was constructed using the implementation of the NAGDPZ. The difference-in-differences (DID) method was employed to systematically evaluate the effect of the NAGDPZ policy on agricultural carbon emissions.The following findings were obtained:(1) The NAGDPZ policy was found to significantly reduce agricultural carbon emissions. A statistically significant negative effect at the 10% level was observed, with an estimated coefficient of -0.008. The robustness of this result was confirmed through parallel trend tests, placebo tests, propensity score matching DID (PSM-DID), exclusion of potential confounding policies, and controls for endogeneity.(2) Mechanism analysis revealed that the emission reduction effect was primarily driven by improvements in agricultural production efficiency, the development of digital inclusive finance, and the promotion of rural innovation and entrepreneurship. Specifically, the NAGDPZ policy had a significantly positive impact on agricultural total factor productivity, the digital inclusive finance index, and the rural innovation and entrepreneurship index, with coefficients of 0.019, 0.008, and 0.018, respectively.(3) Heterogeneity analysis indicated that the carbon reduction effect varied across regions. Significant negative impacts were observed in southern China, non-major grain-producing areas, and regions with higher levels of agricultural financial support, with coefficients of -0.008, -0.016, and -0.015, respectively. In light of these findings, it is recommended that the establishment of NAGDPZ be expanded to further enhance the policy's effectiveness in reducing agricultural carbon emissions.

Based on the 2020 emission inventory of 68 integrated cement plants in the Beijing-Tianjin-Hebei (BTH) region, three emission reduction scenarios were developed using 37 technologies and the CALPUFF model, two exposure-response functions (IER and GEMM), and three economic valuation methods (Value of statistical life(VSL), Age-adjusted value of statistical life(A_VSL), Amended human capital(AHC))were employed to assess the PM_2.5 reduction potential, concentration changes, and health impacts. The result demonstrated that under the technology-based reduction scenarios S1 and S2, the primary PM_2.5 emissions from reduction technologies and the total PM_2.5 concentration declined by 2.17‰~5.50‰ and 3.20%~12.10%, respectively. Under each scenario in three provinces, the avoidable deaths estimated by IER were about 60% of the result estimated by GEMM. Moreover, the avoided deaths under S1 and S2 in each city were 4%~5% and 9%~10% of the data under S0. The main beneficiary group of life extension years was concentrated in the 65+ and 70+ age groups, and the life extension years in Shijiazhuang, Baoding, and Tangshan contributed 57% of the total years in Hebei. Avoidable economic losses under S1were about 50% of those under S2 and only 5% of those under S0 (ideal scenario) which meant "zero emission"was realized in the cement industry. The value evaluated by VSL was highest, followed by the value evaluated by A_VSL and AHC. Taking the estimation of GEMM as an example, the avoidable economic loss in Beijing was the highest among the three provinces under three scenarios, whereas the avoidable economic loss evaluated by VSL and AHC in Hebei was higher than that in Beijing under S0 (4.489 billion yuan vs. 3.873 billion yuan; 0.36 billion yuan vs. 0.34 billion yuan).