Search Results (238)

Traditional intensive agricultural system impedes ecological functions, such as nutrient cycling and biodiversity conservation, resulting in excessive nitrogen discharge, CH₄ emission, and ecosystem service losses. To enhance critical ecosystem services and mitigate environmental externalities in paddy fields, we developed a multi-objective agricultural system (MIA system), which combines two eco-functional units: paddy wetlands and Beitang (irrigation water collection pond). Pilot study results demonstrated that the MIA system enhanced biodiversity and inhibited pest outbreak, with only a marginal reduction in rice production compared with the control. Additionally, the paddy wetland effectively removed nitrogen, with removal rates of total nitrogen and dissolved inorganic nitrogen ranging from 0.06 to 0.65 g N m⁻² d⁻¹ and from 0.02 to 0.22 g N m⁻² d⁻¹, respectively. Continuous water flow in the paddy wetland reduced the CH₄ emission by 84.4% compared with the static water conditions. Furthermore, a simulation experiment indicated that tide flow was more effective in mitigating CH₄ emission, with a 68.3% reduction compared with the drying–wetting cycle treatment. The emergy evaluation demonstrated that the MIA system outperformed the ordinary paddy field when considering both critical ecosystem services and environmental externalities. The MIA system exhibited higher emergy self-sufficiency ratio, emergy yield ratio, and emergy sustainable index, along with a lower environmental load ratio. Additionally, the system required minimal transformation, thus a modest investment. By presenting the case of the MIA system, we provide a theoretical foundation for comprehensive management and assessment of agricultural ecosystems, highlighting its significant potential for widespread application. Full article

Electrocatalytic CO₂ reduction reaction (CO₂RR) is a crucial technology for achieving carbon cycling and renewable energy conversion, yet it faces challenges such as complex reaction pathways, competition for intermediate adsorption, and low product selectivity. In recent years, molecular modification has emerged as a promising strategy. By adjusting the surface properties of catalysts, molecular modification alters the electronic structure, steric hindrance, promotes the adsorption of reactants, stabilizes intermediates, modifies the hydrophilic–hydrophobic environment, and regulates pH, thereby significantly enhancing the conversion efficiency and selectivity of CO₂RR. This paper systematically reviews the modification strategies and mechanisms of molecularly modified materials in CO₂RR. By summarizing and analyzing the existing literature, this review provides new perspectives and insights for future research on molecularly modified materials in electrocatalytic CO₂ reduction. Full article

Urban vegetation shows significant spatial differences due to the combined effects of natural and human factors, yet fine-scale evolutionary patterns and their cross-scale feedback mechanisms remain limited. This study focuses on the Yangtze River Delta (YRD), the top economic area in China. By integrating data from multiple Landsat sensors, we built a high—resolution framework to track vegetation dynamics from 1990 to 2020. It generates annual 30-m Enhanced Vegetation Index (EVI) data and uses a new Vegetation Green—Brown Balance Index (VBI) to measure changes between greening and browning. We combined Mann-Kendall trend analysis with machine—learning based attribution analysis to look into vegetation changes across different city types and urban—rural gradients. Over 30 years, the YRD’s annual EVI increased by 0.015/10 a, with greening areas 3.07 times larger than browning. Spatially, urban centers show strong greening, while peri—urban areas experience remarkable browning. Vegetation changes showed a city-size effect: larger cities had higher browning proportions but stronger urban cores’ greening trends. Cluster analysis finds four main evolution types, showing imbalances in grey—green infrastructure allocation. Vegetation baseline in 1990 is the main factor driving the long-term trend of vegetation greenness, while socioeconomic and climate drivers have different impacts depending on city size and position on the urban—rural continuum. In areas with low urbanization levels, climate factors matter more than human factors. These multi-scale patterns challenge traditional urban greening ideas, highlighting the need for vegetation governance that adapts to specific spatial conditions and city—unique evolution paths. Full article

In this paper, a discrete element method (DEM) coupled with a finite element method (FEM) was used to elucidate the impact of packing structures and size ratios on the cold die compaction behavior of pure copper powders. HCP structure, SC structure, and three random packing structures with different particle size ratios (1:2, 1:3, and 1:4) were generated by the DEM, and then simulated by the FEM to analyze the average relative density, von Mises stress, and force chain structures of the compact. The results show that for HCP and SC structures with a regular stacking structure, the average relative densities of the compact were higher than those of random packing structures, which were 0.9823, 0.9693, 0.9456, 0.9502, and 0.9507, respectively. Compared with their initial packing density, it could be improved by up to 21.13%. For the bigger particle in HCP and SC structures, the stress concentration was located between the adjacent layers, while in the small particles, it was located between contacted particles. During the initial compaction phase, smaller particles tend to occupy the voids between larger particles. As the pressure increases, larger particles deform plastically in a notable way to create a stabilizing force chain. This action reduces the axial stress gradient and improves radial symmetry. The transition from a contact-dominated to a body-stress-dominated state is further demonstrated by stress distribution maps and contact force vector analysis, highlighting the interaction between particle rearrangement and plasticity. Full article

Rural landscape perception is of great significance in understanding the emotional connection between people and rural local environments. Seeking to rectify the problem of incomplete or biased results owing to the separation of objective and subjective landscape perception in previous studies, this study took the village of Chongming District in Shanghai, China, as an example and built an evaluation model that integrated four dimensions and 20 indicators of objective and subjective landscape perception, and used machine learning technology to analyze street view images. Subjective perception has been influenced by landscape color, style, and element perception. Notable spatial disparities have been observed in the distribution of rural landscape indicators across Chongming. This study refines key subjective and objective factors affecting rural landscape perception, and the model provides a new method for the perception evaluation of complex landscapes, providing a theoretical basis and practical reference for rural landscape planning. Full article

With the increasing acceptance of green, low-carbon, and sustainable development principles, the rising number of new energy vehicles (NEVs) has raised public concern over traffic safety risks associated with these vehicles. To assist traffic management authorities in efficiently allocating rescue resources, this paper proposes a severity prediction method for the new energy vehicle accidents based on Cost-sensitive Fuzzy XGBoost (CFXGBoost). First, chi-square filtering and wrapper methods are used to extract 20 key features strongly cor-related with accident severity. Then, A fuzzy neural network is employed to combine fuzzy inference results with original features, forming an extended feature set. Moreover, These features are used as inputs to the XGBoost model for severity prediction of the new energy vehicle traffic accidents. Finally, the proposed approach is validated using traffic accident datasets from multiple provinces and cities. Results show that the FXGBoost model achieves a prediction accuracy of 0.92 and outperforms other models in terms of precision, recall, and F1 score, demonstrating its effectiveness in accurately predicting the severity of NEV-related traffic accidents. Full article

The elevational patterns of plant β diversity and their underlying drivers are known to be scale-dependent, but pinpointing the spatial scales at which different ecological processes occur remains challenging using traditional field inventory methods. Remote sensing has emerged as a promising alternative, providing continuous spatial data for monitoring plant diversity. In this study, we used field inventory data and corresponding Sentinel-2 images from a subtropical mountain to simulate pooled assemblages and assess the potential of using multispectral satellite images in predicting tree β diversity. We further examined the scale-dependent elevational gradient of the spectral β diversity and identified primary topographic variables across different spatial extents (0.16–64 ha). The spectral β diversity showed a consistently positive relationship with the inventory β diversity calculated using various indices (average pairwise Sørensen, Jaccard, and Bray–Curtis dissimilarities, as well as multi-community differentiation measures based on Hill numbers), with the strongest correlation observed for abundance-weighted indices and images from early spring and late autumn (R²_max = 0.63). However, a null model-derived β deviation showed only a weak correlation between remote sensing and field-based measures. A declining trend in the spectral β diversity with an increasing elevation was observed and became more pronounced at larger extents. The topographic heterogeneity, represented by the slope and northness, explained the elevational gradients at spatial extents >4 ha, attesting the significant role of environmental filtering in shaping plant diversity patterns, even at fine scales. While the northness was more influential at smaller spatial extents (<4 ha), the slope had a stronger impact at broader spatial extents (>4 ha). This study showcases the potential of using readily available remote sensing data to address difficult questions in plant diversity research. Full article

In this paper, the analysis method which coupled discrete element method (DEM) and finite element method (FEM) is used to simulate the double compaction of random packing of Cu and Al composite powders with multiple particle sizes. Cu and Al composite powders with varying particle size ratios from 1:2 to 1:5 were generated by DEM and then imported to MSC. Marc software (MSC.MARC2015 version) to construct FEM analysis. The effects of metal ratios, compaction pressure and size ratios on the relative density and von Mises stress of the compact were studied. The results show that the average relative density of the compact increases with the Al content, and the stress decreases. The stress in the Cu particle is particularly higher than that in the Al particle, mainly because the contact normal force of the Cu particle is nearly parallel at each contact surface. Therefore, the phenomenon of stress concentration is easier to occur within copper particles. When Al content is 30wt.%, the particle size difference enhances densification efficiency by up to 12.3%, as evidenced by an initial relative density increase from 0.7915 to 0.8047, primarily due to smaller Cu particles effectively filling interparticle voids. When the compaction pressure is fixed, the average relative density of the compact with the particle size ratio 1:5 is higher than the others, and the contact forces inside the particles significantly decrease. Full article

In this study, the chemical compositions of PM_2.5 (particulate matter < 2.5 μm) and the molecular compositions of methanol-soluble organic carbon (MSOC) in suburban Shanghai during summer were measured to investigate the molecular characteristics of organic aerosol (OA) under high humidity. Diurnal variation analysis reveals the influence of relative humidity (RH) on secondary organic aerosol (SOA) components. Organosulfates (OSs), particularly nitrooxy-OSs, exhibit a positive correlation with increasing humidity rather than atmospheric oxidants in this high-humidity site. This suggests that high RH can promote the formation of OSs, possibly through enhancing particle surface area and volume, and creating a favorable environment for aqueous-phase or heterogeneous reactions in the particle phase. A considerable proportion of CHOS compounds may be derived from anthropogenic aliphatic hydrocarbon derivatives. These compounds exhibit slightly elevated daytime concentrations due to increased emissions of long-chain aliphatics from sources such as diesel combustion, as well as photochemically enhanced oxidation to OSs. In contrast, CHONS compounds increased at night, driven by high-humidity liquid-phase oxidation. Terpenoid derivatives accounted for 13.4% of MSOC and contributed over 40% to nighttime CHONS. These findings highlight humidity’s important role in driving daytime and nighttime processing of anthropogenic and biogenic precursors to form SOA, even under low SO₂ and NO_x conditions. Full article

Hyacinth bean seeds are a good source of vegetable protein and have great potential for medicinal development. However, their metabolic characteristics are unclear. Therefore, in this study, we conducted non-targeted metabolomics research on hyacinth bean seeds from local varieties using ultra-high-performance liquid chromatography combined with high-field quadrupole orbital trap high-resolution mass spectrometry (UHPLC-QE HF HRMS) and evaluated their antioxidant properties. A total of 745 metabolites were identified, including many bioactive medicinal compounds such as chikusetsusaponin IVa, pipecolic acid, and genistin. The seed coat color and origin of hyacinth bean seeds have significant impacts on their metabolic characteristics. Compared with the other four hyacinth beans, the Chongming white hyacinth bean (SCLW) has a higher medicinal value, with glycitin, finsenoside Ro, diferuloyl glycerol, isopongflavone, procyanidin B2, and pratensein speculated to be its characteristic metabolites. DPPH and FRAP assays showed that the antioxidant activity of SCLW was significantly higher than that of the other four hyacinth bean seeds, and 11 metabolites related to antioxidant activity were identified. These findings enrich our knowledge of the metabolites in hyacinth bean seeds, which is of great significance for hyacinth bean cultivation according to local conditions and for the improvement of variety quality. Full article

Urbanization has been suspected to increase the allergic rate of people, and its impact on airborne fungi and potential allergens has drawn attention. In this study, aerosol samples were collected concurrently at proximate urban and rural sites of Shanghai during the four seasons to analyze the changes in abundance and community composition of airborne fungi. In summer, there were significantly higher concentrations of fungi in the urban atmosphere compared to at the rural site. Ascomycota and Basidiomycota were the top two fungal phyla, and Cladosporium was the most abundant genus year round. Alternaria was the second highest genus in spring and winter (only the rural site), whereas Nigrospora ranked second during summer and autumn due to it largely being sourced from marine organisms and predominantly marine-influenced air masses in these seasons. Airborne fungal richness was relatively higher at the rural site than in urban during winter. Allergenic fungal species were found to be more abundant in winter than in other seasons; particularly, the relative abundance of Cladosporium sp. was significantly higher (p < 0.001), and Fusarium culmorum and Cladosporium herbarum also increased more in urban than in rural areas, which may be one of the key factors contributing to the rising allergic rate in the urban population. Full article

Pyrolysis coupled with gas chromatography–mass spectrometry (Py-GC/MS) is a novel technology capable of detecting micro- and nanoplastics without a size limit. However, the application of Py-GC/MS to airborne microplastic analysis remains inconsistent. This study explores optimal Py-GC/MS procedures using a domestic Henxi^TM PY-1S pyrolyzer-based Py-GC/MS. The initial weight loss of PVC occurs at approximately 260 °C, indicating that the maximum thermal desorption temperature prior to pyrolysis should not exceed 250 °C. To avoid interference from semi-volatile organics present in the sample and injected air, it is essential to purge the sample with pure helium at elevated temperatures before pyrolysis. Microplastic standards can be prepared by ultrasonicating a water–microplastic dispersion system. Significant interactions between microplastic mixtures were observed during co-pyrolysis, indicating that the interactions of mixtures cannot be ignored during the optimization of quantitative references. The optimal procedure features good linearity (R² > 0.98), low detection limit (0.06~0.0002 μg), and acceptable precisions (RSD < 10% in 8 days). Microplastics determined by the domestic PY-1S pyrolyzer coupled with a GC/MS system are comparable to those of the well-established PY-3030D-based Py-GC/MS, indicating that the domestic pyrolyzer coupled with GC/MS is a reliable and powerful tool for microplastic analysis. Full article

Elevated O₃ concentrations pose a significant threat to human health and ecosystems, but little research has been performed on coastal wetlands near large cities. This study focuses on investigating the key factors affecting O₃ formation in the ecologically sensitive Dongtan Wetland (Chongming District, Shanghai, China) area. By comparing the performance of O₃ concentration prediction of multiple machine learning models, this study found that the random forest model achieved the highest accuracy (R² = 0.9, RMSE = 11.5). Feature importance and structure mining showed that peroxyacetyl nitrate (PAN), nitrogen oxides (NOx), temperature, wind direction, and relative humidity were the main drivers of O₃ formation. Specifically, PAN concentrations exceeding 0.1 ppb and temperatures above 3 °C were found to have a significant impact on O₃ levels, especially in spring, summer, and autumn. Trajectory analysis showed that westward urban pollution and emissions transported from the ocean were the main factors in O₃ formation in the area. This study highlights the need for targeted emission control strategies, especially for PAN precursors generated by ships and NOx generated by urban industries, providing important insights for improving air quality in ecologically sensitive coastal areas. Full article

The conservation and utilization of livestock genetic resources is essential for the maintenance of biodiversity and breed innovation. Whole genome sequencing (WGS) was performed on 90 samples from Chinese Yangtze River Delta White goats (YRD), sourced from two populations of Chongming island white goats and Haimen white goats, aiming to dissect their genomic characteristics. In addition, 262 WGS data from nine other breeds of goats were downloaded from the NCBI database. These WGS data obtained were used to identify and analyze genetic variation with the goat reference genome, and the genetic structure of goat populations was analyzed. Through selective sweep analysis, the selection-signature genes and their polymorphic features were identified. It was found that the most significant genomic selection region in YRD goats was in the region of 62.9–64.6 Mb on chromosome 13, which contained genes related to the coat color and muscle growth of the goats. Nucleotide diversity of MYH7B, a gene related to the development of the goat’s skeletal muscle, within the Yangtze River Delta white goat population was significantly lower than in other domestic and foreign goat breeds, suggesting that the gene was subject to selection. In addition, the IGF2BP2 gene, reported to be associated with litter size in goats, showed clear selection-signature characteristics in the Boer goats compared to the YRD goats. Full article