Search

Heavy metal soil pollution severely threatens human health and food safety. This study used PRISMA to systematically review heavy metal-contaminated soil remediation patents in the Derwent Patent Database from 2003 to 2023. A total of 1744 patents were selected. The results of the analysis show that related patent applications are growing around the world. Among them, China has the most significant number of patents, but the layout of transnational patents needs to be revised. Countries have different preferences in transnational patent technology. Technological development is generally balanced, and there is no apparent monopoly. However, the need for continuous in-depth research on inventors is an obstacle to technological development. In addition, the technology in this field is concentrated in chemistry and engineering. Currently, the mainstream technology is soil remediation agents, and thermal desorption technology has also attracted much attention. Future technologies will use new polymer materials and advanced machinery to improve efficiency and control repair costs. In addition, remediation has shifted from the total amount of heavy metals to the control of practical parts. This study summarizes the current status of heavy metal-contaminated soil remediation technology and analyzes future development trends, providing a reference for technology development. [ABSTRACT FROM AUTHOR]

This study aims to investigate the impact of diverse forest stand types and soil depths on soil ecological stoichiometry characteristics, shedding light on nutrient limitations and cycling patterns within the mid-subtropical forest ecosystem in southwest China during spring. The research focused on four representative forest stands situated in Fanjing Mountain: Castanopsis fargesii (C. fargesii), Cyclobalanopsis multiervis (C. multiervis), Cyclobalanopsis argyrotricha (C. argyrotricha), and Rhododendron argyrophyllum Franch (R. argyrophyllum). Sample plots were established in these forest types, and soil samples were collected from the 0–20 cm and 20–40 cm soil layers in March, spring of 2023. Various soil parameters, including pH, soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), soil microbial biomass carbon (MBC), soil microbial nitrogen (MBN), and soil microbial phosphorus (MBP) were measured, and their stoichiometric ratios were calculated. The findings of the study were as follows: (1) In the 0–20 cm soil layer, C. argyrotricha exhibited the highest soil organic carbon, followed by C. fargesii, C. multiervis, and R. argyrophyllum with the lowest content. No significant differences in soil organic carbon were observed among the four forests in the 20–40 cm soil layer. Additionally, C. argyrotricha displayed a significantly higher soil C:N ratio compared to other forest types in different soil layers. In the typical broad-leaved forest area of Fanjing Mountain, the TP was classified as deficient. (2) In the 0–20 cm soil layer, the MBC of C. fargesii surpassed C. multiervis, C. argyrotricha, and R. argyrophyllum by 26.59%, 42.92%, and 24.67%, respectively. There were no significant differences in soil MBC:MBP ratio and MBN:MBP ratio, regardless of forest species and soil depths. The low availability of soil nitrogen in different forest stand types in Fanjing Mountain strongly limits soil microorganism biomass. (3) The correlation between SOC, TN, TP, and their stoichiometric ratios varied across different soil layers. Therefore, in managing the Fanjing Mountain forest area, attention should be paid to supplementing N and P in the soil. [ABSTRACT FROM AUTHOR]

Agricultural soil serves as a crucial reservoir for microplastics (MPs), necessitating an understanding of their global‐scale environmental impacts and potential risks that they pose to agricultural soil and crops. Little is known about the potential impact of MPs in agricultural soils, compared with MPs in aquatic sediments, especially their effects on crop traits. The purpose of our study was to explore whether different types, concentrations, sizes, and exposure time of MPs, as well as soil conditions (such as soil pH or organic matter concentration), have different effects on soil properties and crop traits. In addition, differences between soil and crop enzymes in response to MPs were compared in detail. Network analysis was used to understand the current research progress on MPs in agricultural soil. Furthermore, utilizing 63 publications and 3268 observations, a meta‐analysis was conducted to analyze the effects of MPs on soil properties and crop traits. Our result showed that China has contributed the most to MP research. Crop traits, rather than soil properties, were more sensitive to MPs, significantly increasing crop biochemical traits (p < 0.05) and decreasing crop morphological traits (p < 0.001). MPs significantly inhibited fruit, shoot, and root morphological traits by 13.34% (p < 0.05), 9.7% (p < 0.001), and 6.65% (p < 0.001), respectively; inhibited crop physiological traits such as photosynthesis, respiration, and transpiration by 9.1% (p < 0.001), 34.44% (p < 0.001), and 14.74% (p < 0.05), respectively; inhibited crop biochemical traits such as organic and inorganic metabolites， and improved enzyme activity by 11.37% (p < 0.001), 10.07% (p < 0.001), and 10.16% (p < 0.001), respectively. MPs decreased soil enzyme activities of leucine aminopeptidases and sucrase by 7.22% (p < 0.01) and 27.26% (p < 0.001), respectively, and increased peroxidase, acid phosphatase, catalase (CAT), and urease activities by 59.21%, 7.34%, 6.86%, and 13.13%, respectively. MPs increased crop enzyme activities of CAT and malondialdehyde by 12.71% and 14.82%, respectively. Conclusively, the effect of MPs on crop traits warrants considerable attention and an urgent need to explore whether MPs cause differences between crops with regard to crop traits. [ABSTRACT FROM AUTHOR]

This paper aims to explore the difficulty of obtaining source signals from complex mixed signals and the issue that the FastICA algorithm cannot directly decompose the received single-channel mixed signals and distort the signal separation in low signal-to-noise environments. Thus, in this work, a comprehensive single-channel mixed signal separation algorithm was proposed based on the combination of Symplectic Geometry Mode Decomposition (SGMD) and the FastICA algorithm. First, SGMD-FastICA uses SGMD to decompose single-channel mixed signals, and then it uses the Pearson correlation coefficient to select the Symplectic Geometry Components that exhibit higher correlation coefficients with the mixed signals. Then, these components are expanded with the single-channel mixed signals into virtual multi-channel signals and input into the FastICA algorithm. The simulation results show that the SGMD algorithm could eliminate noise interference while keeping the raw time series unchanged, which is achievable through symplectic geometry similarity transformation during the decomposition of mixed signals. Comparative experiment results also show that compared with the EMD-FastICA and VMD-FastICA, the SGMD-FastICA algorithm has the best separation effect for single-channel mixed signals. The SGMD-FastICA algorithm represents an improved solution that addresses the limitations of the FastICA algorithm, enabling the direct separation of single-channel mixed signals, while also addressing the challenge of proper signal separation in noisy environments. [ABSTRACT FROM AUTHOR]