Optical properties of sedimentary dissolved organic matter in intertidal zones along the coast of China: Influence of anthropogenic activities

Soil source, not the degree of urbanization determines soil physicochemical properties and bacterial composition in Ningbo urban green spaces

Urban green spaces provide multiple ecosystem services and have great influences on human health. However, the compositions and properties of urban soil are not well understood yet. In this study, soil samples were collected from 45 parks in Ningbo to investigate the relationships among soil physicochemical properties, heavy metals and bacterial communities. The results showed that soil dissolved organic matter (DOM) was of high molecular weight, high aromaticity, and low degree of humification. The contents of heavy metals were all below the China's national standard safety limit (GB 3660-2018). The bioavailability of heavy metals highly correlated with soil pH, the content of DOC, the fluorescent component, the degree of humification and the source of DOM. The most abundant genera were Gemmatimonadaceae_uncultured, Xanthobacteraceae_uncultured, and Acidothermus in all samples, which were related to nitrogen cycle and bioavailability of heavy metals. Soil pH, bioavailability of Zn, Cd, and Pb (CaCl2 extracted) were the main edaphic factors influencing bacterial community composition. It should be noted that there was no significant impact of urbanization on soil physicochemical properties and bacterial composition, but they were determined by the source of soil in urban green spaces. However, with the passage of time, the effect of urbanization on urban green spaces cannot be ignored. Overall, this study provided new insight for understanding the linkage among soil physicochemical properties, heavy metals, and bacterial communities in urban green spaces.

Exploring optical descriptors for rapid estimation of coastal sediment organic carbon and nearby land-use classifications via machine learning models

This study utilizes ultraviolet and fluorescence spectroscopic indices of dissolved organic matter (DOM) from sediments, combined with machine learning (ML) models, to develop an optimized predictive model for estimating sediment total organic carbon (TOC) and identifying adjacent land-use types in coastal sediments from the Yellow and Bohai Seas. Our results indicate that ML models surpass traditional regression techniques in estimating TOC and classifying land-use types. Penalized Least Squares Regression (PLR) and Cubist models show exceptional TOC estimation capabilities, with PLR exhibiting the lowest training error and Cubist achieving a correlation coefficient 0.79. In land-use classification, Support Vector Machines achieved 85.6 % accuracy in training and 92.2 % in testing. Maximum fluorescence intensity and ultraviolet absorbance at 254 nm were crucial factors influencing TOC variations in coastal sediments. This study underscores the efficacy of ML models utilizing DOM optical indices for near real-time estimation of marine sediment TOC and land-use classification.

Insight into the effect mechanism of sedimentary record of polycyclic aromatic hydrocarbon: Isotopic evidence for lake organic matter deposition and regional development model

Deciphering the temporal patterns of polycyclic aromatic hydrocarbons (PAHs) in sediment cores, and the effect mechanism of sedimentary organic matter (OM) and regional development model on PAHs are crucial for pollution control and environmental management. Herein, sediment core was collected from Chenhu international wetland in Wuhan, central China. Meanwhile, historical trend and source of PAHs and sedimentary OM were presented, respectively. Result demonstrated that the most significant growth of PAHs (increased by 158.8%) was attributed to the significant enhancement of traffic emission (5.57 times), coal combustion (4.59 times), and biomass burning (8.09 times). Similarly, the percentage of phytoplankton (stage Ⅲ: 37.9%; stage Ⅳ: 31.2%) and terrestrial C3 plants (stage Ⅲ: 24.6%; stage Ⅳ: 29.2%) to sedimentary OM hold the dominant position after the stage Ⅱ. The obvious shifts of historical trend and sources in PAHs were highly related to economic development models (r = 0.72, p < 0.001) and sedimentary OM (r = 0.82, p < 0.001). It demonstrated that eutrophication of lake accelerated the burial of PAHs. Redundancy analysis results suggested that TOC was dominating driver of sedimentary PAHs (16.56%) and phytoplankton occupied 9.58%. To further confirm the significant role of economic development models, three different historical trends of PAHs in different regions of China were presented. The result of this study provides the new insight into the geochemistry mechanism of lake sedimentary OM and PAHs. Meanwhile, the relationship of regional development model and sedimentary PAHs was highlighted in this study. Significantly, the main environmental implications of this study are as follows: (1) lake eutrophication of phytoplankton OM accelerated the burial of PAHs in lake sediment; (2) economic development models and energy structure significantly influence the sedimentary PAHs. This study highlights the coupling relationship between OM burial and PAHs sedimentation, and the importance of accelerating the transformation of economic energy structure.