Anthropogenic impact on long-term riverine CODMn, BOD, and nutrient flux variation in the Pearl River Delta

Declining particulate organic carbon flux to estuary yet rising oceanic flux over the past 20 years: A case study of the Pearl River Estuary

A substantial amount of particulate organic carbon (POC) is transported by the Pearl River to the Pearl River Estuary (PRE) and the northern South China Sea (NSCS) via its dense river network and eight outlets. The basin's high-intensity human activities and the estuary's complex hydrodynamic environment result in spatiotemporal variability in the POC flux entering both the estuary and the sea. Utilizing 30-meter spatial resolution Landsat-7/8 satellite data with the Finite Volume Community Ocean Model (FVCOM), this study estimated the monthly POC fluxes entering the PRE and the NSCS from 2001 to 2020. The results indicate that the annual mean POC flux entering the PRE is 0.13 Tg C/yr. Over the past 20 years, increased dam construction in the basin has resulted in a decline in the POC flux entering the PRE and a reduction in its annual variability. Additionally, the decrease in sediment concentration has increased the proportion of autochthonous POC, leading to a significant rise in POC (%TSM) in the Pearl River. Approximately 25 % of the POC from the river deposites in the PRE each year, while the remaining 0.098 Tg C of POC flows into the NSCS. Over the past 20 years, with a reduced POC flux entering the estuary, increased runoff, and a higher proportion of northerly winds, the POC deposition in the PRE has decreased by 47 %, and the POC flux entering the NSCS has increased by 8.7 %. Thus, despite the decrease in POC flux entering the estuary over the past 20 years, the increase in POC flux entering the sea influences seasonal hypoxia, carbon source-sink patterns and the nutrient structure in the PRE. The combined use of satellite data and numerical model provides a comprehensive and effective method for estimating POC transport in estuaries, thereby obtaining effective sea flux estimates.

The impact of marine heatwaves on surface phytoplankton chlorophyll-a in the South China Sea

According to previous studies, marine heatwaves (MHWs) significantly suppress the phytoplankton chlorophyll-a concentration (Chl a) in tropical oceans. However, pre-MHW Chl a has rarely been considered as a reference value. In this study, the Chl a for the periods preceding and during MHWs events was used to explore the impact of MHWs on Chl a from 1998 to 2022 in the South China Sea (SCS). The Chl a response to MHWs in different regions was further discussed based on the Chl a variation characteristics. The results showed that the Chl a response to MHWs exhibited regional variability. Interestingly, there was a large proportion of positive Chl a anomalies (∼0.55) in the estuary and offshore regions during MHWs; however, Chl a anomalies were mostly negative in the upwelling regions. These different response patterns are related to background conditions, including nutrient concentrations, wind-driven dynamics, and light availability. In upwelling regions, negative Chl a anomalies were primarily due to the weakening of wind speeds, Ekman pumping velocities, and upwelling intensities. In estuarine regions, positive Chl a anomalies were caused by enhanced light availability, whereas in offshore regions, there were attributed to the increased atmospheric wet deposition. These results have improved our understanding of the impact of MHWs on marine ecosystems.

Assessment and prediction of Water Quality Index (WQI) by seasonal key water parameters in a coastal city: application of machine learning models

The Water Quality Index (WQI) provides comprehensive assessments in river systems; however, its calculation involves numerous water quality parameters, costly in sample collection and laboratory analysis. The study aimed to determine key water parameters and the most reliable models, considering seasonal variations in the water environment, to maximize the precision of WQI prediction by a minimal set of water parameters. Ten statistical or machine learning models were developed to predict the WQI over four seasons using water quality dataset collected in a coastal city adjacent to the Yellow Sea in China, based on which the key water parameters were identified and the variations were assessed by the Seasonal-Trend decomposition procedure based on Loess (STL). Results indicated that model performance generally improved with adding more input variables except Self-Organizing Map (SOM). Tree-based ensemble methods like Extreme Gradient Boosting (XGB) and Random Forest (RF) demonstrated the highest accuracy, particularly in winter. Nutrients (Ammonia Nitrogen (AN) and Total Phosphorus (TP)), Dissolved Oxygen (DO), and turbidity were determined as key water parameters, based on which, the prediction accuracy for Medium and Low grades was perfect while it was over 80% for the Good grade in spring and winter and dropped to around 70% in summer and autumn. Nutrient concentrations were higher at inland stations; however, it worsened at coastal stations, especially in summer. The study underscores the importance of reliable WQI prediction models in water quality assessment, especially when data is limited, which are crucial for managing water resources effectively.

Evolution of hydrochemical characteristics and the influence of environmental background in the Hailar River basin, China

Understanding the evolution of hydrochemical characteristics in river systems is essential for environmental assessment and water resource management. This study explores the spatiotemporal distribution and the determinants of hydrochemical characteristics in the Hailar River basin, China, over an extensive period. Our results revealed that CODMn and CODCr were the primary concerns for long-term river management, with exceedance rates of 42.92% and 50.62%, respectively. These exceedances were predominantly driven by interactions between riparian soils and surface water, rather than anthropogenic pollution, as suggested by the strong correlations between dissolved organic carbon and soil water-extractable organic carbon, and the limited human footprint in this region. Piper trilinear and Gibbs diagram analysis further revealed that long-term rack weathering shaped the basin's hydrochemical characteristics, resulting in distinct HCO3--Ca2+ and HCO3--Ca2+-Na+ signatures. In addition, APCS-MLR analysis identified that elevated of CODMn and CODCr levels were mainly attributed to the interactions with adjacent soils, which are extensively covered by forests and grasslands. In contrast, leaching and migration processes contributed significantly on total dissolved solids and total phosphorus. The study also found that environmental self-purification processes played a key role in regulating Fe concentrations. This investigation provides a nuanced understanding of the environmental background's influence on hydrochemistry and dissolved organic matter (DOM) in the Hailar River basin, which offers valuable insights and methodologies for the rational assessment of water quality and aquatic ecosystem health in similar riverine systems.

Phytoplankton Diversity, Spatial Patterns, and Photosynthetic Characteristics Under Environmental Gradients and Anthropogenic Influence in the Pearl River Estuary

The Pearl River Estuary (PRE) is one of the world's most urbanized subtropical coastal systems. It presents a typical environmental gradient suitable for studying estuarine phytoplankton communities' dynamics and photosynthetic physiology. In September 2018, the maximum photochemical quantum yield (Fv/Fm) of phytoplankton in different salinity habitats of PRE (oceanic, estuarine, and freshwater zones) was studied, revealing a complex correlation with the environment. Fv/Fm of phytoplankton ranged from 0.16 to 0.45, with taxa in the upper Lingdingyang found to be more stressed. Community composition and structure were analyzed using 18S rRNA, accompanied by a pigment analysis utilized as a supplementary method. Nonmetric multidimensional scaling analysis indicated differences in the phytoplankton spatial distribution along the estuarine gradients. Specificity-occupancy plots identified different specialist taxa for each salinity habitat. Dinophyta and Haptophyta were the predominant taxa in oceanic areas, while Chlorophyta and Cryptophyta dominated freshwater. Bacillariophyta prevailed across all salinity gradients. Canonical correlation analysis and Mantel tests revealed that temperature, salinity, and elevated nutrient levels (i.e., NO3--N, PO43--P, and SiO32--Si) associated with anthropogenic activities significantly influenced the heterogeneity of community structure. The spatial distribution of phytoplankton, along with in situ photosynthetic characteristics, serves as a foundational basis to access estuarine primary productivity, as well as community function and ecosystem health.

Occurrence characteristics and influencing factors of antibiotic resistance genes in rural groundwater in Henan Province

This study determined the antibiotic-resistant gene (ARG) contents of 34 groundwater samples in Henan Province collected from September to October 2022, then assessed the roles of both water quality parameters and intI1 in ARG propagation in groundwater. The results show that there existed universal ARG pollution in groundwater, and sulfonamides-, β-lactem-, and tetracycline-resistance genes were the most prevalent gene types during the time. Sul1 contributed the majority proportion of the total resistance genes (TARGs). The prevalence of ESBLs gene blaTEM and the occurrence of Carbapenems resistant gene blaOXA-1 suggests the pollution of high-risk ARGs in groundwater demands more attention. IntI1 is prevalent and had a significantly positive correlation with almost 50% ARGs, indicating its contribution to ARG propagation in groundwater. Well types contribute little to ARG propagation in rural groundwater of Henan, which means the protective facilities established by the local government for public wells can effectively prevent contamination from exogenous ARGs. However, the economic level has no impact on the abundance of ARGs in rural groundwater, which suggests the local government should pay greater attention to investment in controlling ARG pollution in Henan rural areas.

Recent Declines in Nutrient Concentrations and Fluxes in the Lower Changjiang River

To elucidate nutrient variation patterns and trends over various timescales under combined effects of human activities and climate change, nutrient concentrations were monitored monthly in Lower Changjiang (Yangtze) River from November 2016 to August 2020. They were also monitored daily during an extreme flood in July 2020. Over daily and seasonal timescales, the Changjiang River discharges had a dominant influence on nutrient concentrations. By combining existing data over recent decades with those from the current study, we found that turning points for concentration trends for most nutrients emerged in the recent decade (2010-2020), i.e., 2012 for NO3-, PO43-, and NH4+ and 2014 for SiO32-. After these turning point years, NO3-, SiO32-, and PO43- concentrations decreased at annual rates of 2.953, 3.746, and 0.108 μM/year, respectively. Regarding NO3- and PO43-, their concentrations and fluxes increased from 1960s to 2012, similar to the increasing trends of anthropogenic N and P fertilizer inputs from the drainage basin. After 2012, concentrations and fluxes of NO3- and PO43- showed significant decreasing trends, largely due to the control of N and P fertilizer usage. A comparison among eight rivers in East and South China (including the Changjiang River) indicated that basin latitudes were essential to determining areal nutrient yields, implying that latitude-related factors, such as temperature, precipitation, and areal population density, significantly impacted nutrient fluxes. This study emphasized that the deteriorating Changjiang River aquatic environment (which lasted from 1960s to 2010) has been successfully terminated over the last 10 years in 2010s.