Shellfish and algae mariculture make up an important part of the marine fishery carbon sink. Carbon sink research is necessary to ensure China achieves its goal of carbon neutrality. This study used the material quality assessment method to estimate the carbon sink capacity of shellfish and algae. Product value, carbon storage value, and oxygen release value were used to calculate the economic value of shellfish and algae carbon sequestration. The results showed that the annual average shellfish and algae carbon sink in China was 1.10 million tons from 2003 to 2019, of which shellfish accounted for 91.63%, wherein Crassostreagigas, Ruditapesphilippinarum, and Chlamysfarreri were the main contributors. The annual average economic value of China’s shellfish and algae carbon sequestration was USD 71,303.56 million, and the product value was the main contributor, accounting for 99.11%. The carbon sink conversion ratios of shellfish and algae were 8.37% and 5.20%, respectively, thus making shellfish the aquaculture species with the strongest carbon sink capacity and the greatest carbon sink potential. The estimated growth rate in the shellfish and algae removable carbon sink was 33,900 tons/year in China, but this trend was uncertain. The capacity for carbon sequestration and exchange by aquaculture can be improved by expanding breeding space, promoting multi-level comprehensive breeding modes, and marine artificial upwelling projects.

The blue carbon ecosystem has a strong capacity for carbon sequestration, but its research progress and development are still unclear. This study used CiteSpace to conduct a visual analysis, based on the analysis of 908 articles retrieved from the Web of Science Core Collection. The results showed that blue carbon research has gone through an early exploratory stage based on the scientific concept research, a research stage on the carbon sequestration process of the diverse blue carbon ecosystems, and a blue carbon protection and restoration stage based on climate change and human activities. The blue carbon theoretical framework has been continuously improved and the subject is currently more focused. The hot research topics are different at different stages. In the early stage, they focused on the types of blue carbon ecosystems and the process of carbon sequestration. Blue carbon research has developed from a single ecosystem type to multiple ecosystem types, and from concept recognition to system assessment research. Recently, research on the response, restoration and protection of blue carbon ecosystems has become a hotspot under the combined effect of human activities and climate change. In the future, it is necessary to strengthen the scientific research on blue carbon, to protect the integrity of the ecosystem structure and service functions, and to make a greater contribution to the global carbon neutrality strategy.

Fluoride (F⁻) is widespread in aquatic environments; however, it is not clear whether the fluctuation of F⁻ concentrations in overlying lake water affects the composition and migration of dissolved organic matter (DOM) from sediment. A case study was presented in Sand Lake, China, and an experiment was conducted to analyze the influence of different F⁻ concentrations in overlying water on DOM characteristics. Diffusion resulted in similarities in DOM components between overlying and pore waters, and bacterial activities and enzyme variation resulted in differences between them. Higher F⁻ concentrations in overlying water resulted in a higher pH of pore water, which favored the enrichment of protein-like substances. Higher F⁻ concentrations caused lower DOM concentrations and lower maximum fluorescence intensities (F_max) of protein-like components in pore water. The F⁻ concentrations had significantly negative correlations with Shannon indexes (P < 0.05). Thiobacillus influenced the migration of tyrosine-like substances by decreasing the pH of pore water. Trichococcus and Fusibacter altered the F_max of protein-like, humic-like, and fulvic-like substances. The F⁻ concentrations affected the DOM composition and migration due to the response of functional bacterial communities, which were positively correlated with the relative abundance of Thiobacillus and negatively correlated with the relative abundances of Trichococcus and Fusibacter. The high F⁻ concentrations influenced the biosynthesis and degradation of protein-like substances by shifting the abundances of the relevant enzymes. The results of this study may provide ideas for investigating DOM cycling under the influence of F⁻, especially in lakes with fluctuations in F⁻ concentrations.

With the development of cities, urban area source pollution has become more severe and a significant source of water pollution. To study the relationship between urban area source pollution and water environmental quality in a river network, this study uses a city in the Yangtze River Delta, China, as an example. The Storm Water Management Model (SWMM) model and the MIKE11 model were combined into a unified modeling framework and used to simulate dynamic changes in the water quality of a river network under light rain, moderate rain, and heavy rain. In the study period, the annual urban area source input loads of potassium permanganate (COD_Mn), total phosphorus (TP), and ammonia nitrogen were 29.8, 0.9, and 4.8 t, respectively. The influence of light rain on the water quality of the river network was lagging and temporary, and rainfall area pollution was the primary contributor. Under the scenario of moderate rain, overflow from a pipeline network compounded rainfall runoff, resulting in a longer duration of impact on the water quality in the river. Additionally, the water quality in the river course was worse under moderate rain than under light or heavy rain. Under the scenario of heavy rain, rain mainly served a dilutive function. This research can provide support for urban area source pollution control and management.

The excessive input of nutrients into rivers can lead to contamination and eutrophication, which poses a threat to the health of aquatic ecosystems. It is crucial to identify the sources of contaminants to develop effective management plans for eutrophication. However, traditional methods for identifying pollution sources have been insufficient, making it difficult to manage river health effectively. High-throughput sequencing offers a novel method for microbial community source tracking, which can help identify dominant pollution sources in rivers. The Wanggang River was selected for study, as it has suffered accelerated eutrophication due to considerable nutrient input from riparian pollutants. The present study identified the dominant microbial communities in the Wanggang River basin, including Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Verrucomicrobia, and Firmicutes. The Source Tracker machine-learning classification system was used to create source-specific microbial community fingerprints to determine the primary sources of contaminants in the basin, with agricultural fertilizer being identified as the main pollutant source. By identifying the microbial communities of potential pollution sources, the study determined the contributing pollutant sources in several major sections of the Wanggang River, including industry, urban land, pond culture, and livestock land. These findings can be used to improve the identification of pollution sources in specific environments and develop effective pollution management plans for polluted river water.