Nutrient dynamics in the Bohai and North Yellow seas from seasonal to decadal scales: Unveiling Bohai Sea eutrophication mitigation in the 2010s

A deep learning-based model for estimating pollution fluxes from rivers into the sea and its optimization

Pollution fluxes from rivers into the sea are currently the main source of pollutants in nearshore areas. Based on the source-sink process of the basin-estuary-coastal waters system, the pollution fluxes into the sea and their spatiotemporal heterogeneity were estimated. A deep learning-based model was established to simplify the estimation of pollution fluxes into the sea, with socio-economic drivers and meteorological data as input variables. A method for estimating the contribution rate of pollution fluxes from different spatial gradient was proposed. In this study, we found that (1) the pollution fluxes into the sea of total nitrogen (TN) and total phosphorus (TP) from the Bohai Sea Rim Basin (BSRB) in 1980, 1990, 2000, 2010, and 2020 were 25.38 × 104, 26.12 × 104, 27.27 × 104, 29.82 × 104, 25.31 × 104 and 1.32 × 104, 2.14 × 104, 2.09 × 104, 1.87 × 104, 1.68 × 104 tons, respectively. (2) The proportion of rural life and livestock to the TN was the highest, accounting for 39.18 % and 21.19 %, respectively. The proportion of livestock to the TP was the highest, accounting for 39.20 %, followed by rural life, accounting for 24.72 %. The results indicated that the pollution fluxes in the BSRB were related to human economic activities and relevant environmental protection measures. (3) The deep learning-based model established to estimate runoff pollution fluxes into the sea had the accuracy of over 90 %. (4) As for contribution rate, in terms of the elevation, the range of 0-100 m had the highest proportion, accounting for 39.65 %. The range of 50-100 km from the coastline had the highest proportion, accounting for 18.11 %. In terms of the district, coastal area has the highest proportion, accounting for 38.00 %. This study revealed the changing trends and driving mechanisms of pollution fluxes into the sea over the past 40 years and established a simplified deep learning-based model for estimating pollution fluxes into the sea. Then, we identified regions with high pollution contribution rate. The results can provide scientific references for the adaptive management of the nearshore areas based on the ecosystem.

Spatiotemporal distribution patterns and coupling effects of aquatic environmental factors in the dry-wet season over a decade from the Beibu Gulf, South China Sea

Since the 21st century, the Beibu Gulf area has been affected by increasing anthropogenic activities, which makes the coastal aquatic ecosystem extremely concerning. However, the comprehensive exploration and analysis of the long-term scale behavior change characteristics of various water quality environment factors is still limited. Through comprehensively detecting coastal surface water environmental behavior information from 33 locations in the Beibu Gulf from 2005 to 2015, we revealed and quantified mutual response characteristics and patterns of various environmental indicators. The main environmental pollution indicators (e.g., COD, NH4+, NO3-, and DIP) showed a gradual decrease in concentration from the coast to the offshore sea area, and significantly increases during the wet season. The semi-enclosed Maowei Sea exhibited the most prominent performance with significant differences compared to other regions in Beibu Gulf. The average Chlorophyll-a (Chla) content in the coastal area of the Beibu Gulf during the wet season was more than twice that of the dry season, yet the interaction pattern between Chla and environmental factors in the two seasons was opposite to its concentration behavior, accompanied by a closely significant relationship with thermohaline structure and the input of nitrogen and phosphorous nutrients. The multivariate statistical analysis results of total nutrient dynamics suggested that the Beibu Gulf was clearly divided into different regions in both dry and wet season clusters. The present study can provide a comprehensive perspective for the spatial and temporal migration patterns and transformation laws of coastal water environmental factor, which should contribute to improve the prevention countermeasure of nutrient pollution in coastal environment.

Seafood waste derived carbon nanomaterials for removal and detection of food safety hazards

Nanobiotechnology and the engineering of nanomaterials are currently the main focus of many researches. Seafood waste carbon nanomaterials (SWCNs) are a renewable resource with large surface area, porous structure, high reactivity, and abundant active sites. They efficiently adsorb food contaminants through π-π conjugated, ion exchange, and electrostatic interaction. Furthermore, SWCNs prepared from seafood waste are rich in N and O functional groups. They have high quantum yield (QY) and excellent fluorescence properties, making them promising materials for the removal and detection of pollutants. It provides an opportunity by which solutions to the long-term challenges of the food industry in assessing food safety, maintaining food quality, detecting contaminants and pretreating samples can be found. In addition, carbon nanomaterials can be used as adsorbents to reduce environmental pollutants and prevent food safety problems from the source. In this paper, the types of SWCNs are reviewed; the synthesis, properties and applications of SWCNs are reviewed and the raw material selection, preparation methods, reaction conditions and formation mechanisms of biomass-based carbon materials are studied in depth. Finally, the advantages of seafood waste carbon and its composite materials in pollutant removal and detection were discussed, and existing problems were pointed out, which provided ideas for the future development and research directions of this interesting and versatile material. Based on the concept of waste pricing and a recycling economy, the aim of this paper is to outline current trends and the future potential to transform residues from the seafood waste sector into valuable biological (nano) materials, and to apply them to food safety.

A comprehensive analysis of submarine groundwater discharge and nutrient fluxes in the Bohai Sea, China

Groundwater discharge and associated nutrient fluxes in the Bohai Sea, China has attracted great attention, but most studies lacked high spatial resolution for the whole sea. As the largest semi-enclosed sea in China, the Bohai Sea is confronted with strong environmental pollution problems such as eutrophication induced by terrestrial nutrient inputs. However, the role of SGD has not been evaluated well for the whole Bohai Sea. In this study, stable isotopes (hydrogen and oxygen), radioactive isotope (228Ra), salinity, and temperature were combined to trace the diluted seawater. Mass balances of 228Ra, oxygen isotope, and salinity were used to quantify SGD and nutrient fluxes to the Bohai Sea. The estimated submarine fresh groundwater discharge (SFGD) and SGD to the Bohai Sea were (6.0 ± 0.5) × 109 and (2.7 ± 1.6) × 1011 m3 a-1, respectively. SFGD represents 10 % to 11 % of the total river discharge and SGD is about 2 to 8 folds of the total river discharge to the sea. Moreover, SGD derived dissolved nutrients to the Bohai Sea were (4.8 ± 4.0) × 1010 mol a-1 for dissolved inorganic nitrogen, (1.9 ± 1.7) × 1010 mol a-1 for dissolved inorganic phosphorus, and (6.7 ± 5.5) × 1010 mol a-1 for silicon. These nutrient inputs were about 10 to 20 folds of the total riverine inputs. Overall, this study underscores the importance of evaluating SGD to better understand the terrestrial imported nutrients in regional scale.

Atmospheric deposition and river runoff stimulate the utilization of dissolved organic phosphorus in coastal seas

In coastal seas, the role of atmospheric deposition and river runoff in dissolved organic phosphorus (DOP) utilization is not well understood. Here, we address this knowledge gap by combining microcosm experiments with a global approach considering the relationship between the activity of alkaline phosphatases and changes in phytoplankton biomass in relation to the concentration of dissolved inorganic phosphorus (DIP). Our results suggest that the addition of aerosols and riverine water stimulate the biological utilization of DOP in coastal seas primarily by depleting DIP due to increasing nitrogen concentrations, which enhances phytoplankton growth. This "Anthropogenic Nitrogen Pump" was therefore identified to make DOP an important source of phosphorus for phytoplankton in coastal seas but only when the ratio of chlorophyll a to DIP [Log10 (Chl a / DIP)] is larger than 1.20. Our study therefore suggests that anthropogenic nitrogen input might contribute to the phosphorus cycle in coastal seas.