Compound effect of land reclamation and land-based pollutant input on water quality in Qinzhou Bay, China

The individual and combined effects of coastline changes and riverine input on water quality: A multi-scenario simulation perspective

The Bohai Sea Rim is densely populated and highly industrialized, facing threats from large-scale land reclamation, riverine pollutant discharge, and other anthropogenic activities. Aiming to improve seawater quality, the optimal allocation of land-based total nitrogen (TN) loads among four major rivers around the Bohai Sea has been studied before. However, the individual and combined impacts of coastline changes and riverine input were not previously quantified and analyzed. Therefore, a coupled hydrodynamics-water quality model was used to simulate the variation of dissolved inorganic nitrogen (DIN) and TN caused by reclamation and sedimentation. The results show that coastline changes significantly influence tidal dynamics, tidal prisms, residual currents, and the degree of openness, thereby altering the diffusion pathway of pollutants. Specifically, land reclamation activities and Yellow River mouth movements have led to increased concentrations of DIN and TN in estuarine areas (e.g., Haihe River Estuary, Ziyaxin River Estuary, and Wei River Estuary). Additionally, the combined impacts of coastline changes and TN input variations were found to amplify or diminish their individual impacts on water quality. Considering the individual factors, the impact of coastline change (15-year basis) was much greater than that of land-based TN input (a 10 % and 20 % random error, respectively). This study provides valuable insights into the complex interactions between coastline dynamics and marine water quality, emphasizing the importance of considering both natural and anthropogenic factors in coastal environmental management.

Blue carbon ecosystems for hypoxia solution: how to maximize their carbon sequestration potential

Blue carbon refers to the carbon captured and stored by coastal and oceanic ecosystems, such as mangroves, seagrasses, and salt marshes. These ecosystems are vital for biodiversity and play a crucial role in sequestering carbon dioxide from the atmosphere, helping to mitigate climate change, which can also provide economic value by evaluating payment for ecosystem services (PES) schemes. Additionally, they help regulate dissolved organic carbon, mitigate eutrophication, and improve water quality, reducing the impact of global deoxygenation. Conserving and restoring blue carbon ecosystems are vital for mitigating hypoxia, enhancing biodiversity, and supporting various ecosystem services. Moreover, genomic research on blue carbon plants and microbes reveals adaptive traits that enhance resilience to hypoxia and environmental stress. Integrating conservation, restoration, and molecular approaches will maximize their carbon sequestration potential, ensuring ecological stability and climate adaptation. This review aims to provide an overview of blue carbon and its significance, particularly in addressing hypoxia, highlighting the critical need for investigating hypoxia responses and microbial interactions to fully understand the mechanisms of carbon sequestration and hypoxia mitigation.

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.

Influence of watershed characteristics and human activities on the occurrence of organophosphate esters related to dissolved organic matter in estuarine surface water

Organophosphate esters (OPEs) are widespread in aquatic environments and pose potential threats to ecosystem and human health. Here, we profiled OPEs in surface water samples of heavily urbanized estuaries in eastern China and investigated the influence of watershed characteristics and human activities on the spatial distribution of OPEs related to dissolved organic matter (DOM). The total OPE concentration ranged from 22.3 to 1201 ng/L, with a mean of 162.6 ± 179.8 ng/L. Chlorinated OPEs were the predominant contaminant group, accounting for 27.4-99.6 % of the total OPE concentration. Tris(2-chloroisopropyl) phosphate, tris(1,3-dichloro-2-propyl) phosphate, and tributyl phosphate were the dominant compounds, with mean concentrations of 111.2 ± 176.0 ng/L, 22.6 ± 21.5 ng/L, and 14.8 ± 14.9 ng/L, respectively. Variable OPE levels were observed in various functional areas, with significantly higher concentrations in industrial areas than in other areas. Potential source analysis revealed that sewage treatment plant effluents and industrial activities were the primary OPE sources. The total OPE concentrations were negatively correlated to the mean slope, plan curvature, and elevation, indicating that watershed characteristics play a role in the occurrence of OPEs. Individual OPEs (triisobutyl phosphate, tris(2-butoxyethyl) phosphate, tris(2-chloroethyl) phosphate, and tricresyl phosphate) and Σalkyl-OPEs were positively correlated to the night light index or population density, suggesting a significant contribution of human activity to OPE pollution. The co-occurrence of OPEs and DOM was also observed, and the fluorescence indices of DOM were found to be possible indicators for tracing OPEs. These findings can elucidate the potential OPE dynamics in response to DOM in urbanized estuarine water environments with intensive human activities.

Land reclamation and its consequences: A 40-year analysis of water residence time in Doha Bay, Qatar

Qatar's rapid industrialization, notably in its capital city Doha, has spurred a surge in land reclamation projects, leading to a constriction of the entrance to Doha Bay. By reducing and deflecting the ocean circulation, land reclamation projects have reduced the effective dispersion of wastewater introduced into the bay and hence degraded the water quality. Here, we assess fluctuations in water residence time across three distinct eras (1980, 2000, and 2020) to gauge the impact of successive land reclamation developments. To do this, we couple the multi-scale ocean model SLIM with a Lagrangian model for water residence time within Doha's coastal area. We consider three different topographies of Doha's shoreline to identify which artificial structures contributed the most to increase water residence time. Our findings reveal that the residual ocean circulation in Doha Bay was predominantly impacted by northern developments post-2000. Between 1980 and 2000, the bay's residence time saw a modest rise, of about one day on average. However, this was followed by a substantial surge, of three to six days on average, between 2000 and 2020, which is mostly attributable to The Pearl mega artificial island development. Certain regions of the bay witnessed a tripling of water residence time. Given the ongoing population expansion along the coast, it is anticipated that the growth of artificial structures and coastal reclamation will persist, thereby exacerbating the accumulation of pollutants in the bay. Our findings suggest that artificial offshore structures can exert far-reaching, non-local impacts on water quality, which need to be properly assessed during the planning stages of such developments.

Using benthic macroinvertebrates as bioindicators to evaluate the impact of anthropogenic stressors on water quality and sediment properties of a West African lagoon

This study aimed to investigate the impact of anthropogenic stressors (landfilling, navigation for transport of goods, cooling in fossil fuel, urbanization, industrial expansion, agriculture activities, and recreational activities) on environmental variables, microbiological quality, and sediment properties using benthic macroinvertebrates as a bioindicator within Lagos Lagoon, Nigeria. Four (4) sampling stations were established with respect to their importance/anthropogenic activities within the Lagos Lagoon. Surface water, bottom substrates, and benthic macroinvertebrate fauna samples were collected bimonthly from each sampling station for a year and analyzed using appropriate standard methods and procedures. The highest pH range of 7.96-8.01 (7.98 ± 2.35) was recorded at Site IV, while the lowest range of 6.41-7.01 (6.15 ± 1.14) was observed at Site II, and there was a significant difference (p < 0.05) among the pH mean values across the sites. High values of salinity, chloride, sodium, COD, BOD, manganese, nickel, cadmium, and nitrate were recorded among the surface water physicochemical parameters, which were above WHO (2011) permissible limits, while the high concentrations of toxic metals (Pb, Cr, Zn, and Cd) was recorded in sediment. A total of 26 species of benthic macroinvertebrates were recorded during this study, which belongs to eight (8) classes. Gastropoda recorded the highest percentage contribution of 39.12%, followed by polychaeta accounting for 30.34%, while malacostraca contributed 2.63%. The highest abundance of macroinvertebrates was recorded at Site I (256 Indiv/m2), followed by Site IV (252 Indiv/m2), and the least was observed at Site II (195 Indiv/m2). Based on the results of the physico-chemical, heavy metals, microbial quality, and macroinvertebrates assemblage obtained from this study revealed the adverse effect of anthropogenic activities on water quality degradation. It plays a significant role in the distribution and diversity of benthic macroinvertebrates in an aquatic environment.

An ensemble machine learning model for water quality estimation in coastal area based on remote sensing imagery

The accurate estimation of coastal water quality parameters (WQPs) is crucial for decision-makers to manage water resources. Although various machine learning (ML) models have been developed for coastal water quality estimation using remote sensing data, the performance of these models has significant uncertainties when applied to regional scales. To address this issue, an ensemble ML-based model was developed in this study. The ensemble ML model was applied to estimate chlorophyll-a (Chla), turbidity, and dissolved oxygen (DO) based on Sentinel-2 satellite images in Shenzhen Bay, China. The optimal input features for each WQP were selected from eight spectral bands and seven spectral indices. A local explanation strategy termed Shapley Additive Explanations (SHAP) was employed to quantify contributions of each feature to model outputs. In addition, the impacts of three climate factors on the variation of each WQP were analyzed. The results suggested that the ensemble ML models have satisfied performance for Chla (errors = 1.7%), turbidity (errors = 1.5%) and DO estimation (errors = 0.02%). Band 3 (B3) has the highest positive contribution to Chla estimation, while Band Ration Index2 (BR2) has the highest negative contribution to turbidity estimation, and Band 7 (B7) has the highest positive contribution to DO estimation. The spatial patterns of the three WQPs revealed that the water quality deterioration in Shenzhen Bay was mainly influenced by input of terrestrial pollutants from the estuary. Correlation analysis demonstrated that air temperature (Temp) and average air pressure (AAP) exhibited the closest relationship with Chla. DO showed the strongest negative correlation with Temp, while turbidity was not sensitive to Temp, average wind speed (AWS), and AAP. Overall, the ensemble ML model proposed in this study provides an accurate and practical method for long-term Chla, turbidity, and DO estimation in coastal waters.