Global Navigation Satellite System Receiver Positioning in Harsh Environments via Clock Bias Prediction by Empirical Mode Decomposition and Back Propagation Neural Network Method.

This paper proposes a novel method to improve the clock bias short-term prediction accuracy of navigation receivers then solve the problem of low positioning accuracy when the satellite signal quality deteriorates. Considering that the clock bias of a navigation receiver is equivalent to a virtual satellite, the predicted value of clock bias is used to assist navigation receivers in positioning. Consequently, a combined prediction method for navigation receiver clock bias based on Empirical Mode Decomposition (EMD) and Back Propagation Neural Network (BPNN) analysis theory is demonstrated. In view of systematic errors and random errors in the clock bias data from navigation receivers, the EMD method is used to decompose the clock bias data; then, the BPNN prediction method is used to establish a high-precision clock bias prediction model; finally, based on the clock bias prediction value, the three-dimensional positioning of the navigation receiver is realized by expanding the observation equation. The experimental results show that the proposed model is suitable for clock bias time series prediction and providing three-dimensional positioning information meets the requirements of navigation application in the harsh environment of only three satellites.

Integrated transcriptomics and metabolomics analyses reveal the aerobic biodegradation and molecular mechanisms of 2,3',4,4',5-pentachlorodiphenyl (PCB 118) in Methylorubrum sp. ZY-1.

2,3',4,4',5-pentachlorodiphenyl (PCB 118), a highly representative PCB congener, has been frequently detected in various environments, garnering much attention across the scientific community. The degradation of highly chlorinated PCBs by aerobic microorganisms is challenging due to their hydrophobicity and persistence. Herein, the biodegradation and adaptation mechanisms of Methylorubrum sp. ZY-1 to PCB 118 were comprehensively investigated using an integrative approach that combined degradation performance, product identification, metabolomic and transcriptomic analyses. The results indicated that the highest degradation efficiency of 0.5 mg L-1 PCB 118 reached 75.66% after seven days of inoculation when the bacteria dosage was 1.0 g L-1 at pH 7.0. A total of eleven products were identified during the degradation process, including low chlorinated PCBs, hydroxylated PCBs, and ring-opening products, suggesting that strain ZY-1 degraded PCB 118 through dechlorination, hydroxylation, and ring-opening pathways. Metabolomic analysis demonstrated that the energy supply and redox metabolism of strain ZY-1 was disturbed with exposure to PCB 118. To counteract this environmental stress, strain ZY-1 adjusted both the fatty acid synthesis and purine metabolism. The analysis of transcriptomics disclosed that multiple intracellular and extracellular oxidoreductases (e.g., monooxygenase, alpha/beta hydrolase and cytochrome P450) participated in the degradation of PCB 118. Besides, active efflux of PCB 118 and its degradation intermediates mediated by multiple transporters (e.g., MFS transporter and ABC transporter ATP-binding protein) might enhance bacterial resistance against these substances. These discoveries provided the inaugural insights into the biotransformation of strain ZY-1 to PCB 118 stress, illustrating its potential in the remediation of contaminated environments.

Low SNR multimirror Fabry-Perot pressure sensor optic spectrum signal analysis and demodulation via SVM-KNN regressors.

We demonstrate an ensemble learning based method to solve the problem of low SNR Fabry-Perot sensor spectrum signal demodulation. Taking the eight-layer approximate coefficients of a multilevel discrete wavelet transform as input features, an ensemble model that combines multiple SVM and KNN learners is trained. Bootstrap and booting techniques are introduced for better modeling performance and stability. It is shown that the performance of the proposed ensemble model based on SVM-KNN regressors is excellent; an accuracy of 0.46%F.S. relative mean error is achieved. This method could provide insight into the construction of a large scale fiber based Fabry-Perot sensor network.

Estimating four-decadal variations of seagrass distribution using satellite data and deep learning methods in a marine lagoon.

Seagrasses are marine flowering plants that inhabit shallow coastal and estuarine waters and serve vital ecological functions in marine ecosystems. However, seagrass ecosystems face the looming threat of degradation, necessitating effective monitoring. Remote-sensing technology offers significant advantages in terms of spatial coverage and temporal accessibility. Although some remote sensing approaches, such as water column correction, spectral index-based, and machine learning-based methods, have been proposed for seagrass detection, their performances are not always satisfactory. Deep learning models, known for their powerful learning and vast data processing capabilities, have been widely employed in automatic target detection. In this study, a typical seagrass habitat (Swan Lake) in northern China was used to propose a deep learning-based model for seagrass detection from Landsat satellite data. The performances of UNet and SegNet at different patch scales for seagrass detection were compared. The results showed that the SegNet model at a patch scale of 16 × 16 pixels worked well, with validation accuracy and loss of 96.3 % and 0.15, respectively, during training. Evaluations based on the test dataset also indicated good performance of this model, with an overall accuracy >95 %. Subsequently, the deep learning model was applied for seagrass detection in Swan Lake between 1984 and 2022. We observed a noticeable seasonal variation in germination, growth, maturation, and shrinkage from spring to winter. The seagrass area decreased over the past four decades, punctuated by intermittent fluctuations likely attributed to anthropogenic activities, such as aquaculture and construction development. Additionally, changes in landscape ecology indicators have demonstrated that seagrass experiences severe patchiness. However, these problems have weakened recently. Overall, by combining remote sensing big data with deep learning technology, our study provides a valuable approach for the highly precise monitoring of seagrass. These findings on seagrass area variation in Swan Lake offer significant information for seagrass restoration and management.

Unravelling the removal mechanisms of trivalent arsenic by sulfidated nanoscale zero-valent iron: The crucial role of reactive oxygen species and the multiple effects of citric acid.

The remediation of arsenic-contaminated groundwater by sulfidated nanoscale zero-valent iron (S-nZVI) has raised considerable attention. However, the role of trivalent arsenic (As(III)) oxidation by S-nZVI in oxic conditions (S-nZVI/O2) remains controversial, and the comprehensive effect of citric acid (CA) prevalent in groundwater on As(III) removal by S-nZVI remains unclear. Herein, the mechanisms of reactive oxygen species (ROS) generation and multiple effects of CA on As(III) removal by S-nZVI/O2 were systematically explored. Results indicated that the removal efficiency of As(III) by S-nZVI/O2 (97.81 %) was prominently higher than that by S-nZVI (66.71 %), resulting from the significant production of ROS (mainly H2O2 and OH) under oxic conditions, which played a crucial role in promoting the As(III) oxidation. Additionally, CA had multiple effects on As(III) removal by S-nZVI/O2 system: (i) CA impeded the diffusion of As(III) towards S-nZVI and increased the secondary risk of immobilized As(III) re-releasing into the environment due to the Fe dissolution from S-nZVI; (ii) CA could significantly enhance the yields of OH from 25.29 to 133.00 µM via accelerating the redox cycle of Fe(II)/Fe(III) and increasing the oriented conversion rate of H2O2 to OH; (iii) CA could also enrich the types of ROS (such as O2- and 1O2) in favor of further As(III) oxidation. This study contributed novel findings regarding the control of As(III) contaminated groundwater using S-nZVI technologies.

Analysis of scanning systematic errors for airborne laser bathymetry.

For the Palmer mechanical scanning pattern of an airborne laser bathymetry system, the potential errors of the scanning system are analyzed, and the associated error model is derived. The model composes the description of laser rays, water surface fluctuations, and refraction, and introduces certain simplifications concerning the water surface and column. Based on the scanning error model, the impact of each error source on the vertical and horizontal positioning accuracy is investigated and established through a numerical simulation. The quantitative impacts of each inaccuracy on the coordinates of the laser footprints on the sea surface and bottom were calculated, with a height of 100 m for the airborne platform and a water depth of 10 m. To verify the correctness of the simulation results and the error model based on a theoretical analysis, experiments are utilized with the system that we developed. Both the simulation analysis and experimental results show that this method can effectively obtain the systematic errors. The outcomes of the error model and analysis will give the theoretical foundations for lowering the effect brought on by each error source in the compensation scanning system and improving the point cloud accuracy in the ensuing data processing.

Remodeling tumor immunosuppression with molecularly imprinted nanoparticles to enhance immunogenic cell death for cancer immunotherapy.

Insufficient tumor accumulation and distribution of immunogenic cell death (ICD) inducer as well as low antitumor immunity severely restrict the therapeutic efficacy of tumor immunotherapy. Tumor associated fibroblasts (TAFs) are important in tumor extracellular matrix (ECM) remodeling and immune evasion. Reprogramming tumor immunosuppressive microenvironment via TAFs regulation might present a promising way for enhanced ICD effect and complete tumor elimination. In this study, TAFs derived tryptase imprinted nanoparticles (DMSN@MIPs) are developed to modulate TAFs and improve tumor immunotherapy effect of doxorubicin liposomes (DOX/LIP). Tryptase (TPS), secreted by mast cells, are found to support tumor growth via transcriptionally activating TAFs to an activated state with increased expression of fibroblast activation marker α-smooth muscle actin (α-SMA). DMSN@MIPs canbe used as artificial antibodies, which effectively neutralize TPS, reduce TAFs activation, promote intra-tumor penetration of DOX/LIP and enhance ICD effect induced by DOX/LIP. In addition, the combined administration system remodels immunosuppressive microenvironment, which not only significantly up-regulates immune cells (DC cells, CD8+T cells, NK cells), but also significantly down-regulates immunosuppressive cells (Treg cells, MDSCs cells). Our results support the DMSN@MIPs canbe a promising approach to improve ICD efficacy in cancer immunotherapy.

Bioremediation of PBDEs and heavy metals co-contaminated soil in e-waste dismantling sites by Pseudomonas plecoglossicida assisted with biochar.

Biochar-assisted microbial remediation has been proposed as a promising strategy to eliminate environmental pollutants. However, studies on this strategy used in the remediation of persistent organic pollutants and heavy metals co-contaminated soil are lacking, and the effect of the combined incorporation of biochar and inoculant on the assembly, functions, and microbial interactions of soil microbiomes are unclear. Here, we studied 2,2',4,4'-tetrabrominated diphenyl ether (BDE-47) degradation and heavy metal immobilization by and biochar-based bacterial inoculant (BC/PP) in an e-waste contaminated soil, and corresponding microbial regulation mechanisms. Results showed that BC/PP addition was more effective in reducing Cu and Pb availability and degrading BDE-47 than inoculant alone. Notably, BC/PP facilitated bound-residue formation of BDE-47, reducing the ecological risk of residual BDE-47. Meanwhile, microbial carbon metabolism and enzyme activities (related to C-, N-, and P- cycles) were enhanced in soil amended with BC/PP. Importantly, biochar played a crucial role in inoculant colonization, community assembly processes, and microbiome multifunction. In the presence of biochar, positive interactions in co-occurrence networks of the bacterial community were more frequent, and higher network stability and more keystone taxa were observed (including potential degraders). These findings provide a promising strategy for decontaminating complex-polluted environments and recovering soil ecological functions.

Deciphering the distinct successional patterns and potential roles of abundant and rare microbial taxa of urban riverine plastisphere.

Microbial colonization on microplastics has provoked global concern; however, many studies have not considered the successional patterns and potential roles of abundant and rare taxa of the plastisphere during colonization. Hence, we investigate the taxonomic composition, assembly, interaction and function of abundant and rare taxa in the riverine plastisphere by conducting microcosm experiments. Results showed that rare taxa occupied significantly high community diversity and niche breadth than the abundant taxa, which implies that rare taxa are essential components in maintaining the community stability of the plastisphere. However, the abundant taxa played a major role in driving the succession of plastisphere communities during colonization. Both stochastic and deterministic processes signally affected the plastisphere community assemblies; while, the deterministic patterns (heterogeneous selection) were especially pronounced for rare biospheres. Plastisphere microbial networks were shaped by the enhancement of network modularity and reinforcement of positive interactions. Rare taxa played critical roles in shaping stable plastisphere by occupying the key status in microbial networks. The strong interaction of rare and non-rare taxa suggested that multi-species collaboration might be conducive to the formation and stability of the plastisphere. Both abundant and rare taxa were enriched with plentiful functional genes related to carbon, nitrogen, phosphorus and sulfur cycling; however, their potential metabolic functions were significantly discrepant, implying that the abundant and rare microbes may play different roles in ecosystems. Overall, this study strengthens our comprehending of the mechanisms regarding the formation and maintenance of the plastisphere.

Remediation of Cu and As contaminated water and soil utilizing biochar supported layered double hydroxide: Mechanisms and soil environment altering.

Preparing materials for simultaneous remediation of anionic and cationic heavy metals contamination has always been the focus of research. Herein a biochar supported FeMnMg layered double hydroxide (LDH) composites (LB) for simultaneous remediation of copper and arsenic contamination in water and soil has been assembled by a facile co-precipitation approach. Both adsorption isotherm and kinetics studies of heavy metals removal by LB were applied to look into the adsorption performance of adsorbents in water. Moreover, the adsorption mechanisms of Cu and As by LB were investigated, showing that Cu in aqueous solution was removed by the isomorphic substitution, precipitation and electrostatic adsorption while As was removed by complexation. In addition, the availability of Cu and As in the soil incubation experiments was reduced by 35.54%-63.00% and 8.39%-29.04%, respectively by using LB. Meanwhile, the addition of LB increased the activities of urease and sucrase by 93.78%-374.35% and 84.35%-520.04%, respectively, of which 1% of the dosage was the best. A phenomenon was found that the richness and structure of microbial community became vigorous within 1% dosage of LB, which indirectly enhanced the passivation and stabilization of heavy metals. These results indicated that the soil environment was significantly improved by LB. This research demonstrates that LB would be an imaginably forceful material for the remediation of anionic and cationic heavy metals in contaminated water and soil.

Promotion of the biodegradation of phenanthrene adsorbed on microplastics by the functional bacterial consortium QY1 in the presence of humic acid: Bioavailability and toxicity evaluation.

The adsorption of hydrophobic organic compounds (HOCs) by microplastics (MPs) has attracted great attention in recent years. However, the ultimate environmental fate of the HOCs sorbed on MPs (HOCs-MPs) is poorly understood. In this work, we investigated the potential influence of the biotransformation process on the environmental fate of phenanthrene (PHE, a model HOC) sorbed on MPs (PHE-MPs) under the existence of humic acid (HA, the main ingredient of dissolved organic matter (DOM)) in the aquatic environment. The results indicated that the adsorption behavior of PHE on MPs decreased its bioavailability and thus inhibited its biotransformation efficiency. However, HA significantly promoted the biodegradation rate and percentage of PHE-MPs. This was probably because HA improved the desorption of PHE from MPs, which promoted the acquisition of PHE by bacteria from the aqueous phase. Further, HA dramatically increased the bacterial community diversity and richness and altered the community composition. The richness of some PHE-degrading bacteria, such as Methylobacillus and Sphingomonas, significantly increased, which may also be an important factor for promoting PHE biodegradation. Molecular ecological network analysis implied that HA enhanced the modularity and complexity of bacterial interaction networks, which was beneficial to maintaining the functional stability of the consortium QY1. Besides, HA decreased the cytotoxicity of functional microbes induced by HOCs-MPs. This work broadens our knowledge of the environmental fate of HOCs-MPs and interactions of MPs, HOCs, DOMs and functional microbial consortiums in aqueous environments.

Discrepancy strategies of sediment abundant and rare microbial communities in response to floating microplastic disturbances: Study using a microcosmic experiment.

Floating microplastics (FMPs) in surface water have been extensively studied, but their influence on sedimentary microbial ecosystems is poorly understood. Here, we investigated response patterns of abundant and rare sedimentary microbes to FMP disturbances by performing microcosmic experiments using fluvial sediment with polyethylene (PE), polylactic acid (PLA), polystyrene (PS) and polyvinyl chloride (PVC) MPs. The results indicated that FMPs altered sediment microbial community diversity and composition. Some organic-degrading, nitrifying and denitrifying bacteria significantly decreased in response to FMP disturbances, which may affect the sediment carbon and nitrogen cycles. Rare taxa persisted under FMP disturbances, whereas abundant taxa were more susceptible to FMP disturbances, suggesting a higher sensitivity of abundant taxa to FMP disturbances. Although stochastic processes governed the assembly of the overall microbial communities, the assembly mechanisms of abundant and rare populations have significantly different responses to FMP interference. The relative contribution of deterministic processes was reinforced by enhanced homogenous selection in abundant populations, while it markedly decreased in rare populations under FMP disturbances. Furthermore, FMPs substantially decreased the network complexity, loosened the coexistence relationships, and increased the negative correlations. Rare species play an important role in reshaping complex microbial interactions and coexistence networks in response to FMP disturbances. This research broadens our perspectives for comprehensively evaluating the ecological effects of FMPs in the aquatic environment to formulate further policy controls.

Synergistic removal of Cr(VI) by S-nZVI and organic acids: The enhanced electron selectivity and pH-dependent promotion mechanisms.

The effects of organic acids on hexavalent chromium (Cr(VI)) removal by reduced iron-based materials have been extensively studied. Nevertheless, the promotion mechanism from the perspective of the electron transfer process is still unclear. Herein, sulfidated nanoscale zero-valent iron (S-nZVI) and the selected organic acids, citric acid (containing both -OH and -COOH groups) and oxalic acid (containing only -COOH groups), showed significant synergistic promotion effects in Cr(VI) removal. The FeS and FeS2 on S-nZVI surface could enhance the Cr(VI) reduction as the reductive entity and electron conductor. Furthermore, even though the reactivity of FeS with Cr(VI) is higher than that with FeS2, the Cr(VI) removal efficiency by FeS2 was much higher than that by FeS with organic acids. Under neutral and alkaline conditions (pH 6.0-8.0), organic acids promoted the diffusion, adsorption and complexation of Cr(VI) on S-nZVI surface, thus enhancing the electron selectivity towards Cr(VI). However, when the solution pH changed to acidic conditions (pH 4.0), organic acids facilitated the dissolution of Fe(II) ions from S-nZVI and enhanced the electron utilization towards Cr(VI) via the fast Fe(III) reduction process. This study provided a new insight into the Cr(VI) removal, which was beneficial to understand the application boundaries of S-nZVI for Cr(VI) remediation.

Environmental contamination and human exposure of polychlorinated biphenyls (PCBs) in China: A review.

Polychlorinated biphenyls (PCBs), together with 11 other organic compounds, were initially listed as persistent organic pollutants (POPs) by the Stockholm Convention because of their potential threat to ecosystems and humans. In China, many monitoring studies have been undertaken to reveal the level of PCBs in environment since 2005 due to the introduced stricter environmental regulations. However, there are still significant gaps in understanding the overall spatial and temporal distributions of PCBs in China. This review systematically discusses the occurrence and distribution of PCBs in environmental matrices, organisms, and humans in China. Results showed that PCB contamination in northern and southern China was not significantly different, but the PCB levels in East China were commonly higher than those in West China, which might have been due to the widespread consumption of PCBs and intensive human activities in East China. Serious PCB contamination was found in e-waste disassembling areas (e.g., Taizhou of Zhejiang Province and Qingyuan and Guiyu of Guangdong Province). Higher PCB concentrations were also chronicled in megalopolises and industrial clusters. The unintentionally produced PCBs (UP-PCBs) formed during industrial thermal processes may play an increasingly significant role in PCB pollution in China. Low PCB levels were recorded in rural and underdeveloped districts, particularly in remote and high-altitude localities such as the Tibetan Plateau and the South China Sea. However, these data are limited. Human exposure to PCBs is closely related to the characteristics of environmental pollution. This review also discusses existing issues and future research prospects on PCBs in China. For instance, the accumulation characteristics and migration regularities of PCBs in food webs should be further studied. More investigations should be undertaken to assess the quantitative relationship between external and internal exposure to PCBs. For example, bioaccessibility and bioavailability studies should be supplemented to evaluate human health risks more accurately.

Understanding optical absorption associated with phytoplanktonic groups in the marginal seas.

Marine phytoplankton absorption plays an important role in oceanic biological productivity and ecological environmental dynamics. Understanding the optical absorption variability associated with phytoplanktonic groups still remains a challenge. In this study, samples (n = 206) were collected for the marginal seas of the northwest Pacific Ocean from six cruise surveys that covered different seasons. Using in situ parameters, including phytoplankton absorption coefficients and concentrations of the phytoplanktonic groups derived from phytoplankton pigments collected with high-performance liquid chromatography (HPLC), we developed a Gaussian model to characterize the specific absorption spectra of eight phytoplanktonic groups, including diatoms, chlorophytes, cryptophytes, cyanobacteria, prymnesiophytes, prasinophytes, dinoflagellates, and chrysophytes, without the package effect. The model was established by accurately identifying for the numbers and locations of the Gaussian peaks and their corresponding half-wave widths. The proposed model produced promising results, and a leave-one-out cross validation generated R2 values exceeding 0.7 for the whole visible light range and above 0.85 (correspondingly MAPE <40%) for the simulated wave bands, excluding the range of 550-650 nm. Meanwhile, a comparison with several spectra observed in the lab showed a high degree of similarity, indicative of the superior performance of our model. Applying the documented specific absorption spectra to the investigated water bodies (whether water surface or profiles) enabled us to quantify the absorption coefficients from different phytoplanktonic groups and characterize their relative contributions to the total. The findings of this study support our understanding of the dynamics of phytoplankton community structure with optical data.

Responses of microbial communities and their interactions to ibuprofen in a bio-electrochemical system.

Ibuprofen has caused great concerns due to their potential environmental risks. However, their removal efficiency and their effects on microbial interactions in bio-electrochemical system remain unclear. To address these issues, a lab-scale bio-electrochemical reactor integrated with sulfur/iron-mediated autotrophic denitrification (BER-S/IAD) system exposing to 1000 µg L-1 ibuprofen was operated for about two months. Results revealed that the BER-S/IAD system obtained efficient simultaneous denitrification (98.93%) and phosphorus (82.67%) removal, as well as an excellent ibuprofen removal performance (96.98%). Ibuprofen had no significant impacts on the nitrate (NO3--N) removal and the ammonia (NH4+-N) accumulation, but decreased the total nitrogen (TN) and total phosphorus (TP) removal efficiencies. MiSeq sequencing analysis revealed that ibuprofen significantly (P < 0.05) decreased the microbial community diversity and changed their overall structure. Some bacteria related to denitrification and phosphorus removal, such as Pseudomonas and Thiobacillus, decreased significantly (P < 0.05). Moreover, molecular ecological network (MEN) analysis revealed that ibuprofen decreased the network's size and complexity, and enhanced the negative correlations of Proteobacteria and Firmicutes. Besides, ibuprofen decreased the links of some keystone bacteria related to denitrification and phosphorus removal. This research could provide a new dimension for our comprehending of the responses of microbial communities and their interactions to ibuprofen in bio-electrochemical system.

Removal of heavy metal ions and polybrominated biphenyl ethers by sulfurized nanoscale zerovalent iron: Compound effects and removal mechanism.

Sulfurized nanoscale zerovalent iron (S-nZVI) has been widely reported to be able to quickly remove heavy metals/persistent organic pollutants, but the limited understanding of the complicated removal process of heavy metals-organic combined pollutants restricts the application of S-nZVI. Here, we demonstrate that there is significant difference in the effectiveness of S-nZVI for removing single pollutant and complex pollutants. The removal kinetic constant (kobs) of heavy metals by S-nZVI followed a sequence of Cr(VI)>Pb(II)>Ni(II)>Cd(II) with or without polybrominated diphenyl ethers (PBDEs). While the capacity of co-existing cations increasing the kobs of PBDEs followed the order: Ni(II)>Pb(II)>Cd(II), and the co-existence of Cr(VI) anion inhibited the reduction of PBDE by S-nZVI because the generated Cr-Fe precipitate hindered the electron transfer. The de-passivation process on S-nZVI surface by Cd(II) ions slightly accelerated the transformation rate of electron. Nevertheless, the co-existing Pb(II) significantly accelerated the transformation of BDE-209 via the galvanic effect from the generated Pb0/Fe0 bimetal. Interestingly, the kobs of BDE-47 in Ni(II)/S-nZVI system was 5.51 times higher than that of Pb(II)/S-nZVI system, implying that an atomic hydrogen mechanism dominated the reduction of BDE-47 by Ni(II)/S-nZVI. In conclusion, the results provided a deep comprehending of removal mechanism of heavy metal-organic complex pollutants by S-nZVI.

Daytime sea fog retrieval based on GOCI data: a case study over the Yellow Sea.

In this paper, a new daytime sea fog detection algorithm has been developed by using Geostationary Ocean Color Imager (GOCI) data. Based on spectral analysis, differences in spectral characteristics were found over different underlying surfaces, which include land, sea, middle/high level clouds, stratus clouds and sea fog. Statistical analysis showed that the Rrc (412 nm) (Rayleigh Corrected Reflectance) of sea fog pixels is approximately 0.1-0.6. Similarly, various band combinations could be used to separate different surfaces. Therefore, three indices (SLDI, MCDI and BSI) were set to discern land/sea, middle/high level clouds and fog/stratus clouds, respectively, from which it was generally easy to extract fog pixels. The remote sensing algorithm was verified using coastal sounding data, which demonstrated that the algorithm had the ability to detect sea fog. The algorithm was then used to monitor an 8-hour sea fog event and the results were consistent with observational data from buoys data deployed near the Sheyang coast (121°E, 34°N). The goal of this study was to establish a daytime sea fog detection algorithm based on GOCI data, which shows promise for detecting fog separately from stratus.