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Coastal bays serve as undeniable dissolved organic matter (DOM) reactors and the role of prevalent mariculture in DOM cycling deserves investigation. This study, based on four seasonal field samplings and a laboratory incubation experiment, examined the source and seasonal dynamics of DOM and fluorescent dissolved organic matter (FDOM) in the seawater of fish (Larimichthys crocea, LC), seaweed (Gracilaria lemaneiformis, GL) and abalone (Haliotis sp., HA) culturing zones in Sansha Bay, China. Using three-dimensional fluorescence spectroscopy coupled with parallel factor analysis (EEMs-PARAFAC), three fluorescent components were identified, i.e. protein-like C1, protein-like C2, and humic-like C3. Our results showed that mariculture activities dominated the DOM pool by seasonal generating abundant DOM with lower aromaticity and humification degrees. Accounting for 40-95 % of total fluorescent components, C1 (Ex/Em = 300/340 nm) was regarded the same as D1 (Ex/Em = 300/335 nm) identified in a 180-day degradation experiments of G. lemaneiformis detritus, indicating that the cultured seaweed modulated DOM through the seasonal production of C1. In addition, the incubation experiment revealed that 0.7 % of the total carbon content of seaweed detritus could be preserved as recalcitrant dissolved organic carbon (RDOC). However, fish culture appeared to contribute to liable DOC and protein-like C2, exerting a substantial impact on DOM during winter but making a negligible contribution to carbon sequestration, while abalone culture might promote the potential export and sequestration of seaweed-derived carbon to the ocean. Our results highlight the influences of mariculture activities, especially seaweed culture, in shaping DOM pool in coastal bays. These findings can provide reference for future studies on the carbon accounting of mariculture., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jiaping Wu reports financial support was provided by National Key Research and Development Project. Jiaping Wu reports financial support was provided by The Zhejiang Pioneering R&D Project. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Coastal blue carbon ecosystems offer promising benefits for both climate change mitigation and adaptation. While there have been widespread efforts to transplant mangroves from the tropics to the subtropics and to introduce exotic saltmarsh plants like Spartina alterniflora in China, few studies have thoroughly quantified the chronological records of carbon sequestration with different organic carbon (OC) sources. To understand how variations in OC sources can affect the carbon sequestration potential of coastal wetland environment over time, we conducted a study on typical islands with two scenarios: S. alterniflora invasion and mangrove transplantation. Our study determined chronological records of carbon sequestration and storage from five sediment profiles and traced changes in the OC sources using carbon stable isotope (δ 13 C) and C:N ratios in response to these scenarios. The S. alterniflora invasion resulted in an 84 ± 19 % increase in the OC burial rate compared to unvegetated mudflats, while mangrove transplantation resulted in a 167 ± 74 % increase in the OC burial rate compared to unvegetated mudflats. S. alterniflora and mangroves showed greater carbon sequestration potential in areas with high supplies of suspended particulate matter, while mangroves needed to grow to a certain scale to display obvious carbon sequestration benefits. In the mangrove saltmarsh ecotone, mature mangrove habitats exhibited resistance to the S. alterniflora invasion, while mangrove transplantation in the environment invaded by S. alterniflora had a significant effect on OC contribution. Besides, plant-derived OC can be exported to the surrounding environment due to the rapid turnover of sediments. The blue carbon chronosequence-based estimation of OC sources and burial rates provides a useful reference for establishing carbon accounting policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Sediments are considered to be important sinks of microplastics, but the enrichment process of microplastics by blue carbon ecosystems is poorly studied. This study analyzed the spatial distribution and temporal changes, assessed the polymer types and morphological characteristics of microplastics in sediments of five ecosystems, i.e. forests, paddy fields, mangroves, saltmarshes and bare beaches on Ximen Island, Yueqing Bay, China. The trapping effect of blue carbon (mangrove and saltmarsh) sediments on microplastic was further explored. Temporal trends in microplastic abundance showed a significant increase over the last 20 years, with the enrichment of microplastics in mangrove and saltmarsh sediments being 1.7 times as high as that in bare beach, exhibiting blue carbon vegetations have strong enrichment effect on microplastics. The dominant color, shape, size, and polymer type of microplastics in sediments were transparent, fibers and fragments, <1 mm, and polyethylene, respectively. Significant differences in the abundance and characteristics of microplastics between intertidal sediments and terrestrial soils reveal that runoff input is the main source of microplastics. This study provided the evidence of blue carbon habitats as traps of microplastics., (Copyright © 2022. Published by Elsevier Ltd.)

Sediments of blue carbon vegetation are becoming a sink of natural and anthropogenic pollutants, such as polycyclic aromatic hydrocarbons (PAHs). However, the extent to which PAHs are accumulated and varied in blue carbon sediments, and the impact of blue carbon vegetation on the accumulation and retention capacity of PAHs, have been poorly explored. This study examines the sedimentary records of PAHs in profiles from mangrove plantation, saltmarsh, and mudflat in Ximen Island and Maoyan Island of Yueqing Bay, China. The existence of blue carbon vegetation provides a sheltered environment for the accelerated burial of sediment and OC. Decadal PAH sedimentation records show staged changes characterized by the emission of PAHs and colonization of blue carbon vegetation, reflecting the accelerated burial of PAHs in sediments by blue carbon vegetation colonization. In addition, the colonization of blue carbon vegetation contributes to the shift of PAH compositions in sediments. This study provides new insights into the underestimated PAH accumulation potential and retention capacity of blue carbon vegetation and the corresponding underlying sediments, supporting the environmental benefits of blue carbon vegetation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

This study compared the ability of Sargassum fusiforme to accumulate As, Cd, Cr, Cu, Ni, Pb and Zn in its five tissues (main branch, lateral branch, leaf, receptacles and pneumathode). The concentrations of these trace elements in seawater, surface sediments and different tissues of S. fusiforme were analyzed in different areas in Dongtong County (Wenzhou City, China). The presence of receptacle at all sites indicated that S. fusiforme had entered the mature stage. However, the proportion of each tissue in S. fusiforme in different sites was varied, indicating subtle differences in growth. S. fusiforme has a great capacity to accumulate trace elements, showing relatively high levels of As (28.2-64.2 mg kg -1 ) and Zn (19.9-80.8 mg kg -1 ). The elements are mainly stored in leaf, receptacles and pneumathode. Compared to element concentrations in the surrounding environment, the seaweed exhibited stronger bioconcentration capacity for As and Cd than for other elements. According to our health risk assessment results, the hazard index and carcinogenic risk were below the limit, suggesting that the S. fusiforme ingestion would not pose any health risk and the potential risk of intake branches was even lower than that of other tissues., (Copyright © 2021. Published by Elsevier Ltd.)

Improving the spatiotemporal coverage of remote sensing (RS) products, such as sea surface chlorophyll concentration (SSCC), can offer a better understanding of the spatiotemporal SSCC distribution for ocean management purposes. In the first part of this work, 834 in-situ SSCC measurements of the SeaBASS-NASA (National Aeronautics and Space Administration) during 2002-2016 served as the empirical dataset. A moving window with ±3 days and ±0.5° centered at each of the in-situ SSCC measurements established a search neighborhood for Moderate Resolution Imaging Spectroradiometer Level 2 (MODIS L2) SSCC and MODIS L2 sea surface temperature (SST) data, and the matched SSCC and SST data were used for building a linear SSCC-SST relationship. The unmatched SST was introduced to the linear model for generating soft SSCC data with uniform distributions. The inherent spatiotemporal dependency of the SSCC distribution was then represented by the Bayesian maximum entropy (BME) method, which incorporated the soft SSCC data as auxiliary variable for SSCC estimation and mapping purposes. The results showed that a 75.3% accuracy improvement of remote SSCC retrieval in terms of R 2 can be achieved by BME-based method compared to the original MODIS L2 product. Subsequently, the BME-based method was applied to obtain daily SSCC dataset in Chesapeake Bay (USA) during the period 2010-2019. It was found that the SSCC distribution exhibited a decreasing spatial trend from the upper bay to the outer bay, whereas decreasing and increasing temporal trends were detected during the periods 2011-2014 and 2016-2019, respectively. The generalized Cauchy process was used to quantitatively describe the autocorrelation SSCC function in the Chesapeake Bay. The results showed that the outer bay exhibited the strongest long-range dependence among the four sub-regions, whereas the middle bay exhibited the weakest long-range dependence. Finally, one-point and two-point stochastic site indicators (SSIs) were employed to explore the spatiotemporal SSCC characteristics in Chesapeake Bay. The one-point SSI results showed that nearly 100% of the upper, middle and the lower bay areas experienced a high SSCC level (>5 mg/m 3 ) during the entire study period. The area with SSCC >5 mg/m 3 in the outer bay increased a lot during the winter season, but the area with SSCC >10 or 20 mg/m 3 decreased significantly in the upper, middle and lower bay. Simultaneously, the SSCC dispersion in these areas was rather small during the winter season. On the other hand, the two-point SSI results showed that although the SSCC levels differ among the four sub-regions, but the SSCC connectivity structures between pairs of points also displayed some similarities in terms of their spatiotemporal dependency. In conclusion, the proposed BME-based method was shown to be a promising remote SSCC mapping technique that exhibited a powerful ability to improve both accuracy and coverage of RS products. The SSIs can be also used to explore the spatiotemporal characteristics of a variety of natural attributes in waters., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The COVID-19 has become a pandemic. The timing and nature of the COVID-19 pandemic response and control varied among the regions and from one country to the other, and their role in affecting the spread of the disease has been debated. The focus of this work is on the early phase of the disease when control measures can be most effective. We proposed a modified susceptible-exposed-infected-removed model (SEIR) model based on temporal moving windows to quantify COVID-19 transmission patterns and compare the temporal progress of disease spread in six representative regions worldwide: three Chinese regions (Zhejiang, Guangdong and Xinjiang) vs. three countries (South Korea, Italy and Iran). It was found that in the early phase of COVID-19 spread the disease follows a certain empirical law that is common in all regions considered. Simulations of the imposition of strong social distancing measures were used to evaluate the impact that these measures might have had on the duration and severity of COVID-19 outbreaks in the three countries. Measure-dependent transmission rates followed a modified normal distribution (empirical law) in the three Chinese regions. These rates responded quickly to the launch of the 1 st -level Response to Major Public Health Emergency in each region, peaking after 1-2 days, reaching their inflection points after 10-19 days, and dropping to zero after 11-18 days since the 1 st -level response was launched. By March 29 th , the mortality rates were 0.08% (Zhejiang), 0.54% (Guangdong) and 3.95% (Xinjiang). Subsequent modeling simulations were based on the working assumption that similar infection transmission control measures were taken in South Korea as in Zhejiang on February 25 th , in Italy as in Guangdong on February 25 th , and in Iran as in Xinjiang on March 8 th . The results showed that by June 15 th the accumulated infection cases could have been reduced by 32.49% (South Korea), 98.16% (Italy) and 85.73% (Iran). The surface air temperature showed stronger association with transmission rate of COVID-19 than surface relative humidity. On the basis of these findings, disease control measures were shown to be particularly effective in flattening and shrinking the COVID-10 case curve, which could effectively reduce the severity of the disease and mitigate medical burden. The proposed empirical law and the SEIR-temporal moving window model can also be used to study infectious disease outbreaks worldwide., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Soil heavy metal pollution can be a serious threat to human health and the environment. The accurate mapping of the spatial distribution of soil heavy metal pollutant concentrations enables the detection of high pollution areas and facilitates pollution source apportionment and control. To make full use of auxiliary soil properties information and show that they can improve mapping, a synthesis of the Bayesian Maximum Entropy (BME) theory and the Geographically Weighted Regression (GWR) model is proposed and implemented in the study of the Shanghai City soils (China). The results showed that, compared to traditional techniques, the proposed BME-GWR synthesis has certain important advantages: (a) it integrates heavy metal measurements and auxiliary information on a sound theoretical basis, and (b) it performs better in terms of both prediction accuracy and implementation flexibility (including the assimilation of multiple data sources). Based on the heavy metal concentration maps generated by BME-GWR, we found that the As, Cr and Pb concentration levels are high in the eastern part of Shanghai, whereas high Cd concentration levels were observed in the northwestern part of the city. Organic carbon and pH were significantly correlated with most of the heavy metals in Shanghai soils. We concluded that Cd pollution is mainly the result of agricultural activities, and that the Cr pollution is attributed to natural sources, whereas Pb and As have compound pollution sources. Future studies should investigate the implementation of BME-GWR in the case of space-time heavy metal mapping and its ability to integrate human activity information and soil category variables., (Copyright © 2019 Elsevier B.V. All rights reserved.)

This work is the first systematic quantitative analysis of the heavy metal situation along the Zhejiang coastal region focusing on the integrative assessment of the concentrations of seven heavy metals (Cu, Cd, Hg, Zn, Pb, Cr, and As) in surface sediments during the 2012-2015 period. Different heavy metal contamination indices were used for surface sediment quality assessment purposes. The numerical results revealed a noticeable spatial fluctuation of the degree of contamination throughout the region during the four years considered. Higher contamination levels and ecological risks were detected in the southern part of the Zhejiang coastal region. It was found that the Cu, Cd and Hg were the predominant contaminants along the Zhejiang coast with mean regional concentrations varying between 29.1 and 34.2, 0.12-0.17, and 0.044-0.052 mg/kg, respectively. The Cr and Pb exhibited lower contamination levels than the other metals during each one of the years 2012-2015. Stochastic site indicators of heavy metal contamination were used to assess regional uncertainties and obtain useful physical interpretations of the state of contamination of the Zhejiang coast. These indicators can be expressed explicitly in terms of probabilities of heavy metal contamination (either at a global scale or spatially distributed over the coastal region), and therefore they can be considered as risk indicators. It was found that the fraction of the coastal region where excess contamination occurred could never exceed the ratio of the mean heavy metal contamination over the selected threshold. In half of the coast study region, the degree of heavy metal contamination was higher than the median spatial contamination values during the month of August of the years 2012-2015. The spatial means of excess contamination and excess differential contamination increased as the relative area of over-contamination increased. Within the substantially contaminated sub-region of the Zhejiang coast, stronger contamination correlations were observed between locations separated by shorter distances. These correlations were higher when smaller thresholds were considered. As regards the spatial connectivity of the corresponding contamination risks, it was found that 44%, 31%, 39% and 63% of the location pairs in the Zhejiang coast simultaneously experienced moderate risks during the years 2012, 2013, 2014 and 2015, respectively. The ratio of the probability of excess contamination at both locations separated by distances < 20 km over the probability of excess contamination at either one of these two locations was high even for large thresholds, indicating that locations with high contamination are concentrated rather than being dispersed along the Zhejiang coast. Lastly, another interesting finding is that the characterization of the Zhejiang coastal region as over-contaminated is very sensitive to the DC threshold considered, that is, a small increase in the threshold selected can reduce significantly the probability that region is characterized as over-contaminated., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: The thyroid cancer (TC) incidence in China has increased dramatically during the last three decades. Typical in this respect is the case of Hangzhou city (China), where 7147 new TC cases were diagnosed during the period 2008-2012. Hence, the assessment of the TC incidence risk increase due to environmental exposure is an important public health matter., Methods: Correlation analysis, Analysis of Variance (ANOVA) and Poisson regression were first used to evaluate the statistical association between TC and key risk factors (industrial density and socioeconomic status). Then, the Bayesian maximum entropy (BME) theory and the integrative disease predictability (IDP) criterion were combined to quantitatively assess both the overall and the spatially distributed strength of the "exposure-disease" association., Results: Overall, higher socioeconomic status was positively correlated with higher TC risk (Pearson correlation coefficient=0.687, P<0.01). Compared to people of low socioeconomic status, people of median and high socioeconomic status showed higher TC risk: the Relative Risk (RR) and associated 95% confidence interval (CI) were found to be, respectively, RR=2.29 with 95% CI=1.99 to 2.63, and RR=3.67 with 95% CI=3.22 to 4.19. The "industrial density-TC incidence" correlation, however, was non-significant. Spatially, the "socioeconomic status-TC" association measured by the corresponding IDP coefficient was significant throughout the study area: the mean IDP value was -0.12 and the spatial IDP values were consistently negative at the township level. It was found that stronger associations were distributed among residents mainly on a stripe of land from northeast to southwest (consisting mainly of sub-district areas). The "industrial density-TC" association measured by its IDP coefficient was spatially non-consistent., Conclusions: Socioeconomic status is an important indicator of TC risk factor in Hangzhou (China) whose effect varies across space. Hence, socioeconomic status shows the highest TC risk effect in sub-district areas., (Copyright © 2017. Published by Elsevier B.V.)

Recent studies have demonstrated the persistence of antibiotics in soil, especially in areas of vegetable cultivation. However, there are very few studies of the influence of planting regimes on the levels of antibiotic pollution. This work introduces geographical-detector models to investigate the relationship between planting patterns (vegetable planting model, manure type and quantity, planting age, greenhouse area, and topographic elevation) and residual fluoroquinolones (FQs) in soil in a pilot project in Shouguang County, Shandong Province (the largest vegetable-producing area in China). The results led to the following findings. 1. The vegetable planting model is the major determinant of the spatial stratification of FQ in the soil. For example, the "cucumber-cucumber" model (growing cucumbers after cucumbers) has a three-fold power of determinant compared to the "pepper-melon" model (growing melons after peppers). 2. Planting age (years with continuous vegetable cultivation) does not necessarily affect the spatial distribution of FQ owing to their relatively short degradation period. 3. Interactions between risk factors were more significant than the individual factors for FQ pollution. In particular, the interaction between the vegetable planting model and amount of manure resulted in the highest pollution level. The findings of the present study make it possible to introduce effective and practical measures to alleviate pollution of soils by FQ in the study area. Adjustment of the vegetable cultivation models and application of chicken manure (less than 6 kg/m(2) manure annually with a more dry than fresh manure) could be an effective and flexible approach to alleviate FQ pollution., (Copyright © 2013 Elsevier B.V. All rights reserved.)