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Sea surface salinity (SSS) retrieval from satellite-based microwave radiometer is hampered by uncertainties due to atmospheric and surface scattering contributions. This study presents a comprehensive vector radiative transfer model (VRTM) for estimation of brightness temperature (TB) (for SSS retrieval) from L-band radiometry based on a matrix-operator method. It includes an efficient two-scale model (TSM) that combines a geometrical optics (GO) model and a small-perturbation model (SPM) for computing both the small- and large-scale scattering components of the sea surface. Moreover, it considers the influence of rain effects on TB by including the radiation extinction term (scattering and attenuation). The simulation results using the VRTM were validated with those obtained from the RT4 model for flat sea surface conditions and the RTTOV model for rough sea surface conditions. The relative difference in the estimated TB among the models was small (<1%) for low wind speeds (<1 m/s) and increased up to 3% for high wind speeds and observation angles. Simulations on the influence of wind speed on TB with various parameterizations were further examined. Compared with SMOS-MIRAS and Aquarius measurements, the VRTM simulations agreed well with satellite measurements for both vertically and horizontally polarized TBs with biases of less than 2.2 K for observation angles from 20° to 65°. The binned TBs showed even better results, with a standard deviation of less than 1.45 K and an absolute mean error of less than 1.2 K. [ABSTRACT FROM AUTHOR]

• Statistical model was used to study effects of hemi structures on material property. • High Xylan/Arabinan ratio is favorable to the material property of hemicelluloses. • High Mw and low lignin is favorable to the material property of hemicelluloses. Using originally isolated xylan-type hemicelluloses for material application suffers from poor mechanical properties including low tensile strength and brittleness. The subsequent chemical modifications of hemicelluloses are facing the problems of high costs and toxic chemicals. Consequently, this study tried to investigate the factors affecting the film-forming properties of the originally isolated xylan-hemicelluloses and promoting their material properties from the extraction step. Two different extraction methods, a one-step alkali or alkaline peroxide solution method and a two-step alkali extraction-delignification method were used to extract the hemicellulose with different chemical structures from sugarcane bagasse. For the two-step alkali extraction-delignification method, hemicelluloses were first extracted by alkali solution and then delignified by dioxane/water, hydrogen peroxide solution or sodium hypochlorite solution. The lignin contents of all the extracted hemicelluloses ranged from 1.6%–9.5%, of which the lowest value was obtained through delignification by sodium hypochlorite. The number average molecular weight ranged from 8200 to 26800, while the xylan/arabinan ratio ranged from 5.0 to 9.1. The hemicelluloses were characterized and processed into films. Tensile strength of films could be considerably improved up to ˜52% when using sodium hypochlorite solution as the delignification agents and the lignin content was greatly reduced for the hemicellulose fraction. Statistical models were generated between film mechanical properties and hemicellulose structural characteristics. The models predicted that hemicellulose with higher molecular weight, more linear structure and lower lignin content would result in better mechanical properties. [ABSTRACT FROM AUTHOR]

Bacterial cellulose (BC) is a green biopolymer suitable for heavy metal ion removal from aqueous solution due to its nano-porous microstructure. Polyethyleneimine-bacterial cellulose (PEI-BC) was prepared by reductive amination of dialdehyde BC with polyethyleneimine. The capacity of PEI-BC in Cu(II) and Pb(II) adsorption from aqueous solution was investigated. The adsorption kinetics could be well expressed by pseudo-second-order model and the adsorption isotherm data were well fitted with Freundlich model. Adsorption processes of Cu(II) and Pb(II) by PEI-BC reached equilibrium very rapid in 30 and 60 min, respectively. The maximum adsorption capacity of PEI-BC on Cu(II) and Pb(II) was found to be 148 and 141 mg/g, respectively, which was higher than that of unmodified BC and other modified BC reported. PEI-BC also showed good reusability in the adsorption of Cu(II) and Pb(II). This study demonstrates that polyethyleneimine modification makes BC a potential bioadsorbent for heavy metal ion removal in waste water. [ABSTRACT FROM AUTHOR]

Accurate prediction of sea surface emission is the key for sea surface salinity retrieval from satellite microwave radiometer. In order to retrieve salinity from satellite observation, several sea surface microwave emission models have been developed based on theoretical or empirical methods and validated by in-situ measurements in different regions. However, their performances are still unclear in the Chinese coastal waters. In this study, based on two cruises measurements in the East China Sea (ECS), including the brightness temperature measured by a shipborne microwave radiometer and other auxiliary data (sea surface salinity, sea surface temperature and wind speed), the performances of different sea surface emission models are tested. The results showed that the developed models provide fairly good accuracy in predicting brightness temperature; for example, the accuracy of small perturbance/small scale approximation model (SPM/SSA), two-scale model (TSM) and empirical model is in the range from 0.6 K to 3 K. Moreover, the TSM and empirical models are further improved by optimizing the model parameters in the ECS. Finally, the sea surface salinity were retrieved from shipborne measured data based on the improved models, and the results show that the root mean square (rms) differences between retrieved and in-situ sea surface salinity is about 0.4 psu, indicating the significant improvement by the regional model parameters. [ABSTRACT FROM AUTHOR]

Super adsorbents exhibit great potential to remove pollutants from media or store considerable amounts of water, which may undermine the pressure triggered by environmental pollution and shortage of water resources. Super adsorbents made from biopolymers have been an attractive topic because of biodegradability, renewability and outstanding adsorption capacity. Hemicelluloses are a type of biopolymers very abundant in agricultural, forestry and pulping industrial wastes. Hemicellulose-based bio-adsorbents are thriving because the inherent chemical structures and physical properties of hemicelluloses make themselves easy to be processed into matrix materials applicable in super adsorbents. This review summarizes recent studies in hemicellulose-based bio-adsorbents, i.e. hydrogels and activated carbons, from the perspectives of types, applications, fabrication methods, the elements affecting the adsorption performance and the kinetics of adsorption process, which thus helps to further improve the properties of hemicellulose-based bio-adsorbents and to promote the industrial production and utilization of hemicelluloses and hemicellulose-based bio-adsorbents. [ABSTRACT FROM AUTHOR]

As one of the most abundant natural polymers in nature, polysaccharides have the potential to replace petroleum-based polymers that are difficult to degrade in paper coatings. Polysaccharide molecules have a large number of hydroxyl groups that can bind strongly with paper fibers through hydrogen bonds. Chemical modification can also effectively improve the mechanical, barrier, and hydrophobic properties of polysaccharide-based coating layers and thus can further improve the related properties of coated paper. Polysaccharides can also give paper additional functional properties by dispersing and adhering functional fillers, e.g., conductive particles, catalytic particles or antimicrobial chemicals, onto paper surface. Based on these, this paper reviews the application of natural polysaccharides, such as cellulose, hemicellulose, starch, chitosan, and sodium alginate, and their derivatives in paper coatings. This paper analyzes the improvements and influences of chemical structures and properties of polysaccharides on the mechanical, barrier, and hydrophobic properties of coated paper. This paper also summarizes the researches where polysaccharides are used as the adhesives to adhere inorganic or functional fillers onto paper surface to endow paper with great surface properties or special functions such as conductivity, catalytic, antibiotic, and fluorescence. [ABSTRACT FROM AUTHOR]

Ying, J.Y.; Liang, K.W.; Wu, Q.S.; Xie, M.; Jin, X.C.; Ye, Q., and Yang, Z.L., 2020. Calculation of suspended sediment concentration based on deep learning and OBS turbidity. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 627-630. Coconut Creek (Florida), ISSN 0749-0208. Based on BP and Elman deep learning models with water depth, velocity, flow direction and salinity as input term and suspended sediment concentration as output term were constructed, and the calculated results were compared with the measured suspended sediment concentration and the suspended sediment concentration calculated by OBS turbidity. The results show that the suspended sediment concentration calculated by deep learning model can meet the needs of sediment dynamics research, but the calculation effect is not so good in high water stand, low water stand, fastest flood and fastest ebb periods, and the accuracy is far less than that of OSB calculation results. In the future, deep learning models can be improved in computational accuracy by adding input terms, and experimentally adjusting thresholds and connection weights. [ABSTRACT FROM AUTHOR]

Ying, J.Y.; Liang, K.W.; Wu, Q.S.; Xie, M.; Jin, X.C.; Ye, Q., and Yang, Z.L., 2020. Calculation of suspended sediment concentration based on deep learning and OBS turbidity. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 627-630. Coconut Creek (Florida), ISSN 0749-0208. Based on BP and Elman deep learning models with water depth, velocity, flow direction and salinity as input term and suspended sediment concentration as output term were constructed, and the calculated results were compared with the measured suspended sediment concentration and the suspended sediment concentration calculated by OBS turbidity. The results show that the suspended sediment concentration calculated by deep learning model can meet the needs of sediment dynamics research, but the calculation effect is not so good in high water stand, low water stand, fastest flood and fastest ebb periods, and the accuracy is far less than that of OSB calculation results. In the future, deep learning models can be improved in computational accuracy by adding input terms, and experimentally adjusting thresholds and connection weights. [ABSTRACT FROM AUTHOR]