We investigated the presence of microplastics and other anthropogenic litter in the sediments adhered to rocks of an Arctic freshwater lake at Ny-Ålesund (Svalbard Archipelago, 78°N; 11°E). Most of the sampled microparticles were fibers (>90%). The identification of polymer types and additives was performed by combining three spectroscopic techniques, namely Raman Microscopy, Fourier-Transform Infrared microspectroscopy (μFTIR) and Synchrotron Radiation μFTIR (SR-FTIR). SR-FTIR confirmed the presence of poly(ethylene terephthalate) fibers, while RAMAN spectroscopy provided evidence of fibers containing industrial additives. Our results estimated an average concentration of 400 microparticles/m2 of rocks identified as anthropogenic litter, which included an estimation of 90 microplastics/m2 identified as polyester fibers; the rest are mostly natural fibers with evidence of anthropogenic origin. Taken together, the results proved the occurrence of anthropogenic pollutants in remote polar areas. Their probable origin is the long range atmospheric transport. In recent years, lignocellulosic wastes have gathered much attention due to increasing economic, social, environmental apprehensions, global climate change and depleted fossil fuel reserves. The unsuitable management of lignocellulosic materials and related organic wastes poses serious environmental burden and causes pollution. On the other hand, lignocellulosic wastes hold significant economic potential and can be employed as promising catalytic supports because of impressing traits such as surface area, porous structure, and occurrence of many chemical moieties (i.e., carboxyl, amino, thiol, hydroxyl, and phosphate groups). In the current literature, scarce information is available on this important and highly valuable aspect of lignocellulosic wastes as smart carriers for immobilization. Thus, to fulfill this literature gap, herein, an effort has been made to signify the value generation aspects of lignocellulosic wastes. Literature assessment spotlighted that all these waste materials display high potenti effective utilization of lignocellulosic wastes to develop multi-functional biocatalysts is not only economical but also reduce environmental problems of unsuitable management of organic wastes and drive up the application of biocatalytic technology in the industry. The concern about wastewater effluent toxicity has motivated the innovation of enhancement technologies on sulfur-based denitrification biofilter in recent years. Electrolysis is a common technology to reduce or remove toxic pollutants. However, the effect of electrolysis on simultaneous total nitrogen (TN) removal and toxicity reduction in sulfur-based denitrification biofilter has not been reported yet. Herein, for the first time, this study investigated the synergistic effects of electrolysis-induced TN removal and toxicity reduction of secondary effluent of dyeing wastewater containing 20 μg/L of nonylphenol (NP), at different carbon to nitrogen ratios (C/N) in several sulfur-based denitrification biofilters. All of the biofilters achieved the denitrification rate of 300.15 g∙N/m3∙d during the stabilization period at C/N = 5. The CSAHD (ceramisite and sulfur as filters) biofilter had highest TN removal rate to achieve the denitrification rate of 257.46 g∙N/m3·d at C/N = 2. Siderite and dolomite both facilitated TN removal efficiency by 9.3%-12.6% under low C/N ratio and acted as the buffer agent in biofilters. Toxicity characteristic leaching procedure (TCLP) test showed that the amount of leached heavy metals was lower than the concentration limit standard of USEPA. Electrolysis did not promote the removal of TN, however, it could reduce NP concentration and increase the biotoxicity relative inhibition rate of effluent by 12.5%-167%, and affect the functional microbial community structure. Our work clarified some misunderstandings about the application of electrolysis-based strengthening technology and enlightened the future development of simultaneous TN removal and toxicity reduction of dyeing wastewater. V.Diatoms are a compulsory biological quality element in the ecological assessment of rivers according to the Water Framework Directive. The application of current official indices requires the identification of individuals to species or lower rank under a microscope based on the valve morphology. This is a highly time-consuming task, often susceptible of disagreements among analysts. In alternative, the use of DNA metabarcoding combined with High-Throughput Sequencing (HTS) has been proposed.  https://www.selleckchem.com/products/gdc6036.html  The sequences obtained from environmental DNA are clustered into Operational Taxonomic Units (OTUs), which can be assigned to a taxon using reference databases, and from there calculate biotic indices. However, there is still a high percentage of unassigned OTUs to species due to the incompleteness of reference libraries. Alternatively, we tested a new taxonomy-free approach based on diatom community samples to assess rivers. A combination of three machine learning techniques is used to build models that predict diatom OTUs expected in test sites, under reference conditions, from environmental data. The Observed/Expected OTUs ratio indicates the deviation from reference condition and is converted into a quality class. This approach was never used with diatoms neither with OTUs data. To evaluate its efficiency, we built a model based on OTUs lists (HYDGEN) and another based on taxa lists from morphological identification (HYDMORPH), and also calculated a biotic index (IPS). The models were trained and tested with data from 81 sites (44 reference sites) from central Portugal. Both models were considered accurate (linear regression for Observed and Expected richness R2 ≈ 0.7, interception ≈ 0.8) and sensitive to global anthropogenic disturbance (Rs2 > 0.30 p  less then  0.006 for global disturbance). Yet, the HYDGEN model based on molecular data was sensitive to more types of pressures (such as, changes in land use and habitat quality), which gives promising insights to its use for bioassessment of rivers. V.