Search Results (131)

Arctic shelf waters exhibit high optical variability due to terrestrial inputs and elevated colored dissolved organic matter (CDOM) concentrations, posing significant challenges for the accurate retrieval of chlorophyll-a (Chl-a) and downwelling diffuse attenuation coefficients (${{\rm K}}_{\mathrm{d}}\left(\lambda \right)$). These retrieval biases contribute to substantial uncertainties in estimates of primary productivity and upper-ocean heat flux in the Arctic Ocean. However, the performance and constraints of existing ocean color algorithms in Arctic shelf environments remain insufficiently characterized, particularly under seasonally variable and optically complex conditions. In this study, we present a systematic multi-year evaluation of commonly used empirical and semi-analytical ocean color algorithms across the western Arctic shelf, based on seven expeditions and 240 in situ observation stations. Building on these evaluations, regionally optimized retrieval schemes were developed to enhance algorithm performance under Arctic-specific bio-optical conditions. The proposed OCx-AS series for Chl-a and ${{\rm K}}_{\mathrm{d}}$-DAS models for ${{\rm K}}_{\mathrm{d}}\left(\lambda \right)$ significantly reduce retrieval errors, achieving RMSE improvements of over 50% relative to global standard algorithms. Additionally, we introduce QAA-LS, a modified semi-analytical model specifically adapted for the Laptev Sea, which addresses the strong absorption effects of CDOM and corrects the significant overestimation observed in previous QAA versions. Full article

Chiral molecules are integral to various biological and artificial systems, influencing processes from chemical production to optical activities. In this study, we explore the potential of chiral vinyl[2.2]paracyclophane (vinyl-PCP) as a monomer for the synthesis of homopolymers and copolymers with styrene. We achieved polymerization through anionic, cationic, and radical methods. The resulting polymers demonstrated significant chiral properties, even in copolymers with small fractions of the chiral monomer. Further, we developed a polymerizable vinyl emitter from 10-(4-(4,6-diphenyl-1,3,5-triazin-2-yl)phenyl)-9,9-dimethyl-9,10-dihydroacridine (DMAC-TRZ) through a two-step synthesis with an overall yield of 48%. Copolymerization with chiral vinyl-PCP resulted in emissive polymers that demonstrated circularly polarized luminescence (CPL) properties. The inclusion of the chiral PCP monomer, acting both as a host material and the source of chirality for CPL, enhanced the photoluminescence quantum yield (PLQY) to 47.2% in N₂ at 5–10% emitter content, compared to 26.8% for the pure emitter polymer. CPL-active polymers show clear mirror-image Cotton effects at 240 nm and 267 nm and dissymmetry factors around +2 × 10⁻⁴ and −1 × 10⁻⁴. This self-hosting effect of PCP monomers underscores the potential of chiral vinyl-PCP for advanced functional materials in optical communication and bio-responsive imaging. Full article

Wood cellulose is an abundant bio-based resource with diverse applications in construction, cosmetics, packaging, and the pulp and paper industries. Transparent wood (TW) is a novel, high-quality wood material with several advantages over traditional transparent materials (e.g., glass and plastic). These benefits include renewability, UV shielding, lightweight properties, low thermal expansion, reduced glare, and improved mechanical strength. TW has significant potential for various applications, including transparent roofs, windows, home lighting structures, electronic devices, home decoration, solar cells, packaging, smart packaging materials, and other high-value-added products. The mechanical properties of TW, such as tensile strength and optical transmittance, are typically up to 500 MPa (Young’s modulus of 50 GPa) and 10–90%, respectively. Fabrication methods, wood types, and processing conditions significantly influence the mechanical and optical properties of TW. In addition, recent research has highlighted the feasibility of TW and large-scale production, making it an emerging research topic for future exploration. This review attempted to provide recent and updated manufacturing methods of TW as well as current and future applications. In particular, the effects of structural modification through various chemical pretreatment methods and impregnation methods using various polymers on the properties of TW biocomposites were also reviewed. Full article

This study investigates the potential of Chirich (Asphodelus aestivus) tuber, one of Turkey’s natural resources, for sustainable bio-hybrid film production. Bio-hybrid films developed from Chirich tuber starch in composite form with polyvinyl alcohol (PVOH) were thoroughly examined for their physical, mechanical, and barrier properties. During the production process, twin-screw extrusion and hydraulic hot pressing methods were employed; the films’ optical, chemical, and barrier performances were analyzed through FT-IR spectroscopy, water vapor permeability, solubility, and mechanical tests. To evaluate the films’ durability against environmental factors and model their properties, advanced computational model algorithms such as Gradient Boosting Regression (GBR), Random Forest Regression (RFR), and AdaBoost Regression (ABR) were utilized. The results showed that the GBR algorithm achieved the highest accuracy with 99.92% R² and presented the most robust model in terms of sensitivity to environmental factors. The results indicate that Chirich tuber-based bio-hybrid films exhibit significantly enhanced mechanical strength and barrier performance compared to conventional corn starch-based biodegradable polymers. These superior properties make them particularly suitable for industrial applications such as food packaging and medical materials, where durability, moisture resistance, and gas barrier characteristics are critical. Moreover, their biodegradability and potential for integration into circular economy frameworks underscore their environmental sustainability, offering a viable alternative to petroleum-derived plastics. The incorporation of ML-driven optimization not only facilitates precise property prediction but also enhances the scalability of bio-hybrid film production. By introducing an innovative, data-driven approach to sustainable material design, this study contributes to the advancement of bio-based polymers in industrial applications, supporting global efforts to mitigate plastic waste and promote environmentally responsible manufacturing practices. Full article

Plastic pollution, particularly from microplastics (MPs) and nanoplastics (NPs), has become a critical environmental and health concern due to their widespread distribution, persistence, and potential toxicity. MPs and NPs originate from primary sources, such as cosmetic microspheres or synthetic fibers, and secondary fragmentation of larger plastics through environmental degradation. These particles, typically less than 5 mm, are found globally, from deep seabeds to human tissues, and are known to adsorb and release harmful pollutants, exacerbating ecological and health risks. Effective detection and quantification of MPs and NPs are essential for understanding and mitigating their impacts. Current analytical methods include physical and chemical techniques. Physical methods, such as optical and electron microscopy, provide morphological details but often lack specificity and are time-intensive. Chemical analyses, such as Fourier transform infrared (FTIR) and Raman spectroscopy, offer molecular specificity but face challenges with smaller particle sizes and complex matrices. Thermal analytical methods, including pyrolysis gas chromatography–mass spectrometry (Py-GC-MS), provide compositional insights but are destructive and limited in morphological analysis. Emerging (bio)sensing technologies show promise in addressing these challenges. Electrochemical biosensors offer cost-effective, portable, and sensitive platforms, leveraging principles such as voltammetry and impedance to detect MPs and their adsorbed pollutants. Plasmonic techniques, including surface plasmon resonance (SPR) and surface-enhanced Raman spectroscopy (SERS), provide high sensitivity and specificity through nanostructure-enhanced detection. Fluorescent biosensors utilizing microbial or enzymatic elements enable the real-time monitoring of plastic degradation products, such as terephthalic acid from polyethylene terephthalate (PET). Advancements in these innovative approaches pave the way for more accurate, scalable, and environmentally compatible detection solutions, contributing to improved monitoring and remediation strategies. This review highlights the potential of biosensors as advanced analytical methods, including a section on prospects that address the challenges that could lead to significant advancements in environmental monitoring, highlighting the necessity of testing the new sensing developments under real conditions (composition/matrix of the samples), which are often overlooked, as well as the study of peptides as a novel recognition element in microplastic sensing. Full article

Flammability and smoke generation of glass-fiber-reinforced polyester laminates (GFRPs) modified with L-arginine phosphate (ArgPA) have been investigated. The composition, structure, and thermal degradation processes of ArgPA were assessed by the elemental, FTIR, and thermogravimetric analyses. Flammability and smoke emission of GFRPs varying by different amounts (5–15 wt.%) of bio-based flame retardant (FR) prepared via hand lay-up method were assessed in terms of the limiting oxygen index (LOI) and smoke density tests. It was observed that the addition of ArgPA results in the formation of a charred layer with visible bubbles. The LOI of GFRP with 15 wt.% of ArgPA increased from 20.73 V/V % (non-modified GFRP) to 24.55 V/V %, and the material classification was improved from combustible to self-extinguishing. FRs usually increase the specific optical density of smoke, which was also observed for ArgPA-modified GFRPs. However, the specific optical density of smoke at the 4th minute of measurement (D_s(4)) obtained for ArgPA-modified GFRPs was lower than for GFRPs modified with commercially used APP. TG/FTIR studies of resin modified with ArgPA revealed the presence of phosphorus compounds and non-combustible gases in the decomposition products. Results demonstrate the potential of ArgPA as an effective, bio-based FR for the enhancement of GFRP fire safety. Full article

Bio-nanomaterials are gaining increasing attention due to their renewable and eco-friendly characteristics. Among these, nanocrystalline cellulose (NCC) stands out as one of the most advanced materials for applications in food, healthcare, composite production, and beyond. In this study, NCC was successfully extracted from cotton-based textile waste using a combination of chemical and mechanical methods. The cellulose fibers were first hydrolyzed using a dilute HCl solution, neutralized, and then dried, resulting in microcrystalline cellulose (MCC) with diameters ranging from 7 to 15 µm and lengths up to 300 µm (as observed via optical microscopy and scanning electron microscopy, SEM). To achieve nanoscale dimensions, NaOH/urea solution with mechanical treatment was applied, resulting in the successful extraction of NCC in the supernatant, particularly under room-temperature conditions. Dynamic light scattering (DLS) analysis confirmed the presence of nanostructures (average sizes ranging from 120 nm to 750 nm), and atomic force microscopy (AFM) analysis verified the nanoscale range (diameters between 2 and 4 nm and lengths from 200 nm to 1 µm). Fourier transform infrared (FTIR) spectroscopy revealed the conversion of cellulose I to cellulose II, confirming the successful transformation into NCC. For the first time, NCC was obtained from undyed cotton textile wastes using NaOH/urea treatment after HCl hydrolysis, eliminating the need for pre-treatment and intermediate steps. Full article

Biomass valorization and bio-based material development are of major research interest following the spirit of the circular economy. Aloe vera cultivation is a widespread agricultural activity oriented toward supplement production because of its well-known antioxidant and antimicrobial properties. Aloe vera juice production also produces a large amount of biomass byproducts that are usually landfilled. On the other hand, cellulose nanocrystals are widely used in several applications, such as biomaterials, bio-compatible polymers, nanocomposites, food packaging, medicines, cosmetics, and sensors, due to their unique physical, mechanical, optical, electrical, and healing properties as well as their compatibility with biological tissues. This study introduces a novel approach combining the microwave-assisted extraction (MAE) of cellulose from this residue with the subsequent isolation of cellulose nanocrystals (CNCs). The MAE process, which exhibits a rapid heating and penetrating ability, was optimized to maximize the cellulose yield under various conditions (microwave power, solvent ratio, and time). Analysis using FTIR, XRD, SEM, and DMA indicated that isolated pure cellulose nanocrystals and a stable PVA–CNC porous hydrogel network were produced. The PVA–CNC hydrogel was synthesized to enable the formation of a semi-crystalline network that imparts the material with enhanced mechanical properties. Both final products of this study could potentially be used for various applications. Full article

High-resolution water quality maps derived from imaging spectroscopy provide valuable insights for environmental monitoring and management, but the processing of all pixels of large datasets is extremely computationally intensive and limits the speed of map production. We demonstrate a superpixel approach to accelerating water quality parameter inversion on such data to considerably reduce time and resource needs. Neighboring pixels were clustered into spectrally similar superpixels, and bio-optical inversions were performed at the superpixel level before a nearest-neighbor interpolation of the results back to pixel resolution. We tested the approach on five example airborne imaging spectroscopy datasets from Hawaiian coastal waters, comparing outputs to pixel-by-pixel inversions for three water quality parameters: suspended particulate matter, chlorophyll-a, and colored dissolved organic matter. We found significant reduction in computational time, ranging from 38 to 2625 times faster processing for superpixel sizes of 50 to 5000 pixels (200 to 20,000 m²). Using 1000 paired output values from each example image, we found minimal reduction in accuracy (as decrease in R² or increase in RMSE) of the model results when the superpixel size was less than 750 2 m × 2 m resolution pixels. Such results mean that this methodology could reduce the time needed to produce regional- or global-scale maps and thereby allow environmental managers and other stakeholders to more rapidly understand and respond to changing water quality conditions. Full article

The vertical distribution of the marine total suspended matter (TSM) concentration significantly influences marine material transport, sedimentation processes, and biogeochemical cycles. Traditional field observations are constrained by limited spatial and temporal coverage, necessitating the use of remote-sensing technology to comprehensively understand TSM variations over extensive areas and periods. This study proposes a remote-sensing approach to estimate the vertical distribution of TSM concentrations using MODIS satellite data, with the Bohai Sea and Yellow Sea (BSYS) as a case study. Extensive field measurements across various hydrological conditions and seasons enabled accurate reconstruction of in situ TSM vertical distributions from bio-optical parameters, including the attenuation coefficient, particle backscattering coefficient, particle size, and number concentration, achieving a determination coefficient of 0.90 and a mean absolute percentage error of 26.5%. In situ measurements revealed two distinct TSM vertical profile types (vertically uniform and increasing) and significant variation in TSM profiles in the BSYS. Using surface TSM concentrations, wind speed, and water depth, we developed and validated a remote-sensing approach to classify TSM vertical profile types, achieving an accuracy of 84.3%. Combining this classification with a layer-to-layer regression model, we successfully estimated TSM vertical profiles from MODIS observation. Long-term MODIS product analysis revealed significant spatiotemporal variations in TSM vertical distributions and column-integrated TSM concentrations, particularly in nearshore regions. These findings provide valuable insights for studying marine sedimentation and biological processes and offer a reference for the remote-sensing estimation of the TSM vertical distribution in other marine regions. Full article

In this work, nanocellulose aqueous dispersions were studied as a bio-inspired consolidating agent for the recovery and conservation of ancient wood and compared with two of the most used traditional consolidants: the synthetic resins Paraloid B-72 and Regalrez 1126. The morphology of crystalline nanocellulose (CNC), determined using Scanning Electron Microscopy (SEM), presents with a rod-like shape, with a size ranging between 15 and 30 nm in width. Chemical characterization performed using the Fourier-Transform Infrared Spectroscopy (FT-IR) technique provides information on surface modifications, in this case, demonstrating the presence of only the characteristic peaks of nanocellulose. Moreover, conductometric, pH, and dry matter measurements were carried out, showing also in this case values perfectly conforming to what is found in the literature. The treated wood samples were observed under an optical microscope in reflected light and under a scanning electron microscope to determine, respectively, the damage caused by xylophages and the morphology of the treated surfaces. The images acquired show the greater similarity of the surfaces treated with nanocellulose to untreated wood, compared with other consolidating agents. Finally, a colorimetric analysis of these samples was also carried out before and after a first consolidation treatment, and after a second treatment carried out on the same samples three years later. The samples treated with CNC appeared very homogeneous and uniform, without alterations in their final color appearance, compared to other traditional synthetic products. Full article

Water colour remote sensing is a valuable tool for assessing bio-optical and biogeochemical parameters across the vast extent of the Amazon River Continuum (ARC). However, accurate retrieval depends on selecting the best atmospheric correction (AC). Four AC processors (Acolite, Polymer, C2RCC, OC-SMART) were evaluated against in situ remote sensing reflectance ($R_{rs}$) measurements. K-means classification identified four optical water types (OWTs) that are affected by the ARC. Two OWTs showed seasonal differences in the Lower Amazon River, influenced by the increase in suspended sediment concentration with river discharge. The other OWTs in the Amazon River Plume are dominated by phytoplankton or by a mixture of optically significant constituents. The Quality Water Index Polynomial method used to assess the quality of in situ and orbital $R_{rs}$ had a high failure rate when the Apparent Visible Wavelength was >580 nm for in situ $R_{rs}$. OC-SMART $R_{rs}$ products showed better spectral quality compared to $R_{rs}$ derived from other AC processors evaluated in this study. These results improve our understanding of remotely sensing very turbid waters, such as those in the Amazon River Continuum. Full article

The challenges to feed the world in 2050 are becoming more and more apparent. This calls for producing more with fewer inputs (most of them under scarcity), higher resource efficiency, minimum or zero effect on the environment, and higher sustainability. Therefore, increasing the circularity of production systems is highly significant for their sustainability. This study investigates the utilization of waste streams from greenhouse hydroponic drainage nutrient solutions for the cultivation of the microalgae Desmodesmus sp. The cultivation was done in an automatically controlled container-scale closed tubular Photo Bio-Reactor (PBR). The study included lab-scale open-pond system experiments and in situ container-scale experiments in the greenhouse wastewater system to assess biomass growth, optical density, nitrogen consumption, and the influence of enzymatic complexes on microalgae cell breakdown. A batch-harvesting process was followed, and the harvested microalgae biomass was pre-concentrated using FeCl₃ as a flocculant that has demonstrated efficient sedimentation and biomass recovery. Following microalgae sedimentation, the produced biomass was used for biostimulant production by means of a biocatalysis process. The enzymatic complexes, “EnzProt”, “EnzCell”, and “EnzMix” were tested for cell breakdown, with “EnzMix” at a dosage of 10% showing the most promising results. The results demonstrate successful biomass production and nitrogen uptake in the lab-scale open-pond system, with promising upscaling results within container-scale cultivation. The findings contribute to a better assessment of the needs of Desmodesmus sp. culture and highlight the importance in optimizing culture conditions and enzymatic processes for the production of biostimulants. Full article

Mathematical algorithms relate satellite data of ocean color with the surface Chlorophyll-a concentration (Chl-a), a proxy of phytoplankton biomass. These mathematical tools work best when they are adapted to the unique bio-optical properties of a particular oceanic province. Ocean color algorithms should also consider that there are significant differences between datasets derived from different sensors. Common solutions are to provide different parameters for each sensor or use merged satellite data. In this paper, we use satellite data from the Copernicus merged product suite and in situ data from the southernmost part of the California Current System to test two widely used global algorithms, OCx and CI, and a regional algorithm, CalCOFI2. The OCx algorithm yielded the most favorable results. Consequently, we regionalized it and conducted further testing, leading to significant improvements, especially in eutrophic and oligotrophic waters. The database was then separated according to (a) dynamic boundaries in the area, (b) bio-optical properties, and (c) climatic conditions (El Niño/La Niña). Regional algorithms were obtained and tested for each partition. The Chl-a retrievals for each model were tested and compared. The best fit for the data was for the regional algorithms that considered the climatic conditions (El Niño/La Niña). These results will allow for the construction of consistent regionally adapted time series and, therefore, will demonstrate the importance of El Niño/La Niña events on the bio-optical properties of the area. Full article

This work aims to show the potential of imaging spectroscopy in assessing water quality and aquatic vegetation in Lake Trasimeno, Italy. Hyperspectral reflectance data from the PRISMA, DESIS and EnMAP missions (2019–2022, summer periods) were compared with in situ measurements from WISPStation and used as inputs for water quality product generation algorithms. The bio-optical model BOMBER was run to simultaneously retrieve water quality parameters (Chlorophyll-a (Chl-a) and Total Suspended Matter, (TSM)) and the coverage of submerged and emergent macrophytes (SM, EM); value-added products, such as Phycocyanin concentration maps, were generated through a machine learning approach. The results showed radiometric agreement between satellite and in situ data, with R² > 0.9, a Spectral Angle < 10° and water quality mapping errors < 30%. Both SM and EM coverage varied significantly from 2019 (135 ha, 0 ha, respectively) to 2022 (2672 ha, 343 ha), likely influenced by changes in rainfall and lake levels. The areas of greatest variability in Chl-a and TSM were identified in the littoral zones in the western side of the lake, while the highest variation in the fractional cover of SM and density of EM were observed in the south-eastern region; this information could support the water authorities’ monitoring activities. To this end, further developments to improve the reference field data for the validation of water quality products are recommended. Full article