Determining instrument specifications and analyzing methods for atmospheric retrieval (DISAMAR) is a radiative-transfer (RT) model developed to simulate retrievals of atmospheric components and surface properties. This article evaluates the performance of the DISAMAR retrieval algorithm using Tropospheric Monitoring Instrument (TROPOMI) spectral measurements of the O-2-A (757-770 nm) and O-2-B (685-691 nm) bands for cloud-free scenes and fully cloudy scenes. For fully cloudy scenes, cloud pressure and cloud optical thickness (COT) are retrieved and compared with Fast Retrieval Scheme for Clouds from the O-2-A band-Sentinel (FRESCO-S), Retrieval of Cloud Information Using Neural Network (ROCINN), and Visible Infrared Imager Radiometer Suite (VIIRS) cloud products. For cloud-free scenes, the surface pressure and surface albedo are fit; the results are compared with ERA5 surface pressure and TROPOMI DLER datasets, respectively. Several parameters in DISAMAR retrieval settings are tested, including the stray-light settings, the fitting wavelength windows, the a priori values of the fitting parameters, and the performance of oxygen cross-section datasets (JPL2008, HITRAN 2008/2012/2020). As expected, DISAMAR retrieves cloud mid-level pressure (CLP) values closely matching FRESCO-S and ROCINN, especially when fitting the O-2-A band. COT and cloud-top pressure (CTP) show better correlation with VIIRS data when fitting the O-2-A band than the O-2-B band. For thick clouds, fitting stray light is not advisable, and a specific a priori value of COT is unnecessary. Using the HITRAN2020 dataset provides more accurate spectral simulations. Fitting the O-2-A band yields results closer to both FRESCO-S and VIIRS, while the O-2-B band yields results closer to ROCINN and serves as a useful supplement. Excluding high-residual wavelengths in the fitting window further improves retrievals.

DISAMAR (determining instrument specifications and analysing methods for atmospheric retrieval) is a computer model developed to simulate the retrieval of properties of atmospheric trace gases, aerosols, clouds, and the ground surface from passive remote sensing observations in a wavelength range from 270 to 2400 nm. It is being used for the TROPOMI/Sentinel-5P and Sentinel-4/5 missions to derive Level-1b product specifications. It is also used in some research to obtain aerosol and trace gas properties, but its application to cloud properties retrieval is limited. This study presents the retrieval of cloud pressure and cloud optical thickness as well as surface pressure for cloud free based on TROPOMI Oxygen-A (Band 6) and Oxygen-B (Band 5) band measurements, and compares the results with FRESCO and NPP-Suomi Level 2 cloud property data. Different cross section datasets including JPL2008, HITRAN 2008 and HITRAN2020 are also tested in this study. In conclusion, for surface pressure retrieval, using O2-A band gives more reliable results than O2-B band and is easier to converge in the calculation, especially over land surface. But while over sea surface, using O2-B band in retrieval performs better than O2-A band. Secondly, the retrieval based on the cross section file JPL2008 shows better results when using O2-A band, but HITRAN2020 gives better results when using O2-B band. Thirdly, setting appropriate a-priory value in DISAMAR and removing some of the wavelengths with high residual simulated reflectivity can significantly improve the results , both in terms of convergence and reduction of validation error. The cloud pressure correlation coefficient between the retrieval and NPP or FRESCO data is 0.85 and 0.99 respectively, while the cloud optical thickness has a correlation coefficient of 0.77 between retrieval and NPP COT datasets.

Hypoxanthine (Hx), produced by adenosine triphosphate (ATP) metabolism, is a valuable indicator that determines the quality and degradation status of meat products and is also an important biochemical marker to certain diseases such as gout. The rapid emergence of paper-based enzyme biosensors has already revolutionized its on-site determination. But it is still limited by the complex patterning and fabrication, unstable enzyme and uneven coloration. This work aims to develop an eco-friendly method to construct engineered paper microfluidic, which seeks to produce reaction and non-reaction zones without any patterning procedure. Chitooligosaccharide (COS), derived from shrimp shells, was used to modify nitrocellulose membranes and immobilize xanthine oxidase (XOD) and chromogenic agent of nitro blue tetrazolium chloride (NBT). After modification, micro fluids could converge into the modification area and Hx could be detected by XOD-catalyzed conversion. Due to the positively charged cationic basic properties of COS, the enzyme storage stability and the color homogeneity could be greatly strengthened through the electrostatic attraction between COS and XOD and formazan product. The detection limit (LOD) is 2.30 mu M; the linear range is 0.05-0.35 mM; the complete test time can be as short as 5 min. The COS-based biosensor shows high specificity and can be used directly for Hx in complex samples such as fish and shrimp samples, and different broths. This biosensor is eco-friendly, nontechnical, economical and therefore a compelling platform for on-site or home-based detection of food freshness.

This paper focuses on the proof and application of discriminating between oil spills and seawater (including the “look-alikes”, named low wind areas) based on the polarization ratio. A new relative polarization ratio (PRr) method is proposed, which is based on the difference between the scattering mechanism and the dielectric constant for oil spills compared to that of seawater. The case study found that (1) PRr numerically amplifies the contrast between oil spills and seawater, reduces the difference between low wind areas and ordinary seawater, and exhibits better details of the image; (2) the threshold method based on Euclidean distance can obtain the highest classification overall accuracy within the allowable error range, and can be widely used in the study of different incidence angles and environmental conditions; and (3) the identification of oil spills and seawater by the proposed methods can largely avoid the misjudgment of low wind areas as oil spills. Considering visual interpretation as the reference ‘ground truth’, the overall classification accuracy of all cases is more than 95%; only the edge of the diffuse thin oil slick and oil–water mixture is difficult to identify. This method can serve as an effective supplement to existing oil spill detection methods.

Color indicator films for fish freshness were fabricated by incorporating κ-carrageenan (CAR) polymer with red grape skin extract (GSE) as a pH-sensing agent and silver nanoparticles (AgNPs) as an antimicrobial agent. Anthocyanins in GSE exhibited distinguished pH responsive color changes. GSE and AgNPs were well compatible with CAR with intramolecular interactions, approved by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analysis, thermo-gravimetric analysis (TGA) and differential scanning calorimetry (DSC). GSE-containing films displayed distinguished color changes in response to pH variations and volatile ammonia. Enhanced UV blocking ability and strong antioxidant activity were revealed for GSE included films without sacrificing the physico-chemical properties of the CAR film. Films containing AgNPs showed improved mechanical strength and strong antimicrobial ability against both Escherichia coli and Staphylococcus aureus. The CAR/AgNPs/GSE film displayed a distinctive color change corresponding to changes in the total volatile basic nitrogen (TVB-N) of fish during storage. In addition, the CAR/AgNPs/GSE film showed excellent color stability to consecutive UV exposure and its storage time at 25 °C is expected to be at least 240 days, which indicates that it has high potential as an intelligent food freshness indicator film.

In this study, a paper-based enzyme biosensor for hypoxanthine (Hx) was developed, enabling visual and one-step fish freshness detection. Xanthine oxidase and horseradish peroxidase were immobilized on nitrocellulose membranes with 3,3 ',5,5 '-tetramethylbenzidine to output the colour signal. Chitosan oligosaccharide lactate -modified nitrocellulose membranes entrapped the dual-enzyme system and exhibited excellent microfluidic aggregation effect. The developed enzyme biosensor produced a linear response of 0.01-0.16 mmolL-1 with a detection limit of 8.22 mu molL-1, and was selective for Hx with recoveries of 96.13-103.11 % for fish samples. These biosensors were attached directly to the surface of fish samples and the colour was revealed within 3 min. Colour signals can be judged by the naked-eye to distinguish between fresh and spoiled fish samples and analyzed by a smartphone for quantitative analysis. The biosensor shows great potential as a powerful pattern -and reagent-free device for on-site freshness evaluation of fish.