On Thermal Infrared Remote Sensing of Plastic Pollution in Natural Waters

A comparative study of freeze-drying heat transfer in polymeric vials and glass vials

Implementation of polymeric vials for freeze-dried drug products has been practically non-existent because of unique moisture barrier and thermodynamic technical challenges. Hybrid vials, which combine the benefits of polymer and glass, have been shown to address the challenges of ordinary polymeric vials. Tackling thermodynamic challenges starts with a clear understanding of the heat transfer mechanism. To this end, multi-physics simulations and experimentation were used to compare the heat transfer between hybrid cyclic olefin polymer (COP) vials and borosilicate glass vials during freeze-drying. Parametric models were developed for hybrid COP and glass vials to systematically study the effect of five design parameters based on the arrangement of the vials on a tray inside a lyophilization chamber. Heat transfer in glass vials were dominated by heat conduction with the surrounding vapor, while hybrid COP vials were governed by conduction with the bottom shelf. Furthermore, hybrid COP vials exhibited more consistent heat flow rate and total heat transfer coefficient compared to glass vials, suggesting higher product quality as a result. The distance between adjacent vials and the drug product height were the most important parameters affecting heat transfer irrespective of vial type. Results indicated that hybrid COP vials can be filled to higher fill volumes with higher heat transfer and without the risk of breakage. Results of this study can help design innovative primary packaging systems for freeze drying or optimizing heat transfer for existing glass or hybrid COP vial systems regarding product consistency and drying time.

Transparent Sol-Gel-Based Coatings Reflecting Heat Radiation in the Near Infrared

Thin, flat textile roofing offers negligible heat insulation. In warm areas, such roofing membranes are therefore equipped with metallized surfaces to reflect solar heat radiation, thus reducing the warming inside a textile building. Heat reflection effects achieved by metallic coatings are always accompanied by shading effects as the metals are non-transparent for visible light (VIS). Transparent conductive oxides (TCOs) are transparent for VIS and are able to reflect heat radiation in the infrared. TCOs are, e.g., widely used in the display industry. To achieve the perfect coatings needed for electronic devices, these are commonly applied using costly vacuum processes at high temperatures. Vacuum processes, on account of the high costs involved and high processing temperatures, are obstructive for an application involving textiles. Accepting that heat-reflecting textile membranes demand less perfect coatings, a wet chemical approach has been followed here when producing transparent heat-reflecting coatings. Commercially available TCOs were employed as colloidal dispersions or nanopowders to prepare sol-gel-based coating systems. Such coatings were applied to textile membranes as used for architectural textiles using simple coating techniques and at moderate curing temperatures not exceeding 130 °C. The coatings achieved about 90% transmission in the VIS spectrum and reduced near-infrared transmission (at about 2.5 µm) to nearly zero while reflecting up to 25% of that radiation. Up to 35% reflection has been realized in the far infrared, and emissivity values down to ε = 0.5777 have been measured.

Suspended Particulate Matter Analysis of Pre and During Covid Lockdown Using Google Earth Engine Cloud Computing: A Case Study of Ukai Reservoir

Presence of suspended particulate matter (SPM) in a waterbody or a river can be caused by multiple parameters such as other pollutants by the discharge of poorly maintained sewage, siltation, sedimentation, flood and even bacteria. In this study, remote sensing techniques were used to understand the effects of pandemic-induced lockdown on the SPM concentration in the lower Tapi reservoir or Ukai reservoir. The estimation was done using Landsat-8 OLI (Operational Land Imager) having radiometric resolution (12-bit) and a spatial resolution of 30 m. The Google Earth Engine (GEE) cloud computing platform was used in this study to generate the products. The GEE is a semi-automated workflow system using a robust approach designed for scientific analysis and visualization of geospatial datasets. An algorithm was deployed, and a time-series (2013-2020) analysis was done for the study area. It was found that the average mean value of SPM in Tapi River during 2020 is lowest than the last seven years at the same time.

Close-range remote sensing-based detection and identification of macroplastics on water assisted by artificial intelligence: A review

Detection and identification of macroplastic debris in aquatic environments is crucial to understand and counter the growing emergence and current developments in distribution and deposition of macroplastics. In this context, close-range remote sensing approaches revealing spatial and spectral properties of macroplastics are very beneficial. To date, field surveys and visual census approaches are broadly acknowledged methods to acquire information, but since 2018 techniques based on remote sensing and artificial intelligence are advancing. Despite their proven efficiency, speed and wide applicability, there are still obstacles to overcome, especially when looking at the availability and accessibility of data. Thus, our review summarizes state-of-the-art research about the visual recognition and identification of different sorts of macroplastics. The focus is on both data acquisition techniques and evaluation methods, including Machine Learning and Deep Learning, but resulting products and published data will also be taken into account. Our aim is to provide a critical overview and outlook in a time where this research direction is thriving fast. This study shows that most Machine Learning and Deep Learning approaches are still in an infancy state regarding accuracy and detail when compared to visual monitoring, even though their results look very promising.

Using a UAV Thermal Infrared Camera for Monitoring Floating Marine Plastic Litter

In recent years, the remote sensing of marine plastic litter has been rapidly evolving and the technology is most advanced in the visible (VIS), near-infrared (NIR), and short-wave infrared (SWIR) wavelengths. It has become clear that sensing using VIS-SWIR bands, based on the surface reflectance of sunlight, would benefit from complementary measurements using different technologies. Thermal infrared (TIR) sensing shows potential as a novel method for monitoring macro plastic litter floating on the water surface, as the physics behind surface-leaving TIR is different. We assessed a thermal radiance model for floating plastic litter using a small UAV-grade FLIR Vue Pro R 640 thermal camera by flying it over controlled floating plastic litter targets during the day and night and in different seasons. Experiments in the laboratory supported the field measurements. We investigated the effects of environmental conditions, such as temperatures, light intensity, the presence of clouds, and biofouling. TIR sensing could complement observations from VIS, NIR, and SWIR in several valuable ways. For example, TIR sensing could be used for monitoring during the night, to detect plastics invisible to VIS-SWIR, to discriminate whitecaps from marine litter, and to detect litter pollution over clear, shallow waters. In this study, we have shown the previously unconfirmed potential of using TIR sensing for monitoring floating plastic litter.

Graphene-Silicon Device for Visible and Infrared Photodetection

The fabrication of a graphene-silicon (Gr-Si) junction involves the formation of a parallel metal-insulator-semiconductor (MIS) structure, which is often disregarded but plays an important role in the optoelectronic properties of the device. In this work, the transfer of graphene onto a patterned n-type Si substrate, covered by Si3N4, produces a Gr-Si device, in which the parallel MIS consists of a Gr-Si3N4-Si structure surrounding the Gr-Si junction. The Gr-Si device exhibits rectifying behavior with a rectification ratio up to 104. The investigation of its temperature behavior is necessary to accurately estimate the Schottky barrier height (SBH) at zero bias, φb0 = 0.24 eV, the effective Richardson's constant, A* = 7 × 10-10 AK-2 cm-2, and the diode ideality factor n = 2.66 of the Gr-Si junction. The device is operated as a photodetector in both photocurrent and photovoltage mode in the visible and infrared (IR) spectral regions. A responsivity of up to 350 mA/W and an external quantum efficiency (EQE) of up to 75% are achieved in the 500-1200 nm wavelength range. Decreases in responsivity to 0.4 mA/W and EQE to 0.03% are observed above 1200 nm, which is in the IR region beyond the silicon optical band gap, in which photoexcitation is driven by graphene. Finally, a model based on two parallel and opposite diodes, one for the Gr-Si junction and the other for the Gr-Si3N4-Si MIS structure, is proposed to explain the electrical behavior of the Gr-Si device.

Spectral Emissivity (SE) Measurement Uncertainties across 2.5–14 μm Derived from a Round-Robin Study Made across International Laboratories

Information on spectral emissivity (SE) is vital when retrieving and evaluating land surface temperature (LST) estimates from remotely sensed observations. SE measurements often come from spectral libraries based upon laboratory spectroscopic measurements, with uncertainties typically derived from repeated measurements. To go further, we organised a “round-robin” inter-comparison exercise involving SE measurements of three samples collected at seven different international laboratories. The samples were distilled water, which has a uniformly high spectral emissivity, and two artificial samples (aluminium and gold sheets laminated in polyethylene), with variable emissivities and largely specular and Lambertian characteristics. Large differences were observed between some measurements, with standard deviations over 2.5–14 μm of 0.092, 0.054 and 0.028 emissivity units (15.98%, 7.56% and 2.92%) for the laminated aluminium sheet, laminated gold sheet and distilled water respectively. Wavelength shifts of up to 0.09 μm were evident between spectra from different laboratories for the specular sample, attributed to system design interacting with the angular behaviour of emissivity. We quantified the impact of these SE differences on satellite LST estimation and found that emissivity differences resulted in LSTs differing by at least 3.5 K for each artificial sample and by more than 2.5 K for the distilled water. Our findings suggest that variations between SE measurements derived via laboratory setups may be larger than previously assumed and provide a greater contribution to LST uncertainty than thought. The study highlights the need for the infrared spectroscopy community to work towards standardized and interlaboratory comparable results.

Remote Sensing of Sea Surface Artificial Floating Plastic Targets with Sentinel-2 and Unmanned Aerial Systems (Plastic Litter Project 2019)

Remote sensing is a promising tool for the detection of floating marine plastics offering extensive area coverage and frequent observations. While floating plastics are reported in high concentrations in many places around the globe, no referencing dataset exists either for understanding the spectral behavior of floating plastics in a real environment, or for calibrating remote sensing algorithms and validating their results. To tackle this problem, we initiated the Plastic Litter Projects (PLPs), where large artificial plastic targets were constructed and deployed on the sea surface. The first such experiment was realised in the summer of 2018 (PLP2018) with three large targets of 10 × 10 m. Hereafter, we present the second Plastic Litter Project (PLP2019), where smaller 5 × 5 m targets were constructed to better simulate near-real conditions and examine the limitations of the detection with Sentinel-2 images. The smaller targets and the multiple acquisition dates allowed for several observations, with the targets being connected in a modular way to create different configurations of various sizes, material composition and coverage. A spectral signature for the PET (polyethylene terephthalate) targets was produced through modifying the U.S. Geological Survey PET signature using an inverse spectral unmixing calculation, and the resulting signature was used to perform a matched filtering processing on the Sentinel-2 images. The results provide evidence that under suitable conditions, pixels with a PET abundance fraction of at least as low as 25% can be successfully detected, while pinpointing several factors that significantly impact the detection capabilities. To the best of our knowledge, the 2018 and 2019 Plastic Litter Projects are to date the only large-scale field experiments on the remote detection of floating marine litter in a near-real environment and can be used as a reference for more extensive validation/calibration campaigns.