Achieving of sandwich-like laminated composite materials for robust superhydrophobicity, rapid photochromism and photo-mask writable media

Photochromic materials with anti-water properties have impressed practical values, but their applications are severely hindered by poor stability and slow colour-switching rate. Inspired by the superhydrophobicity of lotus leaf and...

Evolution of Ocean Color Atmospheric Correction: 1970–2005

Retrieval of water properties from satellite-borne imagers viewing oceans and coastal areas in the visible region of the spectrum requires removing the effect of the atmosphere, which contributes approximately 80–90% of the measured radiance over the open ocean in the blue spectral region. The Gordon and Wang algorithm originally developed for SeaWiFS (and used with other NASA sensors, e.g., MODIS) forms the basis for many atmospheric removal (correction) procedures. It was developed for application to imagery obtained over the open ocean (Case 1 waters), where the aerosol is usually non-absorbing, and is used operationally to process global data from SeaWiFS, MODIS and VIIRS. Here, I trace the evolution of this algorithm from early NASA aircraft experiments through the CZCS, OCTS, SeaWiFs, MERIS, and finally the MODIS sensors. Strategies to extend the algorithm to situations where the aerosol is strongly absorbing are examined. Its application to sensors with additional and unique capabilities is sketched. Problems associated with atmospheric correction in coastal waters are described.

Regulation-based probabilistic substance quality index and automated geo-spatial modeling for water quality assessment

Natural environments are recognized as complex heterogeneous structures thus requiring numerous multi-scale observations to yield a comprehensive description. To monitor the current state and identify negative impacts of human activity, fast and precise instruments are in urgent need. This work provides an automated approach to the assessment of spatial variability of water quality using guideline values on the example of 1526 water samples comprising 21 parameters at 448 unique locations across the New Moscow region (Russia). We apply multi-task Gaussian process regression (GPR) to model the measured water properties across the territory, considering not only the spatial but inter-parameter correlations. GPR is enhanced with a Spectral Mixture Kernel to facilitate a hyper-parameter selection and optimization. We use a 5-fold cross-validation scheme along with $$R^2$$ R 2 -score to validate the results and select the best model for simultaneous prediction of water properties across the area. Finally, we develop a novel Probabilistic Substance Quality Index (PSQI) that combines probabilistic model predictions with the regulatory standards on the example of the epidemiological rules and hygienic regulations established in Russia. Moreover, we provide an interactive map of experimental results at 100 m2 resolution. The proposed approach contributes significantly to the development of flexible tools in environment quality monitoring, being scalable to different standard systems, number of observation points, and region of interest. It has a strong potential for adaption to environmental and policy changes and non-unified assessment conditions, and may be integrated into support-decision systems for the rapid estimation of water quality spatial distribution.

Optimization of Landsat Chl-a Retrieval Algorithms in Freshwater Lakes through Classification of Optical Water Types

The application of remote sensing data to empirical models of inland surface water chlorophyll-a concentrations (chl-a) has been in development since the launch of the Landsat 4 satellite series in 1982. However, establishing an empirical model using a chl-a retrieval algorithm is difficult due to the spatial heterogeneity of inland lake water properties. Classification of optical water types (OWTs; i.e., differentially observed water spectra due to differences in water properties) has grown in favour in recent years over traditional non-turbid vs. turbid classifications. This study examined whether top-of-atmosphere reflectance observations in visible to near-infrared bands from Landsat 4, 5, 7, and 8 sensors can be used to identify unique OWTs using a guided unsupervised classification approach in which OWTs are defined through both remotely sensed reflectance and surface water chemistry data taken from samples in North American and Swedish lakes. Linear regressions of algorithms (Landsat reflectance bands, band ratios, products, or combinations) to lake surface water chl-a were built for each OWT. The performances of chl-a retrieval algorithms within each OWT were compared to those of global chl-a algorithms to test the effectiveness of OWT classification. Seven unique OWTs were identified and then fit into four categories with varying degrees of brightness as follows: turbid lakes with a low chl-a:turbidity ratio; turbid lakes with a mixture of high chl-a and turbidity measurements; oligotrophic or mesotrophic lakes with a mixture of low chl-a and turbidity measurements; and eutrophic lakes with a high chl-a:turbidity ratio. With one exception (r2 = 0.26, p = 0.08), the best performing algorithm in each OWT showed improvement (r2 = 0.69–0.91, p < 0.05), compared with the best performing algorithm for all lakes combined (r2 = 0.52, p < 0.05). Landsat reflectance can be used to extract OWTs in inland lakes to provide improved prediction of chl-a over large extents and long time series, giving researchers an opportunity to study the trophic states of unmonitored lakes.

Modelling the effect of submarine iceberg melting on glacier-adjacent water properties

The rate of ocean-driven retreat of Greenland’s tidewater glaciers remains highly uncertain in predictions of future sea level rise, in part due to poorly constrained glacier-adjacent water properties. Icebergs and their meltwater contributions are likely important modifiers of fjord water properties, yet their effect is poorly understood. Here, we use a 3-D ocean circulation model, coupled to a submarine iceberg melt module, to investigate the effect of submarine iceberg melting on glacier-adjacent water properties in a range of idealised settings. Submarine iceberg melting can modify glacier-adjacent water properties in three principle ways: (1) substantial cooling and modest freshening in the upper ~50 m of the water column; (2) warming of Polar Water at intermediate depths due to iceberg melt-induced upwelling of warm Atlantic Water, and; (3) warming of the deeper Atlantic Water layer when vertical temperature gradients through this layer are steep (due to vertical mixing of warm water at depth), but cooling of the Atlantic Water layer when vertical temperature gradients are shallow. The overall effect of iceberg melt is to make glacier-adjacent water properties more uniform with depth. When icebergs extend to, or below, the depth of a sill at the fjord mouth, they can cause cooling throughout the entire water column. All of these effects are more pronounced in fjords with higher iceberg concentrations and deeper iceberg keel depths. These iceberg melt-induced changes to glacier-adjacent water properties will reduce rates of glacier submarine melting near the surface, but increase them in the Polar Water layer, and cause typically modest impacts in the Atlantic Water layer. These results characterise the important role of submarine iceberg melting in modifying ice sheet-ocean interaction, and highlight the need to improve representations of fjord processes in ice sheet-scale models.

Supplemental figure for "Odorous Compound Removal Performance and Water Properties of a Biotrickling Filter Installed in a Piggery"

This is a supplemental figure 1 for the manuscript entitled "Odorous Compound Removal Performance and Water Properties of a Biotrickling Filter Installed in a Piggery." This figure S1 shows trends in elimination capacity.

Supplemental figure for "Odorous Compound Removal Performance and Water Properties of a Biotrickling Filter Installed in a Piggery"

This is a supplemental figure 1 for the manuscript entitled "Odorous Compound Removal Performance and Water Properties of a Biotrickling Filter Installed in a Piggery." This figure S1 shows trends in elimination capacity.

Suitability of water treatment chemicals in the remediation of produced water: a data-driven approach

There exist numerous counts of research works on produced water. We got to know about them because they made it to publishing probably by indicating a positive or promising result. Contrarily, there exist a hundred times unpublished, unreported works on produced water; works rejected based on not yielding desirable results or not being innovative enough. We might have encountered undesirable results but to what depths and time have we committed to mining out intricate details. The world is thinking and demanding sustainability. Is it sustainable for the future of water treatment, the ease and pace at which we transition to the next chemical or treatment option? In this data-centred approach, three common chemicals, aluminium sulphate, ferrous ammonium sulphate and calcium chloride, were used to treat produced water. The collected data (both initial and final analysis) were inferentially analysed. The first statistical analysis was the testing of 2 hypotheses using the Analysis of Variance test. This was done to reveal to compare the dependence of produced water properties on two categorical variables (sample type and treatment chemicals). The second was the test for relevance: correlation and regression analyses. The laboratory experimental analysis revealed that aluminium sulphate was most suitable for the alteration of physical effluent characteristics; ferrous ammonium sulphate for salinity concerns and calcium chloride for a particular heavy metal’s stability. The overall effluent characteristics indicated a greater dependency on ‘sample type’ than ‘treatment chemicals’. Certain produced water properties relationships were highlighted and quantified for instance iron(II) and chloride ion concentrations were dependent on total solids and indicated a significance F of 0.01.