Few studies have used crustal displacements sensed by the Global Positioning System (GPS) to assess the terrestrial water storage (TWS), which causes loadings. Furthermore, no study has investigated the feasibility of using GPS to image TWS over South America (SA), which contains the world’s driest (Atacama Desert) and wettest (Amazon Basin) regions. This work presents a resolution analysis of an inversion of GPS data over SA. Firstly, synthetic experiments were used to verify the spatial resolutions of GPS-imaged TWS and examine the resolving accuracies of the inversion based on checkerboard tests and closed-loop simulations using “TWS” from the Noah-driven Global Land Data Assimilation System (GLDAS-Noah). Secondly, observed radial displacements were used to image daily TWS. The inverted results of TWS at a resolution of 300 km present negligible errors, as shown by synthetic experiments involving 397 GPS stations across SA. However, as a result of missing daily observations, the actual daily number of available stations varied from 60–353, and only 6% of the daily GPS-imaged TWS agree with GLDAS-Noah TWS, which indicates a root-mean-squared error (RMSE) of less than 100 kg/m 2 . Nevertheless, the inversion shows agreement that is better than 0.50 and 61.58 kg/m 2 in terms of the correlation coefficient (Pearson) and RMSE, respectively, albeit at each GPS site.

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Surface structure and chemical properties of adsorbents are important factors required to understand the mechanism of adsorption. The purpose of this study was to produce hydrochars from biomass using hydrothermal carbonisation (HTC) and to analyse their sorption capacities. The biomass used in this study were coco-peat (CP), coconut shell (CS), eggshell (ES), rice husk (RH) and lemon peel (LP). The operating conditions for HTC were 200 °C and 20 h residence time. The characterisation methods consisted of Scanning Electron Microscopy (SEM), Energy Dispersive X-Ray Spectroscopy (EDS), Fourier Transform Infrared Ray (FTIR) Spectroscopy, and Brunauer, Emmett and Teller (BET). The results showed that HTC improved the sorption capacities of the biomass wastes. It was found that hydrochars were crispy and flaky with more micro- and meso-porous structures, indicating that lignin and other components were denatured due to carbonisation. This led to the creation of more active sites for sorption and pollutant binding. The hydrochars showed a percentage increase in carbon content and a decrease in oxygen content with traces of other elements, compared to their corresponding raw biomass. The major functional groups identified were –OH and –COOH. The surface area of the hydrochars which include CP (2.14 m2/g), CS (14.04 m2/g), ES (0.50 m2/g), RH (15.74 m2/g), and LP (6.89 m2/g) were significantly improved compared with those of the raw biomass. The study showed that the hydrochars produced from the biomass wastes have the potential to be used as adsorbents.

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Nowadays, theglobal navigation satellite system (GNSS) positioning techniques based on the International GNSS Service (IGS) products are extensively used for various precise applications. However, specific conditions such as the dual-frequency observations and the final IGS products are required. Consequently, the absence of the final IGS data and using single-frequency observations will degrade these techniques’ accuracy. In this paper, two algorithms through two separated stages are formulated for improving the single-frequency GNSS observations by using one GNSS receiver based on the broadcast ephemerides in real time or close to real time. The first algorithm represents the preparation stage for the second one. It classifies the observations by separating the optimal values of position dilution of precision (PDOP) and the number of satellites (NOS), as well as the corresponding values of coordinates. The second stage includes an algorithm based on the artificial neural network (ANN) approach, which is set at the ANN variables that produce the best precision through the applied tests at the present study. Binary numbers, log sigmoid-Purelin, cascade forward net, and one hidden layer with a size of 10 neurons are the optimal variables of ANN inputs format, transfer functions constellations, feedforward net type, and the number of hidden layers (NHL) and its size, respectively. The simulation results show that the designed algorithms produce a significant improvement in the horizontal and vertical components. Lastly, an evaluation stage is performed in the case of dual-frequency observations by using broadcast ephemerides. The simulation outputs indicate that the precision at applying the proposed integration is completely enhanced compared with the outputs of IGS final data.