Iron (Fe)-based treatment methods are widely applied to remove carcinogenic arsenic (As) from drinking water, but generate toxic As-laden Fe (oxyhydr)oxide waste that has traditionally been ignored for resource recovery by the water sector. However, the European Commission recently classified As as a Critical Raw Material (CRM), thus providing new incentives to re-think As-laden groundwater treatment sludge. Before As recovery techniques can be developed for groundwater treatment waste, detailed information on its structure and composition is essential. To this end, we comprehensively characterized sludge generated from a variety of As-rich groundwater treatment plants in different geographic regions by combining a suite of macroscopic measurements, such as total digestions, leaching tests and BET surface area with molecular-scale solid-phase analysis by Fe and As K-edge X-ray absorption spectroscopy (XAS). We found that the As mass fraction of all samples ranged from ∼200–1200 mg As/kg (dry weight) and the phosphorous (P) content reached ∼0.5–2 mass%. Notably, our results indicated that the influent As level was a poor predictor of the As sludge content, with the highest As mass fractions (940–1200 mg As/kg) measured in sludge generated from treating low groundwater As levels (1.1–22 µg/L). The Fe K-edge XAS data revealed that all samples consisted of nanoscale Fe(III) precipitates with less structural order than ferrihydrite, which is consistent with their high BET surface area (up to >250 m²/g) and large As and P mass fractions. The As K-edge XAS data indicated As was present in all samples predominantly as As(V) bound to Fe(III) precipitates in the binuclear-corner sharing (²C) geometry. Overall, the similar structure and composition of all samples implies that As recovery methods optimized for one type of Fe-based treatment sludge can be applied to many groundwater treatment sludges. Our work provides a critical foundation for further research to develop resource recovery methods for As-rich waste.

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Various studies have been performed to investigate the accuracy of troposphere zenith wet delays (ZWDs) determined from GPS. Most of these studies use dual-frequency GPS data of large-scale networks with long baselines to determine the absolute ZWDs. For small-scale networks the estimability of the absolute ZWDs deteriorates due to high correlation between the solutions of the ZWDs and satellite-specific parameters as satellite clocks. However, as relative ZWDs (rZWDs) can always be estimated, irrespective of the size of the network, it is of interest to understand how the large-scale network rZWD-performance of dual-frequency GPS using an ionosphere-float model compares to the small-scale network rZWD-performance of single-frequency GPS using an ionosphere-weighted model. In this contribution such an analysis is performed using undifferenced and uncombined network parametrization modelling. In this context we demonstrate the ionosphere weighted constraints, which allows the determination of the rZWDs independent from signals on the second frequency. Based on an analysis of both simulated and real data, it is found that under quiet ionosphere conditions, the accuracy of the single-frequency determined rZWDs in the ionosphere-weighted network is comparable to that of the large-scale dual-frequency network without ionospheric constraints. Making use of the real data from two baselines of 15 days, it was found that the absolute differences of the rZWDs applying the two strategies are within 1 cm in over 90% and 95% of the time for ambiguity-float and -fixed cases, respectively.@en

In PPP-RTK network processing, the wet component of the zenith tropospheric delay (ZTD) cannot be precisely modelled and thus remains unknown in the observation equations. For small networks, the tropospheric mapping functions of different stations to a given satellite are almost equal to each other, thereby causing a near rank-deficiency between the ZTDs and satellite clocks. The stated near rank-deficiency can be solved by estimating the wet ZTD components relatively to that of the reference receiver, while the wet ZTD component of the reference receiver is constrained to zero. However, by increasing network scale and humidity around the reference receiver, enlarged mismodelled effects could bias the network and the user solutions. To consider both the influences of the noise and the biases, the mean-squared errors (MSEs) of different network and user parameters are studied analytically employing both the ZTD estimation strategies. We conclude that for a certain set of parameters, the difference in their MSE structures using both strategies is only driven by the square of the reference wet ZTD component and the formal variance of its solution. Depending on the network scale and the humidity condition around the reference receiver, the ZTD estimation strategy that delivers more accurate solutions might be different. Simulations are performed to illustrate the conclusions made by analytical studies. We find that estimating the ZTDs relatively in large networks and humid regions (for the reference receiver) could significantly degrade the network ambiguity success rates. Using ambiguity-fixed network-derived PPP-RTK corrections, for networks with an inter-station distance within 100 km, the choices of the ZTD estimation strategy is not crucial for single-epoch ambiguity-fixed user positioning. Using ambiguity-float network corrections, for networks with inter-station distances of 100, 300 and 500 km in humid regions (for the reference receiver), the root-mean-squared errors (RMSEs) of the estimated user coordinates using relative ZTD estimation could be higher than those under the absolute case with differences up to millimetres, centimetres and decimetres, respectively.@en

Maritime accidents and incidents, such as ship to ship collision or ship grounding, most often occur near ports due to the intensive water traffic and shallow water depth. The occurrence of those accidents place a port in a very dangerous situation, since the port could suffer from a high risk of blockage of port entry, and the consequent economic loss can be substantial. In the case of maritime accidents, it is of great significance for sea-going ships outside of the accident zone to determine a safe and smooth sailing route and efficient speeds at a busy port, thus to reduce the risk of blockage and the economic loss of the port, whilst not disturbing the current emergency logistic response system. In this regard, a decision-making method for safe and smooth sailing route and efficient speeds for sea-going ships encountering an accident can be very valuable. Because of the high nonlinearity of these decisions, PSO algorithm is used to search the safe and smooth sailing route and efficient speeds. The study results show that the proposed method can effectively achieve the safe and smooth sailing route and efficient speeds for ships encountering an accident, thus to be more economic and reduce the risky chance of blockage of the port entry.@en