Organic complexation of copper in estuarine waters: An assessment of the multi-detection window approach

2018 ◽  
Vol 204 ◽  
pp. 144-151 ◽  
Author(s):  
Kuo Hong Wong ◽  
Hajime Obata ◽  
Taejin Kim ◽  
Asami Suzuki Mashio ◽  
Hideki Fukuda ◽  
...  
1990 ◽  
Vol 232 ◽  
pp. 149-159 ◽  
Author(s):  
C.M.G. Van Den Berg ◽  
M. Nimmo ◽  
P. Daly ◽  
D.R. Turner

2021 ◽  
Author(s):  
Loes J. A. Gerringa ◽  
Martha Gledhill ◽  
Indah Ardiningsih ◽  
Niels Muntjewerf ◽  
Luis M. Laglera

Abstract. Competitive ligand exchange–adsorptive cathodic stripping voltammetry (CLE-AdCSV) is used to determine the conditional concentration ([L]) and the conditional binding strength (logKcond) of dissolved organic Fe-binding ligands, which together influence the solubility of Fe in seawater. Electrochemical applications of Fe speciation measurements vary predominantly in the choice of the added competing ligand. Although different applications show the same trends, [L] and logKcond differ between the applications. In this study, binding of two added ligands in three different common applications to three known types of natural binding ligands are compared. The applications are: 1) Salicylaldoxime (SA) at 25µM (SA25) and short waiting time, 2) SA at 5µM (SA5) and 3)2-(2-thiazolylazo)-ρ-cresol (TAC) at 10 µM, the latter two with overnight equilibration. The three applications were calibrated under the same conditions, although having different pH values, resulting in the detection window centers (D) DTAC > DSA25 ≥ SA5 (as log D values with respect to Fe3+: 12.3 > 11.2 ≥ 11). For the model ligands, there is no common trend in the results of logKcond. The values have a considerable spread, which indicates that the error in logKcond is large. The ligand concentrations of the non humic model ligands are overestimated by SA25 which we attribute to the lack of equilibrium between Fe-SA species in the SA25 application. The application TAC more often underestimated the ligand concentrations and the application SA5 over and under estimated the ligand concentration. The extent of overestimation and underestimation differed per model ligand, and the three applications showed the same trend between the non humic model ligands especially for SA5 and SA25. The estimated ligand concentrations for the humic and fulvic acids differed approximately 2 fold between TAC and SA5 and another factor of 2 between SA5 and SA25. The use of SA above 5 µM suffers from the formation of the species Fe(SA)x (x > 1) that is not electro-active as already suggested by Abualhaija and Van den Berg (2014). Moreover, we found that the reaction between the electro-active and non-electro-active species is probably irreversible. This undermines the assumption of the CLE principle, causes overestimation of [L] and could result in a false distinction into more than one ligand group. For future electrochemical work it is recommended to take the above limitations of the applications into account. Overall, the uncertainties arising from the CLE-AdCSV approach mean we need to search for new ways to determine the organic complexation of Fe in seawater.


2021 ◽  
Vol 18 (19) ◽  
pp. 5265-5289
Author(s):  
Loes J. A. Gerringa ◽  
Martha Gledhill ◽  
Indah Ardiningsih ◽  
Niels Muntjewerf ◽  
Luis M. Laglera

Abstract. Competitive ligand exchange–adsorptive cathodic stripping voltammetry (CLE-AdCSV) is used to determine the conditional concentration ([L]) and the conditional binding strength (logKcond) of dissolved organic Fe-binding ligands, which together influence the solubility of Fe in seawater. Electrochemical applications of Fe speciation measurements vary predominantly in the choice of the added competing ligand. Although different applications show the same trends, [L] and logKcond differ between the applications. In this study, binding of two added ligands in three different common applications to three known types of natural binding ligands is compared. The applications are (1) salicylaldoxime (SA) at 25 µM (SA25) and short waiting time, (2) SA at 5 µM (SA5), and (3) 2-(2-thiazolylazo)-ρ-cresol (TAC) at 10 µM, the latter two with overnight equilibration. The three applications were calibrated under the same conditions, although having different pH values, resulting in the detection window centers (D) DTAC > DSA25 ≥ SA5 (as logD values with respect to Fe3+: 12.3 > 11.2 ≥ 11). For the model ligands, there is no common trend in the results of logKcond. The values have a considerable spread, which indicates that the error in logKcond is large. The ligand concentrations of the nonhumic model ligands are overestimated by SA25, which we attribute to the lack of equilibrium between Fe-SA species in the SA25 application. The application TAC more often underestimated the ligand concentrations and the application SA5 over- and underestimated the ligand concentration. The extent of overestimation and underestimation differed per model ligand, and the three applications showed the same trend between the nonhumic model ligands, especially for SA5 and SA25. The estimated ligand concentrations for the humic and fulvic acids differed approximately 2-fold between TAC and SA5 and another factor of 2 between SA5 and SA25. The use of SA above 5 µM suffers from the formation of the species Fe(SA)x (x>1) that is not electro-active as already suggested by Abualhaija and van den Berg (2014). Moreover, we found that the reaction between the electro-active and non-electro-active species is probably irreversible. This undermines the assumption of the CLE principle, causes overestimation of [L] and could result in a false distinction into more than one ligand group. For future electrochemical work it is recommended to take the above limitations of the applications into account. Overall, the uncertainties arising from the CLE-AdCSV approach mean we need to search for new ways to determine the organic complexation of Fe in seawater.


Robotica ◽  
2021 ◽  
pp. 1-26
Author(s):  
Meng-Yuan Chen ◽  
Yong-Jian Wu ◽  
Hongmei He

Abstract In this paper, we developed a new navigation system, called ATCM, which detects obstacles in a sliding window with an adaptive threshold clustering algorithm, classifies the detected obstacles with a decision tree, heuristically predicts potential collision and finds optimal path with a simplified Morphin algorithm. This system has the merits of optimal free-collision path, small memory size and less computing complexity, compared with the state of the arts in robot navigation. The modular design of 6-steps navigation provides a holistic methodology to implement and verify the performance of a robot’s navigation system. The experiments on simulation and a physical robot for the eight scenarios demonstrate that the robot can effectively and efficiently avoid potential collisions with any static or dynamic obstacles in its surrounding environment. Compared with the particle swarm optimisation, the dynamic window approach and the traditional Morphin algorithm for the autonomous navigation of a mobile robot in a static environment, ATCM achieved the shortest path with higher efficiency.


2021 ◽  
Vol 9 (2) ◽  
pp. 161
Author(s):  
Xun Yan ◽  
Dapeng Jiang ◽  
Runlong Miao ◽  
Yulong Li

This paper proposes a formation generation algorithm and formation obstacle avoidance strategy for multiple unmanned surface vehicles (USVs). The proposed formation generation algorithm implements an approach combining a virtual structure and artificial potential field (VSAPF), which provides a high accuracy of formation shape keeping and flexibility of formation shape change. To solve the obstacle avoidance problem of the multi-USV system, an improved dynamic window approach is applied to the formation reference point, which considers the movement ability of the USV. By applying this method, the USV formation can avoid obstacles while maintaining its shape. The combination of the virtual structure and artificial potential field has the advantage of less calculations, so that it can ensure the real-time performance of the algorithm and convenience for deployment on an actual USV. Various simulation results for a group of USVs are provided to demonstrate the effectiveness of the proposed algorithms.


2021 ◽  
Vol 17 (7) ◽  
pp. 155014772110248
Author(s):  
Miaoyu Li ◽  
Zhuohan Jiang ◽  
Yutong Liu ◽  
Shuheng Chen ◽  
Marcin Wozniak ◽  
...  

Physical health diseases caused by wrong sitting postures are becoming increasingly serious and widespread, especially for sedentary students and workers. Existing video-based approaches and sensor-based approaches can achieve high accuracy, while they have limitations like breaching privacy and relying on specific sensor devices. In this work, we propose Sitsen, a non-contact wireless-based sitting posture recognition system, just using radio frequency signals alone, which neither compromises the privacy nor requires using various specific sensors. We demonstrate that Sitsen can successfully recognize five habitual sitting postures with just one lightweight and low-cost radio frequency identification tag. The intuition is that different postures induce different phase variations. Due to the received phase readings are corrupted by the environmental noise and hardware imperfection, we employ series of signal processing schemes to obtain clean phase readings. Using the sliding window approach to extract effective features of the measured phase sequences and employing an appropriate machine learning algorithm, Sitsen can achieve robust and high performance. Extensive experiments are conducted in an office with 10 volunteers. The result shows that our system can recognize different sitting postures with an average accuracy of 97.02%.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 19632-19638
Author(s):  
Lisang Liu ◽  
Jinxin Yao ◽  
Dongwei He ◽  
Jian Chen ◽  
Jing Huang ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document