Total Mercury Concentrations in Lake and Streams Sediments Related to Wet-Area Coverage and Geogenic Sources within Upslope Basins

2018 ◽  
Vol 27 (3) ◽  
pp. 221-248
Author(s):  
Mina Nasr ◽  
Paul A. Arp
2021 ◽  
Author(s):  
Chris Moneyron ◽  
Moe Sakamoto ◽  
Mo Rastgaar ◽  
Nina Mahmoudian
Keyword(s):  

2015 ◽  
Vol 17 (1) ◽  
pp. 109-120
Author(s):  
Zahra Khoshnood ◽  
Reza Khoshnood

Abstract In 2009, 36 fish were sampled from two stations in the Karoon River near an industrial site. Two species of fish, Barbus grypus and Hypophthalmichthys molitrix were analyzed for total mercury (Hg) concentration in liver and muscle tissues. The average concentrations of total Hg in liver of B. grypus were 18.92 and 10.19 μg.g-1 in stations 1 and 2 respectively. The corresponding values for total Hg in edible muscle of Barbus grypus were 8.47 and 0.08 μg.g-1. The average concentrations of Hg in the liver of H. molitrix were 25.49 and 12.52 μg.g-1 in stations 1 and 2 respectively. The values for H. molitrix were 11.88 and 3.2 μg.g-1 in station 1 and station 2 respectively. The results showed that the bioavailability of Hg has increased considerably after industrialization and that these values were higher than the standard values as a result of anthropogenic activities in the region.


Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2400
Author(s):  
Ziyong Zhang ◽  
Xiaoling Xu ◽  
Jinqiang Cui ◽  
Wei Meng

This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.


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