Stone powder (SP) produced from masonry mills has been treated as a specific waste and rarely used for environmental purposes. In this study, we tested its potential as an adsorbent to remove arsenic (As) and lead (Pb) from water. The single-solute sorption isotherms for As(V) and Pb(II) onto SP and chitosan-coated SP (CSP) were investigated. Several sorption models, such as the Langmuir, Freundlich, and Dubinin–Radushkevich (DR) models, were used to analyze the adsorption features. The results demonstrated that As and Pb were successfully adsorbed onto SP and CSP, indicating that SP and CSP had potential as adsorbents of As and Pb. The maximum adsorption capacities of SP and CSP for Pb were 22.8 and 54.5 times higher than those for As, respectively. Chitosan coating increased the adsorption potential in Pb adsorption by 5% but decreased it in As adsorption. The adsorption potential also depended on the pH and temperature. The adsorption amount of As increased with pH but that of Pb decreased as pH increased. In addition, the ln b in the Langmuir model increased with 1/T (K), indicating that the adsorption of As and Pb occurred exothermically and spontaneously.

Adsorption kinetics of As and Pb onto composite beads synthesized with stone powder, chitosan, and maghemite (SCM beads) with weight ratio of 1:1:0.5 were investigated in batch mode. Several kinetic models such as pseudo-first order kinetic model (PFOKM), pseudo-second order kinetic model (PSOKM), two compartment first order kinetic model (TCFOKM), and modified two compartment first order kinetic model (MTCFOKM) were utilized to analyze the kinetics. Although the beads had low specific surface area and pore volume, MTCFOKM, one of two compartment models, could predict the most accurately because the As and Pb were adsorbed onto at least two kinds of adsorption sites such as functional groups in chitosan and Fe in maghemite. In MTCFOKM, both the fast adsorption fraction (f1’) and the fast adsorption constant (k1’) for Pb were higher than those for As. Therefore, the equilibrium time (teq) for Pb adsorption was shorter than that for As adsorption, indicating that Pb adsorption was more affinitive than As adsorption onto SCM beads (especially maghemite). Column study with a bed column reactor packed with the SCM beads was also conducted. For column study, the effect of flow rate and pore volume on removal efficiency of As and Pb was also investigated. Three models such as the Thomas, Adams-Bohart (A-B), and Yoon-Nelson (Y-N) models were used to fit the column experimental data to analyze the breakthrough curves and the saturation time. Both Thomas and Y-N models were most appropriate. Conclusively, the SCM beads are suitable for adsorption treatment of As and Pb from contaminated groundwater and are particularly effective in Pb removal.

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In this paper, we derive the threshold of the maximum likelihood (ML) decision rule, assuming the reliability In this paper, we propose a maximum likelihood detector measure can be modeled with Rayleigh probability density for reliable sound source localization system. It is based on fnction (pdf) and show that the performance of the making a measure of reliability of estimation results. The reliability measure in a fixed talker environment and a reliability can be reduced from waterbed effect of source moving talker environment. localization algorithm. If the calculated reliability measure This paper organized as follows. In Section 2, we introduce has a lower value than a predefined threshold, the estimated the GCC-PHAT DOA estimator. In Section 3, we discuss direction-of-arrival (DOA) is regarded as a wrong result and the definition of the reliability measure. In Section 4, we subsequently discarded. We determine the threshold for derive the threshold for reliable source detection with ML reliable estimate selection using maximum likelihood rule. decision rule. In Section 5, we discuss the experimental Some experiments show that the proposed method can reject results. Finally, we present our conclusions in Section 6.