Global NEST Journal

This paper analysis the contents and variation of heavy metals in wet and dry deposition in Changji (Xinjiang, China) revealed their reducing regularity for heavy metals in atmosphere in arid area. Samples (including 84 dry deposition samples and 16 wet deposition samples) were collected from January 2016 to December 2016, and the contents of heavy metals (Ni, Cu, Cd and Pb) were analyzed by AA-7000 atomic absorption spectrophotometer. The dry deposition fluxes of Ni, Cu, Cd and Pb are 3.70 mg/( m2.a), 4.81 mg/( m2. a), 0.53 mg/( m2•a) and 22.74 mg/( m2•a), respectively; the wet deposition fluxes of Ni, Cu, Cd and Pb are 0.77mg/( m2•a), 3.25mg/( m2•a), 0.04mg/( m2•a) and 0.11mg/( m2•a), respectively. Each of the four heavy metals deposition fluxes during heating period was higher than non-heating period, especially for Pb and Cd, which is mainly due to the emission of coal combustion for heating. During sampling periods, the ratio of wet deposition flux to total for Ni, Cu, Cd and Pb are 17.21%, 40.33%, 7.67% and 0.48%, respectively; the wet deposition flux is far less than dry deposition, especially for Pb. The rate of dry deposition is lower than wet deposition, however dry deposition plays an important role in scavenging heavy metals in arid region. Arid region has a low intensity and frequency of rain event, heavy metals were mainly scavenging by dry deposition attribute to its continuous and dependable process. Dry deposition has much more environmental effect on heavy metal in arid region.

A novel method that utilizes a combination of statistical and clustering techniques is presented in order to classify statistically independent heavy rainstorm events and create a limited number of temporal distribution curves. These curves represent the centers of many unitless cumulative rainstorm events and express the temporal distribution patterns in a probabilistic way. The whole process includes the necessary steps from importing raw precipitation time series data to producing the initially unknown optimal number of representative curves. These hyetographs can be used for stochastic simulation, water resources planning, water quality assessment and global change studying. The present type of analysis is fully unsupervised, as no empirical knowledge of local rainfalls is implicated or any arbitrary introduction of quartiles for grouping as is the case in the pertinent literature. An example using data from a Greek Water Division illustrates that the proposed method produces clusters with superior internal structure and temporal distribution curves that are not coming from the same distribution, in contrast to the results using Huff’s curves classification.

The main aim of this study is to investigate the simultaneous azo dye removal and bioelectricity production at sulfate reducing conditions in continuously-fed dual-chamber microbial fuel cell (MFC). Initially, optimization of sulfate reduction was performed at different sulfate concentrations (100-900 mg/L) and the constant COD of 1000 mg/L, corresponding to COD/sulfate ratio of 1.11-10, and varying HRT of 12-48h. Optimum COD/sulfate ratio and HRT was found 1.66 and 36h, respectively, corresponding to 96% COD removal, 44% sulfate removal and yielded about 24 W/m2 power density. Further, MFC was fed with azo dye containing (50-1000 mg/L) simulated wastewater to evaluate dye removal performance of sulfate reducing bacteria. Addition of azo dye slightly enhanced the power production to 26 W/m2, the highest value obtained during our study, compared to azo dye lacking study periods. Sulfate and COD removals were adversely affected at azo dye concentrations over 300 mg/L and 150 mg/L, respectively. Additionally, color removal performance of MFC was excellent however, chemical azo dye reduction out-competed with enzymatic reduction at high azo dye levels (>500 mg/L) leading to a poor sulfate (<15%) and COD (<45%) removal and recovery of azo dye reduction efficiency to 91%.

Smoothed Particle Hydrodynamics (SPH) is a promising simulation technique in the family of Lagrangian mesh-free methods, especially for flows that undergo large deformations. Particle methods do not require a mesh (grid) for their implementation, in contrast to conventional Computational Fluid Dynamics (CFD) methods. Conventional CFD algorithms have reached a very good level of maturity and the limits of their applicability are now fairly well understood. In this paper we investigate the application of the SPH method in Poiseuille and transient Couette flow along with a free surface flow example. Algorithmically, the method is viewed within the framework of an atomic-scale method, Molecular Dynamics (MD). In this way, we make use of MD codes and computational tools for macroscale systems.