Removal of Copper from Acid Mine Drainage (AMD) or Acid Rock Drainage (ARD)

Acid mine drainage is wastewater from a mine having a low pH and an elevated level of dissolved heavy metals. These metals are harmful to aquatic, animal and human life. This paper looks at the removal of copper from acid mine drainage using ion exchange to less than 1 mg/l. A weak acidic cation resin was used. Spectrophotometric determination of copper with sodium diethyldithiocarbamate was used to determine the copper concentrations in the treated water. Using regression analysis, the experimental results gave a correlation coefficient of 0.977 and a coefficient of determination of 99.5%. Results indicated that the higher the flows rate the shorter the period after which the copper concentration in the treated water reaches 1 mg/l. At pH 3.85 and 5.09, the resin performed better and at pH above 6.62 and between pH 3.0 and below the resin’s does not perform well. The higher the resin height the greater is the resin exchange capacity and the longer it takes for the copper concentration to reach 1 mg/l in the treated water. The higher the wastewater copper concentration the shorter the time it takes the resin to reach 1 mg/l. The results for this experiment indicated that acid mine drainage can be treated well by ion exchange resins, but it is also very important to establish suitable operating conditions.

Surface Water Quality Response to Land Use Land Cover Change in an Urbanizing Catchment: A Case of Upper Chongwe River Catchment, Zambia

The Upper Chongwe River Catchment has recently been overexploited for water resources with increased complaints by various water users about the deteriorating quality of surface water within the sub-catchment. This study was motivated by the need to investigate and understand the response of surface water quality to land use land cover (LULC) change due to urbanization. Water samples, collected at 9 sampling sites from 2006 to 2017, were analyzed for water quality using the weighted arithmetic water quality index and trend using the Mann-Kendall statistics. LULC change is detected and analyzed in ERDAS Imagine 2014 and ArcGIS 10.4 using 2006 Landsat 5 TM and 2017 Landsat 8 OLI imageries. The relationship between LULC change and water quality was performed with multiple regression analysis and Pearson correlation. The results reveal that Built-up area, Grassland and surface water increased by 5.48%, 13.34% and 0.03% respectively while Agricultural land and Forest Land decreased by −13.41% and −5.42% respectively. The water quality index ranged from 43.04 to 110.40 in 2006 and from 170 to 430 in 2017 indicating a deterioration in the quality of surface water from good to unsuitable for drinking at all the sampled sites. Built-up/bare lands exhibited a significant positive correlation with EC (R2 = 0.61, p ≤ 0.05), turbidity (R2 = 0.69, p ≤ 0.05), TDS (R2 = 0.61, p ≤ 0.05), Cl (R2 = 0.62, p ≤ 0.05) and a significant negative correlation with NH4 (R2 = −0.729, p ≤ 0.05). Agriculture exhibited a significant positive correlation with turbidity (R2 = 0.71, p ≤ 0.01) and Fe (R2 = 0.75, p ≤ 0.01. Forest cover correlated negatively with most of the water quality parameters apart from Fe, DO, NO3 but was not statistically significant. Grassland had a significant negative correlation with temperature (R2 = −0.68, p ≤ 0.05). Clearly, urbanization has made a disproportionately strong contribution to the deterioration of surface water quality indicating that intensive anthropogenic activities exacerbate water quality degradation. These results provide essential information for land use planners and water managers towards sustainable and equitable management of limited water resources.

Assessment of the TFM in predicting the onset of turbulent fluidization

Accurate prediction of the onset of turbulent fluidization still remains elusive owing to the dependence of the transition velocity on several factors including measurement methods and interpretation of results. In this work, numerical simulations using the two fluid model (TFM) are performed in an attempt to predict the regime change reported by Gopalan etal.(2016) in a small scale pseudo-2D gas-solid fluidized bed containing Geldart D particles. Various time and frequency domain analyses were applied on predicted absolute and differential pressure time series data to reveal the bed dynamics. Numerical predictions of the transition velocity, Uc are in reasonably good agreement with experimental results from the small scale challenge problem. The literature correlations completely fail to predict the transition velocity for the system considered in this work. This work thus provides a different approach for validating the CFD model against experimental measurements.

CFD-DEM simulation of Small-Scale Challenge Problem 1 with EMMS bubble-based structure-dependent drag coefficient

In this study,the energy minimization multi-scale(EMMS)/Bubbling model is coupled with the computational fluid dynamics/discrete element method(CFD-DEM)model via a structure-dependent drag coefficient to simulate the National Energy Technology Laboratory(NETL)small-scale challenge problem using the open-source multiphase flow code MFIX.The numerical predictions are compared against particle velocity measurements obtained from high-speed particle image velocimetry(HSPIV)and differential pressure measurements.The drag-reduction effect of the EMMS bubble-based drag coefficient is observed to significantly improve predictions of the horizontal particle velocity and granular temperature when compared to several other drag coefficients tested;however,the vertical particle velocity and pressure fluctuation characteristic predictions are degraded.The drag-reduction effect is characterized by a reduction in the sizes of slugs or voids,as identified through spectral decomposition of the pressure fluctuations.Overall,this study shows great promise in employing drag coefficients,developed via multi-scale approaches(such as the EMMS paradigm),in CFD-DEM models.