This study shows the treatment of combined binary mixture of Acid Orange 74 and sugar wastewater with peanut hull and orange peel as low-cost adsorbents. The performance of a combined adsorption-microfiltration process for the color removal is measured and compared using transmittance and absorbance indices at mechanical shaker mix level. This selected treatment procedure is among one of the most economical treatment alternatives to all technologies present now. The parameters studied during this research are analyzed using Langmuir and Freundlich isotherm models on low cost adsorbents. Conclusive results after the treatment are indicated in this paper at their optimum dosages and sizes. This treatment method is applicable in the actual conditions at territory treatment stage.
Transportation sources are a major contributor to air pollution in urban areas, and the role of air quality modeling is vital in the formulation of air pollution control and management strategies. Many models have appeared in the literature to estimate near-field ground level concentrations from mobile sources moving on a highway. However, current models do not account explicitly for the effect of wind shear (magnitude) near the ground while computing the ground level concentrations near highways from mobile sources. This study presents an analytical model (SLINE 1.0) based on the solution of the convective–diffusion equation by incorporating the wind shear near the ground for gaseous pollutants. The dispersion coefficients for stable and unstable atmospheric conditions are based on the near-field parameterization. Initial vertical dispersion coefficient due to the wake effect of mobile sources is incorporated based on a literature review. The model inputs include emission factor, wind speed, wind direction, turbulence parameters, and terrain features. The model is evaluated based on the Idaho Falls field study (2008). The performance of the model is evaluated using several statistical parameters. Results indicate that the model performs well against this dataset in predicting concentrations under both the stable and unstable atmospheric conditions. The sensitivity of the model to compute ground-level concentrations for different inputs is presented for three different downwind distances. In general, the model shows Type III sensitivity (i.e., the errors in the input will show a corresponding change in the computed ground level concentrations) for most of the input variables using the ASTM (American Society for Testing and Materials) method. However, some recalibration of the model constants is needed using several field datasets to make sure that the model is acceptable for computing ground-level concentrations in engineering applications.
Transportation sources are a major contributor to air pollution in urban areas. The role of air quality modelling is vital in the formulation of air pollution control and management strategies. Many models have appeared in the literature to estimate near-field ground level concentrations from mobile sources moving on a highway. However, current models do not account explicitly for the effect of wind shear (magnitude) near the ground while computing the ground level concentrations near highways from mobile sources. This study presents an analytical model based on the solution of the convective-diffusion equation by incorporating the wind shear near the ground for gaseous pollutants. The model input includes emission rate, wind speed, wind direction, turbulence, and terrain features. The dispersion coefficients are based on the near field parameterization. The sensitivity of the model to compute ground level concentrations for different inputs is presented for three different downwind distances. In general, the model shows Type III sensitivity (i.e. the errors in the input will show a corresponding change in the computed ground level concentrations) for most of the input variables. However, the model equations should be reexamined for three input variables (wind velocity at the reference height and two variables related to the vertical spread of the plume) to make sure that that the model is valid for computing ground level concentrations.
The rapid growth of population and fast urbanization has resulted in the reduction of the good quality of available land. Black cotton (BC) soil is one of such problematic soils, though they are very fertile soils, they are not suitable for the foundation of roads and buildings. They are expansive clays with a high potential for shrinking or swelling as a result of changing moisture content. Due to the intensive shrink-swell process, surface cracks appear during dry seasons. A small amount of rainfall, such as 6mm can make these soils impassable for all traffic. About 23% of the area in India is covered by BC soil. To utilize expansive soils effectively, proper ground improvement techniques are to be adopted. One of the most widely used techniques is to stabilize the expansive soil with conventional admixtures like lime, GGBS, cement, and fly ash. In the present study, an attempt is made to modify the engineering properties of black cotton soil. This research work presents the improvement of engineering characteristics of expansive soils using Lime and GGBS as an additive. For experimental work, Lime of 2%, 4%, and 6% used and corresponding 5%, and 10% of GGBS is used. Tests like the California Bearing Ratio (CBR) test, Unconfined Compression Strength (UCS) test, proctor test, Atterberg’s limits performed. After stabilization, it was found that UCS and CBR of soil increased significantly.
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