The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM2.5, PM10, NOx, and SO2. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NOx and SO2 reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.
This study evaluates the benefits of advanced waste management practices in unlocking waste-to-energy opportunities within the solid waste industry. The key drivers of sustainable waste management practices, specifically with respect to packaging waste-to-energy technology options are discussed. The success of a waste-to-energy system depends significantly on the appropriateness of available technologies, including those that are well established as well as those that are less so. There are hard and soft interventions to be considered when packaging an integrated waste treatment solution. Technology compatibility with variation in feedstock (waste) quality and quantities remains a key factor. These factors influence the technology reliability in terms of production efficiencies and product consistency, which in turn, drives the supply and demand network. Waste treatment technologies rely on the waste material as feedstock; the feedstock varies in quality and quantities depending on several factors; hence, the technology fails, as a result. It is critical to design an advanced waste treatment technology in an integrated approach to minimize the possibility of technology failure due to unpredictable feedstock quality, quantities, conversion efficiencies, and inconsistent product yield or quality. An integrated waste-to-energy approach offers a secure system design that considers sustainable waste management practices.
The introduction of more stringent pollution regulations, in relation to financial and social pressures for sustainable development, has pressed toward limiting the volumes of industrial and domestic effluents discharged into the environment - as well as to increase the efforts within research and development of new or more efficient wastewater treatment technologies. Considering both discharge volume and effluent composition, wastewater generated by the textile industry is rated as the most polluting among all industrial sectors. The pollution load is mainly due to spent dye baths, which are composed of unreacted dyes, dispersing agents, surfactants, salts and organics. In the present investigation, the textile dye wastewater was characterized by high color, chemical oxygen demand (COD), total dissolved solids (TDS) and pH. Electrochemical oxidation process for four plate electrodes was carried out at five different current intensities, out of which 0.14A has achieved maximum percentage removal of COD with 75% and 83% of color. The COD removal rate in kg COD/h/m2 decreases with increase in the current intensity. The energy consumption increases with increase in the current intensity. Hence, textile dye wastewater can be effectively pretreated by electrochemical oxidation method where the process limits objectionable color while leaving the COD associated with organics left for natural degradation thus causing a sustainable reduction in pollution load.