Evaluation of Removal and Adsorption Isotherms of Zinc and Copper from Municipal Solid Waste Leachate Using Clinoptilolite Adsorbent

Introduction and Purpose: Heavy metals are among the most important pollutants in leachate waste, causing serious health risks for humans through entering the food chain and reaching the top of food pyramid. Therefore, this study aimed to evaluate the efficacy of modified clinoptilolite in the removal of copper and zinc ions from landfill leachate and modeling of adsorption isotherms and reactions.Methods: This cross-sectional in vitro study was conducted to test waste landfill leachate as a true sample for four seasons in 2014 in Bam, Iran. Natural zeolite (clinoptilolite), modified with 2 M HNO3 solution, was used to remove copper and zinc. Experiments were conducted as batch systems, in which the effects of pH, adsorbent dosage, and contact time on the adsorption of heavy metals in municipal waste landfill leachate by clinoptilolite (as soil amendment) were investigated. Afterwards, the adsorption isotherms of each adsorbent were demonstrated.Results: In total, the removal efficency of zinc in the optimum pH=5, equallied time=120 min and Adsorbent dosage of 120g/l was reached 92%. Adsorption isotherms indicated that the capacity of this adsorbent was higher in zinc, compared to copper, and adsorbents were absorbed with higher energy. The adsorption process was based on Langmuir’s equations (isotherm type II) (R2=0.99).Conclusion: According to the results, adsorption capacity of clinoptilolite was high for copper and zinc and based on isotherm equations, adsorption took place with higher energy. It was concluded that this method could be used for the removal of these metals due to its high removal efficiency. Therefore, it is recommended that further studies be conducted to evaluate the possibility of removal of other heavy metals with this method

Measurement and modeling of particulate matter concentrations: Applying spatial analysis and regression techniques to assess air quality

This paper presented the levels of PM2.5 and PM10 in different stations at the city of Sabzevar, Iran. Furthermore, this study was an attempt to evaluate spatial interpolation methods for determining the PM2.5 and PM10 concentrations in the city of Sabzevar. Particulate matters were measured by Haz-Dust EPAM at 48 stations. Then, four interpolating models, including Radial Basis Functions (RBF), Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and Universal Kriging (UK) were used to investigate the status of air pollution in the city. Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) were employed to compare the four models. The results showed that the PM2.5 concentrations in the stations were between 10 and 500 μg/m3. Furthermore, the PM10 concentrations for all of 48 stations ranged from 20 to 1500 μg/m3. The concentrations obtained for the period of nine months were greater than the standard limits. There was difference in the values of MAPE, RMSE, MBE, and MAE. The results indicated that the MAPE in IDW method was lower than other methods: (41.05 for PM2.5 and 25.89 for PM10). The best interpolation method for the particulate matter (PM2.5 and PM10) seemed to be IDW method. • The PM10 and PM2.5 concentration measurements were performed in the period of warm and risky in terms of particulate matter at 2016. • Concentrations of PM2.5 and PM10 were measured by a monitoring device, environmental dust model Haz-Dust EPAM 5000. • Interpolation is used to convert data from observation points to continuous fields to compare spatial patterns sampled by these measurements with spatial patterns of other spatial entities