An ISM approach to overcome the participation barriers in the waste source separation-a case study: Urmia University Campus.

A procedure developed to identify and facilitate the implementation of waste source separation strategies applicable in higher education centers, as a prerequisite for the expansion of recycling programs. The target materials proper to be separated were selected based on quantitative/qualitative analysis of waste produced on the Nazlou Campus of Urmia University, Iran (as a case study). The barriers to implementation of the program were identified using the interpretive structural modeling (ISM) methodology. Finally, regarding the main obstacles which could be broken down inside the campus complex, an analysis of factors affecting student participation were done. On average, 37.48% of 1.74 tons of waste daily produced on the campus could be recycled. Based on sieve analyses, the categories of non-ferrous metals, glass, and composite packaging have a wider size distribution (i.e., over 150 to under 80 mm) might lead to improper operation of further mechanical separations and be selected as target materials. The weakness of educational programs and persuading the students are considered the main obstacles. A significant relationship was observed between the three training options, namely "installation of announcements," "organizing waste management classes," and "training through holding the exhibition of recycled products" and the student participation in the program (with more emphasis on the last one). Women were estimated to be more likely than men to participate in the program (70 vs 49%). Also, there was a significant relationship between the knowledge and the student's participation. In other words, strengthening public awareness is essential to increase the participation level.

Sensitivity analysis of significant parameters affecting landfill leachate generation rate.

A landfill was designed to evaluate leachate quantity's governing factors using the HELP model. As a case study, the proposed methodology was tested in the Nazlou Landfill, Urmia, Iran. Indeed, the main objective was to illuminate the efficacy of executive parameters defined in the model. Lack of the final cover layer in the pre-closure period affects leachate generation as precipitation enters directly into the waste layers and changes their moisture constituents. Concerning the occurrence of the heaviest precipitation condition in the last 30 years in the pre-closure period, leachate leakage might increase to 0.23 m3/tonne of waste. Due to changes in the layers' initial moisture, the effect of precipitation on leachate generation lasts till the landfill post-closure and would change the drained leachate from 0.083 to 0.089 m3/year-tonne of waste (this amount is generally neglected in the leachate collection system design). During pre-closure, the heaviest precipitation causes an increased generated leachate by 37.59% in the first post-closure year, which is vital especially in landfills with limited capacity treatment plants. The impact of operating conditions involves the landfill leachate generation up to different years. However, over five years of averaging, the precipitation trend was consistent with the leachate leakage. Based on the different scenarios defined regarding the meteorological conditions and design parameters, if the geomembrane layer was removed from the final cover, the leachate quantity will be increased by 79.38%. Replacing 76 cm of dense clay can overcome this challenge.

Landfill Leachate Treatment Through Coagulation-flocculation with Lime and Bio-sorption by Walnut-shell.

Due to the environmental consequences corresponding to leachate penetration, a sequence of inexpensive conventional processes proposed leachate treatment. The main objective was maximizing the COD and heavy metal removal efficiencies while minimizing generated sludge volume and material consumption rate. Walnut-shell adsorption complements lime treatment by eliminating heavy metals and low molecular-weight organic compounds. Samples gathered from Nazlou-landfill, Urmia, Iran. The relative significance of independent variables (lime and walnut-shell dosages and pH) on the removal efficiency was investigated using response surface methodology. By estimating the gradient of relative equations of the experimental results, the ideal direction of independent variable change was found as such increasing COD removal. A new variable called OSVLDR was utilized for measuring the ratio of the observed sludge volume to used lime dosage. The proposed sequence resulted in 43.24% COD removal under optimal conditions (i.e., 6.83, and 25 g/L of lime and walnut-shell dosage and pH values of 6, and 4 for two sets). Furthermore, effective removal in heavy metal concentrations was observed, i.e., 98.17, 67.45, 91.03, and 88.02% for nickel, cadmium, zinc, and lead, respectively. The results showed that a change in variables' amount affects associated costs while making a variation at removal efficiency. Reducing the initial pH value of leachate to 3.50 might decrease the consumed raw materials and OSVLDR value, resulting in a considerable decline in material costs (by 10%). Also, the inactive walnut-shell surface with a more crushing degree was used to reduce costs in walnut-shell set experiments rather than the activated surface.

Energy consumption and relative efficiency improvement of Photo-Fenton - Optimization by RSM for landfill leachate treatment, a case study.

The main objective of this study is to investigate the application of Photo-Fenton process to treat landfill leachate with minimum energy consumption and maximum COD removal efficiencies, simultaneously. Accordingly, an operational assessment of Photo-Fenton process was conducted in terms of variables, namely oxidation pH, [H2O2]/[Fe2+] molar ratio, and Fe2+ dosage. The Central Composite Design (CCD) based on Response Surface Methodology (RSM) was applied for statistical analysis and optimization of target parameters. To assess the rate of energy consumption in Photo-Fenton process, the EEM parameter (Electric Energy consumed per organic Mass removed) was introduced, and the same Fenton experiments were performed to compare the results. Applying UV light in the Fenton process (i.e. Photo-Fenton process) increased COD removal efficiencies up to 10%. The results showed that the Photo-Fenton treatment is capable of removing COD by over 80% of the initial COD (i.e. 17,200 mg/L of AradKooh landfill leachate), applying 195-265 mM iron concentration, [H2O2]/[Fe2+] molar ratio of 15.50-20.55, and the oxidation pH value of 3.75-5.55 (other conditions were oxidation time of 30 min, coagulation pH of 8, and coagulation time of 25 min). The regeneration of Fe(II) from Fe(III) by UV light irradiation resulted in a larger degradation of COD than that of conventional Fenton process, and also reduced the amount of iron catalyst consumption (approximately 25% reduction observed). Furthermore, the cost of energy in Photo-Fenton process could be covered considering lower amounts of sludge generated than conventional Fenton treatment (note that the cost evaluations in current paper were based on batch studies and should be confirmed on full-scale system).

Application of quadratic regression model for Fenton treatment of municipal landfill leachate.

The effectiveness of Fenton process in municipal landfill leachate treatment, as a pre- or post-treatment approach, has been demonstrated. However, no general recommendations of universal validity could be made in the term of optimized conditions affecting Fenton process. At the first stage of this study, collected leachate samples from Aradkooh site, Tehran, Iran, were investigated using one-factor-at-a-time method to find out optimum coagulation pH and flocculation time values. Subsequently, the obtained results in addition to data issued previously by the authors were employed to develop a predictive model of the true response surface, namely chemical oxygen demand (COD) removal efficiency. Finally, the main parameters of Fenton procedure, i.e. initial pH, [H(2)O(2)]/[Fe(2+)] molar ratio, Fe(2+) dosage, and coagulation pH were optimized taking advantage of the above-mentioned quadratic model. The derived second-order model included both significant linear and quadratic terms and seemed to be adequate in predicting responses (R(2)=0.9896 and prediction R(2)=0.6954). It was found that the interaction between initial pH and Fe(2+) dosage has a significant effect on COD removal. While, the optimal [H(2)O(2)]/[Fe(2+)] molar ratio was independent of ferrous ion dosage. The optimum conditions for the maximum COD removal of 50.76% for the parameters of initial pH, [H(2)O(2)]/[Fe(2+)] molar ratio, Fe(2+) dosage, and coagulation pH were found to be 5.8, 8.0, 22,500 mg/L, and 8.7 respectively.