Showing 10 results for Moeinaddini
M Moeinaddini, M.h Tahari Mehrjardi, N Khorasani, A Danekar, A.a Darvishsefat, F Shakeri,
Volume 4, Issue 4 (2 2012)
Abstract
Background and Objectives: Solid waste municipal landfill can have injurious effect on society health, economic and environment. Therefore, spread evaluation in locating landfill is necessary to identifying the best places. The purpose of this paper is locating landfill for solid waste municipal for center of Alborz province.
Materials and Method: In this paper, suitable areas are identified for land filling solid waste municipal by weighted linear combination and cluster analysis in 20 years period. Thus, suitable areas were weighted by FAHP method. Those weights were used for ranking areas by DEA technique.
Result: Results showed among five landfill alternatives for solid waste municipal for center of Alborz province, alternative 1 is the best for land filling. This place is just 7 percent of total suitable places.
Conclusion: The approach are used in this article (combination method of fuzzy analytic hierarchy process & Data envelopment analysis) can be suitable for locating in other areas because when an option add or delete option ranking is not different with previous
N Sistani, M Moeinaddini, N Khorasani, Ah Hamidian, Ms Ali-Taleshi, R Azimi Yancheshmeh,
Volume 10, Issue 1 (6-2017)
Abstract
Background and Objective: Urban and industrial development has increased concentration of heavy metals in the environment. The goal of this study was to assess the impact of Kerman steel complex on their surrounding soil by heavy metals.
Materials and Methods: This study was a snapshot and its type was descriptive-analytical research. Heavy metals contents from 60 soil samples (top soil, 0-15 cm) near two Steel Complexes were analyzed using flame atomic absorption spectroscopy (AAS). Source identification and pollution degree indices including enrichment factor (EF) and its percentage (EF%), geo-accumulation index (Igeo), contamination factor (Cf), degree of contamination (Cd) and modified degree of contamination (mCd) were calculated to assess the soil pollution level.
Results: The average concentration of Ni, Zn, Fe, Pb, Cr and Cd were 9.98, 54.38, 15063.33, 20.86, 3.54 and 0.038 mg/kg, respectively. The order of average EF for heavy metals was Pb > Zn> Cd> Fe> Ni> Cr. Cf index also showed that 90% of the samples were moderately to significantly polluted with lead element. The results of EF% indicated that Fe (68.18%) had higher enrichment than others. The average values of Cd and mCd indices were 2.90 and 0.48, respectively, that showed low degree of pollution.
Conclusion: In this study, Pb and Cd concentration were related with activities of the steel complexes and other metals had a combination of natural and anthropogenic emission sources. The steel complexes should plan to reduce pollutants emission to their environment.
S Mazloomi, A Esmaeili - Sari, N Bahramifar, M Moeinaddini,
Volume 10, Issue 2 (9-2017)
Abstract
Background and Objective: Street dust is considered as one of the important sources of particulate matters and heavy metals in the atmosphere. The goal of this study was to assess the heavy metals pollution in street dust of Tehran and evaluate their ecological risk.
Materials and Methods: The sampling of street dust was carried out in two areas at the east and west of Tehran. After preparation of samples, the concentration of heavy metals was measured by ICP-MS. The pollution level of heavy metals in the street dust was assessed using geo-accumulation index (Igeo), pollution index (PI), integrated pollution index (IPI), enrichment factor (EF) and ecological risk index (RI).
Results: The results of the calculations of the indices showed that the street dust in both studied areas was non-polluted with Li, Al, Ti, V, Cr, Mn, Fe, Ni, Sr and Ba. The origin of these elements was mainly natural sources. However, Cd, Cu, As, Zn, Sn and Pb had medium to high level of contamination. These elements had a very high to extremely high enrichment in both areas. Their origin was mainly anthropogenic sources. The ecological risk index indicated a moderate ecological risk for the east and a low ecological risk for the west area.
Conclusion: The higher level of lead in the East is the main reason of higher ecological risk of this area. Therefore, the heavy metals pollution of the street dust, especially lead and its enterance into the environment, should be considered in this area.
R Rafiee, M Moeinaddini, N Khorasani,
Volume 11, Issue 1 (6-2018)
Abstract
Background and Objective: The aim of this study was to assess the sensitivity and uncertainty analysis of a mass balance model to estimate the rate of aerobic processes in a landfill.
Materials and Methods: Monte Carlo simulation is a common method to evaluate uncertainty of the results of a model. Here, we used a Monte Carlo (MC) simulation. The data obtained from the experiments were used as a baseline. Considering a uniform Probability Distribution Function (PDF) within ±15% deviation, samples were taken from the baseline data. Using randomly selected inputs, model was executed for 1000 iterations and outputs were evaluated. Then, the total Sobol index for each input parameter was determined. The uncertainty of each output was presented by standard error and means observed in MC simulation.
Results: The results of this study revealed that while the uncertainty for the rate of composting process was mainly originated from the measured value of CO2 flux, the evaluated value for the rate of anaerobic digestion process was highly influenced by the value measured for CH4 emission flux. All inputs contributed equally to the uncertainty in the evaluated values for the rate of methane oxidation process. Although a variability of 15% was assumed for the model inputs, the mean value for the outputs from Monto Carlo simulations were close to those obtained by using base values that were in most cases within ±10% limit.
Conclusion: The majority of the uncertainty in the outputs came from the variability in the measurement of the flux of CH4 and CO2. The error in these parameters, however, can be minimized by increasing frequency and replicates of gas samples as these parameters are measured directly for each location.
Mazaher Moeinaddini, Seyed Hassan Mousavi, Zohreh Isakhanbeygi, Somayeh Heidari,
Volume 13, Issue 3 (11-2020)
Abstract
Background and Objective: One of the most important goals for urban environmental management system is the monitoring of air quality. Allocating optimum air quality monitoring stations (AQMS), is a key factor in establishing effective and accurate air quality monitoring program. The objective of this study was to determine optimal allocation for AQMS in Karaj.
Materials and Methods: Based on two stages approach, at first, the suitability map was obtained by WLC method. For AQMS implementation, municipal districts were ranked. The extracted alternatives were graded using TOPSIS. In the next stage, the position of preferred sites were investigated by site visiting and detailed criteria. Finally, the AQMS locations were introduced.
Results: Ten suitable stations were suggested based on population and number of municipal districts. During the first stage important criteria such as distance from roads and street cross-section were weighted and standardized. The distance from roads and green space were the lowest and highest important criteria, respectively. The lowest and highest ranks for AQMS implementation were Nos. 9 and 3 districts, respectively. During the first phase 30 alternatives were obtained. At the second stage, 10 best alternatives were selected following field observation and considering implementation criteria (eg. distance from trees, cross section and pollutants emission sources).
Conclusion: In this study, at the first stage the preferred alternatives were determined. In the next stage the best alternatives for AQMS implementation were selected considering reasonable time and effort. The suggested approach could be used to implement AQMS for other areas.
Azad Mollaei, Reza Rafie, Mazaher Moeinaddini, Sayyed Hossein Khazaei,
Volume 14, Issue 2 (9-2021)
Abstract
Background and Objective: The purpose of this study was to use the HELP model to estimate the leachate generation rate and its pattern in a landfill located in the semi-arid region of Iran.
Materials and Methods: The input data for the model were collected through fieldwork. To evaluate the accuracy of outputs, the actual amount of leachate production has been measured on-site for 10 months. In addition, sensitivity analysis was conducted to find out the most important parameters in leachate generation in the landfill.
Results: The results showed that the model was able to estimate the rate of leachate generation with an accuracy of 75.5% and the correlation between the model's estimated values and actual values was 60%. In addition. the sensitivity analysis showed that the most important factors affecting the leachate generation in the landfill were waste moisture content and rainfall, respectively.
Conclusion: The model showed satisfactory performance in the prediction of leachate generation in the arid area. The model showed that the moisture content of the waste significantly contributes to leachate generation in Karaj landfill and therefore, it is suggested to identify and implement procedures to reduce the moisture content of the waste at the source of generation.
Seyyed Reza Karimi, Nabiollah Mansouri, Lobat Taghavi, Mazaher Moeinaddini,
Volume 15, Issue 2 (8-2022)
Abstract
Background and Objective: The city of Tehran is always exposed to adverse consequences due to the establishment of various sources of heavy metals. Therefore, the purpose of this study is to identify the types of heavy metals in airborne particles and the origin of heavy metals in the 21st district of Tehran.
Materials and Methods: According to the EPA standard, 5 stations from District 21 of Tehran were selected for sampling. Using the ASTM D4096 method and using a high volume sampling pump, 50 samples of total airborne particles were collected. The samples were transferred to the laboratory and the concentration of heavy metals was measured by ICP-OES. The UNMIX source model was used to identify heavy metal sources.
Results: The average concentration of heavy metals in 1400 is a decreasing trend including Li according to the concentration of heavy metals in the air in the SPECIATE database, the role of light vehicle sources was 47 percent 34 percent on the street and 18 percent at the airport.
Conclusion: The source of light vehicles exhibited the highest share of emissions and the element aluminum showed the highest concentration among heavy metals in Region 21. Therefore, the UNMIX source model can correctly identify index elements and priority sources for contaminant control.
Sayyed Hossein Khazaei, Mazaher Moeinaddini, Reza Rafiee, Nematollah Khorasani, Melanie L. Sattler,
Volume 15, Issue 3 (12-2022)
Abstract
Background and Objective: Various models have been developed to predict methane generation and emissions from landfills. Due to their simplicity, the minimum number of required data, and the accuracy of the outputs, First-order decay are the most common models to predict methane generation in landfill,. Three important parameters in modeling landfill gas generation using a first-order model are the total weight of waste buried in the landfill, the methane generation potential, and the methane generation rate constant. The purpose of this research was to accurately estimate the parameters of the first-order model and to optimize it for estimating methane generation in the landfill and also to develop the ILGAM software.
Materials and Methods: ILGAM model consists of two submodels: 1) the gas generation sub-model and 2) the methane oxidation sub-model. The methane oxidation sub-model is based on the MOT model. The gas generation sub-model is based on a first-order equation with an emphasis on the contribution of the aerobic process in the estimation of the ultimate methane potential of waste. The parameters of the equation were modeled using the latest available results in the literature. To evaluate the model, the actual methane emission and methane oxidation were measured in the Karaj landfill. The results of the model, along with a few common models, were compared with actual data obtained from the Karaj landfill.
Results: The ILGAM model predicted the gas emission from the Karaj landfill with an error of 5.8%. In contrast, LandGem, IPCC and CLEEN models predicted the methane gas emission from the Karaj landfill with an error of 74.4%, 40.2%, and 27.1%, respectively.
Conclusion: When compared to other models, the ILGAM model estimated the closest values to actual measurements for methane emission and methane oxidation in the Karaj landfill. Owing to its user-friend Graphical User Interface (GUI), the model can be easily executed in a wide range of landfills by entering a few easy-to-measure data in the field.
Seyyed Shahram Naghibzadeh, Mazaher Moeinaddini, Mehdi Zafaranieh,
Volume 16, Issue 3 (12-2023)
Abstract
Background and Objective: The economic evaluation is a tool for decision-making based on data that helps to select and prioritize waste management components and their implementation based on economic criteria. The purpose of this study was a comprehensive economic evaluation of the waste management components by life cycle costing assessment (LCC) , Net Present Value index (NPV), and Internal Rate of Return (IRR).
Materials and Methods: The cost of each waste management component, was calculated by LCC for one tonne of waste in. The efficiency of each waste management component was obtained using the NPV and IRR indicators.
Results: The results showed that recycling with 260%, and then composting with 40%, have the highest economic returns and the ability to return capital. The sensitivity analysis showed the profitability of these two processes despite the changes of ±30% in the influential calculation parameters.
Conclusion: In this study, comprehensive economic evaluation showed that using LCC, NPV, and IRR with their sensitivity analysis, simultaneity can have an important role in waste management decision-making.
Ehsan Mohammad Hassani, Reza Rafei, Mazaher Moeinaddini, Niki Aghapour,
Volume 17, Issue 1 (6-2024)
Abstract
Background and Objective: One of the largest sources of methane emissions is landfills, and various models have been developed to predict landfill methane production and emissions. The main goal of this research is to utilize the inverse Gaussian model to estimate g methane greenhouse gas emissions and model it using field data. This study introduces a simple method to estimate the amount of methane emissions based on ambient methane concentrations.
Materials and Methods: In this research, the methane emission rates from landfill were estimated for warm (July) and cold (February) seasons using a sampling campaign from 27 stations and standard inverse Gaussian dispersion equations. Monte Carlo simulation was also employed. To determine the model, an optimization-based method, along with inverse scattering modeling, was utilized to process surface emission monitoring data.
Results: The model results indicated during the cold (February) and warm (July) seasons, the methane emission rates were estimated at 1696.99 and 16.53 g/s, respectively. These findings confirm that the methane production and emission during the cold season were lower than in the warm season, likely due to reduced temperature and bacterial activity.
Conclusion: The method used in this study, the inverse Gaussian dispersion model, can be applied to estimate methane gas emission rates from other landfills. However, it necessitates the permanent recording of data and the use of daily or weekly averages in calculations to mitigate potential errors and enhance the accuracy of modeling.
