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Showing 2 results for Khazaei

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.

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.
 


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