Iranian Journal of

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.

Background and Objective: Knowledge about the quantity of municipal solid waste (MSW) generation plays a key role in formulating policies of waste management. So far, different methods have been applied to estimate the quantity of waste generation. In this study, eight specific forms of mathematical functions were evaluated to predict waste generation by the regression analysis method based on population.
Materials and Methods: The significance test of each model and the existence necessity of predictor parameters were performed using the F- and t-statistic, respectively. The statistical indicators of determination coefficient ( ), adjusted determination coefficient ( ), root mean square error (RMSE), mean bias error (MBE) and mean percentage error (MPE) were used for model’s goodness of fit. The predicted determination coefficient ( ) was calculated to assess the predictive ability of models by method of Leave-one-out cross validation.
Results: The results showed that polynomial models of second order and more are not significant (at 0.01 level) despite good accuracy and are not suitable for long-term prediction. Linear, power and exponential models are best with equal to 0.942, 0.932 and 0.936 and  equal to 0.904, 0.893 and 0.898 respectively. However, the uncertainty was greater in the exponential model.
Conclusion: The status of waste generation was investigated in four scenarios based on growth rate of population (increasing, fixing and decreasing births) at Tehran metropolis in 2021-2051. In all scenarios, annual generation and per capita of waste are increased to 2051. The daily waste generation will increase to 12317 ton in 2051.
 

Background and Objective:  one of the major challenges in urban management in human societies is related to the collection, recycling and disposal of solid waste and sewage. Poor waste management causes pollution of water, soil and air. It will have a major impact on public health. The aim of present study was to investigate the current status and select the best options of management of municipal solid waste in Noor city (Mazandaran, Iran) using life cycle assessment (LCA) methodology.
Materials and Methods: This research considered with five scenarios: 1) Recycling, composting and unsanitary landfilling; 2) Recycling, composting and sanitary landfilling; 3) Recycling, incineration and sanitary landfilling; 4) Recycling, composting and anaerobic digestion, incineration, sanitary landfilling; 5) Recycling and unsanitary landfilling. The required data for life cycle assessment inventory were collected through reviewing resources, preparing of questionnaires, completing the questionnaire by staff, and field inspections.The life cycle inventory was approved by the IWM model.
Results: The scenario 5, which is the current situation in the region, had the highest environmental impact in terms of toxic emissions and ecological indicators among all the scenarios. Energy consumption in the scenarios 1 and 5 was higher than the unsanitary landfilling in comparison to the other scenarios. Accordingly, the scenarios 5 and 4 had the most and the least impact on methane gas production.
Conclusion: According to the ecological index, the fourth scenario including recycling, composting and anaerobic digestion, and sanitary landfilling was the best scenario.  Fifth scenario with the highest pollution load was the worst scenario evaluated.

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.

Background and Objective: Corrosion and precipitation are important indicators of water quality assessment. The aim of this study was to analyze water stability water in Semnan distribution networks.
Materials and Methods: To achieve the purpose, samples were taken from 5 points (3 points of storage tanks and 2 distribution network points) and analyzed for physical-chemical analysis. The concentration of common anions and cations was determined by ion chromatography (IC). The sediment formed in the water distribution network was also investigated for studying its structure and main elements by using X-ray fluorescence spectroscopy (XRF) and induced coupling plasma spectroscopy (ICP). The corrosion and scaling indices, including the Ryznar stability index (RSI), Langelier index (LI), and calcium carbonate precipitation potential (CCPP) were also studied.
Results: According to the obtained results, the quality (physically-chemically) of most of the taken samples lies within the permissible limits of Iran's national standard (1053). However, in terms of total harness all sampling point showed values beyond WHO guidelines for drinking water. Magnesium and sulfate concentrations were also exceeded in one of the reservoirs. The results also showed the main sediment structures were calcium carbonate (calcite) and silica oxide. Moreover, According to the results, the average values of LSI and CCPP represented the scaling due to carbonate calcium nature of water. Water stability analysis indicated major roles of calcium and magnesium bicarbonate formation as temporary hardness and minor roles of magnesium sulfate and chloride as permanent hardness.
Conclusion: According to the results, to prevent water scaling in pipes it is recommended to use lime softening at pH=10 which not only removes temporary hardness but enhances silicate ions removal by co-precipitation with Mg(OH)₂ formed followed by filtration.

Background and Objective: Various aspects including the environmental burdens, social and economic consequences of the waste management(WM) scenarios must be considered to come up with a comprehensive WM plan. Life Cycle Assessment (LCA) approach is a systematic method to quantify the environmental burdens of each WM scenario.
Materials and Methods: This study used an LCA approach to develop a decision support system to analyze different scenarios of WM. Local and global databases were used to develop a comprehensive life cycle inventory database. The model comes with a graphical user interface in Persian to make it easier to use by a wide range of customers. Finally, to evaluate the model, three scenarios were assessed in Karaj city, Iran.
Results: To the best of our knowledge, this model is the first attempt to automate the process of waste management scenarios evaluation in Iran. The model enables users to easily and quickly simulate a wide range of scenarios. All calculations will be carried out by the software in the background and the user only needs to determine his/her scenario of concern which is very easy owing to the user-friend GUI of the software. The model was evaluated by analyzing the current WM in Karaj. The results showed that the waste collection system is the main source of environmental pollution of the WM in Karaj city due to the inefficient system of the waste collection and poor fleet fuel efficiency.
Conclusion: This tool allows users to gather detailed information about the waste management systems. In this way, the user can make informed decisions about the most suitable waste management scenario in a city.

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.
 

Background and Objective: Identifying the quality of non-conventional waters and exploring their optimal utilization are fundamental measures for maintaining public health. This study aims to investigate the effluent quality of the irrigation canals in Pakdasht farms.
Materials and Methods: In this cross-sectional descriptive study, 120 samples were collected from 6 irrigation canals in Pakdasht fields over a period of 5 months. The physicochemical and microbial characteristics of the canal effluents were determined based on the standard methods of water and wastewater tests. The concentration of heavy metals was measured using an ICP device. To determine the possibility of using the effluent of Pakdasht canals for agricultural purposes, the Environmental Protection Organization of Iran and FAO standards were used.
Results: The average concentrations of COD, BOD₅, TSS, TDS, NO₃^-, SO₄^-2, PO₄^-3 parameters were 259, 125, 105, 697, 4.5, 94.4, 13.5 mg/L. Additionally, the average number of total and fecal coliforms in the effluent of the canals exceeded the standard values set by IRNDOE and FAO. The mean pH was 6.97, the electrical conductivity (EC) was 1014 μm/cm, and the turbidity was 76.2 NTU. The detected concentrations of heavy metals were awithin the following ranges: Cr (0.025-0.045 mg/L), Cd (0.0006-0.001 mg/L), Pb (0.0006-0.001 mg/L), Co (0.038-0.059 mg/L), and Ni (0.05-0.06 mg/L), which were roughly lower than the suggested standards. However, both HEI and WWQI indices confirmed that the water was unsuitable for agricultural irrigation.
Conclusion: Based on the comparison of the results of the parameters measured in this study with the environmental and FAO standards, the effluent from the irrigation canals of Pakdasht city is deemed unsuitable for the irrigation of warm-season crops but suitable for fodder and industrial crops.
 

Background and Objective: Personal hygiene and adherence with health protocols in food preparation and distribution centers by operators are essential for controlling the transmission of infectious diseases. This study aimed to investigate the microbial contamination and compliance with health protocols among bakery workers in Mahmoudabad, Mazandaran, in 2020.
Materials and Methods: In a cross-sectional descriptive study, 149 samples were collected from the hands of workers in bakeries in Mahmoudabad. The microbial load was determined using the System Sure Plus device. Additionally, standard checklists, which included questions related to compliance with health protocols in the workplace, were used.  The collected data was then analyzed using SPSS 26 software.
Results: Among the studied samples, 51.1%had a microbial load higher than 30 RLU (Relative Light Units), 28.86%  had a microbial load of 10-30 RLU and 20.13% had a microbial load less than 10 RLU. Based on the results of the checklists, the rates of adherence to hand disinfection protocol, observance of social distancing, use of liquid soap, and use of a mask were 43.6%, 61.7%, 59.7%, and 53.7%, respectively. Additionally, data analysis revealed a significant relationship between business gown usage and microbial contamination on personnel's hands (p = 0.031).
Conclusion: Based on the results, it was evident that the workers' hand hygienewas in a concerning condition, posing a potential threat to their overall well-being. Therefore, individual health education and food safety practices should be improved, and inspections by environmental health monitors should be considered to ensure stricter public health standards.