List of Articles Air pollution

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  1 - Short-term prediction of carbon monoxide gas concentration in the air of Ahvaz city using artificial neural network analysis
  Maryam Kavosi سیما سبزعلی پور hossein fathian
  Introduction: Air pollution in cities is one of the most critical environmental problems, representing a constant and severe threat to both the health and hygiene of society and the environment. The primary air pollutants include nitrogen oxides, with a particular empha More

  Introduction: Air pollution in cities is one of the most critical environmental problems, representing a constant and severe threat to both the health and hygiene of society and the environment. The primary air pollutants include nitrogen oxides, with a particular emphasis on nitrogen dioxide, sulfur oxides, especially sulfur dioxide, hydrocarbons, carbon monoxide (CO), carbon dioxide, and suspended particles. Ahvaz, a metropolis in Iran, stands out as one of the most polluted cities. Effective environmental management, particularly in addressing air pollution, is of paramount importance. This research aims to predict the concentration of CO pollutants in Ahvaz city for the first seven days of 2015. Materials and Methods: Based on previous studies, meteorological variables including weather, air temperature and wind speed were selected as gas input titles in the network for gas prediction. CO gas was procured in 2014 through the Environmental Protection Organization of Ahvaz city. In order to develop the Multilayer Perceptron (MLP) neural network, Neuro Solution5 software was used to create the neural network, 70% of the data was used for training (validation), 15% for testing, and the remaining 15% for validating the results of the network. is used. was used. Results and Discussion: In order to determine the best MLP network structure for short-term prediction of CO gas concentration, different structures were considered in terms of the number of intermediate layers, the type of network training algorithm, the type of transfer function, the number of intermediate layer neurons and the number of repetitions (Epoch) of training. The results showed that the MLP network with a structure of 1-5-3 (that is, 3 input neurons, 5 neurons in the middle layer and one neuron for the output layer) with 1500 repetitions of training per Tansig transfer function (Tansant Sigmoid) and Traingdm training algorithm (reduction gradient with momentum), is the best MLP network. In addition, the values of NSE, RMSE and MAE statistical indices for the network training stage are equal to 0.72, 0.22 and 0.15 respectively. Conclusion: Air pollution, the primary environmental challenge in Ahvaz, arises from the intersection of traffic and the oil industry. Its impacts on health and the environment necessitate comprehensive investigation. In this study, an MLP network was employed to predict CO gas concentration values in the air of Ahvaz city. The findings demonstrate that the network's accuracy and performance in forecasting CO gas concentration are at an optimal level. As this research progresses, it is recommended to extend the prediction to other gaseous pollutants and to employ optimization algorithms for determining the optimal structure of the artificial neural network Manuscript profile
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  2 - Detecting the Route and Source of Atmospheric Pollutants Movement in High-Level Air Pollution Periods by Utilizing MODIS and HYSPLIT Model in Tehran Metropolis
  Motahhareh Zargari Abbas Mofidi Azar Zarrin
  10.22034/jest.2020.24033.3314
  Background and Objective: Air pollution is one of the significant problems that have become one of the main issues. In this study, we focus on detecting the route and source of atmospheric pollutant movement in high-level air pollution periods in Tehran. Method: Air po More

  Background and Objective: Air pollution is one of the significant problems that have become one of the main issues. In this study, we focus on detecting the route and source of atmospheric pollutant movement in high-level air pollution periods in Tehran. Method: Air pollution data, Terra MODIS satellite image data, and FNL data were used. The PSI calculated high-level air pollution periods for PM10 and O3. Moreover, the origin of pollutants was detected by the HYSPLIT model and satellite images. HYSPLIT model determined the origin of widespread pollution. It could detect them with the backward method in three levels, which included 10, 1500, and 5000 meters. Some maps were produced for satellite images and HYSPLIT models drawn in GIS. Findings: In the extratropical pattern, the dust from Syria, northeast to south-east Saudi Arabia, central, northern and southern Iraq and parts of Turkey have affected Tehran. According to HYSPLIT model outputs, at a lower level of the atmosphere and the middle level of the atmosphere, not only the local situation but also the regional situation had a considerable role. At the upper level of the atmosphere, environmental pollution could become into Tehran by streams. In the compound pattern, Saudi Arabia, Iraq, Syria, Jordan, and some parts of Turkey had an important function. In the HYSPLIT model, the North-East and North-West of Iran have attempted to influence Tehran in the lower level of the atmosphere. In the middle level of the atmosphere, the local situation is more remarkable. At the upper level of the atmosphere, the origin of dust was western to eastern parts of Iraq and the northeast part of Iraq. Further, the dust on the north-eastern of Syria, Jordan, and parts of Turkey is more notable. Conclusion: These maps were categorized into two main synoptic patterns, including extratropical and intricate patterns. Manuscript profile
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  3 - Prediction of Carbon Monoxide Concentration in Tehran using Artificial Neural Networks
  Hamid Reza Jeddi Rahim Ali Abbaspour Mina Khalesian Seyed Kazem Alavipanah
  Background and Objective: Nowadays, air pollution is one of the most important problems almost all over the world. There are many strategies to control and reduce air pollution, one of which is prediction of this event and getting ready to deal with the negative effects More

  Background and Objective: Nowadays, air pollution is one of the most important problems almost all over the world. There are many strategies to control and reduce air pollution, one of which is prediction of this event and getting ready to deal with the negative effects of it. The aim of this study is to provide a multi-layer structure of artificial neural networks (ANN) for predicting of carbon monoxide pollution at subsequent 24 hours in Tehran metropolis. Method: To predict the amount of CO emissions in near future (subsequent 24 hours), wind speed and direction, temperature, relative humidity, and barometric pressure characteristics are used as meteorological data, and concentration of carbon monoxide is considered as a pollution parameter. To eliminate the noise of data, wavelets transform method and determining the threshold with normal distribution are used before training the ANN. Finally, two neural networks as two general models are proposed and used for modelling. Findings: The results show that the correlation coefficient, index of agreement, accuracy of prediction, and root mean square error for model no. 1 with duplicate data are 0.9012, 0.915, 0.848, and 0.1012 and for model no. 2 with duplicate data are 0.9572, 0.978, 0.963, and 0.0385 respectively. Moreover, the results of listed parameters for model no. 1 with new data are 0.9086, 0.89, 0.885, and 0.0825 and for model No. 2 with new data are 0.8678, 0.928, 0.932, and 0.1163 respectively. Conclusion: Results showed that there is a good agreement between predicted and observed values, hence the proposed models have a high potential for air pollution prediction. Manuscript profile
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  4 - The spatial relationship between climatic factors and air pollution in the last 10 years of Tabriz city
  Fahimeh Banasaleh Mohammad Ebrahim Ramazani Ziba Beheshti
  Air pollution poses a significant threat to many cities in Iran, with Tabriz the bustling metropolis, being particularly affected. Factors such as rapid population growth, rural migration, industrial expansion, vehicular density, topographical features and natural facto More

  Air pollution poses a significant threat to many cities in Iran, with Tabriz the bustling metropolis, being particularly affected. Factors such as rapid population growth, rural migration, industrial expansion, vehicular density, topographical features and natural factors have collectively contributed to Tabriz becoming one of Iran’s most polluted cities. Beyond human-related factors, geographical factors including location, topography, and temperature inversions also play a crucial role in exacerbating air pollution in Tabriz. In this research, descriptive research methods drawing from meteorological and air pollution data sources were employed to investigate the spatial relationship between climatic factors and air pollution in Tabriz. By collecting and analyzing information from meteorological stations in Tabriz and air quality measurement stations related to Tabriz, we created integrated maps using Geographical Information System (GIS) software. These maps visually depicted pollution distribution and zoning. According to the results of the research, a significant spatial relationship and correlation exist between meteorological parameters and air pollution parameters. Additionally, the distribution of air pollution parameters across the surface of Tabriz city reveals that the highest pollution levels, attributed to polluting gases such as SO2, NO2, O3, and CO, occur in the western and central parts of the city. Conversely, suspended particles contribute to the most pollution in the eastern side of Tabriz. Furthermore, the seasonal quality index indicates that summer and spring experience the least air pollution, while autumn and winter exhibit the highest levels. Manuscript profile
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  5 - Evaluating the Relationship between Air Pollution and Economic Growth Based on Kuznets' Environmental Curve Hypothesis (Case Study: Asian Countries)
  Iman danaeifar
  One of the important, substantial and significant issues in recent decades has been the issue of economic growth and the preservation of environmental quality in human societies. Although humanity has long been aware of the importance of the environment in its life, the More

  One of the important, substantial and significant issues in recent decades has been the issue of economic growth and the preservation of environmental quality in human societies. Although humanity has long been aware of the importance of the environment in its life, the last decades of the twentieth century should be regarded as the culmination for the environmental issues. In this study, the relationship between air pollution and economic growth for 12 Asian countries during the period 1990 to 2015, with an emphasis on the Kuznets environmental curve has been investigated using panel data. The Research results indicate that per capita GDP, annual growth of urban population and energy consumption of fossil fuels have a positive and significant effect on per capita carbon dioxide emissions, and also the squared per capita GDP has a negative and significant effect on per capita carbon dioxide emissions. Therefore, according to the results of the research, Kuznets' environmental hypothesis is true in these countries. Manuscript profile
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  6 - Empirical Analysis of the Relationship between Air Pollution and Public Health Expenditures - A Dynamic Panel Data Approach
  maryam fattahi Abbas Esari hosein sadeghi hosein asgharpour
  Abstract This study intends to investigate the effect of air pollution on public health expenditures and to identify the most important factors affecting the relationship between air pollution and public health expenditures. The scope of the study is the developing cou More

  Abstract This study intends to investigate the effect of air pollution on public health expenditures and to identify the most important factors affecting the relationship between air pollution and public health expenditures. The scope of the study is the developing countries during 1995-2011. For this purpose, a dynamic panel and Generalized Method of Moments are used. The empirical results indicate that there is a robust and significant relationship between air pollution, per capita income, urbanization, government size, aging dependency and public health expenditure and unemployment have a negative but significant effect on public health expenditures. Also, per capita income, urbanization and education have significant effect on the relationship between air pollution and public health expenditures. That is, the effects of air pollution on health expenditures in the countries with higher per capita income, higher urbanization rates and lower education levels are significantly higher than other countries.  Manuscript profile
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  7 - The Relationship Between Air Pollutionand Anatomical and Development of the Laurus nobilis L. Plant and Two Effective Enzymes on This Relationship
  Hamideh Sanaeirad Ahmad Majd Hossein Abbaspour Maryam Peyvandi
  Abstract This study aimed to investigate the effect of air pollutants, which is the stressful factors and by human intervention, on some of anatomical and development of the Laurus nobilis L. plant and its relation with Peroxidase (POD) and polyphenol oxidase (PPO) enzy More

  Abstract This study aimed to investigate the effect of air pollutants, which is the stressful factors and by human intervention, on some of anatomical and development of the Laurus nobilis L. plant and its relation with Peroxidase (POD) and polyphenol oxidase (PPO) enzymes. Therefore, perfectly similar samples in terms of age and storage conditions were chosen from two clean area (Jamshidieh Park in northern Tehran) and contaminated area (Besat Park located in southeast of Tehran and near to the South Terminal) and in one day and in every region 4 bushes were harvested as 4 repetitions. Leaf area, types and numbers of stomata, sectioning of leaf, stems and roots was done and the amount of activity of peroxidase and polyphenol oxidase enzymes was investigated. Enzymes'activity, the number of stomata per mm2 of leaf and leaf level in samples of contaminated area was increased significantly (pr<0.01) and anatomical and development revealed changes,suggesting the activation of protective mechanisms in these plants under air pollution stress, and also observed responses are regarded as adaptive and compensative to the adverse effects of air pollution . Manuscript profile