Amir Zarei; Sirvan Zarei; Vahid Kakapor; Mohamad Hossein Vazeri; Eqbal Mohammadi; Hossein Aghighi
Abstract
Background and Purpose: Air quality control is an inevitable issue at the forefront of national concerns. The aim of this study was to predict the daily concentration of PM2.5.Materials and methods: According to the objective, the type of research can be considered practical, and the statistical population ...
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Background and Purpose: Air quality control is an inevitable issue at the forefront of national concerns. The aim of this study was to predict the daily concentration of PM2.5.Materials and methods: According to the objective, the type of research can be considered practical, and the statistical population of the research includes meteorological and pollution measuring stations within the 22 districts of Tehran. However, the statistical sample (synoptic geophysical station and Tarbiat Modares measuring station) was selected using a non-random sampling method. The desired statistical year for the study included the daily data from the selected stations for one year. Eleven input variables were used, which included meteorological data from the geophysical synoptic station (maximum and minimum temperature, minimum and maximum relative humidity, rainfall, maximum wind speed, and wind direction) and pollution data of PM2.5 concentration from the Tarbiat Modares station (daily concentrations of PM2.5 and the previous day). The support vector machine (SVM) model was used for prediction in this step.Results: The model was able to predict the daily concentration values of the PM2.5 pollutant for the upcoming days with a detection coefficient R² = 0.611 and RMSE = 10.87. In the second method, the support vector machine (SVM) model was combined with principal component analysis (PCA) to reduce the number of variables and perform modeling.Conclusion: The results of this study show that the performance of the combined model is superior to the previous model, as the coefficient of determination R² increased to 0.65 and the error value decreased to 10.37 RMSE (root mean square error). This hybrid model (PCA-SVM) can assist city managers and decision-makers in controlling and reducing the amount of PM2.5 pollutants.
Amir Zareei; Vahid Kakapour; Jahangir Abedi Koupai; Reza Ramezani; Sadegh Talebi; Azadeh Nekouei esfahani; Sirvan Zareei
Abstract
Background and Aim: Waste production is a natural consequence of human life and mismanagement of solid waste can result in environmental hazards. Determination of an appropriate location to sanitary landfill site is one of the most common ways to deal with this crisis. The purpose of this research is ...
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Background and Aim: Waste production is a natural consequence of human life and mismanagement of solid waste can result in environmental hazards. Determination of an appropriate location to sanitary landfill site is one of the most common ways to deal with this crisis. The purpose of this research is to find an appropriate location for landfill site in Qorveh city due to its specific location in terms of agriculture and mining. Materials and methods: The research method in this study was descriptive, analytical and quantitative. In order to locate the landfill, firstly effective information layers in landfill site study (land use layer, rivers, roads, conservation areas, soils, groundwater, morphology, …) were identified and developed using the collected data from organizations and information centers. Finally,(GIS), (AHP) and (WLC) were used to integrate the maps. Results: The Analytical Hierarchy Process is one of the most efficient techniques designed for multi-criteria decision making, as it enables the formulation of complex problems. Due to limitations, appropriate landfill site options were identified using GIS and used as input data for the hierarchical analysis process. Distance from population centers (towns and villages), distance from surface and groundwater sources are the most important indicators. Conclusion: By combining two methods of multivariate Weighted Linear Combination (WLC) and Analytical Hierarchy Process(AHP) model, the most priority areas were determined with concentration on distance from population centers (towns and villages), distance from surface and groundwater resources,. After extracting the criteria information layers from the maps and prioritizing the 4-storey location ranges, it became clear that the northern direction of Qorveh city with an area of 210 hectares is the most suitable area for sanitary landfill of solid wastes.