M Shaygan; Marzieh Mokarram
Abstract
Industrial activities and urban traffic contribute to increased air pollution in large cities, resulting in a rise in various diseases among the population. Consequently, studying and investigating polluted areas is crucial for effective city management. This study aims to examine the air pollution levels ...
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Industrial activities and urban traffic contribute to increased air pollution in large cities, resulting in a rise in various diseases among the population. Consequently, studying and investigating polluted areas is crucial for effective city management. This study aims to examine the air pollution levels in Tehran, Isfahan, and Qom cities, focusing on NO2, CO2, CO, and CH4 pollutants, during two distinct periods: pre-COVID-19 (2018-2019) and during COVID-19 (2020-2021), across all four seasons. By employing the Pearson correlation method and RBF neural networks (radial basis function neural network), the relationship between temperature and pollutants was explored. The findings reveal higher levels of air pollution in Tehran and Isfahan compared to other regions. Moreover, the study demonstrates a significant reduction in pollution during the COVID-19 era compared to the pre-COVID-19 period. Additionally, the regression analysis highlights a strong correlation between temperature increase and pollution levels (R2=0.981). Furthermore, the RBF method exhibits high accuracy in predicting air pollution levels (R2 = 0.85, RMSE = 0.08). In conclusion, this research underscores the urgent need for comprehensive measures to mitigate air pollution, particularly in highly polluted areas, and emphasizes the role of temperature as a crucial factor affecting pollution levels.
Mehran Shaygan; Marzieh Mokarram
Abstract
Due to the fact that droughts can affect both water quality and quantity, the purpose of this study is to determine the effect of droughts on water quality and quantity in Northern Fars province, Iran, based on drought indicators. The drought indices PCI, TVDI, and NDVI are used to study drought from ...
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Due to the fact that droughts can affect both water quality and quantity, the purpose of this study is to determine the effect of droughts on water quality and quantity in Northern Fars province, Iran, based on drought indicators. The drought indices PCI, TVDI, and NDVI are used to study drought from 2000 to 2020. Also, the kriging method is used to generate zoning maps of elements in water (Ca, Cl, EC, K, Na, Mg). Then, using the neural network (MLP) method, the amount of elements in the water is predicted based on drought indices. Based on the values of the drought indicators, the trend of drought changes in the region is increasing from 2000 to 2020, with the southern areas of the region experiencing a more acute drought than the rest of the region. In addition, the zoning map of the elements in water indicated that salt concentrations are higher in the southern parts than in the northern parts. Correlation between drought indices and the amounts of elements in water showed that Ca has a high correlation (R2= 0.820) with TVDI index, and also Cl, EC, K, Na, and Mg have significant correlations (R > 0.8) with the index. Using drought indicators, MLP results for predicting water quality status show that southern regions have more solutes and lower water quality. Furthermore, the R2 values of the model for predicting the elements Cl, EC, K, Na, Mg, TDS, TH using PCI index equal to 0.85 and for Ca using TVDI index equal to 0.71, which indicates high accuracy.
Mehran Shaygan; Marzieh Mokarram
Abstract
Fars province has a shortage of surface water resources due to its location in arid and semi-arid regions in Iran. Therefore, in order to exploit groundwater resources, determining water quality is very important. Due to the importance of the subject in this study, the aim is to determine the quality ...
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Fars province has a shortage of surface water resources due to its location in arid and semi-arid regions in Iran. Therefore, in order to exploit groundwater resources, determining water quality is very important. Due to the importance of the subject in this study, the aim is to determine the quality of the southern regions of Shiraz in Fars province. To prepare zoning maps of the sampled points, the Inverse distance weighting (IDW) method was used. Then, to homogenize each of the prepared layers, the fuzzy method was used. In this method, by defining the membership function for each of the zoning maps, the data were placed between zero and one based on the degree of importance they have for water quality. Finally, the analytic network process (ANP) method was used to weigh the layers and prepare the final water quality map. The results showed that about 80% of the study area has good water quality. While about 4% of the region (parts of the north and east) has poor quality in terms of drinking.