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Yayın The statistical analysis of the relationship between particulate matter with traffic and meteorological parameters(Işık Üniversitesi, 2023-06-07) Panhwar, Mehran; Kesten, Ali Sercan; Işık Üniversitesi, Lisansüstü Eğitim Enstitüsü, İnşaat Mühendisliği Yüksek Lisans ProgramıParticulate matter (PM) pollution has become a pressing concern due to its detrimental effects on human health and the environment. Understanding the relationship between PM and meteorological parameters, as well as the impact of traffic, is crucial for effective pollution control strategies. This thesis aims to analyze these relationships by employing an Ordinary Least Squares (OLS) regression model for PM1.0, PM2.5, and PM10 concentrations. A comprehensive dataset of PM measurements, meteorological data, and traffic-related variables is collected from various monitoring stations over a specific time period. Meteorological parameters such as temperature and wind speed, are obtained from corresponding meteorological stations, while traffic data includes vehicle counts and road characteristics. The initial analysis reveals significant associations between PM concentrations, meteorological parameters, and traffic impact. The OLS regression model is used to investigate the individual and combined effects of meteorological variables and traffic on PM levels. The results show that temperature, highway traffic and wind speed changes the PM concentrations, indicating that higher temperatures and traffic contribute to increased PM1.0, PM2.5, and PM10 levels. Wind speed demonstrates a negative correlation, suggesting that higher wind speeds are associated with lower PM concentrations due to dispersion effects. Furthermore, the model reveals that traffic-related variables, significantly influence PM pollution, with increased traffic leading to higher PM concentrations. The findings of this study provide valuable insights into the complex relationships between PM pollution, meteorological parameters, and traffic impact. These finding can assist policymakers and environmental agencies in formulating targeted measures to mitigate PM pollution, such as implementing traffic management strategies and improving urban planning. Moreover, the OLS regression model developed in this study can serve as a useful tool for predicting PM levels based on meteorological conditions and traffic patterns, facilitating proactive pollution control efforts.Yayın Spatial-Temporary analysis of Istanbul air pollution during the pandemic using Google Earth Engine and Google community mobility reports(Gök, Murat, 2023-06-30) Çavdaroğlu, Gülsüm Çiğdem; Arık, Ahmet OkanThe Covid-19 pandemic has brought drastic changes to people's daily life and environmental characteristics. To control the pandemic, all governments have implemented particular policies for their countries and imposed restrictions that affect people's daily life. The traffic index has decreased in many countries and cities depending on the restrictions. Therefore, restrictions in many countries and cities have positively impacted air quality. However, the opposite has also been observed in metropolitan cities. In this study, the change in the air quality of Istanbul, which is accepted as Turkey's largest metropolitan city, has been examined. First, the spatio-temporal distribution of air pollutants (NO2, CO, and SO2) has been analyzed using Sentinel-5P NRTI satellite images. Then six independent variable groups (traffic index of Istanbul, daily deaths in Istanbul, Google community mobility reports of Istanbul, fuel prices, stringency index of Turkey, two logical attributes regarding the Covid-19 restrictions and in-class education) were collected and combined to analyze the correlations between these variable groups and air pollutant concentrations. According to the spatial distribution graphs, there is a tendency to decrease NO2, CO, and SO2 pollutant concentrations in Istanbul when the restrictions are applied in Turkey. There was no significant relationship between the decrease in community mobility in Istanbul and pollutant concentrations, although an increase in air quality has been observed in many cities due to the restrictions of the Covid-19 pandemic.Yayın Economic dynamics of air pollution in Türkiye and Pakistan: an empirical assessment of the Environmental Kuznets Curve and pollution-led growth(IGI Global, 2026) Taşbaşı, Aslı; Akhtar, MahamTürkiye and Pakistan, despite differing levels of economic development, face similar macroeconomic challenges such as income inequality, inflation and debt. Both countries also experience environmental pressures from industrialization and rapid urbanization, with air pollution emerging as a critical concern affecting economic productivity and sustainable development. This study conducts a comparative analysis of air pollution in Türkiye and Pakistan from 1980 to 2023, using the Autoregressive Distributed Lag (ARDL) bounds testing approach to examine the short and long run relationships between air pollution, urbanization, industrialization, energy consumption and macroeconomic policies. The analysis tests the Environmental Kuznets Curve (EKC) for Türkiye and the pollution-led growth hypothesis for Pakistan. Findings reject the EKC for Türkiye but confirm pollution-led growth in Pakistan, offering insights for effective environmental regulation and sustainable development strategies.
