جستجوی مقالات مرتبط با کلیدواژه "pm2.5 pollutant" در نشریات گروه "پزشکی"

High concentrations of particulate matter-25 (PM2.5) have been the cause of the unhealthiest days in Tehran, Iran in recent years. This study was conducted with the aim of the spatio-temporal analysis of traffic volume and its relationship with PM2.5 pollutant concentrations in Tehran metropolis, Tehran during 2015-2018, using the Geographic Information System (GIS).

In this study in different regions of Tehran, the Inverse Distance Weighting (IDW) model was used for prediction and zoning of the PM2.5 concentrations and traffic volume during the period 2015-2018. In addition, the association between the PM2.5 concentrations and traffic volume was determined based on the Geographically Weighted Regression (GWR) model.

The findings showed that the southern and southwestern regions of Tehran had the highest PM2.5 pollutant concentration (annual average more than 40 μg/m3), while the eastern and northern regions had the highest traffic volume. In addition, based on the GWR model, the eastern regions were found to have the highest local R2 values (between 0.36 and 0.70).

In most regions of Tehran, no strong association can be found between high concentrations of PM2.5 and traffic volume. However, based on the findings of this study we cannot reject the relationship between traffic volume and PM2.5 pollutant but postulate other sources to be the main reason for the high concentrations of PM2.5. Thus, in the first step, these sources should be identified, followed by adopting strategies for traffic volume control and reduction aiming at having a cleaner air in Tehran.

Tehran, as the largest and most populous city in Iran, has encountered many problems, of which air pollution is the most common. In recent years, PM2.5 has been the cause of the unhealthiest days in terms of air pollution in Tehran; For this purpose, the present study was conducted with the aim of Spatio-temporal analysis of PM2.5 pollutant in the Tehran metropolis during the years 2014-2017 using GIS.

In this study, Inverse Distance Weighting (IDW) and HotSpots methods have been used to predict and zoning of PM2.5 concentrations during four consecutive years (2014-2017).

The results of hotspot analysis and Getis-Ord-Gi index showed that the southern and southwestern regions with a confidence level above 90% and a concentration of more than 50 μg/m3 are the most polluted areas. And to a lesser extent, the western and central areas are next.; Also, the concentration of PM2.5 pollutants shows an increasing trend from north to south and east to west.

South, southwest, west, and center are the most polluted areas; However, the present study only shows the zoning of PM2.5 concentration and does not identify the various factors and the contribution of each of them in the production of this pollutant; And it is necessary to conduct studies to identify sources and their contribution to control and reduce the concentration of PM2.5 in the Tehran metropolitan.

PM2.5 particulate matter is one of the major air pollutants in cities of Iran especially Tehran, which threaten health of Iranian people due to numerous health hazards. Risk levels of these particulate depend on spatial-temporal changes in the air. Hence, this study aimed spatial-temporal analysis of PM2.5 concentration in Tehran's air using the Geographic Information System.
Material and Hourly data of PM2.5 concentration was collected in 2016-2017 from 38 air pollution monitoring stations and was analyzed monthly, seasonally and annually. Inverse Distance Weighting interpolation method was used in order to present concentration maps of the PM2.5. Existence of spatial autocorrelation in data was analyzed by Moran's I and data clustering was accomplished by Global and Local Moran's I and finally Getis-Ord-Gi index was used to determine hot spots of this pollutant in Tehran.
Results of concentration maps of PM2.5 and global and local spatial autocorrelation with PM2.5 concentration hot spot analysis showed that the concentration of this pollutant has an incremental mode from the north to the south of Tehran so that areas in south of Tehran especially Ray stations were the most polluted areas in Tehran. In addition, results showed that the concentration of this pollutant was more in the two colder seasons so that most hot spots were identified in these seasons.
Using several spatial analyses simultaneously showed that Tehran can be separated into two parts of non-polluted north and polluted south, which this issue should be considered by urban planners to improve Tehran's air quality.