عنوان مقاله [English]
Particulate matter (PM) or aerosols is a generic term used for a mixture of solid particles and liquid droplets in the atmosphere. Monitoring of natural (dust and volcanic ash) and anthropogenic particles (soot from biomass burning and industrial pollution) has attracted much attention in recent years. These particles can affect cloud properties, Earth's radiation budget, overall atmospheric circulation patterns, surface temperature, and precipitation. The emission of particulate matter and its associated stimuli comes from sources such as energy consumption and biomass burning in urban environments, and these two factors are commonly known as major contributors to PM2.5 concentrations in the atmosphere. However, surface PM2.5 concentrations are related to many factors such as meteorological conditions (eg temperature, wind speed, and relative humidity), land use type, population, and road networks, and so on. In recent years, many studies have been conducted using Aerosol Optical Depth (AOD) satellite measurements, AOD is a very important parameter for predicting Particulate matter (PM) at the Earth's surface in unmeasured locations or periods. AOD determines the amount of light absorbed or scattered by particulate matter. It is, therefore, an important parameter for predicting changes in PM although it may have deficiencies in this regard;
The purpose of this study was to estimate the particulate matter in the atmosphere of Tabriz city using a high spatial resolution weighted regression model (0.1-degree arc, 10 km apart). For estimating PM2.5 in Tabriz during the period 1998 to 2016 will be used combined data from SeaWiFS, MISR, and MODIS data.
As mentioned earlier, meteorological conditions can substantially affect the relation of AOD-PM2.5. Aerosol concentration variability can change particle extinction properties and thus affect visibility. Visibility is an indicator of urban air quality, and particular matter is adversely associated with visibility impairment.
Geographically weighted regression (GWR) is a technique mainly intended to indicate where nonstationary is taking place on the map and that is where locally weighted regression coefficients move away from their global values. GWR is also a local form of linear regression used to model spatially varying relationships. Hourly data of particulate matter less than 2.5 µm (PM2.5) in air pollutants were obtained from Tabriz air quality control stations for 2016-2013. Aerosol Optical Depth (AOD) Data from Three Moderate Resolution Imaging Spectroradiometer (MODIS) of Terra and Aqua Satellites with Two Dark Target (DT) and Deep Blue (DB) Algorithms, Multi-angle Imaging SpectroRadiometer (MISR) and the GeoEye's OrbView-2 (AKA SeaStar) SeaWifs satellite sensor were used. The data were downloaded from the Ladsweb database of The National Aeronautics and Space Administration. Finally, non-parametric Mann-Kendall and Sens' slope estimator methods were used to investigate the trend and trend slope of the PM2.5 in Tabriz.
Results and discussion
Statistical indices of R2 and RMSE for PM2.5 showed that satellite data have high accuracy in estimating PM2.5. The R2 of Long-term time series data was 0.878 and RMSE was 1.330. The annual mean distribution of PM2.5 in Tabriz showed that PM2.5 was higher in western parts of the city than in other areas. Therefore, this area was identified as a polluted area in Tabriz. The PM2.5 in the city of Tabriz from 11.29 to 16.86 µ/m3. The southern and northern regions of the city showed the smallest PM2.5. The western and northwestern regions of the city, especially Tabriz's 4th, 6th and 7th districts, are the main areas of heavy industry, high density of roads and accelerated urban sprawl. This geographic environment has a significant impact on the emissions of primary greenhouse gases and secondary mineral pollutants. Unfavorable weather conditions on the planetary boundary layer (PBL), continuous inversion, and poor wind speed in winter can cause more pollutants to accumulate in a shallow layer. The annual mean long-term PM2.5 of Tabriz city was calculated to be 14.04 µ/m3. During the period of the first study period (1998-2002), PM2.5 was lower than the long average but from the second period onwards the particles with a steep slope in Tabriz have increased as in the third period (2012- 2008) and the fourth period (2016-2013) of particulate matter exceeded the long-term average value.
The highest Z-score of the Man-Kendall test was 2.69 in the western and northern parts of the city. Zones 1 and 2 also showed the lowest Z score of 1.75. The trend slope, which shows an increase in PM2.5 per head per year in Tabriz. According to the results, PM2.5 in Tabriz Variability between 0.250 to 0.25 µ/m3 (year-1). According to the results of Mann-Kendall test, Sense test also showed maximum gradient with 0.225 µ/m3 in western parts of Tabriz (4, 6 and 7 urban areas). The Z-score of the Man-Kendall test was 2.69 in the western and northern parts of the city. Zones 1 and 2 also showed the lowest Z score of 1.75. The trend slope, which shows an increase in PM2.5 per head per year in Tabriz.
In this study, Seawifs, MISR and MODIS satellite data were used to estimate PM2.5 using Geographic Weighted Regression (GWR). The results showed that the western and northwestern regions, along with significant parts of central Tabriz, have high PM2.5 values. In Tabriz, the lack of proper ventilation of wind speeds caused by urban buildings, along with the meteorological conditions of the local area, can be attributed to the high accumulation of particles. The least polluted areas were identified in the south and southeast of Tabriz. These areas are highly favorable for atmospheric dispersal due to low greenhouse gas emissions and meteorological conditions. The northern areas of Tabriz have a high PM2.5 due to the possible existence of farmland. However, economic and social factors such as industry, traffic, construction and burning of fossil fuels are direct sources of air pollution in Tabriz. But what is known is that socio-economic factors are less effective than natural factors in the city. Climatic conditions usually have a direct impact on PM2.5 in various aspects of wind-induced diffusion, precipitation of particulate matter, accumulation of particles in the air, and formation of secondary particles.
Keywords: PM2.5, Geographic Weighted Regression (GWR), Air quality control, Tabriz.