Investigation of Tbilisi City Atmospheric Air Pollution with PM in Usual and Emergency Situations Using the Observational and Numerical Modeling Data

Pollution of the Tbilisi atmospheric air with PM2.5 and PM10 in usual and pandemic situations by using the data of 5 stationary observation points is investigated. The values of the statistical characteristic parameters of PM in the atmosphere of Tbilisi are analyzed and trend graphs are constructed. By means of analysis of pollution levels in the quarantine and usual periods the proportion of vehicle traffic in pollution of city is estimated. Experimental measurements of PM2.5, PM10 in the atmosphere have been carried out in different districts of the city and map of the distribution of their concentrations were constructed. It is shown that maximum pollution values are recorded in the city center and along major motorways. It is shown that the average monthly concentrations vary in the range of 0.6-1.6 Maximum Permissible Concentration (MPC). Average daily values of concentration vary at 2-4 days intervals. The distribution of PM10 generated as a result of traffic is numerical modeled. The modeling results are compared with the observation data.

Carcinogenic Polycyclic Aromatic Hydrocarbons in Urban Air Particulate Matter

An assessment of the air quality of Győr (Hungary) was performed by determining the ambient concentrations of PM10-bound carcinogenic polycyclic aromatic hydrocarbons (cPAHs) in different seasons. A high volume sampler was used for the collection of ambient aerosol particles, and the associated cPAH compounds (benzo[a]pyrene (BaP), benzo[a]anthracene, benzofluoranthene isomers, indeno[123-cd]pyrene and dibenzo[ah]anthracene) were analyzed by a gas chromatographic method. Higher mean concentrations of total cPAHs were detected in samples collected in winter (9.62 ng/m3) and autumn (2.69 ng/m3) compared to spring (1.05 ng/m3) and summer (0.21 ng/m3). The calculated BaP toxic equivalent concentrations have also reflected that the local population appears to be exposed to significantly higher cancer risk in the heating seasons. Moreover, the concentration levels of cPAHs determined in this study were compared to other Hungarian urban sites.

Risk Assessment of Particulate Matter (PM10) in Makkah, Saudi Arabia

In recent decades, particulate matter (PM10) have received much attention due to its potential adverse health impact and the subsequent need to better control or regulate these pollutants. The aim of this paper is focused on study risk assessment of PM10 in four different districts (Shebikah, Masfalah, Aziziyah, Awali) in Makkah, Saudi Arabia during the period from 1 Ramadan 1434 AH - 27 Safar 1435 AH. Samples were collected by using Low Volume Sampler (LVS Low Volume Sampler) device and filtration method for estimating the total concentration of PM10. The study indicated that the mean PM10 concentrations were 254.6 (186.1 - 343.2) μg/m3 in Shebikah, 184.9 (145.6 - 271.4) μg/m3 in Masfalah, 162.4 (92.4-253.8) μg/m3 in Aziziyah, and 56.0 (44.5 - 119.8) μg/m3 in Awali. These values did not exceed the permissible limits in PME (340 μg/m3 as daily average). Furthermore, health assessment is carried out using AirQ2.2.3 model to estimate the number of hospital admissions due to respiratory diseases. The cumulative number of cases per 100,000 were 1534 (18-3050 case), which lower than that recorded in the United States, Malaysia. The concentration response coefficient was 0.49 (95% CI 0.05 - 0.70) per 10 μg/m3 increase of PM10.

Daily and Seasonal Changes of Air Pollution in Kuwait

This paper focuses on assessment of air pollution in Umm-Alhyman, Kuwait, which is located south to oil refineries, power station, oil field, and highways. The measurements were made over a period of four days in March and July in 2001, 2004, and 2008. The measured pollutants included methanated and nonmethanated hydrocarbons (MHC, NMHC), CO, CO2, SO2, NOX, O3, and PM10. Also, meteorological parameters were measured, which includes temperature, wind speed and direction, and solar radiation. Over the study period, data analysis showed increase in measured SO2, NOX and CO by factors of 1.2, 5.5 and 2, respectively. This is explained in terms of increase in industrial activities, motor vehicle density, and power generation. Predictions of the measured data were made by the ISC-AERMOD software package and by using the ISCST3 model option. Finally, comparison was made between measured data against international standards.

Estimation of Forest Fire Emission in Thailand by Using Remote Sensing Information

The forest fires in Thailand are annual occurrence which is the cause of air pollutions. This study intended to estimate the emission from forest fire during 2005-2009 using MODerateresolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites, experimental data, and statistical data. The forest fire emission is estimated using equation established by Seiler and Crutzen in 1982. The spatial and temporal variation of forest fire emission is analyzed and displayed in the form of grid density map. From the satellite data analysis suggested between 2005 and 2009, the number of fire hotspots occurred 86,877 fire hotspots with a significant highest (more than 80% of fire hotspots) in the deciduous forest. The peak period of the forest fire is in January to May. The estimation on the emissions from forest fires during 2005 to 2009 indicated that the amount of CO, CO2, CH4, and N2O was about 3,133,845 tons, 47,610.337 tons, 204,905 tons, and 6,027 tons, respectively, or about 6,171,264 tons of CO2eq. They also emitted 256,132 tons of PM10. The year 2007 was found to be the year when the emissions were the largest. Annually, March is the period that has the maximum amount of forest fire emissions. The areas with high density of forest fire emission were the forests situated in the northern, the western, and the upper northeastern parts of the country.