A new approach to the prediction of PM10 concentrations in Central Anatolia Region, Turkey

Atmospheric Pollution Research

GamzeOzel¹ 

关键词: Air pollution;    air pollutant;    meteorology;    particulate matter (PM);    stochastic process;   

DOI  :  10.5094/APR.2015.082

学科分类：农业科学（综合）

来源: Dokuz Eylul Universitesi * Department of Environmental Engineering

【 摘 要 】

Environmental pollution control is one of the most important goals in pollution risk assessment. In this sense, modern and precise tools that allow scientists to quantify and predict air pollution are of particular interest. In this study, we describe an air quality evaluation in terms of particulate matter having a diameter < 10 μm (PM10), using a gamma–Poisson process. PM10 measurements from 2007 to 2013 at 24 air quality monitoring stations of Ministry of Environment and Urbanization (Turkey), was used to predict air pollution levels in Central Anatolia Region of Turkey. We assume that the number of PM10 peaks follows a Poisson process and PM10 amount of each peak fits a gamma distribution. The findings indicate that daily average of number for the threshold exceedance of PM10 concentration is 1.3 for all monitoring stations. The probability of exceedance the PM10 concentration threshold once a day is 0.35 for all monitoring stations. The results also show that the probabilities of total PM10 concentrations exceeding threshold are rapidly decreasing after 158 μg/m3 which will occur in one day. The average of daily total PM10 concentration is 148 μg/m3, the average of monthly total PM10 concentration is 4 437 μg/m3, and the average of yearly total PM10 concentrations is 53 984 μg/m3. It is found that there is a moderate correlation between the number of threshold exceedances and the total PM10 concentrations in Central Anatolia Region. Thus, it was concluded that gamma–Poisson process could be promising for air pollutant prediction for a given period of time.

【 授权许可】

CC BY