A high-time resolution study of PM2.5, organic carbon, and elemental carbon at an urban traffic site in Istanbul

Organic Carbon (OC) and Elemental Carbon (EC) were investigated on selected days between January 2017 and January 2018 in an urban area heavily impacted by traffic in Istanbul megacity. 300 PM2.5 samples were collected with a time resolution of 2 h during the daytime between 07:00–19:00. Nighttime samples were collected with a time resolution of 12 h between 19:00–07:00. Samples were collected for three weeks during the winter and one week during the spring, summer, and fall. The daily PM2.5 concentrations exceeded the standard of 35 μg m−3 29% of the time. Air quality was classified as fair (PM2.5>26.4 μg m−3) and unhealthy (PM2.5>39.9 μg m−3) 43% and 20% of the days, respectively. The annual average OC and EC were 11.3 ± 4.91 and 4.1 ± 1.16 μg m−3, respectively. Organic carbon showed strong seasonal variation with high concentrations during the heating season and low concentrations during the summer. Elemental carbon did not show strong seasonality due to the continuous influence of heavy traffic. Diurnal variations of OC and EC were characterized by high concentrations during the morning and evening rush hours, and low concentrations in the middle of the day due to the dilution effect of an increased mixing layer. Formation of secondary organic carbon was uncertain during the summer due to dilution and low primary organic carbon emissions. Concentrations heavily depended on surface wind speed. Average OC concentrations were 56–72% higher at wind speeds lower than 2 m s−1 compared to that at wind speeds higher than 3 m s−1 during fall and winter. Higher EC concentrations (15–56%) were observed at wind speeds higher than 3 m s−1, showing that in addition to traffic emissions, EC was transported from nearby areas. Continuous measurements of high time resolved OC and EC are necessary for the development and evaluation of air pollution mitigation strategies, particularly from combustion sources. © 2019 Elsevier Lt