Air pollution in an urban street canyon: Novel insights from highly resolved traffic information and meteorology

Abstract

Urban air pollution is a health issue of increasing importance due to globally emerging urbanization. The main sources of ambient air pollution in cities are road traffic, industries and domestic heating. To examine the temporal patterns and sources of air pollutants, this study used fast-response air quality measurements in combination with highly resolved traffic information. The temporal dynamics of NO x and the particle number concentration (PN 10 ) were similar to the diurnal and weekly courses of the traffic density. On very short timescales, the real-world peak ratios of NO x and particulate matter ≤10 μm diameters (PM 10 ) exceeded the predicted pollutant emission ratios of the Handbook for Emission Factors for Road Transport (HBEFA) by a factor of 6.4 and 2.0, respectively. A relative importance model revealed that light-duty vehicles (LDVs) are the major relative contributor to particle number concentrations (PN 10 ) (38%) despite their low abundance (4%) in the local vehicle fleet. Diesel and gasoline vehicles contributed similarly to the concentrations of PM 10 and PN 10 , while the impact of gasoline vehicles on the PM 1 concentration was greater than that of diesel vehicles by a factor of 4.4. The most recent emission class Euro 6 had the highest influence on PM 10 , while older emission classes were more important for other air pollutants. Meteorological parameters explained most of the variations in PM 10 and PM 1 , while meteorology had only a minor influence on PN 10 . Our results indicate that replacing fossil-fuelled LDVs with electrical vehicles would greatly reduce the PN 10 concentrations at this urban site. • Temporal dynamics of NO x and particle number concentration similar to road traffic. • Real-world peak ratios of NO x /CO 2 and PM 10 /CO 2 exceeded modelled emission ratios. • Light-duty vehicles are the major source for fine PM (PN 10 ) (38%). • Diesel and gasoline vehicles contributed similarly to PM 10 and PN 10 . • Meteorology influenced variations in PM 10 and PM 1 , but had minor impact on PN 10 .