Dry winter weather and low level mixing of pollutants from vehicle exhausts in cities leads to the highest concentrations of the tiny soot particles, known as PM10 particles, according to German scientists writing in the January issue of the International Journal of Environment and Pollution. Their findings suggest that traffic controls, other than an outright ban for several days at a time, would have little effect on levels.
Particulate matter of less than 10 nanometres across and smaller can penetrate the deepest parts of the lungs. PM10 have thus been associated with an increased incidence of breathing problems, asthma, and even lung cancer among city dwellers.
Jutta Rost of the Meteorological Institute, at the University of Freiburg, and colleagues there and at the Fraunhofer Institute for Transportation and Infrastructure Systems, in Dresden, and the Federal State Institute for Environmental Protection, in Baden-Wuerttemberg, have carried out a retrospective analysis of the atmospheric conditions that affected PM10 levels in four cities in South-West Germany during the period from 2001 to 2005.
For each city, the team obtained particular, PM10, data from roadside stations and Urban Background (UB) stations. This provided them with two distinct types of official urban air quality data against which they could validate their findings. They then looked at atmospheric exchange conditions as represented by sunlight levels, air temperature, wind speed, rainfall, and the height at which PM10 particles and other pollutants are mixing with the atmosphere.
The results of the statistical analysis indicate that precipitation and mixing-layer height are the two main meteorological variables that influencing concentrations of PM10 particles at road level within cities. "The absence of precipitation and low values of the mixing-layer height lead to comparatively high PM10 levels, particularly in winter," the researchers say. The data from both types of measuring stations gave the same results.
The team hopes to develop a forecasting model of PM10 levels that could be used to advise people at most risk of breathing problems on when to avoid city centres and other urban areas. The work also has implications for ensuring that air quality in urban environments is maintained at levels safe for public health.