Effect of atmospheric stability on air pollutant concentration and its generalization for real and idealized urban block models based on field observation data and wind tunnel experiments

Abstract Near-surface atmospheric stability has a large influence on air pollutant diffusion in urban canopy. However, few systematic and quantitative studies have analyzed the effects of atmospheric stabilities on urban air pollutant concentration due to the uncertainty of field data and limitations of laboratory conditions. This paper aims to systematically and quantitatively study the effects of atmospheric stabilities on urban air pollutant concentration based on statistical analysis of field observation data and wind tunnel experiments. Firstly, we propose an index named stability effect ratio of normalized air pollutant concentration (SER_C∗), which is the ratio of normalized air pollutant concentration under non-neutral stratification to that under neutral conditions. Then we investigated five years of NOx concentration data observed at 25 general air-pollution-monitoring stations of the Tokyo Metropolitan Government and meteorological data of the Japan Meteorological Agency from 2006 to 2010. The Modified Pasquill–Gifford method was adopted to classify the atmospheric stability. In order to avoid uncertain factors in observation data, five wind-tunnel measurements under different atmospheric stability scenarios were conducted in a thermally stratified wind tunnel at Tokyo Polytechnic University. Ethylene gas was used to simulate exhaust emissions from vehicles. Both the results of observation data analysis and the wind tunnel experiments showed that: SER_C∗ is larger than 1 under stable atmospheric conditions, equal to 1 under neutral condition and smaller than 1 under unstable atmospheric conditions. In general, SER_C∗ increases as the atmospheric stability increases. It was interesting to find that the curve of SER_C∗ and Bulk Richardson’s number seems to be independent of wind speed and location. The results have the potential to accelerate the prediction and evaluation of air pollutant concentration in urban areas under various atmospheric conditions. We are continuing to conduct more studies to test the generality of this conclusion.