Motor transport related harmful PM2.5 and PM10: from onroad measurements to the modelling of air pollution by neural network approach on street and urban level

2016 Joint IMEKO TC1-TC7-TC13 Symposium: Metrology Across the Sciences: Wishful Thinking?

Lozhkina, O.^1 ; Lozhkin, V.^1 ; Nevmerzhitsky, N.^1 ; Tarkhov, D.^2 ; Vasilyev, A.^2

St. Petersburg University of State Fire Service of EMERCOM of Russia, 149, Moskovsky, St.-Petersburg

196105, Russia^1

Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, St.-Petersburg

195251, Russia^2

关键词: Measurement techniques;    Meteorological condition;    Nephelometry;    Neural network modelling;    Numerical investigations;    PM10 and PM2.5;    Traffic flow;    Wind directions;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/772/1/012031/pdf
DOI  :  10.1088/1742-6596/772/1/012031

来源: IOP

【 摘 要 】

The level of PM10 and PM2.5 concentrations in the air on seven roads in St. Petersburg, Russia, were investigated using gravimetry and nephelometry measurement techniques in 2013-2015. The effects of meteorological conditions (temperature, relative humidity, wind direction, and speed) and the intensity of traffic flows on the results of the measurements were also evaluated. On the base of the measurements, there was developed a neural network modelling approach that allowed to quantify exhaust / non-exhaust PM10 and PM 2.5 emissions and carry out numerical investigations of air pollution by transport related PM2.5 and PM10 on street and urban level in St. Petersburg.