Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
