Anthropogenic impacts on urban atmosphere: observations and modelling

Author: Assoc. Prod. Aaed Mkhanna, Russian State Hydrometeorological University, Saint-Petersburg, Russia Contact: aaedmohanna(a)

RSHU to students. The Russian State Hydrometeorological University (RSHU) as the University, provides a complex scientific knowledge to students that allow them to understand importance and danger of pollution in cities, and in particular, to study atmospheric transport, dispersion, deposition and chemical transformations of anthropogenic pollutants in the urban atmosphere. The focus is on classification of anthropogenic emission sources, specifics of chemical species’ transport and reactions, dispersion processes in the atmospheric boundary layer, applications of mathematical models for air quality studies, methods of calculation of atmospheric characteristics determining pollution transport and dispersion on a basis of obtained standard hydrometeorological information. Therefore, the main task is to learn and study physical processes and factors that determine pollution of the atmosphere by various anthropogenic emissions based on physical and mathematical methods.

Anthropogenic sources of pollution. The anthropogenic pollution has no borders and no matter where the pollutants are released into the atmosphere, it will have an impact on environment on different scales ranging from global to local scale. The most relevant sources are the burning of fossil fuels to produce energy, heat and electricity, major industrial processes (like metallurgy industry or cement/construction industry) and transportation. The sources, for example, can be stationary point sources and mobile sources. There are four major groups of gaseous air pollutants by historical importance and overall effects on plants and animals (including people). These are the sulphur dioxide (SO2), oxides of nitrogen (NOx: NO, NO2), carbon dioxide (CO2) and ozone (O3). In particular, SO2 and NO are primary pollutants emitted directly from sources.

Major meteorological problems. At no economically substantiated number of monitoring posts or stations (10+ – 100+ devices on a territory of a large metropolitan area or a megapolis, such as for example, St.Petersburg in Russia) it is impossible to correctly solve the problem of spatial analysis of meteorological values and characteristics of air pollution. Interpretation methods on rare observation networks are based on including spatially continuous data as additional information, though very inaccurate. One of approaches for cities could be to include results of simulations using mathematical modeling methods [1] – empirical-statistical, semi-empirical turbulent diffusion, trajectory Lagrangian, stochastic (Monte-Carlo), etc. At RSHU, for example, several such methods are applied such as OND-86, ADMS-urban, HDM+MK and others for urban atmosphere modelling.

Urban pollution in St.Petersburg: (a) measurements and processing. As in any populated urban area [2], both the continuous as well as episodic air quality measurements (time series of automatic gas analytical measurements) are carried out. An example of carbon monoxide (CO) measured concentrations for selected episode during 2-8 Aug 2019 is shown in Figure 1.

Fig. 1. Averaged time-series of carbon monoxide (CO) concentration measured during 2-8 August 2019 (air quality post in St. Petersburg, Russia).

Measured concentrations (at 20 minute intervals; a total of 72 counts per day for 30-31 days, i.e. approximately 2160 values for each month) are statistically analyzed with calculating average, maximum/ minimum, standard deviation as well as building histograms, probability density functions, distribution functions, and determination of concentration values exceeded in 10, 5, 2 and 1% of cases (percentiles). Obtained time-series show air quality conditions at the point of the measurements and closes surroundings, and these can be used also for models’ verification.

(b) Modelling. A simple way is to apply a model (OND-86; [3]), The Voeikov Main Geophysical Observatory, Russia) based on a Gaussian approach. It is possible to investigate the effect of wind speed and source overheating on a shape of a pollution plume and predict maximum concentration. Here, source power, source dimensions, radius of source outlet, height of emissions, air temperature, wind speed are taken into account and simulations can be performed at various distances and time intervals. Calculations are performed for all defined Pasquill-Gifford stability classes (A-F; [4]. An example of the model simulations is shown in Figure 2, depicting changes in the ground level concentration as a function of the distance from the source for A-F stability classes.

Fig. 2. . Ground level concentration as a function of the distance from the source for A-F stability classes.

To teach students on understanding of environmental problems from the meteorologist point of view, and in particular, air quality and pollution in the urban areas the combination of varous types of observations and modeling tools/ techniques is the most useful approach.


  1. Air Quality Dispersion Modeling – Alternative Models, U.S. Environmental Protection Agency.
  2. Gavrilov A.S: Methodology for calculating air pollutant emissions by motor vehicles on urban highways, Handbook ,1996.
  3. Goskomhydromet, OND-86; Method for Calculating Atmospheric Concentration of Hazardous Substances Contained in Industrial Emissions, regulatory documents, 1986.
  4. Hanna, S R; Briggs, G A; Hosker, Jr, R P, Handbook on atmospheric diffusion, 1982, pages 25- 35.

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