Abstract
Concentration of air pollution in urbanized and agricultural areas is related to the activity of various economy sectors (the so-called SNAP categories). Therefore, the change in the emission of pollutants by an anthropogenic source should result in a change in the air pollution level in the selected area. To better understand the nature of changes in air pollution concentration in urban and agricultural areas, an analysis of data of five-year (2012-2016) air quality measurements, carried out at selected automatic air quality monitoring stations in Poland, Europe. The data came from stations located in 5 regions (Lower Silesia, Greater Poland, Lodz, Masovia and Lublin) in central Poland. The average hourly concentrations in selected areas in cities, towns and villages were compared with the hourly emission factors of power generation sector (SNAP1), residential and commercial combustion sector (SNAP2) and road transport sector (SNAP7). The hourly profiles of air pollution level were expressed by means of the “imission factor”, as analogous to the hourly profiles of the “emission factor” that is being used in the LOTOS-EUROS and the CHIMERE chemistry-transport models.
Highlights
Air pollution negatively affects both human health and the condition of the vegetation [1,2]
Variations of air pollution were compared with the hourly emission profiles for road transport (SNAP7) in summer, and non-industrial combustion (SNAP2) and transport (SNAP7) in winter
After carrying out the analysis, it can be concluded that the concentrations of the selected air pollutants varied significantly during a “typical” winter and summer day
Summary
Air pollution negatively affects both human health and the condition of the vegetation [1,2]. Temporal profiles used in air pollution/chemistry transport models, such as ‘Long Term Ozone Simulation - European Operational Smog’ (LOTOS-EUROS) [12,13] and CHIMERE [11] Those temporal profiles are made for anthropogenic emission sources listed in the ‘Selected Nomenclature for Air Pollution’ (SNAP) categories (Fig. 1) [13,14,15,16]. Averaging the data from a large data base of experimental measurements should allow the independence of results from dynamic changes in meteorological conditions, as well as from human activity on a given day By this means become possible obtaining “typical” daily profiles of air pollution concentration in a given location, to assess the daily variation of the air quality
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