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New insights into submicron particles impact on visibility.

Grzegorz MajewskiWioletta Rogula-KozłowskaBartosz SzelągEwa AniołPatrycja Rogula-KopiecAndrzej BrandykAgata WalczakMaja Radziemska
Published in: Environmental science and pollution research international (2022)
The aim of the study was to analyze the impact of very fine atmospheric particles (submicron particulate matter; PM 1 ) on visibility deterioration. Taking into consideration not only their entirely different physio-chemical properties in comparison to a well-recognized PM 10 but also the origin and a growing environmental awareness of PM 1 , the main research problem has been solved in few steps. At first, the chemical composition of PM 1 was determined in two selected urban areas in Poland. Measurements of meteorological parameters, i.e., air temperature and humidity, precipitation, atmospheric pressure, wind speed, and visibility, were also conducted. The next step of the work was the analysis of (1) seasonal changes of the concentration of PM 1 and its main components, (2) the influence of chemical components of PM 1 on light extinction, and (3) the influence of PM 1 and humidity on visibility. Hierarchical cluster analysis, correlation matrixes and a heat map, and classification and regression tree analysis were used. The light extinction coefficient is influenced mainly by coarse mass of PM, and PM 1 -bound ammonium nitrate, organic matter, and by Rayleigh scattering. The less important in the light extinction coefficient shaping has PM 1 -bound ammonium sulfate, elemental carbon, and soil. In this way, the secondary origin PM 1 components were proved to most significantly influence the visibility. The obtained results confirmed the possibility of the use of statistical agglomeration techniques to identify ranges of variation of visibility, including independent variables adopted to analyses (meteorological conditions, chemical composition of PM 1 , etc.).
Keyphrases
  • particulate matter
  • air pollution
  • polycyclic aromatic hydrocarbons
  • heavy metals
  • water soluble
  • nitric oxide
  • computed tomography
  • magnetic resonance
  • organic matter
  • deep learning
  • molecular dynamics