4.6 Article

Quantitative Assessment of PM2.5 Sources and Their Seasonal Variation in Krakow

Journal

WATER AIR AND SOIL POLLUTION
Volume 228, Issue 8, Pages -

Publisher

SPRINGER
DOI: 10.1007/s11270-017-3483-5

Keywords

Particulate matter; Energy dispersive X-ray analysis; Ion chromatography; Positive matrix factorization

Funding

  1. International Atomic Energy Agency [RER/1/013]
  2. Ministry of Science and Higher Education core funds for statutory RD activities
  3. AGH University of Science and Technology [11.11.210.244]

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In industry areas of Poland such as Silesia or urban sites like Krakow and some other cities, the levels of pollutants frequently breach air quality standards. Particulate matter (PM) is the most important constituent of atmospheric pollution. Beginning on 1st February 2014 until 31st January 2015, the samples of fine particulate matter PM2.5 (aerodynamic diameter of particles less than or equal to 2.5 mu m) were collected at a site in the southeastern Krakow urban background area. During this period, 194 samples were taken. The samples showed daily variation of PM2.5 concentration. From these data, monthly variations were estimated and presented in this paper. Monthly integrated data are more representative for the Krakow urban background and show seasonal variation of PM2.5 pollution. The lowest monthly concentration value was found for August 2014-about 10 mu g m(-3), the highest for February 2014-70 mu g m(-3), whereas the average annual value was about 31 mu g/m(3). Utilizing X-ray fluorescence method, concentrations of 15 elements for each sample were determined and 8 inorganic ions were analyzed by ion chromatography. Additionally, the samples were analyzed for black carbon BC). Receptor model PMF (positive matrix factorization) was used for source identification and apportionment. The modeling identified six sources and their quantitative contributions to PM2.5 total mass. The following sources were identified: combustion, secondary nitrate and sulfate, biomass burning, industry or/and soil and traffic. Finally, monthly variations of each source are presented.

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