Explaining the high PM10 concentrations observed in Polish urban areas
Magdalena Reizer , Katarzyna Juda-Rezler
AbstractThe main goal of this paper is to identify the drivers responsible for the high particulate matter concentrations observed in recent years in several urban areas in Poland. The problem was investigated using air quality and meteorological data from routine monitoring network, air mass back trajectories and multivariate statistical modelling. Air pollution in central and southern part of the country was analysed and compared with this in northern-eastern B The Green Lungs of Poland region. The analysis showed that in all investigated locations, there is a clear annual cycle of observed concentra-tions, closely following temperature-heating cycles, with the highest concentrations noted in January. However, the main drivers differ along the country, being either connected with regional background pollution (in the central part of the country) or with local emission sources (in the southern part). The occurrence of high PM 10 concentrations is most commonly associated with the influence of high-pressure systems that brought extremely cold and stable air masses form East or South of Europe. During analysed episodes, industrial point sources had the biggest (up to 70 – 80 %) share in PM 10 levels on the days with maximum PM pollution, while remote and residential/traffic sources determined the air quality in the early stages of the episodes. Principal component analysis (PCA) shows that secondary inorganic aerosols account for longrange transported pollution, As, Cd, Pb and Zn for industrial point sources, while Cr and Cu for residential and traffic sources of PM 10,respectively.
|Journal series||Air Quality Atmosphere and Health, ISSN 1873-9318|
|Pages||517 - 531|
|Publication size in sheets||99.25|
|Keywords in English||PM 10 episode, Poland, Coalcombustion, Source apportionment, PCA-MLRA, Backward trajectories|
|Score|| = 25.0, 28-11-2017, ArticleFromJournal|
= 25.0, 28-11-2017, ArticleFromJournal
|Publication indicators||: 2016 = 3.184 (2) - 2016=3.102 (5)|
|Citation count*||14 (2018-02-16)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.