RESEARCH PAPER
Determination of benzo(a)pyrene content in PM10 using regression methods
1
Department of Chemical and Process Engineering, Chemical Faculty, Gdansk University of Technology, 11/12 G. Narutowicza Str., 80-233 Gdańsk, Head of the Department: Prof. dr hab. inż. M. Kamiński
2
Polish Academy of Sciences, Institute of Fluid-Flow Machinery, 14 Fiszera Str.,80-231 Gdansk,
Head of the Department: Dr hab. inż. J. Pozorski
3
Department of Analytical Chemistry, Chemical Faculty, Gdansk University of Technology, 11/12 G. Narutowicza Str., 80-233 Gdańsk,
Head of the Department: Prof. dr hab. inż. J. Namieśnik
Corresponding author
Jacek Gębicki
Department of Chemical and Process Engineering, Chemical Faculty, Gdansk University of Technology, 11/12 G. Narutowicza Str., 80-233 Gdańsk, Head of the Department: Prof. dr hab. inż. M. Kamiński
Department of Chemical and Process Engineering, Chemical Faculty, Gdansk University of Technology, 11/12 G. Narutowicza Str., 80-233 Gdańsk, Head of the Department: Prof. dr hab. inż. M. Kamiński
Med Srod. 2015;18(4):23-26
KEYWORDS
ABSTRACT
The paper presents an attempt of application of multidimensional linear regression to estimation of an empirical model describing the factors influencing on B(a)P content in suspended dust PM10 in Olsztyn and
Elbląg city regions between 2010 and 2013. During this period annual average concentration of B(a)P in PM10 exceeded the admissible level 1.5-3 times. Conducted investigations confirm that the reasons of B(a)P
concentration increase are low-efficiency individual home heat stations or low-temperature heat sources, which are responsible for so-called low emission during heating period. Dependences between the following
quantities were analysed: concentration of PM10 dust in air, air temperature, wind velocity, air humidity. A measure of model fitting to actual B(a)P concentration in PM10 was the coefficient of determination of the model. Application of multidimensional linear regression yielded the equations characterized by high values of the coefficient of determination of the model, especially during heating season. This parameter ranged from 0.54
to 0.80 during the analyzed period.
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| eISSN: | 2084-6312 |
| ISSN: | 1505-7054 |
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