background site Zakopane was from Home heating. (Table 1). In Krakow this source covers 30-50% and in Zakopane to 80-90% of total PM10, which is in.
Cite abstract as: Author(s) (2008), Title, European Aerosol Conference 2008, Thessaloniki, Abstract T02A030O
Physically constrained receptor modelling of PM10 from winter time Krakow H. Junninen1,2, J. Mønster1, M. Rey1, J. Cancelinha1, K. Douglas1, M. Duane1, V. Forcina1, A. Müller1, F. Lagler1, L. Marelli1, A. Borowiak1, J. Niedzialek1,3, B. Paradiz1, D. Mira-Salama1, J. Jimenez1, U. Hansen1, C. Astorga1, K.Stanczyk4, M. Viana5, X. Querol5, S. Tsakovski7, P. Wåhlin8, B. R. Larsen1 1
European Commission, Joint Research Centre, 21020 – Italy University of Helsinki , P.O. Box 64, Helsinki 00014, Finland 3 Malopolski Voivodship Inspectorate for Environ. Protection, Krakow, 31-011- Poland. 4 Central Mining Institute, 40-166 Katowice, Poland 5 Institute of Earth Sciences, Barcelona, Spain. 7 Faculty of Chemistry, University of Sofia.1164 Sofia, Bulgaria. 8 National Environmental Research Institute, Roskilde, 4000 - Denmark. 2
Keywords: PM10, source apportionment
Krakow is Poland’s second largest city and one of the most polluted cities in Europe with regards to particulate matter (PM) and associated compounds, such as benzo(a)pyrene (B(a)P). The study was designed to apportion coal combustion sources in comparison with other main sources for these pollutants PM10 samples were collected in Krakow during typical winter pollution events from 5 sampling sites, all with little different source profiles, industry, traffic, residential, urban background and rural background areas. The receptor samples were chemically analyzed together with PM emissions samples from 20 major sources and the obtained data was subjected to multivariate receptor modeling. 46 individual compounds were included comprising elementary and organic carbon (EC/OC), major anions and cations, trace elements, polyaromatic hydrocarbons and azaarenes. The source apportionment was accomplished by physically constrained positive matrix factorization (CMF). The hybrid receptor model between chemical mass balance and factor analysis with physically meaningful constraints was developed in the early 90ties by Wåhlin (Wåhlin, 1993). Subject for constraints was to gain reduced rotational ambiguity and physically more interpretable factors. In this study, these ideas are developed further by not only constraining ratios of specific elements, but allowing the constraint to be variable within uncertainty limits. The limits for constraints can be obtained from experimental uncertainties of source profiles or expert knowledge about specific elemental ratios, e.g. evaporation or chemical transformation that changes the original source fingerprint from one form to an other. Furthermore, the uncertainties for semivolatile PACs were scaled using temperature corrected subcooled liquid vapor pressures (Fernández et al., 2002). CMF takes advantage of the multi-linear engine ME-2 model tool developed by Paatero,
(1999), which facilitate the running of PMF in various constrained modes. The highest primary contributions to the PM10 pollution in the city of Krakow and in particular background site Zakopane was from Home heating (Table 1). In Krakow this source covers 30-50% and in Zakopane to 80-90% of total PM10, which is in agreement with high number of small stoves in Krakow and Zakopane. The second highest primary contribution of PM10 was estimated to come from industrial power generation (coal), 30-40% in Krakow and 5-10% in Zakopane to 80-90%. Traffic and re-suspension was estimated by to be lowest primary source explains to 8-10% in Krakow and less than 2% in Zakopane. The contribution from secondary aerosols was estimated to contribute with 20-21% in Krakow and less than 8-10% in Zakopane. Table 1. Source contributions for city of Krakow and background station.
Home heating Industrial power plants Secondary aerosol Traffic and resuspension
City
Background
Boilers
11 ± 5
16 ± 16
Residential heating LE-Boilers (coal) HE-Coal combustion Sulphates, nitrates and chlorides Vehicles Re-suspension Mass coverage R2
13 ± 6 17 ± 3 13 ± 5 16 ± 2
58 ± 31 5.5 ± 4.4 1.1 ± 0.9 9.4 ± 4.4
3.7 ± 1.5 2.0 ± 0.3 84 % 0.96
0.5 ± 0.4 1.2 ± 0.4 82 % 0.89
In the presentation the physically constrained model setup and the qualitative meaning of obtained result will be discussed in details. Fernández, P, Grimalt J, Vilanova R, (2002) Environ Sci Technol 36,1162-8. Paatero, P. (1999) J Comp Graph Stat; 8, 854-88. Wåhlin, P. (1993) In: Heidam, N.Z. (Ed.), Proceedings of the Fifth International Symposium on Arctic Air Chemistry. NERI Technical Report No. 70. Roskilde; Denmark.
