Abstract
Polycyclic aromatic hydrocarbons (PAHs) are complex hazardous organic compounds that are introduced into the atmosphere as by-products of partial combustion processes. For common atmospheric conditions, the large molecular weight PAHs, such as benzo(a)pyrene (B[a]P), are found in the particulate phase and are believed to account for a considerable amount of the fine particulate matter toxic potential. Nonetheless, unlike meteorological variables and criteria pollutants, PAHs are very rarely monitored on a routine basis in most parts of the world. We present methodology for development and evaluation of a model for estimation of daily and monthly ambient B[a]P concentrations. The model utilizes a very large ambient B[a]P database from three sites in the Czech Republic. The difficulties faced when dealing with ambient PAH data are discussed. Model performance was evaluated by a complete internal-, external-, and temporal cross validations. The models reproduced very accurately monthly mean ambient B[a]P concentrations and provided acceptable daily mean B[a]P concentrations. Spatial extrapolations resulted in small deterioration of the models' performance. The temporal backward extrapolation revealed comparable errors to the spatial extrapolations in spite of the dramatic emissions reduction in the early years of the study period.
Original language | English |
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Pages (from-to) | 166-176 |
Number of pages | 11 |
Journal | Atmospheric Environment |
Volume | 101 |
DOIs | |
State | Published - 1 Jan 2015 |
Keywords
- Air pollution monitoring
- B[a]P
- Classification trees
- Multivariate linear regression
- PAHs
All Science Journal Classification (ASJC) codes
- General Environmental Science
- Atmospheric Science