Modeling airborne benzo(a)pyrene concentrations in the Czech Republic. (January 2015)

• Record Type: Journal Article
• Authors: Zalel, Amir; Yuval, ; Svecova, Vlasta; Sram, Radim J.; Bartonova, Alena; Broday, David M.
• Is Part Of: Atmospheric environment. Volume 101(2015)
• Page Start: 166
• Page End: 176
• Publication Date: 2015-01
• Subjects: PAHs -- B[a]P -- Multivariate linear regression -- Classification trees -- Air pollution monitoring; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2014.11.031
• Languages: English
• ISSNs: 1352-2310

Abstract

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. Highlights: Models for estimation of daily and monthly ambient B[a]P levels were developed. The concentrations seasonality was addressed by combined CART–MLR models. The models reproduced very accurately monthly mean ambient B[a]P concentrations. Spatial across-site extrapolations revealed reliable models performance. Temporal extrapolations revealed comparable errors to the spatial extrapolations.