Mathematical Modelling of Partitioning Processes of Polycyclic Aromatic Hydrocarbons as Gas Waste

Transcription

1 Mathematical Modelling of Partitioning Processes of Polycyclic Aromatic Hydrocarbons as Gas Waste Jelena Radonić a, Mirjana Vojinović Miloradov a, Maja Turk Sekulić a, Ivan Holoubek b and Maja Đogo a a University of Novi Sad, Faculty of Technical Sciences, Serbia b RECETOX, Masaryk University, Brno, Czech Republic

2 Introduction Polycyclic aromatic hydrocarbons (PAHs) - the gas waste - group of semi-volatile organic compounds (SVOC) Origin - combustion activities: o Residential heating o Transportation o Open burning of waste o Fires o Incineration of hazardous materials

3 Introduction Elevated levels of PAHs in all environmental compartments as the consequence of their physical chemical characteristics IARC - PAHs into three groups: o Probably carcinogenic for humans o Possibly carcinogenic for humans o Not classifiable Fate and LRTP of gas waste/pahs - determined by partitioning between different media

4 Introduction G-P partitioning process of gas waste - quantified using particle-bound fraction, : C P compound concentration associated with the particle phase (ng m -3 ) C G compound concentration in gas phase (ng m -3 ) TSP - total suspended particulate matter concentration (µg m -3 ) G-P partitioning coefficient, K p (TSP is known):

5 Introduction Several representative models - G-P partitioning of SVOC Junge - Pankow model - adsorption approach (chemicals adsorb to the active sites on the surface of particles): p 0 L c c θ - particle surface area (m 2 m -3 ) p 0 L - sub-cooled liquid vapor pressure (Pa) c - parameter (Pa m) (heat of desorption of the compound from the particle surface, heat of vaporization, surface properties)

6 Introduction The main objectives: To assess G-P partitioning of gaseous waste/pahs in the ambient air using the Jung-Pankow adsorption model and To compare experimental results with estimated values

7 Materials and Methods Sampling locations air samples, 24 sampling sites, three countries Urban, industrial, heavily contaminated, residential and background area Early summer (May-July) of 2003 and 2004 Comparable meteorological conditions (median temperature 19ºC)

8 Materials and Methods Sampling methods - high volume ambient air samplers Two types of sorbents quartz filters (collection of particles) and PUF filter (collection of the gaseous phase)

9 Materials and Methods Duration of sampling - 24 hours PUF filters - extracted with acetone and dichloromethane in a Soxtec extractor QFs - heated to 450 C GC-MS (HP HP 5972)

10 Results and discussion Gas-particle partitioning The overall variability of for the individual chemicals: 100 Median 25%-75% Min-Max Nap Acy Ace Flo Phe Ant Flu Pyr B(a)A Chr B(b)F B(k)F B(a)P I(123cd)P D(ah)A B(ghi)P

11 Results and discussion Gas-particle partitioning Concentration levels of PAHs - varied over three orders of magnitude PAHs - in the gas and particulate phase The lowest variability of - PAHs with high molecular mass B(b)F, B(k)F, B(a)P, I(123cd)P, D(ah)A, B(ghi)P - 100% particle-bound

12 Results and discussion Gas-particle partitioning Exception Pancevo refinery - 50% > gas phase-associated B(a)A and Chr: 100% particle-associated in B&H B(a)A and Chr: 9-72% in Croatia and Serbia Flu and Pyr: 9-26% particle-associated in B&H (1-7% in Croatia and Serbia) Very high fractions in B&H - probably caused by significantly high concentration of TSP in the atmosphere

13 Results and discussion Gas-particle partitioning - Literature Measured particle-bound fractions for PAHs (103 samples published previously): 100 Median 25%-75% Min-Max Flo Phe Ant Flu Pyr B(a)A Chr B(b)F B(k)F B(a)P I(123cd)P D(ah)A B(ghi)P

14 Results and discussion Junge-Pankow model Theoretical value - calculated using Junge-Pankow model Calculations - for urban aerosols: c = Pa m, p L0 at 298 K = m 2 m -3 The ratios between field and predicted - Figure

15 Results and discussion Junge-Pankow model Ratio of modeled and measured particle-bound fraction for selected compounds (129 air samples from this study): 5 Median 25%-75% Min-Max Nap Acy Ace Flo Phe Ant Flu Pyr B(a)A Chr B(b)F B(k)F B(a)P I(123cd)P D(ah)A B(ghi)P log ( measured / modeled)

16 Results and discussion Junge-Pankow model Very good agreement - higher MM PAHs Slightly underestimated - Phe, Ant, Flu, B[a]A Underestimation from orders of magnitude - low MM PAHs Underestimation of 3 orders of magnitude Nap

17 Conclusions Variability of field results - range over several orders of magnitude Significant differences between three countries (atmospheric conditions) confirmed Partitioning behavior - cannot be accurately predicted Junge-Pankow model predicts median values with reasonable precision Possible sources of deviations - extensive sorption potential on black carbon and non-exchangeable fraction

18 Radonic, J., Turk Sekulic, M., Vojinovic Miloradov, M., Čupr, P., Klánová, J. (2008): Gas-particle partitioning of persistent organic pollutants in the Western Balkan countries affected by war conflicts. Environmental Science and Pollution Research, Volume 16, Issue 1

19 This research was financially supported by 5FP EU (ICFP501A2PR02 APOPSBAL) and Provincial Secretariat for Science and Technological Development (Project: )