Quantitative Assessment of Parametric Uncertainty in Northern Hemisphere PAH Concentrations

Abstract

We quantitatively examine the relative importance of uncertainty in emissions and physicochemical properties (including reaction rate constants) to Northern Hemisphere (NH) and Arctic polycyclic aromatic hydrocarbon (PAH) concentrations, using a computationally efficient numerical uncertainty technique applied to the global-scale chemical transport model GEOS-Chem. Using polynomial chaos (PC) methods, we propagate uncertainties in physicochemical properties and emissions for the PAHs benzo[a]pyrene, pyrene and phenanthrene to simulated spatially resolved concentration uncertainties. We find that the leading contributors to parametric uncertainty in simulated concentrations are the black carbon-air partition coefficient and oxidation rate constant for benzo[a]pyrene, and the oxidation rate constants for phenanthrene and pyrene. NH geometric average concentrations are more sensitive to uncertainty in the atmospheric lifetime than to emissions rate. We use the PC expansions and measurement data to constrain parameter uncertainty distributions to observations. This narrows a priori parameter uncertainty distributions for phenanthrene and pyrene, and leads to higher values for OH oxidation rate constants and lower values for European PHE emission rates.

Figure 1

Measured and simulated total (gas and particulate) concentrations at non-urban sites for PHE (top), PYR (middle), and BaP (bottom). The black lines are means across the measurements at all non-urban sites, and their error bars show the standard deviation of the mean for each month. The blue lines are the simulated means across the same sites, with the shaded regions marking the σ and 2σ intervals of the parametric uncertainty distributions for each month.

Figure 2

Constraint of parameter uncertainty distributions by measurement data. (a) PHE, (b) PYR, (c) BaP distributions for the two most important parameters each. Prior distributions (dashed lines), observation-based likelihoods (dot-dashed lines), and posterior distributions (solid lines) shown.