Uncertainty analysis of an ozone deposition model

Cs. Vincze1, I. Gy. Zsély2, D. Szinyei1, R. Mészáros1, I. Lagzi2
1Eötvös University, Department of Meteorology, Hungary; 2Eötvös University, Institute of Chemistry, Hungary
vinczecsilla@gmail.hu

Photochemical air pollutants, especially ozone, are the important chemical species that affects both vegetation and human health. Elevated ozone concentrations can be potentially damaging to agricultural and natural vegetation. Occasional extreme concentrations may cause visible injury to the vegetation while the long-term, growing- season averaged exposure can result in decreased productivity and crop yield. Air quality measures, based on Accumulated exposure Over a Threshold (AOT) such as AOT40 were therefore developed based on experiment in order to try to mitigate the damage. However, since ozone enters plants through the stomata, the response of vegetation to changes in the atmospheric ozone concentrations is more directly influenced by the stomatal ozone flux than its atmospheric concentration. Therefore, it has been suggested that the stomatal ozone flux is a more appropriate measure for ozone damage than the concentration based values. Stomatal flux of ozone is controlled by ozone concentration and by deposition velocity via parameterization of the canopy and stomatal conductances. Plant stomatal conductance plays an important role in most of all deposition models. In Jarvis model, multiplicative algorithm of stomatal conductance is applied. This type of model includes functions for the effects of photosynthetically active radiation, air temperature, soil water content, and other parameters on the stomatal conductance. The values of the model input parameters are very uncertain. Therefore, these parameters may give rise to uncertainties in simulation results. The nonlinear models can magnify the uncertainty of some parameters and damp it to each others. This means that models may overestimate or underestimate the stomatal ozone fluxes. Sensitivity analysis is an effective tool for the exploration of the relation between the output of mathematical models and the input data, which comprise the values of parameters as well as the initial conditions. To investigate the effects of the most important parameters on stomatal conductance of the ozone a Monte Carlo analysis has been performed. The large number of parameter sets is generated according to the probability density functions of these parameters. The model is simulated with each of these parameter sets, and the results are processed with statistical methods. Determination of the probability density functions of the model results from the joint probability density functions of the parameters from measurements will be presented. Estimation of the high spatial variability of the stomatal ozone fluxes over Central Europe under continental climate region will be also discussed. For this purpose a coupled Eulerian photochemical reaction-transport model and a detailed ozone dry deposition model (TREX; Transport EXchange Model) have been developed, and it has been coupled to ALADIN meso-scale limited area numerical weather prediction model. Hereby, estimation of the ozone deposition can be performed for a routine way.

Acknowledgement: We acknowledge the support of the Hungarian OTKA Postdoctoral Fellowship (OTKA D048673) and the Öveges Fellowship of the National Office for Research and Technology.