Simulation of Tropospheric Ozone with MOZART-2:An Evaluation Study over East Asia

Climate changes induced by human activities have attracted a great amount of attention. With this, a coupling system of an atmospheric chemistry model and a climate model is greatly needed in China for better understanding the interaction between atmospheric chemical components and the climate. As the first step to realize this coupling goal, the three-dimensional global atmospheric chemistry transport model MOZART-2 (the global Model of Ozone and Related Chemical Tracers, version 2) coupled with CAM2 (the Community Atmosphere Model, version 2) is set up and the model results are compared against observations obtained in East Asia in order to evaluate the model performance. Comparison of simulated ozone mixing ratios with ground level observations at Minamitorishima and Ryori and with ozonesonde data at Naha and Tateno in Japan shows that the observed ozone concentrations can be reproduced reasonably well at Minamitorishima but they tend to be slightly overestimated in winter and autumn while underestimated a little in summer at Ryori. The model also captures the general features of surface CO seasonal variations quite well, while it underestimates CO levels at both Minamitorishima and Ryori. The underestimation is primarily associated with the emission inventory adopted in this study. Compared with the ozonesonde data, the simulated vertical gradient and magnitude of ozone can be reasonably well simulated with a little overestimation in winter, especially in the upper troposphere. The model also generally captures the seasonal, latitudinal and altitudinal variations in ozone concentration. Analysis indicates that the underestimation of tropopause height in February contributes to the overestimation of winter ozone in the upper and middle troposphere at Tateno.

Impact of Precursor Levels and Global Warming on Peak Ozone Concentration in the Pearl River Delta Region of China

The relationship between the emission of ozone precursors and the chemical production of tropospheric ozone （03） in the Pearl River Delta Region （PRD） was studied using numerical simulation. The aim of this study was to examine the volatile organic compound （VOC）- or nitrogen oxide （NO~ =NO＋NO2）- limited conditions at present and when surface temperature is increasing due to global warming, thus to make recommendations for future ozone abatement policies for the PRD region. The model used for this application is the U.S. Environmental Protection Agency＇s （EPA＇s） third-generation air-quality modeling system; it consists of the mesoscale meteorological model MM5 and the chemical transport model named Community Multi-scale Air Quality （CMAQ）. A series of sensitivity tests were conducted to assess the influence of VOC and NO~ variations on ozone production. Tropical cyclone was shown to be one of the important synoptic weather patterns leading to ozone pollution. The simulations were based on a tropical- cyclone-related episode that occurred during 14-16 September 2004. The results show that, in the future, the control strategy for emissions should be tightened. To reduce the current level of ozone to meet the Hong Kong Environmental Protection Department （EPD） air-quality objective （hourly average of 120 ppb）, emphasis should be put on restricting the increase of NOx emissions. Furthermore, for a wide range of possible changes in precursor emissions, temperature increase will increase the ozone peak in the PRD region; the areas affected by photochemical smog are growing wider, but the locations of the ozone plume are rather invariant.

Middle-High Latitude N_2O Distributions Related to the Arctic Vortex Breakup

The relationship of N2O distributions with the Arctic vortex breakup is first analyzed with a probability distribution function （PDF） analysis. The N2O concentration shows different distributions between the early and late vortex breakup years. In the early breakup years, the N2O concentration shows low values and large dispersions after the vortex breakup, which is related to the inhomogeneity in the vertical advection in the middle and high latitude lower stratosphere. The horizontal diffusion coefficient （Kyy） shows a larger value accordingly. In the late breakup years, the N2O concentration shows high values and more uniform distributions than in the early years after the vortex breakup, with a smaller vertical advection and Kyy after the vortex breakup. It is found that the N2O distributions are largely affected by the Arctic vortex breakup time but the dynamically defined vortex breakup time is not the only factor.

A method for quantifying bias in modeled concentrations and source impacts for secondary particulate matter

Community Multi-Scale Air Quality （CMAQ） estimates of sulfates, nitrates, ammonium, and organic carbon are highly influenced by uncertainties in modeled secondary formation processes, such as chemical mechanisms, volatilization, and condensation rates. These compounds constitute the majority ofPM2.5 mass, and reducing bias in estimated concentrations has benefits for policy measures and epidemiological studies. In this work, a method for adjusting source impacts on secondary species is developed that provides estimates of source contributions and reduces bias in modeled concentrations compared to observations. The bias correction adjusts concentrations and source impacts based on the difference between modeled concentrations and observations while taking into account uncertainties at the location of interest; and it is applied both spatially and temporally. We apply the method over the US for 2006. The mean bias for initial CMAQ concentrations compared to observations is -0.28 （OC）, 0.11 （NO3）, 0.05 （NH4）, and -0.08 （SO4）. The normalized mean bias in modeled concentrations compared to observations was effectively zero for OC, NO3, NH4, and SO4 after applying the secondary bias correction. Ten-fold cross-validation was conducted to determine the performance of the spatial application of the bias correction. Cross-validation performance was favorable; correlation coefficients were greater than 0.69 for all species when comparing observations and concentrations based on kriged correction factors. The methods presented here address model uncertainties by improving simulated concentrations and source impacts of secondary particulate matter through data assimilation. Secondary-adjusted concentrations and source impacts from 20 emissions sources are generated for 2006 over continental US.