1School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
2Department of Physics and Atmospheric Science, Dalhousie University Halifax, NS, Canada
3Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
4School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA
Abstract. Lightning NOx emissions calculated using the U.S. National Lightning Detection Network data were found to account for 30% of the total NOx emissions for July–August 2004, a period chosen both for having higher lightning NOx production and high ozone levels, thus maximizing the likelihood that such emissions could impact peak ozone levels. Including such emissions led to modest, but sometimes significant increases in simulated surface ozone when using the Community Multi-scale Air Quality Model (CMAQ). Three model simulations were performed, two with the addition of lightning NOx emissions, and one without. Domain-wide daily maximum 8-h ozone changes due to lightning NOx were less than 2 ppbv in 71% of the cases with a maximum of 10-ppbv; whereas the difference in 1-h ozone was less than 2 ppbv in 77% of the cases with a maximum of 6 ppbv. Daily maximum 1-h and 8-h ozone for grids containing O3 monitoring stations changed slightly, with more than 43% of the cases differing less than 2 ppbv. The greatest differences were 42-ppbv for both 1-h and 8-h O3, though these tended to be on days of lower ozone. Lightning impacts on the season-wide maximum 1-h and 8-h averaged ozone decreased starting from the 1st to 4th highest values (an average of 4th highest, 8-h values is used for attainment demonstration in the U.S.). Background ozone values from the y-intercept of O3 versus NOz curve were 42.2 and 43.9 ppbv for simulations without and with lightning emissions, respectively. Results from both simulations with lightning NOx suggest that while North American lightning production of NOx can lead to significant local impacts on a few occasions, they will have a relatively small impact on typical maximum levels and determination of Policy Relevant Background levels.