NOAA Air Quality predictions and challenges in large cities

NOAA provides operational predictions of ozone and wildfire smoke for the United States and predictions of airborne dust over the contiguous 48 states. Predictions are produced beyond midnight of the following day at 12 km spatial and hourly temporal resolution and are available at http://airquality.weather.gov/. North American Mesoscale (NAM) weather predictions with inventory based emissions estimates from the U.S. Environmental Protection Agency (EPA) and chemical processes within the Community Multiscale Air Quality (CMAQ) model are combined together to produce ozone predictions at NOAA. Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is used to predict wildfire smoke and dust storm predictions.

Recent updates to operational air quality products at NOAA have focused on mobile emissions using the projections of mobile sources for 2012. All area, mobile and point emissions from Canadian sources were updated to 2006 Environmental Canada Inventory. Emission inventories are complex and take years to assemble and evaluate causing a lag of information for 4-6 years. NAQFC recently began combing inventory information with projections of mobile sources. Evaluation of NOx emissions over large cities in the US was performed. Satellite and ground observations were used to compute NOx trends, which were used to evaluate the emission updates for NAQFC operation. Evaluation of NOx emissions used in NAQFC predictions and comparison with satellite observations and surface observations shows that they are in good agreement over large cities in the US.

Recent testing has been focused on transitioning CMAQ model with updated CB05 chemical mechanism into operations for ozone predictions. Developmental testing of aerosol predictions with NEI inputs using CB05 chemical mechanism and AERO-4 aerosol modules continues to show seasonal biases – overprediction in the winter and underprediction in the summer. Current efforts are focusing on inclusion of bias correction for fine particulate matter (PM2.5) and development of linkages with global atmospheric composition predictions.