GMU Support of ARL Air Quality Work

2017 ANNUAL REPORT

Background

This work is part of the collaboration between NOAA Air Resources Laboratory (ARL) and George Mason University to advance atmospheric modeling and satellite data assimilation. The specific tasks are: 1) to improve windblown dust emissions; and 2) to implement NO_x emission data assimilation (EDA) algorithm in NAQFC.

Accomplishments

In the past year, GMU has completed the following tasks:

1. Implementation of the FENGSHA dust module within HRRR:

This work focuses on the development of a unified dust modeling capability towards a verified NOAA dust model that can be used within all modeling systems. NOAA has developed and is currently operating the U.S. Dust Forecasting Capability (DFC) in concert with one of its core missions to build a “Weather Ready Nation”. The current DFC is based on the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT, forecast available at http://airquality.weather.gov) model (Draxler et al., 2010). The NOAA DFC has been in operations since November 2011. DFC gives dust forecast in the form of hourly surface fine particulate concentration out to 48 h servicing the continental United States (CONUS). NOAA also now uses a version of a dust module from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model within a version of the Global Forecast System (GFS). In addition, the Rapid Refresh (RR), and the High Resolution Rapid Refresh (HRRR) meteorological model, which are run operationally at NCEP are using an aerosol aware microphysics scheme that currently uses climatological dust fields.

This report summarizes the effort to unify several popular dust-emission modules in various readiness levels for operational implementations and considerations, such as various in-line modules developed for HRRR and the modularized FENGSHA-CMAQ code in the operational NAQFC. As the wind-blown dust storms are prevalent in the Western U.S., we focused on the May 11 2014 storm outbreak in UT, AZ, and CA as a test case for the study. All dust modules exhibit shortcomings that include over predictions, false alarms, and missed events. All modules do “know” that this period is an extreme event for dust emissions. Without better availability of data sets for comparisons, it would be difficult to favor one scheme over the other for global applications. In spite of the shortcomings, for our regional CONUS applications, a version of FENGSHA and one of AFWA are favorable, although the GOCART approach is not far behind (without tuning). Much more evaluation work would be needed to identify a clear “winner”. Our preference for further development, testing, and evaluation would be to continue work with the dust emission models that are constantly being developed in the US. These are FENGSHA and GOCART/AFWA. The most important outcome of this study is that at this point all modules would be ready with minimal effort for inline coupling with an NGGPS core.

2. Impact of economic recession on US air quality

Satellite and ground observations detected large variability in nitrogen oxides (NO_x) during the 2008 economic recession, but the impact of the recession on air quality has not been quantified. This study combines observed NO_x trends and a regional chemical transport model to quantify the impact of the recession on surface ozone (O₃) levels over the continental United States. The impact is quantified by simulating O₃ concentrations under two emission scenarios: business-as-usual (BAU) and recession. In the BAU case, the emission projection from the Cross-State Air Pollution Rule (CSAPR) is used to estimate the “would-be” NO_x emission level in 2011. In the recession case, the actual NO₂ trends observed from Air Quality System (AQS) ground monitors and the Ozone Monitoring Instrument (OMI) on the Aura satellite are used to obtain “realistic” changes in NO_x emissions. The model prediction with the recession effect agrees better with ground O₃ observations over time and space than the prediction with the BAU emission. The results show that the recession caused a 1-2 ppbv decrease in surface O₃ concentration over the eastern United States, a slight increase (0.5-1 ppbv) over the Rocky Mountain region, and mixed changes in the Pacific West. The gain in air quality benefits during the recession, however, could be quickly offset by the much slower emission reduction rate during the post-recession period.

Planned work           

None

Publications           

1. Tong, D.Q., L. Pan, W. Chen, L. Lamsal, P. Lee, Y. Tang, H. Kim, S. Kondragunta, I. Stajner, 2016. Impact of the 2008 Global Recession on air quality over the United States: Implications for surface ozone levels from changes in NO_x emissions. Geophysical Research Letter, 43(17), 9280-9288, doi: 10.1002/2016GL069885.
2. Shepherd, Gemma, Enric Terradellas, Alexander Baklanov , Utchang Kang , William A. Sprigg , Slobodan Nickovic , Ali Darvishi Boloorani , Ali Al-Dousari , Sara Basart , Angela Benedetti, Andrea Sealy, Daniel Tong, Xiaoye Zhang, Joy Shumake-Guillemot , Zhang Kebin, Peter Knippertz, Abdulkareem A. A. Mohammed, Moutaz Al-Dabbas, Leilei Cheng, Shinji Otani, Feng Wang, Chengyi Zhang, Sang Boom Ryoo, and Joowan Cha, Gemma Shepherd, editor (2016). Global Assessment of Sand and Dust Storms. United Nations Environment Programme, Nairobi.  Retrieved from uneplive.unep.org.
3. Dong, X., Fu, J. S., Huang, K., Tong, D. and G. Zhuang: Model development of dust emission and heterogeneous chemistry within the Community Multiscale Air Quality modeling system and its application over East Asia, Atmos. Chem. Phys., 16, 8157–8180, 2016.
4. Lei, Hang, Julian XL Wang, Daniel Q. Tong, and Pius Lee. "Merged dust climatology in Phoenix, Arizona based on satellite and station data." Climate Dynamics (2016): 1-15.

Presentations          

Daniel gave ten presentations at national and international conferences.

Other  

Community Services

·         Daniel co-chaired two sessions on dust trends and societal impacts at the 2016 AGU Fall Meeting in San Francisco, CA;

·         Daniel co-chaired the emission forecasting session at the 8^th International Workshop on Air Quality Forecasting Research (IWAQFR) held on Jan, 2017 in Toronto, Canada.