1. Top-Down Emissions Studies using Atmospheric Observations and Modeling Greg Frost NOAA Earth System Research Laboratory Boulder, Colorado, USA  Why top-down emissions analyses are needed  How top-down emissions analyses are carried out  Examples of top-down constraints on emissions In-situ observations Satellite retrievals Inverse modeling  More information Many thanks to my colleagues at NOAA ESRL, U. Colorado/CIRES, U. Bremen, UC Berkeley, NASA

2. Why top-down emissions analyses are needed Frost et al., 2013 Rapid societal development results in new challenges to emissions understanding. Emissions information is needed for many purposes.Emission inventories are inherently uncertain, but these uncertainties are difficult to quantify. Top-down methods based on observations and models can provide objective tests of inventories and help improve the scientific basis of emissions. Bottom-Up Inventories Top-Down Approaches Reconciliation Synthesis to Benefit Stakeholders Improvement

3. 2013 2015 Why top-down emissions analyses are needed

4. How top-down emissions analyses are carried out Top-down emissions approaches Observations of atmospheric abundance Models: abundance  emissions Reconciliation with bottom-up inventories Quantifiable uncertainties Different methods  same answer Pollutants relevant to air quality & climate What can be determined Total emissions Temporal variation Spatial mapping Sector partitioning

5. Los Angeles Basin NOx emissions Fewer heavy- duty diesel vehicles on weekends  lower NO x, higher O 3 Atmospheric modeling Kim et al., 2015 Model NO 2 Aircraft NO 2 Fuel-based emissions McDonald et al., 2012, 2013 CalNex 2010 Weekend Weekday Pollack et al., 2012 Aircraft observations

6. Long-term emissions trends in Los Angeles Hassler et al., 2015 Pollack et al., 2013 INVENTORY OBSERVATIONS

7. US Oil & Natural Gas Emissions mixing height (PBL) Wind emissions Wind Upwind Downwind Aircraft mass balance Hydrocarbon leak rates inferred from observations in oil & gas production basins Karion et al., 2013 Emissions from different oil & gas basins can differ significantly Peischl et al., 2015

8. Kim et al., 2009 Continuously monitored power plants serve as “calibration” for satellite-model NO 2 comparison Satellite NO 2 over US Power Plants Model vs satellite NO 2 over power plants Model vs satellite NO 2 over US power plants Ohio River Valley: Satellite (GOME/SCIA) Ohio River Valley: Inventory Northeast US: Satellite (GOME/SCIA) Northeast US: Inventory Using Satellites to Understand US NOx Emissions SCIAMACHY Summer 2004 Satellite NO 2 detects impact of power plant NOx controls Kim et al., 2006

9. KORUS-AQ Figures from KORUS-AQ White Paper MODIS AOD Spring 2001-2008 OMI NO2, May 2013 South Korea, April-June 2016; NASA, KARI, ESA Lin et al., 2014 Kanaya et al., 2014 Understanding satellite retrievals in presence of high aerosols

10. Using inverse modeling to constrain CH 4 emissions U.S. Methane Emissions CalNex 2010 NOAA P-3 flights Mesoscale inverse modeling system California CH4 Sources Cui et al., 2015

11. Official Inventory Top-Down Results Inverse modeling of CH 4 in Los Angeles Basin NOAA P-3 Flights over LA Basin Methane Emissions Inverse Model CH 4 Results Comparing Top-Down to Bottom-Up Cui et al., 2015

12. More Information Cui, Y. Y., et al. (2015) Top-down estimate of methane emissions in California using a mesoscale inverse modeling technique: The South Coast Air Basin, J. Geophys. Res., doi:10.1002/2014JD023002 Frost, G. J., et al. (2013) New Directions: GEIA’s 2020 vision for better air emissions information, Atmos. Environ., http://dx.doi.org/10.1016/j.atmosenv.2013.08.063 Hassler, B., et al. (2015) Understanding long-term global trends in tropospheric ozone precursors: Comparison of urban measurements with the MACCity global emissions inventory, in preparation Kanaya, Y., et al. (2014) Long-term MAX-DOAS network observations of NO2 in Russia and Asia (MADRAS) during the period 2007– 2012: instrumentation, elucidation of climatology, and comparisons with OMI satellite observations and global model simulations, Atmos. Chem. Phys., doi:10.5194/acp-14-7909-201 Karion, A., et al. (2013) Methane emissions estimate from airborne measurements over a western United States natural gas field, Geophys. Res. Lett., doi:10.1002/grl.50811. Kim, S.-W., et al. (2006) Satellite-observed U.S. power plant NOx emission reductions and their impact on air quality, Geophys. Res. Lett., doi:10.1029/2006GL027749. Kim, S.-W., et al. (2009) NO 2 columns in the western United States observed from space and simulated by a regional chemistry model and their implications for NO x emissions, J. Geophys. Res., doi:10.1029/2008JD011343 Kim, S.-W., et al. (2015) Modeling the weekly cycle of NOx and CO emissions and their impacts on O3 in the Los Angeles-South Coast Air Basin during the CalNex 2010 field campaign, J. Geophys. Res., submitted. Lin, J.-T., et al. (2014). Retrieving tropospheric nitrogen dioxide from the Ozone Monitoring Instrument: effects of aerosols, surface reflectance anisotropy, and vertical profile of nitrogen dioxide, Atmos. Chem. Phys., doi:10.5194/acp-14-1441-2014 McDonald, B.C., et al. (2012) Long-term trends in nitrogen oxide emissions from motor vehicles at national, state, and air basin scales, J. Geophys. Res., doi:10.1029/2012JD018304 McDonald, B.C., et al. (2013) Long-Term Trends in Motor Vehicle Emissions in U.S. Urban Areas, Environ. Sci. Technol., doi:10.1021/es401034z. Peischl, J., et al. (2015) Quantifying atmospheric methane emissions from the Haynesville, Fayetteville, and northeastern Marcellus shale gas production regions, J. Geophys. Res., doi: 10.1002/2014JD022697 Pollack, I. B., et al. (2012) Airborne and ground-based observations of a weekend effect in ozone, precursors, and oxidation products in the California South Coast Air Bain, J. Geophys. Res., doi:10.1029/2011JD016772. Pollack, I. B., et al. (2013) Trends in ozone, its precursors, and related secondary oxidation products in Los Angeles, California: A synthesis of measurements from 1960 to 2010, J. Geophys. Res., doi:10.1002/jgrd.50472. NOAA ESRL CSD: http://www.esrl.noaa.gov/csd/http://www.esrl.noaa.gov/csd/ Greg Frost: gregory.j.frost@noaa.govgregory.j.frost@noaa.gov