AAAR 31st Annual Conference
October 8-12, 2012
Hyatt Regency Minneapolis
Minneapolis, Minnesota, USA
Abstract View
Assimilation of TES Ammonia and Ground-based Aerosol Observations during CalNEX to Refine Emissions Estimates
SHANNON CAPPS, Daven Henze, Armistead Russell, Athanasios Nenes, Georgia Institute of Technology
Abstract Number: 347 Working Group: Remote and Regional Atmospheric Aerosols
Abstract Regions of high ammonia (NH$_3) emissions can challenge the capability of chemical transport models (CTMs) to represent the atmospheric state, especially aerosol concentrations, accurately. Uncertainties in the input of reactive nitrogen through fertilizers as well as the dependence of vegetative and soil NH$_3 emissions on surrounding concentrations complicate model refinement. Satellite-based observations of atmospheric ammonia and ground-site measurements of inorganic aerosol species provide a constraint for the modeled concentrations. A robust inverse modeling system will assimilate these data to refine estimates of inorganic aerosol precursor emissions.
Here, the GEOS-Chem adjoint framework, equipped with ANISORROPIA, ingests two disparate types of observations to refine emissions estimates, which are evaluated with a unique dataset from CalNEX. To represent the distinct regional sources in California, in particular, the GEOS-Chem adjoint is nested from the coarser 2 degree latitudinal by 2.5 degree longitudinal grid sizes with global coverage to 0.5 degrees by 0.666 degrees over the continental US. The assimilation window encompasses the early summer months of 2010. TES NH$_3 special observations provide a constraint on the highly variable tropospheric ammonia concentrations, especially over the Central Valley. The complementary aspect of the aerosol-gas partitioning puzzle is constrained by ground-based IMPROVE site measurements, which are more frequent than TES observations. Refined estimates of emissions of inorganic aerosol precursors are evaluated by comparing optimized results with CalNEX AMS and NH$_3 measurements.