A Global Model of Atmospheric Mercury Chemistry, Emissions, and Deposition: Improvements Through Inverse Modeling of Atmospheric ObservationsEPA Grant Number: F6B10699
Title: A Global Model of Atmospheric Mercury Chemistry, Emissions, and Deposition: Improvements Through Inverse Modeling of Atmospheric Observations
Investigators: Holmes, Christopher
Institution: Harvard University
EPA Project Officer: Just, Theodore J.
Project Period: September 1, 2006 through August 31, 2009
Project Amount: $108,432
RFA: STAR Graduate Fellowships (2006) RFA Text | Recipients Lists
Research Category: Academic Fellowships , Air Quality and Air Toxics , Fellowship - Atmospheric Chemistry , Mercury
Mercury pollution enters remote ecosystems mainly through atmospheric transport and deposition. This study addresses three issues fundamental to the atmospheric cycle of mercury: the identity of dominant reduction and oxidation reactions; the magnitude and distribution of natural and anthropogenic sources; and the geographic source regions that contribute to mercury deposition in North America and elsewhere.
I will use sensitivity studies with the GEOS-Chem global atmospheric chemistry and transport model to identify chemical and emission processes that could explain the discrepancies between global models and atmospheric mercury measurements. Lagrangian re-sampling of polluted air-masses, done for the first time with mercury measurements by the NASA INTEX-B aircraft mission, will clarify which hypothesized chemical reactions dominate under environmental conditions. The INTEX-B flights above the Pacific Ocean, Western United States, and Gulf of Mexico, among other observations, provide information about mercury emissions from these areas and regions upwind. Correlations between mercury and other species will help distinguish natural from anthropogenic sources. The GEOS-Chem model includes coupled atmosphere, ocean, and soil reservoirs; therefore, this study will trace the impact of emissions through multiple cycles of deposition and re-emission. I will use Bayesian inverse analysis of all available measurements – for the first time with a global atmospheric mercury model – to derive optimal estimates of coupled chemical and emission processes.
Improvements in the GEOS-Chem mercury simulation will generate more accurate boundary conditions for use in the EPA CMAQ regional regulatory model. By improving understanding of the dominant environmental chemistry of mercury and distribution of its emissions, this work will create better estimates of the contributions of domestic, foreign and natural sources to mercury deposition in sensitive ecosystems both globally and in the United States.