[ES_JOBS_NET] Research Associateship , EPA’s National Exposure Research Laboratory, Research Triangle Park, North Carolina

Christine Wiedinmyer christin at ucar.edu
Mon Dec 15 11:47:17 MST 2014

FORWARDED from the M3 Mailing List:

A Research Opportunity is currently available at EPA’s National Exposure 
Research Laboratory in Research Triangle Park, North Carolina. This 
appointment will be served in the Emissions and Model Evaluation Branch 
within the Atmospheric Modeling and Analysis Division (AMAD). 
Applications for the current review cycle are due on February 1, 2015.

Numerical air quality models simulate the complex interactions between 
pollutant precursor emissions, meteorology, atmospheric chemistry, and 
deposition. These models are designed to predict atmospheric 
concentrations of a large number of gaseous (O3, NO2, etc.) and 
particulate (sulfate, carbon, etc.) pollutants in an Eulerian grid-based 
framework. The models are used for both scientific study of the fate of 
air pollutants as well as the development of abatement strategies to 
reduce their levels.

Model evaluation is an area of active research in air quality modeling, 
providing a link between model development and model application. In 
2009, scientists from North America and Europe launched the Air Quality 
Model Evaluation International Initiative (AQMEII) as a forum to monitor 
the state-of-the-science in regional-scale air-quality models and model 
evaluation methodologies. Since its inception, AQMEII researchers have 
conducted two model evaluation and intercomparison studies over both 
continents. Among other key findings, both studies reaffirmed the 
critical importance of specifying realistic lateral boundary conditions 
that reflect large-scale pollutant concentrations which can be affected 
by intercontinental transport of air pollution.

In its next phase, AQMEII will contribute to the modeling and analysis 
activities performed under the umbrella of the Task Force on Hemispheric 
Transport of Air Pollutants (TF HTAP). The objectives of this research 
are to systematically intercompare the performance of global and 
regional air quality models using a variety of surface and upper air 
datasets and to perform sensitivity simulations with global and regional 
models that reflect perturbed emissions in key source regions. These two 
elements are aimed at determining the differences between the two 
modeling approaches in quantifying long range transport of air pollution 
and its impact on local air quality.

This research opportunity will involve the application and evaluation of 
the Community Multiscale Air Quality (CMAQ) model for an annual base 
case and several sensitivity simulation over the continental U.S. under 
the planned AQMEII/HTAP collaboration. Some of the sensitivity 
simulations are expected to involve downscaling emission perturbation 
scenarios from global and/or hemispheric chemical transport models to 
the continental U.S. Additional research activities may include the use 
of alternate modeling techniques for providing estimates of the effects 
of intercontinental transport on regional and local air pollution under 
current and future climate scenarios. These alternate approaches may 
include instrumented modeling techniques available in CMAQ such as the 
Integrated Source Apportionment Method (ISAM) or the Decoupled Direct 
Method in three Dimensions (DDM-3D), and/or the use of nested CMAQ 
domains covering scales from hemispheric to local.

The Associate should have training and significant experience in the 
application and evaluation of sophisticated numerical models, and be 
comfortable with software programming (FORTRAN, R, NCL, scripting, etc.) 
in the Linux environment. The Associate should also have background in 
and knowledge of the chemical and physical processes that drive air 
pollutant formation, transport, and deposition. Finally, the Associate 
should possess good technical writing and communication skills as 
evidence from recent publications and presentations.

Please see the NRC website for additional information:





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