Air Quality and
Earth System Modeling
Khairunnisa Yahya
Air Quality Forecasting Lab
North Carolina State University
Air Quality and Earth System Models
used in the Air Quality Forecasting Lab
§  3-D Air Quality Models:
Weather Research and
Forecasting model with
Chemistry (WRF/Chem) ,
Community Multiscale Air
Quality Model (CMAQ)
Community Earth System Model (CESM)
CAM
CICE
CLM
§  Wet deposition output for
PM species (SO42-, NO3-,
NH4+) had to be
implemented in WRF/Chem
§  Community Earth System
Model (CESM) does not
output wet deposition for
now
POP
CAM: Community Atmosphere Model
CICE: Community Ice CodE
CLM: Community Land Model
POP: Parallel Ocean Program
https://www2.ucar.edu/sites/default/files/news/2011/CESM_final.jpg
(Courtesy of Jian He)
Importance of NADP data for
Air Quality Modeling Evaluation
§  Precipitation in the southeastern U.S. is historically difficult to forecast
due to the nature of precipitation systems in this region, i.e., the pulsetype convection in the summer leads to weak atmospheric flows and
synoptic-scale forcings, resulting in horizontal gradients in surface
heating rates (Case et al., 2011)
§  NC has a unique sulfurrich and ammonia-rich
environment resulted
from high sulfur dioxide
emissions from power
plants and very high
ammonia emissions from
the animal industry
Importance of NADP data for
Air Quality Modeling Evaluation
§ Co-located sites for precipitation and wet-deposition of major
inorganic PM species (vs. other networks e.g. NCDC) - to
understand bias in PM2.5 concentrations
Source: Queen and Zhang, 2008
Importance of NADP data to
analyze Aerosol Indirect Effects
§ Aerosol indirect effects have one of the
largest uncertainties for climate forcing
(IPCC, 2007)
§ Aerosol indirect effects through
atmospheric chemistry, radiation, cloud,
precipitation feedbacks
§ Climate forcing:
Relationship
between increased
emissions, cloud
formation and
precipitation?
Importance of NADP Data for
Earth System Modeling
§  Tracers to
indicate the
source, fate,
and
transformation
of water and
pollutants
§  Linking
atmosphere,
hydrosphere,
biosphere and
lithosphere
Summary
§ Importance of long-term NADP data for air quality and
climate simulations (≥10 year simulations)
-  Model evaluation (precipitation and wet deposition) for
simulations over NC and continental U.S.
-  Analysis of relationships between PM concentrations
and deposition, precipitation and wet deposition
-  Analysis of Aerosol Indirect Effects
-  Earth System Modeling: trace fate of pollutants
Past Publications involving NADP data
§  Penrod, A., Y. Zhang, K. Wang, S.-Y. Wu, and L.R. Leung, 2014, Impacts of future climate and emission
changes on U.S. air quality, Atmospheric Environment, 89, 533-547.
§  Wang, K. and Y. Zhang, 2012, Application, evaluation, and process analysis of U.S. EPA’s 2002 multiplepollutant air quality modeling platform, Atmospheric and Climate Sciences, 2, 254-289.
§  Zhang, Y., K. Vijayaraghavan, X. Wen, H. E. Snell, and M. Z. Jacobson (2009), Probing into regional
ozone and particulate matter pollution in the United States: 1. A 1 year CMAQ simulation and evaluation
using surface and satellite data, J. Geophys. Res., 114, D22304, doi:10.1029/2009JD011898
§  Liu, X.-H., Y. Zhang, K. Olsen, W.-X. Wang, B. Do, and G. Bridgers, 2010, Responses of Future Air Quality
to Emission Controls over North Carolina, Part I: Model Evaluation for Current-Year Simulations, Atmos.
Environ., 44(23) 2443-2456.
§  Zhang, Y., X.-H. Liu, K. Olsen, W.-X. Wang, B. Do, and G. Bridgers, 2010, Responses of Future Air Quality
to Emission Controls over North Carolina, Part II: Analyses of Future-Year Predictions and Their Policy
Implications, Atmos. Environ., 44(23), 2767-2779.
§  Liu, P. and Y. Zhang, 2010, Use of a Process Analysis Tool for Diagnostic Study on Fine Particulate Matter
Predictions in the U.S. Part I: Model Evaluation Using Surface, Aircraft, and Satellite Data, Atmos. Pollu.
Res., 2 (1), 49-60, doi: 10.5094/APR.2011.007.
§  Queen, A., Y. Zhang, R. Gilliam, and J. Pleim, 2008, Examining the sensitivity of MM5-CMAQ
predictions to explicit microphysics schemes and horizontal grid resolutions, Part I—Database,
evaluation protocol, and precipitation predictions, Atmos. Environ., 42, 3842-3855.
§  Queen, A. and Y. Zhang, 2008, Examining the sensitivity of MM5-CMAQ predictions to explicit
microphysics schemes and
horizontal grid resolutions, Part III— The Impact of horizontal grid resolution, Atmos. Environ., 42,
3869-3881.
§  Wu, S.-Y., S. Krishnan, and Y. Zhang, and V. Aneja, 2008, Modeling Atmospheric Transport and Fate of
Ammonia in North Carolina, Part I. Evaluation of Meteorological and Chemical Predictions, Atmos.
Environ., 42, 3419–3436.