Our research on atmospheric chemistry
problems aims at exploring the fundamental processes that govern
the concentrations and distributions of trace gases and
aerosols. Our research helps unravel of the
complicated relations between the changing environment and human
activities. We use statistical and numerical methods to analyze
large datasets of tropospheric chemical measurements at surface
sites, from balloons and aircraft, and by satellites. We have
many colleagues in our
school and Civil and
Environmental Engineering working on various aspects of
We use data analysis to extract the
underlying scientific principals from complex measurement data.
Fairly simple statistical analysis can be powerful tools (e.g.,
Wang et al. [2000a]). Increasingly, however, the large amounts
of measurements data demand more advanced statistical methods.
One particular method we have used is the positive matrix
factorization (PMF), which explores the covariance structure of
the datasets. The technique has been used to examine the effects
of intercontinental transport on tropospheric ozone (Wang et al.
[2003b]); the sources of biogenic volatile organic compounds (VOCs);
the sources of aerosols (PM2.5) in the Southeast (Liu et al.
2006], Lee et al. ,
Ke et al. ). It is
also used as a new way to evaluate model simulated ozone
enhancements by tropospheric photochemical production and
transport from the stratosphere (Shim et al. ) and
to estimate sources of biogenic emissions (Shim et al. ).
inversion of trace gas emissions is another advanced statistical
method we use in analyzing measurements and model simulations.
By quantifying the difference between model simulations and
observations, we derive the a posteriori emissions that best
represent our current knowledge of the emissions processes and
available atmospheric measurements. We have used the method to
derive the global emissions of two environmentally important
trace gases, isoprene (Shim et al. ) and CH3Cl
(Yoshida et al. ).
0-1 D modeling
Point (0-D) model is built with our
current understanding of photochemical reactions. It captures
the complexity of photochemical interactions. The models are
generally constrained by the observed concentrations of some
(long-lived) species. The model predictions of the other
(generally shorter-lived) species can be compared to the
observations. Disagreement between simulated and observed
concentrations therefore indicates the problems in our current understanding
of photochemistry and points to the need for laboratory studies.
We have applied a point model to examine the photochemistry at
northern mid and high latitudes (Wang et al. [2003a],
Fried et al. ,
Kondo et al. ).
The 1-D model captures the effects of
vertical transport in addition to photochemical reactions in the
0-D model. Over the tropical Pacific, convective transport is a
critical process that defines the characteristics of the
photochemical environment (Wang et al. [2000b;
analyzing the measurements over the South Pole, we apply the 1-D
model to derive NOx emissions from snow based on
surface measurements. Parameterization of snow NOx emissions
allowed us to conduct the first 3-D chemical transport model
study of photochemistry over the Antarctic Plateau (Wang et al.
Regional and global 3-D modeling
The 3-D models attempt to simulate
the interaction between photochemistry and dynamic transport.
The processes include emissions, transport, photochemistry, and
deposition. We have developed or applied several regional or
global chemical transport models.
We have developed a regional 3-D
chemical transport model. Data assimilation of the
meteorological fields is conducted using the
NCAR/Penn State MM5
model or the
Weather Research and Forecasting (WRF) model. For high-latitude simulations, the
polar version of MM5 is used.
We applied the modeling system to examine the halogen-driven
oxidation of ozone and hydrocarbons in the Arctic spring (Zeng
et al. [2003,
2006], Ridley et al. );
photochemistry driven by snow emissions and aerosol transprot
over the Antarctica (Wang et al. ,
Arimoto et al. ,
Davis et al. ); the
signals of lightning NO production and convective transport of
CO over North America and the western North Atlantic in
satellite measurements (Choi et al. ); the late-spring increase of
trans-Pacific pollution transport in the upper troposphere (Wang
et al. ); the
seasonal transition of ozone photochemistry and outflow from
spring to summer over North America (Jing et al. ,
Choi et al. [2008a,
Using this regional 3-D modeling
system, we have provided operational (daily) 48-hour
forecasts of O3 and its precursors over the U.S
(Guillas et al. )
since summer 2003. In addition to this modeling system, we use
Models-3/CMAQ system to investigate the interactions of
biosphere, forest fires, air quality, and climate over the
Southeast (Tian et al. ;
Zeng et al. ).
Previously we have applied a global
3-D chemical transport model to examine the origin of
tropospheric ozone, global ozone and OH changes due to human
activities since preindustrial tims, and the climatic impacts (Wang et al. [1998a,
Wang and Jacob ,
Hansen et al. ). We currently use the
GEOS-CHEM model for global simulations. The assimilated
meteorological fields are provided by the Goddard Earth
Observing System (GEOS) of the
Modeling Assimilation Office. The model has been used to
investigate the distributions of global CH3Cl
et al. ); Bayesian inversion of
global isoprene and CH3Cl sources (Shim et al.
; Yoshida et al. ); the tracer (ethane and propane) correlation in the
troposphere and its usage in evaluating model transport (Wang
and Zeng ); ozone enhancements at northern
mid latitudes (Shim et al. ).