Platform Presentation
Retrieval of North American Sulfur, Nitrogen, and Ammonia Emission Fields from
Air Quality Data
Bret A. Schichtel
Rudolf Husar
Washington University
Center for Air Pollution Impact
and Trend Analysis
St. Louis, MO, 63130-4899
314-935-6099
314-935-6145
Bret@mecf.wustl.edu
Washington University
Center for Air Pollution Impact
Impact and Trend Analysis
St. Louis, MO, 63130-4899
314-935-6099
314-935-6145
Rhusar@mecf.wustl.edu
Abstract
A general approach is described for the retrieval of emission fields from air quality data. The
approach is based upon the inversion of the source receptor relationship (SRR), where in the
SRR the receptor concentrations are linearly related to the emission fields via the transfer matrix.
In this work the transfer matrix was computed from a regional Monte Carlo particle dispersion
model whose kinetics were calibrated for the simulation of SO2 and SO42- over the Eastern US
using the SO2 emission field from the 1985 NAPAP inventory. The retrieval of North American
seasonal sulfur emissions was then accomplished by inverting the SRR using ambient
concentration and wet deposition data and the model-derived transfer matrices. The retrieved
emission field was then compared to the NAPAP emissions. The inversion method is based
upon a robust version of the singular value decomposition that both estimates the unknown
emissions as well as the standard error. The reconstruction of the quarter 2 and 3 SO2 emissions
compared favorable with the 1985 NAPAP inventory identifying the major source regions, such
as the Ohio river valley, and their source strengths. However, quarter 1 and 4 retrieved
emissions displayed a rather uniform emission pattern over the Eastern US. The inversion
procedure was also applied to NH4+ and NO3- wet deposition data for the retrieval of seasonal
NH3 and NOX emissions over North America. All retrievals used the same transfer matrices as
in the SO2 retrieval. The NOX emission fields compared favorable with 1985 NAPAP estimates.
However, the NH3 retrieved emissions estimated the highest emissions over the Industrial
Midwest while the 1985 NAPAP inventory estimated them over Iowa.
Platform Presentation
Derivation of SO2 – SO42- transformation and deposition rate Coefficients over the
Eastern US using a Semi-Empirical Approach
Bret A. Schichtel
Rudolf Husar
Washington University
Center for Air Pollution Impact
and Trend Analysis
St. Louis, MO, 63130-4899
314-935-6099
314-935-6145
Bret@mecf.wustl.edu
Washington University
Center for Air Pollution Impact
Impact and Trend Analysis
St. Louis, MO, 63130-4899
314-935-6099
314-935-6145
Rhusar@mecf.wustl.edu
Abstract
A semi-empirical approach is described which allows for the derivation of a consistent set of
chemical and physical rate coefficient equations. The main thrust of this approach is to make
maximum use of existing meteorological, emission, and receptor data in conjunction with a
physico-chemical model to derive the best set of rate coefficient equations. Assuming the
pollutant transport and emission rates are known, only the transformation and removal rates are
unknown. These coefficients are then determined via a tuning process to obtain the best fit
between simulated and measured ambient and wet deposition data allowing the transformation
and removal rates to vary within physically reasonable limits. The spatial and temporal
variability of the rate coefficients are modeled by making them dependent upon meteorological,
and chemical variables. It is hypothesized that given sufficient quality and quantity of data, it
will be possible to identify a unique set of rate parameters, thereby properly simulating the
physical/chemical processes.
This approach is applied in the Eastern US during 1992 to derive SO2 to SO42- transformation
and SO2 and SO42- dry and wet deposition rate coefficients. A Monte Carlo long range transport
model is used to simulate the ambient SO2 and SO42- and the total wet deposited sulfur which is
compared to measured data. The resulting best fit spatial and seasonal patterns of the rate
coefficients are presented as well as the simulated SO2 and SO42- ambient concentrations and wet
deposition rates.
Poster Presentation
A World Wide Web based Airmass History Server
Bret A. Schichtel
Rudolf Husar
Washington University
Center for Air Pollution Impact
and Trend Analysis
St. Louis, MO, 63130-4899
314-935-6099
314-935-6145
Bret@mecf.wustl.edu
Washington University
Center for Air Pollution Impact
Impact and Trend Analysis
St. Louis, MO, 63130-4899
314-935-6099
314-935-6145
Rhusar@mecf.wustl.edu
Abstract
Airmass history analysis techniques are useful tools in the interpretation of air quality data, and
their use has expanded considerably over the past ten years. However, the use of these
techniques has been limited to a handful of “experts” due to an inability for most to obtain the
airmass history data.
In order to make airmass history data widely available an airmass history server, assessable from
the World Wide Web, has been established. The server is based upon a Monte Carlo particle
dispersion model and is driven by three dimensional meteorological data from the National
Meteorological Center’s Nested Grid Model. The data set covers most of North America for the
years 1991 – 1995. The server allows for the generation of three dimensional forward and
backward trajectories from multiple locations and time periods. In addition to the trajectories,
meteorological variables such as temperature, relative humidity, precipitation, etc. along the
trajectory pathways can be saved out, creating the airmass history. The data is returned to the
client in a number of formats from raw ASCII data to animations.