MODELS3 – IMPROVE – PM/FRM:Comparison of Time-Averaged Concentrations
R. B. Husar S. R. Falke1 and B. S. Schichtel2 Center for Air Pollution Impact and Trend Analysis (CAPITA)
Washington University, St. Louis
1 Now AAAS Fellow, US EPA, Washington DC
2 Now at CIRA, Colorado State U., Ft. Collins
Progress Report on Coop. No. CR 827981
to
U.S. Environmental Protection Agency
Office of Research and Development
Research Triangle Park, NC 27711
Background
This is the fourth progress report on the spatial comparison MODELS-3 simulation with observations.
This report focuses on the comparison of the IMPROVE chemical speciated data with the MODELS-3 simulation of those species.
Previous progress reports dealt with: PM Concentration Maps for MODELS-3 Comparison: Data Integration and Mapping
Methodology Eastern U.S. PM Concentration Dependence on Elevation Relationship Between Visibility and PM2.5 Concentration
Methodology
The goal of this analysis is to examine if systematic spatial differences exists between the model and the observations.
The comparison was therefore conducted on concentrations averaged over the simulation period.
The MODELS-3 comparison with data was performed using the IMPROVE speciated data.
For each operating IMPROVE site, the average species concentration (July 5, 8, 12, 15) was calculated along with the corresponding 4 day average from the model grid.
The data pairs are presented in model-data scatter plots including the correlation statistic. The measured data are also plotted on the average simulated contour maps.
Fine Mass The measured and modeled FM2.5 concentrations at
the 18 IMPROVE sites correlate well (R2= 0.84).
The model PM2.5 is systematically lower (84%) than the measured values.
The measured values also show an offset of about 4 ug/m3.
There no evidence of systematic spatial bias in the model-data comparison.
Fine M ass: M odels3-IM PROVE Average
y = 0.8385x - 4.1536
R2 = 0.84
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IMPROVE, ug/m3
MO
DE
LS
3,
ug
/m3
PM10 Mass The measured and modeled PM10
concentrations correlate reasonably well (R2= 0.56).
The model PM10 is systematically lower then the IMPROVE values, except for Washington DC.
The measured PM10 also show an offset of about 10 ug/m3.
There no evidence of regional bias in the model-data comparison. However, at the Washington DC urban site, the model significantly overestimates the measured values.
PM10 Mass: Models3-IMPROVE Average
y = 1.0509x - 10.715
R2 = 0.5644
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IMPROVE, ug/m3
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LS
3,
ug
/m3
M3- FRM PM10 Comparison For the ’95 episode, PM10 data exists for over 700
AIRS stations. The measured PM10 data (right) are generally higher
then the values (bottom right). The pattern of the data-model difference (below)
shows the largest deviations (up to ~30 ug/m3) in the western part of the domain.
It is also notable that near urban areas the model exceeds the measured values while in rural areas measured values are higher.
In other words, the data indicate a spatially smoother pattern while the model shows more patchiness near urban areas.
Coarse Mass The measured Coarse Mass was
calculated as CM = PM10 – PM2.5
The measured and modeled Coarse PM10 concentrations have virtually zero correlation (R2= 0.009).
The lack of correlation seems to be throughout the domain.
Coarse Mass: Models3-IMPROVE Average
y = -0.1654x + 6.1346
R2 = 0.0092
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IMPROVE, ug/m3
MO
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LS
3,
ug
/m3
Fine Sulfate The measured and modeled sulfate
concentrations over the Easter US correlate remarkably well (R2= 0.863).
The model PM2.5 is systematically higher (slope 1.26) then the measured values.
The measured values do not show an offset for sulfate.
There no evidence of systematic spatial bias in the model-data comparison.
SO4: Models3-IMPROVE Average
Models3 = 1.26 * IMPROVE
R2 = 0.863
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0.00 5.00 10.00 15.00 20.00IMPROVE SO4, ug/m3
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LS
3 S
O4
, u
g/m
3
Fine Organics The measured organics used in this
comparison is the sum of O1+O2+O3+O4+AC
The measured and modeled organics have virtually zero correlation (R2= 0.03).
At all the IMPROVE sites, the model organics are at about 1.8 ug/m3 (coincidence??) while the measured values range from 2. 5 to 7 ug/m3 .
Unfortunately, there are no organics data in the areas of high model values.
Organics: Models3-IMPROVE Average
y = -0.0455x + 1.8181
R2 = 0.0326
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IMPROVE, ug/m3
MO
DE
LS
3,
ug
/m3
Primary Smoke(?)July 5, 8, 12, 15, 1995
A possible reason for the low model organics is the omission of biomass smoke events in the model (????).
The pictures show estimates of primary organics from biomass burning based on potassium tracer values
Evidently, during the July 95 episode, biomass smoke was a significant contributor to organic PM.
Fine Nitrate In the summer season, the nitrate
concentration is very low compared to other species.
The measured and modeled nitrates have virtually zero correlation (R2= 0.0007).
Because of the meta-stability of nitrates, filter measurement of nitrates are problematic.
Nitrate M ass: M odels3-IM PROVE Average
y = -0.0426x + 0.1663
R2 = 0.0007
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IMPROVE, ug/m3
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3 S
O4
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g/m
3
Fine Soil The measured dust (soil) concentration is
calculated by Malm’s formula: Soil=2.2AL+2.49SI+1.63CA+2.42FE+1.94TI
The measured and modeled fine soil have inverse correlation (R2= 0.08, slope -0.16).
The highest measured Fine Soil is in the Southeast (Florida) where the model Fine Soil is low.
The high model Fine Soil values are in the urban areas.
Limited urban Fine Soil data (Washington DC), but they indicate minor urban contribution.
Fine Soil: Models3-IMPROVE Average
y = -0.1578x + 1.5974
R2 = 0.0849
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IMPROVE, ug/m3
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/m3
Sahara DustJuly 5, 8, 12, 15, 1995
The reason for the high Fine Soil values in Florida is the dominance of Sahara dust in July that is not include in the model simulation.
The maps show the daily average Fine Soil concentration on July 5, 8, 12 and 15. The chemical signature of these dust events indicates Sahara dust.
Evidently, during the July 95 episode (as in any other July), Sahara dust has contributed significantly to the Fine PM mass in the Southeast.
Conclusions
The speciated IMPROVE network and the PM10 FRM network allow a comparison of MODELS-3 simulation with the observed values.
PM2.5 simulation matches the observations very well (R2= 0.84). For sulfate, the model-data correlation over a wide geographic region is
excellent (R2= 0.86) but there is an upward bias of about 25%. The model-data comparison for coarse mass, organics, nitrates and fine soil
is poor.