Documentation of the Evaluation of CALPUFF and Other Long ...
Documentation of the Evaluation of CALPUFF and Other Long ... Documentation of the Evaluation of CALPUFF and Other Long ...
Table 4‐9. CALPUFF model performance statistics using the Irwin plume fitting evaluation approach using the SRL75 field experiment and the 1998 EPA study and the CALPUFF sensitivity tests. CALPUFF Cmax 1 Omax Sigma‐y 1 Plume Centerline CWIC Sensitivity Test (ppt) MNB (ppt) MNB (meters) MNB (degrees) 65 Diff (deg) (ppt/m 2 ) MNB Observed 2.739 5.07 11643 125.59 79,940 EPA 1998 PG 7.20 163% 6.90 36% 7200 ‐38% 143 17 129,000 61% Similarity 5.1 86% 5.00 ‐1% 6000 ‐48% 143 17 77,000 ‐4% MMMIF 4KM_AER 8.791 221% 8.625 70% 6810 ‐42% 135.9 10.31 150,100 88% 4KM_CAL 8.79 221% 8.625 70% 6801 ‐42% 135.9 10.31 149,800 87% 4KM_PG 8.798 221% 8.656 71% 6844 ‐41% 135.9 10.31 150,900 89% 12KM_AER 10.63 288% 10.41 105% 6587 ‐43% 133.8 8.21 175,500 120% 12KM_CAL 10.79 294% 10.42 106% 6492 ‐44% 133.8 8.21 175,500 120% 12KM_PG 10.7 291% 10.49 107% 6545 ‐44% 133.8 8.21 175,500 120% 36KM_AER 11.61 324% 11.4 125% 6315 ‐46% 134.1 8.51 183,800 130% 36KM_CAL 11.62 324% 11.41 125% 6311 ‐46% 134.1 8.51 183,800 130% 36KM_PG 12.46 355% 12.24 141% 6072 ‐48% 133.7 8.11 189,700 137% CALMET BASE_AER 3.495 28% 3.241 ‐36% 6640 ‐43% 145.8 20.21 58,180 ‐27% BASE_CAL 3.505 28% 3.239 ‐36% 6612 ‐43% 145.8 20.21 58,100 ‐27% BASE_PG 7.322 167% 6.734 33% 6941 ‐40% 144.8 19.21 127,400 59% EXP1A_AER 4.849 77% 4.691 ‐7% 6383 ‐45% 144.5 18.91 77,580 ‐3% EXP1A_CAL 4.849 77% 4.691 ‐7% 6385 ‐45% 144.5 18.91 77,600 ‐3% EXP1A_PG 7.138 161% 7.337 45% 6307 ‐46% 143.4 17.81 112,800 41% EXP1B_AER 5.318 94% 5.289 4% 6132 ‐47% 145.3 19.71 81,740 2% EXP1B_CAL 5.303 94% 5.277 4% 6148 ‐47% 145.3 19.71 81,720 2% EXP1B_PG 6.468 136% 7.022 39% 6190 ‐47% 144.7 19.11 100,300 25% EXP1C_AER 7.892 188% 7.754 53% 5939 ‐49% 137.4 11.81 117,500 47% EXP1C_CAL 7.981 191% 7.843 55% 5926 ‐49% 137.4 11.81 118,600 48% EXP1C_PG 8.318 204% 8.167 61% 5697 ‐51% 137.1 11.51 118,800 49% 1. Because of the poor fit of the fitted Gaussian plume with the observed tracer concentrations in the SRL75 experiment, the Cmax and Sigma‐y are not meaningful metrics of model performance.
Figure 4‐2. Comparison of predicted fitted plume with observations for the SRL75 tracer experiments (Source: EPA, 1998a). Note that results from this study are not shown. With the exception of the plume centerline statistic, the Irwin plume fitting evaluation approach was not a very useful evaluation tool for comparing the model predictions and observations using the SRL75 field experiment data. However, it is a useful tool for comparing the CALPUFF simulations using the different versions of CALPUFF/CALMET. The BASE CALPUFF/CALMET sensitivity test in this study was designed to be setup in the same fashion as the 1998 EPA tracer modeling study. Although there are some similarities, there are also some differences. For example, using the PG dispersion results in much higher CWIC in both the 1998 EPA (129,000 ppt/m 2 ) and BASE (127,400 ppt/m 2 ) sensitivity tests versus using the CAL turbulence/similarity dispersions options (77,000 ppt/m 2 for 1998 EPA and ~58,000 ppt/m 2 for BASE). The maximum estimated concentration at any of the 200 receptors along the 100 km arc using the PG dispersion are very similar for the 1998 EPA (6.9 ppt) and BASE sensitivity (6.7 ppt) scenario and lower concentrations are estimated using the CAL turbulence dispersion in the 1998 EPA (5.0 ppt) and the BASE (3.2 ppt) sensitivity test. 4.5 CONCLUSIONS OF THE SRL75 MODEL PERFORMANCE EVALUATION Because the fit of the Gaussian plume to the observed tracer concentrations along the SRL75 100 km receptor arc did not match the observed values well, the fitted plume evaluation approach did not work well using the SRL75 database. Thus, there are few conclusions that can be drawn about the CALPUFF model performance using the SRL75 tracer field experiment data. The plume centerline evaluation is still valid and the use of CALPUFF without using meteorological observations with CALMET either through MMIF or with CALMET using no observations (NOOBS = 2) produces better plume centerline performance than when meteorological observations are used with CALMET. These results are consistent with EPA’s thoughts in the 2009 IWAQM Reassessment Report (EPA, 2009a) and August 2009 Clarification Memorandum (EPA, 2009b); it is better to pass through the wind fields and other meteorological field from MM5/WRF to CALPUFF, rather than running them through CALMET, which can introduce artifacts and upset the dynamic balance of the meteorological fields. 66
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Figure 4‐2. Comparison <strong>of</strong> predicted fitted plume with observations for <strong>the</strong> SRL75 tracer<br />
experiments (Source: EPA, 1998a). Note that results from this study are not shown.<br />
With <strong>the</strong> exception <strong>of</strong> <strong>the</strong> plume centerline statistic, <strong>the</strong> Irwin plume fitting evaluation<br />
approach was not a very useful evaluation tool for comparing <strong>the</strong> model predictions <strong>and</strong><br />
observations using <strong>the</strong> SRL75 field experiment data. However, it is a useful tool for comparing<br />
<strong>the</strong> <strong>CALPUFF</strong> simulations using <strong>the</strong> different versions <strong>of</strong> <strong>CALPUFF</strong>/CALMET. The BASE<br />
<strong>CALPUFF</strong>/CALMET sensitivity test in this study was designed to be setup in <strong>the</strong> same fashion as<br />
<strong>the</strong> 1998 EPA tracer modeling study. Although <strong>the</strong>re are some similarities, <strong>the</strong>re are also some<br />
differences. For example, using <strong>the</strong> PG dispersion results in much higher CWIC in both <strong>the</strong> 1998<br />
EPA (129,000 ppt/m 2 ) <strong>and</strong> BASE (127,400 ppt/m 2 ) sensitivity tests versus using <strong>the</strong> CAL<br />
turbulence/similarity dispersions options (77,000 ppt/m 2 for 1998 EPA <strong>and</strong> ~58,000 ppt/m 2 for<br />
BASE). The maximum estimated concentration at any <strong>of</strong> <strong>the</strong> 200 receptors along <strong>the</strong> 100 km<br />
arc using <strong>the</strong> PG dispersion are very similar for <strong>the</strong> 1998 EPA (6.9 ppt) <strong>and</strong> BASE sensitivity (6.7<br />
ppt) scenario <strong>and</strong> lower concentrations are estimated using <strong>the</strong> CAL turbulence dispersion in<br />
<strong>the</strong> 1998 EPA (5.0 ppt) <strong>and</strong> <strong>the</strong> BASE (3.2 ppt) sensitivity test.<br />
4.5 CONCLUSIONS OF THE SRL75 MODEL PERFORMANCE EVALUATION<br />
Because <strong>the</strong> fit <strong>of</strong> <strong>the</strong> Gaussian plume to <strong>the</strong> observed tracer concentrations along <strong>the</strong> SRL75<br />
100 km receptor arc did not match <strong>the</strong> observed values well, <strong>the</strong> fitted plume evaluation<br />
approach did not work well using <strong>the</strong> SRL75 database. Thus, <strong>the</strong>re are few conclusions that can<br />
be drawn about <strong>the</strong> <strong>CALPUFF</strong> model performance using <strong>the</strong> SRL75 tracer field experiment data.<br />
The plume centerline evaluation is still valid <strong>and</strong> <strong>the</strong> use <strong>of</strong> <strong>CALPUFF</strong> without using<br />
meteorological observations with CALMET ei<strong>the</strong>r through MMIF or with CALMET using no<br />
observations (NOOBS = 2) produces better plume centerline performance than when<br />
meteorological observations are used with CALMET. These results are consistent with EPA’s<br />
thoughts in <strong>the</strong> 2009 IWAQM Reassessment Report (EPA, 2009a) <strong>and</strong> August 2009 Clarification<br />
Memor<strong>and</strong>um (EPA, 2009b); it is better to pass through <strong>the</strong> wind fields <strong>and</strong> o<strong>the</strong>r<br />
meteorological field from MM5/WRF to <strong>CALPUFF</strong>, ra<strong>the</strong>r than running <strong>the</strong>m through CALMET,<br />
which can introduce artifacts <strong>and</strong> upset <strong>the</strong> dynamic balance <strong>of</strong> <strong>the</strong> meteorological fields.<br />
66