Documentation of the Evaluation of CALPUFF and Other Long ...

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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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Documentation of the Evaluation of
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FOREWARD This report documents the
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2.4.3 ATMES‐II Model Evaluation A
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EXECUTIVE SUMMARY ABSTRACT The CALP
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OVERVIEW OF APPROACH Up to six LRT
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CALPUFF performance is evaluated by
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Table ES‐2. ATMES‐II spatial an
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• CALPUFF tended to overstate the
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• The best performing CALPUFF con
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2009a). The key findings from the C
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1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2
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2.4 2 1.6 1.2 0.8 0.4 0 EXP4A EXP4B
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Figure ESS‐4. RANK statistical pe
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Evaluatioon of Six LRT T Dispersion
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Table ES‐6. Summary of model rank
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eproduce the northwest to southeast
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ETEX LRT Dispersion Model Sensitivi
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CONCLUSIONS OF LRT DISPERSION MODEL
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The CAMx and CALGRID Eulerian photo
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July 1980. Both experiments examine
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1.3 ORGANIZATION OF REPORT Chapter
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puffs expand until they exceed the
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that performance evaluation be base
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The ETEX real‐time LRT modeling p
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The ETEX study has formulated the f
Page 51 and 52: In this study we expand the LRT mod
Page 53 and 54: AM ∩ AP FMS = × 100% (2‐2) A
Page 55 and 56: Factor of α (FAα): FAα represent
Page 57 and 58: 3.0 1980 GREAT PLAINS FIELD STUDY 3
Page 59 and 60: compact discs, which were used to o
Page 61 and 62: ILEVZI = 1 Layer of winds to use in
Page 63 and 64: MCHEM = 0 No chemical transformatio
Page 65 and 66: Table 3‐6. CALPUFF/CALMET experim
Page 67 and 68: Table 3‐11. CALPUFF/MMIF sensitiv
Page 69 and 70: evaluation studies and evaluate whe
Page 71 and 72: Tables 3‐13 and Figures 3‐2 thr
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Page 77 and 78: 120% 100% 80% 60% 40% 20% 0% ‐20%
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Page 81 and 82: The fitted Gaussian plume statistic
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Page 89 and 90: with APS, implementing the slug opt
Page 91 and 92: the amount of time that the tracer
Page 93 and 94: Figure 4‐1. CALPUFF/CALMET UTM mo
Page 95 and 96: compact discs, which were used to o
Page 97 and 98: Table 4‐4. CALPUFF parameters use
Page 99 and 100: Table 4‐8. CALPUFF/MMIF sensitivi
Page 101: the fitted Gaussian plume is not a
Page 105 and 106: Figure 5‐1. Location of Dayton an
Page 107 and 108: MM5 runs, the first without FDDA (i
Page 109 and 110: Table 5‐3. MM5 sensitivity tests
Page 111 and 112: Table 5‐6. Definition of the CALM
Page 113 and 114: performance at the monitor location
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Page 117 and 118: 40% 35% 30% 25% 20% 15% 10% 5% 0% F
Page 119 and 120: 40% 35% 30% 25% 20% 15% 10% 5% 0% E
Page 121 and 122: 5.4.1.4 Comparison of CALPUFF CTEX3
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Page 125 and 126: CTEX3 discussed in Section 5.4.1. A
Page 127 and 128: CALPUFF sensitivity simulations are
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Page 131 and 132: sensitivity tests. The “B” seri
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Page 135 and 136: 6.0 1994 EUROPEAN TRACER EXPERIMENT
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Page 139 and 140: Figure 6‐3a. Distribution of the
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Page 151 and 152: Figure 6‐9. Factor of Exceedance
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eceiving a 0.0 score. Figure 6‐13
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Table 6‐1. Summary of model ranki
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plume spread and observed surface c
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Figure 6‐16c. Comparison of spati
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• NoPiG: The tracer emissions wer
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Using the NMSE statistical performa
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6.4.3.2 Effect of PiG on Model Perf
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80 70 60 50 40 30 20 10 0 1 2 3 4 5
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Table 6‐3. Summary of CALPUFF puf
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0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.
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Figure 6‐ ‐22 displays the t sp
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Figure 6‐ ‐23a. Global model pe
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Figure 6‐24. Figure of Merit (FMS
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7.0 REFERENCES Anderson, B. 2008. T
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EPA, 1984: Interim Procedures for E
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Mlawer, E.J., S.J. Taubman, P.D. Br
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148 Appendix A Evaluation of the MM
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Table A‐1. Wind speed and wind di
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Table A‐3. Definition of the CTEX
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Figure A‐ ‐1. Wind speed bias (
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Figure A‐ ‐3. Humidity bias and
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Table A‐5. Comparison of CTEX5 MM
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B.1 CALMET MODEL EVALUATION TO IDEN
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Figure B‐ ‐1 displays th he win
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Table B‐2a. Summary wind speed mo
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B.2 CONCLUSIONS OF CTEX3 CALMET SEN
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C.1 INTRODUCTION In this section, t
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C.2.2 HYYSPLIT GLOB BAL STATISTIICS
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The final panel in Figure C‐3 (bo
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Figure C‐ ‐5. Global model m pe
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C.3 CAMX SENSITIVITY TESTS Followin
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ACM2 Kzz combinatio ons rank as the
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Figure C‐ ‐10. Spatial model pe
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Figure C‐ ‐12. Global model per
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Figure C‐ ‐13. Spatial model pe
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Table C‐3. CAMx FMS and POD spati
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Figure C‐ ‐20. False Alarm Rate
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Figure C‐ ‐23. Factor of o Exce
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The PCC values for th he six LRT mo
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The RANK statistical performancce m
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Table C‐55. Summary y of model r
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Results foor the TS me etric are pr
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Figure C‐ ‐35. Factor of o 2 (F
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a negativve FB. The best b performm
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performing model the most often sco
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United States Environmental Protect
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