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

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Table 3‐12. Tracer plume arrival and duration statistics for the GP80 100 km arc. Arrival on Arc Leave Arc Duration on Arc Scenario Day Hour Day Hour Hours Difference Observed 190 16 190 20 5 1998 EPA Report 1998EPA_PG 190 16 190 21 6 20% 1998_CAL 190 16 190 20 5 0% CALPUFF/CALMET BASEA_AER 190 16 190 20 5 0% BASEA_CAL 190 16 190 20 5 0% BASEA_PG 190 16 190 20 5 0% EXP1A_AER 190 16 190 20 5 0% EXP1A_CAL 190 16 190 20 5 0% EXP1A_PG 190 16 190 20 5 0% EXP1B_AER 190 16 190 19 4 ‐20% EXP1B_CAL 190 16 190 19 4 ‐20% EXP1B_PG 190 16 190 19 4 ‐20% EXP1C_AER 190 17 190 20 4 ‐20% EXP1C_CAL 190 17 190 20 4 ‐20% EXP1C_PG 190 17 190 20 4 ‐20% EXP2A_AER 190 16 190 20 5 0% EXP2A_CAL 190 16 190 20 5 0% EXP2A_PG 190 16 190 21 6 20% EXP2B_AER 190 16 190 19 4 ‐20% EXP2B_CAL 190 16 190 19 4 ‐20% EXP2B_PG 190 16 190 20 5 0% EXP2C_AER 190 17 190 20 4 ‐20% EXP2C_CAL 190 17 190 20 4 ‐20% EXP2C_PG 190 17 190 20 4 ‐20% EXP3A_AER 190 16 190 20 5 0% EXP3A_CAL 190 16 190 20 5 0% EXP3A_PG 190 16 190 20 5 0% EXP3B_AER 190 16 190 20 5 0% EXP3B_CAL 190 16 190 20 5 0% EXP3B_PG 190 16 190 19 4 ‐20% EXP3C_AER 190 17 190 20 4 ‐20% EXP3C_CAL 190 17 190 20 4 ‐20% EXP3C_PG 190 17 190 20 4 ‐20% CALPUFF/MMIF MMIF12_AER 190 17 190 20 4 ‐20% MMIF12_CAL 190 17 190 20 4 ‐20% MMIF12_PG 190 17 190 20 4 ‐20% MMIF36KM_AER 190 17 190 19 3 ‐40% MMIF36KM_CAL 190 17 190 19 3 ‐40% MMIF36KM_PG 190 17 190 19 3 ‐40% 33
Tables 3‐13 and Figures 3‐2 through 3‐6 display the plume fitting model performance statistics for the various CALPUFF sensitivity tests and the 100 km arc of receptors in the GP80 field experiment and compares them with the previous results as reported by EPA (1998a). The fitted predicted and observed plume centerline concentrations (Cmax) and the percent differences, expressed as a mean normalized bias (MNB), are shown in Table 3‐13 with the MNB results reproduced in Figure 3‐2. Similar results are seen for the predicted and observed maximum concentrations at any monitoring site along the arc (Omax) that are shown in Table 3‐13 and Figure 3‐3. The use of either the CALPUFF (CAL) or AERMOD (AER) algorithms for the turbulence dispersion doesn’t appear the affect the maximum concentration model performance. Most CALPUFF sensitivity simulations overestimate the observed Cmax value by over 40%, with the 1998EPA_PG and EXP2C_PG simulations overestimating the observed Cmax value by over a factor of 2 (> 100%). The overestimation of the observed Omax value is even greater, exceeding 60% for most of the CALPUFF simulations. The PG dispersion produces much higher maximum concentrations compared to CAL/AER dispersion for experiments EXP2B and EXP2C. But the PG maximum concentrations are comparable or even a little lower than CAL/AER for the other experiments; although in the 1998 EPA study the PG dispersion option produced much higher maximum concentrations. The EXP1B, EXP2B and EXP3B CALPUFF simulations do not exhibit the large overestimation bias of Cmax and Omax as seen in the other experiments and are closest to reproducing the observed maximum concentrations on the 100 km arc, matching the observed values to within ±25%; note that the “B” series of experiments use MM5 data (12, 36 and 12 km for EXP1, EXP2 and EXP3, respectively) but only surface and no upper‐air meteorological observations. The CALPUFF/MMIF simulation using the 12 km MM5 data and PG dispersion also reproduced the maximum concentrations to within ±25%. Most of the CALPUFF sensitivity simulations underestimate the plume spread (σy) by 20% to 35% (Figure 3‐4), which is consistent with overestimating the observed maximum concentration (i.e., insufficient dispersion leading to overestimation of the maximum concentrations). The exceptions to this are again the “B” series of CALPUFF/CALMET experiments and MMIF12KM_PG. Another exception to this is the EPA1998_PG simulation which agrees with the observed plume spread amount quite well; the explanation for this is unclear and seems inconsistent with the fact that 1998BASE_PG overestimated the observed Cmax/Omax values. The 1998EPA_PG results were taken from the EPA (1998a) report and could not be verified or quality assured so we cannot explain this discrepancy. The deviations between the observed and predicted plume centerline along the 100 km arc of receptors in degrees is shown in Figure 3‐5. The modeled plume centerline tends to be 0 to14 degrees off from the observed plume centerline. The best performing model configuration for the plume centerline location is the BASEA series that uses CALMET with observed surface and upper‐air meteorological data but no MM5 data. The CALPUFF/CALMET sensitivity tests that use surface and upper‐air (“A” series) and just surface (“B” series) meteorological observations tend to perform best for the plume centerline location, whereas the sensitivity tests that uses no meteorological observations (“C” series) performs the worse, with the plume centerline tending to be 10 to 14 degrees too far west on the 100 km arc for the “C” series of CALPUFF/CALMET sensitivity tests. The CALPUFF/MMIF runs, which also do not include any meteorological observations, also tend to have plume centerlines that are 6 to 12 degrees too far to the west. Most of the CALPUFF sensitivity tests have cross wind integrated concentrations (CWIC) that are within ±20% of the observed value along the 100 km arc (Figure 3‐6 and Table 5‐13). The 34
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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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Page 23 and 24: 2.4 2 1.6 1.2 0.8 0.4 0 EXP4A EXP4B
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Page 27 and 28: Evaluatioon of Six LRT T Dispersion
Page 29 and 30: Table ES‐6. Summary of model rank
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Page 33 and 34: ETEX LRT Dispersion Model Sensitivi
Page 35 and 36: CONCLUSIONS OF LRT DISPERSION MODEL
Page 37 and 38: The CAMx and CALGRID Eulerian photo
Page 39 and 40: July 1980. Both experiments examine
Page 41 and 42: 1.3 ORGANIZATION OF REPORT Chapter
Page 43 and 44: puffs expand until they exceed the
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Page 47 and 48: The ETEX real‐time LRT modeling p
Page 49 and 50: 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
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Page 75 and 76: 30% 20% 10% 0% ‐10% ‐20% ‐30%
Page 77 and 78: 120% 100% 80% 60% 40% 20% 0% ‐20%
Page 79 and 80: 20% 10% 0% ‐10% ‐20% ‐30% ‐
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 and 102: the fitted Gaussian plume is not a
Page 103 and 104: Figure 4‐2. Comparison of predict
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 119 and 120: 40% 35% 30% 25% 20% 15% 10% 5% 0% E
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5.4.1.4 Comparison of CALPUFF CTEX3
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0.48 0.36 0.24 0.12 0 ‐0.12 16% 1
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CTEX3 discussed in Section 5.4.1. A
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CALPUFF sensitivity simulations are
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14. Across all the spatial statisti
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sensitivity tests. The “B” seri
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‐0.1 ‐0.2 0 0.8 0.7 0.6 0.5 0.4
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6.0 1994 EUROPEAN TRACER EXPERIMENT
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Figure 6‐2a. Surface synoptic met
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Figure 6‐3a. Distribution of the
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36 kilometers and the vertical stru
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splitting flag near sunset (hour 17
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experienced during the original ETE
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2 1 0 ‐1 ‐2 3 2 1 0 23‐Oct 23
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70% 60% 50% 40% 30% 20% 10% 0% Figu
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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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