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

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Table 4‐6. CALPUFF dispersion options examined in the CALPUFF sensitivity tests. Experiment MDISP MCTURB Comment CAL 2 1 Dispersion coefficients from internally calculated sigma‐v and sigma‐w using micrometeorological variables and CALPUFF algorithms AER 2 2 Dispersion coefficients from internally calculated sigma‐v and sigma‐w using micrometeorological variables and AERMOD algorithms PG 3 ‐‐ PG dispersion coefficients for rural areas and MP coefficients for urban areas The CALMET and CALPUFF simulations used for the sensitivity analyses were updated from the BASE case model configuration that was designed to be consistent with the 1998 EPA study by using recommended settings for many variables from the August 2009 EPA Clarification Memorandum. A summary of CALMET parameters that changed from the BASE case scenarios for the CALPUFF sensitivity tests are presented in Table 4‐7. Table 4‐7. CALMET wind field parameters for the SRL75 tracer experiment. CALMET Option 2009 EPA‐FLM Default BASE EXP1A EXP1B EXP1C NOOBS 0 0 0 1 2 ICLOUD 0 0 0 0 3 IEXTRP ‐4 4 ‐4 ‐4 1 IPROG 14 0 14 14 14 ITPROG 0 0 0 1 2 ZIMIN 50 100 50 50 50 ZIMAX 3000 3200 3000 3000 3000 RMAX1 100 20 100 100 50 RMAX2 200 50 200 200 100 4.2.4 CALPUFF/MMIF Sensitivity Tests With the MMIF software tool designed to reformat the MM5/WRF meteorological model output data for input into CALPUFF, there are much less options available and hence much fewer sensitivity tests as shown in Table 4‐8. 61
Table 4‐8. CALPUFF/MMIF sensitivity tests analyzed with the SRL75 tracer experiment. Grid Resolution MM5 MDISP MCTURB Comment 36 km 36 km 2 1 36 km MM5 with CALPUFF turbulence dispersion 36 km 36 km 2 2 36 km MM5 with AERMOD turbulence dispersion 36 km 36 km 3 ‐‐ 36 km MM5 with Pasquill‐Gifford dispersion 12 km 12 km 2 1 12 km MM5 with CALPUFF turbulence dispersion 12 km 12 km 2 2 12 km MM5 with AERMOD turbulence dispersion 12 km 12 km 3 ‐‐ 12 km MM5 with Pasquill‐Gifford dispersion 4 km 4 km 2 1 4 km MM5 with CALPUFF turbulence dispersion 4 km 4 km 2 2 4 km MM5 with AERMOD turbulence dispersion 4 km 4 km 3 ‐‐ 4 km MM5 with Pasquill‐Gifford dispersion 4.3 QUALITY ASSURANCE The quality assurance (QA) of the CALPUFF modeling system simulations for the SRL tracer experiment was assessed by analyzing the CALMET and CALPUFF input and output files and the dates they were generated. The input file options were compared against the EPA‐FLM recommended settings from the August 2009 Clarification Memorandum (EPA, 2009b) and the definitions of the sensitivity tests to assure that the intended parameters were varied. The QA of the MMIF runs was not completed because no input files or list files were provided to document the MMIF parameters. The CALMET sensitivity simulations used a radius of influence of terrain on wind fields equal to 10 m (TERRAD = 10). The 2009 EPA Clarification Memorandum recommends TERRAD = 15. The CALMET sensitivity simulations used a minimum extrapolation distance between surface and upper air stations of 4 km (RMIN2 = 4). The 2009 EPA Clarification Memorandum recommends RMIN2 = ‐1. Four CALMET parameters (BIAS, NSMTH, NINTR2, and FEXTR2) require a value for each vertical layer processed in CALMET. The CALMET BASE case has six vertical layers, but the sensitivity simulations are based on ten vertical layers. The CALMET sensitivity simulations were provided with only six values for BIAS, NSMTH, NINTR2, and FEXTR2 even though ten vertical layers were simulated. Therefore, CALMET used default values for the upper four vertical layers (i.e., 1200 m, 2000 m, 3000 m, and 4000 m). In addition to the three CALPUFF dispersion options (AERMOD, CALPUFF, and PG), there were other CALPUFF parameters that differed between the CALPUFF/CALMET (BASE and sensitivity cases) and CALPUFF/MMIF modeling scenarios. The CALPUFF parameter differences include: • CALPUFF/CALMET sensitivity runs using AERMOD and CALPUFF dispersion were conducted using near‐field slug formation (MSLUG = 1), but the CALPUFF/CALMET PG and CALPUFF/MMIF runs were conducted using puffs (MSLUG = 0). • CALPUFF/CALMET sensitivity runs using AERMOD and CALPUFF dispersion were set‐up to not allow for partial plume penetration of inversion layer (MPARTL = 0). The quality assurance of the post‐processing of the SRL75 CALPUFF runs uncovered two errors. The first was that the conversion factor to convert the SF6 tracer concentrations from mass per volume to ppt was approximately three times too large. The second error was that when calculating the integrated concentrations along the arc, the wrong time period was specified. These two errors were fixed and the CALPUFF results re‐processed to generate new plume fitting statistical performance measures. 62
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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
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
Page 69 and 70: evaluation studies and evaluate whe
Page 71 and 72: Tables 3‐13 and Figures 3‐2 thr
Page 73 and 74: 140% 120% 100% 80% 60% 40% 20% 0%
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
Page 83 and 84: 0% ‐10% ‐20% ‐30% ‐40% ‐5
Page 85 and 86: 300% 250% 200% 150% 100% 50% 0% 300
Page 87 and 88: 60% 40% 20% 0% ‐20% ‐40% ‐60%
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: Table 4‐4. CALPUFF parameters use
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
Page 115 and 116: 35% 30% 25% 20% 15% 10% 5% 0% 35% 3
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
Page 123 and 124: 0.48 0.36 0.24 0.12 0 ‐0.12 16% 1
Page 125 and 126: CTEX3 discussed in Section 5.4.1. A
Page 127 and 128: CALPUFF sensitivity simulations are
Page 129 and 130: 14. Across all the spatial statisti
Page 131 and 132: sensitivity tests. The “B” seri
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Page 135 and 136: 6.0 1994 EUROPEAN TRACER EXPERIMENT
Page 137 and 138: Figure 6‐2a. Surface synoptic met
Page 139 and 140: Figure 6‐3a. Distribution of the
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Page 145 and 146: experienced during the original ETE
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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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