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

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80 70 60 50 40 30 20 10 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Figure ES‐9. Figure of Merit (FMS) spatial model performance statistics as a function of time at three hour increments since the beginning of the tracer release. The HYSPLIT LRT model was unique among the five LRT dispersion models examined in that it can be run in a particle mode, a Gaussian puff mode or hybrid particle/puff and puff/particle modes. The default configuration used in the HYSPLIT simulations presented previously was the three‐dimensional particle mode. Nine HYSPLIT sensitivity tests were performed using different particle and puff formulation combinations. The RANK scores for the HYSPLIT ETEX sensitivity simulations ranged from 1.01 to 2.09, with the fully puff formulation ranked the lowest and hybrid puff/particle combinations ranked highest. Conclusions of the ETEX LRT Dispersion Model Evaluation Five LRT dispersion models were evaluated using the 1994 ETEX tracer test field experiment data. The CAMx, HYSPLIT and SCIPUFF models were the highest ranked LRT dispersions models, with CAMx performing slightly better than the other two models. The reasons for the poor performance of CALPUFF appear to be due to its inability to adequately treat horizontal and vertical wind shear. The CALPUFF Gaussian puff formulation retains a well‐mixed circular puff despite the presence of wind variations across the puff that would advect tracer concentrations in different directions. Because the puff can only be transported by one wind, CALPUFF is unable to adequately treat such wind variations across the puff. The use of puff splitting, which EPA postulated in 2003 may extend the downwind applicability of the model, failed to have any significant effect on CALPUFF model performance. 28 CAMx CALPUFF FLEXPART HYSPLIT SCIPUFF
CONCLUSIONS OF LRT DISPERSION MODEL TRACER TEST EVALUATION The following are some of the key conclusions of the LRT dispersion model tracer test field experiment evaluation. CALPUFF/CALMET Concentration Predictions are Highly Variable: Use of alternative CALMET input options within their range of reasonableness can produce wide variations in the CALPUFF concentration predictions. Given the regulatory use of CALPUFF, this result points toward the need to have a standard set of recommended CALMET settings for regulatory application of CALPUFF to assure consistency and eliminate the potential of selecting CALMET options to obtain a desired outcome in CALPUFF. No one CALMET configuration consistently produced the best CALPUFF model performance, although use of MM5 data with CALMET did tend to improve CALPUFF model performance with 36 and 12 km MM5 data being better than 80 km MM5 data. Comparison of Current CALPUFF Model Performance with Previous Studies: The comparison of the model performance for current version of CALPUFF with past CALPUFF evaluations from the 1998 EPA study (EPA, 1998a) using the GP80 and SRL75 tracer study field experiments was mixed. For the GP80 100 km receptor arc, the current and past CALPUFF model performance evaluations were consistent with CALPUFF tending to overestimate the plume maximum concentrations and underestimate plume horizontal dispersion. The current version of CALPUFF had difficulty in reproducing the good performance of the past CALPUFF application in estimating the tracer residence time on the GP80 600 km receptor arc. Only by invoking the CALPUFF slug option, as used in the 1998 EPA study, was CALPUFF/CALMET able to reproduce the tracer residence time on the 600 km receptor arc. As the slug option is for near‐source modeling and is a very non‐standard option for LRT dispersion modeling, this result questions the validity of the 1998 CALPUFF evaluation study as applied for CALPUFF LRT modeling. The CALPUFF/MMIF was less sensitive to the slug option and more sensitive to puff splitting than CALPUFF/CALMET. For consistency, the current and EPA 1998 study CALPUFF evaluation approach both used the fitted Gaussian plume model evaluation methodology, along with angular plume centerline offset and tracer receptor arc timing statistics. The fitted Gaussian plume evaluation approach assumes that the observed and predicted concentration along a receptor arc has a Gaussian distribution. At longer downwind distances such an assumption may not be valid. For the CALPUFF evaluation using the SRL75 tracer field experiment, there was a very poor fit of the Gaussian plume to the observations resulting in some model performance statics that could be misleading. We do not recommend using the fitted Gaussian plume evaluation approach in future studies and instead recommend using approaches like the ATMES‐II statistical evaluation approach that is free from any a priori assumption regarding the observed tracer distributions. EPA‐FLM Recommended CALMET Settings from the 2009 Clarification Memorandum: The EPA‐ FLM recommended CALMET settings in the 2009 Clarification Memorandum (EPA, 2009b) produces wind field estimates closest to surface wind observations based on the CAPTEX CALMET modeling. However, when used as input into CALPUFF, the EPA‐FLM recommended CALMET settings produced one of the poorer performing CALPUFF/CALMET configurations when comparing CALPUFF predictions against the observed atmospheric tracer concentrations. Given that the CALMET wind evaluation is not an independent evaluation because some of the wind observations used in the evaluation database are also input into CALMET, the CALPUFF 29
Page 1 and 2: Documentation of the Evaluation of
Page 3 and 4: FOREWARD This report documents the
Page 5 and 6: 2.4.3 ATMES‐II Model Evaluation A
Page 7 and 8: EXECUTIVE SUMMARY ABSTRACT The CALP
Page 9 and 10: OVERVIEW OF APPROACH Up to six LRT
Page 11 and 12: CALPUFF performance is evaluated by
Page 13 and 14: Table ES‐2. ATMES‐II spatial an
Page 15 and 16: • CALPUFF tended to overstate the
Page 17 and 18: • The best performing CALPUFF con
Page 19 and 20: 2009a). The key findings from the C
Page 21 and 22: 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2
Page 23 and 24: 2.4 2 1.6 1.2 0.8 0.4 0 EXP4A EXP4B
Page 25 and 26: Figure ESS‐4. RANK statistical pe
Page 27 and 28: Evaluatioon of Six LRT T Dispersion
Page 29 and 30: Table ES‐6. Summary of model rank
Page 31 and 32: eproduce the northwest to southeast
Page 33: ETEX LRT Dispersion Model Sensitivi
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
Page 45 and 46: 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
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300% 250% 200% 150% 100% 50% 0% 300
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60% 40% 20% 0% ‐20% ‐40% ‐60%
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with APS, implementing the slug opt
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the amount of time that the tracer
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Figure 4‐1. CALPUFF/CALMET UTM mo
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compact discs, which were used to o
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Table 4‐4. CALPUFF parameters use
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Table 4‐8. CALPUFF/MMIF sensitivi
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the fitted Gaussian plume is not a
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Figure 4‐2. Comparison of predict
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Figure 5‐1. Location of Dayton an
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MM5 runs, the first without FDDA (i
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Table 5‐3. MM5 sensitivity tests
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Table 5‐6. Definition of the CALM
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performance at the monitor location
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35% 30% 25% 20% 15% 10% 5% 0% 35% 3
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40% 35% 30% 25% 20% 15% 10% 5% 0% F
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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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