EFFECTS OF MET DATA PROCESSING IN AERMOD CONCENTRATIONS
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This document summarizes the results of a sensitivity analysis using AERMOD to model pollutant concentrations from three hypothetical emission sources under nine different meteorological data processing scenarios. The analysis found that: 1) Changing the meteorological station location had a modest effect on modeled concentrations for short and tall stacks. 2) Surface roughness category (urban vs. rural) had the largest effect on concentrations for tall stacks. 3) Varying the anemometer height resulted in small concentration changes, while surface moisture variation did not significantly affect outcomes. 4) For tall stacks, use of AERMINUTE data to include low wind hours led to much higher modeled concentrations compared to excluding this data.
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EFFECTS OF MET DATA PROCESSING IN AERMOD CONCENTRATIONS
- 1. EFFECTS OF MET DATA PROCESSING IN AERMOD CONCENTRATIONS 2012 A&WMA Conference June 20, 2012 Sergio Guerra, Jared Anderson Wenck Associates, Inc.
- 2. Sensitivity Analysis • Hypothetical point source in Manhattan, KS • Study is based on the processing in AERMET of: – Integrated surface hourly data (ISHD) – Upper air data and – 1‐minute ASOS data • Surface station: Manhattan Regional Airport , KS • Upper Air station: Topeka Municipal Airport Station, KS • Downwash and terrain effects were not considered in this study
- 12. Surface Moisture and Anemometer height‐ Short Stack Scenario Short stack Met Data Used Iteration 1 Iteration 3 Iteration 4 Iteration 5 1‐hr 24‐hr Annual Description g/m3 Percent Difference g/m3 Control 190.7 0.0 69.6 0.0 4.0 0.0 0.0 69.6 ‐0.1 4.2 5.5 0.0 69.6 ‐0.1 3.9 ‐2.9 0.1 66.4 ‐4.7 3.7 ‐6.4 Dry surface moisture 190.7 Wet surface moisture 190.7 10 m anemometer height 190.9 Percent Percent g/m3 Difference Difference
- 13. Surface Moisture and Anemometer height‐ Medium Stack Scenario Medium stack Met Data Used Iteration 1 Iteration 3 Iteration 4 Iteration 5 1‐hr Description Control 24‐hr Annual g/m3 Percent Difference g/m3 29.7 0.0 6.6 0.0 1.1 0.0 4.1 6.6 ‐0.2 1.1 0.4 1.1 6.6 0.0 1.1 ‐0.9 ‐0.2 6.6 ‐0.1 1.1 1.4 Dry surface moisture 30.9 Wet surface moisture 30.1 10 m anemometer height 29.7 Percent Percent g/m3 Difference Difference
- 14. Surface Moisture and Anemometer height‐ Tall Stack Scenario Tall stack Met Data Used Iteration 1 Iteration 3 Iteration 4 Iteration 5 1‐hr Description Control Dry surface moisture Wet surface moisture 10 m anemometer height g/m3 24‐hr Percent Difference g/m3 Annual Percent Percent g/m3 Difference Difference 13.1 0.0 2.0 0.0 0.15 0.0 13.1 0.0 2.0 0.0 0.15 1.0 13.1 0.0 2.0 0.1 0.15 ‐0.7 13.1 6.2 2.0 ‐0.4 0.16 10.2
- 15. Rural vs Urban‐ Short Stack Scenario Short stack Met Data Used Iteration 1 Iteration 7 1‐hr 24‐hr Annual g/m3 Percent Difference g/m3 Control 190.7 0.0 69.6 0.0 4.0 0.0 Rural 201.8 5.8 74.2 6.6 4.0 0.7 Description Percent Percent g/m3 Difference Difference
- 16. Rural vs Urban‐ Medium Stack Scenario Medium stack Met Data Used Iteration 1 Iteration 7 1‐hr 24‐hr Annual g/m3 Percent Difference g/m3 Control 29.7 0.0 6.6 0.0 1.1 0.0 Rural 60.8 104.4 7.8 18.5 1.0 ‐9.9 Description Percent Percent g/m3 Difference Difference
- 17. Rural vs Urban‐ Tall Stack Scenario Tall stack Met Data Used Iteration 1 Iteration 7 1‐hr 24‐hr Annual g/m3 Percent Difference g/m3 Control 13.1 0.0 2.0 0.0 0.15 0.0 Rural 0.8 ‐94.0 0.1 ‐94.4 0.01 ‐92.5 Description Percent Percent g/m3 Difference Difference
- 19. AERMINUTE • Non‐regulatory component of AERMOD • Light wind conditions may be controlling factor in some cases due to limited dilution • Concentrations not calculated in AERMOD for hours with calm or missing meteorological data • Purpose of AERMINUTE is not to increase conservatism but to “reclaim” data that was lost due to METAR reporting in NWS data
- 20. Number and Percent of Calm and Missing Wind Data for Met Data Iterations Met Data Iterations Iterations 1,2,3,4,5,7,8 Iteration 6 Iteration 9 Calm Missing Winds Winds (%) (%) AERMINUTE IFW Total Observations Yes Yes 8760 80 (0.9%) 45 (0.5%) 8760 2316 (26%) 349 (4%) 8760 1303 (15%) 45 (0.5%) No Yes ‐ No
- 23. AERMINUTE and IFWGROUP‐ Short Stack Scenario Short stack Met Data Used Iteration 1 Iteration 6 Iteration 9 1‐hr Description Control 24‐hr Annual g/m3 Percent Difference g/m3 190.7 0.0 69.6 0.0 4.0 0.0 ‐1.1 51.4 ‐26.2 5.2 30.2 0.0 69.6 0.0 4.6 14.3 No AERMINUTE 188.5 AERMINUTE but no IFW group 190.7 Percent Percent g/m3 Difference Difference
- 24. AERMINUTE and IFWGROUP‐ Medium Stack Scenario Medium stack Met Data Used Iteration 1 Iteration 6 Iteration 9 1‐hr Description Control No AERMINUTE AERMINUTE but no IFW group 24‐hr Annual g/m3 Percent Difference g/m3 Percent Percent g/m3 Difference Difference 29.7 0.0 6.6 0.0 1.1 0.0 28.8 ‐3.2 7.3 11.1 1.2 6.7 29.7 0.0 7.4 13.3 1.2 2.1
- 25. AERMINUTE and IFWGROUP‐ Tall Stack Scenario Tall stack Met Data Used Iteration 1 Iteration 6 Iteration 9 1‐hr Description Control No AERMINUTE AERMINUTE but no IFW group 24‐hr Annual g/m3 Percent Difference g/m3 Percent Percent g/m3 Difference Difference 13.1 0.0 2.0 0.0 0.15 0.0 1.9 ‐85.4 0.4 ‐80.9 0.02 ‐88.4 4.7 ‐64.2 0.6 ‐67.6 0.03 ‐77.9
- 26. Summary • Met station location had modest effect on short and tall stack scenarios. • Surface roughness had the greatest effect on tall stack scenario. • Anemometer height had a modest effect on concentrations. • Surface moisture did not have a significant effect. • For tall stacks, use of AERMINUTE data resulted in significantly higher concentrations. • For tall stacks, urban/rural classification has a significant effect on concentrations.