EFFECTS OF MET DATA PROCESSING IN AERMOD CONCENTRATIONS

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Information about EFFECTS OF MET DATA PROCESSING IN AERMOD CONCENTRATIONS
Education

Published on February 26, 2014

Author: sergioalain

Source: slideshare.net

Description

The current study evaluates the effect that different parameters used to process meteorological data have on AERMOD concentrations. Specifically, this study evaluates the effect from the use of AERMET processed with; 1-minute wind data collected by the Automated Surface Observing System (ASOS) and pre-processed using AERMINUTE, refined National Climatic Data Center (NCDC) station location and anemometer height, surface moisture, and urban/rural options. In this evaluation, one year of meteorological data was processed with nine different sets of input parameters and then used in AERMOD to run a short, medium and tall stack scenario for 1-hour, 24-hour and annual averaging periods. Downwash and terrain effects were not considered in this study. The results indicate that the three stack scenarios are sensitive to the location used for the meteorological station. Anemometer height changes had a small effect on concentrations for all scenarios except for the tall stack scenario which produced a modest increase in concentrations for the annual averaging period. Surface moisture was not found to have a strong effect on the scenarios evaluated. The use of AERMINUTE data resulted in significantly higher concentrations for the 1-hour (85%), 24-hour (81%), and annual (88%) averaging periods. The ice free group station option in AERMINUTE was also evaluated. When using AERMINUTE without specifying that the station is part of the ice free wind group stations, the concentrations obtained for tall stack scenario were lower for the 1-hour (64%), 24-hour (68%), and annual (78%) averaging periods. Finally, when it comes to the urban/rural evaluation, the greatest effect is observed in the medium stack scenario where concentrations double for the 1-hour scenario when using the rural option. However, in the tall stack scenario, significantly lower concentrations were obtained by using the urban parameter for the three averaging periods evaluated.
Presented at the 10th Conference of Air Quality Modeling
EPA‐Research Triangle Park, NC Campus on March 15, 2012; at the AWMA UMS Dispersion Modeling Workshop on May 15, 2012 and at the Annual AWMA Conference on June 20, 2012.

EFFECTS OF MET DATA PROCESSING IN AERMOD CONCENTRATIONS 2012 A&WMA Conference June 20, 2012 Sergio Guerra, Jared Anderson Wenck Associates, Inc.

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

Stack location in Manhattan, Kansas

Three Modeling Scenarios Input parameter Short Medium Tall Emission Source Stack height (m) Emission rate (g/s) Exit temperature (degrees K) Diameter (m) Exit velocity (m/s) RICE 3 1 Boiler 23 1 Power Plant 168 1 640 0.46 37.37 420.8 0.76 8.86 325 7.8 10.9

Nine sets of Met Data Met data  Iterations Station  Location Anemometer  Height (m) Surface  Moisture Rural/Urban Use of  AERMINUTE IFW  Group Met Iteration 1 Refined 7.9 Average Urban Yes Yes Met Iteration 2 NCDC 7.9 Average Urban Yes Yes Met Iteration 3 Refined 7.9 Dry Urban Yes Yes Met Iteration 4 Refined 7.9 Wet Urban Yes Yes Met Iteration 5 Refined 10 Average Urban Yes Yes Met Iteration 6 Refined 7.9 Average Urban No ‐ Met Iteration 7 Refined 7.9 Average Rural Yes Yes Met Iteration 8 Surrogate 7.9 Average Urban Yes Yes Met Iteration 9 Refined 7.9 Average Urban Yes No

Nine sets of Met Data Met data  Iterations Station  Location Anemometer  Height (m) Surface  Moisture Rural/Urban Use of  AERMINUTE IFW  Group Met Iteration 1 Refined 7.9 Average Urban Yes Yes Met Iteration 2 NCDC 7.9 Average Urban Yes Yes Met Iteration 3 Refined 7.9 Dry Urban Yes Yes Met Iteration 4 Refined 7.9 Wet Urban Yes Yes Met Iteration 5 Refined 10 Average Urban Yes Yes Met Iteration 6 Refined 7.9 Average Urban No ‐ Met Iteration 7 Refined 7.9 Average Rural Yes Yes Met Iteration 8 Surrogate 7.9 Average Urban Yes Yes Met Iteration 9 Refined 7.9 Average Urban Yes No

Actual and NCDC Location for the  MHK Met Station in Kansas

Surrogate, Actual, and NCDC Location  for the MHK Met Station in Kansas

Location‐ Short stack scenario RICE  Met Data  Used Iteration 1  Iteration 2 Iteration 8 1‐hr  Description Control NCDC location Surrogate  location 24‐hr Annual g/m3 Percent  Difference g/m3 Percent  Percent  g/m3 Difference Difference 190.7 0.0 69.6 0.0 4.0 0.0 189.3 ‐0.8 68.4 ‐1.7 4.1 2.5 163.3 ‐14.4 78.6 12.9 6.6 64.3

Location‐ Medium stack scenario Medium  Stack Met Data  Used Iteration 1  Iteration 2 Iteration 8 1‐hr  24‐hr Annual g/m3 Percent  Difference g/m3 Control 29.7 0.0 6.6 0.0 1.1 0.0 NCDC location 29.6 ‐0.6 7.1 7.4 1.2 4.4 31.0 4.4 9.6 46.5 1.4 26.9 Description Surrogate  location Percent  Percent  g/m3 Difference Difference

Location‐ Tall stack scenario Tall stack Met Data  Used Iteration 1  Iteration 2 Iteration 8 1‐hr  24‐hr Annual g/m3 Percent  Difference g/m3 Control 13.1 0.0 2.0 0.0 0.15 0.0 NCDC location 12.8 ‐2.2 1.9 ‐5.8 0.14 ‐7.2 12.0 ‐8.1 1.6 ‐20.1 0.09 ‐36.9 Description Surrogate  location Percent  Percent  g/m3 Difference Difference

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

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

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

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

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

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

Anemometer Sonic  Cup and vane 

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

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

Comparison AERMINUTE AERMINUTE No AERMINUTE

Comparison IFWGROUP AERMINUTE No IFW GROUP

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

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

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

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.

Contact Sergio A. Guerra Environmental Engineer Phone: (651) 395‐5225 sguerra@wenck.com

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