Guidance on the Use of the Mesoscale Model 

Interface Program (MMIF) for AERMOD 

Applications

EPA-454/B-18-005

April 2018

Guidance on the Use of the Mesoscale Model Interface Program (MMIF) for AERMOD 

Applications 

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards

Air Quality Assessment Division

Air Quality Modeling Group

Research Triangle Park, North Carolina
ii

Preface

This document provides guidance on the use of prognostic meteorological data and the 

Mesoscale Model Interface Program (MMIF) in AERMOD. Included in this document are 

descriptions of the inputs to MMIF and recommendations on using MMIF output in AERMOD. 

This document is an update to Section 3.4 of the December 2016 MMIF guidance document 

(EPA-454/B-16-003) issued as part of the 2016 final update to the Guideline on Air Quality.
iii

Acknowledgements

MMIF was developed by Ramboll Environ International Corporation under EPA contract 

number EP-D-07-102, work assignments 2-06, 4-06, 5-08, and 10-1 and EPA Contract No EP-D12-044, work assignment 4-07. The MMIF user’s guide was developed by Bart Brashers and 

Chris Emery of Ramboll Environ. This guidance document was developed by the Air Quality 

Modeling Group of the Air Quality Assessment Division of the Office of Air Quality Planning 

and Standards in collaboration with representatives of EPA Regions 5, 7, and 8
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Contents

Preface............................................................................................................................................. ii

Acknowledgements........................................................................................................................iii

Tables.............................................................................................................................................. v

1. Introduction................................................................................................................................. 1

2. Guidance on using prognostic meteorological data for use in AERMOD.................................. 1

2.1 Number of years to model..................................................................................................... 2

2.2 Prognostic model options...................................................................................................... 2

2.2.1 Development of meteorological fields........................................................................... 2

2.3 Model output quality assurance ............................................................................................ 3

2.3.1 Operational evaluation................................................................................................... 3

3. Guidance on running MMIF for AERMOD ............................................................................... 3

3.1 MMIF Input File ................................................................................................................... 3

3.2 Recommended options for selected keywords...................................................................... 7

3.2.1 Outputs........................................................................................................................... 7

3.2.1.1 AERMET................................................................................................................ 7

3.2.1.2 AERMOD ............................................................................................................... 8

3.2.2 PBL calculations............................................................................................................ 8

3.2.3 Output layers and heights............................................................................................... 8

3.2.4 Grid cells to process....................................................................................................... 9

3.3 Surface characteristics .......................................................................................................... 9

3.4 Treatment of low winds........................................................................................................ 9

3.5 Minimum mixing height and absolute value of Monin-Obukhov length ........................... 10

3.6 Post-processing of outputs.................................................................................................. 10

4. References................................................................................................................................. 12
v

Tables

Table 1. AERMET/AERMOD keywords in MMIF input file........................................................4
1

1. Introduction

The guidance discussed in this document are recommendations for running the Mesoscale Model 

Interface (MMIF) program1to generate inputs for AERMET and AERMOD. The guidance 

discussed in this document is an update to the July 2015 MMIF guidance (EPA-454/B-15-001). 

In this guidance document, when references are made to running MMIF for AERMOD, it should 

be inferred that this refers to AERMET as well. For regulatory applications, MMIF should be 

run to generate AERMET inputs as stated in section 8.4.2(a) and 8.4.5.1(b) of the final revisions 

to EPA’s Guideline on Air Quality Models (U.S. EPA, 2016)

2

. Regulatory applications that do 

not follow these sections of Appendix W will need to consult with the appropriate reviewing 

authority and guidelines outlined in section 3.2 of Appendix W. Given that Appendix W and 

specific EPA modeling guidance are often cited in relation to other non-regulatory modeling 

applications, such as air quality analysis and disclosure purposes under NEPA, the approach 

presented in this guidance document for regulatory applications also has relevance to these nonregulatory applications. While MMIF can process data for other air quality models (e.g., 

CALPUFF and SCICHEM), the emphasis in this guidance is for AERMOD applications 

conducted for regulatory purposes. 

This guidance document will summarize some of the inputs needed for AERMET and 

AERMOD MMIF processing, but will refer to the MMIF User’s Guide (Ramboll Environ, 2016) 

for more details. MMIF users are strongly encouraged to read this user’s guide to obtain specific 

details on running MMIF. 

2. Guidance on using prognostic meteorological data for use in AERMOD

In general, air quality modeling applications rely on the use of meteorological grid models. 

These models are used to more accurately simulate atmospheric processes (e.g., temperature, 

wind speed and direction, etc.) across a specific area. In retrospective simulations (i.e., modeling 

past events), the blending of observed data with computed fields yields results that are bound by 

ground truth. 

There are several meteorological grid models that can be used to develop inputs for air quality 

models. The most commonly used by EPA and the modeling community is the Weather 

Research and Forecasting (WRF) model (Skamarock et al., 2008)3, which is supported across a 

broad community and provides state-of-the-science parameterizations of the atmosphere. 

Additionally, the Fifth Generation Penn State/NCAR Mesoscale Model (MM5) (Grell et al., 

 

1 http://www.epa.gov/ttn/scram/dispersion_related.htm#mmif

2 Hereafter, the Guideline will be referred to as Appendix W.

3 http://www.wrf-model.org/index.php
2

1994) is capable of generating the necessary meteorological inputs to air quality models; 

however, its development and maintenance is no longer supported. 

2.1 Number of years to model

As discussed in Section 8.4.2(e) of Appendix W, at least three consecutive years are required to 

be modeled in the prognostic model. The most recent three years are preferred and the prognostic 

model domain or selected grid cells should be representative of the domain. See Section 8.4.b of 

Appendix W for more details about representativeness of meteorological data.

2.2 Prognostic model options

2.2.1 Development of meteorological fields

For development of prognostic meteorological fields, a rigorous approach has been established 

within the atmospheric chemistry community. In this section, a basic guideline for 

recommendations on producing prognostic meteorological data will be provided. For more 

details related to approaches on developing modeled meteorology, please see Section 2.6 of the 

Modeling Guidance for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and 

Regional Haze (U.S. EPA, 2014). 

Dynamic meteorological models such as WRF and MM5, have myriad options available to solve 

for various processes within the atmosphere. Specific model options will not be provided, given 

that different areas of interest may respond differently under certain conditions. It is expected 

that the physical options chosen will be thoroughly evaluated to support their use. 

With regards to defining a meteorological modeling domain, it is recommended that the domain 

be of sufficient size and resolution to adequately capture mesoscale characteristics that impact a 

source location. As an example, in an area of complex, mountainous terrain, the nearest NWS 

observation site may not be adequately representative. In this case, the scale of meteorological 

model is recommended to be high enough to capture specific mountain/valley flows and be large 

enough to represent the upstream and other mesoscale meteorological features. Conversely, in 

areas where terrain and mesoscale characteristics may be more homogenous, a reasonably coarse 

model resolution may be applied. In addition, to avoid issues with grid boundary effects, it is 

recommended the modeling domains be centered over the source location. Specific case 

examples are provided in U.S. EPA (2018a).

It is also recommended that any meteorological modeling be performed using four dimensional 

data assimilation (FDDA) as outlined in U.S. EPA (2014). FDDA involves providing the model 

with inputs related to observed and/or analyzed meteorological conditions. This technique is 

useful in improving atmospheric simulations and constraining the model from varying widely 

from actual observations. 
3

2.3 Model output quality assurance

2.3.1 Operational evaluation

Demonstration of the adequacy of prognostic meteorological fields can be established through 

appropriate diagnostic and statistical performance evaluations consistent with recommendations 

provided in the appropriate EPA guidance. A quantitative, statistical, and graphical analysis of 

the prognostic data should be completed, comparing the data to available NWS automated 

surface observation station (ASOS) data, as well as operational profiler data (if available), 

pairing both in space and time. This analysis should be completed for all years (at least three) of

prognostic meteorological data to be used in the air quality simulations. Since the spatial scope 

of each variable could be different, representativeness should be judged for each variable 

separately as discussed in Section 8.4.2(b) of the final Appendix W (U.S. EPA, 2016). For 

example, for a variable such as wind direction, the data should ideally be collected near plume 

height to be adequately representative; especially for sources located in complex terrain, 

whereas, for a variable such as temperature, data from a station several kilometers away from the 

source may be considered to be adequately representative. The grid resolution of the prognostic 

meteorological data should also be considered and evaluated appropriately, particularly for 

projects involving complex terrain. Several software packages are available for use in 

completing this evaluation (e.g., AMET (Appel et al., 2011) and METSTAT 

(http://www.camx.com/download/support-software.aspx)). The adequacy of output from the 

meteorological models is contingent upon the concurrence with the appropriate reviewing 

authorities as defined in section 8.4.5.2(a) of the final Appendix W.

3. Guidance on running MMIF for AERMOD

Much of the guidance presented here follows the MMIF user’s guide (Ramboll Environ, 2016). 

Relevant information from the user’s guide is summarized in this guidance for convenience but 

the user is strongly encouraged to read the full MMIF user’s guide before attempting to run 

MMIF. Section 3.1 below discusses the inputs to MMIF, Section 3.2 discusses the relevant 

options to AERMOD and grid cells to process. Section 3.3 discusses the use of surface 

characteristics outside of MMIF, Sections 3.4 and 3.5 discuss the use of minimum wind speeds, 

mixing height and Monin-Obukhov length, and Section 3.6 discusses post-processing the output 

from MMIF needed for input into AERMOD.

3.1 MMIF Input File

MMIF processing is done via a control file with keywords to denote inputs, processing options, 

and outputs. Table 1 lists the keywords used to run MMIF for AERMET and AERMOD input. 

A sample control file that illustrates all of the keywords can be generated for MMIF by typing 
4

“mmif –sample” at the command prompt. See Section 4.2 of the User’s Guide (Ramboll 

Environ, 2016) for more information.
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Table 1. AERMET/AERMOD keywords in MMIF input file.

Keyword Description Syntax

Start Date and time (Local Standard Time) to start 

processing

Start YYYY MM DD HH

Or

Start YYYYMMDDHH

Or

Start YYYY-MMDD_HH:mm:ss

Stop Date and time (LST) to stop processing Stop YYYY MM DD HH

Or

Stop YYYYMMDDHH

Or

Stop YYYY-MMDD_HH:mm:ss

Timezone The global time zone shift from Greenwich Mean 

Time (GMT); Western 

hemisphere time zones are denoted by negative 

numbers

Timezone HH

Grid Specifies the requested output sub-grid’s lower left 

(LL) and upper right (UR) corners; Grid corners can 

be specified by grid cell I, j coordinates (IJ), latitude 

and longitude (LL or LATLON) or MM5/WRF 

projected coordinate system (KM)

GRID IJ iLL jLL iUR jUR

Or

GRID LL LatLL LonLL LatUR 

LatRR

Or

GRID KM xLL yLL xUR yUR

Point Output point for AERMET, AERMOD, or 

AERCOARE processing. The point can be specified 

by grid cell I, j coordinates (IJ), latitude and 

longitude (LL or LATLON) or MM5/WRF projected 

coordinate system (KM). An optional time zone 

shift can also be listed1. The point keyword can be 

repeated for each point to be outputted.

Point IJ I J [Timezone]

Or

POINT LL Lat Lon [Timezone]

Or

POINT KM X Y [Timezone]

Layers Specify the output layer structure. Layers can be 

aggregated (K), interpolated using layer tops (TOP), 

or interpolated using mid layer (MID).

Layers K Layer1

Layer2...LayerN

Or

Layers TOP Top1 Top2...TopN

Or

Layers MID Mid1 Mid2...MidN

Origin Over-ride the X,Y grid origin values found in the 

MM5 or WRF output file. The user specifies a 

latitude (LAT) and longitude (LON).

Origin LAT LON

CALSCI_MIXHT A value of WRF causes MMIF to pass through the 

PBL depth from the model with no changes. A value 

of MMIF causes MMIF to re-calculate PBL depths 

using a Bulk Richardson approach with 20 times the 

vertical resolution of the model data.

WRF or MMIF

AER_MIXHT Option to specify what mixing heights to use for 

MMIF to AERMET processing. Options are WRF 

(no recalculation of mixing heights), MMIF (MMIF 

recalculated mixing heights) or AER_MIXHT(allow 

AERMET to calculate mixing heights)

WRF, MMIF, or 

AER_MIXHTS

AER_MIN_MIXHT Specify the minimum allowed mixing height for 

AERMOD SFC output. Default is 1 m as based on 

AERMET

AER_MIN_MIXHT VALUE
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Table 1. Continued

Keyword Description Syntax

AER_MIN_OBUK Specify the minimum allowed absolute value of the 

Monin-Obukhov length for AERMOD SFC output. The 

default is 1 m as based on AERMET

AER_MIN_OBUK VALUE

AER_MIN_SPEED Specify the minimum wind speed in m/s (VALUE) for 

AERMOD surface output file. This value should be set 

to 0 for both MMIF to AERMET and MMIF to 

AERMOD output.

AER_MIN_SPEED VALUE

FSL_INTERVAL Specify the number of hours (VALUE) to write for 

each day to the upper air file for input into AERMET. 

The default value is 12 representing the 00Z and 12Z 

soundings. A value of 6 would write output for 00Z, 

06Z, 12Z, and 18Z. A value of 1 would write output 

for each model hour.

FSL_INTERVAL VALUE

AER_LAYERS Specify the lowest and highest layer indices (two 

integers) to write to the AERMET input site-specific 

data and AERMOD profile file (PFL file). All layers 

between the two indices will be written to the file.

AER_LAYERS VALUE

OUTPUT Specifies the outputs from MMIF for AERMET, 

AERCOARE, and AERMOD (MODEL keyword) and 

output files2.

OUTPUT MODEL FORMAT 

FILENAME

INPUT Input MM5 or WRF filename. This input is repeatable 

for a MMIF run.

INPUT FILENAME

METFORM Keyword to tell MMIF which model MM5 or WRF is 

being accessed. MMIF can auto-detect the model type 

so in general this is not needed.

METFORM MM5

Or

METFORM WRF

1. See Section 4.2 of the MMIF user’s guide regarding the global time zone shift and point specific time zone 

shifts.

2. More information about the output options are discussed in Section 3.2 below.
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3.2 Recommended options for selected keywords

While most input options will be left to the discretion of the user, some recommendations on 

inputs are made in this guidance. One such option is the output option of MMIF, keyword 

OUTPUT. While MMIF can process data for input into AERMET, or AERMOD, the 

requirement for regulatory applications is to process the prognostic meteorological data for input 

into AERMET as discussed in Sections 8.4.2(a) and 8.4.5.1(b) of Appendix W, as AERMET is 

the meteorological pre-processor for AERMOD as discussed in those sections. The data is then 

processed in AERMET for input into AERMOD. Processing MMIF output through AERMET 

also allows the user to take advantage of some of the options in AERMET, such as the u* 

adjustment option. See the AERMET user’s guide for details about options (U.S. EPA, 2018b). 

For non-regulatory applications, the user may choose AERMET or AERMOD and should 

consult with and seek concurrence from collaborating agencies or parties involved in such

modeling applications. 

3.2.1 Outputs

For any particular air quality model, the OUTPUT option is used to specify several files. While 

these are discussed in the MMIF user’s guide in detail, they are summarized below for AERMET 

and subsequent input AERMOD and direct input into AERMOD as well (non-regulatory 

applications).

3.2.1.1 AERMET

For AERMET, the first set of files is specified using the USEFUL keyword. This keyword 

creates a DOS batch file or Linux shell script that is used to run all three stages of AERMET in 

batch mode. It also creates the stage 1, stage 2, and stage 3 input files with the appropriate 

values set for the AERMET keywords such as LOCATION, XDATES, etc. Once the stage 1, 2, 

and 3 input files have been created, the user should check those files to ensure the correct GMT 

offset is used. For the upper air pathway of the stage 1 file, the LOCATION keyword should 

have a GMT offset corresponding to the station’s location. For example, if the processed grid 

cell is in the Eastern time zone of the U.S. the GMT offset on the LOCATION keyword should 

be 5. For the surface data, the offset should be zero as that has been formatted for local time.

The second file that is generated is specified using the keyword ONSITE. This creates a sitespecific type meteorological file that is processed via the ONSITE keyword in AERMET (U.S. 

EPA, 2014). This file contains 2-meter and 10-meter data and upper air data up to levels 

specified with the keywords MIN_LAYER, MAX_LAYER, or LAYERS to control the number 

of output layers.

The third keyword, FSL creates a file that mimics an upper air data file in the Forecast Systems 

Laboratory (FSL) format. The keyword UPPERAIR can also be used. See Section 2.2.1 of the 

MMIF user’s guide for more details.
8

The final keyword is AERSFC, which generates an AERSURFACE type output file with surface 

characteristics (albedo, Bowen ratio, and surface roughness). Note, that these are monthly 

surface characteristics for the period being processed. See Section 2.2.1 of the MMIF user’s 

guide for more details.

3.2.1.2 AERMOD

Three files are generated for AERMOD. The USEFUL file is a file containing the ME pathway 

information of the AERMOD input file, i.e. ME STARTING, SURFFILE, PROFFILE, 

SURFDATA, UADATA, etc. information. The SFC keyword generates the AERMOD ready 

surface data file and the PFL keyword generates the profile data file for input into AERMOD.

3.2.2 PBL calculations

Three options are available for PBL or mixing height calculations when processing MMIF to 

output files for AERMET inputs via the AER_MIXHT option, 1) a pass through of the WRF 

PBL heights (AER_MIXHT=WRF), 2) recalculation of the PBL heights using a Bulk 

Richardson approach (AER_MIXHT=MMIF), based on Vogelezang and Holtslag (1996) and 

Louis (1979) and, no PBL heights passed to the AERMET site-specific data file 

(AER_MIXHT=AERMET). This option uses AERMET to use its own algorithms to calculate 

mixing heights. For MMIF inputs to AERMOD, there are still two options available via the 

CALSCI_MIXHT option (formerly the PBL_recalc option). The two options are passing the 

WRF mixing heights (MIXHT=WRF) or recalculation by MMIF (MIXHT=MMIF). At this 

time, the choice of which option to use is left to the discretion of the user as limited evaluations 

(EPA, 2018a) have shown little difference in the three methods. Note that if a user utilizes the 

PBL pass through or recalculation method and wishes to use AERMET derived mixing heights 

later, the user can rerun MMIF or just omit the MIXHT variable and modify the read statement 

for the site-specific meteorological file.

3.2.3 Output layers and heights

An important keyword for output is the LAYERS keyword. As shown in Table 1, the user can 

specify different options for the output layers from MMIF. While the choice of layers is case 

specific and may be dependent on the prognostic model’s layer structure, two possible defaults 

should be adequate in most cases. The first is based on the FLM guidance and the second is aa 

default use of MID (interpolation using layer mid-point heights) and the specification of heights 

corresponding to the AERMOD vertical grid. These heights are: 25, 50, 75, 100, 125, 150, 175, 

200, 250, 300, 350, 400, 450, 500, 600, 700, 800, 900, 1000, 1500, 2000, 2500, 3000, 3500, 

4000, 4500, and 5000. These values have been used in past MMIF evaluations (U.S. EPA, 

2015c). The LAYERS keyword controls the output of the FSL formatted upper air file used by 

AERMET and the profile file used by AERMOD when processing MMIF to AERMOD. The 
9

AER_LAYERS keyword is used to control the output of the site-specific data file read by 

AERMET. The AER_LAYERS can be a subset of the LAYERS values. 

3.2.4 Grid cells to process

An AERMOD run uses surface meteorological data from one point and upper air data from one 

point. While MMIF can process multiple points, i.e. grid cells, the grid cell used in the 

AERMOD simulation should be representative of the modeling domain, following the 

recommendations of Section 8.4.5(b) of Appendix W. Depending on the size of the modeling 

domain and the grid resolution of the prognostic meteorological data, most often the 

representative grid cell will be the grid cell containing the facility of interest. This will often be 

the case for NSR/PSD types of applications. When the AERMOD modeling domain overlaps 

several grid cells of the prognostic meteorological data, such as for SIP demonstrations, the grid 

cell that is most representative of the domain should be selected following guidance on 

representativeness in Sections 8.4.1.b and 8.4.2.b of the final Appendix W, or it may be 

necessary to conduct multiple AERMOD runs for different grid cells and post-process the results 

to calculate the appropriate concentration metrics for the application (i.e. design values). 

3.3 Surface characteristics

MMIF will output surface characteristics, albedo, Bowen ratio, and surface roughness for input 

into AERMET and also in the AERMOD ready surface meteorological file. When outputting 

data for AERMET, MMIF outputs surface characteristics for one 360o sector at monthly 

resolution. The surface characteristics are based on the land use data used by the prognostic 

meteorological model. These surface characteristics should be used as they are representative of 

the processed grid cell as discussed in Section 8.4.2(b) of the final Appendix W. 

3.4 Treatment of low winds

When processing MMIF for input into AERMET or AERMOD, MMIF will use the 

AER_MIN_SPEED value as a wind speed threshold, for which winds below that threshold are 

treated as calms. This is for winds at any vertical level in the input dataset. For input to 

AERMET, MMIF will generate the onsite wind speed threshold option (THRESHOLD keyword) 

with the user supplied value (AER_MIN_SPEED) for the stage 1 AERMET input file. 

Normally, the purpose of the threshold in AERMET is to treat winds below the threshold as calm 

and the threshold speed is a function of the starting threshold of a site-specific anemometer. See 

the AERMET user’s guide (U.S. EPA, 2018b) for details about this option in AERMET. When 

generating MMIF output for direct AERMOD input, winds below the AER_MIN_SPEED value 

will be treated as calms in the AERMOD surface file. For both MMIF to AERMET and MMIF 

to AERMOD, the user should set the minimum wind speed, AER_MIN_SPEED, to zero, since 
10

the input is prognostic data and does not have a functional minimum threshold as found in an 

anemometer. 

When processing MMIF output in AERMET, if the lowest level’s wind speed is below the 

AERMET allowable limit (21/2 x vmin, where vmin=0.2 m/s), AERMET will reset the wind 

speed to the lower limit allowed in AERMET for output to the surface file. This adjustment does 

not take place for other levels in the WRF output file. See Section 4.5.11 in the AERMET user’s 

guide for more details (U.S. EPA, 2018b). When processing MMIF output for direct input to 

AERMOD, no such adjustment will occur in MMIF. The wind speed from WRF is output to the 

AERMOD surface and profile files.

3.5 Minimum mixing height and absolute value of Monin-Obukhov length

New in MMIF 3.3, is the ability to specific a minimum mixing height and minimum value of 

Monin-Obukov length when processing MMIF for AERMOD output. The default minimum 

values for each option are 1 m, as defined in Table 1 and discussed in the MMIF User’s Guide 

(Ramboll Environ, 2016). At this time, the defaults are the recommended values for these 

options.

3.6 Post-processing of outputs

When processing MMIF for AERMET files, a single MMIF run will produce an upper air file in 

the FSL format, a surface data file that will be read into AERMET as site-specific data, and 

surface characteristics (albedo, Bowen ratio, and surface roughness) at monthly resolution for 

twelve sectors. These output files will cover the period processed in MMIF. In most situations, 

a single MMIF run will not cover an entire three period or even a one-year period. If that is the 

case, the ONSITE files generated by the MMIF can be simply concatenated into a single file for 

the three-year period or individual yearly files before input into AERMET. The files must be 

concatenated in temporal order. The same can be done for the FSL files. If using the MMIF 

surface characteristics files, the AERSFC files cannot be simply concatenated. For a single 

MMIF run, the surface characteristics are output for all twelve months and sectors. The months 

outside of the data processing window set by START and STOP will have missing values, while 

the months inside the window will have non-missing values. To create a valid AERSFC file 

covering the entire three-year period or desired period, an AERSURFACE file must be created 

with non-missing values for all months and sectors. This can be created by simply cutting and 

pasting the non-missing values for each month/sector combination into a single file. When 

creating this file, the user should make sure to incorporate the header line from one of the files 

into the concatenated file. This line is “** Generated by MMIF...” This line indicates to 

AERMET that the meteorological data comes from MMIF and not an observed site-specific 

dataset. This information is then passed to AERMOD via the surface meteorological file created 

by AERMET. While this does not affect the data calculations in AERMET and AERMOD, 

including the line ensures transparency when data files are reviewed.
11

An alternative approach to the file concatenation steps described above, is to run AERMET for 

each period processed and concatenate AERMOD ready surface and profile files from the 

multiple AERMET runs. For the profile files, the files can be simply concatenated together, 

preserving the temporal order of the data (e.g., January 1, hour 1 of the first processed year is the 

first line and December 31, hour 24 of the last processed year is the last record of the 

concatenated file). For the surface files, AERMET generates a header record for each file (the 

record that lists the location, station identifiers, and AERMET version). When concatenating the 

surface files, the header record for the first concatenated file should be retained. Only the data 

records from the remaining surface files are needed. If the header records are retained for all 

files, AERMOD will not run correctly. Again, the files should be concatenated in temporal 

order. These steps also apply for processing AERMOD ready files when post-processing MMIF 

output for AERMOD.
12

4. References

Appel, K.W., Gilliam, R.C., Davis, N., Zubrow, A., and Howard, S.C.: Overview of the 

Atmospheric Model Evaluation Tool (AMET) v1.1 for evaluating meteorological and air 

quality models, Environ. Modell. Softw., 26, 4, 434-443, 2011.

Grell, G., J. Dudhia, and D.R. Stauffer: A description of the fifth-generation Penn State/NCAR 

Mesoscale Model (MM5), NCAR Tech. Note NCAR/TN-398+STR, 122 pp.

Louis, J.F. 1979. “A Parametric Model of Vertical Eddy Fluxes in the Atmosphere.” Journal of 

Atmospheric Science, 35, 187-202.

Ramboll Environ, 2016: The Mesoscale Model Interface Program (MMIF) Version 3.3 User’s 

Manual.

Skamarock, W. C., Klemp, J. B., Dudhia J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X.-

Y., Wang, W., and Powers, J. G.: A Description of the Advanced Research WRF 

Version 3, National Centre of Atmospheric Research, Boulder, Colorado, 2008.

U.S. EPA, 2016. Guideline on Air Quality Models. 40 CFR Part 51 Appendix W.

U.S. EPA, 2018a: Evaluation of Prognostic Meteorological Data in AERMOD Applications. 

EPA-454/R-18-002. U.S. Environmental Protection Agency, Research Triangle Park, NC 

27711.

U.S. EPA, 2018b: User’s Guide for the AERMOD Meteorological Preprocessor (AERMET). 

EPA-454/B-18-002. U.S. Environmental Protection Agency, Research Triangle Park, 

NC 27711.

Vogelezang D. and A. Holtslag, 1996. “Evaluation and model impacts of alternative boundarylayer height formulations.” Boundary Layer Meteor., 81, 245-26.

United States

Environmental Protection

Agency

Office of Air Quality Planning and Standards

Air Quality Assessment Division

Research Triangle Park, NC

Publication No. EPA-454/B-18-005

April, 2018