EPA’S NINTH CONFERENCE ON 

AIR QUALITY MODELING

Comments on behalf of the American Petroleum InstituteSteven R. Hanna, Ph.D., CCMHanna ConsultantsBruce A. Egan, Sc.D., CCMEgan Environmental Inc.Elizabeth M. Hendrick, CCMEpsilon Associates Inc.

October 10, 
Introduction

2

 Promulgation of more stringent ambient air s

has resulted in more non-attainment areas anneed for more complex and more regional m

 These comments cover many issues relating to 

of the EPA’s Guideline on Air Quality Models

 Highlights are listed here and our written com

will contain details and references.
Need for Complete Documentation a

Guidance

3

 All codes should be in public domain. All documentation (especially CALPUFF) needs 

brought up-to-date and made publicly availa

 There is a general need for more EPA guidanc

workshops and training for the modeling comm
Distance limits on model applicat

4

 Better guidance on distance limits for models i

needed (esp. AERMOD and CALPUFF). 

 What is the minimum domain size and grid siz

grid models such as CMAQ or CAMx can be uand what is the recommendation for Plume in (PinG) modeling?

 Distance limits should not be arbitrary, but sho

depend upon scientific issues, including topogrwind persistence data and land use variation
Meteorological inputs to mode

5

 There has been an increase in the use of meteorologic

(e.g., diagnostic models such as CALMET and prognosphysics models such as MM5) for both steady state anvarying dispersion models (e.g., AERMOD, CALPUFF, 

 Prognostic meteorological models such as MM5 and W

(often called ‘Met models’) have been improving with in science and resolution.

 Other agencies (DTRA and NOAA) now have linked M

(MM5 or WRF) to Puff AQ models or grid AQ model that are operational.
Meteorological inputs to models (con

6

 Research effort needed to optimize use of Me

and CALMET model predictions with observati

 Specific issues:

 Clarify differences between full-physics Met mode

MM5) and CALMET

 Assess effects of grid size and vertical grid spacing 

and accuracy

 Develop recommendations for optimal grid sizes fo

different topographic and meteorological settings; grid size (Penn State MM5 developers recommend safe general rule, although 1 km can be used in spcases; this is due to physics assumptions in model)
Meteorological inputs to models (Spe

issues continued)

7

 Determine overall model performance of Met mod

coupled with dispersion models vs. field study data possible new field experiments 

 Determine how met observations can best be used 

assimilated in Met models? (note differences betweand Penn State MM5 Met model data assimilation 

 Assess if CALMET (or any diagnostic model) is truly 

as an intermediate step between the Met model anAQM.

 Work with other agencies (DTRA, NOAA) who have 

operational Met model-AQM systems operating anuse of their technology where appropriate.
Regional Models 

(CMAQ, CAMx, and others) 8

 New mechanisms in CMAQ (and CAMx and other models) need 

comprehensively tested and subjected to review by external exp

 We recommend that EPA devote more resources to subgrid scale 

in CMAQ, including consideration of the use of the SCICHEM PinG and set up a decision process for which point sources should be mwith PinG.

 EPA should have comprehensive scientifically based model 

evaluations/comparisons performed for CMAQ vs. CAMx (and acredible regional grid model).

 Databases are being developed in Wyoming and the Four Corn

that will provide monitoring data and emission inventories.

 EPA needs to set a de minimis significance level for project ozon

concentration impacts for regional modeling efforts.
CALMET/CALPUFF

9

 Need overall model evaluations of CALPUFF u

chemistry as very limited evaluations of the mothe mode that it is being used have been cond

 Evaluation should include other models such as 

SCIPUFF.

 Ability to handle complex terrain, short term p

dispersion, chemical reactions, and other incorcapabilities (e.g., FOG) needs to be evaluate

 Modify chemistry based on API/AER recomme

revisions.
CALMET/CALPUFF (Continued)

 Documentation is incomplete, and lack of det

causes many users to rely heavily on default 

 Need to resolve met input questions (CALMET 

model such as MM5 – see previous slides on inputs) 

 Need to test the use of CALPUFF for regiona

analyses (NEPA studies are currently using thapproach in the West).

 Operational use should be based on peer an

holder review using best science approach aopposed to IWAQM mandates. 
Proposed Collaborative Field Experiment for 

Met Model - AQM Evaluation

11

 Purpose: to test and improve the linkage of M

models and air quality models in mountainousuch as Wyoming where there is much currenmesoscale and regional modeling underway.

 EPA should lead effort with invited participat

API and other industries and stakeholders.

 Include meteorological observations, tracer r

and PM and visibility observations over an aabout 200 km by 200 km, sufficient to test thMet model (e.g., MM5) direct input vs CALMEdiagnostic model.
Model Evaluation and Uncertainty

12

 Recent improvements in regional dispersion m

performance measures have been made; EPA (in collaboration with members of an internatworkgroup) are described in a recently submpaper by Dennis et al.

 Rather than having different evaluation appr

and performance measures for the different scales, a comprehensive set of performance mshould be devised for use at all model scales
Model Evaluation and Uncertainty (Cont)

13

 The bootstrap method used in the ASTM and 

software should be recommended to evaluatsignificant differences in model performance for all model scales.

 Model acceptance criteria should be set and 

modeling protocols and decision making. 

 Uncertainty in model predictions (also called 

“probabilistic forecasts”) should become avaand used by regulatory decision makers. EPA investigate and possibly make use of the proAQM system (Met model –SCIPUFF) in use at 
Modeling Protocols and Screening M

14

 Modeling Protocols should be determined up 

and dependent upon science and regulatory 

 When will the screening model AERSCREEN b

released to the public?
AERMOD

15

 Establish a peer–review panel from all segme

the community to review planned improvemendraft documents produced.

 Incorporate algorithms for near calm winds an

with appropriate field data sets.

 Improve algorithms for use in urban areas, esp

for near-ground sources in built-up downtown 

 Determine science-based criteria for deciding 

limits and whether “complex terrain” is signific
ASOS and AERSURFACE

16

 EPA guidance limits the influence of nearby l

in parameterizing surface roughness to a 1 radius of ASOS anemometers generally locaairport property.

 For many pollutant sources this means that the 

dispersion modeling domain is dominated by roughness of airport property. 

 Better guidance is needed for translating the 

wind observations to the land characteristics pollutant source domain.
Meteorological data processing with AER

input to AERMOD

17

 AERMET Stage 3 output should summarize t

processed met data so the user knows durinAERMET processing steps if that year of dasuitable for regulatory modeling purposes (available). 

 Currently this summary information is not pr

until AERMOD is run. 
Plume Molar Volume Ratio Model (PM

18

 EPA should further test this model and, if acc

recommend the use of this model for predictconcentrations in the presence of ambient air concentrations.

 This should be performed for both AERMOD 

CALPUFF. 
Encourage development and use of s

based models

19

 Some non-regulatory driven studies concerned, for e

with health risk assessments use AQ monitoring data with statistical correlations as a substitute for the use detailed dispersion models (AERMOD, CALPUFF, or Cestimating air quality concentrations.

 EPA should promote consistent and general use of di

models that are based on physical understanding of meteorological principles (e.g., AERMOD, CALPUFF, CAMx etc.) as opposed to statistical fits to site speciconcentration data sets.

 The use of statistical models in place of more rigorou

dispersion models should be reviewed by an expert includes all scientific and stakeholder communities.
Encourage development and use of s

based models (

continued)

20

 Avoid arbitrary non-scientific criteria for mode

selection (such as eliminating models with a bover-prediction) 

 Encourage scientific peer review of all models 

both internal EPA and outside models) and of proposed modifications to model algorithms.

 Model acceptance criteria should be develope

through discussions with the entire community odevelopers and stakeholders.
Summary of Key Recommendatio

21

 Need to update and improve model guidance and 

documentation.

 Encourage development and use of science–based mo

through model evaluation efforts and enhanced public involvement.

 Test, validate, and recommend procedures for using 

meteorological models to drive dispersion models.

 Conduct a Mesoscale/Regional collaborative model e

using the existing databases and/or conduct a field ethat could be used to evaluate regional models in rurain the intermountain west or similar location.