# Subject-to-Best Available Retr ofit Technology (BART)

Modeling for the State of Hawaii

Application of the CALPUFF Modeling System

Prepared for:


## Hawaii State Department of Health

Environmental Management Division

Clean Air Branch Prepared by:

Alpine Geophysics, LLC

7341 Poppy Way

Arvada, Colorado 80007



# 3 March 2010

# Table of Contents

Section No. Page No.

PURPOSE ......................................................................................................... 1

1 INTRODUCTION AND STUDY OBJECTIVES ............................................................................. 1

1.1 I NTRODUCTION



## .............................................................................................................................. .............................. 1



# 2 MODELING APPROACH ................................................................................................................. 2

2.1 BART-E LIGIBLE 

## /RP-E LIGIBLE 

## S OURCES 

## .................................................................................................................... 2

2.2 C LASS 

## I A REAS



## .............................................................................................................................. .............................. 3

2.3 P OLLUTANTS TO 

## C ONSIDER



## .............................................................................................................................. ........... 4

2.4 E MISSIONS AND 

## S TACK 

## D ATA



## .............................................................................................................................. ........ 6

2.5 N ATURAL 

## B ACKGROUND



## .............................................................................................................................. ............... 6

2.6 V ISIBILITY 

## C ALCULATION



## .............................................................................................................................. ............. 7

2.7 M ODEL 

## E XECUTION



## .............................................................................................................................. ....................... 8

2.7.1 Subject-to-BART Analysis

.............................................................................................................................. ....... 8

2.7.2 Implementing Subject-to-BART/RP Prioritization Modeling Analysis ................................................................. 9



# 3 VISIBILITY MODELING SYSTEM .............................................................................................. 11

3.1 CALMET

.............................................................................................................................. ............................................ 11

3.1.1 Meteorological Data

.............................................................................................................................. ............... 13

3.1.2 CALMET Control File Settings ........................................................................................................................... 18

3.2 CALPUFF

.............................................................................................................................. ................................... 19

3.2.1 Emissions

.............................................................................................................................. ............................... 19

3.2.2 Ozone Background

.............................................................................................................................. ................. 20

3.2.3 Ammonia Background

.............................................................................................................................. ........... 20

3.2.4 Receptor Locations

.............................................................................................................................. ................. 20

3.3 CALPOST AND VISIBILITY POST-PROCESSING .............................................................................................. 20



# 4. SUBJECT-TO-BART MODELING RESULTS ................................................................................. 21

5. CONCLUSION

.............................................................................................................................. ..... 26

6. REFERENCES

.............................................................................................................................. ..... 27

APPENDIX A CALMET PARAMETER VALUES ............................................................................... 29

APPENDIX B CALPUFF PARAMETER VALUES .............................................................................. 34

APPENDIX C CALPOST PARAMETER VALUES ............................................................................. 43

i

# List of Figures

Figure No. Page No.

Figure 1 BART-Eligible Facility Locations in Proximity to Class I Areas. ................................................................................... 4

Figure 2. Subject-to-BART/ RP Prioritization Flowchart ........................................................................................................... 10

Figure 3: Modeled 36/12/4 km MM5 Domain. ............................................................................................................................ 1 7

Figure 4. Modeled 4km MM5 Domain.

.............................................................................................................................. ......... 18



# ii

# iii 

# List of Tables

Table No. Page No.

Table 1. BART-e ligible Sources. .............................................................................................. .................................................... 3

Table 2. Federal Mandatory Class I Areas in the Mo deling Domain. .............................................................. .............................. 3

Table 3. 20% Best Natural Conditio ns – Concentrations and Rayleigh Scattering By Class I Area. ................................ ............. 7

Table 4. CALPUFF Modeling Sy stem ............................................................................................. ........................................... 11

Table 5. MM5 Vertical Domain Speci ficatio n. .................................................................................. ......................................... 16

Table 6: Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the HC&S Puunene Op erating on either

bagasse or coal. . Visibility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow. Visibility impacts

over 0.5 Δ dv for 98 th 

## percentile (8 th 

## high) are shaded red. ................................................................................................... 23

Table 7. Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for th e Chevron Refinery. . Visibility impacts

over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow. Visibility impacts over 0.5 Δ dv for 98 th 

## percentile (8 th



## high) are sh aded red .......................................................................................................... ................................................... 23

Table 8: Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for th e Tesoro Refinery. Vi sibility impacts over

0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow. Visibility impacts over 0.5 Δ dv for 98 th 

## percentile (8 th 

## high) are

shaded red..................................................................................................................... ........................................................ 24

Table 9. Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the Hu Honua Bioenergy –Pepeekeo facility.

Visibility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow. Visibility impacts over 0.5 Δ dv for 98 th



## percentile (8 th 

## high) are sh aded red ......................................................................................................... ............................. 24

Table 10: Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the MECO - Hahului facility. Visibility

impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow. Visibility impacts over 0.5 Δ dv for 98 th 

## percentile

(8 th 

## high) are shaded red ......................................................................................................... .............................................. 24

Table 11. Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the HELCO Kanoelehua Hill facility.

Visibility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow. Visibility impacts over 0.5 Δ dv for 98 th



## percentile (8 th 

## high) are sh aded red ......................................................................................................... ............................. 25

Table 12. Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the HECO - Waiau facility. Visibility

impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow. Visibility impacts over 0.5 Δ dv for 98 th 

## percentile

(8 th 

## high) are shaded red ......................................................................................................... .............................................. 25

Table 13. Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the HECO - Kahe facility. Visibility impacts

over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow. Visibility impacts over 0.5 Δ dv for 98 th 

## percentile (8 th



## high) are sh aded red .......................................................................................................... ................................................... 25

# PURPOSE

This Report is prepared for the State of Hawaii and describes the application

methodology and results of the CALPUFF Mode l for determining whether the Hawaiian

Best Available Retrofit Technology (BART)-e ligible sources are Subject-to-BART under

the Regional Haze (RH) Rule, 40 CFR 308.

1 INTRODUCTION AND STUDY OBJECTIVES

1.1 Introduction

Under the federal RH Rule, 40 CFR 308, Hawaii is required to develop a plan to establish

Reasonable Progress goals for incremental visi bility improvements in achieving natural

background conditions within its two Federal Class I areas. Natural conditions exist

when a Class I area is absent of anthropoge nic or man-made air pollution emissions. In

establishing RP goals, Hawaii will need to consider emission reduction measures for

specified source groups or activ ities including the application of BART for existing major

stationary sources.

On 6 July 2005, the U.S. Environmental Protection Agency (EPA) published final

amendments to its 1999 RH Rule in the Federal Register, including 40 CFR Part 51,

Appendix Y, the final guidance for BART de terminations (BART Guideline; EPA, 2005;

70 FR 39104-39172). The rule app lies to any BART-eligible source that “emits any air

pollutant which may reasonably be anticipated to cause or contribute to any impairment

of visibility” in any mandatory Class I federal ar ea. States retain the authority to exempt

certain BART-eligible sources based on di spersion modeling demonstrating that the

source cannot reasonably be anticipated to cause or contribute to visibility impairment in

a Class I area. Hawaii has elected to use th is modeling option for BA RT-eligible sources.

According to 40 CFR Part 51, Appendix Y, a BART-eligible source is considered to

“contribute” to visibility impairment in a Class I area if the modeled 98 th 

# percentile

change in deciviews is equal to or greater than the “cont ribution threshold.” Any BARTeligible source, through mode ling, determined to cause or contribute to visibility

impairment above the threshold in any Class I area is subject to BART. The EPA BART

Guidelines suggest a contribution threshold of no greater than a 0.5 change in deciview

be used. Hawaii has chosen to use the r ecommended 0.5 deciview threshold for Subjectto-BART determination.

The U.S. EPA Region 9, U.S. National Park Service (NPS), and the U.S. Fish and

Wildlife Service (FWS) were consulted during development of the Modeling Protocol

(Alpine Geophysics, 2010) and the performance of this project, which follows very

closely the BART Guideline.

1

# 1.2 Objectives

The objectives of this study are to provide:

• A consistent approach in determining which BART-eligible source is Subject-toBART, requiring the 5-fact or analysis pursuant to 40 CFR Part 51, Appendix Y,

Guidelines for BART Determinations under the RH Rule (BART Guideline);

• A clearly delineated modeling methodology;

• A common CALMET/CALPUFF/POSTUTIL/C ALPOST modeling configuration;

and

• A common format for reporting modeling re sults for each BART-eligible source.

2 MODELING APPROACH

This section describes the components or information used for the CALPUFF modeling

and the overall process in determining whet her a source is anticipated to cause or

contribute to visibility impair ment to Hawaii’s federal Class I areas. Eligible source

criteria, Class I area identific ation, pollutants considered, em issions data required, natural

background conditions, visibility impairment de termination, and the analysis process are

covered here.

2.1 BART-Eligible/RP-Eligible Sources

Sources evaluated in this assessment incl ude BART-eligible sour ces. BART-eligible

sources determined to cause or contribute to visibility impairment in any Class I area will

be subject to further air pollution control analyses.

The term “BART-eligible emission unit” refers to any single emissi on unit that meets the

following criteria:

1) Emits greater than 250 tons/year of a visibi lity-impairing pollutant;

2) Was put into place between August 7, 1962 and August 7, 1977; and

3) Falls within one of the 26 liste d source categories in the guidance.

A “BART-eligible source” is the total of all BART-eligible emission units at a single

facility. If a source has se veral emission units, only those that meet the BART-eligible

criteria are included in the defini tion of “BART-eligible source.”

Hawaii identified nine BART-eligible facilities shown in Table 1.

2

# Table 1. BART-eligible Sources.

Facilities

Chevron Refinery

Tesoro Refinery

HECO – Kahe

HECO – Waiau

HC&S Puunene

MECO – Kahului

HELCO – Kanoelehua Hill

Hu Honua Bioenergy, LLC -Pepeekeo

(formerly Hilo Coast)

Kauai Utilities – Port Allen

2.2 Class I Areas

The mandatory Class I federal areas in Hawa ii that could be impacted by BART-eligible

sources, are presented in Table 2. Refer to Figure 1 below showing the location of the

Class I areas in relation to BART-eligible facilities/sources.

Table 2. Federal Mandatory Class I Areas in the Modeling Domain.

Class I Area IMPROVE Monitor Federal Land Manager

Haleakala National Park HALE 1 National Park Service

Hawaii Volcanoes National Park HAVO 1 National Park Service



# The Haleakala National Park consists of 30,183 acres in centr al to eastern portions of the

island of Maui, 24,719 acres of wh ich are designated wilderne ss. Park elevations range

from 3,055 m (10,023 ft) at the summit of Ha leakala to sea level at the mouth of

Kipahulu Valley on the extreme eastern boundar y. The Park thus includes a wide variety

of climate zones, from high mountain eleva tions above the Marine Boundary Layer, to

leeward lowlands that are dry relative to wi ndward lowlands at the same elevation.

The Haleakala National Park IMPROVE site is HALE1, located at an elevation of 1,158

m (3,799 ft) on the northward slope of Haleak ala, ~5.7 km northwest of the Park

Boundary.

The Hawaii Volcanoes National Park IMPROVE Site is HAVO1, located on the east to

southeastern slopes of Mauna Loa on the is land of Hawaii. More specifically, it is

situated on the northeastern rim of the Kila uea crater. The site elevation is 1,204 m (3,949

ft), some 124 m above the crater floor at 1080 m (3,542 ft). One of the major terrain

feature affecting meteorology and air quality at the monitoring site, other than the

erupting Kilauea volcano, is the 4,170 m (13,68 1 ft) high Mauna Loa cone, about 35 km

(22 mi) to the west of the monitoring site.

3

# 4 The IMPROVE data is used to represent meas ured pollutant impact s at the two National

Parks.

Figure 1 BART-Eligible Facility Location s in Proximity to Class I Areas.

2.3 Pollutants to Consider

The BART Guideline specifies that sulfur dioxide (SO2), oxides of nitrogen (NOx) and

direct particulate matter (PM) emissions , including both PM10 and PM2.5 should be

included for the Subject-to -BART modeling analyses.

The BART Guideline also discusses the in clusion of volatile organic compound (VOC),

ammonia and ammonia compounds as visibility impairing pollutants. These pollutants

will be considered separately if it is de termined that these emissions from a BARTeligible source are reasonably anticipated to cau se or contribute to vi sibility impairment.

# 2.4 Emissions and Stack Data

The BART Guideline states, “the emission estimates used in the models are intended to

reflect steady-state operating conditions durin g periods of high capac ity utilization.”

These emissions should not generally in clude start-up, shutdow n, or malfunction

emissions. The BART Guideline recommends th at states use the 24-hour average actual

emission rate from the highest emitting day of the meteorological period modeled.

Hawaii requested source information of the highest emitting day between calendar years

2003 to 2007 from BART-eligible sources and will similarly request the same

information from identified RP-eligible sources.

Depending on the availability of emissions data, the following emissions information

(listed in order of priority) were be us ed with CALPUFF for the Subject-to-BART

modeling:

• 24-hour average actual emission rate fr om the highest emitting day within the

modeling period (preferred) ba sed on representative CEM or stack test data; or

• 24-hour average emissions calculated using emission factors specified in Title V

permits.

• 24-hour average emissions calculated us ing AP-42 emission factors or other

equivalent methods.

• Allowable emissions (maximum 24-hour allowable).

DOH worked with sources to deve lop appropriate emission rates.

If plant-wide emissions for SO 2 

# , NO

x 

# , and PM 10 

# , from eligible sources, are less than the

significant emission rate (SER) used for Prev ention of Significant Deterioration review,

emissions of that pollutant are not included in the Subject-to-BART modeling. However,

if plant-wide emissions exceed the SERs for th ese pollutants, then al l emissions of that

pollutant from individual emission units are evaluated even if emissions are below the

SER for an individual emission unit.

2.5 Natural Background

The BART Guideline references EPA’s “G uidance for Estimating Natural Conditions

under the Regional Haze Rule” (EPA, 2003a). Th is guidance lists three sets of Natural

Conditions corresponding to Annual Average, Best 20% Days and Worst 20% Days.

Due to limited access to available meteorol ogical data, the 20% best natural days are

used, in lieu of annual average natural days, to represent natural visibility background in

Class I areas. This definition of natural b ackground is consistent with the intent of the

BART Guideline (Federal Register Vol. 70, No. 128, pf 39125). The specific natural

background values used in this study are drawn from the Federal Land Managers’ Air

Quality Related Values Workgroup (FLAG) Ph ase I Report – Revised (FLAG, 2008).

Class I specific background extinction coeffici ents are presented in Table 3. The option

6

# presented in EPA’s guidance for refining the de fault visibility background are not used in

this study.

Table 3. 20% Best Natural Conditions – Con centrations and Rayleigh Scattering By

Class I Area.

Background Extinction Coe fficients (20% Best Days)

Class I Area (NH 4 

## ) 2 

## SO 4



## μ g/m3 NH 4 

## NO 3 

## Μ g/m3 OM

μ g/m3 EC

μ g/m3 Soil

μ g/m3 CM

μ g/m3 Sea

Salt

μ g/m3 Rayleigh

Mm-1

Haleakala

National Park 0.05 0.04 0.24 0.01 0.11 1.59 0.13 10

Hawaii

Volcanoes

National Park 0.03 0.04 0.27 0.01 0.06 0.64 0.11 10



# 2.6 Visibility Calculation

The CALPUFF modeling techniques used in this study provide ground level

concentrations of visibility impairing pollu tants. The concentration estimates from

CALPUFF are used with the FLAG referenc ed IMPROVE equation to calculate the

extinction coefficient ( b
ext 

# ) , as shown below.

b ext 

## = 2.2 × f S 

## (RH) × [Small Sulfate] + 4.8 × f L 

## (RH) × [Large Sulfate]

• 2.4 × f S 

## (RH) × [Small Nitrate] + 5.1 × f L 

## (RH) × [Large Nitrate]

• 2.8 × [Small Organic Mass] + 6.1 × [Large Organic Mass]

• 10 × [Elemental Carbon]

• 1 × [Fine Soil]

• 0.6 × [Coarse Mass]

• 1.7 × f SS 

## (RH) × [Sea Salt]

• Rayleigh Scattering (Site Specific)

• 0.33 × [NO 2 

## (ppb)] {or as: 0.1755 × [NO 2 

## ( μ g/m 3 

## )]}

Where:

[ ] indicates concentrations in μ g/m 3



## f S 

## (RH) = Relative humidity adjustment factor for small sulfate and nitrate

f L 

## (RH) = Relative humidity adjustment factor for large sulfate and nitrate

f SS 

## (RH) = Relative humidity adjustment factor for sea salt

For Total Sulfate < 20 μ g/m 3 

## : [Large Sulfate] = ([Total Sulfate] / 20 μ g/m 3 

## ) × [Total Sulfate]

For Total Sulfate ≥ 20 μ g/m 3 

## : [Large Sulfate] = [Total Sulfate]

And:

[Small Sulfate] = [Total Sulfate] – [Large Sulfate]



# To calculate large and small nitrate and organic mass, substitute ({Large, Small,

Total} {Nitrate, Organic Mass}) for Sulfate.

7

# The monthly relative humidity adjustment factors from the above equation are found in

Appendix C.

The change in visibility for the Subject-to-BART analyses are compared against the 20%

best natural background conditions. The delta-deciview, Δ dv, value is calculated from

the source’s contribution to extinction, b ext (source) 

# , and background extinction, b ext(bkg) 

# , as

follows:

Δ dv = 10 ln (b ext(bkg) 

# +b ext (source) 

# ) / b ext(bkg) 

# )

2.7 Model Execution

2.7.1 Subject-to-BART Analysis

The Subject-to-BART modeling is used to determine which eligible sources are

reasonably anticipated to cause or contribute to visibility impairment at any Class I area.

This study uses Option 1 in Section III of the BART Guideline for this analysis. This

option is the Individual Source Attribution Approach. With this approach, each BARTand RP-eligible source is modeled separately and the impact on visibility impairment in

any Class I area is determined.

For determining the visibility threshold, the recommendations in the BART Guideline are

followed to assess whether a BART- source is reasonably anticipated to cause or

contribute to any visibility impa irment in a federal Class I area. According to the BART

Guideline:

“A single source that is re sponsible for a 1.0 deciview change or more should be

considered to “cause” visibility impairm ent; a source that causes less than a 1.0

deciview change may still contribute to vi sibility impairment and thus be subject to

BART. As a general matter, any threshold that you use for determining whether a source

“contributes” to visibility impairment should not be higher than 0.5 deciviews.

As recommended in the BART Guideline, if a single source cause s a 0.5 deciview or

greater change from natural ba ckground, then that source is determined to be reasonably

anticipated to contribute to any visibility im pairment in a Class I area and will be subject

to BART. For this single source analys is, the Subject-to-BART modeling will not

consider the frequency, magnitude , and duration of impairment.

Outside the work of this study, DOH has made a preliminary determination whether an

eligible source is Subject- to-BART by following the screen ing methodology described in

Section III, Option 2 of the BART Guideline. Based on a 0.5 deciview threshold, if a

source calculated Q/D < 10, an eligible sour ce would be exempt from further BART

analysis at least for the first RH planning period.

8

# Q = Potential Emissions (tons/year) of SO 2 

# +NOx+PM 10 

# from all eligible units

within a facility

D = Distance (kilometers) between the el igible source and the boundary of the

nearest Class I area

Generally, if a source is a smalle r emitter or is located far fr om a Class I area, and its Q/D

is less than 10, the source is no t expected to contribute to visi bility impairment at a Class

I area.

Using this approach, the DOC determined that the Kauai Utilities Port Allen facility

should not be Subject-to-BART.

2.7.2 Implementing Subject-to-BART/RP Pr ioritization Modeling Analysis

Alpine Geophysics, LLC (Alpine) has perf ormed the Subject-to-BART modeling in

accordance with the Modeling Protocol for the BART-eligible sources. Figure 2 is a flow

chart of how individual faci lities are evaluated for its eligible emission units.

Consideration for allowing a more refined Subject-to-BART analysis in the event a

source is found to be Subject-to-BART is not a part of this study’s scope.

9

# Figure 2. Subject-to-BART/ RP Prioritization Flowchart

Note: “Pre-BART” units = identified “RP-eligible” units.



# 10

# 3 VISIBILITY MODELING SYSTEM

In general, the Subject-to-BART modeling used the CALPUFF suite of programs and

followed the procedures and recommendations outlined in two documents: the IWAQM

(Interagency Workgroup on Air Quality Models ) and the FLAG (Federal Land Managers

Air Quality Related Values Workgroup) repo rts (EPA 1998, FLAG 2008) . Tables listing

the modeling parameters for each CALPUFF module are located in the Appendices.

The specific CALPUFF programs and their ve rsion numbers that were used in the

Subject-to-BART/ modeling are presented in Table 4. The CALPUFF modeling system

is the regulatory approved versions excep t for the CALPOST processor. CALPOST

version 6.221 is used to enab le this application to use the most up-to-date FLAG (6-29-

2008) guidance. The CALMET model was run using the August 20, 2009, “EPA-FLM

Recommended CALMET i nput File Values.”

The CALMET meteorological domai n, as described below, covers the entire Hawaiian

Island chain.

Table 4. CALPUFF Modeling System

Program Version Level

CALMET 5.8 060911

CALPUFF 5.8 060911

CALPOST 6.221 080724

POSTUTIL 1.56 070627



# 3.1 CALMET

Input requirements for the CALMET mode l include various meteorological and

geophysical data sets, and a control input file with appropriate settings. Required

meteorological data include surface, upper-a ir, and precipitati on observations, and

mesoscale model output data fields. Specifi cs of these data are provided below.

Geophysical input data incl ude terrain elevat ion and land-use data. Though CALMET

may be run with mesoscale model meteorologi cal data, alone (i.e., no observations), the

EPA modeling guideline recommends “blending” observations with the mesoscale model

fields. Therefore, this study included observations in a blended approach.

The dispersion modeling used the CALMET wind fields for the calendar year 2005.

While a minimum of three years of meso scale meteorological model output is

recommended for conducting the initial step in the first-level analysis, meteorological

data sets for more than 2005 were unavailable for the modeling domain under this

contract. The CALMET wind fields for 2005 cover the entire island chain and

11

# sufficiently encompass both Class I areas wi thin 300km of any BART- facility included

in this analysis.

Land Use Processing : CALMET requires both land use/ land cover and terrain height

data for the application region. These are generated using the CALMET CTGPROC,

TERREL and MAKEGEO as described below.

• TERREL is the terrain pre-processor that averages terrain features to the

modeling grid resolution; TE RREL constructs the basic pr operties of the gridded

domain and defines the coordinates upon which meteorological data are stored.

Key parameters include specification of gr id type, location, resolution and terrain

elevation.

• CTGPROC computes the fractional land us e for the modeling grid resolution.

Land use characteristics for each grid cell are assigned using CTGPROC. The

primary variable adjustment associated with CTGRPOC is selection of an

appropriate land use database. Version 2.0 of the North American Land Cover

Characteristics database was used.

• MAKEGEO is the final pre-processor that combines the terrain and land use data

for input to CALMET. Generating the appropriate MAKEGEO.INP control file

requires only minimal alteration of the default assignments. Key modifications

include specifying domain attributes a nd ensuring input f iles are co rrectly

referenced.

Terrain : CALMET requires both terrain height and land use/land cover for the

application region. These are generated using the CALMET CTGPROC, TERREL and

MAKEGEO processors. The terrain data was created using the TERREL (version 3.684

level 070327) processor and the Shuttle Radar Topography Mission (SRTM)-GTOPO 30

second (~1 km) reso lution dataset.

Land Use: The land use data set was created using the Composite Theme Grid

CTGROC processor (version 2.682, level 0704 30) and the United States Geological

Survey (USGS) Global Land Cover Characteri zation (GLCC) version 2.0 database. The

GLCC database is available at 30 second (~1km) resolution.

Observed Data Processing: Observation data from both available surface and upper-air

stations in the modeling will be used. The surface data wer taken from the NOAA

Techniques Development Lab (TDL) database and the upper-air data from the NOAA

Forecast Systems Lab (FSL) database.

CALMET Model Options : The options used in the CALMM5 processing will generally

follow the FLAG (FLAG, 2008) and IWAQ M (EPA, 1998) guidance. Specific

CALMET input values will be updated using the August 20, 2009, “EPA-FLM

Recommended Input File Values.”

12

# 3.1.1 Meteorological Data

3.1.1.1 Mesoscale Model Data

Alpine was contracted to a pply the Pennsylvania State University/National Center for

Atmospheric Research (PSU/NCAR) Mesosc ale Model (MM5) (Dudhia, 1993; Grell et

al., 1994: UCAR, 2003a) for calendar year 2005 to provide data for the

CALMET/CALPUFF modeling as well as for a dditional modeling and analytical studies

conducted for the Hawaiian Islands.

A complete description of the modeling appr oach and a statistical evaluation of the

annual MM5 model are described in McNally and Wilkinson, 2008. A brief description

of the modeling approach follows:

Model Selection : The publicly available non-hydrostatic version of MM5 (version

3.7.4) was used for this modeling study. Pr eprocessor programs of the MM5 modeling

system including TERRAIN, REGRID, LITTLE_R, and INTERPF (UCAR, 2003b) were

used to develop model inputs.

Horizontal Domain Definition: The computational grid is presented in Figures 3 and 4.

The outer 36km domain (D01) has 165 x 129 gr id cells, selected to provide boundary

conditions to the 12km domai n. The mid-scale 12km domain (D02) has 226 x 226 grid

cells, selected to maximize the coverage of the western region around the Hawaiian

Islands. The 4km domain (D03) has 208 x 154 grid cells, selected to cover the Island

chain with a greater than 100km buffer around the perime ter. The projection was in

Lambert Conformal Coordinates (LCC) with a grid projection pole of 23 o 

# , -158 o 

# with true

latitudes of 30 o 

# and 60 o



# .

Vertical Domain Definition: The MM5 modeling was based on 34 vertical layers with

an approximately 38 meter deep surface layer. The MM5 vertical domain is presented in

both sigma and height co ordinates in Table 5.

Topographic Inputs: Topographic information for the MM5 was developed using the

NCAR and the United States Geological Survey (USGS) terrain databases. The grid will

be based on the 2 min (~4 km) Geophysical Data Center global data interpolated to the

model grid using a Cressman-type objective an alysis scheme. To avoid interpolating

elevated terrain over water bodies, after the terrain databases are interpolated onto the

MM5 grid, the NCAR graphic water body databa se is used to corre ct elevations over

water bodies.

Vegetation Type and Land Use Inputs: Vegetation type and land use information were

developed using the most recently releas ed PSU/NCAR databases provided with the

MM5 distribution. Standard MM5 surface char acteristics corresponding to each land use

category were employed.

13

# Atmospheric Data Inputs: Two choices for the first guess meteorological fields were

available: (1) the NCEP Global Tropospheri c Final Analysis; and (2) the NCAR/NCEP

Reanalysis Project (NNRP) data (UCAR, 2007). Though the NNRP data were used in a

previous study of Hawaii (Y ang and Chen, 2003; Yang et. al . 2005), the NNRP data have

relatively coarse 2.5x2.5 degree resolution whereas the NCEP Final Analysis data have

much higher 1x1 degree resolution. For the current modeling study, the NCEP Final

Analysis dataset was used.

Available surface and upper-air observations we re used in the objective analyses. These

data were incorporated into the analyses datasets following the procedures outlined by

Stauffer and Seaman (1990) and were quality -inspected by MM5 pre-processors using

automated gross-error checks and “buddy” checks. In addition, radiosonde soundings

were subjected to vertical consistency checks. The synop tic-scale data used for the

initialization (and in the analysis nudging di scussed later) were obtained from the

conventional National Weather Service (NWS ) twice-daily radiosondes (UCAR, 2008a)

and 3-hr NWS surface observations (UCAR, 2008b).

Water Temperature Inputs: The water temperature data were taken from the NCEP

RTG global one-half degree analysis (Gemmill et al., 2007; NCEP, 2008).

FDDA Data Assimilation: This simulation used both anal ysis and observation based

nudging. For the 36km and 12km grids an alysis nudging coefficients of 2.5x10 -4 

# and

1.0x10 -4 

# were used for winds and temperature, re spectively. For the 4km grid analysis

nudging to observed winds from the NCAR DS472.0 TDL dataset (UCAR, 2008c) was

employed with a coefficient of 1.0x10 -3



# .

Physics Options : Sensitivity testing using approxima tely two-week long episodes in

early February 2005 and early July 2005 were performed to help select the best

performing physics options (McNally, 2008). Although the performance was similar for

the different options, the best performing configuration was the version used by the

University of Hawaii and the National Weat her Service (Yang and Chen, 2003; Yang et.

al. 2005). Namely:

• Warm Rain;

• Grell Cumulus Parameterization;

• MRF PBL;

• NOAH Land Surface Model; and

• Cloud Radiation.

Application Methodology : The MM5 model was executed in 5-day blocks initialized at

12Z every 4 days with a 90 second time st ep. Model results we re output every 60

minutes and output files are split at 24 hour inte rvals. Twelve (12) hours of spin-up were

included in each 4-day block before the data were used in the atmospheric simulations

and subsequent model performance evaluation.

14

# 3.1.1.2 CALMM5 Processing

The final step in the meteorol ogical processing is to refo rmat the MM5 data using the

CALMM5 processor. CALMM5 was run for the 4km MM5 nest to extract the whole

region, less a few grid cells around the perimeter that are contaminated by MM5

boundary artifacts.

15

# Table 5. MM5 Vertical Domain Specification.

k(MM5) sigma pressure.(mb) height(m) depth(m)

34 0.000 10000 15674 2004

33 0.050 14500 13670 1585

32 0.100 19000 12085 1321

31 0.150 23500 10764 1139

30 0.200 28000 9625 1004

29 0.250 32500 8621 900

28 0.300 37000 7720 817

27 0.350 41500 6903 750

26 0.400 46000 6153 693

25 0.450 50500 5461 645

24 0.500 55000 4816 604

23 0.550 59500 4212 568

22 0.600 64000 3644 536

21 0.650 68500 3108 508

20 0.700 73000 2600 388

19 0.740 76600 2212 282

18 0.770 79300 1930 274

17 0.800 82000 1657 178

16 0.820 83800 1478 175

15 0.840 85600 1303 172

14 0.860 87400 1130 169

13 0.880 89200 961 167

12 0.900 91000 794 82

11 0.910 91900 712 82

10 0.920 92800 631 81

9 0.930 93700 550 80

8 0.940 94600 469 80

7 0.950 95500 389 79

6 0.960 96400 310 78

5 0.970 97300 232 78

4 0.980 98200 154 39

3 0.985 98650 115 39

2 0.990 99100 77 38

1 0.995 99550 38 38

0 1.000 100000 0 0

16

# Figure 3: Modeled 36/12/4 km MM5 Domain.

17

# Figure 4. Modeled 4km MM5 Domain.

3.1.2 CALMET Control File Settings

These CALMET wind fields were used by all BART-elegible sources within the

modeling domain. The wind fields were pr epared using CALMET. Details of the

parameter settings in CALMET are provided in Appendix A to this document; however,

the major assumptions are summarized below.

1) The initial-guess fields will use the 4- km MM5 outputs, forecast from hours 13 –

108 of each 5 day run segment, January – December, 2005.

2) Both the Subject-to-BART used th e wind fields at 4km resolution.

18

# 3) There were 10 vertical layers w ith face heights of 0, 20, 40, 65, 120, 200, 400,

700, 1200, 2200, and 4000 meters.

4) 

# CALMET was run using surface, buoy and uppe r air observations. Upper air data

from the LIH (WBAN 22536) site on Kauai and the ITO (WBAN 21504) site on

Hilo were used. Buoy data collected from the National Data Buoy Center for

sites 51001, 51002, 51003, 51004, KLIH1 and OOUHI were used and surface

data from 14 surface stations in the TDL DS472.0 dataset were used.

3.2 CALPUFF

The CALPUFF modeling used Version 5.8. The application generally follows the

recommendation of the IWAQM and FLAG guidance documents. Details of the

parameter settings in CALPUFF are provided in Appendix B to this document; however,

the major features are summarized below:

1) The calendar year 2005 CALMET input file were developed by Alpine

Geophysics, LLC and be provided as input-ready to CALPUFF.

2) The Subject-to-BART modeling examined the visibility impairment on Class I

areas within 300km of each single sour ce or facility. The computational

modeling domain is sufficient to include all Class I areas within a 300km radius

of a source.

3) Pasquill-Gifford Dispersion coefficients are used.

4) MESOPUFF-II chemistry algorithm are used.

5) Puff splitting is not used, following the recommendations of the FLMs.

6) Source elevations are based on the same te rrain files as the receptor elevations.

7) The CALUTIL is used to pe rform HNO3/NO3 repartitioni ng using the parameters

in Appendix B.

CALPUFF is applied separately for each Class I Area (Haleakala National Park and

Hawaii Volcanoes National Park) on the island of Maui and Hawaii.

3.2.1 Emissions

Section 2.4 above presents the emissions a nd stack data that is required from the

facilities. This section only discusses the emissions estimates needed in CALPUFF.

Primary emission, species include av ailable input species of PM, SO 2 

# , SO 4 

# , NO

x 

# ; and the

additional modeled species HNO 3 

# and NO 3 

# . SO 2 

# emissions were reviewed to ensure

“double-counting” was avoided.

The primary PM species are treated as follows:

Filterable:

Elemental Carbon (EC) (<2.5 μ m)

PM Fine (PMF) (<2.5 μ m)

19

# PM Coarse (PMC) (2.5 – 10 μ m)

Condensable:

Organic Carbon (SOA)

Inorganic Aerosol (SO 4 

# )

The condensable fraction is treated as primar y emissions in the CALPUFF input file and

assumed to be 100% in the PM 2.5 

# fraction (see NPS Web site listed below).

Facility specific speciation emissions data are used when provided. The following size

distributions are us ed in CALPUFF:

Pollutant Mean diameter Standard deviation

SO 4 

# , NO 3 

# , PMF, SOA, EC 0.48 2

PMC 2.5 5

3.2.2 Ozone Background

Background ozone will be assumed at an annual constant level of 40 ppb.

3.2.3 Ammonia Background

Because the Hawaiian Island chai n does not fit easily within the three land use values

proposed in IWAQM (10 parts per billion ( ppb) for grasslands, 0.5 ppb for forest, and 1

ppb for arid lands), ammonia background concentr ations were determined in consultation

with the participating FLMs. A review of the ammonia emissions inventory for Hawaii

in comparison with mainland agricultural ar eas indicate a background of 1.5 ppb to be

representative based on land use and agricultural and livestock activity.

3.2.4 Receptor Locations

Predicted visibility impacts are computed at receptors locations for the Class I Areas

within the domain which are available for download from the National Park Service Web

site http://www2.nature.nps.gov/air/Maps/Receptors/index.cfm

, 

# Source and receptor elevations

are based on actual elevations. The elevati ons for the meteorologi cal grid points were

taken from the CALMET modeling.

3.3 CALPOST AND VISIBILITY POST-PROCESSING

The CALPOST processing used Version 6.221 and POSTUTIL Version 1.56. Details of

the parameter settings in CALPOST and PO STUTIL are provided in Appendix C, with

some of the major features summarized be low for calculating visibility impairment:

20

# 1) For the visibility calculation, Method 8, Mode 5 (MVISBK=8, M8_MODE=5) is

employed. This method uses monthly average relative humidity and f(RH) values

for each Class I area, which are based on data from FLAG (FLAG 2008).

2) Particulate species for the vi sibility analysis include SO 4 

# , NO 3 

# , EC, OC, PMF,

and PMC, as reported in the CALPOST output files.

3) POSTUTIL was not be used to speciate modeled PM 10 

# concentrations, as PM 10 

# is

speciated into its components (PMF, PMC, SOA, EC, SO 4 

# ) and entered as

primary emissions in CALPUFF. However, HNO 3 

# /NO 3 

# partition option in

POSTUTIL was used

4) Natural background extinction calculations use the 20% best natural days for each

Class I area in the modeling domain. Tabl es providing the monthly f(RH) and

20% best days coefficients are provided in Appendix C, and are based on data

from FLAG (FLAG 2008).

5) The 98 th 

# percentile value is calculated for all BART-eligible sources at each

mandatory Class I area.

6) The contribution threshold has the implied le vel of precision equal to the level of

precision reported by CALPOS T. Therefore, the 98 th 

# percentile value will be

reported to three decimal places.



# 4. SUBJECT-TO-BART MODELING RESULTS

The change in visibility impairment for the Subject-to-BART/RP prioritization modeling

is based on the increase in the haze index from a BART-eligible source relative to natural

background, defined as the 20% best natural visibility days for each Class I area. This

definition of natural background is consistent with the intent of the BART Guideline

(Federal Register Vol. 70, No. 128, pf 39125). Although the use of the annual 20%

natural visibility days wa s subsequently allowed (EPA 2006, Memorandum from Joseph

W. Paisie to Kay Prince dated July 19, 2006. Subject Regional Haze Regulations and

Guidelines for BART Determinations), the 20% best natural visibility days is being used

due to the availability of one year’s worth of meteorological data. Three years worth of

meteorological data is recommended by guidance.

The U.S. EPA recommends using the 98 th 

# percentile value from the distribution of values

containing the highest m odeled delta-deciview ( Δ dv) value for each day of the simulation

from all modeled receptors at a given Class I area. The 98 th 

# percentile Δ dv value will be

determined with the 8 th 

# highest value for the year modeled (2005).

This 8 th 

# highest value is compared to the contribution threshold ( Δ dv ≥ 0.5 dv). If there

are more than seven (7) days with values gr eater than the contribution threshold in any

single meteorological year for a ny of the Class I areas, then the source is considered

Subject-to-BART in the first RH planning period. Tables for each of BART eligible

sources are presented. For each sour ce the top 8 visibility impacts ( Δ dv) are presented

for both Haleakala and Hawaii Volcanoes. Va lues where the visibility impacts for the

top 1-7 impacts (higher that 98 th 

# percentile) exceed the 0.5 Δ dv threshold are shaded

21

# yellow. Values where the visibilities for the 8 th 

# high (the 98 th 

# percentile) exceed the

threshold, and are thus Subject -to-BART, are shaded red.

Table 6 presents the top 8 visibility impacts ( Δ dv) for the HC&S Puunene facility. Since

this facility can operate on both Bagasse (a fi brous residue from sugar cane processing),

or coal, impacts were examined separately for each fuel. For both fuels at both Class 1

areas none of the top 8 visi bility impacts exceed the 0.5 Δ dv threshold. Based on this

modeling assessment, the HC&S Puunene facility is not Subject-to-BART.

Table 7 presents the t op 8 visibility impacts ( Δ dv) for the Chevron Refinery. At neither of

the Class 1 areas did any of the top 8 visibility impacts exceed the 0.5 Δ dv threshold.

Based on this modeling assessment, the Chev ron Refinery is not Subject-to-BART.

Table 8 presents the top 8 visibility impacts ( Δ dv) for the Tesoro Refinery. At neither of

the Class 1 areas did any of the top 8 visibility impacts exceed the 0.5 Δ dv threshold.

Based on this modeling assessment, the Teso ro Refinery is not Subject-to-BART.

Table 9 presents the top 8 visibility impacts ( Δ dv) for the Ho Honua Bioenergy –

Pepeekeo facility. At the Haleakala cla ss 1 area the impacts are all below the 0.5 Δ dv

threshold. However, at the Hawaii Volcanoe s class 1 area, the top 8 impacts all exceed

the 0.5 Δ dv threshold. Based on this modeling a ssessment, the Ho Honua Bioenergy –

Pepeekeo facility is Subject-to-BART.

Table 10 presents the top 8 visibility impacts ( Δ dv) for the MECO-Kahului facility. The

only impact that exceeds the 0.5 Δ dv threshold was the highest impact at the Haleakala

Class 1 area. No other of the top 8 visibility impacts, including the 8 th 

# high (98 th



# percentile value), exceed the 0.5 Δ dv threshold. Based on this modeling assessment, the

MECO Kahului facility is not Subject-to-BART.

Table 11 presents the t op 8 visibility impacts ( Δ dv) for the HELCO Kanoelehua Hill

facility. For this facility the top 8 visibili ty impacts at both of the Class 1 areas exceed

the 0.5 Δ dv threshold. Based on this modeling a ssessment, the HELCO Kanoelehua Hill

facility is Subject-to-BART.

Table 12 presents the t op 8 visibility impacts ( Δ dv) for the HECO Waiau facility. The

only impacts that exceeds the 0.5 Δ dv threshold were the highest two impacts at the

Haleakala Class 1 area. None other of the top 8 visibility impacts, including the 8 th 

# high

(98 th 

# percentile value), exceed the 0.5 Δ dv threshold. Based on this modeling assessment,

the HECO Waiau facility is not Subject-to-BART.

Table 13 presents the top 8 visibility impacts ( Δ dv) for the HECO Kahe facility. The

only impacts that exceeds the 0.5 Δ dv threshold were the highest five impacts at the

Haleakala Class 1 area. The rest of the top 8 visibility impacts, including the 8 th 

# high (98 th



# percentile value), did not exceed the 0.5 Δ dv threshold. Based on this modeling

assessment, the HECO Kahe facility is not Subject-to-BART.

22

## Table 6: Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the HC&S Puunene

Operating on either bagasse or coal. . Visibility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7)

are shaded yellow. Visibility impacts over 0.5 Δ dv for 98 th 

## percentile (8 th 

## high) are shaded red.

Source High Haleakala Hawaii Volcanoes

Δ dv Δ dv

HC&S Puunene (Bagasse) 1 0.119 0.029

HC&S Puunene (Bagasse) 2 0.102 0.024

HC&S Puunene (Bagasse) 3 0.101 0.017

HC&S Puunene (Bagasse) 4 0.090 0.011

HC&S Puunene (Bagasse) 5 0.061 0.010

HC&S Puunene (Bagasse) 6 0.060 0.010

HC&S Puunene (Bagasse) 7 0.059 0.009

HC&S Puunene (Bagasse) 8 0.059 0.008

HC&S Puunene (Coal) 1 0.236 0.094

HC&S Puunene (Coal) 2 0.224 0.092

HC&S Puunene (Coal) 3 0.184 0.090

HC&S Puunene (Coal) 4 0.181 0.089

HC&S Puunene (Coal) 5 0.170 0.073

HC&S Puunene (Coal) 6 0.150 0.073

HC&S Puunene (Coal) 7 0.140 0.053

HC&S Puunene (Coal) 8 0.133 0.039

Table 7. Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the Chevron

Refinery. . Visibility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow.

Visibility impacts over 0.5 Δ dv for 98 th 

## percentile (8 th 

## high) are shaded red

Source High Haleakala Hawaii Volcanoes

Δ dv Δ dv

Chevron Refinery 1 0.208 0.055

Chevron Refinery 2 0.135 0.032

Chevron Refinery 3 0.083 0.025

Chevron Refinery 4 0.082 0.019

Chevron Refinery 5 0.060 0.019

Chevron Refinery 6 0.031 0.017

Chevron Refinery 7 0.029 0.017

Chevron Refinery 8 0.021 0.016



# 23

## Table 8: Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the Tesoro Refinery.

Visibility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shad ed yellow. Visibility impacts

over 0.5 Δ dv for 98 th 

## percentile (8 th 

## high) are shaded red

Source High Haleakala Hawaii Volcanoes

Δ dv Δ dv

Tesoro Refinery 1 0.237 0.062

Tesoro Refinery 2 0.173 0.038

Tesoro Refinery 3 0.099 0.033

Tesoro Refinery 4 0.092 0.027

Tesoro Refinery 5 0.079 0.023

Tesoro Refinery 6 0.040 0.019

Tesoro Refinery 7 0.027 0.019

Tesoro Refinery 8 0.025 0.017

Table 9. Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the Hu Honua

Bioenergy –Pepeekeo facility. Visibility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are

shaded yellow. Visibility impacts over 0.5 Δ dv for 98 th 

## percentile (8 th 

## high) are shaded red

Source High Haleakala Hawaii Volcanoes

Δ dv Δ dv

Hu Honua Bioenergy –Pepeekeo 1 0.444 1.660

Hu Honua Bioenergy –Pepeekeo 2 0.444 1.102

Hu Honua Bioenergy –Pepeekeo 3 0.404 1.067

Hu Honua Bioenergy –Pepeekeo 4 0.398 0.689

Hu Honua Bioenergy –Pepeekeo 5 0.376 0.651

Hu Honua Bioenergy –Pepeekeo 6 0.373 0.552

Hu Honua Bioenergy –Pepeekeo 7 0.364 0.551

Hu Honua Bioenergy –Pepeekeo 8 0.323 0.540

Table 10: Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the MECO -

Hahului facility. Visi bility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow.

Visibility impacts over 0.5 Δ dv for 98 th 

## percentile (8 th 

## high) are shaded red

Source High Haleakala Hawaii Volcanoes

Δ dv Δ dv

MECO - Hahului 1 0.566 0.250

MECO - Hahului 2 0.467 0.250

MECO - Hahului 3 0.447 0.240

MECO - Hahului 4 0.363 0.238

MECO - Hahului 5 0.345 0.183

MECO - Hahului 6 0.298 0.163

MECO - Hahului 7 0.289 0.163

MECO - Hahului 8 0.232 0.108



# 24

## Table 11. Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the HELCO

Kanoelehua Hill facility. Visibility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded

yellow. Visibility impacts over 0.5 Δ dv for 98 th 

## percentile (8 th 

## high) are shaded red

Source High Haleakala Hawaii Volcanoes

Δ dv Δ dv

HELCO Kanoelehua Hill 1 1.132 4.681

HELCO Kanoelehua Hill 2 1.023 4.088

HELCO Kanoelehua Hill 3 0.872 2.967

HELCO Kanoelehua Hill 4 0.865 2.879

HELCO Kanoelehua Hill 5 0.856 2.759

HELCO Kanoelehua Hill 6 0.846 2.448

HELCO Kanoelehua Hill 7 0.812 2.403

HELCO Kanoelehua Hill 8 0.808 2.334

Table 12. Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the HECO - Waiau

facility. Visibility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow. Visibility

impacts over 0.5 Δ dv for 98 th 

## percentile (8 th 

## high) are shaded red

Source High Haleakala Hawaii Volcanoes

Δ dv Δ dv

HECO - Waiau 1 0.573 0.211

HECO - Waiau 2 0.512 0.131

HECO

- Waiau 3 0.251 0.117

HECO

- Waiau 4 0.248 0.111

HECO

- Waiau 5 0.211 0.092

HECO

- Waiau 6 0.193 0.071

HECO

- Waiau 7 0.103 0.039

HECO

- Waiau 8 0.083 0.038

Table 13

Table 13. Top 8 visibility impacts ( Δ dv) at Haleakala and Hawaii Volcanoes for the HECO - Kahe

facility. Visibility impacts over 0.5 Δ dv over 98 th 

## percentile (Top 1-7) are shaded yellow. Visibility

impacts over 0.5 Δ dv for 98 th 

## percentile (8 th 

## high) are shaded red

Source High Haleakala Hawaii Volcanoes

Δ dv Δ dv

HECO - Kahe 1 1.277 0.299

HECO - Kahe 2 1.153 0.286

HECO - Kahe 3 0.707 0.222

HECO - Kahe 4 0.686 0.198

HECO - Kahe 5 0.656 0.196

HECO

- Kahe 6 0.381 0.162

HECO

- Kahe 7 0.240 0.142

HECO

- Kahe 8 0.221 0.132



# 25

# 26 

# 5. CONCLUSION

A CALPUFF modeling analysis was performed to determine which BART-eligible

sources in Hawaii are Subject-to-BART. Th e modeling assessment looked at the HC&S

Puunene facility, the Chevron Refinery, the Tesoro Refinery, the Hu Honua Bioenergy –

Pepeekeo facility, the MECO – Hahului f acility, the HELCO Kanoelehua Hill facility,

the HECO – Waiau facility, and the HECO – Kahe facility. The only facilities that

showed a 98 th 

# percentile (8 th 

# high) 24-hour average visibility impact over the 0.5 Δ dv

impact threshold were the Hu Honua Bioenergy – Pepeekeo and the HELCO -

Kanoelehua Hill facilities. Thus, the Hu Honua Bioenergy –Pepeekeo and the HELCO -

Kanoelehua Hill facilities are Subject-to- BART. The HC&S Puunene facility, the

Chevron Refinery, the Tesoro Refinery, the MECO – Hahului facility the HECO – Waiau

facility, and the HECO – Kahe f acility are not Subject-to-BART.

# 6. REFERENCES

40 CFR Part 51, Appendix W. Guidelines on Air Quality Models

Alpine Geophysics, 2010. “Subject-to-Best Av ailable Retrofit Technology (BART) and

Reasonable Progress (RP) PrioritizationMode ling Protocol for the State of Hawaii:

Application of the CALPUFF Modeling Sy stem” prepared for the Hawaii State

Department of Health, Environmental Manage ment Division, Clean Air Branch, prepared

by Alpine Geophysics, LLC, Arvada, CO.

Dudhia, J., 1993. “A Non-hydrostatic Versio n of the Penn State/NCAR Mesoscale

Model: Validation Tests and Simulation of an Atlantic Cyclone and Cold Front”, Mon.

Wea. Rev., Vol. 121. pp. 1493-1513.

EPA (U.S. Environmental Protection Ag ency) 1998. Interagency Workgroup on Air

Quality Modeling (IWAQM) Phase 2 Summary Report and Recommendations for

Modeling Long Range Transport Imp acts, EPA-454/R-98-019, December 1998.

EPA 2003. Guidance for Estimating Natural Visibility Conditions under the Regional

Haze Rule, EPA-454/B-03-005, September, 2003.

Federal Register, Vol. 70, No. 128. Regional Ha ze Regulations and Guidelines for Best

Available Retrofit Technology (BART) De terminations. pp. 39104 – 30172, July 6, 2005.

FLAG 2000. Federal Land Managers’ Air Qual ity Related Values Workgroup (FLAG)

2000. Phase I Report. December 2000.

FLAG 2008. Federal Land Managers’ Air Qual ity Related Values Workgroup (FLAG)

2008. Phase I Report—Revised. June 27, 2008 draft.

Gemmill, William, Bert Katz and Xu Li, 2007. Daily Real-Time Global Sea Surface

Temperature - High Resolution Analys is at NOAA/NCEP. NOAA/NWS/NCEP/MMAB

Office Note Nr. 260, 39 pp.

Grell, G. A., J. Dudhia, and D. R. Stauffer. 1994. A Description of the Fifth Generation

Penn State/NCAR Mesoscale Model (MM5). NCAR Tech. Note, NCAR TN-398-STR,

138 pp.

McNally, D.E., 2008,”MM5 Sensitivity to Alte rnate Configurations over the Hawaiian

Islands”, prepared for the Hawaii State Department of Health, Environmental

Management Division, Clean Air Branch, pr epared by Alpine Geophysics, LLC, Arvada,

CO.

McNally, D.E, and J.G. Wilkinson 2008, ”MM5 Application for 2005 Over the

Hawaiian Islands”, prepared for the Hawaii St ate Department of Health, Environmental

27

# Management Division, Clean Air Branch, pr epared by Alpine Geophysics, LLC, Arvada,

CO.

NCEP, 2008. Real-time, global, sea surface temperature (RTG_S ST) analysis. 10-July.

polar.ncep.noaa.gov/sst/oper/Welcome.html

NOAA, 2009. Mauna Loa Observatory. 29-April, mlo.noaa.gov/livedata/livedata.html.

UCAR, 2003a. MM5 Community Model: Current Release. 09-April.

www.mmm.ucar.edu/mm5/overviewCurrent.html

UCAR, 2003b. MM5 Community Model: MM5 M odeling System Overview. 10-April.

www.mmm.ucar.edu/mm5/overviewProgram.html

UCAR, 2008a. ds353.4 Home Page. NCEP ADP Global Upper Air Observation Subsets,

January 1973 – continuing. CISL Research Da ta Archive. dss.ucar.edu/datasets/ds353.4.

UCAR, 2008b. ds464.0 Home Page. NCEP ADP Global Surface Observations, February

1975 – continuing. CISL Research Data Archive. dss.ucar.edu/datasets/ds464.0.

UCAR, 2008c. ds472.0 Home Page. TDL U.S. and Canada Surface Hourly

Observations, daily 1976Dec – cont. CISL Research Data Archive.

dss.ucar.edu.datasets.ds472.0.

28

# Appendix A CALMET Parameter Values

29

# Table A-1. CALMET Parameter Values

The CALMET model will be run using the August 20, 2009, “EPA-FLM Recommended

CALMET input File Values.”

Input

Group Variable Description Default Value Recommended Value

0 DIADAT Input file: preprocessed surface temperature data

(DIAG.DAT) User Defined

0 GEODAT Input file: Geophysical data (GEO.DAT) User Defined User Define

0 LCFILES Convert file name to lower case User Defined

0 METDAT Output file (CALMET.DAT) User Defined

0 METLST Output file (CALMET.LST) User Defined

0 MM4DAT Input file: MM4 data (MM4.DAT) User Defined

0 NOWSTA Input files: Names of NOWSTA overwater stations User Defined 6

0 NUSTA Number of upper air data sites User Defined 2

0 PACDAT Output file: in Mesopuff II format (PACOUT.DAT) User Defined

0 PRCDAT Input file: Precipitation data (PRECIP.DAT) User Defined

0 PRGDAT Input file: CSUMM prognostic wind data (PROG.DAT) User Defined

0 SEADAT Input files: Names of NOWSTA overwater stations

(SEAn.DAT) User Defined

0 SRFDAT Input file: Surface data (SURF.DAT) User Defined

0 TSTFRD Output file (TEST.FRD) User Defined

0 TSTKIN Output file (TEST.KIN) User Defined

0 TSTOUT Output file (TEST.OUT) User Defined

0 TSTPRT Output file (TEST.PRT) User Defined

0 TSTSLP Output file (TEST.SLP) User Defined

0 UPDAT Input files: Names of NUSTA upper air data files (UPn.DAT) UPn.DAT

0 WTDAT Input file: Terrain weighting factors (WT.DAT) User Defined

1 CLDDAT Input file: Cloud data (CLOUD.DAT) User Defined Not used

1 IBDY Beginning day User Defined

1 IBHR Beginning hour User Defined

1 IBMO Beginning month User Defined

1 IBTZ Base time zone User Defined 0

1 IBYR Beginning year User Defined

1 IRLG Number of hours to simulate User Defined User Define

1 IRTYPE Output file type to create (must be 1 for CALPUFF) 1 1

1 ITEST Flag to stop run after Setup Phase 2 2

1 LCALGRD Are w-components and temperature needed? T T

1 MREG Text to options to conrim they c onform to regulatory options User Defined 1

2 PMAP Map Projection UTM LCC

2 FEAST False easting at the projection origin 0.0 0.0

2 FNORTH False northing at the projection origin 0.0 0.0

2 DATUM WGS-G, NWS-27, NWS-84, ESR-S,... WGS-G

2 DGRIDKM Grid spacing User Defined 4

2 UTMHEM Hemisphere for UTM projection N N

2 IUTMZN UTM Zone User Defined User Define

2 LLCONF When using Lambert Conformal map coordinates - rotate

winds from true north to map north? F F

2 NX Number of east-west grid cells User Defined 199

2 NY Number of north-south grid cells User Defined 145

2 NZ Number of vertical layers User Defined 10

2 RLAT0 Latitude used if LLCONF = T User Defined 23.0N

2 RLON0 Longitude used if LLCONF = T User Defined 158.0W

2 XLAT1 Latitude of 1 st standard parallel User Defined 30

2 XLAT2 Latitude of 2 nd standard parallel User Defined 60

2 XORIGKM Southwest grid cell X coordinate User Defined -360



# 30Input

Group Variable Description Default Value Recommended Value

2 YORIGKM Southwest grid cell Y coordinate User Defined -588

2 ZFACE Vertical cell face height s (NZ+1 values) User Defined 0,20,40,80,160,320,640,

1200,2000,3000,4000

3 IFORMO Format of unformatted file (1 for CALPUFF) 1 1

3 LSAVE Save met. data fields in an unformatted file? T T

4 ICLOUD Is cloud data to be input as gridded fields? (0 = No) 0 0

4 IFORMC Format of cloud data (2 = formatted) 2 2

4 IFORMP Format of precipitation data (2 = formatted) 2 2

4 IFORMS Format of surface data (2 = formatted) 2 2

4 NOOBS Use or non-use of surface, over water, upper observations User Defined 0

4 NPSTA Number of stations in PRECIP.DAT User Defined 14

4 NSSTA Number of stations in SURF.DAT file User Defined 14

5 ALPHA Empirical factor triggering kinematic effects 0.1 0.1

5 BIAS Surface/upper-air weighting factors (NZ values) NZ*0 NZ*0

5 CRITFN Critical Froude number 1 1

5 DIVLIM Maximum acceptable divergence 5.00E-06 5.00E-06

5 FEXTR2 Multiplicative scaling factor for extrap surface obs to uppr

layrs NZ*0.0 NZ*0.0

5 ICALM Extrapolate surface calms to upper layers? (0 = No) 0 0

5 IDIOPT1 Compute temperatures from observations (0 = True) 0 0

5 IDIOPT2 Compute domain-average lapse rates? (0 = True) 0 0

5 IDIOPT3 Compute internally inital guess winds? (0 = True) 0 0

5 IDIOPT4 Read surface winds from SURF.DAT? ( 0 = True) 0 0

5 IDIOPT5 Read aloft winds from UPn.DAT? (0 = True) 0 0

5 IEXTRP Extrapolate surface winds to upper layers? (-4 = use

similarity theory and ignore layer 1 of upper air station data) -4 -4

5 IFRADJ Adjust winds using Froude number effects? (1 = Yes) 1 1

5 IKINE Adjust winds using kinematic effects? (1 = Yes) 0 0

5 IOBR Use O’Brien procedure for vertical winds? (0 = No) 0 0

5 IPROG Using prognostic or MM-FDDA data? (0 = No) 0 14

5 ISLOPE Compute slope flows? (1 = Yes) 1 1

5 ISTEPPG Timestep (hours) of t he prognostic model input data 1 1

5 ISURFT Surface station to use for surface temperature (between 1

and NSSTA) User Defined 9

5 IUPT Station for lapse rates (between 1 and NUSTA) User Defined 1

5 IUPWND Upper air station for domain winds (-1 = 1/r**2 interpolation

of all stations) -1 -1

5 IWFCOD Generate winds by diagnostic wind module? (1 = Yes) 1 1

5 KBAR Level (1 to NZ) up to which barriers apply NZ 10

5 LLBREZE Use Lake Breeze module F F

5 LVARY Use varying radius to develop surface winds? F F

5 METBXID Station IDs in the region User Defined

5 NBAR Number of Barriers to interpolation User Defined 0

5 NBOX Number of Lake Breeze regions User Defined 0

5 NINTR2 Max number of stations for interpolations (NA values) 99 99

5 NITER Max number of passes in divergence minimization 50 50

5 NLB Number of stations in region User Defined 0

5 NSMTH Number of passes in smoothing (NZ values) 2, 4*(NZ-1) 2,4*(NZ-1)

5 R1 Relative weight at surface of Step 1 field and obs User Defined 50

5 R2 Relative weight aloft of Step 1 field and obs User Defined 100

5 RMAX1 Max surface over-land extrapol ation radius (km) User Defined 100

5 RMAX2 Max aloft over-land extrapolat ion radius (km) User Defined 200

5 RMAX3 Maximum over-water extrapol ation radius (km) User Defined 200

5 RMIN Minimum extrapolation radius (km) 0.1 0.1



# 31Input

Group Variable Description Default Value Recommended Value

5 RMIN2 Distance (km) around an upper air site where vertical

extrapolation is excluded (Set to -1 if IEXTRP = ±4) 4 -1

5 RPROG Weighting factor for CSUMM prognostic wind data User Defined 0

5 TERRAD Radius of influence of terra in features (km) User Defined 15

5 XBBAR X coordinate of Beginning of each barrier User Defined 0

5 XBCST X Point defining the coastli ne (staight line) User Defined 0

5 XEBAR X coordinate of Ending of each barrier User Defined 0

5 XECST X Point User Defined 0

5 XG1 X Grid line 1 defining region of interest User Defined 0

5 XG2 X Grid line 2 User Defined 0

5 YBBAR Y coordinate of Beginning of each barrier User Defined 0

5 YBCST Y Point User Defined 0

5 YEBAR Y coordinate of Ending of each barrier User Defined 0

5 YECST Y Point User Defined 0

5 YG1 Y Grid line 1 User Defined 0

5 YG2 Y Grid Line 2 User Defined 0

5 ZUPT Depth of domain-average lapse rate (m) 200 200

5 ZUPWND Bottom and top of layer for 1 st guess winds (m) 1, 1000 1.,1000.

6 CONSTB Neutral mixing height B constant 1.41 1.41

6 CONSTE Convective mixi ng height E constant 0.15 0.15

6 CONSTN Stable mixing height N constant 2400 2400

6 CONSTW Over-water mixing height W constant 0.16 0.16

6 CUTP Minimum cut off precip rate (mm/hr) 0.01 0.01

6 DPTMIN Minimum capping potential temperature lapse rate 0.001 0.001

6 DSHELF Coastal/shallow water length scale 0 0

6 DZZI Depth for computing capping lapse rate (m) 200 200

6 FCORIOL Absolute value of Coriolis parameter 1.00E-04 1.00E-04

6 HAFANG Half-angle for looking upwind (degrees) 30 30

6 IAVET Conduct spatial averaging of temperature? (1 = True) 1 1

6 IAVEZI Spatial averaging of mixing heights? (1 = True) 1 1

6 ICOARE Overwater surface fluxes method and parameters 10 0

6 ICOOL COARE cool skin layer computation 0 0

6 ILEVZI Layer to use in upwind averaging (between 1 and NZ) 1 1

6 ILUOC3D Land use category ocean in 3D.DAT datasets 16 16

6 IMIXH Method to compute the c onvective mixing height -1 -1

6 IRAD Form of temperature interpolation (1 = 1/r) 1 1

6 IRHPROG 3D relative humidity from observations or from prognostic

data 0 1

6 ITPROG 3D temps from obs or from prognostic data? 0 2

6 ITWPROG Option for overwater lapse rate s used in convective mixing

height growth 0 0

6 IWARM COARE warm layer computation 0 0

6 JWAT1 Beginning landuse type defining water 999 55

6 JWAT2 Ending landuse type defining water 999 55

6 MNMDAV Max averaging radius (number of grid cells) 1 1

6 NFLAGP Method for precipitation interpolation (2 = 1/r**2) 2 2

6 NUMTS Max number of stations in temperature interpolations 5 5

6 SIGMAP Precip radius fo r interpolations (km) 100 100

6 TGDEFA Default over-water cappi ng lapse rate (K/m) -0.0045 -0.0045

6 TGDEFB Default over-water mixed layer lapse rate (K/m) -0.0098 -0.0098

6 THRESHL Threshold buoyancy flux requi red to sustain convective

mixing height growth overland 0.05 0.0

6 THRESHW Threshold buoyancy flux requi red to sustain convective

mixing height growth overwater 0.05 0.05

6 TRADKM Radius of temperature interpolation (km) 500 500



# 32Input

Group Variable Description Default Value Recommended Value

6 ZIMAX Maximum over-land mixing height (m) 3000 3000

6 ZIMAXW Maximum over-water mixing heigh (m) 3000 3000

6 ZIMIN Minimum over-l and mixing height (m) 50 50

6 ZIMINW Minimum over-water mixing height (m) 50 50



# 33

# 34 

# Appendix B CALPUFF Parameter ValuesTable B-1. CALPUFF Parameter ValuesCALPUFF input settings.Table B-1. CALPUFF Parameter ValuesInputGroupGroupDescriptionVariableDescriptionDefault ValueaRecommended Value1Run ControlMETRUNDo we run all periods (1) or a subset (0)?001IBYRBeginning yearUser Defined20051IBMOBeginning monthUser Defined11IBDYBeginning dayUser Defined11IBHRBeginning hourUser Defined11IRLGLength of run (hours)User Defined87601XBTZBase Time ZoneUser Defined01NSECDTLength of modeling time step (seconds)360036001NSPECNumber of species modeled (for MESOPUFF IIchemistry)581NSENumber of species emitted351ITESTFlag to stop run after Setup Phase221MRESTARTRestart options (0 = no restart) allows splittingruns into smaller segments001NRESPDNumber of periods in Restart001METFMFormat of input meteorology (1 = CALMET, 2 =ISC)111AVETAveraging time lateral dispersion parameters(minutes)60601PGTIMEPG Averaging time60602Tech OptionsMGAUSSNear-field vertical distribution (1 = Gaussian)112MCTADJTerrain adjustments to plume path (3 = Plumepath)332MCTSGDo we have subgrid hills? (0 = No) allowsCTDM-like treatment for subgrid scale hills002MSLUGNear-field puff treatment (0 = No slugs)002MTRANSModeltransitionalplume rise? (1 = Yes)112MTIPTreat stack tip downwash? (1 = Yes)112MBDWMethod to simulate downwashnot used35Table B-1. CALPUFF Parameter ValuesInputGroupGroupDescription VariableDescriptionDefault ValueaRecommended Value(1=ISC,2=PRIME)2MSHEARTreat vertical wind shear? (0 = No)002MSPLITAllow puffs to split? (0 = No)002MCHEMMESOPUFF-II Chemistry? (1 = Yes)112MAQCHEMAqueous phase transformation002MWETModel wet deposition? (1 = Yes)112MDRYModel dry deposition? (1 = Yes)112MTILTPlume Tilt (gravitational settling)002MDISPMethod for dispersion coefficients(2=micromet,3 = PG)332MTURBVWTurbulence characterization? (Only if MDISP =1 or 5)332MDISP2Backup coefficients (Only if MDISP = 1 or 5)332MTAULYMethod for Sigma y Lagrangian timescale002MTAUADVMethod for Advective-Decay timescale forTurbulence002MCTURBMethod to compute sigma v,w using micrometvariables112MROUGHAdjust PG for surface roughness? (0 = No)002MPARTLModel partial plume penetration? (0 = No)112MTINVElevated inversion strength (0 = compute fromdata)002MPDFUse PDF for convective dispersion? (0 = No)002MSGTIBLUse TIBL module? (0 = No) allows treatment ofsubgrid scale coastal areas002MBCONBoundary conditions modeled002MFOGConfigure for FOG model output002MREGRegulatory default checks? (1 = Yes)113Species ListCSPECnNames of species modeled (for MESOPUFF IImust be SO2-SO4-NOX-HNO3-NO3)User DefinedSO2,SO4,NOX,HNO3,NO3,NH3,PM10,PM253SpecieNamesManner species will be modeledSpecies,Modeled,Emitted,Dry Deposited,GroupUser DefinedSO2,1,1,1,0SO4,1,0,2,0NOX,1,1,1,0HNO3,1,0,1,0NO3,1,0,2,036Table B-1. CALPUFF Parameter ValuesInputGroupGroupDescription VariableDescriptionDefault ValueaRecommended ValueNH3,1,0,1,0PM10,1,1,2,0PM25,1,1,2,03SpecieGroupsGrouping of species if anyUser DefinedN/A3CGRUP3CGRUP4MapProjectionXLAT1Latitude of 1ststandard parallel30N4XLAT2Latitude of 2ndstandard parallel60N4PMAPMapProjectionUTMLCCFEASTFalseEasting0.00.0FNORTHFalseNorthing0.00.04DATUMDatum-regionWGS-GWGS-G4NXNumber of east-west grids of input meteorologyUser Defined1994NYNumber of north-south grids of inputmeteorologyUser Defined1454NZNumber of vertical layers ofinput meteorologyUser Defined104DGRIDKMMeteorology grid spacing (km)User Defined4.4ZFACEVertical cell face heights of input meteorologyUser Defined0.,20.,40.,80.,160.,320.,640.,1200.,2000.,3000.,4000.4XORIGKMSouthwest corner (east-west)of input UserDefined meteorology-360.4YORIGIMSouthwest corner (north-south)of input UserDefined meteorology-588.4IUTMZNUTM zoneUser DefinedN/A (17)4UTMHEMHemisphere for UTM ProjectionNN4RLAT0Latitude of Projection OriginUser Defined23.0N4RLON0Longitude of Projection OriginUser Defined158.0W4IBCOMPSouthwest X-index of computational domainUser Defined14JBCOMPSouthwest Y-index of computational domainUser Defined14IECOMPNortheast X-index of computational domainUser Defined1994JECOMPNortheast Y-index of computational domainUser Defined1454LSAMPUse gridded receptors? (T = Yes)FF37Table B-1. CALPUFF Parameter ValuesInputGroupGroupDescription VariableDescriptionDefault ValueaRecommended Value4IBSAMPSouthwest X-index of receptor gridUser Defined4JBSAMPSouthwest Y-index of receptor gridUser Defined4IESAMPNortheast X-index of receptor gridUser Defined4JESAMPNortheast Y-index of receptor gridUser Defined4MESHDNGridded recpetor spacing =DGRIDKM/MESHDN115Output OptionsICONOutput concentrations? (1 = Yes)115IDRYOutput dry deposition flux? (1 = Yes)115IWETOutput west deposition flux? (1 = Yes)115IT2D2DTemperature005IRHO2DDensity005IVISOutput RH for visibility calculations (1 = Yes)105LCOMPRSUse compression option in output? (T = Yes)TT5ICPRTPrint concentrations? (0 = No)005IDPRTPrint dry deposition fluxes (0 = No)005IWPRTPrint wet deposition fluxes (0 = No)005ICFRQConcentration print interval (1 = hourly)115IDFRQDry deposition flux print interval (1 = hourly)115IWFRQWest deposition flux print interval (1 = hourly)115IPRTUPrint output units (1 = g/m**3; g/m**2/s; 3 =ug/m3, ug/m2/s)135IMESGStatus messages to screen? (1 = Yes)125LDEBUGTurn on debug tracking? (F = No)FF5IPFDEBFirst puff to track115NPFDEB(Number of puffs to track)(1)15NN1(Met. Period to start output)(1)15NN2(Met. Period to end output)(10)107Dry Dep ChemDry Gas DepChemical parameters of gaseous depositionSpecies,Diffusivity,AlphaStar,Reactivity,Mesophyll,Henry’sUserDefinedSO2,0.1509,1000.,8.,0.,0.04NOX,0.1656,1.,8,.5.,3.5HNO3,0.1628,1.,18.,0.,8E-8NH3,0.234,0.2,4.,0.,3.59E-438Table B-1. CALPUFF Parameter ValuesInputGroupGroupDescription VariableDescriptionDefault ValueaRecommended Value8Dry Dep SizeDry Part. DepChemical parameters of particulate depositionSpecies,Mass Mean Diameter,Geometric Std DUser DefinedSO4,0.48.,2.,NO3,0.48,2.,PM10,10.,0.,PM25,2.5,0.,9Dry Dep MiscRCUTRReference cuticle resistance (s/cm)30309RGRReference ground resistance (s/cm)10109REACTRReference reactivity889NINTNumber of particle-size intervals999IVEGVegetative state (1 = active and unstressed;2=active and stressed)1110Wet DepWet DepWet deposition parametersSpecies, Liquid Precip, Frozen PrecipUserDefinedSO2,3.0E-05,0.SO4,1.0E-04,3.0E-05NOX,0.,0.HNO3,6.0E-05,0.0NO3,1.0E-04,3.0E-05NH3,8.0E-05,0.0PM10,1.0E-04,3.0E-05PM25,1.0E-04,3.0E-0511ChemistryMOZOzone background? (0 = constant backgroundvalue; 1 = read from ozone.dat)1011BCKO3Ozone default (ppb) (Use only for missing data)80.12*40.11BCKNH3Ammonia background (ppb)101.511RNITE1Nighttime SO2 loss rate (%/hr)0.20.211RNITE2Nighttime NOx loss rate (%/hr)2211RNITE3Nighttime HNO3 loss rate (%/hr)2211MH2O2H2O2 data input option1111BCKH2O2Monthly H2O2 concentrations1not usedBKPMFFine particulate concentration12 * 1.00not usedOFRACOrganic fraction of Fine Particulate2*0.15, 9*0.20, 1*0.15not usedVCNXVOC / NOX ratio12 * 50.00not used12DispersionSYTDEPHorizontal size (m) to switch to timedependence55055012MHFTSZUse Heffter for vertical dispersion? (0 = No)0039Table B-1. CALPUFF Parameter ValuesInputGroupGroupDescription VariableDescriptionDefault ValueaRecommended Value12JSUPPG Stability class above mixed layer5512CONK1Stable dispersion constant (Eq 2.7-3)0.010.0112CONK2Neutral dispersion constant (Eq 2.7-4)0.10.112TBDTransition for downwash algorithms (0.5 = ISC)0.50.512IURB1Beginning urban landuse type101012IURB2Ending urban landuse type191912ILANDUINLand use type (20 = Unirrigated agriculturalland)202012ZOINRoughness length (m)0.250.2512XLAIINLeaf area index3.03.012ELEVINMet. Station elevation (m above MSL)0.00.012XLATINMet. Station North latitude (degrees)-999.0-999.012XLONINMet. Station West longitude (degrees)-999.0-999.012ANEMHTAnemometer height of ISC meteorological data(m)10.010.012ISIGMAVLateral turbulence (Not used with ISCmeteorology)1112IMIXCTDMMixing heights (Not used with ISC meteorology)0012XMXLENMaximum slug length in units of DGRIDKM1.01.012XSAMLENMaximum puff travel distance per samplingstep (units of DGRIDKM)1.01.012MXNEWMaximum number of puffs per hour999912MXSAMMaximum sampling steps per hour999912NCOUNTIterations when computing Transport Wind(Calmet & Profile Winds)2212SYMINMinimum lateral dispersion of new puff (m)1.01.012SZMINMinimum vertical dispersion of new puff (m)1.01.012SVMINArray of minimum lateral turbulence (m/s)6 * 0.50,6*0.376 * 0.50, 6*0.5012SWMINArray of minimum vertical turbulence (m/s)2*(0.20,0.12,0.08,0.06,0.03,0.016)2*(0.20,0.12,0.08,0.06,0.03,0.016)12CDIV (1), (2)Divergence criterion for dw/dz (1/s)0.0,0.00.0,0.012WSCALMMinimum non-calm wind speed (m/s)0.50.540Table B-1. CALPUFF Parameter ValuesInputGroupGroupDescription VariableDescriptionDefault ValueaRecommended Value12XMAXZIMaximum mixing height (m)3000300012XMINZIMinimum mixing height (m)505012WSCATUpper bounds 1st5 wind speed classes (m/s)1.54,3.09,5.14,8. 23,10.81.54,3.09,5.14,8. 23,10.812PLX0Wind speed power-law exponents0.07,0.07,0.10,0.15,0.35,0.550.07,0.07,0.10,0.15,0.35,0.5512PTGOPotential temperature gradients PG E and F(deg/km)0.020,0.0350.020,0.03512PPCPlume path coefficients (only if MCTADJ = 3)0.5,0.5,0.5,0.5,0.35,0.350.5,0.5,0.5,0.5,0.35,0.3512SL2PFMaximum Sy/puff length10.010.012NSPLITNumber of puffs when puffs split3312IRESPLITHours when puff are eligible to splitHour 17=1Hour17=112ZISPLITPrevious hour’s mixing height(minimum)(m)100.0100.012ROLDMAXPrevious Max mix ht/current mix ht ratio mustbe less then this value for puff to split0.250.2512NSPLITHNumber of puffs when puffs split horizontally5512SYSPLITHMin sigma-y (grid cell units) of puff before horizsplit1.01.01212SHSPLITHMin puff elongation rate per hr from wind shearbefore horiz split2.02.012CNSPLITHMin conc g/m3 before puff may split horizontally1.0E-071.0E-0712EPSSLUGConvergence criterion for slug samplingintegration1.00E-041.00E-0412EPSAREAConvergence criterion for area sourceintegration1.00E-061.00E-0612DSRISEStep length for rise integration1.01.012HTMINBC500.0500.012RSAMPBC10.010.012MDEPBC1113Point SourceNPT1Number of point sourcesUser Defined13IPTUUnits of emission rates (1 = g/s)134142Table B-1. CALPUFF Parameter ValuesInputGroupGroupDescription VariableDescriptionDefault ValueaRecommended Value13NSPT1Number of point source-species combinations0013NPT2Number of point sources with fully variableemission rates0013PointSourcesPoint sources characteristicsUser Defined14Area SourceArea SourcesArea sources characteristicsUser Defined15Volume SourceVolumeVolume sources characteristicsUser Defined Sources16Line SourceLine SourcesBuoyant lines source characteristicsUser Defined17ReceptorsNRECNumber of userdefined receptorsUser Defined17ReceptorDataLocation and elevation (MSL)of receptorsUser Defined

# Appendix C CALPOST Parameter Values

43Table C-1. CALPOST Parameter ValuesThe CALPOST utility will be used for computation of visibility parameters using the parameters in this table.Table C-1: CALPOST Parameter ValuesInputGroupVariableDescriptionDefault ValueRecommended Value1ASPECSpecies to processVISIBVISIB1METRUNOption to run subset of met file011BTZONEBase time zoneUser Defined01ILAYERLayer/deposition code (1 = CALPUFFconcentrations; -3 = wet+drydeposition fluxes)111AScaling factor scalar0.00.01BAdditive factor0.00.01LBACKAdd Hourly Background Concentrations/Fluxes?FF1NO2CALCSpecify a single NO2/Nox ratio111RNO2NOXRatio of NO2 to NOx1.01.01MSOURCEProcess only total reported contribution002MVISCHECKConfirm conformity to FLAG 2008 Configuration112MFRHParticle growth curve for hygroscopic species442RHMAXMaximum relative humidity (%) used in particle growth curve98982LDRINGReport results by Discrete receptor Ring, if Discrete Receptors used.(T = true)TTModeled species to be included in computing the light extinction2LVSO4Include SO4?TT2LVNO3Include NO3?TT2LVOCInclude Organic Carbon?TF2LVPMCInclude Coarse Particles?TT2LVPMFInclude Fine Particles?TT2LVECInclude Elemental Carbon?TF2LVNO2Include NO2TT2LVBKwhen ranking for TOP-N, TOP-50, and Exceedance tables IncludeBACKGROUND?TT2SPECPMCSpecies name used for particulates in MODEL.DAT file: COARSE =PMCPM102SPECPMFSpecies name used for particulates in MODEL.DAT file: FINE =PMFPM25Extinction Efficiencies (1/Mm per ug/m**3)44Table C-1: CALPOST Parameter ValuesInputGroup VariableDescriptionDefault Value Recommended Value2EEPMCPM COARSE =0.60.62EEPMFPM FINE =1.01.02EEPMCBKBackground PM COARSE0.60.62EESO4SO4 =3.03.02EENO3NO3 =3.03.02EEOCOrganic Carbon =4.04.02EESOILSoil =1.01.02EEECElemental Carbon =10.010.02EENO2NO2 Gas =0.17550.17552LAVERMethod used for 24-hr avg % change light extinctionFF2MVISBKMethod used for background light extinction (2 = Hourly RHadjustment; 6 = FLAG seasonal f(RH))882RHFACMonthly RH adjustment factors from FLAG (unique for each Class Iarea)Yes if 6N/ABackground monthly extinction coefficients (FLAG) unique for eachClass I area2BKSO4SulfateSee Table 5 (NH3)2SO42BKNO3NitrateSee Table 5 NH4NO32BKPMCCoarse particulateSee Table 5 CM2BKOCParticulate organic carbonSee Table 5 OM2BKSOILSoilSee Table 5 Soil2BKECParticulate elemental carbonSee Table 5 EC2M8_MODEMethod 8 Mode552BKSALTBackground salt concentrationSee Table 2 Sea Salt2RHFSMLSmall ammonium sulfate and nitrate particle f(RH)See Table 72RHFLRGLarge ammonium sulfate and nitrate particle f(RH)See Table 62RHFSEASea salt f(RH)See Table 82BEXTRAYExtinction due to Rayleigh scattering10.010.03LDOCPrint documentation imageFFAveraging time(s) reported3L1PDAveraging period of model outputFF3L1HR1-hr averagesFF45Table C-1: CALPOST Parameter ValuesInputGroup VariableDescriptionDefault Value Recommended Value3L3HR3-hr averagesFF3L24HR24-hr averagesTT3LRUNLRun length (annual)FF3LT50Top 50 table for each averaging time selectedTF3LTOPNFT3NTOP413ITOP113LEXCDThreshold exceedance countFT3THRESH11-hour threshold-1.0-1.03THRESH33-hour threshold-1.0-1.03THRESH2424-hour threshold-1.00.53THRESHNN-hour threshold-1.0-1.03NDAYAccumulated Period (days)003NCOUNTNumber of exceedances allowed11Table C-2: POSTUTIL (Repartition) Parameter ValuesThe CALUTIL will be used to perform HNO3/NO3 repartitioning using the parameters in this table.Table C-2: POSTUTIL (Repartition) Parameter ValuesInputGroupVariableDescriptionDefault ValueRecommendedValue1IBYRBeginning yearUser Defined20051IBMOBeginning monthUser Defined11IBDYBeginning dayUser Defined11IBHRBeginning hourUser Defined11NPERLength of run (hours)User Defined87601NSPECINPNumber of species to processUser Defined71NSPECOUTNumber of species to writeUser Defined71NDUPLCTStop if duplicate species names0046Table C-2: POSTUTIL (Repartition) Parameter ValuesInputGroup VariableDescriptionDefault ValueRecommendedValue1NSCALEDNumber of CALPUFF data files to be scales001MNITRATERecompute HNO3/NO3 concentration partition011BKNH3Background ammonia concentrations10.1.52ASPECISpecies to inputUser DefinedSO2,SO4,NOX,HNO3,NO3,PM10,PM252ASPECOSpeceis to outputUser DefinedSO2,SO4,NOX,HNO3,NO3,PM10,PM25Table C-3.Background Extinction Coefficients (20% Best Days).BackgroundExtinctionCoefficients (20% Best Days)Class I Area(NH4)2SO4μg/m3NH4NO3Μg/m3OMμg/m3ECμg/m3Soilμg/m3CMμg/m3Sea Saltμg/m3RayleighMm-1Haleakala National Park(HALE1)0.050.040.240.010.111.590.1310Hawaii VolcanoesNational Park (HAVO1)0.030.040.270.010.060.640.1110Table C-4.Monthly fL(RH) – Large (NH4)2SO4 and NH4NO3Relative Humidity Adjustment Factor.Class I AreaJanFebMarAprMayJunJulAugSepOctNovDecHaleakala National Park (HALE1)2.342.272.252.202.132.092.162.142.102.192.332.30Hawaii Volcanoes National Park(HAVO1)2.562.452.472.472.472.452.532.592.552.572.782.554748Table C-5.Monthly fS(RH) – Small (NH4)2SO4and NH4NO3Relative Humidity Adjustment Factor.Class I AreaJanFebMarAprMayJunJulAugSepOctNovDecHaleakala National Park (HALE1)2.982.852.812.722.602.532.652.632.562.692.952.89Hawaii Volcanoes National Park(HAVO1)3.353.103.143.133.143.113.243.423.343.383.763.34Table C-6.Monthly fSS(RH) – Sea Salt Relative Humidity Adjustment Factor.Class I AreaJanFebMarAprMayJunJulAugSepOctNovDecHaleakala National Park (HALE1)3.523.433.403.353.253.183.293.273.223.333.523.47Hawaii Volcanoes National Park(HAVO1)3.803.683.713.723.723.693.793.833.793.834.083.80