# Technical Support Document

for the Proposed Action on the Federal Implementation Plan for the Regional Haze Program in the State of Hawaii

Air Division

U.S. EPA Region 9 May 14, 2012ii For information on this technical support document, please contact:

Carol Bohnenkamp Office of Air Quality Assessment and Analysis U.S. Environmental Protection Agency

– Region 9

75 Hawthorne Street San Francisco, California 94105 (415) 947

- 4130 bohnenkamp.carol@epa.gov

Greg Nudd Office of Air Planning U.S. Environmental Protection Agency

– Region 9

75 Hawthorne Street San Francisco, California 94105 (415) 947

- 4107 nudd.gregory@epa.goviii



### Table of Contents

I. Regional Haze and Hawaii

................................ ................................ ................................ ....... 1

I.A. Background on Regional Haze

................................ ................................ ......................... 1

I.B. Regional Haze Requirements

................................ ................................ ............................ 1

I.C. Visibility Impairment Goals

................................ ................................ .............................. 2

I.C.1. Natural, Baseline, and Current Visibility Conditions

................................ .................. 2

I.C.2. Estimation of Visibility Impairment

- The Original and the Revised IMPROVE Equations

................................ ................................ ................................ ............................ 3

I.C.3. Measures of Visibility

................................ ................................ .............................. 5

I.D. Unique Nature of Regional Planning in Hawaii

................................ ................................ 6

II. Description of Hawaii‟s National Parks

................................ ................................ .................. 6

II.A. HALEAKALA NATIONAL PARK

................................ ................................ ................ 6

II.A.1. Park Description

................................ ................................ ................................ ...... 7

II.A.2. Visibility Conditions

................................ ................................ ................................ 9

II.A.3. Causes of Haze

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

II.A.4. Comparison of Baseline 2001

- 2004 data to 2005 Data

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

II.A.4. Uniform Rate of Progress

................................ ................................ ....................... 14

II.A.5. Visibility Trends at Haleakala from 2001

- 2009

................................ ...................... 16

II.B. HAWAII VOLCANOES NATIONAL PARK

................................ ............................... 21

II.B.1. Hawaii Volcanic National Park Description

................................ ............................ 21

II.B.2. Visibility Conditions: baseline and natural (20% best and worst days)

................... 23

II.B.3 Causes of Haze

................................ ................................ ................................ ........ 24

II.B.4. Comparison of Baseline 2001

- 2004 data to 2005 Data

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

II.B.4. Uniform Rate of Progress

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

II.B.5. Visibility Trends from 2001

- 2009

................................ ................................ ........... 30

III. Summary of Previous Visibility Assessments at the Haleakala and Hawaii Volcanoes

National Parks.

................................ ................................ ................................ .......................... 33

III.A. NOAA Assessment of Causes of Haze for Hawaii‟s Two Class I Areas

....................... 33

III.B. Hawaii Department of Health Source Apportionment Results

................................ ...... 34

III.B.1. Hawaii DOH Park Visibility Assessment of Haleakala National Park

- Summary of

Results

................................ ................................ ................................ .............................. 35

II I.B.2. Hawaii DOH Park Visibility Assessment of Hawai‟i Volcanoes National

- Summary

of Results

................................ ................................ ................................ .......................... 36iv

IV. Emissions Inventory

................................ ................................ ................................ ............ 37

IV.A. Statewide Emissions Inventory

................................ ................................ .................... 37

IV. B. Review of the Emissions Inventory for Completeness and Accuracy

........................... 40

IV.C. Assessment of th e Emissions Inventory

................................ ................................ ....... 40

V. Causes of Haze in Hawaii (including volcanic emissions)

................................ ..................... 41

V.A. Island

- Specific Emissions Inventory

................................ ................................ ............. 41

V.B. Synthesis of Emissions Inventory, Monitoring Data, and PMF analysis

......................... 42

V.C. Visibility Impairing Pollutants Subject to Evaluation

................................ .................... 43

VI. Best Available Retrofit Te chnology (BART)

................................ ................................ ....... 44

VI.A. BART Requirements

................................ ................................ ................................ ... 44

VI.B. Identify BART Eligible Sources

................................ ................................ .................. 45

VI.C. Identify BART

- Subject Sources

................................ ................................ .................. 45

VI.C.1. Subject to BART Modeling for the State of Hawaii

................................ ............... 46

VI.C.2. Review of Subject to BART Modeling

................................ ................................ .. 48

VI.C.3. Assessment of Subject to BART Modeling

................................ ........................... 48

VI.C.4. Results of Subject to BART Modeling

................................ ................................ .. 48

VI.D. BART Determination and Federally Enforceable Limits

................................ .............. 49

VI.D.1 BART for NO

x and Particulate Matter (PM)

................................ ........................... 50

VI.D.2 BART for SO 2

................................ ................................ ................................ ....... 51

VII. Reasonable Progress

................................ ................................ ................................ .......... 54

VII.A. Unique Regional Haze Planning Challenge for Hawaii

................................ ............... 54

VII.B. Identification of Pollutants for Reasonable Progress

................................ ................... 55

VII.C. Determining Reasonable Progress Through Island

- Specific Emissions Inventories

..... 55

VII.C.1. Four Factor Analysis for NO

x sources on Maui and the Big Island

....................... 58

VII.C.2 Four Factor Analysis for SO 2 Emissions on Maui

................................ ................. 59

VII.C.3 Four Factor Analysis for SO 2 emissions on the Big Island (Hawaii)

...................... 62

VII.D. Benefits of the Emission Control Area on Emissions from In Transit Marine Vessels

. 64

VII.E. Reasonable Progress Goals

- 2018 Visibility Projections

................................ ............. 65

VII.F. Visibility Improvement Compared to URP and Number of Years to Reach Natural

Conditions

................................ ................................ ................................ ............................. 69

VIII. Monitoring Strategy

................................ ................................ ................................ .......... 70

VIII.A . IMPROVE Monitoring Network

................................ ................................ ............... 70

VIII.B. Analysis of the Haleakala (HALE1) IMPROVE monitoring site and newer Haleakala Crater (HACR1) Monitoring site

................................ ................................ ........................... 71v

Appendix A

Subject

- to

- Best Available Retrofit 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 by Alpine Geophysics, LLC

. March 3, 2010.

Appendix B

MM5 Application for 2005 Over the Hawaiian Islands, Prepared fo r Hawaii State Department of Health, Environmental Management Division, Clean

Air Branch by Alpine Geophysics, LLC1 

## Technical Support Document

for the Proposed Action on the Federal Implementation Plan for the Regional Haze Program in the State of Hawaii

I. Regional Haze and Hawaii

I.A. Background on Regional Haze

Regional haze is visibility impairment that is produced by a multitude of sources and

activities that are located across a broad geographic area and emit fine particulates (PM 2.5 ) (e.g., sulfates, nitrates, organic carbon (OC), elemental carbon (EC), and soil dust), and their precursors (e.g., sulfur dioxide (SO 2 ), nitrogen oxides (NO

x ), and in some cases, ammonia (NH 3 ) and volatile organic compounds (VOC)). Fine particle precursors react in the atmosphere to form

PM 2.5 , which impairs visibility by scattering and absorbing light. Visibility impairment reduces the clarity, color, and visible distance that one can see. P M 2.5 can also cause serious health effects and mortality in humans and contributes to environmental effects such as acid deposition and eutrophication. Data from the existing visibility monitoring network, the “Interagency Monitoring of

Protected Visual Environments” (IMPROVE) monitoring network, show that visibility impairment caused by air pollution occurs virtually all the time at most national parks (NPs) and wilderness areas (WAs). The average visual range 1 in many Class I areas ( i.e. , NPs and memori al parks, WAs, and international parks meeting certain size criteria) in the western United States is

100

- 150 kilometers, or about one

- half to two

- thirds of the visual range that would exist without anthropogenic air pollution. In most of the eastern Class I areas of the United States, the average visual range is less than 30 kilometers, or about one

- fifth of the visual range that would exist under estimated natural conditions. 64 FR 35715 (July 1, 1999).

I.B. Regional Haze Requirements

The Regional Haze R ule (RHR) sets out specific requirements for states‟ initial regional haze implementation plans. In particular, each state‟s plan must establish a long

- term strategy that ensures reasonable progress toward achieving natural visibility conditions in each Cl ass I area affected by the emissions from sources within the state. In addition, for each Class I area within the state‟s boundaries, the plan must establish a reasonable progress goal (RPG) for the first planning period that ends on July 31, 2018. The lon g

- term strategy must include enforceable emission limits and other measures as necessary to achieve the RPG. Regional haze plans must also give specific attention to certain stationary sources that were in existence on August 7, 1977, but were not in opera tion before August 7, 1962. These sources, where appropriate, are required

1 Visual range is the greatest distance, in kilometers or miles, at which a dark object can be viewed against the sky.2

to install Best Available Retrofit Technology (BART) controls to eliminate or reduce visibility impairment. More details on regional haze plan requirements are summarized in the Federal Register notice for this action

.

I

. C

. Visibility Impairment Goals

The goal of the regional haze rule is to restore natural visibility conditions by 2064 through implementation of measures that make “reasonable progress” toward this goal by

reduci ng anthropogenic emissions that cause haze

. Baseline visibility is determined ( through a calculation using the IMPROVE equation ) from particulate concentration data that is converted

into visibility data ( reconstructed light extinction )

.

I.C. 1 . Natural , B aseline, and Current Visibility Conditions

The goal of the regional haze rule is to restore natural visibility conditions at the 156 Class I areas identified in the 1977 Clean Air Act Amendments. 40 CFR 51.301(q) defines natural conditions: “Natural conditions include naturally occurring phenomena that reduce visibility as measured in terms of light extinction, visual range, con trast, or coloration.” The regional haze SIPs must contain measures that make “reasonable progress” toward this goal by reducing anthropogenic emissions that cause haze. For each Class I area, there are three metrics of visibility that are part of the

det ermination of reasonable progress: 1) natural conditions, 2) baseline conditions, and 3) current

conditions. “Natural” visibility is determined by estimating the natural concentrations of visibility pollutants and then calculating total light extinction

. Natural background visibility, as defined in Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Program , EPA

454/B

- 03

- 005, September 2003, is based on annual average concentrations of fine particle components. Natural background visibility for the 20% worst days is estimated by assuming that fine particle concentrations for natural background are normally distributed and the 90 th percentile of the annual distribution represents natural background visibility on the 20% worst days. The natural visibility value estimations for 2064 for Hawaii do not include an estimate of the visibility impairment from the emissions from the Kilauea volcano, which is located in the

Hawaii Volcanoes National Park

. The emissions from the volcano vary f rom year to year, and it

is therefore not possible to estimate the emissions from the volcano or the effect they will have on Class I area visibility in the year 2064

. “Baseline” visibility is the starting point for the improvement of visibility conditions. EPA requires the calculation of baseline conditions [(40 CFR 51.308(d)(2)(i) and (ii)]. T he baseline condition for each Class I area is defined as the five year avera ge (annual values for

2000

- 2004) of Interagency Monitoring of Protected Visual Environments IMPROVE monitoring data (expressed in deciviews) 2 for the most

- impaired (20% worst) days and the least

impaired (20% best) days

. The comparison of initial baselin e conditions to natural visibility conditions indicates the amount of improvement necessary to attain natural visibility by 2064

. T he baseline conditions f or this first regional haze F IP submittal for Hawaii are the reference

2 A one deciview change in the haze index is likely humanly perceptible under ideal conditions regardless of background conditions. The dec iview is discussed in greater detail in Measures of Visibility, below.3

point against which visibility improvement is tracked. For subsequent RH SIP updates (in the year 2018 and every 10 years thereafter), baseline conditions will be used to calculate progress from the beginning of the regional haze program. “Current conditions” are assessed every five y ears as part of the SIP review where actual progress in reducing visibility impairment is compared to the reductions committed to in the SIP. Current conditions for the best and worst days are calculated from a multiyear average, based on

the most recent 5

- years of monitored data available [40 CFR 51.308(f)(1)]. This value will be revised at the time of each periodic SIP revision, and will be used to illustrate: (1) The amount of progress made since the last SIP revision, and (2) the amount of progress mad e from the baseline period of the program.

I.C. 2. Estimation of Visibility Impairment

- The Original and the Revised IMPROVE Equations

Each IMPROVE monitor collects particulate concentration data which are converted into reconstructed light extinction (b ext , defined in greater detail in the following section) through a complex calculation using the IMPROVE equation

. The IMPROVE equation is used to convert

measured or modeled concentrations into extinction for each pollutant chemical species, and then

tota l them, accounting for the effect of relative humidity ; it also includes the Rayleigh scattering that occurs in pure air

. The extinction total is then used to calculate deciviews for use in visibility
progress assessments

. I n December 2005 the IMPROVE Ste ering Committee revised the IMPROVE equation after a scientific assessment of its implications for regional haze planning

. In particular, when compared to nephelometer direct measurements of visibility extinction, the original IMPROVE equation over

- predict s for low extinction conditions and under

- predicts for high extinction

. These biases have direct relevance for estimates for the best 20% and worst 20% visibility days that are used to assess progress

.

Original IMPROVE equation :

b ext = 3 * f(RH) * [ sul fate ] + 3 * f(RH) * [ nitrate ] + 4 * [ organic mass ] + 10 * [ elemental carbon ] + 1 * [ fine soil ] + 0.6 * [ coarse mass ]

+ 10

Each term in the equation is the extinction due to a particular measured component;

bracketed quantities are concentrations of as measured at IMPROVE monitors

. The organic mass is assumed to be 1.4 times the organic carbon mass that is measured by IMPROVE monitors

. The 10 is for Rayleigh scattering which is due to the interaction of light with molecules of a ir itself with no pollutants, and is assumed to be the same for all locations, The f(RH) is a water growth factor for sulfate and nitrate, which are hygros c opic (their particles tend to attract water)

. Its value depends on relative humidity, ranging from 1 at low humidity to 18 at 98% humidity.

New IMPROVE equation :4 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 m ass] + 10 * [ elemental carbon ] + 1 * [ fine soil ]

+ 1.7 * f

ss (RH) * [sea salt] + 0.6 * [ coarse mass ] + Rayleigh scattering (site

- specific) + 0.33 * [NO 2 (ppb)]

Sulfate is assumed to be all “large sulfate” if total sulfate is over 20 μg/m 3

, otherwise its fraction of the total is assumed to increase uniformly between 0 and 1 when the total is in the range between 0 and 20

. I.e. , large sulfate = (total sulfate/20)*total

. A similar definition applies for nitrate and for organic mass

. The organi c mass is assumed to be 1.8 times the organic carbon mass that is measured by IMPROVE monitors, an increase over the original 1.4

. Sea salt is estimated as 1.8 * [chloride] (or chlorine if chloride not available)

. Finally, the f

s , f L , f

ss are water growth factors for small (“S”) and large (“L”) fractions of sulfate and nitrate, and for sea salt (“SS”)

. Their values depend on relative humidity, ranging from 1 at low humidity to over 5 at 95% humidity. The new equation has five changes: 1) greater completene ss though the inclusion of sea salt, which can be important for coastal sites; 2) increased organic carbon mass estimate, based on more recent data for remote areas; 3) Rayleigh scattering using site

- specific elevation and temperature, a refinement over t h e older network

- wide constant; 4) separate estimates for small and large particles of visibility impacts and humidity

- dependent particle size growth rates, which could affect estimates at the low and high ends; and 5) greater completeness though the inclus ion

of NO 2 (Pitchford, 2006) 3

. The new equation shows broader scatter overall, but less bias in matching visibility measurements under high and low visibility conditions

. That is, though it has a somewhat worse fit considering all the data, it has a better fit under visibility conditions most relevant to regional haze planning, the best and worst 20% of days

. The looser overall fit can cause a slightly different set of days to be the ones chosen than the 20% worst, but the chemical species composition for s uch days is little changed (IMPROVE technical subcommittee for algorithm review, 2001, pp. 11

- 12), and so this makes little difference for assessing the contribution of emission sources to current conditions, and for projecting the effect of emission contr ols

. The split between small and large particles was the main factor in reducing the biases. The organic carbon (OC) measured by the IMPROVE network does not include all organic matter (OM); based on 1970s urban data, a scaling factor of 1.4 is embedded in the original equation to account for the full mass

. Based on recent data more relevant to relatively remote Class I areas, the revised IMPROVE equation embeds an OM/OC factor of 1.8

. In practice, for the worst days

, the biggest effect of switching to the revised IMPROVE equation is

3 Pitchford, Marc, 2006, "New IMPROVE algorithm for estimating light extinction approved for use", The

IMPROVE Newsletter , Volume 14, Number 4, Air Resource Specialists, Inc.; web page: http://vista.cira.colostate.edu/improve/Publications/news_letters.htm

direct link: http://vista.cira.colostate.edu/improve/Publications/NewsLetters/IMPNews4thQtr2005.pdf5

this increased organic carbon mass, since the worst days are dominated by organic carbon from fires, rather than the sulfates and nitrates that come mo re from anthropogenic sources. EPA is using the new IMPROVE equation for the Hawaii Regional Haze FIP.

I.C. 3. Measures of Visibility

As discussed in Section 2. Estimation of Visibility Impairment

- The Original and the Revised IMPROVE Equations

, above, particulate concentration data are converted into reconstructed light extinction through a complex calculation using the IMPROVE equation

. The relationship between of measures of visibility; light extinction (Mm - 1 ), haze index (dv)

, and visual range , is discussed below. Light Extinction (b ext )

. Light extinction is the attenu ation of light due to scattering and absorption as it passes through a medium. Reconstructed light extinction (denoted as b ext ) is expressed in units of inverse megameters (1/Mm or Mm - 1 )

. Li ght extinction is the most useful measure for evaluating the relative contributions of pollutants to visibility impairment

. Light extinction affects the clarity and color of objects being viewed. Haze Index (d eciview )

. The Regional Haze Rule requires the tracking of visibility conditions in terms of the Haze Index ( HI) metric

, expressed in the deciview (dv) unit. Generally, a one deciview change in the haze index is likely humanly perceptible under ideal conditions regardless of background conditions. The deciview is a useful measure for tracking progress in improvin g visibility, because each deciview change is an equal incremental change in

visibil ity perceived by the human eye. Relationship between extinction (Mm - 1 ) and haze index (dv)

. T here is a logarithmic relationship between the haze index and reconstructed lig ht extinction expressed by the following conversion equation:

HI = 10 ln (b ext

/10)

Where: HI is the Haze Index ln is the natural log

Bext is the reconstructed light extinction

Visual Range

. Visual range is the greatest distance, in kilometers or miles, at which a dark object can be viewed against the sky. The relationship between extinction (Mm - 1 ), haze index (dv) and visual range (km) are indicated by on the scale in Figure I

- 1 . R elationship between extinction Mm - 1 ), haze index (dv)

and visual ra nge (km)

.

Figure I

- 1 R elationship between extinction Mm - 1 ), haze index (dv) and visual range (km)6

I.D. Unique Nature of Regional Planning in Hawaii

N onanthropogenic emissions are a significant fraction of total SO 2 , VOC

, and PM

emissions in Hawaii

. T he Kilauea volcano dominates statewide SO 2 emissions. Emissions from

the volcano were estimated to be above 900,000 tons per year, and comprise d over 96% of the

SO 2 emissions in 2005

. On days when the volcano is erupting and the winds are carrying those emissions over the Class I area monitors, these natural emissions dominate the measurements. Nonanthropogenic sources also comprise the majority of VOC and PM emissions

. In addition to the difficulty of assessing the effect of n onanthropogenic emissions on visibility in the National Parks , there are several unique challenges for Hawaii regional haze plan ning in this planning period . There is no modeling available for this pl anning period that can reliably predict the change in visibility due to changes in the emission inventory for all sources (shipping, mobile sources, point sources, etc.). 4 In absence of reliable visibility modeling for 2018, EPA is us ing the island

- specific inventories as a surrogate for judging whether reasonable progress is being made during this planning period

. Visibility p rojections for 2018 are based on EPA‟s estimat e of the effect that the changes in the island specific inventories will have on the aerosol composition for each of the parks

.



### II

. Description of Hawaii’s National Parks

EPA has reviewed IMPROVE monitoring data , t he Causes of Haze Assessment provided through the Western Re gional Air Partnership (WRAP) , and information from the National Park

Service (NPS) , and the National Oceanic and Atmospheric Administration (NOAA) as a basis for this technical support document

. In addition

, EPA reviewed visibility assessment s of each park by the Hawaii Department of Health (HDOH)

.

II. A . HALEAKALA NATIONAL PARK

4 There is acceptable modeling for point sources for the BART and the reasonable progress analysis for point source. This modeling is discussed in Identif y BART Subject Sources.7 Figure II .A

- 1. HALEAKALA NATIONAL PARK

National Park Service Photo

II.A.1 . Park Des cription 5

Haleakala National Park consists of 30,183 acres in central to eastern portions of the island of Maui, 24,719 acres of which are designated wilderness

. The s lopes of the Haleakala, or East Maui, volcano comprise the central and western Park areas. The Kip ahulu Valley occupies eastern Park areas. Park elevations range from 3,055 m (10,023 ft) at the summit of Haleakala to sea level at the mouth of Kipahulu Valley on the extreme eastern boundary. The Park thus includes a wide variety of climate zones, from h igh mountain elevations above the Marine Boundary Layer, to leeward lowlands that are dry relative to windward lo wlands at the same

elevation.

A ir quality in Haleakala NP is generally excellent, with few man

- made sources of air pollution nearby. By far the largest source of air pollution is Kilauea Volcano on the island of Hawaii. Southeasterly “kona” winds transport volcanic gases and particles to Haleakala NP. This volcanic smog, or “vog,” contains sulfur dioxide, sulfuric acid, and sulfate particles and affects air quality and visibility. Locally, anthropogenic sources can affect air quality and visibility. 6

5 http://www.coha.dri.edu/web/state_analysis/Hawaii/HaleakalaNP_metdesc.html

6 http://www.nature.nps.gov/air/permits/aris/hale/?CFID=16689542&CFTOKEN=674926828

Figure II .A

- 2

. The Haleakala National Park Visibility Monitoring Sites: IMPROVE sites:

HALE1 and HACR1.

Visibility Monitoring Sites Currently there are two IMPROVE monitoring sites operating in or near the Haleakala

National Park. T he Haleakala ( HALE1 ) IMPROVE monitoring site is located well outside of the

Haleakala National Park nea r to the Maui Central Valley, at an elevation of 1153 meters. The

HALE 1 IMPROVE monitoring site began operation at end of 2000. The Haleakala Crater ( HACR1 ) IMPROVE monitoring site is at the park‟s Western boundary , at an elevation of 2158

meters. The HACR1 IMPROVE monitoring site began operation in 2007

. A discussion comparing the data collected at the HALE 1 and HACR 1 IMPROVE monitoring sites is presented in Section VIII.B. Analysis of the Haleakala (HALE1) IMPROVE monitoring site and newer Haleakala Crater (HACR1) Monitoring site

.

Nearby Population/Industrial Centers and Local Sources

Kahului and the Wailuku area are about 24 km west

- northwest and downslope from HALE1, with no major intervening terrain features. The major active volcano, Kilauea on the9

Big Island, is 188 km southeast of H ALE1. With northeasterly trade winds, SO 2 emissions from Kilauea have been observed to be eddy

- transported clockwise around the west side of the Big Island, and impact on Haleakala National Park is possible Sea salt spray is a natural aerosol

source.

Wind Patterns During trade

- wind conditions, which predominate 80 to 95% of the time from May through September, and 50 to 80% during the rest of the year, prevailing wind directions at HALE1 should be generally northeast to southwest, typically with speeds of 5 mps or greater. Downslope winds from Haleakala should be evidenced at the site by nighttime southeasterly directions, and daytime northwesterly directions. Exceptions to these conditions would occur during frontal passages associated with synoptic weathe r systems, and, at the site elevation, during upper atmosphere low

- pressure system passages. Monthly Kahului wind roses show typical wind patterns at this sea level station 24 km northwest of HALE1, with northeasterly surface flow year round and an additi onal southerly component in the winter.

Inversions/Trapping The predominant inversion phenomenon is the Trade

- layer inversion, or Marine Boundary Layer. The Marine Boundary Layer is more constant and has less diurnal variability

than continental inversio ns because of the oceanic influence. Typical trade

- layer inversion heights in the vicinity of Haleakala NP are around 2000 m above sea level, with some variability (+/

- ~1000 m) due to seasonal effects. The HALE1 site, at an elevation of 1158 m (3799 ft), would thus probably be within this layer most of the time when trade

- wind conditions predominate. During this condition, relative humidity will be typically be high, 70% or greater. When the Marine Boundary Layer height is below the monitoring site, relati ve humidity will be

much lower.

II.A.2. Visibility Conditions

Baseline Conditions at HALE1 in deciview (20% best and worst days)

T he b aseline visibility is determined from the HALE1 monitoring site for the 20% worst
and the 20% best days for the years 2001 through 2004 as specified in the Regional Haze regulations under 40 CFR §51.308(d)(2)(i)

. Data from the year 200 0 is not being used because data from that year is not complete. The baseline visibility for the Haleakala National Park is

c alculated at 13.3 deciviews for the 20% worst day and 4.6 deciviews for the 20% best days

. Figure II .A

- 3 below, shows the baseline data for the 20% worst days for each of the years 2001

- 2004

. Figure II .A

- 4 , below, shows the baseline for the 20% best days f or each of the years 2001

- 2004.10

Figure II .A

- 3: Haleakala National Park (HALE1); Baseline Visibility for the 20% Worst Days 2001

- 2004.

Figure II .A

- 4 : Haleakala National Park (HALE1); Baseline Visibility for the 20% Best Days 2001

- 2004.

Natural Condition in deciview (20% best and worst days) Natural visibility represents the visibility condition that would be experienced in the

absence of human

- caused impairment

. Based on EPA guidance

, 7 the natural visibility for the

Haleakala National Pa rk is 2.7 deciviews for the 20% best days and 7.4 deciviews for the 20% worst days. The natural visibility value estimations for 2064 do not include an estimate of the visibility impairment from the emissions from the Kilauea volcano, which is located in t he

Hawaii Volcanoes National Park

. The emissions from the volcano vary from year to year, and it is not possible to estimate the emissions from the volcano or the effect they will have on Class I area visibility in the year 2064

.

7 http://www.epa.gov/ttn/oarpg/t1/memoranda/rh_envcurhr_gd.pdf11

II.A.3. Causes of Haze

The aerosol c omposition measured at the Haleakala (HALE1) IMPROVE monitor on the

20% best and 20% worst d ays for the years 2001

- 2004 is presents in Figures II .A

- 5 through II .A

7 , below

. The charts show the contribution of aerosol species to light extincti on (b ext )

Figure II .A

- 5: Haleakala National Park; Aerosol Composition (contribution to Light Extinction) on 20% Best and 20% Worst Days for years 2001

- 2004.

Figure II .A

- 6: Haleakala National Park (HALE1); Aerosol Composition (contribution to Light Extinction) on the 20% Worst Days for years 2001

- 2004.12

Figure II .A

- 7: Haleakala National Park (HALE1); Aerosol Composition (contribution to
Light Extinction) on the 20% Best Days for years 2001

- 2004.

Sulfate is the largest cause of visibility degradation on the 20% worst days at Haleakala

National Park , contributing to approximately 60% of the visibility degradation

. Sulfate is also the largest cause of visibility degradation on the 20% best days at th e park, contributing to approximately 37% of the visibility degradation

. Natural causes of sulfate i nclude the emissions

from the Ki lauea volcano, located in the Hawaii Volcanoes National Park, and natural marine

sulfates

. The emissions of the volcano vary substantially from year to year

. Source apportionment assessments have estimated that the volcano causes approximately 60% of the visibility impairment at Haleakala National Park on the 20% worst days

. 8 9 The contribution

from natural marine sulfate is ex pected to be much smaller. 10 International transport may also contribute to sulfur visibility impairment. The major a nthropogenic sources of sulfur are point sources ( oil combustion ) and shipping

. Nitrate contributes 9% to the visibility degradation on th e 20% worst days at Haleakala. The major anthropogenic sources of nitrate on Maui are point sources, on

- road and non

- road mobile sources, and s hipping

. Non

- anthropogenic sources of NO

x include wildfires and biogenic

emission s

. Coarse mass contributes to 9% of the visibility degradation on the 20% worst days and 17% on the 20% best days at the Haleakala

. The local sources of coarse mass include fugitive dust from paved and unpaved roads

. The understanding of the sources that cont ribute to the coarse mass at Haleakala is fairly uncertain

. For the next planning period, a detailed study of the

source contribution to coa rse mass and soil measured at the Haleakala Crater Class 1 area

monitors may be need ed to address this uncertainty. Organic Carbon contributes 10% of the visibility degradation at the Haleakala (HALE1)

monitor for the year 2001

- 2004. Sources of organic carbon include agricultural burning,

8 Haleakala National Park Visibility Assessment , and IMPROVE PMF Factor Identification notes Positive Matrix Factorization Analysis of HALE1 & HAVO1 IMPROVE data sets April 20, 2012, State of Hawaii, Department of Health, Clean Air Bran ch

9 M. Pitchford, “Ca uses of Haze for Hawaii‟s Two Class I Areas”, presented at United States Department of Agriculture, Agricultural Air Quality Task Force Meeting, Wailea, Hawaii, November 13 and 15, 2005; http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs143_008844.pdf

10 Yvon and Saltzman 1996, Atmospheric Sulfur Cycling in the Tropical Marine Boundary Layer. J. Geophys. Res. 101, 6911

- 6918.13

wildfires, oil combustion, and international transport

. A comp arison of recent mon itoring data at the Haleakala Crater monitoring site (HACR1) shows approximately half the level of organic

carbon measured at the HALE1 site. 11 This is discussed in greater detail in Section II. D.2.

, Analysis of the Haleakala (HALE1) IMPROVE monitoring sit e and newer Haleakala Crater (HACR1) Monitoring site, below. Elemental Carbon contributes to 5% of the visibility degradation at the Haleakala (HALE1) IMPROVE monitoring site monitor, which is located outside of the park

. A

comp arison of recent data collected at the Haleakala Crater monitoring site (HACR1) shows

lower levels of elemental carbon than data measured the HALE1 site. 12 This is discussed in greater detail in VIII.B. Analysis of the Haleakala (HALE1) IMPROVE monitor ing site and

newer Haleakal a Crater (HACR1) Monitoring site

. Soil contributes to 1% of the visibility degradation at the Haleakala National Park

. The soil impact varies seasonally, with the highest levels in the springtime, and appears to be associated with international transport

. Sea Salt contributes to 1% of visibility impairment of the 20% worst days at Haleakala National Park, and 18% on the 20% best days.

II .A.4. Comparison of Basel ine 2001

- 2004 data to 2005 Data

For the Hawaii Regional Haze SIP, Hawaii DOH and EPA have sel ected 2005 as the base year inventory because Hawaii‟s 2005 inventory includes a more accurate inventory of point sources emissions than Hawaii‟s 2002 inventory. Since 2005 is not within the baseline period of

2000

- 2004, it is necessary to compare the leve l and the aerosol composition of visibility impairing pollutants in the year 2005 to the year 2001

- 2004 baseline time period

. The Haleakala National Park (HALE1); Aerosol Composition (contribution to Light Extinction) on 20% Best and 20% Worst Days for the year 2005 is presented in the figure below

. The level of light extinction is comparable for the 20% best days (4.6 Mm - 1 in 2005 compared to

5.8 Mm - 1 in 2001

- 2004) and 20% worst days (29 Mm - 1 in 2005 compared to 28.7 Mm - 1 in 2001

- 2004)

. The aer osol composition is similar for the two time periods.

11 Review of VIEWS2.0 2009

- 2010 Haleakala National P ark Organic and Elemental Carbon Data , March 30, 2012, State of Hawaii, Department of Health, Clean Air Branch , and Comparison of Haleakala National Park HALE1 and

HACR1 IMPROVE Monito ring Site 2007

- 2008 Data Sets, March 30, 2012, State of Hawaii, Departme nt of Health,

Clean Air Branch

.

12 Ibid.14

Figure II .A

- 8: Haleakala National Park (HALE1); Aerosol Composition (contribution to Light Extinction) on 20% Best and 20% Worst Days for the year 2005.

Since the measured visibility impairing pollution in 2005 was consistent with the baseline years, it is reasonable to assume that for the purposes of Regional Haze Planning that the 2005 emissions were sufficiently consistent with the emissions in 2000

- 2004 for this year to be used as the baseline for the Regional Haze Plan.

II.A.4. Uniform Rate of Progress

The Regional Haze Rule require s that, in setting RPGs, states must consider the rate of progress needed to reach natural visibility conditions by 2064 (referred to as the “uniform rate of progress” (URP) or the “glide path”) and the emission reduction measures needed to achieve that rate of progress over the period of th e SIP. 40 CFR 51.308(d)(1)(i)(B)

. For the 20% worst days, the URP in deciviews per year (i.e. slope of the glide path) is determined by the following equation:

URP = [Baseline Condition

- Natural Condition] / 60 years

By multiplying the URP by the n umber of years in the planning period one can calculate

the amount of progress needed by 2018 to be on the path to achieving natural visibility conditions by 2064

. T his first Regional Haze implementation plan covers the fourteen

- year period of 2004

- 2018. Thus:

2018 UPG = [URP] x [14 years]

See EPA ‟ s Guidance for Setting Reasonable Progress Goals Under the Regional Haze Rule §

2.2 (June 1, 2007). For the best days at each Class I area, the State must ensure no degradation in visibility for the least

- impaired (20% best) days over the same period. As with n atural conditions, the URP can be adjusted as new visibility information becomes available.15

Figure II

- 9 shows the 2018 URP chart for the w orst 20% days at Hal eakala National Park

.

Figure II .A

- 9: Haleakala National Park: Uniform Rate of Progress, Worst 20% Visibility
Days. 13

Table II .A

- 1 shows the Haleakala National Park URP for the Worst 20% Visibility Days

and Table II .A

- 2 shows the Baseline and Natural Conditions for the Best 20% Visibility Days

. 14

Table II .A

- 1 : Haleakala National Park

- Summary of Uniform Rate of Progress for 20% Worst Days

Baseline

Condition (deciview) Natural

Visibility (deciview) Total

Improve

ment by

2064 (deciview) URP

(deciview/ year) 2018 URP

Goal (deciview) Improve

ment
needed by

2018 (deciview)

13.3 7. 4 5. 9 0.09 8 11. 92 1. 38

Table II .A

- 2: Haleakala National Park

- Summary of Baseline and Natural for 20% Best Days

C lass I Area Baseline

Condition (deciview) Natural Visibility (deciview)

Haleakala National Park 4.6 2.7

13 http://vista.cira.colostate.edu/tss/Results/HazePlanning.aspx

14 http://vista.cira.colostate.edu/tss/Results/HazePlanning.aspx16

II.A.5

. Visibility Trends at Haleakala from 2001

- 2009

The Haze Index (in deciview) at Haleakala National Park, shown in Figure II .A

- 10 appears to indicate that the visibility on the worst 20% days is not improving over the year 2001 through 2009

. The monitoring data indicates that the level of light extinction due to sulfates is increasing, most likely due to the increase in volcano acti vity, as shown in Figure II .A

- 11 : Haleakala National Park; Aerosol Composition (contribution to Light Extinction) on the 20% Worst Days for years 2001

- 2009

. The degree of light extinction due to species other than sulfate appear to be approximately level, as shown in Figure II .A

- 1 2 : Haleakala National Park; Non

– sulfate Aerosol Composition (contribution to Light Extinction) on the 20% Worst Days for years

2001

- 2009

. Th e monitoring data for the 20% Best days shows that the visibility has changed very little over from 2001 to 2009

.

Figure II .A

- 10 : Haleakala National Park; Haze Index (in deciview) on the20% Worst Days for years 2001

- 2009.

Figure II .A

- 11 : Haleakala National Park; Aerosol Composition (contribution to Light Extinction) on the 20% Worst Days for years 2001

- 200917

Figure II .A

- 12 : Haleakala National Park; Non

– sulfate Aerosol Composition (contribution to Light Extinction) on the 20% Worst Days for years 2001

- 2009

Figure II .A

- 13 : Haleakala National Park; Aerosol Composition (contribution to Light Extinction) on the 20% Best Days for years 2001

- 2009

Organic and Elemental C arbon at the two IMPROVE monitors (HALE1 and HACR1) at

Haleakala National Park, 200 9

- 20 10 15

Currently there are two IMPROVE monitoring sites operating in or near the Haleakala

National Park. T he Haleakala ( HALE1 ) IMPROVE monitoring site is located outside of the

Haleakala National Park nea r to the Maui Central Valley, at an elevation of 1153 meters. The

HALE 1 IMPROVE monitoring site began operation at end of 2000, and will close in May of 2012. The Haleakala Crater ( HACR1 ) IMPROVE monitoring site is at the park‟s Western boundary , at an elevation of 2158 meters. A comparison of the dat a for all species is discussed in

15 A comparison of the dat a for all species is discussed in detail in the Section VIII.B. Analysis of the Haleakala
(HALE1) IMPROVE monitoring site and newer Haleakala Crater (HACR1) Monitoring site

.18

detail in the Section VIII.B. of this document

, Anal ysis of the Haleakala (HALE1) IMPROVE monitoring site and newer Haleakala Crater (HACR1) Monitoring site

. Organic and elemental carbon data for the two IMPROVE monitors (HALE1 and HACR1) at Haleakala National Park for 2009 and 2010 is presented in F igures II .A

- 1 4 through

II .A

- 1 7 , below

. The levels of organic and elemental carbon are low at both monitoring sites for most days. At the HALE1 site, the measured fine organic mass is below 1 μ g/m3, except for 5 days

. At the HACR1 site

, the measured levels of organic carbon are below 1 μ g/m3 for all days. ( N ote that the vertical axis scale differs between the HALE1 and HACR1 graphs)

. At the HALE1 site, the measured elemental carbon is below 0.2μg/m3, except for 5 days. At the

HACR1 site

, the measured eleme ntal carbon is below 0.2 μ g/m3 for all days.

Figure II .A

- 14 : Haleakala National Park (HALE1); Organic carbon ( μ g/m3)19

Figure II .A

- 1 5 : Haleakala National Park (HACR1); Organic carbon ( μ g/m3 )

Figure II .A

- 16 : Haleakala National Park (HALE1); Elemental carbon ( μ g/m3 )20

Figure II

- 17 : Haleakala National Park (HACR1); Elemental carbon ( μ g/m3 )21

II.B. HAWAII VOLCANOES NATIONAL PARK

II.B.1

. Hawaii Volcanic National Park Description 16

Hawaii Volcanoes National Park (NP) was first established as Hawaii NP in 1916 to protect the volcanoes, Kilauea and Mauna Loa on Hawaii and Haleakala on Maui. 17 The park now encompasses 209,695 acres ranging over varied ecosystems from the volcano‟s summit to the Pacific Ocean, with many unique plant and wildlife species

. Air quality in Hawaii Volcanoes NP is affected by a number of emission sources, primarily Kilauea Volcano. Currently the volcano emits between 1,000 and 2,000 tons of sulfur dioxide each day, as well as other gases, including h ydrogen sulfide, hydrogen chloride, hydrogen fluoride, and trace metals like mercury. Sulfur dioxide reacts with sunlight, oxygen, dust particles, and water in the air to form a mixture known as volcanic smog or "vog." The vog not only creates a haze that obscures visibility, but it is very acidic, causing acid rain and affecting human health, cultural resources, and vegetation. Adding to the haze are marine aerosols, which can further diminish visibility. In addition, when hot lava reaches seawater , large clouds of mist are formed, called laze, which contain hydrochloric acid and other airborne contaminants harmful to human health. Although the volcano dominates total emissions, local anthropogenic sources like power generating stations and automobiles can also affect air quality and visibility, releasing nitrogen oxides, particulates, and other pollutants as well as sulfur

dioxide. Sulfur dioxide is a significant health concern in Hawaii Volcanoes NP and downwind, so

sulfur dioxide is monitored at two locat ions, Jaggar Museum and the Kilauea Visitor Center. The park posts current sulfur dioxide concentrations from both monitors on its website.

Visibility Monitor Location

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

southeastern slopes of Mauna Loa on the island of Hawaii 18 . More specifically, it is situated on

the northeastern rim of the Kilauea crater. The site elevation is 1204 m (3949 ft), some 124 m above the crater floor at 1080 m (3542 ft). Volcanic emissions (SO 2 ) from the Kilauea crater (caldera) presently amount to 100 to 200 metric tons per day. This area is all part of the active Kilauea Volcano. There are other sources, including lava flows and other craters along the East Rift Zone extending out to ~ 20 km to the east

- southeast from the monitoring site. The most recent and continuing activity, which has been in progress since 1983, is along the East Rift Zone extending out to ~ 20 km to the east

- southeast from the monitoring site. The most recent and continuing activity , which has been in progress since 1983, is centered on the Pu‟u O‟o crater some 20 km (12 miles) east

- southeast from the monitoring site. SO 2 Emissions from Pu‟u O‟o

16 http:// www.coha.dri.edu/web/state_analysis/Hawaii/HawaiiVolcanoesNP_metdesc.html

, Hollingshead, Anette T., S. Businger, R. Draxler, J. Porter, and D. Stevens. Dispersion Modeling of the Kilauea Plume. Boundary Layer Meteorology 108: 124

- 14 4. 2003.,and Okamura, Arnold, Hawaii Volcanoes Observatory, personal conversation

with Dan Freeman

17 http://www.nature.nps.gov/air/Permits/aris/havo/ ?CFID=16689542&CFTOKEN=67492682

18 http://www.coha.dri.edu/web/state_analysis/Hawaii/HawaiiVolcanoesNP_metde sc.html22

amount to 1000 to 2000 metric tons per day, mostly from the main vent at an elevation of ~ 600 m (2 000 ft) (Okamura, 2003). Besides the Kilauea Volcano system, the major terrain feature affecting meteorology and air quality at the monitoring site is the 4170 m (13,681 ft) high Mauna Loa cone, about 35 km (22 mi) to the west of the monitoring s ite.

Wind Located on the Southeast slope of Mauna Loa, the monitoring site is well exposed to the

east

- to

- west trade

- wind flow. During trade

- wind conditions, which predominate 80 to 95% of the time from May through September, and 50 to 80% during the rest of the year, prevailing wind directions should thus be generally east to west, typically with speed of 5 mps or greater. During

northeast trade

- wind conditions, a clock

- wise eddy is produced to the west of the island that has significant effects on transp ort of local (volcanic) emissions to the islands lee

- side (west side).

Mountain

- valley slope flow should be evidenced at the site by nighttime westerly to northerly drainage flow and daytime easterly to southerly upslope flow. Exceptions to these condition s would occur during frontal passages associated with synoptic weather systems, and, at the site elevation, during upper atmosphere low

- pressure system passages.

Inversions The predominant inversion phenomenon is the Trade

- layer inversion, or Marine

Bound ary Layer. The marine layer will have much less diurnal variability than continental inversions because of the oceanic influence. Typical trade

- layer inversion heights in the vicinity of Volcanoes NP are probably near 2000m above sea level, with some varia bility due to seasonal effects. At the site elevation of 1204 m the monitoring site would thus probably be within this layer most of the time, when trade

- wind conditions predominate. During this condition, relative humidity will be typically be high, 70% o r greater. When the trade

- wind layer height is below the monitoring site, relative humidity will be much lower. If more continental types of inversions occur, say within the Kilauea crater during periods when the trade winds are absent or light and variab le, they would occur over a much smaller scale, with significant diurnal variability. Over a period of time aerosol concentrations could presumably build up due to SO 2 emissions within the crater, although it is not clear that such

conditions can occur wit h any frequency.

Meteorological Indicators A unique atmospheric phenomenon of this region is the so

- called vog (volcanic smog)

that occurs when SO 2 and other volcanic pollutants react with oxygen and atmospheric moisture. Information on this phenomenon i s available at: http://wrgis.wr.usgs.gov/fact

- sheet/fs169

- 97/ Thus, volcanic emissions are a likely candidate for the source of aerosols monitored at the IMPROVE site, which are typically high in particulate sulfate composition

. There are nevertheless other potential sources, particularly sea salt sulfate or transported Asian dust, that also typically have high sulfate composition. Asian dust emissions have been detected at the

NO AA Mauna Loa Observatory. A good indicator of Asian dust as a significant aerosol source at the monitoring site would be high correlation with Asian dust events, or occurrence during low relative humidity conditions, when the site is above the trade

- wind l ayer. Local volcanic emissions might be indicated by a strong correlation of high mass concentrations with wind direction from sources to the east southeast clockwise to southwest and low or negligible23

concentrations during light downslope (northerly) wind s, or by buildup during calm or light wind periods. At low concentrations, a significant sea sulfate contribution might be indicated by high

correlation with Haleakala NP measurements when both sites are within the trade

- wind layer and

have similar relativ e humidity measurements. (Note however that significant volcanic plume impaction has been observed at Haleakala NP when transported from the vicinity of Volcanoes NP). (Hollingshead et al., 2003)

Nearby Data Stations Meteorology is monitored at the site, in addition to aerosol composition, and this is probably the best source for representative surface meteorological data (wind direction, wind speed, temperature, relative humidity, etc.) For information on regional vertical structure, especially the heig ht of the marine layer at the monitoring site, twice

- daily upper air sounding data are collected at the NWS upper air site at Hilo. Vertical temperature profile data from Hilo are probably the best routinely collected and long

- term data representative of conditions at

Volcanoes NP.

II.B.2 . V isibility Conditions: baseline and natural (20% best and worst days)

Baseline Conditions for the 20% best and worst days at HAVO1 in deciview

Baseline visibility for this plan is determined from the HAVO1 monitoring site for the 20% best and the 20% worst days for the years 2001 through 2004

, as specified in the Regional Haze regulations under 40 CFR §51.308(d)(2)(i). The baseline visibility for the Hawaii

Volcanoes National Park is calculate d at 4.1 deciviews for the 20% best days and 18.9 deciviews for the 20% worst days.

. Figure II.B

- 1 , below, shows the baseline for the 20% worst days for each of the years 2001

- 2004

. Figure II.B

- 2 , below, shows the baseline for the 20% best days for

each o f the years 2001

- 2004. The natural visibility value estimations for 2064 do not include an estimate of the visibility impairment from the emissions from the Kilauea volcano, which is located in the

Hawaii Volcanoes National Park

. The emissions from the vo lcano vary from year to year, and it is not possible to estimate the emissions from the volcano or the effect they will have on Class I area visibility in the year 2064

.24

Figure II.B

- 1: Hawaii Volcanoes National Park; Baseline Visibility for t he 20% Worst Days 2001

- 2004

Figure II.B

- 2: Hawaii Volcanoes National Park; Baseline Visibility for the 20% Best Days

2001

- 2004

Natural Conditions (20% best and worst days)

Natural visibility represents the visibility condition that would be experienced in the

absence of human

- caused impairment. Based on EPA guidance, the natural visibility for the

Hawaii Volcanoes National Park is 2.2 deciv iews for the 20% best days and 7 .2 deciviews for the 20% worst days.

II.B

. 3 Causes of Haze

The aerosol c omposition measured at the Hawaii Volcanoes National Park (HAVO1) IMPROVE

monitor on the 20% best and 20% worst d ays for the years 2001

- 2004 is presents in Figures II.B

3 through II.B

- 5 II.A.2.c.1

- 3, below

. The charts show the contribution of aerosol species to light extinction (b ext )

.25

Figure II.B

- 3: Hawaii Volcanoes National Park; Aerosol Composition (contribution to Light Extinction) on 20% Best and 20% Worst Days for years 2001

- 2004

Figure II.B

- 4: Hawaii Volcanoes National Park; Aerosol Composition (contribution to Light Extinction) on 20% Worst Days for years 2001

- 200426

Figure II.B

- 5: Hawaii Volcanoes National Park; Aerosol Composition (contribution to Light Extinction) on 20% Best Days for years 2001

- 2004

Sulfate is the largest cause of visibility degradation on the 20% worst days at Hawaii Volcanoes National Park, contributing to approximately 90% of the visibility impairment. Sulfate is the also the largest cause of visibility degradation on the 20% best days at the park, contributing to approximately 42% of the visibility impairment. Natural causes of sulfate include

the emis sions from the Ki lauea volcano, located in the Hawai i Volcanoes National Park, and

natural marine sulfates

. The emissions and impact of the volcano varies substantially from year

to year

. Source apportionment assessments have estimated that the volcano causes approximately 90% of the visibility impairment a t Hawaii Volcanoes National Park on the 20% worst days. 19

, 20
The natural marine sulfate impact is expected to be much smaller. 21 Anthropogenic sources of

sulfur on the Island of Hawaii include point sources ( oil combustion ) , and shipping

. Nitrate contribut es 1% to the visibility degradation on the 20% worst days at Hawaii

Volcanoes National Park. Organic Carbon contributes 4% of the visibility degradation at the Hawaii Volcanoes National Park during the 2001

– 2004 time period

. Natural s ources of organic ca rbon comprise the majority of the emission inventory and include wildfires and biogenic emissions

. Anthropogenic sources of emissions include area sources and mobile sources.

Elemental Carbon contributes to 1 % of the visibility degradation at Hawaii Volcan oes National Park

. Coarse mass contributes to 1 % of the visibility degradation at the Hawaii Volcanoes

National Park. The sources of coarse mass include fugitive dust, for paved and unpaved roads. Soil contributes to 1% of the visibility degradation at ea ch of the Class I Areas

. The soil impact varies seasonally, with the highest levels in the springtime, and appears to be associated with international transport

.

19 Hawaii Volcanoes National Park Visibility Assessment , and IMPROVE PMF Factor Identification notes Positive Matrix Factorization Analysis of HALE1 & HAVO1 IMPROVE data sets April 20, 2012, State of Hawaii, Department of Health, Clean Air Bran ch

20 M. Pitchford, “Causes of Haze for Hawaii‟s Two Class I Areas”, presented at United States Department of Agriculture, Agricultural Air Quality Task Force Meeting, Wailea, Hawaii, November 13 and 15, 2005;

21 Yvon and Saltzman 1996, Atmospheric Sulfur Cycling in the Tropical Marine Boundary Layer. J. Geophys. Res. 101, 6911

- 6918.27

Sea Salt contributes to 1% of visibility impairment of the 20% worst days at Hawaii

Volcanoes National Park, and 17% on the 20% best days.

II.B.4. Comparison of Baseline 2001

- 2004 data to 2005 D ata

For the Hawaii Regional Haze SIP, Hawaii DOH and EPA have selected 2005 as the base year inventory because Hawaii‟s 2005 inventory includes a more accurate inventory of point sources emissions than Hawaii‟s 2002 inventory. Since 2005 is not within the base line period of

2000

- 2004, EPA has performed a comparison of the aerosol composition of the 2005 data and

2001

- 2004 data for Hawaii Volcanoes National Park

. The Hawaii Volcanoes National Park (H AVO1 ); Aerosol Composition (contribution to Light Extinction) on 20% Best and 20% Worst Days for the year 2005 is presented in the figure

below

. The level of light extinction is comparable for the 20% best days (4. 3 Mm - 1 in 2005 compared to 5.8 Mm - 1 in 2001

- 2004) and 20% worst days ( 90.9 Mm - 1 in 2005 compared to 66.5

Mm - 1 in 2001

- 2004)

. The level of organic carbon is lower on 2005 than for the 2001

- 2004 time period, but similar to the level of organic carbon for the years 2003 and 2004

. The difference in the level of sulfate reflects the difference in volcano activity . The levels of nitrate, coarse mass, elemental carbon, sea salt and soil are similar for the two time periods

.

Figure II.B

- 6: Hawaii Volcanoes National Park; Aerosol Composition (contribution to Light Extinction) on 20% Best and 20% Worst Days for the year 2005

Since the measured visibility impairing pollution in 2005 was consistent with the baseline years, it is reasonable to assume that for the purposes o f Regional Haze Planning, that the 2005 emissions were sufficiently consistent with the emissions in 2000

- 2004 for this year to be used as the baseline for the Regional Haze Plan.

II.B.4. Uniform Rate of Progress

Figure II.B

- 6 shows the 2018 URP for the W orst 20% days at Hawaii Volcanoes National Park.28

(See section II. A.4 for an explanation of URP)

. Table II.B

- 1

, Summary of Uniform Rate of Progress for 20% Worst Days , shows the Uniform Rate of Progress for Hawaii Volcanoes

National Park

.

Figure II.B

- 6: H awaii Volcanoes National Park: Uniform Rate of Progress, Worst 20% Visibility Days. 22

T able II

- B

- 1 shows the Hawaii Volcanoes National Park URP for the Worst 20% Visibility Days

and Table II.B

- 2 shows the Baseline and Natural Conditions for the Best 20 % Visibility Days

. 23

Table II.B

- 1: Hawaii Volca noes National Park

- Summary of Uniform Rate of Progress for 20% Worst Days

Class I

Area Baseline

Condition (deciview) Natural

Visibility (deciview) Total

Improvement by 2064 (deciview) URP

(deciview /year) 2018 URP

Goal (deciview) Improve

ment

needed by

2018 (deciview)

Volcanoes 18.9 7.2 11.7 0.1 9 16.17 2.73

Table II.B

- 2 : Hawaii Volcanoes National Park

- Baseline and Natural Conditions for 20% Best Days

C lass I Area Baseline

Condition (deciview) Natural Visibility (deciview)

Hawaii Volcanoes National Park 4.1 2.2

22 http://vista.cira.colostate.edu/tss/Results/HazePlanning.aspx

23 http://vista.cira.colostate.edu/tss/Results/HazePlanning.aspx29

Figure s II.B

- 7 and Figure s II.B

- 8 show historic visibility photos that are representative of

the Worst 20% days and the Best 20% days at Hawaii Volcanoes National Park.

Figure II.B

- 7 : Photograph of Hawaii Volcanoes National Park

- Worst 20% days 24 : 19

deciview

24 Hawaii Volcanoes National Park, Hawaii

, Photographic Archive 1986

– 1990 http://vista.cira.colostate.edu/Datawarehouse/IMPROVE/Data/Photos/HAVO/html/IMG0003.htm30

Figure II.B

- 8 : Photograph of Hawaii Volcanoes National Park

- Best 20% days: 4 deciview

II.B.5

. Visibility Trends from 2001

- 2009

The Haze Index (in deciview) at Hawaii Volcanoes Nati onal Park, shown in Figure II.B

- 9 appears to indicate that the visibility on the worst 20% days is not improving over the year s 2001 through 2009

. The monitoring data indicates that the level of light ex tinction due to sulfates is increasing, most likely due to the increase in volcano activity, as shown in Figure II.B

- 11 : Hawaii Volcanoes National Park; Aerosol Composition (contribution to Light Extinction) on the

20% Worst Days for years 2001

- 2009

. The degree of light extinction due to species other than sulfate appear s to be approximately level, as shown in Figure II.B

- 11 : Hawaii Volcanoes National Park; Non

– sulfate Aerosol Composition (contribution to Light Extinction) on the 20% Worst Days for years 2001

- 2009

. The light extinction attributed to particulate organic mass is higher in the years 2001

- 2002 than in the following years 2003

- 2009

. Th e monitoring data for the 20% Best days show that the visibility is fairly constant from 2001 to 2009

.31

Figur e II.B

- 9 : Hawaii Volcanoes National Park; Haze Index on 20% Worst Days for years

2001

- 2009

Figure II.B

- 1 0 : Hawaii Volcanoes National Park; Aerosol Composition (contribution to Light Extinction) on 20% Worst Days for years 2001

- 200932

Figure II.B

- 11 : Hawaii Volcanoes National Park; Non

- sulfate Aerosol Composition
(contribution to Light Extinction) on 20% Worst Days for years 2001

- 2009

Figure II.B

- 12 : Hawaii Volcanoes National Park; Aerosol Composition (contribution to Light Extinction) on 20% Best D ays for years 2001

- 200933



### III

. Summary of Previous Visibility Assessments at the Haleakala and

Hawaii Volcanoes National Parks.

The causes of v isibility impairment a t the Haleakala and Hawaii Volcanoes National

Parks have been assessed by the NOAA and also by the Hawaii DOH

. The results of these

studies are briefly summarized bel ow

. EPA reviewed these assessments as part of the basis for determining causes of haze for the Haleakala National Park and the Hawaii Volcanoes National

Park

.

III.A. NOAA Assessment of Causes of Haze for Hawaii’s Two Class I Areas

The causes of haze for the Haleakala and Hawaii Volcanoes National Parks were examined by Marc Pitchford of NOAA in 2005

. 25 Th is work identified the possible causes of visibility impairment with in each of Hawaii‟s two Class I National Parks , based on wind trajectories and a source apportionment analysis using Positive Matrix Factorization ( PMF )

. Pitchford found that “w ind trajectories provided a good indication that the SO2 was primarily coming from the Kilauea volcano‟s Pu‟u „O‟o rift zone. ” P article trajectory

calculations for key days indicated that there were some days when high sulfate concentrations

were detected at both HAVO1 an d HALE1, and other days where high sulfate concentrations were only detected at HAVO1. These results indicated that “volcanic sulfate is likely impacting haze on at least some of the worst days for Haleakala”.

The Positive Matrix Factorization ( PMF ) analy sis used combined IMPROVE PM2.5 data

from both the HALE1 and HAVO1 monitors to determine six PMF factors: Volcano Sulfate, Sulfate & Nitrate, Smoke, Nitrate, Dust, and Sea Salt

. The results for each of the 6 factors were based on PM2.5 concentrations at HA LE1 and HAVO1 on the Worst 20% Days , as well as all

d ays, and are shown in Table II I

- 1: Contribution to PM2.5 Concentration, below

. The results

indicate that :

• Hawaii Volcano es National Park has much greater impacts from the “volcano” PMF

factor than Halea kala National Park.

• The “volcano” PMF factor is responsible for most of the haze impacts on worst visibility days at Hawaii Volcano es National Park, and many, but not all o f the worst case days at

Haleaka la National Park.

• Haleaka la National Park has greater impacts from “smoke”, “dust”, and “sulfate/nitrate”

PMF factors compared to Hawaii Volcano es National Park.

25 M. Pitchford, “Causes of Haze for Hawaii‟s Two Class I Areas”, presented at United States Department of Agriculture, Agricultural Air Quality Task Force Meeting, Wail ea, Hawaii, November 13 and 15, 2005; http://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/nrcs143_008844.pdf http://vista.cira.colostate.edu/tss/Results/HazePlanning.aspx http://www.powershow.com/view/4f998

- YmIxN/Causes_of_Haze_Update_flash_ppt_presentation34 Table II I

- 1. Contribution to PM2.5 by PMF Source Factors

Volcano

Sulfate % Sulfate and

Nitrate % Smoke

% Nitrate % Dust % Sea Salt %

HAVO1

Worst 20% Days 88 3 3 4 1 1

HAVO1 All Days 70 7 7 6 3 7

HALE1

Worst 20% Days 41 20 19 11 7 2

HALE1 All Days 33 16 22 14 8 7

Pitchford finds that for the year of 2003 at Haleakala IMPROVE Monitor ( HALE1 )

, “about half of worst case days are associated with volcano emissions, while the others are associated with different factors (e.g. smoke, secondary sulfate and nitrate).” For the Hawaii

Volca noes IMPROVE monitor ( HAVO1 ) in 2003 he find that “all worst ha ze days are dominated by the volcano sulfate factor”. The recommend ations for follow

- on work include:

examination of the smoke factor with respect to burning (e.g. agricultural) events; attribution of dust to local (e.g. high winds) or global (e.g. Asian d ust) sources; including coarse mass into the PMF calculations to support possible attribution to local and non

- local (e.g Asian dust) sources;

and attribution of the “nitrate” and “sulfate/nitrate” PMF factors.

III.B

. Hawaii Department of Health Source Apportionment Results

Hawaii Department of Health has conducted visibility assessments for the Haleakala and

Hawaii Volcanoes National Parks. 26 The purpose of these effort s was to identify candidate sources of visibility impairment for Haleakala National P ark and Hawaii Volcanoes National Park and estimate the associated impacts

. The visibility assessments discuss the potential sources of visibility impairment for the

two National Park s , examine pollutant monitoring data and visibility impacts, present poll utant

source app ortionment results, and examine additional select pollution sources that could potentially impact visibility. The effort fused pollutant monitoring data, particle trajector ies based on gridded wind data and select pollutant sources (forest fire and agricultural burning)

.

26 Haleakala National Park Visibility Assessment, Hawai‟i Volcanoes National Park Visibility Assessment, and IMPROVE PMF Factor Identification notes Positive Matrix Factorization Analysis of HALE1 & HAVO1 IMPROVE data sets April 20, 2012, State of Hawaii, Dep artment of Health, Clean Air Branch.35

T he effort sought to gather information about all pollutants and sources

. T he large magnitude and temporal variability of Kilauea volcano emissions from the island of Hawaii are significant

drivers for the work. The source apportionment analysis was based on IMPROVE data and associated Positive

Matrix Factorization (PMF) analyses

. The PMF categorized visibility impacts into 8 source types for Haleakala National Park, and 6 source types for Hawaii Volcanoes Nationa l Park

. The results provide insight into potential sources, both within and external to the islands of Hawaii

. S ummar ies of the results for each park are presented below

. EPA has reviewed the Hawaii DOH Visibility Assessment for Haleakala and Hawaii Volcan oes National Park

. EPA

concurs with Hawaii DOH that the Volcano PMF factor and the Asian Dust PMF factors appear to be most reliable. T he remaining six factors are less certain

. For example, power plants and ships burn similar fuels, so as noted by Hawaii DOH, this PMF factor may have been inc orrectly attributed to shipping versus other potentially consistent PMF factors

.

III.B.1. Hawaii DOH Park Visibility Assessment of Haleakala National Park

- Summary

of Results

The estimation of contribution to light extinction ( Bext for 2005/2003

- 2008 data sets, respectively ) are presented below , and are base on IMPROVE data f or the w orst 20% Days visibility

.

( 1) The Volcano PMF Factor (46%/56% aerosol Bext for 2005/2003

- 2008 data sets, respectively) should be attributed to emissions from the Kilauea volcano on the island of Hawaii. The very high sulfur content of this factor, and the relatively good correspondence with the time history of one of the HAVO1 v olcano factors are the two primary reasons for this attribution.

( 2) The Dust (Asian) PMF Factor (10%/2% aerosol Bext) should be attributed to emissions from Asia. The good correspondence between with the HAVO1 Dust (Asian) factor time history

indicates a very large plume size consistent with long range transport. The seasonal nature of the time history, and the presence of dust constituents (Al, Ca, Fe, Si, Ti) are also key reasons for this attribution. Source apportionment calculations combined particle trajectory calculations with pollutant concentration levels and indicated several potential source areas in Asia.

For the next five PMF factors, the results were inconclusive in a number of cases. In some cases, there appeared to be strong indications t hat at least portions of the source were located beyond the islands of Hawaii. In one case, there are indications that the source is close, likely small, and unlikely to contribute significantly to visibility impairment. Despite these indications, the resu lts are not yet sufficiently conclusive to attribute the visibility impacts to other than local sources. For the same reason, visibility impacts are treated as if they impacted the entire National Park. Future source attribution analyses (using new monitor ing data and gridded wind modeling results) could help resolve these uncertainties and perhaps enable better attribution of visibility impacts.

( 3) The Nitrate/Sulfate

- Rich Secondary PMF factor (7%/16% aerosol Bext) appears consistent with potential sour ces beyond the islands of Hawaii. Trajectory and source apportionment calculations indicated that impacts were consistent with sources in Asia and Western CONUS.36

( 4) The Smoke PMF factor (14%/6% aerosol Bext) is likely due to Maui sources. Two likely

sou rces of smoke impacts, agricultural burning and forest fires, were investigated and found to not correspond well to the IMPROVE measurements at HALE1. Due to the presence of bromine in the factor, automobile exhaust is a possible contributor. A n examinatio n of the measurement differences between the primary IMPROVE site on Maui, HALE1, and the newer HACR1 site found that HALE1 concentration levels were generally approximately twice those of HACR1. It is believed likely that the elevated smoke levels at HALE 1 are due to nearby sources that would not impact overall visibility within the National Park.

( 5) The Oil Combustion PMF factor (15%/10% aerosol Bext ) appears consistent with potential sources both on the island of Hawaii and beyond the islands of Hawaii. The 2008 National Emission Inventory identified fuel (oil) combustion for power generation as significant contributors to local anthropogenic emissio ns.

( 6) The Sea Salt/Nitrate

- Rich Secondary PMF factor (4%/6% aerosol Bext) appears consistent

with sources beyond the islands of Hawaii.

( 7) The Shipping PMF factor (2%/3% aerosol Bext) could be the result of sources on Maui, beyond the islands of Hawa ii, or a combination of sources. This factor was attributed to shipping largely upon the relatively large quantity of zinc, which was also a characteristic in a prior PMF assessment of Hawaii emission sources. However, this PMF factor may have been incorre ctly attributed to shipping, versus other potentially consistent PMF factors (e.g. Nitrate/Sulfate

- Rich Secondary, Oil Combustion, or Sea Salt/Nitrate

- Rich Secondary).

( 8) The Brush Fire/Burning Vegetation PMF factor (2%/0% aerosol Bext) is likely the re sult of

sources on Maui.

III.B.2. Hawaii DOH Park Visibility Assessment of Hawai’i Volcanoes National

- Summary of Results

The estimation of contribution to light extinction ( Bext for 2005/2003

- 2008 data sets, respectively ) are presented below , and are base d on IMPROVE data f or Worst 20% Days visibility

.

( 1) The three Volcano PMF Factors (93.4%/94.2% aerosol Bext for 2005/2003

- 2008 data sets, respectively) should be attributed to non

- anthropogenic emissions from the Kilauea volcano on

the island of Hawa ii. The very high sulfur content of two of these factors is the primary reasons for this attribution. Source apportionment modeling for these two factors indicates emission sites

that are consistent with the volcanic emissions and associated inter

- island “ vog” visibility impairment. For the third volcanic faction, the fraction of total sulfur is relatively low (~1%), but the source apportionment strongly indicates an emission site consistent with the Kilauea volcano.

( 2) The Dust (Asian) PMF Factor (1.3%/ 0.4% aerosol Bext) should be attributed to emissions from Asia. The good correspondence between with the HALE1 Dust (Asian) factor time history indicates a very large plume size consistent with long range transport. The seasonal nature of the37

time history, and the presence of dust constituents (Al, Ca, Fe, Si, Ti) are also key reasons for this attribution. Source apportionment calculations combined particle trajectory calculations with pollutant concentration levels and indicated several potential source ar eas in Asia.

For the remaining four PMF factors, the results were inconclusive in a number of cases. In some cases, there appeared to be strong indications that at least portions of the source were located beyond the islands of Hawaii. Despite these indi cations, the results are not yet sufficiently conclusive to attribute the visibility impacts to other than local sources. For the same reason, visibility impacts are treated as if they impacted the entire National Park. Future source attribution analyses ( using new monitoring data and gridded wind modeling results) could help resolve these uncertainties and perhaps enable better attribution of visibility impacts.

( 3) The Smoke PMF factor (1.2%/1.4% aerosol Bext ) could be the result of on

- island emissions, but there are some indications of potential sources beyond the islands of Hawaii. Forest fires were investigated and found to not correspond well to the IMPROVE measurements at HAVO1.

The fire data did not matc h well with either the spatial locations indicated by the PSCF results, or

the time

- histories associated with any of the HAVO1 IMPROVE visibility impacting species or PMF Factors. Due to the presence of bromine in the factor, automobile exhaust is a possib le

contributor.

( 4) The Oil Combustion PMF factor (1.1%/1.5% aerosol Bext) could be the result of sources on Hawaii, the Americas, Asia, or a combination of those source regions. The emissions inventory

in Section IV of this document identifie s fuel (oil ) combustion for power generation as significant contributors to local anthropogenic emissions.

( 5) The Sea Salt/Nitrate

- Rich Secondary PMF factor (1.5%/2.0% aerosol Bext) appears consistent with sources beyond the islands of Hawaii.

( 6) The PMF Shippi ng PMF factor (1.4%/0.4% aerosol Bext) could be the result of sources on Hawaii, Maui, beyond the islands of Hawaii, or a combination of sources. This factor was attributed to shipping largely upon the relatively large quantity of zinc, which was also a

ch aracteristic in a prior PMF assessment of Hawaii emission sources. However, this PMF factor may have been incorrectly attributed to shipping, versus other potentially consistent PMF factors (e.g. Nitrate/Sulfate

- Rich Secondary, Oil Combustion, or Sea Salt/ Nitrate

- Rich Secondary).



### IV

. Emissions Inventory

IV.A. Statewide Emissions Inventory

40 CFR 51.308(d)(4)(v) requires that EPA maintain a statewide inventory of emissions of pollutants that are reasonably anticipated to cause or contribute to visibility impairment in any mandatory Class I Federal area

. The inventory must include emissions for a baseline year, emissions for the most recent year for which data are available, and estimates of future projected

emissions

. The Regional Haze Rule does not speci fy the baseline year for the inventory, but EPA38

has recommended that 2002 be used as the inventory base year. 27 2002 is generally appropriate as the baseline year for Regional Haze SIPs because it corresponds with the 2000

- 2004 period for establishing base line visibility conditions , based on available ambient monitoring data

, pursuant to 40 CFR 51.308(d) (2)(i)

. For this first Hawaii Regional Haze implementation plan, Hawaii DOH initially selected 2005 as their base year because it was the most recent year with a full inventory when they began

their technical work. 28 Since 2005 is not within the baseline period of 2000

- 2004, EPA has performed a comparison of the aerosol composition of the 2005 data and 2001

- 2004 data for

each Class I Area in Sections II.A., II.B, and III.B of this document. That analysis found that the 2005 inventory is sufficiently representative of the base period that it is appropriate to use as the base inventory for the plan

. That is, s ince the measured visibility impairing pollution in 2005 was consistent with the baseline years, it is reasonable to assume that for the purposes of Regional Haze Planning, that the 2005 emissions were sufficiently consistent with the emissions in 2000

- 2004 for this year to be used as the baseline for the R egional Haze Plan. The majority of the 2005, 2008 and 2018 inventories were derived from a 2010 study conducted by consulting firm Environ on behalf of the Hawaii DOH. 29 The numbers developed by Environ were then refined and improved by HI DOH. 30 Between th e time when the Environ Study was conducted and the development of this FIP, the EPA finalized a new model for the estimation of emissions from on road vehicles. This new model, MOVES provides for a more

accurate estimation of emissions from these sources. So, the EPA worked with the University of North Carolina (UNC) and consulting firm ICF International to develop a new emissions inventory for on road vehicles for Hawaii for the years 2005, 2008 and 2018. 31 Tables III

- 1 through III

- 3 reflect these revised emissions numbers

. The EPA also worked with UNC and ICF to improve the 2018 emissions estimates for marine sources. The Environ work used the best data that was available at the time, but failed to account for the impact of the economic recession on marin e vessel activity, cruise ships in particular

. In addition, the Environ work did not take into account the impact of the North American Emissions Control Area (NA ECA). The United States Government, together with Canada and France, established the NA ECA u nder the auspices of Annex VI of the International

Convention for the Preve ntion of Pollution from Ships ( MARPOL Annex VI), a treaty developed by the International Maritime Organization

. This ECA will require use of lower sulfur fuels in ships operating wi thin 200 nautical miles of the majority of the U.S. and Canadian coastline, including the U.S. Gulf Coast and Hawaii, beginning in August 2012

. The ECA will result in

lower NO

x and SO 2 emissions from marine sources in Hawaii. Therefore, UNC and ICF have

27 Memorandum from Lydia N. Wegman, “ 2002 Base Year E mission Inventory SIP Planning: 8

- Hour Ozone,

P M2.5 and Regional Haze Programs” (Nov. 18, 2002).

28 E

- mail from Priscilla Ligh, Hawaii DOH, to Gregg Nudd, EPA, May 3, 2 012.

29 “Final Emission Inventory Report: Data Population for Air System for Hawaii Emissions Data (AirSHED)”, Environ International Corporation, April 12, 2010.

30 See email from Priscilla Ligh, HI DOH to Greg Nudd, USEPA, on 11/18/2011 and associated docu ment: “ RevA Emissions inventory response to EPA 11

- 17

- 11 for EPA.doc ” The document also explains any differences between the Hawaii DOH numbers and the emissions inventory in the National Emission Inventory for Hawaii.

31 Technical Analysis for Hawaii‟s Regional Haze FIP Report

– Task 16: On

- Road Mobile Emissions Inventory , ICF International, March 23, 201239

up dated the 2018 inventory to include the benefits of the ECA. The 2018 marine emissions

estimates in Table III

- 3 are based on this more recent work by UNC and ICF. 32

Table III

- 1 Statewide Inventory for 2005

Source Category NO

x SO 2 VOC PM NH 3
Point Sources 22,745 27,072 2,695 3,536 12

Area Sources 1,509 3,716 16,920 33,408 11,136

Windblown Dust 46,808

Wildfire 2,156 591 4,729 9,771 540
Agricultural Burning 406 178 535 1,567 60

O ther fire 1 7 7

On Road Mobile Sources 20,642 321 12,066 638 1,085

Non Road Mobile Sources 4,750 534 6,121 484 5

Aircraft 1,541 135 262 165

In and Near P ort Marine 2,572 2,201 92 183

U nderway M arine (<30

nm 33 ) 3,052 1,418 117 215

Trains 5

Volcano 961,366

Sea Spray 382,637

B iogenic 4,617 130,153

T otal 63,996 997,532 173,697 479,419 12,838
Anthropogenic Total 59

, 379 36

, 166 43

, 544 96

, 782 12,838

Table II I

- 2 Statewide Inventory for 2008

Source Category NO

x SO 2 VOC PM NH 3 Point Sources 20,246 25,849 2,544 3,389 12

Area Sources 1,166 15,767 18,025 34,917 11,275

Windblown Dust 46,808

Wildfire 2,156 591 4,729 9,771 540
Agricultural Burning 406 178 535 1,567 60

O ther fire 1 8 7

On Road Mobile Sources 14,239 97 8,526 547 1,124

Non Road Mobile Sources 4,573 78 4,912 422 5

Aircraft 2,568 260 628 123

In and Near P ort Marine 12,432 2,638 308 605

U nderway M arine (<30nm) 562 282 18 42

Trains 5

Volcano 1,195,314

Sea Spray 382,637

32 “ Technical Analysis for Hawaii‟s Regional Haze FIP Report

– Task 16: Commercial Marine Inventory ”, ICF International, April 2, 2012

33 nautical miles40

B iogenic 4,617 130,153

T otal 62,971 1,241,054 170,386 480,835 13,017
Anthropogenic Total 58,354 45,740 40,233 98,198 13,017

Table II I

- 3 Statewide Inventory for 2018

Source Category NO

x SO 2 VOC PM NH 3 Point Sources 28,594 36,212 4,157 5,052 13

Area Sources 1,723 3,524 20,054 43,506 12,530

Windblown Dust 46,808

Wildfire 2,156 591 4,729 9,771 540
Agricultural Burning 406 178 535 1,567 60

O ther fire 1 8 7

On Road Mobile Sources 5,058 72 3,883 400 1,478

Non Road Mobile Sources 3,090 7 4,579 297 7

Aircraft 1,920 167 466 194

In and Near P ort Marine 2,097 117 92 50

U nderway M arine (<30nm) 1,867 68 78 33

Trains 5

Volcano 683,746

Sea Spray 421,222

B iogenic 4,617 130,153

T otal 51,533 724,681 168,734 528,908 14,628
Anthropogenic Total 46,916 40,935 38,581 107,686 14,628

IV. B. Review of the Emissions Inventory for Completeness and Accuracy

The EPA has reviewed the methods used by Environ, the Hawaii Department of Health and the ICF Corporation in developing this inventory. We propose to find that the best avai lable emissions factors and activity data were used in developing the emissions estimates. We also propose to find that the inventory captures all of the emissions sources relevant to the development of a Regional Haze Plan.

IV. C. Assessment of the Emissio ns Inventory

There are a few interesting and relevant facts to draw from the results in Tables III

- 1 through III

- 3. First, nonanthropogenic emissions are significant for SO 2 , VOC and PM. As one can see from the tables above, the volcano dominates statewide SO 2 emissions. Emissions from the volcano comprise over 96% of the SO 2 emissions in 2005 and 2008

. On days when the volcano is erupting and the winds are carrying those emissions over the Class I area monitors, these41

natural emissions will domina te the measurements. Nonanthropogenic sources also comprise the majority of VOC and PM emissions. Second, total statewide anthropogenic emissions of NO

x and VOC are decreasing.

Human

- made NOx pollution is projected to be 21% lower in 2018 than in 2005. Hu man

- made VOC pollution is projected to decrease by 11%. These reductions are primarily due to EPA regulations for on

- road vehicles. Emissions from cars and trucks are decreasing dramatically, even accounting for economic and population growth. This is due to older, higher emitting vehicles being replaced by ones with more modern air pollution controls. NO

x emissions in this category are projected to decrease by over 15,000 tpy and VOC emissions by over 8,000 tpy

between 2005 and 2018. However, anthropogenic SO 2 emissions are expected to increase between 2005 and 2018, largely due to increased emissions from point sources. The lower sulfur marine fuels required by the ECA are expected to result in a 95% reduction in emissions from shipping, but those

reductio ns are overwhelmed by the increases from point source emissions. The growth rate of point source emissions is very sensitive to assumptions about future economic growth. The Environ report, from which this data is derived, assumes robust economic growth be tween 2005 and 2018. Given the economic recession that began in late 2008 this level of emission growth will likely over

- predict future anthropogenic emissions. Nevertheless, this is the best data

available. Our analysis of the monitoring data indicates t hat SO 2 is the principal pollutant of concern for the regional haze plan. (See sections II.A., II.B, and III.B of this TSD.) The visibility impacts of NO

x and VOC emissions are of secondary importance. The increase in anthropogenic

SO 2 emissions indicates that some additional pollution reductions are needed to ensure reasonable progress toward the goal of eliminating anthropogenic visibility impairment in

Hawaii‟s mandatory class I areas . Our proposal to achieve these reductions is set forth in section

VII of this TSD.



### V . Causes of H aze in Hawaii (including volcanic emissions)

V. A

. Island

- Specific Emissions Inventory

The island specific emission inventory for the years 2005 and 2018 is presented below

. These tables are derived from the same set of references and assumptions as in the Emissions Inventory section.

Table V

- 1. Hawaii (Big Island) Anthropogenic Emissions Inventory 34

2005 Inventory 2018 Inventory Source Category NO

x SO 2 NO

x SO 2 Point 1,036 4,551 1,736 5,266 Nonpoint 1,849 808 1,882 872

On

- Road Mobile 3,217 53 839 11

Non

- Road Mobile 784 95 428 1

34 Does NOT include volcano SO2 emissions of 961,366 tons/year.42

Aircraft 177 18 207 21 Agricultural Burning 2 0 2 0

Wildfires 1,712 469 1,712 469 in/near port Marine 537 418 546 20

Total 9,314 6,412 7,352 6,661

Table V

- 2. Maui Anthropogenic Emissions Inventory

2005 Inventory 2018 Inventory Source Category NO

x SO 2 NO

x SO 2 Point 4,492 4,559 4,597 4,625 Nonpoint 462 481 548 571

On

- Road Mobile 2,957 47 758 10

Non

- Road Mobile 496 57 305 2

Aircraft 310 27 376 33 Agricultural Burning 298 132 298 132

Wildfires 52 14 52 14 in/near port Marine 699 569 836 32

Total 9,765 5,887 7,770 5,420

V. B . Synthesis of Emissions Inventory, Monitoring Data, and PMF analysis

Sulfate is the largest cause of visibility degradation on the 20% worst days at both

Haleakala National Park and Hawaii Volcanoes National Park. Natural causes of sulfate include the emissions from the Kīlauea volcano, located in the Hawaii Volcanoes Natio nal Park, and

natural marine sulfates

. The emissions and impact of the volcano varies substantially from year

to year

. Source apportionment assessments have estimated that the volcano causes approximately 90% of the visibility impairment at Hawaii Volcanoe s National Park and approximately 60% of the visibility impairment at Haleakala National Park on the 20% worst days

. The natural marine sulfate impact is expected to be much smaller. 35 International transport may also contribute to sulfur visibility impair ment

. Anthropogenic sources of sulfur include oil combustion, and shipping

. Nitrate contributes 9% to the visibility degradation on the 20% worst days at Haleakala. Nitrate contributes 1% to the visibility degradation on the 20% worst days at Hawaii Volca noes National Park

. The major anthropogenic sources of nitrate are point sources, on

- road sources

, and marine emissions

. The natural sources of nitrate include wildfire and biogenic emission s

. Organic Carbon contributes 10% of the visibility degradation at the Haleakala (HALE1) monitor, which is located outside of the park. Sources of organic carbon include agricultural burning, oil combustion, and international transport. A comparison of recent monitoring at the Haleakala Crater monitoring site at Park (HA CR1) shows a lower level of organic carbon than

35 Yvon and Saltzman 1996, Atmospheric Sulfur Cycling in the Tropical Marine Boundary Layer. J. Geophys. Res. 101, 6911

- 6918.43

the HALE1 site. 36 Organic Carbon contributes 4% of the visibility degradation at the Hawaii Volcanoes National Park during the 2001

– 2004 time period

. Organic carbon levels measured at the park from 2003

- 200 9 are much lower, as discussed in the section regarding visibility trends at Hawaii Volcanoes Park, above. Elemental Carbon contributes to 5% of the visibility degradation at the Haleakala (HALE1) monitor, which is located outside of the park

. A comparison of recent monitoring at

the Haleakala Crater monitoring site at Park (HACR1) shows a lower level of elemental carbon

of the HALE1 site. 37

Coarse mass contributes to 9% of the visibility degradation at the Haleakala (HALE1)

monitor and 1 % of the visibility degradation at the Hawaii Volcanoes National Park

. The potential sources of coarse mass include fugitive dust, international transport, and shipping

. Soil contributes to 1% of the visibility degradation at the Hawaii Volcanoes National

Park

. The soil impa ct varies seasonally, with the highest levels in the springtime, and appears to be associated with international transport

.

V.C

. Visibility Impairing Pollutants Subject to Evaluation

EPA has evaluated the six particulate pollutants (ammonium sulfate, am monium nitrate, organic carbon (OC), elemental carbon (EC), fine soil and coarse mass (CM)) that contribute to visibility impairment at Hawaii‟s two mandatory Class I federal areas

. Sulfate is the primary

cau se of visibility impairment at each of Hawaii‟s Class I Areas, and EPA proposes that the first Regional Haze Plan RP evaluation should focus on primarily on significant sources of SO2 (sulfate precursor)

. NOx (nitrate precursor) is a secondary concern , as it contributes to 9% of the visibility degradati on on the 20% worst days at Haleakala. Coarse mass contributes to 9% of the visibility degradation at the Haleakala, and is also

of concern

. However, t he sources of coarse mass (CM) are uncertain because of emission inventory limitations associated with na tural sources (predominantly wildfires) and uncertainty of fugitive (windblown) emissions

. Because of the difficulty in attributing the sources of visibility impairment for this pollutant, EPA has determined that it is not reasonable in this planning perio d to recommend emission control measures for coarse mass

. Coarse mass contribution to visibility impairment, emissions sources, and potential control measures should be addressed in future Regional Haze plan updates. Because fine soil appears to be primari ly attributable to international transport, EPA has determined that it is not reasonable in this planning period to recommend emission control measures for fine soil. Although organic and elemental carbon contribute to base year visibility impairment, rece nt monitoring at the Haleakala Crater (HACR1) mon itoring site and the Hawaii Volcanoes (HAVO1) show low contributions to visibility impairment from organic and

elemental carbon.

36 Review of VIEWS2.0 2009

- 2010 Haleakala National Park Organic and Elemental Carbon Data, March 30, 2012, State of Hawaii, Department of Health, Clean Air Branch, and Comparison of Haleakala National Park

, HALE1 and

HACR1 IMPROVE Monito ring Site 2007

- 2008 Data Sets, March 30, 2012, State of Hawaii, Department of Health,

Clean Air Branch.

37 Ibid.44



### VI. Best Available Retrofit Technology (BART)

VI.A

. BART Requirements

Section 169A of the CAA directs states , or EPA if implementing a FIP, to evaluate the use of retrofit controls at certain larger, often uncontrolled, older stationary sources in order to address visibility impacts from these sources

. Specifically, section 169A(b)(2)(A) of the CAA requires states to revise their SIPs , or for EPA to implement a FIP, to contain such measures as may be necessary to make RP towards the natural visibility goal, including a requirement that certain categories of existing major sta tionary sources 38 built between 1962 and 1977 procure, install, and operate the “Best Available Retrofit Technology” as determined by the state , or EPA if implementing a FIP

. Under the Regional Haze Rule, s tates , or EPA if implementing a FIP, are directed t o conduct BART determinations for such “BART

- eligible” sources that may be anticipated to cause or contribute to any visibility impairment in a Class I area. On July 6, 2005, EPA published the Guidelines for BART Determinations Under the Regional Haze Rul e at Appendix Y to 40 CFR Part 51 (hereinafter referred to as the “BART Guidelines”) to assist states , or EPA if implementing a FIP, in determining which of their sources should be subject to the BART requirements and in determining appropriate emission

li mits for each applicable source

. 70 FR 39104

. In making a BART determination for a fossil

fuel

- fired electric generating plant with a total generating capacity in excess of 750 megawatts (MW) , a state , or EPA if implementing a FIP, must use the approach se t forth in the BART

Guidelines

. A state , or EPA if implementing a FIP, is encouraged, but not required, to follow the BART Guidelines in making BART determinations for other types of sources

. Regardless of source size or type, a state, or EPA if implementi ng a FIP, must meet the requirements of the CAA and our regulations for selection of BART, and the state‟s, or EPA‟s if implementing a FIP, BART analysis and determination must be reasonable in light of the overarching purpose of the regional haze program. The process of establishing BART emission limitations can be logically broken down

into three steps: first, states , or EPA if implementing a FIP, identify those sources which meet

the definition of “ BART

- eligible source ” set forth in 40 CFR 51.301 39 ; secon d, states , or EPA if implementing a FIP, determine which of such sources “ emits any air pollutant which may reasonably be anticipated to cause or contribute to any impairment of visibility in any such area” (a source which fits this description is “ subject to BART ”); and third, for each source subject to
BART, states , or EPA if implementing a FIP, then identify the best available type and level of

c ontrol for reducing emissions.

States , or EPA if implementing a FIP, must address all visibility

- impairing po llutants emitted by a source in the BART determination process

. The most significant visibility impairi ng pollutants are SO 2 , NO

x , and PM. Under the BART Guidelines, states , or EPA if implementing a FIP, may select an exemption threshold value for their BART modeling, below which a BART

- eligible source would not be expected to cause or contribute to visibility impairment in any Class I area

. The

38 The set of “major stationary sources” potentially subject to BART is listed in CAA section 169A(g)(7).

39 BART

- eligible sources are those sources that have the potential to emit 250 tons or more of a visibility

- impairing air poll utant, were not in operation prior to August 7, 1962, but were in existence on August 7, 1977, and whose operations fall within one or more of 26 specifically listed source categories

. 40 CFR 51.301.45

state , or EPA if implementing a FIP, must document this exem ption threshold value in the SIP

, or FIP, and must state the basis for its selection of that value

. Any source with emissions that model above the threshold value would be subject to a BART determination review

. The BART Guidelines acknowledge varying circ umstances affecting different Class I areas

. States , or EPA if implementing a FIP, should consider the number of emission sources affecting the Class I areas at issue and the magnitude of the individual sources‟ impacts

. Any exemption threshold set by the state , or EPA if implementing a FIP, should not be higher than 0. 5 deciview

. 40 CFR part 51, appendix Y, section III.A.1. A regional haze SIP , or FIP, must include source

- specific BART emission limits and compliance schedules for each source subject to BAR T

. Once a state , or EPA if implementing a
FIP, has made its BART determination, the BART controls must be installed and in operation as expeditiously as practicable, but no later than five years after the date of EPA approval of the regional haze SIP , or F IP

. CAA section 169(g)(4) and 40 CFR 51.308(e)(1)(iv)

. In addition to what is required by the Regional Haze Rule , general SIP , or FIP, requirements mandate that the

SIP , or FIP, must also include all regulatory requirements related to monitoring, recordkee ping, and reporting for the BART controls on the source

. See CAA section 110(a).

VI.B. Identify BART Eligible Sources

In 2008, the Hawaii DOH conducted a survey of the major sources in the state to identify which sources were BART eligible. This survey was completed and certified by the responsible official at each major source. Through that process, the following facilities were identified as BART eligible: HC&S Puunene facility, Chevron Refinery, Tesoro Refinery, Hu Honua Bioenergy

– Pepeekeo facility, MECO

– Kahului facility, HELCO Kanoelehua Hill

, HECO

– Waiau facility, HECO

– Kahe facility.

These sources were further analyzed to determine which were subject to BART.

VI. C . Identify BART

- Subject 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 determinations (B ART Guideline; EPA, 2005; 70 FR 39104

- 39172)

. The rule applies 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 area

. Stat es retain the authority to exempt certain BART

- eligible sources based on dispersion modeling demonstrating that the source cannot reasonably be anticipated to cause or contribute to visibility impairment in a Class I area

. According to 40 CFR Part 51, App endix 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 “contribution threshold.” Any BART

- eligible source, through modeling , 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

. The State of Hawaii chose to use
the recommended 0.5 deciview threshold for Subject

- to

- BART determination.46

Generally, if a source is a smaller emitter or is located far from a Class I area, and its Q/D

is less than 10 40 , the source is not expected to contribute to visibility impair ment at a Class I area. Using this approach, the Hawaii DO H determined that the Kauai Utilities Port Allen facility should not be Subject

- to

- BART

. For the other BART eligible sources, t he contribution to any impairment of visibility” in the Hawaii Class I area s is based on dispersion modeling

.

VI.C.1

. Subject to BART Modeling for the State of Hawaii

CALPUFF Modeling System

Subject to BART Modeling was performed by Alpine Geophysics on behalf of Hawaii

DOH 41

, EPA proposes to use this modeling as a basis to determine which sources are subject to BART. This modeling is described briefly below, and in greater detail in the modeling protocol and final report which are included in Appendix A of this document

. CALP UFF was applied separately for each Class I Area (Haleakala National Park and Hawaii Volcanoes National Park) on the island of Maui and Hawaii. The CALPUFF modeling
system , shown in Table 1, was the regulatory approved versions

, except for the CALPOST

proc essor

. CALPOST version 6.221 which was used to enable th e 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 input File Values.” Detailed parameter settings for

C ALPUFF, CALMET , and CALPOST are provided in Appendix A to this document

.

Table VI

- 1 : CALPUFF Modeling System

Program Version Level

CALMET 5.8 060911

CALPUFF 5.8 060911

CALPOST 6.221 080724

POSTUTIL 1.56 070627

The application generally follow ed the recommendation of the IWAQM and FLAG guidance

documents:

1) The calendar year 2005 CALMET input file were developed by Alpine Geophysics, LLC and be provided as input

- ready to CALPUFF.

40 Q = Potential Emissions (tons/year) of SO 2 +NOx+PM 10 f rom all eligible units within a facility D = Distance (kilometers) between the eligible source and the boundary of the nearest Class I area

41 Subject

- to

- Best Available Retrofit Technology (BART) Modeling for the State of Hawaii

, Application of the

CALP UFF Modeling System ; Prepared for: Hawaii State Department of Health , E nvironmental Management

Division Clean Air Branch by Alpine Geophysics, LLC

. March 3, 2010

.47

2) The Subject

- to

- BART modeling examined the visibility impairment on C lass I areas within 300km of each single source 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 s are used. 5) Puff splitting is not used, following the recommendations of the FLMs. 6) Source elevations are based on the same terrain files as the receptor elevations. 7) The CALUTIL is used to perform HNO3/NO3 repartitioning using the parameters in Appendix B.

Natural Background

The BART Guideline references EPA‟s “Guidance for Estimating Natural Conditions under the Regional Haze Rule” (EPA, 2003a)

. This guidance lists three sets of Natural Conditions corresponding to Annual Average, Best 20% Days and Worst 20 % Days

. Due to limited access to available meteorological data, the 20% best natural days were used, in lieu of annual average natural days, to represent natural visibility background in Class I areas

. This definition of natural background is consistent wi th the intent of the BART Guideline. 42

Table V I

- 2 : 20% Best Natural Conditions

– Concentrations and Rayleigh Scattering By

Class I Area.

Background Extinction Coefficients (20% Best Days)

Class I

Area (NH 4 ) 2 SO 4

μg/m3 NH 4 NO 3

Μg/m3 OM

μg/m3 EC μg/m3 Soil μg/m3 CM μg/m3 Sea

Salt μg/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

Background ozone was assumed to be at an annual constant level of 40 ppb

. A review of the ammonia emissions inventory for Hawaii in comparison with mainland agricultural areas indicate a background of 1.5 ppb to be representative based on land use and agricultural and livestock activity.

Meteorological Data

Alpine was contracted to apply the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale 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 addi tional modeling and analytical studies conducted for the Hawaiian Islands. A

42 Federal Register Vol. 70, No. 128, p 39125.48

complete description of the modeling approach and a statistical evaluation of the annual MM5 model are described in McNally and Wilkinson, 2008 43 , in Appendix B of this document.

VI.C.2. Review of Subject to BART Modeling

EPA proposes to use a contribution threshold of 0.5 deciviews for determining which sources are subject to BART

. EPA believes this threshold is appropriate , considering the number of sources affecting the Class I areas and the magnitude of the individual sources impacts

. This is

consistent with the State of Hawaii ‟s recommendation to use a 0.5 deciview threshold for the Subject

- to

- 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 m odeling p rotocol for the CALPUFF modeling used for the subject to BART determination

. The EPA has reviewed the methods used by Alpine for the Hawaii Department of Healt h in the application of th e CALPUFF modeling for the subject to BART analysis

. EPA proposes to find the modeling procedures appropriate for the subject to BART determination.

VI. C. 3

. Assessment of Subject to BART Modeling

EPA believes the CALPUFF modeli ng used for the s ubject to BART determination is the most appropriate modeling to use for the proposed Regional Haze FIP

. However, the modeling was based on a single year of mesoscale meteorological data

. A minimum of three years of

mesoscale meteorological model output is recommended for conducting the initial step in the

first

- level analysis

. However, meteorological data sets for more than 2005 were unavailable for the modeling domain at the time the CALPUFF modeling was performed for Hawaii DOH

. More recently, three years (2005

- 2007) of MM5 m eteorological d ata for Hawaii were d evelop ed by

JCA. 44 This data may be an appropriate basis for the mesoscale meteorological model ing for future regional haze plans.

VI.C. 4

. Results of Subject to BART Modeling

Table VI

- 3: Individual BART

- Eligible Source Visibility Impacts on Hawaii Class I Areas

Source and Unit Class I Area Maximum

24

- Hour

98 th Percentile

V isibility Subject to

BART or Exempt

43 MM5 Application for 2005 Over the Hawaiian Islands, p repared for Hawaii State Department of Health, Environmental Management Division, Clean Air Branch Prepared by: Alpine Geophysics, LLC ., October 31, 2008.

44 MM5 Meteorological Dataset Development For Hawaii, Draft December 2008, JCA, Prepared for Hawaiian Electric Company, Inc., Maui Electric Company, Inc. Hawaiian Electric Light Company, Ltd.49 Impact (deciview)

HC&S Puunene facility (Bagasse)

HC&S Puunene facility (Coal) Haleakala

Hawaii Volcanoes

Haleakala

Hawaii Volcanoes 0.059

0.008

0.133

0.039 Exempt

Exempt

Chevron Refinery Haleakala

Hawaii Volcanoes 0.021

0.016 Exempt

Tesoro Refinery Haleakala

Hawaii Volcanoes 0.025

0.017 Exempt

Hu Honua Bioenergy

– Pepeekeo facility Haleakala

Hawaii Volcanoes 0.323

0.540 Subject to

BART

MECO

– Kahului facility, Haleakala

Hawaii Volcanoes 0.232

0.108 Exempt

HELCO Kanoelehua Hill Haleakala

Hawaii Volcanoes 0.808

2.334 Subject to

BART

HECO

– Waiau facility Haleakala

Hawaii Volcanoes 0.083

0.038 Exempt

HECO

– Kahe facility Haleakala

Hawaii Volcanoes 0.221

0.132 Exempt

The Hu Honua Bioenergy

– Pepeeko facility has had its permit revoked. The facility has been issued a new permit to burn exclusively biomass materials. This new permit included the application of Best Available Control Technology. As a result of these changes, the facility is no longer BA RT eligible. The one remaining facility that is subject to BART is the HELCO

Kanoelehua Hill facility. This facility was analyzed to determine BART controls.

VI.D. BART Determination and Federally Enforceable Limits
The third step of a BART evaluation is to perform the BART analysis

. The BART Guidelines (70 FR 39164 (July 6, 2005)) describe the BART analysis as consisting of the following five steps:

Step 1: Identify All Available Retrofit Control Technologies;50 Step 2: Eliminate Technically Infeasible O ptions; Step 3: Evaluate Control Effectiveness of Remaining Control Technologies; Step 4: Evaluate Impacts and Document the Results; and Step 5: Evaluate Visibility Impacts.

In determining BART, the state, or EPA if implementing a FIP, must consider th e five statutory factors in section 169A of the CAA: (1) the costs of compliance; (2) the energy and

non

- air quality environmental impacts of compliance; (3) any existing pollution control technology in use at the source; (4) the remaining useful life of the source; and (5) the degree of improvement in visibility which may reasonably be anticipated to result from the use of such technology

. See also 40 CFR 51.308(e)(1)(ii)(A)

. The actual visibility impact analysis occurs during steps 4 and 5 of the process

. As mentioned previously, the only source in Hawaii subject to BART is the Kanoelehua Hill Generating Station on the Big Island. Specifically, there are two residual fuel

- oiled fired boilers at this plant that are subject to BART (Hill 5 & Hill 6). Hill 5 is a 14 MW front

- fired boiler. Hill 6 is a 21 MW tangentially fired boiler. Both boilers currently bur n residual (~ No. 6)

oil with sulfur content not to exceed 2% by weight. Table V

- 1 summarizes the baseline emission rates and modeled visibility impact o f these sources. The annual emissions are based on 2009 operations.

Table V I

- 1 Baseline Emissions and Visibility Impacts of Hill

SO 2 emissions tons per year [tpy] 2,778

NO

x emissions [tpy] 735

PM emissions tpy 70 Visibility impact on Haleakala 45 ∆ deciview [∆/dv] 0.44 Visibility impact on Volcanoes [∆/dv] 1.56

Trinity Consu lting, on behalf of the Hawaii Elec tric Company, the plant operator, performed a five

- factor analysis for this plant 46

. 2009 was used as the baseline for the analysis because that was the most current, complete year available when Trinity performed the BART analysis in 2010. We have reviewed this analysis and believe it appropriately addresses the five BART factors. Althoug h the BART guidelines are not mandatory for Hill because the plant‟s total generating capacity is less than 750 megawatts , the Trinity analysis generally adheres to the guidelines. Our analysis of the five factors is largely based on the Trinity work.

VI

. D.1 BART for NO
x and Particulate Matter (PM)

The Trinity report appropriately examined BART controls for NO

x and PM. However,

45 These results are from Trinity‟s modeling. These indicate a lower impact than was indicated by the Alpine modeling. But, even in Trinity‟s modeling, the baseline impacts are high enough to make the source subject to

BART.

46 BART FIVE FACTOR ANALYSIS Prep ared for Hawaiian Electric Light Company, October 2010, Trinity

Consultants51

due to the overwhelming contribution of sulfate to visibility impairment at the nearby Hawaii Volcanoes Class I area, it is unlikely that reductions in these pollutants from this site would have a measurable impact on visibility at that area. For PM, the Trinity report considered the following technologies: Dry Electrostatic Precipitator (ESP), Wet Electrostatic Precipitator ( ESP), Fabric Filter, Wet Scrubber, Cyclone and Fuel Switching. Dry ESPs, Cyclones and Fabric Filters are not appropriate for the type of particulate emitted by this plant. A wet scrubber would work, but these types of devices are better suited to larger pa rticulate than is emitted from an oil

- fired boiler and their control efficiency would be small. A wet ESP would have good control efficiency and is technically feasible. Similarly, switching to distillate fuel would be an effective and technically feasible

control for PM

. Trinity estimated the cost effectiveness of a wet ESP as $13,000 per ton of PM controlled. They estimated the cost effectiveness of switching to distillate fuel as $170,000 per

ton. N either of these controls would be cost effective for PM

. For NOx, the Trinity report considered both combustion controls such as flue gas

recirculation and low

- NOx burners as well as post

- combustion controls such as selective catalytic reduction (SCR). There were no technical barriers to implementing any of t hese controls. The post

- combustion controls were not found to be cost effective

. Low

- NOx burners were found to be cost effective by the Trinity report. However, given the monitoring data on Hawaii, EPA finds that the emission reductions provided by low

- NO

x burners is unlikely to provide a measurable visibility benefit at Hawaii Volcanoes or Haleakala. Based on our consideration of the five BART factors, EPA has determined that no control

for NO

x and PM at the Hill plant is consistent with BART, given the u nique conditions in

Hawaii. NO

x reductions may need to be pursued in future planning periods as anthropogenic sulfates are reduced and nitrates become a larger portion of anthropogenic visibility impairment.

VI .D.2 BART for SO 2

The principal visibility

- impairing pollutant from the Hill Plant is SO 2 . Sulfates are the largest component of visibility impairment at Hawaii Volcanoes and at Haleakela, even on the best days. The Hill Plant is by far the largest source of anthropogenic SO 2 emissions on the Big

Island. The Trinity report considered both flue gas desulfurization (FGD) and fuel switching as possible controls. The report found that no other oil

- fired electric generating unit had installed FGD technology and due to the lack of industry experience, the technology was infeasible. Even if it were feasible, the control effectiveness would be in question. EPA agrees that FGD technology is unproven for this application and concurs with Trinity‟s decision to focus on fuel switching. However, the Trinity an alysis only looked at switching to distillate fuel oil. Distillate fuel oil is substantially more expensive than residual fuel oil and it provides less energy per gallon. As a result, it is not a cost effective control measure

. EPA requested HECO to cons ider switching to lower sulfur residual fuel oil, which would be a less expensive option. HECO responded with their cost effectiveness estimate 47 . The lowest cost option, residual fuel oil no more than 1% sulfur by weight had a cost effectiveness of

between $6,6 77 /ton and $7,3 63 /ton.

47 Letter from Brenner Munger, Manager, Environmental Department, Hawaiian Electric Company to Tom Webb, U.S. EPA Region 9, January 27, 201252

EPA considered this cost estimate too high in light of available market data and conducted our own analysis, which is summarized in Table V I

- 2, below. Based on this analysis,

we estimate the cost effectiveness of this control to be approximately $5,600/ton.

Table VI

- 2 : Cost and Benefits of Switching Hill to 1% Fuel Oil
Baseline Weigh t % S 1.57 Baseline Fuel Consumption [gal/yr] 18,650,604
Baseline Emissions [tons SO 2 /yr] 2,344

New F uel Weigh t % S 1.00

Cost D ifferential [$/gal] 0.255
Controlled Emissions [tons SO 2 /yr] 1493 Annual Costs [$/yr] $4,755,90 4

Annual E mission Reductions [tons SO 2 /yr] 851 Cost Efficiency [$/ton SO 2 reduced] $5,587

In Table VI

- 2, the baseline sulfur content is the average of two years of fuel oil analysis conducted by the electric utility for fuel they have received at Maui and the Big Island. This is more representative than taking the actual fuel sulfur content for the year 2 009. The fuel is guaranteed by the suppliers to be less than 2% sulfur, but the actual sulfur content varies depending on feedstock. The fuel consumption numbers are from the Trinity BART analysis

. The SO 2 emissions were calculated based on stack testing c onducted at Kanoelehua Hill, and adjusting for sulfur input for the new fuel. The new fuel is conservatively assumed to have exactly 1% sulfur, although in practice the actual sulfur content is likely to be lower. The key assumption in Table VI

- 2 is the c ost differential between the current residual fuel oil and the cost of a lower sulfur fuel, which is estimated here as 0.255 $/gallon, based on the following analysis. Removing sulfur from the crude oil feedstock is a cost for the refinery, so

a lower sulf

ur level usually means a higher cost. The Energy Information Agency (EIA) tracks the prices of refinery products over time. The 5 year average cost differential between residual fuel oil with a sulfur content greater and 1% and residual fuel oil with a sul fur content less than 1% is 0.184 $/gal (2005

- 2010). The ten year average is 0.165 $/gal (2000

- 2010) 48 . But the EIA

data is for the continental United States. However, the EIA data is for the continental United

States and does not reflect various factors th at influence fuel oil supply and costs in Hawaii. In order to obtain a more accurate estimate of the cost differential for Hawaii, EPA looked at the long

- term average costs of residual fuel oil delivered to Oahu, Maui and the Big Island.
All of the state‟ s fuel is received or refined on Oahu and is shipped by barge to the neighboring islands. Because of the additional distance, fuel oil delivered to the Big Island is roughly 0.050 to 0.060 $/gal more expensive than fuel delivered to Maui. The more difficul t question is how to estimate the cost differential due to the lower sulfur. EPA looked at the cost

differential between the lower sulfur fuel burned on Oahu and the 2% sulfur fuel burned on Maui. The power plants on Oahu burn oil that is no more than 0.5 sulfur by weight. This is waxier oil that can‟t be burned in power plants on Maui or the Big Island without some modification of the storage and shipping infrastructure. Nevertheless, it is reasonable to assume

that 1% sulfur fuel oil would cost no more th an the 0.5% sulfur fuel burned on Oahu. So, using the Oahu product as an upper limit, EPA assumes that 1% sulfur fuel oil will on average cost

48 http://www.eia.gov/dnav/pet/PET_PRI_R ESID_DCU_NUS_M.htm53

0.190 $/gal more than the 2% sulfur fuel oil currently being burned. This is the six

- year (2006

- 2011) average cos t differential between 0.5% fuel oil used on Oahu and the 2% fuel oil used on Maui and the Big Island. This 0.190 $/gal estimate is consistent with and a little higher than the EIA data. Since Hill is on the Big Island, we needed to account for transportat ion costs. So, we added 0.065 $/gal to the estimate for a total of 0.255 $/gal. The 0.065 $/gal estimate is derived

from the six

- year (2006

- 2011) cost differential between residual fuel oil delivered to Maui and the same oil delivered to the Big Island 49 . E PA considers this estimate to be reasonable and

conservative.

Figure V I

- 1 Fuel Oil Costs Over Time

Figure VI

- 1 shows the variation in costs between low sulfur fuel oil delivered to Oahu (LSFO) and the 2% sulfur residual fuel oil (also known as number 6 fuel oil or No. 6) delivered to Maui and the Big Island (BI). The costs are in $/barrel. There are 42 gallons in a barrel of oil. With these assumptions, EPA estimates an annual increase in fuel costs of over $4.8 million/year. EPA contracted with energy economics consulting firm Energy Strategies to estimate the impact of these increased fuel costs on electric rates. Based on their analysis 50 , these increased costs would translate into a roughly 1% increase in retail electric rates on the Big

Island. The benefit of this change would be a reduction in SO 2 emissions of 851 tons per year.

The next factors to consider are (2) the energy and non

- air quality environmental impacts of compliance; (3) any existing pollution control technology in use at the source; and (4) the remaining useful life of the source . There are no existing pollution controls at the site for SO 2

. We ha ve considered factors (2) and (4) in the context of the Hawaii Clean Energy Initiative, which sets the goal of 70% clean energy by 2030. The Initiative includes the 2009 Clean Energy Omnibus Bill ( ACT 155 (09), HB 1464, signed June 25, 2009 ). This statute calls for 30%

49 EPA Hawaii Residual Fuel Oil Summary Spreadsheet

50 Fuel Cost Screening Tool (r1 4

- 18

- 12), Energy Strategies Incorporated, April 18, 2012 $50.00 $60.00 $70.00 $80.00 $90.00 $100.00 $110.00 $120.00 $130.00 $140.00

Jul - 09 Aug - 09 Sep - 09 Oct - 09 Nov - 09 Dec - 09 Jan - 10 Feb - 10 Mar - 10 Apr - 10 May - 10 Jun - 10 Jul - 10 Aug - 10 Sep - 10 Oct - 10 Nov - 10 Dec - 10 Jan - 11 Feb - 11 Mar - 11 Apr - 11 May - 11 Jun - 11

Oahu

- LSFO Maui

- No.6 BI No.654

reduction in energy use via efficiency and increases the renewable portfolio standard to 40% by

2030. EPA contracted with UNC and ICF to project the 2018 emissions of power plants considering the requirements of the Clean Energy Omnibus Bill. These projections are compared to the current 2018 projections based on the most recent Integrated Resource Plan (IRP) for

Hawaii electric utilities 51 . This IRP predates the 2009 bill and so does not account for its requirements. Table V

- 5 compares the bas eline emission projections for 2018, derived from the current IRP and the projections that take into account the requirements of the Clean Energy Bill.

Table I V

- 3 : Range of 2018 Emissions Projections for Hill [tons per year]

2018 SO 2 Emissions 2018 SO 2

Emissions

IRP Clean Energy Bill Kanoelehua Hill Generating Station 3,264 765

The projections based on the goals of the Clean Energy Bill assume that the energy conservation and renewable energy goals will be met in a more or less even fashion year to year. So, by 2018, most of these projects will be in place. This is a fairly optim istic scenario, but it gives some insight into the impact of the Clean Energy Bill on these plants. By 2018 Hill is projected to be operating at a significantly lower capacity factor and/or burning biofuels with

much less sulfur

. The final factor to cons ider is the visibility benefits of controls. Trinity modeled the lower emission rates associated with lower sulfur fuels and estimated the following visibility benefits. The delta deciview [∆/dv] dropped from 1.56 for baseline conditions to 1.05 when

burni ng the 1% sulfur fuel, which represents approximately 0.5 dv benefit. Taking into consideration all of these factors, we propose to determine that BART for Hill is no additional controls. In particular, although we consider 0.5 dv to be a significant imp rovement in visibility, we do not believe it justifies the imposition of a control with a cost effectiveness of approximately $5,600/ton in this case. We are particularly concerned about unduly increasing electricity rates in Hawaii, given that these rates are already three times the national average according to the Energy Information Agency. 52 Therefore, we propose to determine that no BART controls be required for Hill.



### VII. Reasonable Progress

VII.A. Unique Regional Haze Planning Challenge for Hawaii

In determining if reasonable progress is being made, states, or EPA if implementing a FIP, are required to consider the following factors established in section 169A of the CAA and in our Regional Haze Rule at 40 CFR 51.308(d)(1)(i)(A): (1) the costs of co mpliance; (2) the time necessary for compliance; (3) the energy and non

- air quality environmental impacts of compliance; and (4) the remaining useful life of any potentially affected sources (“the four RP

51 Email from Juanita Haydel, ICF Corporation to Greg Nudd, U.S. EPA Region 9, April 4, 2012, with spreadsheet
titled: “ Hawaii Emissions Values_Revised_040412_FTC.xlsx ”

52 http://205.254.135.7/state/state

- energy

- rankings.cfm?keyid=18&orderid=155

factors”). Once these factors have been considered, the typical method for determining if a state is making reasonable progress is to use meteorological and air quality computer models to predict the visibility at Class I areas for the end of the planning period (2018). Those modeling

results are then asse ssed to ensure that visibility is not degrading on the best days and that it is improving on the worst days at a reasonable rate, taking into consideration the relevant statutory factors, as well as the base period visibility conditions and the goal of zer o anthropogenic visibility impairment by 2064. In the case of Hawaii, though, a different method of determining reasonable progress is required. As explained in sections II.A., II.B, and III.B. , the dominant cause of visibility impairment at Hawaii‟s Clas s I areas is sulfate compounds and over 96% of the sulfate emissions in Hawaii are from the volcano [see section IV.A. Statewide Emissions Inventory]. However, because the volcanic eruptions vary greatly from year to year with no discernible pattern, it is impossible to predict future volcanic emissions. The emissions vary by hundreds of thousands of tons per year. As a result, there is little value in attempting to model visibility at the Class I areas

in 2018.

VII.B. I dentification of Pollutants for Rea sonable Progress

EPA has evaluated the six particulate pollutants (ammonium sulfate, ammonium nitrate, organic carbon (OC), elemental carbon (EC), fine soil and coarse mass (CM)) that contribute to visibility impairment at Hawaii‟s two mandatory Class I f ederal areas . Sulfate is the primary cause of visibility impairment at each of Hawaii‟s Class I Areas, and EPA has determined that the first Regional Haze Plan RP evaluation should focus on primarily on significant sources of SO2 (sulfate precursor)

. NOx ( nitrate precursor) is a secondary concern , as it contributes to 9% of the visibility degradation on the 20% worst days at Haleakala. Coarse mass contributes to 9% of the visibility degradation at the Haleakala, and is also

of concern

. However, t he sources of coarse mass (CM) are uncertain because of emission inventory limitations associated with natural sources (predominantly wildfires) and uncertainty of fugitive (windblown) emissions

. Because of the difficulty in attributing the sources of visibility impa irment for this pollutant, EPA has determined that it is not reasonable in this planning period to recommend emission control measures for coarse mass

. Coarse mass contribution to visibility impairment, emissions sources, and potential control measures sho uld be addressed in future Regional Haze plan updates. Because fine soil appears to be primarily attributable to international transport, EPA has determined that it is not reasonable in this planning period to recommend emission control

measures for fine s oil. Although organic and elemental carbon contribute to base year visibility impairment, recent monitoring at the Haleakala Crater ( HACR1) monitoring site and the Hawaii

Volcanoe s (HAVO1) show low contributions to visibility impairment from organic and

el emental carbon.

VII. C . Determining Reasonable Progress Through Island

- Specific Emissions Inventories

Due to the absence of modeling to project visibility at Hawaii‟s Class I areas in 2018, EPA is focusing its reasonable progress analysis on reducing ant hropogenic visibility impairing56

pollution. The EPA is focusing on the broader goals of the Regional Haze Program. Specifically, we are focusing on the reduction of anthropogenic visibility impairing pollution. The discussion

earlier in this document determ ined that the key anthropogenic pollutants of concern are SO 2 and

NO

x , especially SO 2 . So, we will look at trends in the emission of anthropogenic SO 2 and NO

x in order to judge if reasonable progress is being achieved

. Rather than use a full statewide inventory to judge reasonable progress, it makes sense to

focus on the inventories for the islands where the Class I areas are located: Maui and the island of Hawaii. Population, economic activity and therefore anthropogeni c emissions in the state of Hawaii are concentrated on the island of Oahu. But, as explained below, our analysis indicates

that those emissions do not significantly impair visibility at the Class I areas

. Prevailing winds at the Honolulu Airport on Oahu ar e from the east

- north

- east 53 . The prevailing winds on Maui are

from the northeast 54 . The Class I areas are south and west of Oahu. Therefore, these trade winds tend to transport pollution from Oahu away from the Class I areas. Air quality modeling of source s on Oahu support this determination. In order to identify point sources that may be candidates for additional air pollution control under this Regional Haze Plan, the Hawaii Department of Health (DOH) contracted with Alpine Geophysics to conduct air quali ty modeling of large pollution sources statewide. This modeling is described more completely elsewhere in this document (see section VI.C.) This modeling was designed to estimate the visibility impact of currently operating individual sources of pollution on the Class I

areas in the state. Several of t he highest emitting source s on Oahu are shown in Table V II

- 1, below along with their estimated visibility impacts on the Class I areas. The visibility impacts are expressed in terms of the change in deciviews or ∆ deciview [∆/dv].

Table V II

- 1: Modeled Visibility Impacts of Major Sources on Oahu
Emissions [tpy] Impact [ ∆ /dv]

Source Nox PM

- 10 SO2 VOC HALE HAVO
HECO

- Kahe Power Plant 4,848 694 6,684 83 0.2 21 0.1 3 2

HECO

- Waiau Power Plant 2,597 310 2,970 37 0.083 0.0 38 Chevron Hawaii Refinery 751 133 2,128 1,106 0.021 0.016

Tesoro

- Campbell Industrial Park & Barbers Point Marine Loading 1,204 88 816 543 0.0 25 0.0 17

The Kahe Power Plant is a very highly polluting source with combined NO

x and SO 2 emissions that exceed 11,500 tons per year. This power plant is 197 kilometers (about 122 miles) from the Haleakala(HALE) monitor. But, even this very large source has a relatively small visibility impact on Haleakela (0. 2 21 deciview change).

Given these modeling results and the prevailing winds in Oahu and Maui for this planning period, we will focus our reasonable progress analysis on the islands that contain the

Class I areas. The tables below show the emission inventories for the islands of Maui and

H awaii. These tables are based on methods and assumptions described in the Emissions Inventory chapter of this TSD.

Table V II

- 2 Maui Anthropogenic Emissions Inventory

53 See prevailing winds data from the Western Regional Climate Center ( http://www.wrcc.dri.edu/htmlfiles/westwinddir.html#HAWAII )

54 Ibid.57 2005 Inventory 2018 Inventory
Source Category N O

x SO 2 N O

x SO 2 Point 4,492 4,559 4,597 4,625
Nonpoint 462 481 548 571

On Road Mobile 2,957 47 758 10

Non

- Road Mobile 496 57 305 2

Aircraft 310 27 376 33
Agricultural Burning 298 132 298 132

Wildfires 52 14 52 14 in/near port Marine 699 569 836 32

Total 9,765 5,887 7,770 5,420

Table V II

- 2.1 Maui Point Source Emissions

2005 20 1 8

N O

x SO 2 N O

x SO 2 MECO

- Kahului Power Plant 536 3,198 542 3,233
Maalaea Generating Station 3,255 913 3,291 923

HC & S

- Puunene Sugar Mill 617 424 760 469
Ameron Hawaii Camp 10 Quarry 4 0 4 0

Maui Pineapple Co. 80 24

Total 4,492 4,559 4,597 4,625

Table V II

- 3 Hawaii (Big Island) Anthropogenic Emissions Inventory

2005 Inventory 2018 Inventory
Source Category N O

x SO 2 N O

x SO 2 Point 1,036 4,551 1,736 5,266
Nonpoint 1,849 808 1,882 872

On Road Mobile 3,217 53 839 11

Non

- Road Mobile 784 95 428 1

Aircraft 177 18 207 21 Agricultural Burning 2 0 2 0

Wildfires 1,712 469 1,712 469 in/near port Marine 537 418 546 20

Total 9,314 6,412 7,352 6,661

Table V II

- 3 .1 Hawaii (Big Island) Point Source Emissions

2005 20 1 8

N O

x SO 2 N O

x SO 2 HELCO

- Kanoelehua Hill Generating
Station 514 2,822 595 3,26458

HELCO

- Puna Power Plant 241 1,345 279 1,556

HELCO

- Keahole Power Plant 154 157 178 182

HELCO

- Shipman Power Plant 38 222 28 166

Pepeekeo Power Plant/9

- 16

- 10 Hu Honua Bioenergy 420 78

Tradewinds Forest Products, LLC 133 15

HELCO

- Waimea Power Plant 89 5 103 5

Total 1,036 4,551 1,736 5,266

V II

. C .1. Four Factor Analysis for NO
x sources on Maui and the Big Island

On Maui, NOx emissions are being reduced by almost 2,000 tpy between 2018 and 2005, even while assuming fairly robust economic growth. This is over a 20% reduction in emissions of a pollutant that is of secondary concern for this planning period

. In general, EPA finds this to

be a reasonable amount of NO

x reduction s, considering the small part the pollutant plays in visibility impairment in Hawaii.

Point sources of NO

x in Hawaii are predominantly electric utility units. Emissions from the Camp 10 quarry are quite small and not expected to impact visibility at the C lass I areas. The Maui Pineapple plant closed in 2008. The HC&S Puunene Sugar Mill on Maui was modeled by Alpine Geophysics and the modeling indicated that the plant would have no more than a 0.286 deciview impact at the nearest Class I area, Haleakela. An y additional controls are not likely to be cost effective, given the small impact of this source. The other sources are electric utility sources. Considering the costs of compliance and the 20% reduction in emissions from existing regulations, and the smal l contribution of nitrates to visibility impairment, the EPA does not consider it reasonable to require additional NO

x controls for point sources in this planning period.

Mobile sources of NO

x (on road, non

- road, aircraft and marine) constitute the large st fraction of base year emissions on these islands (48%). The NO

x emissions from these categories are projected to drop by over 7,100 tpy between 2005 and 2018. These decreases are largely attributable to a dramatic drop in emissions from on

- road mobile s ources, resulting from the replacement of older, higher emitting vehicles with new vehicles that must meet more stringent standards under the Clean Air Act. In addition to these requirements for on

- road source, EPA regulations also require newer non

- road a nd marine mobile sources to meet stricter control requirements

. Collectively, these federal mobile source requirements will result in substantial NOx reductions over the course of the first planning period. Given this context and taking into consideration the four reasonable progress factors, we believe that requiring additional NO

x controls on mobile sources would not be reasonable at this time. Therefore, we are not proposing any additional NO

x controls for mobile sources for this implementation period.59 Agricultural burning is a notable NO

x source on Maui. EPA has evaluated the monitoring data for the Class I areas and determined that there is no evidence that agricultural burning is significantly affecting visibility at the Class I areas . See TSD Sectio ns II.A., II.B, and

III.B. The current Hawaii DOH agricultural burning permitting process appears to be sufficient to prevent visibility impacts at the Class I areas. Wildfires have been included in the anthropogenic emissions inventory because the

Hawai i DOH and EPA have not been able to determine if the fires had natural causes or not. Nevertheless, it would not be helpful to introduce further restrictions on wildfires, because these are by definition, not intentional. So, regulations restricting them w ould not have any appreciable

effect.

V II

. C .2 Four Factor Analysis for SO 2 Emissions on Maui

Our analysis shows that current controls will result in net reductions of anthropogenic

emissions of SO 2 on Maui during this first planning period. So it is rea sonable to assume that the visibility at Haleakela on the best days is not getting worse. Similarly, with this drop in emissions, it is reasonable to assume that the worst visibility days will be getting better.

V II.C .2.1 Mobile Source SO 2 Emissions on Ma ui

Mobile source SO 2 emissions on Maui (on road, non

- road, aircraft and marine) are dropping 89% under current regulations, driven primarily by reductions in marine emissions due

to the ECA. This control measure is in addition to the benefits of fleet tur nover as described

above in the discussion NO

x . Given the existing benefits from the ECA (see section IV.A.) and the fleet turnover benefits that take into account the four factors, EPA finds that no additional

SO 2 reductions from mobile sources on Maui are needed in order to show reasonable progress.

V II

. C .2.2 Point Source SO 2 Emissions on Maui

Point Sources comprise 77% of the SO 2 emissions on Maui and are expected to increase slightly by 2018. However, this i ncrease is more than offset by the reduction in SO 2 from mobile source emissions. The principal point sources on Maui are the Kahului Power Plant and the

Maalaea Power Plant, neither of which are BART

- eligible. Maalea is downwind of the Class I

area and it s SO 2 emissions are not expected to impact visibility at Haleakala. Prevailing winds should also transport emissions from Kahului away from Haleakala. Alpine Geophysics estimated the visibility impact of Kahului plant using the CalPUFF computer model. The result was an estimated change in visibility of 0.667 deciviews at Haleakala. The modeling assumed the plant would be running at its maximum 24

- hr capacity and burning the highest sulfur content fuel that it is authorized to burn (2% sulfur by weight). Whi le these are very conservative assumptions that are unlikely to occur during normal operations, we believe this level of modeled impact is sufficient to warrant further scrutiny of this source under the four reasonable progress factors.

The first factor t o consider in reasonable progress is costs of compliance . The HECO (the electric utility) performed a detailed analysis of the cost of reducing SO 2 emissions at the60

Kanoelehua Hill Generating Station as part of the BART analysis for that source 55 . EPA

revie wed and largely concurred with the results of that analysis. With Hill, the most cost

effective control measure is to reduce the amount of sulfur in the fuel. This is also true for Kahului. However, even that method is expensive. The lowest cost method for reducing SO 2 emissions at these plants is to switch to a fuel with no more than 1% sulfur by weight. To estimate the total cost of the converting this plant to 1% fuel oil and estimate the impact of those costs on electric rates, EPA developed a base case scenario derived from 2009 operating

conditions 56 . This scenario is summarized in Table V II

- 4 below

. This analysis indicates that the cost effectiveness of this control is approximately $4,200 per ton of SO 2 reduced

.

Table V II

- 4 : Costs and Benefits from Switching to 1% Sulfur Fuel Oil

Kahului
Baseline Weigh t % S 1.57 Baseline Fuel Consumption [gal/yr] 19,790,111
Baseline Emissions [tons SO 2 /yr] 2, 489

New F uel Weigh t % S 1.00

Cost D ifferential [$/gal] 0. 190 Controlled Emissions [tons SO 2 /yr] 1,586 Annual Costs [$/yr] $ 3,760,121

Annual E mission Reductions [tons SO 2 /yr] 904 Cost Efficiency [$/ton SO 2 reduced] $ 4,160

In Table V II

- 4 , the baseline sulfur content is the average of two years of fuel oil analysis conducted by the electric utility for fuel they have received at Maui and the Big Island. This is more representative than taking the actual fuel sulfur content for the year 2009. The fuel is guaranteed by the suppliers to be less than 2% sulfur, but the actual sulfur content varie s depending on feedstock. The fuel consumption numbers are from emissions inventory reports submitted by the utility to the Hawaii Dept. of Health. The SO 2 emissions were calculated based on stack testing conducted at Kanoelehua Hill and assuming that Kahu lui also had a more than

99% conversion rate of fuel sulfur to SO 2 . The new fuel is conservatively assumed to have exactly 1% sulfur, although in practice the actual sulfur content is likely to be lower. In Table

VII

- 4 , we assume that the cost differential between the current fuel and the 1% sulfur fuel to be 0.190 $/gal based on an analysis of prices historically paid for lower sulfur fuel in Hawaii, as described in the BART analysis for Hill. The price is lower than for Hill, because the fuel is

delivered to Maui, not the Big Island. With these assumptions, EPA estimates an increase in fuel costs of over $3.7 million/year. EPA contracted with energy economics consulting firm Energy Strategies to estimate the impact of these increased fuel costs on electri c rates. Based on their ana lysis 57 , these increased costs would translate into a roughly 1% increase in retail electric rates on Maui. The benefit of this change would be a reduction in SO 2 emissions of 900 tons per year.

55 BART Five

- Factor Analysis Prepared for Hawaiian Electric Light Company, October 2010, Trinity Consultants.

56 2009 was selected because it was consistent with the year used in the BART ana lysis for Hill. It is also a year where the actual capacity factors for the electric plants on the Big Island were comparable to the 4

- year average.

57 Fuel Cost Screening Tool (r1 4

- 18

- 12), Energy Strategies Incorporated, April 18, 201261

The second factor to consider is th e time necessary for compliance. The switch to a lower sulfur version of the residual fuel oil currently being burned does not require any capital investment or construction, but it does require time to get new fuel contracts into place with the

new sulfur limits. It may take time for the fuel suppliers to secure the new fuel and it will take time for the current fuel inventory to be consumed

. The third and fourth factors to consider are the energy and non

- air quality impacts of

control measures and the re maining useful life of the source. EPA considered these factors in the context of the Hawaii Clean Energy Initiative that sets the goal of 70% clean energy by 2030. The Initiative includes the 2009 Clean Energy Omnibus Bill ( ACT 155 (09), HB 1464, signed

J une 25, 2009 ). This statute calls for 30% reduction in energy use via efficiency and increases the renewable portfolio standard to 40% by 2030. EPA contracted with UNC and ICF to project the 2018 emissions of power plants considering the requirements of th e Clean Energy Omnibus

Bill 58 . These projections are compared to the current 2018 projections based on the most recent Integrated Resource Plan (IRP) for Hawaii electric utilities. This IRP predates the 2009 bill and so does not account its requirements. Ta ble V II

- 5 compares the baseline emission projections for 2018, derived from the current IRP and the projections that take into account the goals of the Clean Energy Bill.

Table V II

- 5 : Range of 2018 Emissions Projections for Key Power Plants on the Maui [tons per year]

2018 SO 2 Emissions 2018 SO 2

Emissions

IRP Clean Energy Bill

Kahului Power Plant 2,822 0 Maalaea Generating Station 923 591

The projections based on the goals of the Clean Energy Bill assume that the energy conservation and renewable energy goals will be met in a more or less even fashion year to year. So, by 2018, most of these projects will be in place. Under this scenario, K ahului will cease operations by 2018 and Maalaea will operate at a significantly lower capacity factor and/or burn

biofuels that contain much less sulfur than their current fuel

.

V II

. C .2.3 Conclusion of Reasonable Progress Analysis for SO 2 Emissions on Ma ui

Based on the foregoing analysis for the four RP factors, we propose to determine that it is not reasonable to require additional SO 2 controls for point sources on Maui in this planning period. In addition, as mentioned above, electric utility rates in Hawaii are over three times the national average. Even in the absence of the Hawaii Clean Energy Bill, emissions on Maui are projected to decrease during this planning period. Therefore, based on our consideration of the four RP factors, EPA proposes to de termine that this level of emissions reduction is reasonable for this planning period.

58 Email from Juanit a Haydel, ICF Corporation to Greg Nudd, U.S. EPA Region 9, April 4, 2012, with spreadsheet
titled: “ Hawaii Emissions Values_Revised_040412_FTC.xlsx ”62

V II

. C .3 Four Factor Analysis for SO 2 emissions on the Big Island (Hawaii)

Unlike on Maui, EPA is projecting that without additional controls SO 2 emissions on the Big Island will increase between 2005 and 2018. As noted above, SO 2 is the key anthropogenic visibility

- impairing pollutant in Hawaii. Therefore, we propose to determine that additional SO 2 control measures are needed on the Big Island in order to ensure reasonable progress toward the national goal of no anthropogenic visibility impairment.

V II .C .3.1 Mobile Source SO 2 Emissions on the Big Island (Hawaii)

Mobile source emissions of SO 2 on t he Big Island are dropping 91% under current regulations, driven primarily by reductions in marine emissions due to the ECA. This control

measure is in addition to the benefits of fleet turnover as described above in the discussion NO

x . Given the existing benefits from the ECA and the fleet turnover benefits and taking into account the four reasonable progress factors, EPA proposes to determine that no additional SO 2 reductions from mobile sources on the Big Island are needed in order to show reasonable

pro gress.

V II.C .3.2 Point Source SO 2 Emissions on the Big Island (Hawaii)

Point sources comprise roughly 71% of the anthropogenic SO 2 emissions on the Big Island. All of these emissions come from electric power plants. Therefore, all of these power plants were considered for additional controls. Because of their relatively low emission rates and distance from the Class I areas, EPA elim inated the Keohole and Waimea Power Plants. Due to their emission rates and positions close to and upwind of Hawaii Volcanoes National Park, Hill, Shipman and Puna are the focus of the review. Alpine Geophysics estimated the visibility impact of these plan ts using the CalPUFF computer model. The results are summarized below:

Table V II

- 6 : Modeled Visibility Impacts of Key Power Plants on Hawaii
Visibility Impact
[ ∆ /dv]

HAVO HALE
HELCO

- Kanoelehua Hill Generating Station 2.334 0.808
HELCO

- Puna Power Plant 1.594 0.358
HELCO

- Shipman Power Plant 0.777 0.321

These plants were also modeled with the same conservative assumptions as Kahului. The results for Hill and Puna indicate that these plants may be causing visibility impairment at Hawaii Volcanoes. In addition, the results indicate that Hill may be contributing to impairment at Haleakala and Shipman may be contributing to visibility impairment at Hawaii Volcanoes

. The first factor to consider in re asonable progress is the costs of compliance. The HECO (the electric utility) performed a detailed analysis of the cost of reducing SO 2 emissions at Hill as part of th e BART analysis for that source 59 . EPA reviewed and largely concurred with the results

of that analysis. As described previously, the most cost

- effective control measure is to reduce the amount of sulfur in the fuel. This is also true for Shipman and Puna. Table V

- 7 provides the full

59 BART Five

- Factor Analysis Prepared for Hawaiian Electric Light Company, Octob er 2010, Trinity Consultants63

cost/benefit calculation for the Big Island sources. Based on this analysis, EPA estimates that the

cost effectiveness of this control is approximately $5,500 per ton of SO 2 reduced for sources on the Big Island

.

Table V

- 7 : Costs and Benefits from Switching to 1% Sulfur Fuel Oil

Hill Shipman Puna Baseline Weigh t % S 1.57 1.57 1.57

Baseline Fuel Consumption [gal/yr] 18,650,604 2,241,876 9,930,648
Baseline Emissions [tons SO 2 /yr] 2,344 282 1,249

New F uel Weigh t % S 1.00 1.00 1.00

Cost D ifferential [$/gal] 0.255 0.255 0.255
Controlled Emissions [tons SO 2 /yr] 1493 180 796 Annual Costs [$/yr] $4,755,90 4 $571,678 $2,532,315

Annual E mission Reductions [tons

SO 2 /yr] 851 102 454 Cost Efficiency [$/ton SO 2 reduced] $5,587 $5,583 $5,583

Total Annual Cost $7,859,89

Total Annual Emissions Reduction 1

, 407

In Table V

- 7, most of the assumptions are the same as in Table V

- 4, but the cost differential is a bit higher due to the extra transport costs. We added 0.065 $/gal to the estimate for a total of 0.255 $/gal. The 0.065 $/gal estimate is derived from the si x

- year (2006

- 2011) cost differential between residual fuel oil delivered to Maui and the same oil delivered to the Big

Island. With these assumptions, EPA estimates an annual increase in fuel costs of over $7.9 million/year. EPA contracted with energy ec onomics consulting firm Energy Strategies to estimate the impact of these increased fuel costs on electric rat es. Based on their analysis 60 , these increased costs would translate into a 2% increase in retail electric rates on the Big Island. The

benefit of this change would be a reduction in SO 2 emissions of at least 1,400 tons per year. The second factor to consider is the time necessary for compliance. The considerations

here are the same as for Maui. The third and fourth factors to consider are the energy and non

- air quality impacts of control measures and the remaining useful life of the source. In order to fully consider the energy

and non

- air quality impacts of control measures and the remaining use ful life of the source, EPA is taking into account the anticipated results of the Clean Energy Bill described above. Table

VII

- 8 compares the baseline emission projections for 2018 and the projections that take into account the goals of the Clean Energy Bi ll.

60 Fuel Cost Screening Tool (r1 4

- 18

- 12), Energy Strategies Incorporated, April 18, 201264

Table V II

- 8 : Range of 2018 Emissions Projections for Key Power Plants on the Big Island [tons per year]

2018 SO 2 Emissions 2018 SO 2

Emissions

IRP Clean Energy Bill

HELCO

- Kanoelehua Hill Generating Station 3,264 765
HELCO

- Puna Power Plant 1,566 365
HELCO

- Shipman Power Plant 166 0

Again, these are optimistic assumptions, but they are useful. Under this scenario, Shipman is projected to cease operations by 2018 and Hill and Puna are projected to be operating at a significantly lower capacity factor and/or burning biofuels with much lower sulfur content

than their current fuel.

V II .C .3.3 Conclusion of Reasonable Progress Analysis for SO 2 Emissions on the Big Island (Hawaii)

Some additional, federally enforceable SO 2 reductions are needed on the Big Island to ensure reasonable progress. Based on the above analysis of the four reasonable progress factors, EPA believes that any control measure for SO 2 should be structured so tha t it could be achieved through increased energy efficiency and increased reliance on renewable energy

. Therefore, EPA is proposing to cap total emissions at the fuel oil

- fired boilers at Hill, Shipman and Puna at 3,500 tons per year, beginning in January 1 , 2018. This is a reduction of 1,400 tons per year from the baseline estimate of emissions in 2018. If HECO is on track with implementing the Hawaii Clean Energy Bill, it should be able to meet this cap with no additional costs to the ratepayers. In the

wo rst case scenario where the cap has to be met with a lower sulfur fuel oil, the utility should be able to meet this cap at a cost of roughly $7.9 million/year. EPA is structuring this control requirement to allow the utility to minimize costs. We are takin g the other three factors into account by structuring the control requirement to be consistent with the State‟s goals for energy conservation and reduced dependence on fossil fuels.

V II .D

. Benefits of the Emission Control Area on Emissions from In Transit Marine Vessels

In addition to reducing emissions from ships in and near ports, the ECA also significantly reduces emissions from ships traveling from port

- to

- port. As part of the evaluation of the benefits of the ECA, EPA asked UNC and ICF to calculate the 2005 and 2018 emissions from ships passing within 150 km of each of the Class I areas. Table V

- 9 summarizes these results. Since the 150 km includes some ports and those ports are already accounted for in the “In and Near Port Marine” category in the i sland

- specific inventories, those emissions have been

excluded from Table V

- 9.65 Figure V II

- 2: Class I Visibility Areas

Table V II

- 9: Benefits of the ECA from In Transit Shipping within 150 km of the Class I

Areas

2005 2018

Class I area NO

x SO 2 NO

x SO 2 Haleakala 2,740 2,610 3,419 141

Hawaii Volcano e s 566 530 447 15

EPA considered this as supplemental information when determining whether reasonable progress is being made with existing regulations. These emission reductions are expected to benefit visibility at the Class I areas, but it is difficult to determine by how much. For example, prevailing winds may transport the emissions away from the Class I areas. Specifically, much of the reductions for the Haleakala zone are from ships traveling to and from Oahu. These SO 2 emission reductions from shipping in the vicinity of Maui support our decision not to require

additional SO 2 controls on that island in this planning period.

VII.E

. Reasonable Progress Goals

- 2018 Visibility Projections

There is no modeling available for this planning period that can reliably predict the change in visibility due to changes in the emission inventory for all sources (shipping, mobile sources, point sources, etc.). 61 In absence of reliable visibility modeling for 2018, EPA is us ing projec tions based on the island

- specific inventories as a surrogate for judging whether reasonable progress is being made.

61 EPA believes that t here is acceptable modeling for point sources for identifying BART Subject Sources and for the reasonable progress an alysis. This modeling is discussed in Section IVC: Identify BART Subject Sources,

above.66

In order to show the how the future emission changes may affect the aerosol levels in each of the parks, EPA estimated the effect that the changes in the island specific inventories for NOx and SO2 may have on the levels of nitrate and sulfate for each of the parks

. EPA projected visibility conditions in 2018 using the following assumptions:

1. Sea salt, Soil, Coarse mass, Organic Carbon, a nd Elemental Carbon are assumed to be constant for the 20% best days and 20% worst days for both the Haleakala and Hawaii

Volcanoes National Park s

.

2. Nitrate is projected based on the change (in percentage ) in the 2018 anthropogenic NOx inventory, compar ed to the 2005 inventory on each island

. Nonanthropogenic

emissions are assumed to be unchanged from the year 2005 inventory. Benefits from the

ECA in t ransit s hipping emissions are not considered in the projections

.

3. Sulfate for Haleakala National Park

. Sulfate visibility impact is projected based on the reductions in the 2018 anthropogenic S Ox inventory, compared to the 2005 inventory on the island of Maui. The anthropogenic visibility impact is assumed to be 33% of the total

for the Isla nd of Maui on the 20% worst days

, and 70% of the total on the 20% best days

. The FIP option projection is based on a 1400 ton per year reduction of SO2 on the Island

of Hawaii

. A lthough this reduction would likely reduce sulfate at Haleakala National

Park to some extent , this reduction is not reflected in the projections for 2018.

4 . Sulfate at Hawaii Volcanoes National Park

. Sulfate visibility impact is projected based on the percentage reductions in the 2018 anthropogenic SO 2 inventory, compared to the 2005 inventory on the island of Hawaii

. The anthropogenic visibility impact is assumed

to be 10% of the total on the Island of Hawaii on the 20% worst days and 70% of total on the 20% best days

. The FIP option assumed a 1400 ton per year reduction of SO2 on the

Island of Hawaii

. This reduction is reflected in the 2018 projections for the FIP option.

The visibility projections for 2018, based on these assumptions, are shown below.

Visibility Projection Results

The projected visibility (light extinction (b ext ) in Mm

- 1) in the year 2018 is shown in the
figures below

. At Hawaii Volcanoes National Park, the projected visibility for the year 2018

, without the emission reductions form the FIP, is slightly worse than the visibility for the year

2005

. With the e mission reductions from the FIP

, there is a slight improvement in visibility

conditions in the year 2018 compared to the year 2005 for both the 20% best and 20% worst
days

. At Haleakala National Park, there is a slight improvement in visibility conditions in the
year 2018 compared to the year 2005 for both the 20% best and 20% worst days.

Figure VII

- 3: Projected Visibility (light extinction, bext Mm

- 1) for Hawaii Volcanoes

National Park

– 20% best days.67

Figure VII

- 3: Projected Visibility (light extinction, bext Mm

- 1) for Hawaii Volcanoes

National Park

– 20% worst days.

Figure VII

- 4: Projected Visibility (light extinction, bext Mm

- 1) for Hawaii Volcanoes

National Park

– 20% worst days

– with revised axis to highlight changes from 2005 to 2018. 0 1 2 3 4 5 

### Hawaii Volcanos NP Estimate of Light Extinction (b ext 

### )


### Best 20% Days

2005 2018 2018

With FIP SeaSalt Extinction

CM Extinction

Soil Extinction

EC Extinction

OMC Extinction

Nitrate Extinction

Sulfate Extinction

0 20 40 60 80 100 

### Hawaii Volcanos NP Estimate of Light Extinction(b ext 

### )

Worst 20%



### 2005 2018 2018

With FIP SeaSalt Extinction

CM Extinction

Soil Extinction

EC Extinction

OMC Extinction

Nitrate Extinction

Sulfate Extinction68

Figure VII

- 5: Projected Visibility (light extinction, bext Mm

- 1) for Haleakala National

Park

– 20% best days. 80 85 90 95 

### Hawaii Volcanos NP Estimate of Light Extinction (b ext 

### )
Worst 20% Days

2005 2018 2018

With FIP
SeaSalt Extinction

CM Extinction

Soil Extinction

EC Extinction

OMC Extinction

Nitrate Extinction

Sulfate Extinction

0 1 2 3 4 5 

### Haleakala NP Estimate of Light Extinction (b ext 

### )
20% Best Days



### 2005 2018 2018

With FIP

SeaSalt Extinction

CM Extinction

Soil Extinction

EC Extinction

OMC Extinction

Nitrate Extinction69

Figure VII

- 6 : Projected Visibility (light extinction, bext Mm

- 1) for Haleakala National

Park

– 20% w orst days.

VII. F . Visibility Improvement Compared to URP and Number of Years to Reach Natural

Conditions

T he amount of improvement needed (Δ deciview) to meet the Uniform Rate of Progress

for 2018 for Haleakala National Park is 1.38 Δ deciview

. Based on the projections of visibility, discussed above, the amount of improvement by 2018 would be 0.2 5 Δ deciview. This would result in a 2018 level of visibility of 13.0 d eciview

. The amount of improvement needed (Δ deciview) to meet the Uniform Rate of Progress for 2018 for Hawaii National Park is 2.73 Δ

deciview

. Based on the projections of visibility, discussed above, the amount of improvement by
2018 would be 0.18 Δ dec iview. This would result in a 2018 level of visibility of 18.7 deciview. Based on the projections for 2018, discussed above, the URP w ill not be met at either

National Park. Because RPGs are not achieving URP by 2018 and natural conditions by 2064, EPA is required by the Regional Haze rule to re

- calculate and state the length of time necessary to achieve
natural conditions, as shown below

. EPA has calculated the number of years it would take to reach natural conditions, based on the rate of visibility im provement in this first planning period. Because the baseline conditions include the effect of the emissions from the volcano, the calculation of number of years to reach natural conditions may not represent a realistic scenario

in this case

. In addition, the visibility projections for 2018, discussed above, are based on very simplified assumptions

. Instead of achieving natural conditions in 2064 (60 years) at the two Class I areas, the year and the length of time is re

- calculated

. The rate of improvement at Haleakala is approximately

0.0 18 Δ deciview per year and t he needed improvement to reach natural conditions is 5.9

deciview

. Therefore, at this rate of improvement natural conditions would be met in approximately 300 years

. The rate of improvement at Ha waii Volcanoes National Park is 0.013 0 10 20 30 40 

### Haleakala NP Estimate of Light Extinction (b ext 

### )
20% Worst Days

2005 2018 2018

With FIP

SeaSalt Extinction

CM Extinction

Soil Extinction

EC Extinction

OMC Extinction

Nitrate Extinction70

Δ deciview per year , and t he needed improvement to reach natural conditions is 11.7 deciview

. Therefore, at this rate of improvement natural conditions would be met in approximately 900

years.



### VIII. Monitoring Strateg y

VIII.A. IMPROVE Monitoring Network

The Regional Haze SIP is to be accompanied by a strategy for monitoring regional haze visibility impairment. Specifically, the regional haze rule states at 40 CFR 51.308(d)(4):

“(4) Monitoring strategy and other implementation plan requirements. The State must submit with the implementation plan a monitoring strategy for measuring, characterizing, and reporting of regional haze visibility impairment that is representative of all mandatory Class I Federal

areas wit hin the State. This monitoring strategy must be coordinated with the monitoring strategy required in §51.305 for reasonably attributable visibility impairment. Compliance with this requirement may be met through participation in the IMPROVE network. The im plementation plan must also provide for the following:

(i) The establishment of any additional monitoring sites or equipment needed to assess whether reasonable progress goals to address regional haze for all mandatory Class I

Federal areas within the St ate are being achieved.

(ii)

- (vi) [Other implementation plan requirements that pertain to reporting and use of monitoring data and an emission inventory.]”

Such monitoring is intended to provide the data needed to satisfy four objectives:

1. Track t he expected visibility improvements resulting from emissions reductions

identified in this SIP

.

2. Better understand the atmospheric processes of importance to haze

3. Identify chemical species in the ambient particulate matter and relate them to

emiss ions from sources

4. Evaluate regional air quality models for haze and construct relative response factors for using those models

The primary monitoring network for regional haze, both nationwide and in Hawaii is the

IMPROVE network. Given that I MPROV E monitoring data from 2001

- 2004 serves as the baseline for the regional haze program, the future regional haze monitoring strategy must necessarily be based on, or directly comparable to, IMPROVE. The IMPROVE measurements71

provide the only long

- term record available for tracking visibility improvement or degradation and therefore EPA and Hawaii intend to rely on the IMPROVE network for complying with the regional haze monitoring requirement in the Regional Haze Rule

. Data produced by the IMPROVE monitoring network will be used nearly continuously for preparing the 5

- year progress reports and the 10

- year SIP revisions, each of which relies on analysis of the preceding five years of data. Consequently, the monitoring data from the

IMPROVE sites needs to be re adily accessible and to be kept up to date. Presumably, IMPROVE will continue to process information from its own measurements at about the same pace and with the same attention to quality as it has shown in the recent past. The VIEWS web site has been

mai ntained by the WRAP and the other Regional Planning Organizations to provide ready access to the IMPROVE data and data analysis tools.

T here are two IMPROVE monitoring sites currently operating in or near the Haleakala

National Park. T he Haleakala ( HALE1 ) IMPROVE monitoring site is located outside of the

Haleakala National Park and the Haleakala Crater ( HACR1 ) IMPROVE monitoring at the park‟s Western boundary

. In this proposal, EPA is using monitoring data from the HALE1 monitoring site, as the HACR1 site w as not yet in operation for the base year time period of 2000

- 2004

. Hawaii DOH has prepared two reports comparing data from the two sites

. The conclusions from these reports are summarized section II.D. 2. Analysis of the Haleakala (HAL E1) IMPROVE monitori ng site and newer Haleakala Crater (HACR1) Monitoring site,

below

. The reports conclude that, based on t he available data , the HACR1 IMPROVE monitoring site is more representative of visibility conditions within the Haleakala National Park

than the HALE1 I MPROVE monitoring site.

VIII.B. Analysis of the Haleakala (HALE1) IMPROVE monitor ing site and newer Haleakala Crater (HACR1) Monitoring site

Currently there are two IMPROVE monitoring sites operating in or near the Haleakala

National Park. T he Haleakala ( HALE1 ) IMPROVE monitoring site is located outside of the

Haleakala National Park nea r to the Maui Central Valley, at an elevation of 1153 meters. The

HALE 1 IMPROVE monitoring site began operation at end of 2000 , and will close in May 2012.

The Haleakala Crater ( HACR1 ) IMPROVE monitoring site is at the park‟s Western boundary , at
an elevation of 2158 meters. The HA CR1 IMPROVE monitoring site began operation in 2007

. In this proposal, EPA is using monitoring data from the HALE1 monitoring site, as the HACR1 site was not yet in operation for the base year time period of 2000

- 2004

.72

Figure VIII

- A: HALE and HACR Monitoring Locations

Hawaii DOH has prepared two reports comparing the two IMPROVE monitoring sites at

Haleakala National Park 62 , includin g a detailed comparison of organic and elemental carbon data

at the two sites. 63 The reports find that t he most significant difference between data measured at the two sites appears to be that HALE1 site has higher levels of organic and elemental carbon

. T he levels of the other species are generally lower at the HACR1 IMPROVE moni toring site than at the

HALE1 monitoring site

. The reports conclude that, based on t he available data , the HACR1 IMPROVE monitoring site is more representative of visibility condit ions within the Haleakala

National Park than the HALE1 IMPROVE monitoring site.

62 Comparison of Haleakala National Park HALE1 and HACR1 IMPROVE Monito ring Site 2007

- 2008 Data Sets, March 30, 2012, State of Hawaii, Department of Health, Clean Ai r Branch

63 Review of VIEWS2.0 2009

- 2010 Haleakala National Park Organic and Elemental Carbon Data, March 30, 2012, State of Hawaii, Department of Health, Clean Air Branch, and Comparison of Haleakala National Park HALE1 and HACR1 IMPROVE Monitoring Site 20 07

- 2008 Data Sets, March 30, 2012, State of Hawaii, Department of Health, Clean Air Branch73

Background Information on the Haleakala HALE1 IMPROVE Site 64

HALE1 is located at an elevation of 1,158 m (3,799 ft) on the northward slope of Haleakala, ~5.7 km northwest of the Park Boundary

. In general, aerosol measurements at HALE1 should be representative of ambient concentrations at National Park locations at the same elevation. However, the extreme climate variability over the range of elevation and exposure in the Natio nal Park compels caution in aerosol source attribution, especially with the sensitivity of particle size to moisture. Rainfall gradients in Hawaii are among the steepest in the world. The HALE1 site has exposure to northeasterly trade winds and may be more susceptible to rain caused by orographic lifting than are most National Park areas on the leeward side. Being at an elevation that is lower than the typical Marine Boundary Layer height most of the time, the HALE1 IMPROVE site may frequently be more repre sentative of aerosols near the surface with different back trajectories than those of upper air aerosols transported from distant global scale source regions by upper level winds.

Hawaii DOH Comparison of the Haleakala (HALE1) and Haleakala Crater (HACR1 ) IMPROVE Monitoring Sites

- Summary

Hawaii DOH examined the 2007

- 2008 IMPROVE Data from the HACR1, HALE1, and HAVO1 monitoring sites using the EPA Positive Matrix Factorization (PMF) 3.0 code. The monitoring data from each site was analyzed separately

. The focus of the Hawaii DOH document

was the correspondence between monitored values at the HACR1 and HALE1 site.

For the 7 visibility impacting mass concentrations (e.g. Ammonium Sulfate), the mean HALE1 values are typically about a factor of two larger than for HACR1. The exception to this is Fine Soil, which is approximately equal. This approximate equivalence in Fine Soil measurements appears consistent with long

- range transport of dust (e.g. Asian Dust). The most significant difference between mean da ta measured at the two sites appears to be that HALE1 is impacted more by organic and elemental carbon associated with the Positive Matrix Factorization Smoke factor. This appears to be consistent with the relatively close proximity and

location of the HAL E1 monitor with respect to agricultural burning in the Central Valley of

Maui. For HACR1, the largest organic carbon and elemental carbon IMPROVE measurements occurred in late January 2007. The character of the organic carbon and elemental carbon time

his tories for HACR1 appear significantly different than for those of HALE1. The HACR1 measurements show a few very large mass concentrations in January and April 2007 followed by much lower values throughout the rest of 2007 and 2008. The HALE1 measurements, while showing variability, do not have such large outliers. While the average HACR1 mass concentrations for organic carbon and elemental carbon are approximately 50% of those for HALE1, the maximum HACR1 organic carbon mass concentration is approximately 6 00% the HALE1 value and the maximum HACR1 elemental carbon mass concentration is approximately

300% the HALE1.

The HACR1 IMPROVE measurement s appear consistent with a 2291 acre forest fire in Census Tract 303 that was also produced numerous MODIS detection s. The second largest organic carbon and elemental carbon IMPROVE measurements at HACR1 occurred in early April 2007. These measurements appear consistent with a HC&S field burns that was also

64 http://www.coha.dri.edu/web/state_analysis/Hawaii/HaleakalaNP_metdesc.html74

produced 2 MODIS detections. While the details of why HACR1 was impacted significantly more than HALE1 for these two isolated cases during 2007 and 2008 would require a more extensive examination of the winds patterns for those days, the available data seems sufficient to

conclude that these few measurements are not r epresentative of HACR1 measurements. The remaining HACR1 and HALE1 monitoring measurements appear consistent with the general observation that HACR1 IMPROVE monitoring values are generally much lower than

those at HALE1. The available data indicates that HACR1 IMPROVE monitoring data is more representative of visibility conditions within the Haleakala National Park.75

Appendix A

Subject

- to

- Best Available Retrofit Technology (BART) Modeling for the State of Hawaii, Application of the CALPUFF Modeling Sys tem

Prepared for Hawaii State Department of Health, Environmental Management Division Clean Air Branch by Alpine Geophysics, LLC

. March 3, 2010.76

Appendix B

MM5 Application for 2005 Over the Hawaiian Islands, Prepared fo r Hawaii State Department of Health, Environmental Management Division, Clean

Air Branch by Alpine Geophysics, LLC , October 31, 2008