1 

# Alaska Department of Environmental Conservation



# Amendments to:

State Air Quality Control Plan

Vol. III: Appendices (to Vol. II, Section III. D.3 )



# Adopted

February 20, 2009Adopted February 20, 2009 2 

### Volume III, Appendices, of the State Air Quality Control Plan is amended to include additional documents based on amendments to Volume II, Section III. D.3 of that plan. In particular, Appendix III. D.3.5, III.D.3.8, and III. D

. 3.9 are proposed to be amended by adding the

documents listed below (refer to Appendix III D.3.5 for complete ordinance language ) :

Appendix III. D.3.5

City & Borough of Juneau Ordinances:

#83

- 63

– “ An Ordinance Regulati ng Open Burning and the Use of Wood

- Fired Heating

Devices in Smoke Hazard Areas ”

#88

- 59

– “ An Ordinance Amending the Woodsmoke Control Code to Implement a New Measurement System for Measuring Air Pollution, to Adopt Federal Standards

for the Issuance of Cl ass I Permits for NonCatalytic Solid Fuel

- Fired Heating Devices, and to Delete References to Oregon State Woodstove Standards. ”

#91

- 52

– “ An Ordinance Amending the Woodsmoke Control Code to Lower the Particulate Count Threshold for Declaring Air Alerts, to Authorize the Manager to Declare an Air Alert According to Certain Qualitative Criteria, to Provide for the Expiration of All Existing Class I Permits on July 1, 1997, to Terminate the Manager’s Authority to Issue New Class I Permits, and to Prohibit the Burning

in Woodstoves of Substances Other Than Paper, Cardboard, and Untreated

Wood. ”

#91

- 53

– “ An Ordinance Amending the Woodsmoke Control Fine Schedule to Increase

the Fines for Violations of the Woodsmoke Control Code. ”

#93

- 01

– Ordinance on Local Improvement Districts

#93

- 06

– An Ordinance Creating Local Improvement District No. 76 of the City and Borough....

#2008

- 2 8

- “ An Ordinance Amending the Woodsmoke Control Program Regarding Solid

Fuel

- Fired Burning Devices”. This ordin ance has been incorporat ed into City & Borough of Juneau C ode at Title 36.40.040 “Air pollution alert and emergencies”.

Fiscal Year 1994 CP

- 1s

City & Borough of Juneau Resolution # 1612

Memorandum of Understanding between ADEC, ADOT/PF, and CBJ

– 1992/1993

City & Borough of Juneau Resolution #2448

- With this resolution, the City & Borough of Juneau approved the draft PM10 Limited Maintenance Plan, dated May 10, 2007. Resolution approved August 11, 2008.

Appendix III. D.3.8

Mendenhall Valley PM 10 

### Emission Invent ory, January 2006

Appendix III.D.3.9

EPA Region 10 Analysis of PM 10 

### Design Value

# Alaska Department of Environmental Conservation



# Amendments to:

State Air Quality Control Plan

Vol. III: Appendices

Appendix III.D.3.5



# Adopted February 20, 2009Presented by: The Manager

Introduced: 0811 1/2008

Drafted by: J.W. Hartle



### RESOLUTION 

### OF THE 

### CITY AND BOROUGH 

### OF JUNEAU, ALASKA

Serial 

### No. 2448

A Resolution Regarding the Alaska Department of Environmental Conservation’s Mendenhall Valley Ambient 

### Air Quality Standards.

WHEREAS, the Juneau Mendenhall Valley has not violated the 24-hour 

### I’Mlo ambient air quality standard since 1994 and can now develop a Limited Maintenance

Plan (LMP) which would be incorporated into Alaska’s State Implementation Plan (SIP) according to the Alaska Department of Environmental Conservation 

### (ADEC); and

WHEREAS, the ADEC has prepared the Mendenhall Valley PM,, Limited Maintenance Plan, and requests that the Assembly indicate concurrence with the air quality plan by resolution; and

WHEREAS, the resolution and the 

### LMP will be submitted to the Environmental

Protection Agency 

### (EI’A) with a request from 

### ADEC to redesignate the Juneau Mendenhall Valley from nonattainment to attainment for the 

## I”,, national ambient air quality standard; and

WHEREAS, the Alaska Department of Environmental Conservation, Division of Ar Quality, has determined that the cJuneau Mendenhall Valley has met the criteria to qualify for the Limited Maintenance Plan option; and

WHEREAS, the Lands Committee at its July 7, 2008 meeting, recommended this

rcsolution be forwarded to the Assembly for approval.

NOW, 7‘HEIlEFORE, HE IT 

### RESOJ,VED BY THE ASSEMBLY OF THE CITY ANI) BOROUGH

OF ,JUNEAU, ALASKA:

Section 1. That the Assembly approvcs Juneau’s Mendenhall Valley Proposed 

## PM,, Limited Maintenance Plan, drafted by the Alaska Department of Environmental Conservation, dated May 10, 2007.Section 2. Effective Date. This resolution shall be effective immediately upon adoption.

Adopted this llth day of August, 2008.

Bruce 

### Botelho, Mayor

Attest: c-- fl.

-2- Res. 2448

# Alaska Department of Environmental Conservation



# Amendments to:

State Air Quality Control Plan

Vol. III: Appendices

Appendix III.D.3.8



# Adopted February 20, 2009

# DRAFT



# Mendenhall Valley PM 10 

# Emission Inventory

prepared for:



## Alaska Department of Environmental

Conservation

January 6, 2006

prepared by:

Sierra Research, Inc.

1801 J Street Sacramento, California 95814 (916) 444-6666

### DRAFT REPORT



### MENDENHALL VALLEY PM 10 

### EMISSION INVENTORY

prepared for:

Alaska Department of En vironmental Conservation

January 6, 2006

Principal authors:

Robert G. Dulla

Lori Williams Siona Delaney

Sierra Research, Inc.

1801 J Street Sacramento, CA 95814 (916) 444-6666

### -i

### MENDENHALL VALLEY PM 10 

### EMISSION INVENTORY

Table of Contents

Page

Executive Summary..............................................................................................ES-1

1. Introduction................................................................................................................ .1 1.1 Background........................................................................................................1 1.2 Approach............................................................................................................2 1.3 Organization.......................................................................................................2

2. On-Road..................................................................................................................... .3 2.1 Modeling Parameters .........................................................................................3 2.2 Juneau Travel Activity.......................................................................................7

2.3 PM 10 

### Inventory Results....................................................................................10

3. Nonroad..................................................................................................................... 12 3.1 Calculation Methodology.................................................................................12

3.2 Modifications to EPA’s NONROAD M odel Default Equipment Population and Activity Factors.........................................................................................13

3.3 Emission Estimates ..........................................................................................16

4. Area........................................................................................................................ ...20

4.1 Residential Fuel Use ........................................................................................20

4.2 Other Area Sources..........................................................................................26 4.3 Fugitive Dust....................................................................................................28

4.4 PM 10 

### Area Source Inventory............................................................................34

5. Point ...................................................................................................................... ....35

6. Refere nces.................................................................................................................3 6

Appendix A – Inventory Preparation Plan Appendix B – Demographic Estimates for City and Borough of Juneau, Mendenhall Valley Appendix C – On-Road Source Calculations Appendix D – Nonroad S ource Calculations Appendix E – Area Source Calculations

### -iiList of Tables

Page

ES-1 Summary of Mendenhall Valley PM 10 

### Emissions by Season and Source Category..........................................................................................ES-2 2-1 Seasonal Ambient Temperature in Juneau...............................................................4

2-2 Seasonal VMT Distribu tion by Vehicle Class.........................................................5 2-3 Mendenhall Valley Gasoline and Diesel Fuel Characteristics.................................6 2-4 VMT and Speeds by Facility Type for Mendenhall Valley.....................................6 2-5 Available Roadway Data fo r Mendenhall Valley by Source...................................8 2-6 Available Roadway Data for Mendenhall Valley by Facility..................................8 2-7 Mendenhall Valley P opulation Estimates................................................................9 2-8 Mendenhall Valley Aver age Travel Estimates ......................................................10 2-9 2004 Mendenhall Valley Seasonal On-Road PM 10 

### Emissions in Tons/Day .........10 2-10 2018 Mendenhall Valley Seasonal On-Road PM 10 

### Emissions in Tons/Day .........11 3-1 Fraction of Households in City and Borough of Juneau vs. Mendenhall Valley

Nonattainment Area...............................................................................................13

3-2 2004 and 2018 Nonroad PM 10 

### Emissions..............................................................17 3-3 2004 Mendenhall Valley Nonattainment Area Nonroad Source Emissions -

Summer..................................................................................................................17 3-4 2004 Mendenhall Valley N onattainment Area Nonroad Source Emissions -

Winter ....................................................................................................................18 3-5 2018 Mendenhall Valley N onattainment Area Nonroad Source Emissions -

Summer..................................................................................................................18 3-6 2018 Mendenhall Valley Nonattainment Area Nonroad Source Emissions -

Winter ....................................................................................................................19 4-1 Summary of Heating Degr ee Days for J uneau, Alaska .........................................21 4-2 Allocation of Survey Fuel Use to Summer & Winter Seasons..............................22

4-3 PM 10 

### Emission Estimates for Residential Heating, Mendenhall Valley in 2004 ..25

4-4 PM 10 

### Emission Estimates for Residential Heating, Mendenhall Valley in 2018 ..25

4-5 PM 10 

### Emissions from Burn Barrels in the Mendenhall Valley .............................28 4-6 Seasonal Paved Roads Silt Loading by Facility Type ...........................................30 4-7 Mendenhall Valley Annual Av erage VMT/Day by Facility..................................31 4-8 Mendenhall Valley Unpaved Road VMT and Data Sources.................................32

4-9 2004 and 2018 Mendenha ll Valley Paved Road VMT by Facility........................33 4-10 Seasonal Road Fugitive Dust Emissions in Mendenhall Valley............................33

4-11 2004 and 2018 PM 10 

### Area Source Emissions for the Mendenhall Valley

Nonattainment Area...............................................................................................34 5-1 Mendenhall Valley Point Source Summary, Asphalt Batch Plant.........................35

### ES-1 

### EXECUTIVE SUMMARY

The Mendenhall Valley (Valley) is currently classified as a moderate PM 10 

### nonattainment area. Despite this classification, no exceed ances of either the annual or the 24-hour standard have been recorded in more than a decade (based on a review of EPA monitoring data between 1994 and 2004). 1 

### This is the result of planning and implementation efforts by both the state De partment of Envir onmental Conservation (DEC) and the City and Borough of Juneau (CBJ). Those efforts, documented in a 1993 State Implementation Plan (SIP) submission, 2 

### identified the following key emission

sources:

• Smoke from residential wood combustion (home heating);

• Fugitive dust from travel on unpaved roads; and

• Fugitive dust from travel on paved roads.

To reduce emissions from these sources, th e SIP implemented a wood smoke control program and a fugitive dust abatement progra m. Elements of the wood smoke control program included an aggressive public education program; implementation of a real-time monitoring system linked to episodic controls of wood burning; prohibition of open burning (during winter months); new stove certification requireme nts; and enforcement of the CBJ woodsmoke ordinance. The fugitive dust abatement program focused on paving unpaved roads in the Valley. No e mission inventories have been developed to track the impact of these programs since the SIP was prepared in 1993.

To document the status of the control progra ms and to provide a basis for developing a Maintenance Plan and redesign ation request, the Alaska De partment of Environmental Conservation (ADEC) commissi oned the development of a base and horizon year (2004 and 2018) PM 10 

### emission inventory for the Valley. A summary of the updated inventory for these years is presented in Table ES-1. It shows that fugitive dust from traffic operating on paved roads is the dominant source of PM 10 

### emissions as it is estimated to account for 83% of the inventory in 2004 and 84% of the inventory in 2018. This is a sharp contrast with the 46% share estimated in the last emission inventory prepared for calendar year 1988. The increase reflects the success of the locally implemented control programs and changes in emission factors availa ble to quantify the emissions of different source categories. It does not reflect a huge increase in traffic, as the growth rate in Juneau is very modest at an annualiz ed rate of less than 1% per year.

### ES-2 Table ES-1 Summary of Mendenhall Valley PM 10 

### Emissions By Season and Source Category (tons/day)
Source Category Calendar Year 2004 Calendar Year 2018

Winter PM 10 

### Emissions

On-Road 0.022 0.011

Non-Road 0.027 0.012

Area

Residential – Wood 0.091 0.099

Residential – Pellet 0.006 0.007

Residential – Oil 0.002 0.002

Residential Burn Barrels 0.000 0.000 Paved Road Fugitive Dust 1.478 1.612 Unpaved Road Fugitive Dust 0.161 0.176

Other Area Sources 0.182 0.181

Area Subtotal 1.920 2.077

Point 0.000 0.000

Total All Sources 1.969 2.100

Summer PM 10 

### Emissions

On-Road 0.021 0.011

Non-Road 0.049 0.021

Area

Residential – Wood 0.031 0.034

Residential – Pellet 0.002 0.002

Residential – Oil 0.001 0.001

Residential Burn Barrels 0.057 0.062 Paved Road Fugitive Dust 4.135 4.510 Unpaved Road Fugitive Dust 0.190 0.207

Other Area Sources 0.182 0.183

Area Subtotal 4.598 4.999

Point 0.155 0.155

Total All Sources 4.823 5.186
Annual Average 3.400 3.647

In the 1988, fugitive dust from unpaved roads was estimated to account for 40% of the overall inventory. In 2004, that share declin ed to 5.2% and is projected to be 5.3% in 2018. The projected level of emissions from unpaved roads in 2018 is based on the conservative assumption that all unpaved roads in the Mendenhall Valley in 2004 would remain unpaved in 2018. Efforts by CBJ and the State to continue to pave sections of unpaved roads in the Valley would reduce the emission contributions of unpaved roads in

the future.

### ES-3 PM 10 

### emissions from wood burning (both fireplaces and stoves) were estimated to

account for almost 9% of the annual inventor y in 1988. In 2004, that share declined to less than 2% and is projecte d to remain at roughly that level in 2018. Based on the results of an extensive survey of homeown ers conducted in 2004, it is estimated that the combination of new technology, related sh ifts in wood use, a nd implementation of control measures reduced wood burning by 85% from 1993 to 2004.

Other trends of note are that emissions from both the on-road and non-road source categories represent a trivial portion of the overa ll inventory and that they are projected to decline despite the increase in activity proj ected to occur between 2004 and 2018. This is the result of replacing older, higher-emitting vehicles/equipment populations with newer, lower-emitting populations and fe deral requirements for cleaner fuels (lower sulfur gasoline and Diesel fuel).

According to ADEC, there is only one permitted source located in the Valley and its operations are limited to 5 months per year.

Overall, the inventory is es timated to have declined by almost 30% between 1993 and

2004.

###

### -1- 

### 1. INTRODUCTION

1.1 Background

The Mendenhall Valley, located nine miles from downtown Juneau, is the largest residential area in the region. Bounded by sh arply rising mountains on the east and west and the Mendenhall Glacier to the north, the valley is well sheltered from prevailing winds. This topography, combined with a low winter sun angle that limits solar heating, supports the development of re latively severe temperature i nversions. These inversions trap emissions close to the valley floor and in the past led to seve re concentrations of airborne particulate matter that exceeded state and federal ambient air quality standards

for PM 10



### .

The Mendenhall Valley is currently classified as a moderate PM 10 

### nonattainment area. Despite this classification, no exceedances of either the annual or the 24-hour standard have been recorded in more than a decade (based on a review of EPA monitoring data between 1994 and 2004). 1 

### This is the result of planni ng and implementation efforts by both DEC and the City and Borough of Juneau (CBJ). Those efforts, documented in a 1993 State Implementation Plan (SIP) submission, 3 

### identified the following key emission

sources:

• Smoke from residential wood combustion (home heating);

• Fugitive dust from travel on unpaved roads; and

• Fugitive dust from travel on paved roads.

To reduce emissions from these sources, th e SIP implemented a wood smoke control program and a fugitive dust abatement progra m. Elements of the wood smoke control program included an aggressive public education program; implementation of a real-time monitoring system linked to episodic controls of wood burning; prohibition of open burning (during winter months); new stove certification requireme nts; and enforcement of the CBJ woodsmoke ordinance. The fugitive dust abatement program focused on paving unpaved roads in the Valley. Both programs have been successful and led to significant reductions in key emission sources within the Valley. Recent work by Sierra, 4



### under contract to ADEC, indicates the intr oduction of new technology has also had a significant impact on home heating emissions. We estimate that collectively the combination of new technology, related sh ifts in wood use, a nd implementation of

control measures has reduced PM 10 

### emissions by 85% from 1993 to 2004. Key contributors to these reductions include the following:

• Initiatives (e.g., burn bans, public edu cation, new stove requirements, etc.) implemented under the Juneau wood smoke control program;

### -2- • A drop in wood use per household from 1.8 cords per heating season in 1993 to 1.1 cords in 2004;

• Widespread use of direct vent type fuel oil heaters; and

• Reductions in emission factors for both fuel oil and wood burning.



### 1.2 Approach

Sierra followed the source-specific data collection and modeling procedures detailed in the EPA emission inventory guidance document “PM-10 Emission Inventory Requirements,” Final Report, September 1994. As noted above, key emission sources identified in the previous inventory were smoke from residential wood combustion and fugitive dust from both paved and unpaved roads. Given the significance of these sources and the efforts placed on controlling their emissions, effort was focused on collecting new data to characterize activity levels for each of these sources. The home heating survey conducted last year provide s detailed insight into the impact of both technology changes and related activity leve ls on residential heating emissions. No similar survey has been conducted to support an update of fugitive dust from paved and unpaved roads.

In order to prepare an accurate update to these source categories, Sierra contacted state (Alaska Department of Transportation and Public Facilities, or ADOT&PF) and local CBJ agencies to obtain data on the mileage of paved/unpaved roads in the Valley and

recent traffic counts and rela ted speed estimates. Aside from these activity estimates, another key element of fugitive dust calculations is the silt content of the roads. A review of the last emission inventory prepared for the Valley 5 

### shows that silt loadings were collected locally to support the preparati on of fugitive dust emissions for unpaved roads and that national average silt loadings were used to estimate on-road levels. Since no controls have been targeted at controlling silt loadings for unpaved roads, Sierra sees no need to update those estimates. However, c ontrols have been targeted at reducing the mileage of unpaved roads and a corollary benef it of these controls should be a reduction of silt loadings (i.e., and fugitive dust) on pa ved roads. For this reason, we developed a protocol to collect silt loadings for a representative sample of paved roads (samples will be distributed across both road type and tra ffic volume) and use the results along with recent traffic counts to support an update of fugitive dust emitted from this source category. A description of the methodology to be used on collecting the silt samples is presented in Appendix A.



### 1.3 Organization

The remainder of this report is organized to document the activity data, emission factors and emission estimates for each of the prima ry source categories: on-road, nonroad, area and point sources. The appendices include a copy of the Inventory Preparation and Quality Assurance Plan, Demographic For ecasts, and documentation of the emission calculations for each of the source categories.

###

### -3- 

### 2. ON-ROAD SOURCES

The calendar year 2004 and 2018 PM 10 

### on-road mobile source inventories were prepared for Mendenhall Valley using EPA’s latest vehicle emission factor model, MOBILE6. *


### The model estimates the following PM 10 

### pollutants from on-road motor vehicles:

• Sulfate (SO 4 

### );

• Organic Carbon (OC) portion of Diesel exhaust particulate;

• Elemental Carbon (EC) portion of Diesel exhaust particulate;

• Total carbon (GASPM) portion of ga soline exhaust particulate;

• Lead (Pb) portion of exhaust particulate; †



### • Brake-wear particulate emissions; and

• Tire-wear particulate emissions.

Separate inventories were prepared for winter (October to March) and summer (April to September) of each year, with corresponding modeling runs for each season. The MOBILE6 model inputs were customized to re flect the local traffic, fuel, and ambient characteristics as much as possible. The MOBILE6 model inputs and associated files are shown in Appendix A, and a discussion of the modeling procedures and results follows.



### 2.1 Modeling Parameters

The parameters needed for modeling on-road PM 10 

### emissions from Mendenhall Valley using MOBILE6 were compiled by contacting local and state agencies and reviewing

historical data on ambient c onditions and local vehicle activity. There are a number of inputs that can be specified by the user to tailor a standard MOBILE6 run for a local area,

and these are discussed below.

Temperature Data – Temperature data were compiled from www.weatherbase.com, which is a website that records historical climatological data for cities all over the world. The monthly average highs and lows for Juneau for the more than 40 years on record in

the website database were obtained. The av erage highs and lows for summer (April to September) and winter (October to March) were estimated and are shown in Table 2-1.

* MOBILE6 version 6.2.03 dated September 24, 2003.

† Lead emissions are basically zero since Pb has been eliminated from gasoline fuels.

### -4- Table 2-1 Seasonal Ambient Temp erature in Juneau(oF) Season Low High

Summer 42.3 57.7

Winter 25.7 36.3

Registration Distribution – June 2000 Department of Mo tor Vehicle (DMV) registration data were used to estimate the vehicle age distribution for light-duty cars and trucks, which make up the majority of traffic in the Juneau area. However, the registration data were found to contain records for very old vehicles that are chronically unregistered (registration is not continuous over the last fe w years). These vehicles are not operated on a regular basis and tend to bias the regi stration fraction towards vehicles that are 25 years old and older—the oldest model year grouping in MOBILE6. Because of this, the light-duty vehicle registration fractions used for vehicles 25 years old and older were

derived from the MOBILE6 default fractions instead of from the 2000 DMV registration data. The DMV registration fractions fo r the newer light-duty vehicles were

renormalized in order to accommodate the default fractions in MOBILE6 for the oldest model year grouping. The MOBILE6 default registration fractions were used for the

other vehicle classes in Juneau. Because no data are available to adjust the DMV registration data to reflect seasonal shifts in fleet mix, only one set of registration fractions was used for the Mendenhall Valley ru ns for the summer and winter seasons. In addition, it was assumed that the registra tion distribution used applies to the 2018 forecasted scenario as well. Appendix A shows the registration distribution used as model input in MOBILE6 for the model runs.

Mileage Accumulation Rates – Local data to estimate mileage accrual rates for Juneau were not available; therefore, the national average default rates in MOBILE6 were used

for 2004 and 2018.

VMT by Vehicle Class – No local data were available to characterize the VMT by vehicle class; therefore the “default” MOBILE6 VMT fractions were used for modeling Mendenhall Valley. MOBILE6 calculates the “default” VMT distribution from national average and/or user-supplied local data fo r the registration distribution by age, registration distribution by vehicle class, mileage accrual rates, Diesel fractions, and the calendar year given in the model run. Theref ore, for the model runs, the “default” VMT distribution is partly based on the local 2000 DMV registration data used in developing the registration distribution by age for the area. The resulting 2004 and 2018 VMT fractions used for the Mendenhall Valley are s hown in Table 2-2. The fractions for the

different vehicle classes sum to 1.000 for each season. Although the summer and winter model runs for the Valley used the same re gistration distribution by vehicle age, the resulting VMT fractions differ slightly within each calendar year because MOBILE6 ages the default fleet population by six months fo r the summer runs, which adjusts the model default annual mileage and aver age accumulation rates by vehicle age and affects the

calculated “default” VMT fractions in the model.

### -5- Table 2-2

Seasonal VMT Distributi ons by Vehicle Class

Calendar Year 2004 Calendar Year 2018 Vehicle Class Winter Summer Winter Summer

LDV 0.4463 0.4404 0.2986 0.2972

LDT1 0.0699 0.0705 0.0937 0.0936

LDT2 0.2321 0.2342 0.3121 0.3117

LDT3 0.0793 0.0801 0.1066 0.1066

LDT4 0.0369 0.0373 0.0496 0.0496

HDV2B 0.0417 0.0423 0.0429 0.0435

HDV3 0.0041 0.0041 0.0042 0.0043

HDV4 0.0033 0.0033 0.0035 0.0036

HDV5 0.0025 0.0025 0.0026 0.0027

HDV6 0.0093 0.0094 0.0097 0.0098

HDV7 0.0109 0.0111 0.0114 0.0115

HDV8A 0.0119 0.0121 0.0123 0.0125

HDV8B 0.0425 0.0431 0.0438 0.0444

HDBS 0.0017 0.0017 0.002 0.0021

HDBT 0.0014 0.0014 0.0011 0.0012

MC 0.0062 0.0063 0.0056 0.0057

Fuel Parameters – The fuel parameters that affect PM 10 

### emissions, gasoline, and Diesel

fuel sulfur content were customized to reflect the seasonal fuel properties in the Mendenhall Valley. The 2004 average fuel parameters were obtained from the 2004 Alliance of Automobile Manufacturers’ (AAM) summer and winter fuel survey data. The Mendenhall fuel propertie s were based on fuel from Seattle, Washington, which is shipped into Juneau.

For 2018, gasoline fuel sulfur levels are assu med to fall within the requirements of the Tier 2 Gasoline Sulfur Rule, which in Alaska are currently required to be phased-in in

2007. The Diesel fuel sulfur in 2018 is assu med to follow the requirements of the EPA Low-Sulfur Diesel Rule, which takes effect in 2006. Although Alaska has been given the option by EPA to design an alternative low-sulfur transition plan to ease the hardships of converting both gasoline and Diesel to low sulfur within a relatively short time frame, it is assumed that the provisions of both the gasoline and Diesel low-sulfur rules are completely satisfied by 2018. Table 2-3 summa rizes the characteristics of the fuel used for the Juneau area during the winter and summer of 2004 and 2018. The gasoline Reid vapor pressures (RVPs) used in the model runs are shown in Table 2-3 since it is a required input into MOBILE6; ho wever, RVP does not affect PM 10 

### levels from vehicles.

### -6- Table 2-3 Mendenhall Valley Gasoline and Diesel Fuel Characteristics

Calendar Year 2004 Calendar Year 2018 Fuel Parameter Winter Summer Winter Summer
Gasoline RVP (psi) 13.6 7.8 13.6 7.8 Gasoline Avg Sulfur (ppm) 90 60 30 30 Gasoline Max Sulfur (ppm) 140 150 80 80 Diesel Avg Sulfur (ppm) 380 380 15 15

Other Modeling Considerations – For the MOBILE6 modeling of on-road vehicle emissions in Alaska, off-cycle effects or the Supplemental Fede ral Test Procedure (SFTP) Bag 4-equivalent were disabled during the winter r uns. This was done because the aggressive driving represented by these effects is not observed with winter road conditions. In addition, the Valley wa s modeled as a low-altitude area.

Facility Types and Average Vehicle Speeds – The average daily VMT data for 2004 for the Mendenhall Valley were estimated as a function of average vehicle speeds, which were then used as inputs to the MOBILE6 m odel. In order to do this, the 2004 VMT and average speed estimates by facility were developed using local traffic data. Table 4 lists the VMT distribution and average speeds modeled by facility type for the Mendenhall Valley. No seasonal data were available to adjust any changes in VMT (i.e., possible VMT reduction in the winter), and the same average annual daily VMT by facility was

used for both the summer and winter seasons as a conservative approach. MOBILE6

scenarios were created to result in PM 10 

### emission factors for each combination of speed and facility type shown in Table 2-4 for the calendar years considered in the study (2004 and 2018). The detailed development of the facility VMT and speed data for the Mendenhall Valley is discussed in detail in the following section.

Table 2-4 VMT and Speeds by Facility Type for Mendenhall Valley

Facility Type Avg Speed (mph) 2004 VMT/day % of Total

VMT

Urban Collector 35.6 58,370 19%

Urban Minor Arterial 37.2 39,585 13% Urban Principal Arterial 50.5 63,278 21%

Local Road 20.8 141,367 47%

ALL TOTAL 302,599 100%

### -7- 

### 2.2 Juneau Travel Activity

Once the input parameters were compiled and model runs were comp leted, the resulting

PM 10 

### emissions factors for each combination of facility type and average speed were combined with the local estimates of VMT in order to generate an emissions inventory. For the Mendenhall Valley, the 2004 VMT and average speed estimates by facility had to be developed by extrapolating average daily travel and speed data on Alaska Department of Transportation and Public Facilities (DOT&PF) monitored roadways to the rest of the roadways in the Valley. After this, the 2004 VMT estimates were forecasted to 2018 levels using yearly population data for the area. The data sources and analysis involved in this procedure are presented below.

Traffic Data Sources – The VMT and average speed by facility for the Mendenhall Valley were developed from traffic databa ses for monitored roadways and roadway mileage data obtained from DOT&PF and from the County and Borough of Juneau (CBJ). 6,7 

### The following four sources of roadway data were used in generating the most complete picture of on-road tr avel in the nonattainment area:

• The current DOT&PF routelist for Southeastern Alaska (2004 routelist), which includes Coordinated Data System (CDS ) route numbers, route or roadway descriptions, mile points, functional class definitions or facility types, averagedaily traffic (ADT), length in miles, and the segment VMT for DOT&PFmanaged roadway segments;

• A current DOT&PF record of routes with limited posted speed limit information for Southeastern Alaska (2004 speed list * 

### ) with CDS route number, mile points, roadway length in miles, and facility type;

• The current CBJ street inventory database , which lists the CBJ-managed streets, location within the borough, lengths, and surface description, but no traffic activity data; and

• The 1999 Juneau travel activity estimates de veloped by Sierra Research for the 1999 criteria pollutant inventory for Juneau (1999 routelist), which list CDS route numbers, mile points, lengths, facility types, and speeds for all routes on record

for Juneau in 1999. †



### Mendenhall Valley Roadway Inventory – In order to develop the average travel characteristics for the Valley, roadway segments located outside of the nonattainment area boundary were eliminated from the 2004 rout elist and speed list. This was done based on the route descriptions, comparisons with area street maps, and the routes included in the 1999 routelist, which was alread y cleaned up during a previous analysis to include only roadways in the Borough of Juneau. This exercise showed that the 2004 routelist, 2004 speed list, and 1999 routelis t do not map completely to each other

* Although this database is referred to as the “speed” list, only 66 of the 558 roadway segments in the complete database had speed limit data, and none of the segments with speed data are in the Mendenhall Valley nonattainment area.

† The 1999 Juneau travel activity estimates were developed following the same procedure outlined here using DOT&PF traffic data from 1999 for the roadways monitored at the time.

### -8- (beginning and ending mile points vary by roadway), and that various roadway segments

were included in one source and not another. Therefore, a combined list of all roads in the Valley was created.

After eliminating the roadways outside the nonattainment area boundary in all the data sets, the 2004 routelist was used as the basis for creating the combined list of roadways for the Mendenhall Valley. First, the 2004 routelist was compared to the 2004 speed list, and segments missing from the former were added from the speed list in order to create a current list of roadways in the Valley—most with ADT data, and some with speed limit data. The resulting roadway listing was th en compared to the 1999 routelist, and roadway segments found in the 1999 routelist that were not included in the 2004 lists of

monitored routes within the nonattainment area were added to the combined list. Lastly, the CBJ-managed roadways located within the Valley were identified from the CBJ

database and were added as local roads to the list. Table 2-5 summarizes the data included in the combined list of roadway segm ents by primary data source, and Table 2-6 summarizes the data in the combined list by facility type. * 

### As shown in Table 2-6, the majority of roadway segments with missing sp eed and ADT data are local roads, most of which are CBJ-managed roads.

Table 2-5 Available Roadway Data for Mendenhall Valley by Source Primary Data

Source No. of Segments Length in

Miles Segments w/ Speed Data Segments w/

ADT

2004 Routelist 70 30.5 36 70 2004 Speed List 198 35.3 0 0

1999 Routelist 15 12.7 13 15

CBJ database 272 55.0 0 0

ALL 555 133.4 49 85

Table 2-6 Available Roadway Data for Mendenhall Valley by Facility

Facility Type No. of Segments Length in

Miles Segments w/ Speed Data Segments w/

ADT

Collector 48 19.9 23 44

Minor Arterial 10 3.2 10 10 Principal Arterial 6 3.5 6 6

Local 491 106.8 10 25

ALL 555 133.4 49 85

* Facility types included in the Juneau list of roadway segments include principal arterials, minor arterials, collectors, and locals.

### -9- ADT and Speed Estimates – After the combined list of roadway segments was developed, it was sorted by facility type, and a straight average of the known ADT levels was calculated for each facility type. In addition, VMT-based harmonic average speeds were developed for each facility type using th e roadway segments with known speeds and VMT (VMT=ADT*length in miles). For the roadway segments that were derived from the 1999 routelist, the speed estimates were a ssumed to still apply, as no other source of traffic monitoring data for these segments were available. The average ADT and harmonic average speeds estimated was used to fill in the missing ADT and speed data for the roadway segments within each facility type. This resulted in a complete roadway segment data set—with ADT, length, VMT, and speed estimates.

Traffic Level Adjustment by Calendar Year – The ADT and VMT levels used from the 1999 routelist were adjusted to 2004 levels using yearly population estimates for the Mendenhall Valley. Details of deriving yearly population levels within the nonattainment area (1993, 2004, and 2018) are included in Appendix B. The 1999 population level was interpolat ed between the 2004 and 1993 levels. After complete VMT estimates by facility were developed for 2004, the VMT were then forecasted to 2018 using the population forecast. Table 2-7 shows the estimated borough population levels used in adjusting the estimated ADT and VMT in the roadways in the Mendenhall Valley.

Table 2-7 Mendenhall Valley Population Estimates

Calendar Year Population

1999 12,724
2004 13,327
2018 14,535

Mendenhall Valley Nonattainment Area Travel Estimates – The estimated 2004 and 2018 average travel characteristics resulting from the combined Valley roadway segment data set are shown in Table 2-8 by facility type. As shown, the average ADT for local roads is higher than expected at 1,385 vehicles per day. This may stem from the small sample

size of local roads with ADT data and from DOT&PF monitoring traffic counts on the larger, longer, and busier roadway segments , for which maintena nce and improvements are more needed. No other data from local roadways were available to adjust this estimated average ADT, however, and the ADT for the local roads were kept as a conservative assumption.

The VMT-based harmonic average speeds shown in Table 2-8 were used in developing the MOBILE6 input files for the nona ttainment area. The resulting PM 10 

### emission factors from the model runs were then combined with the total daily VMT by calendar year and season to result in the average PM 10 

### emissions for the area by facility type.

### -10- Table 2-8 Mendenhall Valley Average Travel Estimates

Facility type ADT Harmonic Avg Speed (mph) 2004 Daily

VMT 2018 Daily

VMT
Collector 3,156 35.6 58,370 63,661
Minor Arterial 7,317 37.2 39,585 43,173 Principal Arterial 16,082 50.5 63,278 69,013
Local 995 20.8 141,367 154,180

ALL 302,599 330,028



### 2.3 PM 10 

### Inventory Results

Tables 2-9 and 2-10 show the re sulting 2004 and 2018 on-road mobile PM 10 

### emission

estimates for the Mendenhall Va lley nonattainment area by po llutant, season, and facility type. The annual average emission inventor ies were estimated by weighting the summer and winter emission levels by the number of days in each season as defined by ADEC—

183 for the summer and 182 for the winter. As shown in the tables, very little seasonal

variation is seen in the PM 10 

### emissions from on-road motor vehicles. All exhaust particulate emissions are reduced in 2018 as compared to the 2004 levels, even with increasing VMT, due to the more stringent standards on emissions for the later model year vehicles. Brake- and tire-wear emissions are based only on total miles driven; therefore, the increase in VMT for 2018 resulted in the increase in break- and tire-wear

PM 10 

### emissions.

Table 2-9 2004 Mendenhall Valley Seasonal On-Road PM 10 

### Emissions in Tons/Day a
Season Facility GASPM EC OC SO4 Brake Tire

Collector 3.1E-04 9.3E-04 4.7E-04 1.5E-04 5.5E-04 4.2E-04

Minor Arterial 4.9E-04 1.5E-03 7.5E-04 2.4E-04 8.7E-04 6.7E-04
Principal Arterial 1.1E-03 3.3E-03 1.7E-03 5.9E-04 1.9E-03 1.5E-03

Local 4.5E-04 1.4E-03 6.9E-04 2.2E-04 8.0E-04 6.2E-04 Winter

ALL TOTAL 0.0023 0.0071 0.0036 0.0012 0.0042 0.0032

Collector 3.1E-04 9.1E-04 4.6E-04 1.3E-04 5.5E-04 4.2E-04

Minor Arterial 4.9E-04 1.5E-03 7.3E-04 2.1E-04 8.7E-04 6.8E-04
Principal Arterial 1.1E-03 3.2E-03 1.6E-03 5.1E-04 1.9E-03 1.5E-03

Local 4.5E-04 1.3E-03 6.8E-04 1.9E-04 8.0E-04 6.2E-04 Summer

ALL TOTAL 0.0023 0.0069 0.0035 0.0010 0.0042 0.0032
Annual Average 0.0023 0.0070 0.0036 0.0011 0.0042 0.0032

a Lead emissions are zero for all scenarios.

### -11- Table 2-10 2018 Mendenhall Valley Seasonal On-Road PM 10 

### Emissions in Tons/Day a
Season Facility GASPM EC OC SO4 Brake Tire

Collector 2.9E-04 2.1E-04 1.1E-04 3.5E-05 8.8E-04 6.8E-04

Minor Arterial 2.0E-04 1.4E-04 7.1E-05 2.4E-05 5.9E-04 4.6E-04 Principal Arterial 3.1E-04 2.3E-04 1.1E-04 3.8E-05 9.5E-04 7.4E-04

Local 6.6E-04 5.1E-04 2.5E-04 1.0E-04 2.1E-03 1.6E-03 Winter

ALL TOTAL 0.0015 0.0011 0.0005 0.0002 0.0045 0.0035

Collector 2.8E-04 2.0E-04 1.1E-04 3.5E-05 8.8E-04 6.8E-04

Minor Arterial 1.9E-04 1.4E-04 7.1E-05 2.4E-05 5.9E-04 4.6E-04 Principal Arterial 3.0E-04 2.2E-04 1.1E-04 3.8E-05 9.5E-04 7.4E-04

Local 6.6E-04 4.9E-04 2.5E-04 1.0E-04 2.1E-03 1.6E-03 Summer

ALL TOTAL 0.0014 0.0011 0.0005 0.0002 0.0045 0.0035
Annual Average 0.0014 0.0011 0.0005 0.0002 0.0045 0.0035

a Lead emissions are zero for all scenarios.



### ###

### -12- 

### 3. NONROAD SOURCES

The nonroad mobile source inventories presen ted in this report were developed using

EPA’s draft NONROAD model. * 

### This model calculates emissions from approximately 80 different types of nonroad equipment, and categorizes them by technology type (i.e., gasoline, diesel, LPG, CNG, 2-stroke, and 4- stroke) and horsepower range. Note that default model input was replaced with Jun eau-specific data when ever possible, as described in the methodology section below.

For purposes of this inventory, the Alaska n summer and winter are defined as April through September, and October through March, respectively. Sierra performed NONROAD modeling runs for calendar years 2004 and 2018 and determined emissions, in tons per day, for both a typical winter and a typical summer day for the Mendenhall Valley community. Unless otherwise sp ecified, NONROAD default activity and population inputs were used in the modeling asso ciated with these nonroad inventories.



### 3.1 Calculation Methodology

The NONROAD model calculates tons of emi ssions for a given geographical area using the following factors:

• equipment population;

• an equipment-specific emission fact or (in grams per horsepower-hour);

• the average horsepower rating of the equipment;

• the estimated annual equipment ac tivity (hours per year); and

• the average load factor for the given engine.

In addition, seasonal (month or season) and day of week (i.e., weekend vs. weekday) adjustments are applied depending on whet her the end-user requests an inventory estimate expressed on an annual, seasonal, or daily basis. The equipment populations are based on national averages, and then scaled down to represent smaller geographic areas on the basis of human population and prox imity to recreational, industrial, and

commercial facilities. It shoul d be noted that the model ha s undergone dramatic revisions and corrections with regard to estimates of equipment populations and activity rates, which has resulted in reduced emissions estimates from some equipment categories. For example, the emissions attributed to summertime marine equipment, which formerly constituted a large percentage of the total summer inventory, have been reduced primarily

* U.S. EPA NONROAD Model, draft version 2.3c, released April 2004.

### -13- as a result of EPA’s revised population estima tes for Alaska, which are generally two orders of magnitude lower than in the previous version of the model.

Scaling Methodology for Mendenhall Valley Results – Because the NONROAD model provides output on a county-wide, or borough-wide basis only, we performed the runs for the City and Borough of Juneau, then scaled the results by the ratio of the number of households in the Borough vs. nonattainment area, as shown in Table 3-1 below. Population information for the Borough was obtained from U.S. Census data, * 

### and the nonattainment area population wa s determined according to the methodology presented in Appendix B.

Table 3-1 Fraction of Households in City and Borough of Juneau vs. Mendenhall Valley Nonattainment Area

Calendar

Year # Mendenhall Valley

Nonattainment Area

Households # City & Borough of

Juneau Households Nonattainment Area Housing Fraction

2002 4,608 12,422 0.37

2004 4,888 12,810 0.38

2018 5,331 14,491 0.37



### 3.2 Modifications to EPA’s NONROAD Model Default Equipment Population and Activity Factors

Because EPA uses a top-down approach in developing populations and estimated annual activity factors for the equipment in the NONROAD model (i.e., distributed national equipment populations to individual states and counties based primarily on human population), it is recognized that locally gene rated data will improve the accuracy of the resulting NONROAD emissions estimates. As part of several studies completed for ADEC in the 2000 to 2002 calendar year timeframe, † 

### it was possible to generate more accurate estimates for population and/or activity for a number of key summer and wintertime equipment categories (e.g., personal watercraft, lawn and garden equipment, snowmobiles) which operate in the Juneau area. ADEC staff and other local agencies provided key activity and population estimates that were used to adjust some of the more general NONROAD defaults. For example, th ere is little if any personal watercraft activity in the Juneau area during the summer months because of the cold water

* Juneau household population data for 1999 and 2002 was obtained from U.S. Census Data. 2004 and 2018 household population estimates were then calculated by increasing the 2002 population by the annual percent increase from 1999 to 2002 (i.e., 1.04 %).

† The “1995-2001 Fairbanks CO Inventory,” the “1999 Air Toxics Emission Inventory,” the “2000 Anchorage CO Inventory,” and the “2002 Criteria Pollutant Emissions Inventory.”

### -14- temperature of all surrounding bodies of water. With the exception of these modifications, described in greater deta il below, the NONROAD model defaults were used for all modeling associated with the development of this Inventory.

Personal Watercraft (PWC)

Equipment Population – ADEC staff contacted the U.S. Coast Guard and obtained calendar year 2000 registration data for PWC in the Juneau area. According to ADEC, boating registration enforcement is fairly rigo rous in Juneau, and although the geography is not a deterrent to PWC use in Juneau, s easonal constraints (in particular low water temperature and inclement weather) severely limit their use. Therefore, ADEC staff felt it was appropriate to assume that 50% of the PWC in Juneau are registered with the Coast Guard. Therefore, it was decided that regist ration data provided by the Coast Guard, with the 50% registration assumption discussed above, woul d provide a more accurate total. Note that the NONROAD estimate shown below was associated with the previous version of that model. However, because the current model defaults show PWC populations which appear to be unrealistical ly low (i.e., 26 units for Juneau), the populations shown below were used for this analysis, with minor adjustments to account for population increases between 2000 and 2018 *



### .

PWC Registered w/ Coast Guard 63 NONROAD PWC Estimate: 2,452 Modified PWC Population: 126

Note that the above population es timates refer to the Borough of Juneau; these totals were subsequently adjusted to represent the equipment population in the Mendenhall Valley nonattainment area, according to th e methodology discussed previously.

Activity Estimates – Because there are no bodies of water within the boundaries of the Mendenhall Valley nonattainment area that would accommodate motorized watercraft, the activity for all pleasure craft (including PWCs) has been reduced to one hour per year for engine maintenance. The NONROAD default seasonal activity distribution † 

### was also retained for all recreational marine categories.

Offroad Motorcycles and All Terrain Vehicles (ATVs)

Lacking more accurate data, we have retained the NONROAD assumptions for ATV activity and populations (with the requisite nonattainment area popul ation adjustments), with the added assumption that all annual activity occurs dur ing the summer months (i.e., April through September). ADEC staff belie ve the population numbers are too high, but

* According to U.S. Census data, the 2000 to 2002 population increase in Juneau was 0.18%.

† The default seasonal activity distribution for recreatio nal marine equipment is 15% during the Spring and Fall, and 70% during the Winter (i.e., December through February).

### -15- have no local data to offer as a substitu te. The 2004 and 2018 populations for offroad motorcycles and ATVs are shown below.

2004 ATV Population Estimate: 2,938 2004 Offroad Motorcycle Population Estimate: 756 2018 ATV Population Estimate: 5,261 2018 Offroad Motorcycle Population Estimate: 1,251

Snowmobiles

Equipment Population – ADEC staff obtained 1999 snowmobile registration from the Alaska DMV for use in developing the 2002 Cr iteria Pollutant Inventory. At that time, ADEC believed that assuming 50% of all operating snowmobile s are registered provided a more accurate population estimate than th e defaults in the NONROAD model currently in use. Therefore, this logic was applied to the DMV registration totals. The revised population estimate is considered by ADEC staff to be more representative than either the current model defaults or those from the previous version of the NONROAD model – both of which appeared to be too high for J uneau. (According to ADEC staff, there are few areas to ride a snowmobile in Juneau due to the terrain and climate, and it is not possible to easily transport the equipment to neighboring areas outside the Borough as is routinely done in Anchorage and Fairbanks.) And, despite the fact that the current NONROAD population estimates do appear to be more reasonable than those in the preceding version of the model, we believe that the population estimates shown below remain the most accurate available, as they are based on actual Alaska DMV registration data. Accordingly, the population figures shown below were used for the current analysis, after adjustments for popul ation increases between 1999 and 2002.

Old 1999 NONROAD Population Estimate: 368 Current 1999 NONROAD Population Estimate: 2,898 DMV Registration: 71 Modified Population 142

Note that, as discussed in earlier sections , the above population estimates refer to the Borough of Juneau; these population estimates we re subsequently adjusted to represent the equipment population in the Mendenhall Valley nonattainment area, according to the methodology discussed previously.

Activity Estimates – According to ADEC staff, there are no areas within the confines of

the nonattainment area that are suitable for snowmobile use. Therefore, we have

assumed that the entire Juneau snowmobile population is used a total of 1.0 hours/year for maintenance purposes only, all of wh ich occurs during the winter months.

### -16- Snowblowers

The default NONROAD assumptions regarding sn owblower activity were retained, with the exception of seasonal dist ribution; for this analysis, it was assumed that all snowblower activity was evenly distributed throughout the winter season.

General Modifications

– Lawn and Garden

Lacking more accurate data, the basic N ONROAD assumptions for summertime lawn and garden activity and popul ations have been retaine d. ADEC staff believe the population numbers are too high, but have no local data to use as a replacement. However, some adjustments to these default i nputs have been made, as described below.

Activity Estimates – Adjustments to the seasonal activity assumptions were made to reflect the fact that the weather patterns in Juneau effectively eliminate lawn and garden activity during a substantial portion of the year. Following the methodology used in previous inventory calculations, it was assume d that all lawn and garden activity takes place during the Alaska summer season, April through September. Using residential lawn mowers as an example, this gives the following estimated weekly activity factor:

58 hours/yr ) 26 weeks/yr = 2.2 hours/week (NONROAD default for res. lawnmowers)

Due to regional weather patterns, however, ADEC staff feel it is appropriate to limit the duration of lawn and garden activity to the 17.5 weeks from May 1 through August 31. This equates to approximately 17.5 weeks/yr of lawn and garden activity, rather than 26 weeks/yr. Distributing the 2.2 hours per week of residential lawnmower activity over this time period reduces the annual activity from 58 hours/week to 39 hours/week—a decrease of approximately 30%. This categorical decrease in the annual activity for all lawn and garden equipment seems appropri ate, given that the NONROAD model default assumption is that 30% of all lawn and gard en activity takes place during what we have defined as the Alaska winter. So, in essen ce, 30% of lawn and garden activity that the NONROAD model had assumed took place during the October through March time period was simply eliminated.



### 3.3 Emission Estimates

Table 3-2 below shows the summer and winter Nonroad inventory totals for Juneau for calendar years 2004 and 2018. These totals show a pattern of sustained, gradual decrease

in PM 10 

### emissions over time as older equipment is replaced with newer equipment.

### -17- Table 3-2

2004 and 2018 Nonroad PM 10 

### Emissions

Calendar Year Season PM 10 

### (tpd)

2004 Summer 0.05

Winter 0.03

2018 Summer 0.02

Winter 0.01



### Tables 3-3 through 3-6 show a more deta iled presentation of th e calculated Nonroad emission totals. For each table, the equipment has been sorted in descending order of

total PM 10 

### emissions. The top 20 emission sour ces are listed individually, and the remaining sources are grouped together. These tables show that, generally, a handful of equipment types (e.g., snowmobiles and s nowblowers in the winter, construction equipment in the summer) are responsible for the majority of the emissions for that season. However, it is important to note th at the emissions from some of these key sources, particularly for the summer totals , are based on default equipment population and activity estimates in the current versi on of the NONROAD model, which may not be adequately representative of the Juneau equipment population and usage patterns, as discussed previously.

Table 3-3

2004 Mendenhall Valley Nonattainment Area Nonroad Emissions - Summer (tpd)

Equipment Description Equipment Type PM 10 Population (# units) Activity (hrs/unit/month)

Logging Equipment Forest Eqp - Feller/Bunch/Skidder 0.0090 65 104
Recreational Equipment All Terrain Vehicles 0.0057 1,121 268 Logging Equipment Chain Saws > 6 HP 0.0051 119 25
Recreational Equipment Mot orcycles: Off-road 0.0044 288 267 Construction and Mining Equipment Tractors/Loaders/Backhoes 0.0038 37 125 Construction and Mining Equipment Skid Steer Loaders 0.0035 58 89 Construction and Mining Equipment Rubber Tire Loaders 0.0025 15 84 Construction and Mining Equipment Crawler Tractor/Dozers 0.0020 10 104 Construction and Mining Equipment Excavators 0.0019 14 121 Construction and Mining Equipment Off-highway Trucks 0.0014 2 182 Construction and Mining Equipment Rough Terrain Forklifts 0.0011 12 73 Construction and Mining Equipment Rollers 0.0007 10 83 Construction and Mining Equipment Concrete/Industrial Saws 0.0005 11 67 Construction and Mining Equipment Scrapers 0.0005 2 101 Construction and Mining Equipment Graders 0.0005 3 107 Industrial Equipment AC\Refrigeration 0.0004 10 123 Construction and Mining Equipment Trenchers 0.0004 9 59
Commercial Equipment Generator Sets 0.0004 157 12 Construction and Mining Equipment Cranes 0.0004 4 107 Construction and Mining Equipment Bore/Drill Rigs 0.0004 15 24
All Other Equipment 0.0039

TOTAL 0.05

### -18- Table 3-4 2004 Mendenhall Valley Nonattainment Area Nonroad Emissions - Winter (tpd)

Equipment Description Equipment Type PM 10 Population (# units) Activity (hrs/unit/month)

Logging Equipment Forest Eqp - Feller/Bunch/Skidder 0.0090 65 104 Logging Equipment Chain Saws > 6 HP 0.0051 119 25 Construction and Mining Equipment Tractors/Loaders/Backhoes 0.0019 37 63 Construction and Mining Equipment Skid Steer Loaders 0.0017 58 45 Construction and Mining Equipment Rubber Tire Loaders 0.0013 15 42 Construction and Mining Equipment Crawler Tractor/Dozers 0.0010 10 52 Construction and Mining Equipment Excavators 0.0009 14 61 Construction and Mining Equipment Off-highway Trucks 0.0007 2 91 Construction and Mining Equipment Rough Terrain Forklifts 0.0006 12 37 Commercial Equipment Generator Sets 0.0004 157 12 Industrial Equipment AC\Refrigeration 0.0004 10 100 Construction and Mining Equipment Rollers 0.0004 10 42 Construction and Mining Equipment Concrete/Industrial Saws 0.0003 11 34 Airport Ground Support Equipment Airport Ground Support Equipment 0.0003 3 61 Construction and Mining Equipment Scrapers 0.0003 2 51 Lawn and Garden Equipment Snowblowers 0.0002 376 3 Construction and Mining Equipment Graders 0.0002 3 54 Construction and Mining Equipment Trenchers 0.0002 9 29 Commercial Equipment Welders 0.0002 14 44 Construction and Mining Equipment Cranes 0.0002 4 54 All Other Equipment 0.0018

TOTAL 0.03



### Table 3-5 2018 Mendenhall Valley Nonattainment Area Nonroad Emissions - Summer (tpd)

Equipment Description Equipment Type PM 10 Population (# units) Activity (hrs/unit/month)

Logging Equipment Chain Saws > 6 HP 0.0073 171 25 Recreational Equipment Motorcycles: Off-road 0.0036 460 267 Construction and Mining Equipment Skid Steer Loaders 0.0019 76 90 Recreational Equipment All Terrain Vehicles 0.0019 1,935 268 Construction and Mining Equipment Tractors/Loaders/Backhoes 0.0019 48 125 Construction and Mining Equipment Concrete/Industrial Saws 0.0005 11 67 Construction and Mining Equipment Rubber Tire Loaders 0.0004 20 84 Lawn and Garden Equipment Chain Saws < 6 HP 0.0003 284 2 Lawn and Garden Equipment Trimmers/Edgers/Brush Cutters 0.0003 760 1 Commercial Equipment Generator Sets 0.0003 219 12 Lawn and Garden Equipment Leafblowers/Vacuums 0.0003 400 2 Construction and Mining Equipment Rough Terrain Forklifts 0.0003 16 73 Recreational Equipment Specialty Vehicles/Carts 0.0002 114 11 Construction and Mining Equipment Tampers/Rammers 0.0002 16 18 Commercial Equipment Pumps 0.0002 56 20 Construction and Mining Equi pment Bore/Drill Rigs 0.0002 16 26 Commercial Equipment Welders 0.0001 19 44 Construction and Mining Equipment Crawler Tractor/Dozers 0.0001 14 104 Logging Equipment Shredders > 6 HP 0.0001 1,056 4 Construction and Mining Equipment Rollers 0.0001 12 83 All Other Equipment 0.0010

TOTAL 0.02

### -19- Table 3-6 2018 Mendenhall Valley Nonattainment Area Nonroad Emissions – Winter (tpd)

Equipment Description Equipment Type PM 10 Population (# units) Activity (hrs/unit/month)

Logging Equipment Chain Saws > 6 HP 0.0073 171 25 Construction and Mining Equipment Skid Steer Loaders 0.0010 76 45 Construction and Mining Equipment Tractors/Loaders/Backhoes 0.0009 48 63 Lawn and Garden Equipment Snowblowers 0.0003 467 3 Commercial Equipment Generator Sets 0.0003 219 12 Construction and Mining Equipment Concrete/Industrial Saws 0.0003 11 34 Construction and Mining Equipment Rubber Tire Loaders 0.0002 20 42 Commercial Equipment Pumps 0.0002 56 20 Commercial Equipment Welders 0.0001 19 44 Construction and Mining Equipment Rough Terrain Forklifts 0.0001 16 37 Logging Equipment Shredders > 6 HP 0.0001 1,056 4 Recreational Equipment Specialty Vehicles/Carts 0.0001 114 5 Construction and Mining Equipment Tampers/Rammers 0.0001 16 9 Construction and Mining Equipment Bore/Drill Rigs 0.0001 16 13 Construction and Mining Equipment Crawler Tractor/Dozers 0.0001 14 52 Industrial Equipment Forklifts 0.0001 11 134 Construction and Mining Equipment Rollers 0.0001 12 42 Construction and Mining Equipment Trenchers 0.0000 11 30 Commercial Equipment Air Compressors 0.0000 12 51 Construction and Mining Equipment Other Construction Equipment 0.0000 2 33 All Other Equipment 0.0003

TOTAL 0.01



### ###

### -20- 

### 4. AREA SOURCES

Area sources are small sources that individually emit a small quantity of emissions, but collectively can have a significant impact on regional air quality. The quantifiable area sources present in the Mendenhall Valley area that are integrated into this analysis include combustion sources generally used for heating and cooking, residential wood burning, fuel oil, propane, coal, and natura l gas combustion, and structural fires.

Emissions from these sources are primarily based on activity estimates obtained from local agencies and/or fuel di stributors. In cases where we were not able to procure current activity information for this analysis, it was necessary to extrapolate emission estimates from one community to another via hu man population, or to adjust past activity estimates from the four reports discussed in earlier sections * 

### according to 2004 and 2018 population estimates.

The following is a description of the met hodology used to calculate emissions from each

area source.



### 4.1 Residential Fuel Use

Over the years, DEC has conducted several su rveys of residential wood burning in the Mendenhall Valley. Past surveys, conducted in 1981, 1985, and 1993, however, did not address other sources of home heating. R ecognizing that wood burning practices have shifted over the past decade, DEC commissi oned a broader survey of home heating practices in the spring of 1994 to (a) upda te estimates of wood use, (b) document the influx of direct vent fuel oil stoves, and (c) quantify their combined impact on home heating emission estimates. A total of 435 homes participated in the survey, which represents almost 10% of the households locat ed in the nonattainment area. Key findings

from that effort † 

### include the following:

• Initiatives (e.g., burn bans, public education, new stove certification requirements, etc.) implemented under the Juneau wood smoke control program were effectively implemented;

* The “1995-2001 Fairbanks CO Inventory,” the “1999 Air Toxics Emission Inventory,” the “2000 Anchorage CO Inventory,” and the “2002 Criteria Pollutant Emissions Inventory.”

† Memorandum to Alice Edwards, ADEC from Bob Dulla, Sierra Research, “Results of Juneau Home Heating Survey and Related PM 10 Emission Estimates, July 19, 2004.

### -21- • Wood use per household dropped from 1.8 cords per heating season in 1993 to 1.1 cords in 2004;

• There is widespread use of direct vent -type fuel oil heaters, which were not addressed in previous surveys and had little market penetra tion in 1993; and

• Between 1993 and 2004, there were significan t reductions in the AP-42 emission factors for both fuel oil and wood burning.

Collectively, these changes were estimated to reduce annual PM 10 

### emissions from residential heating (for all fuels) by a lmost 85% from 152.0 tons/year in 1993 to 23.2 tons/year in 2004. The emission estimates produ ced in that effort, however, need to be

revised to address the i ssues discussed below.

Differences in Seasonal Definitions – The survey collected data for the winter heating season, which was defined to last from Octobe r through May (a total of 243 days) and for the year. The seasonal definitions employed in this analysis are winter (October – March or 182 days) and summer (April – September or 1 83 days). The approach used to modify the survey data to match the seasonal definitions employed in this analysis was to proportion the 243-day winter survey data to the 182-day winter season on the basis of heating degree-days. * 

### A summary of the degree-days a nd related proportions is presented

in Table 4-1. It shows that on the basis of degree-days, the winter accounts for 71.8% of

fuel use and the summer for 28.2%. It also shows that the October through March period accounts for 85% of the degree-days recorded during the October through May period addressed in the survey.

Table 4-1 Summary of Heating Degree Days for Juneau, Alaska (April 2004 – March 2005)

Period Degree Days % of Year % of Oct – May
April 2004 – Sept. 2004 2,229 28.2

- Oct. 2004 – March 2005 5,680 71.8 85.0 April 2004 – March 2005 7,909 100.0

-

Oct. 2004 – May 2005 6,684 84.5 100.0

The survey collected data on the number of cords of wood, the number of 40-lb bags of wood pellets, and the gallons of distillate used in home heating for three different periods of time: winter, summe r, and annual. Many respondents reported having multiple types of heaters. In some cases, it was easier for them to provide seasonal

information and in others it was annual information. The challenge is correctly allocating the reported fuel use to the seasons being addressed in this analysis.

* Data on heating degree days for different periods of time are available at http://www.w underground.com/history/airport/PAJN/2004/10/1/CustomHistory.html

### -22- Table 4-2 documents how the degree-day data were used to allocate the seasonal and

annual fuel use data into two seasons:

• Winter – October – March, and

• Summer – April – September.

Table 4-2 Allocation of Survey Fuel Us e to Summer & Winter Seasons (fuel use by participating households)
Survey Winter Summer Season Fuel Use Adjustment Fuel Used Adjustment Fuel Used

Wood (cords)
Oct. – May 133 0.85 113.05 0.15 19.95 June – Sept. 19

- - 1.00 19.00

Annual 1 0.72 0.72 0.28 0.28

Total - - 113.77 - 39.23

Fuel Use/Household 127 homes 0.90 127 homes 0.31

Pellets (40 lb bags)
Oct. – May 1,291 0.85 1,097 0.15 194 June – Sept. 181 - - 1.00 181

Annual 0 - - - -
Total - - 1,097 - 375

Fuel Use/Household 22 homes 49.86 22 homes 17.05

Fuel Oil (gallons)
Oct. – May 148,891 0.85 126,557 0.15 22,334 June – Sept. 51,944 - - 1.00 51,944 Annual 35,403 0.72 25,420 0.28 9,984
Total - - 151,977 - 84,261

Fuel Use/Household 390 homes 389.68 390 homes 224.96

The winter survey data, which covers Oc tober – May, were adjusted by 85% to compute the amount of fuel used during the period of October – March. The remaining 15%, which covers April and Ma y, was allocated to the summer season. Summer survey data, which covers the period of June – September, was fully allocated (100%) to the summer season. The annual survey data were alloca ted on the basis of winter (71.8%) and summer (28.2%) heating degree-day splits recorded over a 12- month period. The computed seasonal fuel-use values were then divided by the number of homes that reported wood, pellet, a nd fuel oil use in the survey to estimate fuel use per household.

### -23- A total of 435 homes participated in the overall survey. The proportion of homes reporting each fuel use was used to extrapol ate the results of the survey to the overall population of homes in the Valley.

More Recent Demographic Data – At the time the survey was conducted, the most recent population estimates available for Juneau were for 2001, and a review of the growth rate suggested that there would be little gr owth between 2001 and 2004. Therefore, no adjustment was applied to account for th e growth between 2001 and 2004. More recent demographic data have become available for J uneau and were used to prepare an updated

estimate of the number of households in th e nonattainment area in 2004 and a projection for 2018. A description of how those estimates were developed is presented in Appendix B. The 2001 estimate of households employed in the survey was 4,608. The number of households is projected to increase to 4,888 in 2003 and 5,331 in 2018.

Presented below is a brief summary of the approach used to compute home heating emissions using the fuel use and population da ta described above. A detailed listing of the calculations is presented in Appendix E.

Wood-Use Heating - The survey collected data on wood use by home and the types of wood burning devices in the home (e.g., pellet stoves, wood st oves, conventional fireplaces, modified fireplaces, etc.). Because wood use was reported on a per-household and not a per wood burning unit basis, and ma ny households reported a mixture of wood burning devices, a method had to be develo ped to allocate wood use by type of wood burning device (i.e., those with different e mission factors). This was accomplished by first determining the total number of wood heaters and th en determining number of homes equipped with one or mo re non-pellet type wood heaters (i.e., getting rid of the overlap caused by homes having multiple heaters). The distribution of the total number of these heaters (which summed to 169) was normalized to the number of homes equipped with one or more heaters (which su mmed to 127), as shown in Tables 1 and 2 in Appendix E. * 

### Total wood use was then distributed to the survey domain based on these percentages, and total emissi ons were calculated for the 435 households that participated in the survey using the appropriate AP-42 emission factors. The results were then extrapolated to represent emissions for the entire Valley. Because no detailed information regarding pellet stove technolog y was included in the survey, no similar distribution of pellet use by stove type was necessary.

The tables presented in Appendix E show the details of the calculations used to prepare wood burning emission estimates on both an a nnual and a winter seasonal basis. The general calculation method for re sidential wood combustion emissions has been used in a

number of emissions inventor ies over the past few years, most recently for the 2003

Fairbanks Carbon Monoxide Maintenance Plan. The methodology is as follows:

(Cords of wood burned/day) x [EF (lbs CO/cord burned)] x (% homes w/ wood stoves)

* Of the 127 survey households, that reported the use of at least one type of wood stove or fireplace, 104 used only one unit and 23 used two units.

### -24- EPA’s AP-42 contains emissi on factors for several specific types of wood-burning appliances. For example, AP-42 * 

### lists emission factors for conventional, noncatalytic, and catalytic type wood stoves. However, the 2004 survey includes information only for the more general “woodstove” category. In the absence of more detailed information regarding the mix of technology present in the Valley woodstoves, the general AP-42 woodstove emission factor (30.6 pounds/ton of wood burned) was used to calculate

emissions for all Mendenh all Valley woodstoves, as shown in the tables in Appendix E.

Fireplaces are the other major source of PM 10 

### emissions from wood combustion used in home heating. Although the 2004 survey cont ains information on both conventional and modified fireplaces, the most current available emission factor (23.6 pounds/ton of wood burned) is only for the more general “fireplace” category. This emission factor was included in a paper presented at EPA’s 10 th 

### Annual Emissions Inventory Conference in May 2001. † 

### The results documented in that paper show PM 10 

### (and CO) emission factors for wood-burning fireplaces, which are signific antly lower than those found in the most current AP-42 publication. (The study documen ted in this paper examined over a dozen more recent data sources for wood-burning fireplaces than contained in AP-42. PM 10 

### emission factors were compiled from a database of 388 tests conducted on 112 fireplace models, which exceeds the number of tests and models on which the AP-42 factors are based.) In the absence of mo re detailed information, this fireplace emission factor was used to calculate emissions for all firepl ace categories included in the 2004 survey, as well as those for the catch-all “any ot her wood device” survey category.

Both the woodstove and fireplace emission f actors are given in units of pounds of PM 10 

### produced per ton of wood burned. These were converted to units of pounds of PM 10 

### per cord of wood burned by applying an assu med wood density of 30 pounds per cord, and a cord volume area of 80 cubic feet per cord. Bo th of these conversion factors were used in

the 1988 PM 10 

### Emission Inventory, and are the same as, or substantially similar to,

conversion factors used in other recent ADEC reports. These converted emission factors were then applied to the total cords of wood used in the Valley, to give total PM 10 

### emissions from wood burning sources. The actual conversions, and the overall emission calculations, are documented in Appendix E. A summary of the seasonal emissions in 2004 and 2018 is presented in Tables 4-3 and 4-4.

Emission factors for pellet stoves did not requi re any conversion, as total usage was given in pounds, which was then multiplied directly with AP-42 emissi on factors for pellet stoves, given in units of pounds of PM 10 

### produced per ton of pellets burned. Specific

seasonal and annual calculations are shown in Appendix E.

Fuel Oil Heating - In calculating emissions from Fuel Oil Combustion, AP-42 emission factors were again applied to seasonal and annual fuel-use totals collected in the recent survey. Because not all survey respondents provided fuel-use data, average fuel use by season was assumed to apply to the 390 fuel oil users recorded in the survey. These values were apportioned to Toyo/Monitor-type st oves and central oil furnaces according

* Compilation of Air Pollutant Emission Factors, Volume I, Fifth Edition, Chapter 1.09, October 1996.

† J. E. Houck, J. Crouch and R. H. Huntley, “Review of Wood Heater and Fireplace Emission Factors,” proceedings from U.S. Environmental Protection Agency’s 10 th Annual Emissions Inventory Conference, May 2001.

### -25- Table 4-3

PM 10 

### Emission Estimates for Residential Heating Mendenhall Valley in 2004

Fuel Type Homes Equipped Cords per

Household 40 # bags per

Household Gallons per

Household Emissions (tons)

Winter
Wood 1,427 0.90 - - 16.60

Pellet 247 - 49.86 - 1.09
Oil 4,382 - - 389.68 0.34

Total 18.02

Summer Wood 1,427 0.31 - - 5.72

Pellet 247 - 17.05 - 0.37
Oil 4,328 - - 224.96 0.19

Total 6.28

Annual 24.30

Table 4-4

PM 10 

### Emission Estimates for Residential Heating Mendenhall Valley in 2018

Fuel Type Homes Equipped Cords per

Household 40 # bags per

Household Gallons per

Household Emissions (tons)

Winter Wood 1,556 0.90 - - 18.11

Pellet 270 - 49.86 - 1.18
Oil 4,780 - - 389.68 0.37

Total 19.66

Summer Wood 1,556 0.31 - - 6.24

Pellet 270 - 17.05 - 0.40
Oil 4,780 - - 224.96 0.21

Total 6.85

Annual 26.51

to the percentage of households that reporte d the use of each, normalized to account for households that operate more than one unit (u sing the same method described for the cord wood heaters). * 

### Total emissions for the survey domain were then calculated, and the result was then adjusted to represent the Mendenhall Valley using the ratio of surveyed households vs. Valley households.

* Of the 390 survey households (90%) that reported use of either a fuel oil or kerosene heating source, 55 said they use more than one type.

### -26- Contrary to emission factors for wood burni ng sources, individual emission factors for each type of fuel oil heater are not available. Therefore, a single emission factor, which

was suitable for all residential fuel oil furnaces (from EPA’s AP-42, 0.4 pounds of PM 10 

### per 1000 gallons of fuel burned), was used in both calculations. The results are shown in Appendix E and displayed in Tables 4-3 and 4-4.

Used Oil Combustion – Although we do not believe there is a significant amount of used oil combustion in Juneau, and were not able to procure any used oil throughput totals, it is likely that it is used for heating in so me automotive repair shops, and other similar facilities where it is easily accessible. Theref ore, following the methodology used in the 1999 Criteria Pollutant Inventory and 1999 Ai r Toxics report, national used oil consumption (not to be confused with waste oil, which is officially designated as hazardous waste and whose combustion is illegal in the state of Alas ka) was allocated to Juneau based on population data. The total U.S. consumption for 1983 (590,000,000 gallons) was prorated to 2004 and 2018 Juneau levels (78,222 and 85,312 gallons, respectively) based on U.S. Census popula tion data, and our projected 2018 population estimate for the Mendenhall Valley. PM 10 

### emissions were then calculated by applying AP-42 emission factors (Table 1.3-1) to thes e activity totals. All used oil combustion was assumed to occur during the winter months.

Propane – In calculating emissions from Propa ne Combustion, AP-42 emission factors were again applied to monthly fuel use totals provided by local Juneau fuel distributors. The Juneau totals were apportioned to th e Mendenhall Valley via human population. The surprisingly constant annual usage totals for propane indicate that this fuel is used more for cooking and waterheaters than for home h eating, a theory that the Mendenhall Valley Survey seems to support.

Natural Gas – Juneau does not use natural gas as a heating source because the landlocked geography makes its distribution impractical.

Coal –According to ADEC staff, coal is not used as a heating source in Juneau.



### 4.2 Other Area Sources

Asphalt Plants – The only asphalt plant in the Mendenhall Valley is the AEDCO Asphalt Plant, which is classified as a point source as discussed in Section 5 of this analysis.

Asphalt Paving – All particulate emissions from as phalt paving are in the form of condensable hydrocarbons (i.e., TOG or VO C emission factors), as shown in AP-42 section 4.5 for Asphalt Paving Operations. These emissions are included in VOC or TOG emission inventories, and should not be double-counted in particulate emission inventories. Therefore, there are no PM 10 

### emissions associated with asphalt paving.

Wildfires – There were no wildfires in th e Mendenhall Valley in either 2002—as confirmed by the Western Regional Air Pa rtnership’s (WRAP) recently completed 2002 air emission inventory for fire—or in 2004. Therefore, there are zero emissions from this

### -27- source in 2004. As wildfires are relatively rare in the Mendenhall Valley region, we are assuming that this will be the case as well in 2018.

Open Burning (Firefighter Training) – Local ADEC staff in Anchorage provided activity data for this emission source, which is assumed proportional to the activity in the Mendenhall Valley. In Anchorage, firefighter training was estimated to occur 28 times per year and to utilize 200 gallons of fuel pe r exercise, for a total of 5,600 total gallons burned during the summer months. This tota l was extrapolated to the Mendenhall Valley based on human population.

All fuel burned was assumed to be diesel. In the absence of any more accurate emission factors, the methodology used in the 1999 Ai r Toxics report was used to calculate emissions from this source; AP-42 emission fact ors for residential furnaces (Table 1.3-2) were applied to the activ ity data discussed above

Structural Fires – The total number of incidences fo r structural fires in 2004 was obtained

from the Juneau Fire Marshal. 8 

### Only a borough-wide total of 27 structural fires in 2004 was available; however, the Fire Marshal estimated that 70% of these fires occurred in the Mendenhall Valley and that about 65% of the fires occu rred in the wintertime and 35% occurred during the summer. Lacking projected estimates, the incidence level was assumed to be the same for calendar year 2018. Emission factors developed by the

California Air Resources Board * 

### (CARB) were applied to this activity estimate to generate the emission totals shown in Table 4-11.

Burn Barrels – Burn barrels are used in the Mendenhall Valley to supplement trash pickup during the summer (use of burn barrels is prohibited during the winter). However, no data on the frequency and degree of use of burn barrels have been collected for the Juneau area. In order to estimate the potential emissions from these sources, a sensitivity analysis was performed. The analysis used an estimate of 2,137 lbs of refuse generated per household in a year, which was derived from estimates develope d for California by CARB, 9 

### and assumed that 10% to 25% of the refuse is burned while the rest is picked up.

The estimated PM 10 

### emissions from burn barrels are shown in Table 4-5. As shown, burn

barrels contribute 0.5% of the total PM 10 

### area source emissions in the Valley at the 10% burning level estimate and about 1.2% of the total area source PM 10 

### emissions at the 25% burning level estimate. Since the PM 10 

### contribution from burn barrels becomes significant at the higher percentages of refuse burned, a survey effort should be

undertaken to estimate the actual contribution from these sources in the Valley. As a conservative assumption, emissions from burning 25% of the total refuse generated were

used in the area source emission summaries in Table 4-11 and in the Executive Summary.

Gasoline Distribution – This area source category is a source of VOC emissions only, and

therefore is not included in this effort.

Surface Coatings – This area source category is a source of VOC emissions only, and

therefore is not included in this effort.

* “Area Source Methodologies Manual,” California Air Resources Board, March 1999.

### -28- Table 4-5

PM 10 

### Emissions from Burn Barrels in the Mendenhall Valley (tons/day)

Summer 2004 Summer 2018 Source 10% Burned 25% Burned 10% Burned 25% Burned

Burn Barrels 0.023 0.057 0.025 0.062

Total Area Sources 4.598 4.598 4.809 4.809

Burn Barrels as % of Total 0.5% 1.2% 0.5% 1.3%



### 4.3 Fugitive Dust

Paved and Unpaved Roads

Emissions of PM 10 

### in the form of fugitive dust from paved and unpaved roads were developed for the Mendenhall Valley nonattainment area. The equations used for estimating both paved and unpaved road emi ssions on a per-VMT basis were derived from current procedures in the U.S. Envir onmental Protection Agency’s (EPA’s) AP-42

report. 10 

### Calendar year 2004 roadway miles of unpaved roads, along with the associated vehicle miles traveled (VMT), were estimated from local data and discussions with state and local agency staff. Paved roadway VMT was estimated by subtracting the unpaved road VMT from the total VMT for all roads. For calendar year 2018, VMT were estimated from the 2004 levels using projec ted population growth data for the Mendenhall Valley. It was conservatively assumed that the percentage of total VMT on unpaved roads (0.33%) remained the same in 2018 as in 2004. A discussion of the procedures, data sources, and inventory results follows.

Estimating Roadway Particulate Emissions - EPA’s AP-42 is the agency’s compilation of emission factors and procedures for estimating emissions from a variety of stationary sources. The methods described in the repo rt for estimating fugitive dust emissions from unpaved and paved roads are summarized below.

Unpaved Roads – The equation in AP-42 for estimating particulate emissions from “dry” (no precipitation), unpaved publicly accessible ro ads dominated by light-duty vehicles is given as Equation 1 below:

Eqn. 1 C M Ssk E

− = 2.0 5.0



### )5.0/( )30/)(12/(

where: E is the dry emission factor in lb/VMT; k is a particle size em pirical constant (1.8 for PM 10 

### , 0.27 for PM 2.5 

### ); s is the surface material % silt content; M is the surface soil % moisture content; S is the mean vehicle speed in miles per hour (mph); and

### -29- C is the 1980’s motor vehicle particulate emission factor in lb/VMT (0.00047 for

PM 10 

### , 0.00036 for PM 2.5 

### ). *



### Juneau- or Alaska-specific factors were us ed in Equation 1 as much as possible for estimating unpaved road emissions for the Mende nhall Valley. For the surface material silt content, 15% was used, which was th e average from samples collected on unpaved streets in the Mendenhall Valley for a 1988 PM 10 

### inventory prepared by Engineering

Science for EPA. 5 

### The soil moisture content used in this analysis was 1.1%—the average found for measured unpaved roads in Region 10. 11 

### Based on discussions with the City and Borough of Juneau, the m ean vehicle speed on unpaved roadways was estimated at 25 mph.

The fugitive dust emissions estimated using Equation 1 are during the average “dry” conditions of unpaved roads in a given area. That is, the natural mitigating effect of precipitation would need to be considered since any increase in moisture reduces the

level of emissions from the roads. In orde r to account for the natural precipitation that control fugitive dust in the local areas, the dry emission factor E is adjusted using Equation 2 from AP-42

Eqn. 2 

## [ ] NpNEE

unpaved 

### /)( −=



### where: E unpaved 

### is the final unpaved roads emission fa ctor adjusted for natural mitigation in lb/VMT; N is the total number of days in the study period (182 for summer and 183 for winter); and p is the number of days in the study period with measurable amounts (at least 0.01 inch) of precipitation.

Locality-specific precipitation days for Juneau were derived from the monthly averages available from the Western Regional Climate Center (WRCC). 12 

### The WRCC keeps records for days per month with measurab le precipitation (at least 0.01 inch) and has monthly averages over the last 50 years. The data for Juneau indicate that the area receives measurable precipitation for 117 days du ring the winter (October to March) and 106 days during the summer (April to September).

Paved Roads – Similar to unpaved roads, fugitive e missions from paved roads take into account road surface properties, traffic cond itions and climate fo r natural mitigation. Equation 3 shows the equation from AP-42, which considers all these factors for estimating paved road emissions:

* The previous versions of the unpaved and paved road emission factor equations in AP-42 included exhaust, brake-wear, and tire-wear emissions from vehicles in the 1980 calendar year fleet. These emissions are now estimated as part of the on-road mobile emissions and have decreased since 1980 due to lower new vehicle emission standards and new fuel specifications. Therefore, this needs to be removed from the AP-42 paved and unpaved road emissions in order to prevent double-counting of emissions.

### -30- Eqn. 3 

## [ ] NpNC WsL kE

paved 

### 4/)4( 32 5.1 65.0



### −    

   

−            

=

where: E paved 

### is the final unpaved roads emission f actor adjusted for natural mitigation in lb/VMT; k is a particle size empirical constant (0.016 for PM 10 

### and 0.004 for PM 2.5 

### ); sL is the road surface silt loading in g/m 2 

### ; W is the average weight of vehicle traveling the road in tons; C is the 1980’s motor vehicle particulat e emission factor in lb/VMT (0.00047

for PM 10 

### , 0.00036 for PM 2.5 

### ); N is the total number of days in the study period (182 for summer and 183 for winter); and p is the number of days in the study period with measurable (at least 0.01 inch) precipitation.

Equation 3 is analogous to the combination of Equations 1 and 2 for fugitive dust from unpaved roads. However, Equation 3 includes a factor of “4” in the natural precipitation mitigation effects because paved roads dry qui cker than unpaved roads after precipitation

events.

No paved road silt loading data are available from the Juneau area. Therefore, the road surface silt loading values for the paved roads in Mendenhall Valley were based on paved road samples collected from different roadway facility types in Anchorage in 1996. 13


### The silt loading values used by season are shown in Table 4-6. * 

### The average weight of the vehicle traveling on the roads was set to 2.0 tons, which was used for the Mendenhall Valley paved roads in the 1988 Engi neering Science report for EPA. 5 

### The days per season with measurable precipitation were the same ones used for Equation 2.

Table 4-6 Seasonal Paved Roads Silt Loading (g/m 2 

### ) by Facility Type 

### Facility Winter Summer
Interstate/Major Arterial 2.6 20.4

Minor Arterial 1.1 6.7

Collector 2.9 9.4

Local Roads 4.7 18.4

* The paved road silt loadings used in this analysis are different from those used in a 1988 EngineeringScience report prepared for the Mendenhall Valley, which applied national average default values in AP42. Since the silt loading measurements taken in Anchorage represent at least state-specific measurements, these Anchorage silt loadings were deemed as bette r estimates for the paved road silt loading in the Mendenhall Valley than the national defaults.

### -31- Both the paved and unpaved road emission fa ctors calculated using the AP-42 equations are expressed on a per VMT basis (lb/VMT) . Therefore, the VMT for the paved and unpaved roadways in the nonattainment area need to be estimated. The following section describes the traffic data and sources used in estimating the VMT for the paved and unpaved roads in the Mendenhall Valley.

Roadway Activity Estimates and Data Sources
- 

### The total daily VMT for a road is calculated as the product of the annual av erage daily traffic (AADT) and the roadway length in miles (VMT = AADT × Road Length). First, the total daily VMT for all roads in the Valley were estimated. The VMT and associated emissions for the unpaved roads were then estimated using the unpaved road mileage and AADT. Lastly, the VMT for unpaved roads were subtracted from the Valley VMT, and the remaining VMT was used to estimate emissions from the paved roads.

Total Mendenhall Valley Nonattainment Area VMT – The total 2004 VMT estimates by facility were developed for the nonattainment area by extrapolating average daily travel on DOT&PF monitored roadways in the Mendenhall Valley to the rest of the network, and adjusting some 1999 VMT estimates to 2004 levels using yearly population data for the nonattainment area. After this, the 2004 VMT estimates were forecasted to 2018 levels using yearly population data for the ar ea. This results in the 2004 and 2018 annual average total VMT shown in Table 4-7. The detailed development of the total Mendenhall Valley VMT levels is discussed as part of the On-Road section of this report. No seasonal data are available to reflect any seasonal variation in VMT; therefore, the average annual daily VMT was used for both the summer and winter seasons as a conservative approach.

Table 4-7 Mendenhall Valley Annual Average VMT/Day by Facility 

### Facility 2004 VMT 2018 VMT
Major/Principal Arterial 63,278 69,013

Minor Arterial 39,585 43,173 Collector/Intrazonal 58,370 63,661
Local 141,367 154,180

ALL TOTAL 302,599 330,028

Unpaved Roadway VMT – The 2004 pavement data from DOT&PF 14 

### were used to estimate the miles of unpaved roads in the Valley. In addition, DOT&PF provided data on unpaved roadways that were not included in the 2 004 pavement data. 15 

### DOT&PF indicated that the pavement road data are up-to-date for the DOT&PF-maintained roadways, but that the information on roads maintained by other agencies may be outdated. Consequently, the CBJ was c ontacted for 2004 unpaved road data for roadways under their management, 7 

### and the CBJ data were compared with the DOT&PF data to eliminate duplicates and double countin g. Because DOT&PF indicated that their

### -32- information on roads maintained by other ag encies might be outdated, more confidence was given to the CBJ data when conflicting information existed on paving status for some roadways between the DOT&PF and CBJ data sets. From these, 2004 unpaved roadway

miles and VMT were estimated.

For VMT and AADT, data within the Mendenha ll Valley are limited. Consequently, the only unpaved local road AADT available for Juneau comes from the 1988 PM 10 

### emissions inventory prepared for the Mendenhall Valley by Engineering Science. 5 

### In the report, an AADT of 171 was obtained from counts performed on 12 local streets. This estimate was adjusted to 2004 levels using the Borough population growth between 1988 and 2004. The 1988 population was estim ated by Engineering Science in the PM 10 

### inventory report, while the 2004 Borough po pulation came from the Alaska Department of Labor and Workforce Development (DLWD). * 

### The resulting adjusted AADT applied to all unpaved local roadways in Juneau is 177 vehicles per day. This, combined with the total miles of unpaved roads in the Valley, resulted in a total unpaved road daily VMT of 995 in the Mendenhall Valley nonattainment area. In 2018, the conservative assumptions were made that the same stretch of local unpaved roadways in 2004 remained unpaved and the percentage of total VMT (forecasted to 2018 using population forecasts) on unpaved roads remained the same. This resulted in a total unpaved road daily VMT of 1,085 in 2018 for the nonattainment area.

A summary of the data sources, unpaved roadway miles, and VMT estimated for Mendenhall Valley is shown in Table 4-8. As shown, a to tal of 5.62 miles of unpaved roadways—all local roads—were found for the Mendenhall Valley for 2004. Of this, about 5.21 miles are gravel or aggregate road s, 0.14 miles are undeveloped dirt roads, and 0.28 miles are overlaid with recycled asphalt pavement (RAP). † 

### The same distribution of unpaved surface types was assumed for 2018.

Table 4-8 Mendenhall Valley Unpaved Road VMT and Data Sources 

### 2004 Unpaved Roads 2018 Unpaved Roads Data Source Facility Type Miles VMT Miles VMT

DOT&PF Local 1.15 203 1.15 222

CBJ Local 4.47 791 4.47 863

ALL TOTAL 5.62 995 5.62 1,085

* The 1998 population for just the Mendenhall Valley was not available; therefore, borough-wide population growth was used. The 1988 total boro ugh population was 29,946, and the 2004 population was 30,966.

† Recycled asphalt pavement (RAP) is reprocessed pa vement materials containing asphalt and aggregates that, when processed properly, consist of high-quality, well-graded aggregates coated by asphalt cement. RAP provides some, but not complete, control on fugitive dust emissions from unpaved roads.

### -33- Paved Roadway VMT – The resulting paved roadway VMT for the Mendenhall Valley nonattainment area after the unpaved roadway VMT were subtracted from the total VMT are shown in Table 4-9 by facility.

Table 4-9 2004 and 2018 Mendenhall Valley Paved Road VMT by Facility 

### Facility 2004 VMT 2018 VMT
Major/Principal Arterial 63,278 69,013

Minor Arterial 39,585 43,173 Collector/Intrazonal 58,370 63,661 Local 140,372 153,096

ALL TOTAL 301,605 328,943

PM 10 

### Fugitive Dust Emission Inventories
- 

### The emission factors for paved and unpaved roads found using Equations 1 through 3 from AP-42 were combined with the paved and unpaved road VMT estimates to result in the PM 10 

### fugitive dust emissions for Mendenhall Valley. The 2004 and 2018 seasonal PM 10 

### inventories are shown in Table 4- 10. The annual average emission inventories were estimated by weighting the summer and winter emission levels by the number of days in each season as defined by ADEC—

183 for the summer and 182 for the winter.

Table 4-10 Seasonal Road Fugitive Dust Emissions in Mendenhall Valley



### PM 10 

### (tons/day) Calendar

Year Source Winter Summer Annual Avg

Paved Roads 1.48 4.14 2.81 Unpaved Roads 0.16 0.19 0.18 2004

TOTAL 1.64 4.33 2.99

Paved Roads 1.61 4.51 3.07 Unpaved Roads 0.18 0.21 0.19 2018

TOTAL 1.79 4.72 3.26

Wind Blown Dust



### There are two categories of windblown dust incl uded in this inventory: glacial riverbeds and cleared areas, both of whic h are discussed in detail below.

Glacial River Beds – This category includes sand bars along glacial rivers, which are large enough to generate significant emi ssions during periods of high winds. In

### -34- developing the 1988 PM 10 

### emissions inventory, Engineering Science examined aerial photographs of the Mendenhall Valley and concluded that only area where such

emissions would occur is at the eastern shore of the Mendenhall Lake near the mouth of Nugget Creek. The sand bars located in that area were estimated to be 41 acres and produce 28.6 tons of PM 10 

### per year. To be conservative, the acreage of sand bars was assumed to be unchanged. A review of AP-42 showed that the emission factor calculation methodology is unchanged; therefore, the previous estimates of emissions for this category are unchanged.

Cleared Areas – This category includes open areas where the vegetation has been destroyed and the surface material is susceptible to entrainment by wind. Engineering Science examined aerial photographs and determined that 154 acres of land were open

and cleared for the 1988 PM 10 

### emissions inventory. Using wind speed data collected from the Juneau Airport and silt loading values estimated from local bulk samples, they estimated this source category to produce a total of 4.4 tons of PM 10 

### per year. Lacking any new data on the number of acres, the silt loadings or the wind speed, it has been conservatively assumed (since the amount of cleared land has dropped as development in the Valley has expanded) that the emissions for this source are unchanged.



### 4.4 PM 10 

### Area Source Inventory

Table 4-11 shows the PM 10 

### total area source emissions for the Mendenhall Valley Area, by source category, and illustrates the fact that fugitive and windblown dust comprises the majority (approximately 97%) of the average annual PM 10 

### emissions in the Mendenhall Valley for both 2004 and 2018. Ot her source categories that show relatively high totals of PM 10 

### emissions include woodstoves/fi replaces and burn barrels.

Table 4-11

2004 and 2018 PM 10 

### Area Source Emissions for the Mendenhall Valley Nonattainment Area (tons/day)

Calendar Year 2004 Calendar Year 2018

Area Sources Summer Winter Annual Summer Winter Annual
Asphalt Production N/A N/A 0.0000 N/A N/A 0.0000 Asphalt Paving 0.0000 N/A 0.0000 0.0000 N/A 0.0000

Gasoline Distribution N/A N/A 0.0000 N/A N/A 0.0000

Used Oil Combustion N/A 0.00004 0.00002 N/A 0.00004 0.00002

Fuel Oil Combustion 0.0010 0.0019 0.0014 0.0020 0.0011 0.0016 Surface Coatings N/A N/A 0.0000 N/A N/A 0.0000

Wildfires 0.0000 N/A 0.0000 0.0000 N/A 0.0000 Open Burning (firefighter training) 0.0000003 N/A 0.0000002 0.0000003 N/A 0.0000002 Burn Barrels (refuse burning) 0.0571 0.0000 0.0286 0.0623 0.0000 0.0312 Woodstoves/Fireplaces 0.0333 0.0972 0.0652 0.0363 0.1060 0.0711
Propane Use 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 Natural Gas Heating N/A N/A 0.0000 N/A N/A 0.0000 Paved Road Fugitive Dust 4.1353 1.4785 2.8106 4.5102 1.6125 3.0653 Unpaved Road Fugitive Dust 0.1899 0.1612 0.1756 0.2071 0.1758 0.1915

Glacial/Cleared Areas Windblown Dust 0.1808 0.1808 0.1808 0.1808 0.1808 0.1808

Structural Fires 0.0002 0.0005 0.0004 0.0002 0.0005 0.0004

TOTAL 4.598 1.920 3.263 4.999 2.077 3.542



### ###

### -35- 

### 5. POINT SOURCES

Discussions with ADEC staff confirmed that there is only one permitted source that is located in the Mendenhall Valley nonattainment area—an asphalt batch plant. The terms of the permit authorize the plant to operate c ontinuously (24 hours per day) at a rate of 60 tons per hour for a 5-month period. There are two sources at the facility: a generator and a burner. The generator is rated at 400 hp/hr, and the burner has a maximum fuel rate of 180 gallons/hr. The activity rates, permitted limits, and daily emission rates are

summarized in Table 5-1. It should be noted that the daily value is extremely conservative as it is based on the potential of the facility to emit.

Table 5-1 Mendenhall Valley Point Source Summary Asphalt Batch Plant

Source Activity Rate 5-Month PM 10 

### Emission Limit (tons) Daily Emissions

PM 10 

### (tons)



### Generator 400 hp/hr 23.10 0.128

Burner 180 gallons/hr 4.86 0.027

Total 27.96 0.155

###

### -36- 

### 6. REFERENCES

1. http://epa.gov/air/data/monvals.html

2. Amendments to Volume II, Section III, Areawide Pollutant Control Program, Subpart D “Particulate Matter”, 3. Control Plan for Mendenhall Valley of Juneau,

Rev. 5/12/93.

3. Amendments to Volume II, Section III, Areawide Pollutant Control Program, Subpart D “Particulate Matter”, 3. Control Plan for Mendenhall Valley of Juneau,

Rev. 5/12/93.

4. Memo to Alice Edwards from Bob Dulla, “Results of Juneau Home Heating Survey

and Related PM 10 

### Emission Estimates,” July 19, 2004.

5. “PM10 Emission Inventories for the Mendenhall Valley and Eagle River Areas,” prepared for U.S. Environmental Protection Agency, Region X, by Engineering Science, February 1988.

6. Communication with Mary Ann Dierck man, Transportation Planner, JuneauHeadquarters, Department of Transportation and Public Facilities (DOT&PF), MayJune 2005.

7. Communication with Mike Scott, Str eets Superintendent, City and Borough of Juneau, June 2005.

8. Communication with Richard Etheridge, Fire Marshal, Capital City Fire/Rescue Fire Department, Juneau, Alaska, August 2005.

9. “Staff Report: Initial Statement of Reasons for the Proposed Airborne Toxic Control

Measure to Reduce Emissions of Toxic Ai r Contaminants from Outdoor Residential Waste Burning,” California Air Resources Board, January 4, 2002.

10. “AP 42, Fifth Edition, Compilation of Air Pollutant Emission Factors, Volume 1: Stationary Point and Area Sources,” Se ction 13.2.1-13.2.2 Paved and Unpaved Roads, Environmental Protection Agency, December 2003.

11. C. Cowherd, Jr., et al., “Improved Activ ity Levels for National Emission Inventories of Fugitive Dust from Paved and Unpaved Roads,” Presented at the 11th International Emission Inventory Confer ence, Atlanta, Georgia, April 2002.

### -37- 12. Average Number of Days with Measurable Precipitation for Alaska, Historical Climate Information, Western Regional Climate Center website, http://www.wrcc.dri.edu/htmlfiles/ ak/ak.01.html, Updated to 2004.

13. “Identification, Quantification, and Control of PM-10 Sources in Anchorage,” prepared by Midwest Research Institute for the Municipality of Anchorage, April 15,

1999.

14. Communication with Kathleen Ramage, Road Network Service Manager, Division of Program Development, Alaska Department of Transportation and Public Facilities (DOT&PF), May 2005.

15. Communication with David Hawes, Tr ansportation Planner, Southeast Region, Department of Transportation and Public Facilities (DOT&PF), May 2005.

## Appendix A Inventory Preparation and Quality Assurance Plan

### Inventory Preparation and Quality Assurance Plan

for Juneau – Mendenhall Valley PM 10 

### Emission Inventory

Prepared for:

Alaska Department of Environmental Conservation

June 3, 2005

Prepared by:

Sierra Research, Inc.

1801 J Street Sacramento, CA 95814 (916) 444-6666

### A-1 

## INTRODUCTION

Background

The Mendenhall Valley, located nine miles from downtown Juneau, is the largest residential area in the region. Bounded by sh arply rising mountains on the east and west and the Mendenhall Glacier to the north, the valley is well sheltered from prevailing winds. This topography, combined with a low winter sun angle that limits solar heating, supports the development of re latively severe temperature i nversions. These inversions trap emissions close to the valley floor and in the past led to seve re concentrations of airborne particulate matter that exceeded state and federal ambient air quality standards

for PM 10



### .

The Mendenhall Valley is currently classified as a moderate PM 10 

### nonattainment area. Despite this classification, no exceedances of either the annual or the 24-hour standard have been recorded in more than a decade (based on a review of EPA monitoring data between 1994 and 2004). 1 

### This is the result of planni ng and implementation efforts by both DEC and the City and Borough of Juneau (CBJ). Those efforts, documented in a 1993 State Implementation Plan (SIP) submission, 2 

### identified the following key emission

sources:

• Smoke from residential wood combustion (home heating);

• Fugitive dust from travel on unpaved roads; and

• Fugitive dust from travel on paved roads.

To reduce emissions from these sources, th e SIP implemented a wood smoke control program and a fugitive dust abatement progra m. Elements of the wood smoke control program included an aggressive public education program; implementation of a real-time monitoring system linked to episodic controls of wood burning; prohibition of open burning (during winter months); new stove certification requireme nts; and enforcement of the CBJ woodsmoke ordinance. The fugitive dust abatement program focused on paving unpaved roads in the Valley. Both programs have been successful and led to significant reductions in key emission sources within the Valley. Recent work by Sierra, 3



### under contract to ADEC, indicates the intr oduction of new technology has also had a significant impact on home heating emissions. Collectively, we estimate that the combination of new technology, related sh ifts in wood use, a nd implementation of control measures, reduced PM 10 

### emissions by 85% from 1993 to 2004. Key contributors to these reductions include the following:

### A-2 • Initiatives (e.g., burn bans, public edu cation, new stove requirements, etc.) implemented under the Juneau wood smoke control program;

• A drop in wood use per household from 1.8 cords per heating season in 1993 to 1.1 cords in 2004;

• Widespread use of direct vent -type fuel oil heaters; and

• Reductions in emission factors for both fuel oil and wood burning.



### Approach

Sierra will follow the source-specific data collection and modeling procedures detailed in the EPA emission inventory guidance document: “PM-10 Emission Inventory Requirements,” Final Report, September 1994. As noted above, key emission sources identified in the previous inventory were smoke from residential wood combustion and fugitive dust from both paved and unpaved roads. Given the significance of these sources and the efforts placed on controlling their emissions, it is imperative that new activity information be collected to characterize current emission levels from each of these sources. The home heating survey condu cted last year provides detailed insight into the impact of both technology changes and related activity le vels on residential heating emissions. No similar survey has been conducted to support an update of fugitive dust from paved and unpaved roads.

In order to prepare an accurate update to these source categories, Sierra intends to collect information on the mileage of paved/unpaved roads in the Valley, and obtain recent traffic counts and related speed estimates. A description of the methodology is presented

in the next section. Aside from these activit y estimates, another key element of fugitive dust calculations is the silt content of the roads. A review of the last emission inventory prepared for the Valley 4 

### shows that silt loadings were collected locally to support the preparation of fugitive dust emissions for unpaved roads, and that national average silt loadings were used to estimate on-road levels. Since no controls have been targeted at controlling silt loadings for unpaved roads, Sierra sees no need to update those estimates. However, controls have been targeted at reducing the mileage of unpaved roads and a corollary benefit of these controls should be a reduction of silt loadings (i.e., fugitive dust) on paved roads. For this reason, we intend to collect silt loadings for a representative sample of paved roads (samples will be distributed across both road type and traffic volume) and use the results alon g with recent traffic counts to support an update of fugitive dust emitted from this s ource category. A description of the methodology to be used for collecting the silt samples is presented in Appendix X.

### A-3 

### Organization

The remainder of this report is organized to address the methods that will be used to compute emissions from the data obtained in the surveys and the quality assurance procedures that will be employed in the development of the emission inventory estimates.

###

### A-4 

## EMISSIONS DATA AND METHOLOGY

The development of an emissions inventory can be divided into two primary steps: (1) identifying and collecting the activity data needed to characterize source-specific operations, and (2) selecting and using methodologies to translate the activity measurements into emissions. Presented below is a review of the activity data needed to characterize each of the source categories a nd the methods that will be used to compute emissions for each source category.



### Collection of Activity Data

On-Road Mobile Sources – For on-road mobile sources, this effort will focus on collecting information on vehicle activity data and identifying the miles of roadway in the Valley that remain unpaved. Juneau is not large enough to qualify as a metropolitan planning organization (MPO) a nd related funds for the deve lopment of a travel demand model. As a result, the only option for estimating vehicle miles of travel (VMT) is to obtain local traffic counts and related speed measurements, and to develop a method for extrapolating that information to represent all of the roads in the Valley. In a previous study, 5 

### Sierra contacted both CBJ and the Alaska Department of Transportation and Public Facilities (ADOT&PF) and obtained c ounts for information on the Juneau VMT

data. Sierra received three data files from ADOT&PF:

• JunroutebyFC.txt - contains the route description, route number, mile points, termination name (end of segment), and functional class (FC). The functional classes are identified as any of these f our descriptions: Urban Minor Arterial, Urban Other Principal Arterial, Urba n Collector, or Urban Local Road.

• Juneau_vmt99.txt - contains the route number, route name, mile point, feature (landmark), Average Daily Traffic (ADT), length (miles), and the resulting

VMT.

• Juneauspeed.prn - contains the route numbe r, route name, beginning mile point, end mile point, length, and posted sp eed limit. Out of 720 segments, 614 segments have no posted speed limit.

These three data sets were used to prepare estimates of the functional class, VMT, and average speed for each Juneau roadway segment. Sierra plans to contact ADOT&PF to

### A-5 obtain updates to these files as part of a relate d NTP. Once that information is available, Sierra will then need to extract information for the roads located within the Valley. This will be accomplished by contacting CBJ and ADOT&PF staff for information on the miles of roadway that are unpaved within the Valley.

Non-Road Mobile Sources – For non-road mobile sources, Sierra has prepared estimates of activity and emissions for Juneau in the previously referenced study. Since little information is available to characterize local activity levels in Juneau, that effort focused on identifying those sources that actually exist and operate within the Valley. Examples of source categories that should be exclude d are boats, locomotives, and aircraft. * 

### Sierra plans to review each of the non-road source categories to determin e if operation should

be excluded on a seasonal basis and to deter mine if any local operating data are available to characterize activity levels.

Area Sources – For area sources, Sierra plans to use the activity and fuel use information collected in last year’s home heating survey to quantify residentia l emissions. Data on the mixture of devices used to heat commercial businesses located within the Valley will be obtained through phone calls. To provi de a conservative estimate of windblown dust emissions, the Engineering Science estimate of the acreage of cleared land located within the Valley in 1988 will be held constant.

Data collected from the Western Regional Climate Center (WRCC) 6 

### indicate that the Juneau area receives measurable precipitation for 117 days during the winter (October to March) and 106 days during the summer (April to September). In light of the extensive rainfall and lack of large scale agriculture within the nonattainment area, no emission estimates will be prepared for agricultural burning, prescribed burning, or wildfires.

Point Sources – Sierra will contact ADEC to obtain information on permits for point sources located within the Valley. Key va riables to be obtained include the following:

• Maximum allowable emission limit or federally enforceable permit limit;

• Actual or design capacity (whichever is greater) or federally enforceable permit limit; and

• Actual operating factor averaged over most recent two years.

Valley Demographics – In the course of preparing the estimate of Juneau home heating emissions, Sierra found that updating the population statistics to account for the growth that occurred since 1993 is not an easy task. This is because the boundaries of available demographic measurement systems (e.g., censu s tracts, etc.) do not match those of the Mendenhall Valley. We found th at all available population metrics come from systems that bifurcate the Valley. Census Tract 2, fo r example, covers the eastern portion of the

* No water bodies, airports, or railroads are located within the boundaries of the nonattainment area. Therefore, boats and locomotives cannot contribute to the inventory. While an airport and heliport are adjacent to the southern boundary of the nonattainment area, aircraft and helicopter flights skirt the nonattainment area due to noise concerns and do not contribute to the inventory.

### A-6 Valley. Census Tract 1, however, combines the western portion of the Valley with the Mendenhall Peninsula and Auke Bay. The we stern portion of the Mendenhall Peninsula and Auke Bay lie beyond the ridge that forms the western boundary of the Valley. No sources of population data could be identified for these areas (i.e., so that the population for the western portion of the Valley could be ne tted out of the available data). A further complicating factor is that portions of the south end of the Valley (i.e., the area surrounding the airport) were also excluded from the formal boundaries of the nonattainment area. No populati on data for this area could be identified either. A map of CBJ geographic areas presented in Figure 1 illustrates the problem.

Figure 1

In light of the inconsistency between Valley boundaries and demogr aphic boundaries, we

determined that the best me thod to update the population and dwelling estimates for the Valley was to assume that the growth experienced in the Valley was proportional to the growth experienced throughout the whole CB J area. Borough-wide population statistics

were obtained from the CBJ. Growth between 1988 * 

### and 2001 (the year most recently

* The emission inventory values reported in the 1993 SIP were the values produced in a 1988 report prepared by Engineering Science entitled “PM 10 Emission Inventories for the Mendenhall Valley and Eagle River Areas.” Emission calculations in that effort were based on 4,465 residential dwellings.

### A-7 available) was determined to be 3.2%. This value was a pplied to the base estimates reported in the 1993 SIP. The resulting estimate of 4,608 dwellings was used to extrapolate the results of the survey to the rest of the Valley. Sierra plans to review the accuracy of these assumptions with CBJ staff to confirm their reasonableness for (a) estimating base year populati on levels in 2004 and (b) iden tifying appropriate growth indices for forecasting population levels in 2018.



### Emission Calculation Methodologies

Annual and seasonal PM 10 

### emissions will be computed on the basis of the activity data developed in Task 2 and emission factors de rived from EPA’s AP-42. 7 

### Emissions will be computed on an annual basis and on a 24-hour basis for average summer and winter days as requested in the RFP.

The method to be used to compute on-road emissions will distinguish between fugitive and vehicle exhaust, tire, and brake wear emissions. Since unpaved road characteristics have not changed since development of the 1993 PM 10 

### attainment plan, the silt loadings published in the 1988 Engineering Science e mission inventory and relied upon in the 1993 plan will be used to compute emissions fo r this source category. Estimates of the miles of unpaved roads and tra ffic levels will be updated with information obtained through contacts with relevant state and local agencies.

The fugitive dust source category in which substantial change has occurred, with respect to emission factor strength since 1993, is pa ved road travel. With the paving of a significant fraction of unpaved roads in the study region since 1993, the track-on of soil onto paved roads has declined substantially. Since the unpaved roads were the sources of much of the track-on material, the paving of these roads has resulted in the reduction of surface silt loadings during non-sanding periods to levels similar to those of average urban streets as reported in AP-42. Therefor e, we will use average urban silt loadings incomputing paved road emission factors for paved road travel, except during the roadsanding season. These values will be updated once the results of the silt survey become

available.

Information on road sanding operations will be collected as a subtask under Task 2. Changes in abrasive composition, size distribu tion, and application ra te will be identified through interviews of road maintenance agencies. Based on this information, adjustments to the silt loadings used in the 1993 emission inventor y will be made and new emission factors for paved road travel during the road-sanding season will be developed.

Estimates of exhaust, tire, and brake wear emissions will be computed using MOBILE6.2. To develop these estimates, MO BILE6 will be configured to represent Juneau using average summer and winter temp erature values, VMT by speed (using data collected in Task 2), Juneau-specific vehicle registration data, and VMT mix computed for Juneau. Available mileage accumulation rates (e.g., Anchorage, Fairbanks, national

### A-8 default, etc.) will be reviewed to determine the data source that most appropriately represents Juneau since the local data needed to characterize this profile is not currently available. The development of the Juneau profile will be prepared under a related NTP.

Area Source Emissions – Area source emissions will be computed for residential and commercial facilities located within the Valley. Sierra plans to use the results of last year’s home heating survey and related emi ssion calculations to quantify residential heating emissions in 2004. That effort pr epared separate emission estimates for wooduse and fuel-oil heating. If the demographi c information obtained in Task 2 revises the number of homes located in the Valley in 2004, the previous estimates will be adjusted to

account for those revisions. Th e emission factors employed in that residential analysis

will be combined with the number of commercial facilities and related fuel-use estimates to estimate commercial heating emissions.

Windblown dust emissions will be calculate d using the emission factor methodology used by Engineering Science in the 1988 emi ssion inventory report. The emission factor methodology relies on the current emission m odel described in AP -42, which will be configured using the soil par ticle size distribution data published in the 1988 emission inventory report.

Non-Road Emissions – Non-road emissions will be computed using EPA’s NONROAD

model. It calculates tons of emissions for a geographical area using the following factors:

• Equipment population;

• An equipment-specific emission fact or (in grams per horsepower-hour);

• The average horsepower rating of the equipment;

• The estimated annual equipment activity factor (hours per year); and

• The average load factor for the engine.

In addition, seasonal (month or season) and da y or week (i.e., weekday versus weekend) adjustments are applied depending on the requi rements of the analysis. The equipment populations are based on national averages, a nd then scaled down to represent smaller geographic areas on the basis of human population and proximity to recreational, industrial, and co mmercial facilities.

Sierra is well aware that many of the national average default values employed in the NONROAD model do not well represent activity leve ls in Juneau (or Alaska). However, the development of location-specific info rmation can be expensive and non-road equipment represents a relatively small portion of the Juneau PM 10 

### inventory. For this reason, Sierra plans to focus on model assump tions about the equipment categories that are operating in Juneau during the summer and th e winter based on data collected in Task 2 and making adjustments to assumed activity levels ba sed on available Alaska- or Juneau-specific data.

### A-9 Point Source Emissions – Point source emissions will be derived from permits obtained from ADEC for any sources that are currently operating within the Valley. If any sources are operating in the Valley, one issue that will need to be addressed is whether rule effectiveness has been applied to the emission calculations.

Demographic forecasts obtained in Task 2 w ill be used to support the extrapolation of activity levels from 2004 to 2018. Emission f actors used to project emissions in 2018 will be updated from 2004 where information on th e benefits of new control measures is available (e.g., MOBILE6).

###

### A-10 

## QUALITY ASSURANCE PLAN

This section presents a review of the QA procedures to be employed during the development of the Mendenhall Valley PM 10 

### emission inventory. It includes all of the

critical elements recommended in the U.S. EPA document Guidance for the Preparation of Quality Assurance Plans for Ozone/C arbon Monoxide State Implementation Plan

Emission Inventories

, 8 

### as well as guidance provided through the Emission Inventory Improvement Program (EIIP). 9 

### It also provides written instructions for the technical and quality aspects associated with development of the new emission inventories. It is designed so that QA/QC procedures are implemented throughout the entire inventory development process. This will ensure that the inventory is as complete, accurate, comparable, and representative as possible.

Inventory tasks and QC procedures will include data checking by the inventory development team (IDT) throughout the devel opment of the inventory and final emission report. These procedures include, but are not limited to, the following:

• The development and implementation of written procedures for data collection, data assessment, data handling, cal culation of emissions, and reporting;

• Adequate management and supervision of the work;

• Review of all calculations for tec hnical soundness and accuracy, including verification that the appropriate emission factors were used and the impacts of controls were correctly addressed;

• Correct assignment of Source Category Codes;

• Assignment of DARS scores;

• Use of technically sound approaches when developing results based on engineering judgment;

• Documentation of the data in a manner that will allow reconstruction of all inventory development activities; and

• Maintenance of an orderly master file of all the data gathered and a copy-ready version of the final inventory submitted to the Project Manager.

### A-11 The emission inventories develope d in accordance with this plan are for SIP development and are considered Level II, based on guid ance provided by the 1996 EIIP. The estimates

contained in the inventories will be used to make decisions about the need for and types of control strategies required to ensure attainment with the ambient PM 10 

### standards. As a result, they must satisfy applicable quality assurance (QA) requirements.

The first step in this process is establishing the data quality objectives (DQO) for the new inventories. Table 1 summarizes of the proce dures to be employed in meeting the DQOs. It shows that considerable effort will be focused on meeting accuracy, completeness, representativeness, and comparability objectives. Table 2 shows the data quality indicators (DQIs) that will be used to m easure progress towards the DQOs. The Data Attribute Rating System (DARS) 10 

### will be used to verify the desired inventory accuracy.

Table 1 Data Quality Objectives

DQO Procedure for Achieving Objective

Accuracy For point and onroad mobile sources, the data generator will check 100% of the calculations, and another equally qualified inventory development team member will check 20% of the calculations. For area and nonroad mobile sources, the data generator will check 100% of the calculations, and another equally qualified IDT member will check 10% of the calculations. In all cases, the data validator will develop a written summary of his or her activities, and will conduct follow-up activities to ensure that data are corrected as needed. If more than 5% of the calculations checked by the data validator need to be revised, then

100% of the calculations will be checked.

Completeness Extensive planning will be conducted prior to data collection to identify all applicable emission sources. After identifying these sources, the goal will be to determine 100% of the emissions from the largest emitting sources from each source category and as many of the minor sources as possible within the time frame allotted for the work. Those sources identified but not included in the inventory will be identified in the data file and final report.

Representativeness Technical personnel will review all of the primary source data AND compare them to previous emission results and similar results from comparable regions to determine the reasonableness of the emissions estimates and representativeness of the data.

Comparability To ensure that the data are comparable, standard procedures will be followed and results will be presented in the same units that were used in previous criteria and toxic pollutant

inventories.

### A-12 Table 2 Data Quality Indicators

DQO Inventory DQI Target Values

Accuracy Achieve DARS score >= 0.7 for all area sources contributing >10% of total emissions of CO Achieve DARS score >=0.8 for all point sources >=70 tons per year (TPY). Achieve DARS score >=0.7 for onroad mobile source inventory. Achieve DARS score <=0.5 for nonroad mobile source inventory.

Completeness 100% of all point sources >= 70 tpy. 90% of all other point sources

Comparability Results to be compared to the previous Mendenhall Valley inventory.



### Managerial Responsibilities

Sierra will lead the preparation of the community emission inventories. Key assignments

shall include those outlined below.

Source Inventory Development Managers – The source inventory development managers are responsible for planning and leading sour ce-specific inventory development activities.

QA/QC Coordinator – The QA/QC Coordinator is respons ible for ensuring that adequate QA/QC procedures are incorporated into th e inventory development process. The QA Coordinator’s responsibilities a nd activities are as follows:

• Help develop the QAP;

• Provide QA training to inventory development and QA personnel;

• Attend inventory status meetings;

• Follow up on recommendation for corrective actions;

• Keep the Inventory Development Manager informed of actions;

• Work with the Project Manager to resolve any quality concerns that cannot be

resolved at the inventor y management level; and

• Maintain a file of findings a nd corresponding corrective actions.

The QA Coordinator reports directly to Sierra’s Project Manager overseeing the development of the inventory. These reportin g lines help provide an objective approach to the implementation of the QA program and reporting of quality issues.



### Schedule

Data collection activities are to be completed by early June. Emission inventory estimates will be completed and documented by the end of June.

### A-13 

### General QA/QC Procedures

QA/QC procedures described in this QAP were developed to help ensure data accuracy, completeness, representativeness, and comparability. These procedures have been incorporated in the technical procedures, where applicable, and will be implemented by the IDT throughout the planning, data collection, emission es timation, and reporting phases of the inventory development program.

QC procedures will be implemented by the IDT during inventory development to meet the technical objectives and DQOs. These activities will be conducted at the following steps in the inventory development process:

• Data collection;

• Data documentation;

• Calculation of emissions;

• Data checking and DARS scoring;

• Reporting; and

• Maintenance of the master file.

Data collection will be conduc ted according to U.S. EPA-approved procedures. The approach and supporting documents or refere nces will be thoroughly documented and included in the emissions report.

All activities conducted by the IDT will be documented. The traditional approach is to

use bound notebooks with indices to facilitate th e retrieval of recorded information. An alternate approach is to record activities electronically and make this information available to team members located in different parts of the state. To enhance communication and productivity, team members will be allowed to employ either approach but will be encouraged to track information relative to the development of the inventory electronically. This daily log of activities will help another IDT member reproduce the emission results and allow an evaluation of data accuracy and completeness.

The following procedures are to be followed when documenting data in the notebooks:

• Data will be recorded legibly and in black ink;

• Entries will be corrected by drawing a single line through the data and writing the

correct data above or below the correcti on (with initials, date, and explanation of corrections to allow reconstruction of the work);

• Complete descriptions of all data sources will be included (references to be included in final inventory report);

### A-14 • Units of measurements will provided for emission sources that are omitted from the final inventory (justifi cation required in report);

• The procedures used to calculate emissions will be described and example calculations will be provided;

• The approach used to determine completeness for each source type will be described;

• Documents from which emission factors are taken will be identified and referenced; and

• The source, agency, group, or company providing information by telephone will be identified (include te lephone number and date in formation was provided).

Worksheets and contact reports may also be used to maintain records of data sources or calculations; however, the same guidelines must be followed when recording information on them. A file will be developed specifically for these forms to ensure that they are retained and are easily located when the data are needed to calculate emissions. A contact report should include the date of c ontact; originator name, title, organization, and address of person contacted; and a summary. All worksheets, electronic spreadsheets, and notebooks will be reviewed periodically by the inventory development task leaders to determine whether the procedures describe d above are being followed. This review should be evidenced by a dated signature on the notebook pages or worksheets reviewed (i.e., reviewed by ________ on _______).

Data used in calculation emissions should be checked for data accuracy, reasonableness, and completeness. The results from data checking will be documented to further qualify the emission estimates. In addition to the DARS scores assigned, the number of data points checked assists reviewers in evaluating the accuracy of the completed emissions report. Documentation of DAR S scoring and data checking should include descriptions of the rationale for scoring, the data checke d, and the dated signature of the reviewer.



### Data Reporting

Reporting will be accomplished by submitting written documentation and emissions summaries to the Project Manager. A ll supporting documentation, project notebooks, data sheets, and calculations shall be submitted for review.

The report will include summary tables, raw listings of equipment, activity levels and emissions from individual sources, and a QA documentation section. A detailed inventory report allows compar ison of baseline inventories between one area and another and the evaluation of the impact of control strategies, and also facilitates updates to the inventory and development of projection inventories.

### A-15 In addition to EIIP guidance, the U.S. EPA report PM-10 Emission Inventory Requirements will be followed. These documents provide guidance for presenting and documenting SIP emissions inve ntories, and contain exampl es of how to present and verify inventory development efforts. The QA documentation section of the emissions inventory will provide enough detail so that the inventory development described in the report can be compared to the information provided in this QAP. Any discrepancies will be identified and explained.

At a minimum, documentation should describe in general terms how the inventory data were collected and where they came from. The report will include the components listed

below.

• A description of the geographic area in cluded in the inventory, including documentation for any adjustments made to the original designated area.

Documentation shall reference all sources of current or projected data, and include maps of borough bounda ries for excluded areas.

• The base year of the emissions inventory.

• The population of the area, and the source of the population data.

• Efforts taken as part of the QA program.

• Procedures used to temporally allocate each source category (e.g., selection of the months comprising the seasons, seasonal va riations in activity levels at sources, daily variation in activity levels, etc.).

The QA documentation section of the inventory report will describe each deviation from approved procedures or findings that could compromise the successful outcome of the inventory. Documentation of each finding will include a description of the action or data reviewed that led to the quality concern, along with a recommendation for corrective action. The QA documentation section of the inventory report will then discuss how the recommended corrective actions were implemented.

###

### A-16 

## REFERENCES

1. http://epa.gov/ai r/data/monvals.html

2. Amendments to Volume II, Section III , Areawide Pollutant Control Program, Subpart D “Particulate Matte r”, 3. Control Plan for Mendenhall Valley of Juneau,

Rev. 5/12/93.

3. Memo to Alice Edwards from Bob Dulla, Results of Juneau Home Heating Survey

and Related PM10 Emission Estimates, July 19, 2004.

4. “PM10 Emission Inventories for the Me ndenhall Valley and Eagle River Areas,” prepared for U.S. Environmental Protection Agency, Region X, by Engineering Science, February 1988.

5. Memorandum to Alice Edwards from Bob Dulla, et al, “Documentation for Criteria Pollutant Emission Inventories,” May 17, 2002.

6. Average Number of Days with Measur able Precipitation for Alaska, Historical Climate Information, Western Regi onal Climate Ce nter website, http://www.wrcc.dri.edu/htmlfile s/ak/ak.01.html, Updated to 2004.

7. Compilation of Air Pollutant Emission Factors, AP-42, U.S. Environmental Protection Agency, September 1995.

8. “Guidance for the Preparation of Qualit y Assurance Plans for O3/CO SIP Emission Inventories,” EPA-450/4-88-023, U.S. Envir onmental Protection Agency, Office of Air Quality Planning and Standards, Rese arch Triangle Park, North Carolina, 1988.

9. “Emission Inventory Improvement Program,” Volumes II-VI, prepared by State and Territorial Air Pollution Program Administrators and the Association of Local Air Pollution Control Officials (STAPPA/ALAPCO), 1996.

10. Beck, L.L., R.L Peer, L.A. Bravo, and Y. Yan, “A Data Attribute Rating System,” presented at the Air & Waste Management Association Specialty Conference on Emission Inventory Issues, Raleig h, North Carolina, November 1994.

###

## Appendix B

Demographic Estimates for City and Borough of Juneau, Mendenhall Valley

### B-1 

## Demographic Estimates for

City and Borough of J uneau and Mendenhall Valley

Three separate demographic data sources are available for Juneau:

• U.S. Census Bureau (Census Bureau)

• Alaska Department of Labor a nd Workforce Development (DLWD)

• City and Borough of Juneau (CBJ)

The Census Bureau conducts detailed demographic surveys once every decade. The most recent census reports available are for 1990 and 2000. Additiona l population estimates are also available for more recent years. The Research and Analysis Section of the DLWD develops population growth forecasts for the state and individual Boroughs. The most current is for the period of 1998 – 2018. DLWD also has population and household estimates for recent years. CBJ has populati on estimates for the entire Borough and its subregions (e.g., Douglas, Lemon Creek, etc.). CBJ is the only source of population and

household data for the nonattain ment area; that estimate was prepared in 1993 for the

“wood smoke control area of the Mendenhall Va lley.” A review of the 1993 SIP for the Mendenhall Valley shows that the boundaries of the wood smoke control area are the

same as the boundaries of the nonattainment area.

The problem with developing demographic estimates for the Mendenhall Valley

nonattainment area is that its boundaries do not match the boundaries of the demographic measurement systems (e.g., census tracts, Jun eau subregions, etc.). Figure 1 displays CBJ geographic areas. It shows that the Me ndenhall Valley is divi ded into two areas: east and west. The West Mendenhall Valley incl udes data for both the peninsula and for Auke Bay. The western portion of the Me ndenhall Peninsula and Auke Bay lie beyond the ridge that forms the western boundary of the nonattainment area. The southern portion of the East Mendenha ll Valley (the airport and adjacent areas) is below the southern boundary of the nonattain ment area. Because of thes e inconsistencies, it is not possible to map population estimates from the available surveys to the nonattainment

area.

The only approach available to prepare demographic estimates for the nonattainment area is to start with the 1993 CBJ estimates and assume that growth is proportional to the growth seen for the entire Borough. Implementing this assumption, however, is not straightforward as the population estimates available from DLWD and the Census Bureau are not always consistent. A summary of th e demographic information needed to make the projections is presented by source in Table 1. The discussion is organized by calendar year.

### B-2 Figure 1

Table 1 Population and Housing Estimates for City and Borough of Juneau and Mendenhall Valley Nonattainment Area
City and Borough Juneau Nonattainment Area Year Population Households Population Households

1988 29,946 4,465
1990 26,751 9,902

1993 27,882 12,000 4,401
2000 30,711 11,543

2002 30,584 11,591
2004 30,966 13,327 4,888

2018 33,774 14,535 5,331

### B-3 • 1988 – the year addressed in the Engineering Science PM 10 

### emission inventory for the nonattainment area. Populati on estimates for the entire Borough are available from CBJ. The Engineering Scie nce report did not present an estimate

of either the number of households or the population of the nonattainment area. An estimate of the number of households, however, can be derived from fuel use information presented in the report.

• 1990 – year for which detailed census records are available.

• 1993 – year in which DEC conducted a w ood smoke survey in the nonattainment area. Population and househol d estimates, prepared by CBJ for the nonattainment area (i.e., the wood smoke control area), were reported in the documentation * 

### and used to support an evaluation of the survey coverage.

• 2000 – year for which detailed census records are available.

• 2002 – the year to be addressed in the cr iteria pollutant emi ssion inventories for Anchorage, Fairbanks, and Juneau.

• 2004 – the base year of the PM 10 

### emission inventory for the nonattainment area, also recent population estimates are av ailable from DLWD and the Census

Bureau.

• 2018 – the horizon year of the PM 10 

### emission inventory for the nonattainment

area.

All values obtained from the sources noted above are presented in a normal font. Derived values are presented in bold. Presented below is a description of the methodology used to prepare the derived values.

• The 1988 estimate of households was derived by dividing the total amount of fuel oil used for residential heating by the average amount of fuel use per home (2,179

x 10 3 

### gallons/800 gallons per home). Th e resulting estimate of 2,724 homes was

increased to account for the fraction of homes that that did not use fuel oil (39%). The resulting estimate of 4,465 agrees very well with the CBJ value estimated for

1993. The difference between the estimates is 1% and the decline seen between 1988 and 1993 is consistent with the popula tion decline reported over the same period.

• The 1993 City and Borough population estimate was derived by interpolating the annualized growth rate between the 1990 and 2000 Census values.

* 1993 Wood Heating Survey of Mendenhall Valley Residents, Alaska Department of Environmental Conservation, October 20, 1993

### B-4 • The 2002 City and Borough population estimate was derived by selecting the mid-point between the 2000 Census va lue and the DLWD estimate for 2004. Surprisingly, the Census Bureau and DLWD offer different population estimates for 2004. (31,118 versus 30,966). The DLWD value was selected since that agency is focused exclusively on tracking Alaska demographic trends and is the sole source of growth projections for Juneau.

• The 2002 City and Borough household values were assumed to be proportional to the growth in population observed between 2000 and 2002. A review of the 1990

and 2000 Census values conf irmed that housing growth tracks population growth very closely.

• The 2018 population projection for the Ci ty and Borough was derived from

DLWD forecasts. Discussions with st aff confirmed that the most current population forecast for Juneau was last prepared for the period 1998 – 2018. * 

### A summary of the forecast is presented in Table 2. It shows that the growth rate for Juneau was projected to decline over the 20-year period addressed in the forecast. The annualized growth rate from 1998 – 2018 is 0.7% per year. Updates to this forecast are expected to be available late r this year. As noted above, more current estimates of Juneau popula tion levels are availabl e (see the Department’s

website † 

### ). Those values, 30,966 for 2004 and 31,246 for 2003 show that population levels actually declined by 280 in 2004. Using the 2004 value as the baseline, options for projecting growth ar e to use (a) the Juneau-specific values employed in the somewhat dated 1998 – 2018 forecast or (b) the more current statewide forecast available at the above cited website. The current middle range forecast for the state is 1.0% per year for the period of 2004 – 2018. Since this value very closely matches the statewide forecast of 1.1% employed in the 1998 – 2018 forecast, the Juneau-sp ecific forecast from 1998 – 2018 was used to project the 2004 base year population levels to 2018. The aggregate growth rate over this period is 9.0% (with an annualized rate of 0.62% per year) and the 2018 population level is forecasted to be 33,774.

Table 2 Mid-Range Population Forecasts for Juneau, Alaska

Year Population Growth Rate (%)
1998 30,236 -
2003 31,388 3.8
2008 32,413 3.3
2013 33,475 3.3
2018 34,447 2.9

* http://www.labor.state.ak.us/research/pop/pop-proj.pdf

† http://labor.state.ak.us/trends/feb05.pdf

### B-5 • The 2018 population and household values for the nonattainment area were assumed to be proportional to the growth in Borough-wide population between

2004 and 2018.

###

## Appendix C

On-Road Source CalculationsP:\ADEC\Mendenhall Valley PM10 Inventory\OnRoad\MVW04.in

Printed at 16:15 on 14 Jul 2005 Page 1 of 1

* CY2004 WINTER run for Mendenhall Valley Nonattainment Area

* PM10 Maintenance Plan

MOBILE6 INPUT FILE :

SPREADSHEET :

PARTICULATES :

RUN DATA :

MIN/MAX TEMP : 25.7 36.3

FUEL RVP : 13.6 REG DIST : jun_reg.prn

FUEL PROGRAM : 4

338.0 338.0 338.0 160.0 90.0 90.0 60.0 60.0

30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0

690.0 690.0 690.0 380.0 140.0 140.0 140.0 80.0

80.0 80.0 80.0 80.0 80.0 80.0 80.0 80.0

SCENARIO RECORD : Freeway - 50.5 mph

CALENDAR YEAR : 2004

EVALUATION MONTH : 1 AVERAGE SPEED : 50.5 Freeway

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 380

SCENARIO RECORD : Arterial - 37.2 mph

CALENDAR YEAR : 2004

EVALUATION MONTH : 1

AVERAGE SPEED : 37.2 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 380

SCENARIO RECORD : Arterial - 35.6 mph

CALENDAR YEAR : 2004

EVALUATION MONTH : 1

AVERAGE SPEED : 35.6 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 380

SCENARIO RECORD : Arterial - 20.8 mph

CALENDAR YEAR : 2004

EVALUATION MONTH : 1

AVERAGE SPEED : 20.8 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 380

END OF RUN :P:\ADEC\Mendenhall Valley PM10 Inventory\OnRoad\MVS04.in

Printed at 16:14 on 14 Jul 2005 Page 1 of 1

* CY2004 SUMMER run for Mendenhall Valley Nonattainment Area

* PM10 Maintenance Plan

MOBILE6 INPUT FILE :

SPREADSHEET :

PARTICULATES :

RUN DATA :

MIN/MAX TEMP : 42.3 57.7

FUEL RVP : 7.8 REG DIST : jun_reg.prn

FUEL PROGRAM : 4

338.0 338.0 338.0 160.0 60.0 60.0 60.0 60.0

30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0

690.0 690.0 690.0 380.0 150.0 150.0 150.0 80.0

80.0 80.0 80.0 80.0 80.0 80.0 80.0 80.0

SCENARIO RECORD : Freeway - 50.5 mph

CALENDAR YEAR : 2004

EVALUATION MONTH : 7 AVERAGE SPEED : 50.5 Freeway

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 380

SCENARIO RECORD : Arterial - 37.2 mph

CALENDAR YEAR : 2004

EVALUATION MONTH : 7
AVERAGE SPEED : 37.2 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 380

SCENARIO RECORD : Arterial - 35.6 mph

CALENDAR YEAR : 2004

EVALUATION MONTH : 7
AVERAGE SPEED : 35.6 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 380

SCENARIO RECORD : Arterial - 20.8 mph

CALENDAR YEAR : 2004

EVALUATION MONTH : 7
AVERAGE SPEED : 20.8 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 380

END OF RUN :P:\ADEC\Mendenhall Valley PM10 Inventory\OnRoad\MVW18.in

Printed at 16:15 on 14 Jul 2005 Page 1 of 1

* CY2018 WINTER run for Mendenhall Valley Nonattainment Area

* PM10 Maintenance Plan

MOBILE6 INPUT FILE :

SPREADSHEET :

PARTICULATES :

RUN DATA :

MIN/MAX TEMP : 25.7 36.3

FUEL RVP : 13.6 REG DIST : jun_reg.prn

FUEL PROGRAM : 4

338.0 338.0 338.0 160.0 90.0 90.0 60.0 60.0

30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0

690.0 690.0 690.0 380.0 140.0 140.0 140.0 80.0

80.0 80.0 80.0 80.0 80.0 80.0 80.0 80.0

SCENARIO RECORD : Freeway - 50.5 mph

CALENDAR YEAR : 2018

EVALUATION MONTH : 1 AVERAGE SPEED : 50.5 Freeway

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 15

SCENARIO RECORD : Arterial - 37.2 mph

CALENDAR YEAR : 2018

EVALUATION MONTH : 1

AVERAGE SPEED : 37.2 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 15

SCENARIO RECORD : Arterial - 35.6 mph

CALENDAR YEAR : 2018

EVALUATION MONTH : 1

AVERAGE SPEED : 35.6 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 15

SCENARIO RECORD : Arterial - 20.8 mph

CALENDAR YEAR : 2018

EVALUATION MONTH : 1

AVERAGE SPEED : 20.8 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 15

END OF RUN :P:\ADEC\Mendenhall Valley PM10 Inventory\OnRoad\MVS18.in

Printed at 16:15 on 14 Jul 2005 Page 1 of 1

* CY2018 SUMMER run for Mendenhall Valley Nonattainment Area

* PM10 Maintenance Plan

MOBILE6 INPUT FILE :

SPREADSHEET :

PARTICULATES :

RUN DATA :

MIN/MAX TEMP : 42.3 57.7

FUEL RVP : 7.8 REG DIST : jun_reg.prn

FUEL PROGRAM : 4

338.0 338.0 338.0 160.0 60.0 60.0 60.0 60.0

30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0

690.0 690.0 690.0 380.0 150.0 150.0 150.0 80.0

80.0 80.0 80.0 80.0 80.0 80.0 80.0 80.0

SCENARIO RECORD : Freeway - 50.5 mph

CALENDAR YEAR : 2018

EVALUATION MONTH : 7 AVERAGE SPEED : 50.5 Freeway

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 15

SCENARIO RECORD : Arterial - 37.2 mph

CALENDAR YEAR : 2018

EVALUATION MONTH : 7
AVERAGE SPEED : 37.2 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 15

SCENARIO RECORD : Arterial - 35.6 mph

CALENDAR YEAR : 2018

EVALUATION MONTH : 7
AVERAGE SPEED : 35.6 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 15

SCENARIO RECORD : Arterial - 20.8 mph

CALENDAR YEAR : 2018

EVALUATION MONTH : 7
AVERAGE SPEED : 20.8 Arterial

PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV

PARTICLE SIZE : 10

DIESEL SULFUR : 15

END OF RUN :P:\ADEC\Mendenhall Valley PM10 Inventory\OnRoad\jun_reg.prn

Printed at 16:18 on 14 Jul 2005 Page 1 of 1

REG DIST

*

* JUNEAU AREA REGISTRATION DISTRIBUTION BY VEHICLE AGE
* (DATA SOURCE INDICATED AFTER VEHICLE CLASS)

*

* LDV 2000 DMV data

1 0.0366 0.0593 0.0553 0.0524 0.0465 0.0630 0.0611 0.0605 0.0590 0.0690

0.0693 0.0654 0.0537 0.0469 0.0437 0.0418 0.0364 0.0214 0.0142 0.0091

0.0072 0.0077 0.0058 0.0046 0.0102

* LDT1 2000 DMV data

2 0.0263 0.0495 0.0456 0.0557 0.0490 0.0638 0.0634 0.0500 0.0478 0.0522

0.0615 0.0562 0.0396 0.0326 0.0416 0.0456 0.0424 0.0336 0.0248 0.0225

0.0155 0.0183 0.0149 0.0116 0.0359

* LDT2 2000 DMV data

3 0.0263 0.0495 0.0456 0.0557 0.0490 0.0638 0.0634 0.0500 0.0478 0.0522

0.0615 0.0562 0.0396 0.0326 0.0416 0.0456 0.0424 0.0336 0.0248 0.0225

0.0155 0.0183 0.0149 0.0116 0.0359

* LDT3 2000 DMV data

4 0.0263 0.0495 0.0456 0.0557 0.0490 0.0638 0.0634 0.0500 0.0478 0.0522

0.0615 0.0562 0.0396 0.0326 0.0416 0.0456 0.0424 0.0336 0.0248 0.0225

0.0155 0.0183 0.0149 0.0116 0.0359

* LDT4 2000 DMV data

5 0.0263 0.0495 0.0456 0.0557 0.0490 0.0638 0.0634 0.0500 0.0478 0.0522

0.0615 0.0562 0.0396 0.0326 0.0416 0.0456 0.0424 0.0336 0.0248 0.0225

0.0155 0.0183 0.0149 0.0116 0.0359

* HDV2B MOBILE62 default

6 0.0503 0.0916 0.0833 0.0758 0.0690 0.0627 0.0571 0.0519 0.0472 0.0430

0.0391 0.0356 0.0324 0.0294 0.0268 0.0244 0.0222 0.0202 0.0184 0.0167

0.0152 0.0138 0.0126 0.0114 0.0499

* HDV3 MOBILE62 default

7 0.0503 0.0916 0.0833 0.0758 0.069 0.0627 0.0571 0.0519 0.0472 0.043

0.0391 0.0356 0.0324 0.0294 0.0268 0.0244 0.0222 0.0202 0.0184 0.0167

0.0152 0.0138 0.0126 0.0114 0.0499

* HDV4 MOBILE62 default

8 0.0388 0.0726 0.0679 0.0635 0.0594 0.0556 0.052 0.0486 0.0455 0.0425

0.0398 0.0372 0.0348 0.0326 0.0304 0.0285 0.0266 0.0249 0.0233 0.0218

0.0204 0.0191 0.0178 0.0167 0.0797

* HDV5 MOBILE62 default

9 0.0388 0.0726 0.0679 0.0635 0.0594 0.0556 0.052 0.0486 0.0455 0.0425

0.0398 0.0372 0.0348 0.0326 0.0304 0.0285 0.0266 0.0249 0.0233 0.0218

0.0204 0.0191 0.0178 0.0167 0.0797

* HDV6 MOBILE62 default

10 0.0388 0.0726 0.0679 0.0635 0.0594 0.0556 0.052 0.0486 0.0455 0.0425

0.0398 0.0372 0.0348 0.0326 0.0304 0.0285 0.0266 0.0249 0.0233 0.0218

0.0204 0.0191 0.0178 0.0167 0.0797

* HDV7 MOBILE62 default

11 0.0388 0.0726 0.0679 0.0635 0.0594 0.0556 0.0520 0.0486 0.0455 0.0425

0.0398 0.0372 0.0348 0.0326 0.0304 0.0285 0.0266 0.0249 0.0233 0.0218

0.0204 0.0191 0.0178 0.0167 0.0797

* HDV8a MOBILE62 default

12 0.0388 0.0726 0.0679 0.0635 0.0594 0.0556 0.0520 0.0486 0.0455 0.0425

0.0398 0.0372 0.0348 0.0326 0.0304 0.0285 0.0266 0.0249 0.0233 0.0218

0.0204 0.0191 0.0178 0.0167 0.0797

* HDV8b MOBILE62 default

13 0.0388 0.0726 0.0679 0.0635 0.0594 0.0556 0.0520 0.0486 0.0455 0.0425

0.0398 0.0372 0.0348 0.0326 0.0304 0.0285 0.0266 0.0249 0.0233 0.0218

0.0204 0.0191 0.0178 0.0167 0.0797

* HDBS MOBILE62 default

14 0.0393 0.0734 0.0686 0.0641 0.0599 0.0559 0.0522 0.0488 0.0456 0.0426

0.0398 0.0372 0.0347 0.0324 0.0303 0.0283 0.0264 0.0247 0.0231 0.0216

0.0201 0.0188 0.0176 0.0165 0.0781

* HDBT MOBILE62 default

15 0.0307 0.0614 0.0614 0.0614 0.0614 0.0614 0.0614 0.0614 0.0614 0.0613

0.0611 0.0607 0.0595 0.0568 0.0511 0.0406 0.0254 0.0121 0.0099 0.0081

0.0066 0.0054 0.0044 0.0037 0.0114 * Motorcycles MOBILE62 default

16 0.1440 0.1680 0.1350 0.1090 0.0880 0.0700 0.0560 0.0450 0.0360 0.0290

0.0230 0.0970 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

0.0000 0.0000 0.0000 0.0000 0.0000

## Appendix D

Nonroad Source Calculations

### Summer 2004 Nonroad Model Output Details

Equipment Description Equipment Type PM (tons/season) Population

(# units) Activity

(total hrs) Logging Equipment Forest Eqp - Feller/Bunch/Skidder 1.6544 65 40,819 Recreational Equipment All Terrain Vehicles 1.0435 1,121 1,802,858 Logging Equipment Chain Saws > 6 HP 0.9268 119 18,092 Recreational Equipment Motorcycles: Off-road 0.8007 288 461,470 Construction and Mining Equipment Tractors/Loaders/Backhoes 0.6923 37 27,979 Construction and Mining Equipment Skid Steer Loaders 0.6358 58 31,139 Construction and Mining Equipment Rubber Tire Loaders 0.4662 15 7,762 Construction and Mining Equipment Crawler Tractor/Dozers 0.3705 10 6,535 Construction and Mining Equipment Excavators 0.3458 14 9,921 Construction and Mining Equipment Off-highway Trucks 0.2573 2 1,873 Construction and Mining Equipment Rough Terrain Forklifts 0.2026 12 5,400 Construction and Mining Equipment Rollers 0.1276 10 4,834 Construction and Mining Equipment Concrete/Industrial Saws 0.0988 11 4,537 Construction and Mining Equipment Scrapers 0.0936 2 1,124 Construction and Mining Equipment Graders 0.0826 3 2,086 Industrial Equipment AC\Refrigeration 0.0819 10 7,686 Construction and Mining Equipment Trenchers 0.0811 9 3,330 Commercial Equipment Generator Sets 0.0766 157 11,331 Construction and Mining Equipment Cranes 0.0765 4 2,385 Construction and Mining Equipment Bore/Drill Rigs 0.0702 15 2,078 Lawn and Garden Equipment Chain Saws < 6 HP 0.0561 162 4,490 Construction and Mining Equipment Other Construction Equipment 0.0558 1 566 Recreational Equipment Specialty Vehicles/Carts 0.0548 105 6,699 Lawn and Garden Equipment Trimmers/Edgers/Brush Cutters 0.0545 434 7,248 Construction and Mining Equipment Off-highway Tractors 0.0490 0 254 Construction and Mining Equipment Pavers 0.0442 3 1,573 Lawn and Garden Equipment Leafblowers/Vacuums 0.0427 228 5,282 Commercial Equipment Welders 0.0402 14 3,613 Commercial Equipment Pumps 0.0342 41 4,839 Construction and Mining Equipment Tampers/Rammers 0.0341 16 1,731 Commercial Equipment Air Compressors 0.0300 8 2,553 Industrial Equipment Forklifts 0.0285 8 8,274 Construction and Mining Equipment Signal Boards/Light Plants 0.0193 7 2,475 Logging Equipment Shredders > 6 HP 0.0184 736 18,411 Construction and Mining Equipment Crushing/Processing Equipment 0.0172 2 737 Lawn and Garden Equipment Lawn and Garden Tractors 0.0165 367 25,303 Lawn and Garden Equipment Lawn Mowers 0.0112 1,005 39,988 Construction and Mining Equipment Paving Equipment 0.0111 13 1,746 Railroad Equipment Railway Maintenance 0.0097 1 294 Industrial Equipment Terminal Tractors 0.0086 0 273 Industrial Equipment Other General Industrial Equipment 0.0080 2 721 Lawn and Garden Equipment Chippers/Stump Grinders 0.0073 0 329 Construction and Mining Equipment Surfacing Equipment 0.0070 2 772 Commercial Equipment Pressure Washers 0.0066 63 3,642 Industrial Equipment Sweepers/Scrubbers 0.0066 1 512

Pleasure Craft Outboard 0.0052 75 63 Lawn and Garden Equipment Front Mowers 0.0051 2 824 Lawn and Garden Equipment Rotary Tillers < 6 HP 0.0051 105 4,341 Industrial Equipment Aerial Lifts 0.0046 2 348 Construction and Mining Equipment Cement and Mortar Mixers 0.0045 26 1,637 Construction and Mining Equipment Plate Compactors 0.0044 14 2,023 Lawn and Garden Equipment Turf Equipment 0.0038 5 4,548 Construction and Mining Equipment Dumpers/Tenders 0.0023 3 402

Continued on following page

### Summer 2004 Nonroad Model Output Details, Continued

Equipment Description Equipment Type PM (tons/season) Population (#

units) Activity

(total hrs) Construction and Mining Equipment Dumpers/Tenders 0.0023 3 402 Agricultural Equipment Agricultural Tractors 0.0020 0 34 Industrial Equipment Other Material Handling Equipment 0.0012 0 30 Lawn and Garden Equipment Rear Engine Riding Mowers 0.0011 54 2,935

Pleasure Craft Personal Water Craft 0.0011 10 9 Lawn and Garden Equipment Other Lawn and Garden Equipment 0.0009 21 1,870 Commercial Equipment Gas Compressors 0.0005 0 82 Agricultural Equipment Combines 0.0004 0 2 Lawn and Garden Equipment Shredders < 6 HP 0.0001 1 103 Agricultural Equipment Other Agricultural Equipment 0.0001 0 1

Pleasure Craft Inboard/Sterndrive 0.0000 18 15 Agricultural Equipment Sprayers 0.0000 0 1 Agricultural Equipment Swathers 0.0000 0 0 Agricultural Equipment Irrigation Sets 0.0000 0 1 Agricultural Equipment Hydro-power Units 0.0000 0 1 Agricultural Equipment Balers 0.0000 0 0 Agricultural Equipment Tillers > 6 HP 0.0000 0 2 Agricultural Equipment 2-Wheel Tractors 0.0000 0 0 Agricultural Equipment Agricultural Mowers 0.0000 0 0 Industrial Equipment Other Oil Field Equipment 0.0000

- - Lawn and Garden Equipment Snowblowers 0.0000 263

- Recreational Equipment Golf Carts 0.0000

- - Recreational Equipment Snowmobiles 0.0000 1,347

-

Total (tons/season) 8.90

Total (tons/day) 0.05

### Winter 2004 Nonroad Model Output Details

Equipment Description Equipment Type PM
(tons/season) Population

(# units) Activity

(total hrs) Logging Equipment Forest Eqp - Feller/Bunch/Skidder 1.6544 65 40,819 Logging Equipment Chain Saws > 6 HP 0.9268 119 18,092 Construction and Mining Equipment Tractors/Loaders/Backhoes 0.3477 37 14,053 Construction and Mining Equipment Skid Steer Loaders 0.3194 58 15,640 Construction and Mining Equipment Rubber Tire Loaders 0.2341 15 3,898 Construction and Mining Equipment Crawler Tractor/Dozers 0.1861 10 3,282 Construction and Mining Equipment Excavators 0.1737 14 4,983 Construction and Mining Equipment Off-highway Trucks 0.1292 2 941 Construction and Mining Equipment Rough Terrain Forklifts 0.1018 12 2,712 Commercial Equipment Generator Sets 0.0766 157 11,331 Industrial Equipment AC\Refrigeration 0.0672 10 6,300 Construction and Mining Equipment Rollers 0.0641 10 2,428 Construction and Mining Equipment Concrete/Industrial Saws 0.0496 11 2,279 Construction and Mining Equipment Scrapers 0.0470 2 564 Lawn and Garden Equipment Snowblowers 0.0451 376 6,741 Construction and Mining Equipment Graders 0.0415 3 1,048
Construction and Mining Equipment Trenchers 0.0407 9 1,672 Commercial Equipment Welders 0.0402 14 3,613 Construction and Mining Equipment Cranes 0.0384 4 1,198 Construction and Mining Equipment Bore/Drill Rigs 0.0353 15 1,044 Commercial Equipment Pumps 0.0342 41 4,839 Commercial Equipment Air Compressors 0.0300 8 2,553 Construction and Mining Equipment Other Construction Equipment 0.0280 1 284 Recreational Equipment Specialty Vehicles/Carts 0.0248 105 3,029 Construction and Mining Equipment Off-highway Tractors 0.0246 0 127 Industrial Equipment Forklifts 0.0234 8 6,782 Construction and Mining Equipment Pavers 0.0222 3 790 Logging Equipment Shredders > 6 HP 0.0184 736 18,411 Construction and Mining Equipment Tampers/Rammers 0.0171 16 869 Railroad Equipment Railway Maintenance 0.0097 1 294 Construction and Mining Equipment Signal Boards/Light Plants 0.0097 7 1,243 Construction and Mining Equipment Crushing/Processing Equipment 0.0086 2 370 Industrial Equipment Terminal Tractors 0.0070 0 224 Commercial Equipment Pressure Washers 0.0066 63 3,642 Industrial Equipment Other General Industrial Equipment 0.0065 2 591 Construction and Mining Equipment Paving Equipment 0.0056 13 877 Industrial Equipment Sweepers/Scrubbers 0.0054 1 420 Industrial Equipment Aerial Lifts 0.0038 2 285 Construction and Mining Equipment Surfacing Equipment 0.0035 2 388
Recreational Equipment Snowmobiles 0.0029 59 59 Construction and Mining Equipment Cement and Mortar Mixers 0.0023 26 822 Construction and Mining Equipment Plate Compactors 0.0022 14 1,016 Construction and Mining Equipment Dumpers/Tenders 0.0011 3 202 Industrial Equipment Other Material Handling Equipment 0.0010 0 24

Pleasure Craft Outboard 0.0009 75 11 Agricultural Equipment Agricultural Tractors 0.0008 0 13 Commercial Equipment Gas Compressors 0.0005 0 82

Pleasure Craft Personal Water Craft 0.0002 10 2 Agricultural Equipment Combines 0.0002 0 1 Agricultural Equipment Other Agricultural Equipment 0.0000 0 0 Agricultural Equipment Sprayers 0.0000 0 0 Agricultural Equipment Swathers 0.0000 0 0

Pleasure Craft Inboard/Sterndrive 0.0000 18 3

Continued on following page

### Winter 2004 Nonroad Model Output Details

, Continued

Equipment Description Equipment Type PM (tons/season) Population

(# units) Activity

(total hrs) Agricultural Equipment Irrigation Sets 0.0000 0 0 Agricultural Equipment Hydro-power Units 0.0000 0 0 Agricultural Equipment Balers 0.0000 0 0 Agricultural Equipment Tillers > 6 HP 0.0000 0 1
Agricultural Equipment 2-Wheel Tractors 0.0000 0 0 Agricultural Equipment Agricultural Mowers 0.0000 0 0 Recreational Equipment All Terrain Vehicles 0.0000 1,121

- Lawn and Garden Equipment Chain Saws < 6 HP 0.0000 231

- Lawn and Garden Equipment Chippers/Stump Grinders 0.0000 1

- Lawn and Garden Equipment Front Mowers 0.0000 3

- Recreational Equipment Golf Carts 0.0000

- - Lawn and Garden Equipment Lawn and Garden Tractors 0.0000 524

- Lawn and Garden Equipment Lawn Mowers 0.0000 1,436

- Lawn and Garden Equipment Leafblowers/Vacuums 0.0000 326

- Recreational Equipment Motorcycles: Off-road 0.0000 288

- Lawn and Garden Equipment Other Lawn and Garden Equipment 0.0000 31

- Industrial Equipment Other Oil Field Equipment 0.0000

- - Underground Mining Equipment Other Underground Mining Equipment 0.0000

- - Lawn and Garden Equipment Rear Engine Riding Mowers 0.0000 77

- Lawn and Garden Equipment Rotary Tillers < 6 HP 0.0000 150

- Lawn and Garden Equipment Shredders < 6 HP 0.0000 2

- Lawn and Garden Equipment Trimmers/Edgers/Brush Cutters 0.0000 620

- Lawn and Garden Equipment Turf Equipment 0.0000 7

- Total (tons/season) 4.92

Total (tons/day) 0.03

### Summer 2018 Nonroad Model Output Details

Equipment Description Equipment Type PM (tons/season) Population (# units) Activity

(total hrs) Logging Equipment Chain Saws > 6 HP 1.33 171 25,942
Recreational Equipment Motorcycles: Off-road 0.66 460 736,252 Construction and Mining Equipment Skid Steer Loaders 0.35 76 40,708 Recreational Equipment All Terrain Vehicles 0.35 1,935 3,111,907 Construction and Mining Equipment Tractors/Loaders/Backhoes 0.34 48 36,496 Construction and Mining Equipment Concrete/Industrial Saws 0.09 11 4,639 Construction and Mining Equipment Rubber Tire Loaders 0.07 20 10,143 Lawn and Garden Equipment Chain Saws < 6 HP 0.06 284 3,854
Lawn and Garden Equipment Trimmers/Edgers/Brush Cutters 0.06 760 6,223 Commercial Equipment Generator Sets 0.05 219 15,844 Lawn and Garden Equipment Leafblowers/Vacuums 0.05 400 4,540 Construction and Mining Equipment Rough Terrain Forklifts 0.05 16 7,062 Recreational Equipment Specialty Vehicles/Carts 0.04 114 7,759 Construction and Mining Equipment Tampers/Rammers 0.03 16 1,759
Commercial Equipment Pumps 0.03 56 6,729 Construction and Mining Equipment Bore/Drill Rigs 0.03 16 2,497 Commercial Equipment Welders 0.03 19 5,089 Construction and Mining Equipment Crawler Tractor/Dozers 0.02 14 8,558 Logging Equipment Shredders > 6 HP 0.02 1,056 26,399 Construction and Mining Equipment Rollers 0.02 12 6,203 Lawn and Garden Equipment Lawn and Garden Tractors 0.02 654 22,128 Construction and Mining Equipment Trenchers 0.02 11 4,104 Construction and Mining Equipment Other Construction Equipment 0.01 2 735 Industrial Equipment Forklifts 0.01 11 10,662 Construction and Mining Equipment Scrapers 0.01 2 1,472 Construction and Mining Equipment Signal Boards/Light Plants 0.01 9 3,232 Commercial Equipment Air Compressors 0.01 12 3,597 Construction and Mining Equipment Off-highway Tractors 0.01 1 332 Lawn and Garden Equipment Lawn Mowers 0.01 1,776 34,603 Commercial Equipment Pressure Washers 0.01 87 5,030 Construction and Mining Equipment Cranes 0.01 5 3,114

Pleasure Craft Outboard 0.01 80 68 Railroad Equipment Railway Maintenance 0.00 1 395 Lawn and Garden Equipment Rotary Tillers < 6 HP 0.00 187 3,784 Construction and Mining Equipment Paving Equipment 0.00 13 1,859 Lawn and Garden Equipment Chippers/Stump Grinders 0.00 1 337 Industrial Equipment Aerial Lifts 0.00 2 388 Industrial Equipment AC\Refrigeration 0.00 14 10,404 Lawn and Garden Equipment Turf Equipment 0.00 8 3,986 Construction and Mining Equipment Pavers 0.00 4 1,989 Construction and Mining Equipment Cement and Mortar Mixers 0.00 26 1,727 Logging Equipment Forest Eqp - Feller/Bunch/Skidder 0.00 56 34,736 Construction and Mining Equipment Plate Compactors 0.00 15 2,258 Construction and Mining Equipment Crushing/Processing Equipment 0.00 2 926 Construction and Mining Equipment Surfacing Equipment 0.00 2 817 Lawn and Garden Equipment Front Mowers 0.00 4 887 Construction and Mining Equipment Excavators 0.00 18 12,992 Construction and Mining Equipment Dumpers/Tenders 0.00 3 452 Industrial Equipment Other General Industrial Equipment 0.00 1 574 Lawn and Garden Equipment Rear Engine Riding Mowers 0.00 96 2,561 Industrial Equipment Other Material Handling Equipment 0.00 0 35 Construction and Mining Equipment Graders 0.00 4 2,732

Pleasure Craft Personal Water Craft 0.00 11 9

Continued on following page

### Summ er 2018 Nonroad Model Output Details, Continued

Equipment Description Equipment Type PM (tons/season) Population

(# units) Activity

(total hrs) Lawn and Garden Equipment Other Lawn and Garden Equipment 0.00 38 1,632
Commercial Equipment Gas Compressors 0.00 0 114 Agricultural Equipment Agricultural Tractors 0.00 0 44 Agricultural Equipment Combines 0.00 0 3 Industrial Equipment Sweepers/Scrubbers 0.00 1 613 Industrial Equipment Terminal Tractors 0.00 1 362

Pleasure Craft Inboard/Sterndrive 0.00 20 17
Lawn and Garden Equipment Shredders < 6 HP 0.00 3 90 Agricultural Equipment Sprayers 0.00 0 1 Agricultural Equipment Swathers 0.00 0 0 Agricultural Equipment Other Agricultural Equipment 0.00 0 1 Agricultural Equipment Irrigation Sets 0.00 0 1 Agricultural Equipment Balers 0.00 0 0 Agricultural Equipment Tillers > 6 HP 0.00 0 2
Agricultural Equipment Hydro-power Units 0.00 0 1 Agricultural Equipment 2-Wheel Tractors 0.00 0 0 Agricultural Equipment Agricultural Mowers 0.00 0 0 Construction and Mining Equipment Off-highway Trucks

- 2 2,452 Industrial Equipment Other Oil Field Equipment

- - - Lawn and Garden Equipment Snowblowers

- 467

- Recreational Equipment Golf Carts

- - - Recreational Equipment Snowmobiles

- 2,028

- Underground Mining Equipment Other Underground Mining Equipment

- - - Total (tons/season) 3.87

Total (tons/day) 0.02

### Winter 2018 Nonroad Model Output Details

Equipment Description Equipment Type PM (tons/season) Population

(# units) Activity

(total hrs) Logging Equipment Chain Saws > 6 HP 1.33 171 25,942 Construction and Mining Equipment Skid Steer Loaders 0.18 76 20,446
Construction and Mining Equipment Tractors/Loaders/Backhoes 0.17 48 18,330 Lawn and Garden Equipment Snowblowers 0.06 467 8,372 Commercial Equipment Generator Sets 0.05 219 15,844 Construction and Mining Equipment Concrete/Industrial Saws 0.05 11 2,330 Construction and Mining Equipment Rubber Tire Loaders 0.04 20 5,095 Commercial Equipment Pumps 0.03 56 6,729 Commercial Equipment Welders 0.03 19 5,089 Construction and Mining Equipment Rough Terrain Forklifts 0.02 16 3,547 Logging Equipment Shredders > 6 HP 0.02 1,056 26,399 Recreational Equipment Specialty Vehicles/Carts 0.02 114 3,508
Construction and Mining Equipment Tampers/Rammers 0.02 16 884 Construction and Mining Equipment Bore/Drill Rigs 0.02 16 1,254 Construction and Mining Equipment Crawler Tractor/Dozers 0.01 14 4,298 Industrial Equipment Forklifts 0.01 11 8,739 Construction and Mining Equipment Rollers 0.01 12 3,116 Construction and Mining Equipment Trenchers 0.01 11 2,061 Commercial Equipment Air Compressors 0.01 12 3,597 Construction and Mining Equipment Other Construction Equipment 0.01 2 369 Commercial Equipment Pressure Washers 0.01 87 5,030 Railroad Equipment Railway Maintenance 0.00 1 395
Construction and Mining Equipment Scrapers 0.00 2 739 Recreational Equipment Snowmobiles 0.00 89 89 Construction and Mining Equipment Signal Boards/Light Plants 0.00 9 1,623 Construction and Mining Equipment Off-highway Tractors 0.00 1 167 Industrial Equipment Aerial Lifts 0.00 2 318 Industrial Equipment AC\Refrigeration 0.00 14 8,528 Construction and Mining Equipment Cranes 0.00 5 1,564 Logging Equipment Forest Eqp - Feller/Bunch/Skidder 0.00 56 34,736 Construction and Mining Equipment Paving Equipment 0.00 13 934 Construction and Mining Equipment Pavers 0.00 4 999
Construction and Mining Equipment Cement and Mortar Mixers 0.00 26 867 Construction and Mining Equipment Plate Compactors 0.00 15 1,134 Construction and Mining Equipment Crushing/Processing Equipment 0.00 2 465 Construction and Mining Equipment Surfacing Equipment 0.00 2 410 Construction and Mining Equipment Excavators 0.00 18 6,526 Industrial Equipment Other General Industrial Equipment 0.00 1 470

Pleasure Craft Outboard 0.00 80 12 Industrial Equipment Other Material Handling Equipment 0.00 0 29 Construction and Mining Equipment Dumpers/Tenders 0.00 3 227 Commercial Equipment Gas Compressors 0.00 0 114
Construction and Mining Equipment Graders 0.00 4 1,372 Agricultural Equipment Agricultural Tractors 0.00 0 17 Industrial Equipment Sweepers/Scrubbers 0.00 1 503

Pleasure Craft Personal Water Craft 0.00 11 2 Agricultural Equipment Combines 0.00 0 1 Industrial Equipment Terminal Tractors 0.00 1 297 Agricultural Equipment Sprayers 0.00 0 0 Agricultural Equipment Swathers 0.00 0 0

Pleasure Craft Inboard/Sterndrive 0.00 20 3 Agricultural Equipment Other Agricultural Equipment 0.00 0 0 Agricultural Equipment Irrigation Sets 0.00 0 0

Continued on following page

### Winter 2018 Nonroad Model Output Details, Continued

Equipment Description Equipment Type PM (tons/season) Population

(# units) Activity

(total hrs) Agricultural Equipment Balers 0.00 0 0 Agricultural Equipment Tillers > 6 HP 0.00 0 1 Agricultural Equipment Hydro-power Units 0.00 0 0
Agricultural Equipment 2-Wheel Tractors 0.00 0 0 Agricultural Equipment Agricultural Mowers 0.00 0 0 Construction and Mining Equipment Off-highway Trucks

- 2 1,232 Recreational Equipment All Terrain Vehicles

- 1,935

- Lawn and Garden Equipment Chain Saws < 6 HP

- 284

- Lawn and Garden Equipment Chippers/Stump Grinders

- 1

- Lawn and Garden Equipment Front Mowers

- 4

- Recreational Equipment Golf Carts

- - - Lawn and Garden Equipment Lawn and Garden Tractors

- 654

- Lawn and Garden Equipment Lawn Mowers

- 1,776

- Lawn and Garden Equipment Leafblowers/Vacuums

- 400

- Recreational Equipment Motorcycles: Off-road

- 338

- Lawn and Garden Equipment Other Lawn and Garden Equipment

- 38

- Industrial Equipment Other Oil Field Equipment

- - - Underground Mining Equipment Other Underground Mining Equipment

- - - Lawn and Garden Equipment Rear Engine Riding Mowers

- 96

- Lawn and Garden Equipment Rotary Tillers < 6 HP

- 187

- Lawn and Garden Equipment Shredders < 6 HP

- 3

- Lawn and Garden Equipment Trimmers/Edgers/Brush Cutters

- 760

- Lawn and Garden Equipment Turf Equipment

- 8

-
Total (tons/season) 2.13

Total (tons/day) 0.01

## Appendix E

Area Source Calculations

### E-1 Used Oil Calculations:

1983 National burn rate (gallons/yr) 590,000,000

Prorated 2004 National burn rate (gallons/yr) 741,071,948

Prorated 2004 Mendenhall Consumption (gallons/yr) 33,632
Prorated 2018 Mendenhall Consumption (gallons/yr) 36,681

2004 2018
AP-42 Table 1.3-1 EFs (lbs/1,000 gal) 0.4 0.4

Winter (lbs/season) 13 15
Winter (lbs/day) 0.07 0.08
Winter (tons/day) 0.000037 0.000040



### Propane Calculations:

Propane Throughput

2004 Juneau 2004 Mendenhall 2018 Mendenhall gallons/year 711,392 gallons/winter 366,321 157,503 171,779 gallons/summer 345,071 148,366 161,815



### PM10
PM10 EF (lbs/1000 gal) 0.4

2004 Winter (tpd) 0.00017 2004 Summer (tpd) 0.00016

2018 Winter (tpd) 0.00019 2018 Summer (tpd) 0.00018

Emission Factor: AP-42 Table 1.5-1, for Commercial Boilers

### E-2 Open Burning (Firefighter Training) Calculations:

gallons burned/exercise: 200 Exercises/yr: 28 Total gallons burned/yr in MOA 5,600 Assumed gallons burned in 1999 in Mendenhall Valley: 273

PM10 EFs (lbs/10^3 gal), AP-42 table 1.3-1 0.4

Summer tons 0.0001

Summer tpd 0.0000003



### Structural Fires Calculations:

Data from Capital City Fire/Rescue Fire Marshal data on 2004 (Rich Etheridge, 907-586-0251, 8/18/05) Incidences in 2004 (fires/year) = 27 % of fires in Valley = 70%

% of fires in Winter = 65% # fires/day

winter 0.0675

summer 0.0361

PM10
EF (lbs/fire) 13.8

winter tpd 0.0005 summer tpd 0.0002

CARB's Index of Areawide Source Methodologies Section 7.14: Structure and Automobile Fires (March 1999)



### Fugitive Dust Calculations:

Windblown Dust (from 1988 PM10 Inventory)

glacial riverbeds 28.6 tons/yr
cleared areas 4.4 tons/yr

TOTAL Windblown Dust: 33.0 tons/yr

Calendar Year Season Paved Road PM10 (tpd) Unpaved Road PM10 (tpd) Windblown Dust (tpd) TOTAL

2004 Winter 1.478 0.161 0.181 1.821

2004 Summer 4.135 0.190 0.181 4.506

2018 Winter 1.612 0.176 0.181 1.969

2018 Summer 4.510 0.207 0.181 4.898E-3Burn Barrels Calculations:PM10 Emission Factor (lb/ton) =16 EPA AP-42 Emissions from Municipal Refuse Burning, 10/92.Annual waste generation rate (lb/household) =2137 CARB "ISOR Proposed ATCM to Reduce Emissions of TACs from Outdoor ResidentialWaste Burning," 1/4/02CY2004 CY2018Total households in Valley =48885331Other Assumptions:All burning in summer (prohibited in winter)Some percentage to trash pick up90%75%Sensitivity Analysis for range burned10%25%Summer PM10 Emissions (tpd) =0.023 0.057 Summer 2004Summer PM10 Emissions (tpd) =0.025 0.062 Summer 2018E-4Winter 2004 Woodburning Emission Calculations:Equipment Description# SurveyHouseholdsEquipped% SurveyHouseholdsEquipped*Projected ValleyHouseholdsEquippedCords Burned bySurveyHouseholds(cords/season)Cords Burnedby ValleyHouseholds(tons/season)Tons Burned byValleyHouseholds(tons/season)PM10(#/ton of woodburned)PM10(tons/day)Wood Stove 93 16.8% 81965.3 575690.40 30.6 0.058Conventional Fireplace53 9.6%46737.2 328393.4523.6 0.025Modified Fireplace12 2.2%1068.47489.0823.6 0.006Other Non-Pellet woodburning device4 0.7%352.82529.6923.6 0.002Total162 29.2%1,427113.8 1,0021202.6Total # Homes Equipped with One orMore Non-Pellet Woodburning Unit127 29.2%1,4270.091# 40 lb StovePellet bagstons Pelletsburned perseasonTons Burned byValleyHouseholdsPM10(#/ton of Pelletsburned)PM10(tons/day)Pellet Stove22 5.1%2471,09721.9246.618.8 0.006Total435 34.3%4,888TOTAL (tpd): 0.097E-5Summer 2004 Woodburning Calculations:Equipment Description# SurveyHouseholdsEquipped% SurveyHouseholdsEquipped*Projected ValleyHouseholdsEquippedCords Burned bySurveyHouseholds(cords/season)Cords Burnedby ValleyHouseholds(tons/season)Tons Burned byValleyHouseholds(tons/season)PM10(#/ton of woodburned)PM10(tons/day)Wood Stove 93 16.8% 81922.5 198238.08 30.6 0.020Conventional Fireplace 53 9.6% 46712.8 113135.68 23.6 0.009Modified Fireplace 12 2.2% 1062.9 2630.72 23.6 0.002Other Non-Pellet woodburning device 4 0.7% 351.0 910.24 23.6 0.001Total 162 29.2% 1,42739.2 346414.7Total # Homes Equipped with One orMore Non-Pellet Woodburning Unit 127 29.2% 1,4270.031# 40 lb StovePellet bagstons Pelletsburned perseasonTons Burned byValleyHouseholdsPM10(#/ton of Pelletsburned)PM10(tons/day)Pellet Stove 22 5.1% 2473757.584.208.8 0.002Total 435 34.3% 4,888TOTAL (tpd): 0.033E-6Winter 2018 Woodburning Emission Calculations:Equipment Description# SurveyHouseholdsEquipped% SurveyHouseholdsEquipped*Projected ValleyHouseholdsEquippedCords Burned bySurveyHouseholds(cords/season)Cords Burnedby ValleyHouseholds(tons/season)Tons Burned byValleyHouseholds(tons/season)PM10(#/ton of woodburned)PM10(tons/day)Wood Stove93 16.8%89365.3 627752.9730.6 0.063Conventional Fireplace53 9.6%50937.2 358429.1123.6 0.028Modified Fireplace12 2.2%1158.48197.1623.6 0.006Other Non-Pellet woodburning device4 0.7%382.82732.3923.6 0.002Total162 29.2%1,556113.8 1,0931311.6Total # Homes Equipped with One orMore Non-Pellet Woodburning Unit127 29.2%1,5560.099# 40 lb StovePellet bagstons Pelletsburned perseasonTons Burned byValleyHouseholdsPM10(#/ton of Pelletsburned)PM10(tons/day)Pellet Stove22 5.1%2701,09721.9268.968.8 0.007Total435 34.3%5,331TOTAL (tpd): 0.106E-7Summer 2018 Woodburning Emission Calculations:Equipment Description# SurveyHouseholdsEquipped% SurveyHouseholdsEquipped*Projected ValleyHouseholdsEquippedCords Burned bySurveyHouseholds(cords/season)Cords Burnedby ValleyHouseholds(tons/season)Tons Burned byValleyHouseholds(tons/season)PM10(#/ton of woodburned)PM10(tons/day)Wood Stove 93 16.8% 89322.5 216259.66 30.6 0.022Conventional Fireplace 53 9.6% 50912.8 123147.98 23.6 0.010Modified Fireplace 12 2.2% 1152.9 2833.50 23.6 0.002Other Non-Pellet woodburning device 4 0.7% 381.0 911.17 23.6 0.001Total 162 29.2% 1,55639.2 377452.3Total # Homes Equipped with One orMore Non-Pellet Woodburning Unit 127 29.2% 1,5560.034# 40 lb StovePellet bagstons Pelletsburned perseasonTons Burned byValleyHouseholdsPM10(#/ton of Pelletsburned)PM10(tons/day)Pellet Stove 22 5.1% 2703757.591.838.8 0.002Total 435 34.3% 5,331TOTAL (tpd): 0.036E-82004 Fuel Oil Emission Calculations:* Note that these percentages were normalized to 89.7% to account for homes with more than one type of unit.2018 Fuel Oil Calculations:* Note that these percentages werenormalized to 89.7% to account for homes with more than one type of unit.Equipment Description# SurveyHouseholdsEquipped% SurveyHouseholdsEquipped*ProjectedValleyHouseholdsEquippedAverage WinterFuel Use forSurvey Households(gal/hhold/season)Average SummerFuel Use forSurveyHouseholds(gal/hhold/year)Total Winter FuelUse for ValleyHouseholds(103 gallons/season)Total SummerFuel Use forValley Households(103 gallons/year)# PM10per103gallonsburnedDirect Vent Heater (i.e., Toyo, Monitor) 147 31.5% 1,537Central Oil Furnace 272 58.2% 2,845Total 419 89.7% 4,3823902161,7089470.4Total # Homes Equipped with One or MoreOil Heating Units390 89.7% 4,382Totals 435 4,888tons/day:WinterPM10Emissions(tons/season)SummerPM10Emissions(tons/season)0.340.190.002 0.001Equipment Description# SurveyHouseholdsEquipped% SurveyHouseholdsEquipped*ProjectedValleyHouseholdsEquippedAverage WinterFuel Use for SurveyHouseholds(gal/hhold/season)Average SummerFuel Use forSurveyHouseholds(gal/hhold/year)Total Winter FuelUse for ValleyHouseholds(103 gallons/season)Total Summer FuelUse for ValleyHouseholds(103 gallons/year)# PM10per103gallonsburnedWinterPM10Emissions(tons/season)Direct Vent Heater (i.e., Toyo, Moni147 31.5% 1,677Central Oil Furnace272 58.2% 3,103Total419 89.7% 4,7803902161,8631,0330.4 0.37Total # Homes Equipped with Oneor More Oil Heating Units390 89.7% 4,780Totals4355,331tons/day: 0.002SummerPM10Emissions(tons/season)0.210.001

# Alaska Department of Environmental Conservation



# Amendments to:

State Air Quality Control Plan

Vol. III: Appendices

Appendix III.D.3.9



# Adopted February 20, 2009