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, 2009
Adopted 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 Regulating 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 Class 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....

#2008-28- “An Ordinance Amending the Woodsmoke Control Program Regarding Solid 

Fuel-Fired Burning Devices”. This ordinance has been incorporated into City & 

Borough of Juneau Code 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 PM10 Emission Inventory, January 2006

Appendix III.D.3.9

EPA Region 10 Analysis of PM10 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, 2009

3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
Presented 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 ofEnvironmental 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 ofAr 

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. 

50
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 

51
Alaska Department of Environmental Conservation

Amendments to:

State Air Quality Control Plan

Vol. III: Appendices

Appendix III.D.3.8

Adopted

February 20, 2009

52
DRAFT

Mendenhall Valley PM10 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

53
DRAFT REPORT 

MENDENHALL VALLEY PM10 EMISSION INVENTORY

 prepared for: 

Alaska Department of Environmental 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 

54
-iMENDENHALL VALLEY PM10 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 PM10 Inventory Results....................................................................................10 

3. Nonroad.....................................................................................................................12 

 3.1 Calculation Methodology.................................................................................12 

 3.2 Modifications to EPA’s NONROAD Model 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 PM10 Area Source Inventory............................................................................34 

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

6. References.................................................................................................................36 

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 Source Calculations 

Appendix E – Area Source Calculations 

55
-iiList of Tables

Page

ES-1 Summary of Mendenhall Valley PM10 Emissions by Season 

 and Source Category..........................................................................................ES-2 

2-1 Seasonal Ambient Temperature in Juneau...............................................................4 

2-2 Seasonal VMT Distribution 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 for Mendenhall Valley by Source...................................8 

2-6 Available Roadway Data for Mendenhall Valley by Facility..................................8 

2-7 Mendenhall Valley Population Estimates................................................................9 

2-8 Mendenhall Valley Average Travel Estimates ......................................................10 

2-9 2004 Mendenhall Valley Seasonal On-Road PM10 Emissions in Tons/Day .........10 

2-10 2018 Mendenhall Valley Seasonal On-Road PM10 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 PM10 Emissions..............................................................17 

3-3 2004 Mendenhall Valley Nonattainment Area Nonroad Source Emissions - 

 Summer..................................................................................................................17 

3-4 2004 Mendenhall Valley Nonattainment Area Nonroad Source Emissions - 

 Winter ....................................................................................................................18 

3-5 2018 Mendenhall Valley Nonattainment Area Nonroad Source Emissions - 

 Summer..................................................................................................................18 

3-6 2018 Mendenhall Valley Nonattainment Area Nonroad Source Emissions - 

 Winter ....................................................................................................................19 

4-1 Summary of Heating Degree Days for Juneau, Alaska .........................................21 

4-2 Allocation of Survey Fuel Use to Summer & Winter Seasons..............................22 

4-3 PM10 Emission Estimates for Residential Heating, Mendenhall Valley in 2004 ..25 

4-4 PM10 Emission Estimates for Residential Heating, Mendenhall Valley in 2018 ..25 

4-5 PM10 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 Average VMT/Day by Facility..................................31 

4-8 Mendenhall Valley Unpaved Road VMT and Data Sources.................................32 

4-9 2004 and 2018 Mendenhall Valley Paved Road VMT by Facility........................33 

4-10 Seasonal Road Fugitive Dust Emissions in Mendenhall Valley............................33 

4-11 2004 and 2018 PM10 Area Source Emissions for the Mendenhall Valley 

 Nonattainment Area...............................................................................................34 

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

56
ES-1 

EXECUTIVE SUMMARY 

The Mendenhall Valley (Valley) is currently classified as a moderate PM10 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 planning and 

implementation efforts by both the state Department of Environmental 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, the SIP implemented a wood smoke control 

program and a fugitive dust abatement program. 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 requirements; and enforcement 

of the CBJ woodsmoke ordinance. The fugitive dust abatement program focused on 

paving unpaved roads in the Valley. No emission 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 programs and to provide a basis for developing a 

Maintenance Plan and redesignation request, the Alaska Department of Environmental 

Conservation (ADEC) commissioned the development of a base and horizon year (2004 

and 2018) PM10 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 PM10 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 available 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 annualized rate of less than 1% per year. 

57
ES-2 

Table ES-1 

Summary of Mendenhall Valley PM10 Emissions 

By Season and Source Category (tons/day)

Source Category Calendar Year 2004 Calendar Year 2018 

Winter PM10 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 PM10 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 declined 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. 

58
ES-3 

PM10 emissions from wood burning (both fireplaces and stoves) were estimated to 

account for almost 9% of the annual inventory in 1988. In 2004, that share declined to 

less than 2% and is projected to remain at roughly that level in 2018. Based on the 

results of an extensive survey of homeowners conducted in 2004, it is estimated that the 

combination of new technology, related shifts in wood use, and 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 overall inventory and that they are projected to 

decline despite the increase in activity projected to occur between 2004 and 2018. This is 

the result of replacing older, higher-emitting vehicles/equipment populations with newer, 

lower-emitting populations and federal 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 estimated to have declined by almost 30% between 1993 and 

2004. 

 

###

59
 -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 sharply 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 relatively severe temperature inversions. These inversions 

trap emissions close to the valley floor and in the past led to severe concentrations of 

airborne particulate matter that exceeded state and federal ambient air quality standards 

for PM10. 

The Mendenhall Valley is currently classified as a moderate PM10 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 planning 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, the SIP implemented a wood smoke control 

program and a fugitive dust abatement program. 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 requirements; 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 introduction of new technology has also had a 

significant impact on home heating emissions. We estimate that collectively the 

combination of new technology, related shifts in wood use, and implementation of 

control measures has reduced PM10 emissions by 85% from 1993 to 2004. Key 

contributors to these reductions include the following: 

• Initiatives (e.g., burn bans, public education, new stove requirements, etc.) 

implemented under the Juneau wood smoke control program; 

60
 -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 provides detailed insight into the impact of both 

technology changes and related activity levels 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 related 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 Valley5

 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., and fugitive dust) on paved 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 traffic 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 primary source categories: on-road, nonroad, area 

and point sources. The appendices include a copy of the Inventory Preparation and 

Quality Assurance Plan, Demographic Forecasts, and documentation of the emission 

calculations for each of the source categories. 

### 

61
 -3-

2. ON-ROAD SOURCES 

The calendar year 2004 and 2018 PM10 on-road mobile source inventories were prepared 

for Mendenhall Valley using EPA’s latest vehicle emission factor model, MOBILE6.* 

The model estimates the following PM10 pollutants from on-road motor vehicles: 

• Sulfate (SO4); 

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

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

• Total carbon (GASPM) portion of gasoline 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 reflect 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 PM10 emissions from Mendenhall Valley 

using MOBILE6 were compiled by contacting local and state agencies and reviewing 

historical data on ambient conditions 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 average 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. 

62
 -4-

Table 2-1 

Seasonal Ambient Temperature in Juneau(oF) 

Season Low High 

Summer 42.3 57.7 

Winter 25.7 36.3 

Registration Distribution – June 2000 Department of Motor 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 few years). These vehicles are not operated 

on a regular basis and tend to bias the registration 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 for 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 runs for the summer and winter seasons. In 

addition, it was assumed that the registration 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 for the registration distribution by age, 

registration distribution by vehicle class, mileage accrual rates, Diesel fractions, and the 

calendar year given in the model run. Therefore, 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 shown 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 registration distribution by vehicle age, the 

resulting VMT fractions differ slightly within each calendar year because MOBILE6 ages 

the default fleet population by six months for the summer runs, which adjusts the model 

default annual mileage and average accumulation rates by vehicle age and affects the 

calculated “default” VMT fractions in the model. 

63
 -5-

Table 2-2 

Seasonal VMT Distributions 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 PM10 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 properties were based on fuel from Seattle, Washington, which is 

shipped into Juneau. 

For 2018, gasoline fuel sulfur levels are assumed 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 assumed 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 summarizes 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; however, RVP does not affect PM10 levels from vehicles. 

64
 -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 Federal Test Procedure 

(SFTP) Bag 4-equivalent were disabled during the winter runs. This was done because 

the aggressive driving represented by these effects is not observed with winter road 

conditions. In addition, the Valley was 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 model. 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 PM10 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% 

65
 -7-

2.2 Juneau Travel Activity

Once the input parameters were compiled and model runs were completed, the resulting 

PM10 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 databases 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 travel 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, average 

daily 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 developed 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 routelist 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 already 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 routelist 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. 

66
 -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 then 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 segments 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 speed 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. 

67
 -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 the 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 assumed 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 interpolated 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 maintenance 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 nonattainment area. The resulting PM10 emission 

factors from the model runs were then combined with the total daily VMT by calendar 

year and season to result in the average PM10 emissions for the area by facility type. 

68
 -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 PM10 Inventory Results

Tables 2-9 and 2-10 show the resulting 2004 and 2018 on-road mobile PM10 emission 

estimates for the Mendenhall Valley nonattainment area by pollutant, season, and facility 

type. 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. As shown in the tables, very little seasonal 

variation is seen in the PM10 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 

PM10 emissions. 

Table 2-9 

2004 Mendenhall Valley Seasonal On-Road PM10 Emissions in Tons/Daya 

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. 

69
 -11-

Table 2-10 

2018 Mendenhall Valley Seasonal On-Road PM10 Emissions in Tons/Daya 

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. 

### 

70
 -12-

3. NONROAD SOURCES 

The nonroad mobile source inventories presented 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 Juneau-specific data whenever possible, as 

described in the methodology section below. 

For purposes of this inventory, the Alaskan 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 specified, NONROAD default activity and 

population inputs were used in the modeling associated with these nonroad inventories. 

3.1 Calculation Methodology

The NONROAD model calculates tons of emissions for a given geographical area using 

the following factors: 

• equipment population; 

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

• the average horsepower rating of the equipment; 

• the estimated annual equipment activity (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 whether 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 proximity to recreational, industrial, and 

commercial facilities. It should be noted that the model has 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. 

71
 -13-

as a result of EPA’s revised population estimates 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 was 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 generated 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, there 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.” 

72
 -14-

temperature of all surrounding bodies of water. With the exception of these 

modifications, described in greater detail 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 rigorous in Juneau, and although the geography 

is not a deterrent to PWC use in Juneau, seasonal 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 registration data provided by the Coast Guard, with 

the 50% registration assumption discussed above, would 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 unrealistically 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 estimates refer to the Borough of Juneau; these totals were 

subsequently adjusted to represent the equipment population in the Mendenhall Valley 

nonattainment area, according to the 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 population adjustments), 

with the added assumption that all annual activity occurs during the summer months (i.e., 

April through September). ADEC staff believe 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 recreational marine equipment is 15% during the Spring and 

Fall, and 70% during the Winter (i.e., December through February). 

73
 -15-

have no local data to offer as a substitute. 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 Criteria Pollutant Inventory. At that time, 

ADEC believed that assuming 50% of all operating snowmobiles are registered provided 

a more accurate population estimate than the 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 Juneau. (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 population 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 were 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 which occurs during the winter months. 

74
 -16-

Snowblowers

The default NONROAD assumptions regarding snowblower activity were retained, with 

the exception of seasonal distribution; 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 NONROAD assumptions for summertime lawn 

and garden activity and populations have been retained. 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 inputs 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 assumed 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 appropriate, given that the NONROAD model default 

assumption is that 30% of all lawn and garden activity takes place during what we have 

defined as the Alaska winter. So, in essence, 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 PM10 emissions over time as older equipment is replaced with newer equipment. 

75
 -17-

Table 3-2 

2004 and 2018 Nonroad PM10 Emissions

Calendar Year Season PM10 (tpd)

2004 Summer 0.05

Winter 0.03

2018 Summer 0.02

Winter 0.01

Tables 3-3 through 3-6 show a more detailed presentation of the calculated Nonroad 

emission totals. For each table, the equipment has been sorted in descending order of 

total PM10 emissions. The top 20 emission sources are listed individually, and the 

remaining sources are grouped together. These tables show that, generally, a handful of 

equipment types (e.g., snowmobiles and snowblowers 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 that 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 version 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 PM10

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 Motorcycles: 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

76
 -18-

Table 3-4

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

Equipment Description Equipment Type PM10

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 PM10

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 Equipment 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

77
 -19-

Table 3-6 

2018 Mendenhall Valley Nonattainment Area Nonroad Emissions – Winter (tpd)

Equipment Description Equipment Type PM10

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

### 

78
 -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 natural gas combustion, and structural fires. 

Emissions from these sources are primarily based on activity estimates obtained from 

local agencies and/or fuel distributors. 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 human 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 methodology used to calculate emissions from each 

area source. 

4.1 Residential Fuel Use

Over the years, DEC has conducted several surveys 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. Recognizing that wood burning practices have 

shifted over the past decade, DEC commissioned a broader survey of home heating 

practices in the spring of 1994 to (a) update 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 located 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 PM10 Emission Estimates, July 19, 2004. 

79
 -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 penetration in 1993; and 

• Between 1993 and 2004, there were significant reductions in the AP-42 emission 

factors for both fuel oil and wood burning. 

Collectively, these changes were estimated to reduce annual PM10 emissions from 

residential heating (for all fuels) by almost 85% from 152.0 tons/year in 1993 to 23.2 

tons/year in 2004. The emission estimates produced in that effort, however, need to be 

revised to address the issues discussed below. 

Differences in Seasonal Definitions – The survey collected data for the winter heating 

season, which was defined to last from October 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 183 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 and 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, summer, 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.wunderground.com/history/airport/PAJN/2004/10/1/CustomHistory.html 

80
 -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 Use 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 October – 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 May, 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 allocated 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, and fuel oil use in the survey to estimate 

fuel use per household. 

81
 -23-

A total of 435 homes participated in the overall survey. The proportion of homes 

reporting each fuel use was used to extrapolate 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 growth between 2001 and 2004. Therefore, no 

adjustment was applied to account for the growth between 2001 and 2004. More recent 

demographic data have become available for Juneau and were used to prepare an updated 

estimate of the number of households in the 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 data 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 stoves, conventional 

fireplaces, modified fireplaces, etc.). Because wood use was reported on a per-household 

and not a per wood burning unit basis, and many households reported a mixture of wood 

burning devices, a method had to be developed to allocate wood use by type of wood 

burning device (i.e., those with different emission factors). This was accomplished by 

first determining the total number of wood heaters and then determining number of 

homes equipped with one or more 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 summed 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 emissions 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 technology 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 annual and a winter seasonal basis. The 

general calculation method for residential wood combustion emissions has been used in a 

number of emissions inventories 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. 

82
 -24-

EPA’s AP-42 contains emission 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 Mendenhall Valley woodstoves, as shown in the tables in Appendix E. 

Fireplaces are the other major source of PM10 emissions from wood combustion used in 

home heating. Although the 2004 survey contains 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 10th Annual Emissions Inventory Conference in 

May 2001. † The results documented in that paper show PM10 (and CO) emission factors 

for wood-burning fireplaces, which are significantly lower than those found in the most 

current AP-42 publication. (The study documented in this paper examined over a dozen 

more recent data sources for wood-burning fireplaces than contained in AP-42. PM10

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 more detailed information, this fireplace emission factor was 

used to calculate emissions for all fireplace categories included in the 2004 survey, as 

well as those for the catch-all “any other wood device” survey category. 

Both the woodstove and fireplace emission factors are given in units of pounds of PM10

produced per ton of wood burned. These were converted to units of pounds of PM10 per 

cord of wood burned by applying an assumed wood density of 30 pounds per cord, and a 

cord volume area of 80 cubic feet per cord. Both of these conversion factors were used in 

the 1988 PM10 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 PM10

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 require any conversion, as total usage was given 

in pounds, which was then multiplied directly with AP-42 emission factors for pellet 

stoves, given in units of pounds of PM10 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 stoves 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 10th Annual Emissions Inventory Conference, 

May 2001. 

83
 -25-

Table 4-3 

PM10 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 

PM10 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 reported the use of each, normalized to account for 

households that operate more than one unit (using 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. 

84
 -26-

Contrary to emission factors for wood burning 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 PM10

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 some automotive repair shops, and other similar 

facilities where it is easily accessible. Therefore, following the methodology used in the 

1999 Criteria Pollutant Inventory and 1999 Air 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 Alaska) 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 population data, and our projected 2018 population 

estimate for the Mendenhall Valley. PM10 emissions were then calculated by applying 

AP-42 emission factors (Table 1.3-1) to these activity totals. All used oil combustion 

was assumed to occur during the winter months. 

Propane – In calculating emissions from Propane 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 the 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 heating, 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 asphalt paving are in the form of 

condensable hydrocarbons (i.e., TOG or VOC 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 PM10 emissions associated with asphalt paving. 

Wildfires – There were no wildfires in the Mendenhall Valley in either 2002—as 

confirmed by the Western Regional Air Partnership’s (WRAP) recently completed 2002 

air emission inventory for fire—or in 2004. Therefore, there are zero emissions from this 

85
 -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 per exercise, for a total of 5,600 total gallons 

burned during the summer months. This total 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 Air Toxics report was used to calculate 

emissions from this source; AP-42 emission factors for residential furnaces (Table 1.3-2) 

were applied to the activity data discussed above 

Structural Fires – The total number of incidences for 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 occurred 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 developed for California by 

CARB,9 and assumed that 10% to 25% of the refuse is burned while the rest is picked up. 

The estimated PM10 emissions from burn barrels are shown in Table 4-5. As shown, burn 

barrels contribute 0.5% of the total PM10 area source emissions in the Valley at the 10% 

burning level estimate and about 1.2% of the total area source PM10 emissions at the 25% 

burning level estimate. Since the PM10 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. 

86
 -28-

Table 4-5 

PM10 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 PM10 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 emissions on a per-VMT basis were derived 

from current procedures in the U.S. Environmental 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 projected 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 report 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 roads 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 empirical constant (1.8 for PM10, 0.27 for PM2.5); 

 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 

87
 -29-

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

PM10, 0.00036 for PM2.5).*

Juneau- or Alaska-specific factors were used in Equation 1 as much as possible for 

estimating unpaved road emissions for the Mendenhall Valley. For the surface material 

silt content, 15% was used, which was the average from samples collected on unpaved 

streets in the Mendenhall Valley for a 1988 PM10 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 mean 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 order 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: Eunpaved is the final unpaved roads emission factor 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 measurable 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 during the winter (October to March) and 

106 days during the summer (April to September). 

Paved Roads – Similar to unpaved roads, fugitive emissions from paved roads take into 

account road surface properties, traffic conditions and climate for 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. 

88
 -30-

Eqn. 3 [ ] NpNC WsL

paved kE 4/)4( 32

65.0 5.1

−















  − 

 



 



 



 =

where: Epaved is the final unpaved roads emission factor adjusted for natural mitigation 

in lb/VMT; 

 k is a particle size empirical constant (0.016 for PM10 and 0.004 for PM2.5); 

 sL is the road surface silt loading in g/m2

; 

 W is the average weight of vehicle traveling the road in tons; 

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

for PM10, 0.00036 for PM2.5); 

 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 quicker 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 Engineering 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/m2

) 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 Engineering 

Science 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 better estimates for the paved road silt loading in the 

Mendenhall Valley than the national defaults. 

89
 -31-

Both the paved and unpaved road emission factors 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 average 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 area. 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&PF14 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 2004 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 contacted 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 counting. Because DOT&PF indicated that their 

90
 -32-

information on roads maintained by other agencies 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 Mendenhall Valley are limited. Consequently, the 

only unpaved local road AADT available for Juneau comes from the 1988 PM10

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 estimated by Engineering Science in the PM10

inventory report, while the 2004 Borough population 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 total 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 roads, 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 borough population was 29,946, and the 2004 population was 

30,966. 

†

 Recycled asphalt pavement (RAP) is reprocessed pavement 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. 

91
 -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 

PM10 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 PM10 fugitive dust emissions for 

Mendenhall Valley. The 2004 and 2018 seasonal PM10 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 

Calendar PM10 (tons/day) 

Year Source Winter Summer Annual Avg 

Paved Roads 1.48 4.14 2.81 

2004 Unpaved Roads 0.16 0.19 0.18 

TOTAL 1.64 4.33 2.99 

Paved Roads 1.61 4.51 3.07 

2018 Unpaved Roads 0.18 0.21 0.19 

TOTAL 1.79 4.72 3.26 

Wind Blown Dust

There are two categories of windblown dust included in this inventory: glacial riverbeds 

and cleared areas, both of which are discussed in detail below. 

Glacial River Beds – This category includes sand bars along glacial rivers, which are 

large enough to generate significant emissions during periods of high winds. In 

92
 -34-

developing the 1988 PM10 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 PM10 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 PM10 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 PM10 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 PM10 Area Source Inventory

Table 4-11 shows the PM10 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 PM10 emissions in the 

Mendenhall Valley for both 2004 and 2018. Other source categories that show relatively 

high totals of PM10 emissions include woodstoves/fireplaces and burn barrels. 

Table 4-11 

2004 and 2018 PM10 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

### 

93
 -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 continuously (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 PM10

Emission Limit 

(tons) 

Daily Emissions 

PM10

(tons) 

Generator 400 hp/hr 23.10 0.128 

Burner 180 gallons/hr 4.86 0.027 

Total 27.96 0.155 

### 

94
 -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 PM10 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 Dierckman, Transportation Planner, Juneau 

Headquarters, Department of Transportation and Public Facilities (DOT&PF), MayJune 2005. 

7. Communication with Mike Scott, Streets 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 Air 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,” Section 13.2.1-13.2.2 Paved and Unpaved 

Roads, Environmental Protection Agency, December 2003. 

11. C. Cowherd, Jr., et al., “Improved Activity Levels for National Emission Inventories 

of Fugitive Dust from Paved and Unpaved Roads,” Presented at the 11th 

International Emission Inventory Conference, Atlanta, Georgia, April 2002. 

95
 -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, Transportation Planner, Southeast Region, 

Department of Transportation and Public Facilities (DOT&PF), May 2005. 

96
Appendix A 

Inventory Preparation and Quality Assurance Plan 

97
Inventory Preparation and Quality Assurance Plan 

for 

Juneau – Mendenhall Valley PM10 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

98
A-1 

INTRODUCTION 

Background

The Mendenhall Valley, located nine miles from downtown Juneau, is the largest 

residential area in the region. Bounded by sharply 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 relatively severe temperature inversions. These inversions 

trap emissions close to the valley floor and in the past led to severe concentrations of 

airborne particulate matter that exceeded state and federal ambient air quality standards 

for PM10. 

The Mendenhall Valley is currently classified as a moderate PM10 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 planning 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, the SIP implemented a wood smoke control 

program and a fugitive dust abatement program. 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 requirements; 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 introduction of new technology has also had a 

significant impact on home heating emissions. Collectively, we estimate that the 

combination of new technology, related shifts in wood use, and implementation of 

control measures, reduced PM10 emissions by 85% from 1993 to 2004. Key contributors 

to these reductions include the following: 

99
A-2 

• Initiatives (e.g., burn bans, public education, 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 conducted last year provides detailed insight 

into the impact of both technology changes and related activity levels 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 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 Valley4

 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 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 for collecting the silt samples is presented in Appendix X. 

100
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. 

### 

101
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 and 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) and related funds for the development 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 counts 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 four descriptions: Urban Minor Arterial, 

Urban Other Principal Arterial, Urban 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 number, route name, beginning mile point, 

end mile point, length, and posted speed 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 

102
A-5 

obtain updates to these files as part of a related 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 excluded are boats, locomotives, and aircraft.* Sierra 

plans to review each of the non-road source categories to determine if operation should 

be excluded on a seasonal basis and to determine 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 residential emissions. Data on 

the mixture of devices used to heat commercial businesses located within the Valley will 

be obtained through phone calls. To provide 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 variables 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., census tracts, etc.) do not match those of the 

Mendenhall Valley. We found that all available population metrics come from systems 

that bifurcate the Valley. Census Tract 2, for 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. 

103
A-6 

Valley. Census Tract 1, however, combines the western portion of the Valley with the 

Mendenhall Peninsula and Auke Bay. The western 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 netted 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 population 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 demographic boundaries, we 

determined that the best method 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 CBJ 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 “PM10 Emission Inventories for the Mendenhall Valley and Eagle 

River Areas.” Emission calculations in that effort were based on 4,465 residential dwellings. 

104
A-7 

available) was determined to be 3.2%. This value was applied 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 population levels in 2004 and (b) identifying appropriate growth 

indices for forecasting population levels in 2018. 

Emission Calculation Methodologies

Annual and seasonal PM10 emissions will be computed on the basis of the activity data 

developed in Task 2 and emission factors derived 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 PM10 attainment plan, the silt loadings 

published in the 1988 Engineering Science emission inventory and relied upon in the 

1993 plan will be used to compute emissions for this source category. Estimates of the 

miles of unpaved roads and traffic 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 paved 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. Therefore, we will use average urban silt loadings in 

computing 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 distribution, and application rate will be identified 

through interviews of road maintenance agencies. Based on this information, 

adjustments to the silt loadings used in the 1993 emission inventory 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, MOBILE6 will be configured to represent 

Juneau using average summer and winter temperature 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 

105
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 emission calculations to quantify residential 

heating emissions in 2004. That effort prepared separate emission estimates for wooduse and fuel-oil heating. If the demographic 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. The 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 calculated using the emission factor methodology 

used by Engineering Science in the 1988 emission inventory report. The emission factor 

methodology relies on the current emission model described in AP-42, which will be 

configured using the soil particle 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 factor (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 day or week (i.e., weekday versus weekend) 

adjustments are applied depending on the requirements of the analysis. The equipment 

populations are based on national averages, and then scaled down to represent smaller 

geographic areas on the basis of human population and proximity to recreational, 

industrial, and commercial facilities. 

Sierra is well aware that many of the national average default values employed in the 

NONROAD model do not well represent activity levels in Juneau (or Alaska). However, 

the development of location-specific information can be expensive and non-road 

equipment represents a relatively small portion of the Juneau PM10 inventory. For this 

reason, Sierra plans to focus on model assumptions about the equipment categories that 

are operating in Juneau during the summer and the winter based on data collected in Task 

2 and making adjustments to assumed activity levels based on available Alaska- or 

Juneau-specific data. 

106
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 will be used to support the extrapolation of 

activity levels from 2004 to 2018. Emission factors used to project emissions in 2018 

will be updated from 2004 where information on the benefits of new control measures is 

available (e.g., MOBILE6). 

###

107
A-10 

QUALITY ASSURANCE PLAN 

This section presents a review of the QA procedures to be employed during the 

development of the Mendenhall Valley PM10 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/Carbon 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 development 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, calculation of emissions, and reporting; 

• Adequate management and supervision of the work; 

• Review of all calculations for technical 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. 

108
A-11 

The emission inventories developed in accordance with this plan are for SIP development 

and are considered Level II, based on guidance 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 PM10 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 procedures 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 measure 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. 

109
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 source-specific inventory development activities. 

QA/QC Coordinator – The QA/QC Coordinator is responsible for ensuring that adequate 

QA/QC procedures are incorporated into the inventory development process. The QA 

Coordinator’s responsibilities and 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 inventory management level; and 

• Maintain a file of findings and corresponding corrective actions. 

The QA Coordinator reports directly to Sierra’s Project Manager overseeing the 

development of the inventory. These reporting 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. 

110
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 estimation, 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 conducted according to U.S. EPA-approved procedures. The 

approach and supporting documents or references 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 the 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 correction (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); 

111
A-14 

• Units of measurements will provided for emission sources that are omitted from 

the final inventory (justification 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 telephone number and date information 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 contact; 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 described 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 DARS scoring and data checking should include descriptions 

of the rationale for scoring, the data checked, and the dated signature of the reviewer. 

Data Reporting

Reporting will be accomplished by submitting written documentation and emissions 

summaries to the Project Manager. All 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 comparison 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. 

112
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 inventories, and contain examples 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 included 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 boundaries 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 variations 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. 

### 

113
A-16 

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. 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 Mendenhall 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 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. 

7. Compilation of Air Pollutant Emission Factors, AP-42, U.S. Environmental 

Protection Agency, September 1995. 

8. “Guidance for the Preparation of Quality Assurance Plans for O3/CO SIP Emission 

Inventories,” EPA-450/4-88-023, U.S. Environmental Protection Agency, Office of 

Air Quality Planning and Standards, Research 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, Raleigh, North Carolina, November 1994. 

### 

114
Appendix B 

Demographic Estimates for City and Borough 

of Juneau, Mendenhall Valley 

115
B-1

Demographic Estimates for 

City and Borough of Juneau and Mendenhall Valley

Three separate demographic data sources are available for Juneau: 

• U.S. Census Bureau (Census Bureau) 

• Alaska Department of Labor and 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. Additional 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 population 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 nonattainment area; that estimate was prepared in 1993 for the 

“wood smoke control area of the Mendenhall Valley.” 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, Juneau subregions, etc.). Figure 1 displays 

CBJ geographic areas. It shows that the Mendenhall Valley is divided into two areas: 

east and west. The West Mendenhall Valley includes data for both the peninsula and for 

Auke Bay. The western portion of the Mendenhall Peninsula and Auke Bay lie beyond 

the ridge that forms the western boundary of the nonattainment area. The southern 

portion of the East Mendenhall Valley (the airport and adjacent areas) is below the 

southern boundary of the nonattainment area. Because of these 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 the demographic information needed to make 

the projections is presented by source in Table 1. The discussion is organized by 

calendar year. 

116
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 

117
B-3

• 1988 – the year addressed in the Engineering Science PM10 emission inventory 

for the nonattainment area. Population estimates for the entire Borough are 

available from CBJ. The Engineering Science 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 wood smoke survey in the nonattainment 

area. Population and household 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 criteria pollutant emission inventories for 

Anchorage, Fairbanks, and Juneau. 

• 2004 – the base year of the PM10 emission inventory for the nonattainment area, 

also recent population estimates are available from DLWD and the Census 

Bureau. 

• 2018 – the horizon year of the PM10 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 103

 gallons/800 gallons per home). The 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 population 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 

118
B-4

• The 2002 City and Borough population estimate was derived by selecting the 

mid-point between the 2000 Census value 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 confirmed that housing growth tracks population growth 

very closely. 

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

DLWD forecasts. Discussions with staff 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 later this year. As noted above, more current 

estimates of Juneau population levels are available (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 are 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-specific 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 

119
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. 

###

120
Appendix C 

On-Road Source Calculations 

121
P:\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 :

122
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 :

123
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 :

124
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 :

125
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

126
Appendix D 

Nonroad Source Calculations 

127
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

128
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

129
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

130
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

131
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

132
Summer 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

133
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

134
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

135
Appendix E 

Area Source Calculations 

136
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

137
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 4.898

138
E-3

Burn 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 Reside

CY2004 CY2018

Total households in Valley = 4888 5331

Other Assumptions:

All burning in summer (prohibited in winter)

Some percentage to trash pick up 90% 75%

Sensitivity Analysis for range burned 10% 25%

Summer PM10 Emissions (tpd) = 0.023 0.057 Summer 2004Summer PM10 Emissions (tpd) = 0.025 0.062 Summer 2018
E-4

Winter 2004 Woodburning Emission Calculations:

Equipment Description

# Survey 

Households 

Equipped

% Survey 

Households 

Equipped*

Projected Valley 

Households 

Equipped

Cords Burned by 

Survey 

Households 

(cords/season)

Cords Burned 

by Valley 

Households 

(tons/season)

Tons Burned by 

Valley 

Households 

(tons/season)

(

Wood Stove 93 16.8% 819 65.3 575 690.40 

Conventional Fireplace 53 9.6% 467 37.2 328 393.45 Modified Fireplace 12 2.2% 106 8.4 74 89.08 Other Non-Pellet woodburning device 4 0.7% 35 2.8 25 29.69 

Total 162 29.2% 1,427 113.8 1,002 1202.6

Total # Homes Equipped with One or More Non-Pellet Woodburning Unit 127 29.2% 1,427 

# 40 lb Stove 

Pellet bags

 tons Pellets 

burned per 

season 

Tons Burned by 

Valley 

Households 

(#

Pellet Stove 22 5.1% 247 1,097 21.9 246.61 

Total 435 34.3% 4,888
E-5

Summer 2004 Woodburning Calculations:

Equipment Description

# Survey 

Households 

Equipped

% Survey 

Households 

Equipped*

Projected Valley 

Households 

Equipped

Cords Burned by 

Survey 

Households 

(cords/season)

Cords Burned 

by Valley 

Households 

(tons/season)

Tons Burned by 

Valley 

Households 

(tons/season)

(

Wood Stove 93 16.8% 819 22.5 198 238.08 

Conventional Fireplace 53 9.6% 467 12.8 113 135.68 

Modified Fireplace 12 2.2% 106 2.9 26 30.72 

Other Non-Pellet woodburning device 4 0.7% 35 1.0 9 10.24 

Total 162 29.2% 1,427 39.2 346 414.7Total # Homes Equipped with One or More Non-Pellet Woodburning Unit 127 29.2% 1,427 

# 40 lb Stove 

Pellet bags

 tons Pellets 

burned per 

season 

Tons Burned by 

Valley 

Households 

(

Pellet Stove 22 5.1% 247 375 7.5 84.20 Total 435 34.3% 4,888
E-6

Winter 2018 Woodburning Emission Calculations:

Equipment Description

# Survey 

Households 

Equipped

% Survey 

Households 

Equipped*

Projected Valley 

Households 

Equipped

Cords Burned by 

Survey 

Households 

(cords/season)

Cords Burned 

by Valley 

Households 

(tons/season)

Tons Burned by 

Valley 

Households 

(tons/season)

(

Wood Stove 93 16.8% 893 65.3 627 752.97 

Conventional Fireplace 53 9.6% 509 37.2 358 429.11 

Modified Fireplace 12 2.2% 115 8.4 81 97.16 

Other Non-Pellet woodburning device 4 0.7% 38 2.8 27 32.39 

Total 162 29.2% 1,556 113.8 1,093 1311.6

Total # Homes Equipped with One or More Non-Pellet Woodburning Unit 127 29.2% 1,556 

# 40 lb Stove 

Pellet bags

 tons Pellets 

burned per 

season 

Tons Burned by 

Valley 

Households 

(#

Pellet Stove 22 5.1% 270 1,097 21.9 268.96 

Total 435 34.3% 5,331
E-7

Summer 2018 Woodburning Emission Calculations:

Equipment Description

# Survey 

Households 

Equipped

% Survey 

Households 

Equipped*

Projected Valley 

Households 

Equipped

Cords Burned by 

Survey 

Households 

(cords/season)

Cords Burned 

by Valley 

Households 

(tons/season)

Tons Burned by 

Valley 

Households 

(tons/season)

Wood Stove 93 16.8% 893 22.5 216 259.66 

Conventional Fireplace 53 9.6% 509 12.8 123 147.98 

Modified Fireplace 12 2.2% 115 2.9 28 33.50 

Other Non-Pellet woodburning device 4 0.7% 38 1.0 9 11.17 

Total 162 29.2% 1,556 39.2 377 452.3Total # Homes Equipped with One or More Non-Pellet Woodburning Unit 127 29.2% 1,556 

# 40 lb Stove 

Pellet bags

 tons Pellets 

burned per 

season 

Tons Burned by 

Valley 

Households 

(

Pellet Stove 22 5.1% 270 375 7.5 91.83 

Total 435 34.3% 5,331
E-8

2004 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 were normalized to 89.7% to account for homes with more than one type of unit.

Equipment Description

# Survey 

Households 

Equipped

% Survey 

Households 

Equipped*

Projected 

Valley 

Households 

Equipped

Average Winter 

Fuel Use for 

Survey Households 

(gal/hhold/season)

Average Summer 

Fuel Use for 

Survey 

Households 

(gal/hhold/year)

Total Winter Fuel 

Use for Valley 

Households 

(103 gallons/season)

Total Summer 

Fuel Use for 

Valley Households 

(103 gallons/year)

# PM10 pe

103 gallon

burned

Direct Vent Heater (i.e., Toyo, Monitor) 147 31.5% 1,537Central Oil Furnace 272 58.2% 2,845Total 419 89.7% 4,382 390 216 1,708 947 0Total # Homes Equipped with One or More Oil Heating Units 390 89.7% 4,382Totals 435 4,888 tons/da

Equipment Description

# Survey 

Households 

Equipped

% Survey 

Households 

Equipped*

Projected 

Valley 

Households 

Equipped

Average Winter 

Fuel Use for Survey 

Households 

(gal/hhold/season)

Average Summer 

Fuel Use for 

Survey 

Households 

(gal/hhold/year)

Total Winter Fuel 

Use for Valley 

Households 

(103 gallons/season)

Total Summer Fuel 

Use for Valley 

Households 

(103 gallons/year)

# PM10 pe

103 gallon

burned

Direct Vent Heater (i.e., Toyo, Moni 147 31.5% 1,677

Central Oil Furnace 272 58.2% 3,103

Total 419 89.7% 4,780 390 216 1,863 1,033 0

Total # Homes Equipped with One or More Oil Heating Units 390 89.7% 4,780

Totals 435 5,331 tons/da
Alaska Department of Environmental Conservation

Amendments to:

State Air Quality Control Plan

Vol. III: Appendices

Appendix III.D.3.9

Adopted

February 20, 2009

145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186