FINAL
FEASIBILITY ANALYSIS OF THE
IMPLEMENTATION OF
WRAP’S DUST DEFINITION
Prepared for
Western Governors’ Association
1515 Cleveland Place, Suite 200
Denver, CO 80202
Prepared by
Alison K. Pollack
Jason Conder
Julia Lester
Mary Sorensen
Gerard Mansell
ENVIRON International Corporation
707 Wilshire Boulevard, Suite 4950
Los Angeles, CA 90017
Andrew Comrie, University of Arizona
Draft: May 9, 2005
Final: January 2007
P:\W\WRAP\Final Reports\Dust Defn Feasibility Report FINAL.doc [0613782A]
CONTENTS
Page
1. INTRODUCTION
Report Organization
1
4
2. RELATED EFFORTS AND APPROACHES
Dust definitions at different spatial scales
USGS Conference
Local and Air Basin
Regional / Interstate
Global
6
6
6
6
8
15
3. FEASIBILITY ASSESSMENT APPROACH
Purpose of the WRAP Dust definition
Draft Definition
Anthropogenic and Natural Dust
Technical Approach to the Implementation of the Dust Definition
Anthropogenic and Natural Dust Estimation and Partitioning of Category 3 Emissions
17
17
19
19
20
21
4. DATA RESOURCE AND METHODOLOGY ASSESSMENT
Information Needs
Availability and Suitability of Information
Example Dust Emission Estimation
34
34
36
38
5. FEASIBILITY ASSESSMENT PROTOCOL
Introduction
Feasibility Assessment Protocol
Step 5: Identify Available data Resources and Methods for Major Category 3 Sources
51
51
51
55
6. CONCLUSIONS AND RECOMMENDATIONS
Related Efforts
Feasibility of Implementing the Draft Dust Definition
Data Resource and Methodology Assessment
Feasibility Assessment Protocol and Case Studies
56
56
56
58
59
REFERENCES
60
APPENDICES
Appendix A. Data Resources Table
Appendix B: Saguaro West Case Study (Separate Report)
Appendix C: Salt Creek Wilderness Case Study (Separate Report)
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CONTENTS
(continued)
Page
TABLES
Table 2-1: Anthropogenic Contribution to Global Dust Loadings (from Kohfeld, et al.,
October 2004 USGS conference presentation)
16
Table 3-1. Potential uses of a feasible dust definition (WRAP identified).
26
Table 3-2. Current conceptual method of partitioning natural and anthropogenic dust
emissions.
27
Table 3-3. Dust sources in the draft definitions of dust and preliminary identification of the
natural and anthropogenic portion of each source.
28
Table 3-4. Dust sources in the draft definitions of dust and category identification.
30
FIGURES
Figure 2-1.
WRAP Regional Haze Rule Conceptual Glide Path
Figure 2-2.
Class I Areas in the Western Continental US with 50-km analysis areas around
each. ENVIRON has characterized the emissions within and near each of these
analysis areas for the WRAP Sources In and Near Forum.
14
Figure 3-1.
WRAP Draft Dust Definition.
30
Figure 3-2.
Amended WRAP Dust Definition, focusing on three categories of dust sources.
31
Figure 3-3.
Procedure for estimating dust emission for a Category 3 dust source.
32
Figure 3-4.
Dustfall mass (heavy line) and dustfall particle mean diameter (light line)
versus depth in sediment core from the bottom of Fourth of July Lake in
eastern Washington. The dotted line approximates the long-term trend in
dustfall mass. Arrows indicate approximate year when dustfall occurred along
the length of the sediment core. Methods used to investigate pre-industrial
dustfall may be useful in understanding natural dust emissions for natural
lands, including the variability with climate and vegetation changes. In turn,
this may facilitate partitioning of current dust emission estimates into natural
and anthropogenic portions. Reproduced from Busacca et al. (1998).
33
Location of example study point in southern California (Resource: USGS
National Map Viewer).
42
Figure 4-1.
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CONTENTS
(continued)
Page
Figure 4-2.
Figure 4-3.
Figure 4-4.
Figure 4-5.
Figure 4-6.
Figure 4-7.
Figure 4-8.
Figure 4-9.
Results of the query for a list of mammals that could be found at the
hypothetical site (Resource: Smithsonian National Museum North American
Mammals Database).
43
Life history data potentially useful in constructing a dust emission mode for
mule deer (Resource: Cumulative Index for the Mammalian Species).
44
Distribution of desert scrub in California (Resource: California Wildlife
Habitats Relationships software).
45
Habitat preference data (habitat suitability values) for mule deer in desert scrub
habitat (Resource: California Wildlife Habitats Relationships software).
46
Hyperspectral map of predicted bare ground cover; bare soil areas subject to
erosion are shown in yellow (Resource: Eolian Mapping Index). Example map
only (location shown in northern Arizona).
47
GIS file depicting soil types present at hypothetical southern California site
(Resource: Soil Data Mart, Soil Survey Geographic database).
48
Urban land uses near hypothetical southern California site (highlighted
yellow), obtained via land use GIS data (Resource: California GAP Analysis
Project).
49
Locations of roads at hypothetical southern California site (Resource: USGS
National Map).
50
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PREFACE
Regulatory Framework for Tribal Visibility Implementation Plans
The Regional Haze Rule explicitly recognizes the authority of tribes to implement the provisions of the
Rule, in accordance with principles of Federal Indian law, and as provided by the Clean Air Act
§301(d) and the Tribal Authority Rule (TAR) (40 CFR §§49.1– .11). Those provisions create the
following framework:
1. Absent special circumstances, reservation lands are not subject to state jurisdiction.
2. Federally recognized tribes may apply for and receive delegation of federal authority to
implement CAA programs, including visibility regulation, or "reasonably severable" elements
of such programs (40 CFR §§49.3, 49.7). The mechanism for this delegation is a Tribal
Implementation Plan (TIP). A reasonably severable element is one that is not integrally related
to program elements that are not included in the plan submittal, and is consistent with
applicable statutory and regulatory requirements.
3. The Regional Haze Rule expressly provides that tribal visibility programs are “not dependent
on the strategies selected by the state or states in which the tribe is located” (64. Fed. Reg.
35756), and that the authority to implement §309 TIPs extends to all tribes within the GCVTC
region (40 CFR §51.309(d)(12).
4. The EPA has indicated that under the TAR tribes are not required to submit §309 TIPs by the
end of 2003; rather they may choose to opt-in to §309 programs at a later date (67 Fed. Reg.
30439).
5. Where a tribe does not seek delegation through a TIP, EPA, as necessary and appropriate, will
promulgate a Federal Implementation Plan (FIP) within reasonable timeframes to protect air
quality in Indian country (40 CFR §49.11). EPA is committed to consulting with tribes on a
government to government basis in developing tribe-specific or generally applicable TIPs
where necessary (See, e.g., 63 Fed. Reg.7263-64).
It is our hope that the findings and recommendations of this report will prove useful to tribes, whether
they choose to submit full or partial 308 or 309 TIPs, or work with EPA to develop FIPs. The amount
of modification necessary will vary considerably from tribe to tribe. The authors have striven to
ensure that all references to tribes in the document are consistent with principles of tribal sovereignty
and autonomy as reflected in the above framework. Any inconsistency with this framework is strictly
inadvertent and not an attempt to impose requirements on tribes which are not present under existing
law.
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Tribes, along with states and federal agencies, are full partners in the WRAP, having equal
representation on the WRAP Board as states. Whether Board members or not, it must be remembered
that all tribes are governments, as distinguished from the “stakeholders” (private interest) which
participate on Forums and Committees but are not eligible for the Board.
Despite this equality of representation on the Board, tribes are very differently situated than states.
There are over four hundred federally recognized tribes in the WRAP region, including Alaska. The
sheer number of tribes makes full participation impossible. Moreover, many tribes are faced with
pressing environmental, economic, and social issues, and do not have the resources to participate in an
effort such as the WRAP, however important its goals may be. These factors necessarily limit the
level of tribal input into and endorsement of WRAP products.
The tribal participants in the WRAP, including Board members Forum and Committee members and
co-chairs, make their best effort to ensure that WRAP products are in the best interest of the tribes, the
environment, and the public. One interest is to ensure that WRAP policies, as implemented by states
and tribes, will not constrain the future options of tribes who are not involved in the WRAP. With
these considerations and limitations in mind, the tribal participants have joined the state, federal, and
private stakeholder interests in approving this report as a consensus document.
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1. INTRODUCTION
Historically, particulate matter (PM) issues (and related visibility issues) have focused on
anthropogenic sources, since it is these sources that are emphasized in the Clean Air Act and are
subject to control to achieve or maintain air quality standards. Similarly, most modeling
assessments in State Implementation Plans (SIPs) focused on anthropogenic sources and used
source-receptor models and rollback analyses. In certain areas, such as the South Coast Air Basin,
the presence of both secondary and primary PM10 led to the use of increasingly sophisticated threedimensional, photochemical models, such as those used in ozone modeling. The same trend is now
occurring in visibility assessments, based on the multiple PM components that affect visibility.
Unlike ozone modeling, where biogenic (e.g. natural) sources of hydrocarbons are estimated and
included in the modeling inventories (but not the reporting inventories), most PM (and visibility)
modeling does not explicitly include “natural” sources of PM. Nor do standard reporting PM
inventories discriminate between natural and anthropogenic sources of PM; indeed, most SIP
inventories do not include natural sources of PM. In previous modeling exercises, the impact of
natural PM was often described as “background,” and excluded from rollback analyses. As
planners and policy makers formulate and communicate their plans to improve visibility and PM air
quality, there is an increasing need to discriminate between uncontrollable and controllable sources
to better assess PM control and visibility improvement strategies. The need exists for PM emission
inventories that report both the natural and anthropogenic components of dust sources.
The WRAP draft dust definition is a first step in creating such inventories. The goal of this project
is to assess if the draft definition can be feasibly applied, on a source type by source type basis, to
identify the natural and anthropogenic contributions of certain dust sources. To support the latest
modeling tools used in PM and visibility analyses, a feasible application of the dust definition
would also need to produce spatially and temporally resolved inventories of natural and
anthropogenic contributions. To be feasible for these types of applications, implementation of the
draft definition would have to be capable of producing these spatially and temporally resolved
inventories of natural and anthropogenic emissions.
Section 169 of the Clean Air Act declares as a national goal “the prevention of any future, and the
remedying of any existing impairment of visibility in mandatory Class I federal areas which
impairment results from man-made air pollution.” In 1999, the U.S. Environmental Protection
Agency (EPA) promulgated the Regional Haze Rule (RHR) to meet this national goal. The
Western Regional Air Partnership (WRAP) is a collaborative effort of tribal governments, state
governments, and various federal agencies to implement the recommendations of the Grand Canyon
Visibility Transport Commission (GCVTC) and to develop the technical (e.g. information and data
gathering, data analysis, emission inventory development, and modeling) and policy tools needed
by western states and tribes to comply with the RHR. WRAP also seeks to provide technical
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assistance to States in the development of emission control strategies to improve visibility. In the
WRAP region, dust (as opposed to point sources of primary particulates, such as elemental carbon,
and secondary particulates formed in the atmosphere) is a significant component in visibility
degradation. As implied by the national goal definition, only visibility impairments from man-made
pollution must be prevented and/or remedied. Mobile sources and stationary point sources are
clearly man-made sources of pollution, but dust sources, particularly fugitive dust sources, can
result from both man-made and natural conditions. As noted by the co-chair of WRAP’s Dust
Emission Joint Forum (DEJF) at the April 2004 Best Available Control Measures (BACM)
Working Group meeting, “The distinction between anthropogenic and natural dust will help us to
identify and prioritize sources of dust that are most appropriate to control.”
To assist in the identification of anthropogenic and natural dust the DEJF has created a draft
definition with broad criteria for categorizing dust emissions as natural or anthropogenic. Even at
this broad level, there is a potential overlap where sources may be considered both natural and
anthropogenic (c.f. the following figure, “Examples of Anthropogenic and Natural Emissions Under
a Draft Definition of Dust, taken from the RFP).
The absence of a solid line separating natural from anthropogenic sources is one of the issues that
increases the difficulty in applying the definition for operational purposes, such as inventories,
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modeling and control strategy development and assessment. The DEJF has identified several
potential purposes of a feasible dust definition. These include:

Clarify how the WRAP defines dust, its sources, and causes;

Provide an operational definition for use in receptor- and emissions-based source
apportionment techniques; and

Identify and prioritize sources of dust which are most appropriate to control for
purposes of improving visibility in Class I areas.
A potential use of a definition would be to delineate anthropogenic and natural dust emission in the
WRAP emissions inventory. Each emission type could then be “tagged” separately in the WRAP’s
air quality simulation model to estimate the contribution of natural and anthropogenic sources of
dust to visibility impairment in Class I areas. The definition may also be useful for describing
predominant source types (i.e., natural versus anthropogenic) when analyzing specific dust events
and/or discussing them with a variety of WRAP stakeholders. Other common western regional air
quality issues raised by the WRAP membership may also be addressed through the results of this
project. As many areas near attainment or work to maintain their attainment status, better
information on sources subject to control (anthropogenic sources) and those that are not (natural
sources) would allow more targeted and cost-effective “end game” strategies, compared to more
traditional across-the-board control strategies. Lastly, as the RFP notes, the “dust definitions are not
intended for use in refining EPA’s estimates of natural visibility conditions, although they may be
useful for that purpose. These definitions may also be used with regard to dust emanating from
outside of the U.S. – that is, dust from other countries can be either natural and/or anthropogenic.”
It will be noted when certain data/methods may be available (and at what cost) that would allow the
feasible use of the dust definition for these purposes.
The DEJF believes the draft definition is conceptually sound, but is uncertain whether it can be
implemented in practice (e.g., for the applications above), and at a reasonable cost. This report
describes the potential criteria and related data/methods that would allow for the delineation of
natural and anthropogenic origins of dust. One test for feasibility is the “reasonableness” of the
availability of and the cost of obtaining the needed data and applying the appropriate method(s).
The report presents an initial assessment of data resources and methods. The assessment includes
information on the availability, cost, extent, and applicability to end uses (e.g. emission
characterization, estimation, or partitioning). This report identifies the breadth and depth of the
needed data, the qualifications of necessary interpreters of the data, and, where available, its cost.
The feasibility of implementing the dust definition may vary by project and purpose. To address
this issue, the report contains a Feasibility Assessment Protocol, which will allow users to identify
the data sources that are relevant to their projects based on the purposes of those projects (e.g.,
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inventory development, current inventory partitioning, air or visibility modeling of current, future,
or restored natural scenarios). The report will provide conclusions as to the general level of
feasibility for implementing the dust definition for regional haze purposes based on the readily
available data/methods for each source type. If such data exists for general applications of interest
to WRAP and its forums, the dust definition can be generally considered feasible. For specialized
applications, additional data/methods may be needed that are not currently available (e.g. satellite
imagery, field studies, novel GIS applications) and the cost would be higher. The feasibility of the
application of the dust definition in these cases would depend on the importance of the project and
the resources available.
Report Organization
This report is organized as follows:

Section 2 presents a brief review of other efforts related to characterizing, estimating, and
partitioning natural and anthropogenic sources of dust.

Section 3 presents the current WRAP draft dust definition and the feasibility assessment
approach of this report.

Section 4 presents the assessment of data resources and methods that could be used to
implement the dust definition.

Section 5 presents the Feasibility Assessment Protocol, a tool to determine the feasibility of
implementing the dust definition for specific projects and purposes. This section also looks
at the general feasibility of implementing the dust definition for regional haze inventory and
modeling assessments.

Section 6 presents the conclusions and recommendations of this report on the feasibility of
implementing the draft dust definition.

References

Appendix A presents the data resources that have been identified and assessed as useful in
implementing the draft dust definition.
The data resources are presented in a
comprehensive, tabular form.
After the release of the draft Feasibility Assessment in May 2005, ENVIRON conducted to case
studies to evaluate the effectiveness of the Feasibility Assessment Protocol proposed in this Report.
During the development of these case studies, revisions and additions to the Feasibility Assessment
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Protocol were made. Those revisions and additions are discussed in the two case studies, which
have been included under separate covers as Appendix B and C of this final Report.

Appendix B is the first case study of the Draft Dust Definition. The area of study was the
Saguaro West Class I area in Arizona, chosen to represent an area with significant dust
impacts to visibility with relatively few data resources for implementing the Dust Definition.

Appendix C is the second case study of the Draft Dust Definition. The area of study was
the Salt Creek Wilderness Class I area in New Mexico, chosen to represent an area with
significant dust impacts to visibility with relatively rich data resources for implementing the
Dust Definition. It was also chosen because results from this case study were used in
WRAP’s New Mexico SIP Pilot Study.
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2. RELATED EFFORTS AND APPROACHES
Dust definitions at different spatial scales
USGS Conference
The United States Geological Survey (USGS) hosted a workshop on October 23-24, 2004 entitled
“Linking the Scales of Process, Observation, and Modeling of Dust Emissions.” Topics at the
workshop included how to integrate dust studies of different scales (spatial and temporal), what
physical and biotic conditions are associated with spatial and temporal variability of dust emissions,
how to produce regional maps of dust-emission potential suitable for linking to meteorological and
climate models, and identifying what portion of emissions are attributable to anthropogenic
disturbances, directly (e.g. construction, agriculture) or indirect consequences resulting from
climate change. Over 17 presentations and other contributions related to these topics can be found
at the USGS web site (http://esp.cr.usgs.gov/info/dust). Several of the presentations dealt with
emissions from sources with both natural and anthropogenic contributions. The focus, however, is
still on studies that produce inputs to meso- and macro-scale dust emissions, transport, and
deposition models rather than identifying specific anthropogenic and natural contributions. For the
field studies, workshop participants identified the desert regions of western North America, with the
Mojave Desert as a good study area. They noted that western North America is historically
significant because human intervention and land management practices have dramatically altered
the landscape and related dust emissions. Also, dust storms have arisen from several different types
of conditions in the Mojave Desert, the western Great Plains, and northern Mexico. They
characterized the Mojave Desert as an area where extensive documentation exists of geological,
ecological, and surface characteristics, as well as information concerning anthropogenic activities
and climate changes.
Local and Air Basin
Most studies of fugitive dust at the local and air basin level have focused on anthropogenic sources
and their emissions. For local areas, the issue has been identifying and mitigating nuisance dust.
For air basins, State Implementation Plans (SIPs) have focused on attaining the National Ambient
Air Quality Standards (NAAQS) for PM10. SIP inventories and modeling have historically only
described anthropogenic sources of PM10 or PM10 pre-cursors. (In contrast, ozone SIP modeling
inventories will often include biogenic VOC emissions, although those emissions are not reported in
annual average or planning emission inventories used for SIP tracking purposes. Some areas do
identify a small fraction of “background” PM10 during modeled attainment demonstrations.)
Several areas have also prepared Natural Event Action Plans (NEAPs), as allowed under U.S.
EPA’s Natural Events Policy (NEP). The NEP was promulgated in June 1996 and covers high
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PM10 levels from natural sources such as volcanic eruptions, wildfires, and windblown dust. The
focus of the NEP is the education and alerting of populations that could be affected by natural
events, controlling anthropogenic sources with best available controls, and studying other potential
mitigation strategies. The policy does not require the quantification of emissions from natural
sources, although they may need to be characterized in documenting individual natural events.
The Arizona DEQ used a slightly different approach, determining "normal" and "extreme" climate
conditions to subsequently determine if certain PM events were extraordinary because of an
extreme natural climate event (windy and dry). More information about this approach can be found
in Arizona Department of Environmental Quality (ADEQ) “Technical Criteria Document for
Determination of Natural Exceptional Events For Particulate Matter Equal to or Less Than Ten
Microns in Aerodynamic Diameter (PM10),” dated May 31, 2000 and “Climatological Analysis for
PM10 Natural Exceptional Events in Arizona” (Comrie and Garfin, June 2001).
The WRAP Sources In and Near Class I Areas Forum is currently conducting a review of PM10
State Implementation Plans (SIPs) and Natural Events Action Plans (NEAPs) that have been
prepared for locations within the WRAP region. These reviews are focused on the development of
information which can ultimately be used for the evaluation, selection, and implementation of
emission management strategies. A preliminary summary of past and current PM 10 nonattainment
areas, status, and types of plans submitted has been completed (Roe, S. 2005. WRAP PM10 SIP
Review Project Technical Memorandum #1: Initial Selection of Candidate Nonattainment Areas.
E.H.Pechan & Associates, 24 March 2005, http://www.wrapair.org/forums/class1/projects/pm10
sips/TM-1.pdf).
WRAP’s review of emission management strategies is focused on control measures with proven
effectiveness in reducing ambient PM levels. At this point, a group of 23 PM10 nonattainment areas
have been identified for further analysis. One result of this preliminary review is that most of the
PM10 nonattainment areas within the WRAP region are characterized by situations in which PM10
violations are primarily attributable to a very limited number of source groups (commonly
residential wood smoke, agricultural tilling and cultivation, or travel on unpaved roads). However,
there are of course some very large and important areas (San Joaquin Valley, South Coast) with
complex source mixtures and a greater variety of control measures. Of particular interest to the
issue of anthropogenic vs. non-anthropogenic fugitive dust sources is the types of sources for which
control measures have been included in the SIPs being reviewed by WRAP. The In and Near Class
I Areas Forum’s schedule calls for completion of this project by June 30, 2005.
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Regional / Interstate
NAPAP:
As part of the National Acid Precipitation Assessment Program (NAPAP), a state-of-the-scienceand-technology report was prepared for visibility. The report (Trijonis, 1990) focused on the causes
and effects of existing and historical conditions, related to visibility. The default annual natural
levels of PM components in the EPA's Guideline for Estimating Natural Conditions Under the
Regional Haze Rule (EPA, 2003) were based on values that were developed for the NAPAP by
Trijonis, 1990. It was assumed that half of the fine soils were natural, resulting in 0.5 g/m3 of
annual average concentration. The coarse mass was assumed to be all natural and to contribute
about 3 g/m3 to the annual average concentrations. The coarse contribution was assumed to be the
same in the eastern and western United States. These estimates were very simplistic and,
particularly for the coarse contribution, arbitrary. The analysis is based on older measurements and
is a top-down estimate, independent of dust source characterization or quantification. It does not
account for new information on regional dust storm characterization and global transport (e.g., Gobi
and Saharan dust storms).
Western Regional Air Partnership
In response to regulatory requirements for regional haze SIPs (see Chapter 1), WRAP provides
technical and policy tools needed by the western states and tribes to comply with the RHR. WRAP
has prepared a conceptual glide path to describe the goals and challenges of the RHR.
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Figure 2-1. WRAP Regional Haze Rule Conceptual Glide Path
As shown in Figure 2-1, the goal of the RHR is to attain natural visibility conditions by 2064. A
key concept is “natural conditions.” For WRAP, natural sources include natural windblown dust,
biomass smoke, and other natural processes. Manmade sources include industrial activities and
man-perturbed smoke and dust emissions. Distinguishing between natural and man-made sources
has been a key issue for WRAP.
From the WRAP “Policy for Categorizing Fire Emissions:” The WRAP Fire Emissions Joint Forum
(FEJF) was established to develop policy and technical tools to address smoke effects caused by
wildland and agricultural fire on public, tribal, and private lands. Due to the limitations of the
current visibility monitoring technology to determine fire impacts, the FEJF was charged with
addressing fire emissions’ contribution to natural background conditions. The FEJF formed the
Natural Background Task Team (NBTT) to develop a methodology to categorize fire emissions as
either “natural” or “anthropogenic”; thus providing the basis for fire’s inclusion in natural
background condition values and ultimately, the tracking of reasonable progress. This Policy has
been developed over an 18-month period by the NBTT; a group made up of state, tribal, and federal
agency representatives, as well as those from industry, agriculture, academia, and environmental
organizations. During this process, the NBTT solicited public input regarding both technical and
policy issues. The resulting Recommended Policy for Categorizing Fire Emissions was granted
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consensus approval by the FEJF on August 30, 2001. The WRAP granted consensus approval for
the Policy on November 15, 2001.
The WRAP Dust Emissions Joint Forum (DEJF) has developed a draft dust definition to distinguish
between natural and anthropogenic fugitive dust emission sources (see Chapter 3 for the DEJF’s
draft dust definition). The purpose of this report is to assess the feasibility of implementing this
dust definition in the tools and policies used by the states and tribes to comply with the RHR. If
feasible, this definition would provide a basis for natural dust to be included in the natural
background conditions and future reasonable progress assessments.
WRAP has commissioned the compilation of detailed information on PM composition, component
contributions to visibility impairment, ambient PM trends, and other information which will be used
to identify the causes of haze (CoH) in each Class I area (see CoH Assessment project web site at
http://coha.dri.edu/index.html). WRAP is using this and other information to develop a preliminary
report on the Attribution of Haze (AoH) in each Class I area (see http://www.wrapair.org/forums/
aoh/ars1/index.html). Results from the CoH Assessment and AoH projects will be useful for
identifying potential high priority source categories for analysis.
In addition, two recent studies funded by WRAP have been completed by ENVIRON which will
provide important background information for the proposed study. Under contract to the WRAP
and its forums, ENVIRON completed a windblown dust emission inventory that covered the WRAP
air quality modeling domain (Mansell et al., 2005) and an extensive emission inventory compilation
(Pollack et al., 2004) for all non-windblown PM sources located in and within 50 km of the
boundaries of each of the 116 Federal and 5 Tribal Class I areas in the WRAP states. The results of
these emission inventory development and analysis projects provide a better understanding of the
benefits and limitations of the various methods and data available to quantify natural and
anthropogenic dust sources in the inventories.
Attribution of Haze and Causes of Haze Projects
The WRAP has established the Attribution of Haze Workgroup to prepare a policy-level report
describing the emissions source categories and geographic source regions presently contributing to
visibility impairment at each of the tribal and mandatory federal Class I Areas within the WRAP
region. The Workgroup included a broad representation of technical and policy representatives and
established an open meeting format to foster additional input and coordination among the various
stakeholders. The project was designed in two Phases, with the first Phase designed as a “trial” run
for Phase II. Phase II will build upon the findings and recommendations of Phase I.
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The goals of the Attribution of Haze (AoH) project are:

To provide state and tribal air regulators with an initial, regional assessment of the
attribution of haze in their Class I Areas:

To provide an initial assessment of how and to what extent natural and anthropogenic
emissions from each state affect western Class I Areas; and

Ultimately, to provide air regulators with the information and tools necessary to prepare stat
and tribal implementation plans (SIPs and TIPs) under the Regional Haze Rule (RHR).
The attribution of haze results of Phase I were designed neither to explicitly single out individual
sources nor to identify the amount of reductions needed by a given source or group of sources in
order to meet the RHR goals. Rather, the results of the project are intended to give a preliminary
assessment of the natural and anthropogenic emissions from geographic source regions that
contribute to visibility impairment at Class I Areas. In addition, conducting original research was
not the intent of the project, but rather, the project was designed to assemble existing information
from various analyses and utilize that information to determine the source types and regions
impacting each of the Class I Areas. Specifically, three major of analyses and data used for the
project include:

Emission inventories – Although in some cases the emission inventories were incomplete or
uncertain, the inventories defined the geographic regions and provided estimates of the
magnitude of emissions;

Monitoring data – Light extinction calculated from measures speciated fine mass and total
coarse mass define the scope of visibility impacts in or near Class I Areas;

Modeling results – Atmospheric chemistry and transport models were used to provide the
connection between emissions from geographic source regions and measured fine mass in or
near Class I Areas.
Source attribution was described and evaluated using a weight of evidence approach. The
methodology involved reviewing emission inventories, monitoring data, and modeling results for
the 2002 calendar year. One or two independent source apportionment methods were applied to
each Class I Area, results compared and supporting data and information were used to corroborate
or further scrutinize apportionment result.
Supporting data and analyses used in the project included the results of the Causes of Haze
Assessment (COHA) conducted by the Desert Research Institute under contract to WRAP. The
COHA project used meteorological back trajectory analyses for all Class I Area monitoring
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locations with the WRAP region using NOAA’s HYSPLIT model. Combining back trajectory
results and monitoring data enabled a Trajectory Regression Analysis for each monitoring location.
The analysis related the amount of time air spends over a source region, as determined by a
compilation of many back trajectories, .to the aerosol species measured at a receptor site ad was
applied to sulfate and aerosol extinction only.
As previously noted, the AoH results and recommendations were based on a weight of evidence
approach rather than any single data set, analysis result, or line of reasoning. As such, a significant
amount of information and analysis results, including apportionment and attribution methods,
meteorological back trajectory summaries, and emissions and monitoring data and summaries are
available for use in the development and application of a refined dust definition and development of
a dust definition feasibility protocol. The results of Phase II of the AoH project may provide
additional supporting data and analyses for use in current efforts regarding dust definition
refinements and implementation.
Fugitive Windblown Dust Emissions From Wind Erosion
Fugitive PM emissions from wind erosion were estimated by a team led by ENVIRON for WRAP.
Emission estimates were made using a model developed based upon the most recent information
available in the literature and implemented in a variety of models (Mansell, et al., 2005). The
development and application of the estimation methodology relies on detailed knowledge
concerning surface characteristics of vacant lands susceptible to wind erosion. Given the large
regional scale domain to which the model was applied, certain assumptions were made due to the
lack of detailed information available to characterize the vacant land surfaces. In particular,
assumptions regarding the various landuse types, vegetative cover and disturbance levels of the
soils were required.
The results of the Windblown Dust Project indicated a strong dependence on the assumed values for
surface roughness lengths, as determined by the land use types, and the level of disturbance of the
soils. One of the major limitations of the modeling results is directly related to the assumed level of
soil disturbance. Assumptions were necessary due to the large geographic extent of the modeling
domain and the lack of data to adequately characterize surface conditions. It is anticipated that the
results of the current feasibility study would be invaluable in providing additional supporting
information to better resolve and characterize the surface parameters most important in the
estimation of dust from wind erosion.
In addition, while it is currently difficult, if not impossible, to distinguish between anthropogenic
and natural sources of windblown dust, the results of the feasibility assessment presented herein can
be useful in providing additional data and information to apply as a first attempt to address these
concerns. Also, the results of the dust definition refinements and assessment protocol, particularly
the various surface characterization data identified, may allow for improvements to the application
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of the windblown dust model. Refinements to the methodology would be focused on those areas
most susceptible to, or known to be caused by, human related activity (i.e., anthropogenic sources).
These refinements will also provide WRAP with information to allow more focused control strategy
development efforts.
In And Near Class I Areas Emission Inventory Development – Non-Windblown
In Pollack et al., 2004, emission estimates were obtained for primary PM10, PM2.5, and precursors
(VOC, NOx, SO2, NH3). This effort involved estimating area and mobile source emissions based on
mapping of appropriate surrogate data within the identified 50 km analysis zones (shown in Figure
2-2 for the western conterminous US – Class I areas are also present in Alaska) and spatially
allocating area and mobile source emissions contained in the 1996 county-level WRAP inventories
to the analysis zone around each Class I area. ENVIRON also surveyed state officials and Federal
Land Managers with local knowledge of Class I areas in the WRAP region to obtain basic
information on the presence and role of local emission sources and their impact on visibility in all
Class I areas. This project resulted in the development of an extensive set of spreadsheets and maps
that summarize the inventories for each area (or area group) by emissions source category. These
maps and spreadsheets along with other work products from this project are available on the WRAP
project web page (http://www.wrapair.org/forums/class1/near/htmlfiles/main.html).
Source
categories for which emission summaries were developed include non-windblown dust area
sources, fire and on- and off-road mobile sources. Although most of these sources are not directly
related to the issues that have arisen for the draft dust definition, databases related to spatially and
temporally resolving wild vs. prescribed fires, unpaved roads (e.g., penetration of human activity
into native lands), and logging equipment may be useful in establishing new methods or as a source
of data that could distinguish natural from anthropogenic dust emissions for related sources. In
addition, the results of the project provides some information concerning the relative importance of
various emission sources, particularly dust sources, which can be used to prioritize further efforts
associated with the distinction between natural and anthropogenic sources.
The emission inventory analysis and evaluation of survey results conducted for the in and near
Class I areas project provided valuable information regarding the types of activities and their
importance with respect to particulate matter emissions near Class I Areas throughout the Western
US. Results showed that of the PM sources examined, fugitive dust from construction, agricultural
tillage and harvesting, and paved and unpaved road dust, along with PM from residential wood
combustion and industrial processes account for 94 percent of PM10 and 84 percent of PM2.5
emissions from non-windblown/non-natural area and nonroad mobile sources over all of the Class I
analysis areas combined. Survey respondents contacted for this project provided information on
trends in emission sources and on local regulations and control measures intended to address the
largest source categories. Information collected and identified through the survey efforts of this
project will be useful in evaluating the feasibility of applying the dust definition to specific Class I
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areas, addressing feasibility issues by targeted data acquisition, and ultimately, applying the dust
definition to the relevant inventories for use in modeling or other assessments.
Figure 2-2. Class I Areas in the Western Continental US with 50-km analysis areas around
each. ENVIRON has characterized the emissions within and near each of these
analysis areas for the WRAP Sources In and Near Forum.
Vegetated Surfaces in the Southwestern United States
Okin and Gillette (2004) reviewed a state of the science for modeling wind erosion and dust
emission from naturally-vegetated lands in the Southwestern United States. They note that while
many dust emission models can accommodate a fair degree of complexity at a regional scale, few
can produce spatially-explicit estimates of dust flux. Modeling approaches incorporating
instruments such as the Total Ozone Mapping Spectrophotometer (TOMS) are useful in very coarse
(regional) scales. For example, previous work by Ginoux et al. (2001) suggests that the
overwhelming majority of desert dust originates from ephemeral lake basins. Other researchers
suggest that a majority of dust is associated with anthropogenic land uses (Mahowald et al., in
press). Models such as the Spatially Explicit Wind Erosion and Dust Flux Model (SWEMO) are in
development, using data from the Journada Basin in south-central New Mexico. SWEMO uses
maps of soil texture and vegetation, in addition to knowledge of vegetation and size parameters, to
create maps of wind erosion susceptibility and dust flux. A key weakness the authors identify in the
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model is that the bulk of dust emissions at a regional scale often appear to occur in very small “hot
spot” areas that are beyond the predictive capacity of the model due to the comparatively low
resolution of soil and vegetative cover maps. Mapping hot spots may be the key to producing
reliable models for regional and site-specific dust emission. Okin and Gillette (2004) remark that
hyperspectral analysis, geostatistical analysis of aerial photographs, and remote sensing of
vegetation density using optical canopy models may be useful tools in this effort. Spatial modeling
of dust emission on vegetated lands in the Southwestern United States remains in its infancy, and
models such as SWEMO are only first steps in estimating dust emissions at a regional scale on these
vegetated surfaces. Models such as SWEMO do not possess the ability to partition anthropogenic
and natural dust emissions.
Global
Zender et al. (2004) reviewed terminology and constraints associated with current approaches which
are being used to quantify mineral dust mass budgets on a global scale. The authors note several
key concerns with current global modeling approaches:

Emission estimates cover a wide range (more than a factor of 2). This variability is
primarily due to the goals of the emission models and their inherent assumptions.

Dust particle size varies widely among models. Zender et al. (2004) recommend
standardization of particle size in future efforts (i.e., particle diameter < 10 μm).

There is high uncertainty with all models. For example, substituting one set of
meteorological dataset for another (collected by two different organizations) produce
estimates of global dust loads that vary by four-fold or more.

Few models distinguish between natural and anthropogenic dust emissions. Zender et al.
(2004) propose a more complex partitioning scheme for emission sources. Natural sources
are identified as regions that emitted dust in pre-industrial times (e.g., prior to 1750 in North
America). Zender et al. (2004) further subdivide anthropogenic sources into “1st kind”,
which are due to direct modifications to the land that alter soil erodibility, and “2nd kind”,
which are due to anthropogenic changes to the global climate.
As noted in the Kohfeld et al. presentation at the October 2004 USGS conference, there is a great
deal of uncertainty as to the impact of natural sources in global dust loadings. From her
presentation:
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Table 2-1: Anthropogenic Contribution to Global Dust Loadings (from Kohfeld, et
al., October 2004 USGS conference presentation)
Study
IPCC, 2001
Anthropogenic
Contribution
Up to 50%
Comment
tuned to AVHRR AOT
Prospero et al. 2002
small
Natural sources dominant
Luo et al. 2003
0-50%
New desert sources
Tegen et al., 2004
<10%
Comparing simulated and observed dust
storm frequencies
Mahowald et al. subm.
0-50%
Comparing simulated and observed dust
storm frequencies
For future efforts, Zender et al. (2004) note that modeling and observation strategies should attempt
to partition natural and anthropogenic sources of dust in order to be of relevance to decision makers.
The authors admit that this is extremely challenging and will require a focused interdisciplinary
effort, given the complexity and high natural variability associated with natural dust emissions.
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3. FEASIBILITY ASSESSMENT APPROACH
Purpose of the WRAP Dust definition
Historically, particulate matter (PM) issues (and related visibility issues) have focused on
anthropogenic sources, since it is these sources that are emphasized in the Clean Air Act and are
subject to control to achieve or maintain air quality standards. Similarly, most modeling
assessments in State Implementation Plans (SIPs) focused on anthropogenic sources and used
source-receptor models and rollback analyses. In certain areas, such as the South Coast Air Basin,
the presence of both secondary and primary PM10 led to the use of increasingly sophisticated threedimensional, photochemical models, such as those used in ozone modeling. The same trend is now
occurring in visibility assessments, based on the multiple PM components that affect visibility.
Unlike ozone modeling, where biogenic (e.g. natural) sources of hydrocarbons are estimated and
included in the modeling inventories (but not the reporting inventories), most PM (and visibility)
modeling does not explicitly include “natural” sources of PM. Nor do standard reporting PM
inventories discriminate between natural and anthropogenic sources of PM; indeed, most SIP
inventories do not include natural sources of PM. In previous modeling exercises, the impact of
natural PM was often described as “background,” and excluded from rollback analyses. As
planners and policy makers formulate and communicate their plans to improve visibility and PM air
quality, there is an increasing need to discriminate between uncontrollable and controllable sources
to better assess PM control and visibility improvement strategies.
The need exists for PM emission inventories that report both the natural and anthropogenic
components of dust sources. The WRAP draft dust definition is a first step in creating such
inventories. To support the latest modeling tools used in PM and visibility analyses, a feasible
application of the dust definition would also need to produce spatially and temporally resolved
inventories of natural and anthropogenic contributions. To be feasible for these types of
applications, implementation of the draft definition would have to be capable of producing these
spatially and temporally resolved inventories of natural and anthropogenic emissions.
Section 169 of the Clean Air Act declares as a national goal “the prevention of any future, and the
remedying of any existing impairment of visibility in mandatory Class I federal areas which
impairment results from man-made air pollution.” In 1999, the U.S. Environmental Protection
Agency (EPA) promulgated the Regional Haze Rule (RHR) to meet this national goal. The
Western Regional Air Partnership (WRAP) is a collaborative effort of tribal governments, state
governments, and various federal agencies to implement the recommendations of the Grand Canyon
Visibility Transport Commission (GCVTC) and to develop the technical (e.g. information and data
gathering, data analysis, emission inventory development, and modeling) and policy tools needed
by western states and tribes to comply with the RHR. WRAP also seeks to provide technical
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assistance to States in the development of emission control strategies to improve visibility. In the
WRAP region, dust (as opposed to point sources of primary particulates, such as elemental carbon,
and secondary particulates formed in the atmosphere) is a significant component in visibility
degradation. As implied by the national goal definition, only visibility impairments from man-made
pollution must be prevented and/or remedied. Mobile sources and stationary point sources are
clearly man-made sources of pollution, but dust sources, particularly fugitive dust sources, can
result from both man-made and natural conditions.
The absence of a solid line separating natural from anthropogenic sources is one of the issues that
increases the difficulty in applying the definition for operational purposes, such as inventories,
modeling and control strategy development and assessment. To assist in the identification of
anthropogenic and natural dust the DEJF has created a draft definition with broad criteria for
categorizing dust emissions as natural or anthropogenic. The definition serves to:

Clarify how the WRAP defines dust, its sources, and causes;

Provide an operational definition for use in receptor- and emissions-based source
apportionment techniques; and

Identify and prioritize sources of dust which are most appropriate to control for purposes of
improving visibility in Class I areas.
A potential use of a definition would be to delineate anthropogenic and natural dust emission in the
WRAP emissions inventory. Each emission type could then be “tagged” separately in the WRAP’s
air quality simulation model to estimate the contribution of natural and anthropogenic sources of
dust to visibility impairment in Class I areas. The definition may also be useful for describing
predominant source types (i.e., natural versus anthropogenic) when analyzing specific dust events
and/or discussing them with a variety of WRAP stakeholders. Other common western regional air
quality issues raised by the WRAP membership may also be addressed through the results of this
project. As many areas near attainment or work to maintain their attainment status, better
information on sources subject to control (anthropogenic sources) and those that are not (natural
sources) would allow more targeted and cost-effective “end game” strategies, compared to more
traditional across-the-board control strategies. Lastly, as the RFP notes, the “dust definitions are not
intended for use in refining EPA’s estimates of natural visibility conditions, although they may be
useful for that purpose. These definitions may also be used with regard to dust emanating from
outside of the U.S. – that is, dust from other countries can be either natural and/or anthropogenic.”
In ENVIRON’s approach to this project, these other purposes will be kept in mind and notes made
when certain data/methods may be available (and at what cost) that would allow the feasible use of
the dust definition for these purposes.
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In the RFP, WRAP identified several potential uses of a feasible dust definition. Table 3-1 presents
a list of these uses, their identified purposes, and a brief comment on how the use and purposes may
affect the feasibility analysis. This may not be an exhaustive list, and ENVIRON will work with
WRAP and its forums to identify other uses and the scope of what would define a feasible dust
definition in the context of those uses.
Any discussion of feasibility of implementing the draft dust definition must include the purpose for
which it is to be used. The feasibility of using the draft dust definition to identify natural and
anthropogenic contributions will be highly dependent on the ultimate purpose of the project to
which it is being applied.
Draft Definition
The WRAP DEJF has proposed a draft dust definition as follows: “Dust is particulate matter which
is or can be suspended into the atmosphere as a result of mechanical, explosive, or wind-blown
suspension of geologic, organic, synthetic, or dissolved solids. Dust does not include non-geologic
particulate matter emitted directly by internal and external combustion processes.” Fugitive dust
was defined as “dust which could not reasonably pass through a stack, chimney, vent, or other
functionally equivalent opening.”
Anthropogenic and Natural Dust
From the draft definition: “Examples of anthropogenic and natural dust are provided below (Table
3-2). Any mitigation of dust for regional haze control would likely be focused on those
anthropogenic sources which are most likely to contribute to visibility impairment in Class I areas
and which are technically feasible and cost-effective to control. Sources that are already controlled
or partially controlled may be technically infeasible or not cost-effective to control further.
Anthropogenic emissions do not include any emissions which would occur if the surface were not
disturbed or altered beyond a natural range. Such emissions should be subtracted, if practicable,
from the total dust emissions to determine the precise anthropogenic emission quantity.”
Table 3-3 lists the dust sources in the definition and classifying them as anthropogenic, natural or
potentially either. A key determinant of the feasibility of the dust definition is the ability to clearly
classify a source in a particular area as natural or anthropogenic or an explicit combination.
ENVIRON has also added a column of potential controls or mitigations for each source, since
certain applications of the dust definition are for purposes of developing control strategies or
assessing progress. This list is preliminary. ENVIRON intends to work with WRAP staff and
others that WRAP recommends in its preparation of a final list. The final list will be an interim
deliverable of the project.
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The focus of this report is whether anthropogenic and natural emission contribution for those
categories where both exist can be distinguished through the technical implementation of the draft
dust definition.
Technical Approach to the Implementation of the Dust Definition
WRAP’s Draft Definition of Dust is summarized in Figure 3-1,
“Examples of Anthropogenic and Natural Emissions under a
Draft Definition of Dust”.
An alternative to the five categories of emissions presented in
Figure 3-1 is a three category approach presented in Figure 3-2.
As very different dust sources may spatially co-occur on the
same site, it may be more useful to express dust sources on the
basis of activity rather than a description of spatial location. In
this way, dust sources fall into three categories:

Figure 3-1. See end of chapter.
Category 1: Purely anthropogenic sources
o Examples: Particle emission from cooling towers, wind erosion of agricultural soils,
wind erosion and particle emission from unpaved and paved roads
Category 2: Purely natural sources
o Examples: Ash emission by volcanoes, mineral
particle emission from wave action/sea spray,
wind erosion of unstable soil following
landslides

Examples of Anthropogenic and Natural Emissions Under a Draft Definition of
Dust
Anthropogenic
emissions
Category 1:
Purely
anthropogenic
sources
Natural
emissions
Category 2:
Purely natural
sources
Category 3:
Natural sources
which may be
anthropogenically
influenced
Emissions due to
anthropogenic
influence
Category 3: Natural sources, which may be
anthropogenically, influenced. A portion of the dust
emissions may be due to anthropogenic influences.
o Examples: Wind erosion and mechanical
suspension of soil due to animal movement,
wind erosion of bare areas on natural lands,
wind erosion of sediment from dried, ephemeral
water bodies
Total Dust
Emissions

Emissions under
healthy, natural
conditions
 Construction, mining, etc.
 Particle emission from
cooling towers
 Agricultural operations
 Wind erosion of agricultural
soils
 Emissions from unpaved
and paved roads
 Ash emission by volcanoes
 Mineral particle emission
from wave action/sea spray
 Wind erosion of unstable
soil following landslides
 Wind erosion and
mechanical suspension of
soil due to animal
movement (native and nonnative)
 Wind erosion of bare areas
on natural lands
(undisturbed vs. previously
disturbed)
 Wind erosion of sediment
from dried, ephemeral water
bodies (natural or
anthropogenic)
Figure 3-2. See end of chapter.
Table 3-4 allocates the fugitive dust sources in Table 3-3 into the three categories. Category 1
sources have been studied intensely through the SIP process, are relatively well defined, and several
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tested emission methodologies and models are available to estimate emissions from these sources.
Category 2 sources are less well studied and generally have had little impact on SIP and related
studies. They are unlikely to contribute significantly to NAAQS or haze violations except on a
local and/or event basis. Category 3 sources provide the greatest technical challenge, both in
general emission estimation and in identifying natural and anthropogenic emissions. Table 3-3
allocates the fugitive dust sources in Table 3-2 into these categories. Category 3 dust sources are
the focus of the feasibility analysis.
Category 3 sources are: 1) Animal movement, 2) Windblown dust from grass, range, and forest
lands, 3) Windblown dust from undeveloped lands (previously disturbed), 4) Areas burned by fires,
and 5) Exposed beds of lakes and rivers. For any these sources, the emissions can be natural or
partly natural and partly anthropogenic.
Anthropogenic and Natural Dust Estimation and Partitioning of Category 3 Emissions
One of the overall goals of WRAP’s draft dust definition is to partition Category 3 dust emissions
into natural and anthropogenic portions. According to the above conceptual framework, a binary
allocation of dust emissions between anthropogenic and natural categories is based on the level of
anthropogenic disturbance for a site. For example, if a site is found to be “disturbed or altered by
humans beyond a natural range”, Category 3 dust emissions would be classified as anthropogenic.
Under the current conceptual framework, using disturbance to partition Category 3 dust sources
may present several fundamental challenges. An approach which incorporates modeling or
comparison with reference areas may allow more flexibility and precision.

Disturbance as a Partitioning Tool: The term “disturbance” is potentially too simplistic for
an accurate and complete understanding of Category 3 dust emissions necessary to partition
emissions between natural and anthropogenic portions. The current approach also leads to a
binary partitioning of dust emissions which would likely overestimate anthropogenic
emissions.
o Natural Disturbance: Disturbance is a natural, vital part of healthy, functioning
natural lands (Pellant et al., 2000). While methods exist which may be useful in
providing information regarding natural levels of disturbance on natural lands
(Pellant et al., 2000; Mendoza et al., 2002; O’Brien et al., 2003), disturbances cannot
be clearly and cleanly classified as “natural” or “anthropogenic” (Grossman et al.,
1998). Some anthropogenic disturbances are similar enough to natural disturbances
that the resulting effects cannot be clearly distinguished via inspection of the land,
while others may create novel modified communities that are unprecedented in the
natural landscape (Grossman et al., 1998).
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o Indirect Disturbance: For many Category 3 dust sources, anthropogenic influences
may not be directly observable, yet greatly affect dust emissions. Indirect influences
would not be readily apparent from approaches which directly define natural ranges
of disturbance or assess ecological health on rangelands and forestlands (Pellant et
al., 2000; Mendoza et al., 2002; O’Brien et al., 2003). For example:

Anthropogenically-induced climate change is not easily observable as
disturbance, yet it arguably could have a very large impact on natural dust
emissions (Zender et al., 2004). Demonstrating global change at local scales
is an extreme challenge, especially in the West, which has a highly variable
climate. Although there may be a measured regional warming trend, the
effect of anthropogenic influences on climate is a decadal to century-scale
concern. Estimating the variability in climate due to this change and
translating this to estimates of anthropogenic dust emissions will require
substantial effort.

Suppression of natural fire regimes, neglecting population control for large
herbivores (e.g., deer, antelope), and the diversion of surface water are not
readily-observable disturbances, yet they may have as much or more impact
on dust emissions than more traditional, more easily-observed anthropogenic
disturbances, such as suppressed vegetation cover on overgrazed natural
rangelands.
o Binary Partitioning: Even at natural sites severely affected by anthropogenic
influenced beyond a natural range, it is unlikely that 100% of dust emissions could
be credited to anthropogenic influences. This binary allocation would result in
overestimation of anthropogenic dust emissions.

Direct Comparison as a Partitioning Tool: The direct comparison approach encourages
partitioning on a source-by-source and site-by-site basis. This method uses direct
comparisons between site and reference conditions with the assistance of dust emission
modeling to investigate anthropogenic influence and provide quantitative estimates of
natural and anthropogenic emissions in cases in which anthropogenic influence is identified.
The direct comparison approach is far superior to the more simplistic binary approach,
which would tend to restrict the process to an examination of readily-observable
disturbance.
o Reference Areas: Comparison with reference areas is routine in natural resource
management and ecological risk assessment and would enable a better understanding
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of the natural dust emissions in ecologically-healthy areas free (or with a minimum)
of anthropogenic influence.

For many dust sources and sites, reference area identification and the
understanding of anthropogenic influences can be achieved via examining
ecosystem health rather than disturbance. Ecosystem health is defined as the
degree to which the integrity of the soil, vegetation, water, air, as well as the
ecological processes of the ecosystem, are balanced and sustained (Pellant et
al., 2000). This concept not only incorporates assessments of disturbance but
other key factors related to the ability of the land to repair itself, integrity of
ecosystem processes, and the normal variability of a site. Understanding
ecological health (rather than just disturbance) would enable a more holistic
approach to characterizing the anthropogenic influences and understanding
the relationships between anthropogenic influences and dust emissions. In
general, a difference in measurable environmental conditions (also known as
“metrics”) greater than 20% for two given areas may indicate differences
outside the range of natural variability (Suter et al., 2000).
o Reference Time Periods: Comparison of anthropogenically influenced sites with
historical record of dust emissions during pre-industrial period (Busacca et al., 1998;
Zender et al., 2004) may also be potentially powerful to understand the “natural
background” of dust emissions in an area.
o Modeling: Dust emission modeling is a necessary step in comparing reference
situations with site conditions and estimating dust emission portions.

Modeling would be conducted on a source-by-source basis. Category 3 dust
sources are not equally vulnerable to anthropogenic influence. For example,
the minimum level of anthropogenic influence necessary to negatively
influence vegetative coverage resulting in increases in windblown dust
emissions is not necessarily equal to the minimum level of influence
necessary to increase dust emissions from animal movement. Anthropogenic
influence could be assessed in many ways (e.g., presence of roads, livestock
grazing, proximity of urban land uses), and it is likely that a wide variety of
land attributes would be examined to assess anthropogenic influence.

Modeling would be conducted on a site-by-site basis. Even for the same dust
source type, it is likely that the relationship between anthropogenic influence
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and dust emission would vary by site. In some cases, site-specific models
may need to be developed.

At even the most anthropogenically-influenced sites there will be some
portion of Category 3 dust emissions that is natural. Modeling could account
for natural dust emissions and avoid the situation in which 100% of Category
3 dust emissions are attributed to anthropogenic influences.
A revised figure “Examples of Anthropogenic and Natural Emissions under a Draft Definition of
Dust” is presented in Figure 3-2 to illustrate a conceptual dust definition which would avoid
potential limitations associated with the use of the term “disturbance”. This definition would enable
the partitioning of Category 3 dust sources on the basis of more holistic investigations of ecological
health and natural conditions, as facilitated by cause-and-effect dust source modeling and
comparisons with reference conditions.
Figure 3-3 illustrates a hypothetical example of a Category 3
direct comparison procedure for estimating the dust emissions
on a site-by-site, source-by-source basis (Fig. 3-3):

Step 1: Dust source identification
o Example: In the area of interest (Fig. 3-3) three
Category 3 dust sources are present:


Wind erosion from ephemeral lakes

Wind erosion from bare soil

Mechanical suspension of soil due to
mule deer movement
Figure 3-3. See end of chapter.
Step 2 and Step 3: Estimation of the Category 3 dust source emissions (Step 3) for the site
using previously-developed generic dust source models and site-specific data (Step 2)
o Example: Estimating dust emissions from the on-site ephemeral lake using sitespecific data and generic models capable of predicting dust emissions from dry
lakebeds

Step 4: Investigation of the anthropogenic influences that may affect of the Category 3 dust
source and quantitative assessment of anthropogenic influence on dust emission and
estimation of anthropogenic portion, which may include:
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o Identification of anthropogenic influence

For the on-site ephemeral lake dust source, this might include an analysis of
the water management strategies associated with anthropogenic diversion of
water from the lake, location of anthropogenically-influenced bare soil areas
near/overlapping the lake, and/or quantification of vehicle traffic which may
occur on the lakebed due to proximity to nearby roads
o Estimation of anthropogenic dust emission portion

Comparison of source-specific dust emissions at the site with source-specific
dust emissions at reference areas
-

Example: Comparison of dust emission estimates of suitable
“reference” ephemeral lakes which do not incur vehicle traffic
Adjusting dust emission models by analyzing the effects of variables linked
with anthropogenic influence
-
Example: Analyzing the magnitude of dust emissions associated with
the time period during which the lakebed is dry due to anthropogenic
diversions of water
This could require a substantial effort involving many disciplines (geology, ecology, climatology,
paleontology, engineering, statistics, etc.) to determine the impact of this partitioning effort on
overall dust emissions.

For example, Category 3 dust emissions may be very small in relation to Category 1 or 2. It
may be possible to simply include Category 3 dust emissions with Category 2 if it is
reasonable to assume that Category 3 dust emissions are very small in relation to Category 2
emission, or that the anthropogenic portions of Category 3 dust emissions are small relative
to other dust emissions. Thus, it is recommended that WRAP assess the overall dust
emissions of Category 3 sources relative to Category 1 and Category 2 emissions.
o A simple comparison of the sum of Category 1, 2, and 3 dust emissions may be
feasible using the data resources and approaches outlined in the next section.
o Investigating case studies such as the Columbia River PM10 Project (CP3) may also
be useful in understanding approaches in partitioning dust emissions. This project is
in the 12th year of its research. Although the main goal of the project is to from its
inception and yet today is to “develop conservation practices that will enable
Dust Definition Feasibility Analysis
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ENVIRON
growers to control wind erosion and dust emissions” in Washington’s Columbia
Plateau region, several key research thrusts may be directly useful for partitioning
and modeling Category 3 dust emissions, including:

Quantifying pre-farming (natural) dust
emissions via a study of dust emissions
from 620 A.D. to the present (Figure 3-4).

Producing data to validate regional and
global dust emissions models to better
backcast dust emissions from the plateau
and forecast future emissions.
Figure 3-4. See end of
chapter.

Reconstructing dust accumulation from dynamic source areas in the Plateau
region under the controlling influences of climate, plant, cover and
topography to quantify dust emissions.

Using satellite imagery on a large-scale to differentiate bare, smooth fields
including those with inadequate residue from those with sufficient residue or
green cover for protection against wind erosion.
Table 3-1. Potential uses of a feasible dust definition (WRAP identified).
Identified Use
Clarification of how WRAP
defines dust, its sources, and
causes
Purpose
Clearer policy directives, better
outreach to agencies and the public
Operational definition for
use in receptor- and
emissions-based source
apportionment techniques
Visibility projections, control
strategy assessment
Identification and
prioritization of sources of
dust which are most
appropriate to control for
purposes of improving
visibility in Class I areas
Control strategy development and
assessment
Dust Definition Feasibility Analysis
-26-
Quantification Needs For
Feasible Implementation
of the Dust Definition
Relies on general identification of methods
and associated data to distinguish natural
and anthropogenic contributions from a
given source type.
Relies on specific, quantifiable parameters
that can be applied on spatially and
temporally-resolved data for specific
sources in specific areas. The need for
high resolution data in specific area may
require the acquisition of new data or the
development of new methods to meet
feasibility requirements. Feasibility of
application would be project specific,
particularly if there are resource
constraints.
Feasibility depends on being able to “tag”
natural and anthropogenic portions of each
specific source, for at least the major
emissions contributors (or alternatively, the
major visibility impairers). The definition
of “major” may be case- or area-specific.
ENVIRON
Table 3-1. Potential uses of a feasible dust definition (WRAP identified).
Quantification Needs For
Feasible Implementation
of the Dust Definition
As above.
Identified Use
Identifying anthropogenic
and natural dust emissions
in the WRAP inventory
Purpose
Clarify extent of sources subject to
controls. Support modeling
assessments of visibility trends with
and without controls.
Addressing other common
western regional air quality
issues raised by WRAP
members.
Common issues can include the need
for Natural Event documentation,
NEAPs and NEAP revisions, “end
game” control strategies to address
remaining PM10 “hot spots” within a
non-attainment area.
As above.
Refining of EPA’s estimate
of natural visibility
conditions
Establishing natural visibility
conditions as baselines/goals as
referenced in the Clean Air Act and
RHR.
As above.
Categorizing dust emissions
from outside of the U.S.
Assess the limits of U.S. control
strategies and, if requested, provide
assistance in the development of nonU.S. control strategies.
Feasibility may be limited by the
availability of relevant non-U.S. data.
Feasibility analysis may identify data gaps
and needs.
Mechanical
Table 3-2. Current conceptual method of partitioning natural and anthropogenic dust emissions.
Anthropogenic Dust
Mechanically- and explosively-suspended solids and
dissolved solids from activities including but not
limited to:
 Agriculture
 Construction, mining, and demolition
 Material handling, processing, and transport
 Vehicular movement on paved and unpaved
surfaces
 Animal movement on surfaces which have been
disturbed or altered by humans beyond a natural
range
 Animal movement on undisturbed or unaltered
surfaces by a number of animals which is greater
than native populations
 Cooling towers
Dust Definition Feasibility Analysis
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Natural Dust
 Movement of a number of indigenous
animals on surfaces which have not been
disturbed or altered by humans beyond a
natural range
 Natural landslides, rockslides, and
avalanches
 Solids and dissolved solids emitted by
volcanoes, geysers, waterfalls, rapids, and
other types of splashing
 Extraterrestrial material and impacts
ENVIRON
Windblown
Table 3-2. Current conceptual method of partitioning natural and anthropogenic dust emissions.
Anthropogenic Dust
Solids and dissolved solids entrained by wind passing
over surfaces which have been disturbed or altered by
humans beyond a natural range. Such surfaces may
include, but are not limited to:
 Undeveloped lands
 Construction and mining sites
 Material storage piles, landfills, and vacant lots
 Agricultural crop, range, and forest lands
 Roadways and parking lots
 Artificially-exposed beds of natural lakes and
rivers
 Exposed beds of artificial water bodies
 Areas burned by anthropogenic fires (as defined
by the WRAP Policy for Categorizing Fire
Emissions) which have yet to be revegetated or
stabilized
Natural Dust
Solids and dissolved solids entrained by wind
passing over surfaces which have not been
disturbed or altered by humans beyond a natural
range. Such surfaces may include, but are not
limited to:
 Naturally-dry river and lake beds
 Barren lands, sand dunes, and exposed rock
 Natural water bodies (e.g., sea spray)
 Non-agricultural grass, range, and forest
lands
 Areas burned by natural fires (as defined by
the WRAP Policy for Categorizing Fire
Emissions) which have yet to be
revegetated or stabilized
Wind-blown particulate matter from sources created
by natural events over 12 months ago, similar to
EPA’s natural events policy
Note: Anthropogenic emissions are only that portion of the total emissions which occur in excess of what would occur
naturally. Wherever practical, natural emissions should be estimated and subtracted from total emissions to determine a
more precise anthropogenic quantity.
Table 3-3. Dust sources in the draft definitions of dust and preliminary identification of the
natural and anthropogenic portion of each source.
Dust Source
Agriculture (mechanical and
windblown)
Construction, mining, and
demolition (mechanical and
windblown)
Material handling, processing,
and transport (mechanical and
windblown)
Paved and unpaved roadways
(traffic and windblown)
Cooling towers
Natural Portion
None
All
Potential Controls
or Mitigations
BACM/RACM
None
All
BACM/RACM
None
All
BACM/RACM
None
All
BACM/RACM
None
All
Unknown
Dust Definition Feasibility Analysis
Anthropogenic Portion
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ENVIRON
Table 3-3. Dust sources in the draft definitions of dust and preliminary identification of the
natural and anthropogenic portion of each source.
Dust Source
Animal movement
Natural Portion
Native animals on
natural lands that
have not been
disturbed by humans
beyond a natural
range.
Anthropogenic Portion
Native animals on natural
lands that have been
disturbed by humans beyond
a natural range.
Non-native animals
introduced by humans (e.g.,
cattle ranching) on
undisturbed natural lands.
Non-native animal movement
on disturbed range lands.



Windblown from grass, range,
and forest lands
Windblown from undeveloped
lands (previously disturbed)
Areas burned by fires
Exposed beds of lakes and
rivers
Natural water bodies
Natural landslides, rockslides,
and avalanches
PM emitted by volcanoes,
geysers, waterfalls, rapids, and
other types of splashing
Extraterrestrial material and
impacts
Windblown PM from sources
created by natural events over
12 months previously

Potential Controls
or Mitigations
TBD
Non-agricultural
grass, range, and
forest lands that have
not been disturbed by
humans beyond its
natural range.
If the undeveloped
land has returned to
its natural state, i.e.,
is no longer disturbed
beyond its natural
range.
Areas burned by
natural fires, as
defined by the
WRAP Policy for
Categorizing Fire
emissions, and which
have yet to be
revegetated or
stabilized.
Natural river and lake
beds that may
become naturally dry
(may be seasonal or
through a drought
cycle).
Agricultural grass, range, and
forest lands
 Non-agricultural grass, range,
and forest lands that have
been disturbed by humans
beyond its natural range.
If the land remain disturbed
beyond its natural range.
Re-establishment
of surfaces to
within its natural
range
Areas burned by anthropogenic
fires, as defined by the WRAP
Policy for Categorizing Fire
emissions, and which have yet to
be revegetated or stabilized.
Accelerated
revegetation or
stabilization
All (sea spray)
All
None
None
Unknown
Unknown
All
None
Unknown
All
None
Unknown
None
All
Removal or
stabilization of
created sources
Dust Definition Feasibility Analysis


-29-
Artificially exposed by the
action of humans (e.g. water
transfer, damming, in-fill
projects).
The exposed beds of
artificial (man-made) water
bodies.
Others, TBD.
Re-establishment
of surfaces to
within its natural
range
Mitigations
considered and
used in Owens
Valley.
Others, TBD.
ENVIRON
Table 3-4. Dust sources in the draft definitions of dust and category identification.
Dust Source
Agriculture (mechanical and windblown)
Construction, mining, and demolition (mechanical and windblown)
Material handling, processing, and transport (mechanical and windblown)
Paved and unpaved roadways (traffic and windblown)
Cooling towers
Animal movement
Windblown from grass, range, and forest lands
Windblown from undeveloped lands (previously disturbed)
Areas burned by fires
Exposed beds of lakes and rivers
Natural water bodies (sea spray)
Natural landslides, rockslides, and avalanches
PM emitted by volcanoes, geysers, waterfalls, rapids, and other types of splashing
Extraterrestrial material and impacts
Windblown PM from sources created by natural events over 12 months previously
Category
1
1
1
1
1
3
3
3
3
3
2
2
2
2
3
Figure 3-1. WRAP Draft Dust Definition.
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ENVIRON
Examples of Anthropogenic and Natural Emissions under a Draft Definition of
Dust
Anthropogenic
emissions
Category 1:
Purely
anthropogenic
sources
Natural
emissions
Category 2:
Purely natural
sources
Category 3:
Natural sources
which may be
anthropogenically
influenced
Total Dust
Emissions
Emissions due to
anthropogenic
influence
Emissions under
healthy, natural
conditions
 Construction, mining, etc.
 Particle emission from
cooling towers
 Agricultural operations
 Wind erosion of agricultural
soils
 Emissions from unpaved
and paved roads
 Ash emission by volcanoes
 Mineral particle emission
from wave action/sea spray
 Wind erosion of unstable
soil following landslides
 Wind erosion and
mechanical suspension of
soil due to animal
movement (native and nonnative)
 Wind erosion of bare areas
on natural lands
(undisturbed vs. previously
disturbed)
 Wind erosion of sediment
from dried, ephemeral water
bodies (natural or
anthropogenic)
Figure 3-2. Amended WRAP Dust Definition, focusing on three categories of dust sources.
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ENVIRON
Area of interest
Step 1: Dust source identification
Mule deer population range
Bare soil
Step 2: Dust source
characterization
Ephemeral lake
Unpaved road
Step 3: Estimation of site-specific
dust emission
Site data + Model
Generic dust emission model
for dust source
= Site-specific dust emission
Step 4: Dust partitioning
Anthropogenic influences + Site-specific dust emission + Model =
Anthropogenic and Natural Dust Emission Portions
Figure 3-3. Procedure for estimating dust emission for a Category 3 dust source.
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ENVIRON
Figure 3-4. Dustfall mass (heavy line) and dustfall particle mean diameter (light line) versus depth
in sediment core from the bottom of Fourth of July Lake in eastern Washington. The
dotted line approximates the long-term trend in dustfall mass. Arrows indicate
approximate year when dustfall occurred along the length of the sediment core.
Methods used to investigate pre-industrial dustfall may be useful in understanding
natural dust emissions for natural lands, including the variability with climate and
vegetation changes. In turn, this may facilitate partitioning of current dust emission
estimates into natural and anthropogenic portions. Reproduced from Busacca et al.
(1998).
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ENVIRON
4. DATA RESOURCE AND METHODOLOGY ASSESSMENT
Information Needs
Four primary types of information are required to provide site-specific estimates of dust emission
for Category 2 and 3 dust sources (Fig. 3-2, Fig. 3-3).
1. Dust source geographic distribution: This information type includes data needed to define the
spatial extent of dust sources which vary geographically in the Western United States. Most
spatial extent data are in map format. Once the spatial extents of dust sources are known, an
inventory of dust sources can be compiled for any particular site.

Examples include spatial extent (distribution) of:
o ephemeral lakes in the United States
o disturbed areas in the Mojave Desert
o burrowing animal species in the United States
o populations of large mammal species in the United States
2. Dust source characterization: This information type includes data and conceptual information
required to construct new dust emission models or modify existing dust emission models.
Models will be used to estimate dust emissions by a dust source using site-specific data.
Although many dust emission models will be generic, in some cases it may be necessary to
construct site-specific models. Both conceptual information and data are needed to construct
dust emission models.

Conceptual information is needed to construct the model framework, and includes
knowledge from a wide variety of fields in various forms (expertise, examples, case studies,
literature, etc.). Examples include:
o approaches with which to estimate the population densities of large animal species
using land cover information
o understanding of the scale of climate data needed to predict the effects of
precipitation on wind erosion from dry lake beds
o case study illustrating the effects of cattle grazing on vegetative cover on rangelands
o understanding of the most important meteorological factors affecting the formation
of aerosols from sea spray
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ENVIRON
o methods to predict the effects of habitat change and vegetative cover due to fire
suppression

Data are needed to provide constants or ranges of parameters for the model. Data and
conceptual information can be in a variety of forms. Examples include:
o ranges of soil moisture content of ephemeral lakes
o average wind speed and direction for the United States
o range of soil displacement rates for burrowing animals in various ecosystems
o range of ash production per volcano eruption
o ranges of population densities for large mammal populations
3. Spatially-explicit dust emission: This information type includes site-specific spatial data
needed to produce site-specific dust emission estimates using the appropriate dust source model.
This information is in a wide variety of forms, but serves as site-specific input for dust emission
modeling.

Examples of spatially-explicit data include:
o percentage of bare ground coverage in southwestern Kern County, California
o dominant vegetation types in Grand Canyon National Park
o average monthly precipitation for northwestern Montana
o physical soil structure (percent sand-silt-clay) at a site in central Idaho
o number of active volcanoes within 100 miles of Yosemite National Park
4.
Dust partitioning: This information type includes site-specific information required to
identify and quantify site-specific natural and anthropogenic portions of Category 3 dust
emissions. Information may include data with which to evaluate the anthropogenic influences
in the area via modeling, comparison with suitable natural reference areas, and/or investigating
natural background (pre-industrial) dust emissions.

Examples of data include:
o sediment coring data with which to estimate pre-industrial dust emissions in Rocky
Mountain National Park
Dust Definition Feasibility Analysis
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ENVIRON
o range of bare ground cover in healthy mountain big sagebrush compared to bare
ground cover in areas of mountain big sagebrush in Bridger-Teton National Forest
which may be anthropogenically influenced
o area estimate of unpaved roads in Larimer County, Colorado
o current and historic wildlife management strategy for population control of large
mammal species in Yellowstone National Park
o history of hydrological management of water bodies which dry due to anthropogenic
diversion of water during droughts
o current logging activity in Kaibab National Forest
o information on land use to identify a reference site with minimal anthropogenic
influence within 20 miles of Santa Fe, New Mexico
Availability and Suitability of Information
Appendix A provides an example list of potentially-applicable online data, models, and conceptual
approaches capable of providing resources required to implement the WRAP Dust Definition.
Whereas Appendix A is not an all-inclusive list of resources and it is highly likely that other
resources may yield additional useful or different information, it provides a sample of the
information resources available. Appendix A also shows a hierarchy of potential usefulness of a
particular resource for WRAP (see the scale of 1 to 10, with 10 indicating resources that are most
useful).
The majority of the resources in Appendix A provide spatially-linked data which could be used to
supply a wealth of site-specific information for defining dust source spatial extent and estimating
site-specific dust emission via modeling. Many resources are data-rich and provide data in formats
easily compatible with extremely powerful GIS applications. Resources providing information
useful for dust source characterization are less abundant. Most information is in the form of
conceptual models, case studies, and projects. These resources may be best utilized to create new
dust emission models or understanding methods in which existing data and models can be combined
to model Category 2 and 3 dust emissions. As the information is mainly conceptual, its use may
require a high level of interpretation and understanding from a variety of experts. Information
resources necessary for the partitioning of Category 3 dust emissions are also less abundant. As this
information type is less well defined, resources include a wide range of conceptual approaches and
examples and data. It is likely that many more secondary resources for this type of information
(e.g., lists of experts capable of providing input during model creation) could be derived from
example resources identified in Appendix A.
Dust Definition Feasibility Analysis
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ENVIRON
Resources are often provided by local, state, or federal agencies at no cost (Appendix A identifies
cost per resource). For resources providing spatial data, spatial extent varies from regional (e.g.,
Mojave Desert) to national levels. Most user interfaces are intuitive and very powerful, with many
resources (such as the National Atlas) allowing a cursory analysis of areas via a simplified internet
browser map interface similar to GIS software. Other sources, such as software and models, may
require substantial expertise or development to apply to the WRAP Dust Definition. Data output
formats include text, graphical displays (maps and figures), and tables. Especially for many of the
federal sources, GIS files can be downloaded for more precise or custom analyses via GIS.
There is no single resource of information capable of providing all the four necessary information
types for any dust source in any given area, which means that significant effort could be required to
compile and quantify natural dust emissions. The complexity will vary depending on the available
resources for a particular geographic region, and it is clear that most applications of the WRAP Dust
Definition will require information that originates in many different resources. In addition,
substantial expertise may be required to merge this information. For example, whereas air
modeling expertise will be required to adapt information to existing dust emission models or
develop new dust emission models, successful interpretation and application of many resources may
require the expertise of climatologists, ecologists, and/or geologists. For example, most resources
are capable of providing information regarding the spatial extent of dust sources, but a
multidisciplinary approach would be required to utilize resources to construct new dust models for
dust source characterization. Also, the information varies greatly in their applicability to the WRAP
Dust Definition due to spatial extent, ease of translation to dust emission modeling, availability,
spatial resolution, and/or user-friendliness of user interface. Substantial effort may be required to
rigorously evaluate applicability of the available information.
Expertise will also be required to identify reference locations appropriate for a given site and to
evaluate whether differences between a site and a reference location are anthropogenically
influenced. For example, the designation of an appropriate reference location will be based on a
variety of specific attributes of the ecoregion (geology, ecology, and meteorology). A conservative
and simplistic criterion can be assumed for preliminary screening of potential anthropogenic
influence (e.g., a 20% difference between a site and a reference location). However, more realistic
estimates of anthropogenic influence may require close scrutiny of individual metrics to account for
high natural variability (e.g., wildlife population fluctuations or vegetative cover following an
extreme seasonal change, such as a drought).
Dust Definition Feasibility Analysis
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ENVIRON
Example Dust Emission Estimation
Dust emissions from animal movement represent one of the most
significantly challenging dust sources to quantify. The following
example provides a qualitative illustration of the steps necessary
to estimate a Category 3 dust emission by wild mule deer
(Odocoileus hemonus) movement at a hypothetical site in
Figure 4-1. See end of chapter.
southern California (Latitude: 33º 45' North, Longitude: 116º
West; Fig. 4-1). This example integrates available information
resources of Appendix A with the conceptual approaches detailed in Figures 3-2 and 3-3.
As in Figure 3-3, there are four key steps to a hypothetical framework for estimating a Category 3
dust source such as mule deer movement:
1. Dust source identification. This step uses geographic
distribution of potential dust sources to identify dust sources
at a site. For this step, the Smithsonian North American
Mammals database was queried using the hypothetical site’s
latitude and longitude to provide a list of mammalian species
at the site that are capable of producing dust via movement.
As seen in Figure 4-2, mule deer are likely present at this
site. Thus, it can be assumed that one of the Category 3 dust
sources present at this site is mechanical suspension of dust
by mule deer movement.
Figure 4-2. See end of chapter.
2. Dust source characterization. This step is not site-specific,
and would be completed prior to site-specific investigations.
Characterization of dust emission from mule deer movement
would involve constructing a generic model capable of
predicting dust emission due to the movements of a mule
deer. Constants needed to parameterize the model might
include life history data on the spatial ecology of mule deer
Figure 4-3. See end of chapter.
(average daily movement distance and home range data), size
of hooves, and average individual animal mass. Life history
data could be obtained from a variety of sources. For example, the results of a query for mule
deer from Cumulative Index for the Mammalian Species yielded information about average
population size, density, movement, average body weight, and other physiological, ecological,
and behavioral characteristics of mule deer (Fig. 4-3). Other information useful in constructing
the model, such as the responses of mule deer populations to anthropogenic influences (such as
Dust Definition Feasibility Analysis
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ENVIRON
roads, land use, prohibition of deer hunting, etc.) could be provided by a study of these types of
information sources in collaboration with ecological experts.
3. Spatially-explicit dust emission estimation. This step would involve obtaining site-specific
data for input into the dust emission model used to estimate site-specific dust emissions
associated with mule deer movement. For example, a key piece of information would be the size
of the mule deer population at the site, as this would have a large influence on dust production
by this dust source. Mule deer population would vary by habitat, land use, and other spatial
factors among sites. At a coarse level, population size at a site could be estimated by combining
natural history information regarding habitat preference and
population density and site-specific habitat information and
site suitability. As mentioned above, the Cumulative Index
for the Mammalian Species provided information regarding
habitat preferences and ranges of population sizes and
densities for mule deer (Fig. 4-3). Habitat information for
the hypothetical site can be obtained by querying the
California Wildlife Habitat Relationship (CWHR) software
Figure 4-4. See end of chapter.
program using the site’s county (Fig. 4-4). Although this
software is specific to California, other state- or region-level
approaches may also be available. By querying the CWHR software for mule deer, habitat
preference for the species in the site’s habitat type (desert scrub, Fig. 4-5) can be used to provide
information regarding the mule deer population density at the site. Another key piece of
information would be the coverage of bare soil areas for the site. Bare soil areas would be
extremely susceptible for disturbance (dust emissions) due to mule deer movements. Site
specific information on bare soil coverage can be obtained by approaches using hyperspectral
satellite data, such as the Eolian Mapping Index database, which predicts bare soil areas
susceptible to erosion (Fig. 4-6). GIS data downloaded from the Soil Survey Geographic
database could be used to further estimate and quantify the site-specific susceptibility to dust
emissions from mule deer movement (Fig. 4-7).
Dust Definition Feasibility Analysis
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ENVIRON
Figure 4-5. See end of chapter.
Figure 4-6. See end of chapter.
Figure 4-7. See end of chapter.
4. Dust partitioning. Only category 3 dust sources would undergo this step, which partitions sitespecific dust emission estimates between natural and anthropogenic portions. As mule deer
populations can be anthropogenically-influenced, dust emissions associated with mule deer
movement would be classified as a Category 3 dust source. As with most Category 3 dust
sources, a cause-and-effect approach may be the best way to partition natural and anthropogenic
dust emissions from the mule deer movements. In many
cases, anthropogenic influences would serve to negatively
influence mule deer populations, and thus, dust emissions
from mule deer movement. For example, it might be
expected that mule deer populations near urban areas or
major roads would be negatively impacted and that
constrained use/movement of mule deer can lead to
negative impacts on vegetative cover as the animals
Figure 4-8. See end of chapter.
exploit more limited home ranges.
By examining land uses (such as urban land use) near the hypothetical site (Fig. 4-8), mule deer
population estimates could be negatively adjusted in the dust emission model. This could be
modeled according to a predefined quantitative relationship between mule deer population
density and distance to roads and/or proximity to urban land uses. For this example, this would
likely result in a refinement of the overall dust estimate rather than a partitioning between
natural and anthropogenic sources, as partitioning for negative effects on dust emissions due to
anthropogenic influence would be irrelevant.
Partitioning of mule deer movement dust emissions would most likely focus on soil- and
surface-specific cause-and-effect analysis. If increased coverage of bare soil was due to
anthropogenic causes, such as overgrazing, off-road vehicle activity, or diversion of water from
streambeds, it would be expected that a portion of the mule deer movement dust emissions
would be anthropogenic. As an example, this can be evaluated explicitly by comparing the
Dust Definition Feasibility Analysis
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ENVIRON
population and vegetative cover in the vicinity of the site to an appropriate reference location.
If greater than a specific criterion of difference is observed (e.g., 20%), then anthropogenic
influence might be considered relevant and necessitating emission partitioning. This example
can be taken one step further such that if a 50% difference is observed, and 20% is considered
related to natural variability in the metric, then the additional 30% difference might be
considered the anthropogenic influence. The 30% difference could be accounted for within the
dust emission model, allowing a quantification of the anthropogenic dust emission portion. It
must be noted by WRAP and users of this approach that the actual criteria (20% vs. some other
percentage) will vary for a variety of reasons; close scrutiny and rationale should be provided by
knowledgeable practitioners to establish these criteria. In some cases, guidelines using a
percentage-based approach to identify anthropogenic influences may not be relevant or
appropriate.
Further illustrating the steps that can be followed, the
coverage of unpaved roads for the area could be determined
via a site-specific query for the site (using longitude and
latitude) using the USGS National Map (Fig. 4-9). Using
this estimate of anthropogenically-influenced portion of the
bare soils at the site, the portion of the original dust emission
attributed to roads could be quantified within the dust
emission model. This would yield an estimate of the
anthropogenic portion of dust emissions from mule deer
movement.
Dust Definition Feasibility Analysis
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Figure 4-9. See end of chapter.
ENVIRON
Figure 4-1. Location of example study point in southern California (Resource: USGS National
Map Viewer).
Dust Definition Feasibility Analysis
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ENVIRON
Figure 4-2. Results of the query for a list of mammals that could be found at the hypothetical site
(Resource: Smithsonian National Museum North American Mammals Database).
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ENVIRON
Figure 4-3. Life history data potentially useful in constructing a dust emission mode for mule deer
(Resource: Cumulative Index for the Mammalian Species).
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Figure 4-4. Distribution of desert scrub in California (Resource: California Wildlife Habitats
Relationships software).
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Figure 4-5. Habitat preference data (habitat suitability values) for mule deer in desert scrub habitat
(Resource: California Wildlife Habitats Relationships software).
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Figure 4-6. Hyperspectral map of predicted bare ground cover; bare soil areas subject to erosion
are shown in yellow (Resource: Eolian Mapping Index). Example map only (location
shown in northern Arizona).
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Figure 4-7. GIS file depicting soil types present at hypothetical southern California site (Resource:
Soil Data Mart, Soil Survey Geographic database).
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Figure 4-8. Urban land uses near hypothetical southern California site (highlighted yellow),
obtained via land use GIS data (Resource: California GAP Analysis Project).
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Figure 4-9. Locations of roads at hypothetical southern California site (Resource: USGS National
Map).
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5. FEASIBILITY ASSESSMENT PROTOCOL
Introduction
As noted in the introduction, the specific project (e.g., purpose, goals, geographic location, and the
type and extent of its dust sources) may determine if it is feasible to partition dust emissions into
natural and anthropogenic contributions using the draft dust definition. For example, if only a
simple inventory partition was required in an area with undisturbed and disturbed rangeland, areawide estimates of animal populations and average range may be sufficient. For certain sourcereceptor or other modeling studies, the actual location and temporal activity of the animals may be
necessary. If only area-wide estimates are available, application of the dust definition would be
feasible for the first study, but not the second. Thus, the feasibility of applying the dust definition is
a function of sources within the study area, the goals of the specific study, and the available or
obtainable data. Chapter 4 presented the available databases and methods that could be used to
implement the dust definition for Category 3 sources. But to the feasibility of applying the dust
definition for specific projects of interest to WRAP and its stakeholders, one would have to assess
whether the available data resources correspond to the dust sources of interest and are suitable to the
project’s purpose. This chapter presents a “Feasibility Assessment Protocol,” that can be applied to
specific projects to determine if there is sufficient technical information to implement the dust
definition in a way that meets the project’s goals.
Feasibility Assessment Protocol
A feasibility assessment protocol includes the following steps:
1. Identify the purpose and goals of the analysis, specifically as it relates to the importance of
identifying and discriminating between natural and anthropogenic sources.
2. Rank order the dust sources in the project area, using the CoH Assessment, source-receptor
modeling, emission inventory, or other appropriate ranking scheme, based on the project’s
purpose and goals. Identify the major contributors of interest.
3. Identify which major contributors have both natural and anthropogenic components (e.g.
Category 3 sources), using Table 3-3.
4. Identify which major contributors have potential controls or mitigations available, if
desired.
5. For those major contributors with natural and anthropogenic components, determine if
existing methods/databases are available to characterize, estimate, and/or partition the
emissions.
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IF YES, it is feasible to use the dust definition for this specific project.
IF NO, continue.
6. If existing methods/databases are not available to partition the emissions sufficiently to
meet the goals of the project, can the scope of necessary methods/databases be established?
What would be the resources (cost and time) required to acquire sufficient
methods/databases.
IF YES, determine if resources are available and justified for the project’s purpose and
goals.
IF NO, the dust definition cannot be feasibly implemented for this project.
Step 1: Purpose And Goals Of The Project
The purpose and goals of the project set the technical requirements. Table 5-1 identifies the
technical requirements of the data sources/methods for specific project purposes and goals.
Identified Use
Clarification of how WRAP
defines dust, its sources, and
causes
Operational definition for
use in receptor- and
emissions-based source
apportionment techniques
Purpose
Clearer policy directives, better
outreach to agencies and the public
Technical Requirements
Data sources and methods that characterize
natural vs. anthropogenic emissions.
Visibility projections, control
strategy assessment
Identification and
prioritization of sources of
dust which are most
appropriate to control for
purposes of improving
visibility in Class I areas
Control strategy development and
assessment
Identifying anthropogenic
and natural dust emissions
in the WRAP inventory
Clarify extent of sources subject to
controls. Support modeling
assessments of visibility trends with
and without controls.
Addressing other common
western regional air quality
issues raised by WRAP
members.
Common issues can include the need
for Natural Event documentation,
NEAPs and NEAP revisions, “end
game” control strategies to address
remaining PM10 “hot spots” within a
non-attainment area.
Spatially and temporally-resolved data for
specific sources in specific areas. The
need for high resolution data in specific
area may require the acquisition of new
data or the development of new methods to
meet feasibility requirements. Feasibility
of application would be project specific,
particularly if there are resource
constraints.
For current inventories, partitioning of
Category 3 source emissions. For some
areas, inventories of certain Category 3
sources, such as emissions from animal
movement (cattle/sheep or wildlife) may
not currently be inventoried and could be
estimated using the available data
sources/methods.
For current inventories, partitioning of
Category 3 source emissions to determine
extent of sources subject to controls. To
support modeling, the data
sources/methods would have to be spatially
and probably temporally-resolved
consistent with the model requirements.
Improved local inventories where Category
3 sources exist, partitioning of current
inventories to better target/assess controls
and support NEAPs.
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Identified Use
Refining of EPA’s estimate
of natural visibility
conditions
Purpose
Establishing natural visibility
conditions as baselines/goals as
referenced in the Clean Air Act and
RHR.
Categorizing dust emissions
from outside of the U.S.
Assess the limits of U.S. control
strategies and, if requested, provide
assistance in the development of nonU.S. control strategies.
Technical Requirements
Data resources and methods to create
future “natural” conditions. Some data
resources and methods may allow the
impact of predicted climatic changes
(independent of their origins) to be
incorporated.
Relevant non-U.S. data. Feasibility
analysis may identify data gaps and needs.
Step 2: Rank Ordering of Emission Sources
In this step, rank order the PM sources in the project area, using the CoH Assessment, sourcereceptor modeling, emission inventory, or other appropriate ranking scheme, based on the project’s
purpose and goals. Identify the major contributors of interest.
WRAP has commissioned the compilation of detailed information on PM composition, component
contributions to visibility impairment, ambient PM trends, and other information which will be used
to identify the causes of haze (CoH) in each Class I area (see CoH Assessment project web site at
http://coha.dri.edu/index.html). WRAP is using this and other information to develop a preliminary
report on the Attribution of Haze (AoH) in each Class I area (see http://www.wrapair.org/forums/
aoh/ars1/index.html). Results from the CoH Assessment and AoH projects will be useful for
identifying potential high priority source categories for analysis.
Alternatively, if the CoH/AoH analysis is unavailable or the project manager prefers, the PM
sources can be ranked on an inventory basis. For non-windblown PM sources, previous inventory
characterizations such as that developed in the WRAP –sponsored “In and Near Class I Areas
Emission Inventory Development – Non-Windblown” study. Pollack et al. 2004 can be used. This
effort involved estimating area and mobile source emissions based on mapping of appropriate
surrogate data within the identified 50 km zones of Class I areas and spatially allocating area and
mobile source emissions contained in the 1996 county-level WRAP inventories to the analysis zone
around each Class I area. State officials and Federal Land Managers with local knowledge of Class
I areas in the WRAP region were surveyed to obtain basic information on the presence and role of
local emission sources and their impact on visibility in all Class I areas. This project resulted in the
development of an extensive set of spreadsheets and maps that summarize the inventories for each
area (or area group) by emissions source category. These maps and spreadsheets along with other
work products from this project are available on the WRAP project web page
(http://www.wrapair.org/forums/class1/near/htmlfiles/main.html). Source categories for which
emission summaries were developed include non-windblown dust area sources, fire and on- and offroad mobile sources.
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Fugitive PM emissions from wind erosion were estimated under a contract by WRAP. Emission
estimates were made using a model developed based upon the most recent information available in
the literature and implemented in a variety of models (Mansell, et al., 2005). The development and
application of the estimation methodology relies on detailed knowledge concerning surface
characteristics of vacant lands susceptible to wind erosion. Given the large regional scale domain to
which the model was applied, certain assumptions were made due to the lack of detailed
information available to characterize the vacant land surfaces. In particular, assumptions regarding
the various landuse types, vegetative cover and disturbance levels of the soils were required. For
specific project areas, local windblown emission estimates can be used.
A summary inventory for the project should be prepared and can be rank-ordered by size. The
project manager can then identify those sources anticipated to impact the NAAQS or visibility to
the greatest extent, based on inventory contribution.
If the high priority (CoH/AoH) or most prevalent sources fall in Category 1 only, then standard
procedures for dealing with anthropogenic source and their control will most likely be sufficient. If
some high priority sources are in Category 2, they can clearly be identified as natural sources and
their inventories, if available, be marked as such. If some of the high priority sources are Category
3, then they should be identified (as in Step 3) for further evaluation.
Step 3: Identify Which High Priority Sources are Category 3 Sources
Using Table 3-3, the project manager should identify which high priority or major contributors have
both natural and anthropogenic components (e.g. Category 3 sources). For example, if the
inventory analysis in Step 2 indicates that windblown emissions from rangelands are major
contributors, Table 3-3 indicates that it is a Category 3 source and that there may be contributions
from both natural (e.g. undisturbed) and anthropogenic (e.g. disturbed) sources.
Step 4: Identify Which Categories Have Potential Controls or Mitigations, if desired
The purpose of this step is to consider the broader picture of whether controls or mitigations are
being considered for the major Category 3 sources. The Category 3 sources are: 1) Animal
movement, 2) Windblown dust from grass, range, and forest lands, 3) Windblown dust from
undeveloped lands (previously disturbed), 4) Areas burned by fires, and 5) Exposed beds of lakes
and rivers. For any of these sources, the emissions can be natural, anthropogenic, or both,
depending on location. Controls or mitigations may be applied to either type of source. For
example, restoration projects for previously disturbed lands and mitigations for dry lakebeds created
by human actions.
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Step 5: Identify Available data Resources and Methods for Major Category 3 Sources
For those major contributors with natural and anthropogenic components (e.g. Category 3 sources),
determine if existing methods/databases are available to characterize, estimate, and/or partition the
emissions. In this case, the project manager will match the purpose and goals from Step 1 and the
data resources and methods relevant to the specific Category 3 source to the listing in Appendix A
(as described in Section 4). If there is a match, then it is feasible to implement the dust definition
and the natural and anthropogenic emissions can be identified. EXAMPLE. Appendix A also
provides information about cost and needed expertise to implement the definition for each source.
If a match cannot be made, then it is not currently feasible to implement the dust definition for this
project. For example, there may be data resources that would allow characterization of the
emissions, but not to estimate or partition them. Alternatively, there may be information to partition
a current summary inventory, but not the data resources to produce spatially-resolved anthropogenic
and natural inventories for modeling. If this is the case, go to Step 6.
Step 6 (if necessary): Further Steps If Implementation Is Not Initially Determined To Be
Feasible
If existing methods/databases are not available to partition the emissions sufficiently to meet the
goals of the project, can the scope of necessary methods/databases be established? What would be
the resources (cost and time) required to acquire sufficient methods/databases.
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6. CONCLUSIONS AND RECOMMENDATIONS
Related Efforts
There is active research in the field of dust emissions and impacts at all spatial scales, from the very
smallest (e.g., mechanisms of production and entrainment) to the very largest (e.g. global dust
budgets and the impact of climate change.) Some of these researchers are also considering the
natural and anthropogenic sources of fugitive dust at these different spatial scales. New research
programs have been proposed, including one in the southwestern desert areas of the United States
and Mexico. These research programs are designed to improve the information necessary for dust
model development and implementation. The results of these studies should be incorporated in a
database of identified data resources, such as the one in Appendix A. Separate from the issue of
natural and anthropogenic dust sources, this research may provide better inputs and enhanced tools
to quantify dust emissions in the WRAP region.
Feasibility of Implementing the Draft Dust Definition
Dust definition based on dust sources
The major goal of the WRAP Dust Definition is to facilitate the partitioning of natural and
anthropogenic dust emissions. In contrast to the current definition, which includes a classification
based on both spatial location and dust sources, it may be more useful to express dust sources on the
basis of activity rather than a description of spatial location. In this way, dust sources fall into three
categories:

Category 1: Purely anthropogenic sources

Category 2: Purely natural sources

Category 3: Natural sources which may be anthropogenically influenced.
According to this conceptual definition, a possible estimation procedure for a site would include the
following steps on a site-by-site, source-by-source basis:
1. Dust source identification: Identification of dust sources present.
2. Dust source characterization: Construction or adaptation of dust emission models to
produce generic, source-specific dust source models.
3. Estimation of site-specific dust emission: Use of models and site-specific information to
estimate site- and source-specific dust emissions.
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4. Dust partitioning: Cause-and-effect investigation of anthropogenic influences to partition
precise estimates of anthropogenic and natural portions of Category 3 dust emissions.
Partitioning of Category 3 dust sources
Category 3 dust sources are the most challenging element of the dust definition conceptual
framework, as these sources have both natural and anthropogenic dust emissions which must be
separated. The current WRAP Dust Definition appears to conduct a binary partitioning of dust
emissions based on disturbance in relation to a “natural range”. This concept is potentially too
restrictive to be useful for partitioning Category 3 emissions, as many anthropogenic influences that
are capable of greatly influencing Category 3 dust emissions are neither disturbances nor factors
that can be identified by tools which are useful for deducing or quantifying disturbance beyond a
natural range. Instead, the Category 3 emissions partitioning process should focus on a cause-andeffect dust emission modeling approach. Removing the focus on “disturbance” allows a more
holistic, flexible approach which would allow WRAP to use a variety of metrics (i.e., ecological
health) for characterizing the often indirect nature of anthropogenic influences. This approach
would also enable a more precise estimate of the anthropogenic and natural dust emissions, rather
than an overly simplistic, binary partitioning between the categories. However, this partitioning
process would likely require substantial effort that may outweigh the benefit to dust emission
stakeholders. It is recommended that WRAP more closely examine previous or ongoing studies that
have used methods or approaches to understanding natural background sources of dust (e.g.,
Columbia Plateau PM10 Project) and/or conduct preliminary investigations to determine the
potential magnitude of Category 3 dust emissions compared to Category 1 and 2 emissions.
Usefulness of report results to determine or improve emission inventories for animal movement and
windblown dust.
The results of the Windblown Dust Project indicated a strong dependence on the assumed values for
surface roughness lengths, as determined by the land use types, and the level of disturbance of the
soils. One of the major limitations of the modeling results is directly related to the assumed level of
soil disturbance. Assumptions were necessary due to the large geographic extent of the modeling
domain and the lack of data to adequately characterize surface conditions. It is anticipated that the
results of the current study would be invaluable in providing additional supporting information to
better resolve and characterize the surface parameters most important in the estimation of dust from
wind erosion. Data resources related to current conditions and to conditions representative of
ecosystem health (e.g. natural conditions) can be used in establishing the difference between
anthropogenically disturbed natural areas and areas in their natural condition.
It is currently difficult, if not impossible, to distinguish between anthropogenic and natural sources
of windblown dust. It is anticipated that the results of this report would provide additional data and
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information to apply as a first attempt to address these concerns. This in turn would allow
improvements to the application of the windblown dust model in that various refinements to the
methodology could be focused on those areas most susceptible to, or known to be caused by, human
related activity (i.e., anthropogenic sources). These refinements will also provide WRAP with
information to allow more focused control strategy development efforts for these areas. In
particular, the data bases presented in this report could be used to establish goals for restoration
projects and allow progress toward restoration to be tracked as part of a further progress report.
Data resources with information on the range and population of native and non-native (e.g. grazing)
animals can be used to estimate emissions from animal movement and natural soil disturbance (e.g.
burrowing animals). This may only be necessary in those areas where significant animal
populations exist or are thought to be a major cause of haze.
Data Resource and Methodology Assessment
Information needed to estimate and partition emissions
Four primary information types would be required to estimate and partition dust emissions from
natural sources resources:

Dust source spatial extent: Data needed to define the spatial extent of dust sources which
vary spatially.

Dust source characterization: Data and conceptual information required to construct new
dust emission models or modify existing dust emission models.

Spatially-explicit dust emission: Site-specific spatial data needed to produce site-specific
dust emission estimates using the appropriate dust source model.

Dust partitioning: Information required to identify and quantify site-specific natural and
anthropogenic portions of Category 3 dust emissions.
Availability and applicability of information
There is no one resource of information capable of providing all the four necessary information
types for any dust source in any area. Most applications of the WRAP Dust Definition will require
information from many different resources and require varying levels of effort to satisfy each of the
four main information needs. There is a wealth of site-specific information useful for defining dust
source spatial extent and obtaining site-specific data with which to estimate dust emission via dust
emission models, however, resources providing information useful for dust source characterization
(building and adapting dust emission models) and partitioning of Category 3 dust emissions are less
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abundant. Although the understanding of natural and anthropogenic dust emission estimation and
partitioning is in its infancy (Zender et al., 2004), the high availability, low cost, completeness, high
quality, and ability of the data to be used in GIS or other formats would facilitate the effort required
to implement the WRAP Dust Definition.
Feasibility Assessment Protocol and Case Studies
The feasibility Assessment Protocol provides guidance for those seeking to estimate or partition
natural fugitive dust emissions for specific projects and project areas. To test whether it is feasible
to implement the draft dust definition, it is necessary to apply the feasibility assessment protocol to
case studies. The draft report identified possible case studies, such as the Columbia Plateau PM10
project. Another area with significant Category 3 sources where good existing data resources exist
would be Imperial County, including the Salton Sea area. In addition, the USGS is conducting a
Recoverability and Vulnerability of Desert Ecosystems (RVDE) project in the Mojave Desert (c.f.
Appendix A, first table entry). In this study, the vulnerability of desert surfaces to wind erosion and
their recoverability after disturbance has been modeled using data from portable wind-tunnel
measurements, soil characteristics (chemical and physical) and vegetative community
characteristics (cover, density, and arrangement). This model is being field-tested, using new sites
that represent a range of soil surface age, altitude, soil grain size, and parent material.
Subsequent to the release of the Draft Feasibility Assessment Report (May 2005), ENVIRON
conducted case studies to test the application of the Feasibility Assessment Protocol for two Class I
areas. In conjunction with the DEJF, the two areas chosen were Saguaro West in Arizona (a
relatively data-limited area) and the Salt Creek Wilderness Area in New Mexico (a relatively datarich area). The Salt Creek Wilderness case study was conducted in coordination with the New
Mexico SIP Pilot Project led by staff from the New Mexico Environmental Department. Separate
reports were prepared for each case study. The draft Saguaro West case study report was released
for comment in March 2006. The draft Salt Creek Wilderness case study report was released in
October 2006. The final case study reports for the Saguaro West and Salt Creek Wilderness Area
are included in Appendix B and C, respectively, of this final report.
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APPENDIX A
Data Resources Table