Potential methods and research needs for receptor methods to distinguish among fugitive dust sources




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НазваниеPotential methods and research needs for receptor methods to distinguish among fugitive dust sources
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THE FUGITIVE DUST CHARACTERIZATION STUDY

(FDCS):

POTENTIAL METHODS AND RESEARCH NEEDS FOR RECEPTOR METHODS TO DISTINGUISH AMONG FUGITIVE DUST SOURCES


Prepared for

California Regional PM10/PM2.5 Air Quality Study (CRPAQS)

Draft, 8/1/97


Prepared by

John G. Watson Desert Research Institute, Reno, NV

Lowell Ashbaugh, University of California, Davis, CA

Gary Casuccio, RJ Lee Group, Monroeville, PA

Judith C. Chow, Desert Research Institute, Reno, NV

Stephen Francis, California Air Resources Board, Sacramento, CA

Patrick Gaffney, California Air Resources Board, Sacrament, CA

Jamie Fine, Consultant, San Anselmo, CA

Tom Gill, USDA-ARS, Lubbock, TX

John Gillies, Desert Research Institute, Reno, NV

Ron Higashi, University of California, Davis, CA

Philip K. Hopke, Clarkson University, Potsdam, NY

Ann Kennedy, ARS, Spokane, WA

Mary Lahren, University of Nevada, Reno, Reno, NV

Douglas Lowenthal, Desert Research Institute, Reno, NV

Karen Magliano, California Air Resources Board, Sacramento, CA

Philip Roth, ENVAIR, San Anselmo, CA

John Sagebiel, Desert Research Institute, Reno, NV

Steve Shaw, San Joaquin Valley Unified Air Pollution Control District, Fresno, CA

Dale Shimp, California Air Resources Board, Sacramento, CA

Tony VanCurran, California Air Resources Board, Sacramento, CA

Barbara Zielinska, Desert Research Institute, Reno, NV

Steven Ziman, Chevron Research, Richmond, CA

Ted Zobeck, USDA-ARS, Lubbock, TX



Table of Contents


1.1 Statement of Problem 4

1.2 Objectives 4

1.3 Coordination with Other CRPAQS Studies 5

2.Fugitive Dust Emissions Categories 7

2.1 Emissions Estimates in the San Joaquin Valley 7

2.2 Sampling Period 7

2.3 Sampling Domain 7

2.4 Priorities for Characterization 8

3.Potential Characteristics of Different Dusts and Activities 9

3.1 Distinguishing Features 9

3.2 Differences Between Source Types 9

3.3 Differences Within Source Types 10

3.4 Markers for Distinguishing Features 10

3.5 FCDS Method Priorities 12

3.6 Priority Recommendations 13

3.7 Site Selection 15

3.8 Site Documentation 15

3.9 Number of Samples 16

3.10 Sample Collection 17

3.11 Sample Preservation, Preparation, and Storage: 17

3.12 Sample Requirements. 18

3.13 Data base requirements 18

3.14 Source Mixtures 19

3.15 Testing Methods 19

3.16 Performance Measures 20

Introduction

Both annual average and 24-hour PM10 standards are exceeded at most measurement locations in the San Joaquin Valley, with the highest concentrations measured during fall and winter. Chow et al. (1993, 1996, 1997) show that suspended fugitive dust is a major PM10 and a significant PM2.5 component during the summer and fall in the SJV, though dust contributions are much lower during the winter.

Significant contributors to the PM10 geological fraction are believed to be: 1) paved and unpaved roads (including unpaved shoulders) and unpaved parking lots and staging areas; 2) agricultural operations such as land preparation, cultivation, harvesting, and wind erosion of fallow land; 3) animal husbandry in feedlots and dairies; and 4) road and building construction (Ahuja et al., 1989; Houck et al., 1989, 1990). Contributions from these fugitive dust sources to PM10 and PM2.5 measured at receptors need to be estimated to assign priorities emissions studies and to determine the degree to which dust emissions must be controlled.

Saturation studies near SJV fugitive dust sources (Chow et al., 1997a, 1997b, 1997c; Watson et al., 1997; Flocchini et al., 1994) show that the zone of influence around a specific emitter, such as an unpaved road, is typically <100 m. Beyond this distance, the PM10 contribution from the specific dust source blends in with dust contributions from many other sources. Nevertheless, PM10 dust concentrations on an urban scale tend to increase and decrease in unison from day to day, indicating that many individual emitters combine their contributions to create excessive PM10 levels.

Source profiles consist of the fractional mass abundances of measured properties and the uncertainties of those abundances for specified particle size fractions. Profiles from fugitive dust and other source types (Watson and Chow, 1994) include measurements of: 1) elements by x-ray fluorescence (XRF) or proton induced x-ray emission (PIXE) spectrometry, 2) water-soluble sulfate, nitrate, ammonium, chloride, phosphate, potassium, sodium, iron, magnesium, calcium, and bromine by ion chromatography (IC), automated colorimetry (AC), and atomic absorption spectrophotometry (AA); and 3) organic and elemental carbon by thermal optical reflectance (TOR), thermal optical transmission (TOT), or thermal manganese oxidation (TMO). The carbon methods are operational, meaning that the quantities achieved are defined and reproducible by the method, but are not comparable between methods. The other analyses are absolute, meaning that equivalent results can be achieved by applying different analytical methods.

Profiles with elemental, ion, and carbon abundances are sufficient to distinguish geological PM10 contributions from those of non-geological contributors such as motor vehicle exhaust, vegetative burning, coal-burning, residual oil combustion, several industrial emissions, and even among certain industrial dusts. Chow et al. (1992a, 1992b) identified cement dust, often used as a surrogate for construction, owing to its high calcium abundance. Freeman et al. (1993) separated gold ore from overburden by the unique metal content in the ore. Much of the geological material in the San Joaquin Valley results from alluvial deposits that originated in the Sierra Nevadas and Coastal mountains and have mixed and deposited over centuries to form a relatively homogeneous mixture of mineral compounds and elements. Figure 1.1 shows examples of profiles SJV paved roads, unpaved roads, agricultural fields, and construction sites (Houck et al., 1989) that have been used in previous source apportionment studies. While there are evident differences between these SJV profiles, and while these might be sufficient to distinguish between a contributions of equal magnitude, the currently measured species are insufficient to distinguish contributions from each other across a wide range of contributions. Elemental, ionic, and carbon characterization are necessary, but insufficient fugitive dust measurements when resolution of fugitive dust contributions is required.
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