Estimating Volume, Biomass, 

and Potential Emissions of 

Hand-Piled Fuels

Clinton S. Wright, Cameron S. Balog, and Jeffrey W. Kelly

United States 

Department of 

Agriculture

Forest Service

Pacific Northwest 

Research Station

General Technical 

Report

PNW-GTR-805

January 2010
Authors

Clinton S. Wright is a research forester and Jeffrey W. Kelly was a forestry technician, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research 

Station, Pacific Wildland Fire Sciences Laboratory, 400 North 34th Street, Suite 

201, Seattle, WA 98103; Cameron S. Balog is a research scientist, School of Forest 

Resources, University of Washington, 400 North 34th Street, Suite 201, Seattle, WA 

98103.

The Forest Service of the U.S. Department of Agriculture is dedicated to the principle of 

multiple use management of the Nation’s forest resources for sustained yields of wood, 

water, forage, wildlife, and recreation. Through forestry research, cooperation with the 

States and private forest owners, and management of the National Forests and National 

Grasslands, it strives—as directed by Congress—to provide increasingly greater service to a 

growing Nation.

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Abstract

Wright, Clinton S.; Balog, Cameron S.; Kelly, Jeffrey W. 2009. Estimating volume, 

biomass, and potential emissions of hand-piled fuels. Gen. Tech. Rep. PNW-GTR805. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 23 p.

Dimensions, volume, and biomass were measured for 121 hand-constructed piles 

composed primarily of coniferous (n = 63) and shrub/hardwood (n = 58) material at 

sites in Washington and California. Equations using pile dimensions, shape, and type 

allow users to accurately estimate the biomass of hand piles. Equations for estimating 

true pile volume from simple geometric shapes and measurements of pile dimensions 

were also developed for users who require estimates of pile volume for regulatory 

reporting. Biomass and volume estimation equations were developed to allow users to 

estimate either value from pile dimensions. Hand pile biomass estimates can be used 

to predict fuel consumption and smoke emissions by applying proportional consumption estimates and emission factors. Equations to estimate pile volume, pile biomass, 

fuel consumption, and pollutant emissions from pile shape, dimensions, and quantity 

are programmed into a Web-based calculator for use by the management and regulatory communities.

Keywords: Hand piles, fuel, fuel treatment, biomass, emissions, smoke management.

Contents

1 Introduction

4 Objectives

4 Methods

8 Results and Discussion

8 Pile Data

12 Errors Related to Characterizing Piled Fuels

13 Comparison With Machine Pile Methods

15 Procedure for Estimating Emissions

16 Conclusion

17 Acknowledgments

17 English Equivilants

17 Literature Cited

20 Appendix

Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

Introduction

Understory growth is present in excess of historical natural levels and may contribute 

to more extreme wildland fire behavior and elevated fire hazard in many dry forests. 

Anomalously high amounts of understory biomass may cause potentially more 

extreme fire behavior than was common historically, leading to fires that are potentially more intense, severe, dangerous, and difficult to control. Thinning of the forest 

understory, midstory, and overstory coupled with reduction or removal of this biomass 

is being implemented in forests throughout the Western United States as one approach 

for mitigating elevated fire potential and preventing catastrophic surface and crown 

fire events (Agee 1996, Agee et al. 2000, Graham et al. 1999).

Federal land management policies, such as the National Fire Plan and the Healthy 

Forest Restoration Act of 2003 (HFRA 2003) direct managers of forests and woodlands that are at risk of catastrophic wildland fire to modify fuels to reduce risk and 

restore ecosystem pattern and process. Mechanical treatments such as thinning, brush 

cutting, and mastication are being used to reshape dry forests and woodlands with the 

intention of reducing their susceptibility to catastrophic fires. Substantial increases in 

dead and down surface fuels related to management activity (i.e., activity fuels) are 

one consequence of mechanical treatments. Surface fuel treatment following thinning 

or brush cutting is necessary to effectively mitigate wildland fire risk.

Traditionally, broadcast prescribed burning was one of the main treatment methods for reducing or removing understory vegetation and activity fuels. However, with 

increases in prescribed fire complexity and risk associated with elevated fuel levels, 

proximity to the wildland/urban interface, and air quality regulations (i.e., Federal 

Clean Air Act and State Smoke Management Plans), the use of conventional broadcast 

burning as a fuel treatment is now more difficult in some circumstances. 

Heavy accumulations of activity fuels were historically piled by using heavy 

equipment following clearcut and partial-cut harvest operations. Machines, however, 

can cause soil compaction and may be less practical for piling the surface fuels that are 

created from thinning where the overstory is left in place. Piling by hand followed by 

burning is being used more frequently in many forest and woodland types to remove 

or reduce the residue created by mechanical manipulation of excessive understory 

(and sometimes overstory) growth (fig. 1). Past pile characterization research (Hardy 

1996; Johnson 1984; Little 1982; McNab 1980, 1981; McNab and Saucier 1980) dealt 

only with large, crane-constructed and tractor-built piles and windrows. Machineconstructed piles have different physical properties than hand-constructed piles owing 

in part to the inclusion of larger fuel particles (tree boles and large limbs) and mineral 

soil. In hand-piling operations, in contrast, smaller nonmerchantable material is commonly thinned and piled on site without the aid of machinery and contains needles, 

Piling by hand 

followed by burning 

is being used more 

frequently in many 

forest and woodland 

types to remove or 

reduce the residue 

created by mechanical 

manipulation of 

excessive understory 

(and sometimes 

overstory) growth.


GENERAL TECHNICAL REPORT PNW-gtr-805

twigs, and small-diameter branches and boles. In areas with a major shrub component, 

cutting and hand piling is also used for reducing heavy surface fuels. Compositional 

and structural differences between hand and machine piles result in different relationships between pile volume and pile biomass and in different combustion environments 

(table 1).

Hand piling and burning mitigates some of the concerns about environmental 

impacts, safety, and air quality and is a viable alternative for treating a variety 

of areas. Use of hand piling mitigates soil compaction concerns and widens the 

prescribed burning window, allowing managers to use fire under weather and fuel 

moisture conditions that are inappropriate or ineffective for broadcast burning. Fire 

managers have more flexibility when burning piles. For example, piles can be burned 

under weather conditions and with reduced staffing levels that are not conducive to 

safe and effective broadcast burning (fig. 2). Pile burning can be more easily monitored and controlled, minimizing escape potential. Likewise, fire and fuel managers 

can choose to not burn all piles in an area at once, thereby distributing total smoke 

production over multiple days or burning periods and reducing the air quality impacts 

of smoke. Furthermore, piled fuels burn more efficiently than broadcast fuels, thereby 

reducing the quantity of smoke emitted for comparable quantities of fuel consumed 

(Johansen 1981, Ward et al. 1989).

Figure 1—Typical hand-piled fuels after thinning in sample area near Naches, Washington.

Ernesto Alvarado

Hand piling and 

burning mitigates 

some of the concerns 

about environmental 

impacts, safety, and air 

quality and is a viable 

alternative for treating 

a variety of areas.
Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

Table 1—Some differences between hand- and machine-constructed piles

Characteristic Hand piles

Woody material Lack large logs; have a greater proportion of biomass in small 

size classes

Dimensions Are smaller 

Soil content Are cleaner with less soil contamination for more efficient 

combustion

The Healthy Forest Restoration Act (HFRA 2003) specifies that 50 percent of 

funds allocated for fuel reduction should be used for treatments within the wildland/

urban interface (typically referred to as the “WUI”). Use of mechanical treatment and 

hand piling is widespread in the WUI because of concerns about the risks and impacts 

associated with broadcast prescribed burning of accumulated fuels (e.g., potential for 

escape or private property damage, public health impacts of widespread and potentially extended-duration smoke events, etc.). Approximately 25,000 ha were treated 

with hand piling and burning in the Pacific Northwest (U.S. Forest Service, Region 6

—Washington and Oregon) in 2005.1 The need for land managers to mitigate risk 

1 Russell, J. 2007. Personal communication. Air Resources/Smoke Management Program Manager, 

U.S. Forest Service and Bureau of Land Management, Pacific Northwest Region, 333 SW First 

Avenue, Portland, OR 97204.

Figure 2—Hand pile burning during winter conditions on the Bear Valley National Wildlife Refuge, Oregon.

Eric Siemer
GENERAL TECHNICAL REPORT PNW-gtr-805

associated with wildland fire by reducing fuel loading, while also complying with federal and state air quality regulations, provides an impetus for research that improves 

the accuracy of the impact of fuel reduction activities. The ability to accurately 

quantify the mass of hand-piled fuels will allow fire and air resource managers to 

make more accurate estimates of potential emissions and smoke impacts. This project 

improves assessments of volume and biomass of hand piles, leading to better smoke 

production estimates, improved burn scheduling, and compliance with the maximum 

allowable emissions as determined by various state smoke management plans.

Objectives

Land managers and air quality regulators need a tool to accurately and efficiently 

estimate the biomass and emissions from burning of hand-piled fuels as pile burning becomes a more widespread and common practice for treating high fire hazard 

areas with surface fuels in excess of desired levels. Our objective was to quantify the 

relationships between pile composition, pile size, and pile biomass by measuring and 

weighing hand-constructed piles. We sampled piles composed of different types of 

debris (i.e., conifer, shrub, and hardwood) with a variety of shapes and sizes to develop 

equations for estimating the volume and biomass of hand piles. We provide methods 

for calculating emissions from the burning of hand-piled biomass, and also compare 

pile loading estimates using relationships developed from this study to estimates based 

on relationships reported by Hardy (1996) that are implemented in CONSUME 3.02

(Prichard et al., n.d.) to evaluate the different outcomes that are predicted by the two 

models.

Methods

The field portion of this study was concentrated in forest and woodland types in the 

Western United States. Forested stands with hand piles were selected in Washington 

(Naches) and California (Whiskeytown, Porterville, and San Luis Obispo) with the 

assistance of local and regional fire and fuels managers (fig. 3). Sampling sites were 

typical of hand-piling operations. Our intention in selecting study sites and pile types 

was that the results of this study would have utility throughout the West where surface 

fuels are being treated with the use of hand piling and burning.

We had proposed to characterize three types of piles with our sampling: conifer, 

hardwood, and shrub. Pure hardwood-dominated piles were difficult to find and were 

typically mixed with shrub material. Therefore, our data represent hand-constructed 

2 CONSUME 3.0 is a software decision-support tool used by fire, fuel, and air quality 

managers to predict fuel consumption and emissions during prescribed and wildland fires.

The ability to 

accurately quantify 

the mass of hand-piled 

fuels will allow fire and 

air resource managers 

to make more accurate 

estimates of potential 

emissions and smoke 

impacts.
Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

piles composed primarily of either coniferous 

material or various combinations of shrub 

and hardwood material owing to the general 

scarcity of pure hardwood piles.

We measured and weighed 121 hand 

piles (63 conifer, 58 shrub/hardwood) of 

varying size in a total of seven stands at 

four locations. Within stands, piles were 

chosen by using a random walk procedure to 

remove bias from the pile-selection process. 

The pile that was closest to a point 10 m at a 

random azimuth from a randomly-selected 

starting point was chosen, with each successive pile located 10 m at a random 

azimuth from the last measured pile. Once 

located, pile volume was measured using 

two methods: geometric volume and surface 

shape volume. For estimates of geometric 

pile volume, we measured the dimensions 

required to compute the volume of one of seven specific geometric shapes (fig. 4) 

and applied the appropriate volume formula (table 2). For estimates of surface shape 

volume, we mapped the contours of the pile surface using an angle gauge and level 

system. A series of level lines were projected from the center to the edge of the pile 

in 30° increments using a string line and a bubble level. We measured the vertical 

offset (to the nearest 3 cm) from the level line at 15-cm intervals in the horizontal 

from the pile center (fig. 5). This method allowed us to compute a three-dimensional 

coordinate for systematically located points on the surface of the pile from which 

volume was estimated using a triangular irregular network (TIN) lattice constructed 

in ArcGIS 9.1 (ESRI 2008).3 4 For the purposes of this study, we consider the TINderived volume (fig. 6) to be the best representation of the true volume of the pile.

Following dimension and surface measurements, piles were deconstructed and 

fuel particles were sorted into species and size class groups (<2.5, 2.5 to 7.6, and >7.6 

Figure 3—Approximate hand pile sample locations.

WA

Nache s

S an Lu is Ob is po

Wh is keytown

P orter ville

OR

CA

3 For piles located on sloping ground, the estimated height of the center of the pile was used 

to determine the effective ground level in pile volume calculations. 

4 Use of trade or firm names in this publication is for reader information and does not imply 

endorsement by the U.S. Department of Agriculture of any product or service.
GENERAL TECHNICAL REPORT PNW-gtr-805

Table 2—Volume formulas for geometric shapesa

Geometric shape Volume formula

Half-sphere V = (π × h × w2)/6

Paraboloid V = (π × h × w2)/8

Half-cylinder V = (π × w × l × h)/4

Half-frustum of cone V = {π × l[h1

2

 + h2

2

 + (h1 × h2)]}/6 or 

V = {π × l[w1

2

 + w2

2

 + (w1 × w2)]}/24

Half-frustum of cone V = π{l[w1

2

 + w2

2

 + (w1 × w2)] + w1

3

 + w2

3

}/24

 with rounded ends

Half-ellipsoid V = (π × w × l × h)/6

Irregular solid V = [(l1 + l2)(w1 + w2)(h1 + h2)]/8

a See figure 4 for illustration of dimensions.

Figure 4—Geometric pile shapes and required dimensions. Redrawn from Hardy (1996).

w

h

l

h

w

h

w

h

w

h

w

h1

l

w2

h2

w1

h

l

w

h1

l

w2

w1

h2

h2

h1

l1 l2

w1

w2

Half frustum 

of cone with 

rounded ends

Half frustum 

of cone

Half-cylinder

Half-sphere Paraboloids

Half-ellipsoid Irregular

solid

cm diameter). Species and size class groups of separated piles were weighed in the 

field with a precision hanging scale (nearest 0.01 kg). One moisture content subsample 

was collected for each species/size class category for each pile to convert field-measured weight to oven-dry weight. Each moisture content subsample included several 

appropriately-sized pieces for each species/size class category.

Volume, biomass, and composition data were synthesized and used to calculate 

physical properties, including packing ratio (the ratio of solid wood volume to total 

pile volume) and bulk density (the ratio of total pile biomass to total pile volume). 
Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

Estimates of the volume of solid wood were derived by dividing the total mass of fuel 

particles of a given species by the wood density (Chojnacky 1984, Countryman and 

Philpot 1970, Dohr 1958, USDA FS 1999, Gray 1982, Jacobsen et al. 2008, Schniewind 

and Gammon 1983, Zhou et al. 2005). For those species for which published wood 

density values were unavailable, the wood density of species with similar wood qualities was substituted (e.g., Arbutus menziesii for Arctostaphylos spp.).

Ordinary least-squares regression was used to develop equations: (1) to estimate 

true volume from dimension measurements and shape assignments (i.e., from geometric volume), and (2) to estimate biomass from true volume for different pile types (i.e., 

conifer and shrub/hardwood). T-tests were used to test for differences in pile physical 

properties (packing ratio and bulk density) and differences in regression slopes and 

intercepts between pile types and shapes (Zar 1984). We evaluated the bias of our 

Figure 6—Example triangular irregular network lattice for a typical pile at the Naches, Washington, field site. 

This pile was 0.73 m high and 1.86 m wide; the “true” volume of this pile was 1.08 m3.

90 °

30 °

60 °

12 0°

15 0° 18 0°

0°

30 0°

27 0°

24 0°

21 0°

33 0°

15 cm

Ve rtica l

offs e t

Figure 5—Overhead plan view (left) and cross-section view (right) of pile surface measurement methodology.

Vertical 

offset
GENERAL TECHNICAL REPORT PNW-gtr-805

equations as the average of the absolute value of the relative difference between the 

modeled and measured true volume for each pile and assigned a negative or positive 

direction to the bias based on the number of over- or under-predictions. We also evaluated precision as the standard deviation of the relative difference between the modeled 

and measured true volume for each pile.

The equations developed by this analysis have been encoded in a Web-based 

calculator that allows users to accurately estimate volume and biomass of handconstructed piles for use in determining potential emissions impacts from burning.

Results and Discussion

Pile Data

Summary data for sampled hand-constructed piles appear in table 3, and individual 

pile data are reported in the appendix (tables 7 and 8). In general, hand piles are of 

modest size (overall mean volume of 3.01 m3; overall mean biomass 156.63 kg); the 

largest pile we measured was 14.47 m3, and the heaviest pile weighed 672.14 kg. Packing ratio ranged from 0.01 to 0.40, and bulk density ranged from 7.59 to 152.45 kg/m3

. 

The packing ratios of the hand piles we measured encompass the range of typical 

values noted by Hardy (1996) for machine piles (0.10 to 0.25). The median packing 

ratio for conifer hand piles is centered on the range of typical values for machine piles 

(conifer median packing ratio = 0.18), but the median packing ratio for shrub hand 

piles is lower than is typical for either conifer-dominated hand piles or machine piles 

(shrub/hardwood median packing ratio = 0.05). Of the 121 hand piles measured, the 

packing ratio of 58 piles was less than 0.10, the packing ratio of 53 piles was between 

0.10 and 0.25, and the packing ratio of 10 piles was greater than 0.25.

Table 3—Summary hand pile dataa

 All piles (n = 121) Conifer (n = 63) Shrub (n = 58)

 Mean ± standard error

Geometric volume (m3) 3.23 ± 0.26 2.61 ± 0.19 3.90 ± 0.49

True volume (m3) 3.01 ± 0.19 2.45 ± 0.18 3.63 ± 0.33

Biomass (kg) 156.63 ± 10.42 177.34 ± 12.10 134.13 ± 16.95

Bulk density (kg/m3) 56.45 ± 2.86 76.79 ± 3.37 34.36 ± 2.43

Packing ratio (m3/m3) 0.12 ± 0.01 0.19 ± 0.01 0.05 ± 0.00

Mass <2.5 cm 40.3 ± 2.4 24.9 ± 1.5 57.0 ± 3.7

 (percentage of total)

Mass 2.5-7.6 cm 30.3 ± 1.8 28.1 ± 2.0 32.8 ± 3.0 

 (percentage of total)

Mass >7.6 cm 29.4 ± 2.4 47.0 ± 2.9 10.3 ± 2.0

 (percentage of total)

a Shrub and hardwood categories were combined for all analyses.

The equations 

developed by this 

analysis have been 

encoded in a Webbased calculator 

that allows users to 

accurately estimate 

volume and biomass of 

hand-constructed piles 

for use in determining 

potential emissions 

impacts from burning.
Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

Pile shape—

Most piles were classified as either paraboloids (n = 64) or half-ellipsoids (n = 44). 

Only a few half-cylinders (n = 4), half-frustums of a cone (n = 6), and irregular solids 

(n = 3) were observed among the 121 piles sampled in the field (fig. 7). This may be a 

result of how material is piled when done by hand in contrast to machine piling where 

windrows, which have a half-cylinder shape, are common. During hand piling, material 

is dragged from a relatively small radius (compared to machine piles) around the pile 

location toward a center point yielding piles that have round or oval plan-view shapes.

The distribution of points in fig. 7a suggested that the relationship between 

geometric volume and true volume may have been different for piles of different 

shape (paraboloids vs. half-ellipsoid+half-cylinders+half-frustums of a cone+irregular 

solids) and might be best modeled by using two different equations. T-tests, however, 

revealed that the slope (t = 1.915; p = 0.058) and intercept (t = 1.579; p = 0.117) terms of 

the resulting regressions were not significantly different, so we opted to pool the data 

and develop one equation for all pile shapes.

(a) -1

0

1

2

3

-1 0 1 2 3

ln geometric volume (m 3)

ln true volume (m

3 )

Ellipsoid

1/2 Frustum of cone

Irregular solid

Paraboloid

1/2 Cylinder

(b) -4

-2

0

2

4

-0.5 1 2.5

Expected ln true volume (m 3)

Standardized residuals

(d) -4

-2

0

2

-3 -1.5 0 1.5 3

Theoretical quantiles

Standardized residuals

(c)

0

10

20

30

-3 -2 -1 0 1 2 3

Standardized residuals

Frequency

Figure 7—Relationship between the natural logarithm (1n) of geometric volume and the natural log of true volume 

(a). Data points above and below the dashed 1:1 line indicate instances in which the geometric volume under- or 

over-predicts the true volume, respectively. Note that most piles were classified as either paraboloids or halfellipsoids. Residual diagnostic plots, including standardized residuals against expected natural logarithm of true 

volume (b), frequency distribution (c), and against theoretical quantiles of the normal distribution (d).

1/2 Ellipsoid

1n geometric volume (m3) expected 1n true volume (m3)

1n true volume (m3

)
10

GENERAL TECHNICAL REPORT PNW-gtr-805

Pile volume—

Geometric pile volume underestimated true pile volume for very small piles (<2.5 m3), 

and overestimated true pile volume for larger piles (fig. 7a); however, the relationship 

between pile volume determined using pile dimensions and geometric formulas (geometric volume) and true pile volume was not linear. Natural log transformation of both 

the geometric and true pile volumes linearized the relationship and made the distribution of the residuals normal and homoscedastic (fig. 7b-d). Retransforming predictions 

from logarithmic to arithmetic units can produce bias. Calculation and application 

of a correction factor has been suggested as a method to reduce the bias (Baskerville 

1971). We evaluated bias for predicted values with and without the correction factor 

specified by Sprugel (1983)5 and found the differences to be small, and the uncorrected 

predictions to be slightly less biased and more precise. The equation for predicting 

true volume from geometric volume (fig. 8a and table 4) is implemented without the 

correction factor in the Web calculator.

The equation for predicting true pile volume from geometric volume is appropriate for a range of pile sizes owing to the relatively wide span in our data; however, 

extrapolation beyond the range of the data should be done with caution, particularly 

for very large piles (>25 m3). Our regression does not pass through the origin, so to 

accommodate very small piles, we chose to encode a straight proportional reduction of 

(a)

0

5

10

15

20

25

0 5 10 15 20 25

Geometric volume (m 3)

True volume (m

3 )

Uncorrected for bias

Corrected for bias

(b)

0

1

2

3

4

0 1 2 3 4

Geometric volume (m 3)

True volume (m

3 )

Figure 8—The relationship between geometric pile volume and true pile volume is nonlinear. Equations, both 

corrected and uncorrected for logarithmic retransformation bias, are plotted for comparison. The dashed diagonal 

line indicates a 1:1 relationship for reference. Shown are plots of all data points and the modeled equations (a), 

and for clarity, a view of the data and modeled equations for piles less than 4 m3 (b). Note that the regression lines 

show a linear extrapolation through the origin for geometric volumes <1 m3.

5 Sprugel (1983) calculated the logarithmic transformation correction factor (CF) as:

CF = exp {[ ∑ ( ln yi - ln yi )

2 / ( N - 2 ) ] / 2 },

where ln yi is the natural logarithm of the dependent variable, and ln yi is the corresponding 

predicted value calculated from the equation.

Geometric volume (m3) Geometric volume (m3)
11

Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

the modeled true volume of piles < 1 m3, which is approximately equal to the smallest 

pile we measured (fig. 8b and table 4). We feel justified adjusting the extrapolation 

for very small piles as we know that true pile volume approaches zero as geometric 

volume approaches zero. This adjustment eliminates nonsensical extrapolation values 

(i.e., positive modeled true volume when pile volume is zero) related to the nonzero 

intercept term in the regression equation as pile sizes approach zero.

The larger the pile, the more the geometric method of calculating volume appears 

to overestimate true volume (fig. 8). This could have important implications for 

prescribed burning of piles in states such as Utah, where up to 850 m3 (30,000 ft3) of 

piled debris (i.e., the volume of numerous small piles that sum to 850 m3) constitutes 

a small prescribed burn that does not require special permitting or approval provided 

adequate smoke dispersion conditions exist. The ability to correct for this overestimation could allow land managers to accomplish more fuel treatment under current 

guidelines without the added burden of special permitting.

Pile composition—

Conifer and shrub/hardwood piles had different physical characteristics (table 3). 

Piles composed primarily of coniferous material had significantly higher bulk density 

(t = 10.199; p < 0.001) and packing ratio (t = 14.145; p < 0.001) than piles composed 

primarily of shrub and hardwood material, in large part owing to the greater percentage of large (>7.6 cm diameter) woody particles in the conifer piles (table 3). Based on 

these differences in composition, separate equations were developed for describing 

the relationships between true pile volume and biomass (table 4, fig. 9). The dependent 

and independent variables (pile weight and true volume) for both the conifer and 

shrub/hardwood hand-pile data were natural log-transformed making the distribution 

of the residuals normal and homoscedastic. The resulting regressions described 59 and 

Table 4—Prediction equations for estimating true volume and oven-dry biomass 

of hand piles

 Adjusted Root Percentage

Equationa R2 MSEb bias Precision

1. If GV < 1, TV = exp(0.2106) × GV 

2. If GV ≥ 1, 

 TV = exp(0.2106 + 0.7691 × ln[GV]) 0.79 0.253 0.206 0.270

3. If conifer, 

 W = exp(4.4281 + 0.8028 × ln[TV)]) 0.59 0.353 0.292 0.438

4. If shrub/hardwood, 

 W = exp(3.0393 + 1.3129 × ln[TV]) 0.64 0.534 0.468 0.647

a TV = true volume (m3

); GV = geometric volume (m3); W = weight (kg); ln = natural logarithm (base e). b MSE = Mean squared error.

Conifer and shrub/

hardwood piles had 

different physical 

characteristics.
12

GENERAL TECHNICAL REPORT PNW-gtr-805

64 percent of the variability in the data for the conifer and shrub piles, respectively. 

As with the geometric-to-true volume regression, we calculated a correction factor to 

account for the bias that results from retransforming from logarithmic to arithmetic 

units, and as with the volume-to-volume regressions, the uncorrected predictions were 

slightly less biased and slightly more precise. 

Coefficients of the conifer and shrub/hardwood piles were significantly different 

for slope (t = 3.282; p = 0.001) and intercept (t = 7.806; p < 0.001), indicating that pile 

composition was important, and that the relationship between volume and biomass 

was different for hand piles composed of primarily conifer and primarily shrub/hardwood material (fig. 9a).

Errors Related to Characterizing Piled Fuels

The largest errors in characterizing piled fuels are related to estimating pile volume 

(Hardy 1996). Piles rarely conform perfectly to a geometric shape. Our data indicate 

that the use of shapes and volume formulas tends to overestimate the true volume of 

the pile, except for very small piles (<2.5 m3). This is in contrast to McNab and Saucier 

Figure 9—Relationship between the natural log of true pile volume and the natural log of pile biomass (a). The 

relationship between true pile volume and pile biomass is nonlinear when plotted in arithmetic units (b). Residual 

diagnostic plots of standardized residuals against the expected natural log of biomass for the conifer regression (c) 

and the shrub/hardwood regression (d).

(a)

2

3

4

5

6

7

-1 0 1 2 3

ln true volume (m 3)

ln biomass (kg)

Conifer

Shrub/hardwood

Conifer

Shrub/hardwood

(c)

-3

-2

-1

0

1

2

3

4 5 6

Expected ln biomass (kg)

Standardized residuals

Conifer

(d) -3

-2

-1

0

1

2

3

3 4 5 6

Expected ln biomass (kg)

Standardized residuals

Shrub/hardwood

(b) 0

200

400

600

0 5 10 15

True volume (m 3)

Biomass (kg)

Conifer

Shrub/hardwood

Conifer

Shrub/hardwood

Our data indicate that 

the use of shapes and 

volume formulas tends 

to overestimate the 

true volume of the pile, 

except for very small 

piles (<2.5 m3). 

1n biomass (m3

)

1n true volume (m3) True volume (m3)

Expected 1n biomass (m3) Expected 1n biomass (m3)
13

Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

(1980) who observed that their simple geometric method for windrowed fuels tended 

to underestimate the cross-sectional area and volume by approximately 19 percent.

Errors also occur when relating pile volume to pile biomass; the relationship 

between pile volume and mass is sensitive to estimates of the proportion of the pile 

volume that is actually composed of solid material (i.e., the packing ratio). Packing 

ratio can be quite variable (Little 1982, McNab 1980, tables 7 and 8 in this study), 

however, so determining the correct value for a given pile is problematic. For example, 

the guidelines in Hardy (1996) specify general species, particle size, and construction 

methods (hand-construction is not considered) to help select the correct packing ratio. 

However, these guidelines are for machine-constructed piles and do not describe 

the characteristics of hand-piled fuels; additional analysis and development of more 

detailed guidelines would be necessary to be able to select the correct packing ratio for 

hand piles.

Additional inaccuracies can be introduced when converting wood volume to wood 

biomass. McNab (1980) suggested a general wood density of 0.56 g/cm3 (35 lbs/ft3) 

when “species composition is not important.” However, wood density varies considerably by species (USDA FS 1999): for example, ponderosa pine (Pinus ponderosa C. 

Lawson)(0.38 g/cm3) is approximately one-third less dense than tanoak (Lithocarpus 

densiflorus [Hook. & Arn.] Rehder)(0.58 g/cm3). Use of general wood density values 

or woody density values for species different than those present in a pile can affect pile 

biomass calculations and thus estimates of emissions from burning.

Comparison With Machine Pile Methods

In comparison to the methodological approaches that employ approximations of wood 

volume as a fraction of total pile volume to estimate biomass, we developed a model to 

estimate pile biomass directly from measurements of pile volume. Weighing of large 

machine-constructed piles is logistically difficult (Little 1982), hence the volumebased methods of Hardy (1996) and McNab (1980, 1981). Because hand piles were 

smaller, we were able to weigh them directly. At least for hand piles, the ability to 

model pile biomass directly from pile volume removes two potential sources of error 

identified above: estimating packing ratio and selecting wood density.

We hypothesized that using the machine-pile-based recommendations of Hardy 

(1996) for hand piles could overestimate biomass, as we expected machine-constructed piles to contain mechanically compacted and larger fuel particles. This was 

true for hand piles composed of shrub and hardwood debris (142.6 percent mean 

overestimate), but not for hand piles composed of primarily coniferous material (32.5 

percent mean underestimate) when using a packing ratio of 0.10, which is the most 

appropriate value based on the guidelines included in Hardy (1996). Adjusting the 

At least for hand piles, 

the ability to model 

pile biomass directly 

from pile volume 

removes two potential 

sources of error 

identified above: 

estimating packing 

ratio and selecting 

wood density.
14

GENERAL TECHNICAL REPORT PNW-gtr-805

Table 5—Comparison of measured and estimated biomass using the methods of 

Hardy (1996) with two different packing ratios (PR) and the methods of this study 

for 121 hand piles

 Measured Modeleda

 this study Hardy (0.10 PR) Hardy (0.15 PR) This study

Conifer-dominated:

 Mean biomass (kg) 177.3 106.4 159.6 172.4

 Mean difference 

 (percentage) -32.5 +1.3 +7.7

 Underestimate 

 (no. of piles) 56/63 41/63 34/63

 Overestimate 

 (no. of piles) 7/63 22/63 29/63

Shrub/hardwooddominated:

 Mean biomass (kg) 134.1 235.6 353.4 109.1

 Mean difference 

 (percentage) +142.6 +263.9 +4.2

 Underestimate 

 (no. of piles) 9/58 1/58 32/58

 Overestimate 

 (no. of piles) 49/58 57/58 26/58

a The Hardy method calculates pile volume geometrically, multiplies by a packing ratio to estimate the amount of 

the pile volume that is solid material, and multiplies the solid material volume by the wood density of the material 

present in the pile. This study corrects geometric volume to true volume and relates true volume to biomass using 

regression models.

Table 6—Emission factors used to calculate the mass of emission produced 

from burning hand piles

 Emission factor

Pollutanta Flaming Smoldering Residual

- - - - - - - - - - - - kg/Mg - - - - - - - - - - - -

PMb10.95 10.95 10.95

PM10

b

7.75 7.75 7.75

PM2.5

b

6.75 6.75 6.75

COc26.33 65.19 65.19

CO2

c

857.31 772.47 772.47

CH4

c

1.64 5.52 5.52

NMHCc1.78 3.39 3.39

a PM = particulate matter; PM10 = particulate matter <10 m in aerodynamic diameter; PM2.5 = particulate matter 

<2.5 m in aerodynamic diameter; CO = carbon monoxide; CO2 = carbon dioxide; CH4 = methane; NMHC = 

nonmethane hydrocarbons.

b The same emission factor from Hardy (1996) is assumed for flaming, smoldering, and residual combustion as is 

done in CONSUME 3.0 (Prichard et al., n.d.).

c Emission factors from Steven Baker, personal communication as cited in Prichard et al. (n.d.).
15

Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

packing ratio from 0.10 to 0.15 when using the Hardy methodology improved the 

accuracy of biomass predictions for conifer-dominated piles (1.3 percent mean overestimate), but made shrub hand pile biomass predictions worse (263.9 percent mean 

overestimate). Using the relationships observed in this study (table 4) to predict pile 

biomass based on measured dimensions, we observed 7.7 and 4.2 percent overestimates for conifer and shrub/hardwood hand piles, respectively.

Using the method of Hardy (1996), which was developed for machine piles, for 

shrub and hardwood hand piles tended to overestimate biomass and would therefore 

overestimate emissions from burning, whereas the opposite was true for conifer hand 

piles. As outlined in the previous section, the Hardy method is sensitive to inaccuracies in estimating the true pile volume and packing ratio. We feel that our procedure, 

which is outlined in the following section, improves the accuracy of estimates of 

hand-piled biomass and therefore subsequent smoke emissions by eliminating the need 

to estimate true pile volume and packing ratio.

Procedure for Estimating Emissions

Hardy (1996) provided a very helpful section outlining a six-step process necessary 

to calculate the biomass of machine-piled fuels and the resulting emissions when 

machine piles are burned. In this section, we offer companion directions for handpiled fuels. The steps outlined are encoded into a Web calculator (http://depts.washington.edu/nwfire/handpiles), and require that the user enter only a few easily measured 

variables (pile shape, pile dimensions, pile type, number of piles, and estimated 

proportion consumed).

Step 1—

Select the pile shape that most closely resembles your pile(s) and measure the necessary dimensions as shown in figure 4. We found hand piles to be predominantly 

paraboloid and half-ellipsoid in shape. From the shape assignment and dimensions we 

calculate geometric volume; geometric volume is then adjusted to reflect what we have 

termed true volume by using equations 1 or 2 in table 4, depending on the calculated 

geometric volume.

Step 2—

Determine the pile composition (conifer-dominated or shrub/hardwood-dominated). 

Conifer-dominated hand piles tend to be heavier for a given pile volume than shrub/

hardwood-dominated hand piles in our data set; the relationship between volume 

and mass is modeled with separate equations. From the composition assignment we 

calculate pile biomass by using equations 3 or 4 in table 4 as appropriate.

The steps outlined are 

encoded into a Web 

calculator (http://depts.

washington.edu/nwfire/

handpiles), and require 

that the user enter only 

a few easily measured 

variables (pile shape, 

pile dimensions, 

pile type, number of 

piles, and estimated 

proportion consumed).
16

GENERAL TECHNICAL REPORT PNW-gtr-805

Step 3—

Count and enter the number of piles that meet the shape, size, and composition criteria 

above.

Step 4—

Estimate the proportion of the fuel in pile(s) that will be consumed during burning 

operations. Hardy (1996) noted that between 75 and 95 percent of piled fuels are 

consumed during typical pile burning conditions. CONSUME 3.0 (Prichard et al., n.d.) 

assumes 90 percent of piled biomass is consumed. We supply a default value of 90 

percent, although users may override this at their discretion, and should consider doing 

so if burning operations are being conducted under wet or snowy conditions when less 

consumption is expected. Regardless of weather or fuel conditions, like CONSUME 

3.0, we assume that 70 percent of the consumption occurs during the flaming phase 

of combustion, 15 percent occurs during the smoldering phase of combustion, and 15 

percent occurs during the glowing phase of combustion.

Step 5—

Calculate the mass of emissions produced from flaming, smoldering and glowing 

combustion. We calculate emissions by multiplying the estimated proportional consumption by emission factors (table 6) for seven important pollutant species, including 

all particulate matter (PM), PM smaller than 10 μm in aerodynamic diameter (PM10), 

PM smaller than 2.5 μm in aerodynamic diameter (PM2.5), carbon monoxide, carbon 

dioxide, methane, and nonmethane hydrocarbons. In comparison with machine piles, 

we observed hand piles to be very clean, resulting in maximal combustion efficiency 

and fewer emissions when compared with comparably-sized machine piles that are 

contaminated with mineral soil during their construction (Hardy 1996).

Conclusion

Regulations in Oregon and several other Western States require prescribed fire 

practitioners to estimate emissions from prescribed burning activities, including pile 

burning (see Hardy et al. 2001 for a thorough discussion of fire and smoke management and regulation). Emissions predictions require estimates of preburn pile biomass. 

Therefore, it is important that fuel managers and air quality regulators have the tools 

necessary to accurately estimate the volume and biomass of hand-piled fuels to better 

estimate emissions from pile burning activities to address both mitigation and regulatory compliance. This study collected data and developed tools to improve the characterization of hand piles using direct methods in an attempt to reduce the compounding 

inaccuracies that can result from estimates based on pile volume, packing ratio, and 

wood density.
17

Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

Acknowledgments

We thank our cooperators on the Okanogan-Wenatchee, Los Padres, and Sequoia 

National Forests and Whiskeytown National Recreation Area for their assistance 

with this research. Paige Eagle assisted with data management and processing. Many 

people participated in the field data collection: Ernesto Alvarado, Kyle Jacobson, Amy 

Jirka, Joe Restaino, Shawn Smith, and Mike Tjoelker. We acknowledge funding from 

the Joint Fire Science Program under Project JFSP 07-2-1-57.

English Equivalents

When you know: Multiply by: To find:

Micrometers (μm) 0.039 Mil

Centimeters (cm) .394 Inches

Meters (m) 3.281 Feet

Cubic meters (m3) 35.315 Cubic feet

Hectares (ha) 2.471 Acres

Grams per cubic centimeter (g/cm3) 62.428 Pounds per cubic foot

Kilograms per cubic meter (kg/m3) .062 Pounds per cubic foot

Kilograms (kg) 2.205 Pounds

Megagrams (Mg) 1.102 Tons

Kilograms per megagram (kg/Mg) 2.000 Pounds per ton

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20

GENERAL TECHNICAL REPORT PNW-gtr-805

Appendix

Table 7—Conifer hand pile data

Pile IDa Shapeb

Geometric 

volume

True

volume Biomass

Bulk 

density

Packing 

ratio

<2.5 cm 

diameter

2.5–7.6 cm 

diameter

>7.6 cm 

diameter

 m3 m3 kg kg/m3 m3/ m3 - - - - Proportion of biomass - - - -

BC01 E 3.13 2.68 84.72 31.57 0.06 0.35 0.57 0.07

BC03 P 2.36 2.26 61.19 27.08 0.05 0.71 0.24 0.05

BC04 P 1.53 1.48 44.47 30.10 0.07 0.65 0.29 0.06

BC05 P 3.29 3.41 384.60 112.91 0.30 0.09 0.06 0.85

BC06 P 4.07 3.78 188.60 49.91 0.13 0.30 0.06 0.64

BC07 E 2.95 3.63 243.72 67.23 0.17 0.10 0.09 0.82

BC08 P 3.29 3.74 177.95 47.53 0.12 0.20 0.22 0.59

BC09 P 4.22 4.43 245.63 55.47 0.13 0.20 0.12 0.68

BC10 P 5.32 5.76 410.48 71.28 0.18 0.25 0.06 0.69

BC11 E 3.99 3.45 266.79 77.28 0.20 0.22 0.07 0.71

BC12 E 4.25 3.71 225.63 60.75 0.16 0.28 0.10 0.62

BC13 E 3.74 3.13 249.41 79.73 0.21 0.20 0.09 0.71

BC14 E 5.19 6.11 292.45 47.88 0.12 0.18 0.08 0.74

CS01 P 6.28 7.81 379.82 48.61 0.12 0.21 0.15 0.64

CS02 P 5.98 6.46 379.24 58.71 0.15 0.16 0.12 0.72

CS03 P 2.95 3.19 217.42 68.07 0.16 0.25 0.28 0.47

DT01 P 1.59 1.50 107.92 71.81 0.16 0.18 0.15 0.67

DT02 P 1.46 2.01 160.30 79.81 0.20 0.21 0.19 0.60

DT03 P 1.31 1.07 76.83 72.10 0.18 0.33 0.22 0.45

DT04 P 0.99 1.08 73.14 67.44 0.17 0.31 0.24 0.45

DT05 E 1.06 1.12 106.70 95.08 0.23 0.13 0.28 0.59

DT06 E 3.33 2.45 136.50 55.70 0.15 0.33 0.23 0.44

DT07 P 1.30 1.41 122.95 87.05 0.23 0.20 0.11 0.69

DT08 P 1.05 0.95 108.33 113.93 0.30 0.21 0.13 0.66

DT09 E 3.11 2.41 195.32 81.10 0.21 0.24 0.29 0.48

DT10 E 3.06 2.59 213.80 82.63 0.22 0.16 0.17 0.67

DT11 E 1.03 1.02 109.30 107.67 0.28 0.15 0.23 0.62

DT12 P 1.15 0.92 78.25 84.90 0.22 0.32 0.23 0.45

DT13 P 1.38 1.14 60.70 53.43 0.14 0.40 0.31 0.29

DT14 P 1.23 1.76 154.42 87.72 0.24 0.16 0.33 0.51

DT15 P 1.12 1.52 231.77 152.45 0.40 0.13 0.11 0.76

DT16 E 2.21 1.92 151.57 79.03 0.21 0.26 0.26 0.48

DT17 E 2.65 2.05 224.29 109.24 0.27 0.14 0.10 0.76

DT18 P 1.28 0.99 104.72 105.54 0.28 0.13 0.10 0.77

DT19 P 1.01 1.91 90.04 47.06 0.12 0.29 0.39 0.32

DT20 P 0.75 0.91 107.95 118.06 0.29 0.17 0.51 0.33

DT21 E 2.06 1.96 179.11 91.48 0.24 0.14 0.21 0.65

DT22 E 1.46 1.21 178.24 146.86 0.39 0.18 0.18 0.65

RS01 E 5.75 4.32 316.03 73.16 0.17 0.26 0.47 0.28

RS02 P 1.12 1.28 76.17 59.62 0.15 0.43 0.52 0.05

RS03 P 1.30 1.27 66.72 52.56 0.12 0.41 0.60 0.00
21

Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

Pile IDa Shapeb

Geometric 

volume

True

volume Biomass

Bulk 

density

Packing 

ratio

<2.5 cm 

diameter

2.5–7.6 cm 

diameter

>7.6 cm 

diameter

 m3 m3 kg kg/m3 m3/ m3 - - - - Proportion of biomass - - - -

RS04 P 3.04 2.29 219.36 95.59 0.23 0.25 0.34 0.41

RS05 C 3.74 2.41 164.74 68.39 0.15 0.32 0.57 0.11

RS06 C 2.32 1.37 75.60 55.12 0.13 0.40 0.60 0.00

RS07 P 2.39 2.75 142.45 51.79 0.12 0.27 0.37 0.35

RS08 P 0.77 1.31 76.00 58.18 0.13 0.35 0.50 0.15

RS09 P 1.40 1.84 129.73 70.68 0.16 0.28 0.43 0.29

RS10 F 5.12 2.85 246.53 86.39 0.20 0.24 0.37 0.39

RS11 P 2.01 1.71 116.13 67.96 0.15 0.19 0.47 0.34

RS12 C 5.40 2.46 218.65 88.97 0.19 0.22 0.45 0.33

RS13 C 4.64 2.43 74.91 30.83 0.07 0.36 0.42 0.22

RS14 P 2.70 2.93 257.46 87.82 0.20 0.20 0.30 0.49

RS15 P 0.95 1.38 88.32 64.16 0.14 0.24 0.09 0.68

RS16 P 2.11 2.13 132.27 62.03 0.15 0.44 0.40 0.16

RS17 E 1.55 1.94 138.79 71.54 0.16 0.22 0.24 0.54

RS18 E 2.40 2.34 202.21 86.29 0.20 0.22 0.49 0.30

RS19 P 1.15 1.32 101.67 76.82 0.18 0.21 0.29 0.50

RS20 E 1.80 2.15 152.82 71.20 0.16 0.23 0.33 0.44

RS21 I 4.80 3.85 313.34 81.44 0.20 0.22 0.40 0.38

RS22 E 2.19 1.95 173.92 89.35 0.22 0.25 0.45 0.30

RS23 P 1.91 2.15 225.78 104.80 0.23 0.12 0.56 0.32

RS24 E 4.14 3.90 468.96 120.20 0.26 0.15 0.35 0.51

RS25 E 1.49 1.23 169.80 138.45 0.30 0.11 0.13 0.76 a Pile ID abbreviations refer to stands at different sites: BC and CS = Bear Creek (Porterville, California), DT = Devil’s Table (Naches, Washington), RS = 

Rattlesnake (Naches, Washington).

b Shapes are E = half-ellipsoid, P = paraboloid, C = half-cylinder, F = half-frustum of a cone, I = irregular solid.

Table 8—Shrub/hardwood hand pile data

Pile IDa Shapeb

Geometric 

volume

True

volume Biomass

Bulk 

density

Packing 

ratio

<2.5 cm 

diameter

2.5–7.6 cm 

diameter

>7.6 cm 

diameter

 m3 m3 kg kg/m3 m3/ m3 - - - - Proportion of biomass - - - -

BC02 E 3.22 3.01 94.32 31.29 0.05 0.65 0.35 0.00

CH01 E 10.35 11.07 318.56 28.77 0.04 0.97 0.03 0.00

CPM01 P 3.65 5.24 213.49 40.74 0.07 0.22 0.70 0.07

CPM02 F 4.97 3.16 83.99 26.58 0.04 0.43 0.51 0.06

CPM03 P 6.74 7.62 270.65 35.53 0.06 0.21 0.79 0.00

CPM04 P 2.67 3.17 92.48 29.18 0.05 0.27 0.58 0.15

CPM05 E 6.91 4.07 158.29 38.91 0.06 0.28 0.68 0.04

CPM06 P 1.63 2.66 77.91 29.27 0.04 0.21 0.79 0.00

CPM07 E 23.56 14.47 553.87 38.28 0.06 0.19 0.69 0.12

CPO02 I 4.17 3.25 66.39 20.43 0.03 0.41 0.59 0.00

Table 7—Conifer hand pile data (continued)
22

GENERAL TECHNICAL REPORT PNW-gtr-805

Pile IDa Shapeb

Geometric 

volume

True

volume Biomass

Bulk 

density

Packing 

ratio

<2.5 cm 

diameter

2.5–7.6 cm 

diameter

>7.6 cm 

diameter

 m3 m3 kg kg/m3 m3/ m3 - - - - Proportion of biomass - - - -

FM01 P 6.39 8.34 344.85 41.36 0.07 0.48 0.44 0.08

FM02 E 9.53 5.52 211.19 38.23 0.06 0.55 0.42 0.03

FM03 E 2.89 2.53 155.41 61.46 0.10 0.29 0.45 0.27

FM04 P 1.46 1.58 50.94 32.19 0.06 0.58 0.42 0.00

FM05 E 17.03 10.23 672.14 65.69 0.10 0.21 0.59 0.20

FM06 P 4.48 6.19 158.24 25.58 0.04 0.49 0.40 0.11

FM07 P 5.21 5.29 308.35 58.30 0.09 0.36 0.60 0.04

FM08 F 3.63 3.94 62.14 15.76 0.02 0.67 0.33 0.00

FM09 P 1.92 1.90 60.96 32.05 0.05 0.57 0.43 0.00

FM10 E 2.62 2.30 60.42 26.24 0.04 0.38 0.35 0.28

FM11 F 2.74 2.21 91.96 41.57 0.06 0.38 0.62 0.00

FM12 P 1.60 2.78 70.32 25.29 0.04 0.48 0.43 0.08

FM13 E 2.22 2.04 43.19 21.17 0.03 0.62 0.38 0.00

FM14 P 2.99 3.19 77.06 24.14 0.04 0.59 0.41 0.00

FM15 I 1.50 1.74 158.77 91.11 0.14 0.24 0.65 0.10

MM08 P 1.92 1.83 28.78 15.76 0.03 0.78 0.22 0.00

MM09 E 3.12 1.95 41.13 21.04 0.04 0.75 0.16 0.09

MM10 F 4.59 1.82 30.09 16.54 0.03 0.88 0.12 0.00

MM11 E 4.53 3.33 51.28 15.40 0.02 0.87 0.13 0.00

MM12 P 1.71 2.25 35.59 15.80 0.02 0.97 0.03 0.00

MM13 P 0.79 1.03 27.04 26.25 0.04 1.00 0.00 0.00

MM14 P 1.13 1.50 33.72 22.52 0.03 0.76 0.25 0.00

MM15 E 2.13 1.69 53.81 31.79 0.05 1.00 0.00 0.00

MM16 E 1.19 1.87 42.46 22.75 0.03 0.99 0.01 0.00

MM17 E 3.19 3.09 66.88 21.64 0.03 0.96 0.04 0.00

MM18 P 2.06 2.63 27.98 10.64 0.02 1.00 0.00 0.00

MM19 P 1.02 2.07 15.70 7.59 0.01 0.98 0.02 0.00

MM20 P 6.10 5.92 65.44 11.06 0.02 0.64 0.36 0.00

MM21 P 0.97 1.46 19.78 13.56 0.02 0.93 0.07 0.00

MM22 P 1.52 1.98 27.55 13.92 0.02 1.00 0.00 0.00

MM23 E 3.59 3.57 88.48 24.78 0.03 0.74 0.26 0.00

MM24 E 2.46 2.05 30.59 14.95 0.02 0.93 0.07 0.00

MM25 E 4.16 3.54 71.82 20.27 0.03 0.93 0.07 0.00

MM26 P 2.01 2.58 47.81 18.54 0.03 0.86 0.14 0.00

MM27 P 1.32 1.77 27.87 15.74 0.02 0.99 0.02 0.00

RP01 F 2.45 2.67 131.06 49.11 0.07 0.33 0.25 0.43

RP02 E 2.99 2.65 135.45 51.04 0.07 0.32 0.14 0.54

RP03 P 1.28 2.24 96.96 43.19 0.06 0.44 0.31 0.25

RP04 P 3.31 5.51 269.58 48.89 0.07 0.31 0.47 0.22

RP05 E 5.73 4.38 253.76 57.89 0.08 0.36 0.29 0.35

RP06 P 2.15 2.65 180.69 68.12 0.10 0.29 0.34 0.37

RP07 P 3.50 4.26 243.33 57.15 0.08 0.21 0.27 0.52

RP08 E 3.86 3.50 179.78 51.40 0.08 0.24 0.43 0.33

RP09 E 4.09 4.89 295.21 60.42 0.09 0.37 0.23 0.40

Table 8—Shrub/hardwood hand pile data (continued)
23

Estimating Volume, Biomass, and Potential Emissions of Hand-Piled Fuels

Pile IDa Shapeb

Geometric 

volume

True

volume Biomass

Bulk 

density

Packing 

ratio

<2.5 cm 

diameter

2.5–7.6 cm 

diameter

>7.6 cm 

diameter

 m3 m3 kg kg/m3 m3/ m3 - - - - Proportion of biomass - - - -

RP10 P 2.44 2.38 135.28 56.91 0.08 0.19 0.55 0.26

RP11 P 1.95 2.52 149.54 59.26 0.09 0.39 0.48 0.13

RP12 P 5.18 4.24 315.16 74.25 0.11 0.28 0.30 0.42

RP13 E 3.57 2.94 104.07 35.46 0.05 0.64 0.34 0.02 a Pile ID abbreviations refer to stands at different sites: BC = Bear Creek (Porterville, California), CH = Chamise (Porterville, California), CPM and CPO 

= Carr Powerhouse (Whiskeytown, California), FM = Figueroa Mountain (San Luis Obispo, California), MM = Muletown Manzanita (Whiskeytown, 

California), RP = Ray’s Place (Porterville, California).

b Shapes are E = half-ellipsoid, P = paraboloid, F = half-frustum of a cone, and I = irregular solid.

Table 8—Shrub/hardwood hand pile data (continued)

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