air pollutant emissions associated with forest, grassland, and agricultural burning in texas

Atmospheric Environment 36 (2002) 3779–3792

Air pollutant emissions associated with forest, grassland, andagricultural burning in Texas

Ann Dennisa, Matthew Fraserb, Stephen Andersonc, David Allena,*aDepartment of Chemical Engineering and Center for Energy and Environmental Resources, University of Texas at Austin,

Building 133 MC-R7100, Austin, TX 78758, USAbDepartment of Environmental Science and Engineering, Rice University, Houston, TX, USA

cTexas Natural Resource Conservation Commission, Austin, TX, USA

Received 11 September 2001; accepted 14 February 2002

Abstract

Outdoor fires, such as wildfires and prescribed burns, can emit substantial amounts of particulate matter and other

pollutants into the atmosphere. In Texas, an inventory of forest, grassland and agricultural burning activities revealed

that fires consumed vegetation on 1.6 and 1.7 million acres of land, in 1996 and 1997, respectively. Emissions from the

fires were estimated based on survey and field data on acres burned and land cover and literature data on fuel

consumption and emission factors. Fire data were allocated spatially by county and temporally by month. While fire

events can cause high transient air pollutant concentrations, for most criteria pollutants, the fire emissions were a

relatively small fraction of the annual emission inventory for the State. For fine particulate matter, however, the annual

emission estimates were 40,000 tons/yr, which is likely to represent a significant fraction of the State’s emission

inventory, especially in the counties where the emissions are concentrated.

r 2002 Elsevier Science Ltd. All rights reserved.

Keywords: Fire; Texas; Emission inventory; Land cover; Particulate matter; Criteria pollutants

1. Introduction

Outdoor fires, such as wildfires and prescribed burns,

can emit substantial amounts of particulate matter (PM)

and other pollutants into the atmosphere. These

emissions may significantly impact air quality on both

local and regional scales. Some events are extreme and

the contributions of fires to air pollutant concentrations

are readily observable. For example, in 1998, fires in

Mexico and Central America consumed an estimated

3.45 million acres prompting air pollution emergencies

in dozens of cities and creating smoke traveling as far as

Florida and North Dakota (NRDC, 1999). More

commonly, however, fires of various types contribute

sporadically and at a moderate level to air pollutant

emissions. Individually, some of these events are well

documented, but annual frequencies and the spatial

distribution of fire events are not well characterized. Yet,

these events may be a significant contributor to PM and

other air pollutant emissions in some regions. In this

work, the spatial and temporal distributions of a variety

of different types of fire events are estimated for Texas.

These analyses indicate that fire events can be significant

contributors to total PM concentrations in areas with

extensive agricultural and forestry activity, such as

Texas.

Specifically, annual and monthly emission inventories

for 2 years are reported. One year (1997) had relatively

few extreme weather events with high temperatures and

dry conditions. The other year, 1996, had a greater

frequency of extreme weather events. Emissions are

reported for PM, PM o10mm in diameter (PM10), PM

o2.5mm in diameter (PM2.5), carbon monoxide (CO),*Corresponding author.

E-mail address: [email protected] (D. Allen).

1352-2310/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved.

PII: S 1 3 5 2 - 2 3 1 0 ( 0 2 ) 0 0 2 1 9 - 4

methane (CH4), non-methane hydrocarbons (NMHC),

nitrogen oxides (NOx), and ammonia (NH3). The

emissions are reported for several types of fire events,

which are defined as follows:

1. Wildfires: Unwanted and accidentally, maliciously,

or naturally ignited fires that occur in wildland.

2. Prescribed burning: Non-agricultural controlled for-

est/understory, grassland, and rangeland manage-

ment fires excluding slash burning.

3. Slash burning: Planned non-agricultural fires of

biomass residues resulting from timber harvesting

practices and land clearing operations.

4. Agricultural field burning: Agricultural land clearing

burning, planting preparation burning, stubble burn-

ing, crop residue/waste burning, and burning of

standing fields such as sugarcane.

Finally, the accuracy of the emissions estimates was

assessed by comparing the fine PM emissions related to

fires, estimated for the Houston area, to emissions

estimated based on the concentration of levoglucosan, a

molecular tracer for cellulose combustion, found in fine

PM (Simoneit et al., 1999).

2. Methodology

2.1. Emission inventory overview

Emissions were estimated by applying the following

expression:

Emissions ðlb:Þ ¼Emission factor ðlb:=tonÞ

*Fuel consumption ðtons=acreÞ

*Area burned ðacresÞ: ð1Þ

Therefore, the construction of the emissions inventory

involved estimating acreage burned, fuel consumption

and emission factors. Acreage burned was estimated

using county level information on frequency and extent

of various fire events. The methods used depended on

the type of fire event, and are documented below. Most

of the data on acreage burned were obtained by

surveying land management agencies. Fuel availability

was estimated based on landcover mappings of wild-

lands and croplands. An extensive database on land-

cover types found in Texas has been reported by

Wiedinmyer et al. (2000, 2001) and these data were

used extensively in estimating fuel availability. Fuel

consumption estimates and emission factors were drawn

from the literature. Finally, the data on acreage burned,

fuel loadings, and emission factors were assembled into

a Geographical Information System (GIS) to facilitate

manipulation and display of the data. The specific

methodologies used for each of the major types of fire

events are described below.

2.2. Wildfires

2.2.1. Estimates of acreage burned

Estimates of the acreage burned by wildfires in Texas

during 1996 and 1997 were obtained by surveying the

agencies listed in Table 1. The significance of each of the

sources of data is indicated by the burned acreage

reported by the agency. State and federal agencies

supplied all of the fire records as acreage burned, with

the exception of the Texas Fire Incident Reporting

System (TEXFIRS). The TEXFIRS (Texas Department

of Insurance, 1997a, b), a voluntary reporting system for

local fire departments, only reports the number of fires

rather than the area burned. For counties that reported

fires, the number of fires was converted into acreage

burned using data on fire size reported by the Depart-

ment of the Interior (Department of the Interior, 1998;

Dennis, 2000). The average size for fires in rural areas

was assumed to be 1.2 acres and in urban areas, the size

was assumed to be 0.25 acres. In addition, not all

counties in the state participate in the system. For these

counties, an extrapolation procedure was devised to

estimate the acreage burned for non-reporting counties

(Dennis, 2000). The extrapolation procedure involved

dividing the state into five regions (Panhandle, North

Central, West, East/Central, and Valley/Far South).

Counties for which data were available in each of these

regions were used to estimate data for other counties in

the same region. Specifically, if data on acres burned in

wildfires were not available for a county, the fraction of

wildland acres burned was estimated based on the

fraction of wildland burned in other counties in the

region. Details are described by Dennis (2000). Texas

had an above average wildfire year in 1996, as is

reflected by the nearly twice as many acres consumed in

1996 than in 1997.

2.2.2. Fuel availability

To assess fuel availability, the major vegetation types

in the fire location were identified using a land cover

Table 1

Total acres of wildfires reported by various agencies for 1996

and 1997

Agency Acres burned

1996 1997

Fish and Wildlife Service 18,310 16,366

National Park Service 1631 366

US Forest Service 7937 1317

Texas Fire Incident Reporting System 44,065 28,861

Texas Forest Service—Piney Woods 36,426 8203

Texas Parks and Wildlife Department 756 1068

Total 109,125 56,181

A. Dennis et al. / Atmospheric Environment 36 (2002) 3779–37923780

map described by Wiedinmyer et al. (2001). The data for

rural areas in this map are primarily drawn from

landcover maps developed by the Texas Parks and

Wildlife Department (Texas Parks and Wildlife Depart-

ment, TP&WD, 1998) and field biomass density surveys

performed by the University of Texas (Wiedinmyer,

1999; Wiedinmyer et al., 2000, 2001; Dennis, 2000). The

landcover data have a spatial resolution of 1 km,

therefore, biomass types available as fuel can either be

estimated using the exact location of the fire, or by using

county-average data for biomass density. For the Fish

and Wildlife Service and the National Park Service data,

obtained in GIS format as point locations, biomass

availability could be estimated directly for the precise

location of these fires. For the remaining data, because

the exact burn locations are not known, a distribution of

the fraction of each wildland cover type in every county

was assembled. Then, the acreage burned by county was

multiplied by the fractions to determine the estimated

acres burned by cover type.

2.2.3. Emission factor

A variety of emission factors for wildfires were

reviewed, including those available in the US Environ-

mental Protection Agency’s AP-42 Documents (1992,

1996a, b), data available from the California Air

Resources Board (1997), the Emission Inventory Im-

provement Program (1998, 1999), and data available in

models developed by the United States Forest Service.

The First Order Fire Effects Model (FOFEM 4.0) was

selected for use in the emissions estimation process

(Reinhardt et al., 1997). This choice was made based on

input required for the models and the desire to use a

consistent modeling methodology across source cate-

gories. Using FOFEM to estimate emissions, based on

acreage burned (sorted by land cover type), involves two

steps. The first step is to use fuel models to estimate the

fuel consumption. To estimate fuel loading and con-

sumption in FOFEM, the user can select a vegetation

cover type (to which a fuel model has been designated),

that best represents the dominant overstory species or

species mix in the fire area. The coverages and fuel

models in FOFEM were developed using the Society of

American Foresters cover types (Eyre, 1980) for forested

areas and the Forest-Range Environmental Study

ecosystem types (Garrison et al., 1977) for shrub and

grassland areas. The cover types are grouped into four

geographic regions. The cover types available in the

regions ‘Interior West’ and ‘South East’, which together

have 72 different cover types, are suggested for the state

of Texas. In this work, each of the 600 land cover types

used by Wiedinmyer et al. (2001) to characterize Texas

was mapped onto a land cover type in the FOFEM

model. This resulted in a fuel consumption (tons/acre)

categorized based on the landcover definitions of

Wiedinmyer et al. (2001). Details are described by

Dennis (2000). The consumption is reported in fuel

components of litter, duff, dead fuel, and live fuel. Dead

fuel is broken down into three categories based on

diameter: Wood 0–1 in, Wood 1–3 in, and Wood 3 in or

greater. Live fuels include herb, shrub, conifer regenera-

tion (regen), and canopy fuel components. Fuel con-

sumption for wildfires in Texas ranged from o1 ton/

acre to more than 10 tons/acre, depending on the

landcover type.

The second step in applying FOFEM was to develop

an emission factor, based on tons of fuel burned. The

emission factors selected for wildfire, prescribed and

slash burning were taken from the combustion efficiency

algorithms derived by the USFS (Ward et al., 1993) for

PM, PM2.5, PM10, CO, CH4, and NMHC (Table 2).

These emission factors depend on assumptions of

combustion efficiency. Combustion efficiencies assumed

in this work are reported in the table and the rationale

for choosing these values is described at length by

Dennis (2000).

Nitrogen containing compounds have been measured

in biomass burning emissions and several emission

factors are available (Hegg et al., 1989; Ward and

Hardy, 1991; Yokelson et al., 1997; Lee and Atkins,

1994; Dignon and Penner, 1991). The dominant

nitrogenous species detected are NOx in the flaming

Table 2

Selected hydrocarbon and particulate emission factors (lb/ton) for wildfire, prescribed, and slash burns. The factors were calculated

under dry conditions for each fuel component

Fuel component Average CE Emission factor (lb/ton)

CO CH4 NMHC PM PM2.5 PM10

Litter, Wood 0–100 0.95 52 3 6 15 8 9

Wood 1–300 0.92 111 6 9 20 12 14

Wood 3+00 0.89 174 9 12 26 16 19

Herb, shrub, regen 0.85 249 12 16 33 21 25

Duff 0.82 316 15 20 39 26 30

Canopy fuels 0.85 249 12 16 33 21 25

A. Dennis et al. / Atmospheric Environment 36 (2002) 3779–3792 3781

phase and NH3 in the smoldering phase of combustion.

However, the quantity of these nitrogenous compounds

is highly dependent on fuel nitrogen, which is variable

between vegetation coverages, from 0.19% to 0.85%

(Dignon and Penner, 1991; Lee and Atkins, 1994). There

are few data on nitrogen content in fuel components by

landcover type. Thus, a nitrogen content of 0.7%, which

is a midrange value and is a value representative of the

dominant species types in Texas, was selected for all fuel

components, across all vegetation types. This is a rough

estimate, due to the lack of information available, and it

must be emphasized that this emission factor is only a

first estimate. The NOx emission factor, was assumed to

be proportional to the percent fuel nitrogen, as reported

in Eq. (2) (Dignon and Penner, 1991):

EFNOx ðlb=tonÞ ¼ �3þ 7:8nf ; ð2Þ

where nf ¼ 0:7% fuel nitrogen.

A similar relationship, using the percent fuel nitrogen,

has not been developed for ammonia emissions. How-

ever, recognizing that fuel nitrogen will also influence

ammonia emissions suggests using a molar ratio of NH3

to NOx to calculate the ammonia emission factor (3)

(Yokelson et al., 1997).

NH3

NOx

¼ 14½1�MCE�; ð3Þ

where MCE is the modified combustion efficiency:

MCE ¼DCO2

DCO2 þ DCOð4Þ

and D refers to the measured fire production of a gas

above background levels.

Because this relationship requires CO2 and CO

emission factors, in the modified combustion efficiency

equation, the ammonia emission factors will be different

for each fuel component since the CO2 and CO emission

factors vary with combustion efficiency. The NOx and

NH3 emission factors used in this work are shown by

fuel component in Table 3. Details of the calculations

are presented by Dennis (2000).

2.3. Prescribed burning on wildlands


Estimates of the acreage consumed in Texas by

prescribed burns on wildlands during 1996 and 1997

were obtained by surveying private, state and federal

agencies. The significance of each of the sources of data

is indicated by the burned acreage reported by the

agency, given in Table 4. In this work, prescribed

burning on wildland included any managed fire con-

ducted for wildland management purposes, such as to

reduce forest understory, control grassland or shrubland

vegetation, or to improve wildlife habitat. Prescribed

burning of wildland is primarily conducted by public

agencies, even though the majority of Texas lands

are privately owned. The one exception is in the

Piney Woods region of East Texas where private

industrial and non-industrial timberland is burned.

Fire history data were collected from four public

agencies and from an estimate of practices on private

lands in the Piney Woods region (described in detail

by Dennis, 2000). The acreage collected for 1996 and

1997 shows that two and half times more area was

burned in 1997 than 1996 (Table 4). This may be due

to the fire prevention activities by public agencies in

1997, in response to an above average wildfire year in

1996.

Table 3

Selected nitrogenous emission factors (lb/ton) and parameters used in the calculations by fuel component for wildfire, prescribed and

slash burns

Fuel component Average CE CO2 CO MCE NOx NH3

Litter, Wood 0–100 0.95 3483 52 0.99 2.5 0.5

Wood 1–300 0.92 3373 111 0.97 2.5 1.1

Wood 3+00 0.89 3263 174 0.95 2.5 1.7

Herb, shrub, regen 0.85 3116 249 0.93 2.5 2.6

Duff 0.82 3006 316 0.91 2.5 3.2

Canopy fuels 0.85 3116 249 0.93 2.5 2.6

CE=Combustion Efficiency. MCE=modified combustion efficiency.

Table 4

Acres consumed in prescribed wildland fire emissions, by

agency for 1996 and 1997

Agency Acres burned

1996 1997

Fish and Wildlife Service 19,212 57,835

National Park Service 90 2792

US Forest Service 17,164 63,009

Texas Parks and Wildlife Department 8589 14,991

Private—Piney Woods Region 18,735 22,263

Total 63,790 160,890


2.3.2. Fuel availability and emission factors

The procedures used to assess fuel availability and

emissions were analogous to those used for wildfires.

The major vegetation type in the fire location was

identified using a land cover map described by Wie-

dinmyer et al. (2001). For the Fish and Wildlife Service

and the National Park Service data, obtained in GIS

format as point locations, biomass availability could be

estimated directly for the precise location of these fires.

For the remaining data, because the exact burn locations

are not known, a distribution of the fraction of each

wildland cover type in every county was assembled.

Then, the acreage burned by county was multiplied by

the fractions to determine the estimated acres burned by

cover type and county. Then, the fuel consumption and

emission factors from FOFEM were used to calculate

the emissions by reporting agency, county, and month.

2.4. Prescribed burning on rangelands


Estimates of the acreage consumed in Texas by

prescribed burns on rangelands during 1996 and 1997

were estimated through a county-level survey to the

Agricultural Extension Service (AEXS). The AEXS assists

local farmers and ranchers and maintains 250 agricultural

extension agents, with one being stationed in nearly every

one of the 254 counties in Texas. A survey was sent to

each extension agent to obtain county-level estimates on

the number of acres burned during a typical year.

Identical surveys were also sent to the sheriff of each

county, since the sheriff was regarded as a potential source

of information about local fires. However, the surveys

sent to sheriffs had a low response rate, approximately

12%, and were often returned blank, whereas the surveys

to the AEXS had a 67% response rate.

County agricultural agents were asked to provide data

on range burning activities by month. Not all county

agents in the State responded, so an extrapolation

procedure was devised to estimate the acreage burned

for non-reporting counties. The extrapolation procedure

involved dividing the state into five regions (Panhandle,

North Central, West, East/Central, and Valley/Far

South). For each region, a weighted average fraction

of total rangeland burned was calculated. This was

converted to acreage burned per county using the

National Agricultural Statistics Service (NASS) 1997

report on estimated range area by county (US Depart-

ment of Agriculture, 1999a-c). Details are described by

Dennis (2000). In total, approximately 867,000 acres of

range are burned during a typical year.


The procedures used to assess fuel availability were

analogous to those used for wildfires. The major

vegetation type in the county in which the fire occurred

was identified using a land cover map described by

Wiedinmyer et al. (2001). To assign fuel consumption

values to the data, a procedure identical to that

conducted for wildland emissions was completed, except

cover types and fuel loading appropriate for rangeland

were selected. The cover types selected had fuel

consumptions that ranged between 0.3 and 6.7 tons/

acre, mostly in the categories of live herb and shrub

fuels. Emission factors for the fuels were assumed to be

consistent with the emission factors used for wildfires,

however, since the fuel availability for rangeland is

different than for wildlands, the emissions per acre

burned were significantly less than for wildfires.

2.5. Slash burning


Two types of slash burning were identified as

potentially significant sources of the total outdoor

burning emissions. First, in the Piney Woods Region

of East Texas, where commercial timber production

occurs, residue from logging operations is sometimes

burned as part of site preparation practices. Very little

documentation on these fires is available, as there is no

centralized reporting outside of individual company

records. Second, the burning of debris from land

clearing operations is thought to be problematic in

some areas of the state, particularly in the Piney Woods,

where forested land is cleared for development. How-

ever, no documentation on these fires or even on land

clearing practices in general exists. The Outdoor

Burning Rule (Title 30 Texas Administrative Code

Sections 111.201–111.221) allows land clearing waste

combustion where no practical alternative exists (Texas

Natural Resource Conservation Commission, TNRCC,

1998). Otherwise, there are no regulations, outside of

local jurisdiction that permit, prohibit or require the

recording of slash burning. Nevertheless, an effort was

made to determine the level of these two types slash

burning activities occurring in Texas. Because so little

information is currently available, the procedures used

here provide only a first estimate.

In the East Texas Piney Woods region, approximately

11.8 million acres of forested land is used as commercial

timberland (Texas Forest Service, TFS, 1999). After

timber is harvested, several site preparation practices

may be employed to prepare the cleared land for future

use. The removal of logging debris, such as stumps and

branches, is part of a typical site preparation. Often,

especially if the area is to be replanted, the logging

debris is burned on site. In the East Texas commercial

timberland, individual logging companies and site

preparation contractors dominate these burning activity

practices. Two large companies dominate logging

operations in Texas. Both of these companies were


contacted to determine the degree of logging slash

burning. One company, which owns about 1 million

acres of timberland, estimates that only 1 acre of residue

out of every 200 acres harvested, or 0.5%, is burned by

the company, a number typical of most large logging

companies (Carroll, 1999). However, smaller companies

are thought to burn a higher percentage. The second

large producer of timber in Texas estimates that their

company burns about 15,000–16,000 acres annually,

which constitutes approximately 70% of harvested land

to be replanted (Ray, 1999).

The Harvest Trends Report, an annual Texas Forest

Service (TFS) publication, lists the total industrial

timber harvest volume (in cubic feet) by county for pine

and hardwood timber removal, but the estimated area

harvested is not reported (Xu, 1998a, b). The Harvest

Trends Report does estimate, however, the total acreage

of tree planting by land ownership that occurred in the

entire Piney Woods area during 1996 and 1997. The

forest industry reportedly replanted 85,680 and 78,730

acres in 1996 and 1997, respectively. Using the

approximation suggested by one large producer in Texas

that slash burning occurs on 70% of harvested land that

is replanted, results in an estimated 59,976 and 55,111

acres of logging slash consumed during 1996 and 1997,

respectively. These totals were allocated to the each of

the 43 counties in the region based on the fraction of

total industrial timberland in each county. The Forest

Inventory and Analysis database provided the estimated

industrial timberland area by county (USFS, 1999).

In addition to slash burning for timber replanting,

burning of debris from land clearing operations is

sometimes used as a way to rapidly remove a large

quantity of waste. Because there are no permits required

for slash burning in Texas, other than on a local level,

determining the level of activity can be long and

complicated process. Due to lack of data, and in order

to provide a first estimate of the acres cleared from land

clearing operations, an estimation procedure was

devised based on population growth. That is, the

number of acres cleared is estimated by applying the

fraction of annual population growth to the urban area

in each county (5).

Estimated acres cleared ¼Fraction population growth

*acres urban area: ð5Þ

First, the composite landcover database described by

Wiedinmyer et al. (2001), was used to determine the

total urban area in each county. Only 66 of the 254

counties had significant urban areas. Next, census data

for 1996 and 1997 populations by county were

assembled (US Census Bureau, 1999). After calculating

the fraction of population change for each county, 61

counties of the 66 were found to have experienced

growth. The five counties with negative population

change were assigned zero growth. Finally, applying the

growth fractions to the total urban area, an estimated

total of 50,200 acres were cleared annually from the 61

counties. It was assumed that between 1% and 10% of

the land cleared is burned, resulting in an estimate of

500–5000 acres burned for land clearing. Since even the

upper bound on the percentage of acreage burned (10%)

results in estimates of acreage burned that are small

compared to other source categories, the upper bound

(10% of land cleared is burned) was used. This is, of

course, only a very rough estimate, but it provides a

preliminary estimate of magnitude of these operations.


Since the only commercial timberland in the state is in

the Piney Woods region of East Texas, only one fuel

type, pine-hardwood mixed forested, is burned in timber

operations. The fuel consumption was calculated by

using the same procedures as employed for wildlands,

except that all wood types with a diameter >1 in were

assumed to have been cleared. Fuel consumed was

generally about 10 tons/acre. The first order fire effects

model (FOFEM 4.0) was used to determine the average

combustion efficiency of each fuel component.

For land clearing, the same procedures that were used

in estimating fuel consumption and emissions for

rangeland were employed, except that fires were

assumed to occur only in the counties with urban areas

experiencing population growth.

2.6. Agricultural field burning


Agricultural waste, typically crop residues, can be

managed in a number of ways. Depending on the crop

type, waste can be tilled or plowed back into the field,

taken to a compost or landfill, used as supplemental

feed, or burned directly in the field. The burning of crops

residue is thought to be the least frequent disposal

method, except for sugarcane. In the US, wheat, rice,

sugarcane, peanut, soybeans, barley, and corn are

thought to have the most significant burning activity.

National inventories, including the US Greenhouse Gas

Emission Inventory and the National Emissions Trends,

estimate that 3% of all crop residues is burned annually

(EPA, 1998). However, the largest source of uncertainty

in these emission inventories is the estimated fraction of

crop residue burned each year because few states collect

such information and agricultural and burning practices

vary widely from state to state. Since Texas does not

maintain any records on crop burning activity, survey

data from the AEXS were used to estimate the fraction

of residue burned in each county.

The data requested from the agricultural extension

agents included the number of fires and acres burned

monthly during a typical year for a crop type specified


by the agent. Next, after inspection of the survey data, a

list of reported crop types was compiled. Grasses, such

as ‘hay pasture’ and ‘Bermuda grass’, were collectively

grouped together into a ‘Hay’ crop type. This category

also included Conservation Reserve Program lands,

forage, and unspecified pasture grass. The most frequent

crop residues for which burning activities were reported

were wheat, hay/grasses, and corn. The other crop types

burned were milo, oats, rice, sorghum, and sugarcane.

Four counties reported ‘agricultural land clearing

debris’. The majority of agricultural burning in the state

is most likely of wheat, corn, and hay/grass residues

since these crops were the most frequently reported on

the surveys.

Not all counties reported data, so the burning activity

for crops in non-reporting counties was estimated by

extrapolating the reported data. The first step in the

extrapolation procedure was to determine the number of

acres burned by month of each crop (wheat, corn, and

hay/grasses burning). The fraction of the harvested acres

that were burned was determined for each crop in each

of five regions in the State using county data on crop

harvests available from the Texas Agricultural Statistics

Service (TASS, 1999). This fraction, for each crop, in

each region, was averaged and the appropriate average

value was extrapolated to non-reporting counties. The

fraction of acres burned, by crop, in each county was

multiplied by the acres of crop harvested to yield acreage

burned, given in Table 5. Table 6 reports the emission

factors by crop type and Table 7 lists the estimated

emissions, based on the acreage burned and the emission

factors.

Sugarcane residue, consisting of the tops and leaves of

the sugarcane plant, is typically burned in the field as a

regular crop management practice, either a few days

before or after each harvest, which normally falls

between November and March. Only three counties in

the Lower Rio Grande Valley of Texas grow sugarcane:

Cameron, Hidalgo and Willacy. These counties collec-

tively harvested approximately 34,600 and 26,688 acres

of sugarcane in 1996 and 1997, respectively (USDA,

1999a). Because the burning of sugarcane residue has no

technically or economically feasible alternative, the

practice is allowed in Texas within guidelines established

by the TNRCC to ensure safe burning (TNRCC, 1998).

Rio Grande Valley Sugar Growers’ Association

(1998), a farmer’s cooperative, regulates the burning

activity in conjunction with the TNRCC. During each

season, the sugar growers burn only on days when

meteorological conditions are satisfactory as authorized

by the TNRCC. The sugar growers keep records of

weather conditions during authorized burning days, the

crop areas burned, as well as the estimated fuel loading

available to each burn.

Table 5

Total acres burned and fuel loading values used to estimate

agricultural burning emissions

Crop

residue

Estimated

acres

burned

Percent of

acres

harvested

Fuel load

(tons/acre)

Corn 131,203 7 4.2

Hay/grass 148,584 3 1.0

Sugarcane 17,195 64 2.7

Wheat 220,633 8 1.9

Table 6

Emission factors selected for crop residue burning

Pollutant Crop residue emission factors (lb/ton)

Corn Hay/

grassesaWheat and

sugarcaneb

CO 80.3 204.3 76.4

NOx 3.7 5.1 5.8

NH3a 1.6 6.7 2.1

CH4 3.4 6.3 0.9

NMHC 9.7 32.7 4.8

PM 9.6 17.6 9.0

PM10 9.4 17.4 8.8

PM2.5 9.1 16.9 8.3

aBased on barley straw emission factors.bBased on wheat straw emission factors.

Table 7

Estimated annual emissions from agricultural burning source categories during a typical year

Crop residue Emissions (short tons/yr)

CO CH4 NMHC PM PM10 PM2.5 NOx NH3

Corn 22,136 931 2667 2634 2595 2502 1030 399

Hay/grasses 15,178 470 2431 1306 1293 1257 382 501

Sugarcane 1773 20 111 209 205 194 134 50

Wheat 16,014 184 1006 1886 1849 1748 1211 449

Total 55,000 1600 6200 6000 5900 5700 2800 1400


The Growers’ Association reported a total of 17,195

acres of residue burned during the 1997 season (data for

1996 were not available; Rio Grande Valley Sugar

Growers’ Association, 1998). Normalizing by the annual

acreage harvested in all the counties (26,688 acres), it

was found that approximately 64% of residues from

harvested acres were burned during the year. The acres

harvested in each county were multiplied by this fraction

to estimate the acres burned for each individual county

(Table 8).


Emission factors specific to crop types are reported in

Chapter 2.5 of AP-42 (EPA, 1992), but these factors are

given a ‘D’ rating indicating that the factors are of below

average quality, and are therefore not used in this

inventory. The University of California at Davis derived

specific factors for corn stover, and wheat, barley, and

rice straw combustion for the California Air Resources

Board (CARB, 1997; Jenkins et al., 1996). However,

because the CARB did not report on hay, pasture

grasses, or sugarcane emissions, the factors for these

residues were taken from the crop type thought to be the

closest representation and by comparing the older

emission factors found in AP-42. Ultimately, the barley

straw factor was chosen for hay/grasses, and the wheat

straw factor was selected for sugarcane. The final

emission factors used in this work are listed in Table 8.

The fuel loading value selected for sugarcane burning

is the average load of values reported by the Rio Grande

Sugar Growers’ Association. For corn, hay/pasture, and

wheat crop residues, the fuel loads, which ranged from 1

to 4 tons/acre, were estimated from the EPA’s AP-42

Document (1992).

3. Results and discussion

The total annual acreage burned in wildfires, pre-

scribed wildfires, prescribed rangeland fires, agricultural

fires, and slash burns, for 1996 and 1997 are reported in

Table 9. Tables 10 and 11 report the estimated emissions

from these activities. Examination of Tables 9–11

suggests that prescribed range burning contributes over

half of the total emissions associated with burning

operations, with estimated emissions approximately 5

times greater than other source categories. This is due in

part to the large acreage burned, but higher fuel

consumption per acre (especially compared to agricul-

tural operations) also makes a contribution.

Emissions due to burning operations are not dis-

tributed uniformly throughout the state. Fig. 1 shows

the PM2.5 emission distributions from all categories of

burning operations, expressed as tons/mile2. Similar

distributions would be obtained for the other pollutants,

since the emissions are all linearly dependent on fuel

Table 8

Annual acres sugarcane harvested and burned during the 1997

growing season. Allocated by county using the Rio Grande

Sugar Growers’ Association reports and the NASS crop

production data

County Acres harvested Annual acres burned

Cameron 9726 6266

Hidalgo 14,582 9395

Willacy 2380 1533

Table 9

Total estimated acres burned by source category during 1996

and 1997

Source category Acres burned

1996 1997

Wildfire 109,125 56,181

Prescribed wildland 63,790 160,890

Prescribed range 867,053 867,053

Agricultural 517,616 517,616

Logging slash 59,976 55,111

Land clearing slash 5020 5020

Total 1,622,579 1,661,871

Table 10

Annual emissions estimates for all source categories during 1996

Source category Emissions (short tons/yr)


Wildfire 47,969 2317 3170 6449 4900 4152 510 428

Prescribed wildland 29,233 1416 1940 3951 2998 2539 316 232

Prescribed range 323,508 15,542 21,145 42,671 32,617 27,642 3232 3312

Agricultural 55,101 1606 6215 6035 5942 5700 2758 1398

Logging slash 49,203 2371 3236 6559 4997 4235 509 192

Land clearing slash 2528 129 21 11 5 2 0 0

Total 510,000 23,000 36,000 66,000 51,000 44,000 7300 5600


consumed per county and the pollutant specific emission

factor. East Texas exhibits the most concentrated

emissions. Counties in the Panhandle, Central Texas,

and parts of South Texas also have high emissions.

More insight regarding the contributors to the

emissions can be gained from examining the spatial

and temporal distribution of the emissions from

individual source categories. Figs. 2–10 show the spatial

and temporal distributions of PM2.5 emissions from

wildfires, prescribed wildfires, prescribed rangeland fires,

agricultural operations and slash burns, for 1996.

The spatial distributions show that wildfires, pre-

scribed burns of wildlands and slash burning are most

heavily concentrated in the heavily forested lands in the

eastern half of Texas. In contrast, agricultural burning

activities are concentrated in the Panhandle region.

Rangeland prescribed burns are distributed throughout

west and west Central Texas.

The temporal distributions also differ among the

source categories. Prescribed fires on rangeland, the

largest source of emissions, are most significant during

Table 11

Annual emissions estimates for all source categories during 1997

Source category Emissions (short tons/yr)


Wildfire 24,341 1173 1602 3248 2474 2096 253 191

Prescribed wildland 80,690 3901 5339 10,874 8255 6996 864 601

Prescribed range 323,508 15,542 21,145 42,671 32,617 27,642 3232 3312

Agricultural 55,101 1606 6215 6035 5942 5700 2758 1398

Logging slash 45,212 2179 2973 6027 4592 3891 468 177

Land clearing slash 2528 129 21 11 5 2 0 0

Total 530,000 25,000 37,000 69,000 54,000 46,000 7600 5700

Fig. 1. Spatial allocation of annual PM2.5 emission density

(short tons/mile2) from all source categories associated with

fires during 1996.

0

200

400

600

800

1.000

1.200

1.400

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

PM

2.5

Em

issi

on

s (s

ho

rt t

on

s)

1996

1997

Fig. 2. Temporal distribution of PM2.5 emission estimates from wildfires during 1996 and 1997.


the winter. In contrast, the monthly distribution of

wildfires and agricultural burning, shown in Figs. 4 and

8, can be significant in virtually any month. For

agricultural burning, the specific crop residuals that

are burned vary seasonally. Fig. 8 shows that corn and

sugarcane residues are burned primarily in the winter,

while wheat is burned primarily in the late spring and

early summer.

The emissions data presented in Tables 8–10 and in

Figs. 2–10 have significant uncertainty associated with

them. The uncertainties are due to uncertainties in the

frequency and extent of fires, the landcover character-

izations, the fuel loadings and the emission factors. A

detailed uncertainty analysis is beyond the scope of this

manuscript, however, an indication of the reliability of

these data can be obtained by comparing the emission

inventory to ambient observations of pollutant concen-

trations. For CO, CH4, NMHC, and NOx, the

contributions from fires are difficult to distinguish

chemically from other sources, and are generally small

in magnitude relative to other sources. For example, the

statewide annual emissions of NOx are approximately

106 tons/yr (EPA, 2000), compared to 7000 tons/yr from

all burning activities. The annual emissions of NMHC

from anthropogenic and biogenic sources are well in

excess of 106 tons/yr, compared to 40,000 tons/yr from

all burning activities. For CO, the total emissions due to

fires may approach 10% of the statewide inventory


(short tons/mile2) from wildfires during 1996.

0

200

400

600

800

1.000

1.200

1.400

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

PM

2.5

Em

issi

on

s (s

ho

rt t

on

s)

1996

1997

Fig. 4. Temporal distribution of PM2.5 emission estimates from prescribed fires on wildland reported by state and federal agencies

during 1996 and 1997. (Fires occurring on private lands are not included as only annual data were available.)


(short tons/mile2) from prescribed burning of wildland during

1996.


(500,000 tons/yr out of 5� 106 tons/yr from all sources),

but the CO emissions from fires are not easily

distinguishable from CO from fossil, anthropogenic

sources.

In contrast, the emissions of fine PM from fires can be

distinguished chemically from other sources, and may be

significant relative to other sources (no statewide

inventory data are currently available). The feature that

distinguishes the particulate emissions from fires chemi-

cally is a molecular marker of cellulose combustion,

levoglucosan. Fraser and Yue (2001) made measure-

ments of levoglucosan at three sites in the Houston area,

using seasonal composites of samples taken every 6 days

over a year long period (Tropp et al., 1998). Fraser and

Yue (2001) found concentrations averaging 13, 18

and 92 ng/m3 for composite samples collected in the

spring, summer and winter, respectively. This seasonal

distribution is consistent with the seasonal distribution

predicted by the emission inventory. The contribution

of fires to PM concentrations can be assessed by

assuming that levoglucosan represents 15–30% of the

fine PM mass emitted from wood fires (Schauer, 1998),

and that average annual concentrations of fine PM are

15 mg/m3 (Tropp et al., 1998). For an annual average

levoglucosan concentration of 40 ng/m3, an annual

average of 0.2 mg/m3 can be attributed to fires. This

represents approximately 1% of the annual average fine

PM concentration.

A preliminary estimate of the magnitude of fine PM

emissions from fires can also be derived from the

levoglucosan measurements. Assume that approxi-

mately half of the elemental carbon in the fine PM in

the Houston area (1.6 mg/m3 annual average elemental

carbon concentration; analytical procedures for these

elemental carbon measurements are provided by Tropp

et al., 1998) is derived from diesel fuel combustion. This

is generated by the combustion of 1,000,000 kg/day of

diesel fuel combustion (Texas Comptrollers Office,

2000), which results in the formation of 0.6 g of

elemental carbon per kg fuel burned (Fraser et al.,

2002). Therefore, an emission rate of approximately

600 kg/day of elemental carbon is associated with

elemental carbon concentrations that are roughly 4

times the concentrations of fine PM associated with

burning activities. Therefore, an approximate emission

rate expected for fine PM from fires in the Houston area

is 100–200 kg/day. The estimated annual emissions from

fires in Harris County (includes all of urban Houston

and some surrounding rural lands) is 100 tons/yr or

0.3 tons/day (300 kg/day). This is slightly higher than the

estimate based on levoglucosan concentrations and

other estimates, but is certainly within the range of

uncertainty associated with the calculations.

0

2.000

4.000

6.000

8.000

10.000

12.000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

PM

2.5

Em

issi

on

s (s

ho

rt t

on

s)

Fig. 6. Temporal distribution of PM2.5 emission estimates from prescribed burning of rangeland during a typical year.


(short tons/mile2) from prescribed burning of rangeland from a

typical year.


This calculation also suggests that fires may be a

significant contributor to fine PM emissions statewide.

Fires appear to account for about 1% of the mass found

in fine PM in urban Houston, where fire emissions are

low and contributions from other sources (such as diesel

fuel combustion) are high.

4. Conclusions

Outdoor fires, such as wildfires and prescribed burns,

can emit substantial amounts of PM and other

pollutants into the atmosphere. In Texas, an inventory

of forest, grassland and agricultural burning activities

revealed that fires consumed vegetation on 1.6 and 1.7

million acres of land, in 1996 and 1997, respectively. For

most criteria pollutants, the fire emissions were a

relatively small fraction of the total emission inventory

for the State. For fine PM, however, the annual emission

estimates were 40,000 tons/yr, which is likely to repre-

sent a significant fraction of the State’s emission

inventory, especially in the counties where the emissions

are concentrated.

Uncertainties in the emission inventory arise from

uncertainties in emissions factors taken from the

0

400

800

1200

1600

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

PM

2.5

Em

issi

on

s (s

ho

rt t

on

s)SUGAR

WHEAT

HAY/GRASS

CORN

Fig. 8. Temporal allocation of PM2.5 emission estimates during a typical year for agricultural burning source categories.


(short tons/mile2) from agricultural burning for a typical year.


(short tons/mile2) from logging slash burning during 1996.


literature, uncertainties in fuel consumption estimates

and uncertainties in area burned. Any one of these

factors could be uncertain by a factor of two, but if these

values used for emission factors, fuel loads and acres

burned in the work are not biased, it is likely that the

overall uncertainty is within a factor of 2. This overall

uncertainty assessment is supported by a comparison of

measurements of the concentrations of a tracer of

cellulose combustion, measured near Houston, to

estimates of the concentrations that would be expected

based on emission rates predicted in this study.

Acknowledgements

This work was funded by the Texas Natural Resource

Conservation Commission, through contract number

9880077600-05 with the University of Texas.

References

California Air Resources Board (CARB), 1997. Area Source

Methodologies, Section 9.3 Wildfires. http://www.arb.ca.

gov/emisinv/areasrc/onehtm/one9-3.htm.

Carroll, L., 1999. Personal communication on site preparation

practices by Champion International.

Dennis, A., 2000. Inventory of Air Pollutant Emissions

Associated with Forest, Grassland and Agricultural Burn-

ing in Texas, MS Thesis, University of Texas, Austin, TX,

USA.

Dignon, J., Penner, J.E., 1991. Biomass burning: a source of

nitrogen oxides in the atmosphere. Levine, J.S. (Ed.),

Global Biomass Burning, Vol. 1. pp. 370–375 (Chapter

44). MIT Press, Cambridge, Mass.

Emission Inventory Improvement Program (EIIP), 1998.

Methods for Estimating Greenhouse Gas Emissions from

Burning of Agricultural Crop Wastes, Review Draft,

Volume VIII, Chapter 11. http://www.epa.gov/ttn/chief/

eiip/viii11.pdf.

Emissions Inventory Improvement Program (EIIP), 1999. Open

Burning. Volume III, Chapter 16. Area Sources Committee,

http://www.epa.gov/ttn/chief/eiip/iii16.pdf.

Eyre, F.H., 1980. Forest Cover Types of the United States and

Canada. Society of American Foresters (SAF) www.safnet.

org.

Fraser, M.P., Yue, Z., 2001. Quantification of molecular

markers in samples of PM2.5 in Houston. Final report to

the American Chemistry Council.

Fraser, M.P., Lashmanan, K., Fritz, S., Ubanwa, B., 2002.

Variation in composition of fine particulate emissions from

heavy duty diesel vehicles. Journal of Geophysical Re-

search, accepted for publication.

Garrison, G.A., Bjugstad, A.J., Duncan, D.A., Lewis, M.E.,

Smith, D.R., 1977. Vegetation and environmental features

of forest and range ecosystems. USDA Forest Service,

Agriculture Handbook No. 475.

Hegg, D.A., Radke, L.F., Hobbs, P.V., Rasmussen, R.A.,

Riggan, P.J., 1989. Emissions of some biomass fires. In:

Proceedings of the National Air and Waste Management

Association, June 25–30, Anaheim, CA, Pittsburgh, PA,

No. 089-025.003.

Jenkins, B.M., Turn, S.Q., Williams, R.B., 1996. Atmospheric

pollutant emission factors from open burning of agricultural

and forest biomass by wind tunnel simulations, Vol. 2.

Results, Cereal Crop Residues. California Air Resources

Board (CARB) Project No. A932-126 Reproduced by the

National Technical Information Service, PB97-126940.

Lee, D.S., Atkins, D.H.F., 1994. Atmospheric ammonia

emissions from agricultural waste combustion. Geophysical

Research Letters 21 (4), 281–284.

Natural Resources Defense Council (NRDC), 1999. Scorched

Earth: impacts and implications of the 1998 fire disaster in

North and Central America. http://www.nrdc.org/nrdcpro/

reports/inse.html.

Ray, K., 1999. Personal communication on site preparation

practices by Temple-Inland.

Reinhardt, D.E., Keane, R.E., Brown, J.K., 1997. First order

fire effects model: FOFEM 4.0, User’s Guide. USDA Forest

Service. Intermountain Research Station, Ogden, Utah.

Rio Grande Valley Sugar Growers’ Association, 1998. Log of

burning records.

Schauer, J.J., 1998. Source contributions to atmospheric

organic compound concentrations: emissions measurements

and model predictions, Ph.D. Thesis, California Institute of

Technology.

Simoneit, B.R.T., Schauer, J.J., Nolte, C.G., Oros, D.R., Elias,

V.O., Fraser, M.P., Rogge, W.F., Cass, G.R., 1999.

Levoglucosan, a tracer for cellulose in biomass burning

and atmospheric particles. Atmospheric Environment 33,

173–182.

Texas Agricultural Statistics Service (TASS), 1999. Crop

production data. http://www.io.com/Btass.

Texas Comptroller’s Office, 2000, personal communication.

Texas Department of Insurance, 1997a. Fires in Texas 1996.

Annual Report, TEXFIRS, State Fire Marshal’s Office,

Texas Department of Insurance, January, 1997.

Texas Department of Insurance, 1997b. Fires in Texas 1997.

Annual Report, TEXFIRS, State Fire Marshal’s Office,

Texas Department of Insurance, December 1997.

Texas Forest Service (TFS), 1999. Texas Forestry Best

Management Practices Handbook. http://txforestservice.

tamu.edu/tfshome/manage/bmpfol/handbk1.htm.

Texas Natural Resource Conservation Commission (TNRCC),

1998. Outdoor burning in Texas. http://www.tnrcc.state.

tx.us/admin/topdoc/rg/049.pdf.

Texas Parks and Wildlife Department (TPWD), 1998. Vegeta-

tion Types of Texas. http://www.tpwd.state.tx.us/admin/

veg/.

Tropp, R.J., Kohl, S.D., Chow, J.C., Frazier, C.A., December

1998. Final Report for the Texas PM2.5 Sampling and

Analysis Study. Document No. 6570-685-7770.1F Desert

Research Institute, TRC Environmental Corporation.

US Department of Agriculture National Agriculture Statistics

Service (NASS), 1999a. Crop Production Data. http://

www.usda.gov/nass.

US Department of Agriculture, 1999b. Texas Crop Production

Data Sets by County, USDA Economic and Statistics

System. http://www.mannlib.cornell.edu/data-sets/crops/

9� 100/E/.


http://www.arb.ca.gov/emisinv/areasrc/onehtm/one9-3.htm

http://www.arb.ca.gov/emisinv/areasrc/onehtm/one9-3.htm

http://www.epa.gov/ttn/chief/eiip/viii11.pdf

http://www.epa.gov/ttn/chief/eiip/viii11.pdf

http://www.epa.gov/ttn/chief/eiip/iii16.pdf

http://www.safnet.org

http://www.safnet.org

http://www.nrdc.org/nrdcpro/reports/inse.html

http://www.nrdc.org/nrdcpro/reports/inse.html

http://www.io.com/&sim;tass

http://txforestservice.tamu.edu/tfshome/manage/bmpfol/handbk1.htm

http://txforestservice.tamu.edu/tfshome/manage/bmpfol/handbk1.htm

http://www.tnrcc.state.tx.us/admin/topdoc/rg/049.pdf

http://www.tnrcc.state.tx.us/admin/topdoc/rg/049.pdf

http://www.usda.gov/nass

http://www.usda.gov/nass

http://www.mannlib.cornell.edu/data-sets/crops/9×100/E/



US Department of Agriculture National Agricultural Statistics

Service (NASS), 1999c. 1997 Census of Agriculture Geo-

graphic Area Series 1B: County Level Data, CD-ROM Set

(AC97-CD-VOL1-1B).

US Department of Interior (DOI), 1998. Wildland Fire Statis-

tics, 1997, http://fire.r9.fws.gov/fm/stats/doi/doi1997/htm.

US Environmental Protection Agency (EPA), 1992. Open

Burning. Compilation of Air Pollution Emission Factors,

Volume I: Stationary Point and Area Sources, Fifth Edition,

Chapter 2.5, Ap-42 (GPO 055-000-00500-1), Research

Triangle Park, North Carolina.

US Environmental Protection Agency (EPA), 1996a. Evalua-

tion of emissions from the open burning of land-clearing

debris. EPA-600/R-96-128, Research Triangle Park, North

Carolina.

US Environmental Protection Agency (EPA), 1996b. Wildfires

and prescribed burning. Compilation of Air Pollution

Emission Factors, Volume I, Stationary Point and Area

Sources, Fifth Edition, Chapter 13.1, AP-42 (GPO 055-000-

00500-1), Research Triangle Park, North Carolina.

US Environmental Protection Agency (EPA), 1998. National

Air Pollutant Emission Trends, Procedures Document

1900–1996. EPA-454/R-98-008, Research Triangle Park,

North Carolina.

US Environmental Protection Agency (EPA), 2000. National

Air Pollutant Emission Trends, Procedures Document

1900–1998, Research Triangle Park, North Carolina.

US Forest Service, 1999. Forest Inventory and Analysis (FIA)

Database, http://www.srsfia.usfs.msstate.edu/scrips/ew.htm.

US Census Bureau, 1999. Annual Time Series Population

Estimates, April 1, 1990 to July 1, 1998. http://www.cen-

sus.gov/population/www/estimates/co 98 8.html#pkzip.

Ward, D.E., Hardy, C.C., 1991. Smoke emissions from

wildland fires. Environment International 17, 117–134.

Ward, D.E., Peterson, J., Hao, W.M., 1993. An Inventory of

Particulate Matter and Air Toxic Emissions from Prescribed

Fires in the USA for 1989. Report A1299, USDA Forest

Service, Intermountain Research Station, Missoula, MT.

Wiedimeyer, C., 1999. Biogenic Hydrocarbons in Texas: Source

Characterization and Chemistry, Ph.D. Dissertation, the

University of Texas at Austin.

Wiedinmyer, C., Strange, I.W., Estes, M., Yarwood, G., Allen,

D.T., 2000. Biogenic hydrocarbon emission estimates

for North Central Texas. Atmospheric Environment 34,

3419–3435.

Wiedinmyer, C., Guenther, A., Strange, W.I., Estes, M.,

Yarwood, G., Allen, D.T., 2001. A landuse database and

biogenics emissions inventory for the State of Texas.

Atmospheric Environment 35, 6465–6477.

Xu, W., 1998a. Harvest Trends 1997, Publication 156, Texas

Forest Service, Texas A&M University System.

Xu, W., 1998b. Harvest Trends 1996, Publication 155, Texas

Forest Service, Texas A&M University System.

Yokelson, R.J., Susott, R.A., Babbitt, R.E., Hao, W.M., Ward,

R.E., 1997. Trace Gas Emissions from Specific Biomass

Fire-types. START Synthesis Workshop on Greenhouse

Gas Emission, Aerosols and Land Use and Cover Change in

Southeast Asia, 15–18 November.


http://fire.r9.fws.gov/fm/stats/doi/doi1997/htm

http://www.srsfia.usfs.msstate.edu/scrips/ew.htm

http://www.census.gov/population/www/estimates/co_98_8.html#pkzip


