United States Department of Agriculture

DEPAR TMENT OF AGRICULT URE

Combustion Efficiency and 

Emissions Analysis for a

School Wood Energy System

in Interior Alaska

David L. Nicholls and Daisy Huang

Forest 

Service

Pacific Northwest 

Research Station

Research Paper

PNW-RP-616

February

2020
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Authors

David L. Nicholls (david.l.nicholls@usda.gov) is a research forest products technologist, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research 

Station, 204 Siginaka Way, Sitka, AK 99835; Daisy Huang (dhuang@alaska.edu) is 

an assistant professor of mechanical engineering, University of Alaska Fairbanks, 

Alaska Center for Energy and Power, Lola Tilly Commons, 411 Tanana Loop, P.O. 

Box 755910, Fairbanks, AK 99775-5910.

Cover photo: building that houses the wood energy system at Delta Junction High 

School, Delta Junction, Alaska. Photo by David Nicholls.
Abstract

Nicholls, David L.; Huang, Daisy. 2020. Combustion efficiency and emissions 

analysis for a school wood energy system in interior Alaska. Res. Pap. PNWRP-616. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 18 p.

A recent expansion in wood energy use at schools in Alaska has resulted in more 

than a dozen wood energy systems in operation. However, few have been evaluated for fuel efficiency and pollution impacts, both of which can be examined via 

combustion gas analysis. In this research, we monitored the wood energy system 

at a public school during winter heating conditions. Wood energy parameters were 

sampled on three occasions during early, mid, and late winter in northern Alaska. 

Combustion gas was sampled for a range of parameters that indicated boiler performance, including gas emmissions of oxygen (O2), carbon dioxide (CO2), carbon 

monoxide (CO), excess air, combustion efficiency, and stack temperature, which 

were monitored over 6 days. We observed differences in combustion gas composition between seasons as well as the response of combustion efficiency to gas 

concentrations. Combustion efficiency most strongly correlated with excess air (R2

= 0.693), but poorly correlated with stack temperature (R2 = 0.005). The primary 

combustion gases (O2, CO2, and CO) were moderately correlated with combustion 

efficiency (with R2 values of 0.40, 0.56, and 0.55, respectively). Seasonal differences were found between early, mid, and late winter, with generally less variation 

in combustion gas contents occurring during late winter. Mean combustion gas 

concentrations also varied with heating season. In all cases, mid-winter means were 

significantly different than early and late winter values. This research found that 

more efficient combustion of wood fuels should lead to cost savings, especially during early and late heating seasons. The findings should also be relevant to those of 

other wood-energy-using schools (in Alaska and elsewhere) that experience severe 

mid-winter conditions coupled with milder shoulder seasons. 

Keywords: Wood energy, schools, Alaska, chip-fired, combustion, sawmill 

residue, biomass, thermal energy.

Summary

We monitored the wood energy system at a public school during winter heating 

conditions. Wood energy combustion parameters were sampled on three occasions during early, mid, and late winter in northern Alaska. We observed differences in combustion gas composition between seasons as well as the response 

of combustion efficiency to gas concentrations. Seasonal differences were found 

between early, mid, and late winter, with generally less variation in combustion 

gas contents occurring during late winter. This research found that more efficient 

combustion of wood fuels should lead to cost savings, especially during early and 

late heating seasons. 
Contents

1 Introduction

2 Review of Literature 

4 Wood Energy System Background

4 Overview

4 Lessons Learned

5 Methods

5 Part I: Correlation of Combustion Gas With Operating Efficiency 

7 Part II: Seasonal Differences in Combustion Gas Emissions

7 Part III: Variation of Individual Combustion Gases

7 Limitations of This Study

7 Results

7 Combustion Gas Analysis

14 Discussion and Conclusions

15 Metric Equivalents

15 Literature Cited
1

Combustion Efficiency and Emissions Analysis for a School Wood Energy System in Interior Alaska

Introduction

Wood has been used as a source of heat for centuries, and recent advances such 

as gasification technologies, automated fuel handling systems, emissions control 

devices, and the use of hydronic heating systems have led to cleaner burning and 

higher efficiencies. All these advances are changing the way wood energy users 

interact with forest environments—this is especially true in rural areas. School-size 

systems often have outputs of between about 1 and 5 million British thermal units 

(MMBTUs) per hour, a scale that is considerably larger than the scale used for residential systems, but smaller than that of most industrial systems. In Alaska, recent 

adoption of wood energy has been significant and growing, with close to 25 smallscale industrial systems currently in use.1

 As recently as a decade ago, there were 

only about 10 operating systems (Nicholls 2009). One reason for this growth is that 

Alaska lends itself well to wood energy. It has high winter heating loads (especially 

in interior locations), vast forests, and a low population density. Renewable energy 

adoption has created many economic benefits for rural Alaska, including fuel cost 

savings, increased employment, and reduced reliance on imported fossil fuels. 

There is greater environmental risk associated with transporting fossil fuels than 

there is with wood fuels. For example, in Alaska, three recent fuel spills worth noting 

occurred in 2018: up to 3,000 gal of fuel oil spilled north of Kodiak Island (Andrews 

2018); more than 20,000 gal spilled in Savoonga, (Grueskin 2018); and about 800 gal 

spilled from a tanker truck in interior Alaska (Granger 2018).

A disadvantage associated with using wood energy systems in interior Alaska, 

however, is the high cost of wood fuel. Temperatures can drop as low as -50 °F, 

necessitating extensive use of wood fuel. Costs associated with transporting wood 

fuel can be rather high as some facilities in Alaska are quite remote, making it 

sometimes necessary to transport wood fuel over long distances. In addition, highquality wood residues are in limited supply. All of these factors make it important 

to maximize the utility of this fuel to provide maximum economic benefit to users. 

Often, wood energy users in interior Alaska communities are school districts, 

government agencies, and other facilities that previously used heating oil or other 

fossil fuels. Nonetheless, wood energy often offers less volatile pricing than fossil 

fuels and can allow for greater control of fuel costs. One Alaska school that uses a 

wood energy system reported that their cost savings allowed them to add a full-time 

teacher (Tressel 2016).

In Alaska, recent 

adoption of wood 

energy has been 

significant and 

growing, with close 

to 25 small-scale 

industrial systems 

currently in use.

1 Daniel Parrent. Personal communication. Natural resource specialist (retired), USDA 

Forest Service, State and Private Forestry, Utilization and Forest Stewardship, 161 East 1st

Avenue, Door 8, Anchorage, AK 99501.
2

GENERAL TECHNICAL REPORT PNW-RP-616

Although combustion gas composition and operating efficiencies can reveal a 

great deal about wood energy operating conditions, very few studies have evaluated these parameters at larger than residential scales. In larger systems (schools, 

businesses, etc.), volatile gases released from the fuel are combusted along with 

the fuel, often with the assistance of fans, resulting in increased efficiency. Thus, 

there is a strong need to provide detailed operating information for larger scale 

wood energy systems that often use bulk wood chips. Although wood chips are 

often the preferred fuel for heating schools (in systems that produce from 1 to 5 

MMBTUs per hour), cordwood burners can be used for smaller installations. This 

report adds to past research by also evaluating three different parts of the heating 

season—early, mid, and late season, which encompass a period from about midNovember through mid-April. We focused on combustion efficiency and emissions 

of the primary combustion gases (oxygen [O2], carbon monoxide [CO], and carbon 

dioxide [CO2]). Our research objectives included (1) a comparison of combustion 

gas differences for three parts of the heating season (early, mid, and late) and (2) 

an evaluation of combustion efficiency as influenced by combustion gas concentrations. Both of these factors can have direct implications on fuel cost, which is often 

a leading operational expence for school districts. For example, high levels of CO 

are an indicator of incomplete combustion (which in turn indicates inefficient use 

of wood fuel). Thus, the findings of this research may enable facility managers to 

operate their wood fuel systems in the most efficient manner and to better monitor 

their combustion procedures, resulting in cost savings for their school districts.

Review of Literature 

Much past research has focused on combustion emissions of residential wood 

energy systems that included evaluations of CO, CO2, and nitrogen oxides (NOx), 

as well as other gases. Many other additional studies have evaluated particulate 

emissions, a prime concern for residential wood energy use in many environments 

(Buchmayr et al. 2015, Hedberg et al. 2002, Johansson et al. 2003). Methods to 

reduce particulate emissions have also been investigated (Hukkanen et al. 2012). 

Combustion efficiency of wood burning systems has also been studied, mostly 

at smaller scales. Eskilsson et al. (2004) optimized the efficiency of pellet burners 

at commercial and prototype scales by recognizing the tradeoffs between NOx and 

CO emissions at different excess air levels. Serrano et al. (2013) evaluated combustion efficiency of pine chips and pine pellets, finding similar efficiency and gaseous 

emissions for both types of wood fuels. Other research has considered wood pellets 

(Dias et al. 2004), focusing on the particulate emissions from wood pellet systems 

(Garcia-Maraver et al. 2014) and the range of technologies available for wood pellet 

Although combustion 

gas composition and 

operating efficiencies 

can reveal a great deal 

about wood energy 

operating conditions, 

very few studies 

have evaluated these 

parameters at larger 

than residential scales.
3

Combustion Efficiency and Emissions Analysis for a School Wood Energy System in Interior Alaska

burners (Míguez et al. 2012). Roy et al. (2013) measured combustion efficiency in 

wood pellet stoves, evaluating four types of biomass fuels. 

Combustion of agricultural residues has also been evaluated under numerous 

conditions. Fournel et al. (2015) predicted emissions from combustion of shortrotation crops such as willow, reed canary grass, switchgrass and miscanthus, 

and used these findings to suggest optimum harvesting seasons. Still other 

researchers (Krugly et al. 2014) considered wood, agricultural fuels, and sewage sludge. Koyuncu and Pinar (2007) evaluated 11 separate types of biomass 

for CO, NOx, and sulfur dioxide emissions, while Pilusa et al. (2013) considered 

emissions from briquettes composed of four biomass types. Similarly, Dias et al. 

(2004) tested four types of pellets, evaluating CO, O2, and NOx emissions. 

Several researchers have considered log (i.e., firewood) combustion in residential-scale wood stoves (Hedberg et al. 2002, Johansson et al. 2004, Lamberg et al. 

2017). Related work compared the emissions of wood pellets to those from fire logs 

(Johansson et al. 2004). Mitchell et al. (2016) evaluated eight fuels in domestic-scale 

stoves, including biomass and coal mixtures. Obaidullah et al. (2014) evaluated only 

CO emissions from residential-scale burners, while Ozgen et al. (2014) evaluated 

CO emissions in addition to other compounds, and Ozil et al. (2009) considered 

catalytic reduction of CO in similarly sized burners. Because much of the recent 

research on the use of wood for heating has focused on residential uses, information 

is lacking on fuel storage, handling, and emissions. 

Several studies considered wood chip combustion at larger than residential 

scales. Buchmayr et al. (2015) investigated wood chip combustion in a small-scale 

commercial boiler. They found that primary air ratio and fuel moisture content 

were important in influencing combustion products as well as particulate formation. 

Caposciutti and Antonelli (2018) studied excess air ratios on a small-scale (140 kW) 

biomass burner also fueled by wood chips. They found that levels of excess air can 

directly influence emissions of CO, CO2, and NOx. Similarly, Zhang et al. (2010) 

evaluated a 320-kW biomass grate system, finding that excess air influenced both 

bed temperatures and combustion gas composition.

These studies and others that focus on residential-scale wood energy systems 

reveal a significant research deficiency for larger wood energy systems typically 

fired with wood chips. There has also been very little research in arctic or semiarctic conditions, where heating seasons can be longer and heating loads more 

severe than those at lower latitudes. Furthermore, much past research has evaluated combustion gases for just a few hours at a time (often in a laboratory setting), 

basing conclusions on limited testing parameters. Thus, there is a need for multiday 

research that evaluates combustion gases under a wide range of daily and seasonal 

conditions. Our current research attempts to address all three of these research gaps. 
4

GENERAL TECHNICAL REPORT PNW-RP-616

Wood Energy System Background

Overview

Wood energy systems have become an effective means of providing heat and other 

benefits to schools, government buildings, small businesses, and other community 

users. These systems typically burn wood chips, wood pellets, or cordwood to generate hot water, which is circulated via pipes to individual buildings. The Biomass 

Energy Resource Center maintains a database of more than 500 community-scale 

wood energy systems (VEIC 2017). This resource illustrates the breadth of potential 

wood energy applications, including those in schools, hospitals, government buildings, and small-business facilities. In Alaska, numerous wood energy systems have 

been installed, including at least four at schools.

The Delta/Greely School District in Delta Junction started operating its wood 

energy system in September 2011 and completed its first heating season in April 

2012. The thermal system burns between 1,400 and 2,000 green tons of wood chips 

per year at a delivered wood cost of about $63 per ton (Tressel 2016). During the 

first three heating seasons, nearly $300,000 was saved by burning wood instead of 

heating oil (Tressel 2016). The school district burns mostly clean wood processing 

residues containing little or no bark or needles. The delivered wood fuel moisture 

content is typically 30 percent green basis or drier. The wood energy system 

includes a Messersmith2

 burner rated at 5.5 MMBTUs per hour. The project was 

financed by the Alaska Renewable Energy Fund and other state funding to meet the 

total installed cost of about $2.8 million. 

The boiler is a chip-fired system that uses chipped slab wood from a local 

lumber mill. The burner design is such that volatile gases released from the fuel 

are burned along with the fuel, increasing efficiency and decreasing incomplete 

combustion products. The boiler heats water, and the energy is transferred using a 

double-plate heat exchanger with a glycol-water mixture; this is circulated throughout the school for heat. The boiler is designed to comply with AP-42 federal emission standards (US EPA 2018). 

Lessons Learned

Delta/Greely School District maintains its fuel oil system as an automatic backup 

in case of unexpected downtime for the wood system. However, operation has been 

fairly smooth during the first seven heating seasons, and there has been little need 

for the fuel oil backup system. One problem to note with the school district’s system 

2 The 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.

The Delta/Greely 

School District 

in Delta Junction 

started operating its 

wood energy system 

in September 2011 

and completed its 

first heating season 

in April 2012. The 

thermal system burns 

between 1,400 and 

2,000 green tons of 

wood chips per year.
5

Combustion Efficiency and Emissions Analysis for a School Wood Energy System in Interior Alaska

(as well as several others in Alaska) is that softwood foliage, dirt, and contaminants 

can create solid slag residues within the combustion chamber, resulting in greater 

maintenance time.

The neighboring community of Tok, Alaska, uses the same kind of boiler 

to heat its school. However, the operators added a steam turbine to the boiler 

to generate electricity (approximately 50-kW capacity) as well as heat. Thus, it 

consumes a larger quantity of fuel than does the Delta/Greely system. Another 

difference is that, during the first few years in operation, the Tok operators burned 

chips that came from low-quality black spruce that was cleared for fire remediation. 

The spruce trees were chipped whole and included the needles, bark, and roots. 

Because these materials were included, in addition to using a higher burn rate, the 

Tok system produced solid residues in the burn box (including slag), which needed 

frequent removal. The operators have since switched their fuel to clean chips, and 

the maintenance problems have abated. Thus, wood has become an effective energy 

source for both of these school systems, although their fuel sources and modes of 

operation are different.

Methods

Part I: Correlation of Combustion Gas With Operating Efficiency 

This research was an observational study measuring combustion gases during 

normal operation of a 5.5-MMBTU per hour school wood heating system. Combustion gas measurements were taken with a Bacharach® PCA3 portable combustion 

gas analyzer inserted about 1 ft from the outlet of the combustion chamber, before 

the cyclone and stack (fig. 1). 

Measurements were taken in real time for percentages of O2, CO2, excess air, 

and combustion efficiency as well as CO (in parts per million [ppm]), and stack 

temperature (°F). Combustion gases were sampled on three different occasions, 

representing different parts of a typical heating season in interior Alaska: late 

autumn (December), mid-winter (February), and early spring (April). Mean emissions data were compared for each of the three sampling dates for each parameter 

of interest. Data were collected at 2-minute intervals over a cumulative sampling 

period of more than 32 hours. Each data point was collected as a “snapshot” point 

in time (rather than an average value over a sampling period). A primary goal 

was to determine differences between mid-winter heating conditions and the two 

shoulder seasons. Our statistical analysis included regression analyses of combustion efficiency against independent variables of interest (including CO, O2, CO2, 

and stack temperature). 

Combustion gases 

were sampled on three 

different occasions, 

representing different 

parts of a typical 

heating season in 

interior Alaska.
6

GENERAL TECHNICAL REPORT PNW-RP-616

Figure 1—(A) Wood energy burner at Delta Junction High School; (B) closeup of combustion gas 

analyzer showing insertion point for sampling. 

A

B
7

Combustion Efficiency and Emissions Analysis for a School Wood Energy System in Interior Alaska

Part II: Seasonal Differences in Combustion Gas Emissions

We also conducted an analysis of variance on all independent variables of interest comparing early, mid, and late winter heating season. We evaluated mean differences in O2, CO2, CO, combustion efficiency, and stack temperature. Significant 

differences between treatment means were determined using Bonferroni’s pairwise 

means comparison test, at the 0.05 significance level.

Part III: Variation of Individual Combustion Gases

We compared differences within combustion gases during combustion cycles. The 

burner alternated between two firing modes—a low-fire mode (in which little or 

no fuel was metered into the combustion chamber), and a high-fire mode (in which 

greater amounts of wood were actively burned to increase the heating load). As a 

result, there was a clear cyclic nature for several of the response variables (CO2, 

CO, O2, stack temperature). This typically lasted about 15 to 20 minutes per cycle, 

in response to changes in the firing mode described above. We compared the results 

of each heating season. 

Limitations of This Study

Several limitations to this exploratory study are worth noting. Our sampling period 

for the three testing periods totaled 6 days; a longer period would have been ideal. 

The study was limited to one fuel type (sawmill waste wood chip residues). Data on 

additional fuel types could provide greater insights to wood energy managers. We 

did not evaluate fuel usage directly; therefore, we were not able to determine the 

direct effects of combustion efficiency on wood fuel use. Last, the study was largely 

observational; there was very little experimental control over system variables. 

Many of these limitations would have been ameliorated had the data collection site 

been less remote, allowing researchers to spend more time onsite.

Results

Combustion Gas Analysis

Part I: correlation with combustion efficiency—

Combustion efficiency is important because of its influence on fuel use and hence 

fuel cost as well as air quality, which are often related to the system scale (Dornburg and Faaij 2001). The school system we evaluated burns more than 1,400 tons 

of wood each year at a purchase price of nearly $90,000 per year (Tressel 2016). 

Thus, operational changes that can enhance wood-fuel-use efficiency are desirable. 

Combustion efficiency 

is important in wood 

energy systems 

because of its 

influence on fuel use 

and hence fuel cost as 

well as air quality.
8

GENERAL TECHNICAL REPORT PNW-RP-616

We found strong correlations between combustion efficiency and certain parameters. Correlations ranged from 0.0005 (stack temperature vs. combustion efficiency) (fig. 2) to 0.693 (excess air vs. combustion efficiency) (fig. 3), with CO vs. 

combustion efficiency having an intermediate correlation of 0.40 (fig. 4). Similar 

correlations for O2 and for CO2 were close to 0.55 (table 1) (figs. 5 and 6).

Combustion efficiency has been found to have strong correlations to level of 

excess air, and in the Delta/Greely School District wood energy system, this was 

influenced by time spent in low-fire mode. Although relating combustion efficiency 

to firing mode was outside the scope of our study, it likely played a role. A practical 

outcome of this study would be to monitor the time spent in pilot standby mode, 

in which relatively little air would flow through the combustion chamber. This 

would be in contrast to low-fire mode, where substantially more air would be forced 

through the combustion chamber.

Part II: seasonal differences in combustion gas emissions— 

There were seasonal differences for all variables of interest. For mean O2, mean 

CO, and mean stack temperature, all three seasons were statistically different from 

each other (0.05 level of significance) (table 2). For CO2 and combustion efficiency, 

mid-winter conditions were statistically different from early or late winter conditions. Seasonal differences were found between early, mid, and late winter, with 

generally less variation in combustion gas contents occurring during late winter. 

Mean combustion gas concentrations also varied with heating season. In all cases, 

mid-winter means were significantly different than early and late winter values. 

We could find no other studies that evaluated chip-fired systems over three heating 

regimes, and therefore we are not able to make comparisons to past research. 

Part III: variation of individual combustion gases—

During our testing, the combustion system automatically alternated between two 

distinct modes of operation: a low-fire mode and a pilot standby mode. Typically, 

these modes lasted between 10 and 30 minutes. Therefore, certain combustion gas 

concentrations alternated over a wide range. For example, O2 varied from about 

20.9 percent (the maximum possible) to as low as about 11 percent (fig. 7). CO 

varied over an even wider range, from about 100 to 1,800 ppm (fig. 8). Likewise, 

stack temperatures varied over a wide range during a single cycle—more than 100 

°F in some cases (fig. 9). It appears that the magnitude of cycling between low-fire 

and high-fire mode was less pronounced during the late winter sampling for CO, 

O2, and stack temperatures.
9

Combustion Efficiency and Emissions Analysis for a School Wood Energy System in Interior Alaska

200 220 240 260 280 300 320 340

y = -0.0016x + 80.311

R2

 = 0.0005

n = 272 

75

76

77

78

79

80

81

82

83

84

Combustion efficiency (percent)

Excess air (percent)

y = -0.0286x + 85.251

R2

 = 0.693

n = 215 

75

76

77

78

79

80

81

82

83

84

95 115 135 155 175 195 215 235 255

Combustion efficiency (percent)

Excess air (percent)

Figure 2—Stack temperature versus combustion efficiency for Delta/Greely School District wood 

energy system (all observations).

Figure 3—Excess air versus combustion efficiency for Delta/Greely School District wood energy 

system (all observations).
10

GENERAL TECHNICAL REPORT PNW-RP-616

0 200 400 600 800 1,000 1,200 1,400

y = -0.0026x + 80.96

R2

 = 0.3993

n = 271

75

76

73

74

77

78

79

80

81

82

83

84

Combustion efficiency (percent)

Carbon monoxide content (parts per million)

Figure 4—Carbon monoxide content versus combustion efficiency for Delta/Greely School District 

wood energy system (all observations).

Table 1—Combustion efficiency as related to other 

variables during early, mid, and late winter sampling

Variable R2a Number of observations

Stack temperature 0.0005 272

Carbon monoxide 0.3993 271

Carbon dioxide 0.5611 271

Oxygen 0.5557 271

Excess air 0.693 215

a

 Versus combustion efficiency.
11

Combustion Efficiency and Emissions Analysis for a School Wood Energy System in Interior Alaska

10 11 12 13 14 15 16 17

y = -0.8566x + 91.665

R2

 = 0.5557

n = 271 75

76

74

77

78

79

80

81

82

83

84

Combustion efficiency (percent)

Oxygen content (percent)

4 5 6 7 8 9 10 11

y = 0.8594x + 73.903

R2

 = 0.5611

n = 271

75

76

77

78

79

80

81

82

83

84

Combustion efficiency (percent)

Carbon dioxide content (percent)

Figure 5—Oxygen content versus combustion efficiency for Delta/Greely School District wood 

energy system (all observations).

Figure 6—Carbon dioxide content versus combustion efficiency for Delta/Greely School District 

wood energy system (all observations).
12

GENERAL TECHNICAL REPORT PNW-RP-616

6

8

10

12

14

16

18

20

22

24

1 101 201 301 401 501 601

Oxygen content (percent)

Sample number

Figure 7—Oxygen content of combustion gases for early, mid, and late winter samples.

Table 2—Average combustion gas concentrations by season for wood energy 

thermal system at a school in interior Alaskaa

Season

Early winter Mid winter Late winter

Oxygen (percent) Average 18.45 a 15.36 b 17.49 c

Variance 3.82 7.76 5.30

151 318 132

Carbon dioxide (percent) Average 5.45 a 7.35 b 5.79 a

Variance n 0.32 1.07 0.51

28 196 48

Carbon monoxide (parts 

per million)

Average 514.41 a 613.32 b 440.35 c

Variance n 143,403 139,352 36,948

340 325 300

Combustion efficiency 

(percent)

Average 79.05 a 80.02 b 79.35 a

Variance n 1.98 1.99 1.69

28 196 48

Stack temperature (°F) Average 255.45 a 289.45 b 227.39 c

Variance n 1,355.17 772.71 1,387.46

340 325 300

a

 Averages having common letters are not statistically different at the 5-percent level by the Bonferroni multiple 

comparison test.
13

Combustion Efficiency and Emissions Analysis for a School Wood Energy System in Interior Alaska

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

Carbon monoxide content (parts per million)

1 201 401 601 801

Sample number

150

170

190

210

230

250

270

290

310

330

350

1 101 201 301 401 501 601 701 801 901

Stack temperature (°F)

Sample number

Figure 8—Carbon monoxide content of combustion gases for early, mid, and late winter.

Figure 9—Stack temperature of combustion gases for early, mid, and late winter.
14

GENERAL TECHNICAL REPORT PNW-RP-616

Discussion and Conclusions

This research was among the first to investigate combustion gas emissions of a 

chip-fired wood energy school heating system. We found that there was relatively 

little daily variation in combustion gas emissions of CO, CO2, and O2 during 

normal operations of the chip-fired wood energy system. However, because of 

differences in firing modes (low-fire and high-fire), there were pronounced shortterm variations in combustion gas concentrations. Combustion efficiency (often 

a measure of fuel usage and economy) also varied cyclically, however, to a lesser 

degree than O2, CO, or stack temperature. Several variables were well correlated 

with combustion efficiency, including excess air, O2, and CO2. However, stack 

temperatures were poorly correlated with combustion efficiency. Combustion gas 

composition was found to vary, depending on heating season (early, mid, or late). 

For O2 and combustion efficiency, mean mid-winter values were different from 

early season or late season values. For CO, O2, and stack temperature, responses 

also varied significantly by season. Mean values for each season were significantly 

different from each other. 

Combustion efficiency is important because of its relation to fuel use and therefore cost, as well as its impact on air pollution. Actions to fine-tune combustion efficiency (such as adjusting overfire and underfire air rates, regulating fuel-feed rate, 

and optimizing fuel moisture) can often be easily accomplished by onsite personnel. 

This research found that more efficient combustion of wood fuels should lead to 

cost savings, especially during shoulder heating seasons such as late winter, when 

conditions can be more easily controlled. During shoulder seasons, facility operators 

also are assessing when to stop heating for the summer season. This research will 

also help enable this decisionmaking process. The findings should also be relevant 

to other school wood energy sites in Alaska and other high-latitude interior locations 

experiencing severe mid-winter conditions coupled with milder shoulder seasons. 

These study results may benefit Delta/Greely schools in Alaska because they 

provide operating data under a range of conditions, outdoor temperatures, and heating loads. This information can be used to fine-tune operating parameters, potentially reducing wood fuel consumption and saving money for the school district. 

A standard “currency” for savings attributable to wood energy has been in terms 

of the number of teaching positions saved. Delta/Greely School District reported 

that savings from the first 3 years of operation allowed at least one new teaching 

position to be established (Tressel 2016). Furthermore, the educational benefits for 

students learning to operate a wood energy system at a high school are not to be 

overlooked, including moisture content measurements, wood properties, and the 

environmental benefits of using renewable biomass energy.

These study results 

may benefit Delta/

Greely schools in 

Alaska because they 

provide operating 

data under a range of 

conditions, outdoor 

temperatures, and 

heating loads.
15

Combustion Efficiency and Emissions Analysis for a School Wood Energy System in Interior Alaska

Results of this study will also benefit the broader wood energy community 

in Alaska because similar systems are either under construction or have recently 

started being used. For example, a system in Tok, Alaska, has much of the same 

equipment and infrastructure (though it also includes an electrical cogenerating 

unit). Potential wood energy adopters will be able to learn firsthand lessons in 

optimizing wood energy system performance, evaluating combustion gas analysis, 

and determining economic benefits. Several Alaska schools (including those in Tok, 

Thorne Bay, and Coffman Cove) have added wood-energy-heated greenhouses as 

an efficient use of excess thermal load. These greenhouses increase the quantity 

of locally produced and consumed food, while also eliminating lengthy transport 

distances. Efficient wood energy operations will ultimately save money for schools 

and other adopters, which could be used for additional employment or other constructive purposes.

Metric Equivalents

When you know: Multiply by: To find:

Feet (ft) .305 Meters

Gallons (gal) 3.78 Liters

Tons (ton) 907 Kilograms

British thermal units (Btu) 1,050 Joules

Degrees Fahrenheit (°F) .56(°F – 32) Degrees Celsius

Literature Cited

Andrews, L. 2018. Up to 3,000 gallons of fuel oil spilled in ‘critical habitat’ north 

of Kodiak. Anchorage Daily News. 22 February. https://www.adn.com/alaskanews/environment/2018/02/27/up-to-3000-gallons-of-fuel-oil-spilled-in-criticalmarine-habitat-north-of-kodiak/. (31 August 2018).

Buchmayr, M.; Gruber, J.; Hargassner, M.; Hochenauer, C. 2015. Experimental 

investigation of the primary combustion zone during staged combustion of 

wood-chips in a commercial small-scale boiler. Biomass and Bioenergy. 81: 

356–363.

Caposciutti, G.; Barontini, F.; Antonelli, M.; Tognotti, L.; Desideri, U. 2018.

Experimental investigation on the air excess and air displacement influence on 

early stage and complete combustion gaseous emissions of a small scale fixed 

bed biomass boiler. Applied Energy. 216: 576–587.

Results of this study 

will also benefit the 

broader wood energy 

community in Alaska 

because similar 

systems are either 

under construction or 

have recently started 

being used.
16

GENERAL TECHNICAL REPORT PNW-RP-616

Carvalho, L.; Lundgren, J.; Wopienka, E.; Öhman, M. 2007. Challenges in 

small-scale combustion of agricultural biomass fuels. International Journal of 

Energy for a Clean Environment. 9(1–3): 127–142.

Dias, J.; Costa, M.; Azevedo, J.L.T. 2004. Test of a small domestic boiler using 

different pellets. Biomass and Bioenergy. 27(6): 531–539.

Dornburg, V.; Faaij, A.P.C. 2001. Efficiency and economy of wood-fired biomass 

energy systems in relation to scale regarding heat and power generation using 

combustion and gasification technologies. Biomass and Bioenergy. 21(2): 91–108.

Eskilsson, D.; Rönnbäck, M.; Samuelsson, J.; Tullin, C. 2004. Optimisation of 

efficiency and emissions in pellet burners. Biomass and Bioenergy. 27(6): 541–546.

Fournel, S.; Marcos, B.; Godbout, S.; Heitz, M. 2015. Predicting gaseous 

emissions from small-scale combustion of agricultural biomass fuels. 

Bioresource Technology. 179: 165–172. 

Garcia-Maraver, A.; Zamorano, M.; Fernandes, U.; Rabaçal, M.; Costa, M. 

2014. Relationship between fuel quality and gaseous and particulate matter 

emissions in a domestic pellet-fired boiler. Fuel. 119: 141–152.

Granger, E. 2018. Rolled tanker spilled 800 gallons of fuel, could endanger Tanana 

River. Fairbanks Daily News- Miner. 9 March. http://www.newsminer.com/news/

local_news/rolled-tanker-spilled-gallons-of-fuel-could-endanger-tanana-river/

article_237ed578-2376-11e8-a251-ff6da145f237.html. (31 August 2018).

Grueskin, Z. 2018. Cleanup continues for fuel spills in Savoonga and Nome. 

Alaska Public Media. 20 April. https://www.alaskapublic.org/2018/04/20/

cleanup-continues-for-fuel-spills-in-savoonga-and-nome. (31 August 2018).

Hedberg, E.; Kristensson, A.; Ohlsson, M.; Johansson, C.; Johansson, P.-A.; 

Swietlicki, E.; Vesely, V.; Wideqvist, U.; Westerholm, R. 2002. Chemical and 

physical characterization of emissions from birch wood combustion in a wood 

stove. Atmospheric Environment. 36: 4823–4837.

Hukkanen, A.; Kaivosoja, T.; Sippula, O.; Nuutinen, K.; Jokiniemi, J.; Tissari, 

J. 2012. Reduction of gaseous and particulate emissions from small-scale wood 

combustion with a catalytic combustor. Atmospheric Environment. 50: 16–23.

Johansson, L.S.; Leckner, B.; Gustavsson, L.; Cooper, D.; Tullin, C.; Potter, A. 

2004. Emission characteristics of modern and old-type residential boilers fired 

with wood logs and wood pellets. Atmospheric Environment. 38(25): 4183–4195.
17

Combustion Efficiency and Emissions Analysis for a School Wood Energy System in Interior Alaska

Johansson, L.S.; Tullin, C.; Leckner, B.; Sjovall, P. 2003. Particle emissions 

from biomass combustion in small combustors. Biomass and Bioenergy. 25(4): 

435–446.

Koyuncu, T.; Pinar, Y. 2007. The emissions from a space-heating biomass stove. 

Biomass and Bioenergy. 31(1): 73–79.

Krugly, E.; Martuzevicius, D.; Puida, E.; Buinevicius, K.; Stasiulaitiene, I.; 

Radziuniene, I.; Minikauskas, A.; Kliucininkas, L. 2014. Characterization of 

gaseous- and particle-phase emissions from the combustion of biomass-residuederived fuels in a small residential boiler. Energy & Fuels. 28(8): 5057−5066.

Lamberg, H.; Sippula, O.; Tissari, J.; Viren, A.; Kaivosoja, T.; Aarinen, A.; ́

Salminen, V.; Jokiniemi, J. 2017. Operation and emissions of a hybrid stove 

fueled by pellets and log wood. Energy & Fuels. 31(2): 1961−1968.

Míguez, J.L.; Morán, J.C.; Granada, E.; Porteiro, J. 2012. Review of 

technology in small-scale biomass combustion systems in the European market. 

Renewable and Sustainable Energy Reviews. 16(6): 3867–3875.

Mitchell, E.J.S.; Lea-Langton, A.R.; Jones, J.M.; Williams, A.; Layden, P.; 

Johnson, R. 2016. The impact of fuel properties on the emissions from the 

combustion of biomass and other solid fuels in a fixed bed domestic stove. Fuel 

Processing Technology. 142: 115–123.

Nicholls, D.L. 2009. Wood energy in Alaska—case study evaluations of selected 

facilities. Gen. Tech. Rep. PNW-GTR-793. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research Station. 33 p.

Obaidullah, M.; Dyakov, I.V.; Thomassin, J.D.; Duquesne, T.; Bram, S.; 

Contino, F.; De Ruyck, J. 2014. CO emission measurements and performance 

analysis of 10 kW and 20 kW wood stoves. Energy Procedia. 61: 2301–2306.

Ozgen, S.; Caserini, S.; Galante, S.; Giugliano, M.; Angelino, E.; Marongiu, 

A.; Hugony, F.; Migliavacca, G.; Morreale, C. 2014. Emission factors from 

small scale appliances burning wood and pellets. Atmospheric Environment. 

94: 144–153.

Ozil, F.; Tschamber, V.; Haas, F.; Trouvé, G. 2009. Efficiency of catalytic 

processes for the reduction of CO and VOC emissions from wood combustion in 

domestic fireplaces. Fuel Processing Technology. 90: 1053–1061.

Pilusa, T.J.; Huberts, R.; Muzenda, E. 2013. Emissions analysis from combustion 

of eco-fuel briquettes for domestic applications. Journal of Energy in Southern 

Africa. 24(4): 30–36.
18

GENERAL TECHNICAL REPORT PNW-RP-616

Roy, M.M.; Dutta, A.; Corscadden, K. 2013. An experimental study of 

combustion and emissions of biomass pellets in a prototype pellet furnace. 

Applied Energy. 108: 298–307.

Serrano, C.; Portero, H.; Monedero, E. 2013. Pine chips combustion in a 50 kW 

domestic biomass boiler. Fuel. 111: 564–573.

Tressel, Z. 2016. Delta Junction wood chip heating. Anchorage, AK: Alaska 

Energy Authority. 2 p.

U.S. Environmental Protection Agency [US EPA]. 2018. Air emissions factors 

and quantification—AP-42: compilation of air emissions factors. https://

www.epa.gov/air-emissions-factors-and-quantification/ap-42-compilation-airemissions-factors. (31 August 2018).

Vermont Energy Investment Corporation [VEIC]. 2017. Biomass Energy 

Resource Center community-scale database. https://www.biomasscenter.org/

database. (7 May 2018).

Zhang, X.; Chen, Q.; Bradford, R.; Sharifi, V.; Swithenbank, J. 2010.

Experimental investigation and mathematical modelling of wood combustion in a 

moving grate boiler. Fuel Processing Technology. 91(11): 1491–1499.
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