Emissions from Small-Scale Combustion of Biomass Fuels - Extensive Quantification and Characterization

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Emissions from small-scale combustion of biomass fuels - extensive quantification and characterization

Christoffer Boman Anders Nordin Marcus Öhman Dan Boström

Energy Technology and Thermal Process Chemistry Umeå University

Roger Westerholm

Analytical Chemistry, Arrhenius Laboratory Stockholm University

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Emissions from small-scale combustion of biomass fuels - extensive quantification and characterization

Christoffer Boman1, Anders Nordin1, Roger Westerholm2, Marcus Öhman1, Dan Boström1

1Energy Technology and Thermal Process Chemistry, Umeå University, SE-901 87 Umeå, Sweden

2Analytical Chemistry, Arrhenius Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden

STEM-BHM (P12648-1 and P21906-1)

Umeå, February 2005

SUMMARY

This work was a part of the Swedish national research program concerning emissions and air quality ("Utsläpp och Luftkvalitet") with the sub-programme concerning biomass, health and environment ("Biobränlen, Hälsa, Miljö" - BHM). The main objective of the work was to systematically determine the quantities and characteristics of gaseous and particulate emissions from combustion in residential wood log and biomass fuel pellet appliances and report emission factors for the most important emission components. The specific focus was on present commercial wood and pellet stoves as well as to illustrate the potentials for future technology development. The work was divided in different sub- projects; 1) a literature review of health effects of ambient wood smoke, 2) design and evaluation of an emission dilution sampling set-up, 3) a study of the effects of combustion conditions on the emission formation and characteristics and illustrate the potential for emission minimization during pellets combustion, 4) a study of the inorganic characteristics of particulate matter during combustion of different pelletized woody raw materials and finally 5) an extensive experimental characterization and quantification of gaseous and particulate emissions from residential wood log and pellet stoves.

From the initial literature search, nine relevant health studies were identified, all focused on effects of short-term exposure. Substantial quantitative information was only found for acute asthma in relation to PM10. In comparison with the general estimations for ambient PM and adverse health effects, the relative risks were even stronger in the studies where residential wood combustion was considered as a major PM source. However, the importance of other particle properties than mass concentration, like chemical composition, particle size and number concentration remain to be elucidated.

A whole flow dilution sampling set-up for residential biomass fired appliances was designed, constructed and evaluated concerning the effects of sampling conditions on the emission characteristics. Robust and applicable sampling conditions were identified and the system was then used in the following emission studies within the project.

Emission factors for a large number of gaseous and particulate components were determined for different residential wood log and pellet fired stoves as functions of variations in fuel, appliance and operational properties. Considerable variability of emission performance for wood log stoves was determined, with potentially high emissions of products of incomplete combustion (PIC) like CO, methane, NMVOC, PAH and soot during specific combustion conditions. However, by proper technical and/or operational measures the emission performance can be rather well controlled, and a significant potential for further technical development and improvement of the emission performance exists. The emissions of PIC as well as PM from the wood log stove were generally considerably higher compared to those from the pellet stoves. The use of upgraded biomass fuels, combusted under controlled conditions therefore gives advantageous conditions for optimization of the combustion process. Accordingly, present fuel pellets technology is well suited for the residential marked but also provides possibilities for further improvements of the combustion technology and further minimization of the emissions of PIC, especially at low load operation.

The extensive characterization of hydrocarbons included 34 specific VOC´s and 48 specific PAH´s. Beside methane, ethene, acetylene benzene were the most dominant VOC´s and the dominating PAH´s were in all cases phenantrene, fluoranthene and pyrene. Typical emission factors during "normal" conditions in the wood log stove of 100 mg/MJfuel for NMVOC and 3600 µg/MJfuel for PAHtot can be compared with typical

variations in the pellet stoves of 2-20 mg/MJfuel for NMVOC and 10-200 µg/MJfuel of PAHtot, respectively.

The PM was in all cases (wood log and pellet appliances) dominated by fine (<1µm) particles with mass median and count diameters in the range of 100-300 nm and 50-250 nm respectively as well as number concentrations in the range of 4.6*1012- 14 1.1*10 /MJfuel, with a trend of increase particle sizes at poorer combustion performance. The minor coarse fraction (1-25% of PM mass) consisted of carbonaceous unburned fuels residues with inclusions of calcium containing grains (1-10 µm). Total PM emissions for the wood log stove varied in the range of 37-160 mg/MJfuel and for the pellet stove in the range of 15-46 mg/MJfuel. During optimized combustion of biomass pellets, the fine PM totally consists of fine inorganic particles with mass median diameters between 100 and 120 nm and emission factors at 15-20 mg/MJfuel. When burning different woody raw materials the inorganic fine particles is dominated by alkali salts like KCl, K3Na(SO4)2 and K2SO4. Beside the alkali compounds, zinc is found in a more complex form than e.g ZnO, ZnCl2 and ZnSO4. However, the formation mechanism and exact phase composition remain to be determined.

SAMMANFATTNING

Detta projekt ingick som en del i det omfattande svenska forkningsprogrammet "Utsläpp och Luftkvalitet" med underprogrammet "Biobränsle, Hälsa, Miljö" (BHM) som finansierats av Energimyndigheten. Huvudsyftet med det föreliggande projekt var att systematiskt kvantifiera och karakterisera utsläppen av gas- och partikelformiga föroreningar till luften vid förbränning i småskaliga ved- och pelletseldade anläggningar och rapportera emissionsfaktorer för de dominerande emissionskomponenterna. Fokuset i arbetet med emissionsfaktorer var på dagens komersiella teknik vad gäller ved- och pelletskaminer men även att visa på potentialen för framtida teknik. Arbetet, som pågått under åren 2001-2004, delades in i olika delprojekt; 1) litteraturgenomgång kring hälsoeffekter av exponering för vedrelaterade luftföroreningar, 2) design, konstruktion och utvärdering av en provtagningsuppstälning som bygger på utspädning av rökgaserna, 3) experimentell systematisk studie av hur emissionskarakteristiken påverkas av förbränningsförhållanden vid pelletseldning och samtidigt visa på potentialen för framtida pelletsteknik, 4) studie av den oorganiska karakakteristiken på partikelutsläppen vid förbränning av pellets med olika råvaror (stamved, hyggesavfall och bark) och slutligen 5) en omfattande experimentell studie med kvantifiering och karakterisering av gas- och partikelformiga utsläpp från dagens ved- och pelletseldade kaminer.

I den inledande litteraturgenomgången kring hälsoeffekter kunde endast 9 relevanta epidemiologiska studier identifieras i vilka alla fokuserade på effekter av korttidsexponering. Substansiell kvantitativ information återfanns endast för relationen mellan akuta astmabesvär och ökning av PM10-halten i omgivningsluften. Sammantaget var dock skattningarna av de relativa riskerna för olika korttidseffekter i samband med exponering för vedrelaterade partikelföroreningar högre i de funna studierna jämfört med de allmänna riskbedömningar som gäller för partiklar i omgivningsluft. Betydelsen av andra partikelmått än masskoncentration, t ex kemisk sammansättning, partikelstorlek och partikelantal är dessutom inte klarlagda i dagsläget.

För att genomföra det omfattande arbetet med emissionsstudier konstruerades en provtagningsuppställning för småskaliga anläggningar som bygger på utspädning och kylning av rökgaserna. I ett inledande projekt studerades hur olika förhållanden i denna utspädningstunnel påverkade emissionskarakteristiken. Robusta och applicerbara provtagingsförhållanden bestämdes och uppställningen användes sedan i samtliga efterföljande mätkampanjer inom projektet.

Emissionsfaktorer för ett stort antal gas- och partikelformiga utsläppskomponenter bestämdes för olika småskaliga ved- och pelletseldade kaminer som funktion av olika bränsle- , anläggnings- och handhavandevariabler. En betydande variation i emissionsprestanda kunde konstateras vid eldning i vedkaminer med potentiellt mycket höga emissioner av oförbrända produkter som CO, metan, NMVOC, PAH och sot under specifika omständigheter. Med rätt anpassning av vedbränsle, teknik och handhavande kan dock sådana situationer sannolikt undvikas och utsläppen relativt väl kontrolleras på rimliga nivåer. Utsläppen av oförbrända produkter var generellt betydligt lägre vid eldning i pelletskaminer jämfört med vedkaminer. Studien visar således på de stora förutsättningar som användandet av förädlade biobränslen (t ex pellets) som eldas i väl anpassande anläggningar ger att optimera förbränningen och minska utsläppen av t ex CO, kolväten och sot. Även fast dagens pelletsutrustning är relativt väl fungerande med låga utsläpp generellt, finns dock ytterligare potential att reducera utsläppen av oförbrända produkter, speciellt vid låglast förhållanden.

Den omfattande karakteriseringen av kolväten i utsläppen innefattade 34 st VOC´s och 48 st PAH´s. Förutom metan var eten, acetylen och bensen de dominerande VOC komponenterna och de dominerande PAH komponenterna var generellt phenantrene, fluoranthene och pyrene. Typiska emissionsfaktorer för "normal" eldning i vedkaminer på 100 mg/MJbränsle för NMVOC (non-methane VOC) och 3600 µg/MJfuel för PAHtot kan jämföras med motsvarande typiska emissioner i pelletskaminer på 2-20 mg/MJfuel för NMVOC och 10-200 µg/MJbr för PAHtot.

Partikelutsläppen dominerades i samtliga lägen (ved- och pelletseldning) av submikrona (<1 µm) partiklar med massmedian- och antalsmediandiametrar kring 100-300 nm och 12 14 50-250 nm respektive samt i antalskoncentrationer mellan 4.6*10 -1.1*10 /MJbränsle. Under sämre (mer ofullständiga) förbränningsförhållanden tenderade partikelstorleks- fördelningen att förskjutas uppåt. Den mindre fraktionen (1-25 vikts-%) av grövre partiklar (>1 µm) bestod av oförbrända kolhaltiga bränslerester med en mindre andel kalciuminnehållande korn (1-10 µm). De totala partikelemissionerna från ved- och pelletkaminerna varierade mellan 37-160 mg/MJbränsle och 15-46 mg/MJbränsle, respektive. Vid optimerad förbränning av träpellets ligger partikelemissionerna på 15-20 mg/MJbränsle som då består enbart av submikrona oorganiska partiklar med massmediandiametrar på 100-120 nm. Det oorganiska partikulära materialet i utsläppen vid förbränning av pellets från skogsbaserade råvaror består till största delen av alkalisalter, t ex KCl, K3Na(SO4)2 och K2SO4. Förutom dessa alkalisalter återfinns zink som det dominerande spårämnet i partiklarna sannolikt i en mer komplex form än ren zinkoxid, zinkklorid eller zinksulfat, men bildningsmekanismer och kemisk (fas)sammansättning återstår att bestämma.

ACKNOWLEDGEMENTS

The authors would like to acknowledge a number of persons and institutions for valuable contribution in different parts of the project, although not specified here but in the enclosed separate papers or manuscripts.

This work was a part of the Swedish national research program "Utsläpp och Luftkvalitet" with the specific sub-program concerning biomass, health and environment, called "Biobränlen, Hälsa, Miljö" (BHM), financed by the Swedish Energy Agency.

The work was also initially supported by the Center for Environmental Research in Umeå (CMF).

CONTENTS

1 Introduction 1 1.1 Background 1 1.2 Objectives 1

2 Summary of designs, experimental procedures and results 3 2.1 Health effects review (Appendix 1) 3 2.2 Dilution sampling set-up (Appendix 2) 4 2.3 Emission minimization - "future technology" (Appendix 3) 6 2.4 Inorganic PM from combustion of different woody raw materials (Appendix 4) 8 2.5 Wood log and pellet stoves - emission characterization and quantification (Appendix 5) 10 2.6 Emission factors - Summary 13

3 Conclusions 16

References 18

Publications 19

Appendices (1-5)

1 INTRODUCTION

1.1 Background

Biomass is a sustainable energy source with significant potentials for replacing fossil fuels and electricity for heating purposes, not at least in the residential sector. Present residential wood combustion can, however, be a significant source of ambient urban air pollution and the potential environmental health effects of e.g. volatile organic compounds (VOC), polycyclic aromatic hydrocarbons (PAH) and particulate matter (PM) are of special concern. Ambient exposure to these pollutants in general has been associated with different health effects such as cardiopulmonary disease/mortality and cancer risks [1]. It has further been shown that the PM from combustion sources is dominated by fine (<1 µm) particles and there is an increasing interest in their formation mechanisms, characteristics and specific implications to human health [2, 3]. Compared to modern technology, the majority of the presently used wood fired appliances often suffer from poorly optimized conditions, resulting in considerable emissions of products of incomplete combustion (PIC), e.g. CO, hydrocarbons and soot particles. New and upgraded biomass fuels provide possibilities of more controlled and optimized combustion with less emission of PIC. Wood pellets are generally a clean, dry and easily fed fuel to be used in special boilers, burners and stoves on the residential market. For future health impact assessments, regulatory standards and evaluations concerning present and future residential biomass combustion, a solid qualitative and quantitative knowledge of the emissions from different sources is of vital importance. Although, some limited work has been performed previously, there is still a strong need for detailed characterization and quantification of the emissions from residential biomass appliances when using different fuels and combustion techniques.

During the years of 2001-2004, an extensive national research program concerning emissions and air quality ("Utsläpp och Luftkvalitet") with a sub-program concerning biomass, health and environment ("Biobränslen, Hälsa, Miljö" - BHM) has been in progress financed by the Swedish Energy Agency. The overall objective with the BHM- program was to describe the influence of the use of biofuels for heat production in small and medium-sized combustion appliances regarding the emission distribution, air quality and potential health effects. Additionally, the program should aim to describe the situation in a possible future with increased use of biomass and also concern the potential for technology development. Within the residential sector, both water based heating systems (i.e. boilers) and air based heating systems (i.e. stoves and other fireplaces) were included for emission quantification and characterization, and the work was therefore divided between different national research groups. Further information concerning the BHM-research program and the included projects can be found elsewhere [4].

1.2 Objectives

The present work, which was a part of the BHM-program, had the main objective to systematically determine the quantities and characteristics of gaseous and particulate emissions from biomass combustion in residential appliances, as well as to report emission factors for the most important emission components. The focus was on present commercial wood log and fuel pellet stoves as well as to illustrate the potentials for future technology regarding emission minimization.

In addition to the work with emission studies, a literature review of adverse health effects related to ambient wood smoke exposure, were initially accomplished. The literature review contributed to the evaluation of the present knowledge concerning air pollution from biomass combustion and related adverse health effects, and was used as background material in the health effects cluster within the BHM-program.

The work included in this report was divided in five separate sub-projects which reports are enclosed in appendix 1-5. Appendix 5 is a manuscript including an extensive amount of emission data for the studied wood and pellet stoves. The sixth appendix is a summarizing proceeding presented at the international bioenergy conference in Rome, Italy 2004.

The separate sub-projects in appendix 1-5 had the following specific objectives: i) To review the scientific literature concerning adverse health effects from ambient air pollution in relation to residential wood combustion in modern society and if possible extract quantifications for the associations. ii) To design a dilution sampling system for emission measurements in residential biomass fired appliances and determine the influence of dilution sampling conditions on the characteristics and distributions of PM and PAH. iii) To determine the effects of temperature and residence time on the formation/ destruction and characteristics of products of incomplete combustion, especially PAH, and particulate matter during combustion of conifer stem-wood pellets in a laboratory fixed-bed reactor (<5 kW). iv) To determine the mass size, elemental and inorganic phase distributions of particulate matter from residential combustion appliances using different pelletized woody biomass fuels. v) To determine the characteristics and quantities of gaseous and particulate emissions from combustion in residential wood log and pellet stoves, and report emission factors for the most important emission components.

2 2 SUMMARY OF DESIGNS, EXPERIMENTAL PROCEDURES AND RESULTS

2.1 Health effects review (Appendix 1)

Initially, a literature review of reported adverse health effects from ambient air pollution in relation to residential wood combustion (RWC) in modern society was performed. The work focused on epidemiological studies from settings where RWC was mentioned as an important air pollution source. Beside epidemiological studies, also animal toxicology and controlled human studies contribute to the knowledge of the toxicity of different compounds or pollution mixtures. However, no controlled human exposure study has been reported dealing with wood smoke. On the other hand, a significant number of animal toxicology studies with wood smoke have been reviewed [5] as well as some epidemiological studies [6]. These and other relevant aspects of RWC, air quality and human health were also briefly summarized.

From the literature search, nine relevant studies were identified, all focused on effects of short-term exposure such as asthma admissions, respiratory symptoms, daily mortality and lung function. In Table 1, information of these nine studies and their results are briefly summarized.

Table 1. Summary of addressed health effects and brief results from the reviewed papers. The reference numbers in the table refers to the references in the full article (Appendix 1).

Effect Reference Subjects age Pollution indicators Significant positive associations with

Daily mortality 38 all ages PM10, SO2, CO, NOx PM10

Asthma symptoms 39 5-13 years PM10, PM1, SO2, CO PM10, PM1, CO

Asthma hospital admissions 40 < 65 years PM10, PM2.5, CO, SO2, O3 PM10, PM2.5, CO, O3

41 < 18 years PM10, PM2.5, CO, NO2 PM10, PM2.5, CO

Asthma emergency room visits 36 all ages PM10, NO2, O3, CoH PM10

43 all ages PM10, SO2, O3 PM10

Peak expiratory flow and 35 children PM10 PM10 (in asthmatics)

respiratory symptoms 42 > 55 (COPD) PM10, SO2, CO, NO2 PM10, NO2

Forced expiratory volume in 37 children Fine particulate, PM2.5 PM2.5 (in asthmatics) 1 sec and forced vital capacity (grade 3 to 6)

Substantial quantitative information was only found for acute asthma in relation to particulate matter with an aerodynamic diameter of <10 µm (PM10). In comparison with the present general estimations for ambient PM and adverse health effects (Figure 1), the relative risks are even stronger in the studies where residential wood combustion is considered as a major PM source. Thus, there seem to be at least no reason to assume that the PM effects in wood smoke polluted areas are weaker than elsewhere. Ambient exposure to combustion related fine particles in general have also been associated with cardiopulmonary disease and mortality as well as cancer risks, but the importance of other particulate properties than mass concentration, like chemical composition, particle size and number concentration remain to be elucidated.

3 Asthma hospital admissions WHO * Pope and Dockery * APHEA 2 (0-14 years) APHEA 2 (15-64 years) Sheppard et al (< 65 years) Norris et al (< 18 years) Lipsett et al (all-mean temp) ** Lipsett et al (all-low temp) ** Schwartz et al (< 65 years) **

Asthma symptoms WHO * Pope and Dockery * Yu et al (5-13 years)

Cough WHO * Vedal et al (6-13 years)

1.00 1.02 1.04 1.06 1.08 1.10 1.12 1.14 1.16 1.18 1.20 * summary estimates ** emergency room visits Relative risks

3 Figure 1. Relative risks for different morbidity outcomes associated with a 10 µg/m increase in PM10 (particulate matter with an aerodynamic diameter <10 µm) with 95% confidence intervals as error bars. Studies where wood smoke is considered as a major air pollution source are shown by closed columns, and comparison estimates are represented by open columns. Detailed reference information is given in the full article (Appendix 1).

2.2 Dilution sampling set-up (Appendix 2)

Traditionally, emission measurements have been performed in undiluted hot (e.g. 120- 180°C) flue gases. However, in some aspects traditional sampling in raw flue gases suffers from severe drawbacks for example related to; transient conditions with varying flue gas flows, and the condensable nature of many of the semi-volatile organic compounds. This may lead to different characteristics and distributions between the raw hot gases and the ambient air, as well as erroneous results and incorrect conclusions. Sampling at lower temperatures and under constant flow conditions is therefore desirable. The most extensively used and general applicable method is based on whole flow dilution in a dilution tunnel where a constant flow of diluted flue gases enables constant volume sampling (CVS). The methodology of using a CVS system was first designed and used for gasoline fuelled vehicles in the beginning of the 1970´s [7] and has then been used and evaluated extensively. While the use of this kind of dilution sampling has become the standard reference method for internal engine emission measurements, the experiences and use of such methods for stationary sources and solid fuel combustion are presently more limited although some work have been performed. One example is the dilution sampling system defined by U.S. Environmental Protection Agency (US EPA) [8], which has been used for characterization of fine particulate matter and organic compounds from residential wood stoves. In Norway, there is also a standardized method with a dilution tunnel for determination of particulate emissions from residential wood stoves and furnaces [9], which in many aspects resembles the US EPA method.

4 An appropriate CVS system for residential biomass combustion appliances was therefore successfully designed constructed and evaluated (Figure 2). The effects of sampling conditions on the characteristics and distribution of PM and PAH as well as concentrations of CO, organic gaseous carbon (OGC) and NO, were evaluated by a factorial experimental design. Robust and optimal sampling variable settings for the sampling method were also determined. Dilution ratio (3-7), sampling temperature (45- 75°C) and dilution tunnel residence time (1-3 s) were varied during combustion of typical softwood pellets combusted in a residential stove. The sampling of PAH was performed using quartz fiber filters for particulate PAH with subsequent polyurethane foam (PUF) plugs for semi-volatile PAH.

Pressurized HEPA filters dilution air

Air heating

T dP T T Exhaust gases

T PM/PAH filter P Cyclone Excess dilution Dust air flow O2 filter PUF CO2 Impactor Water CO (DLPI) cooler Combustion NO appliance OGC Water Flow cooler Drying agent Gas meter meter Drying agent O2 CO2

DMA 2 Ejector dilutors (1st heated) CPC

Figure 2. Schematic illustration of the experimental dilution set-up for constant volume sampling (CVS). In the present study the distance between the mixing point (A) and sampling probes (B) were varied between 0.5 and 3.0 m and the temperature of the equipment for PM and PAH sampling (within the dashed line) were varied between 45 and 75°C according to the experimental design. Sampling hose for OGC was heated to approximately 150°C. The SMPS (DMA+CPC) system was not used in the present design and evaluation study, but in the following emission studies (Appendix 3, 5 and 6).

The results showed that the sampling conditions did not influence the PMtot concentrations, MMD, CO and NO. However, positive correlations to dilution ratio were found for the concentrations of OGC, PAHtot and specific PAH compounds, but the variations in emission levels were relatively small and insignificant compared to the considerably higher emissions from commercial wood log appliances. The distributions between particulate and gas phase were influenced for 13 of the 45 analyzed PAH compounds, with significant negative correlations between fractions of particulate bound material and increased sampling temperature for anthracene, 1-methylphenantrene, fluoranthene and pyrene. The variations in dilution tunnel residence time showed no significant effects for any of the studied emission parameters. Total PAH concentrations

5 (particulate + semi-volatile PAH) were not influenced by the variations in sampling temperature. The dominating PAH compounds were in all cases phenanthrene, fluoranthene and pyrene, which constituted approximately 70% of the total amount of PAH. The concentrations of those compounds were positively correlated with dilution ratio but no effects of variations in temperature were found.

The conditions and variations in the presently studied CVS system with a lower dilution ratio and somewhat longer residence time are also probably rather appropriate to closely simulate the conditions for residential combustion emissions. To minimize potential recovery losses and maximize the detection possibilities, the results from the present study suggests sampling at 50±5°C with a dilution ratio of 3-4 times as robust and applicable sampling conditions.

2.3 Emission minimization - "future technology" (Appendix 3)

Present wood log appliances often suffer from extensive temperature in-homogeneities and short residence times at sufficiently high temperatures, resulting in excessive amounts of PIC. Recent preliminary results have shown that the waste amounts of simple gaseous PIC (e.g. CO and gaseous hydrocarbons) relatively easily can be avoided by isothermal, high temperature combustion of biomass pellets. However, no similar data is available for PAH and PM and many PAH components are generally considered to be relatively thermally stable.

In the present project the effects of temperature and residence time in a laboratory fixed- bed pellets reactor (Figure 3) on the emission formation/destruction and characteristics and of PIC, especially PAH, and PM was studied. Temperature and residence after the bed section in the reactor time was varied according to statistical experimental designs covering the ranges 650-970°C and 0.5-3.5 s, respectively. Also in this study, typical softwood pellets were used and combusted at 2 kWfuel, corresponding to a typical situation for small houses during wintertime. The previously designed and evaluated dilution sampling setup was used and the emission responses were; CO, organic gaseous carbon (OGC), NO, VOC including 20 specific compounds, PAH (particulate + semi-volatile PAH) including 43 specific compounds, PMtot, particle mass and count median diameter (MMD and CMD) and particle number concentration.

Temperature was negatively correlated with the emissions of all studied PIC, i.e. higher temperature resulted in lower PIC emissions with no significant effect of residence time. For NO a reversed correlation with temperature was determined, i.e. increasing emissions with increasing temperature. The PMtot emissions were in the range of 15-20 mg/MJfuel with no effect of variations in temperature or time determined. The PM was totally dominated by fine (<1 µm) particles consisting of potassium, oxygen, sulfur, carbon, chlorine, sodium and zinc. Fine particle mass and count median diameters as well as number concentration were significantly influenced of residence time, i.e. increased time resulted in increased particle sizes and decreased number concentrations. The mass and count median diameters varied in the range of 100-180 nm and 80-105 nm respectively, with number concentrations in the range of 3- 13 7*10 /MJfuel.

Figure 3. Schematic illustration of the experimental fixed-bed pellets reactor (<5 kWfuel).

The results in the present study have shown that it exist a significant potential to obtain optimized combustion conditions in residential pellet appliances with in principal a total depletion of PIC´s by high temperature, intensive, air rich and well mixed conditions in the bed section. During such conditions the importance of residence time at high temperature was shown to be limited, although isothermal conditions during 0.5-1.0 s would be preferable for optimized results in practical situations. Such high temperature conditions in the fuel bed, which resembles the conditions in present commercial pellet appliances, may, however, increase the risk for potential ash related problems like slagging, especially during combustion of some qualities of more ash rich pellet fuels [10]. If such fuels are to be used and potential ash related problems should be prevented, air staging with lower fuel bed temperatures is preferable and the importance of sufficiently long residence time in the post-combustion zone for minimizing the emissions of PIC will therefore increase.

The extremely low emissions of PAH and other PIC can probably be explained by a prevention of the formation or instant oxidation rather then thermal destruction in the post-combustion zone. Although these results and conclusions are exciting and encouraging they may be consequences of both the excess surface temperatures of the burning fuel pellets and more reactor specific conditions, emphasizing the need for further verification studies and technology development work.

7 1.6 1. phenanthrene 2. retene 1 2 3. flouranthene 1.4 3 4. 9,10-dimethylanthracene 4 5. pyrene 6. anthracene 1.2 5 7. 2-methylphenanthrene 8. 2-phenylnaphtalene 9. 3-methylphenanthrene 1 10. chrysene 6 11. 2-methylanthracene 12. cyclopenta(cd)pyrene 0.8 7 8 0.6 Background

Concentration (ug/Nm3) concentration 0.4 9 10 11 0.2 12

0 650 700 750 800 850 900 950 Temperature (deg C)

Figure 4. Concentrations of separate PAH compounds in the flue gases during combustion of softwood pellets as a function of temperature in the post-combustion zone after the fuel bed.

2.4 Inorganic PM from combustion of different woody raw materials (Appendix 4)

The presently used raw materials for production of fuel pellets are generally stem-wood assortments (≈95%) such as sawdust, planer shavings or dried chips from sawmills and the wood working industry while bark, agricultural residues and other forest fuels only occasionally occurs [11]. However, in a future with an increasing utilization of the forest resources, also other types of wood forest based materials (e.g. bark and logging residues) might be used for pellet production.

Therefore, the mass size, elemental and inorganic phase distributions of PM from different residential combustion appliances using different pelletized biomass fuels was determined. In addition, chemical equilibrium model calculations of the combustion process were used to interpret the experimental findings. Six different typical pellet fuels of softwood sawdust, logging residues and bark were combusted in three commercial pellet burners (10-15 kW). Total PM mass concentrations as well as particle mass size distributions were determined using a 13-stage low-pressure impactor with a pre- cyclone. The PM was analyzed for morphology (using ESEM), elemental composition (using EDS) and crystalline phases (using XRD). Selected impactor samples were also analyzed by time-of-flight secondary ion mass spectrometry (TOF-SIMS), X-ray photoelectron spectroscopy (XPS) and X-ray absorption fine structure (XAFS) spectroscopy. These analyses methods provide chemical structural information and were used as complementary tools to ESEM/EDS and XRD for possible further detailed chemical characterization.

The emitted particles were mainly found in the fine sub-micron mode with mass median aerodynamic diameters between 0.20 and 0.39 µm, and an average PM1 of 92.3±6.2%. Minor coarse mode fractions (>1 µm) were present primarily in the experiments with bark and logging residues. Relatively large and varying fractions (28-92%) of PM were

8 determined to be products of incomplete combustion. The inorganic elemental compositions of the fine particle samples were dominated by K, Cl and S with minor amounts of Na and Zn (Figure 5). The relative distribution of these five elements within the fine mode in the different cases was rather homogeneous, only with a small trend of increased sulfur content with increased particle sizes in some cases (Figure 6). The dominating alkali phase detected was KCl with minor but varying amounts of K3Na(SO4)2 and in some cases also K2SO4.

90 90 S0 S0 80 80 S6 S6 70 L0 70 L0 L6 L6 60 60 B0 B0 50 B6 50 B6

40 40 weight-% weight-%

30 30

20 20

10 10

0 0 C O Na Mg Si P S Cl K Ca Mn Fe Zn C O Na Mg Al P S Cl K Ca Mn Fe Zn

Figure 5. Elemental composition of the fine PM from burner B (left) and burner C (right). Standard deviations within the fine mode (i.e. different impactor substrates) are shown as error bars. For burner B (using Al-foils) Al was excluded from the analysis, and for burner C (using quartz fiber filters) Si was excluded.

Fresh sawdust pellets (S0) Fresh bark pellets (B0) 60 60 Na Na K K 50 50 S S Cl Cl 40 40 Zn Zn

30 30

20 20

10 10 Rel. elemental distribution (atomic-%) distribution elemental Rel. Rel. elemental distribution (atomic-%) distribution Rel. elemental 0 0 0.13 0.21 0.33 0.53 0.84 0.13 0.21 0.33 0.53 0.84 Geometric mean diameter (um) Geometric mean diameter (um)

Figure 6. Typical relative elemental distributions of the five elements present within the fine mode on a carbon and oxygen free basis, illustrated by the results during combustion of pelletized softwood sawdust (left) and bark (right) in a residential burner. The average distribution (in atomic-%) is shown for each impactor substrate number 3-7 (0.13-0.84 µm) with standard deviations as error bars.

The results further indicated zinc to be almost fully volatilized in the reducing atmospheres of burning fuel particles and presumably forming a more complex solid phase than pure zinc oxide or some zinc salt. However, the formation mechanism and exact phase composition remain to be elucidated. With some constraints, the results also showed that the amounts and speciation of the inorganic PM seemed to be quite similar to what was predicted by chemical equilibrium calculations.

9 2.5 Wood log and pellet stoves - emission characterization and quantification (Appendix 5)

Present residential wood combustion can be a major air pollution source mainly of hydrocarbons and PM in urban environments. The potential for increased use of biomass and reduction of emissions by using new technologies is, however, significant. Despite the previously well documented extent and importance of these pollution sources and components, relatively limited information is available concerning detailed emission characteristics and quantification for different appliances and fuels. The characteristics and quantities of gaseous and particulate emissions from combustion in residential wood log and pellet stoves were therefore determined and emission factors for the most important emission components reported in an extensive experimental study. A large number of gaseous and particulate components were studied for wood log and pellet stoves with systematic variations in fuel, appliance and operational properties. Birch wood logs were combusted in a wood stove under different simulated operation conditions (modes) and conifer logs of pine and spruce were also included for comparison. Two conifer sawdust pellets (6 and 8 mm in diameter) were combusted with variations in chimney draught and fuel load.

Considerable variability of emission performance in the wood log stove was determined, with potentially very high emissions of products of incomplete combustion (PIC) during specific conditions (Figure 7). However, by proper technical and/or operational measures the emission performance can be rather well controlled, and a significant potential for further development and optimization therefore exists. 134000

8000 CO

7000 TOC NMVOC

6000 Methane PM tot

5000 PAH tot

4000

3000

2000

1000

0 Mode 1a Mode 1b Mode 2 Mode 3 Figure 7. Comparison between the average emissions of the main components from the wood stove during different operation modes, given as mg/MJfuel (PAH given as µg/MJfuel). TOC given as CH4- equivalents. The conditions in the different modes aimed to simulate; Mode 1 (a) = "Normal" stove and fuel conditions (2 experiments with birch wood), Mode 1 (b) = "Normal" stove and fuel conditions (2 experiments with conifer wood), Mode 2 = "Cold and air starved" combustion with moist and large logs (2 experiments with birch wood), Mode 3 = "Intensive" combustion with high draught and extra dry and cleaved logs (2 experiments with birch wood).

10 The emissions of PIC as well as PM from the wood log stove were generally considerably higher than from the pellet stoves. Accordingly, the use of up-graded biomass fuels with controlled combustion conditions gives advantageous conditions for optimization of the combustion process compared to traditional batch wise firing of wood logs. There is, however, still a potential for further minimization of PIC emissions in residential pellets applications, especially at low loads.

The extensive characterization of hydrocarbons included 34 specific VOC´s and 48 specific PAH´s. Beside methane, ethene, acetylene and benzene were the most dominant VOC´s and the dominating PAH´s were in all cases phenantrene, fluoranthene and pyrene. Fine sub-micron particles dominated in all cases the PM with 80-95% as PM1. The minor coarse fraction consisted of carbonaceous unburned fuels residues with inclusions of calcium containing grains (1-10 µm). Fine particle mass median and count diameters were in the range of 100-300 nm and 50-250 nm respectively with number 12 14 concentrations at 4.6*10 -1.1*10 /MJfuel (Figure 11-13).

1000 100 Stove A (1.7 kW) Intermediate 90 Stove A (5 kW) Start-up 800 80 Stove B (6kW)

70 Stove B (Start-up)

600 60

400 40 dm/dlog(Dp) [mg/Nm³] dm/dlog(Dp) dm/dlog(Dp) [mg/Nm³] 30

200 20

0 0 0.01 0.1 1 10 0.01 0.1 1 10 Aerodynamic Diameter Dp [µm] Aerodynamic Diameter Dp [µm]

Figure 11. Typical particle mass size distribution for the wood log stove (left) and pellet stoves (right), measured by the LPI. Upper impactor stage and pre-cyclone not included. (concentrations are normalized to 10% O2)

Pellet stove A (5 kW) Pellet stove A (1.7 kW) 1.E+09 1.E+09 8 mm, 5 Pa 8 mm, 5 Pa 8 mm, 30 Pa 8 mm, 30 Pa 6 mm, 5 Pa 6 mm, 5 Pa 1.E+08 6 mm, 30 Pa 1.E+08 6 mm, 30 Pa ] ] -3 -3 -3 n n

1.E+07 1.E+07 dN/dlog(Dp) [cm dN/dlog(Dp) dN/dlog(Dp) [cm dN/dlog(Dp) 1.E+06 1.E+06

1.E+05 1.E+05 10 100 1000 10 100 1000 Mobility Diameter Dp [nm] Mobility Diameter Dp [nm]

Figure 12. Average fine particle number size distributions for one of the pellet stoves measured by the SMPS. For each case, the size distributions during experiments with variations in pellet fuels (6 and 8 mm) and chimney draught (5 and 30 Pa) are included.

Wood stove (Exp 6) 1.E+09 Start-up Intermediate 1.E+08 Burn-out ] -3 n 1.E+07

1.E+06 dN/dlog(Dp) [cm dN/dlog(Dp)

1.E+05

1.E+04 10 100 1000 Mobility diameter (Dp) [nm] Figure 13. Typical average fine particle number size distributions for the wood stove during different phases of a combustion cycle, measured by the SMPS. The tail of the intermediate distribution below 25 nm is most probably an artefact of the operation (ventilation) of the CPC. (concentrations are normalized to 10% O2)

The emissions of PMtot varied in the range of 37-160 mg/MJfuel for the wood log stove and 15-46 mg/MJfuel for the pellet stoves. Previous studies of "optimized" combustion of softwood pellets with almost a total depletion of PIC have shown that the emissions of inorganic PM are in the range of 15-20 mg/MJfuel (see Appendix 3 and [12]). Assuming similar ash composition and volatilization conditions therefore confirms that the PM from the wood stove experiments were dominated by PIC (i.e. carbonaceous material) which also was illustrated by the high content of carbon detected by SEM/EDS in the fine PM. The elemental composition of the fine PM from the birch wood combustion is shown in Figure 14.

100 5.0 Weight-% Weight-% 90 4.5 Mole-% Mole-% 80 4.0

70 3.5

60 3.0

50 2.5

40 2.0

30 1.5

20 1.0

10 0.5

0 0.0 C O Na Mg Si P S Cl K Ca Cr Mn Fe Ni Cu Zn As Rb Na Mg Si P S Cl K Ca Cr Mn Fe Ni Cu Zn As Rb

Figure 14. Elemental composition of fine mode particles in the emissions from birch wood combustion in the wood stove (mode 1, exp 2, intermediate phase). Results presented as average values of 3 area analyses (100*100 µm) on impactor stage 3 (Dg=130 nm) with standard deviation shown as error bars. In the left diagram all analyzed elements are shown, and in the right diagram a different scaling is used to get a better resolution of the less abundant elements (C and O not shown). Aluminum was excluded from the analysis since Al-foils were used as sampling substrates.

12 The amount of carbonaceous material was relatively low in the pellet stove PM and in Figure 15, the relative elemental composition of inorganic elements in the fine particles from the pellet stoves are shown on a carbon and oxygen free basis. In accordance with previous data from residential pellet burners, the fine inorganic PM was dominated by potassium, sulfur and chlorine in the form of K2SO4, K3Na(SO4)2 and KCl. Sodium and in some cases also zinc were also found as important elements in the fine PM. Alkali carbonates were not detected in the analysis but could not be excluded as additional alkali phases in some cases. The degree of volatilization, subsequent gas-to-particle conversion and final phase composition may, however, differ significantly and is influenced by combustion temperature, local air to fuel ratio and fuel properties/composition.

100 Stove B (6 mm) 90 Stove B (8 mm) 80 Stove A 5 kW (8 mm) Stove A 1.7 kW (8 mm) 70

50 Mole-% 40

0 Na Mg Si P S Cl K Ca Cr Mn Fe Ni Cu Zn As Rb

Figure 15. Relative elemental composition (on a C, O and Al free basis) for the fine mode particles in the emission from combustion of softwood pellets in two pellet stoves. Results presented as average values of 3 area analyses (100*100 µm) on impactor stage 3 (Dg=130 nm) with standard deviation shown as error bars.

2.6 Emission factors - Summary

Based on the extensive characterization and quantification work within the project with residential wood log and pellet stoves, as discussed above, emission factors and their variability can be extracted. As discussed previously, significant higher emissions, mainly of PIC, were generally determined during wood log combustion than pellets combustion. However, significant variations in emission factors were also determined for specific appliances as a function of variations in combustion conditions, fuel properties and operation. In Figure 16, the average emissions of the main components determined during the different campaigns are presented. To better illustrate the emission levels and their variations for the pellet stoves, the emissions factors determined at different fuel loads are presented in Figure 17.

CO (mg/MJ) NOx (mg/MJ) 8000 80

7000 70

6000 60

5000 50

4000 40

3000 30

2000 20

1000 10

0 0 Wood log stove Pellet stoves (tot) Wood log stove Pellet stoves (tot)

Methane (mg/MJ) NMVOC (mg/MJ) 1800 3000

1600 2500 1400

1200 2000

1000 1500 800

600 1000

400 500 200

0 0 Wood log stove Pellet stoves (tot) Wood log stove Pellet stoves (tot)

PMtot (mg(MJ) PAHtot (ug/MJ) 400 250000

350 200000 300

250 150000

200

150 100000

100 50000 50

0 0 Wood log stove Pellet stoves (tot) Wood log stove Pellet stoves (tot)

Figure 16. Summary of average emission factors of the main components determined for the wood log and pellet stoves, with the interval shown for highest and lowest average values determined during different experiments in the present campaigns.

14 900

Pellet stoves (high load) 800 Pellet stoves (low load) 700

600

500

400

300

200

100

0 CO NOx NMVOC Methane PMtot PAHtot

Figure 17. Summary of average emission factors for the pellet stoves during high (5-6 kWfuel)) and low (~2 kWfuel) load operation, with the interval shown for highest and lowest average values determined during different experiments in the present campaigns.

15 3 CONCLUSIONS

Based on the results in the separate sub-projects included in this report, the following general conclusions with significant implications for future environmental health impact assessments, legislations and technical development can be draw:

• Emissions from residential biomass combustion include a number of air pollutants with potential adverse health effects, and an increasing interest concerning their potential implications to human health can be seen. A limited number of dedicated epidemiological studies have been performed but substantial quantitative information is found for acute asthma in relation to PM10. Ambient exposure to combustion related fine particles in general have also been associated with cardiopulmonary disease and mortality as well as cancer risks, but the importance of other particulate properties than mass concentration, like chemical composition, particle size and number concentration remain to be elucidated.

• Emission factor ranges for different residential biomass fired stoves have been determined as functions of variations in fuel, appliance and operational properties. There was a considerably variability of emission performance during different fuel, combustion and operation conditions. Considerably emissions of products of incomplete combustion (PIC), e.g. CO, hydrocarbons and soot, can obtain during specific situations during batch wise firing of wood logs. However, the emissions of PIC can be rather well controlled by proper technical and/or operational measures, and a significant potential for further development and optimization therefore exists.

• The emissions of PIC as well as PM from the wood stove were in all cases shown to be considerably higher compared to those from the pellet stoves. Accordingly, the use of up-graded pellets biomass fuels, combusted under continuous and controlled conditions give advantageous combustion conditions compared to traditional batch wise firing of wood logs. There is, however, still a significant potential for further minimization of PIC emissions in future pellets technology, especially at low load operation.

• The importance of high temperature (>850°C) in the bed zone with intensive, air rich and well mixed conditions with isothermal conditions for 0.5-1.0 s in the post combustion zone was illustrated for small-scale softwood pellets combustion to obtain complete combustion conditions with almost a total depletion of PIC.

• Extensive VOC and PAH characteristics were determined for a wide range of residential biomass combustion appliances during different fuel and operational conditions. Beside methane, ethene, acetylene and benzene were the dominating VOC´s and phenantrene, fluoranthene and pyrene were in the dominating PAH´s.

• The PM from residential pellet appliances combusted is totally dominated by fine (<1 µm) particles in the range of 100-300 nm (aerodynamic diameter) depending on combustion conditions. The minor and varying fraction of coarse (>1 µm) particles, consisting of carbonaceous unburned fuel residues and mineral grains (e.g CaO and/or CaCO3) which is more pronounced when burning e.g. bark and logging residues.

• During optimized and complete combustion of biomass fuels, the emissions of inorganic particulate matter still remain. This inorganic PM is dominated by fine (<1

16 µm) particles deriving from volatilized ash forming elements, with mass concentrations below in the range of 15-20 mg/MJfuel.

• The fine inorganic PM is dominated by potassium, sodium, sulfur and chlorine in varying amounts strongly depending on fuel composition, mainly found in the form of KCl, K3Na(SO4)2 and K2SO4. Besides the alkali material, zinc is found in considerable amounts presumably in a more complex form than ZnO, ZnCl2 and ZnSO4. During combustion, zinc is to large degree volatilized within the reducing atmospheres of the burning fuel particles, subsequently forming fine particles. However, the formation mechanism and exact phase composition remain to be determined.

• The present problems with potentially high emissions of PIC (e.g. CO, hydrocarbons and soot) from residential biomass (i.e. wood log) combustion can be avoided by relatively simple technical and/or operational measures and future small-scale biomass technology shows significant potentials.

• Considering the use of modern and "low-emitting" residential biomass combustion technologies using different biomass fuels and their potential implications for air quality and human health, some of the most urgent questions at issue seem to be to determine the formation mechanisms, detailed chemical characteristics and potential environmental health effects for the alkali and trace element (e.g. zinc) containing fine particles.

17 REFERENCES

1. Holgate ST, Samet JM, Koren HS, Maynard R, editors. Air pollution and health. London: Academic Press; 1999.

2. Lighty JS, Veranth JM, Sarofim AF. Combustion aerosols: factors governing their size and composition and implications to human health. Journal of Air and Waste Management Association 2000;50(9):1565-1618.

3. Avakian MD, Dellinger B, Fiedler H, Gullet B, Koshland C, Marklund S, Oberdorster G, Safe S, Sarofim A, Smith KR, Schwartz D, Suk WA. The origin, fate and health effects of combustion by-products: a research framework. Environmental Health Perspectives 2002;110(11):1155-1162.

4. Swedish Energy Agency. National research programme "Biobränslen, Hälsa och Miljö" (BHM). Preliminary Report 2003. Available at http://www.itm.su.se/bhm. (In Swedish)

5. Zelikoff JT, Chen LC, Cohen MD, Schlesinger RB. The toxicology of inhaled woodsmoke. Journal of Toxicolology and Environmental Health, Part B 2002;5:269- 82.

6. Larson TV, Koenig JQ. Wood smoke: emissions and noncancer respiratory effects. Annual Review of Public Health 1994;15:133-56.

7. Habbi K. Characterization of particulate lead and vehicle exhausts-experimental techniques. Environmental Science and Technology 1970;4:239-59.

8. U.S. Environmental Protection Agency. Method 5 G - Determination of particulate matter emissions from wood heaters (dilution tunnel sampling location). Federal Register 2000;65(201):61867-76.

9. Enclosed wood heaters - Smoke emission - Part 2: Determination of particulate emission. Norwegian Standard NS 3058-2, 1994. p. 1-12.

10. Öhman M, Boman C, Hedman H, Nordin A, Boström D. Slagging tendencies of wood pellet ash during combustion in residential pellet burners. Biomass and Bioenergy 2004;27:585-596.

11. Hillring B, Vinterbäck J. Wood pellets in the Swedish residential market. Forest Products Journal 1998;48(5):67-72.

12. Wiinikka H. Particle emissons from wood pellet combustion. Licentiate thesis. Luleå University of Technology, Luleå, Sweden, 2003.

18 PUBLICATIONS

(Appendix 1-5)

1. Boman BC, Forsberg AB, Järvholm BG. Adverse health effects from ambient air pollution in relation to residential wood combustion in modern society.

Scandinavian Journal of Work, Environment and Health 2003;29(4):251-260.

2. Boman C, Nordin A, Westerholm R, Pettersson E. Evaluation of a constant volume sampling set-up for residential biomass fired appliances - influence of dilution conditions on particulate and PAH emissions.

Submitted to Biomass and Bioenergy

3. Boman C, Pettersson E, Lindmark F, Öhman M, Nordin A, Westerholm R. Effects of temperature and residence time on emission characteristics during fixed- bed combustion of conifer stem-wood pellets.

Manuscript

4. Boman C, Nordin A, Boström D, Öhman M. Characterization of inorganic particulate matter from residential combustion of pelletized biomass fuels.

Energy and Fuels 2004;18:338-348.

5. Boman C, Pettersson E, Nordin A, Westerholm R, Boström D. Gaseous and particulate emissions from combustion in residential wood log and pellet stoves - experimental characterization and quantification.

Manuscript

Licentiate thesis:

Particulate matter and products of incomplete combustion from residential biomass pellet appliances - emissions and potential for future technology

Christoffer Boman, Umeå University, June 2003

APPENDICES

[Manuscript, Submitted to Biomass and Bioenergy]

Evaluation of a Constant Volume Sampling Set-up for Residential Biomass Fired Appliances - Influence of Dilution Conditions on Particulate and PAH Emissions

Christoffer Bomana*, Anders Nordina, Roger Westerholmb, Esbjörn Petterssona,c

a Energy Technology and Thermal Process Chemistry, Umeå University, SE-901 87 Umeå, Sweden b Department of Analytical Chemistry, Arrhenius Laboratory, Stockholm University, S-106 91 Stockholm, Sweden c Energy Technology Centre, Box 726, SE-941 28 Piteå, Sweden

* Corresponding author: Telephone; +46-90-786 6756 Fax; +46-90-786 9195 E-mail: [email protected]

Abstract Increased concerns about particulate matter (PM) and polycyclic aromatic hydrocarbons (PAH) emissions from residential biomass combustion and their potential health effects, motivates detailed emission measurements under controlled conditions. Traditional sampling in raw flue gases can suffer from drawbacks mainly related to transient flows and the condensable nature of organic compounds. Whole flow dilution with constant volume sampling (CVS) is an alternative method but different sampling conditions may, however, influence the emission characteristics. The objective was to design a CVS system for emission measurements in residential biomass fired appliances and determine the influence of dilution sampling conditions on the characteristics and distributions of PM and PAH. Softwood pellets were combusted in a pellet stove with variations in; dilution ratio (3-7x), sampling temperature (45-75 °C), dilution tunnel residence time (2-4 s) and fuel load (2.3 and 4.8 kW) according to a statistical experimental design. The sampling conditions did not influence either the concentrations of PM, CO and NO or the particle size distribution. Variations in residence times had no significant effect on any studied emission parameter. However, increased concentrations of organic gaseous carbon (OGC), PAHtot and 38 specific PAH compounds were observed with increased dilution ratio. The distribution between the particulate and semivolatile phase was influenced for 13 of the 38 analyzed PAH compounds, with increased particulate bound material at lower sampling temperature. No temperature effect was observed for the concentrations of PAHtot or the dominating PAH compounds, i.e. phenanthrene, fluoranthene and pyrene. The results also suggest sampling at 50±5°C and 3-4 times dilution as robust and applicable conditions. However, the sensitivity of draft variations on the combustion conditions in residential appliances makes further evaluation of the whole flow dilution methodology necessary.

Keywords: combustion, pellets, emission sampling, dilution, particulate matter, polycyclic aromatic hydrocarbons

Introduction

Residential wood log combustion (RWC) is considered to be a major emission source of local ambient air pollution, especially for particulate matter (PM) and hydrocarbons, such as volatile organic compounds (VOC) and polycyclic aromatic hydrocarbons (PAH) [1, 2]. PAH is a group of aromatic compounds that is formed during incomplete combustion and has been in particular focus mainly concerning the emissions from vehicles and RWC [2]. Some specific PAH compounds, especially benzo(a)pyrene, have been shown to be genotoxic in animal studies and are therefore also considered as potentially carcinogenic in humans [2-4].

Combustion related PM can be fractionated as inorganic ash material, soot and condensable organic material (e.g. PAH). The main part of the PM from residential biomass combustion consists of fine submicron particles (<1 µm) by number and often also by mass, and there is an increasing interest in their characteristics and implications to human health [5]. Exposure

1 to ambient PM in general and fine combustion related particles in particular have recently been associated with cardiopulmonary disease and mortality [6-8].

New and upgraded biomass fuels have become more common and especially fuel pellets are well suited for the residential biomass market, providing possibilities of more automated and optimized systems with higher combustion efficiency and less products of incomplete combustion (PIC), i.e. CO, hydrocarbons and soot. Although some work has been performed [9-16] there is still a need for detailed characterization and quantification of the emissions under controlled and standardized conditions, using different fuels and combustion techniques, not the least concerning particulate matter and PAH.

Traditionally, these emission measurements have been performed in undiluted hot (e.g. 150- 200°C) flue gases, which certainly is an appropriate method in many cases. However, in some aspects, traditional sampling in raw flue gases may suffer from several drawbacks; 1) the amount of total emissions during several cycles can for example not be correctly measured under transient combustion conditions with varying flue gas flows, 2) varying flue gas flows will cause problems with claims of isokinetic sampling of particles and 3) the condensable nature of many of the semivolatile organic compounds in the emissions may lead to different characteristics and distributions (i.e. particulate/gas phase) between the raw hot gases and the ambient air. Sampling at lower and more realistic temperatures is therefore desirable and dilution of the flue gases is a suitable alternative method. A primary condition when performing emission measurements at ambient or near-ambient temperature is that sufficient dilution is needed to avoid condensation of water.

Within the area of internal engine combustion, different kinds of dilution systems for characterization have been used for emission measurement R&D for the last three decades. The most extensively used and general applicable method is based on whole flow dilution in a dilution tunnel where a constant flow of diluted flue gases enables constant volume sampling (CVS). The methodology of using a CVS system was first designed and used for gasoline fuelled vehicles in the beginning of the 1970´s [17] and has then been used extensively [18-21]. While CVS has become the standard reference method for internal engine emission measurements, the experiences and use of such methods for stationary sources and solid fuel combustion are presently more limited. U.S. Environmental Protection Agency (US EPA) has defined a dilution sampling system [22], which has been used for characterization of fine particulate matter and organic compounds from residential wood stoves [12]. The system consists of a hood above a chimney of a few meters where the flue gas is diluted with ambient (room) air sucked into a sampling duct. Similar dilution systems have also been developed and used for emission studies of different residential wood appliances [23-25]. In Norway, there is also a standardized method with a dilution tunnel for determination of particulate emissions from residential wood stoves and furnaces [26], which in many aspects resembles the US EPA method. A method with full flow dilution and CVS for characterization of particulate matter from small oil combustion sources has recently also been developed [27]. In a large number of diesel emission studies it has further been shown that different sampling conditions (e.g. dilution ratio, temperature and residence time) can have a significant influence on the emission characteristics and PM distributions [19, 20, 28- 30].

The objective of the present work was therefore to design a CVS system for emission measurements in residential biomass fired appliances and determine the influence of dilution sampling conditions on the characteristics and distributions of PM and PAH.

2 Experimental Procedure

A typical softwood pellet fuel of a mixture of >90% Scots pine (Pinus sylvestris) and the rest of Norway spruce (Picea abies) with a diameter of 8 mm was combusted in a commercial residential pellet stove. The characteristics of the pellet fuel used is given in Table 1, and corresponded well with the general composition of woody biomass fuels [31]. The stove was a typical modern pellet stove that previously has been certified according to the national certification criteria "P-marking" at the Swedish National Testing and Research Institute (SP) [32].

Table 1 Characteristics of the used softwood sawdust pellet fuel.

Parameter Unit Result Diameter mm 8 Effective heating value MJ/kg of dry weight 19.3 Moisture content % of fuel weight 7.7 Ash content % of dry weight 0.3 Amount of additives % of dry weight 0 Carbon content % of dry weight 51.6 Hydrogen content % of dry weight 6.3 Oxygen content % of dry weight 41.8 Nitrogen content % of dry weight <0.1 Chlorine content % of dry weight <0.01 Sulfur content mg/kg of dry weight 84.7

In accordance with the aspects of emission sampling from combustion sources previously discussed, a new dilution setup for CVS was designed. A schematic diagram of the experimental setup and sampling system is shown in Figure 1. The setup consists of a 5.0 meter long horizontal stainless steel tube with an inner diameter of 160 mm. A variable speed controlled fan in one end of the tunnel creates a constant flow through the tunnel and in the other end ambient dried, high-efficiency particulate air (HEPA) filtered and temperature conditioned air is used as dilution air which is drawn into the tunnel from a controlled excess flow. Just before the entrance of the flue gases, the dilution air is made turbulent by a number of triangular plates, which provide good mixing of the two flows. Temperature measurements in the cross-section of the tunnel at the sampling points showed a homogeneous temperature profile which indicated that the two flows was mixed.

The variables that were included in the evaluation of the experimental setup were; dilution ratio, sampling temperature and dilution tunnel residence time. In addition to those three variables, fuel load was included as a forth variable. The dilution ratio was defined as the volume ratio between the total diluted flow and the undiluted flue gas and calculated by dividing the CO2 concentration in the flue gases with the CO2 in the diluted gas. Sampling temperature was defined as the temperature of the sampled gas as well as the sampling probes and PM equipment. The residence time between mixing and sampling was varied by using six different sampling probe holes present at the dilution system between 0.5 and 3.0 m from the mixing point. Continuous standard gas measurements of O2, CO2, CO, NO/NOx and OGC (organic gaseous carbon measured with flame ionization detector), were also performed in the dilution tunnel as well as O2 and CO2 in the raw flue gas before dilution. Experiments were performed during 1.5-2 hours under continuous combustion both at high (4.8 kW) and low (2.3 kW) constant fuel load of the stove, to evaluate the sampling system both under "good" combustion conditions (i.e. high load) and somewhat "poorer" combustion conditions (i.e. low load).

3 Pressurized HEPA filters dilution air Air heating

T dP T T Exhaust gases

B A

T PM/PAH filter P Cyclone Excess dilution Dust air flow O2 filter PUF CO2 Impactor Water CO (DLPI) cooler Combustion NO appliance OGC Water Flow cooler P Drying agent T Gas meter meter Drying agent O2 CO2

Fig 1. Schematic illustration of the experimental dilution system for constant volume sampling (CVS). In the present study the distance between the mixing point (A) and sampling probes (B) were varied between 0.5 and 3.0 m and the temperature of the equipment for PM and PAH sampling (within the dashed line) were varied between 45 and 75°C according to the experimental design. Sampling hose for OGC was heated to approximately 150°C.

4 To structure the experimental work and enable maximum interpretation possibilities, a statistical experimental design was used. This type of design of experiments is based on an optimum mathematical scheme in which all potentially important variables are changed systematically and significantly facilitating the identification of the separate effects of the different variables [33, 34]. The experiments were performed according to a full (24) factorial design [34] with 16 experimental runs and 3 center replicates. To be able to fully evaluate the effects of sampling conditions at low and high load separately, 3 additional center replicates were performed for both high and low load. Two of the experimental points at high load (5 kW) had to be excluded because the dilution tunnel was too short to obtain the required residence time and dilution ratio simultaneously in those experiments. Thus, a total number of 23 experiments were performed. The software program MODDE 5.0 [35] was used to facilitate the design of the experiments and evaluation of the results. In Table 2, the factors and their design levels are shown with their high (+), medium (0) and low (-) values given.

Table 2 Factors and their design levels.

Abbreviation (+) (0) (-)

Sampling temperature (ºC) Temp 75 60 45 Dilution ratio (x) Dil 7 5 3 Residence time (s) Time 4 3 2 Fuel load (kW) Load 2.3 3.55 4.8

The following parameters were used as responses to determine the influence of sampling conditions on the characteristics and distribution of PM and PAH; PMtot mass concentration, fine particle mass median diameter (MMD), PAHtot concentration and fraction of particle bound PAH. The distributions between particulate and semivolatile phase were studied for PAHtot as well as for 38 separate PAH compounds. In addition to the aforementioned responses, the standard gaseous combustion by-products CO, OGC and NOx were also included in the evaluation.

Sampling of PMtot mass concentrations was performed isokinetically in the dilution tunnel using conventional dust sampling equipment with glass fiber filters (MG 160, Munktell Filters, Sweden). The particle mass size distributions were determined by isokinetic sampling using a 13-stage low-pressure cascade impactor (LPI, Dekati Ltd, Finland) equipped with a pre- cyclone. The LPI separates particles by aerodynamic diameter between approximately 0.03- 10 µm. Aluminum foils were used as impactor substrates and all PMtot filters impactor substrates and cyclone cups were analyzed gravimetrically before and after sampling with an analytical balance (±0.01 mg) after at least 8 hours of conditioning in a desiccator. Particulate PAH emission samples were collected on the previously mentioned glass fiber filters for PMtot. Polyurethane foam (PUF) plugs (75 mm diameter x 50 mm, 60 PPI; Specialplast AB, Sweden) were used for sampling of the semivolatile PAH. The PUF plugs were washed prior to use as described elsewhere [18]. After sampling, the filter and PUF samples were Soxhlet extracted separately with acetone (p.a.; Merck, Germany) (225 mL) for 12h. The extract was evaporated under reduced pressure and stored at -18°C until analysis. The crude extracts were fractionated into two fractions before chemical analysis, as described previously [36] but with other solvent volumes used. The PAH fraction was analyzed by gas chromatography-mass spectrometry (GC-MS) for quantification as described in detail elsewhere [37]. Prior to fractionation, internal standards were added (d10-phenanthrene, d10-pyrene, d12-benz(a)pyrene, picene, and 2,2'-binaphthyl) for quantification. A PAH standard mixture with internal standards was used for the determination of retention times and response factor calculations.

5 Results and Discussion

In Table 3, a summary of the experimental design and main emission responses is given. The effects of the sampling variables on the emission characteristics were evaluated by statistical methods according to Box et al. [33] and Eriksson et al. [34]. Separate PLS (Projection to Latent Structures by means of Partial Least Squares Analysis) [38] models were determined for each of the dependent responses. PLS is a commonly used projection- based regression method for analyzing multivariate data where a quantitative relationship between a variable matrix (X) and a response matrix (Y) may exist [39]. The effects of sampling conditions were determined for low (2.3 kW) and high (4.8 kW) loads separately for each of the responses. For MMD and fraction of particle bound PAH as well as the distribution between particulate and gas phase for each PAH compound the effects of sampling conditions were also evaluated for the whole design matrix, with fuel load included as a variable. From the statistical evaluation, it was clear that the variations in sampling conditions did not significantly influence the concentrations of CO and NO, which is in accordance with the expectations. Also no influence on MMD or PMtot concentrations could be seen. However, concentrations of PAHtot and OGC were influenced during load low operation, mainly positively correlated to dilution with a similar, smaller but significant, effect of sampling temperature. The effect for OGC and PAHtot may indicate that the combustion conditions were somewhat affected by variations in dilution ratio, i.e. higher dilution ratio decreased the combustion efficiency with increased OGC and PAH concentrations. However, no similar effect could be seen for the CO concentrations. Overall, the variations determined for OGC (gaseous hydrocarbons) and PAHtot concentrations were relatively small and insignificant compared to the considerable higher emission levels from typical commercial wood stove appliances [12, 14, 15].

The three most dominant PAH compounds were in all cases phenanthrene, fluoranthene and pyrene, which constituted 70±5.1 and 71±4.4% of the total amount of PAH (particulate + semivolatile) at low and high load respectively. The concentrations of those three compounds were all also positively correlated with dilution ratio. However, no significant effect between the total concentrations of these PAH compounds and sampling temperature was found. This indicates that the recovery of the sampling method for PAHtot is unaffected of the variations in sampling temperature studied in this work. Variations in dilution tunnel residence time showed no significant effect for any of the studied emission parameters. The distribution between particulate and semivolatile phase was to some extent influenced for 13 of the 38 analyzed PAH compounds. Potential counteracting artifacts concerning the partitioning between particulate and semivolatile phase may occur as a result of revolatilization of particulate material and adsorption of gaseous PAH on the filters. However, by assuming these effects to be rather constant during the different experiments, some trends concerning could be seen. Using PLS, statistical significant negative correlations between fractions of particulate bound material and increased sampling temperature were determined for 4 of these compounds, i.e. anthracene, 1-methylphenantrene, fluoranthene and pyrene. In Table 4, a summary of the 38 analyzed PAH compounds and their distribution between particulate and semivolatile phase during different sampling conditions is given. The compounds were divided into four groups; 1) always found as particulate bound, 2) always found in semivolatile phase, 3) influenced by sampling conditions and 4) not detected in any case. At ambient conditions, PAH compounds with low molecular weight (i.e. 2-3 ring aromatics) are mainly in the gas phase, 4 ringed compounds are both in gas and particle phase and heavier 5-6 ringed PAH´s are mainly particulate associated [40]. The tendency to vaporize/condense for different PAH compounds are, however, not direct correlated to its molecular weight since the presence of substituents on and/or atoms like N/S within the aromatic ring structure can substantially change a compounds volatility. This was clearly illustrated in the present study by the different behavior of substituted and non-substituted analogues as well as between fluorene and its sulfur containing analogue dibenzothiophene.

6 Table 3 Summary of the experimental design and all emission responses, except the separate PAH compounds. Average excess O2 for the different experiments varied in the range of 11-15%.

a Exp. Run Load Temp. Dil. Time CO OGC NO PMtot MMD PAHtot Particle bound order (kW) (°C) (times) (s) (mg/MJfuel) (mg/MJfuel) (mg/MJfuel) (mg/MJfuel) (nm) (µg/MJfuel) PAH (%) 1 12 2.3 45 ± 5 4.4 2.1 314 15 31 81 137 17 95 2 13 2.3 75 ± 5 3.8 2.2 250 12 33 74 132 12 93 3 14 2.3 45 ± 5 6.6 1.8 383 26 29 46 130 42 71 4 15 2.3 75 ± 5 6.4 2.1 323 23 29 35 130 32 52 5 18 2.3 45 ± 5 4.3 4.0 218 9 31 64 136 8 100 6 19 2.3 75 ± 5 2.9 4.7 379 21 33 77 138 42 39 7 20 2.5 45 ± 5 7.0 3.4 243 18 30 42 131 27 93 8 21 2.5 75 ± 5 5.6 4.1 309 22 29 34 125 33 50 9 16 2.3 60 ± 5 4.6 3.0 243 13 29 32 136 15 57 10 17 2.3 60 ± 5 4.4 3.1 310 17 29 36 130 17 60 11 23 2.3 60 ± 5 4.9 3.0 312 17 33 37 130 21 82

12 6 4.6 45 ± 5 4.7 2.3 100 5 35 13 136 2 87 13 7 4.5 75 ± 5 4.9 2.7 152 8 33 11 133 5 15 14b 3 5.0 45 ± 5 7.8 2.6 63 8 31 15 141 13 99 15 4 4.9 75 ± 5 7.1 2.7 62 7 33 13 131 5 3 16 9 4.5 45 ± 5 4.1 4.5 81 6 35 14 135 1 96 17 10 4.6 75 ± 5 3.6 5.4 104 6 36 13 133 1 60 18c 4.6 45 ± 5 7 5 19c 4.5 75 ± 5 7 5 20b 2 4.7 60 ± 5 6.5 4.1 87 9 31 20 146 19 68 21 5 4.9 60 ± 5 5.7 4.1 52 6 32 13 117 3 98 22 8 4.5 60 ± 5 4.8 4.0 94 6 32 20 131 - -

23b 1 3.7 60 ± 5 5.2 4.3 82 7 32 19 - 13 89 24 11 3.6 60 ± 5 4.0 4.3 144 8 32 11 141 3 57 25 22 3.6 60 ± 5 4.6 4.3 220 11 35 18 134 8 80 a The very low OGC concentrations in the diluted gas (1-3 ppm) resulted in somewhat low accuracy. b A different air fan was used than in the other experiments, i.e. may be irrelevant results especially for PAH. c Missing experiments because of restrictions in the experimental setup, i.e. too short dilution tunnel.

Table 4 Summary of the 38 analyzed PAH compounds and their distribution between particulate and semivolatile phase during different sampling conditions. In increasing order sorted by molecular weight within each group respectively.

Always found as particulate bound Always found in semi-volatile Influenced by sampling conditions Not detected in any case phase Dibenzothiophene 2-Methylfluorene Fluorene 9-Methylanthracene 9,10-Dimethylanthracene 3,6-Dimethylphenanthrene Phenanthrene Benz(b)fluorene Benz(a)fluorene Anthracene Benzo(b)fluoranthene 2-Methylpyrene 3-Methylphenanthrene Indeno(1,2,3-cd)fluoranthene 4-Methylpyrene 2-Methylphenanthrene Dibenz(a,h)anthracene 1-Methylpyrene 2-Methylanthracene Benzo(ghi)fluoranthene 9-Methylphenanthrene Benzo(c)phenanthrene 1-Methylphenanthrene Benzo(b)naphto(1,2-d) thiophene 2-Phenylnaphthalene Cyclopenta(cd)pyrene 3,9-Dimethylphenanthrenea Benzo(a)anthracene Fluoranthene Chrysene Pyrene Benzo(k)fluoranthene Benzo(e)pyrene Benzo(a)pyrene Perylene Indeno(1,2,3-cd)pyrene Benzo(ghi)perylene Coronene

8 As mentioned in the introduction the sampling conditions can have a significant influence on the emission characteristics and particle distributions, and the potential formation of ultrafine (<0.01 µm) particles in the exhausts have been of special concern. Previous studies of diesel engine emissions have shown that sampling conditions normally used in CVS systems, i.e. dilution ratio of 10-20 times, dilution air temperature of 30-50°C and residence time of 1-1.5 seconds, constitutes the most favorable conditions considering nucleation and generation of ultrafine particles from gaseous sulfur and semivolatile hydrocarbons [20, 41]. It has also been claimed that the mixing ratio of vehicle exhausts in practice can be very high and up to 1000 times dilution within 1-2 seconds has been suggested [42]. In the present study the influence of dilution sampling conditions on the formation of ultrafine particles was not evaluated. However, the conditions and variations in the presently studied CVS system with a lower dilution ratio and somewhat longer residence time are probably appropriate to more closely simulate the conditions for residential combustion emissions.

Based on the results from the present study, sampling at 50±5°C with a dilution ratio of 3-4 times is suggested as robust and applicable sampling conditions to minimize potential recovery losses and maximize the detection possibilities.

Conclusions

• The variations in sampling conditions (dilution ratio, sampling temperature and dilution tunnel residence time) did not influence the PMtot concentrations or the particle mass median diameters. Also the concentrations of CO and NO were unaffected by the studied variations. • The concentrations of OGC and PAHtot as well as the concentrations of specific PAH compounds were influenced by sampling conditions, mainly by a positive correlation to dilution ratio. However, the variations in emission levels were in all cases relatively small and insignificant compared to the considerable higher emission levels from commercial wood stove appliances. • The distributions between particulate and semivolatile phase were influenced for 13 of the 38 analyzed PAH compounds. Significant negative correlations between fractions of particulate bound material and increased sampling temperature were found for anthracene, 1-methylphenantrene, fluoranthene and pyrene. • Variations in dilution tunnel residence time showed no significant effects for any of the studied emission parameters. • Concentrations of PAHtot were not influenced by the variations in sampling temperature (i.e. 45-75°C). • The three most dominant PAH compounds were in all cases phenanthrene, fluoranthene and pyrene, which constituted approximately 70±5% of the total amount of PAH. The concentrations of those compounds were positively correlated with dilution ratio but no effects of variations in temperature were found. • To minimize potential recovery losses and maximize the detection possibilities, the results from the present study suggests sampling at 50±5°C with a dilution ratio of 3-4 as robust and applicable sampling conditions.

Acknowledgement

Lena Elfver at the Department of Analytical Chemistry at Stockholm University is acknowledged for the analytical work concerning PAH and Fredrik Lindmark is acknowledged for valuable help during the experimental work. The financial support from the Center for Environmental Research in Umeå and the Swedish Energy Agency is finally gratefully acknowledged.

9 References

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[Manuscript]

Effects of Temperature and Residence Time on Emission Characteristics during Fixed- Bed Combustion of Conifer Stem-wood Pellets

Christoffer Bomana*, Esbjörn Petterssona,b, Fredrik Lindmarka, Marcus Öhmana, Anders Nordina, Roger Westerholmc

a Energy Technology and Thermal Process Chemistry, Umeå University, SE-901 87 Umeå, Sweden b Energy Technology Centre, Box 726, SE-941 28 Piteå, Sweden c Department of Analytical Chemistry, Arrhenius Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden

* Corresponding author: Telephone; +46-90-786 6756 Fax; +46-90-786 9195 E-mail: [email protected]

Abstract Residential wood combustion is considered to be a major emission source of products of incomplete combustion (PIC) like volatile organic carbons (VOC) and polycyclic aromatic hydrocarbons (PAH) as well as particulate matter (PM). Present wood log appliances often suffers from extensive temperature in-homogeneities and short residence times at sufficiently high temperatures, resulting in excessive amounts of PIC. Recent preliminary results have shown that the waste amounts of simple gaseous PIC (e.g. CO and gaseous hydrocarbons) relatively easily can be avoided by isothermal, high temperature combustion of biomass pellets. However, no similar data is available for PAH and PM and many PAH components are generally considered to be relatively thermally stable. The objective was to determine the effects of temperature and residence time on the formation/destruction and characteristics of PIC, especially PAH, and PM during combustion of conifer stem-wood pellets in a laboratory fixed-bed reactor (<5 kW). Temperature and residence time in the reactor after the bed section were varied according to statistical experimental designs covering the ranges 650-970°C and 0.5-3.5 s, respectively. A whole flow dilution setup with constant volume sampling were used and the emission responses were; CO, organic gaseous carbon (OGC), NO, VOC including 20 specific compounds, PAH (particulate + semi-volatile PAH) including 43 specific compounds, PMtot, particle mass and count median diameter (MMD and CMD) and particle number concentration. Temperature was negatively correlated with the emissions of all studied PIC, i.e. higher temperature resulted in lower PIC emissions with limited effects of residence time. For NO a reversed correlation with temperature was determined, i.e. increasing emissions with increasing temperature. The PMtot emissions were in the range of 15-20 mg/MJfuel with no effect of variations in temperature or time determined. The PM was totally dominated by fine (<1 µm) particles consisting of potassium, oxygen, sulfur, carbon, chlorine, sodium and zinc. Fine particle mass and count median diameters as well as number concentration were significantly influenced by residence time, i.e. increased time resulted in increased particle sizes and decreased number concentrations. The mass and count median diameters varied in the range of 100-180 nm and 80-105 nm respectively, with number concentrations 13 13 in the range of 3*10 -7*10 particles/MJfuel. Accordingly, the importance of high temperature (>850°C) in the bed zone with intensive, air rich and well mixed conditions with isothermal conditions for 0.5-1.0 s in the post combustion zone was illustrated for small-scale softwood pellets combustion to obtain complete combustion conditions with almost a total depletion of PIC, including all studied PAH compounds. However, during combustion of some qualities of more ash rich pellet fuels air staging with lower fuel bed temperatures is preferable to prevent potential ash related problems (e.g. slagging) and the importance of sufficiently long residence time for minimizing the emissions of PIC will increase. The extremely low emissions of PAH and other PIC can probably be explained by a prevention of the formation or instant oxidation rather then thermal destruction in the post-combustion zone and the results emphasize the need for further verification studies and technology development work.

Keywords: residential biomass combustion, pellets, emission minimization, appliance design, products of incomplete combustion, particulate matter, polycyclic aromatic hydrocarbons

1 Introduction

Residential combustion of biomass can often be a major local emission source of volatile organic compounds (VOC), polycyclic aromatic hydrocarbons (PAH) and particulate matter (PM). In many residential areas and smaller communities, there are severe problems with the air quality during wintertime. Ambient exposure to these air pollutants have also been associated with different adverse health effects, i.e. cardiopulmonary disease/mortality and cancer risks [1-4]. In Sweden, combustion processes are responsible for 38% of the non- methane VOC emissions, of which one fourth is estimated to derive from residential wood burning. Domestic heating is presently also responsible for 66% of the national total PAH emission [5]. The desired significant conversion from residential oil and electricity heating to extended use of renewable biomass fuels must therefore be accomplished by a contemporaneous development and employment of new combustion technologies minimizing the emissions of such products of incomplete combustion (PIC). Traditionally, combustion plants in general and residential wood log appliances in particular have suffered from extensive temperature in-homogeneities and short residence times at sufficiently high temperatures, resulting in excessive production of most PIC.

Upgraded biomass fuels (pellets and briquettes) are now readily available in several countries, enabling significantly improved control possibilities and prerequisites for more efficient combustion technologies. However, the emission performance and combustion efficiency in present pellet burners and stoves as well as the potential for further improvements have not been fully evaluated. Present residential pellet combustion techniques generally operates with high temperatures (1000-1100°C) in the fuel bed but relatively short residence times at high temperatures after the bed section. In a recent study the potential for minimization of simple gaseous PIC, like CO and total hydrocarbons (THC), was shown for pellet fired appliances by relatively simple measures, i.e. sufficiently high temperature (>850°C) and long residence time (>1s) [6]. However, similar data concerning the behavior of specific VOC´s and PAH’s, as well as detailed PM characteristics during such complete combustion are still not available. Formation and destruction of tars and PAH have recently been reviewed and many compounds are generally considered to need high temperature and reaction severities for thermal destruction [7, 8]. Actual controlled studies of the effects of combustion temperature, isothermal conditions and residence times in the post- combustion zone during firing of pelletized softwood fuels have not yet been reported.

The objective of the present work was therefore to determine the effects of temperature and residence time on the formation/destruction and characteristics of products of incomplete combustion, especially PAH, and particulate matter during combustion of conifer stem-wood pellets in a laboratory fixed-bed reactor (<5 kW).

Method and Material

Fuel and combustion setup A standard pelletizied softwood mixture of Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) was used as fuel throughout the work. The proximate and ultimate characteristics (Table 1) agreed well with corresponding typical characteristics of conifer stem-wood fuels [9].

2 Table 1 Characteristics of the pelletized softwood sawdust fuel. Parameter Unit Result Pellet diameter mm 6 Effective heating value MJ/kg of dry weight 19.2 Moisture content % of fuel weight 8.2 Ash content % of dry weight 0.4 Amount of additives % of dry weight 0 Carbon content % of dry weight 50.9 Hydrogen content % of dry weight 6.3 Oxygen content % of dry weight 42.4 Nitrogen content % of dry weight < 0.1 Chlorine content % of dry weight < 0.01 Sulfur content mg/kg of dry weight 68.1

An isothermal laboratory fixed-bed reactor, consisting of a vertical stainless steel tube (85 mm diameter) with surrounding electric wall heaters, was used (Figure 1). The length of the reactor was sequentially reduced from 2.5 to 0.5 meters, to attain the residence time aimed at in each experiment. The fuel load was kept at 2 ± 0.3 kW and the excess O2 was set to 10- 11%. Only primary air was used during the experiments, introduced from the bottom of the reactor through a grate with 86 holes (each 0.8 mm in diameter). The primary airflow was controlled by a mass flow controller and preheated in order to avoid any cooling effects from the air at the burner grate and attain a sufficiently homogeneous temperature profile throughout the fuel bed. The variations in temperature and residence time after the bed section in the reactor were accomplished by controlling both the temperature of the wall heaters and the temperature of the preheated air, and sequentially reducing the reactor height. An air-based heat exchanger was connected to the top of the reactor, which decreased the temperature of the flue gases to 90-105°C. The conditions in the bed section of the experimental fixed-bed reactor rather well simulated the conditions in present commercial residential pellet appliances with the major part of the air supply as primary air with rather turbulent, intensive and hot conditions.

Experimental design and emission responses The experiments were performed according to underlying statistical experimental designs [10] for the two variables temperature (850-950°C) and residence time (1-3 s). The temperature was defined as the temperature in the reactor after the bed section measured by a thermocouple (type K) and the residence time was defined as the time for the flue gases in the post-combustion zone before the heat exchanger. The software program MODDE 5.0 [11] was used to facilitate the design and evaluation of the experiments. An initial five-level central composite circumscribed (CCC) design was subsequently expanded with supplementary experiments according to a full factorial design (FFD) with one center point in the low-temp and low-time area. In Table 2, the factors and their design levels are shown with their high (+), medium (0) and low (-) values given.

The following responses were quantified for each experimental run; CO, organic gaseous carbon (OGC), NO, non-methane VOC (NMVOC), 20 specific VOC compounds, PMtot, fine particle mass median diameter (MMD), fine particle number concentration, fine particle count median diameter (CMD), PAHtot (particulate+semi-volatile) and 48 separate PAH compounds.

Fig. 1. Schematic illustration of the experimental fixed-bed pellets reactor (<5 kWfuel).

Table 2 Factors and their design levels. Abbreviation + 0 -

Design 1 - CCC Temperature (post-comb. zone) (ºC) Temp 850 900 950 Residence time (s) Time 1.0 2.0 3.0

Design 2 - FFD Temperature (post-comb. zone) (ºC) Temp 650 750 850 Residence time (s) Time 0.5 0.75 1.0

4 Experimental dilution sampling system Because of the semi-volatile and condensable nature of many of the organic compounds present in the emissions from the combustion processes, the characteristics and distribution (i.e. particle phase/gas phase) of the organic material may differ between the raw hot gases and the ambient air. To avoid condensation of water at lower sampling temperatures, dilution of the raw gases is also needed. The emission measurements were therefore performed in a previously designed whole flow dilution sampling system that enables constant volume sampling (CVS) system as described in more detail by Boman et al. [12]. The dilution ratio and sampling temperature in the CVS system were kept constant in all experiments at approximately 6.5 times dilution and 60°C, respectively.

Gas analysis Continuous gas analysis of O2 and CO2, where performed in the dilution tunnel as well as in the raw undiluted flue gases. O2 was measured by an electrochemical sensor in the raw gases and by a paramagnetic sensor in the diluted gases. CO2 was measured by non- dispersive infrared spectroscopy (NDIR) in both cases. OGC was analyzed in the raw flue gases before dilution by a flame ionization detector (FID). NO and CO were measured in the dilution tunnel by chemiluminescence and NDIR respectively. All gas components were all analyzed for cold and dry gases, except for OGC where the gases were kept at 120°C. All measured gas concentrations were recalculated from ppm or % to mg/MJfuel.

VOC sampling and analysis Volatile organic carbon components were sampled in the raw flue gases, through a 250 ml washing bottle to 10 L Tedlar bags. The bags were then analyzed for C1 to C6 compounds using gas chromatography (GC) with flame ionization detection (FID). The GC-FID system consisted of a Chrompack back-flush system containing a pre-column and a separating column. Baseline separation of all hydrocarbons, including 1,3–butadiene and propyn were established. Of the extracted flue gases 50 ml were also collected from each bag and injected through an adsorbent (Tenax) using a syringe. The Tenax tubes were stored in a freezer before analysis by a GC-FID system equipped with thermal desorption/auto-injection (Perkin Elmer ATD 400). During the evaluation of the results, the VOC components were divided into methane and NMVOC. Overall, 20 specific VOC compounds were analyzed (Table 3).

Table 3 All VOC compounds analyzed by GC-FID. Tedlar bags Tenax adsorbent methane benzene ethane toluene ethene octane propene butyl acetate ethyne (acetylene) ethylbenzene (benzene) m+p xylene o-xylene nonane dekan undekan dodekan 123-TMB 124-TMB 135-TMB

5 PMtot and PAH sampling/analysis Sampling of PMtot mass concentrations was performed isokinetically in the dilution tunnel using conventional dust sampling equipment with glass fiber filters (MG 160, dia=90 mm, Munktell Filters, Sweden). The PM sample filters were analyzed gravimetrically before and after sampling with an analytical balance (±1 µg) after at least 12 hours of conditioning in a desiccator.

Particulate PAH emission samples were collected on the previously mentioned glass fiber filters for PMtot. Polyurethane foam (PUF) plugs (75 mm diameter x 50 mm, 60 PPI; Specialplast AB, Sweden) were used for sampling of the semi-volatile PAH. The PUF plugs were washed prior to use as described elsewhere [13]. After sampling, the filter and PUF samples were Soxhlet extracted separately with acetone (p.a.; Merck, Germany) (225 mL) for 12h. The extract was evaporated under reduced pressure and stored at -18°C until analysis. The crude extracts were fractionated into two fractions before chemical analysis, as described by Alsberg et al [14] but using other solvent volumes. The PAH fraction was analyzed by gas chromatography-mass spectrometry (GC-MS) for quantification as described in detail elsewhere [15]. Prior to fractionation, internal standards were added (d10- phenanthrene, d10-pyrene, d12-benz(a)pyrene, picene, and 2,2'-binaphthyl) for quantification. A PAH standard mixture with internal standards was used for the determination of retention times and response factor calculations. Overall, 43 specific PAH compounds were analyzed (Table 4).

Table 4 All PAH compounds analyzed by GC-MS. Fluorene 1-Methylpyrene 2-Methylfluorene Benzo(ghi)fluoranthene Dibenzothiophene Benzo(c)phenanthrene Phenanthrene Benzo(b)naphto(1,2-d)thiophenanthrene Anthracene Cyclopenta(cd)pyrene 3-Methylphenanthrene Benzo(a)anthracene 2-Methylphenanthrene Chrysene 2-Methylanthracene 3-Methylchrysene 9-Methylphenanthrene 2-Methylchrysene 1-Methylphenanthrene 6-Methylchrysene 9-Methylanthracene 1-Methylchrysene 2-Phenylnaphthalene Benzo(b)fluoranthene 3,6-Dimethylphenanthrene Benzo(k)fluoranthene 3,9-Dimethylphenanthrene Benzo(e)pyrene Fluoranthene Benzo(a)pyrene Pyrene Perylene 9,10-Dimethylanthracene Indeno(1,2,3-cd)fluoranthene Benz(a)fluorene Indeno(1,2,3-cd)pyrene Retene Dibenz(a,h)anthracene Benz(b)fluorene Benzo(ghi)perylene 2-Methylpyrene Coronene 4-Methylpyrene

6 Fine particle sampling and measurements A 13 stage low-pressure cascade impactor (LPI, Dekati Ltd, Finland) was used to measure the particle mass size distribution in the range 0.03-10 µm. Diluted sample gas was drawn through the impactor at a rate of 17.9 L/min through an exchangeable nozzle that enables sampling as close to isokinetic velocity as possible. A pre-cyclone with cut-size approximately at 8 µm during the present conditions was used before the impactor. Non- greased Al-foils were used as impactor substrates and Al-cups in the cyclone. The mass of the PM samples were determined gravimetrically with an analytical balance (±1 µg) after conditioning of the Al-substrates and cyclone cups in a desiccator for at least 12 hours before and after sampling.

A scanning mobility particle sizer (SMPS) system was used to classify particles regarding number size distribution and concentration within 16 to 673 nm (equivalent mobility diameter). The system consisted of a differential mobility analyzer (DMA) from TSI (model 3071A, TSI Inc) and a condensation particle counter (CPC) also from TSI (model 3010, TSI Inc). Sample gas flow was additionally diluted by two ejector diluters (Dekati Ltd) in series that was supplied with dried pressurized air filtered through a high-efficiency particulate air (HEPA) filter. The dilution air to the first dilutor was heated to 60°C and kept at ambient room temperature at the second. The total dilution ratio of the two diluters was 56.

Results and Discussion

The desired conditions were generally accomplished within most of the reactor. An excess temperature of burning fuel particles and in the combustion zone could, however, not be completely avoided. Although the actual temperature at the burner grate was not measured, the temperature of the burning fuel particles can be significantly higher than in the rest of the reactor [16].

The effects of the sampling variables on emission characteristics were evaluated by statistical methods according to Box et al. [17] and Eriksson et al. [18]. Separate PLS (Projection to Latent Structures by means of Partial Least Squares Analysis) [19] models were determined for each of the dependent responses. PLS is a commonly used projection- based regression method for analyzing multivariate data where a quantitative relationship between a variable matrix (X) and a response matrix (Y) may exist [20]. In Table 5, a complete summary of the measured responses and their results for all the performed experiments is given. In the following text, the evaluation of each group of responses is then presented in separated paragraphs.

CO, OGC and NO During the initial 11 experiments, the measured concentrations of CO were very low (<0.1- 1.5 ppm), except for experiment 7 (4.5 ppm), which is around the detection limit of the instrument. However, in the complementary experiments with low temperature and short residence time, the concentrations were increased significantly. In the PLS analysis, temperature was found to be negatively correlated with the CO concentration with no significant effect of residence time. A model for CO including linear terms of temperature and time (non-significant) as well as the quadratic term of temperature was extracted and shown in Figure 2, with very good fit (R2=0.96) and predicting power (Q2=0.93).

7 Table 5 Summary of all measured responses and their results for each experiment.

Particle numb. 1 Temp Time CO NO OGC PMtot MMD PAHtot Methane NMVOC CMD conc. 13 (°C) (s) (mg/MJfuel) (mg/MJfuel)(mg/MJfuel)(mg/MJfuel) (nm) (ug/MJfuel)(mg/MJfuel)(mg/MJfuel) (nm) ([#/MJfuel]x10 ) 1 850 1.0 4.6 47 <1.0 14 107 0.19 <0.04 0.36 78 4.6 2 950 1.0 1.0 52 <1.0 18 109 0.23 <0.04 0.48 88 4.9 3 850 3.0 <1.0 53 <1.0 16 123 0.17 <0.04 7.61 91 3.9 4 950 3.0 6.7 56 <1.0 301 176 8.61 <0.04 0.84 105 3.5 5 829 2.0 <1.0 41 <1.0 17 113 2.21 <0.04 0.78 84 4.3 6 970 2.0 6.3 58 <1.0 181 109 1.11 <0.04 0.61 85 5.81 7 900 0.59 20 54 <1.0 17 106 0.24 <0.04 0.36 87 5.5 8 900 3.41 5.0 54 <1.0 14 160 1101 <0.04 4.31 98 3.0 9 900 2.0 <1.0 47 <1.0 20 136 131 <0.04 0.18 94 3.7 10 900 2.0 <1.0 40 <1.0 15 123 0.69 <0.04 0.40 88 3.7 11 900 2.0 <1.0 36 <1.0 13 112 0.34 <0.04 0.09 82 3.6 12 650 0.5 510 38 11 16 104 14 4.0 6.0 73 6.0 13 850 0.5 47 49 <1.0 15 103 0.57 0.59 0.28 78 6.6 14 750 0.75 96 42 <1.0 13 106 0.48 0.47 0.31 77 4.7 15 650 1.0 390 36 6.4 17 109 14 2.7 4.0 83 4.7 1 Not included or specially considered data in the statistical evaluation due to reasons discussed in the text.

Fig. 2. Combined effects of combustion temperature and residence time on the emissions of CO extracted by the PLS analysis.

The levels of the OGC were also very low (<1 ppm propane-equ) in the initial 11 experiments, and even in the additional experiments with increased CO levels OGC only increased to 5 and 8 ppm in two cases. This made it difficult to perform any PLS modeling and no predicting model of the effects of the time and temperature on the emissions of OGC could therefore be estimated. However, the increased OGC concentrations in two of the additional experiments indicated the importance also of mainly high combustion temperature for minimized emissions of gaseous hydrocarbons. In all experiments NO varied between 36 and 58 mg/MJfuel. NO was positively correlated with temperature with no significant effect of residence time. The model extracted by PLS included only linear terms of temperature and time (non-significant) is shown Figure 3. Experiments 10 and 11 were detected as "outliers" in the model and the resulting fit (R2=0.82) and predicting power (Q2=0.74) became good.

Fig. 3. Combined effects of combustion temperature and residence time on the emissions of NO extracted by the PLS analysis.

9 VOC (Methane and NMVOC) Similar results for methane and NMVOC with a strong significant influence (i.e. negative correlation) of temperature on the emissions. A PLS model for methane was determined with a fit (R2) and predicting power (Q2) of 0.92 and 0.85 respectively (Figure 4), including linear terms as well as the quadratic term of temperature. These results are in agreement with the results for CO and as discussed for OGC, the effect of increased temperature for reducing the VOC levels was the dominating effect.

Fig. 4. Combined effects of combustion temperature and residence time on the emissions of methane extracted by the PLS analysis.

Particle mass concentrations (PMtot) and composition The total particle mass emissions in all performed experiments varied between 13 and 20 mg/MJfuel, except in experiment 4 where the PM emissions was 30 mg/MJfuel which was shown to be an “outlier” in the statistical analysis and therefore considered in-relevant. However, there were no significant trends of the influence of the studied variations in temperature and time on the PMtot emissions.

No detectable mass of coarse (>1 µm) PM was found in any case and all sampled PM mass therefore consisted of fine (<1 µm) particles. During “poor" combustion, one may expect that the PM levels should increase as a result of increased particulate carbonaceous PIC, i.e. soot and organics. However, in these experiments the worst case of “poor” combustion did not presumably produce sufficiently amounts of carbonaceous material to result in any significant effects on the total particle mass concentration. This is also illustrated by the fact that the carbon content in the fine particle samples based on the EDS analysis were relatively similar in all experiments (7.4±1.8% by weight) and not increased during experiment 12 and 15 which were the cases with most increased CO, methane and PAH emissions.

Beside carbon and oxygen, the fine PM was totally dominated by potassium, sulfur and chlorine also with minor amounts of sodium and zinc. Chromium was also found in considerable concentrations in the fine PM, however in decreasing amounts chronologically, i.e. decreasing from approximately 10 to 0.1% by weight during the campaign. Chromium is

10 assumed to derive from the new stainless steel reactor walls by release of gaseous chromium species during high temperature combustion conditions subsequently forming condensed alkali chromates as identified in the present study [Nordin et al, manuscript].

The potential effect of increased inorganic fine particles at higher temperatures caused by increased volatilization of ash forming elements was not significant in the present study. The results therefore illustrated that PM emissions of fine inorganic compounds in the range of 15-20 mg/MJfuel is relevant to consider during near-complete combustion of conifer stem- wood pellets in small-scale appliances. The emission of fine PM is, however, influenced by fuel composition (i.e. fine particle forming elements) and combustion conditions. In a recent study it was shown that the emission of fine PM was significantly higher during combustion of bark pellets compared to stem-wood pellets, as well as that the fine PM decreased if the air supply was shifted from 100% primary air to 50% as primary and secondary air respectively [21]. The decrease in fine PM emissions determined in that study was assumed to be a result of lower oxygen concentrations and thus temperatures in the fuel bed, resulting in less volatilization of ash forming elements.

Fine particle size distributions and number concentration The MMD and CMD varied in the range of 103-176 nm and 78-105 nm respectively. From the PLS evaluation, both MMD and CMD showed positive correlations with time and a minor but non-significant correlation with temperature. The fine particle number concentrations 13 13 varied in the range of 3.5*10 -6.6*10 particles/MJfuel and a negative correlation with residence time were determined. The relationship between residence time and fine particle number concentrations and count median diameters are shown in Figure 5.

The correlation between residence time and fine particle size distributions may be explained by effects of higher coagulation during longer residence times. Since the variations presently studied includes isothermal conditions in the post-combustion zone before cooling of the flue gases, several other aerosol processes may, however, proceed in parallell with a potential coagulation of primarily formed particles of e.g. nucleated alkali sulfates.

1.1E+08 110 Numb Conc

2 1.0E+08 R = 0.64 100 CMD

) 9.0E+07 90 fuel

8.0E+07 80

7.0E+07 70

Number conc. (#/MJ 6.0E+07 60 Count median particle dia. (nm)

5.0E+07 R2 = 0.77 50

4.0E+07 40 0 0.5 1 1.5 2 2.5 3 3.5 4 Residence time (s)

Fig. 5. Fine particle number concentrations and count median diameters as a function of residence time in the post-combustion zone in the pellet reactor (<5 kW).

11 Total PAH In accordance with all other PIC, a strong negative correlation between PAH and temperature in the post-combustion zone was determined with no significant effect of residence time. The PLS model that included the two linear terms as well as the quadratic term of temperature showed very good fit (R2=0.95) and predicting power (Q2=0.92) (Figure 6). The total PAH emissions in the relevant experiments varied in the range of 0.17-14 µg/MJfuel. Although somewhat increased during colder conditions, the PAH emissions determined in the present reactor were significantly lower than PAH emissions in commercial pellet burners during full load operation (50-300 µg/MJfuel) [22]

As mentioned earlier, the temperature in the fuel bed of burning particles can be significantly higher than in the rest of the reactor [16]. The previous knowledge of the severe conditions needed for thermal destruction of secondary PAH compounds and the strong correlation between increasing temperature and lower PAH emissions together with no significant effect of residence time may indicate a non-formation of PAH rather then thermal destruction of already formed PAH species. This could also be an effect of fast instant oxidation, or reactor specific conditions.

Fig. 6. Combined effects of combustion temperature and residence time on the emissions of PAHtot extracted by the PLS analysis.

Specific PAH compounds The concentrations of the specific PAH compounds versus combustion temperature are presented in Figure 7. It can be seen that all PAH´s were reduced below the total background concentration of PAH when the temperature in the post-combustion zone were increased above 800-850°C. At lower temperatures <800°C, the dominant species were phenanthrene, retene and fluoranthene. Also 9,10-dimethylanthracene, pyrene, antracene were found in significant concentrations.

12 1.6 1. phenanthrene 2. retene 1 2 3. flouranthene 1.4 3 4. 9,10-dimethylanthracene 4 5. pyrene 6. anthracene 1.2 5 7. 2-methylphenanthrene 8. 2-phenylnaphtalene 9. 3-methylphenanthrene 1 10. chrysene 6 11. 2-methylanthracene 12. cyclopenta(cd)pyrene 0.8 7 8 0.6 Background

Concentration (ug/Nm3) concentration 0.4 9 10 11 0.2 12

0 650 700 750 800 850 900 950 Temperature (deg C)

Fig. 7. Concentrations of separate PAH compounds in the flue gases during combustion of softwood pellets as a function of temperature in the post-combustion zone after the fuel bed.

Practical residential appliance considerations The results in the present study have shown that it exists a significant potential to obtain optimized combustion conditions in residential pellet appliances with in principal a total depletion of PIC´s by high temperature, intensive, air rich and well mixed conditions in the bed section. During such conditions the importance of residence time at high temperature was shown to be limited, although isothermal conditions during 0.5-1.0 s would be preferable for optimized results in practical situations. Such high temperature conditions in the fuel bed, which resembles the conditions in present commercial pellet appliances, may, however, increase the risk for potential ash related problems like slagging, especially during combustion of some qualities of more ash rich pellet fuels [23]. If such fuels are to be used and potential ash related problems should be prevented, air staging with lower fuel bed temperatures is preferable and the importance of sufficiently long residence time in the post- combustion zone for minimizing the emissions of PIC will therefore increase.

Conclusions

The results in the present study illustrated that:

• During small-scale combustion of softwood pellets sufficient high temperatures (>850 °C) with air rich and well mixed conditions in the bed section will enable near-complete combustion conditions with almost a total depletion of PIC, including all 43 studied PAH compounds. During such conditions, the residence time in the post-combustion is only of minor importance for minimizing the emissions of PIC.

• PMtot emissions were not influenced by the studied variations in combustion conditions, either of increased soot and organics during poorer combustion or higher degree of volatilization of ash elements at higher temperatures. This consideration indicates that the temperature in the fuel bed was not significantly influenced by the temperature variations after the bed section. Fine particle mass and count median diameters as well as number concentration were, however, significantly influenced of residence time, i.e. increased time resulted in increased particle sizes and decreased number

13 concentrations. The mass and count median diameters varied in the range of 100-180 nm and 80-105 nm respectively, with number concentrations in the range of 3*1013-7*1013 particles/MJfuel.

• During complete combustion of softwood pellets, the particulate matter almost fully consists of inorganic volatilized and fine particle forming material with mass concentrations in the range of 15-20 mg/MJfuel, consisting mainly of potassium, sulfur and chlorine also with minor amounts of sodium and zinc.

• The extremely low emissions of PAH and other PIC can probably be explained by a prevention of the formation or instant oxidation rather then thermal destruction in the post-combustion zone. Although these results and conclusions are exciting and encouraging they may be consequences of both the excess surface temperatures of the burning fuel pellets and more reactor specific conditions, emphasizing the need for further verification studies and technology development work.

Acknowledgement

Lena Elfver at the Department of Analytical Chemistry, Stockholm University is acknowledged for the analytical work concerning PAH. FOI in Umeå is gratefully acknowledged for the kindness of supplying the project with the SMPS system. Joakim Pagels at the Division of Ergonomics and Aerosol Technology, Lund Institute of Technology and Erik Swietlicki at the Division of Nuclear Physics at Lund Institute of Technology are acknowledged for help with the SMPS equipment. The financial support from the Center for Environmental Research in Umeå and the Swedish Energy Agency is finally gratefully acknowledged.

References

[1] Holgate ST, Samet JM, Koren HS, Mayland R, editors. Air pollution and health. London: Academic Press, 1999. [2] Pope CA III, Thun MJ, Namboodiri MM, Dockery DW, Evans JS, Speizer EF, et al. Particulate air pollution as a predictor of mortality in a prospective study of US adults. American Journal of Critical Care Medicine 1995;151:669-74. [3] Törnqvist M, Ehrenborg L. On cancer risk estimation of urban air pollution. Environmental Health Perspectives 1994;102(suppl 4):173-81. [4] Katsouyanni K, Pershagen G. Ambient air pollution exposure and cancer. Cancer Causes and Control 1997;8:284-91. [5] Boström C E, Gerde P, Hanberg A, Jernström B, Johansson C, Kyrklund T, Rannug A, Törnqvist M, Victorin K, Westerholm R. Cancer risk assessment, indicators and guidelines for polycyclic aromatic hydrocarbons in the ambient air. Environmental Health Perspectives 2002;110:451-489. [6] Pettersson E, Nordin A, Öhman M, Effect of temperature and residence time on emissions of CO, THC, tars and NOx during pellet combustion. Proceeding of the Nordic Seminar of Thermochemical Convention. Trondheim, 1996. [7] Abatzoglou N, Evans R, Milne TA. Biomass gasifiers "tars": their nature, formation and conversion. National Renewable Energy Laboratory, IEA Review, 1998. [8] Mastral AM, Callén MS. A review on polycyclic aromatic hydrocarbon (PAH) emissions from energy generation. Environmental Science and Technology 2000;34(15):3051-7. [9] Nordin A., Chemical Elemental Characteristics of Biomass Fuels. Biomass and Bioenergy 1994;6(5);339-47. [10] Eriksson L, Johansson E, Kettaneh-Wold N, wikström C, Wold S. Design of experiments principles and applications, Umetrics AB, Umeå, 2000.

14 [11] MODDE 5.0. Users Manual 1999. [12] Boman C, Nordin A, Westerholm R, Pettersson E. Influence of dilution sampling conditions on particulate and PAH characteristics from residential biomass fired appliances. Submitted to Biomass and Bioenergy. [13] Westerholm RN, Almén J, Li H. Chemical and biological characterization of particulate-, semivolatile- and gas-phase associated compounds in diluted heavy-duty exhausts: a comparison of three different semivolatile-phase samplers. Environmental Science and Technology 1991;25:332-8. [14] Alsberg T, Stenberg U, Westerholm R, Strandell M, Rannug U, Sundvall A, Romert L, Bernson V, Petterson B, Toftgård R, Franzen B, Jansson M, Gustafsson J-Å, Egebäck K-E, Tejle G. Chemical and biological charaterization of organic material from gasoline exhaust particles. Environmental Science and Technology 1985;19:43-50. [15] Westerholm R, Christensen A, Törnqvist M, Ehrenberg L, Rannug U, Sjögren M, Rafter J, Soontjens C, Almén J, Grägg K. A comparison of exhaust emissions from Swedish environmental classified diesel fuel (MK1) and European program on emissions, fuels and engine technologies (EPEFE) reference fuel: a chemical and biological characterization, with viewpoints on cancer risk. Environmental Science and Technology 2001;35:1748-54. [16] Öhman M. Experimental studies on bed agglomerations during fluidized bed combustion of biomass fuels. Dissertation. Umeå University, Umeå, Sweden, 1999. [17] Box G E P, Hunter W G, Hunter J S. Statistics for Experiments; An Introduction to Design, Data Analysis and Model Building. Wiley, New York, 1978. [18] Eriksson L, Johansson E, Kettaneh-Wold N, Wikström C, Wold S. Design of Experiments; Principles and Applications. Umetrics AB, Sweden, ISBN 91-973730-0-1, 2000. [19] Wold S, Sjöström M, Eriksson L. PLS in Chemistry. In: The Encyclopedia of Computational Chemistry. Schleyer PvR, Allinger NL, Clark T, Gasteiger J, Kollman PA, Schaefer III HF, Schreiner PR, Eds. John Wiley & Sons, Chichester, 1999, p. 2006- 20. [20] Eriksson L, Johansson E, Kettaneh-Wold N, Wold S. Introduction to Multi- and Megavariate Data Analysis using Projection Methods (PCA & PLS). Umetrics AB, Sweden, 1999. [21] Wiinikka H, Gebart R. Critical parameters for particle emissions in small-scale fixed bed combustion of wood. Energy and Fuels 2004;18:897-907. [22] Johansson LS, Leckner B, Gustavsson L, Cooper D, Tullin C, Potter A. Emission characteristics of modern and old-type residential boilers fired with wood logs and wood pellets. Atmosheric Environment 2004;38(25):4183-4195. [23] Öhman M, Boman C, Hedman H, Nordin A, Boström D. Slagging tendencies of wood pellet ash during combustion in residential pellet burners. Biomass and Bioenergy 2004;27:585-596.

338 Energy & Fuels 2004, 18, 338-348

Characterization of Inorganic Particulate Matter from Residential Combustion of Pelletized Biomass Fuels

Christoffer Boman,* Anders Nordin, Dan Bostro¨m, and Marcus O¨ hman

Energy Technology and Thermal Process Chemistry, Umeå University, SE-901 87 Umeå, Sweden

Received July 7, 2003. Revised Manuscript Received October 31, 2003

The increased focus on potential adverse health effects associated with exposure to ambient particulate matter (PM) motivates a careful characterization of particle emissions from different sources. Combustion is a major anthropogenic source of fine PM, and, in urban areas, traditional residential wood combustion can be a major contributor. New and upgraded biomass fuels have become more common, and fuel pellets are especially well-suited for the residential market. The objective of the present work was to determine the mass size distributions, elemental distributions, and inorganic-phase distributions of PM from different residential combustion appliances and pelletized biomass fuels. In addition, chemical equilibrium model calculations of the combustion process were used to interpret the experimental findings. Six different typical pellet fuels were combusted in three different commercial pellet burners (10-15 kW). The experiments were performed in a newly designed experimental setup that enables constant-volume sampling. Total- PM mass concentrations were measured using conventional filters, and the fractions of products of incomplete combustion and inorganic material were thermally determined. Particle mass size distributions were determined using a 13-step low-pressure cascade impactor with a precyclone. The PM was analyzed for morphology (using environmental scanning electron microscopy, ESEM), elemental composition (using energy-dispersive spectroscopy, EDS), and crystalline phases (using X-ray diffractometry, XRD). For complementary chemical structural characterization, time-of- flight secondary ion mass spectrometry (TOF-SIMS), X-ray photoelectron spectroscopy (XPS) and X-ray absorption fine structure (XAFS) spectroscopy were also used. The emitted particles were mainly found in the fine (<1 µm) mode with mass median aerodynamic diameters of 0.20- 0.39 µm and an average PM1 of 89.5% ( 7.4% of total PM. Minor coarse-mode fractions (>1 µm) were present primarily in the experiments with bark and logging residues. Relatively large and varying amounts (28%-92%) were determined to be products of incomplete combustion. The inorganic elemental compositions of the fine particles were dominated by potassium, chlorine, and sulfur, with minor amounts of sodium and zinc. The dominating alkali phase was KCl, with minor but varying amounts of K3Na(SO4)2 and, in some cases, also K2SO4. The results showed that zinc is almost fully volatilized, subsequently and presumably forming a more complex solid phase than that previously suggested (ZnO). However, the formation mechanism and exact phase identification remain to be elucidated. With some constrains, the results also showed that the amounts and speciation of the inorganic PM seemed to be quite similar to that predicted by chemical equilibrium calculations.

Introduction industry, whereas the use of bark, agricultural residues, and other forest fuels occurs only occasionally.1 How- Globally, an increasing interest for sustainable energy ever, in a future with an increasing utilization of forest production can be observed, and biofuels, as a renewable resources, other types of wood forest-based materials and CO2-neutral energy source, are expected to be a (e.g., bark and logging residues) might also be used for major contributor. New and upgraded biomass fuels (i.e., pellet production. To accomplish a substantially in- pellets, briquettes, and powder) have become more creased use of biomass fuels, careful evaluations must common, and fuel pellets are especially well-suited for therefore be made concerning the consequences for the the residential biomass market, providing possibilities environment and human health. In this extensive area of more automated and optimized systems with higher of multidisciplinary issues, detailed characterization of combustion efficiency and less products of incomplete the emissions from different sources is a fundamental combustion (PIC). The raw materials presently used for part. production of fuel pellets are generally stem-wood The emissions of particulate air pollution are pres- assortments (∼95%), such as sawdust, planer shavings, ently an intensely debated issue from the perspective or dried chips from sawmills and the wood working of both global warming and human health. Anthro- * Author to whom correspondence should be addressed. E-mail: [email protected]. (1) Hillring, B.; Vinterba¨ck, J. For. Prod. J. 1998, 48 (5), 67-72.

10.1021/ef034028i CCC: $27.50 © 2004 American Chemical Society Published on Web 12/06/2003 Inorganic PM from Biomass Pellet Combustion Energy & Fuels, Vol. 18, No. 2, 2004 339 pogenic-derived atmospheric aerosols are important for plants, the conditions are more easily optimized and the climate on a global and regional scale. The emissions stable, and, therefore, the PM is dominated by inorganic of carbonaceous aerosols are especially considered as an (ash) constituents that contain mainly potassium, so- important contributor to the heating of the global dium, sulfur, and chlorine in the fine mode with a minor atmosphere.2 Furthermore, combustion processes in the but varying fraction of coarse fly-ash particles that urban environment are major anthropogenic sources of contain refractory elements such as calcium, silicon, fine particulate matter (PM) pollution, and the present magnesium, and aluminum.9-11 If trace elements such residential wood-log combustion is a significant reason as cadmium, lead, and zinc are present in the fuel, they for the deterioration of ambient air quality in residential can be volatilized during combustion in all types of areas.3 PM in the ambient air today is generally devices and be found as condensed species of fine PM.12 considered to be an important indicator of air pollution Although the principal PM formation and transforma- that causes adverse health effects. Epidemiological tion mechanisms are more or less the same, independent evidence exists that links increases in PM mass con- of the size of the combustion appliance, an important centrations with cardiopulmonary disease4 and mortal- difference between biomass combustion in large plants ity.5 No specific particle property or component respon- and residential appliances is that the coarse fraction is sible for the toxicological effects has yet been identified. often limited in the latter. The emission characterization However, the importance of particle properties other work conducted thus far that concerns PM from resi- than mass concentration, such as chemical composition, dential biomass combustion comprises mass concentra- particle size, and number concentration, have been tion, mass/number size distribution, and elemental emphasized.6,7 composition.13-17 Some work that involves speciation of The present knowledge of combustion particles is the particle-bound organic fraction has also been - mainly based on the research and development (R&D) performed.18 20 However, few studies have been devoted work performed within coal and internal engine com- to the actual inorganic-phase composition of the PM bustion and has recently been reviewed.7 One conclud- from biomass combustion,17,21,22 and the effects of dif- ing remark was that more characterization studies of ferent combustion techniques and fuels have never been combustion aerosols, including transient emissions, considered. Today, the testing and certification of these detailed chemical speciation, and number of ultrafine types of appliances only comprise the emissions of particles are needed, given the basis for further work carbon monoxide (CO), organic gaseous carbon (OGC), with atmospheric particle transformation and health- and total PM (dust). To increase the possibilities to link related hypothesis. From studies of coal combustion, it specific toxicological effects with exposure to combus- is known that the particle mass size distribution most tion-related PM and also to make health impact assess- often consists of two modes: one fine mode in the ments of future combustion technologies, detailed physi- submicrometer range (particle diameters of <1 µm) and cal and chemical characterization of the PM is needed a coarse mode (particle diameters of >1 µm).7 Fine-mode for different fuels and appliances. particles are formed by nucleation and/or condensation (9) Chriestensen, K. A. Dissertation. Technical University of Den- processes of volatilized gas phase precursors, which mark: Lyngby, Denmark, 1995. subsequently coagulate and form agglomerates. The (10) Valmari, T.; Lind, T.; Kauppinen, E. I.; Sfiris, G.; Nilsson, K.; coarse mode can consist of a wide variety of mechani- Maenhaut, W. Energy Fuels 1999, 13 (2), 390-395. (11) Brunner, T.; Dahl, J.; Obernberger, I.; Po¨lt, P. In Proceedings cally generated particles, which are normally ash ag- of the 1st World Conference and Exhibition Biomass for Energy and gregates that have been entrained with the flue gases Industry, Sevilla, Spain, 2000; Kyritsu, S., Beenackers, A. A. C. M., from the fuel bed during combustion. Important differ- Helm, P., Grassi, A., Chiaramonti, D., Eds.; James and James, Ltd.: London, 2001; pp 1991-1994. ences between biomass and coal regarding ash trans- (12) Nordin, A.; Backman, R. In Ashes and Particulate Emissions formation and PM formation are the low mineral, high from Biomass CombustionsFormation, Characterization, Evaluation, 8 Treatment. Obernberger, I., Ed.; dbv-Verlag: Graz, Austria, 1998; pp volatile, and high alkali contents in biomass fuels. 119-134. PM from biomass combustion can be classified either (13) Rau, J. A. Aerosol Sci. Technol. 1989, 10, 181-192. (14) Purvis, C. R.; McCrillis, R. C.; Kariher, P. H. Environ. Sci. as inorganic ash material, soot, or organic material, and Technol. 2000, 34, 1653-1658. the distribution varies with the combustion conditions (15) Hueglin, C.; Gaegauf, C.; Ku¨ nzler, S.; Burtscher, H. Environ. for different fuels in different appliances. The amount Sci. Technol. 1997, 31, 3439-3447. (16) Wieser, U.; Gaegauf, C. K. In Proceedings of the 1st World of carbonaceous material can be substantially reduced Conference and Exhibition Biomass for Energy and Industry, Sevilla, relatively easily by primary measures that facilitate Spain, 2000; Kyritsu, S., Beenackers, A. A. C. M., Helm, P., Grassi, increased combustion efficiency, which is illustrated by A., Chiaramonti, D., Eds.; James and James, Ltd.: London, 2001; pp 805-808. the ongoing technical development of residential bio- (17) Johansson, L. S.; Tullin, C.; Leckner, B.; Sjo¨vall, P. Biomass mass appliances. In large and medium-sized combustion Bioenergy 2003, 25 (4), 435-446. (18) Kleeman, M. J.; Schauer, J. J.; Cass, G. R. Environ. Sci. Technol. 1999, 33, 3516-3523. (2) Ramanathan, V.; Crutzen, P. J.; Kiehl, J. T.; Rosenfeld, D. (19) Schauer, J. J.; Kleeman, M. J.; Cass, G. R.; Simoneit, B. R. T. Science 2001, 294, 2119-2124. Environ. Sci. Technol. 2001, 35, 1716-1728. (3) Larson, T. V.; Koenig, J. Q. Annu. Rev. Public Health 1994, 15, (20) McDonald, J. D.; Zielinska, B.; Fujita, E. M.; Sagebiel, J. C.; 133-156. Chow, J. C.; Watson, J. G. Environ. Sci. Technol. 2000, 34, 2080- (4) Pope, C. A., III.; Dockery, D. W. In Air Pollution and Health. 2091. Holgate, S. T., Samet, J. M., Koren, H. S., Maynard, R., Eds; Academic (21) Lind, T.; Valmari, T.; Kauppinen, E.; Maenhaut, W.; Huggins, Press: London, 1999; pp 673-705. F. In Ashes and Particulate Emissions from Biomass Combustions (5) Pope, C. A., III.; Burnett, R. T.; Thun, M. J.; Calle, E. E.; Krewski, Formation, Characterization, Evaluation, Treatment. Obernberger, I., D.; Ito, K.; Thurston, G. D. JAMA 2002, 287 (9), 1132-1141. Ed.; dbv-Verlag: Graz, Austria, 1998; pp 155-169. (6) Harrison, R. M.; Yin, J. Sci. Total Environ. 2000, 249,85-101. (22) Kaufmann, H.; Nussbaumer, T. In Proceedings of the 10th (7) Lighty, J. S.; Veranth, J. M.; Sarofim, A. F. J Air Waste Manage European Conference and Technology Exhibition on Biomass for Energy Assoc. 2000, 50 (9), 1565-1618. and Industry. Kopetz, H., Weber, T., Palz, W., Chartier, P., Ferrero, (8) Jenkins, B. M.; Baxter, L. L.; Miles, T. R., Jr.; Miles, T. R. Fuel G. L., Eds.; Wu¨ rzburg, Germany, 1998. C. A. R. M. E. N: Rimpar, 1998; Process Technol. 1998, 54,17-46. pp 1326-1329. 340 Energy & Fuels, Vol. 18, No. 2, 2004 Boman et al.

Table 1. Characteristics of the Studied Pellet Fuelsa Sawdust Logging Residues Bark fresh stored fresh stored fresh stored (S0) (S6) (L0) (L6) (B0) (B6) effective heating value (MJ kg-1 d.wt.) 18.7 18.9 19.4 19.5 18.8 18.2 moisture content (% d.wt.) 13.1 13.3 10.2 11.4 11.2 10.1 ash content (% d.wt.) 0.49 0.61 2.44 2.53 3.35 7.89 elemental compositionb Cc 51.9 51.9 51.6 51.6 52.5 52.5 Hc 6.0 6.0 6.0 6.0 5.7 5.7 Oc 41.8 41.8 39.0 39.0 39.3 39.3 Nc 0.12 0.12 0.48 0.48 0.40 0.40 S 0.02 0.01 0.05 0.04 0.03 0.04 Cl 0.004 0.008 0.04 0.02 0.03 0.02 Si 0.06 0.10 0.32 0.27 0.37 1.86 Al 0.01 0.02 0.04 0.04 0.07 0.39 Fe 0.02 0.02 0.02 0.02 0.04 0.27 Mg 0.01 0.02 0.08 0.07 0.08 0.11 Ca 0.10 0.11 0.53 0.54 0.81 1.11 Na 0.01 0.01 0.03 0.02 0.03 0.14 K 0.05 0.06 0.21 0.20 0.26 0.37 P 0.01 0.01 0.08 0.08 0.07 0.07 Mn 0.01 0.01 0.09 0.08 0.06 0.07 Cr 0.82 ppm 1.30 ppm 0.935 ppm 1.12 ppm 2.66 ppm 27.3 ppm Co 0.0703 ppm 0.0866 ppm 0.370 ppm 0.255 ppm 0.462 ppm 1.28 ppm Cu 1.36 ppm 0.229 ppm 0.803 ppm 1.38 ppm 1.51 ppm 5.37 ppm Sr 7.11 ppm 7.17 ppm 26.4 ppm 18.8 ppm 42.2 ppm 56.9 ppm V 0.112 ppm 0.191 ppm 0.612 ppm 0.781 ppm 0.567 ppm 4.47 ppm Zn 14.0 ppm 13.5 ppm 58.1 ppm 73.2 ppm 131 ppm 136 ppm Zr 0.352 ppm 1.15 ppm 1.37 ppm 1.01 ppm 1.86 ppm 17.3 ppm a % d.wt. ) percentage based on dry weight.24 b Values are in % d.wt., unless noted otherwise. c Average values taken from Nordin.24

Therefore, the objective of the present work was to centrations probably originate from typical contamination in determine the mass size distributions, elemental dis- the form of quartz or silicates during the production, handling, tributions, and inorganic-phase distributions of PM from and/or storage of the fuels. More detailed information about the quality properties of the different pellet fuels is given by different residential combustion appliances and pellet- 25 ized biomass fuels. In addition, chemical equilibrium Lehtikangas. Experimental Procedure. The boiler was connected to a models were used to interpret the experimental find- water-based heat exchanger system, where the heat output ings. was set to a constant value of 3 kW, which corresponds to a typical situation for small houses during wintertime. The fact Methods and Materials that the nominal output of the pellet burners exceeded 3 kW during operation resulted in intermittent operation conditions, Appliances and Fuels. The emissions from the combustion which are also typical for residential use. Each emission of six different fuels were characterized from three different measurement started after 2-3 initial cycles when the system commercial pellet burners (with nominal heat outputs of 10- was in thermal balance and continued over 4-6 combustion 15 kW) installed in a reference boiler that is presently used cycles, corresponding to 3-6 h for burners A and C and 6-9 for national certification tests of residential pellet burners in h for burner B. Temperature measurements with thermo- Sweden. The three burners, all of which had been certified couples (type K) were performed at different locations in the according to the national certification criteria “P-marking” at combustion zone in the burners. To be able to determine the the Swedish National Testing and Research Institute,23 were total gas and PM concentrations and allow for representative representative for the present European market. They isokinetic sampling during the intermittent operation, the also represented different classes of burner constructions with experiments were performed using a previously designed overfeeding, horizontal feeding, and underfeeding of the fuel, dilution setup that enables constant volume sampling (CVS). respectively. Fresh and stored (for six months) material from The presently used dilution tunnel sampling system has been softwood sawdust (S0/S6), logging residues (L0/L6) and bark more carefully described and evaluated by Boman.26 (B0/B6) were used as raw materials, and the raw material Continuous gas measurements of oxygen gas (O2), carbon originated from the same felling district, with 60% Norway dioxide (CO2), CO, and total gaseous hydrocarbons (THC) were spruce and 40% Scots pine. These raw materials are all either performed with conventional instruments in the dilution presently used or are potential new biomass resources aimed tunnel, as well as O2 and CO2 in the raw flue gas before at the pellets market. All six pellet assortments were produced dilution. The dilution ratios were calculated as the ratios in the same plant, and the raw materials were dried with the between CO2 in the diluted gas and CO2 in the undiluted gas. flue gases from an oil burner before milling and pelletizing. In the present study, the intent was to dilute the flue gas just The characteristics of the pelletized fuels are given in Table enough to maintain a constant flow during the intermittent 1. The ash compositions of the fuels corresponded closely to burner operation. The dilution ratios varied within the range previously reported data24 for wood, logging residues, and bark, of 1.5-2.0 during the combustion periods, depending on except for the silicon content, which was relatively high for combustion intensity, and the flue-gas temperature at the sawdust (wood) and stored bark. The increased silicon con- sampling points was consistently controlled to 60 ( 5 °C.

(23) Swedish National Testing and Research Institute, Report SPCR (25) Lehtikangas, P. Biomass Bioenergy 2001, 20 (5), 351-360. 028, 1999. (26) Boman, C. Licentiate Thesis. Umeå University, Umeå, Sweden, (24) Nordin, A. Biomass Bioenergy 1994, 6 (5), 339-347. 2003. Inorganic PM from Biomass Pellet Combustion Energy & Fuels, Vol. 18, No. 2, 2004 341

Table 2. Elements and Solution Models Used in the Chemical Equilibrium Model Calculationsa Modeling Stage 1: “Volatilization” Modeling Stage 2: “Condensation” elements C, H, O, N, S, Cl, P, K, Na, Ca, Mg, Si, Al, Zn C, H, O, N, S, Cl, K, Na, Zn solution models Slagg: ASlag-liq Salt: Salt-liq (-SALT) Alk-Cl (-ACLA) Na,K/OH (-AOH) Salt: Salt-liq (-SALT) CO3,SO4/Li,Na,K (-CSOB) Na,K/SO4 (-NKSO) K2SO4-solid (-KSO) (Ca, Mg): liq-K,Ca/CO3,SO4 (-LCSO) K2CO3 (-KCO) s-K,Ca/CO3,SO4 (-SCSO) Na,K/CO3 (-NKCA) s-Ca(SO4), Mg(SO4) (SCMO) Na,K/CO3 (-NKCB) liq-Ca,Mg,Na/(SO4) (-LSUL) K3Na(SO4)2 (-KNSO) s-Ca,Mg,Na/(SO4) (-SSUL) A Na,K/OH,F,Cl (-NKXA) CaCl2 (-CACL) B Na,K/OH,F,Cl (-NKXB) Na/Cl,OH (-NCOA) Na/Cl,OH (-NCOB)

a Designations of the solution models were taken from FACT-Win 3.05. Sampling of Particulate Matter. Total-PM concentra- this work, they were used first and foremost as complementary tions were determined by isokinetic sampling, using conven- tools to ESEM/EDS and XRD for possible further detailed tional equipment with glass fiber filters in the experiments chemical characterization. The TOF-SIMS analyses were with burners A and B and quartz fiber filters for burner C. performed at the Swedish National Testing and Research The particle mass size distributions were determined by Institute in Borås, using model TOF-SIMS IV, Ion-TOF isokinetic sampling, using a 13-step low-pressure cascade GmbH. The XPS analyses were performed using a Kratos Axis impactor (Dekati, Ltd.) with a precyclone and a downstream Ultra spectrometer. Wide spectra (pass energy 160 eV) and Teflon filter. The cyclone cutoff was ∼16 µm, and the impactor spectra of individual photoelectron lines were acquired using separates the particles by aerodynamic diameter in a range a monochromatized Al KR source that was operated at 225 of ∼0.03-10 µm. An ejector dilutor (Dekati, Ltd.) was used W. To compensate for surface charging, a low-energy electron before the impactor, to dilute the sample gas (∼7.64 times) gun was used. Spectra were processed with Kratos software, with clean dried air, thereby allowing for integrated sampling and the binding energy scale was referenced to the C 1s line during several combustion cycles without overloading the of aliphatic carbon contamination set at 285.0 eV. Zn K-edge substrates. To allow for extensive phase and elemental analy- extended XAFS (EXAFS) data were measured at the Stanford ses, aluminum foils were used as impactor substrates for Synchrotron Radiation Laboratory (Stanford, California) on burners A and B and quartz filters were used for burner C. beam line 4-1. The ring energy, was 3.0 GeV with ring current The aluminum substrates were greased with Apiezon L between 60 and 100 mA. A Si(220) double-crystal monochro- vacuum grease, to prevent particle bounce, and heated for 2 h mator was used and detuned 50% to eliminate higher harmon- at 105 °C, to avoid mass losses during sampling. The sampling ics. The data were measured at room temperature in the probes, filter holders, precyclone, ejector dilution air, and fluorescence mode, with a Lytle detector27 that was filled with impactor were all kept at 60 ( 5 °C. After at least8hof argon gas. A Ni-6 filter and a Soller slit setup were used to conditioning in a desiccator, total-PM filters and impactor reduce Kâ fluorescence and scattering contributions to the substrates were analyzed gravimetrically with an analytical signal. Internal calibration was performed by simultaneously balance (0.01 mg) before and after sampling. To separate the measuring spectra from a Zn foil in transmission mode, total-PM samples into different fractions, a standard thermal throughout the duration of all scans. method was used. Subsequent heating and weighing one of Chemical Equilibrium Model Calculations. To help the two equivalent filters per sample in oxidizing atmosphere interpret the experimental findings, chemical equilibrium (air) for2hatdifferent temperature intervals resulted in model calculations were performed using the software program content of water (105 °C), unburned material (105-550 °C), FACT-Win 3.05. The program uses the method of minimization and residual ash (550 °C). of the total Gibb’s free energy of the system. Thermodynamic Chemical Analysis of Particulate Matter. Total-PM data were taken from the FACT database28 including stoichio- samples and impactor samples were analyzed for morphology metric data as well as nonideal solid and liquid solution and elemental composition, using a Philips model XL30 models. Fuel characteristics were taken from Table 1. The environmental scanning electron microscopy-field emission calculations were performed using both local (i.e., reducing gun (ESEM-FEG) that was equipped with an EDAX energy- atmospheres within fuel particles) and global (i.e. oxidizing) dispersive spectroscopy (EDS) detector. Selected impactor approaches under atmospheric pressure (1 bar). An air-to-fuel samples were further analyzed by X-ray diffractometry (XRD) ratio (λ) of 2.0 was used for the global calculations, which for identification of crystalline phases. The XRD investigations corresponds to the typical average conditions present in the were performed using a Bruker d8Advance instrument in θ-θ burners during operation. The process temperature in the mode, with an optical configuration that involved primary and combustion zone over the burner grates varied over a range secondary Go¨bel mirrors. The sample foils were mounted on of 900-1100 °C, and the particle sampling was performed a rotating, low-background, silicon single-crystal sample holder. downstream the boiler at 60 ( 5 °C; therefore, the high Continuous scans at a rate of 1 °/min were applied. By adding temperature and cooling stages were studied separately: repeated scans, the total data-collection time for each sample (1) The degree of volatilization of ash elements was deter- amounted to at least 15 h. A Fourier smoothing was applied mined in the temperature range of 900-1100 °C, using fuel to the scans and the background was removed. Analyses of data from Table 1. Two liquid phases were assumed to coexist: the diffraction patterns were performed, using Bruker software i.e., an oxide/silicate (slag) melt and an alkali salt melt. In together with the PDF2 databank. In addition, a small number (1-3) of impactor samples were analyzed by time-of-flight (27) Lytle, F. W.; Greegor, R. B.; Sandstrom, D. R.; Marques, D. R.; secondary ion mass spectrometry (TOF-SIMS), X-ray photo- Wong, J.; Spiro, C. L.; Huffman, G. P.; Huggins, F. E. Nucl. Instrum. - - electron spectroscopy (XPS), and X-ray absorption fine struc- Methods Phys. Res., Sect. A 1984, 226 (2 3), 542 548. (28) Bale, C. W.; Pelton, A. D. FACT-database of FACT-Win version ture (XAFS) spectroscopy. These analysis methods can provide 3.05, CRCT EÄ cole Polytechnique de Montre´al: Montreal, Quebec, chemical structural information on a molecular level, and, in Canada, 1999. 342 Energy & Fuels, Vol. 18, No. 2, 2004 Boman et al.

Table 3. Summary of Average Gas and Particle Measurement Resultsa b b O2 CO2 CO THC (CH4-equ) PM mass PM mass PM ash fuel (%) (%) (mg/MJ) (mg/MJ) concentration (mg/MJ) median diameter (µm) contentc (%) Burner A S0 1000 361 241 0.37 27 S6 970 375 300 0.38 4 L0 1840 650 377 0.36 10 L6 1630 556 296 0.33 14 B0 12.5 8.0 1850 418 140 48 B6 10.7 9.7 1480 322 114 0.23 15 Burner B S0 7.2 13.2 1610 61 79 54 S6 6.6 13.7 1350 38 57 0.21 15 L0 6.3 13.9 1090 44 88 0.20 60 L6 4.8 15.2 2340 65 88 0.22 37 B0 4.5 15.4 2010 60 101 0.21 63 B6 6.2 14.1 157 0.23 3 Burner C S0 14.1 6.4 940 66 94 0.21 64 S6 13.5 7.0 1310 94 64 0.39 46 L0 12.7 7.8 1430 159 178 0.25 37 L6 11.0 9.3 1680 111 134 0.24 47 B0 13.5 7.1 990 169 183 0.28 49 B6 12.4 8.1 580 189 192 0.39 21 a S0, fresh sawdust; S6, stored sawdust; L0, fresh logging residues; L6, stored logging residues; B0, fresh bark; B6, stored bark. b Average values during burner operation in the nondiluted gas. c Standard ashing method at 550 °C.

Figure 1. SEM images of total PM samples on quartz fiber filters, showing three different typical particle types that could be identified: fine submicrometer-sized particles/aggregates (Type 1), spherical coarse particles (Type 2), and irregular aggregated coarse particles (Type 3). addition, all relevant binary solid and liquid solutions with calcium and magnesium were included. The elements and solution models used in the calculations for the first modeling stage are shown in Table 2. The local conditions that prevail within a burning fuel particle were obtained by assuming dry particles without access to O2 from air. (2) The chemical equilibrium condensation behavior of the volatilized material at 900 and 1100 °C, respectively, during cooling downstream from the boiler were then determined by calculations, down to a temperature of 50 °C. Because all slag is left as bottom ash or deposits on the grate, only the relevant alkali salt models were used for the post-combustion zone (i.e., the liquid salt solution model and relevant binary solid alkali salt solutions models). The elements and solution models used in the calculations for modeling stage 2 are shown in Table 2. The elements carbon, hydrogen, oxygen, and nitrogen were included as the equilibrium levels of CO2, water (H2O), O2, and nitrogen gas (N ), nitrogen monoxide (NO), and nitrogen 2 Figure 2. Particle mass size distributions for the different dioxide (NO2) at 900 and 1100 °C, respectively. biomass fuels combusted in pellet burner (burner B). (No data are given for S0.) Results and Discussion burner A, compared to the other two, because of differ- Experimental Results. The results from the gas and ences in burner construction and operation. Compared particle measurements are summarized in Table 3. The to typical emission levels for residential pellet burners, emission levels of CO were relatively similar between the concentrations of CO, THC, and PM determined in the different burners and fuels, whereas the emissions the present study were relatively high. This was prob- of THC and total PM were significantly higher for ably caused by the nature of intermittent operation Inorganic PM from Biomass Pellet Combustion Energy & Fuels, Vol. 18, No. 2, 2004 343

Figure 3. Elemental composition of the fine PM for the different fuels combusted in burner B (left) and burner C (right). Standard deviations within the fine mode (i.e., composition at different impactor substrates) are shown as error bars. For burner B (using aluminum foils), aluminum was excluded from the analysis; for burner C (using quartz fiber filters), silicon was excluded. typically that is used, which creates less-stable combus- fibers and aluminum foils), compared to that for burner tion situations with increased average and total emis- C (quartz fiber filters). sions. This has also been shown in previous studies29,30 Elemental analyses with ESEM/EDS of Type 2 and and illustrates some of the benefits with using constant Type 3 particles were performed by a significant number volume sampling (CVS) or other similar methods with of random spot analyses of typical particles that were controlled gas flows and sampling conditions (e.g., identified on total-PM samples from burner C with temperature and dilution) for testing and development quartz fiber filters. The “larger” spherical particles of appliances during these types of intermittent opera- (Type 2) contained mainly calcium and phosphorus, with tion at typical low heat outputs. some minor content of magnesium, which indicated Ca/ Three different typical particle types could be identi- Mg phosphates and/or oxides. The formation mecha- fied by the ESEM analysis, in regard to morphology nisms for those particles are not exactly elucidated but (Figure 1): (1) fine submicrometer particles/agglomer- probably involve melt droplet formation and entrained ates, (2) spherical “larger” particles, and (3) irregular melt from the hot furnace zone. The larger coarse-mode “large” agglomerated particles. The PM was dominated particles (Type 3) contained mainly calcium, potassium, by the fine mode (type 1), by mass, and, therefore, even magnesium, chlorine, and sulfur, as well as some more by number. The particles of type 2 and 3 were least sodium, phosphorus, and, potentially, also silicon. These common in PM from sawdust and most common in PM particles presumably are derived from ash aggregates from bark, although the PM varied relatively much in that have been entrained with the flue gases from the size and was limited in mass, which is consistent with fuel bed during combustion with heterogeneous con- the results from the impactor measurements. densed alkali chlorides and sulfates on the surfaces. The particle mass size distributions were, in all cases, Because the particle mass is totally dominated by the dominated by a fine mode with mass median (aero- fine mode with only a minor coarse-mode fraction, the dynamic) diameters (MMD) of 0.20-0.39 µm. In Figure following discussion is focused on the fine PM. This is 2, the results from the impactor measurements with also motivated by the general research interest regard- burner B are shown to illustrate this observation. Minor ing fine combustion particles and their characteristics, fractions of the PM mass were also found in the coarse formation processes, and potential health effects. mode fraction, primarily from the experiments with To study the elemental distribution of the PM within bark and logging residues, although they varied rela- the fine mode (Type 1), careful ESEM/EDS analyses of tively much and was indistinct. From the impactor impactor substrate numbers 3-7 (0.13-0.84 µm) were results and the fact that no significant mass (<0.01 mg) performed for burners B and C. For each substrate, was found in the precyclone in any case, in principle, three area analyses (∼50 µm × 50 µm) on different all particulate material can be considered as PM10 sample stacks were performed. As shown in Figure 3, (particles with an aerodynamic diameter of <10 µm) the fine PM samples were dominated by carbon, oxygen, with an average PM1 of 89.5% ( 7.4% of total PM. Those and the ash-forming elements potassium, sodium, sul- results are in qualitative agreement with previously fur, chlorine, and zinc, with no other elements present reported results13-17 and confirm that the PM from in significant levels. In all cases, potassium and chlorine combustion of wood fuels is dominated by fine particles. were the dominating elements, with minor and varying The chemical characterization portion of the fine PM amounts of sodium, sulfur, and zinc. The carbon can was only made for burners B and C, or just burner B in either derived from unburned material (i.e., soot and/ the extended analysis, and the following results are or organics) or carbonates, presumably alkali carbon- therefore illustrated considering that fact. There were ates, and the oxygen can be derived either from organic two reasons to exclude the samples from burner A: (i) material or from inorganic compounds, presumably the impactor samples contained large amounts of unburned material and the distribution measurements (29) Bachs, A.; Dahlstro¨m, J.-E.; Person, H.; Tullin, C. Swedish National Energy Agency, Report ER 7:1999, 1999. became somewhat inaccurate, and (ii) the filter and foil (30) Aspfors, J.; Larfeldt, J. Swedish National Energy Agency, material were the same for burners A and B (i.e., glass Report ER 14:1999, 1999. 344 Energy & Fuels, Vol. 18, No. 2, 2004 Boman et al.

Figure 4. Relative distribution for the five elements present within the fine mode on a carbon- and oxygen-free basis from the combustion of the different fuels in burner B. For each fuel, the average distribution (in atomic percent) is shown for each impactor substrate 3-7(dg ) 0.13-0.84 µm) with standard deviations as error bars. sulfates and/or carbonates. It can also be seen that the trend for zinc in the PM seemed to be correlated with amount of silicon on the aluminum foils (burner B), as the content of zinc in the different fuels, where bark well as the amount of aluminum on the quartz fiber showed the highest values and sawdust showed the filters (burner C), were negligible, which confirms that lowest values. According to these results, the elemental no significant levels of silicon or aluminum were present distribution within the fine mode also seems to be more in the fine PM. or less homogeneous for all studied fuels, with some In Figures 4 and 5, the average elemental composi- minor remarks. A small trend is observed in that the tions of the fine mode for each fuel are shown for relative sulfur content seems to increase as the particle burners B and C, respectively, on a carbon- and oxygen- size increases, which could indicate that sulfation at the free basis. As can be observed from the figures, the surface of submicrometer-sized particles might occur in elemental distribution pattern for the six different fuels parallel to the accumulation process. was relatively similar between both burners. Further- From the elemental distribution data, some clue more, the relation between the five present ash elements information about the inorganic-phase distribution can also seemed to be relatively equal between the studied also be elucidated. By assuming all alkali present as fuels, except for stored bark (B6), where the PM either chlorides, sulfates, and/or carbonates and com- contained less potassium and sulfur, more sodium and paring the molar (atomic) ratios between the cations (K+ + 2- - zinc, and approximately the same level of chlorine. The and Na ) and the anions (SO4 and Cl ), the presence Inorganic PM from Biomass Pellet Combustion Energy & Fuels, Vol. 18, No. 2, 2004 345

Figure 5. Relative distribution for the five elements present within the fine mode on a carbon- and oxygen-free basis from the combustion of the different fuels in burner C. For each fuel, the average distribution (in atomic-%) is shown for each impactor substrate 3-7(dg ) 0.13-0.84 µm) with standard deviations as error bars. of carbonates can potentially be estimated. In Figure resembled that of potassium sulfate (K2SO4) was ob- 6, the corresponding molar ratios within the fine mode served. In regard to the alkali sulfates, the situation is for each fuel are shown. Zinc was excluded because the complicated by the fact that aphthitalite is a solid content was relatively low. The molar ratios differed solution with a considerable range of composition where somewhat between the two burners. In burner B, the potassium and sodium are varying. No alkali carbonates trend was slightly decreasing as the particle size were identified by the XRD analyses. An estimated increased, which is possibly an indication of the pres- quantification from the TOF-SIMS data also showed ence of carbonates in the larger particle size ranges. that only some few percent (<4%) of the alkali in the However, no such trend could be seen for burner C and fine PM consisted of carbonates. In Figure 7, typical the molar ratio was >1.0 in all cases, presumably diffractograms of the fine PM from the combustion of indicating no presence of carbonates. the different fuels is given, where the main peaks used The impactor substrate numbers 3, 5, and 7 from all for phase identification are marked with numbers. From experiments with burner B were further analyzed with the EDS analyses, it was apparent that zinc also should XRD for identification of the crystalline phases. Potas- be present in some form. Considering the remaining sium chloride (KCl) could unambiguously be identified peaks in the diffractograms, the only zinc-containing in all samples. Aphthitalite (K3Na(SO4)2) was present phase in the PDF-2 database that possible could be a in most of the samples. In some cases, a pattern that choice was Zn4SO4(OH)6‚4H2O. However, it is not likely 346 Energy & Fuels, Vol. 18, No. 2, 2004 Boman et al.

+ + 2- - Figure 6. Molar ratios between alkali cations (K and Na ) and anions (SO4 and Cl ) in the fine PM from burner B (left) and burner C (right).

Figure 7. XRD diffractograms of the fine PM from impactor substrate 5 (dg ) 0.33 µm) from the combustion of the different pelletized fuels. The most relevant peaks used for phase identification are marked with numbers (1, KCl; 2, K3Na(SO4)2; and 3, possibly a zinc phase, although presently unidentified) and the peaks marked by vertical lines denote aluminum from the sampling foils. (S0, fresh sawdust; S6, stored sawdust; L0, fresh logging residue; L6, stored logging residue; B0, fresh bark; and B6, stored bark.) that this specific zinc phase should be present in the which presumably can be explained by the presence of fine PM in this case. One reason for this is that the some type of layer structure. specific 4-hydrated phase suggested by the PDF data- The complementary analyses performed with XPS bank is an unstable intermediate phase in the de- and XAFS gave additional chemical information on a hydration process between the corresponding 5- and molecular level and, more specifically, information about 31 3-hydrated phase. Furthermore, the fact that the two the immediate chemical surroundings of zinc. Both XPS relevant peaks in the low 2θ region of the diffractograms and XAFS were capable of identifying Zn-O interac- ) ) (2θ 8.5° and 17.1°, corresponding to d 10.4 and 5.2 tions, where O atoms are most possibly derived from Å, respectively) still remains, even after heating the ZnO or Zn(OH)2; however, some of this oxygen could also samples to 400 °C, indicates that a hydrated phase is 2- 2- be derived from anions such as SO4 or CO3 . Besides less probable. However, the presence of two prominent the Zn-O interaction, the “fingerprint” from XAFS peaks at such low 2θ values must be derived from a analysis also revealed distinct Zn-Zn interactions, as structure with relatively long crystal-plane distances, well as interactions between Zn and some possible - 2- 2- (31) Bear, I. J.; Grey, I. E.; Madsen, I. C.; Newnham, I. E.; Rogers, anion, presumably Cl or SO4 or CO3 . Therefore, the L. J. Acta Crystallogr. Sect. B: Struct. Sci. 1986, 42,32-39. concise chemical information indicated that it is a Inorganic PM from Biomass Pellet Combustion Energy & Fuels, Vol. 18, No. 2, 2004 347

Table 4. Fraction of Total Fuel Input Experimentally Found in Fine (<1 µm) Particulate Matter for the Pellet Fuels of Different Raw Materials Combusted in a Pellet Burner (Burner B)a Fraction of Total Fuel Input (%) fresh sawdust, stored sawdust, fresh logging residues, stored logging residues, fresh bark, stored bark, element S0 S6 L0 L6 B0 B6 potassium 9.2 ( 4.9 7.0 ( 4.4 8.8 ( 5.5 5.5 ( 3.8 13.8 ( 4.2 1.9 ( 1.0 sodium 14.4 ( 7.9 8.9 ( 6.5 7.5 ( 4.4 5.1 ( 3.5 16.4 ( 8.1 3.3 ( 2.6 sulfur 7.1 ( 2.8 8.7 ( 3.1 7.2 ( 3.6 6.9 ( 3.9 38.5 ( 10.2 7.2 ( 2.7 chlorine 106 ( 59 57.5 ( 34.2 48.3 ( 33.7 47.2 ( 32.3 70.5 ( 26.2 48.9 ( 30.5 zinc 97.0 ( 54.0 75.6 ( 36.0 61.5 ( 45.3 43.4 ( 33.4 54.9 ( 27.5 112 ( 73 a Errors represent the standard deviations derived from the average elemental contents at different size classes within the fine mode. complex zinc phase and not pure ZnO as been suggested previously for other fuels.11,21,22 However, the precise chemical speciation of zinc identified in the fine particles from the combustion of woody biomass still remains to be determined and dedicated experiments with further careful analysis will be performed soon. The particular interest for zinc is motivated by the fact the zinc, beside the alkali metals, has been shown to be the major element in these biomass combustion PM samples and it has also been proposed to be a culprit metal, in regard to PM exposure and some toxicological effects.32-35 Comparison with Calculated Chemical Equilib- rium Results. The fine PM mainly consists of alkali salts; therefore, the behavior of those elements is of vital importance for particle formation and characteristics. Sodium and potassium will be captured to a varying Figure 8. Typical predicted chemical equilibrium distri- degree in the bottom ash as silicates (slagg) and/or as bution diagram for potassium for combustion of softwood salt mixtures, whereas the remainder will volatilize and sawdust. subsequently condense as fine particles. A significant results are shown in Table 4. The chemical equilibrium but varying silicate (slag) formation was experimentally results for stored sawdust showed that ∼20% and 68% determined (2%-46% of the total ash constituents), of the total amount of potassium is predicted to be which is further reported and discussed elsewhere.36 In volatilized as chloride, sulfate, and hydroxide at 900 and Figure 8, a typical predicted distribution diagram for 1100 °C, respectively, whereas the remainder is cap- potassium is shown for stored sawdust (S6). The be- tured as silicates or a salt-liquid solution. The corre- havior of zinc will be discussed separately later in the sponding values for sodium are 3.5% and 21%. For all text. Qualitatively, the global calculations predicted other studied fuels, except stored bark (B6), the distri- potassium, sodium, sulfur, and chlroine to be the only bution of potassium and sodium showed similar results. elements to be volatilized to any significant extent. This For stored bark, basically all alkali was predicted to is in agreement with the experimental results where form aluminum silicates up to 1100 °C. The fractions all other measured elements where found to be captured of theoretically volatilized potassium were not influ- in different solid phases in the bottom ash. enced by the air-to-fuel ratio, i.e., the same degree of During combustion, all volatilized potassium and volatilization was predicted under local reducing condi- sodium will occur as solid phases at ambient tempera- tions that prevail within a burning fuel particle λ ) 0 tures, and the degree of volatilization for those elements as those under fully oxidized conditions λ ) 1.1-2.0. will therefore determine the emissions of inorganic fine Because the maximum temperature in the combustion PM. Only a marginal fraction of coarse-mode particles zone during the experiments was estimated to 1100- were present on which alkali vapors may condense; 1150 °C in all cases, the experimentally determined therefore, almost all volatilized potassium and sodium fraction of alkalismainly potassiumsseems to be lower will accordingly end up as fine PM. On the basis of the than what was predicted by chemical equilibrium. This EDS analyses, the fractions of fuel input for the present may be explained by varying temperatures at the burner elements experimentally found in the fine PM for each grate, where the ash elements are volatilized and/or fuel combusted in one burner was calculated, and the more potassium silicate formation occurs experimentally than theoretically predicted. (32) Adamson, I. Y. R.; Prieditis, H.; Hedgecock, C.; Vincent, R. Model calculations of the condensation processes of Toxicol. Appl. Pharmacol. 2000, 166, 111-119. (33) Fernandez, A.; Davis, S. B.; Wendt, J. O. L.; Cenni, R.; Young, the volatilized material from the six different fuels R. S.; Witten, M. L. Nature 2001, 409 (6823), 998. showed some common qualitative general trends but (34) Kodavanti, U. P.; Schladweiler, M. C. J.; Ledbetter, A. L.; Hauser, R.; Christiani, D. C.; Samet, J. M.; McGee, J.; Richards, J. differed quantitatively by a relatively large amount. KCl H.; Costa, D. L. Toxicol. Sci. 2002, 70,73-85. showed two different behaviors. For S6, L0, L6, and B0, (35) Riley, M. R.; Boesewetter, D. E.; Kim, A. M.; Sirvent, F. P. homogeneous condensation of KCl(g) to KCl(s) was Toxicology 2003, 190, 171-184. ∼ (36) O¨ hman, M.; Boman, C.; Hedman, H.; Nordin, A.; Bostro¨m, D. predicted at 600 °C. For S0 and B6, the sulfation of Biomass Bioenergy, in press. KCl(g)toK2SO4(s) occurred at 900 and 750 °C, respec- 348 Energy & Fuels, Vol. 18, No. 2, 2004 Boman et al.

The volatilized gaseous zinc may be oxidized, sulfated, chlorinated, and/or carbonated, as well as hydrated during the cooling of the flue gases.

Conclusions (1) Alkali salts in the fine mode (<1 µm) dominate the mass of inorganic particulate matter (PM) from the combustion of pelletized biomass fuels (i.e., sawdust, logging residues, and bark) in all studied residential pellet burners. This indicates that gas-to-particle conversion, followed by coagulation processes, are the main particle formation mechanism. (2) The elemental distribution within the fine mode seems to be relatively homogeneous, with potassium and chlorine as the dominating elements, except from the Figure 9. Chemical equilibrium diagram for potassium combustion of stored bark, where sodium and potassium during cooling, calculated for stored sawdust (S6). Only the major phases are marked with headings. were present at the same level. (3) KCl was the dominant inorganic phase in all cases, tively, with stable KCl(s) forming below ∼100 °C. By with minor but varying amounts of K3Na(SO4)2 and, in assuming super-equilibrium residual concentrations of some cases, also K2SO4. SO2 that are due to kinetically limited calcium sulfate (4) The reduced amount of potassium within the fine formation, different alkali sulfates were predicted to PM from stored bark can be explained by a larger form at lower temperatures. At temperatures near capture of potassium in the bottom ash (i.e., silicate/ sampling conditions (<150 °C), solid forms of KCl, slag formation). K2SO4,K3Na(SO4)2,K2CO3, KHCO3, and KNO3 were (5) With some constraints, the amounts and speciation shown to be stable, although not present in all cases of the inorganic PM seemed to be quite similar to that and with quantitative differences between the fuels. In predicted by chemical equilibrium calculations. Figure 9, the theoretical distribution of the volatilized (6) Zinc is almost fully volatilized in the reducing potassium at 950 °C down to 50 °C is shown for stored atmospheres of burning fuel particles, presumably sawdust (S6). Because of kinetic restrictions at low forming a more complex solid phase than previously temperatures and excess amounts of SO2, sulfates will suggested (ZnO). However, the formation mechanism preferably be present, instead of carbonates and ni- and exact composition remain to be elucidated. trates. As shown previously, KCl, K3Na(SO4)2, and, in some cases, K SO , were the only alkali phases identi- 2 4 Acknowledgment. Henry Hedman (Energy Tech- fied experimentally. nology Center, Piteå) is acknowledged for his valuable The experimental results clearly indicate that the help during the experimental work. Docent Per Persson major portion (∼50%-100%) of the total zinc input (Department of Inorganic Chemistry, Umeå University) ended up in the fine PM. Using global oxidizing condi- is acknowledged for performing the XAFS analyses tions, zinc was mainly predicted to form different solid and Dr. Andrei Shchukarev (Department of Inorganic phases, i.e., silicates and oxides, with only some few Chemistry, Umeå University) is acknowledged for per- percent (1%-18%) volatilized as gaseous zinc, even at forming the XPS analysis. Lastly, the financial support 1100 °C. However, in reducing atmospheres of burning from the Center for Environmental Research (Umeå, fuel particles, zinc is predicted to be almost fully Sweden) and the Swedish National Energy Agency is volatilized as gaseous zinc. The mechanistic pathways gratefully acknowledged. from volatilized gaseous zinc at high temperature to the form experimentally found are not yet fully understood. EF034028I

[Manuscript]

Gaseous and particulate emissions from residential wood log and pellet stoves - experimental characterization and quantification

Christoffer Bomana*, Esbjörn Petterssona,b, Anders Nordina, Roger Westerholmc, Dan Boströma

* Corresponding author: Telephone; +46-90-786 6756 Fax; +46-90-786 9195 E-mail: [email protected]

Abstract Present residential wood combustion is considered to be a major pollution source in urban environments, however with a significant potential for increased use of biomass and reduction of emissions by using new technologies. The emissions of hydrocarbons and particulate matter (PM) are of special concern and careful evaluation of the potential adverse health effects is needed. Despite the previously well documented extent and importance of these pollution sources and components, relatively limited information is available concerning detailed emission characteristics and quantification. The objective of the present work was to determine the characteristics and quantities of gaseous and particulate emissions from combustion in residential wood log and pellet stoves and report emission factors for the most important emission components. A large number of gaseous and particulate components were studied for wood log and pellet stoves with systematic variations in fuel, appliance and operational properties. Considerable variability of emission performance in the wood log stove was determined, with potentially very high emissions of products of incomplete combustion (PIC) during specific conditions. However, by proper technical and/or operational measures the emission performance from these kinds of wood log appliances can be rather well controlled. The emissions of PIC as well as PM from the wood log stove were generally considerably higher than from the pellet stoves. Accordingly, the use of up-graded biomass fuels with controlled combustion conditions gives advantageous conditions for optimization of the combustion process. There is, however, still a potential for further minimization of PIC emissions in residential pellets applications, especially at low loads. The extensive characterization of hydrocarbons included 34 specific VOC´s and 43 specific PAH´s. Beside methane, ethene, acetylene and benzene were the most dominant VOC´s and the dominating PAH´s were in all cases phenantrene, fluoranthene and pyrene. Fine sub-micron particles dominated in all cases the PM with 80-95% as PM1. The minor coarse fraction consisted of carbonaceous unburned fuels residues with inclusions of calcium containing grains (1-10 µm). Fine particle mass median and count diameters were in the range of 100- 300 nm and 50-250 nm respectively with number concentrations at 4.6*1012-1.1*1014 particles/MJfuel. Total PM emissions varied in the range of 160-37 mg/MJfuel for the wood log stove and 15-46 mg/MJfuel for the pellet stoves. During optimized combustion of softwood pellets, the PM is totally dominated by inorganic particles with emission factors at 15-20 mg/MJfuel. Potassium, sulfur and chlorine dominated the fine inorganic PM in the form of K2SO4, K3Na(SO4)2 and KCl. Sodium and zinc were also found as important elements in the fine PM.

Keywords: biofuels, residential combustion, wood logs, pellets, emissions, particulate matter, hydrocarbons

1 Introduction

Residential wood combustion (RWC) is considered to be a major source of ambient air pollution in certain urban areas and the potential adverse health effects of volatile organic compounds (VOC), polycyclic aromatic hydrocarbons (PAH) and particulate matter (PM) have recently been of special concern [1-7]. Compared to modern combustion technologies, the majority of the presently used residential wood combustion appliances often suffer from poorly optimized conditions, resulting in considerable emissions of products of incomplete combustion (PIC), e.g. CO, hydrocarbons and carbonaceous soot particles. It has been shown [8-15] that the PM emitted from these kind of small-scale combustion devices are mainly sub-micrometer sized (<1 µm) fine particles and there is an increasing interest in their formation mechanisms, characteristics and implications to human health [16, 17]. Further, the potential for new biomass combustion technologies using up-graded pelletized fuels is significant with possibilities of drastically decreased emissions of PIC [18, 19]. Wood pellets is in general a clean, dry and easily fed fuel to be used in dedicated boilers, burners and stoves on the residential market. The presently used raw materials for production of fuel pellets are generally stem-wood assortments (~95%) such as sawdust, planer shavings or dried chips from sawmills and the wood working industry while bark, agricultural residues and other forest fuels are used only occasionally [20]. In light of the ongoing ambitions to increase the use of biomass as a renewable and CO2-neutral energy source as well as the issue concerning ambient air quality and potential environmental health effects, it is important to quantify and carefully determine the characteristics of the particulate and gaseous emissions from different sources. Despite the previously well documented extent and importance of these pollution sources and pollution components, relatively limited information about residential biomass emissions in general and detailed PM characteristics in particular has been reported in the open literature. However, it is a rather well-known fact that the emission factors from different kinds of residential biomass systems can vary significantly, depending on a number of factors, e.g. appliance type, fuel properties and operation [18, 19, 21, 22].

In Sweden, an extensive national research program financed by the Swedish Energy Agency "Emissions and Air Quality" with the sub-programme "Biofuels, Health and Environment", has been in progress during the years of 2001-2004. The overall objective with the sub-program was to describe the influence of the present use of biofuels for heat production in small and medium-sized combustion appliances regarding the emission distribution, air quality and potential health effects. Additionally, the program should aim to describe the situation in a possible future with increased use of biomass and also concern the potential combustion technology development. Within the residential sector, both water based heating systems (i.e. boilers) and air based heating systems (i.e. stoves and other fireplaces) were included for detailed emission quantification and characterization, although the work were divided between different research groups [23]. The present work, which was a part of the aforementioned research program, had the specific objective to determine the characteristics and quantities of gaseous and particulate emissions from combustion in residential wood log and pellet stoves, and report emission factors for the most important emission components.

Materials and Methods

Appliances, Fuels and Experimental Procedures For the wood log study, a typical natural-draft wood stove with a nominal effect of 9 kW was used and fired under different conditions simulating the potential variations under practical use. The stove is one of the most commonly installed modern wood log stoves in Sweden and also of a type that very well represents the present market at least in the Nordic countries. It was also recently tested and certified according to the national certification criteria "P-marking" [24]. The wood log fuels used consisted of birch (Betula) and conifer wood, i.e. Scots pine (Pinus sylvestris) and Norway spruce (Picea abies), with controlled

2 variations in size and moisture content as discussed below. The characteristics of the wood log fuels are given in Table 1.

Table 1 Characteristics of the wood log fuels.

Unit Birch Pine Spruce Effective heating MJ/kg dry weight 18.98 18.98 19.02 value (d.wt.) Moisture content* % d.wt. 8/16/23 8/16/23 8/16/23 Volatile matter % d.wt. 85.8 85.1 83.4 Ash content % d.wt. 0.6 0.4 0.6 Carbon content % d.wt. 51.2 51.0 51.2 Hydrogen content % d.wt. 6.0 6.0 5.9 Oxygen content % d.wt. 42.0 42.4 42.1 Nitrogen content % d.wt. 0.2 0.2 0.2 Chlorine content % d.wt. 0.01 0.02 0.01 Sulfur content mg/kg d.wt. 89.8 68.3 71.5 * Varied according to the experimental design given in Table 2.

The effects of wood log size (i.e. cleaving degree) and fuel moisture content as well combustion intensity were determined by varying these factors using birch wood. In addition, two reference combustion experiments with conifer wood were performed. To try to simulate the conditions in other commonly used fireplaces without ceramic lining, the high- temperature ceramic stone tiles normally present in the stove were taken out in some experiments resulting in a non-lined furnace and thus colder walls and combustion conditions. The effect of varying combustion intensity was determined by combined changes of chimney draught in the stove and the open area of the combustion air inlet.

Overall, a number of 8 combustion experiments with the wood log stove were performed and the experimental design is shown in Table 2. The design was not statistically based to cover all possible variable settings, but aimed at simulating three different stove operation modes during practical use; 1) "normal" stove conditions for both birch and conifer wood logs, 2) cold and air starved conditions using moist and large birch wood logs and finally 3) intensive combustion with high draught conditions using extra dry and cleaved birch wood logs. The wood firing procedure was accomplished according to a typical procedure according to the firing instructions from the manufacture. Initially, 3.5 kg fine splitted wood logs with bark were used as kindling wood. After about 30 minutes, a glowing char bed occurred and a first batch of 3 kg test wood consisting of 3-5 logs approximately 0.3 m long was introduced. The front door was then closed and the wood batch usually lighted subsequently. However, in some cases the lightning process was elongated, and the ash damper was temporarily opened to facilitate the lightning process, according to normal procedure. After additional 90 minutes approximately, when the first batch of test wood had been combusted and the CO2 concentration decreased to about 5%, a second and final batch of test logs was introduced.

3 Table 2 Experimental design for the wood stove experiments with three different operation modes; 1) "normal" stove conditions using "normal" birch and conifer wood respectively, 2) cold and air starved conditions using moist and large birch wood logs and 3) intensive combustion with high draught conditions using extra dry and cleaved birch wood.

Exp. nr. Operation Wood Ceramic Air inlet Chimney Fuel Log mode species stone opening draught moisture cleavage lining (%) (Pa) (%) degree (yes/no) (times) 1 2 Birch no 40 -10 23 1 2 1 Birch yes 60 -15 16 2 3 1 Birch yes 60 -15 16 2 4 3 Birch yes 100 -20 8 3 5 3 Birch yes 100 -20 8 3 6 1 Spurce yes 60 -15 16 2 7 2 Birch no 40 -10 23 1 8 1 Pine yes 60 -15 16 2

Combustion experiments were also performed with two types of commercial pellet stoves. One of the stoves (A) was a modern Swedish stove certified according to the national certification criteria "P-marking" [25], and the other stove (B) was a classic North American pellet stove in its previous design before it became certified according to the "P-marking" criteria. The pellet stoves represented two different operation and modulation principles at low heat out-put. Burner A works with continuous operation and fuel feeding between 2 and 6 kW, while stove B works with intermittent operation at three pre-set heat out-puts between 4 and 9.5 kW. Two typical softwood pellets produced from stem-wood based sawdust of Scots pine (Pinus sylvestris) and Norway spruce (Picea abies), were used. The characteristics of the pellet fuels are given in Table 3.

Table 3 Characteristics of the pelletized softwood fuels.

Unit Pellet fuel 1 Pellet fuel 2

Pellets diameter mm 6 8 Raw material Unknown mixture of >90% Pine and Pine and Spruce the rest Spruce Effective heating value MJ/kg dry weight 19.2 19.3 (d.wt.) Moisture content % d.wt. 8.2 7.7 Volatile matter % d.wt. 84.6 85.1 Ash content % d.wt. 0.4 0.3 Carbon content % d.wt. 50.9 51.6 Hydrogen content % d.wt. 6.3 6.3 Oxygen content % d.wt. 42.4 41.8 Nitrogen content % d.wt. <0.1 <0.1 Chlorine content % d.wt. <0.01 <0.01 Sulfur content mg/kg d.wt. 68.1 84.7

4 The pellet stove experiments were performed with systematic variations of chimney draught, fuel load and pellet diameter, according to a full (23) factorial design [26, 27] with 8 "corner" experiments and 3+3 center replicates (for 6 and 8 mm pellets respectively) for each stove. Overall, 14 combustion experiments with each pellet stove were performed and the software program MODDE 5.0 [28] was used to facilitate the experimental design and evaluation of the results. In Table 4, the factors used and their design levels are shown with their high (+), medium (0) and low (-) values given.

Table 4 Factors and their design levels for the full factorial (23) experimental design used in biomass fuel pellet stove experiments.

Unit Abbreviation (+) (0) (-)

Pellet diameter mm Dia 8 - 6 Fuel load kW Load 5 3.5 2 Chimney draught Pa Draught 30 17.5 5

All the emission measurements were performed in a previously designed and evaluated dilution sampling set-up that enables constant volume sampling (CVS) under controlled and standardized conditions [29]. The system is based on whole flow dilution with dried and temperature controlled dilution air that is filtered through a high-efficiency particulate air (HEPA) filter. The main purposes of using such dilution system are that it enables; 1) sampling at lower, near-ambient, temperature and 2) accurate emission quantification during transient exhaust flow conditions. The sampling temperature and dilution ratio during the different experiments varied from 45 to 75°C and 1.6 to 3.6 times, respectively.

Main gases measurements The concentrations of O2 and CO2 were continuously monitored in the raw undiluted flue gases by an electrochemical sensor and non-dispersive infrared spectroscopy (NDIR) respectively, as well as in the diluted gases by a paramagnetic sensor and NDIR respectively. The dilution ratio was defined as the volume ratio between the total diluted flow and the undiluted flue gas and calculated as the ratio between the CO2 concentrations in the undiluted and diluted gas. Continuous monitoring of total organic compounds (TOC) by a flame ionization detector (FID), NO by chemiluminescence and CO by NDIR were also performed in the diluted gases. All gas components were analyzed for cold and dry gases, except for TOC for which the sampling line was kept at 120°C.

VOC sampling and analysis Volatile organic compounds were sampled in the raw flue gases, through a 250 ml washing bottle to 10 L Tedlar bags. The bag samples were analyzed by direct injection in two separate gas chromatography (GC) flame ionization detection (FID) systems; firstly a Chrompack back-flush system containing a pre-column and a PLOT Al2O3 column for identification of C1-C6 aliphatic compounds (i.e. alkanes and olefines) and secondly a CP- Wax 52 CB column for identification of (mono)aromatic volatile hydrocarbons. Baseline separation of all hydrocarbons, including 1,3–butadiene and propyn, were established. The GC was calibrated with propane (884 ppm) and a mixture of C4-hydrocarbons was used for accurate peak identification. Of the extracted flue gases, 50 ml were also collected from each Tedlar bag using a syringe and injected through a Tenax-adsorbent for analysis mainly of C6- C9 aromatic volatile hydrocarbons and butyl acetate but also for C10 monoterpenes (wood log stove experiments) and C8-C10 alkanes (pellet stove experiments). The Tenax tubes were stored in a freezer before analysis by IVL Swedish Environmental Research Institute Ltd in

5 Gothenburg by using a GC-FID system equipped with thermal desorption/auto-injection (Perkin Elmer ATD 400). To enable increased detection possibilities and accuracy mainly for 1,3-butadien, 50 ml of the Tedlar bag samples from a total number of 8 (4+4) "corner" experiments with 6 mm pellets for the two stoves respectively were also injected through a Carbopac-adsorbent. The Carbopac samples were then analysed according to the same procedure as for the Tenax-adsorbent samples. For the wood log stove experiments, however, no such Carbopac samples were taken and 1,3-butadien concentrations were instead determined from the GC direct injection analysis of the Tedlar bag samples previously described. External standards were used for all compounds analyzed by GC-FID from the adsorbent sampling. Transport blanks of the VOC adsorbents were collected at different occasions during the campaigns, but were in all cases insignificant. The specific VOC compounds analyzed in the measurements campaigns are accounted for in the results.

PMtot and PAH sampling and analysis Sampling of total PM mass concentrations (PMtot) was performed isokinetically in the dilution tunnel using conventional equipment with glass fibre filters (MG 160 with a diameter of 90 mm, Munktell Filters, Sweden). After at least 12 hours of conditioning in a desiccator, the PM filters were analyzed gravimetrically before and after sampling with an analytical balance (± 10 µg) and the total sampled mass of PM determined.

Particulate PAH emission samples were collected on the previously mentioned glass fibre filters. Polyurethane foam (PUF) plugs (75 mm diameter x 50 mm, 60 PPI; Specialplast AB, Sweden) were used for sampling of the semi-volatile PAH. The PUF plugs were washed prior to use as described elsewhere [30]. After sampling, the filter and PUF samples were Soxhlet extracted separately with 225 mL of acetone (p.a.; Merck, Germany) for 12h. The extract was evaporated under reduced pressure and stored at -18°C until analysis. The crude extracts were fractionated into two fractions before chemical analysis, as described elsewhere [31] but using other solvent volumes. The PAH fraction was analyzed by gas chromatography- mass spectrometry (GC-MS) for quantification as described in detail elsewhere [32]. Prior to fractionation, internal standards were added (d10-phenanthrene, d10-pyrene, d12- benz(a)pyrene, picene, and 2,2'-binaphthyl) for quantification. A PAH standard mixture with internal standards was used for the determination of retention times and response factor calculations. Background PAH samples were collected on different occasions during the campaigns and average background concentrations for specific compounds were estimated and corrected for in the evaluation of the results. The background concentrations of PAH were in general very low and most often insignificant compared to the emission concentrations, only relevant to consider during the experiments with highest combustion efficiency, i.e. high load (5 kW) combustion in the pellet stoves. Overall, 43 specific PAH compounds were analyzed and reported in the results.

Particle size distribution and number concentration measurements A 13 stage low-pressure cascade impactor (LPI, Dekati Ltd, Finland) was used to determine the aerodynamic particle mass size distribution within the range of 0.03-10 µm. Diluted sample gas was drawn through the impactor at a flow rate of 17.9 L/min through an exchangeable nozzle that enables sampling as close to isokinetic velocity as possible. A pre- cyclone with cut-size of approximately 8 µm during the present conditions was used before the impactor. Aluminum foils (25 mm in diameter) were used as impactor substrates and aluminum cups were used for PM collection in the pre-cyclone. The impactor plates and cyclone cup were analyzed gravimetrically before and after each experiment with an analytical balance (±1 µg) and the size fractionated mass of PM was determined. The gravimetrical analyses were performed after the substrates had been conditioned in a desiccator for at least 12 hours before and after sampling.

A scanning mobility particle sizer (SMPS) system was used to classify particles regarding number size distribution and concentration within 16 to 673 nm (equivalent mobility

6 diameter). The system consisted of a differential mobility analyzer (DMA model 3071A, TSI Inc, USA) and a condensation particle counter (CPC model 3010, TSI Inc, USA). Sample gas flow to the SMPS system was additionally diluted by two ejector diluters (Dekati Ltd, Finland) in series that was supplied with dried pressurized and high-efficiency particulate air (HEPA) filtered air heated to 60-100 °C at the first dilutor and kept at ambient room temperature at the second. The total dilution ratio of the two diluters varied in the range of 55-59 and 52-61 for the pellet (6 mm) and wood log stove experiments, respectively. Total scan times of 3 minutes, i.e. 120 s up and 60 s down, were applied. According to a previous study of biomass combustion particle emissions using the same type of fine particle sampling set-up the penetration of particles <1 µm through the sampling system should be close to 100% [33].

Particle morphology and chemical characterization Selected samples from the LPI and cyclone measurements were analyzed for particle morphology and elemental composition, using a Philips model XL30 environmental scanning electron microscope-field emission gun (ESEM-FEG) equipped with an EDAX energy- dispersive spectroscopy (EDS) detector. Complementary microscopic analyses of fine particle samples were also performed using a Cambridge Stereoscan 360 IXP scanning electron microscope.

Further, a number of impactor substrates with fine particle samples were analyzed by X-ray diffraction (XRD) for identification of crystalline phases. The XRD analyses were performed using a Bruker d8Advance instrument in θ–θ mode, with an optical configuration involving primary and secondary Göbel mirrors. The sample foils were mounted on a rotating low- background Si-single-crystal sample holder. Continuous scans at a rate of 1 degree/min were applied. By adding repeated scans, the total data-collection time for each sample amounted to at least 15 hours. Analyses of the diffraction patterns were done by Bruker software together with the PDF2 databank.

Sampling periods and data collection During batch wise combustion such as in wood log fireplaces, transient conditions with varying temperatures and air to fuel ratios generally causes significant variations in performance and emission characteristics, both quantitatively and qualitatively. Three different and typical phases during a combustion cycle can normally be identified; 1) initial start-up phase, 2) main load (intermediate) phase and 3) charcoal burn-out phase, although the appearance and significance of these phases can vary somewhat between different situations. Traditionally, considerable emissions of PIC arise during the start-up phase before more stable combustion conditions have been established (i.e. intermediate phase). In the present study, the start-up phase was defined as a 15 minute period after a batch of wood logs had been added. The following intermediate phase was considered continue for approximately additionally 30-40 minutes until the CO2 concentrations in the flue gases (i.e. combustion intensity) started to decrease and the burn-out of the charcoal with increased CO emissions became predominant. The burn-out phase was considered to continue until the CO2 concentrations in the flue gases decreased below 4%. In Figure 1, a typical combustion experiment with the wood log stove is therefore illustrated by the concentrations of O2, CO and TOC over the two combustion cycles with the different combustion phases (i.e. start-up, intermediate and burn-out) marked out. In the present experiments on wood log and pellet stoves, average quantifications of the main gaseous and particulate components were determined during varying combustion situations relevant for practical conditions. In addition, detailed fine particle characterizations were performed during the different combustion phases in the wood log stove experiments and during continuous operation at different fuel loads as well as start-ups (stove B).

7 20 20000 O2 TOC 2nd wood batch supply 18 18000 CO 16 16000 1st wood batch supply C 14 A 14000

12 12000 B

(%) 10 10000 2 O 8 8000

6 6000 CO and TOC (ppm) diluted 4 4000

2 2000

0 0 13:26:24 13:55:12 14:24:00 14:52:48 15:21:36 15:50:24 16:19:12 16:48:00 17:16:48

Figure 1. Illustration of a typical combustion experiment in the wood stove over two combustion cycles. The different phases during combustion of a batch of wood logs are marked as; (A) Start-up, (B) Intermediate phases and (C) Burn-out phase.

Average concentrations of CO, TOC and NOx were calculated from the wood log stove experiments, including two complete combustion cycles starting from the introduction of the first main batch of wood logs and in progress until the CO2 concentration had decreased to about 4% during combustion of the second batch. The PMtot and PAH measurements during the wood log stove experiments were also accomplished to give "average" data, although by sampling during only one combustion cycle, i.e. the second batch. The corresponding data for the main gases as well as PMtot/PAH from the pellet stove experiments are 1-3 hours average values during continuous operation at low and high load respectively for stove A as well as high load for stove B, and as average values during 2-3 combustion cycles (i.e. 3-5 hours) of intermitted operation at low load for stove B.

The presented VOC data for the wood log stove are taken from 3 times 1 minute of composite sampling during each start-up phase of the first batch of wood logs after the kindling wood and 5 times 1 minute of composite sampling during 30 minutes of the more stable intermediate phase of the last batch. In the subsequent calculations of average VOC concentrations, typical start-up and intermediate phases were estimated to constitute 15 and 45 minutes respectively. For the pellet stoves, the corresponding VOC data are taken from 5 times 1 minute of composite sampling during 30 minutes of continuous operation for both stoves at high load and also for stove A at low load. For stove B during intermittent operation at low load, the VOC data are taken from 3 times 1 minute of composite sampling during two start-up phases and 10 times 1 minute during the stable continuous phase. Presented average VOC concentrations were then calculated by estimating typical start-up and intermediate phases to constitute 5 and 25 minutes respectively.

The particle measurements with the LPI during the wood log stove experiments were performed during the start-up phase (3 times 10 s of the first 15 minutes) and the intermediate phase (5 times 10 s during 30 minutes) separately. For pellet stove A at all loads as well as stove B at high load, the LPI measurements were performed during

8 approximately 20 minutes of continuous operation. At low load for stove B, sampling during both start-up phases (2 periods per sample) and continuous intermittent operation (start-up excluded) were performed separately. The fine particle measurements with the SMPS were performed as continuous scans during the second batch for the wood log stove tests as well as during periods of 2-4 hours in all pellet stove experiments. This procedure allowed for extracting specific information of the number size distribution and concentration during different operation modes for the different tested appliances.

Results and Discussion

Emission factors of main components All combustion tests were successfully performed as planned according to the experimental designs. In Table 5 and 6, the resulting emission concentrations of the main gaseous and particulate emission components determined are summarized and presented as mg/MJfuel (µg/MJfuel for PAH). These can easily be re-calculated as mg(or µg)/kgdry weight by using the effective heating values given in Table 1 and 3. For the wood log stove experiments, the emission factors from the whole experimental matrix (i.e. mode 1, 2 and 3) as well as for mode 1 and 2 only (i.e. mode 3 excluded), are presented separately, as discussed later in the text. For the pellet stoves, the corresponding emission factors are presented for high and low load respectively for each of the two tested stoves. This enables a comparison and discussion concerning the emission performance at different fuel loads and operation conditions for typical pellet stove appliances. In

The emissions of gaseous PIC (e.g. CO, VOC and PAH) from the wood log stove experiments were generally significantly higher compared to the pellet stove experiments. Significant quantitative and qualitative variations within the experimental operational designs were also determined. Generally, the emission factors and their potential variability determined in the present study were in the same range as previous reported data for wood log stoves [1, 8, 12, 34, 35], with large variations in CO, VOC and other gaseous PIC relatively small variations in NOx. The emissions of PMtot varied less but still significant during the different experiments and were shown to be somewhat lower than previously reported data. Further, the variability of the PAH emissions was shown to be considerable during the present wood log stove experiments. Such large variations in PAH data for wood combustion in similar kind of appliances have also been reported in previous studies [1, 34-37] almost with maximum values of the same magnitude as presently determined.

The emissions of NOx including all wood log and pellet stove experiments varied between 50 and 60 mg/MJfuel. The dominating NOx-specie in the flue gases was in all cases NO (75-99%) and assuming fuel nitrogen to be the dominating N-source for NOx formation at these moderate combustion temperatures [38-40] the range corresponds to 14-21% and more than 30-38% of the fuel nitrogen in the wood log and pellet fuels, respectively.

9 Table 5 Emission factors of the main gaseous and particulate emission components for the wood stove. All data presented as mg/MJfuel (PAH data given as µg/MJfuel).

All experimental fuel and stove variation Only operation mode 1 and 2 included (6 Reference included, i.e. operation mode 1,2 and 3 (8 experiments) valuesc experiments) average median max min Average median Max Min

CO 3800 2900 7700 1200 2600 2500 3600 1200 2700-19000d TOCa 1200 600 4800 310 600 550 1000 310

b e NOx 50 51 71 37 52 55 71 37 11-51 NMVOC 600 130 2500 18 100 90 200 18 300-1400f Methane 430 100 1700 9.9 73 68 136 9.9 220-1300g

h PMtot 160 150 350 37 110 110 170 37 110-2100

PAHtot 36000 3800 220000 1300 3600 1900 9700 1300 370(1.2)- 14800(67000)i a Given as CH4-equivalents b Given as NO2 c Intervals of average reference emission factors for different residential wood appliances (i.e. fireplaces and stoves) recalculated from g(or mg)/kgfuel by assuming a heating value of 19 MJ/kg. d Reference 1, 8, 12, 35, 36 e Reference 1, 8, 36 f Reference 1, 8, 36 g Reference 1, 36, 41 h Reference 1, 8, 12, 36 i Reference 35-37. 1.2 µg/MJ is reported in reference 36 for modern "best technology" wood stoves and 67000 µg/MJ is reported in reference 37 as maximum PAH emission during birch wood combustion i a residential stove.

The experimental conditions for the wood log stove during mode 3 resulted in high burning rates, corresponding to estimated average fuel outputs of 18-19 kW, with considerably increased emissions of PIC. Normally, good air supply with high intensity and dry splitted wood is considered to favour high combustion performance with low emissions of PIC. However, the results obtained in these experiments can most probably be explained by the too high burning rate causing insufficient air supply conditions when full loads of extra dry and fine splitted logs were combusted. During mode 1 and 2, the O2 concentration generally decreased to approximately 5% during the intermediate phase, but dropped to 1-3% in experiment 5 and 6 (mode 3) during the most intensive combustion periods after the start-up phases. The operation conditions can perhaps be considered rather extreme, however not irrelevant, since the phenomenon in general quite often may occur in all kinds of batch fired devices with limited control of the air to fuel ratio during different conditions. The extra dry wood logs used in the present study (i.e. 8% moisture content) is also relevant since a previous field survey within the research programme showed that the moisture content of the wood log used in practical use varied between 6 and 18% [21].

Another interesting observation regarding the wood log stove experiments was that the emissions during operation mode 1 and 2 were relatively equal. Apparently, the emission performance was not deteriorated during mode 2 although the ceramic lining was excluded and relatively moist and large wood logs were used. This means that the stove was rather robust considering the influence of the specific variations in fuel properties and operation conditions on the combustion behaviour and emission performance. This is also illustrated by the fact that there was no difference in estimated burning rates during mode 1 and 2 conditions with estimated average fuel outputs of 10-13 kW. In Figure 2, a comparison between the average emissions of the main emission components during the different operation modes included in the wood log stove experiments is made. It is however important to consider the fact that the results presented here are based on a limited number of measurements in a single type of wood log stove, although with the ambition to illustrate

10 the variability in emission performance during different fuel, appliance and operational conditions in general and not for the specific stove used.

134000

8000 CO

7000 TOC NMVOC

6000 Methane PM tot

5000 PAH tot

4000

3000

2000

1000

0 Mode 1a Mode 1b Mode 2 Mode 3

Figure 2. Comparison between the average emissions of the main components from the wood stove during different operation modes, given as mg/MJfuel (PAH given as µg/MJfuel). TOC given as CH4- equivalents. The conditions in the different modes aimed to simulate; Mode 1 (a) = "Normal" stove and fuel conditions (2 experiments with birch wood), Mode 1 (b) = "Normal" stove and fuel conditions (2 experiments with conifer wood), Mode 2 = "Cold and air starved" combustion with moist and large logs (2 experiments with birch wood), Mode 3 = "Intensive" combustion with high draught and extra dry and cleaved logs (2 experiments with birch wood).

The emissions of PMtot varied less between the wood log and pellet stoves, but still with significant higher concentrations in the wood log stove experiments. The potential presence of coarse fly ash particles can significantly influence the total PM mass concentrations and some of the variation in PMtot emissions is explained by variations in the amount of coarse particles in the present measurements. However, even more important for the variations of PM emissions from different kind of residential appliances observed in this and other studies are the increased production of fine particle associated carbonaceous material (i.e. soot and condensable organics) during poor combustion conditions. Soot and organics are products of incomplete combustion and the strong influence of combustion conditions, i.e. amount of unoxidized carbonaceous material, on the characterization and quantification of the particulate emissions shown previously [9, 18, 22] during residential biomass combustion was clearly illustrated both for wood log and pellet stoves in the present study. An indication of the chemical fractionation of the PM can be given simply by the colour of the filter samples. The PM from the wood log stove was in all cases dark (black) by soot particles. During low load operation in pellet stove A, the filter samples were also black. However, the filter samples from the pellets stoves during high fuel loads were lighter in colour (medium grey), which indicates very low soot levels and that the PM from the pellet stoves was

11 dominated by fine inorganic ash particles. The amount of inorganic fine PM is not correlated to the completeness of the combustion, but rather controlled by the volatilization of ash forming elements during combustion and subsequent particle formation during cooling of the flue gases. During optimized combustion of softwood pellets in small-scale appliances with almost a total depletion of PIC, the emissions of inorganic fine particles have been shown to be around 15 mg/MJfuel [18, 19]. In the present study, the PMtot emissions from the pellet stoves during high load operation were in the range of 15-25 mg/MJfuel. Assuming similar ash composition and volatilization conditions and comparing these numbers with corresponding PMtot emissions both from present and reference wood log stoves and fireplaces (i.e. 37- 2100 mg/MJfuel) would indicate that the carbonaceous material most often completely dominates (60-99%) the PM from wood log stoves and fireplaces. Some earlier studies have included estimation and fractionation of the carbonaceous PM during residential wood combustion. One early study [9] estimated that hot burning resulted in 20-60% of carbon (primarily elemental carbon) in the PM, while cool burning resulted in 55-60% of carbonaceous PM (mostly organic carbon). In a study of fireplace combustion of different wood species, 40-60% of the fine PM was identified as organic carbon and 1.4-3.2% as elemental carbon [41]. In a corresponding study it was estimated that organic carbon contributed over 80% and elemental carbon 4-30% of the fine PM during combustion of different wood species [42].

So far, a relatively limited amount of work has been published concerning emission quantification and characterization during combustion in residential pellet stoves. In accordance with the scarce previous data [18, 43], however, the present study also illustrates the significant potential for more effective combustion and low emissions of PIC by using upgraded homogeneous fuels like pellets combusted under continuous and controlled conditions compared to traditional batch wise firing of wood logs. The influence of furnace design and operation conditions on the emission performance during pellets combustion have also been illustrated in a limited number of studies [19, 44], where low load operation typically creates lower temperature and intensity and less stable combustion conditions with increased emissions of PIC. During full (nominal) load with continuous operation the combustion process is warmer, more intense and easily controlled and optimized which often results in less PIC.

As seen in Table 6, the emissions of PIC during high load were rather low for both studied pellet stoves. However, stove B operated with very high amounts of excess air also during combustion at high fuel loads, i.e. O2 concentrations at 18-19%. This phenomenon is probably an effect of the manufacturers ambitions to keep the window in the stove free from dust on the inside by supplying air at the front door of the stove. In stove A during high load operation the amount of excess air was more moderate, although still rather high with O2 concentration at 11-16%. During low load operation, the emissions of CO, TOC and PAH as well as PMtot were significantly increased compared to high load operation for both pellet stoves. Since the average heat output requirement in a typical small house in northern countries during wintertime normally is 2-3 kW, the potential for further development and emission reduction in all kinds of residential pellet appliances is evident. During intermittent operation (stove B) significant PIC peaks occurred during the start-up and burn-out phases. During continuous operation at low load (stove A) the increased amount of PIC is most probably explained by decreased combustion temperature caused by heat losses around the grate and/or cooling effects from the unnecessary high amount of excess air, i.e. O2 concentrations at 16-18%. The somewhat higher emissions of PMtot from pellet stove B compared to pellet stove A may further be explained by a higher fraction of coarse particles, which is discussed later in the text.

Table 6 Emission factors of the main gaseous and particulate emission components for the biomass fuel pellet stoves. All data presented as mg/MJfuel (PAH data given as µg/MJfuel).

Pellet stove A - high load (5 kWfuel) Pellet stove A - low load (1.7 kWfuel) Pellet stove B - high load (5-6 kWfuel) Pellet stove B - low load (2 kWfuel)

average median max min average median max min average median max min average median max min

CO 140 150 170 110 580 590 810 320 110 100 160 79 500 500 560 420

TOC 3.7 3.5 4.4 3.2 51 52 69 28 6.0 5.9 8.0 4.0 16 16 21 13

NOx 61 60 65 57 54 55 57 52 61 63 64 54 60 61 62 58

NMVOC 2.0 2.0 3.1 0.85 19 20 22 14 1.6 1.54 2.0 1.3 4.5 4.8 5.0 3.5

Methane 1.4 1.3 2.4 0.67 14 15 18 9.5 4.8 4.5 5.8 4.5 6.1 6.0 7.0 5.4

PMtot 16 16 17 15 34 35 43 21 23 23 25 22 39 37 46 36

PAHtot 13 4.9 40 3.3 200 200 330 89 7.0 6.4 13 2.0 33 32 55 13

* Given as CH4-equivalents

** Given as NO2

13 Further, at low loads the emissions of hydrocarbons were significantly more increased for stove A than for stove B. From experiences in this and a previous study [30] it has been found that the emission performance of stove A is significantly deteriorated during operation at fuel loads below 2 kW (1.7 kW in the present study), especially for hydrocarbons (both VOC and PAH). During combustion at 2-3 kWfuel with stove A, however, the emissions of PIC (e.g. CO and hydrocarbons) were shown to be of the same magnitude for both studied pellet stoves.

Volatile organic compounds Considerable variations in VOC concentrations were determined in the present study with several magnitudes of scattering in emission levels for some compounds (e.g. benzene toluene) for the wood log and pellet stoves. Therefore, the results from different analysis methods were in some cases used to enable accurate determination of the emission factors.

For the wood log stove, with all experimental variation included, the emission factors for NMVOC varied from 18 to 2500 mg/MJfuel. Drastically increased emissions were determined during mode 3 compared to mode 1 and 2, as previously shown in Table 5 and Figure 2. In Table 7, the emission data for specific VOC compounds during the wood log stove campaign are summarized. Methane was in all cases the dominating VOC compound with an average of 41±5.5 % of total VOC emissions during whole combustion cycles. However, the emission factors of methane varied from 10 to 1700 mg/MJfuel. Beside methane, the VOC´s found in highest concentrations were in all cases ethene and acetylene generally followed by benzene, propene, ethane and toluene. These six most dominant NMVOC´s constituted 93±2.9 % of total NMVOC. The emission factors for 1,3-butadiene, a compounds discussed in cancer risk assessments of urban air [2], during mode 1 and 2 in the wood log stove varied in the range of 0.09-1.8 mg/MJ and were increased up to 66 mg/MJ during mode 3.

The use of biomass in combustion applications is normally considered to be a renewable and energy source concerning direct CO2-emissions. The potentially high emissions of methane from residential wood appliances may, however, be relevant to consider regarding the issue of greenhouse gas emissions since methane has a global warming potential 21 times higher per unit than CO2 in a 100-years perspective [45]. During some specific air starved situations, as for example been shown for stoves in the present study, considerable emissions of methane can occur. In a recent study it has also been shown that the emission of methane from old-type residential wood log boilers in "worst-case" situations can result in global warming potentials of the same magnitudes as from residential oil burners [18]. However, based on emission data from both studies, the global warming potential during normal combustion conditions (i.e. not gasification mode) for both residential wood log and pellet appliances can be estimated to be 30-4400 and 200-7400 times lower than for residential oil burning, respectively.

In Table 7, the emissions of specific VOC´s during each of the experiments within mode 1 operation are also specified as a comparison between combustion of different wood species (i.e. birch, spruce and pine). No significant difference regarding the relative occurrence of specific compounds between birch and softwood combustion were seen for the aliphatic or (mono) aromatic hydrocarbons (e.g. benzene, toluene and xylenes). However, the emissions of terpenes, especially d-3-carene, α-pinene, myrcene and limonene, were considerably higher during combustion of pine wood compared to both birch and spruce wood. This difference in terpene emissions is presumably explained by differences in the chemical composition of the resin in different tree species, also discussed by others [34] during combustion of hardwoods and softwoods.

14 Table 7. Emission factors of the specific VOC compounds for the wood log stove (mg/MJfuel). Methoda All experimental fuel and stove variation included, Only operation mode 1 and 2 included (6 Birch wood - Birch wood - Spruce wood - Pine wood - i.e. operation mode 1,2 and 3 (8 experiments) experiments) Mode 1 Mode 1 Mode 1 (Exp Mode 1 (Exp nr 2) (Exp nr 3) nr 6) (Exp nr 8)

average median max min average median max min methane Tedlar d.i. 430 100 1700 9.9 73 68 140 9.9 39 90 140 120 ethane Tedlar d.i. 24 6.0 110 0.18 3.6 3.7 6.5 0.18 1.5 6.2 5.9 6.5 ethene Tedlar d.i. 240 53 990 7.7 43 36 84 7.7 25 38 85 67 acetylene Tedlar d.i. 140 31 510 4.4 25 31 43 4.4 14 43 31 propane Tedlar d.i. 2.5 1.0 10 0.14 0.77 0.49 1.9 0.14 0.27 2.0 0.70 1.4 propene Tedlar d.i. 27 5.3 130 0.49 3.6 3.5 7.1 0.49 2.3 4.6 5.9 7.1 propyne Tedlar d.i. 7.9 1.2 38 0.21 0.95 0.82 1.7 0.21 0.69 0.78 1.7 1.5 n-butane Tedlar d.i. 0.41 0.35 1.2 <0.01 0.28 0.23 0.71 <0.01 0.14 0.49 0.71 0.32 isobutane Tedlar d.i. 0.27 0.10 1.1 <0.01 0.15 0.01 0.65 <0.01 <0.01 0.18 0.01 0.65 1-butene Tedlar d.i. 3.1 0.68 17 <0.01 0.45 0.45 0.93 <0.01 0.41 0.93 0.48 0.87 isobutene Tedlar d.i. 2.0 0.51 9.9 <0.01 0.30 0.35 0.58 <0.01 0.18 0.58 0.52 0.51 cis-2-butene Tedlar d.i. 0.58 0.15 2.7 <0.01 0.15 0.07 0.53 <0.01 0.10 0.21 0.04 0.53 Trans-2-butene Tedlar d.i. 0.70 0.24 3.3 <0.01 0.16 0.08 0.41 <0.01 0.09 0.41 0.07 0.40 1,3-butadiene Tedlar d.i. 12 0.85 66 0.09 0.78 0.69 1.8 0.09 0.66 0.98 1.8 0.72 pentane Tedlar d.i. 0.31 0.02 1.8 <0.01 <0.04 <0.02 0.16 <0.01 <0.02 <0.01 <0.02 0.16 ethylacetylene Tedlar d.i. 1.1 0.15 6.5 <0.01 0.10 0.09 0.22 <0.01 0.09 0.22 0.08 0.21 hexane Tedlar d.i. 0.21 <0.02 1.1 <0.02 <0.03 <0.02 0.10 <0.02 <0.02 0.10 <0.02 <0.02 benzene Tedlar d.i. 120 29 480 2.7 23 24 43 2.7 11 25 43 33 toluene Tedlar d.i. 19 3.7 84 0.61 2.8 2.2 5.2 0.61 1.4 2.6 5.2 4.8

butylacetate Tenax t.d. <0.04 <0.01 0.18 <0.01 <0.02 <0.01 <0.02 <0.01 <0.01 <0.02 ethylbenzene Tenax t.d. 0.87 0.20 3.3 0.02 0.13 0.12 0.25 0.02 0.18 0.07 0.25 0.23 m+p-xylene Tenax t.d. 2.2 0.56 9.1 0.10 0.44 0.43 0.72 0.10 0.48 0.32 0.63 0.72 o-xylene Tenax t.d. 0.50 <0.04 2.8 <0.01 <0.04 <0.03 0.10 <0.01 0.10 0.02 0.04 0.04 124-TMBb Tenax t.d. <0.02 <0.01 0.05 <0.01 <0.01 <0.01 0.02 <0.01 <0.02 <0.01 <0.01 <0.01 123-TMBb Tenax t.d. 0.06 0.04 0.16 0.01 0.05 0.02 0.16 0.01 0.05 <0.01 <0.03 0.16 135-TMBb Tenax t.d. <0.03 <0.02 0.08 <0.01 <0.02 <0.01 0.03 <0.01 0.03 <0.01 <0.01 <0.02 α-pinene Tenax t.d. 1.4 0.87 3.2 0.52 1.2 0.87 3.2 0.52 0.52 0.88 0.86 3.2 β-pinene Tenax t.d. 0.16 0.02 0.91 <0.01 <0.05 <0.02 0.24 <0.01 0.03 0.01 <0.01 0.24 campene Tenax t.d. 0.25 0.23 0.52 0.12 0.19 0.21 0.25 0.12 0.12 0.15 0.23 0.23 myrcene Tenax t.d. 0.34 <0.03 1.7 <0.01 0.30 <0.02 1.7 <0.01 <0.04 <0.01 <0.02 1.7 d-3-carene Tenax t.d. 0.40 <0.02 2.9 <0.01 0.52 <0.01 2.9 <0.01 <0.01 0.15 <0.01 2.9 eucalyptolene Tenax t.d. <0.03 <0.01 0.11 <0.01 <0.01 <0.01 0.03 <0.01 <0.01 <0.03 <0.01 <0.01 limonene Tenax t.d. <0.11 <0.02 0.71 <0.01 <0.13 <0.02 0.71 <0.01 <0.03 <0.02 <0.01 0.71 a Tedlar d.i. = Tedlar bags with direct injection, Tenax t.d. = Tenax adsorbent with thermal desorption/auto-injection b TMB = trimethylbenzene

15 Table 8. Emission factors of the specific VOC compounds for the pellet stoves (mg/MJfuel). a Method Pellet stove A - high load (5 kWfuel) Pellet stove A - low load (1.7 kWfuel) Pellet stove B - high load (5-6 kWfuel) Pellet stove B - low load (2 kWfuel) average median max min average median max min average median max min average median max min

methane Tedlar d.i. 1.4 1.3 2.4 0.67 14 15 18 9.4 4.8 4.5 5.8 4.5 6.1 6.0 7.0 5.4 ethane Tedlar d.i. <0.02 <0.01 1.2 1.2 2.1 0.56 <0.04 <0.03 0.26 0.26 0.38 0.15 ethene Tedlar d.i. 0.42 0.34 0.99 <0.01 6.3 6.7 7.1 4.6 <0.04 <0.03 1.1 1.2 1.3 0.77 acetylene Tedlar d.i. 0.70 0.72 1.0 0.36 5.3 4.7 8.1 3.9 <0.03 <0.03 0.90 0.98 1.1 0.49 propane Tedlar d.i. <0.03 <0.01 <0.04 <0.03 <0.06 <0.05 <0.06 <0.04 propene Tedlar d.i. <0.03 <0.01 1.2 1.2 2.5 <0.03 <0.05 <0.04 0.20 0.22 0.28 0.10 propyne Tedlar d.i. <0.03 <0.01 0.56 0.42 1.4 <0.03 <0.05 <0.04 <0.07 <0.05 0.15 <0.04 n-butane Tedlar d.i. <0.04 <0.02 <0.05 <0.04 <0.08 <0.06 <0.08 <0.05 isobutane Tedlar d.i. <0.04 <0.02 <0.05 <0.04 <0.08 <0.06 <0.08 <0.06 1-butene Tedlar d.i. <0.04 <0.01 0.23 0.17 0.53 <0.04 <0.07 <0.06 <0.09 <0.06 isobutene Tedlar d.i. <0.04 <0.01 <0.05 <0.04 <0.07 <0.06 <0.08 <0.06 cis-2-butene Tedlar d.i. <0.04 <0.01 <0.05 <0.04 <0.07 <0.06 <0.08 <0.06 trans-2-butene Tedlar d.i. <0.04 <0.01 <0.05 <0.04 <0.07 <0.06 <0.08 <0.06 ethylacetylene Tedlar d.i. <0.03 <0.01 <0.05 <0.03 <0.07 <0.06 <0.08 <0.05

1,3-butadiene Carbopac t.d. 0.007 0.011 0.002 0.33 0.46 0.21 0.022 0.023 0.021 0.048 0.049 0.047 pentane Carbopac t.d. 0.013 0.018 0.009 0.044 0.067 0.023 0.035 0.038 0.031 0.039 0.043 0.035 isopentane Carbopac t.d. <0.001 <0.001 <0.003 0.004 <0.001 <0.003 <0.003 <0.003 <0.003 t2-pentene Carbopac t.d. <0.001 <0.001 0.009 0.012 0.006 <0.003 <0.003 <0.003 <0.003 c2-pentene Carbopac t.d. <0.001 <0.001 0.011 0.014 0.007 <0.003 <0.003 <0.004 <0.004 hexane Carbopac t.d. <0.002 <0.001 0.035 0.062 0.008 0.006 0.007 0.005 0.009 0.010 0.008

octane Tenax t.d. 0.04 0.03 0.10 0.02 0.05 0.05 0.07 0.02 0.08 0.06 0.17 0.03 0.14 0.15 0.19 0.09 nonane Tenax t.d. 0.08 0.04 0.20 0.02 0.07 0.06 0.13 0.02 0.19 0.12 0.47 0.04 0.19 0.21 0.22 0.12 decane Tenax t.d. <0.03 <0.01 <0.04 <0.03 <0.06 <0.05 <0.06 <0.05 benzene Tenax t.d. 0.17 0.17 0.28 0.07 2.30 1.8 4.1 1.4 0.12 0.12 0.19 0.07 0.41 0.42 0.44 0.36 toluene Tenax t.d. 0.11 0.02 0.39 0.01 0.34 0.35 0.45 0.23 0.04 0.04 0.07 0.02 0.12 0.13 0.16 0.08 butylacetate Tenax t.d. <0.03 <0.01 <0.04 <0.03 <0.06 <0.05 <0.06 <0.05 ethylbenzene Tenax t.d. 0.01 <0.01 0.05 <0.01 0.04 0.04 0.05 0.02 <0.01 <0.01 0.01 <0.01 0.02 0.02 0.02 0.01 m+p-xylene Tenax t.d. 0.10 0.10 0.20 0.01 0.14 0.13 0.21 0.11 0.13 0.05 0.38 0.04 0.13 0.15 0.20 0.04 o-xylene Tenax t.d. <0.02 <0.01 0.06 <0.01 <0.02 <0.02 0.03 <0.01 <0.03 <0.03 0.04 <0.02 <0.03 <0.03 0.05 <0.03 123-TMBb Tenax t.d. <0.02 <0.02 0.03 <0.01 <0.04 <0.03 <0.06 <0.05 <0.06 <0.06 0.07 <0.05 124-TMBb Tenax t.d. <0.03 <0.01 <0.04 <0.03 <0.06 <0.05 <0.06 <0.05 135-TMBb Tenax t.d. <0.03 <0.01 <0.04 <0.03 <0.06 <0.05 <0.06 <0.05 a Tedlar d.i. = Tedlar bags with direct injection, Carbopac t.d. = Carbopac adsorbent with thermal desorption/auto-injection, Tenax t.d. = Tenax adsorbent with thermal desorption/auto-injection b TMB = trimethylbenzene

16 In Table 8, the emission data from the VOC measurements during the pellet stoves campaign are summarized. For the two pellet stoves together, the emissions of NMVOC varied from 0.85 to 3.1 mg/MJfuel at high load and from 3.5 to 22 mg/MJfuel at low load. The dominating compound methane constituted an average of 54±14 % of total VOC but the emissions were limited to 0.7-5.8 mg/MJfuel at high load and to 5.4-18 mg/MJfuel at low load. As for the wood log stove, ethene and acetylene were the most dominant NMVOC´s, at least at low fuel loads, generally followed by benzene, ethane, propene toluene. At high fuel loads, however, the concentration of many VOC´s was below the detection limit and such ranking of different compounds and their relative contributions became associated with significant uncertainties.

Polycyclic aromatic hydrocarbons The emissions of PAHtot from the wood log stove varied considerably (1300-220000 µg/MJfuel) if all experimental variation is considered. This is in agreement with the large variations of total PAH determined also in other studies on residential wood log stove and fireplace emissions [34-37]. The major part of the PAH was in all present cases detected as semi-volatile material with an average of 83±11% of total PAH found in the PUF-samples. The partitioning between particulate and gas phases for different PAH´s is influenced by the chemical properties of the specific compounds as well as the sampling conditions, e.g. temperature and dilution, which have been evaluated for the present sampling set-up previously [29]. In the following, the sum of particulate and semi-volatile samples of specific PAH compounds will be discussed.

In Table 9, the emission factors determined for the 43 specific PAH´s during the wood log stove campaign are summarized. In accordance with the presentation of VOC data, the PAH emissions are presented for the different experimental conditions and wood species (i.e. birch, spruce and pine). The three most dominant PAH´s were phenanthrene, fluoranthene and pyrene which constituted 59±7.1% of total PAH from the wood log stove. Other major PAH compounds were generally anthracene, 2-phenylnaphthalene and benzo(b)fluoranthene. For all specific PAH compounds, except fluorene and retene, the emissions seemed to be rather well correlated with combustion performance and other PIC. High emissions of fluorene were in accordance with other PAH´s, determined in the mode 3 experiments but also in mode 1 for birch (exp 3) and spruce (exp 6). Retene, however, was found in considerable concentrations during combustion of conifer wood but was below the detection limit in the birch wood experiments. The emission factors of retene were in the same level for spruce and pine wood (115 and 113 µg/MJfuel) although the PAHtot emissions in the two experiments differed rather much (9700 and 2000 µg/MJfuel). Retene is a pyrolysis product of resin acids in conifer woods and has been suggested as a marker for conifer wood combustion [46, 47]. However, retene has also been detected in the emissions from hardwoods [34, 37, 41] as well as in traffic emissions [48] and its use as a tracer for coniferous wood smoke may be questioned.

The addressed interest of PAH emissions in general is partly caused by the extensive evidences which concludes that exposure to PAH-containing substances increases the risk of cancer in humans [6]. Based on previous reported data, domestic wood burning together with road traffic have further been considered as major sources of PAH´s in Sweden [6]. However, when considering the chemical composition of wood smoke in general and biomass combustion particles in specific, PAH is only a minor group of organic constituents, although with potential health impact relevance. In the present wood log stove study, the particulate associate PAH constituted only an average of 1.2% (0.29-3.2%) of the total PM emissions. Instead, the organic fraction of the PM has been found to consist of a large number of other organic compounds of different classes, extensively characterized by others [34, 37, 41, 42]. Some specific prominent organic particulate constituents found in residential wood smoke are the sugar derivative levoglucosan [41, 42] which is a major pyrolysis product of cellulose [49] that has been discussed as an organic tracer for wood smoke [50],

17 and methoxyphenols like guaiacols and syringols [34, 37, 41, 42, 51, 52] which are major pyrolysis products of wood lignin [48, 53] and also discussed as wood smoke tracers [49].

The emission factors determined for the 43 specific PAH´s during the pellet stove campaigns are summarized in Table 10. These PAH emissions were generally several magnitudes lower than for the wood log stove and the PAHtot varied in the range 1.7-330 µg/MJfuel. As discussed earlier, significant increased PAH emissions were determined during low load operation, especially for stove A. Also in the pellet stove experiments phenanthrene, fluoranthene and pyrene were the three most dominant PAH´s which constituted 49±12% of total PAH. Since the pellets used were produced of conifer sawdust, retene was found in the emissions in all cases, although in rather varying concentrations in general and low emission factors during efficient combustion at high fuel loads. The particulate associated fraction of PAH constituted as little as an average of 0.10% (0.002-0.45%) of total PM emissions from the pellet stoves and accordingly more or less totally insignificant to the particle mass, at least during combustion at high fuel loads.

Particle size distributions and number concentrations The PM was in all cases dominated by fine particles with approximately 80-95% of the total particle mass as PM1. For the wood log stove, the fractions of PM1 were relatively similar between the intermediate phase (mean=84%) and the start-up phase (mean=79%). Concerning pellets combustion, the fraction of coarse particles seemed to be in the same range as the wood log stove for pellet stove B, whereas almost a total absence of coarse particles were determined for pellet stove A. Coarse PM generally derives from entrained particles from the fuel bed and may consist of unburned carbonaceous fuel residues and/or inorganic fly ash particles formed of fuel associated mineral inclusions/impurities, which is discussed later in the text concerning chemical composition of the PM.

Data from the fine particle measurements with the wood log and pellet stoves are summarized in Table 11 and 12, respectively. From the mass size distribution measurements with the LPI combined with a pre-cyclone, the fractions of PM1 as well as mass median particle diameters of the fine mode (MMD) were extracted. The fine particle number concentrations and count median particle diameter (CMD) were extracted from the SMPS measurements.

18 Table 9. Emission factors of the specific PAH compounds for the wood log stove (µg/MJfuel). All experimental fuel and stove variation included, i.e. Only operation mode 1 and 2 included (6 experiments) Birch wood - Birch wood - Spruce wood Pine wood - operation mode 1,2 and 3 (8 experiments) Mode 1 Mode 1 - Mode 1 Mode 1 (Exp nr 2) (Exp nr 3) (Exp nr 6) (Exp nr 8)

average median max min average median max min

fluorene 110 66 370 2.0 86 16 370 2.0 13 110 370 2.0 2-methylfluorene 45 2.9 250 <0.002 11 0.84 57 <0.002 <0.002 <0.003 57 0.68 dibenzothiophene 6.6 1.8 37 0.20 1.5 0.51 4.5 0.20 0.56 3.1 4.5 0.46 phenanthrene 8100 1400 51000 120 1100 550 3000 120 670 2000 3000 250 anthracene 2400 230 16000 23 195 95 570 23 110 350 570 42 3-methylphenanthrene 910 44 6500 6.6 42 17 130 6.6 19 69 130 15 2-methylphenanthrene 950 50 6800 8.6 50 22 150 8.6 21 76 150 24 2-methylanthracene 420 13 3100 2.5 15 6.2 48 2.4 6.2 20 48 6.2 9-methylphenanthrene 610 28 4400 3.6 28 11 91 3.6 13 44 91 10 1-methylphenanthrene 1100 58 7500 7.6 53 27 160 7.6 21 82 160 33 9-methylanthracene 120 2.7 800 0.92 3.1 2.0 9.9 0.92 1.0 2.9 9.9 2.5 2-phenylnaphthalene 1800 140 11400 48 130 84 350 48 56 171 350 110 3,6-dimethylphenanthrene 80 1.8 560 0.66 1.8 1.4 4.9 0.66 0.66 1.8 4.9 1.7 3,9-dimethylphenanthrene 110 5.4 760 1.7 5.4 4.7 14 1.7 1.7 5.5 14 5.5 fluoranthene 7100 660 44000 240 600 410 1400 240 300 800 1400 510 pyrene 6400 540 39000 210 470 330 1000 210 270 680 1000 390 9,10-dimethylanthracene 180 100 600 13 110 100 240 13 13 130 100 100 benz(a)fluorene 680 40 4300 15 43 37 110 15 15 43 110 37 retene 29 0.006 120 <0.001 38 0.50 120 <0.001 <0.002 <0.003 120 110 benz(b)fluorene/2-methylpyrene 490 25 3200 11 27 24 66 11 11 26 66 24 4-methylpyrene 300 18.966 2000 8.5 19 17 44 8.5 8.5 21 44 16 1-methylpyrene 380 21 2400 9.8 22 20 47 9.8 9.8 22 47 19 benzo(ghi)fluoranthene 150 22 1000 6.8 17 16 29 6.8 17 29 27 6.8 benzo(c)phenanthrene 90 12 620 3.6 9.5 8.1 18 3.6 8.6 15 18 3.6 benzo(b)naphto(1,2-d)thiophene 0.099 0.053 0.40 0.005 0.13 0.064 0.40 0.009 0.050 0.055 0.40 0.19 cyclopenta(cd)pyrene 430 7.7 3300 2.5 6.0 3.7 12 2.5 2.6 3.2 11 2.5 benzo(a)anthracene 230 28 1600 9.3 21 20 34 9.3 18 34 34 11 chrysene 200 32 1400 10 26 25 44 10 22 44 37 13 3-methylchrysene 15 2.0 100 0.57 1.4 1.5 2.3 0.57 0.89 2.3 2.0 1.0 2-methylchrysene 6.2 1.1 40 0.36 0.86 0.83 1.4 0.36 0.54 1.4 1.0 0.66 6-methylchrysene 3.1 0.68 19 0.19 0.53 0.49 0.92 0.19 0.34 0.92 0.74 0.34 1-methylchrysene 4.4 0.78 29 0.24 0.68 0.62 1.2 0.24 0.40 0.94 0.62 0.62 benzo(b)fluoranthene 680 140 2500 30 150 70 500 30 59 200 500 81 benzo(k)fluoranthene 250 45 1000 9.3 51 22 160 9.3 20 66 160 25 benzo(e)pyrene 270 54 970 11 58 27 180 11 25 80 180 29 benzo(a)pyrene 610 71 2400 16 88 40 300 16 30 100 300 38 perylene 88 10 350 2.4 13 5.6 43 2.4 4.6 15 43 5.2 indeno(1,2,3-cd)fluoranthe 35 7.2 120 1.4 7.8 3.5 25 1.4 3.1 11 25 4.0 indeno(1,2,3-cd)pyrene 410 74 1500 13 77 37 240 13 32 110 240 42 dibenz(a,h)anthracene 55 9.2 300 1.4 7.9 3.8 21 1.4 3.8 15 21 3.8 benzo(ghi)perylene 280 46 990 8.5 45 23 130 8.5 22 67 130 24 coronene 190 18 700 3.1 18 8.7 51 3.1 8.2 27 51 8.9

19 Table 10. Emission factors of the specific PAH compounds for the pellet stoves (µg/MJfuel).

Pellet stove A - high load (5 kWfuel) Pellet stove A - low load (1.7 kWfuel) Pellet stove B - high load (5-6 kWfuel) Pellet stove B - low load (2 kWfuel)

average median max min average median max min average median max min average median max min fluorene 0.016 0.019 0.014 6.7 11 2.8 0.018 0.036 <0.0003 0.69 0.95 0.43 2-methylfluorene 0.0012 0.0023 <0.0002 0.31 0.33 0.29 <0.0003 <0.0003 0.094 0.12 0.071 dibenzothiophene 0.0019 0.0022 0.0017 0.38 0.39 0.26 0.019 0.036 0.0021 0.049 0.062 0.036 phenanthrene 3.1 1.4 9.0 0.63 54 60 75 20 2.5 2.2265 5.0 0.65 8.4 8.1 14 3.9 anthracene 0.33 0.074 1.1 0.048 8.9 10 12 3.2 0.31 0.2405 0.69 0.059 1.2 1.2 1.8 0.49 3-methylphenanthrene 0.065 0.033 0.18 0.016 1.4 1.6 1.8 0.77 0.071 0.0669 0.14 0.014 0.39 0.35 0.71 0.17 2-methylphenanthrene 0.065 0.058 0.11 0.030 2.2 2.0 3.4 1.4 0.14 0.1580 0.20 0.047 0.60 0.57 0.97 0.31 2-methylanthracene 0.014 0.0093 0.037 0.0024 0.63 0.58 1.0 0.34 0.022 0.0193 0.045 0.0022 0.22 0.19 0.42 0.061 9-methylphenanthrene 0.032 0.023 0.077 0.0063 1.0 1.0 1.4 0.65 0.083 0.0832 0.15 0.012 0.33 0.33 0.55 0.13 1-methylphenanthrene 0.11 0.11 0.16 0.060 3.5 2.7 6.4 2.3 0.25 0.2697 0.41 0.044 0.68 0.59 1.1 0.42 9-methylanthracene <0.0012 <0.0002 0.0043 <0.0002 0.14 0.034 0.49 0.015 0.0080 0.0060 0.020 <0.0003 0.16 0.13 0.36 0.0077 2-phenylnaphthalene 0.12 0.059 0.33 0.038 3.2 3.6 4.6 0.94 0.14 0.1165 0.31 0.030 0.60 0.56 1.0 0.23 3,6-dimethylphenanthrene 0.0011 0.0012 0.0020 <0.0002 0.058 0.026 0.16 0.018 0.0030 0.0027 0.0065 <0.0003 0.020 0.018 0.036 0.0076 3,9-dimethylphenanthrene 0.016 0.0080 0.049 <0.0002 0.13 0.084 0.30 0.043 0.011 0.0102 0.024 <0.0003 0.046 0.037 0.10 0.0044 fluoranthene 1.4 0.49 4.2 0.39 22 22 38 7.9 0.94 0.8119 1.9 0.26 3.0 2.8 5.0 1.4 pyrene 1.4 0.46 4.4 0.43 20 18 38 7.8 0.96 0.8683 1.9 0.23 2.8 2.7 4.7 1.3 9,10-dimethylanthracene <0.0002 <0.0002 <0.0005 <0.0003 <0.0003 <0.0003 <0.0005 <0.0004 benz(a)fluorene 0.022 0.0053 0.076 <0.0002 0.95 0.66 2.0 0.43 0.017 0.0138 0.040 <0.0003 0.39 0.37 0.72 0.12 retene 0.38 0.44 0.62 0.023 6.8 6.8 8.4 5.2 0.47 0.4607 0.73 0.22 0.62 0.52 1.4 0.094 benz(b)fluorene/2-methylpyrene 0.030 0.0085 0.096 0.0060 0.91 0.70 1.8 0.39 0.027 0.0185 0.069 <0.0003 0.52 0.45 1.1 0.080 4-methylpyrene 0.037 0.019 0.12 0.0061 0.88 0.56 2.0 0.36 0.015 0.0128 0.033 <0.0003 0.21 0.18 0.39 0.071 1-methylpyrene 0.028 0.011 0.088 0.0030 0.88 0.53 2.1 0.39 0.019 0.0141 0.047 <0.0003 0.19 0.19 0.36 0.043 benzo(ghi)fluoranthene 0.40 0.22 1.0 0.13 3.3 3.3 5.4 1.2 0.13 0.1140 0.24 0.058 0.58 0.55 0.96 0.24 benzo(c)phenanthrene 0.060 0.035 0.15 0.025 0.86 0.83 1.4 0.43 0.030 0.0259 0.057 0.0100 0.15 0.16 0.26 0.0327 benzo(b)naphto(1,2-d)thiophene 0.0018 <0.0002 0.0067 <0.0002 0.0020 <0.0004 0.0069 <0.0004 <0.0003 <0.0003 <0.0005 <0.0004 cyclopenta(cd)pyrene 1.3 0.17 4.7 0.084 5.4 5.6 8.0 2.2 0.14 0.1027 0.29 0.058 2.7 2.4 5.5 0.51 benzo(a)anthracene 0.21 0.14 0.53 0.053 2.6 2.7 4.4 0.60 0.072 0.0538 0.15 0.026 0.69 0.63 1.3 0.17 chrysene 0.33 0.23 0.76 0.0904 3.5 3.6 5.9 1.0 0.13 0.1013 0.27 0.059 0.62 0.57 1.1 0.24 3-methylchrysene 0.0038 0.0021 0.011 <0.0002 0.16 0.13 0.33 0.042 0.0032 0.0026 0.0074 <0.0003 0.099 0.085 0.22 0.0045 2-methylchrysene 0.0029 0.0011 0.0091 <0.0002 0.069 0.052 0.14 0.027 0.0019 0.0013 0.0049 <0.0003 0.042 0.033 0.10 <0.0005 6-methylchrysene <0.0013 <0.0002 0.0048 <0.0002 0.051 0.027 0.14 0.0078 <0.0006 <0.0003 0.0016 <0.0003 0.018 0.014 0.044 <0.0004 1-methylchrysene 0.0017 0.0014 0.0039 <0.0002 0.072 0.070 0.11 0.040 0.0021 0.0017 0.0049 <0.0003 0.047 0.035 0.12 <0.0005 benzo(b+k)fluoranthene 0.57 0.59 1.1 0.0608 14 9.8 32 3.6 0.14 0.1070 0.29 0.072 1.1 1.1 1.8 0.55 benzo(e)pyrene 0.24 0.24 0.46 0.0290 3.9 2.1 9.8 1.6 0.047 0.0412 0.070 0.034 0.38 0.37 0.56 0.20 benzo(a)pyrene 0.31 0.18 0.84 0.0173 6.7 4.4 16 1.8 0.035 0.0287 0.079 0.0022 0.75 0.71 1.3 0.32 perylene 0.023 0.0008 0.089 <0.0002 0.87 0.44 2.3 0.26 0.0023 0.0019 0.0049 <0.0003 0.088 0.082 0.19 <0.0005 indeno(1,2,3-cd)fluoranthe 0.021 <0.0002 0.082 <0.0002 0.41 0.24 1.1 0.040 <0.0003 <0.0003 0.023 0.010 0.071 <0.0004 indeno(1,2,3-cd)pyrene 0.83 0.0073 3.3 <0.0002 7.4 5.9 17 1.4 0.039 0.0312 0.095 <0.0003 0.81 0.64 2.0 <0.0005 dibenz(a,h)anthracene 0.064 0.0090 0.24 <0.0002 0.13 0.071 0.36 <0.0004 0.0032 <0.0003 0.012 <0.0003 0.074 0.056 0.18 <0.0004 benzo(ghi)perylene 1.1 0.25 3.9 0.0184 7.0 5.5 17 <0.0005 0.047 0.0337 0.12 <0.0003 0.86 0.86 1.4 0.27 coronene 0.58 0.060 2.2 0.0322 14 6.5 40 2.6 0.020 0.0127 0.055 <0.0003 2.3 1.5 6.0 0.077

Table 11. Fine particle data for the wood stove during the intermediate phase. PM1 fraction and MMD determined from the LPI, and number concentrations and CMD determined from the SMPS. Unit Mode 1, 2 and 3 (8 experimetns) Mode 1 and 2 (6 experiments)

Average Median Max Min Average Median Max Min

PM1* % 84 81 93 75 85 85 93 75

MMD (PM1)* nm 236 212 322 195 212 206 249 195

Numb. Conc. (PM0.7)** #/MJ 2.5E+13 2.3E+13 4.2E+13 1.3E+13 2.4E+13 2.0E+13 4.2E+13 1.3E+13

CMD (PM0.7)** nm 230 232 289 209 215 220 232 209

* Missing LPI data for Exp 7 (mode 2, birch wood) ** Missing SMPS data for Exp 3 (mode 1, birch wood) and Exp 4 (mode 3, birch wood)

Table 12. Fine particle data for the pellet stoves. Each of the operation situation accounted for includes four experiments. PM1 fraction and MMD determined from the LPI, and number concentrations and CMD determined from the SMPS.

Unit Pellet stove A - high load (5 KWfuel) Pellet stove A - low load (1.7 kWfuel) Pellet stove B - high load (5-6 kWfuel) Pellet stove B (Start -ups, intermittent operation)

Average Median Max Min Average Median Max Min Average Median Max Min Average Median Max Min

PM1* % 95 96 99 89 91 93 96 83 84 86 90 75 70 69 86 58

MMD (PM1)* nm 142 144 147 135 132 135 143 114 118 118 120 115 191 193 212 165

Numb. Conc. #/MJ 4.7E+13 5.6E+13 7.1E+13 4.6E+12 6.8E+13 6.2E+13 1.1E+14 4.3E+13 2.3E+14 2.3E+14 2.7E+14 1.9E+14 1.7E+14 1.6E+14 2.8E+14 8.7E+13

(PM0.7)

CMD (PM0.7) nm 75 76 81 67 91 83 110 79 50 50 51 49 38 39 39 36

* Missing LPI data for one (of four) experiments at 5 kW with stove A

21 Fine particle MMD were generally significantly higher during wood log combustion compared to pellets combustion and in Figure 3, typical particle mass size distributions are shown. During the intermediate wood combustion phases MMD varied in the range of 200-300 nm, which can be compared to MMD in range of 100-150 nm during continuous operation of the two pellets stoves. During the start-ups, both in the wood log stove and pellet stove B the fine particle mass size distributions were also shifted to larger particle sizes, i.e. around 200 nm for the pellet stove and in the range 300-600 nm for the wood log stove. During low load operation of pellet stove A, with somewhat increased amount of PIC, no significant change in particle mass size distribution was, however, determined. The influence on mass size distributions of increased amount of PIC during poorer combustion conditions is presumably caused both by increased formation of soot aggregates as well as condensation of organic material on existing sub-micron particles (i.e. soot and/or inorganic particles) during cooling of the flue gases. The limited numbers of previous studies concerning emission particle size characteristics from residential biomass combustion have focused on wood log fireplaces [8, 9, 11] or boilers [18], with some scarce data on residential wood pellets combustion in burners/boilers [18]. A consistent conclusion is that the PM from residential wood combustion in general is dominated by sub-micron particles in the range of 100-300 nm. However, detailed particle size and composition characteristics data determined under systematic variations in combustion conditions and fuel properties in residential wood log and pellet stoves were lacking prior to the present study.

1000 100 Stove A (1.7 kW) Intermediate 90 Stove A (5 kW) Start-up 800 80 Stove B (6kW)

70 Stove B (Start-up)

600 60

400 40 dm/dlog(Dp) [mg/Nm³] dm/dlog(Dp) dm/dlog(Dp) [mg/Nm³] 30

200 20

0 0 0.01 0.1 1 10 0.01 0.1 1 10 Aerodynamic Diameter Dp [µm] Aerodynamic Diameter Dp [µm]

Figure 3. Typical particle mass size distribution for the wood log stove (left) illustrated by results during pine wood combustion (exp nr 9, mode 1) and pellet stoves (right), measured by the LPI. Upper impactor stage and pre-cyclone not included. (concentrations are normalized to 10% O2)

Particle number concentrations and size distributions of fine particles varied between different appliances and combustion conditions but some general trends could bee seen. Compared to the pellet stoves, the particle number concentrations were lower and CMD higher in the wood log stove emissions. Also between the pellet stoves some clear differences were determined since the number concentrations generally were higher and CMD lower for stove B compared to stove A. The average number concentrations were approximately 5 and 10 times higher in the emissions from pellet stove B than from pellet stove A and the wood log stove, respectively. As shown in Table 11, the particle number concentrations during the intermediate combustion phases during the wood log stove 13 13 7 experiments were in the range of 1.3*10 -4.2*10 particles/MJfuel, corresponding to 2.4*10 - 7 3 7.3*10 particles/cmn (at 10% O2), with CMD varying from 209 to 289 nm. Corresponding 13 13 values for the pellet stoves, as shown in Table 12, were 0.5*10 -27*10 particles/MJfuel, 7 7 3 which corresponds to 0.9*10 -45*10 particles/cmn (at 10% O2), with CMD during continuous

22 combustion from 49 to 110 nm. The magnitudes and ranges of the fine particle number concentrations determined in the present study agrees with previous limited data for wood log stoves [10, 36] as well as residential pellet burners and stoves [14]. However, the concise impression is that the data on fine particles are significantly affected by specific fuel properties, appliance design and operation as well as sampling conditions and instrumentation.

For the wood log stove, the number concentrations and size distributions were relatively similar for different fuels and operation modes included. However, distinct differences were in all cases determined for different phases within specific combustion cycles concerning the fine particle number and size characteristics. In Figure 4, typical fine particle number size distributions are further shown for the different phases and in Table 13 the corresponding data for typical SMPS scans during the different phases are specified. Although associated with uncertainties regarding the particle morphology (shape) and densities, the data clearly illustrate the relationship between particle number concentrations, size and mass concentrations, e.g. very low aerosol mass flux during the burn-out phase compared to the other phases. During the intermediate and burn-out phases, the fine mode number size distributions seemed to be monomodal, although shifted to lower particle sizes during the charcoal combustion. The distinct differences between the two phases may be explained by different particle forming mechanism and characteristics. During the start-ups, however, the number distributions were more mixed and seemed to consist of a bimodal fine particle mode. Some scarce previous studies have also characterized the fine particles during different combustion phases in wood log stoves, although with rather different results. In one study the fine mode seemed to be bimodal in all three phases with the most dominant nucleation mode around 40-50 nm in the start-up phase [36]. In another study, similar fine mode size distributions as in the present study were determined for the intermediate and burn-out phases, although with an increased and totally dominating accumulation mode during the start-ups. [10].

Wood stove (Exp 6) 1.E+09 Start-up Intermediate 1.E+08 Burn-out ] -3 n 1.E+07

1.E+06 dN/dlog(Dp) [cm dN/dlog(Dp)

1.E+05

1.E+04 10 100 1000 Mobility diameter (Dp) [nm]

Figure 4. Typical average fine particle number size distributions for the wood stove (Exp 6) during different phases of a combustion cycle, measured by the SMPS. The tail of the intermediate distribution below 25 nm is most probably an artefact of the operation (ventilation) of the CPC.

23 Table 13 Fine particle data from typical scans with the SMPS during different combustion phases in the wood stove experiment 6. Volume concentrations and volume median diameter (VMD) calculated assuming spherical particles and mass concentrations calculated assuming spherical particles with a density of 1 g/cm3. All concentrations are normalized to 10% O2.

Number conc. Volume conc. Mass conc. CMD (nm) VMD (nm) 3 3 3 3 (#/cmn ) (nm /cmn ) (mg/mn )

Start-up 4.0 * 107 2.2 * 1014 220 89 393

Intermediate 2.5 * 107 4.0 * 1014 400 204 461

Burn-out 3.2 * 107 4.5 * 1012 4.5 47 87

Since the pellet stoves operate under continuous combustion conditions, except for the start- ups during intermittent operation with stove B, the formation and emission of fine particles should be rather stable and constant. Some short-time variations may, however, occur as consequences of fluctuating fuel feeding as well as potential influences of different pellet fuel properties and operating conditions. In Figure 5, fine particle number size distributions are shown for different operation conditions with the pellet stoves. Generally, the size distributions seemed in all cases to be monomodal with only small variations between the experiments at different fuel loads. Evident variations were only seen for the experiments during low load in stove A, where the variations in chimney draught seemed to influence the results. At a closer look, however, a similar trend also at high loads, with higher number concentrations at higher chimney draught (30 Pa) was determined compared to lower draught conditions (5 Pa). Higher chimney draught is presumably associated with higher air supply which then may influence the fine particle concentrations. This potential effect is confirmed by the strong correlation between O2 concentrations in the flue gases and the particle number concentrations shown in Figure 6. A similar reversed trend with decreasing particle diameter at higher O2 concentrations was also seen, although not as pronounced as for number concentrations. This correlation between number concentration (and particle diameter) and excess air may be explained by lower degree of coagulation, which is direct associated to initial number concentration and residence time before detection assuming particle growth to be dominated by coagulation [54]. The potential effect of increased soot formation due to lower combustion temperature or increased volatilization of inorganic material due to increased bed temperature was probably insignificant since the PMtot emissions were not correlated to excess oxygen concentrations. Assuming constant total mass of particles to be formed per fuel unit, higher excess O2, i.e. increased air to fuel ratio, may therefore explain the observed effects by the combined effects of increased dilution (i.e. decreased initial particle concentrations) and higher flue gas velocities (i.e. shorter coagulation times). The assumption that particle growth is dominated by coagulation is certainly valid for the aerosol dynamics after the heat exchanger in the stoves and also since the amounts of condensable organics was very low.

The results generally indicate that during poorer combustion conditions, as for the wood log stove with increased amount of PIC and total (fine) particle mass concentrations, the number concentration of fine particles decreases and the particle sizes increases compared to more optimized combustion conditions. However, the differences determined between the pellet stoves were also significant, although with very low amounts of PIC in both cases at high fuel loads. These differences were instead preferably caused by differences in parameters that govern the formation of inorganic fine particles.

24 Pellet stove A (5 kW) Pellet stove A (1.7 kW) 1.E+09 1.E+09 8 mm, 5 Pa 8 mm, 5 Pa 8 mm, 30 Pa 8 mm, 30 Pa 6 mm, 5 Pa 6 mm, 5 Pa 1.E+08 6 mm, 30 Pa 1.E+08 6 mm, 30 Pa ] ] -3 -3 -3 -3 n n

1.E+07 1.E+07 dN/dlog(Dp) [cm [cm dN/dlog(Dp) dN/dlog(Dp) [cm [cm dN/dlog(Dp) 1.E+06 1.E+06

1.E+05 1.E+05 10 100 1000 10 100 1000 Mobility Diameter Dp [nm] Mobility Diameter Dp [nm]

Pellet stove B (6 kW-continuous operation) Pellet stove B (start-ups, 2 kW intermittent) 1.E+10 1.E+10 8 mm, 5 Pa 8 mm, 5 Pa 8 mm, 30 Pa 8 mm, 30 Pa 1.E+09 6 mm, 5 Pa 1.E+09 6 mm, 5 Pa 6 mm, 30 Pa 6 mm, 30 Pa ] ] -3 -3 -3 n n 1.E+08 1.E+08

1.E+07 1.E+07 dN/dlog(Dp) [cm dN/dlog(Dp) dN/dlog(Dp) [cm [cm

1.E+06 1.E+06

1.E+05 1.E+05 10 100 1000 10 100 1000 Mobility Diameter Dp [nm] Mobility Diameter Dp [nm] Figure 5. Average fine particle number size distributions for the pellet stoves measured by the SMPS. For stove A high and low load operation and for stove B continuous operation and start-ups are shown, respectively. For each case, the size distributions during experiments with variations in pellet fuels (6 and 8 mm) and chimney draught (5 and 30 Pa) are included.

3.5E+14 Stove A (1.7 kW)

3.0E+14 Stove B (6 kW) ) R2 = 0.86 fuel Stove A (5 kW) 2.5E+14

2.0E+14

1.5E+14

1.0E+14 R2 = 0.98 R2 = 0.97 Fine particle number conc. Fine particle number (#/MJ 5.0E+13

0.0E+00 10 11 12 13 14 15 16 17 18 19 20 Excess O (%) 2 Figure 6. Fine particle number concentrations versus excess oxygen concentrations in the flue gases for the pellet stoves.

25 While the production of soot and organic PM are governed by the completeness of the combustion, the degree of volatilization of ash forming elements in general increases with higher combustion temperatures. In previous studies on residential biomass combustion those fine particle forming processes have been shown to be influenced by different parameters e.g. fuel properties, combustion conditions and furnace design [10, 12-15, 55] Extensive experiences from diesel emission studies have further shown that different sampling conditions (e.g. dilution ratio, temperature and residence time) can have a significant influence on particle characteristics and distributions [56-59]. Variations in excess air supply have been discussed as an important parameter for particle emissions in small- scale biomass combustion applications and it has been shown that the fine particle number concentrations were decreased as the excess oxygen concentrations were reduced from 12 to 3% during controlled combustion in wood chip burners [10, 13]. Contradictory influences of air supply on the number size distributions were, however, determined in the two studies. In the present study the excess oxygen concentrations for the pellet stoves during high load operation, which is relevant to compare, were significantly higher in stove B than in stove A as discussed previously. In principal, variations in air supply (amount and distribution) will affect both the local gas atmosphere (oxidizing/reducing conditions) within the fuel bed and the combustion intensity (i.e. temperature) and thus volatilization as well as the gas velocity through the fuel bed. Some of these aspects have recently been studied in a small-scale pellets lab-reactor [55], however not further discussed in the present work.

PM morphology and chemical composition As mentioned earlier, minor and varying fractions of coarse particles were found in the PM mainly in the wood log stove emissions, but to some extent also for the pellet stoves. In Figure 7, micrographs of typical coarse particles found both in the wood log and pellet stove emissions are shown. These coarse particles were found in the cyclone samples in the size range of 10-150 µm and consisted of carbonaceous material presumably deriving from unburned fuel residues during incomplete combustion conditions. Within or on the surface of the carbonaceous particle matrix, calcium containing grains (approximately 1-5 µm) were also found.

Figure 7. SEM image of a typical coarse mode particles sampled with the PM8-cyclone during combustion in the wood log and pellet stoves. Left image shows a typical particle found both in the emissions from wood log combustion and pellets combustion. The right image show a second type of carbonacous coarse particle found in the emissions during the start-ups with pellet stove B.

Differences in the coarse fraction were determined for the pellet stoves with 1-10% of PMtot in the emissions from stove A and 10-25% from stove B during high load operation. The coarse fraction was further increased during the start-ups with stove B, and a second type of carbonaceous coarse particles was found in the PM. Also this particle contained minor

26 amounts of inclusions mainly of calcium and some magnesium. The difference in coarse particle formation between the stoves may be explained by differences in combustion intensity, local air to fuel ratios, air distribution and velocities through the fuel bed as well as aerodynamics in the stoves. The results illustrated that a minor fraction of coarse mode particles is produced during combustion in residential wood log and pellet stoves consisting almost entirely of carbonaceous fuel residues with very low content of inorganic ash material. During combustion of other woody fuels than pure stem wood like bark and logging residues in residential or medium-sized grate boilers, a more pronounced coarse fraction of entrained ash particles containing e.g. calcium and magnesium have been found [15, 60, 61]. The elemental analysis showed that the content of sulfur and chlorine in the calcium containing grains was insignificant, and the calcium must instead be associated with anions like O2- or 2- CO3 , in the form of CaO or CaCO3. In trees and other plants, calcium can exist both as - 2+ organically associated ((R-COO )2 Ca ) in cell walls and as included mineral ash-forming matter [62, 63]. In living tree cells, the concentration of calcium ions in solution can be controlled by the production of oxalic acid (H2C2O4) that reacts with free calcium ions and forms calcium oxalate (CaC2O4) crystals. This procedure is a sink for calcium in the tree and the calcium oxalate crystals are enriched in the bark and foliage [62-64]. A plausible hypothesis is therefore that these calcium oxalate crystals forms CaO and/or CaCO3 during combustion and subsequently are entrained from the fuel bed either as inclusions in unburned fuel residues or as separate particles (1-10 µm).

Selected particle samples from the fine particle fractions, sampled with the 13-stage impactor were analyzed for morphology and elemental composition by SEM/EDS and crystalline phase composition by XRD. For the wood log stove, the fine PM mode peak samples (i.e. impactor stage 3 or 4) during the intermediate combustion phase was analyzed from all mode 1 experiments, i.e. birch, spruce and pine wood. For the pellet stoves, a total number of 4 fine mode samples were analyzed; high load in stove A (8 mm pellets), low load in stove A (8 mm pellets), continuous operation in stove B (8 mm pellets) and continuous operation in stove B (6 mm pellets).

As a result of the incomplete combustion conditions the carbon content in the fine particle samples from the wood log stove was very high. Although associated with some uncertainties regarding the quantification of "light" elements, the EDS analysis revealed that the samples both from spruce and pine wood were totally dominated by carbon (~90% by weight) and oxygen (~10% by weight). Any quantification of different inorganic elements was therefore not possible to perform. In the fine mode samples from the birch wood experiments, the fraction of carbon was somewhat lower accordingly with a higher relative contribution of inorganic ash material. In Figure 8, the elemental distribution of the fine mode particles in the emissions from birch wood combustion is shown. Beside carbon and oxygen, the main elements found were potassium, sodium, zinc and chlorine with minor amounts of sulfur, silicon, magnesium and rubidium. The enrichment of potassium, sodium, chlorine, sulfur and zinc in fine particles during combustion of woody biomass fuels in general have been documented previously, both in residential appliances [14, 15, 36, 41, 42] and larger boilers [60, 61, 65-68]. The degree of volatilization, subsequent gas-to-particle conversion and final phase composition may differ significantly and is influenced by combustion temperature, local air to fuel ratio and fuel properties/composition. Bases on the elemental analysis, the high molar ratio of potassium, sodium and zinc, compared to chlorine and sulfur indicates that metal oxides, hydroxides and/or carbonates should be found beside chlorides and sulfates. From the XRD analyses, however, only KCl and K2SO4 were clearly identified in the sample and the low concentrations of inorganic material made any further detailed analysis of the inorganic phase composition of the fine particles from the wood log stove not possible.

27 100 5.0 Weight-% Weight-% 90 4.5 Mole-% Mole-% 80 4.0

70 3.5

60 3.0

50 2.5

40 2.0

30 1.5

20 1.0

10 0.5

0 0.0 C O Na Mg Si P S Cl K Ca Cr Mn Fe Ni Cu Zn As Rb Na Mg Si P S Cl K Ca Cr Mn Fe Ni Cu Zn As Rb

Figure 8. Elemental composition of fine mode particles in the emissions from birch wood combustion in the wood stove (mode 1, exp 2, intermediate phase). Results presented as average values of 3 area analyses (100*100 µm) on impactor stage 3 (Dg=130 nm) with standard deviation shown as error bars. In the left diagram all analyzed elements are shown, and in the right diagram a different scaling is used to get a better resolution of the less abundant elements (C and O not shown). Aluminum was excluded from the analysis since Al-foils were used as sampling substrates.

In Figure 9, a micrograph of fine particles sampled on impactor stage 3 (Dg=130 nm) during high load combustion in pellet stove B, is shown. The bulk of fine PM seems to consist of spherical particles in the range of 100 nm more or less agglomerated in larger structures which probably is an effect of impaction during sampling. Sine the sample had been stored in a desiccator for quite some time before the image was taken, the morphology of the particles may have been affected, e.g. by water up-take of hygroscopic alkali salts.

Figure 9. SEM image of a bulk sample of fine mode particles on impactor stage 3 (Dg=130 nm) sampled in the emissions from pellet stove B during high load combustion. The sample was stored in a desiccator for quite a long time before the image was taken which may have affected the morphology of the particles.

28 The content of carbonaceous material was significantly lower in the fine PM from the pellet stoves compared to the wood log stove fine PM, at least during high fuel loads. During low load operation with stove A, however, the carbon content was increased as a result of incomplete combustion conditions. The elemental composition of the fine PM in the emissions from the pellet stoves are illustrated by the analyses presented in Figure 10 (low load, stove A) and Figure 11 (high load, both stoves). Potassium, sulfur, chlorine and sodium were the dominating elements in all cases, with minor amounts of other elements like magnesium, silicon, zinc and rubidium. Accordingly, the inorganic elemental composition of the fine PM was relatively similar during birch wood combustion as during conifer pellets combustion. However, a difference in the relative contribution of sodium and zinc was determined, which may be an effect of differences in fuel composition and/or ash transformation processes during combustion.

90 9 Weight-% Weight-% 80 8 Mole-% Mole-% 70 7

60 6

50 5

40 4

30 3

20 2

10 1

0 0 i l i Na Mg Si P S Cl K Ca Cr Mn Fe Ni Cu Zn As Rb C O P S C K Cr n e n Na Mg S Ca M F N Cu Z As Rb

Figure 10. Elemental composition of fine mode particles in the emissions from combustion of softwood pellet (8 mm) in stove A at low load (1.7 kWfuel). Results presented as average values of 3 area analyses (100*100 µm) on impactor stage 3 (Dg=130 nm) with standard deviation shown as error bars. In the left diagram all analyzed elements are shown, and in the right digram a different scaling is used to get a better resolution of the less abundant elements (C and O not shown). Aluminum was excluded from the analysis since Al-foils were used as sampling substrates.

Pellet stove B (6 mm pellets) Pellet stove B (8 mm pellets) Pellet stove A (5 kW, 8 mm pellets) 50 50 50

Weight-% Weight-% 45 Weight-% 45 45 Mole-% Mole-% Mole-% 40 40 40

35 35 35

30 30 30

25 25 25

20 20 20

15 15 15

10 10 10

5 5 5

0 0 0 C O Na Mg Si P S Cl K Ca Cr Mn Fe Ni Cu Zn As Rb C O Na Mg Si P S Cl K Ca Cr Mn Fe Ni Cu Zn As Rb C O Na Mg Si P S Cl K Ca Cr Mn Fe Ni Cu Zn As Rb

Figure 11. Elemental composition of fine mode particles in the emissions from combustion of softwood pellets (8 mm upper and 6 mm lower) during high fuel loads (5-6 kWfuel) in the pellet stoves. Results presented as average values of 3 area analyses (100*100 µm) on impactor stage 3 (Dg=130 nm) with standard deviation shown as error bars. Aluminum was excluded from the analysis since Al- foils were used as sampling substrates.

29 In Figure 12, the relative elemental composition is shown for the analyzed fine particle samples during different pellet stove experiments on a carbon, oxygen and aluminum free basis. The higher relative concentrations of potassium and lower concentrations of sulfur between 6 mm and 8 mm pellets are most likely caused by different fuel compositions, i.e. potassium concentrations of 0.060 and 0.038% and sulfur concentrations of 68 and 85 mg/kgdry weight (as seen in Table 3) for 6 and 8 mm pellets respectively. The sodium concentration was approximately the same in the two pellet fuels and the chlorine content below 0.01% in both.

100 Stove B (6 mm) 90 Stove B (8 mm) 80 Stove A 5 kW (8 mm) Stove A 1.7 kW (8 mm) 70

50 Mole-% 40

0 Na Mg Si P S Cl K Ca Cr Mn Fe Ni Cu Zn As Rb

Figure 12. Relative elemental compostion (on a C, O and Al free basis) for the fine mode particles in the emission from combustion of softwood pellets in two pellet stoves. Results presented as average values of 3 area analyses (100*100 µm) on impactor stage 3 (Dg=130 nm) with standard deviation shown as error bars.

The dominating inorganic phases of the fine PM samples from the pellet stoves determined by XRD was shown to be K3Na(SO4)2 and KCl in all analyzed samples. K3Na(SO4)2 is a solid solution of potassium and sodium sulfate thermodynamically stable under 470°C [69], also found in the fine PM in an earlier study during combustion of pelletized softwood sawdust, logging residues and bark in residential burners [15]

Most previous work has focused on elemental and ion composition, but very scarce data is available on the actual phase composition of the PM during biomass combustion. Using time- of-flight secondary ion mass spectrometry (TOF-SIMS) on fine PM from residential softwood pellet burners K2SO4 were found to be the dominant compound followed by KCl and in some cases also significant amounts of K2CO3 [14]. In contrast to methods like ion chromatography and TOF-SIMS, however, XRD is a non-destructive and non-fragmenting method capable of determine complex phases, e.g. solid solutions and intermediate phases. Since alkali, sulfur and chlorine were the dominating elements the molar ratios (K+Na)/(2S+Cl) will indicate the presence of other alkali compounds, e.g. carbonates. This molar ratio was 3.1 in the experiment with 6 mm pellets and approximately 1.5 and 1.0 in the experiments with 8 mm pellets at high and low load respectively. Accordingly, alkali carbonates or some other alkali compound may be found in the fine particles in some cases strongly depending on the fuel composition, although not detected by XRD in the present study.

In contrast to the birch wood experiments, zinc was depleted in the fine PM during combustion in the pellet stoves. This is probably explained by the low concentration of zinc in

30 the pellet fuels (9 and 10 mg/kgdry fuel) compared to the birch wood logs (36 mg/kgdry fuel). The concentration of zinc is normally considerably higher in bark than in stem wood and have to a large extent been shown to be volatilized during combustion. In the earlier study also discussed above [15], zinc was found in increasing concentrations in the fine PM when burning pellets of sawdust, logging residues and bark. However, the phase composition of the fine particle containing zinc could not be determined but the results indicated the presence of a complex zinc phase. Accordingly, zinc is an important trace element in the fine particles from different biomass fuels, but its fate and emitted forms during combustion still remains to be determined.

In the present study, no calcium was detected in the fine mode in any case. However, in a previous study, considerably amounts of calcium in the fine particle fraction have been reported during fixed-bed combustion of bark in pilot scale (440 kWth) and large scale (40 MWth) moving grate plants [60]. The authors could not explain the presence of calcium in the fine particles but assumed very small (submicron) calcium particles to be released from the fuel bed and entrained with the flue gases. Also in another recent study small but significant amounts of calcium were detected in the submicron fly ash fractions during combustion in an 80 MWth pulverized wood fuel boiler [68]. Due to thermodynamic considerations volatilization of calcium should be insignificant during conditions normally prevailing in biomass combustion applications and therefore non-relevant for the formation of fine particles. The potential for calcium to form fine submicron particles during combustion of different biomass fuels is therefore uncertain but may be linked to the release of organically associated calcium under certain conditions.

Parametric analysis and emission modelling The use of statistical experimental design (SED) in emission studies gives benefits in the performance and evaluation proceedings of the experiments. SED is especially useful if the effects of several variables on several emission responses are to be evaluated and to create numerical models for the relationships between variables and responses. Such "soft" statistical emission models are suitable both for emission factor modelling on specific combustion appliances and also to facilitate the development and optimization of new technology. In the present study, a statistical experimental design (i.e. full factorial design) was used only in the pellet stove experiments since the influencing parameters and combustion conditions are more easily controlled and adjusted in those appliances compared to batch fired wood log systems. In the following some illustrative results will be presented and discussed.

As shown in the coefficient plot for stove A in Figure 13, the fuel load was the most important variable for the emissions of CO and PMtot, with increased emissions at low load operation, as discussed previously. Also the influence of pellet diameter was significant, where 8 mm pellets showed to be favourable for the emission performance. Further analysis showed that the variation of pellet diameter influenced the emissions only during low load operation and not at higher loads. Variations in chimney draught, however, showed only a small a non- significant effect. No interaction term between the three variables were significant, but to increase the fit (R2) and predicting power (Q2) of the model, a quadratic term with fuel load 2 2 was included. With "draught" excluded, the PLS models for CO (R =0.86, Q =0.74) and PMtot (R2=0.82, Q2=0.68) were very good. The trends and magnitude of the variable importance for stove B where comparable to those for stove A, although with smaller influence of pellet diameter for stove B than for stove A.

100 5

0 0

CO (mg/MJ) -100 PM-tot (mg/MJ) PM-tot -5

-200 -10 Dra Dra Load Load Dia(6 mm) Dia(8 mm) Dia(6 mm) Dia(8 mm) Load*Load Load*Load

Figure 13. Intercomparable effects (i.e. scaled and centered coefficients) of the different variables on the experimentally determined emissions of CO (left) and PMtot (right) in pellet stove A.

The influence of fuel load separately (i.e. main effect) on the emissions of CO and PMtot are shown for both stoves in Figure 14. The typical trends for the emission performance during continuous (stove A) and intermittent (stove B) operation within the studied fuel load interval (i.e. 2-5 kW) are clearly illustrated.

Based on the PLS analysis, the relation between the significant variables (i.e. fuel load and pellet diameter) and the emissions of CO and PMtot in stove A with 8 mm pellets, are described by the following regression models:

CO = 1318 - 537 * fuel load - 72.5 + 60.3 * fuel load2 (2)

2 PMtot = 61.6 - 20.4 * fuel load - 3.00 + 2.26 * fuel load (3)

In the corresponding model for 6 mm pellets, the negative coefficient for pellet diameter, i.e. - 72.5 in equation (2) and -3.00 in equation (3), should be replaced by a positive coefficient with the same value, i.e. +72.5 and +3.00 respectively.

It is important to consider the fact that this kind of parametric analysis and emission modelling is case specific, and basically valid only for the specific appliances and fuels presently used. However, the general trends and relative importance of different variables is probably relevant also for other pellet stoves, although further and more extensive work is needed if generally applicable and parametric derived emission models for different type of residential appliances are to be determined. Beside the influence of furnace design, it has previously also been shown that variations in quality properties of different pellet fuels can influence the combustion performance significantly [70, 71].

700 40 Pellet stove A Pellet stove A 600

500 30 400

300 CO (mg/MJ) (mg/MJ) 20 PM-tot (mg/MJ) 200

100 10 2345 2345 Fuel Load (kW) Fuel load (kW)

600 Pellet stove B Pellet stove B 500 40

400

300 30 200 CO (mg/MJ) 100 PM-tot (mg/MJ) 20 0

-100

2345623456 Fuel load (kW) Fuel load (kW)

Figure 14. Main effects of fuel load on the emissions of CO and PMtot in pellet stove A (upper) and B (lower).

Acknowledgement The authors would like to acknowledge a number of persons and institutions for valuable contribution to the project; Fredrik Granberg for the experimental work at Energy Technology Centre in Piteå, Lena Elfver at the Department of Analytical Chemistry, Stockholm University, for the analytical work concerning PAH, IVL Swedish Environmental Research Institute in Gothenburg for the VOC analyses, Per Hörstedt at the Department of Medical Biosciences, Umeå University for the complementary SEM work and FOI in Umeå for supplying the project with the SMPS system. Finally, the financial support from the Swedish Energy Agency and the Center for Environmental Research in Umeå is gratefully acknowledged.

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