POLITECNICO DI MILANO

Department of Civil and Environmental Engineering

Thesis of M.S degree

Ultrafine and nanoparticle emissions of different biomass

combustion appliances

Supervisor : Prof. Stefano Cernuschi

Assitant supervisor : Senem Ozgen

Peng Yu

Academic year: 2012 - 2013

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Abstract

Biomass combustion generates large amount of fine particles, especially

nanoparticles (NP) and ultrafine particles (UFP), may influence the

environment and cause consequent adverse human health problems. The

objectives of this work were to characterize NP and UFP emitted from

different scale biomass combustion units and to assess the roles of

dilution conditions and combustion conditions in NP and UFP formation.

In this study, a vibration grate bed biomass power plant (nominal

thermal output: 15MW), a pellet boiler (nominal thermal output: 100kW)

and a closed modern fireplace (nominal thermal output: 11 kW) were

studied. The influence of dilution condition, the operation parameters such

as load of the boiler and combustion conditions were investigated. The

special designed sampling systems were used to measure the

nanoparticles and ultrafine particles. Electrical low-pressure impactor was

applied to record the real-time number concentrations and number size

distributions for all the cases. The regulated gaseous pollutants (CO, CO2,

SO2, NOx, CH4, NMHC) and relevant operation parameters such as flue

gas temperature, and oxygen content of flue gas were continuously

measured in all cases.

The results suggested that different combustion technologies lead to

very different particle emission characteristics. The total particle number

concentration of the continuous operation power plant was in the order of

106, with NP and UFP fractions accounted more than 90% and 99%,

respectively. The GMD was around 27 nm.

The pellet boiler was operated under nominal and non nominal

(reduced load) conditions. The average particle total number

concentration of this pellet boiler was around 107. There was a tendency

that the peak number concentration of particle shifted to coarser particles

when loads reduced due to worse combustion. The NP and UFP fractions

also decreased obviously with the decreasing load. The condensation of

semi volatile flue gas pollutants was associated with the NP fractions

emitted in both the boiler and the power plant.

The fireplace emitted significant amount of particles since the total

particle number concentration was in the order around 108. The emissions

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changed phase by phase and cycle by cycle. The average fraction of NP

and UFP were respectively 59% and 75%. Correlation analysis indicated

that there was a strong statistic correlation between NP emission and

NMHC mass concentration.

Proper primary and secondary measures should be adopted to reduce

the PM emissions from biomass combustion units. The comparison

between different combustion systems suggested emissions from small

scale appliances like fireplace are significant than larger units. The

regulations of PM should also be considered not only based on mass but

also on other properties like number concentrations since the huge

adverse effects of very fine particles.

Key words: biomass combustion, nanoparticle, ultrafine particle, PM

emissions, power plant, pellet boiler, fireplace, semi volatile species,

NMHC, primary measures, secondary measures

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Acknowledgement

This work would not been carried out without the people who helped me

and supported me all the time.

First, I would like to thank my supervisor Professor Stefano

Cernuschi, for his invaluable guidance, suggestions and support from the

beginning to the end. And I also appreciate the help from my assistant

supervisor Senem Ozgen. Her patience, kindness and constructive advice

impressed me a lot. Thank my supervisors for the time spent on my thesis,

also for answering all my questions and explaining me so patiently.

Thanks for all the data provided from the plant and laboratory.

In past two years, I had studied energy engineering in Politecnico di

Milano, I had my most meaningful two years because of all my

professors, teachers and my classmates. I learned a lot from them not only

from class but also from daily life.

My dear friends I met here, whom I spent a lot of happy time with,

especially my roommates, are those people I would like to thank for.

Without your help and support I can’t imagine how my life would be.

They make me feel so lucky.

Finally, I would like to thank my mother and father for their love,

support and understanding for all these years. No matter when and where,

I always get their encouragement and love, thanks a lot for being here

with me.

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List of acronyms and definitions

Aerodynamic diameter (da) Diameter of a standard-density (100 kg/m3)

spherical particle having the same

gravitational settling velocity as the

observed particle

CEMS Continuous emission monitoring system

Coarse particles Particles larger than 1 micron in diameter

dp Particle diameter

DR Dilution ratio

EC Elemental carbon

ELPI Electrical low pressure impactor

ESP Electrostatic precipitator

FF Fabric filter

Fine particles Particles smaller than 1 micron in diameter

FGCS Flue gas cleaning system

FID Flame ionization detector

GMD Geometric mean diameter

GSD Geometric standard deviation

HEPA High efficiency particulate air (filter)

IPCC Intergovernmental Panel on Climate

Change

NMHC Non methane hydrocarbon

NP Nanoparticle with aerodynamic diameter

smaller than 50 nanometers

NTP Normal temperature and pressure (in this

work 273 K and 101325 Pa)

OC Organic carbon

OXYCAT catalytic oxidizer

PAH Polycyclic aromatic hydrocarbons

PM Particulate matter

PM1 aerodynamic diameter of particles smaller

than1 micron

PM2.5 aerodynamic diameter of particles smaller

than 2.5 microns

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PM10 aerodynamic diameter of particles smaller

than 10 microns

SNCR Selective non catalytic reduction

Soot Fine particles composed of elemental

carbon

TN Total number concentration of particles

THC Total hydrocarbon

TOC Total organic carbon

TSP Total suspended particles

UFP Ultrafine particle with aerodynamic

diameter smaller than 100 nanometers

VOC Volatile organic compounds

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Contents

1. Introduction ........................................................................................ 8

1.1 Environmental effect of particle matter ...................................... 9

1.2 Epidemiological studies of PM ................................................ 10

1.3 Regulation of PM .................................................................... 11

2. Scientific background ....................................................................... 11

2.1 Combustion technologies ......................................................... 11

2.2 PM and other gaseous emission issues .................................... 12

2.3 Control technology of PM ....................................................... 15

3. Material and methods ........................................................................ 19

3.1 Investigated combustion systems.............................................. 19

3.1.1 Woody biomass power plant .......................................... 19

3.1.2 Advanced wood pellet boiler ......................................... 20

3.1.3 Modern closed fireplace ................................................ 21

3.2 Measurement systems ............................................................. 22

3.3 Sampling ................................................................................. 26

3.3.1 . Hot sampling……………………………………………26

3.3.2 . Diluted sampling………………………………………..27

4. Results .............................................................................................. 27

4.1 Woody biomass power plant ..................................................... 28

4.1.1 Particle number concentration and size distribution ....... 29

4.1.2 Gaseous emissions and correlation with NP .................. 33

4.2 Advanced wood pellet boiler ................................................... 34

4.2.1 . Particle number concentration and size distribution……35

4.2.2 Gaseous emissions and correlation with NP .................. 40

4.3 Modern closed fireplace ........................................................... 41

4.3.1 Particle number concentration and size distribution ....... 42

4.3.2 Gaseous emissions and correlation with NP .................. 46

4.4 Comparison of different appliances .......................................... 50

5. Conclusions ...................................................................................... 51

References ............................................................................................. 55

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1. Introduction

Biomass is one of the most important renewable energy sources widely

used around the world nowadays. Not only due to the limitation of the

availability of fossil fuels but also because it is considered as a CO2

neutral energy source. Biomass provides 14% of the global primary

energy and it ranks the fourth energy source except coal, oil and natural

gas (Demirbas, 2004).

Biomass includes any biological materials from living or recently

living organisms, such as forest by-products (wood residues), agricultural

waste (sugar cane residue) and animal husbandry residues (poultry litter).

Generally, biomass can be directly or indirectly used by thermal

conversion, chemical conversion or biochemical conversion. The

characteristics and quality of biomass fuels mainly depends on the kind of

biomass and the pretreatment technologies applied, and they vary wildly.

Compared with coal, biomass generally contains a higher volatile content

and a lower char content, which make biomass a highly reactive fuel (Van

Loo et al., 2008).

Biomass contains five main fuel elements: C, H, S, N and O. Various

trace elements such as Zn, Cd, Cu, Pb, Cr and Hg can be found in

biomass (Demibras, A., 2005), and the major ash-forming elements such

as Si, Ca, Mg, K, Na, Cl and P occur in biomass fuels (Werkelin et al.,

2005).

Combustion technology of biomass accounts for more than 90% of

the global contribution of bioenergy. With the proper design and

operation, biomass energy can be a technically efficient, economically

viable, and environmentally sustainable fuel option (Van Loo et al., 2008).

However, there are still some problems caused by burning of biomass

because it is a significant source of gaseous and particulate matter (PM)

emissions to the troposphere on a local, regional and even global scale.

First of all, the emission of CO, CH4 and Volatile organic carbon (VOC)

affect the oxidation capacity of the troposphere by reacting with OH

radicals, and emissions of nitric oxides (NOX) and VOC may alter the

photo-stationary equilibrium, then lead to the formation of ozone and

other photo oxidants in atmosphere (Koppmann et al., 2005).

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Moreover, biomass furnaces emit relatively high quantities of

particles when compared with natural gas and light fuel oil furnaces

(Nussbaumer, T., 2001), due to the higher ash content of biomass. The

particle size distribution and number concentration of particulate matters

emitted from biomass combustion units vary from different fuels and

combustion systems (Nussbaumer, 2003). The particles which generated

during combustion process may deposit on the surfaces of boiler and

other heat exchangers, and will lead to some operational problems such as

corrosion and lower efficiency. What’s more, if there is no effective flue

gas cleaning system (FGCS) applied for biomass combustion appliances,

the significant amount of particles will be directly emitted to the ambient

air. The emission of particles would certainly change the air quality

locally even regionally. And recent studies show that there is a strong

correlation between particle concentration and human health (Peters et al.,

1997; Dockery et al., 1993; Schwartz, J., 1994).

1.1 Environmental effect of particle matter

The sources of particulate matter are both anthropogenic and natural.

Besides the significant amount of fine and ultrafine particles deriving

from natural processes, the PM emitted directly from industrial activities,

transportation, power plants, or indirectly through conversion of gaseous

precursors such as ammonia and sulfur oxides (Yinon et al., 2010 ).

Nowadays particulate matter emission becomes an important issue of

air pollution worldwide. Like most of the environmental pollutants, the

effects of PM are complex, and the characteristics of the particles

(particle size, chemical composition and structure) determine the effects.

The majority of the big amount of particles emitted due to biomass

combustion have an aerodynamic diameter smaller than 10 microns

(PM10), besides, a high percentage of fine particles which have an

aerodynamic diameter smaller than 2.5 microns (PM2.5) can be found

(Nussbaumer et al., 2002).

In addition, fine particle emissions from combustion sources have

direct effects on the climate by absorbing and scattering sunlight and their

chemical properties have a strong influence on the effects. Particles

contain elemental carbons which tend to absorb sunlight and contribute to

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global warming. While Sulphate particles will scatter sunlight and have a

cooling effect (Shindel et al., 2009; IPCC, 2007). The complicated

chemical properties of the particles will cause numerous effects on the

climate.

1.2 Epidemiological studies of PM

The PM not only effects on the environment but also effects on human

health, and the effects were determined by the characteristics of the

particles such as particle size, chemical composition and structure as well

(Nussbaumer, 2002). The fine particles and ultrafine particles

(aerodynamic diameter da<0.1 microns) are specially concerned with

respect to human health effects (Dockery et al., 1993) because of their

ability to penetrate lungs as far as the alveolar region upon inhalation, and

this may cause cellular damage (Peters et al., 1997). The chemical

properties such as the contents of transition metals, polycyclic aromatic

hydrocarbons (PAH), organic material, elemental carbon (EC) and acidity

of the fine particles have been suggested to be the key properties related

to adverse health effects (Lighty et al, 2000; Kennedy, 2007). Moreover,

the high specific surface area of fine particles may increase the transport

of surface enriched toxic trace metals with respect to larger particles

(Wichmann et al., 2003).

Short-term and long-term exposure studies are the typical available

epidemiology studies of particulate air pollution (Braun-Fahrländer, C.,

2001). Several short-term studies suggested that there is a strong causal

relation between particulate air pollution and respiratory symptoms, lung

function, exacerbation of asthma, hospital admissions and mortality

(Dockery et al., 1994; Schwartz, J., 1994; Ostrong et al., 1998; Pope et

al., 1995; Samet et al., 1998). Cardiovascular deaths are increased with

the increased particle exposure, besides respiratory deaths.

Long-term studies showed that there is a risk of reduction of lung

function when people exposure in particulate polluted air. And some other

studies showed that there are associations between particulate air

pollution and chronic respiratory symptoms or disease.

The ultrafine particle will have larger health influence than fine

particle with the same mass based on the study. And ultrafine particles

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due to combustion of coal and mobile sources will cause a respectively

increasing in daily mortality (Braun-Fahrländer, C., 2001).

1.3 Regulation of PM

Now there are some regulations for particle emission of biomass power

plant, which focus on the mass concentration. PM10 is an important

parameter to be monitored in United States, and in 1997, the United

States established a new regulation of PM2.5 in addition to existing

standards of PM10. The European authorities also established a

regulation of PM10 in 2005, then a new regulation of PM2.5 three years

later in 2008 (Maguhn et al.,2003).

Ultrafine particles have huge influences on both environmental and

human health. Based on the fact, that the number of ultrafine particles

emission is huge while their mass is not in proportion and generally it is

negligible, the indicator of particle mass concentration is reasonable but

may not be enough (Cernuschi et al., 2010). Nowadays several studies

also found out there is a correlation between increased ambient

particulate number concentrations and adverse health effect, even when

the particle mass concentration reached the requirement of the air quality

standards (Lighty et al., 2000).

In order to assess potential health effects better, several

epidemiological studies suggested that different particle characteristics

should be also considered and monitored, such as particle number

concentration, morphology and chemical speciation (Braun-Fahrländer,

C., 2001; Lightly et al., 2000).

2. Scientific background

2.1 Combustion technologies

The nature of biomass combustion process depends on the fuel properties

and the combustion appliances, and the process can be divided into four

steps: drying, pyrolysis, gasification and combustion (Van Loo et al.,

12

2008). For different purpose and different fuel types, the different

technologies should be applied. We can divide them into different

categories based on different ways.

The appliances can be used for domestic heating, industrial and

district heating, power generation, etc. Wood stove, fireplace and wood

pellet boiler which commonly burn wood and provide domestic heat. This

kind of appliances is generally manually fuel feeding and controlling.

And the emissions of PM and other gaseous species are high because of

no FGCS equipped with. There are several techniques for industrial

utilization or power generation: fixed bed combustion, fluidized bed

combustion and pulverized fuel combustion. They are equipped with

automatic fuel feeding system, FGCS and fully operated automatically by

the control system to achieve the strict emission limits (Van Loo et al.,

2008).

Based on thermal power capacity, we can generally divide

combustion systems into the small-scale system which has a thermal

power output less than 100 kW, the medium-scale system which has a

thermal power ranged from 100 kW to 2 MW, and the large-scale system

which has a thermal power output larger than 2 MW. Small-scale biomass

combustion systems are commonly used for residential heating. Medium

or large scale combustion systems are usually applied for industrial and

district heating purpose.

2.2 PM and other gaseous emission issues

Particulate matter is a complex mixture of airborne particles and liquid

droplets which are composed of acids (such as nitrates and sulfates),

ammonium, water, elemental carbon, organic chemicals, metals and soil

(crustal) material (Nussbaumer et al., 2008). The dimensions of PM range

from few nanometers up to around hundred microns. The particles from

biomass combustion are grouped into two categories base on

aerodynamic dimensions (EPA, 2008): coarse particles which range from

2.5 to 10 microns, and fine particles. For better understanding of PM

behavior, particles with an aerodynamic diameter less than 100

nanometers are distinguished as ultrafine particle (UFP) while

nanoparticle (NP) defined as particle aerodynamic diameter is less than

13

50 nanometers. Their dimensions are shown in figure 2.2.1.

Figure 2.2.1 Particulate matter air pollution size distribution (Brook et

al., 2004)

The physical and chemical properties of particles formed from

biomass combustion depend on several factors such as fuel properties,

combustor design, operation conditions, etc. The different appliances of

combustion systems can lead to significant variations of particle

emissions.

Particle emissions from combustion systems originate from different

sources. The primary particles which formed during combustion process

directly included coarse fly-ash and combustion aerosols. Fly-ash

(particle diameter larger than 1 micron) is the entrainment of ash particles

in the flue gas. Combustion aerosols (particle diameter less than 1 micron)

are formed multimodal.

One type of aerosol is originated from inorganic compounds, like

alkali salts (such as alkali sulphates and chlorides), which is due to the

reaction between K or Na and Cl or S released from fuel to gas phase

during combustion process, and subsequently form sub-micron particles

by nucleation and condensation process directly (Van Loo et al., 2008).

Soot (elemental carbon) is produced at high temperature in fuel rich

condition due to the incomplete combustion, and it is a kind of

combustible material. With enough reaction time and oxygen, soot can be

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oxidized to CO and CO2 (Lighty et al., 2000). The growth mechanism of

aerosol is due to some species, which are vaporized during combustion

process, saturate and form fine particles by homogeneous or

heterogeneous nucleation. The nucleated particles undergo coagulation

and agglomeration, condensation and surface reactions. The final particle

dimension depends on the residence time of the flue gas in the

combustion system, and a longer residence time makes a bigger

opportunity for particles to coagulate and grow (Liank et al., 1993).

In addition, some particles are formed as products of reactions

between gases released in combustion process or on the surface of

previously formed particles, during diluting exhaust plume or in the

atmosphere. This type of particles is called secondary particles, and this

process is called gas-to-particle conversion. The particles formation

caused by compounds is approximately equal to the amount of initially

vaporized compounds that is in excess of equilibrium at the ambient

temperature (Lighty et al., 2000).

There are at least three modes of gas-to-particle conversion. One is

near source condensation of primary low vapor pressure organics. For

example, the long chain organic carbons condense onto smoke particles

immediately after the plume leaves the flame zone. Another one is the

production of inorganic particulate matter such as sulfate, ammomium

and nitrate, and much of the formation is from primary gas emissions of

SO2, NOx, and NH3. Last but not least, there is also the conversion of

organics, such as the reactive non methane hydrocarbon (NMHC) and

organic acids (Reid et al., 2005; Kreidenweis et al., 2001).

The growth mechanisms of secondary aerosol particles involve vapor

condensation, coagulation, agglomeration, surface reactions and

adsorption. Particle size and saturation ratio S are two important

parameters for condensation process.

( )S

PS

P T

Where P is the partial pressure of a vapor, and Ps is the saturation

pressure which changes with temperature. Generally, condensation onto

the surface of existing particles is thermodynamically favored over

nucleation, but when the S is sufficiently high for a given mixture, the

homogeneous nucleation may occur. Thus the dilution conditions such as

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dilution temperature and dilution ratio are important for the particle

condensation.

Except for particle matter emissions, there are other gaseous

emissions generated during biomass combustion processes from

incomplete and complete combustions.

Incomplete combustion is due to the inadequate mixing of

combustion air and fuel in the combustion chamber, the overall lack of

oxygen, low combustion temperature, too short residence time, etc.

Carbon monoxide (CO), methane (CH4), non methane hydrocarbon

components (NMHC) and polycyclic aromatic hydrocarbons (PAH) are

emitted as incomplete combustion products (Van Loo et al., 2008).

Emissions from complete combustion are carbon dioxide (CO2),

nitrogen oxides (NOX), sulfur dioxide (SO2) and hydrogen chloride (HCl).

The regulations of these pollutants are applied due to their negative

influences on environment. Furthermore, NOX, SO2 and VOCs participate

in the secondary particle formation in the atmosphere (IPCC, 2007). The

real emissions of these pollutants are mainly dependent on combustion

conditions and flue gas cleaning system.

2.3 Control technology of PM

Primary measures aim to prevent or reduce the PM formation and

emission in combustion chamber. Primary measures such as pretreatment

of biomass fuel via modification of the fuel composition, the moisture

content of the fuel and the fuel size can be adopted for all the combustion

units if the benefits overweight the costs.

Besides the pretreatment of biomass, the very important concepts of

primary measures are optimization of combustion, and they will reduce

the incomplete combustion productions as well. Sufficient high

combustion temperature, long residence times, homogeneous mixture of

fuel and air when changing of fuel should be achieved to ensure a

complete combustion. Well designed combustion appliances and proper

controlled of the combustion process are common primary measures,

which are widely used in real applications (Van Loo et al., 2008).

When there are limitations for emissions, the secondary measures

downstream to remove particles from the flue gas are necessary. Cyclone

16

or multi cyclones, electrostatic precipitators (ESP), fabric filter (FF) and

other methods are available equipments to reduce the particles in the flue

gas.

Different primary measures and secondary measures are used for

varied biomass combustion systems in order to meet the regulations. The

primary consideration to choose the measures is the heat or power

capacity of the units. Technological and economical considerations are

important as well (Van Loo et al., 2008).

2.3.1 Control technology for large appliances

Automatically fuel feeding systems are applied in the big biomass

combustion units. This system allows an optimum adjustment of the fuel

flow to the actual load conditions. A well designed fuel bed and grate

systems combine with proper combustion air supply can make a

homogeneous mixture of fuel and air and a complete combustion. Air

supply strategies have turned out to be the most effective method. Low

primary air is used to control the burn rate and secondary air is used later

to complete oxide the gaseous species released from the fuel (Brunner et

al., 2009). In addition, the automatic control systems should be

programmed for simultaneous optimization of the combustion process to

minimize emissions and maximize the efficiency.

However, the studies show that the reduction potential of primary

measures will not be sufficiently effective to achieve the emissions

limitations (Gaefauf et al., 1998; Wagner et al., 2000; Wehinger et al.,

2000). Hence, secondary measures are applied for regulation of PM

emission, and multi cyclones, electrostatic precipitators and fabric filter

are commonly used devices.

Multi cyclones are economical and widely used in medium and large

scale biomass combustion systems for particle precipitation. Centrifugal

forces are used by cyclones to separate particles from flue gas, and they

have relative a good efficiency around 80% for PM10. However, the

efficiency decreases to 20% for particulates whose aerodynamic diameter

is smaller than 5 microns (Jiao et al., 2007), and efficiencies for remove

UFP and NP are close to zero. These characteristics of cyclones make the

main fraction, which under good combustion conditions, not be separated

17

from flue gas (Nussbaumer, T., 2001).

Electrostatic precipitators electrically charge the particles in the flue

gas and then collect them to the electrode plate. The overall efficiency of

ESP general more than 99% in terms of mass. Though the efficiencies for

removal of UFP and NP decrease, they are still higher than 95% with

modern advanced ESP. The good efficiencies suggest that the ESP can be

an efficient device to remove all size range PM form flue gas for

industrial purpose (Ghafghazi et al., 2011).

Another highly efficient and economical device used for industrial

emission control is fabric filter (baghouse), which collects the particles on

the surface of the sieving textile media. A well designed baghouse can

remove multiple pollutants such as particles, heavy metals, dioxins and

furans from flue gas (Tejima et al., 1996). The capture efficiency is good

which is higher than 99.5% for all particle size ranges, so even the UFP

and NP fractions can be efficiently separated from flue gas. And figure

2.3.1.1 shows the efficiencies of all the three conventional used emission

control systems.

Figure 2.3.1.1 Collection efficiency of conventional gas cleaning

technologies (Hasler et al., 1999)

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2.3.2 Control technology for medium and small scale appliances

The primary measures for reducing the emission of PM are very

important for medium and small scale applications due to the

technological and economical considerations. Better combustion and

lower emissions are the goal of primary measures for smaller size

combustion units as well.

Automatically feeding screws are applied for modern pellet boiler to

ensure an optimum adjustment of the fuel flow to the actual load

conditions. The pellet boiler should have a well designed grate system to

guarantee a good mixture of fuel and air. Air strategies and proper air

supply can also be very efficient ways to improve the thermal efficiency

and reduce the emissions. The combustion chamber of pellet boiler can be

divided into two zones, a primary combustion zone and a secondary zone,

and the proper designed chamber dimension can optimize the combustion

process. Advance control systems also equipped with modern wood chip,

pellet boilers, which maintain the good combustion and low emissions of

the boilers (Brunner et al., 2009).

Typical batch burning devices like wood stove and fireplace are

different from other appliances. They don’t have automatic control

systems, and the user may significantly influence the emissions by using

improper fuel, implying wrong charging and ignition, etc. A basic training

for users of stoves and fireplace is necessary. And proper designs of

stoves and fireplaces such as appropriate air staging and combustion

chamber design are very useful ways to reduce the emissions (Brunner et

al., 2009).

The cyclone and multi cyclones are applied for boilers to separate

particles form flue gas, and as stated before, their efficiency of capturing

NP and UFP are not ideal. There still are significant fine particles

emissions from the boilers. What is worse, installation of FGCS for batch

burning devices is not attractive from the economical point of view, so

the stoves and fireplaces are generally not equipped with any flue gas

cleaning devices. The PM emissions could be very significant compared

with other appliances.

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3. Material and methods

In this study, a biomass power plant, a wood pellet boiler and a fireplace

in different scales of biomass combustion systems, which firing three

different biofuels were investigated. The nominal thermal capacities were

in the range of 11 kW to 15 MW.

Due to a focus on UFP and NP fractions of total particle emissions in

these three types of appliances, the real-time sampling systems were

equipped with a specifically designed sampling line, which included

dilution systems and particle counting devices. All the measurements

were done simultaneously in the stack in the three cases.

3.1 Investigated combustion systems

3.1.1 Woody biomass power plant

The 15MW thermal output water cooled vibrating grate–firing bed, which

feeds untreated wood 20 t h-1

. The grate-firing furnace is a typical fixed

bed combustion technology, which is appropriate for biomass fuels with

high moisture content and varying size since the vibrating grates can

ensure a mixture of the fuels across the grate (Van Loo et al., 2008).

In order to achieve the requirements of air quality limits, a flue gas

cleaning system was installed in the power plant. The flue gas cleaning

system consists of a dry electrostatic precipitator (ESP), an alkaline dry

sorbent injection and a fabric filter (FF) for removal of particulate matter

(table 3.1.1.1). To remove NOX, a urea based-SNCR (Selective Non

Catalytic Reduction) was installed in the post combustion zone. Between

ESP and FF a catalytic oxidizer (OXYCAT) were installed, and no

alkaline sorbent injection when SNCR and OXYCAT units stopped

working or sampling measurements took place.

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ESP FF

Type Dry Fabric material Glass fiber + PTFE

Number of sections 2 Filter bag number 1170

Voltage (kV) 110 dimensions of bag Φ153×4800mm

Inlet temperature (℃) 250-300 Inlet temperature (℃) 130-135

Table 3.1.1.1 The characters of particle clean units

3.1.2 Advanced wood pellet boiler

A Kob-Pyrot residential heating wood pellet boiler with a nominal 100

kW thermal power output was investigated in this study, and the

configuration of the boiler is shown in figure 3.1.2.1. This boiler is

representative of the typical residential scale heating application in Italy.

The boiler is equipped with an axial flow cyclone dust removal device

due to the simplicity and low cost of cyclone.

The boiler has two stages of combustion air with flue gas

recirculation. Primary combustion air supplied by an electric fan with

minimal value and then secondary air mixed with gasification

combustible gas in the rotary combustion chamber. The high combustion

efficiency and low emissions will be achieved since the gasification of

the fuel.

All the tests were carried out at the laboratory Sazione Sperimentale

per i Combustibili. The automatic fuel feeding device supplied the fuel

21.4 kg h-1

continuously at nominal load condition. An advanced control

system adjusted the fuel feeding to meet the load demanded. The fuel

used has low sulfur content around 0.03%, chlorine content less than

0.01%, and moisture around 7% based on wet weight. All the

measurements were conducted during the boiler operation at steady state.

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Figure 3.1.2.1 Kob-Pyrot wood pellet boiler

3.1.3 Modern closed fireplace

The modern closed fireplace with a nominal 11 kW thermal power output

was investigated in this study. The primary and secondary airs were

supplied to the fireplace by natural air convection. The boiler was

manually fed with beech wood logs, which with low moisture level less

than 10% and ash content was around 0.5% based on wet weight. This

appliance performed without any flue gas clean devices and relative

lower thermal efficiency was achieved.

The traditional small scale batch–fired systems such as fireplace, heat

stoves generally applied for domestic heating. The fuel feed in this kind

of system is not continuous and automatic, so the combustion

characteristics are dynamic changing with operation of time.

Because of the unstable combustion process, the concentrations of

pollutants are higher than the larger scale appliances. What’s more, the

flue gas cleaning system is not economically feasible for this kind of

system. The lack of any emission control device of small-scale

combustion appliances leads to pollutants emission and especially for

particulate matter issues. In winter time, the small-scale appliances are

popular around European countries, and the big amount of users may

cause problems of local air quality (Johansson et al., 2001).

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3.2 Measurement systems

Different measurement and sampling methods have been used for particle

size distribution and number concentration. The special dilution sampling

systems was used in this study for pellet boiler based on the EPA

CTM-093 train (US-EPA, 2004). Both UFP and NP fractions from

primary and secondary condensation can be evaluation through dilution

processes of sampled flue gas.

The measurement line was assembled with a PM10 and a PM2.5

cyclone in series as pre-cut multi cyclones to collect particles with

aerodynamic diameter bigger than 2.5 microns for pellet boiler, and only

a PM2.5 pre-cut cyclone was equipped for power plant. For the purpose

of reaching the range measurable by the ELPI, a two-stage dilutor

(FPS-4000, Dekati Ltd., Finland) was equipped for diluting sampling flue

gas. The first perforated dilutor is to minimize the particle losses and the

second dilutor is an ejector type diluter. And the first diluter can be heated

with a probe heater, then dehumidified and HEPA filtered dilution air

diluted the sampling gas in a conical mixing zone. Carbon dioxide

concentrations measured before and after were used to calculate the

dilution ratio (DR). By changing the dilution temperature and dilution

ratio, we can find the influence of dilution on particle number

concentration and size distribution.

The real-time particle size spectrometer electrical low pressure

impactor (Dekati Ltd., Finland) is used to measure the particle number

concentration and the size distribution in these three cases by analyzing

the particle aerodynamic diamter. The ELPI (Figure 3.2.1) measures

airborne particle size distribution in the size range of 0.03-10 microns

with 12 channels. With filter stage, the size range can be extended down

to 7 nm. In this study, the filter and first stage together are used to

account nanoparticles. The operating principle of ELPI is based on

particle inertia when they are charged and collected in a cascade low

pressure impactor.

23

Figure 3.2.1 Structure of ELPI

The main components of ELPI are a corona charge, a low-pressure

cascade impactor and multi channel electrometer. The impactor classifies

the particle according to their aerodynamic diameter. The range Di and

geometric mean median diameter Dp of each stage are listed in table 3.2.1.

Greased aluminum foils were used on the collection plates to protect the

collection plates from fouling and prevent cleaning plates every time after

each measurement.

stage 1 2 3 4 5 6 7 8 9 10 11 12

Di (μm) 0.03 0.06 0.09 0.16 0.26 0.39 0.62 0.96 1.61 2.41 4.02 9.98

Dp (μm) 0.02 0.04 0.07 0.12 0.20 0.32 0.49 0.77 1.24 1.97 3.11 6.33

Table 3.2.1 Calibration data of ELPI

When the sample passes through a unipolar positive polarity charger,

where the particles in the sample are charged and the charged particle

were collected in specific impactor stage, it produce an electrical current,

which was recorded by the respective electrometer channel. The particle

number collected is proportional to the current value recorded by the

24

respective channel. The larger the current is, the larger number of particle

will be collected. Total particle number concentration (TN) is the sum of

each stage recorded.

During sampling process, the sampling gas was extracted

isokinetically with a stainless steel heated probe, after passing through the

pre-cut cyclones and a venture, it reached to the conical mixing zone,

where it was rapidly mixed with the dilution air. Then it entered into a

tubular residence chamber for proper residence time and finally arrived to

the ELPI for particle measurement. The system was monitored and

controlled by software and regulated with a control unit. The general

figure of sampling and measurement system are briefly shown in figure

3.2.2.

Figure 3.2.2 Measurement and sampling system

The sampling and measurement system for fireplace is different from

the others. As figure 3.2.3 shows, the sampling flue gas preliminary

diluted with local ambient air in a dilution tunnel and then underwent

further dilution by the two-stage dilutor (FPS-4000, Dekati Ltd., Finland).

The calculation of the tunnel dilution ratio was also based on the carbon

dioxide concentration measured of the flue gas before and after the

preliminary dilution.

25

Figure 3.2.3 Sampling and measurement system (Ozgen et al, 2012)

During the process of measurement, sampling flue gas was extracted

from the preliminary dilution tunnel with a heated probe equipped with a

pre-cut PM2.5 cyclone. Then it further was diluted by the two-stage

dilutor with dehumidified, and HEPA filtered dilution air. The same kind

of 12-stage ELPI was used to measure the particle number concentration

and size distribution of the fireplace.

Continuous flame ionization detector (FID) was installed in two

points as the figure 3.2.3 shows to measure the gaseous hydrocarbon,

such as methane and non methane compounds. One is in the dilution

tunnel, which was used to quantify the amount of hydrocarbon generated

in the fireplace and then to make a correlation with nanoparticles

concentration measured. The other one was equipped after the secondary

diluter for more detailed information about the influence of non methane

hydrocarbons on nanoparticle formation during dilution process.

An analyzer based on catalytic separation of hydrocarbons was

installed in the dilution tunnel, and it will determine the total hydrocarbon

(THC) and methane concentration in the flue gas, then non methane

26

hydrocarbon (NMHC) concentration can be calculated. After the FID first

determined the THC concentration of the flue gas, all the organic

compounds except methane of a portion of flue gas were directly

oxidized in a catalytic converter. Then the FID will detect the methane

concentration in the flue gas. 5 seconds time revolution was used to

measure the THC from 0 to 1000 ppm.

The other FID analyzer separated the hydrocarbons in the sampling

flue gas by the chromatographic columns equipped. The concentrations

are the integral of the chromatograms of the analyzer and the range was

from 0 to 5000 mg mn-3

with a corresponding 180 seconds for response.

3.3 Sampling

In the real world, the total emissions of PM consist both primary particles

that generated in combustion process, and secondary particles of

condensable origin, formed immediately after gas emission at stack due

to cooling by air dilution. In this study, the effects of fumes emitted into

the atmosphere which cooled and diluted by the ambient air were

evaluated. During this process, the secondary UFP and NP could generate

undergoing the nucleation and condensation processes.

The sampling flue gas diluted by cold dilution air with different DR

which named dilution sampling was applied in all these three cases. In

order to assess the amount of primary particles, another sampling method

named hot sampling also adopted when higher temperature maintained.

During hot sampling process, no condensation or only a part of

compounds may have condensed. The comparison between the different

samplings can provide useful information about the behavior of UFP and

UP emissions when flue gas was diluted under different conditions.

3.3.1 Hot sampling

Hot dilution sampling measurements were taken when all parts of

sampling system, included the ELPI, were heated before sampling, and

kept the temperature approximates to the stack gas temperature. It can

minimize the thermophoretic losses and to avoid unwanted nucleation

and condensation of semi volatile species inside the sampling line

27

(Cernuschi et al., 2009).

Hot sampling flue gas was first isokinetically extracted with the

heated probe and passed through the pre-cut cyclone, was diluted in the

first stage of dilution tunnel with heated dilution air, and finally reached

to the ELPI. Only primary particle size distribution and number

concentration can be evaluated by analyzing hot sampling.

3.3.2 Dilution sampling

Different dilution ratios (DR) were applied in order to investigate the

effects of dilution conditions on particle behavior of samples. The

dilution ratios can be divided into three ranges, low dilution, medium

dilution and high dilution.

The difference from hot sampling is that there is no need for diluted

sampling to heat all the sampling system, which dilution conducted with

preconditioned air at actual ambient temperature. This kind of sampling

evaluated not only the primary particles but also the condensable raction.

4. Results

Particle number concentration and size distribution were evaluated for all

the three different boilers investigated. Several statistical parameters were

utilized for analyzing particle number concentrations and size

distributions, such as the average, median, maximum, minimum, and

interquartile range (IOR, range between 25th and 75

th percentile), as well

as the respectively proportions of NP and UFP on total particle number

concentrations. Total number concentration (TN) in this study was

calculated as the sum of 12 stages. Box plots will be used to show the

mean, median, minimum, maxim and the interquartile range (IQR).

Nanoparticles were counted as the sum of first two stages, while ultrafine

particles were counted as the sum of first four stages. Geometric mean

diameter (GMD) and geometric standard deviation (GSD) were utilized

as indicators of particle size distribution.

Besides these, also some gaseous emissions levels such as CO2, CO,

NOX and some other flue gas parameters like flue gas temperature and O2

28

were measured at the same time to track the general characteristics of flue

gases.

The influence of different sampling conditions on NP emissions was

assessed with nonparametric statistic methods, which applied in this study

to analys the median values needed to compare whether they are similar

or not. The Mann-Whitney U test was applied for two independent

samples. It performs a two-sided rank sum test with the hypothesis that

two independent samples come from distributions with equal medians,

and returns the p-value from the test. P-value is the probability of

observing the given result. Small values of p cast doubt on the validity of

the null hypothesis at certain significance level and 5% of significance

adopted in this study. All the data programming and statistic analysis

were conducted using matlab 7.0 and SPSS v.20.

Based on the formation mechanism of particles, there could be

correlations between the amount of condensable organic compounds or

other gaseous species and the number concentration of particle as well as

their size distributions. There are several statistic methods to estimate the

dependence of variables. The commonly used Pearson product-moment

correlation coefficient is a measure of the strength of linear dependence

between two variables, and the estimation will give the r value between

+1 and -1. Another non-parametric test of statistic dependence between

two variables can be estimated by using Spearman’s rank correlation

coefficient. The value of Spearman’s rho reflects the dependence and it

ranges from +1 to -1. And when the each of the variable is a perfect

monotone function of the other the absolute value of rho is 1, while the

value of 0 means that the two variables are independent from each other.

The detailed results of each investigated combustion system are

described case by case in the following paragraphs.

4.1 Woody biomass power plant

11 tests were carried out during continuous operation at design conditions

of the biomass power plant. The durations of tests were from 2 to 14

hours, and the time interval of each particle number counting record is 1

minute.

The hot samplings as well as the dilution samplings which were

29

applied with different dilution ratio (DR) were measured. The dilution

procedure was regulated automatically: the system dilution air flow was

adjusted to achieve dilution ratios ranging from low to medium (15-40),

with the corresponding residence times in the chamber were from 2 to

0.5s. Temperature and relative humidity sensors were applied to control

the required sampling conditions. All the dilution samplings were

grouped into low dilution samplings (DR=10-20) and medium dilution

samplings (DR=20-40). Characteristics of PM in ambient air were also

measured as reference.

4.1.1 Particle number concentration and size distribution

All the data of PM was normalized to normal temperature and pressure

(NTP) condition (P=1 atm, T= 273K) and dry basis. The reference

volumetric oxygen contents O2 ref is 11%_vol. Particle number

concentrations and the main statistical parameters of corresponding size

distributions under different sampling conditions are listed in Table

4.1.1.1.

sampling

condition TN (cm

-3) Rang(cm

-3) NP (%) UFP (%)

GMD

(nm) GSD

Hot sampling 9.8×105±4.2×10

5 1.7×10

5-2.7×10

6 85.2% 99.1% 29.8 1.7

Low dilution 2.3×106±7.8×10

5 5.3×10

5- 5.1×10

6 92.5% 99.6% 26.5 1.5

Medium dilution 8.8×105±4.0×10

5 1.2×10

5-2.7×10

6 90.7% 99.5% 27.3 1.6

Ambient air 2.0×104±1.2×10

4 4.7×10

3-5.9×10

4 85.0% 97.3% 29.4 1.8

Table 4.1.1.1 Number concentration measurement results under different

sampling conditions. (TN: average number concentration ± standard

deviation; range: minimum – maximum; NP: cumulative fraction of

nanoparticles; UFP: cumulative fraction of ultrafine particles; GMD:

geometric mean diameter; GSD: geometric standard deviation).

Measurement results showed during hot sampling presented the

average TN values around 9.8×105 cm

-3 with standard deviation around

4.2×105 cm

-3. NP accounted for 85.2% while the UFP accounted for

99.1%. Sampling at the lower dilutions (DR=10-20) presented average

values of TN around 2.3×106 cm

-3 with standard deviation around

30

7.8×105 cm

-3. NP accounted for 92.5% while the UFP accounted for

99.6%. Sampling at medium dilutions (DR=20-40) presented average TN

values around 8.8×105 cm

-3 with standard deviation around 4.0×10

5 cm

-3.

NP accounted for 90.7% while the UFP accounted for 99.5%. Ambient air

condition measurement presented average TN values around 2.0×104 cm

-3

with standard deviation around 1.2×104 cm

-3. NP accounted for 85.0%

while the UFP accounted for 97.3%. The results suggest that the

statistical parameters of all the samplings, TN, NP and UFP

concentrations were at least one order of magnitude larger than the

corresponding concentrations at ambient air conditions.

The TN concentration of low dilution sampling was almost 3 times

of hot sampling. As figure 4.1.1.1 shows, the difference of UPF fractions

between the two samplings was not so big, because both of them were

larger than 99% and close to 100%. But difference of NP fractions

between the two samplings was obvious, the NP fraction increased from

85.2% to 92.5% due to low dilution condition. The result illustrates the

fact that when the flue gas diluted with cold ambient air by a low dilution

ratio, new particles formed in the dilution process. In the dilution process

of the flue gas, a decreased saturation ratio of semi volatile organic

species (such as semi volatile Polycyclic Aromatic Hydrocarbons

occurred in wood combustion) may cause the new particle formation by

homogeneous and heterogeneous condensation.

Figure 4.1.1.1 Number concentration fractions of NP and UFP under

different sampling conditions.

When flue gas diluted with increased DR, the medium dilution

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

100%

Hot sampling Low dilution Medium dilution

Ambient air

NP (%)

UFP (%)

31

sampling was obtained. The fractions of UFP and NP under medium

dilution condition decreased slightly when it was compared with low

dilution sampling. But they were still bigger than the respective fractions

of hot sampling. This result suggests that when further dilution was

applied, the partial pressure of semi volatile species decreased with the

increasing dilution ratio, and the newly formed particles reduction was

due to the changes of particle formation mechanisms. A corresponding

reduction of TN concentration occurred under medium dilution, which is

shown in figure 4.1.1.2.

Figure 4.1.1.2 TN concentration (cm-3) of particles under different

dilution conditions and in ambient air

The GMD of low dilution sampling was 26.5 nm with the

corresponding GSD around 1.5, and GMD of medium dilution was 27.3

nm with the GSD around 1.6. The hot sampling has a slightly bigger

GMD around 29.8 nm, and the corresponding GSD was 1.7. The GMD

decreased from 29.8 nm to 26.5 nm due to the finer particles formed

under cold dilutions. But GMDs of all the samplings including hot

sampling and dilution sampling which was diluted at different DRs, were

located in the NP range, and the UFP fractions accounted for more than

99% of the TN concentrations. The NP behavior was associated with the

2.0E+04

9.8E+05

2.3E+06

8.8E+05

1.00E+03

1.00E+04

1.00E+05

1.00E+06

1.00E+07

ambient air hot sampling low dilution medium dilution

TN c

on

trti

on

(cm

-3)

□IQR -maximum -●-average --median -minimum

32

TN concentration and the size distribution of the samplings.

Mann-Whitney U tests were applied to investigate the statistical

significance of the variation in NP number concentrations under the

different three sampling conditions. The results are reported in Table

4.1.1.2, showing that low dilution sampling has a significant statistic

differences from hot sampling and medium sampling (the p-value <

0.001). But the test between hot sampling and medium dilution gave a

p-value bigger than 0.05， suggesting that there is no statistically

significant difference of NP number concentration under both sampling

conditions.

Test samplings Mann-Whitney U p-value

Hot sampling-Low dilution 22826 <0.001

Low dilution-Medium dilution 23990 <0.001

Hot sampling-Medium dilution 89200 0.07

Table 4.1.1.2 Results of Mann-Whitney U tests on NP concentration

The median diameter is one of an important parameter characterizing

particle size, and it is the value of the particle diameter at 50% in the

cumulative distribution. In this study, the median value is chosen to

represent the particle size of group particles in the same size range. The

median particle number size distribution dN/Ddp (cm-3

nm-1

) of different

sampling conditions is plotted in Figure 4.1.1.3.

The figure suggests that there were not significant changes of the size

distributions among all the samplings. The peak of particle number

concentrations of all the samplings located in the range from 7 nm to 20

nm, but the low dilution sampling had a higher emission of the peak

range. Generally speaking, the influences of dilution conditions on

particle size distributions are not so significant.

33

Figure 4.1.1.3 Particle number size distributions under different

samplings

4.1.2 Gaseous emissions and correlation with NP

The regulated pollutants concentrations of the flue gas, such as HCl, CO,

NOX, NH3, SO2, total organic carbon (TOC) and total suspended particles

(TSP), were measured by the equipped continuous emission monitoring

system (CEMS) in the power plant. Other relevant operation parameters

such as oxygen content, relative humidity, temperature, pressure and flue

gas flow rate were also measured at the same time. The average value and

the corresponding standard deviation of the parameters, which obtained

under different dilution conditions, are reported in table 4.1.2.1. And all

the data was normalized to NTP condition and the reference oxygen

content was 11%_vol.

34

parameter Low dilution Medium dilution Hot sampling

mean±std.dev mean±std.dev mean±std.dev

HCL (mg mn-3

) 0.36±0.05 0.36±0.06 0.35±0.03

CO (mg mn-3

) 85±45 83±33 94±30

NO2 (mg mn-3

) 104±9 103±7 100±9

SO2 (mg mn-3

) 0.60±0.06 0.59±0.02 0.60±0.04

NH3 (mg mn-3

) 0.17±0.16 0.08±0.07 0.09±0.08

CO2 (% volum) 9.4±0.3 9.6±0.3 9.4±0.5

HF (mg mn-3

) 0.06±0.01 0.06 0.06

TOC (mg mn-3

) 0.93±0.01 0.76±0.55 0.69±0.44

TSP (mg mn-3

) 0.03 0.03 0.03

O2 (% volum) 11.3±0.4 11.1±0.3 11.3±0.47

H2O (% volum) 15.2±0.6 15.6±0.6 15.0±0.8

Tflue (°C) 131±0.7 133±0.6 134±0.8

Table 4.1.2.1 Average flue gas composition of flue gas (mean±standard

deviation at 273K, 1atm, 11% O2)

There is almost no flue gas species that seemed to have significantly

statistical correlation with NP and UFP emissions by calculating statistical

Spearman’s rho with different species. The nucleation of particle

formation may cause by the presence of SO3, which could form sulfuric

acid with water vapor in the flue gas. Nucleated particles occurred during

the dilution process may due to the condensation of H2SO4.

It is hard to analyze the correlation because of the stable values of the

gaseous emissions and other parameters monitored during sampling,

essentially arising from proper operation, good combustion and very

effective FGCS of the power plant.

4.2 Advanced wood pellet boiler

37 tests of the pellet boiler were carried out in the laboratory from May

2007 to March 2008. In order to investigate the effects of dilution ratios

on particle characteristics, dilution samplings which was applied with low

dilution ratio (DR=15-20), medium dilution ratio (DR=20-35) and high

dilution ratio (DR=35-50) were investigated together with hot sampling.

Another factor evaluated in this study, which could also influence the

35

characteristics of PM, is the operation method. In this study, two

operation methods were performed. Under nominal condition, the boiler

was working at design conditions with a 100% thermal output and

optimization fuel/air ratio. When reduced load condition was applied, the

boiler only had a 30% thermal load output. The boiler had an

automatically fuel feeding and control system. And it allowed a proper

reduction of combustion air supply according to the reduction of fuel

supply when the load was reduced.

4.2.1 Particle number concentration and size distribution

All the data of PM was normalized to NTP condition and dry basis. The

reference volumetric oxygen contents O2 ref is 10%_vol. Particle number

concentrations and the main statistical parameters of corresponding size

distributions under different sampling conditions and different operation

methods are summarized in Table 4.2.1.1.

Load

(%)

sampling

condition TN (cm

-3) Range(cm

-3) NP (%) UFP (%)

GMD

(nm) GSD

100%

Low

dilution 6.8×10

7±2.2×10

7 4.2×10

6-

8.4×10

8 17.4% 92.6% 81.8 1.7

Medium

dilution 6.6×10

7±1.7×10

7 6.3×10

5-2.20×10

8 19.4% 92.3% 80.2 1.7

High

dilution 7.8×10

7±1.4×10

7 3.3×10

7-1.5×10

8 27.4% 95.5% 69.2 1.8

30% Medium

dilution 3.6×10

7±1.2×10

7 2.3×10

7-2.7×10

8 0.4% 41.0% 175.4 1.6

Table 4.2.1.1 Number concentration measurement results under different

sampling conditions and loads. (TN: average number concentration ±

standard deviation; range: minimum – maximum; NP: cumulative

fraction of nanoparticles; UFP: cumulative fraction of ultrafine particles;

GMD: geometric mean diameter; GSD: geometric standard deviation).

It turned out that the particle number concentrations of hot sampling

without further dilution were too high and the values exceeded the

detection limits of ELPI. When the boiler operated at nominal condition,

36

sampling at low dilutions (DR=15-20) presented average values of TN

around 6.8×107 cm

-3 with standard deviation around 2.2×10

7 cm

-3. NP

accounted for 17.4% while the UFP accounted for 92.6%. Sampling at

medium dilutions (DR=20-35) presented average values of TN around

6.6×107 cm

-3 with standard deviation around 1.7×10

7 cm

-3. NP accounted

for 19.4% while the UFP accounted for 92.3%. Sampling at high dilutions

(DR=35-50) presented the average values of TN around 7.8×107 cm

-3

with standard deviation around 1.4×107

cm-3

. NP accounted for 27.4%

while the UFP accounted for 95.5%. While the boiler operated at non

nominal conditions, the medium dilution sampling (DR=30)

measurement presented the average values of TN around 3.6×107 cm

-3

with standard deviation around 2.3×107 cm

-3. NP accounted for 0.4%

while the UFP accounted for 41.0%.

The results suggested, also as figure 4.2.1.1 shows, when boiler

operated at nominal condition, variation of dilution ratio did not influence

the TN concentrations because they were in the same order and not

significantly different from each other (TN average concentrations from

6.6×107 to 7.8×10

7 cm

-3). But the fractions of NP increased from 17.4%

(low dilution) to 27.4% (high dilution). And the UFP fractions just

slightly increased from 92.3% to 95.5% with an increasing dilution ratio

from 15 to 50. The increased TN was mainly due to the contribution of

NP fraction.

The GMDs of nominal operated samplings decreased from 81.2 to

69.2 nm with an increasing dilution ratio applied. The dilution sampling

with higher dilution ratio seemed to emit finer particles. This result

suggested that the saturation vapor pressure of semi volatile (semi volatile

PAHs) species in the flue decreased with the increasing dilution ratio as

well as the decreasing temperature. The newly formed particles were due

to the homogeneous and heterogeneous condensation of semi volatile

species.

37

Figure 4.2.1.1 Fractions of NP and UFP of number concentration under

different sampling conditions and operation methods.

It is clear that the percentages of UFP and NP of partial load sampling

were much lower when compared with cold dilution samplings, since the

NP fraction almost 0 and that of UFP was just 41%. The figure 4.2.1.2

didn’t show significant differences between TN concentrations of the two

medium dilution samplings under different operation conditions. When

the load reduced, the control system will reduce the fuel and combustion

air supply automatically. The changing of fuel and combustion air supply

will finally lead to a worse combustion and coarser particles formation.

The presence of the significant amount of coarser particles makes it

possible for the further condensation and agglomeration of semi volatile

species on the existed surfaces of the coarser particles. And the

condensation of species on existed surfaces is favored than their

homogeneous condensation to form new particles.

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0%

100.0%

Low dilution

Medium dilution

High dilution

Medium dilution

nominal non nominal

NP (%)

UFP (%)

38

Figure 4.2.1.2 TN concentration (cm-3

) of particles under different

dilution conditions and different operation methods

The main number concentrations differences between the samplings

were caused by NP fractions. Mann-Whitney U tests were applied to

investigate the statistical significance of the variation in NP number

concentrations under the different three sampling conditions which

sampled at nominal conditions. Samplings under non nominal operation

were diluted at medium dilution ratio. The results are shown in Table

4.2.1.2, suggesting that all samplings had significant statistic differences

from each other (all p-values <0.001). Although the dilution ratio didn’t

influence the TN concentrations so much, it did influence the NP

emissions significantly when sampled at nominal condition. NP

concentration of the medium sampling under full load was significantly

different from that of medium sampling under non nominal operation

from the statistic point of view. The reduced medium sampling had a

much larger GMD around 175.4 nm when compared with other sampling,

and with the corresponding GSD was 1.6. It was seemed that the pellet

boiler operated at non nominal condition will emit coarser particles as

stated before. The operation conditions do have influence on NP and UFP

fractions of PM number concentrations.

6.8E+07

6.6E+07 7.8E+07

3.5E+07

1.00E+05

1.00E+06

1.00E+07

1.00E+08

1.00E+09

TN c

on

trti

on

(cm

-3)

-maximum □IQR -●-average ---median -minimum

39

Load (%) dilution ratio Mann-Whitney U p-value

100%-100% Low dilution-Medium dilution 5.7×108 <0.001

100%-100% Low dilution-High dilution 5.7×107 <0.001

100%-100% Medium dilution-High dilution 1.7×107 <0.001

100%-30% Medium dilution-Medium dilution 4560 <0.001

Table 4.2.1.2 Results of Mann-Whitney U tests on NP concentration

The median particle size distribution dN/Ddp (cm-3

nm-1

) of different

sampling conditions was unimodal as Figure 4.2.1.3 showing. The figure

suggests there are no significant changes of the size distributions among

full load samplings under different dilution ratios, and the peaks all

located in the same UFP size range. But when dilution ratio increased, the

finer particles accounted more. Generally speaking, the influences of

dilution conditions on particle size distributions were not so significant.

However, we can find the shapes of particle size distribution changed

when the operation conditions changed. The main fraction of particles

shifted to coarser size range and it was bigger than 100 nm and was out of

UFP size range.

Figure 4.2.1.3 Particle size distributions under different samplings

40

4.2.2 Gaseous emissions and correlation with NP

The corresponding gaseous emissions parameters CO, NOX, SO2, CH4,

the non methane hydrocarbon (NMHC) and other relevant operation

parameters were measured as well during pellet boiler operation time.

The average gaseous emissions of pellet boiler under different

operation conditions were investigated, and the main parameters are

reported in table 4.2.2.1 at NTP condition, dry basis with the O2 ref

11%_vol.

Load (%) CO (ppm) NOX (ppm) SO2 (ppm) CH4

(mgC/Nm-3

)

NMHC

(mgC/Nm-3

) O2 (%v)

30% 58.1± 72.5 84.0±3.5 5.5±1.2 0.20±0.16 3.77±0.52 5.9±0.5

100% 16.3±59.0 50.0±4.2 6.9±0.7 0.10±0.06 3.75±0.38 8.2±2.2

Table 4.2.2.1 gaseous emissions (average value ± standard deviation)

under different operation methods

Measurement of the CO concentration of reduced load sampling is

around 58 ppm almost 3 fold for nominal operation samplings. It also

pointed out the combustion under reduced load operation is incomplete as

CO is an indicator of combustion condition.

Spearman’s rank correlation applied to calculate the dependence

between the number concentration of NP and gaseous emissions (CH4,

NMHC, NOx, SO2). The data of CH4 and NMHC recorded every 3

minutes, while the other gaseous parameter recorded every 6 seconds.

The statistic correlation analysis was applied to all the gaseous

parameters but no very significant correlation was found. Only SO2 and

NOX were shown to have very weak correlations with NP formation.

41

Data of test Parameter correlated with NP Spearman's rho p

19/09/2007 NOx -0.135 < 0.001

SO2 0.141 < 0.001

11/07/2007 NOx -0.097 0.057

SO2 0.176 < 0.001

16/07/2007 NOx -0.218 < 0.001

SO2 0.146 < 0.001

28/05/2007 NOx -0.298 < 0.001

SO2 0.341 < 0.001

Table 4.2.2.2 The results of Spearman correlation between NOx and NP ,

SO2 and NP.

The calculation results of spearman’s rho between NOx and NP, SO2

and NP are listed in table 4.2.2.2, respectively. SO2 is correlated

positively with NP formation while NOx correlated with NP formation

negatively. The very weak correlation of the results suggested that the

SO2 and NOx may not directly participate in the formation of NP

emissions during dilution process. The main reason caused the increased

NP fraction was the homogeneous and heterogeneous condensations of

semi volatile species.

4.3 Modern closed fireplace

Tests of fireplace performed lasted from 38 to 51 minutes within 2.5 kg/

batch for the fireplace. The fuel used was beech wood, which is widely

used in Italy. The average size of logs used in the experiments was 8 cm

in diameter and 49 cm in length.

The sampling flue gas first diluted in the dilution tunnel with an

average dilution ratio around 6. In order to investigate the influence of

dilution condition on particles formation, “hot dilution sampling” and

“cold dilution sampling” were applied in the tests. Hot dilution sampling

means the sampling diluted at the actual stack temperature in the first

stage dilution tunnel to reduce the possibility of condensation. And the

“cold dilution sampling” was further diluted by ambient air and achieved

the ambient temperature finally. All the samplings were diluted at an

average dilution ratio of 15.

42

However, for small scale combustion applications (fireplace and

wood stove), the combustion conditions such as temperature and fuel/air

ratio vary within each cycle. This leads to variations in performance of

fireplace and emission characteristics. Moreover, the emissions are not

only varied cycle by cycle but also changed in one cycle. The products of

combustion may vary a lot since the existing of different combustion

phases. Generally we can indentify three different phases during batch

combustion applications, initial start-up phase, intermediate (main) phase,

and burn-out (final) phase (Figure 4.3.1). The identification is based on

the combustion conditions, which can be indicated by the flue gas

parameters such as concentration of CO, organic carbon (OGC), flue gas

temperature and oxygen content (Ozgen et al., 2013).

Figure 4.3.1 Pictures of different combustion phases

4.3.1 Particle number concentration and size distribution

All the data of PM and gaseous species is normalized to NTP condition

and dry basis. The reference volumetric oxygen contents O2 ref is 13%_vol.

Data of PM recorded one time per second continually. Statistic

parameters of particle number corresponding size distributions under

different sampling conditions are summarized in Table 4.3.1.1.

sampling

condition TN (cm

-3) Rang(cm

-3) NP (%) UFP (%)

GMD

(nm) GSD

cold dilution 2.8×108±7.2×10

8 6.8×10

6-1.2×10

10 59.2% 74.6% 55.7 1.6

hot dilution 3.0×108±9.6×10

8 3.4×10

6-4.0×10

10 51.2% 86.6% 60.0 1.5

Figure 4.3.1.1 Number concentration measurement results under

different sampling conditions (TN: average number concentration ±

standard deviation; range: minimum – maximum; NP: cumulative

43

fraction of nanoparticles; UFP: cumulative fraction of ultrafine particles;

GMD: geometric mean diameter; GSD: geometric standard deviation).

The results of hot dilution sampling presented the average values of

TN around 2.8×108 cm

-3 with standard deviation around 7.2×10

8 cm

-3. NP

accounted for 59.2% while the UFP accounted for 74.6%. The cold

dilution sampling presented the average value of TN around 3.0×108 cm

-3

with standard deviation around 9.6×108 cm

-3. NP accounted for 51.2%

while the UFP accounted for 86.6%.

Mann-Whitney U tests were applied to investigate the statistical

significance of the variation in NP number concentrations caused by

dilution condition. The calculation results suggested that the statistical

difference between fractions of NP is not significant (Mann-Whitney U=

18, p-value=0.289). When the flue gas first diluted preliminary in the

dilution channel, the sampling was already cooled and gas-particle

conversion took place. After enough residence time, the new formed

particles stabilized in the flue gas, and there is a limitation for nucleation

or condensation of volatile organic species in further dilution.

The median particle size distribution dN/dDp (cm-3

nm-1

) was studied

of the two different samplings. The figure 4.3.1.1 showing that there was

not significant size distribution between these two different types of

samplings. The dominant size range of total particles was located in the

first nanoparticle size range. The GMD of hot sampling was 60.0 nm

while the GMD of cold sampling decreased to 55.7 nm. The cold

sampling emitted finer particles than hot sampling.

Figure 4.3.1.2 Normalized median size distribution of different samplings

44

The detailed information of TN concentrations and NP and UFP

fractions varied phase by phase were reported in table 4.3.1.2. The TN

concentrations of initial, main, and final phase at hot dilution conditions

presented the average values around 1.1×109 cm

-3, 1.4×10

8 cm

-3 and

1.9×108 cm

-3, respectively. And the NP fractions accounted 53.7%, 47.5%

and 55.6%, while the respectively UFP fractions accounted 84.1%, 86.5%

and 87.8% from initial to final phase. The initial phase emitted significant

amount of TN due to the contribution of NP fraction. TN concentrations

of initial, main, and final phase were around 3.9×108 cm

-3, 3.3×10

7 cm

-3

and 1.3×108 cm

-3, respectively. The respectively NP fractions were 54.8%,

37.1% and 77.1%, while the UFP accounted for 71.7%, 59.8% and 87.8%.

The results suggested that TN concentrations, NP and UFP fractions

increased significantly in initial and final phase.

sampling

condition

cold sampling hot sampling

initial phase main phase final phase initial phase main phase final phase

TN (cm-3

) 3.9×108 3.3×10

7 1.3×10

8 1.1×10

9 1.4×10

8 1.9×10

8

NP% 54.8% 37.1% 77.1% 53.7% 47.5% 55.6%

UFP% 71.7% 59.8% 87.8% 84.1% 86.5% 87.8%

GMD (nm) 59.5 69.1 44.5 57.7 70.7 45.4

Table 4.3.1.2 TN (average value), fractions of NP and UFP, and GMD in

different phases of different samplings

NP number concentrations varied with the changing of combustion

conditions phase to phase significantly. Mann-Whitney U tests were

applied to investigate the variations and the calculation results shows in

table 4.3.1.2. As the results shows, there was significant statistic

difference between NP concentrations of different phases at cold

sampling conditions. And for hot sampling, the NP concentration of

initial phase was significant different from main phase and final phase,

while that of main phase and final phase was not so significant different

as Figure 4.3.1.3 shows.

45

sampling phase Mann-Whitney U p-value

hot sampling

initial-main 9.1×107 <0.001

initial-final 6.4×106 <0.001

main-final 2.6×107 0.145

cold sampling

initial-main 2.1×107 <0.001

initial-final 2.7×107 <0.001

main-final 5.2×107 <0.001

Table 4.3.1.3 Results of Mann-Whitney U tests on NP concentration

Figure 4.3.1.3 Box plots of different combustion phases of cold and hot

samplings of NP concentration

The median size distribution dN/dDp in different phases of cold

sampling was different and are shown in figure 4.3.1.4. All the peaks of

number concentrations were located in the first nanoparticle size range,

and more nanoparticles emitted in initial and final phase. The GMD of

initial phase was 59.5 nm, which increased to 69.1 nm in main phase, and

decreased to 44.5 nm in final phase. The results suggested that finer

particles formed in initial and final phase during cold diluting.

46

Figure 4.3.1.4 Median size distribution dN/dDp in different phases of

cold sampling

4.3.2 Gaseous emissions and correlation with NP

The values of regulated flue gas parameters such as CO2, CH4, CO,

NMHC and dust were measured in real time with the time resolution 5

seconds. All the data was normalized to NTP condition in dry basis, and

the reference oxygen content is 11%_vol. Other relevant operation

parameters measured such as O2, ambient air temperature (Tamb), exhaust

gas temperature (Texh gas) and dilution tunnel temperature (Ttunnel) in actual

conditions were measured as well and are reported in table 4.3.2.1.

The two FID analyzers used in the experiments give different results

of hydrocarbon concentrations because of different technology applied.

After comparison of two groups of data, the catalytic analyzer equipped

in the dilution tunnel was selected in this study.

47

parameter Cold sampling Hot sampling

CO2 (%v) 7.2±0.3 7.1±0.4

CH4 160.2±166.4 166.6±186.7

CO (mg mn-3

) 3767.4±2355.8 4035.0±2725.7

NMHC (mg mn-3

) 478.2±537.9 513.1±623.7

Dust (mg mn-3

) 141.4±267.0 152.7±400.0

O2 (%v) 14.7±2.9 14.3±3.4

Tamb (oC) 14.6±1.1 14.9±1.6

Texh gas(oC) 239.1±40.0 240.8±44.0

Ttunnel (oC) 67.0±11.4 65.9±14.8

Table 4.3.2.1 Flue gas pollutant concentrations and characteristics

measured during particle sampling tests (average value ± standard

deviation)

The results show that parameters such as CO, CH4, THC, NMHC and

dust varied with the operation time changing or cycle by cycle. They are

indicators of combustion condition which changing with different

combustion phases (Table 4.3.2.2). The average NMHC concentration

measured by the catalytic analyzer for cold sampling is 653.3 mg mn-3

,

and 457.2， 604.9 mg mn-3

for initial, main and final phases, respectively.

It seems that, the NMHC concentrations were higher during initial and

final phases due to the incomplete combustion. In initial phase, the

increasing temperature associated with the decreasing O2 concentration.

The cold start and excess O2 of fireplace will lead the peak of methane,

NMHC and PM emissions. In final phase, the charcoal burnout took place,

with the decreasing of O2 concentration and temperature, there were

increasing of methane, NMHC and PM emissions again. Incomplete

combustion produced some volatile organic carbons later underwent a

homogeneous condensation and formation of nanoparticles and ultrafine

particles during cold diluting.

48

sampling cold sampling hot sampling

parameter initial phase main phase final phase initial phase main phase final phase

CH4 (mg mn-3

) 167.3 155.8 196.6 155.6 102.7 249.2

CO (mg mn-3

) 4394.3 3159.6 5688.1 4910.0 2677.9 4899.6

THC (mg mn-3

) 816.2 605.1 800.4 919.4 425.3 833.7

NMHC (mg mn-3

) 653.3 457.2 604.9 769.9 322.6 584.5

DUST (mg mn-3

) 409.9 100.8 173.5 362.8 46.3 189.0

Table 4.3.2.2 Average values of emission parameters in different phases.

A typical cold dilution sampling test was selected when the

concentration of NP number and NMHC mass concentration were

showed together in figure 4.3.2.1. Dynamic variations of NP

concentration and NMHC mass concentration can be easily found during

the burning process phase by phase. Both NP and NMHC concentrations

had the same tendency, which increased in initial phase then decreased

and became relative stable in main phase, at final phase increased again.

It proved that, the combustion characteristics will significantly influence

the characters of PM.

Figure 4.3.2.2 NMHC mass concentration, NP number concentration

change with operation time

0.0E+00

1.0E+07

2.0E+07

3.0E+07

4.0E+07

5.0E+07

6.0E+07

7.0E+07

0

200

400

600

800

1000

1200

1400

1600

1800

2000

0 500 1000 1500 2000 2500 3000

NP

co

nce

ntr

atio

n (

cm-3

)

NM

HC

mas

s co

nce

ntr

atio

n (

mg

mn

-3)

Operation time (s)

NMHC

NP

Initial main final

49

Person’s rank correlation was applied to assess the dependence

between the number concentration of NP and corresponding mass

concentration of NMHC. The different levels of dependence among

different size ranges, and it varied phase by phase of the cold sampling

(Figure 4.3.3.3). Among all the phases the coarser particles had the less or

no correlation with NMHC, and finer particles had more correlation with

NMHC, especially NP fractions. There are strong correlations between

NP fraction and NMHC concentration in all the combustion phases

(rho=0.788，p< 0.01).

Figure 4.3.2.3 Person’s rho with different phases

Generally, in initial phase, there will be a peak of NMHC emission as

figure 4.3.2.3 showing, then it goes down in main phase and at last an

increasing again in final phase. The big mass concentration may cause a

bigger saturation ratio of NMHC leads to homogenous and heterogeneous

condensation of NMHC contributes to nanoparticle and ultrafine particle

fractions. In main phase the combustion was complete and stable, more

complete combustion products emitted instead of incomplete products

(NMHC, methane, etc.), then smaller amount of NMHC associated with

the coarser particles. In final phase, emission of NMHC increased again,

finer size particles formed again due to the condensation of NMHC.

Pearson’s rho coefficients suggested that during all the phases, there

were strong correlations between NP and NMHC, UFP and NMHC

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1 10 100 1000 10000

Pea

rso

n's

rh

o

Particle diameter (nm)

initial

main

final

50

respectively (Table 4.3.2.3), and the highest correlations between NP,

UFP and NMHC achieved in final phase. Average GMD of initial phase

was 59.5 nm then increased to 69.1 nm in main phase. GMD of final

phase was 44.5 nm, and the finest size suggesting that homogeneous

condensation process of NMHC released in final phase associated with

the NP formation. Coarser particles emitted in main phase may due to

better combustion conditions and less NMHC emissions. Generally

speaking, secondary particle formation was associated with the emission

of NMHC by both homogeneous and heterogeneous condensations.

Phase Pearson rho_NP Person rho_UFP

cold_initial 0.78 0.77

cold_main 0.68 0.74

cold_final 0.79 0.80

Table 4.3.2.3 Person’s rho of NP and UFP during different phases of cold

sampling

4.4 Comparison of different appliances

Different characteristics of particles emission characters of the three

different typical applications were summarized in table 4.4.1. For large

scale power plant, there could be a significant big faction of NP around

90% and more than 99% of TN was UFP. The average GMD was less

than 30 nm and located in nanoparticle size range. The average TN

concentration measured was in the order around 106.

For pellet boiler, the average TN was in the order around 108, and the

NP fraction was around from 18% to 28% with the increasing dilution

ratio, and the UFP fraction was around 93% when it sampled under

nominal load operation. There was a significant reduction of NP and UFP

fractions when the load of boiler reduced from 100% to 30%. The

average GMD was around 81 nm for nominal load condition and

increased to 175 nm when load reduced to 30%.

The combustion condition of fireplace was not continuous, so the NP

and UFP fractions were changing phase to phase. The average value of

NP fraction was more than 59% and more than 75% was UFP. TN was in

the order of 108, with the average GMD 56 nm.

51

Parameter Power plant pellet boiler fireplace

Thermal power 15 MW 100 kW 11 kW

O2 ref (%v) 11% 10% 13%

TN (cm-3) 10 6 10

7 10

8

NP (%) 91% 18%-28% (nominal)

59% 0.4% (non nominal)

UFP (%) 99% 93% (nominal)

75% 41% (non nominal)

GMD (nm) 27 81 (nominal)

56 175 (non nominal)

Table 4.4.1 Summary of main PM characteristics of the systems

investigated

We can find that the power plant tends to have higher fractions of

UFP and NP than smaller scale applications. And as lack of FGCS, the

emissions of NP and UFP from the small scale applications like the

fireplace investigated in this study could be considerable amount.

5. Conclusions

Three typical wood combustion appliances with different thermal outputs

were investigated in this study. The emissions of PM, which including

primary particles directly emitted from combustion process and

secondary particles due to gas-to-particle conversion when flue gas

released into atmosphere, were assessed in this study. And this study

mainly focused on variations of NP and UFP due to secondary particle

formation mechanisms.

The power plant, which was operated continuously under good

combustion conditions, was equipped with an efficient FGCS (both ESP

and FF) has a lower TN concentration of PM which in the order around

106. The NP fraction accounted around 90% of the TN concentration,

while UFP accounted more than 99% in dilution samplings. The GMDs

of all different sampling were located in the nanoparticle size range. The

52

homogeneous and heterogeneous condensations of semi volatile organic

carbons were associated with dilution ratio and temperature, and further

influenced the NP formations as well as TN concentrations. Some

studies pointed out that the majority of the emitted very fine particles

were attributed to high emissions of inorganic particles and the emissions

strongly depended on the type of FGCS (Nussbaumer et al., 2008; Jorma

et al., 2001).

Tests of the boiler were carried out in laboratory were applied at

different dilution conditions, and the PM emissions of boiler under full

load and partial load operations were investigated as well. The

investigations of different samplings at nominal conditions which were

applied with an increasing dilution ratio from 15 to 50, illustrated a

corresponding increasing of NP emissions and a reduction of GMDs.

When the boiler underwent a load reduction, significantly increasing of

particle size occurred due to the worse combustion. The TN

concentrations of all the samplings were in the order of 107, but under

partial load operation, the emitted NP and UFP were much lower than the

respectively emissions of the full load condition. The analysis results

suggested the saturation vapor pressure of semi volatile (PAHs) species in

the flue decreased with the increasing dilution ratio as well as the

decreasing temperature. The homogeneous and heterogeneous

condensation of semi volatile species during dilution processes could be

the main reason of the increasing NP fractions for samplings which at

nominal conditions. A statistic correlation analysis between NP emission

and other gaseous parameters didn’t give any clue of the directly

association between them. The weakly correlations between NP emission

and NOX, SO2 may suggest that these two gaseous species may indirectly

participate in NP formation.

For fireplace, the emissions changed cycle by cycle due to the

characters of batch combustion appliances, and the average TN

concentration was in the order of 108. Compared with TN concentrations,

there was a significant increasing of NP concentrations when cold

dilution applied for the sampling flue gas. Besides, the combustion

conditions varied phase by phase as well as the corresponding PM

emissions. In initial phase and final phase, NMHC emission increased

due to the low combustion temperature. The good statistical correlation

53

Pearson’s rho coefficients suggests that the homogeneous and

heterogeneous condensation of NMHC contributed to the formation of

NP and UFP fractions. What’s more, the NP emissions of initial phase

were significantly higher than other phases, especially big amount of

emission will occur due to cold start.

There were big variances of PM and other gaseous emissions between

different scales of applications, which due to the applied combustion

techniques, fuel feeding systems, operation principle, flue gas cleaning

systems, fuel quality, etc. The proper primary and secondary measures

should be adopted for the combustion systems.

The main factors which determine PM emissions are the local

emission standards, and the advanced particle removal devices such as

ESP and FF can be effective to move the primary particles. Excessive PM

emissions were found in wood boilers operated without heat storage tank.

Heat storage tank installation could be a useful way to avoid the high PM

emissions due to partial load operation (Nussbaumer et al., 2008). The

advanced control system which could optimize the adjustment of fuel/air

ratio and load demand simultaneously is effective to reduce PM

formation. The emissions of fireplace were significant compared with

larger scale appliances. The performances of initial and final phases of

fireplace should be paid more attention, especially the worst initial phase.

Besides the well designs of combustion chamber and air supply, the

proper training of users is necessary. There is study suggests that ignition

of the wood from the top end instead of the traditional method that

ignition of the wood from the bottom, enable better combustion during

the whole batch (Nussbaumer et al., 2008).

In this study, different dilution ratios were applied to investigate the

very fine secondary particles formation during flue gas plume and

released into atmosphere. However, in real world, the processes of PM

formation, diffusion, transportation and further conversion take place in

the atmosphere, so it is very hard to get more detailed information of the

complex NP and UFP formation processes. And the aged flue gas is

different from newly flue gas on physical properties and chemical

properties. More deep study and advanced measuring technologies are

needed for future study in this field.

Now we already know why we should control finer particles

54

emissions, but how to regulate the emission is still a question. And the

application of effective measurements and methods to reduce the

emissions is a challenge with the growing use of biomass in near future.

Especially, the small scale domestic heating applications are unregular

fed manually and there are fluctuations in combustion process. The

complete combustion should be obtained to reduce the possibilities for

the condensation of the NHMC.

55

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