Queensland University of Technology
School of Physical and Chemical Sciences

Analysis of Dispersion and Propagation of Fine
and Ultra Fine Particle Aerosols from a Busy
Road

Submitted by Galina GRAMOTNEV, School of Physical and Chemical Sciences,
Queensland University of Technology in partial fulfilment of the requirements of the
degree of Doctor of Philosophy

January 2007


Keywords
Combustion aerosols, urban aerosols, outdoor aerosols, background aerosols, nanoparticles, ultra-fine particles, particle formation, aerosol evolution, busy road,
aerosol dispersion, air quality, transport emissions, emission factors, canonical
correlations analysis, multi-variate analysis, degradation processes, turbulent
diffusion, atmospheric monitoring, hydrodynamics, statistical mechanics,
probability, particle deposition.

ii


Statement of original
authorship

The work contained in this Thesis has not been previously submitted for a degree or
diploma at any other higher education institution. To the best of my knowledge and
belief, the Thesis contains no material previously published or written by another
persons except where due reference is made.

Galina Gramotnev

iii


Acknowledgements

I note my appreciation of financial support for this research from the Queensland
University of Technology (QUT), Faculty of Science, School of Physical and
Chemical Sciences, and QUT Office of Research.

I would like to express my sincere gratitude and appreciation to Dr. Richard J.
Brown for very helpful discussions, support, useful directions, and introduction to
the theory of turbulent atmospheric processes. I also thank Mr Pierre Madl and Ms
Maricella Yip for their substantial help and consultations with respect to monitoring
equipment, and all my friends from the International Laboratory for Air Quality and
Health for their support during my PhD studies.
Special thanks go to my husband, Dr Dmitri K. Gramotnev, for the
comprehensive support during my studies and suggested ideas.

iv


Abstract
Nano-particle aerosols are one of the major types of air pollutants in the urban
indoor and outdoor environments. Therefore, determination of mechanisms of
formation, dispersion, evolution, and transformation of combustion aerosols near the
major source of this type of air pollution – busy roads and road networks – is one of
the most essential and urgent goals. This Thesis addresses this particular direction of

research by filling in gaps in the existing physical understanding of aerosol
behaviour and evolution.
The applicability of the Gaussian plume model to combustion aerosols near busy
roads is discussed and used for the numerical analysis of aerosol dispersion. New
methods of determination of emission factors from the average fleet on a road and
from different types of vehicles are developed. Strong and fast evolution processes
in combustion aerosols near busy roads are discovered experimentally, interpreted,
modelled, and statistically analysed.
A new major mechanism of aerosol evolution based on the intensive thermal
fragmentation of nano-particles is proposed, discussed and modelled. A
comprehensive interpretation of mutual transformations of particle modes, a strong
maximum of the total number concentration at an optimal distance from the road,
increase of the proportion of small nano-particles far from the road is suggested.
Modelling of the new mechanism is developed on the basis of the theory of turbulent
diffusion, kinetic equations, and theory of stochastic evaporation/degradation

v


processes.
Several new powerful statistical methods of analysis are developed for
comprehensive data analysis in the presence of strong turbulent mixing and
stochastic fluctuations of environmental factors and parameters. These methods are
based upon the moving average approach, multi-variate and canonical correlation
analyses.

As

a


result,

an

important

new

physical

insight

into

the

relationships/interactions between particle modes, atmospheric parameters and
traffic conditions is presented. In particular, a new definition of particle modes as
groups of particles with similar diameters, characterised by strong mutual
correlations, is introduced. Likely sources of different particle modes near a busy
road are identified and investigated. Strong anti-correlations between some of the
particle modes are discovered and interpreted using the derived fragmentation
theorem.
The results obtained in this thesis will be important for accurate prediction of
aerosol pollution levels in the outdoor and indoor environments, for the reliable
determination of human exposure and impact of transport emissions on the
environment on local and possibly global scales. This work will also be important
for the development of reliable and scientifically-based national and international
standards for nano-particle emissions.


vi


LIST OF AUTHOR PUBLICATIONS

1. Refereed journal papers
[A1]. Gramotnev, G., Brown, R., Ristovski, Z, Hitchins, J., Morawska, L. 2003.
Determination of emission factors for vehicles on a busy road. Atmospheric
Environment, 37, pp. 465-474 (Number 13 out of 25 most downloaded papers in
2004).
[A2]. Gramotnev, G., Ristovski Z., Brown, R., Madl, P. 2004. New methods of
determination of emission factors for two groups of vehicles on a busy road,
Atmospheric Environment, vol.38, pp.2607-2610.
[A3]. Gramotnev, G., Ristovski, Z. 2004. Experimental investigation of ultra fine
particle size distribution near a busy road, Atmospheric Environment, vol.38,
pp.1767-1776.
[A4]. Gramotnev, D.K., Gramotnev, G. 2005. A new mechanism of aerosol
evolution near a busy road: fragmentation of nano-particles, Journal of Aerosol
Science, vol.36, pp.323-340. (Number 9 out of 25 most downloaded papers in 2005).
[A5]. Gramotnev, D.K., Gramotnev, G. 2005. Modelling of aerosol dispersion from
a busy road in the presence of nanoparticle fragmentation, Journal of Applied
Meteorology, vol.44, pp.888–899.
[A6]. Gramotnev, G., Gramotnev, D.K. Multi-channel statistical analysis of
combustion aerosols. Part I: Canonical correlations and sources of particle modes
Atmospheric Environment (accepted 9 January 2007).
[A7]. Gramotnev, D.K., Gramotnev, G. Multi-channel statistical analysis of
combustion aerosols. Part II: Anti-correlations of particle modes and fragmentation
theorem. Atmospheric Environment (accepted 9 January 2007).
[A8]. Gramotnev, D.K., Gramotnev, G. Kinetics of stochastic degradation /


vii


evaporation processes in polymer-like systems with multiple bonds, J. Appl. Phys.
(submitted).
[A9]. Gramotnev, D. K., Mason, D. R., Gramotnev, G., Rasmussen A. J. Thermal
tweezers for surface manipulation with nano-scale resolution. Appl. Phys. Lett.
(accepted 2 January 2007).
[A10]. Gramotnev, G., Madl, P., Gramotnev, D. K., Urban background aerosols:
Anti-correlations of particle modes and fragmentation mechanism. Geophysical
Research Letters (submitted).

2. Full-length refereed conference papers
[A11]. Gramotnev, G., Brown, R., Ristovski, Z., Hitchins, J., Morawska, L. 2002.
Estimation of fine particles emission factors for vehicles on a road using Caline4
program. Proceedings of 4th Queensland Environmental Conference, Brisbane,
Australia, 30 & 31 May 2002, pp. 43-48.
[A12]. Gramotnev, G., Ristovski, Z., Brown, R., Morawska, L, Jamriska, M.,
Agranovski, V. 2003. A new method for obtaining fine particles emission factors
with validation from measurements near a busy road in Brisbane. Proceedings of
National Environmental Conference, Brisbane, Australia, 18 & 20 June 2003, pp.
206-211.

3. Conference papers in refereed journals
[A13]. Gramotnev, G., Ristovski, Z., Brown, R., Morawska, L., Madl, P. 2003.
New method of determination of emission factors for different types of vehicles on a
busy road. Journal of Aerosol Science, EAC 2003, vol.34s, S259-S260.
[A14]. Gramotnev, G., Ristovski, Z. 2003. Nanoparticles near a busy road:
experimental observation of the effect of formation of a new mode of particles.
Journal of Aerosol Science, EAC 2003, vol.34s, S255-S256.


viii


[A15]. Gramotnev, G., Ristovski, Z. and Gramotnev, A. 2003. Dependence of
concentration of nanoparticles near a busy road on meteorological parameters:
canonical correlation analysis. Journal of Aerosol Science, EAC 2003, vol.34s,
S257-S258.
[A16]. Gramotnev, G., Ristovski, Z., Morawska, L., Thomas, S. 2003. Statistical
analysis of correlations between air pollution in the city area and temperature and
humidity. Journal of Aerosol Science, EAC 2003, vol.34s, S715-S716.
[A17]. Gramotnev, G. 2004. Determination of the average emission factors for
three different types of vehicles on a busy road. Journal of Aerosol Science, EAC
2004, vol.35, S1089-S1090.
[A18]. Gramotnev, D.K., Gramotnev, G. 2004. A new mechanism of aerosol
evolution near a busy road: fragmentation of nanoparticles. Journal of Aerosol
Science, EAC 2004, vol.35, S221-S222.
[A19]. Gramotnev, D.K., Gramotnev, G. 2004. Modelling of aerosol dispersion
from a busy road in the presence of nano-particle fragmentation. Journal of Aerosol
Science, EAC 2004, vol.35, S925-S926.

4. Other conference publications
[A20]. Gramotnev, G., Brown, R., Ristovski, Z, Hitchins, J., Morawska, L. 2002.
Dispersion of fine and ultra fine particles from busy road: the comparison of
experimental and theoretical results, in Chiu-Sen Wang (Ed) Proc. of Sixth
International Aerosol Conference, Taipei, Taiwan (September 9 – 13, 2002), pp.
839-840.
[A21]. Gramotnev, G., Thomas, S., Morawska, L., Ristovski, Z. 2002. Canonical
correlation analysis of fine particle and gaseous pollution in the city area, in ChiuSen Wang (Ed) Proc. of Sixth International Aerosol Conference, Taipei, Taiwan
(September 9 – 13, 2002), pp. 873-874.

[A22]. Gramotnev, D.K., Gramotnev, G. 2004. Fragmentation of nanoparticles near

ix


a busy road: Justification and modelling. Proceedings of 8th International
Conference on Carbonaceous Particles in the Atmosphere, Vienna, Austria, 14-16
September 2004, H3.
[A23]. Gramotnev, G., Gramotnev, D.K. 2004. New statistical method of
determination of particle modes in the presence of strong turbulent mixing.
Proceedings of 8th International Conference on Carbonaceous Particles in the
Atmosphere, Vienna, Austria, 14-16 September 2004, H4.
[A24]. Gramotnev, G., Gramotnev, D. K. 2005. Theoretical analysis of multiple
thermal fragmentation of aerosol nanoparticles from a line source: Evolution of
particle modes. Biannual AIP Congress, Canberra, Australia, February, 2005, p.210.
[A25]. Gramotnev, G., Gramotnev, D. K. 2005. Numerical and experimental
investigation of thermal fragmentation of aerosol nano-particles from vehicle
exhaust. Biannual AIP Congress, Canberra, Australia, February, 2005, p.210.
[A26]. Gramotnev, D. K., Gramotnev, G. 2005. Combustion nano-particle aerosols:
Mechanisms of evolution and modelling, Aerosol Workshop, 30 March – 1 April
2005, Sydney, Australia (invited talk).
[A27]. Gramotnev, D. K., Gramotnev, G. 2005. Time delays during multiple
thermal fragmentation of nanoparticles: evolution of particle modes. European
Aerosol Conference (EAC 2005), Ghent, Belgium, p. 690.
[A28]. Gramotnev, G., Madl, P. 2005. Multi-channel statistical analysis of
background fine particle aerosols, European Aerosol Conference (EAC 2005),
Ghent, Belgium, p. 697.
[A29]. Gramotnev, D. K., Bostrom, T. E., Devine, N., Gramotnev, G. 2005.
Experimental investigation of deposition of aerosol particles near a busy road.
European Aerosol Conference (EAC 2005), Ghent, Belgium, p. 696.

[A30]. Mason, D.R., Gramotnev, D.K., Rasmussen, A., Gramotnev, G. 2005.
Feasibility of thermal tweezers for effective manipulation of nano-particles on
surfaces. ACOLS’05, 6 December, Christchurch, New Zealand, ThC6.

x


[A31]. Gramotnev, D. K., Bostrom, T. E., Gramotnev, G., Goodman, S. J.
“Deposition of Composite Aerosol Particles on Different Surfaces near a Busy
Road”, 7th International Aerosol Conference (IAC 2006), 10-15 September 2006, St.
Paul, Minnesota, USA, p.616-617.
[A32]. Gramotnev, D. K., Gramotnev, G. “Multiple thermal fragmentation of
nanoparticles: evolution of particle total number concentration”, 7th International
Aerosol Conference (IAC 2006), 10-15 September 2006, St. Paul, Minnesota, USA,
p.107-108.
[A33]. Gramotnev, G., Gramotnev, D. K. “Multi-channel statistical analysis of
combustion aerosols: Canonical correlations and sources of particle modes”, 7th
International Aerosol Conference (IAC 2006), 10-15 September 2006, St. Paul,
Minnesota, USA, p.177-178.
[A34]. Gramotnev, D. K., Gramotnev, G. “Anti-correlations of particle modes and
fragmentation theorem for combustion aerosols”, 7th International Aerosol
Conference (IAC 2006), 10-15 September 2006, St. Paul, Minnesota, USA, p.734735.
[A35]. Gramotnev, G., Madl, P., Gramotnev, D. K. “Anti-symmetric correlations of
particle modes in urban background aerosols”, 7th International Aerosol Conference
(IAC 2006), 10-15 September 2006, St. Paul, Minnesota, USA, p.1764-1765.
[A36]. Mason, D. R., Gramotnev, D. K., Gramotnev, G., Rasmussen, A. J.
“Thermal tweezers with dynamic evolution of the heat source”, 17th AIP Congress,
December 2006, Brisbane, Australia, abstract 461.
[A37]. Gramotnev, D. K., Bostrom, T. E., Mason, D. R., Gramotnev, G., Burchill,
M. J. “Deposition and Surface Evolution of Composite Aerosol Particles”, 17th AIP

Congress, December 2006, Brisbane, Australia, abstract 796.
[A38]. Gramotnev, D. K., Gramotnev, G. “Anti-Symmetric Correlation Pattern for
Particle Modes in Combustion and Background Aerosols: Fragmentation Theorem”,
17th AIP Congress, December 2006, Brisbane, Australia, abstract 795.

xi


[A39]. Gramotnev, G., Gramotnev, D. K. “Multi-Channel Statistical Analysis for
the Detailed Investigation of Combustion Aerosols”, 17th AIP Congress, December
2006, Brisbane, Australia, abstract 797.
[A40].

Gramotnev, D. K., Flegg, M. B., Gramotnev,

G. “Stochastic

evaporation/degradation processes in complex structures with multiple bonds”, 17th
AIP Congress, December 2006, Brisbane, Australia, abstract 748.

xii


LIST OF FIGURES

Fig. 3.1. Monitoring place

49

Fig. 3.2. Average wind parameters


50

Fig. 3.3. Theory and experiment (linear scale)

60

Fig. 3.4. Theory and experiment (logarithmic scale)

61

Fig. 3.5. Consultancy example

64

Fig. 5.1. Monitoring place

83

Fig. 5.2. Size distribution near the kerb

85

Fig. 5.3. Size distributions with experimental points (20 November 2002)

86

Fig. 5.4. Comparison of size distributions (20 November 2002)

87


Fig. 5.5. Size distributions with experimental points (23 December 2002)

89

Fig. 5.6. Comparison of size distributions (23 December 2002)

91

Fig. 5.7. Total number concentration

92

Fig. 5.8. Size distributions with experimental points (24 November 2002)

94

Fig. 5.9. Number concentrations (8 January 2003)

95

Fig. 6.1. Monitoring place

103

Fig. 6.2. Average wind parameters (25 November 2002)

105

Fig. 6.3. Size distributions with experimental points (25 November 2002)


106

Fig. 6.4. Moving average correlation coefficients

109

Fig. 6.5. Error curves

110

Fig. 6.6. Size distributions (20 November 2002)

116

Fig. 6.7. Size distributions (23 December 2002)

119

Fig. 6.8. Evolution pattern

123

Fig. 7.1. Geometry of the problem

132

Fig. 7.2. Fragmentation rate coefficient

135


Fig. 7.3. Total number concentrations (theoretical dependencies)

138

Fig. 7.4. Total number concentrations (comparison with experiment)

144

Fig. 8.1. Size distributions; moving average approach (25 November 2002) 159
Fig. 8.2. Moving average correlation coefficients

161

Fig. 8.3. Simple correlations with traffic

169

xiii


Fig. 8.4. Canonical correlation coefficients

173

Fig. 8.5. Canonical weights and loadings for heavy trucks

175

Fig. 8.6. Canonical weights and loadings for cars


176

Fig. 8.7. Canonical weights and loadings for temperature

187

Fig. 8.8. Canonical weights and loadings for solar radiation

188

Fig. 9.1. Moving average cross-correlation coefficients

195

Fig. 9.2. Anti-symmetric correlation pattern

197

Fig. 9.3. Anti-correlations with 13.6 nm mode

201

Fig. 9.4. Anti-correlations with 7 nm mode

202

Fig. 9.5. Anti-symmetric correlation pattern (later evolution stage)

203


Fig. 9.6. Fragmentation theorem

206

Fig. 10.1. Evolution of the 3-particle from the 1-2 state

215

Fig. 10.2. Random graph representation

216

Fig. 10.3. Particle concentrations (no dispersion)

226

Fig. 10.4. Particle concentrations (with dispersion)

227

Fig. 11.1. Monitoring place

230

Fig. 11.2. Background size distribution (before sunset)

231

Fig. 11.3. Comparison of size distributions before and after sunset


232

Fig. 11.4. Moving average correlation coefficients for background

233

Fig. 11.5. Anti-symmetric correlation pattern for background

236

xiv


Contents
Abstract

v

List of Author Publications

vii

List of Figures

xiii

Contents

xv


1. Introduction

1

1.1. Aims

7

2. Background and Theory

10

2.1. Ambient aerosols and their origins

10

2.2.

15

Turbulent dispersion of air pollutants

2.2a.

Taylor theorem and asymptotic properties
of the diffusing cloud

18


2.2b. Turbulent diffusion from a point continuous sources

20

2.2c. Continuous ground level line source

23

2.3.

Dispersion of fine particles from a busy road

26

2.4. Monitoring equipment

34

2.5. Statistical approaches: correlation techniques in data analysis

36

3. Determination of average emission factors for vehicles on a busy road
3.1.

45

Introduction

45


3.2. CALINE4 model

46

3.3.

Experimental measurements

48

3.4.

Model adaptation

50

xv


3.4.1.

Model emission factors

52

3.4.2.

Determination of the emission factor


54

3.5.

Comparison of numerical and experimental results

58

3.6.

An example of application of the model for road design

64

3.7.

Conclusions

65

4. New methods of determination of average particle emission factors
for two groups of vehicles on a busy road

68

4.1.

Introduction

68


4.2.

Emission factors for two different groups of vehicles

69

4.3.

Constrained optimization

73

4.4. Three types of vehicles on the road

74

4.5.

Turbulent corrections to the w-factors

77

4.6.

Conclusions

80

5. Experimental investigation of ultra fine particle size distribution

near a busy road

81

5.1.

81

Introduction

5.2. Experimental procedure

82

5.3. Experimental results and discussion

84

5.4. Level of confidence and errors

96

5.5.

99

Conclusions

6. A new mechanism of aerosol evolution near a busy road:
fragmentation of nano-particles


101

6.1.

101

Introduction

6.2. Modes of particle size distribution

102

xvi


6.3.

Maximum of the total number concentration

111

6.4.

Failure of the conventional mechanisms of the aerosol evolution

113

6.5.


Fragmentation model of aerosol evolution

120

6.6.

Conclusions

126

6.7. Appendix for Chapter 6

127

7. Modelling of aerosol dispersion from a busy road
in the presence of nano-particle fragmentation

130

7.1.

130

Introduction

7.2. Dispersion as a chemical reaction

131

7.3. Fragmentation of particles


133

7.4.

Existence conditions for the maximum

of the total number concentration

140

7.5.

Comparison with the experimental results

143

7.6.

Applicability conditions

150

7.7.

Conclusions

154

8. Multi-channel statistical analysis of aerosol particle modes

near a busy road

155

8.1.

Introduction

155

8.2.

Experimental data and particle modes

156

8.3. Moving average approach and the canonical correlation analysis

163

8.4.

Sources of particle modes

169

8.5.

Meteorological parameters


183

8.6.

Conclusions

189

9. Correlations between particle modes: fragmentation theorem

xvii

191


9.1.

Introduction

191

9.2. Moving average approach for particle modes

192

9.3. Numerical results and their discussion

194

9.4. Fragmentation Theorem


204

10. Probabilistic time delays during multiple stochastic
degradation/evaporation processes

213

10.1.

Introduction

213

10.2.

Time delays

214

10.3.

Evolution time and kinetics of degradation

218

11. Multi-channel statistical analysis of background fine particle aerosols

229


12. Conclusions

239

List of main results

240

Bibliography

243

xviii


CHAPTER 1
INTRODUCTION
Rapid development of high-technology industry, transport, and ever increasing
consumption of energy have resulted in increasing changes to our environment, climate,
atmosphere, natural resources, etc. (Seinfeld and Pandis, 1998). All these changes
should prompt a rapid and decisive response, if we want to stop adverse effects of our
technological activities on the quality of life, environment, and health. Finding such a
response is one of the major aims of modern science, including all of its mainstream
branches such as environmental sciences, engineering, physics, chemistry, medicine,
and applied mathematics.
Transport emissions are one of the major sources of atmospheric and
environmental pollution with the global effect on climate, environment, and quality of
life (Whelan, J. 1998, Schauer, et al, 1996, Shi, et al, 1999, Shi, et al, 2001). Choking
atmospheres in major world cities and reducing air quality in residential areas of large
metropolitan centres require urgent measures on reduction, control, and effective

prediction of air pollution levels from busy roads and road networks. One of the major
types of pollutants from modern transport and road networks is combustion aerosols
comprising fine and ultra-fine particles with diameters from several nanometres to
several hundreds of nanometres (Schauer, et al, 1996, Shi, et al, 1999). It is long known
that such aerosols may have an effect on climate, mainly through cloud formation and
rainfall patterns (Seinfeld and Pandis, 1998, Jacobson, 1999). In addition, during the last
decade, researchers have established links between fine and ultra-fine particle aerosols
and noticeable health risks for humans in city areas (Pope, et al, 1995, Van Vliet, et al,
1997).
During the last several years, numerous studies have observed health effects of
particulate air pollutants. Compared to early studies that focused on severe air pollution
1


episodes (Beaver, H., 1953), recent research is more relevant to understanding health
effects of pollution at levels common to contemporary cities in the developed world.
Observed health effects include increased respiratory symptoms, decreased lung
function, increased hospitalizations and other health care visits for respiratory and
cardiovascular disease, increased respiratory morbidity as measured by absenteeism
from work and school, or other restrictions in activity, and increased cardiopulmonary
disease mortality. These health effects have been observed at levels common to many
U.S. cities including levels below current U.S. National Ambient Air Quality Standards
for particulate air pollution (Pope, et al, 1995).
It has also been found that those children who have been living within 100 m of
a freeway had significantly more coughs, wheezes, runny noses, and doctor-diagnosed
asthmas (Van Vliet, et al, 1997). In addition, the same study identified a significant
association between truck traffic density and black smoke concentration on the one hand
and chronic respiratory symptoms on the other.
Until recently, the main concern has been related to emission of relatively large
particles with diameters > 1 µm (Friedlander, 1977). Therefore the current emission

standards establish the limits on emission of overall particulate mass, rather than
concentration of particles. However, recent investigations have made it apparent that
fine and ultra-fine aerosol particles (within the ranges < 1 µm and < 0.1 µm,
respectively) emitted from combustion sources may present a significant health risk for
humans (Wichmann, and Peters, 2000, Zhiqiang, et al, 2000, Ziesenis, et al, 1998,
Borja-Aburto, et al, 1998), especially for people with specific health problems (e.g.,
heart, vascular, respiratory, etc. problems (Borja-Aburto et al, 1998). Moreover, it is
now clear that adverse health effects related to ultra-fine (< 100 nm) particles with large
number concentration but small overall mass appear to be significantly stronger than the
effects from larger (fine) particles with diameters between ~ 100 nm and ~ 1 µm (Stone,
2


2000, Brown, et al 2000). For example, proinflammatory response is greater for ultrafine particles, and is directly proportional to the surface area of the particles (Brown, et
al, 2001). Therefore, one of the possible explanations of increased health effects of
ultra-fine aerosol particles is related to the fact that decreasing particle diameters and
increasing their number concentrations results in a strong increase of particle surface
area per unit volume (Peters, 1997, Brown, et al, 2001, Nemmar, et al, 2002). This is
the surface area of the particles that probably drives inflammation in the short term,
resulting in significantly larger effect from ultra-fine particles having very large number
concentrations and surface area (Nemmar, et al, 2002). During a study of the
penetration of pollutant particles into the blood stream, it was found that ultra-fine
aerosol particles penetrate into the blood just in ~ 1 minute (Nemmar, et al, 2002). The
concentration in the blood reaches a maximum within ~ 10 – 20 minutes, and remains at
this maximal level for up to ~ 60 minutes (Nemmar, et al, 2002). One of the reasons for
these enhanced and fast effects is probably related to the fact that fine and ultra-fine
particles tend to penetrate much deeper into the respiratory tract (Siegmann, et al,
1999). However, the complete understanding of the observed health problems and risks
related to fine and ultra-fine particle aerosols still needs further studies including
research into physical mechanisms of particle transformation and evolution, in order to

understand which types of particles tend to play a predominant role in human exposure.
As mentioned above, the current particulate emission standards restrict the
overall particulate mass emissions. These standards are thus focusing only on PM10 and
PM2.5 (i.e., the overall particulate mass concentration for particle diameters < 10 µm and
< 2.5 µm, respectively). They are obviously of little use for the development of
regulations and policies when it comes to the strong adverse effects of fine and ultrafine particles, because the contribution of such particles to the overall aerosol mass is
negligible. Therefore, new standards for fine and ultra-fine particle aerosols are

3


required, based on number concentrations rather than overall particulate mass. This will
also require detailed and comprehensive understanding of the major mechanisms of
formation and evolution of combustion aerosols, transformation of particle modes,
determination of their possible sources, possible places of enhanced health risks,
mechanisms of removal and self-removal of particles from the atmosphere, etc. At the
same time, our current knowledge about fine and ultra-fine aerosol particles, their
possible sources and mechanisms of transformation is fairly limited and some times
inconsistent with experimental observations (for more detail see Chapter 2).
It is also clear that the development of adequate standards for fine and ultra-fine
particle aerosols may only help to determine and identify the existing and potential
problems with air pollution and transport and industry emissions. Solution of these
problems will be another very complex task that will require new approaches for
effective reduction and control of air pollution levels (including particulate pollutants)
and improvement of the air quality in major metropolitan centres. And this is again not
possible without the detailed understanding of processes of aerosol formation,
interaction, evolution, and eventual removal and/or self-removal from the atmosphere.
As a result, significant efforts of a number of aerosol scientists have recently
been focused on the advancement of our fundamental knowledge of behaviour of
combustion aerosols and their prediction in the urban environment. In particular,

detailed understanding of dispersion of nanoparticle aerosols is one of the most
important goals for achieving reliable and accurate forecast of aerosol pollution levels
and the resultant human exposure. One of the major physical mechanisms of dispersion
of air pollutants (including nanoparticle aerosols) in the atmosphere is turbulent
diffusion (Seinfeld & Pandis, 1998, Jacobson, 1999). If only this mechanism is taken
into account, dispersion of aerosols and gasses can be described by the Gaussian plume
model (Csanady, 1980, Pasquill and Smith, 1983, Zannetti, 1990). Several successful

4


software packages for different types of sources including point sources (industry)
(Bowers & Anderson, 1981), area sources (bushfires) (Hanna, et al, 1984), line sources
(busy roads) (Benson, 1992) have been developed for non-reactive pollutants. However,
modelling of dispersion of reactive gasses and rapidly evolving aerosols is a much more
complex problem (Bilger, 1978, Fraigneau, et al, 1995).
Previously, it was fairly commonly assumed that fine and ultra fine particle
aerosols do not undergo significant and rapid transformations (Shi et al, 1999). In this
case, particle size distributions should be more or less constant within a significant
period of time, and the Gaussian plume approximation should be applicable for the
approximate description of aerosol dispersion from different sources. In this case the
above-mentioned software packages should be applicable (after the appropriate rescaling) for the prediction of aerosol dispersion in the atmosphere. Therefore, the main
interest of aerosol scientists has been focused on the study of decay of the total number
concentration of particles with distance from a source, e.g., a busy road (Shi, et al,
1999, Hitchins, et al, 2000, Zhu, et al, 2002a,b). In particular, exponential decay laws
were used for the description of the total number concentration of fine particles as a
function of distance from the road (Zhu, et al, 2002a,b).
However, several recent experimental observations have suggested that the
Gaussian plume approximation is not always applicable, especially for smaller particles
within the range < 30 nm. Noticeable deviations of the size distributions of fine and

ultra fine particles near a busy road from those predicted by the Gaussian plume model
have been observed by Zhu, et al (2002a,b). This suggests that there are significant
processes of evolution of particles during their transport away from the road – see also
(Ketzel and Berkowicz, 2004). Such evolution processes may include particle formation
by means of homogeneous and heterogeneous nucleation (Alam, et al, 2003, Kulmala,
et al, 2000, Kerminen, et al, 2002, Lehtinen and Kulmala, 2003, Pirjola, 1999),

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coagulation (Jacobson, 1999, Kostoglou & Konstandopoulos, 2001, Piskunov &
Golubev, 2002), deposition (Jacobson, 1999, Meszaros, 1999), condensation and
evaporation (Zhang et al, 2005, Uvarova, 2003).
Nevertheless, there are still noticeable discrepancies between the theoretical
predictions based on the mentioned mechanisms of aerosol evolution and the
experimental observations and monitoring data near busy roads. For example, Zhu, et al
(2002a,b) have observed a shift of one of the particle modes (maximums of the particle
size distribution) towards smaller particle diameters when the distance from the road is
increased. This observation is in obvious contradiction with the suggested coagulation
mechanism, of evolution of the particle size distribution (Zhu, et al, 2002a,b).
Contradictory suggestions regarding the nature of combustion nanoparticles have been
presented in the literature. Some of the researchers assume that particles with diameters
< 30 nm are mostly volatile (Sakurai, et al, 2003), whereas others suggest that they are
predominantly solid – graphite, carbon, or metallic ash (Pohjola, et al, 2003, AbdulKhalek, et al, 1998, Bagley, et al, 1996). Very few experiments on direct particle
observation and determination of their properties and structure under field conditions
have been undertaken so far, while laboratory analysis may give significantly different
results from the real-world situations with stochastically varying atmospheric conditions
and natural variability of the source (different types of vehicles, their maintenance, etc.).
Problems with such field experiments are well known. They are related to significant
fluctuations/dispersion of monitoring data associated with strong natural stochastic

processes, such as atmospheric turbulence, variability of temperature, humidity, solar
radiation, traffic conditions, etc. Therefore, deriving sensible conclusions about the
nature of different types of aerosol particles and their evolution in the presence of strong
turbulent mixing requires the development of new extensive and complex methods of
statistical analysis.

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As a result, a number of important questions about the nature of particle modes
in combustion aerosols and their evolution/transformation and physical and chemical
structure in the real-world environment have so far been left unanswered. Some of these
questions can be listed as follows. (1) What is the predominant nature of the exhaust
nanoparticles? Are they mainly solid or volatile? (2) What are the dominant sources (if
any) of different particle modes? (3) How can we determine emission factors from
different types of vehicles on an actual road (these factors are essential for accurate
prediction of aerosol pollution levels)? (5) How do particle modes evolve with time and
distance from the source at different atmospheric, physical, and climate conditions? (6)
Are the known mechanisms sufficient for the complete description of aerosol evolution,
or we are missing something?
Detailed investigation of these and other questions is essential for accurate
forecast of aerosol pollution in the urban environment, establishment of working
emission standards and, ultimately, reduction or elimination of the impact of these
emissions on our environment, air quality and health.
Therefore, the general aim of this thesis is to gain better understanding of
behaviour of nanoparticle aerosols by means of detailed experimental, statistical and
theoretical investigation of evolution mechanisms, dispersion, and deposition of
combustion airborne nanoparticles in the real-world environment, and develop new
predictive models and statistical methods of data analysis in the presence of natural
variability of the source and environmental conditions.

The specific aims of the project can be listed as follows.
1. Adaptation of the currently available models for the analysis of dispersion of nonreactive air pollutants from a busy road (CALINE4 model) for the reliable forecast
of aerosol pollution levels.

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