university of genoa - infn.it aerosols may also be classified as hygroscopic or non-hygroscopic; in...

University of Genoa

Faculty of Mathematical, Physical and Natural Sciences

An optical set-up for the multi-wavelength characterization of

carbonaceous particulate matter

Thesis

FOR THE ATTAIMENT OF THE PHILOSOPHIÆ DOCTOR

DEGREE IN MATERIAL SCIENCE AND TECHNOLOGY

Scientific – disciplinary sector: FIS/07

BY

Dario MASSABO’

Supervisor:

Prof. Paolo Prati (University of Genoa)

3

Contents

Introduction……………………………………………………………………………..5

Atmospheric Aerosols ................................................................................................... 8

1.1 Overview ...................................................................................................................... 8

1.2 Effects on Climate ..................................................................................................... 12

1.3 Health Effects and Air Quality .................................................................................. 15

1.4 Carbonaceous Aerosol Components .......................................................................... 16

1.5 Aerosol measurements and sampling ........................................................................ 18

1.5.1 PM Samplers .............................................................................................................. 19

The carbonaceous fraction of PM: measurement techniques ...................... 22

2.1 Introduction ............................................................................................................... 22

2.2 Thermo-optical transmittance methods ..................................................................... 24

2.2.1 The Sunset EC/OC Analyzer ...................................................................................... 25

2.3 Optical Methods ........................................................................................................ 28

2.3.1 The Aethalometer ....................................................................................................... 31

2.3.2 The Multi-Angle Absorption Photometer (MAAP) ................................................... 35

2.3.3 Other measurement techniques................................................................................... 38

The Multi-Wavelength Absorbance Analyzer ................................................... 40

3.1 Introduction ............................................................................................................... 40

3.2 The radiative transfer theory...................................................................................... 42

4

3.2.1 The Adding Method ................................................................................................... 45

3.2.2 The Two-stream Approximation ................................................................................ 48

3.2.3 The Aerosol Absorption Coefficient .......................................................................... 51

3.2.4 The light phase function ............................................................................................. 53

3.3 The MWAA optical set-up ........................................................................................ 58

3.3.1 Light Detection ........................................................................................................... 61

3.4 MWAA: ABS calculation .......................................................................................... 66

3.5 MWAA: Validation of the instrument ....................................................................... 71

3.6 The BC absorption cross-section ............................................................................... 75

3.7 Analysis with other collecting media ........................................................................ 77

3.8 Analysis of impactor stages ....................................................................................... 81

Multi-wavelength Analysis and Source Apportionment ................................ 84

4.1 Introduction ............................................................................................................... 84

4.2 The case of a urban site: Genoa ................................................................................. 85

4.2.1 The Ångström absorption exponent ........................................................................... 88

4.3 The case of a rural site: Propata ................................................................................ 89

4.3.1 Source apportionment ................................................................................................. 91

Conclusions……………………………………………………………………………101

Bibliography…………………………………………………………………………..103

introduzione

Introduction

Atmospheric aerosols are a central topic in atmospheric physics and chemistry, with

consistent effects on climate and public health. Aerosols consist in solid or liquid particles

suspended in the atmosphere in the size range between few nanometers to some tens of

microns. Although aerosols are a small fraction of the atmosphere, they influence the

Earth's energy budget (climate forcing), the hydrologic cycle, and atmospheric circulation:

they can affect formation and transformation of clouds and the abundance of greenhouse

and reactive trace gases. Moreover, they are of paramount importance in the reproduction

of biological organisms and can cause or enhance diseases, so that nowadays air quality

standards impose limits on their concentration. Effects on the health of human being are

also well established and, for instance, the monitoring of PM10 and PM2.5 (particulate

matter with aerodynamic diameter lower than 10 m and 2.5 m, respectively) on a 24-

hour basis is prescribed and daily and annual limit values are set, for instance, in

accordance with the European Directive 2008/50/EC. At rural background sites, ionic and

carbonaceous (organic and elemental carbon) speciation is also prescribed for PM2.5. The

primary parameters determining the aerosol particles effects on health and environment are

the concentration, size, structure and chemical composition. The scientific community has

a need for extensive measurements and detailed characterizations, permitting to improve

the overall picture and get more insight on production and transport mechanisms. These

parameters, in fact, are spatially and temporally highly variable. In particular, the

quantification and identification of biological particles and carbonaceous components of

fine particulate matter in the air (organic compounds and black or elemental carbon,

Introduction

6

respectively) represent demanding analytical challenges.

Carbonaceous aerosols has only recently become one of the most studied topics in

the field of atmospheric sciences. The scientific community started this research in 1950s,

particularly after some catastrophic events (e.g. the “London smog”, in which more than

4000 people died in winter 1952). However, until the early 1990’s, the carbonaceous

aerosols were seen as a pollutant of local or regional importance; only in the last two

decades the recognition of its global importance has been completely accepted.

Even in the most remote areas of the Earth, like Antarctica or Himalaya, the

presence of black carbon has been revealed. According to the IPCC, 2007

(Intergovernmental Panel on Climate Change), “the presence of black carbon and organic

carbon from biomass combustion over highly reflective surfaces, such as snow and ice, or

clouds, may cause a significant positive radiative forcing”. In this regard, it is worthy to

note that the largest uncertainties related to the climate change are associated with the

carbonaceous aerosols. On the other hand, if we look at the health effects of atmospheric

pollution, there are thousands of potentially harmful organic compounds associated with

the breathable fraction of atmospheric aerosols.

The study of the carbonaceous aerosols presents considerable difficulties, both in

experiments and theoretical models, mainly due to the extreme variety of its components

and to the fact that, in the atmosphere, carbonaceous particles react and are mixed with the

other components of PM. This effect increase with the “aging” of the particles, that

depends on the residence times in the atmosphere. Moreover, there is a lack even of

solidified terminology and classification criteria. A generally accepted distinction in

carbonaceous aerosol terminology is that between elemental/black and organic carbon

(EC/BC and OC, respectively). Whereas the different atmospheric and health-related

effects of these generic classes may justify such a division, there is no clear borderline

between the two [Pöschl, 2003; Gelencsér, 2004]. Conceptually, there is a smooth

transition between organic and elemental/black carbon, so that any division can only be

operationally defined and arbitrary [Gelencsér, 2004]. Since there is a large number of

analytical methods, it is not surprising that they introduce a large uncertainty into the

determination of the basic forms of carbonaceous aerosol. As a matter of fact, several

methodologies have been proposed and used to measure the carbonaceous components of

particulate matter; however, a generally accepted reference method is still missing [Bond

Introduction

7

and Bergstrom, 2006].

This work describes a new instrument, designed and developed to provide a non-

destructive, fast and handling approach to the determination of the optical properties of

carbonaceous aerosol and of its sources.

Thesis Layout:

In Chapter 1, the main characteristics of atmospheric aerosols are described, with

details about its carbonaceous fraction and sampling methodology. In Chapter 2, an

overview on existing methods and instrumentation to analyse carbonaceous aerosols is

given, with a critical discussion on advantages and limits of each technique. A new optical

set-up for the multi-wavelength characterization of carbonaceous aerosol collected on

filters (MWAA – Multi-Wavelength Absorbance Analyzer) is then illustrated in Chapter

3. Finally, in Chapter 4, results of multi-wavelength analysis of PM samples collected

during field campaigns are reported to show as the MWAA can be used to apportion

different sources of the carbonaceous PM, in particular fossil fuel and biomass combustion.

Chapter 1

Atmospheric Aerosols

1.1 Overview

Atmospheric aerosols are a complex and dynamic mixture of solid and liquid

particles from natural and anthropogenic sources, showing very differentiated

concentration, composition, granulometric, and morphological properties [Seinfeld, 1986;

Singh, 1995; Maynard and Howard, 1999]. The effects of aerosols on the atmosphere,

climate, and public health are among the central topics in current environmental research.

Aerosol particles scatter and absorb solar and terrestrial radiation, they are involved in the

formation of clouds and precipitation as cloud condensation and ice nuclei (CCN and IN),

and they affect the abundance and distribution of atmospheric trace gases by heterogeneous

chemical reactions and other multiphase processes [Seinfeld and Pandis, 1998; Finlayson-

Pitts, 2000; Houghton et al., 2001; Lohmann et al., 2005]. Moreover, airborne particles

play an important role in the spreading of biological organisms, reproductive materials, and

pathogens (pollen, bacteria, spores, viruses, etc.), and they can cause or enhance

respiratory, cardiovascular, infectious, and allergic diseases [Finlayson-Pitts, 1997; Hinds,

1999; Finlayson-Pitts, 2000; Bernstein et al., 2004]. An aerosol is generally defined as a

Chapter 1: Atmospheric Aerosols

9

suspension of liquid or solid particles in a gas, with particle diameters in the range of 10-9

m - 10-4

m (lower limit: molecules and molecular clusters; upper limit: rapid

sedimentation) [Seinfeld and Pandis, 1998; Hinds, 1999]. Particle shapes can be widely

different: spheres are usually assumed for liquid aerosols, and irregular shapes or crystals

for solid particles. Aerosols may also be classified as hygroscopic or non-hygroscopic; in

the first case the size-distribution is modified under the influence of the humidity field. The

hygroscopic particles may as well favor cloud drop formation acting as CCN; acidic

aerosols can also cause or enhance acidic fog and rain [Johansson et al., 1995]. The most

evident examples of aerosols in the atmosphere are clouds, which consist primarily of

condensed water with particle diameters on the order of approximately 10 m. In

atmospheric science, however, the term aerosol traditionally refers to suspended particles

that contain a large proportion of condensed matter other than water, whereas clouds are

considered as separate phenomena [Pruppacher et al., 1997].

Atmospheric aerosol particles originate from a wide variety of natural and

anthropogenic sources. Primary particles are directly emitted as liquids or solids from

sources such as biomass burning, incomplete combustion of fossil fuels, volcanic

eruptions, and wind-driven or traffic-related suspension of road, soil, and mineral dust, sea

salt, and biological materials (plant fragments, microorganisms, pollen, etc.). Secondary

particles, on the other hand, are formed by gas-to-particle conversion in the atmosphere

(new particle formation by nucleation and condensation of gaseous precursors). In both

cases, primary particles are continuously emitted into and secondary particles are formed

in the atmosphere.

Figure 1.1: Atmospheric cycling of Aerosols [Pöschl, 2005].


10

As illustrated in Figure 1.1, airborne particles undergo various physical and chemical

interactions and transformations (atmospheric aging), that is, changes of particle size,

structure, and composition (coagulation, restructuring, gas uptake, chemical reaction).

Particularly efficient particle aging occurs in clouds, which are formed by condensation of

water vapor on pre-existing aerosol particles (cloud condensation and ice nuclei). Most

clouds re-evaporate, and modified aerosol particles are again released from the evaporating

cloud droplets or ice crystals (cloud processing). If, however, the cloud particles form

precipitation which reaches the Earth’s surface, not only the condensation nuclei but also

other aerosol particles are scavenged on the way to the surface and removed from the

atmosphere. This process, termed “wet deposition”, is actually the main sink of

atmospheric aerosol particles. Particle deposition without precipitation of airborne water

particles - that is, “dry deposition” by convective transport, diffusion, and adhesion to the

Earth’s surface - is less important on a global scale, but is highly relevant with respect to

local air quality, health effects (inhalation and deposition in the human respiratory tract),

and the soiling of buildings and cultural monuments.

Depending on aerosol properties and meteorological conditions, the characteristic

residence times of aerosol particles in the atmosphere range from hours to weeks [Raes et

al., 2000; Williams et al., 2002]. The concentration, composition, and size distribution of

atmospheric aerosol particles are temporally and spatially highly variable. In the lower

atmosphere (troposphere) the total particle number and mass concentrations typically vary

in the range of about 102 - 10

5 cm

-3 and 1-100 g m

-3, respectively [Raes et al., 2000;

Williams et al., 2002; Van Dingenen et al., 2004; Krejci et al., 2005]. In general, the

predominant chemical components of air particulate matter (PM) are sulfate, nitrate,

ammonium, sea salt, mineral dust, organic compounds, and black or elemental carbon,

each of which typically contribute about 10–30% of the overall mass load. At different

locations, times, meteorological conditions, and particle size fractions, however, the

relative abundance of different chemical components can vary by an order of magnitude or

more [Finlayson-Pitts, 2000; Seinfeld and Pandis, 1998; Raes et al., 2000; Putaud et al.,

2004].

The aerodynamic properties of the particles govern their transport and removal from

the air, as well as the deposition within the human respiratory system. For this reason, it is

convenient to classify particles by their aerodynamic diameter (Dae) that is the size of a


11

unit-density sphere with the same aerodynamic characteristics [Marple, 1976]. Particles are

sampled and described on the basis of this parameter, usually called simply the particle

size.

In atmospheric research the term “fine air particulate matter” is usually restricted to

particles with aerodynamic diameters (Dae) less than 1 m (PM1) or 2.5 m (PM2.5).

Especially in air pollution control it also includes larger particles up to 10 m (PM10).

The size distribution (in mass or in number) of particles in the atmosphere is

determined by the competition between sources and removal mechanisms. The aerosols

observed in the atmosphere are thus the result of the balance between different and

competing processes: emission by sources, transport, and deposition. In the troposphere,

for dry conditions, aerosols tend to form a characteristic bimodal distribution, where most

of the mass is confined in two separate modes or fractions, the fine and the coarse modes

[Johansson et al., 1995], as shown in Figure 1.2.

Figure 1.2: Idealized schematic (a) of the distribution of particle surface area of an atmospheric aerosol

[Whitby and Cantrell, 1976]. Principal modes, sources, and particle formation and removal mechanisms

are indicated. Aerosol particles examined by SEM (b) and example of number and volume concentrations

in the troposphere range.

The smallest particles, less than 0.1 µm, are generally formed by nucleation, i.e.

condensation of low vapor-pressure substances formed by high-temperature vaporization

or by chemical reactions in the atmosphere to form new particles (nuclei). Particles in this

nucleation range or mode grow rapidly by coagulation (i.e. the combination of two or more

a) b)


12

particles to form a larger particle) or by condensation (i.e. condensation of gas or vapor

molecules on the surface of existing particles). The efficiency of both coagulation and

condensation decreases as particle size increases, which effectively produces an upper limit

such that particles do not grow by these processes beyond approximately 23 µm. All

particles smaller then 23 µm are generally referred as fine fraction particulate (Figure

1.2a). The smallest ones, less than 0.1 µm, are efficiently removed by diffusion. However,

neither settling nor diffusion is efficient between 0.1 and 1 m, thus particles tend to

"accumulate" in this range, the so-called accumulation range (Figure 1.2a). Particles of

this size can survive up to 10 days in the lower troposphere and thus travel long distances.

However, in wet conditions, such particles are easily incorporated into clouds, and such

wet removal processes are very rapid and efficient. Acidic aerosols incorporated into

clouds can enhance or cause acidic clouds/fog and acid rain [Johansson et al., 1995].

The coarse fraction particles are mechanically produced by the break-up of larger solid

particles, and can include: wind-blown dust (from agricultural processes, uncovered soil,

unpaved roads or mining operations), road dust re-suspended by traffic, sea spray particles,

pollen grains, mould spores, plant and insect parts. The amount of energy required to break

these particles into smaller sizes increases as the size decreases, which effectively

establishes a lower limit for the production of these coarse particles of approximately 12

µm. Coarse particles removal is generally by settling and, since the process is quite

efficient, the residence time in the atmosphere is short, typically of the order of hours. In

Figure 1.2b some examples of SEM analysis are reported for different particle sources.

1.2 Effects on Climate

Aerosol effects on climate are generally classified as direct or indirect with respect to

radiative forcing of the climate system. Radiative forcings are changes in the energy fluxes

of solar radiation (maximum intensity in the spectral range of visible light) and terrestrial

radiation (maximum intensity in the infrared spectral range) in the atmosphere, induced by

anthropogenic or natural changes in atmospheric composition, Earth surface properties, or

solar activity. Negative forcings such as the scattering and reflection of solar radiation by

aerosols and clouds tend to cool the Earth’s surface, whereas positive forcings such as the


13

absorption of terrestrial radiation by greenhouse gases and clouds tend to warm it

(greenhouse effect) [Houghton et al., 2001]. Figure 1.3 illustrates the distinction between

direct and indirect aerosol effects and some major feedback loops in the climate system

[Pöschl, 2005]. Direct effects result from the scattering and absorption of radiation by

aerosol particles, whereas indirect effects result from their CCN and IN activity (influence

on clouds and precipitation), or from their chemical and biological activity (influence on

aerosol and trace gas emissions and transformation).

Figure 1.3: Direct and indirect aerosol effects and major feedback loops in the climate system [Pöschl,

2005].

The optical properties relevant for the direct effects (scattering and absorption

coefficient or extinction cross section and single scattering albedo, etc.) as well as the

CCN, IN, chemical and biological activities relevant for indirect effects are determined by

aerosol particle size, structure, and chemical composition. Thus they are strongly

influenced by the atmospheric processes outlined above (coagulation, chemical

transformation, water interactions). The climate feedback loops illustrated in Figure 1.3

involve the interaction of atmospheric aerosols with solar and terrestrial radiation, clouds

and precipitation, general circulation and hydrological cycle, and with natural and

anthropogenic aerosol and trace gas sources on global and regional scales. On microscopic

and molecular scales, each of the interactions outlined in Figure 1.3 comprises a multitude


14

of physicochemical processes that depend on atmospheric composition and meteorological

conditions and are largely not quantitatively characterized. In many cases, even the sign or

direction of the feedback effect is unknown, that is, it is not clear whether a perturbation

will be reinforced (positive feedback) or decreased (negative feedback). Therefore, the net

effect of aerosols on climate is difficult to quantify and this uncertainty is shown in Figure

1.4, extracted from the 2007 report of the Intergovernmental Panel on Climate Change.

The estimates of the total net anthropogenic radiative forcing ranges between 0.6 and 2.4

W m-2

.

Figure 1.4: Global average radiative forcing in 2005 (best estimates and 5 to 95% uncertainty ranges) with

respect to 1750 for CO2, CH4, N2O and other important agents and mechanisms, together with the typical

geographical extent (spatial scale) of the forcing and the assessed level of scientific understanding

(LOSU). Aerosols from explosive volcanic eruptions contribute an additional episodic cooling term for a

few years following an eruption. The range for linear contrails does not include other possible effects of

aviation on cloudiness [IPCC 2007].

Negative climate forcing by anthropogenic aerosols due to increased scattering and

indirect cloud effects is comparable in magnitude (but opposite in sign) to climate forcing

due to increased concentration of greenhouse gases [Houghton et al, 2001]. Consequently,

aerosols could be negating a significant part of greenhouse effect: it has been suggested

that aerosols are masking the real response of the climate system and that the temperature


15

sensitivity of the Earth is higher than observed [Schwartz et al, 1996].

1.3 Health Effects and Air Quality

The impact on human health is clearly connected with the different capacity of the

particles to penetrate into the breathing apparatus, with smaller ones reaching more easily

the deeper parts of the lungs and being therefore more dangerous. Particles with Dae greater

than 10 m are stopped in the first part of the respiratory system and then easily expelled.

Particles with Dae between about 10 and 3.5 m tend to be inhaled and stopped in the nose,

throat, and upper bronchial tract. The removal from the body is generally by swallowing.

Particles smaller than about 3.5 m enter the deep lung and are retained in the alveoli;

removal tends to be through the blood stream, which is generally more hazardous than

through the respiratory system. Numerous epidemiological studies show that fine air

particulate matter and traffic-related air pollution are correlated with severe health effects,

including enhanced mortality, cardiovascular, respiratory, and allergic diseases [Bernstein

et al., 2004; Gauderman et al., 2004; Pope et al., 2004; Samet et al., 2005]. Moreover,

toxicological investigations in vivo and in vitro have demonstrated substantial pulmonary

toxicity of model and real environmental aerosol particles, but the biochemical

mechanisms and molecular processes that cause the toxicological effects such as oxidative

stress and inflammatory response have not yet been resolved. Among the parameters and

components potentially relevant for aerosol health effects are the specific surface,

transition metals, and organic compounds. [Bernstein et al., 2004, Bömmel et al., 2003;

Donaldson et al., 2003; Schins et al., 2004].

Ultrafine particles (Dae < 100 nm) are suspected to be particularly hazardous to

human health, because they are sufficiently small to penetrate the membranes of the

respiratory tract and enter the blood circulation or be transported along olfactory nerves

into the brain [Oberdörster et al., 2005; Nemmar et al., 2002]. Neither for ultrafine nor for

larger aerosol particles, however, it is clear which physical and chemical properties

actually determine their adverse health effects (particle size, structure, number, mass

concentration, solubility, chemical composition, and individual components, etc.).

Particularly little is known about the relations between allergic diseases and air quality.


16

Nevertheless, traffic-related air pollution with high concentration levels of fine air

particulate matter, nitrogen oxides, and ozone is one of the prime suspects besides non-

natural nutrition and excessive hygiene practices, which may be responsible for the strong

increase of allergies in industrialized countries over the past decades [Ring et al., 2001;

Brunekreef et al., 2003; Bernstein et al., 2004].

With regard to atmospheric aerosol effects on human health not only the quantitative

but also the qualitative and conceptual understanding is very limited. Epidemiological and

toxicological studies indicate strong adverse health effects of fine and ultrafine aerosol

particles as well as gaseous air pollutants, but the causative relations and mechanisms are

hardly known [Bernstein et al., 2004; Samet et al., 2005]. Their understanding, however, is

required for the development of efficient strategies for air-quality control and medical

treatment of related diseases that will enable the minimization of adverse aerosol health

effects at minimum social and economic costs.

1.4 Carbonaceous Aerosol Components

Carbonaceous aerosol components (organic compounds and black or elemental

carbon) account for a large fraction of air particulate matter, exhibit a wide range of

molecular structures, and have a strong influence on the physicochemical, biological,

climate and health related properties, and effects of atmospheric aerosols [Seinfeld and

Pandis, 1998; Finlayson-Pitts, 2000; Gelencsér, 2004; Kulmala et al., 2004; Henning et al.,

2005; Kanakidou et al., 2005]. Traditionally the total carbon (TC) content of air particulate

matter is defined as the sum of all carbon contained in the particles, except in the form of

inorganic carbonates [Pöschl, 2005]. TC is usually determined by thermo-chemical

oxidation and evolved gas analysis (CO2 detection), and divided into an organic carbon

(OC) fraction and a black carbon (BC) or elemental carbon (EC) fraction (for more details

see Chapter 2). Measurements of BC and EC are generally based on optical and/or thermo-

chemical techniques, and OC is operationally defined as the difference between TC and

BC or EC (TC = BC + OC or TC = EC + OC) [Gelencsér, 2004].

As illustrated in Figure 1.5, however, there is no real sharp boundary but a

continuous decrease of thermo-chemical refractiveness and specific optical absorption


17

going from graphite-like structures to non-refractive and colorless organic compounds,

respectively [Pöschl, 2003]. Both BC and EC consist of the carbon content of the graphite-

like material usually contained in soot (technically defined as the black product of

incomplete hydrocarbon combustion or pyrolysis) and other combustion aerosol particles,

which can be pictured as more or less disordered stacks of graphene layers or large

polycyclic aromatics [Homann, 1998; Sadezky et al., 2005].

Figure 1.5: Optical and thermochemical classification and molecular structures of black carbon (BC),

elemental carbon (EC), and organic carbon (OC = TC - BC or TC - EC). Depending on the method of

analysis, different amounts of carbon from refractory and colored organic compounds are included in OC

and BC or EC [U. Pöschl, Anal. Bioanal. Chem. 2003, 375, 30].

Depending on the applied optical or thermo-chemical methods (absorption

wavelength, temperature gradient, etc.), however, BC and EC measurements also include

the carbon content of colored and refractory organic compounds, which can lead to

substantially different results and strongly limits the comparability and suitability of BC,

EC, and OC data for the determination of mass balances and physicochemical properties of

air particulate matter. Elemental carbon, as used in atmospheric chemistry, usually

identifies carbon that does not volatilize below a certain temperature, usually about 550 °C.

This term is an operational definition based on the stability of carbon at elevated

temperatures [Huntzicker et al., 1982; Chow et al., 1993; Birch and Cary, 1996]. A more

precise name for this substance is refractory carbon. The fraction identified as elemental

carbon under this method depends on the heating conditions [Schmid et al., 2001]. In this

work, for elemental carbon, I assume an operationally obtained quantity of carbon

measured with a thermo-optical analysis, with a specific thermal protocol.

Black carbon is instead the most widely used term for defining light-absorbing


18

carbonaceous aerosols. The term implies carbonaceous aerosols that have strong

absorption across a wide spectrum of visible wavelengths. Some instruments such as the

Aethalometer [Hansen et al., 1984] report concentrations of black carbon based on light

attenuation (see Chapter 2). In this work I assume, for black carbon, the quantity of mass

of carbon obtained by a measure of the optical properties of the aerosol samples, i.e.

attenuation/absorption at a specific lambda. Of course, the two quantities of EC and BC,

although quite similar, coincide almost never. This difference leads to find different values

of OC because of it is defined, as already said before, as the difference OC = TC – EC or

BC.

Nevertheless, most information available on the abundance, properties, and effects of

carbonaceous aerosol components so far is based on measurement data of TC, OC, and BC

or EC [Gelencser, 2004; Kanakidou et al., 2005]. These data are now increasingly

complemented by measurements of water-soluble organic carbon (WSOC), its

macromolecular fraction (MWSOC), and individual organic compounds. Moreover, the

combination of thermo-chemical oxidation with 14

C isotope analysis (radiocarbon

determination in evolved CO2 by accelerator mass spectrometry) allows a differentiation

between fossil-fuel combustion and other sources of carbonaceous aerosol components

[Pöschl, 2005]. Recent results confirm that the EC is dominated by fossil-fuel combustion

and indicate highly variable anthropogenic and biogenic sources and proportions of OC

[Szidat et al., 2004; Sandradewi et al., 2008; Favez at al., 2009]. In this work a new way to

separate these contributions starting from the “Aethalometer model” by [Sandradewi et al.,

2008] is proposed (Chapter 4).

1.5 Aerosol measurements and sampling

Sampling is an indispensable and quite often critical step for the chemical

characterization of atmospheric aerosol particles. Except for some on-line techniques

which are capable of measuring the chemical composition of individual particles, most

analytical methods require prior collection of the particles on a substrate. The main

objective of sampling is to collect sufficient amount of particulate matter from relatively

large volumes of air which can satisfy the demands of the analytical techniques. Reliable


19

sampling methods have long been established for atmospheric aerosol. They can be

basically classified into two broad classes, filter-based and impactor sampling. There is

actually no clear cut delineation between the two classes, because in filter-based sampling

the larger particles are eliminated by a pre-impaction stage.

1.5.1 PM Samplers

Since only particles with Dae


20

diameter circular filters (Figure 1.6).

The particulate matter concentration is obtained by weighting the filters before and

after the sampling, always after a storage period (48 hours) in a temperature and humidity

controlled room with ambient temperature = (20 1) °C, relative humidity = (50 5)%),

by an analytical balance (sensitivity: 1 g); electrostatic effects are avoided by the use of a

de-ionizing gun.

Filters to collect PM may be divided in two main classes:

- screen-filters: thin membranes that collect particles on their surface (pore size

defined);

- depth-filters: fibrous filter media that trap particles in their matrix (pore size not

defined).

The choice of the filter type has to be made considering both sampling properties and

suitability with measurements and compositional analysis methods, ensuring an optimal

possibility to measure its carbonaceous fraction too.

Filter Type Material Advantages Disadvantages

Depth ● Quartz fibres

● Glass fibres

● High retain capacity

● Can withstand high

temperatures

● Internal contamination

● Loss of fibres

● Can adsorb volatile

organic compounds

● Undefined porosity

Screen

● Poly-Carbonate

● PTFE

● Cellulose esters

● No release of filter material

● Well defined porosity

● High purity

● High impedance

● Can not withstand

high temperatures

Table 1.1: Different characteristics of the two types of filtering matrices.

To do this, the choice of the collection substrate is fundamental. Two kinds of filters

were chosen for their characteristics: Poly-tetra-fluoro-ethylene (PTFE) and quartz fiber

filters. The first one is a screen-filter composed by a PTFE ring supported thin membrane


21

with 2 m pore size, while the second is a depth-filter with a density around 6.5 mg · cm-2

.

PTFE filters have surface area several times smaller than that of quartz filters, and unlike

quartz, they are chemically inert. In Chapter 2 and 3, advantages and disadvantages of

these substrata for optical and thermo-optical analyses are discussed.

The sampling of carbonaceous PM is subjected to artifacts, in particular for the

organic part. These artifacts are generally classified by the sign of the error they cause

relative to the particulate phase concentrations. Thus, positive artifact (also known as

adsorption artifact), and negative artifact (also known as volatilization or evaporation

artifact) can be distinguished, causing over- and underestimation of particulate phase

concentration of organic carbon, and also of semi-volatile organic species, respectively.

There is another type of organic sampling artifact, namely the reaction artifact, which

results from the reaction of organic species on the filter substrate with reactive trace gases

and radicals passing through the filter. It can be either positive or negative, depending on

whether it produces less volatile or more volatile species, respectively. As a matter of fact,

these artifacts depend on the ambient temperatures.

The major artifact is, in general, the positive one. During short airborne sampling,

the magnitude of the positive artifact could be as high as a factor of 3-18, and in some

cases the amount of total carbon measured on single quartz fiber filters even exceeds the

total aerosol mass determined gravimetrically on PTFE filters [Novakov et al., 1997]. If,

however, blank filters were allowed to be in contact with ambient air for sufficient time to

establish equilibrium, preferably at the sampling site during sampling, this positive artifact

can be greatly reduced.

Chapter 2

The carbonaceous fraction of PM:

measurement techniques

2.1 Introduction

The carbonaceous aerosol is a major component of urban PM. The quantity of Total

Carbon present in the atmosphere is composed of Elemental Carbon (EC) and Organic

Carbon (OC) although a minor fraction of carbonate carbon could be also present.

Elemental carbon is mainly found in the finer PM fractions (PM2.5 and PM1, i.e.

Particulate Matter with aerodynamic diameter, Dae, smaller than 2.5 and 1 m,

respectively) and it is strongly light absorbing in the visible range. When determined by

optical methods, it is usually called black carbon (BC). It has only primary origin and is a

product of incomplete combustion of fossil fuels in transportation, heating, and power

generation, and of wood and biomass in residential heating, and agriculture activities. It is

ubiquitous in the fine aerosol particles and appears at measurable levels even in the most

remote locations [Putaud et al., 2004]. EC has been observed to comprise from 8% to 17%

Chapter 2: The carbonaceous fraction of PM: measurement techniques

23

of the atmospheric fine aerosol at European rural and urban background sites and kerbside

sites, respectively [Putaud et al., 2004]. These percentages are considered a problem

because EC has a role in adverse effects on human health [Adar and Kaufman, 2007;

Bèrubè et al., 2007]. However, the most abundant fraction in carbonaceous aerosol is OC

and it consists of thousands of chemical constituents belonging to many compound classes,

such as aromatics as alcohols alkanes, and it covers a wide range of molecular forms,

solubilities, reactivities and physical properties which make a complete characterization

extremely difficult. In many areas organic compounds represent the majority of particulate

matter [Jacobson et al, 2000] and a lot of organic species have recognised as biologically

toxic [Chow et al, 2007].

Carbonaceous particles have great importance at both local and global scale. In fact,

at the local scale they account for a large part of PM concentration and there is evidence

for a relationship between the presence of carbonaceous PM and cardiovascular disease

and mortality. Carbon interacts with light, removing it from a sight path and thus

influencing visibility. Carbonaceous particles, together with sulphates, are the main

responsible for the damage of monuments in urban area. The dark component of

carbonaceous aerosols (BC) plays a key role in surface soiling and black crust formation.

At the global scale carbonaceous particles influence the radiative budget of the Earth-

Atmosphere system in two different ways: they can scatter and adsorb solar and thermal

infrared radiation (direct effect), and they modify the microphysical proprieties of clouds

with effects on their interaction with the radiation and lifetimes (indirect effect, see

Chapter 1). Carbonaceous fraction can be of primary or secondary origin and they can

have either natural or anthropogenic origin. Primary carbonaceous particles of natural

origin are plants debris, spores, bacteria and wild fires in general, while primary

anthropogenic carbonaceous particles are mainly originated by incomplete combustion

processes. Secondary particles of natural origin are formed by biogenic VOCs-to-particle

conversion, while secondary anthropogenic carbonaceous particles are mainly originated

from oxidation due to hydroxyl radical, ozone and nitrate radical.

The two quantities, EC and BC, even if both related to the refractory components of

carbonaceous aerosols (see Chapter 1), do not exactly define the same PM component

[Bond and Bergstrom, 2006; and references therein]. In addition to the problem of the

definition between EC and OC, there are a number of different methods (based on thermal


24

or optical proprieties) used to quantify them. Result of test carried out on samples of

atmospheric aerosol show good agreement (better than 10%) for TC concentrations

obtained by different instruments and techniques, while discrepancies up to a factor 2 are

commonly found in the results of EC measurement carried out with different

methodologies (i.e. optical, thermal and others) [Schmid et al., 2001; Watson et al., 2005].

Further problems have to be ascribed to the absence of commonly accepted standards and

reference materials that can be used to quantify EC as it appears in the atmosphere [Chow

et al., 2001], thus it is impossible to characterize the EC thermal behaviour under different

thermal analysis conditions [Yu et al., 2002]. Several methodologies have been proposed

and used to measure the carbonaceous component of particulate matter; however, a

generally accepted reference method is still missing [Bond and Bergstrom, 2006].

2.2 Thermo-optical transmittance methods

Thermal-optical methods [Huntzicker et al., 1982; Chow et al., 1993] are presently

the most widespread approach to OC/EC speciation. Despite their popularity, there is still

a disagreement among the results, especially for what concerns EC [Chow et al., 2001;

Subramanian et al., 2006; Piazzalunga et al., 2011a] as different thermal protocols can be

currently used (CEN/TR 16243:2011). Thermal-optical methods necessarily require the

collection of PM on quartz fiber filters. These filters are not as performing as the PTFE or

polycarbonate membranes for elemental/chemical analyses (due to their thickness,

composition and internal contamination) so that, in campaigns where both EC/OC and

elements/ions concentration values are required, two parallel samplers collecting PM on

quartz fiber filters and on filters with low blank values are often necessary. Problems

induced by positive and negative artefacts can arise when comparing PM collected on

different media [Vecchi et al., 2009]. Finally, thermal-optical analyses are time and man-

power consuming and the portion of the sample under analysis gets destroyed.


25

2.2.1 The Sunset EC/OC Analyzer

The schematic of the Sunset EC/OC analyzer is showed in Figure 2.1. This is the

most widespread instrument to perform thermo-optical analysis of the carbonaceous

fraction in PM samples. The thermal analysis is based on the different evolution

characteristic of the two fractions as a function of the temperature and type of atmosphere

and on the quantification of the evolved CO2 at the thermal steps chosen for the separation.

Different approaches are reported in the literature for thermal analysis, but they can be

divided in two main categories:

Figure 2.1. Schematic of thermal-optical instrumentation. Gas stream selected by four-port switching

valve (V1). Pure He used during first stage of analysis; 02 (5%) - He mix used during second stage [Birch

and Cary, 1996].

a) OC separation in inert atmosphere (He) [Chow et al, 1993, Birch and Cary,

1996, Cavalli et al, 2010];

b) OC separation in Oxygen at low temperature (320-450°C) for different

combustion periods [Chachier et al, 1989, Kirchstetter et al, 2001, Watson et al, 2005 and

therein literature].

After the first step for OC separation, the remaining carbon is oxidized at 850 -

900°C and the carbon evolving during this second step is considered to be the EC fraction


26

(possibly corrected for measurement artifacts, as explained in the following). One of the

most widespread techniques for the thermal quantification of OC and EC fraction is the

Thermal-Optical Transmittance method (TOT) [Birch and Cary, 1996]. TOT analysis

consists of two main steps (Figure 2.2): in the first part of the analysis, the thermal

evolution is carried out in inert atmosphere and a pyrolysis of the material deposited on the

filter can occur. Pirolysis consists in the conversion of an organic compound into one or

more different compounds by thermal energy and it mainly occurs in inert environments

(lack of oxygen or presence of catalysts and above all for particular materials like tobacco

smoke, pollen, etc.). Carbonization occurs in extreme pyrolysis to form EC [Chow et al,

2007]. In this condition, pyrolysed OC (PyC) cannot evolve in the inert atmosphere

anymore, thus an underestimation of OC and an overestimation of EC are registered if the

separation of the two fractions is carried out only considering the atmosphere of evolution

without any correction. Pyrolysis leads to the variation of the optical proprieties of the

sample as PyC is light-adsorbing; thus, in the TOT analysis, the optical transmission of a

laser thought the filter is continuously monitored. Due to pyrolysis, the transmittance of the

filter decreases during the first part of the analysis (He atmosphere).

Figure 2.2: Example of a thermogram by TOT. The three traces correspond to temperature (T), filter

transmittance (Laser), and detector (FID) response. Peaks correspond to organic (OC), pyrolytic (PC), and

elemental (EC) carbon. The final peak is a methane calibration peak [Birch and Cary, 1996].


27

When oxygen is injected into the line, EC (both originally present on the filter and

derived from OC pyrolysis) evolves causing an increase of the laser transmission. When

the filter transmittance reaches the values registered at the beginning of the analysis, the

method assumes that a quantity of EC equal to the one formed by pyrolysis has combusted

and therefore all the carbon evolved up to this point has to be considered OC. All

remaining carbon is instead considered EC. It is noteworthy that this method does not

physically separate the two fractions, but it simply corrects the measured concentration

using EC optical proprieties. The whole analysis is carried out through a sequence of

thermal steps of different amplitude and width called “protocol”.

So far, IMPROVE and NIOSH have been the most widely thermal-optical protocols

used in the atmospheric science community. Traditionally, the IMPROVE protocol [Chow

et al., 1993] has been applied to samples from non-urban background sites in the US

IMPROVE network; in 2005, the IMPROVE network started to apply the IMPROVE A

protocol, an only slightly modified version of IMPROVE thanks to refined measures of the

sample temperature [Chow et al., 2007]. The EPA/NIOSH (or STN) protocol [Peterson and

Richards, 2002] has been applied to samples from urban sites in USA-EPA’s Speciation

Trends Network. These protocols differ in temperature set points – higher for EPA/NIOSH

(e.g. the highest temperature in He is 900 °C) than for IMPROVE (e.g. the highest

temperature in He is 550/580 °C) – and in the residence times at each temperature step –

typically longer for IMPROVE than for EPA/NIOSH. Moreover, the IMPROVE protocol

uses the reflectance method to correct for charring, while the EPA/NIOSH protocol has

adopted the transmittance method. Previous studies have demonstrated that such

differences might significantly alter the measured amounts of OC and EC [Chow et al.,

1993; Conny et al., 2003]. Since October 2009, the US urban network is also adopting the

IMPROVE A protocol, and consistent OC and EC measurements have been obtained

throughout the US urban and nonurban networks. In Europe, there is currently no standard

procedure for analysing the carbonaceous aerosol fraction, thus data from different

laboratories at various sites are of unknown accuracy and cannot be compared. Addressing

this issue is becoming more and more important as the EU Directive 2008/50/EC states

that “measurements shall be made, at rural background locations [. . . ] for the purposes of

providing, as a minimum, information on the total mass concentration and the chemical

speciation concentrations of fine particulate matter (PM2.5)”. The EU-project EUSAAR


28

(European Supersites for Atmospheric Aerosol Research, www.eusaar.net) integrates 20

high quality European regional background stations with the objective of harmonizing

aerosol measurements of interest to air quality and global climate through coordinated

protocols. In this framework many studies have been carried out to identify the causes of

differences in the EC measured using different thermal evolution protocols; thereby the

major positive and negative biases affecting thermal-optical analysis have been isolated

and minimised to define an optimised protocol, EUSAAR_2 [Cavalli et al, 2010], suitable

for European aerosols. Because EUSAAR_2 is the most used protocol in EU, in this work

EC and OC were measured with this protocol only.

2.3 Optical Methods

As already highlighted in §1.4 and §2.2, Carbon is one of the most abundant

constituents of ambient particulate matter and is either present as organic carbon (OC),

which is mainly volatile and/or reactive in a heated air stream, or as elemental carbon

(EC), which is non-volatile and non-reactive, or as carbonate. Mainly due to the presence

of EC, ambient particulate material appears black when collected on a filter. Therefore,

black carbon (BC) is defined as the most efficient light-absorbing aerosol species in the

visible spectral range [Rosen et al., 1978; Lindberg et al., 1993], and is generally measured

by determining the attenuation/absorption of light transmitted through a sample. Thus, the

measurement of aerosol light absorption babs in the visible spectral range is strongly

correlated to the measurement of BC. The relationship between babs and the corresponding

BC mass concentration CBC is established by an aerosol mass-specific absorption

coefficient abs via the relationship babs = CBC ∙ abs. However, there is a variety of abs

values reported in the literature [Horvath, 1993a; Fuller et al., 1999; Bond and Bergstrom,

2006]. The relationship between aerosol absorption and black carbon mass concentration is

therefore not unambiguous for different kinds of BC aerosol.

The refraction index of a population of particles depends on how the diffusing and

absorbent constituents are distributed within the particles. The term external mixture

implies a heterogeneous population of homogeneous particles (Figure 2.3a).


29

Figure 2.3: Representation of various mixtures of absorbing and scattering particles (a) External mixture

(b) Volume averaged mixture (c) Heterogeneous particle composition and population (from Bond and

Bergstrom, 2006).

The term internal mixture is used loosely to define two very different situations.

The simplest case is the volume mixture (Figure 2.3b) in which the different components

of the particles are distributed homogeneously within their volume. In the other type of

internal mixture (Figure 2.3c), the particles are formed by a "core" of a chemical species

(for example: black carbon) coated by a "shell" formed by another chemical species (for

example: salt, which is a typical diffusing material) [Hitzenberger, 1993, Bond &

Bergstrom, 2006]. It is worthy to note that in the case of “encapsulated” particles,

concentricity is only a possibility.

Absorption calculated for a set of particles depends very much on how absorbing

and scattering components are mixed together [Ackerman and Toon, 1981; Chylek and

Hallett, 1992; Chylek et al., 1995; Haywood and Ramaswamy, 1998; Jacobson 2000]. The

refractive index of the population of particles thus depends on the type of mixing; in

general, with external mixture, the absorbent particles only absorb the radiation, while in

the case of internal mixture, all the particles contribute to the absorption of radiation. When

particles are emitted into the atmosphere, the degree of particle mixing varies over time,

thus making optically different “fresh” and “aged” particulate. The “aging” of the

particulate matter is very difficult to assess and is one of the main parameters influencing

the value of the aerosol mass-specific absorption coefficient, abs, as explained in more

detail in §2.3.2.

A possible and frequently used approach for aerosol extinction/absorption

measurement is the collection of aerosol particles on a fibre filter matrix and the analysis

of the sampled aerosol by optical means. The advantage of these methods is sampling over

a long period of time in order to improve the limit of detectable absorption coefficients

well below 10−6

m−1

[Petzold and Schönlinner, 2004]. Two different instrumental set-ups


30

are presently in use, both of which rely on the modification of the optical properties of a

fibre filter matrix by deposited particles: filter transmission measurements and filter

reflectance measurements.

Table 2.1: Direct methods of measuring absorption by particles (from Bond and Bergstrom, 2006).

In Table 2.1, the most diffused methods of measuring absorption by particles are

quoted [Bond and Bergstrom, 2006]. The Aethalometer [Hansen et al., 1984] and the laser

transmission method [Rosen et al., 1983], as well as the Particle Soot Absorption

Photometer, PSAP [Bond et al., 1999], measure the light transmission through a quartz

fibre filter tape while Reflectometer methods [e.g., Bailey and Clayton, 1982] measure the

light reflectance of a filter. Integrating plate methods [Clarke et al., 1987; Hitzenberger,

1993; Horvath, 1997] also use a transmission measurement set-up, but adopting membrane

filters for the particle sampling. These techniques (so-called "integrative"), as the methods

of the integrating plate (IPM), sandwich and sphere, collect or integrate the diffused light

and assume that light reduction is only due to absorption. The integrating sphere, whose

inner surface is covered with a diffusive material with high reflectivity, is a simple device

used to spatially integrate the flow of the radiation that enters it. This method is more


31

precise than the integrating plate since it eliminates the disadvantage of the loss of the

scattered radiation.

In general, these techniques are affected by several kinds of uncertainties. At first,

aerosol scattering affects transmitted light despite of the instrumental design [Hitzenberger,

1993; Horvath, 1993b; Petzold, Kopp and Niessner, 1997; Bond et al., 1999]. Also,

absorption by particles collected on a filter is increased because multiple scattering by the

filter allows more than one chance for a photon to be absorbed [Bond et al., 1999; Arnott et

al., 2005]. In recent years, a new instrument that takes into account both filter transmission

and reflectance has been developed: the Multi-Angle Absorption Photometer (MAAP)

[Petzold and Schönlinner, 2004] (see §2.3.2). Actually, BC concentration data can be

presently provided by three commercial equipment only: the MAAP, the PSAP and the

Aethalometer. While the MAAP, through the measurement of both transmitted and

scattered (at three different angles) light, directly deduces the sample absorbance and

hence the BC via a radiative transfer scheme [Hänel, 1987 and 1994], the other two

instruments require ad hoc corrections even if the MAAP approach too is not completely

bias free [Slowik et al., 2007]. In particular, the Aethalometer measures the attenuation at

several wavelengths ( = 370 – 950 nm) through the PM continuously deposited on a glass

fiber filter tape. The working principle of the PSAP is similar to the Aethalometer: the light

transmission is continuously measured through a quartz fibre substrate at a wavelength

of 550 nm, but the PSAP does not perform automatic filter changes. In the last 20 years,

these three instruments have been employed for massively measurements of BC; in this

work of thesis the most recent MAAP was employed for comparison and calibration of the

new instrument that will be discuss in Chapter 3. In the next paragraphs I will introduce the

basic theory and the principle of operation of these two instruments.

2.3.1 The Aethalometer

Among all available optical absorption or light attenuation methods, the

Aethalometer, as described by [Hansen et al., 1984], is the most frequently used technique

to measure real-time BC mass concentrations. The classic Aethalometers (AE9 and AE10,

MAGEE Scientific; Berkeley, USA) work with an incandescent lamp and broadband


32

detectors. Hundreds of these instruments are installed worldwide, and some have been in

continuous operation for over a decade. In the last years, new Aethalometers (e.g. the two-

λ AE-42, Figure 2.4) have been developed operating with several light sources with

narrow bandwidths ranging from the near ultraviolet to the near infrared. The multi-

wavelength analysis was implemented to gather information about different components of

the carbonaceous fraction, particularly organics; more details about this possibility are

discussed in § 4.2.1. In the next part the basic theory and the principle of operation of this

instrument is briefly discussed.

Figure 2.4: The portable model AE-42 Aethalometer.

The attenuation coefficient (batn) is defined with Beer-Lambert’s law:

where I0 is the intensity of the incoming light and I the remaining light intensity after

passing through a medium with thickness x. The attenuation (ATN) is typically given as

percentage values and is defined by the relationship:

( )

The Aethalometer measure the light attenuation through a quartz filter matrix where the

fibre filter is assumed to act as a perfect diffuse scattering matrix in which the light-


33

absorbing particles are embedded. Two detectors monitor the light transmission through

the filter; one measures the light passing through the particle-loaded sample spot while the

other measures the light passing through the particle-free reference part of the filter. This is

done to correct for variations in incident light intensity and drift in electronics.

During operation, for the first detector from time t to time t + t the column of

aerosol-laden sample air will deposit particles to the filter, resulting in an increase of ATN.

According to the Beer-Lambert’s law (Eq. (1)), the aerosol attenuation coefficient of the

filtered aerosol particles bATN is defined as:

where A is the area of the sample spot to which particles are deposited, Q the

volumetric flow rate and ATN is the change in attenuation during the time interval t. BC

mass concentration can be obtained by the equation:

In the words of the manufacturer, ATN is the “specific attenuation cross-section for

the particle black carbon deposit on this filter, using the optical components of this

instrument, [m2 g

-1]”. The factory default value for this parameter is empirically set by the

manufacturer and is expressed as:

It is well known that bATN may differ significantly from the true aerosol absorption

coefficient babs of airborne particles. This is because an aerosol not only absorbs light but

generally, to an even higher extent, scatters light. This produces significant uncertainties in

the assessment of BC concentrations.

As a matter of fact several algorithms have been proposed to correct the


34

Aethalometer data, taking into account the diffusive component of PM collected on filters,

the filter-matrix effect and the filter loading [Weingartner et al., 2003; Arnott et al., 2006;

Schmid et al., 2006; Virkkula et al., 2007, Collaud Coen et al., 2010]. In these works

generally two calibration factors (C and R(ATN)) are introduced, which can be used to

convert Aethalometer attenuation measurements to “real” absorption coefficients:

where C and R(ATN) describe the two effects which change the optical properties of filter

embedded particles with respect to the properties of the same particles in the airborne state.

The first effect is responsible for C being greater than unity and is caused by multiple

scattering of the light beam at the filter fibres in the unloaded filter. This leads to an

enhancement of the optical path and thus to enhanced light absorption of the deposited

particles [Liousse et al., 1993]. Any other effects that are caused by deposited particles are

described by the empirical function R(ATN) which varies with (a) the amount of aerosol

particles embedded in the filter and (b) optical properties of the deposited particles. For

unloaded filters R is set to unity, i.e. R(ATN = 0) = 1. With the gradual increase in

attenuation due to the accumulating particles in the filter the absorbing particles absorb a

higher fraction of the scattered light which leads to a reduction of the optical path in the

filter (R < 1). As a consequence, generally lower attenuation coefficients are measured for

higher filter loadings than for lightly loaded filters. This effect is named shadowing effect.

One has to mention that this term is a somewhat misleading description as submicrometer

particles do not visibly cast shadows. If light scattering particles are embedded in the filter

matrix, the shadowing effect may be partially reduced and R may exhibit a smaller

decrease with increasing loading of the filter. This phenomenon is due to additional light

scattering arising from the transparent aerosol material. R will thus also depend on the

single scattering albedo ω0 of the sampled aerosol, which is defined as:


35

where bs and be are the aerosol light scattering and extinction coefficients, respectively. For

the derivation of babs, the exact knowledge of the empirical calibration values C and R is of

course of great importance. The evaluation of these two values is, in general, site

depending and requires the knowledge of other parameters like the scattering properties of

the aerosol (e.g. by Nephelometer measures) and the aging of the particles, both very

difficult to produce/evaluate. Without these corrections, the Aethalometer approach is quite

reliable only for thin aerosol layers with a high black carbon mass fraction (> 10%) and a

low scattering coefficient of the particles (∼ 1000 cm−1). These conditions are usually met

for samples of an urban aerosol, but they are no longer valid for background aerosols

[Petzold and Schölinner, 2004].

It is important to remember that, in addition to the problem of evaluating babs, all

optical methods convert light absorption/attenuation using conversion coefficients (i.e.

mass absorption cross section, abs [Bond and Bergstrom, 2006] that can bias BC values

and could need an in-situ calibration [Jeong et al., 2004].

2.3.2 The Multi-Angle Absorption Photometer (MAAP)

Fibre filter-based methods show a cross-sensitivity to particle-related scattering

effects and multiple scattering effects caused by the filter fibres [e.g., Liousse, Cachier, &

Jennings, 1993; Petzold, Kopp, & Niessner, 1997]. An inadequate treatment of these

effects may result in an incorrect absorption coefficient (babs) measurement.

In this work of Thesis, a Multi-Angle Absorption Photometer (MAAP) model 5012

by Thermo Scientific was used (Figure 2.5). This instrument can provide high temporal

resolution BC data measuring the light absorption (λ = 670 nm) of particles sampled on a

quartz filter tape and converting it to BC concentration by the relationship BC = babs · abs

(the aerosol mass cross-section is set by the manufacturer at 6.6 m2 g

-1). The MAAP is

based on a simultaneous measurement of radiation penetrating through and scattered back

from a particle-loaded fiber filter.

A detailed description of the method is given by [Petzold and Schönlinner, 2002

and 2004].


36

Figure 2.5: The Multi-Angle Absorption Photometer, model 5012 by Thermo Scientific.

Figure 2.6: Schematic of the Multi-angle photometry. Top: schematic set up for attenuation and

reflectivity measurements compared to the multi-angle photometer set up. Bottom: layout of the MAAP

sensor unit.

Figure 2.6 top shows the differences in the case of simply attenuation, reflectance

and multi-angle photometry set-ups. The arrangement of the light source and the detectors

in the MAAP optical sensor unit is showed in Figure 2.6 bottom. The physical background

of the arrangement of detectors can be briefly summarized as follows:


37

The measurement of the angular distribution of light scattered back and penetrated

through a particle-loaded fiber filter showed that the radiation that has penetrated through

the filter is completely diffuse and can be parameterized by a cos(θ) relationship, with θ

being the scattering angle relative to the incident radiation.

The back-scattered radiation contains a diffusely scattered fraction proportional to

cos(θ − π), and a fraction that is parameterized best by a Gauss law proportional to

, with ρ being a measure for the surface roughness of the aerosol

layer deposited on the filter. The Gaussian-distributed fraction of the back-scattered

radiation can be taken as radiation “reflected” from a rough surface. The partitioning of

back-scattered radiation between diffuse and Gaussian type depends on the sampled

aerosol. The measurement of the radiation penetrating through the filter at the scattering

angle θ = 0°, and the simultaneous measurement of the radiation scattered back from the

filter at two detection angles θ =130°, and 165°, permits the full determination of the

irradiances in the forward and back hemisphere relative to the incident light beam. The

exact position of the detection angles was chosen such that the partitioning between diffuse

and Gaussian types can be determined with highest resolution. In MAAP, the

determination of the aerosol absorption coefficient babs of the deposited aerosol uses

radiative transfer techniques. The particle-loaded filter is treated as a two-layer system: the

aerosol-loaded layer of the filter and the particle-free filter matrix. Radiative processes

inside the layer of deposited aerosol and between this layer and the particle-free filter

matrix are taken separately into account.

In this approach, originally developed by [Hänel, 1987] and modified for this

purpose by [Petzold and Schönlinner, 2004], multiple reflections between the aerosol-

loaded filter layer and the particle-free filter matrix are treated by the adding method [Van

de Hulst, 1980]. Starting from quantities directly measurable, the model resolution gives

the two parameters needed to calculate the absorbance ABS (fraction of light absorbed in a

filter sample):

where is the single scattering albedo (7) and is the total optical depth of the particle-

loaded aerosol-filter layer. The babs is therefore calculated by the equation (9):


38

where A is the area of the sample spot to which particles are deposited, Q the volumetric

flow rate.

The figure abs = 6.6 m2 g

-1 has been set by the MAAP manufacturer after some

comparisons between MAAP absorption data and EC values provided by a BC-sensitive

thermal technique, with artificial and ambient aerosol samples [Petzold and Schönlinner,

2004]. However, many works report abs values ranging between 4 m2 g

-1 and 25 m

2 g

-1 at

λ ≈ 650 nm [Bond and Bergstrom, 2006; and references therein; Reche et al., 2011]. This

large variety of abs values suggests that the aerosol mass cross-section depend on the

composition and the aging of the particles, as already highlighted in §2.3. For this reason,

it is important to note that in general terms “absorption can not be a proxy for light-

absorbing carbon mass” [Bond and Bergstrom, 2006]. The assumption that there is a

constant ratio between absorption and BC concentration is only valid when the particles to

be measured have the same optical properties of the particle used to determine this ratio.

2.3.3 Other measurement techniques

In the recent years, other measurement techniques have been developed to provide

BC concentration values using different principles. Two instruments measure a change in

temperature resulting from an absorption of light and redistribution of energy. The photo-

acoustic method [Terhune and Anderson, 1977; Foot, 1979; Adams et al., 1988; Arnott et

al., 1997] and a calorimetric approach [Hänel and Hildebrant, 1989]. In particular, the

photo-acoustic method exploits the absorption of light and the consequent change in

pressure. The instruments that take advantage of these physical principles are in general

more complicated than filter-based instruments [Moosmuller et al. 1998] and have, in

general, higher detection limits. In the last years, some improvements have allowed these

instruments to measure absorption at ambient concentrations. In any case, the particulate is

not collected, so that these instruments do not produce samples to analyse with other

techniques.


39

Another possibility to obtain information on the carbonaceous fraction is with the

PESA (Particle Elastic Scattering Analysis). PESA is an extension of the classical

Rutherford backscattering analysis. It gives quantitative information about the composition

of the sample measuring the number and the energy distribution of the incident ions

elastically scattered from the target nuclei [Chu et al., 1978] and it has been proven to be

successful with Teflon filters [Chiari et al., 2005] to measure the total C concentration in

the PM.

A different approach to obtain the PM speciation is the AMS (Aerosol Mass

Spectrometry), in which diluted aerosol is first ionized and then analyzed by means of

mass spectrometry. With this technique, information about organic fraction components

can be also achieved. This technique, like PESA too, is very complicated and expensive;

for these reasons, their availability is limited to a few sites in the world.

Chapter 3

The Multi-Wavelength Absorbance

Analyzer

3.1 Introduction

As highlighted in the previous chapter, the measurement of the aerosol absorption

coefficient is a complicated issue. On the other hand, the knowledge of this parameter is

extremely important to study the atmospheric aerosol optical properties and fundamental

for the quantification of BC.

Starting from the measurement of aerosol attenuation/absorption coefficient, BC

concentration data with high time resolution can be provided by several equipments like

the MAAP (§2.3.2), the PSAP (§2.3), and the Aethalometer (§2.3.1). While the MAAP,

through the measurement of both transmitted and scattered (at three different angles) light,

takes into account the multiple scattering and deduces the sample absorbance and hence

the BC via a radiative transfer scheme [Hänel, 1987 and 1994], the other two instruments

require ad hoc corrections, even if the MAAP approach too is not completely bias free

Chapter 3: The Multi-Wavelength Absorbance Analyzer

41

[Slowik et al., 2007; Hyvärinen et al., 2012]. Moreover, the MAAP measures babs at one

wavelength (λ = 670 nm) only, hence excluding the possibility to obtain information on

the Ångström exponent and the different components of the carbonaceous fraction of PM

(see §4.2.1). On the other hand, the most widespread Aethalometer measures the

attenuation at several wavelengths (λ = 370 – 950 nm) through the PM continuously

deposited on a glass fibre filter tape. Many correction algorithms has been proposed in the

last decade to convert attenuation to absorption [Weingartner et al., 2003; Arnott et al.,

2006; Schmid et al., 2006; Virkkula et al., 2007, Collaud Coen et al., 2010]. The

application of these algorithms to attenuation data is, in general, very critical: they take

into account the diffusive component of PM collected on filters, the filter-matrix effect and

the filter loading. These corrections are site depending and require the knowledge of other

parameters like scattering properties of the aerosol (e.g. by Nephelometer measurements)

and the aging of the particles, both information very difficult to produce/obtain.

An optical off-line approach to BC determination, developed for samples collected

on PTFE filters, was introduced in the IMPROVE network in the USA and discussed in

several papers [Bond et al., 1999; Campbell et al., 1995; Neiedly et al., 2003]. Actually,

the former approach of [Hänel, 1994] with a polar photometer was also adopted with PM

collected on polycarbonate membranes [see also Kopp et al., 1999].

PM samples are routinely collected in urban areas to monitor PM10 and/or PM2.5

concentration. Low volume sequential samplers are often equipped with 47 mm diameter

quartz fibre filters and operated on daily basis (for more details, see §1.5.1). The filters are

then gravimetric analyzed to determine the PM concentration and, in some cases, analyses

for chemical characterisation are also carried out. Although less used because more

expensive, PTFE filters are very stable during gravimetric analysis and they are also very

clean and thin and therefore they are appropriate for compositional studies by X-ray

Fluorescence [Marcazzan et al., 2004; Ariola et al., 2006; Mazzei et al., 2008] and/or by

Ion Beam Analysis [Chiari et al., 2005]. They are also suitable for obtaining the ion

concentration by ion-chromatography [Chow and Watson, 1999, Marenco et al., 2006;

Piazzalunga et al., 2012].

The principal aim of this work is the realization and calibration of a new instrument,

able to solve the lack of information underlined above and to improve the knowledge of

the carbonaceous fraction through an optical measurement, easily performed, with PM


42

collected on filters routinely sampled worldwide for regulatory purposes. I have therefore

designed and built a fully automatic, multi-wavelength and not-destructive optical system

to measure off-line the light absorption of PM and to obtain, without any sizeable extra-

cost, the absorption properties of particles collected on a filter (in the following I refer to

this new instrument as MWAA: Multi Wavelength Absorbance Analyzer). My system

provides an off-line information but, considering the limited analysis time (≈ 10 minute

per sample), it can be used in the frame of campaigns with several sampling sites with the

possibility to analyze tens of filters per day. Moreover, the multi-wavelength analysis

gives the possibility to apportion the contributions of different sources of carbonaceous

PM (e.g. fossil fuels and wood combustion, see Chapter 4) improving previous approaches

to the same problem [Sandradewi et al., 2008; Favez et al., 2010]. This is an important

piece of information when using receptor models [Gordon, 1988] to identify the sources of

PM and/or gaseous pollutants, their emission profile and loading. A complete knowledge

of the composition of PM samples collected on daily or hourly basis is a major issue for all

the receptor models currently in use. Several PM sources, mainly in urban areas, can emit

OC and EC/BC (traffic, heavy oil and coal combustion, industries, biomass burning, etc)

together with other chemical markers. The analysis of not-standard samples collected with

peculiar devices (e.g. multi stage cascade impactor and two-stage continuous streaker

sampler) is also feasible with the MWAA and will be discussed in §3.8.

First, the theory behind the MWWA will be described briefly in the next paragraph.

Then, the development and design of a new optical set-up will be reported. In the last part

of this chapter calibration and sensitivity tests will be presented.

3.2 The radiative transfer theory

The radiative transfer theory was introduced by Hänel in 1987. This theory was

originally developed for aerosol samples in which the system "particles + filter" can be

considered as a system of well distinct two layers: the first consisting only of particles

deposited on filter ("aerosol-filter layer"), and the second consisting only of the matrix of

the filter ("particle-free filter matrix"). This condition is verified in the case of a screen-

filter (§1.5.1), where the particles are collected only on its surface. In [Petzold and


43

Schönlinner, 2004], this approach was successfully extended to depth filters as in quartz

fibre filters: particles are embedded in a diffusely scattering environment of quartz or glass

fibres which, however, do not contribute to light absorption because they are transparent in

the visible spectral region [Bohren and Huffman, 1983]. In this case the condition of two

well distinct layers is not completely true, since particles are partially collected on the

surface of the filter and in part deposited within the filter matrix, thus penetrating a certain

thickness. Nevertheless it is possible to make the approximation of the two-layer system

also in this case: observing with an electron microscope a cross section of a loaded glass

fibre filter, it is clear that the layer of filter matrix in which particles are deposited

constitutes only 10-15% of the total thickness of the filter (Figure 3.1). The transition

region between particle-loaded filter layer and particle-free matrix extends over less than

5% of the particle-loaded layer. Hence, the microscopy analysis of loaded fibre filter cross-

sections supports the assumption of a two layer model.

Figure 3.1: Cross section of a loaded glass fibre filter (left) and scheme of the two layers system, aerosol-

filter layer and fibre filter matrix (right) [Petzold and Schönlinner, 2004].

The discussion of radiative processes which are relevant in this system has to treat

two different processes:

1. The radiative interactions within the aerosol-filter layer which depend on the

optical properties of the layer, i.e., optical thickness, single scattering albedo,

and angular distribution of scattered radiation. These interactions are described

by the two-stream approximation, developed by [Coakley and Chýlek in 1975].


44

2. The radiative interactions between the particle-loaded aerosol-filter layer and

the particle-free filter matrix, described by the adding method [Van de Hulst,

1980]. The radiative interactions within the particle-free filter matrix are not

considered because the optical properties of this layer are not affected by

deposited particles and remain therefore unchanged from particle-free to

particle-loaded filter samples.

In the MAAP set-up, the perpendicularly incident radiation is collimated. The

radiation passing through the aerosol-filter layer is mostly diffuse because of multiple

scattering processes, with only a small fraction remaining collimated. The radiation

impinging on the particle-free filter matrix is thus partly collimated (transmitted through

the aerosol-filter layer) and partly diffuse (scattered forward by the aerosol-filter layer).

The radiation scattered back from the aerosol-filter layer as well as from the filter matrix

toward the aerosol-filter layer is regarded as diffuse.

Measurable radiative properties of the particle-loaded filter are the transmitted plus

forward scattered and the back scattered radiation. These properties are described in terms

of energy budget equations for the particle-loaded filter, the aerosol-filter layer alone, and

the blank filter alone [Hänel, 1987]. The optical properties of the various layers are

described as the fractions of forward scattered, back scattered, and transmitted radiation

(the light transmitted in the same direction of the incident light) by the dimensionless

parameters F, B, and T, respectively. Other dimensionless parameters that have to be

considered are the absorbance A (fraction of absorbed lig

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