Atmospheric Aerosols E-Book
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- Herausgeber: Wiley-VCH Verlag GmbH & Co. KGaA
- Kategorie: Wissenschaft und neue Technologien
- Serie: Wiley Series in Atmospheric Physics and Remote Sensing
- Sprache: Englisch
The book describes the morphological, physical and chemical properties of aerosols from various natural and anthropogenic sources to help the reader better understand the direct role of aerosol particles in scattering and absorbing short- and long-wave radiation.
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Veröffentlichungsjahr: 2016
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Table of Contents
Wiley Series in Atmospheric Physics and Remote Sensing
Title Page
Copyright
List of Contributors
Preface
Foreword
Acknowledgments
Chapter 1: Primary and Secondary Sources of Atmospheric Aerosol
1.1 Introduction
1.2 A General Classification of Aerosol Sources
1.3 Primary Aerosols of Natural Origin
1.4 Secondary Aerosols of Natural Origin
1.5 Primary Anthropogenic Aerosols
1.6 Secondary Anthropogenic Aerosols
1.7 Concluding Remarks on the Global Annual Emission Fluxes of Natural and Anthropogenic Aerosol Mass
Abbreviations
List of Symbols
References
Chapter 2: Aerosol Nucleation in the Terrestrial Atmosphere
2.1 Introduction
2.2 Theoretical Basis of Nucleation and Growth of New Particles in the Atmosphere
2.3 Observation and Detection Tools
2.4 Precursor Candidates for Nucleation and Early Growth from Observations
2.5 Parameterizations and Chamber Experiments
2.6 Importance of Nucleation for the Production of Aerosols and CCN at the Global Scale
2.7 Conclusions
Abbreviations
List of Symbols
References
Chapter 3: Coagulation, Condensation, Dry and Wet Deposition, and Cloud Droplet Formation in the Atmospheric Aerosol Life Cycle
3.1 Introduction
3.2 Physical Growth Processes
3.3 Aerosol Removal Processes
3.4 Formation of Cloud Particles
3.5 Concluding Remarks
Abbreviations
List of Symbols
References
Chapter 4: Chemical Composition of Aerosols of Different Origin
4.1 Introduction
4.2 Global Distribution and Climatology of the Main Aerosol Chemical Constituents
4.3 Size Distributions of Aerosol Chemical Compounds
4.4 Issues Related to Aerosol Chemical Composition
Abbreviations
List of Symbols
References
Chapter 5: Aerosol Optics
5.1 Introduction
5.2 Absorption
5.3 Scattering
5.4 Polarization
5.5 Extinction
5.6 Radiative Transfer
5.7 Image Transfer
Abbreviations
List of Symbols
References
Chapter 6: Aerosol Models
6.1 Introduction
6.2 Modeling of the Optical and Microphysical Characteristics of Atmospheric Aerosol
6.3 General Remarks on the Aerosol Particle Number, Surface, and Volume Size-Distribution Functions
6.4 Size-Distribution Characteristics of Various Aerosol Types
6.5 Concluding Remarks
Abbreviations
List of Symbols
References
Chapter 7: Remote Sensing of Atmospheric Aerosol
7.1 Introduction
7.2 Ground-Based Aerosol Remote Sensing Measurements
7.3 Airborne Remote Sensing Measurements of Aerosol Optical Properties
7.4 Satellite-Borne Aerosol Remote Sensing Measurements
Abbreviations
List of Symbols
References
Chapter 8: Aerosol and Climate Change: Direct and Indirect Aerosol Effects on Climate
8.1 Introduction
8.2 The Instantaneous DARF Effects at the ToA and BoA Levels and in the Atmosphere
8.3 The Diurnally Average DARF Induced by Various Aerosol Types over Ocean and Land Surfaces
8.4 Variations of DARF Efficiency as a Function of Aerosol Single Scattering Albedo
8.5 Concluding Remarks on the DARF Effects over the Global Scale
8.6 On the Indirect Aerosol Effects Acting in the Earth's Climate System
Abbreviations
List of Symbols
References
Chapter 9: Aerosol and Air Quality
9.1 Introduction
9.2 Aerosol Load as Derived from Satellite-Based Measurements
9.3 Characterization of Mass Concentration and Optical Properties of Desert Dust in Different Areas of the Earth
Abbreviations
List of Symbols
References
Chapter 10: Impact of the Airborne Particulate Matter onthe Human Health
10.1 Introduction
10.2 Epidemiological Evidences
10.3 Toxicological Evidences
10.4 Mechanism of Effects
10.5 Conclusions
Abbreviations
List of Symbols
References
Chapter 11: Aerosol Impact on Cultural Heritage: Deterioration Processes and Strategies for Preventive Conservation
11.1 Introduction
11.2 Monitoring for Cultural Heritage Conservation
11.3 Damage and Black Crusts Formation on Building Materials
11.4 Bioaerosol Effects on Cultural Heritage
11.5 Guidelines for the Preventive Conservation of Cultural Heritage in Urban Areas
Abbreviations
List of Symbols
References
Index
End User License Agreement
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Guide
Cover
Table of Contents
Preface
Foreword
Begin Reading
List of Illustrations
Chapter 1: Primary and Secondary Sources of Atmospheric Aerosol
Figure 1.1 Schematic representation of an aerosol particle for dry air conditions (left) and humid air (for relative humidity (RH) = 75–80%) conditions (right), consisting of particulate matter pieces of soluble (i.e., soluble acid substances, sea-salt crystal, ammonium sulfates) and insoluble substances (carbonaceous matter, mineral dust, organic substances), which remain suspended inside the moist particle gradually growing by condensation until becoming a water droplet with soluble salts, acids, and organic compounds. (Adapted from a draft presented by Gottfried Hänel in a seminar given in 1985 at the FISBAT-CNR Institute, Bologna, Italy.)
Figure 1.2 Size range of aerosol particles in the atmosphere and their role in atmospheric physics and chemistry.
Figure 1.3 Schematic sequence of the various phases through which the film droplets and jet drops are produced when an air bubble bursts at the sea surface: (a) the air bubble is coming to sea surface; (b) the air bubble reaches the surface; (c) the sea water film starts to break; (d) droplets of ∼5–30 µm diameter form when the upper portion of the bubble film bursts; (e) film droplets start to evaporate leaving sea-salt particles and other materials in the air; and (f) when the bubble bursts, 1–5 large drops (of sizes equal to about 15% the air bubble diameter) break away from the jet formed during the bubble burst. The time between phases (c) and (f) is ∼2 ms.
Figure 1.4 SEM images of sea-salt and other maritime particles: (a) particles sampled off the shore of Sardinia (Italy); (b) aggregates of sea-salt (halite) particles and numerous small sea-salt crystals of about 1 µm sizes, with a large-size (∼4 µm) particle on the left, containing sea-salt crystals and mineral dust, and a large-size (∼4 µm) particle on the right, consisting of various sea-salt crystals; (c) sea-salt and anthropogenic particles sampled off the shore of Malta (Mediterranean Sea), including some sea-salt crystals of cubic shape and a larger irregular-shaped particle (on the right) formed by aggregation of marine particles, together with a large-size spherical particle (having a diameter of ∼14 µm) in the middle, presumably due to coal combustion (from the intense ship traffic in the Sicily Channel, near Malta); and (d) several submicron sea-salt cubic crystals sampled near the island of Malta. (Reproduced with permission of Alessandra Bonazza, ISAC-CNR Institute, Bologna, Italy.)
Figure 1.5 Schematic representation of the saltation mechanism through which sand particles are mobilized by wind: a large particle (a) is lifted by wind and then lands on the ground (b), creating a burst of smaller dust particles (c).
Figure 1.6 Schematic picture of the mineral dust particle mass size distributions generated in different ground sands, characterized by multimodal features associated with the various mobilization processes. (Adapted from a graph of Junge (1979).)
Figure 1.7 Scanning electron microscopy (SEM) images of mineral (aeolian) dust particles consisting of (a) quartz, (b) dolomite, (c) kaolinite, (d) palygorskite of Saharan origin, (e) smectite, (f) illite, and (g), and (h) gypsum (calcium sulfate dihydrate) in both cases. (Reproduced with the permission from Emanuela Molinaroli, Ca' Foscari University, Dept. of Environmental Sciences, Venice, Italy.)
Figure 1.8 SEM images of aerodiffuse biological particles sampled at rural sites of the Po Valley (northern Italy): (a) pollen of
Ambrosia
sp. (Po Valley), (b) pollen of Convolvulaceae sp. (Po Valley), (c) pollen of Asteraceae (Helian.) (Po Valley), (d) pollen of
Castanea sativa
sp. (Po Valley), (e) pollen of Liliaceae sp. (Po Valley), and (f) fungus spore of
Ustilago
sp. (Po Valley). (Reproduced with the permission from Paolo Mandrioli, ISAC-CNR Institute, Bologna, Italy.).
Figure 1.9 Upper part: time patterns of the daily mean values of aerosol optical thickness τ
a
(λ) measured by us at the 380 nm (solid circles), 500 nm (solid squares), and 875 nm (solid triangles) wavelengths (Tomasi, Vitale, and Tarozzi, 1997) at the Pyramid Laboratory (5050 m a.m.s.l.) in Nepal, during summer 1991 (left-hand side) and summer 1992 (right-hand side), and of the monthly mean values of τ
a
(λ) measured by Pueschel
et al
. (1993) at the Mauna Loa Observatory (Hawaii) in July and September 1991 (left-hand side) and in July and August 1992 (right-hand side) at the 382 nm (open circles), 451 nm (open down triangles), 528 nm (open squares), 865 nm (open up triangles), and 1060 nm (open diamonds) wavelengths. Middle part: time patterns of the daily mean values of Ångström's (1964) exponent α (solid circles) and atmospheric turbidity parameter β (open circles), determined at the Pyramid Laboratory during summer 1991 (left-hand side) and summer 1992 (right-hand side) and compared with the monthly mean values of α and β (open triangles) determined by Pueschel
et al
. (1993) in July and September 1991 at the Mauna Loa Observatory. Lower part: time patterns of the daily mean values of the Pinatubo aerosol mass loading
M
s
, as determined by us from the spectral values of τ
a
(λ) measured during summer 1991 and summer 1992, in terms of variable linear combinations of background aerosol model and bimodal extinction model defined by Pueschel
et al
. (1993) for volcanic particles a few months old (summer 1991) and the trimodal model of Pueschel
et al
. (1993) for an aged population of Pinatubo particles (summer 1992).
Figure 1.10 Pathways of particle formation during the combustion of pulverized coal through different combinations of swelling, shrinking, fragmentation, vaporization, condensation, nucleation, coagulation, expansion, quenching, and disintegration processes. (Adapted from a graph of Okazaki (1993).)
Figure 1.11 SEM images of industrial aerosol particles: (a, b) particles formed from fuel oil combustion, (c) soot particles from coal combustion, (d) particle from distilled oil fuel combustion, and (e) atmospheric diesel soot particles. ((a)–(d) Reproduced with permission and courtesy of Cristina Sabbioni, ISAC-CNR Institute, Bologna, Italy. (e) Reproduced with permission and courtesy of Annie Gaudichet (LISA, Paris, France) and Hélène Cachier.)
Chapter 2: Aerosol Nucleation in the Terrestrial Atmosphere
Figure 2.1 Schematic representation of nucleation, growth, and activation of aerosol particles.
Figure 2.2 Pure water homogeneous nucleation computations for different saturation ratios (
T
= 293 K).
Figure 2.3 Evolution of the formation rate
J
as a function of the relative humidity and the sulfuric acid concentration at 250 K.
Figure 2.4 Growth rate simulation due to sulfuric acid condensation (10
+8
molecules cm
−3
) on a neutral seed. The difference between Nieminen and Gopalakrishnan and Hogan approaches in the kinetic regime is due to the fact Gopalakrishnan and Hogan consider the vapor as a punctual point and that the seed particle is nonmobile while the Nieminen approach accounts for the seed motion and the vapor properties.
Figure 2.5 Example of growth simulation made for an aerosol population in clean atmosphere.
Figure 2.6 Example of a new particle formation event occurring around 10:00 (UTC) detected with a scanning mobility particle sizer (SMPS).
Chapter 3: Coagulation, Condensation, Dry and Wet Deposition, and Cloud Droplet Formation in the Atmospheric Aerosol Life Cycle
Figure 3.1 Idealized schematic of the distribution of particle surface area of an atmospheric aerosol as a function of particle diameter, showing the principal modes, sources, particle formation processes, and removal mechanisms discussed in the present study. (Adapted from a graph of Whitby and Cantrell (1976).)
Figure 3.2 Schematic representation of the sequence of processes involving the atmospheric life of aerosol particles after the emission of the precursor gases, until their removal from the atmosphere through dry deposition and wet (rainout) mechanisms.
Figure 3.3 Dependence curves of Brownian coagulation coefficient
K
12
on particle diameter in a coagulation process occurring in air at a temperature of 25 °C and involving pairs of spherical aerosol particles, the former having diameter
a
1
and the latter having diameter
a
2
equal to 10
−2
µm, 10
−1
µm, 1 µm, and 10 µm, and diameter
a
2
=
a
1
over the whole diameter range from 10
−3
to 10 µm (gray curve), providing in the last case the patterns of coagulation rate
K
11
. All the five curves have been calculated according to the Fuchs (1964) theory. To use this graph, find the smaller of the two particles as the abscissa and then locate the line corresponding to the larger particle. (Adapted from a graph of Seinfeld and Pandis (2006).)
Figure 3.5 (a) Example of variation in the number density size distribution curve of coagulated aerosol particles plotted versus the particle diameter
a
, as evaluated at time
t
= 0 (open circles, before coagulation) and at time
t
= 12 h (solid squares, after coagulation) in an exercise made by applying the Fuchs (1964) theory to the initial size distribution curve. Note that such a variation in the particle number density size distribution curve is characterized by more marked changes within the small particle size range
a
< 5 × 10
−2
µm and gradually weaker changes as particle diameter increases. (b) Schematic representation of the differential particle volume balance for the derivation of Eq. (3.7) used to represent the particle growth by condensation.
Figure 3.4 Three-dimensional representation of the coagulation coefficient
K
12
(
a
1
,
a
2
) of unequal spherical particles (measured in cubic centimeter per second) defined in Eq. (3.5) according to the Fuchs (1964) theory applied to a pair of spherical particles having diameters
a
1
and
a
2
, respectively, both varying over the 10
−3
≤
a
≤ 10 µm range.
Figure 3.6 Evolution of a log-normal size distribution function of
N
a
(
a
,
t
) as a function of aerosol particle diameter
a
at different times of its coagulation growth: (i)
t
= 0 min (solid curve, with mode diameter
a
max
≈ 0.2 µm, and standard deviation σ = 1.50) assuming in Eq. (3.7), diffusion coefficient
D
i
= 10
−1
cm
2
s
−1
, molecular weight μ
i
= 10
2
g mol
−1
, difference
p
i
−
p
eq,
i
= 1 ppb, absolute temperature
T
= 298 K, and particulate density ρ = 1.0 g cm
−3
; (ii)
t
= 1 min (dashed curve); (iii)
t
= 10 min (dashed and dotted curve); and (iv)
t
= 20 min (dotted curve).
Figure 3.7 Gibbs free energy change for the formation of a droplet having a diameter
a
from a vapor with saturation ratio equal to
S
sat
. In the case represented for
S
sat
< 1 (dashed curve), Δ
G
is given by Eq. (3.19) reported in the text, in which both terms are positive. In the case represented for
S
sat
> 1 (solid curve), Δ
G
results to be negative, the first term of Eq. (3.19) being negative and the second term positive.
Figure 3.8 Variations of growth factor φ
g
=
a
(RH)/
a
o
given by the ratio between the equivalent diameter
a
(RH) of an aerosol particle suspended in wet air and the equivalent diameter
a
o
of the initial dry air particle (for RH = 0) as a function of increasing RH (lower dashed curve) and decreasing RH (upper dashed and dotted curve), as determined by Hänel and Bullrich (1978) for (a) aerosol model A, consisting of maritime aerosols sampled on 13–16 April 1969 over the central Atlantic Ocean (with dry particulate matter mass density ρ
o
= 2.45 g cm
−3
) and (b) three representative values of initial diameter
a
o
equal to (i) 2 × 10
−2
µm (indicative of a nucleus and represented by open circles), (ii) 6 × 10
−1
µm (indicative of an accumulation particle and represented by gray squares), and (iii) 20 µm (indicative of a coarse particle and represented by solid triangles).
Figure 3.9 Example of a multimodal size distribution curve of particle number density
N
(
a
) over the overall diameter range from 10
−4
to 10
2
µm, consisting of (i) a nucleation mode formed by homogeneous nucleation of new particles; (ii) an Aitken nuclei mode consisting of particles having diameters
a
mainly ranging from 10
−2
to 10
−1
µm and formed for the most part through secondary processes, such as nucleation/condensation of low vapor pressure substances and coagulation/condensation; (iii) an accumulation mode mainly consisting of particles with diameters
a
ranging from 0.2 to 2 µm and mainly formed through the chemical reactions occurring in cloud droplets; (iv) a coarse particle mode mainly consisting of primary particles having diameters ranging from 2 to 10 µm and principally formed by wind-borne mechanical processes on oceanic surfaces (forming sea-salt droplets) and land surfaces (mobilizing mineral dust particles); and (v) a giant particle mode produced for the most part by fragmentation of terrain particles by winds.
Figure 3.10 Semiempirical correlation curves of collection efficiency
E
col
(
a
,
a
f
) of two drops (having diameters
a
and
a
f
, respectively) as a function of the collected particle diameter
a
(measured in micrometer) for particles assumed to have unit density ρ, as evaluated by Slinn (1983) for raindrop diameters
a
f
= 0.1 mm (gray curve) and
a
f
= 1 mm (dashed curve). (Adapted from a graph of Seinfeld and Pandis (2006).)
Figure 3.11 Dependence curves of scavenging coefficient Λ(
a
) as a function of collected particle diameter
a
for monodispersed particles collected by monodispersed raindrops with diameters
a
f
equal to 0.2 mm (gray solid curve) and 2 mm (dashed curve), assuming a rainfall intensity of 1 mm h
−1
. (Adapted from a graph of Seinfeld and Pandis (2006).)
Figure 3.12 Ice supersaturation as a function of air temperature for water saturation (gray thick curve) and for condensation-freezing and ice deposition conditions. Ice nucleation starts above the indicated lines, obtained for methaldehyde (solid squares), silver iodide (gray circles), lead iodide (solid circles), and kaolinite (solid triangles). (Adapted from graphs of Schaller and Fukuta (1979) and Wallace and Hobbs (2001).)
Figure 3.13 Variations of RH (%) and supersaturation (%) as a function of droplet diameter
a
, as measured in the adjacent surroundings of droplets consisting of (i) pure water and adjacent to solution droplets containing the following fixed masses of salt (solid curve with open circles), (ii) 10
−19
kg of NaCl (dashed curve with solid circles), (iii) 10
−18
kg of NaCl (dotted curve with open squares), (iv) 10
−17
kg of NaCl (dotted curve with solid squares), (v) 10
−19
kg of (NH
4
)
2
SO
4
(dashed and dotted curve with open triangles), and (vi) 10
−18
kg of (NH
4
)
2
SO
4
(dashed and dotted curve with solid triangles). Note the discontinuity in the ordinate at RH = 100%. (Adapted from a graph of Pruppacher (1973).)
Figure 3.14 Köhler curves describing the variations obtained for two of the cases shown in Figure 13: curve 2 (gray solid curve), which refers to a solution droplet containing 10
−19
kg of NaCl, and curve 5 (dashed black curve), which refers to a solution droplet containing 10
−19
kg of (NH
4
)
2
SO
4
. The horizontal gray line refers to RH = 100%. The horizontal dotted line refers to the ambient supersaturation value of case A discussed in the text. (Adapted from a graph of Wallace and Hobbs (2001).)
Figure 3.15 Köhler curves drawn for the (NH
4
)
2
SO
4
solution (gray curves) and NaCl solution (solid curves) and particles having three different values of the dry initial diameter
a
o
= 5 × 10
−2
µm,
a
o
= 10
−1
µm, and
a
o
= 5 × 10
−1
µm at air absolute temperature
T
= 293 K. The supersaturation is defined in ordinate as the saturation minus 1: for instance, supersaturation = 1% corresponds to an RH = 101%. The corresponding short-dashed horizontal lines indicate the three values of critical saturation
S
c
for NaCl. (Adapted from a graph of Seinfeld and Pandis (2006).)
Chapter 4: Chemical Composition of Aerosols of Different Origin
Figure 4.1 Mass of PM
1
and percent distribution of inorganic compounds (white), organic compounds (dash), and elemental carbon (black) in various environments: (a) marine clean environment, (b) marine polluted, (c) biomass burning aerosol, (d) continental polluted regions, and (e) remote forested area.
Figure 4.2 Schematic representation of secondary aerosol formation through heterogeneous phase chemistry.
Figure 4.3 Evolution of organic aerosol in the atmosphere. (Donahue
et al.,
2012 http://www.atmos-chem-phys.net/12/615/2012/. Used under CC-BY 3.0 license https://creativecommons.org/licenses/by/3.0/.)
Figure 4.4 Dependence of sulfur(IV) oxidation rate on water solution acidity. Rate is calculated for the following conditions: SO
2
(g) 3 ppb, O
3
(g) 30 ppb, H
2
O
2
(g) 1 ppb, Fe
3+
0.3 μM, Mn
2+
0.03 µM.
Figure 4.5 Seasonal variation of pollutant dispersion in urban and rural environments.
Figure 4.6 Chemical composition of submicron and supermicron marine aerosol; WSOC is water-soluble organic carbon, WIOC is water-insoluble organic carbon, and BC is black carbon.
Figure 4.7 Chemical component mass size distribution in areas affected by anthropogenic emissions.
Figure 4.8 Mass size distribution of organic aerosol, sulfate, ammonium, and nitrate in several urban and rural environments. (McFiggans
et al.,
2005. Reproduced with the permission of Royal Society of Chemistry.)
Figure 4.9 Scanning electron microscopy of soot particles: embedded (a), partly coated (b), bare (c), and with inclusion (d). ( China
et al.,
2013. Reproduced with the permission of Nature Publishing Group.)
Figure 4.10 Size distribution of black carbon and organic aerosol downwind of traffic emission sources. ( Massoli
et al.,
2012. Reproduced with permission of Taylor and Francis.)
Figure 4.11 Size distribution of main inorganic species during the wet and the dry season in the Amazon forest. ( Fuzzi
et al.,
2007. Reproduced with permission of Wiley.)
Figure 4.12 Size-segregated aerosol chemical composition at the Mt. Cimone station during summer and winter. ( Carbone
et al.,
2010. Reproduced with permission of Elsevier.)
Figure 4.13 Annual average size-segregated aerosol chemical composition at Halley, Antarctica. ( Rankin and Wolff, 2003 Reproduced with the permission of Wiley.)
Figure 4.14 Average surface SO
2
and sulfate concentrations from 1980 to 2008 at two European sites, Tange in Denmark and Chopok in Slovakia (data from EMEP network). Observations are shown in black lines and model results on gray bars. (Chin
et al.,
2014 http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20140013029.pdf created under creative commons license 3.0)
Figure 4.15 Schematic representation of potential artefacts affecting the accurate determination of BC light attenuation.
Figure 4.16 Organic aerosol measurement techniques.
Figure 4.17 Schematic description of the time-of-flight aerosol mass spectrometer. (DeCarlo
et al.,
2006. Reproduced with the permission of American Chemical Society.)
Figure 4.18 Schematic representation of OA aging.
Figure 4.19 CCN efficiency at
S
= 0.4% as a function of aerosol size for different aerosol types. (Andreae and Rosenfeld, 2008, Reproduced with the permission of Elsevier.)
Figure 4.20 Schematic summary of ice formation processes.
Chapter 5: Aerosol Optics
Figure 5.1 The dependence of the absorption efficiency factor on the attenuation parameter at various values of the refractive index.
Figure 5.2 The dependence of the absorption efficiency factor on the size parameter at various values of the refractive index (
n
= 1.36, 1.46, 1.56). The imaginary part of the complex refractive index is equal to 0.01 for the upper curves. It is equal to 0.001 for the lower curves.
Figure 5.3 The dependence of the scattering efficiency factor on the size parameter at various values of the refractive index (
n
= 1.36, 1.46, 1.56). The imaginary part of the complex refractive index is equal to 0.01. The maximal values of the efficiency factor decrease with
n
.
Figure 5.4 The phase functions of typical aerosol media (see Table 5.2).
Figure 5.5 The same as in Figure 5.4 except for the degree of polarization.
Figure 5.6 The same as in Figure 5.4 except for the ratio P34/P11.
Figure 5.7 The same as in Figure 5.4 except for the ratio P44/P11.
Figure 5.8 The dependence of the extinction efficiency factor on the size parameter at various values of the refractive index (
n
= 1.36, 1.46, 1.56). The imaginary part of the complex refractive index is equal to 0, 0.001, and 0.01. The maximal values of the efficiency factor decrease with
n
.
Chapter 6: Aerosol Models
Figure 6.1 (a) Spectral curves of the real part
n
(λ) of particulate matter refractive index over the 0.30–2.50 µm wavelength range for (i) oceanic aerosol (dashed curve), mainly containing sea salts; (ii) water-insoluble substances (dotted curve with open circles), mainly consisting of soil dust; (iii) water-soluble substances (solid curve), mainly containing sulfate and nitrate components; (iv) soot substances (dotted and dashed curve with open triangles), mainly produced by natural and anthropogenic combustion processes (World Climate Programme, WCP-112, 1986); and (v) liquid water (solid curve with solid circles), according to Hale and Querry (1973). (b) As in the (a) for the imaginary part χ(λ) of the same five substances.
Figure 6.2 (a) Angular dependence curves of phase function
p
(cos θ) calculated at wavelength λ = 0.55 µm by Vermote
et al.
(1997b) for the six following aerosol types: (i) continental (solid curve), (ii) maritime (dashed curve), (iii) urban (dotted curve), (iv) desert dust (dashed curve with small solid circles), (v) biomass burning (dashed curve with small open circles), and (vi) stratospheric (dashed and dotted curve with small open triangles). (b) As in the (a) for the aerosol particle contents analyzed by means of sky-brightness measurements performed in almucantar using the Prede radiometer (POM-02L model) at the San Pietro Capofiume (Italy) station on four measurement days during the AEROCLOUDS field campaigns: (i) 15 May 2007 (solid curve), for maritime–continental aerosol transported from Atlantic Ocean, southern France, and Ligurian Sea; (ii) 21 June 2007 (dashed curve), for continental-polluted aerosol from central and southern Italy, with marine aerosols from southern Mediterranean Sea and desert dust from the Libyan coasts; (iii) 8 February 2008 (dotted curve), for continental–anthropogenic aerosol from northwestern Europe; and (iv) 15 February 2008 (dotted and dashed curve), for continental aerosol from eastern Europe and northern Balkans.
Figure 6.3 Size-distribution curves of particle number concentration
N
(
a
) over the 10
−3
≤
a
≤ 10
2
µm diameter range determined by Vermote
et al.
(1997b) to represent the four 6S basic aerosol components – dustlike (DL) (solid curve), water soluble (WS) (dashed curve), oceanic (OC) (dotted and dashed curve), and soot (SO) (dashed curve solid circles) – for dry-air conditions. Each lognormal size-distribution curve is normalized to give the overall particle number density
N
T
= 10
3
cm
−3
.
Figure 6.4 Size-distribution curves of particle number density
N
(
a
) over the 10
−3
≤
a
≤ 10
2
µm diameter range determined by Vermote
et al.
(1997b) to represent the three dry-air aerosol models of continental (6S-C) particles (solid curve), maritime (6S-M) particles (dashed curve), and urban (6S-U) particles (dashed and dotted curve). All the three multimodal size-distribution curves are normalized to give the overall particle number concentration
N
T
= 10
3
cm
−3
.
Figure 6.5 Size-distribution curves of particle number density
N
(
a
) over the 10
−3
≤
a
≤ 10
2
µm diameter range determined to represent the following four additional aerosol models: (i) background desert dust (BDD) model (solid curve) of Shettle (1984); (ii) El Chichón stratospheric volcanic (ESV) aerosol model (dashed curve) of King, Harshvardhan, and Arking (1984); (iii) BBS particle model (solid curve with solid circles), based on the Remer
et al.
(1998) measurements; and (iv) winter Po Valley (WPV) aerosol model (dashed curve with open squares), defined on the basis of the AOT measurements conducted by Tomasi
et al.
(2015a) and the chemical composition data of Carbone
et al.
(2010). All the four multimodal size-distribution curves are normalized to give the overall particle number concentration
N
T
= 10
3
cm
−3
.
Figure 6.6 Size-distribution curves of particle number density
N
(
a
) over the 10
−3
≤
a
≤ 10
2
µm diameter range for (i) model M-1 (pure oceanic aerosol) (solid curve), (ii) model M-2 (maritime aerosol) (dashed curve), (iii) model M-3 (mixed maritime–continental aerosol) (solid curve with solid circles), (iv) model M-5 (mixed maritime–continental aerosol) (dashed curve with open squares) models, (v) model M-8 (pure continental aerosol) (solid curve with open circles) model, (vi) model M-10 (continental-polluted aerosol) (dashed curve with solid squares), (vii) model M-12 (continental-polluted aerosol) (dashed curve with solid triangles) models, and (viii) model M-14 (heavy polluted aerosol) (dashed curves with open triangles) model. All the eight aerosol models were defined by Tomasi
et al.
(2013) as linear combinations of the 6S basic aerosol components and are normalized to give the total particle number concentration
N
T
= 10
3
cm
−3
.
Figure 6.7 (a) Size-distribution curves of particle number density
N
(
a
) over the 10
−3
≤
a
≤ 10
2
µm diameter range for the five OPAC wet-air (RH = 50%) aerosol models labeled by Hess, Koepke, and Schult (1998) with the acronyms CC (solid curve), CA (dashed curve), CP (dashed curve with open circles), UR (dashed curve with solid circles), and DE (dashed curve with open squares) listed in Table 6.18. (b) As in the (a) for the five OPAC wet-air (RH = 50%) aerosol models labeled with acronyms MC (solid curve), MP (dashed curve), MT (dashed curve with open circles), AR (dashed curve with solid circles), and AN (dashed curve with open squares) listed in Table 6.18. All the 10 aerosol models are calculated for RH = 50% and normalized to give the overall particle number concentration
N
T
= 10
3
cm
−3
.
Figure 6.8 Size-distribution curves of particle number density
N
(
r
) over the 10
−3
≤
a
≤ 10
2
µm diameter range for (i) rural aerosol model (SF-R) (solid curve), (ii) maritime aerosol model (SF-M) (dashed curve), (iii) urban aerosol model (SF-U) (dashed curve with open circles), and (iv) tropospheric aerosol model (SF-T) (dashed curve with solid circles), defined by Shettle and Fenn (1979) for RH = 50%. All the four models are normalized to give the overall particle number concentration
N
T
= 10
3
cm
−3
.
Figure 6.9 (a) Size-distribution curves of particle number density
N
(
r
) over the 10
−3
≤
a
≤ 10
2
µm diameter range for (i) Saharan dust model SD-1 (solid curve), (ii) Saharan dust model SD-2 (dashed curve), (iii) BBS model for particles suspended in the free troposphere (FT) (dashed curve with open circles), and (iv) BBS model for particles suspended in the boundary layer (BL) (dashed curve with solid circles). (b) As in the (a), for (i) model PV-1 representing the background stratospheric aerosol during a volcanic quiescence period in Antarctica (solid curve), (ii) model PV-2 representing the 2-month aged stratospheric volcanic aerosol after the Pinatubo volcanic eruption (dashed curve), and (iii) model PV-3 representing the 9-month aged stratospheric volcanic aerosol after the Pinatubo volcanic eruption (dashed curve with open circles). All the seven aerosol models are normalized to give the overall particle number density
N
T
= 10
3
cm
−3
.
Figure 6.10 (a) Size-distribution curves of particle number density
N
(
r
) over the 10
−3
≤
a
≤ 10
2
µm diameter range for the following four Arctic aerosol models: (i) model AH, representing the winter–spring Arctic haze aerosol (solid curve), (ii) model ASB, representing the Arctic summer background aerosol (dashed curve), (iii) model AD, representing the Asian dust transported over the Arctic (dashed curve with open circles), and (iv) model BFFS, representing the boreal forest fire smoke particles (dashed curve with solid circles), determined by Tomasi
et al.
(2015a,b). (b) As in the (a), for the following three Antarctic aerosol models: (v) model AASC, representing the Antarctic austral summer coastal aerosol (solid curve), (vi) model ASAP, representing the austral summer aerosol on the Antarctic Plateau (dashed curve), and (vii) model AAWC, representing the Antarctic austral winter coastal aerosol (dashed curve with open circles), determined by Tomasi
et al.
(2015a,b). All the aerosol models are normalized to give the overall particle number density
N
T
= 10
3
cm
−3
.
Figure 6.11 Example of a four-modal best-fit aerosol number density lognormal size-distribution curves of background continental aerosols, determined from the multimodal size-distribution curve represented by Tomasi and Tampieri (1977) over the 10
−2
≤
a
≤ 50 µm diameter range as a combination of four modes of particles sampled at altitudes of 6–7 km over continental Russia.
Figure 6.12 Typical curves of number concentration size distribution
N
(
a
) =
dN
/
d
(ln
a
) of atmospheric aerosols presenting different modes over the 10
−3
≤
a
≤ 10
2
µm diameter range: (i) nucleation mode (solid curve), (ii) Aitken nuclei mode (dashed curve), (iii) condensation submode (dashed curve with open circles), (iv) accumulation mode (dashed curve with solid circles), (v) droplet submode (dashed curve with open squares), and (vi) coarse mode (dashed curve with solid triangles). Note that accumulation mode and droplet submode are very similar.
Figure 6.13 Example of trimodal size-distribution curves of (a) particle number density
N
(
a
) =
dN
/
d
(ln
a
), (b) particle surface area
S
(
a
) =
dS
/
d
(ln
a
), and (c) particle volume
V
(
a
) =
dV
/
d
(ln
a
), obtained over the 10
−3
≤
a
≤ 10
2
µm diameter range by Tomasi
et al.
(2015a) from AOT measurements performed during an episode of continental aerosol transport from eastern Europe observed at SPC (Po Valley, Northern Italy) on 19 December 2007 (08:22 UTC), during the AEROCLOUDS winter field campaign. The trimodal number concentration curve is normalized to
N
T
= 10
3
cm
−3
. The areas below the three curves provide the total aerosol number
N
T
, total surface area
S
T
, and total volume
V
T
, respectively.
Figure 6.14 Left-hand side: Multimodal size-distribution curves of (a) particle number concentration
N
(
a
) =
dN
/
d
(ln
a
), (b) particle surface area
S
(
a
) =
dS
/
d
(ln
a
), and (c) particle volume
V
(
a
) =
dV
/
d
(ln
a
) defined over the 10
−3
≤
a
≤ 10
2
µm diameter range, determined for the following remote continental aerosol models: (i) the model determined by Jaenicke (1993) (solid curves) and (ii) the OPAC continental clean aerosol model CC (dashed curves with solid circles) defined by Hess, Koepke, and Schult (1998). Both number concentration size-distribution curves are normalized to
N
T
= 10
3
cm
−3
. Right-hand side: As in the left-hand side part, for the following free tropospheric aerosol models: (i) model SF-T (solid curves) of Shettle and Fenn (1979), (ii) continental aerosol model 6S-C (dashed curves with open triangles) of Vermote
et al.
(1997a), and (iii) pure continental aerosol model M-8 (solid curves with solid circles) of Tomasi
et al.
(2013). The three number concentration size-distribution curves are normalized to
N
T
= 10
3
cm
−3
.
Figure 6.15 Left-hand side: As in Figure 6.14, for the following rural-continental aerosol models: (i) model SF-R (solid curves) of Shettle and Fenn (1979), (ii) OPAC continental average aerosol model CA (dashed curves with open diamonds) of Hess, Koepke, and Schult (1998), (iii) continental clean aerosol model (solid curves with solid circles) of Tomasi
et al.
(2015a) (9 May 2003 (14:08 UTC), DOE/ARM/AIOP field campaign), (iv) continental aerosol model (dashed curves with open squares) of Tomasi
et al.
(2015a) (10 June 2003 (10:03 UTC), PRIN-2004 field campaign, Lecce (Italy)), and (v) continental aerosol model (solid curves with solid triangles) of Tomasi
et al.
(2015a) (15 October 2007 (11:45 UTC), summer AEROCLOUDS field campaign at San Pietro Capofiume (Italy)). The five multimodal aerosol number concentration size-distribution curves are normalized to
N
T
= 10
3
cm
−3
. Right-hand side: As in the left-hand side part, for the following continental-polluted aerosol models: (i) OPAC model CP (solid curves) of Hess, Koepke, and Schult (1998), (ii) model M-10 (dashed curves) of Tomasi
et al.
(2013), (iii) anthropogenic–continental aerosol model M-12 (solid curves with solid circles) of Tomasi
et al.
(2013), and (iv) heavy polluted aerosol model M-14 (dashed curves with open squares) of Tomasi
et al.
(2013). The four aerosol number size-distribution curves are normalized to
N
T
= 10
3
cm
−3
.
Figure 6.16 Left-hand side: As in Figure 6.14, for the following maritime aerosol models: (i) model 6S-M (solid curves) of Vermote
et al.
(1997b), (ii) pure oceanic aerosol model M-1 (dashed curves with solid squares) of Tomasi
et al.
(2013), (iii) model M-2 (solid curves with solid diamonds) of Tomasi
et al.
(2013), (iv) OPAC maritime clean aerosol model MC (dashed curves with open circles) of Hess, Koepke, and Schult (1998), (v) OPAC maritime tropical aerosol model MT (solid curves with solid circles) of Hess, Koepke, and Schult (1998), (vi) model SF-M (dashed curves with open squares) of Shettle and Fenn (1979), and (vii) the bimodal aerosol model (dashed curves with open triangles) of Tomasi
et al.
(2015a) determined for pure maritime aerosol observed during the Aerosols99 cruise. The seven aerosol number size-distribution curves are normalized to
N
T
= 10
3
cm
−3
. Right-hand side: As in the left-hand side part, for the following maritime-polluted aerosol models: (i) OPAC model MP (solid curves) of Hess, Koepke, and Schult (1998), (ii) mixed maritime–continental aerosol model M-3 (dashed curves with open circles) of Tomasi
et al.
(2013), (iii) mixed maritime–continental aerosol model M-5 (solid curves with solid circles) of Tomasi
et al.
(2013), and (iv) trimodal mixed marine/continental aerosol model (dashed curves with open squares) retrieved by Tomasi
et al
. (2013) from the AEROCLOUDS measurements conducted at SPC (Po Valley, Italy) on 1 July 2007 (07:45 UTC), during an aerosol transport episode from the Atlantic Ocean, southern France, and Ligurian Sea. The four number size-distribution curves are normalized to
N
T
= 10
3
cm
−3
.
Figure 6.17 As in Figure 6.14, for the following aerosol models: (i) OPAC desert dust model DE (dashed curves with open circles) of Hess, Koepke, and Schult (1998), (ii) trimodal background desert dust model BDD (solid curves) of Shettle (1984), (iii) Saharan dust model SD-1 (solid curves with solid circles) of Tomasi
et al.
(2013), (iv) Saharan dust model SD-2 (dashed curves with open triangles) of Tomasi
et al.
(2013), and (v) mixed anthropogenic–continental–Saharan dust aerosol model (solid curves with solid squares) observed by Tomasi
et al.
(2015a) during the PRIN-2004 experiment (30 August 2003 (07:30 UTC)) conducted at Lecce (Italy). The five desert dust number size-distribution curves are normalized to
N
T
= 10
3
cm
−3
.
Figure 6.18 Left-hand side: As in Figure 6.14, for the following aerosol models: (i) continental-polluted aerosol model, containing soot and Siberian forest fire (SFF) smoke particles (solid curves with solid circles), retrieved by Tomasi
et al.
(2015a) from the DOE/ARM/AIOP field measurements conducted on 25 May 2003 (22:58 UTC); (ii) continental-polluted aerosol model, containing soot and SFF smoke particles (dashed curves with open circles), retrieved by Tomasi
et al.
(2015a) from the DOE/ARM/AIOP field measurements conducted on 27 May 2003 (16:28 UTC); (iii) bimodal model BBS (solid curves), derived from the measurements conducted by Remer
et al.
(1998) during the burning season in the Amazon Basin and Cerrado region of Brazil; (iv) aerosol model FT (dashed curves with open squares) of Tomasi
et al.
(2013); and (v) aerosol model BL (solid curves with solid triangles) of Tomasi
et al.
(2013). The five aerosol number size-distribution curves are normalized to
N
T
= 10
3
cm
−3
. Right-hand side: As in the left-hand side part for the following urban aerosol models: (i) model 6S-U (solid curves) of Vermote
et al.
(1997b), (ii) OPAC model UR (dashed curves with open triangles) of Hess, Koepke, and Schult (1998), (iii) model SF-U (solid curves with solid circles) of Shettle and Fenn (1979), and (iv) winter-polluted Po Valley aerosol model WPV (solid curves with open squares), determined by using the field data of Carbone
et al.
(2010). The four urban aerosol number size-distribution curves are normalized to
N
T
= 10
3
cm
−3
.
Figure 6.19 Left-hand side: As in Figure 6.14, for the following Arctic aerosol models: (i) OPAC model AR (solid curves with solid circles) of Hess, Koepke, and Schult (1998), (ii) model ASB for Arctic summer background aerosol (dashed curves with solid squares) of Tomasi
et al.
(2015a), (iii) model AH for Arctic haze (dashed curves with open circles) of Tomasi
et al.
(2015a), (iv) model AD for Asian dust (dashed curves with open triangles) of Tomasi
et al.
(2015a), and (v) model BFFS for boreal forest fire smoke particles (dashed curves with solid diamonds) of Tomasi
et al.
(2015a). The five aerosol number size-distribution curves are normalized to
N
T
= 10
3
cm
−3
. Right-hand side: As in the left-hand side for the following Antarctic aerosol models: (i) OPAC model AN (dashed curves with open diamonds) of Hess, Koepke, and Schult (1998), (ii) model AASC for Antarctic austral summer coastal aerosols (solid curves with solid circles) of Tomasi
et al.
(2015a,b), (iii) model ASAP for austral summer particles on the Antarctic Plateau (solid curves with open squares) of Tomasi
et al.
(2015a,b), and (iv) model AAWC for Antarctic austral winter coastal particles (solid curves with solid triangles) of Tomasi
et al.
(2015a,b). The four aerosol number size-distribution curves are normalized to
N
T
= 10
3
cm
−3
.
Figure 6.20 As in Figure 6.14, for the following aerosol models: (i) aerosol model ESV for the El Chichón stratospheric volcanic particles (solid curves), defined in the present study using the King, Harshvardhan, and Arking (1984) data; (ii) aerosol model PV-1 for background stratospheric particles (dashed curves) during the long volcanic quiescence period over Antarctica before the Mt Pinatubo eruption (Tomasi
et al.,
2013); (iii) aerosol model PV-2 for the 2-month aged stratospheric Mt Pinatubo volcanic particles (solid curves with solid circles), defined by (Tomasi
et al.,
2015a) on the basis of the airborne spectral measurements of the Mt Pinatubo volcanic aerosol extinction coefficient conducted in July–August 1991 over the Caribbean region by Pueschel
et al.
(1993); and (iv) aerosol model PV-3 for the 9-month aged stratospheric Mt Pinatubo volcanic particles (dashed curves with open triangles), defined by (Tomasi
et al.,
2015a) from airborne measurements of the Mt Pinatubo volcanic aerosol extinction coefficient performed in March 1992 by Pueschel
et al.
(1993). The four stratospheric volcanic particle number size-distribution curves are normalized to
N
T
= 10
3
cm
−3
.
Chapter 7: Remote Sensing of Atmospheric Aerosol
Figure 7.1 (a) Photograph of the Radiance Research M903 nephelometer employed by the ISAC-CNR group at San Pietro Capofiume (SPC) (Italy) during the AEROCLOUDS experiment campaigns conducted in the 2007–2010 multiyear period to measure the ground-level aerosol scattering coefficient . (b) Photograph of the Radiance Research Particle Soot Absorption Photometer (PSAP) measuring at SPC the ground-level aerosol absorption coefficient .
Figure 7.2 Examples of Langley plot best-fit lines determined for the measurements performed during the morning hours of 10 September 1985 (open circles), and September 11 1985 (solid circles), at the top of Sass Pordoi (2950 m a.m.s.l.) (Canazei, Trento, Italy) using the UVISIR-1 sun-photometer (Tomasi, Vitale, and Tagliazucca, 1989; Tomasi
et al.,
1999) measurements taken at wavelength . The values of slope coefficient and intercept of the two regression lines are given separately for the two calibration days. Both regression lines were obtained for values of regression coefficient equal to . An average value of calibration constant equal to was obtained by applying the Langley plot procedure to the two daily sets of calibration measurements shown in the graph.
Figure 7.3 Spectral curves of the water vapor absorption coefficient , ozone absorption coefficient , nitrogen dioxide and dimer absorption coefficient , and oxygen dimer optical thickness , as derived over the wavelength range using the MODTRAN 2/3 computational code and the LOWTRAN 7 model (Kneizys
et al.,
1996) and additional data available in the literature (Hall and Blacet, 1952; Inn and Tanaka, 1953) for water vapor, ozone, and nitrogen dioxide and the spectral features of provided by Michalsky
et al.
(1999). Note that absorption coefficient is measured in , giving the volume occupied by the and molecules within the vertical atmospheric column of unit cross section, in which standard temperature and pressure (STP) conditions have been assumed at all levels.
Figure 7.4 Scatter plots of the natural logarithms of aerosol optical thickness versus the logarithm of wavelength according to the Ångström (1964) formula , as obtained over the spectral range from 0.40 to for four sets of measurements of conducted at San Pietro Capofiume using the Prede POM-02L sun/sky radiometer of the SKYNET network at 12:00 local time of the following measurement days: (a) 22 May 2007 (open circles), giving the best-fit values of and (with regression coefficient ) for continental aerosol with thin layers of Saharan dust at 2–3 km levels; (b) 23 June 2007 (solid triangles), giving the best-fit values of and (with ) (, , ) for anthropogenic–continental (polluted) aerosol with a Saharan dust layer; (c) 8 February 2008 (open squares), giving the best-fit values of and (with ) for clear-sky conditions and background continental aerosols from northwestern Europe; and (d) 15 February 2008 (solid diamonds), giving the best-fit values of and (with ) for anthropogenic aerosol transported from eastern Europe and northern Russia at all levels.
Figure 7.5 Picture of the Prede POM-02L Sun/sky radiometer employed at San Pietro Capofiume (Italy) during the AEROCLOUDS field campaigns from 16 May 2007 to 31 August 2008.
Figure 7.6 Time patterns of the daily mean values of (a) aerosol optical thickness , (b) Ångström (1964) wavelength exponent , and (c) fine particle fraction , as derived from the aerosol optical thickness measurements conducted with the Prede POM-02L Sun/sky radiometer at San Pietro Capofiume (Italy) from 16 May 2007 to 31 August 2008. The values of parameter have been calculated using the O'Neill, Dubovik, and Eck (2001) procedure.
Figure 7.7 Time patterns of the daily mean values of (a) real part of columnar aerosol refractive index, (b) imaginary part of columnar aerosol refractive index, (c) asymmetry factor of columnar aerosols, and (d) single scattering albedo of columnar aerosols, as derived from the sky-brightness measurements in the almucantar conducted at the wavelength with the Prede POM-02L Sun/sky radiometer at San Pietro Capofiume (northern Italy) from 16 May 2007 to 1 September 2008, using the SkyRad 4.2 inversion code (Nakajima, Tanaka, and Yamauchi, 1983; Nakajima
et al.,
1996).
Figure 7.8 Size-distribution curves of the overall volume occupied by the aerosol particles in the vertical atmospheric column (measured in cubic micrometer per unit cross section (equal to ) of the atmospheric column), as determined at various local times (LT) of the following days: (1) 22 May 2007 (08:27 LT), for continental aerosols; (2) 23 June 2007 (11:45 LT), for anthropogenic–continental aerosols; (3) 17 July 2007 (17:27 LT), for anthropogenic–continental aerosols and Saharan dust; (4) 8 February 2008 (10:45 LT), for continental aerosols; and (5) 15 February 2008 (11:00 LT), for anthropogenic–continental aerosols.
Figure 7.9 (a) Scatter plot of fine particle fraction calculated using the algorithm of O'Neill, Dubovik, and Eck (2001) represented as a function of simultaneous Ångström's wavelength exponent , as obtained by examining the Prede POM-02L Sun/sky-radiometer measurements conducted at SPC during the last 2 weeks of May 2007 at different hours from sunrise to sunset. Open squares refer to the measurements performed for atmospheric loads with predominant rural-continental aerosol particles, and small solid circles to those performed for loads with prevailing content of Saharan dust. (b) As in part (a), for the whole set of daily mean values of parameters and derived from the Prede POM-02L Sun/sky-radiometer measurements conducted for all aerosol types (gray circles) and for cloudless-sky conditions during the period of the 15-month AEROCLOUDS field campaign conducted from 1 June 2007 to 31 August 2008.
Figure 7.10 (a) Time patterns of the daily mean values of aerosol volume scattering coefficient (open circles) derived from the nephelometer measurements and approximate volume extinction coefficient determined as equal to the sum of and (solid squares), recorded at SPC (Italy) over the two periods from 16 May to 27 July 2007, and from 24 January to 31 March 2008. (b) As in part (a), for the daily mean values of aerosol volume absorption coefficient (solid squares) derived from the PSAP measurements and surface-level aerosol single scattering albedo in the visible (open upward triangles), estimated in terms of ratio determined examining the nephelometer and PSAP measurements. The measurement days characterized by the presence of Saharan dust in the low troposphere during the two seasonal field campaigns are marked with gray thin vertical strips.
Figure 7.11 Automated Vaisala LD-40 ceilometer used by Angelini
et al.
(2009) at the Torre Sarca (Milano-Bicocca University) station in the center of Milan (Italy) during the QUITSAT field campaigns of summer 2007 and winter 2008. (Reproduced with kind permission of G. P. Gobbi and F. Angelini, ISAC-CNR, Rome Tor Vergata, Via del Fosso del Cavaliere 100, 00133 Roma, RM Lazio, Italy).
Figure 7.12 (a) Vertical profiles of the volume extinction coefficient derived over the first 4 km of the atmosphere from the automated Vaisala LD-40 ceilometer measurements performed by Angelini
et al.
(2009) as a part of the national QUITSAT project (Di Nicolantonio, Cacciari, and Tomasi, 2009) on 19 July 2007, above the urban site of Torre Sarca in Milan (45°31′N, 9°13′E, Milano-Bicocca University) at three hours of early morning: (i) 04:03 UTC (solid curve), (i) 05:15 UTC (dashed curve), and 06:40 UTC (dashed and dotted curve). (b) As in the left-hand part, for the Vaisala LD-40 ceilometer measurements conducted during the warmest part of 19 July 2007, at (i) 10:00 UTC (solid curve with open circles), (ii) 12:00 UTC (dashed curve with solid squares), and (iii) 14:00 UTC (dotted curve with open triangles).
Figure 7.13 Picture of the optical particle counter (GRIMM 1.108 “DUSTcheck”) model mounted on board the Milano-Bicocca University-tethered balloon and used at the Torre Sarca (Milano-Bicocca University) station in the center of Milan (Italy) during the 3 years from 2005 to 2008 to measure the aerosol size spectra at various levels of the atmospheric boundary layer. (Reproduced with kind permission of Ezio Bolzacchini and Luca Ferrero, Department of Earth and Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza 1, 20126, Milano, Italy).
Figure 7.14 Comparison between the seasonal mean size-distribution curves of aerosol number concentration obtained as a function of the natural logarithm of particle diameter from (i) an overall number of 142 size-distribution curves measured at the Torre Sarca (Milano-Bicocca University) station in the center of Milan (Italy) during the winter months of 3 years from 2005 to 2008 (solid circles) and (ii) a set of 72 ground-level size-distribution curves measured during the summer months from 2005 to 2008 (open squares). (This graph was prepared using the data sets of Ferrero
et al.
(2010).)
Figure 7.15 Vertical profiles of the aerosol particle number concentration within the mixing layer of the urban atmosphere with (a) sizes varying between 0.3 and (fine particle mode) and (b) with sizes (coarse particle mode), as measured over three different periods of 19 July 2007, using an optical particle counter (OPC GRIMM 1.108 “DUSTcheck” model) mounted on board the tethered balloon of the Milano-Bicocca University (Ferrero
et al.,
2010) above the urban site of Torre Sarca (Milan) (45°31′N, 9°13′E). The measurement periods were (i) from 03:55 UTC to 04:12 UTC (solid circles), (ii) from 05:05 UTC to 05:25 UTC (open squares), and (iii) from 06:25 UTC to 06:55 UTC (gray diamonds).
Figure 7.16 Vertical profiles of aerosol backscattering coefficient derived from the multiwavelength LIDAR measurements conducted on board the NASA DC-8 aircraft during the Second Airborne Arctic Stratospheric Expedition (AASE-II) at altitudes ranging from about 10 to 30 km on different measurement days: (a) 19 January 1992, at wavelength (solid curve); (b) 28 January 1992, at wavelength (dashed curve with solid circles); (c) 14 March 1992, at wavelength (dashed curve with open triangles); and (d) 20 March 1992, at wavelength (dashed curve with gray squares). (Graph prepared using the AASE-II data of Russell
et al.
(1993).)
Figure 7.17 (a) Vertical profiles of aerosol volume extinction coefficient obtained by Redemann
et al.
(2000b) for the first band of the Fu and Liou (1992) radiative transfer model applied over the wavelength range from 0.2 to to the field data collected on the two TARFOX measurement days of 17 July 1996 (solid curve), and 24 July 1996 (gray dashed curve). (b) As in the left-hand side, for the vertical profiles of asymmetry factor calculated by averaging the Fu and Liou (1992) data over the wavelength range from 0.2 to .
Figure 7.18 (a) Vertical profiles of volume extinction coefficient (solid curve) retrieved from the AATS-14 sun-photometer measurements performed aboard the Pelican aircraft during the tf15 flight (8 July 1997) and the vertical profiles derived from the nephelometer and PSAP airborne measurements (dotted curve) and the Caltech OPC airborne measurements (black dashed curve). (b) As in the left-hand side for the AATS-14, nephelometer and PSAP and Caltech OPC airborne measurements performed aboard the Pelican aircraft during the tf20 flight (17 July 1997). (Graph prepared using the ACE-2 data sets of Schmid
et al.
(2000).)
Figure 7.19 Examples of vertical profiles of the aerosol extinction coefficient derived from the measurements of aerosol optical thickness performed with the AATS-6 sun-photometer on board the SSC San Diego Navajo aircraft during the flights of (i) 6 July 2000 (ascent flight, 14:42–15:30 UTC), for a predominant load of clean marine aerosol in the low troposphere from sea level to 6 km altitude (dashed curve) and (ii) 21 July 2000 (descent flight, 13:51–14:51 UTC), for a dense layer of Saharan dust (SAL) extended from about 1 to 4.6 km altitudes (solid curve). (Graph prepared using the PRIDE data sets of Livingston
et al.
(2003).)
Figure 7.20 (a) Vertical profiles of (i) mean black carbon (BC) mass concentration (solid curve with solid circles), (ii) mean refractory submicrometer (RS) aerosol mass concentration (for mass density ) (dashed curve with open squares), and (iii) mean sea-salt (SS) mass concentration (dashed curve with solid triangles). (b) Vertical profiles of mean submicrometer aerosol mass concentration (for mass density ) (dashed curve with open circles). (c) Vertical profiles of mean dust mass concentration (for dry bulk density ) (dashed curve with open diamonds). All the mass concentrations are measured in microgram per cubic meter. The graphs were prepared using the ARCTAS/ARCPAC data published by McNaughton
et al.
(2011) in Table 5.
Figure 7.21 (a) Vertical profiles of the mean values of total light extinction coefficients (open circles), (solid squares), and (gray diamonds), as measured in per kilometer by McNaughton
et al.
(2011) examining the 1 min averaged data measured on board the NASA DC-8 and the P-3B aircraft during the ARCTAS airborne campaign. (b) As in (a) for the mean values of aerosol single scattering albedo (open circles), (solid squares), and (gray diamonds) obtained as ratios between the respective aerosol scattering and aerosol extinction coefficients. Both graphs were prepared using the ARCTAS/ARCPAC data published by McNaughton
et al.
(2011) in Table 6.
Figure 7.22 Vertical profiles over the altitude range from surface to 4 km of (a) aerosol optical thickness measured on board the Polar-5 aircraft of the Alfred Wegener Institute for Polar and Marine Research (Germany) using the 8-channel Sun-photometer system developed by the NOAA ESRL GMD (Boulder, Colorado, USA) and ISAC-CNR (Bologna, Italy) at (i) Ny-Ålesund on 6 April 2009 (solid circles), (ii) Resolute on 14 April 2009 (open squares), and (iii) Barrow on 25 April 2009 (gray diamonds); and (b) volume extinction coefficient derived from the Sun-photometer measurements of shown in (a) and conducted in the atmospheric columns above the same sites. (Graph prepared using the PAM-ARCMIP data of Stone
et al.
(2010).)
Figure 7.23 Average vertical profiles derived from the AMALi measurements conducted above Ny-Ålesund on 3–6 April 2009: (a) backscatter coefficient calculated by using iteratively the Klett (1981) algorithm, (b) LIDAR ratio derived from altitude step-by-step comparisons with Sun-photometer data, (c) linear volume depolarization ratio measured with the AMALi LIDAR, and (d) volume extinction coefficient calculated as the product (solid curve), which is compared in part (d) with the vertical profile of aerosol optical thickness derived by smoothing and integrating the values of obtained from the airborne Sun-photometer measurements (gray solid curve). The graphs were prepared using the PAM-ARCMIP data of Hoffmann
et al.
(2012).
Figure 7.24 The 3MI concept, multiview, multispectral, and multipolarization sampling (Marbach
et al.,
2015).
Figure 7.25 Comparison of satellite and ground measurements of AOT at (Kokhanovsky
et al.,
2007).
Figure 7.26 A multilayer perceptron with one hidden layer (after Xiao
et al.,
2015).
Figure 7.28 Mean aerosol optical thickness from the Terra MODIS collection 6 data, March 2001–October 2015.
Figure 7.27 Mean fine fraction of aerosol optical thickness over ocean and normalized Ångström exponent over land from the Terra MODIS collection 6 data, March 2001 – October 2015.
Figure 7.29 Comparison of global mean AOD computed from five versions of PATMOS experimental products, with reference to the TOMS/OMI, SeaWiFS, MODIS, and MISR (after Li
et al.,
2009).
Figure 7.30 GOCI image (top line), retrieved GOCI AOT at 550 nm (second line) with selected aerosol types (third line), and MODIS L2 AOT (bottom line) on 1–2 May 2011. Aerosol types are given by dark grey (maritime clean) and light grey (desert dust) (after Lee
et al.,
2012).
Figure 7.31 CALIOP-retrieved mean AOD distribution map with longitude and latitude directional mean AOD and mean extinction profile plots during 2012 (after Lee, 2014).
Chapter 8: Aerosol and Climate Change: Direct and Indirect Aerosol Effects on Climate
Figure 8.1 Comparison between the spectral curve of a blackbody having an emission temperature of 5777 K for a mean Earth–Sun distance (solid curve) (Fröhlich, 2013) and the spectral curve of solar irradiance
I
ToA
(λ) outside the atmosphere (dashed curve). The gray area represents the sea-level spectrum of solar radiation which has crossed the standard atmosphere for relative optical air mass μ = 2 (i.e., for solar zenith angle ), which shows a number of absorption bands by water vapor, carbon dioxide, oxygen, and ozone.
Figure 8.2 Average composition diagrams of particulate matter sampled at various sites of central Europe and northern Italy in different seasonal periods, giving the particle mass concentration of each aerosol component (OM = organic matter, EC = elemental carbon): (a) from left to right, fine aerosol samples (with diameter
a
< 2.5 µm) collected at urban, nonurban continental, and remote sites (Heintzenberg, 1994); (b) fine continental-polluted aerosol (
a
< 2.5 µm) sampled in winter at the Milan (urban), Bologna (urban), San Pietro Capofiume (rural), and Oasi Bine (rural) sites in the Po Valley (northern Italy); and (c) fine continental aerosol (
a
< 2.5 µm) sampled in summer at the Milan (urban), Bologna (urban), San Pietro Capofiume (rural), and Oasi Bine (rural) sites in the Po Valley (northern Italy) (E. Bolzacchini, private communication).
Figure 8.3 Spectral curves of surface albedo
R
L
(λ) (Lewis and Barnsley, 1994), as defined in Eq. (8.7) over the 0.40–2.50 µm wavelength range for the four OS, VS, BS, and PS classes of BRDF surface reflectance models considered in the present study. All the reflectance models were determined for (i) the optical characteristics of the US62 atmosphere model (Dubin, Sissenwine, and Teweles, 1966), (ii) the scattering and absorption properties of the M-8 aerosol model consisting of pure continental particles (Tomasi
et al.
2013), (iii) aerosol optical thickness τ
a
(0.55 µm) = 0.10, and (iv) solar zenith angle ϑ
o
= 60°. Note that the range of
R
L
(λ) is from 0 to 1 for the VS, BS, and PS BRDF models and from 0 to 0.3 for the OS BRDF models.
Figure 8.5 Spectral curves of white-sky albedo
R
ws
