and the cloud single scattering albedo is
with ts and Ta being the scattering and near-infra-red absorption cloud optical depths, respectively, while the asymmetry factor gc is set to a lower value of about 0.8. The cloud absorption is then given by a;rc = 1 — Rirc — tirc.
6.5 Aerosol absorption and scattering
A major difference between aerosols and greenhouse gases is that aerosols have a much shorter atmospheric lifetime (from 10~4 days for natural, to tens of days for anthropogenic aerosols) compared with the important greenhouse gases (decades to centuries). This, together with microphysical and mixing processes, results in larger spatial and temporal aerosol variability. Thus, quantification of aerosol radiative effects is complex, as this requires comprehensive global micro-physical, microchemical, and radiative aerosol properties. Characteristics such as size distribution, composition, and radiative properties have to be adequately determined on a global scale.
Given the high spatial and temporal variability of atmospheric aerosols, unique aerosol types never occur in the atmosphere; in fact, aerosol size-distribution spectra are present as internal plus external mixtures of various aerosol components. Such mixtures, along with complex aerosol properties, can only be simulated and represented by global aerosol models.
Table 6.4 Long-term mean annual global aerosol optical thickness (raers), aerosol single scattering albedo (uaer), and aerosol asymmetry parameter (gaer) derived from, the Global Aerosol Data Set (GADS) for actual atmospheric and surface conditions at wavelengths 0.25, 0.5, and 0.8 (Hatziannastassiou et al. 2004)
Wavelength (/xm) raers ujael gael
The Global Aerosol Data Set (GADS), (Koepke et al. 1997) is a starting point by providing long-term mean aerosol radiative properties. These properties are highly dependent on the atmospheric relative humidity, which controls the water content of the aerosols and hence their scattering properties. The aerosol radiative properties are very sensitive to the ambient relative humidity, because it determines, along with the particle composition and the ambient temperature, the rate of condensation of water vapour on the particle's surface, thereby determining the growth rate of the aerosol particle, and hence the particle size and refractive index. In Table 6.4 are given the global mean spectral radiative properties of aerosols derived from the GADS data and NCEP/NCAR humidity data for the globe.
The aerosol extinction coefficient, j\ in cm2 (combined scattering and absorption) is generally a function of wavelength, depending on the size of the particle. For large particles we saw that we can employ Mie theory to compute the extinction properties of particles with Rayleigh scattering being the small-size limit. We may approximate the wavelength dependence of the extinction coefficient by the form
where the extinction optical depth at wavelength Xo (also known as the Angstrom turbidity coefficient) is To = joW and W is the absorber amount in particles per cm2 (the number column density). The wavelength exponent a is known as the Angstrom parameter, based on the observations of Angstrom (1929) in the wavelength range 0.35-1.00 ¡m. This parameter can be written as dlncrA . .
and thus approximately can be calculated from ln(ji/<2)
0.1 1 Parameter Size(|jm)
FlG. 6.12. Angstrom parameter as a function of particle radius for a single particle with refractive index 1.33-0.5i, calculated from the scattering efficiency at wavelengths of 440 nm and 870 nm.
Thus, if the aerosol extinction optical depth is known at two wavelengths (usually one taken in the visible and the other in the near-infra-red) then the Angstrom parameter can be estimated. The variation of the Angstrom parameter with particle radius for a single particle with refractive index 1.33-0.5i, calculated from the scattering efficiency at wavelengths 440 nm and 870 nm is shown in Fig 6.12. We see that as the particle radius becomes small we approach the Rayleigh scattering limit and a ^ 4. At the other limit of very large particles the extinction cross-section becomes wavelength independent. This variation of the Angstrom parameter is very useful for distinguishing between large and fine aerosol particles. Values of a above unity indicate fine particles (r < 0.1 pm), while below 0.5 we have coarse particles (r > 0.5 pm). In Fig. 6.13 is shown a scatter diagram of the Angstrom parameter, taking Ai = 440 nm and A2 = 870 nm, as a function of rs7o, from actual aerosol measurements by the AERONET site in Crete. The measurements in the region of low a and the higher t870 values correspond to major dust events transported from the Sahara, whilst the fine-aerosol measurements correspond to industrial pollution events from Europe. Small values of a (< 0.5) and the larger values of t870 (> 0.20) correspond to
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Aerosol Optical Thickness (870 nm)
FlG. 6.13. Scatter plot of Angstrom parameter as a function of aerosol optical depth at 870 nm, measured by the AERONET site in Crete. (Fotiadi et al. 2006)
coarse particles, associated with dust outbreaks in North African deserts during spring and late summer to autumn. Points corresponding to small values of a (< 0.5) and small T870 (0.10-0.15) correspond to transported dust during winter, whereas the small t870 values are due to frequent and efficient wet removal processes during the Mediterranean winter. These points can be also associated with transport of maritime aerosols (sea-spray). There is a wide range of a values (~0.10-2.0) for t870 < 0.2, which is due to the presence of various types of aerosol for background conditions, arising from transport and mixing processes. Such mixtures can involve background sulphate maritime aerosols, along with mineral dust, soot, and other continental natural or anthropogenic particles. The contribution of each of these particles varies with time, but coexistence of many types as internal and/or external mixture, is often possible. The bimodal nature of Mediterranean aerosols is clearly seen in Fig. 6.14, where the size distribution is shown for the four seasons. The fine mode (composed of the smaller particles) is principally of anthropogenic origin, with radius between 0.05 and 0.5 ^m, whilst the coarse mode consists of larger particles of basically natural origin, with radius ranging from 0.5 to 15 pm.
The presence of aerosols of different size distributions correspond to different chemical compositions, and these result in different aerosol extinction optical depths. In Fig. 6.15 are shown monthly mean values of aerosol extinction optical thickness (AOT) at 340, 500, 870 and 1020 nm, and Angstrom parameter a mea-
FlG. 6.14. Seasonal variation of aerosol columnar volume size distribution measured by the AERONET site in Crete. (Fotiadi et al. 2006)
sured by the AERONET station in Crete. The AOT values at 340, 500, 870 and 1020 nm indicate a significant spectral dependence of aerosol optical thickness, with decreasing values from 0.34 ±0.14 at 340 nm down to 0.11 ±0.09 at 1020 nm, implying an AOT reduction of 68% from the near-UV to near-IR wavelengths. The higher spring and autumn AOT values are associated with strong dust episodes taking place in these seasons when dust particles are transported from North African deserts. This is indicated by decreased values of Angstrom parameter during spring and autumn. Spectral differences in terms of AOT indicate a heterogeneous aerosol population, which is composed of mineral dust, marine biogenic particles and anthropogenic aerosols at different layers. Table 6.5 presents computed parameters such as the aerosol effective radius (reff) and the columnar volume, Vc, of particles per unit cross-section of atmospheric column yU,m3/yU,m2 where
for each mode, where V(ln r) is a log-normal aerosol columnar volume size distribution defined by
2 ln2 ag j
where r is the particle radius, rg is the geometric mean particle radius (50% of the particles have a radius below this value) and ag is the geometric standard
deviation. These are defined for particles with columnar population ni of radius ri by ln rg ln2 a g
Was this article helpful?
Your Alternative Fuel Solution for Saving Money, Reducing Oil Dependency, and Helping the Planet. Ethanol is an alternative to gasoline. The use of ethanol has been demonstrated to reduce greenhouse emissions slightly as compared to gasoline. Through this ebook, you are going to learn what you will need to know why choosing an alternative fuel may benefit you and your future.