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FIGURE 14.36 Predicted mean radiative forcing at the top of the atmosphere due to mineral dust from scattering, absorption, and their total (adapted from Tegen et at., 1996).

dust were about as important as that due to carbonaceous aerosols and scattering by sulfate aerosols. Soko-lik and Toon (1996) point out that on a regional basis, direct radiative forcing due to dust aerosols can significantly exceed that of sulfate. Light scattering by mineral dust has been shown to be relatively insensitive to the relative humidity (Li-Jones et al., 1998).

Because scattering and absorption contribute to radiative forcing in opposite directions (Fig. 14.36), the positive radiative forcing and negative radiative forcing largely cancel at the top of the atmosphere. For example, for the model study shown in Fig. 14.36, the global mean net radiative forcing at the top of the atmosphere due to dust associated with disturbances from anthropogenic processes was only +0.09 W m~2. However, the net radiative effect of this dust at the surface is calculated to be negative, —1 W m~2, since both scattering and absorption reduce the sun intensity reaching the ground (Tegen et al., 1996). Finally, the absorption of infrared radiation by mineral dusts leads to direct heating of the atmosphere, which may alter atmospheric circulation processes (Tegen et al., 1996).

In short, the combination of absorption and scattering of light by mineral dusts, combined with an increase in these due to anthropogenic activities, has the potential to contribute to climate change. However, many uncertainties need to be removed before these effects can be confidently quantified. For example, the infrared absorption depends on the composition of the dust and as seen in Fig. 14.35, this can be quite variable from location to location and even as a function of time from one source. This one effect alone can lead to a large variability in the predicted effects on radiative forcing (Sokolik et al., 1998).

2. Indirect Effects of Aerosol Particles a. Clouds

In addition to the direct effects on radiative forcing due to scattering and absorption of light, aerosol particles also have indirect effects, which may, in many instances, be more important than the direct radiative forcing. These indirect effects are based on the ability of some (but as we shall see, not all) aerosol particles to act as cloud condensation nuclei, CCN. This changes the number concentration of droplets in clouds and their size distribution, which can alter the precipitation rate. In addition, such changes in the cloud characteristics are believed to alter the lifetime and extent of the cloud (e.g., see Cess et al., 1997; and Lohmann and Feichter, 1997). As discussed in more detail shortly, clouds decrease the incoming solar radiation by reflecting a significant amount back out to space (the



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Solar scattering xv '

Solar scattering xv '

predominant effect), but high clouds can also lead to tropospheric warming through interaction with the longwave terrestrial thermal radiation. In addition, there are some data, which are presently controversial, suggesting that clouds absorb solar radiation directly to a larger extent than expected. If proven true, this can lead to thermal heating and effects on atmospheric circulation processes that are greater than have been understood to the present.

Twomey suggested in 1974 that anthropogenic emissions could affect cloud properties and albedo, i.e., have an indirect effect on global climate. Attention was further drawn to such indirect effects in 1987 when Charlson, Lovelock, Andreae, and Warren proposed a series of feedbacks involving dimethyl sulfide emitted by phytoplankton in seawater, CCN, and clouds. Dimethyl sulfide (DMS) is known to be oxidized in part to sulfate (see Chapter 8.E.f), which acts as a source of CCN and hence affects cloud properties, including albedo. Thus, DMS and its oxidation products such as methanesulfonate have been shown in a number of studies to correlate with CCN (Durkee et al., 1991; Hegg et al., 1991a,b; Ayers and Gras, 1991; Berresheim et al., 1993; Quinn et al., 1993; Putaud et al., 1993; Lawrence, 1993; Andreae et al., 1995; Ayers et al., 1995). The relationship between DMS and CCN may not be linear, however. For example, the model of Pandis et al. (1994) predicts that small DMS emission fluxes (<1.3 /¿mol m 2 day-1) do not lead to new CCN since much of the oxidation of SOz from DMS occurs in existing sea salt particles (e.g., see Sievering et al., 1992; Chameides and Stelso, 1992). However, at fluxes > 2.3 /¿mol m~2 day-1, new CCN are predicted by the model to be formed in an approximately linear relationship. Average DMS fluxes measured over the North Atlantic have been observed that span this range, from 1.2 to 12 ^mol m~2 day-1, with peaks up to 39 ;u,mol m"2 day-1 (Tarrason et al., 1995). Over the Southern Ocean, a range from 0.2 to 5 /¿mol m~2 day-1 has been measured (Ayers et al., 1995). This suggests that the effect of DMS on CCN may vary geographically and seasonally.

The seasonal cycle of CCN has also been shown to be correlated with that of cloud optical depth in one remote marine area (Boers et al., 1994), and the isotope composition of non-sea salt sulfate over remote regions of the southern Pacific Ocean has been shown to be consistent with a DMS source (Calhoun et al., 1991).

Based on such correlations, it is reasonable to assume that the Twomey proposal is applicable, i.e., that anthropogenic emissions of S02 and other species that form particles in the atmosphere may contribute to CCN and hence have indirect effects on climate.

Charlson et al. (1987) drew attention to the potential importance of feedback loops in which increased DMS emissions lead to increased sulfate CCN, increased clouds, and cloud albedo, followed by changes in the temperature and solar radiation at the surface. Changes in temperature and solar radiation might then alter DMS production, although whether in terms of increased or decreased emissions is uncertain. Despite many studies, the details and importance of such feedbacks remain to be elucidated (e.g., see Schwartz, 1988; Baker and Charlson, 1990; Lin et al., 1992; Hegg, 1990, 1993a, 1993b; Chameides and Stelson, 1992; Raes and Van Dingenen, 1992, 1995; Sievering et al., 1992; Lin et al., 1993a, 1993b; Russell et al., 1994; Pandis et al., 1994, 1995; Raes, 1995; Capaldo and Pandis, 1997; and Andreae and Crutzen, 1997). For example, Bates and Quinn (1997) report that the DMS concentration in the surface seawater of the equatorial Pacific was relatively insensitive to changes in the properties of the atmosphere (e.g., cloud cover and precipitation) and oceans (e.g., sea surface temperature, mixed layer depths, and upwelling rates) associated with El Nino-Southern Oscillation events.

The following sections focus on the potential indirect effects of aerosol particles due to anthropogenic contributions, which, unlike the natural emissions, are expected to provide a contribution that changes with time.

Effect of aerosol particles on cloud drop number concentrations and size distributions Clouds and fogs are characterized by their droplet size distribution as well as their liquid water content. Fog droplets typically have radii in the range from a few pm to ~ 30-40 pm and liquid water contents in the range of 0.05-0.1 g m~3. Clouds generally have droplet radii from 5 /jlm up to ~100 pm, with typical liquid water contents of ~0.05-2.5 g m"3 (e.g., see Stephens, 1978, 1979). For a description of cloud types, mechanisms of formation, and characteristics, see Wallace and Hobbs (1977), Pruppacher (1986), Cotton and Anthes (1989), Heyms-field (1993), and Pruppacher and Klett (1997).

There are several basic physical-chemical principles involved in the ability of aerosol particles to act as CCN and hence lead to cloud formation. These are the Kelvin effect (increased vapor pressure over a curved surface) and the lowering of vapor pressure of a solvent by a nonvolatile solute (one of the colligative properties). In Box 14.2, we briefly review these and then apply them to the development of the well-known Köhler curves that determine which particles will grow into cloud droplets by condensation of water vapor and which will not.

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