5.2.2.5 Primary biogenic aerosols

Primary biogenic aerosol consists of plant debris (cuticular waxes, leaf fragments, etc.), humic matter, and microbial particles (bacteria, fungi, viruses, algae, pollen, spores, etc.). Unfortunately, little information is available that would allow a reliable estimate of the contribution of primary biogenic particles to the atmospheric aerosol. In an urban, temperate setting, Matthias-Maser and Jaenicke (1995) have found concentrations of 10 to 30% of the total aerosol volume in both the sub-micron and super-micron size fractions. Their contribution in densely vegetated regions, particularly the moist tropics, could be even more significant. This view is supported by analyses of the lipid fraction in Amazonian aerosols (Simoneit et al., 1990).

The presence of humic-like substances makes this aerosol light-absorbing, especially in the UV-B region (Havers et al., 1998), and there is evidence that primary biogenic particles may be able to act both as cloud droplet and ice nuclei (Schnell and Vali, 1976). They may, therefore, be of importance for both direct and indirect climatic effects, but not enough is known at this time to assess their role with any confidence. Since their atmospheric abundance may undergo large changes as a result of land-use change, they deserve more scientific study.

5.2.2.6 Sulphates

Sulphate aerosols are produced by chemical reactions in the atmosphere from gaseous precursors (with the exception of sea salt sulphate and gypsum dust particles). The key controlling variables for the production of sulphate aerosol from its precursors are:

1. the source strength of the precursor substances,
2. the fraction of the precursors removed before conversion to sulphate,
3. the chemical transformation rates along with the gas-phase and aqueous chemical pathways for sulphate formation from SO₂.

The atmospheric burden of the sulphate aerosol is then regulated by the interplay of production, transport and deposition (wet and dry).

The two main sulphate precursors are SO₂ from anthropogenic sources and volcanoes, and DMS from biogenic sources, especially marine plankton (Table 5.2). Since SO₂ emissions are mostly related to fossil fuel burning, the source distribution and magnitude for this trace gas are fairly well-known, and recent estimates differ by no more than about 20 to 30% (Lelieveld et al., 1997). Volcanic emissions will be addressed in Section 5.2.2.8.

Estimating the emission of marine biogenic DMS requires a gridded database on its concentration in surface sea water and a parametrization of the sea/air gas transfer process. A 1ºx1º monthly data set of DMS in surface water has been obtained from some 16,000 observations using a heuristic interpolation scheme (Kettle et al., 1999). Estimates for data-sparse regions are generated by assuming similarity to comparable biogeographic regions with adequate data coverage. Consequently, while the global mean surface DMS concentration is quite robust because of the large data set used (error estimate ± 50%), the estimates for specific regions and seasons remain highly uncertain in many ocean regions where sampling has been sparse (error up to factor of 5). These uncertainties are compounded with those resulting from the lack of a generally accepted air/sea flux parametrization. The approach of Liss and Merlivat (1986) and that of Wanninkhof (1992) yield fluxes differing by a factor of two (Kettle and Andreae, 2000). In Table 5.2, we use the mean of these two estimates (24 Tg S(DMS)/yr).

The chemical pathway of conversion of precursors to sulphate is important because it changes the radiative effects. Most SO₂ is converted to sulphate either in the gas phase or in cloud droplets that later evaporate. Model calculations suggest that aqueous phase oxidation is dominant globally (Table 5.5). Both processes produce sulphate mostly in sub-micron aerosols that are efficient light scatterers, but the precise size distribution of sulphate in aerosols is different for gas phase and aqueous production. The size distribution of the sulphate formed in the gas phase process also depends on the interplay between nucleation, condensation and coagulation. Models that describe this interplay are in an early stage of development, and, unfortunately, there are substantial inconsistencies between our theoretical description of nucleation and condensation and the rates of these processes inferred from atmospheric measurements (Eisele and McMurry, 1997; Weber et al., 1999). Thus, most models of sulphate aerosol have simply assumed a size distribution based on present day measurements. Because there is no general reason that this same size should have applied in the past or will in the future, this lends considerable uncertainty to calculations of forcing. Many of the same issues about nucleation and condensation also apply to secondary organic aerosols.

Table 5.5: Production parameters and burdens of SO2 and aerosol sulphate as predicted by eleven different models.
Model	Sulphur source Tg S/yr	Precursor deposition %	Gas phase oxidation %	Aqueous oxidation %	SO2 burden Tg S	t (SO2) days	Sulphate dry deposition %	Sulphate wet deposition %	SO42- burden Tg S	t(SO42-) days	P days
A	94.5	47	8	45	0.30	1.1	16	84	0.77	5.0	2.9
B	122.8	49	5	46	0.20	0.6	27	73	0.80	4.6	2.3
C	100.7	49	17	34	0.43	1.5	13	87	0.63	4.4	2.2
D	80.4	44	16	39	0.56	2.6	20	80	0.73	5.7	3.3
E	106.0	54	6	40	0.36	1.2	11	89	0.55	4.1	1.9
F	90.0	18	18	64	0.61	2.4	22	78	0.96	4.7	3.8
G	82.5	33	12	56	0.40	1.9	7	93	0.57	3.8	2.5
H	95.7	45	13	42	0.54	2.4	18	82	1.03	7.2	3.9
I	125.6	47	9	44	0.63	2.0	16	84	0.74	3.6	2.2
J	90.0	24	15	59	0.60	2.3	25	75	1.10	5.3	4.5
K	92.5	56	15	27	0.43	1.8	13	87	0.63	5.8	2.5
Average	98.2	42	12	45	0.46	1.8	17	83	0.77	4.9	2.9
Standard deviation	14.7	12	5	11	0.14	0.6	6	6	0.19	1.0	0.8
Model/Reference: A MOGUNTIA/Langner and Rodhe, 1991; B: IMAGES/Pham et al., 1996; C: ECHAM3/Feichter et al., 1996; D: Harvard-GISS / Koch et al., 1999; E: CCM1-GRANTOUR/Chuang et al., 1997; F:ECHAM4/Roelofs et al., 1998; G: CCM3/Barth et al., 2000 and Rasch et al., 2000a; H: CCC/Lohmann et al., 1999a.; I: Iversen et al., 2000; J: Lelieveld et al., 1997; K: GOCART/Chin et al., 2000.

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