Fate of products of degradation processes: consequences for climatic change.

The end products of atmospheric degradation are not only CO2 and H2O but also sulfate and nitrate depending on the chemical composition of the substances which are subject to degradation processes. Atmospheric degradation has thus a direct influence on the radiative balance of the earth not only due to formation of greenhouse gases but also of aerosols. Aerosols of a diameter of 0.1 to 2 micrometer, reflect short wave sunlight very efficiently leading to a radiative forcing which is estimated to be about -0.8 watt per m2 by IPCC. Aerosols also influence the radiative balance by way of cloud formation. If more aerosols are present, clouds are formed with more and smaller droplets and these clouds have a higher albedo and are more stable compared to clouds with larger droplets. Not only sulfate, but also nitrate and polar organic compounds, formed as intermediates in degradation processes, contribute to this direct and indirect aerosol effect. Estimates for the Netherlands indicate a direct effect of -4 watt m-2 and an indirect effect of as large as -5 watt m-2. About one third is caused by sulfates, one third by nitrates and last third by polar organic compounds. This large radiative forcing is obviously non-uniform and depends on local conditions.

North atlantic deepwater temperature change during late pliocene and late quaternary climatic cycles

Variations in the ratio of magnesium to calcium (Mg/Ca) in fossil ostracodes from Deep Sea Drilling Project Site 607 in the deep North Atlantic show that the change in bottom water temperature during late Pliocene 41,000-year obliquity cycles averaged 1.5°C between 3.2 and 2.8 million years ago (Ma) and increased to 2.3°C between 2.8 and 2.3 Ma, coincidentally with the intensification of Northern Hemisphere glaciation. During the last two 100,000-year glacial-to-interglacial climatic cycles of the Quaternary, bottom water temperatures changed by 4.5°C. These results show that glacial deepwater cooling has intensified since 3.2 Ma, most likely as the result of progressively diminished deep-water production in the North Atlantic and of the greater influence of Antarctic bottom water in the North Atlantic during glacial periods. The ostracode Mg/Ca data also allow the direct determination of the temperature component of the benthic foraminiferal oxygen isotope record from Site 607, as well as derivation of a hypothetical sea-level curve for the late Pliocene and late Quaternary. The effects of dissolution on the Mg/Ca ratios of ostracode shells appear to have been minimal.

Statistical analysis of crystallization database links protein physico-chemical features with crystallization mechanisms.

X-ray crystallography is the predominant method for obtaining atomic-scale information about biological macromolecules. Despite the success of the technique, obtaining well diffracting crystals still critically limits going from protein to structure. In practice, the crystallization process proceeds through knowledge-informed empiricism. Better physico-chemical understanding remains elusive because of the large number of variables involved, hence little guidance is available to systematically identify solution conditions that promote crystallization. To help determine relationships between macromolecular properties and their crystallization propensity, we have trained statistical models on samples for 182 proteins supplied by the Northeast Structural Genomics consortium. Gaussian processes, which capture trends beyond the reach of linear statistical models, distinguish between two main physico-chemical mechanisms driving crystallization. One is characterized by low levels of side chain entropy and has been extensively reported in the literature. The other identifies specific electrostatic interactions not previously described in the crystallization context. Because evidence for two distinct mechanisms can be gleaned both from crystal contacts and from solution conditions leading to successful crystallization, the model offers future avenues for optimizing crystallization screens based on partial structural information. The availability of crystallization data coupled with structural outcomes analyzed through state-of-the-art statistical models may thus guide macromolecular crystallization toward a more rational basis.