Thermodynamic properties of water sorption of jackfruit (Artocarpus heterophyllus Lam.) as a function of moisture content

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Photosynthetic responses and proline content of mature and young leaves of sunflower plants under water deficit

In mature and young leaves of sunflower (Helianthus annuus L. cv. Catissol-01) plants grown in the greenhouse, photosynthetic rate, stomatal conductance, and transpiration rate declined during water stress independently of leaf age and recovered after 24-h rehydration. The intercellular CO 2 concentration, chlorophyll (Chl) content, and photochemical activity were not affected by water stress. However, non-photochemical quenching increased in mature stressed leaves. Rehydration recovered the levels of non-photochemical quenching and increased the F v/F m in young leaves. Drought did not alter the total Chl content. However, the accumulation of proline under drought was dependent on leaf age: higher content of proline was found in young leaves. After 24 h of rehydration the content of proline returned to the same contents as in control plants.

A study of the effect of overshooting deep convection on the water content of the TTL and lower stratosphere from Cloud Resolving Model simulations

Simulations of overshooting, tropical deep convection using a Cloud Resolving Model with bulk microphysics are presented in order to examine the effect on the water content of the TTL (Tropical Tropopause Layer) and lower stratosphere. This case study is a subproject of the HIBISCUS (Impact of tropical convection on the upper troposphere and lower stratosphere at global scale) campaign, which took place in Bauru, Brazil (22° S, 49° W), from the end of January to early March 2004. Comparisons between 2-D and 3-D simulations suggest that the use of 3-D dynamics is vital in order to capture the mixing between the overshoot and the stratospheric air, which caused evaporation of ice and resulted in an overall moistening of the lower stratosphere. In contrast, a dehydrating effect was predicted by the 2-D simulation due to the extra time, allowed by the lack of mixing, for the ice transported to the region to precipitate out of the overshoot air. Three different strengths of convection are simulated in 3-D by applying successively lower heating rates (used to initiate the convection) in the boundary layer. Moistening is produced in all cases, indicating that convective vigour is not a factor in whether moistening or dehydration is produced by clouds that penetrate the tropopause, since the weakest case only just did so. An estimate of the moistening effect of these clouds on an air parcel traversing a convective region is made based on the domain mean simulated moistening and the frequency of convective events observed by the IPMet (Instituto de Pesquisas Meteorológicas, Universidade Estadual Paulista) radar (S-band type at 2.8 Ghz) to have the same 10 dBZ echo top height as those simulated. These suggest a fairly significant mean moistening of 0.26, 0.13 and 0.05 ppmv in the strongest, medium and weakest cases, respectively, for heights between 16 and 17 km. Since the cold point and WMO (World Meteorological Organization) tropopause in this region lies at ∼ 15.9 km, this is likely to represent direct stratospheric moistening. Much more moistening is predicted for the 15-16 km height range with increases of 0.85-2.8 ppmv predicted. However, it would be required that this air is lofted through the tropopause via the Brewer Dobson circulation in order for it to have a stratospheric effect. Whether this is likely is uncertain and, in addition, the dehydration of air as it passes through the cold trap and the number of times that trajectories sample convective regions needs to be taken into account to gauge the overall stratospheric effect. Nevertheless, the results suggest a potentially significant role for convection in determining the stratospheric water content. Sensitivity tests exploring the impact of increased aerosol numbers in the boundary layer suggest that a corresponding rise in cloud droplet numbers at cloud base would increase the number concentrations of the ice crystals transported to the TTL, which had the effect of reducing the fall speeds of the ice and causing a ∼13% rise in the mean vapour increase in both the 15-16 and 16-17 km height ranges, respectively, when compared to the control case. Increases in the total water were much larger, being 34% and 132% higher for the same height ranges, but it is unclear whether the extra ice will be able to evaporate before precipitating from the region. These results suggest a possible impact of natural and anthropogenic aerosols on how convective clouds affect stratospheric moisture levels.

The kinetic of mullite crystallization: Effect of water content

The kinetic of mullite crystallization from sol–gel method, with different water content, was investigated under non-isothermal conditions using DTA. The sols were obtained from Al(NO3)3.9H2O (ANN) and Si(OC2H5)4 (TEOS) mixtures by varying the water–alcohol content of the system. The crystalline phase changes were verified by X-ray diffraction (XRD). For a sample prepared using ethanol-based alkoxide solution (M0), only Al-poor mullite (p-mullite) crystallizes at 1000 °C; for the one synthesized with low water concentration (M6) Al-rich mullite (r-mullite) and spinel crystallize together; and for a sample prepared using a water-based alkoxide solution only spinel is formed. Thus, the variation of water contents during the synthesis caused great variations in the course of mullitization process. The average value of the apparent activation energy determined for p-mullite, r-mullite and spinel phase crystallization were found to be E = (899 ± 61) kJ mol−1, E = (1015 ± 272) kJ mol−1 and E = (980 ± 196) kJ mol−1, respectively. These results showed that sample M(0) was a monophasic gel, where aluminum and silicon atoms are mixed at a molecular level while sample M(100) was a diphasic gel, where silicon and aluminum atoms are distributed in a nanometric level. The fast reaction between TEOS and water molecules is responsible for this great difference in the sample's homogeneity. The kinetic model of the crystallization process was determined using Malek's procedure. It was established that the crystallization of p-mullite, r-mullite and spinel phase can be described by Šesták–Berggren autocatalytic model.