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Sucrose is among the main products of photosynthesis that are deemed necessary for plant growth and survival. It is produced in the mesophyll cells of leaves and translocated to different parts of the plant through the phloem. Progress in understanding this transport process remains fraught with experimental difficulties, thereby prompting interest in theoretical approaches and laboratory studies. The Münch pressure and mass flow model is one of the accepted hypotheses describing the physics of sucrose transport in the phloem. It is based on osmosis creating an energy potential difference between the source and the sink. The flow responding to this energy potential is assumed laminar and described by the Hagen–Poiseuille equation. This study revisits such osmotically driven flows in tubes with membrane walls by including the effects of Taylor dispersion on mass transport. This effect has been overlooked in phloem flow studies. Taylor dispersion can increase the effective transport of solutes by increasing the apparent diffusion coefficient. It is shown that, in addition to the conventional diffusive correction derived for impermeable tube walls, a new adjustment to the mean advective terms arises because of osmotic effects. Because the molecular Schmidt number is very large for sucrose in water, the sucrose front speed and travel times have a direct dependence on the Péclet number for different ranges of the Münch number. This study establishes upper limits on expected Taylor dispersion enhancement of sucrose transport. 

The significance of the water-side gas transfer velocity for air–sea CO2 gas exchange (k) and its non-linear dependence on wind speed (U) is well accepted. What remains a subject of inquiry are biases associated with the form of the non-linear relation linking k to U (hereafter labeled as f(U), where f(.) stands for an arbitrary function of U), the distributional properties of U (treated as a random variable) along with other external factors influencing k, and the time-averaging period used to determine k from U. To address the latter issue, a Taylor series expansion is applied to separate f(U) into a term derived from time-averaging wind speed (labeled as ⟨U⟩, where ⟨.⟩ indicates averaging over a monthly time scale) as currently employed in climate models and additive bias corrections that vary with the statistics of U. The method was explored for nine widely used f(U) parameterizations based on remotely-sensed 6-hourly global wind products at 10 m above the sea-surface. The bias in k of monthly estimates compared to the reference 6-hourly product was shown to be mainly associated with wind variability captured by the standard deviation σσU around ⟨U⟩ or, more preferably, a dimensionless coefficient of variation Iu= σσU/⟨U⟩. The proposed correction outperforms previous methodologies that adjusted k when using ⟨U⟩ only. An unexpected outcome was that upon setting Iu2 = 0.15 to correct biases when using monthly wind speed averages, the new model produced superior results at the global and regional scale compared to prior correction methodologies. Finally, an equation relating Iu2 to the time-averaging interval (spanning from 6 h to a month) is presented to enable other sub-monthly averaging periods to be used. While the focus here is on CO2, the theoretical tactic employed can be applied to other slightly soluble gases. As monthly and climatological wind data are often used in climate models for gas transfer estimates, the proposed approach provides a robust scheme that can be readily implemented in current climate models.