975 resultados para Stomatal conductance to water vapour


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A multiplicative and a semi-mechanistic, BWB-type [Ball, J.T., Woodrow, I.E., Berry, J.A., 1987. A model predicting stomatalconductance and its contribution to the control of photosynthesis under different environmental conditions. In: Biggens, J. (Ed.), Progress in Photosynthesis Research, vol. IV. Martinus Nijhoff, Dordrecht, pp. 221–224.] algorithm for calculating stomatalconductance (gs) at the leaf level have been parameterised for two crop and two tree species to test their use in regional scale ozone deposition modelling. The algorithms were tested against measured, site-specific data for durum wheat, grapevine, beech and birch of different European provenances. A direct comparison of both algorithms showed a similar performance in predicting hourly means and daily time-courses of gs, whereas the multiplicative algorithm outperformed the BWB-type algorithm in modelling seasonal time-courses due to the inclusion of a phenology function. The re-parameterisation of the algorithms for local conditions in order to validate ozone deposition modelling on a European scale reveals the higher input requirements of the BWB-type algorithm as compared to the multiplicative algorithm because of the need of the former to model net photosynthesis (An)

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Fluctuations of trace gas activity as a response to variations in weather and microclimate conditions were monitored over a year in a shallow volcanic cave (Painted Cave, Galdar, Canary Islands, Spain). 222Rn concentration was used due to its greater sensitivity to hygrothermal variations than CO2 concentration. Radon concentration in the cave increases as effective vapour condensation within the porous system of the rock surfaces inside the cave increases due to humidity levels of more than 70%. Condensed water content in pores was assessed and linked to a reduction in the direct passage of trace gases. Fluctuations in radon activity as a response to variations in weather and microclimate conditions were statistically identified by clustering entropy changes on the radon signal and parameterised to predict radon concentration anomalies. This raises important implications for other research fields, including the surveillance of shallow volcanic and seismic activity, preventive conservation of cultural heritage in indoor spaces, indoor air quality control and studies to improve understanding of the role of subterranean terrestrial ecosystems as reservoirs and/or temporary sources of trace gases.