The Experts below are selected from a list of 47829 Experts worldwide ranked by ideXlab platform
Ilona Riipinen - One of the best experts on this subject based on the ideXlab platform.
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succinic acid in aqueous solution connecting microscopic Surface composition and Macroscopic Surface tension
Physical Chemistry Chemical Physics, 2014Co-Authors: Josephina Werner, Jan Julin, Maryam Dalirian, Nonne L Prisle, Gunnar Ohrwall, Ingmar Persson, Olle Bjorneholm, Ilona RiipinenAbstract:The water-vapor interface of aqueous solutions of succinic acid, where pH values and bulk concentrations were varied, has been studied using Surface sensitive X-ray photoelectron spectroscopy (XPS) and molecular dynamics (MD) simulations. It was found that succinic acid has a considerably higher propensity to reside in the aqueous Surface region than its deprotonated form, which is effectively depleted from the Surface due to the two strongly hydrated carboxylate groups. From both XPS experiments and MD simulations a strongly increased concentration of the acid form in the Surface region compared to the bulk concentration was found and quantified. Detailed analysis of the Surface of succinic acid solutions at different bulk concentrations led to the conclusion that succinic acid saturates the aqueous Surface at high bulk concentrations. With the aid of MD simulations the thickness of the Surface layer could be estimated, which enabled the quantification of Surface concentration of succinic acid as a multiple of the known bulk concentration. The obtained enrichment factors were successfully used to model the Surface tension of these binary aqueous solutions using two different models that account for the Surface enrichment. This underlines the close correlation of increased concentration at the Surface relative to the bulk and reduced Surface tension of aqueous solutions of succinic acid. The results of this study shed light on the microscopic origin of Surface tension, a Macroscopic property. Furthermore, the impact of the results from this study on atmospheric modeling is discussed.
Jesus Revuelto - One of the best experts on this subject based on the ideXlab platform.
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snow albedo sensitivity to Macroscopic Surface roughness using a new ray tracing model
The Cryosphere, 2020Co-Authors: Fanny Larue, Laurent Arnaud, Ines Ollivier, Clement Delcourt, Maxim Lamare, Francois Tuzet, Ghislain Picard, Jesus RevueltoAbstract:Abstract. Most models simulating snow albedo assume a flat and smooth Surface, neglecting Surface roughness. However, the presence of Macroscopic roughness leads to a systematic decrease in albedo due to two effects: (1) photons are trapped in concavities (multiple reflection effect) and (2) when the sun is low, the roughness sides facing the sun experience an overall decrease in the local incidence angle relative to a smooth Surface, promoting higher absorption, whilst the other sides have weak contributions because of the increased incidence angle or because they are shadowed (called the effective-angle effect here). This paper aims to quantify the impact of Surface roughness on albedo and to assess the respective role of these two effects, with (1) observations over varying amounts of Surface roughness and (2) simulations using the new rough Surface ray-tracing (RSRT) model, based on a Monte Carlo method for photon transport calculation. The observations include spectral albedo (400–1050 nm) over manually created roughness Surfaces with multiple geometrical characteristics. Measurements highlight that even a low fraction of Surface roughness features (7 % of the Surface) causes an albedo decrease of 0.02 at 1000 nm when the solar zenith angle ( θs ) is larger than 50 ∘ . For higher fractions (13 %, 27 % and 63 %), and when the roughness orientation is perpendicular to the sun, the decrease is of 0.03–0.04 at 700 nm and of 0.06–0.10 at 1000 nm. The impact is 20 % lower when roughness orientation is parallel to the sun. The observations are subsequently compared to RSRT simulations. Accounting for Surface roughness improves the model observation agreement by a factor of 2 at 700 and 1000 nm (errors of 0.03 and 0.04, respectively) compared to simulations considering a flat smooth Surface. The model is used to explore the albedo sensitivity to Surface roughness with varying snow properties and illumination conditions. Both multiple reflections and the effective-angle effect have a greater impact with low specific Surface area (SSA; m 2 kg −1 ). The effective-angle effect also increases rapidly with θs at large θs . This latter effect is larger when the overall slope of the Surface is facing away from the sun and has a roughness orientation perpendicular to the sun. For a snowpack where artificial Surface roughness features were created, we showed that a broadband albedo decrease of 0.05 may cause an increase in the net shortwave radiation of 80 % (from 15 to 27 W m −2 ). This paper highlights the necessity of considering Surface roughness in the estimation of the Surface energy budget and opens the way for considering natural rough Surfaces in snow modelling.
Maxim Lamare - One of the best experts on this subject based on the ideXlab platform.
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snow albedo sensitivity to Macroscopic Surface roughness using a new ray tracing model
The Cryosphere, 2020Co-Authors: Fanny Larue, Laurent Arnaud, Ines Ollivier, Clement Delcourt, Maxim Lamare, Francois Tuzet, Ghislain Picard, Jesus RevueltoAbstract:Abstract. Most models simulating snow albedo assume a flat and smooth Surface, neglecting Surface roughness. However, the presence of Macroscopic roughness leads to a systematic decrease in albedo due to two effects: (1) photons are trapped in concavities (multiple reflection effect) and (2) when the sun is low, the roughness sides facing the sun experience an overall decrease in the local incidence angle relative to a smooth Surface, promoting higher absorption, whilst the other sides have weak contributions because of the increased incidence angle or because they are shadowed (called the effective-angle effect here). This paper aims to quantify the impact of Surface roughness on albedo and to assess the respective role of these two effects, with (1) observations over varying amounts of Surface roughness and (2) simulations using the new rough Surface ray-tracing (RSRT) model, based on a Monte Carlo method for photon transport calculation. The observations include spectral albedo (400–1050 nm) over manually created roughness Surfaces with multiple geometrical characteristics. Measurements highlight that even a low fraction of Surface roughness features (7 % of the Surface) causes an albedo decrease of 0.02 at 1000 nm when the solar zenith angle ( θs ) is larger than 50 ∘ . For higher fractions (13 %, 27 % and 63 %), and when the roughness orientation is perpendicular to the sun, the decrease is of 0.03–0.04 at 700 nm and of 0.06–0.10 at 1000 nm. The impact is 20 % lower when roughness orientation is parallel to the sun. The observations are subsequently compared to RSRT simulations. Accounting for Surface roughness improves the model observation agreement by a factor of 2 at 700 and 1000 nm (errors of 0.03 and 0.04, respectively) compared to simulations considering a flat smooth Surface. The model is used to explore the albedo sensitivity to Surface roughness with varying snow properties and illumination conditions. Both multiple reflections and the effective-angle effect have a greater impact with low specific Surface area (SSA; m 2 kg −1 ). The effective-angle effect also increases rapidly with θs at large θs . This latter effect is larger when the overall slope of the Surface is facing away from the sun and has a roughness orientation perpendicular to the sun. For a snowpack where artificial Surface roughness features were created, we showed that a broadband albedo decrease of 0.05 may cause an increase in the net shortwave radiation of 80 % (from 15 to 27 W m −2 ). This paper highlights the necessity of considering Surface roughness in the estimation of the Surface energy budget and opens the way for considering natural rough Surfaces in snow modelling.
Francois Tuzet - One of the best experts on this subject based on the ideXlab platform.
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snow albedo sensitivity to Macroscopic Surface roughness using a new ray tracing model
The Cryosphere, 2020Co-Authors: Fanny Larue, Laurent Arnaud, Ines Ollivier, Clement Delcourt, Maxim Lamare, Francois Tuzet, Ghislain Picard, Jesus RevueltoAbstract:Abstract. Most models simulating snow albedo assume a flat and smooth Surface, neglecting Surface roughness. However, the presence of Macroscopic roughness leads to a systematic decrease in albedo due to two effects: (1) photons are trapped in concavities (multiple reflection effect) and (2) when the sun is low, the roughness sides facing the sun experience an overall decrease in the local incidence angle relative to a smooth Surface, promoting higher absorption, whilst the other sides have weak contributions because of the increased incidence angle or because they are shadowed (called the effective-angle effect here). This paper aims to quantify the impact of Surface roughness on albedo and to assess the respective role of these two effects, with (1) observations over varying amounts of Surface roughness and (2) simulations using the new rough Surface ray-tracing (RSRT) model, based on a Monte Carlo method for photon transport calculation. The observations include spectral albedo (400–1050 nm) over manually created roughness Surfaces with multiple geometrical characteristics. Measurements highlight that even a low fraction of Surface roughness features (7 % of the Surface) causes an albedo decrease of 0.02 at 1000 nm when the solar zenith angle ( θs ) is larger than 50 ∘ . For higher fractions (13 %, 27 % and 63 %), and when the roughness orientation is perpendicular to the sun, the decrease is of 0.03–0.04 at 700 nm and of 0.06–0.10 at 1000 nm. The impact is 20 % lower when roughness orientation is parallel to the sun. The observations are subsequently compared to RSRT simulations. Accounting for Surface roughness improves the model observation agreement by a factor of 2 at 700 and 1000 nm (errors of 0.03 and 0.04, respectively) compared to simulations considering a flat smooth Surface. The model is used to explore the albedo sensitivity to Surface roughness with varying snow properties and illumination conditions. Both multiple reflections and the effective-angle effect have a greater impact with low specific Surface area (SSA; m 2 kg −1 ). The effective-angle effect also increases rapidly with θs at large θs . This latter effect is larger when the overall slope of the Surface is facing away from the sun and has a roughness orientation perpendicular to the sun. For a snowpack where artificial Surface roughness features were created, we showed that a broadband albedo decrease of 0.05 may cause an increase in the net shortwave radiation of 80 % (from 15 to 27 W m −2 ). This paper highlights the necessity of considering Surface roughness in the estimation of the Surface energy budget and opens the way for considering natural rough Surfaces in snow modelling.
Josephina Werner - One of the best experts on this subject based on the ideXlab platform.
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succinic acid in aqueous solution connecting microscopic Surface composition and Macroscopic Surface tension
Physical Chemistry Chemical Physics, 2014Co-Authors: Josephina Werner, Jan Julin, Maryam Dalirian, Nonne L Prisle, Gunnar Ohrwall, Ingmar Persson, Olle Bjorneholm, Ilona RiipinenAbstract:The water-vapor interface of aqueous solutions of succinic acid, where pH values and bulk concentrations were varied, has been studied using Surface sensitive X-ray photoelectron spectroscopy (XPS) and molecular dynamics (MD) simulations. It was found that succinic acid has a considerably higher propensity to reside in the aqueous Surface region than its deprotonated form, which is effectively depleted from the Surface due to the two strongly hydrated carboxylate groups. From both XPS experiments and MD simulations a strongly increased concentration of the acid form in the Surface region compared to the bulk concentration was found and quantified. Detailed analysis of the Surface of succinic acid solutions at different bulk concentrations led to the conclusion that succinic acid saturates the aqueous Surface at high bulk concentrations. With the aid of MD simulations the thickness of the Surface layer could be estimated, which enabled the quantification of Surface concentration of succinic acid as a multiple of the known bulk concentration. The obtained enrichment factors were successfully used to model the Surface tension of these binary aqueous solutions using two different models that account for the Surface enrichment. This underlines the close correlation of increased concentration at the Surface relative to the bulk and reduced Surface tension of aqueous solutions of succinic acid. The results of this study shed light on the microscopic origin of Surface tension, a Macroscopic property. Furthermore, the impact of the results from this study on atmospheric modeling is discussed.
