scholarly journals Influence of stress, temperature and crystal morphology on isothermal densification and specific surface area decrease of new snow

2014 ◽  
Vol 8 (5) ◽  
pp. 1825-1838 ◽  
Author(s):  
S. Schleef ◽  
H. Löwe ◽  
M. Schneebeli
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Linear Relation ◽  
Crystal Habit ◽  
High Temporal Resolution ◽  
Densification Rate ◽  
Experimental Conditions ◽  
Data Set ◽  
Decrease Rate

Abstract. Laboratory-based, experimental data for the microstructural evolution of new snow are scarce, though applications would benefit from a quantitative characterization of the main influences. To this end, we have analyzed the metamorphism and concurrent densification of new snow under isothermal conditions by means of X-ray microtomography and compiled a comprehensive data set of 45 time series. In contrast to previous measurements on isothermal metamorphism on time scales of weeks to months, we analyzed the initial 24–48 h of snow evolution at a high temporal resolution of 3 hours. The data set comprised natural and laboratory-grown snow, and experimental conditions included systematic variations of overburden stress, temperature and crystal habit to address the main influences on specific surface area (SSA) decrease rate and densification rate in a snowpack. For all conditions, we found a linear relation between density and SSA, indicating that metamorphism has an immediate influence for the densification of new snow. The slope of the linear relation, however, depends on the other parameters which were analyzed individually to derive a best-fit parameterization for the SSA decrease rate and densification rate. In the investigated parameter range, we found that the initial value of the SSA constituted the main morphological influence on the SSA decrease rate. In turn, the SSA decrease rate constituted the main influence on the densification rate.

scholarly journals Influence of stress, temperature and crystal habit on isothermal densification and specific surface area decrease of new snow

2014 ◽  
Vol 8 (2) ◽  
pp. 1795-1829
Author(s):  
S. Schleef ◽  
H. Löwe ◽  
M. Schneebeli
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Crystal Habit ◽  
High Temporal Resolution ◽  
Time Behavior ◽  
Densification Rate ◽  
Experimental Conditions ◽  
Data Set ◽  
Decrease Rate

Abstract. Laboratory-based, experimental data for the microstructural evolution of new snow is scarce, though applications would benefit from a quantitative characterization of the main mechanism underlying the initial microstructural changes. To this end we have analyzed the metamorphism and concurrent densification of new snow under isothermal conditions by means of X-ray microtomography and compiled a comprehensive data set of 45 time series covering the practically relevant short time behavior within the first 24–48 h in high temporal resolution. The data set comprises natural and laboratory grown snow and experimental conditions include systematic variations of overburden stress, temperature and crystal habit to address the main influences on specific surface area (SSA) decrease rate and densification rate in a natural snowpack. For all conditions we find a linear increase of the density with the SSA, indicating that metamorphism has a key influence for the densification of new snow. Corroborated by the analysis of the individual influences of external conditions we derive a best-fit parametrization for the SSA decrease rate and the densification rate as required for applications.

scholarly journals Simulation of the specific surface area of snow using a one-dimensional physical snowpack model: implementation and evaluation for subarctic snow in Alaska

2010 ◽  
Vol 4 (1) ◽  
pp. 35-51 ◽  
Author(s):  
H.-W. Jacobi ◽  
F. Domine ◽  
W. R. Simpson ◽  
T. A. Douglas ◽  
M. Sturm
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Winter Season ◽  
Data Set ◽  
Thermal Budget ◽  
One Dimensional ◽  
Snow Model ◽  
Physics Model ◽  
Snow Physics

Abstract. The specific surface area (SSA) of the snow constitutes a powerful parameter to quantify the exchange of matter and energy between the snow and the atmosphere. However, currently no snow physics model can simulate the SSA. Therefore, two different types of empirical parameterizations of the specific surface area (SSA) of snow are implemented into the existing one-dimensional snow physics model CROCUS. The parameterizations are either based on diagnostic equations relating the SSA to parameters like snow type and density or on prognostic equations that describe the change of SSA depending on snow age, snowpack temperature, and the temperature gradient within the snowpack. Simulations with the upgraded CROCUS model were performed for a subarctic snowpack, for which an extensive data set including SSA measurements is available at Fairbanks, Alaska for the winter season 2003/2004. While a reasonable agreement between simulated and observed SSA values is obtained using both parameterizations, the model tends to overestimate the SSA. This overestimation is more pronounced using the diagnostic equations compared to the results of the prognostic equations. Parts of the SSA deviations using both parameterizations can be attributed to differences between simulated and observed snow heights, densities, and temperatures. Therefore, further sensitivity studies regarding the thermal budget of the snowpack were performed. They revealed that reducing the thermal conductivity of the snow or increasing the turbulent fluxes at the snow surfaces leads to a slight improvement of the simulated thermal budget of the snowpack compared to the observations. However, their impact on further simulated parameters like snow height and SSA remains small. Including additional physical processes in the snow model may have the potential to advance the simulations of the thermal budget of the snowpack and, thus, the SSA simulations.

scholarly journals Adsorption of pharmaceuticals from aqueous solutions using biochar derived from cotton gin waste and guayule bagasse

Biochar ◽  
2020 ◽  
Author(s):  
Marlene C. Ndoun ◽  
Herschel A. Elliott ◽  
Heather E. Preisendanz ◽  
Clinton F. Williams ◽  
Allan Knopf ◽  
...  
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Functional Groups ◽  
Specific Surface Area ◽  
High Surface ◽  
Strong Interactions ◽  
Solution Ph ◽  
Experimental Conditions ◽  
Cotton Gin Waste ◽  
Cotton Gin

Abstract Biochars produced from cotton gin waste (CG) and guayule bagasse (GB) were characterized and explored as potential adsorbents for the removal of pharmaceuticals (sulfapyridine-SPY, docusate-DCT and erythromycin-ETM) from aqueous solution. An increase in biochar pyrolysis temperature from 350 οC to 700 οC led to an increase in pH, specific surface area, and surface hydrophobicity. The electronegative surface of all tested biochars indicated that non-Coulombic mechanisms were involved in adsorption of the anionic or uncharged pharmaceuticals under experimental conditions. The adsorption capacities of Sulfapyridine (SPY), Docusate (DCT) and Erythromycin (ETM) on biochar were influenced by the contact time and solution pH, as well as biochar specific surface area and functional groups. Adsorption of these pharmaceutical compounds was dominated by a complex interplay of three mechanisms: hydrophobic partitioning, hydrogen bonding and π–π electron donor–acceptor (EDA) interactions. Despite weaker π–π EDA interactions, reduced hydrophobicity of SPY− and increased electrostatic repulsion between anionic SPY− and the electronegative CG biochar surface at higher pH, the adsorption of SPY unexpectedly increased from 40% to 70% with an increase in pH from 7 to 10. Under alkaline conditions, adsorption was dominated by the formation of strong negative charge-assisted H-bonding between the sulfonamide moiety of SPY and surface carboxylic groups. There seemed to be no appreciable and consistent differences in the extent of DCT and ETM adsorption as the pH changed. Results suggest the CG and GB biochars could act as effective adsorbents for the removal of pharmaceuticals from reclaimed water prior to irrigation. High surface area biochars with physico-chemical properties (e.g., presence of functional groups, high cation and anion exchange capacities) conducive to strong interactions with polar-nonpolar functionality of pharmaceuticals could be used to achieve significant contaminant removal from water. Graphic Abstract

Synthesis and Photocatalytic Property of BiVO4/FeVO4 Composite Novel Photocatalyst

2010 ◽  
Vol 129-131 ◽  
pp. 784-788 ◽  
Author(s):  
Min Wang ◽  
Qiong Liu ◽  
Dong Zhang
Keyword(s):  
Photocatalytic Activity ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Photocatalytic Property ◽  
Precipitation Method ◽  
X Ray Diffraction ◽  
Experimental Conditions ◽  
Triclinic Phase ◽  
Xrd Patterns

BiVO4/FeVO4 composite photocatalyst samples were prepared by calcining the mixture of FeVO4 and BiVO4 precusor which were prepared through liquid phase precipitation method for further increasing the photocatalytic efficiency of FeVO4. The catalysts were characterized by X-ray diffraction (XRD), scanning electron microsoope（SEM）and specific surface area (BET). The photocatalytic activity was evaluated by photocatalytic degradation of methyl orange (MO) solution under visible light. The XRD patterns indicate that BiVO4/FeVO4 composite photocatalysts consist of triclinic phase and the lattice was not distorted beacause of doping Bi. But the morphology change greatly and the specific surface area has little change. In the experimental conditions used, the optimal photocatalytic activity for all the prepared samples was reached when BiVO4 doping was 22 at%. The degradation rate of MO was increased by 20％ or so than that of pure FeVO4.

Optimization of Experimental Conditions for the Preparation of High Specific Surface Area Bamboo-Based Activated Carbon

2015 ◽  
Vol 1090 ◽  
pp. 154-159
Author(s):  
Sheng Zhou Zhang ◽  
Hong Ying Xia ◽  
Li Bo Zhang ◽  
Jin Hui Peng ◽  
Jian Wu ◽  
...  
Keyword(s):  
Activated Carbon ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Pore Volume ◽  
Total Pore Volume ◽  
High Specific Surface Area ◽  
Raw Material ◽  
Experimental Conditions ◽  
Average Pore

Bamboo as the raw material is carbonized to prepare high specific surface area activated carbon by microwave heating under nitrogen atmosphere in our present work. Influences of activation agents on the preparation of activated carbon are studied. The results show that activation agents have a significant influence on the preparation of activated carbon. Under the heating time of 15 min, the adsorption capacity of the activated carbon prepared utilizing KOH as activation agent is the best. When the KOH/C ratio is 4, the iodine number and yield of activated carbon are 2298 mg/g and 39.82%, respectively. The BET specific surface area, total pore volume and average pore diameter of activated carbon are 3441 m2/g, 2.093 ml/g and 2.434 nm, respectively. The micropore volume of 1.304 ml/g is 62.30% of total pore volume, indicating that the activated carbon is microporous activated carbon.

scholarly journals The RHOSSA campaign: Multi-resolution monitoring of the seasonal evolution of the structure and mechanical stability of an alpine snowpack

2019 ◽  
Author(s):  
Neige Calonne ◽  
Bettina Richter ◽  
Henning Löwe ◽  
Cecilia Cetti ◽  
Judith ter Schure ◽  
...  
Keyword(s):  
Specific Surface ◽  
Crack Length ◽  
Surface Area ◽  
Specific Surface Area ◽  
Measurement Techniques ◽  
Swiss Alps ◽  
High Temporal Resolution ◽  
Critical Crack ◽  
Critical Crack Length ◽  
Seasonal Evolution

Abstract. The necessity of characterizing snow through objective, physically-motivated parameters has led to new model formulations and new measurement techniques. Consequently, essential structural parameters such as density and specific surface area (for basic characterization) or mechanical parameters such as the critical crack length (for avalanche stability characterization) gradually replace the semi-empirical indices acquired from traditional stratigraphy. These advances come along with new demands and potentials for validation. To this end, we conducted the RHOSSA field campaign, in resemblance of density (ρ) and specific surface area (SSA), at the Weissfluhjoch research site in the Swiss Alps to provide a multi-instrument, multi-resolution dataset of density, SSA, and critical crack length over the complete winter season 2015–2016. In this paper, we present the design of the campaign and a basic analysis of the measurements alongside with predictions from the model SNOWPACK. To bridge between traditional and new methods, the campaign comprises traditional profiles, density cutter, IceCube, SnowMicroPen (SMP), micro-computed-tomography, propagation saw tests, and compression tests. To bridge between different temporal resolutions, the traditional weekly to bi-weekly snow pits were complemented by daily SMP measurements. From the latter, we derived a re-calibration of the statistical retrieval of density and SSA for SMP version 4 that yields an unprecedented, spatio-temporal picture of the seasonal evolution of density and SSA in a snowpack. Finally, we provide an inter-comparison of measured and modeled estimates of density and SSA for 4 characteristic layers over the entire season to demonstrate the potential of high temporal resolution monitoring for snowpack model validation.

scholarly journals The RHOSSA campaign: Multi-resolution monitoring of the seasonal evolution of the structure and mechanical stability of an alpine snowpack

2020 ◽  
Author(s):  
Neige Calonne ◽  
Betti Richter ◽  
Henning Löwe ◽  
Cecilia Cetti ◽  
judith Ter Schure ◽  
...  
Keyword(s):  
Specific Surface ◽  
Crack Length ◽  
Surface Area ◽  
Specific Surface Area ◽  
Measurement Techniques ◽  
Swiss Alps ◽  
High Temporal Resolution ◽  
Critical Crack ◽  
Critical Crack Length ◽  
Seasonal Evolution

<p>The necessity of characterizing snow through objective, physically-motivated parameters has led to new model formulations and new measurement techniques. Consequently, essential structural parameters such as density and specific surface area (for basic characterization) or mechanical parameters such as the critical crack length (for avalanche stability characterization) gradually replace the semi-empirical indices acquired from traditional stratigraphy. These advances come along with new demands and potentials for validation. To this end, we conducted the RHOSSA field campaign, in resemblance of density (ρ) and specific surface area (SSA), at the Weissfluhjoch research site in the Swiss Alps to provide a multi-instrument, multi-resolution dataset of density, SSA, and critical crack length over the complete winter season 2015-2016. In this paper, we present the design of the campaign and a basic analysis of the measurements alongside with predictions from the model SNOWPACK. To bridge between traditional and new methods, the campaign comprises traditional profiles, density cutter, IceCube, SnowMicroPen (SMP), micro-computed-tomography, propagation saw tests, and compression tests. To bridge between different temporal resolutions, the traditional weekly to bi-weekly snow pits were complemented by daily SMP measurements. From the latter, we derived a re-calibration of the statistical retrieval of density and SSA for SMP version 4 that yields an unprecedented, spatio-temporal picture of the seasonal evolution of density and SSA in a snowpack. Finally, we provide an inter-comparison of measured and modeled estimates of density and SSA for 4 characteristic layers over the entire season to demonstrate the potential of high temporal resolution monitoring for snowpack model validation.</p>

scholarly journals The RHOSSA campaign: multi-resolution monitoring of the seasonal evolution of the structure and mechanical stability of an alpine snowpack

2020 ◽  
Vol 14 (6) ◽  
pp. 1829-1848 ◽  
Author(s):  
Neige Calonne ◽  
Bettina Richter ◽  
Henning Löwe ◽  
Cecilia Cetti ◽  
Judith ter Schure ◽  
...  
Keyword(s):  
Specific Surface ◽  
Crack Length ◽  
Surface Area ◽  
Specific Surface Area ◽  
Measurement Techniques ◽  
Swiss Alps ◽  
High Temporal Resolution ◽  
Critical Crack ◽  
Critical Crack Length ◽  
Seasonal Evolution

Abstract. The necessity of characterizing snow through objective, physically motivated parameters has led to new model formulations and new measurement techniques. Consequently, essential structural parameters such as density and specific surface area (for basic characterization) or mechanical parameters such as the critical crack length (for avalanche stability characterization) gradually replace the semiempirical indices acquired from traditional stratigraphy. These advances come along with new demands and potentials for validation. To this end, we conducted the RHOSSA field campaign, in reference to density (ρ) and specific surface area (SSA), at the Weissfluhjoch research site in the Swiss Alps to provide a multi-instrument, multi-resolution dataset of density, SSA and critical crack length over the complete winter season of 2015–2016. In this paper, we present the design of the campaign and a basic analysis of the measurements alongside predictions from the model SNOWPACK. To bridge between traditional and new methods, the campaign comprises traditional profiles, density cutter, IceCube, SnowMicroPen (SMP), micro-computed-tomography, propagation saw tests and compression tests. To bridge between different temporal resolutions, the traditional weekly to biweekly (every 2 weeks, used in this sense throughout the paper) snow pits were complemented by daily SMP measurements. From the latter, we derived a recalibration of the statistical retrieval of density and SSA for SMP version 4 that yields an unprecedented spatiotemporal picture of the seasonal evolution of density and SSA in a snowpack. Finally, we provide an intercomparison of measured and modeled estimates of density and SSA for four characteristic layers over the entire season to demonstrate the potential of high-temporal-resolution monitoring for snowpack model validation.

Effect of different experimental conditions on the specific surface area calculation of coal

2015 ◽  
Vol 58 (8) ◽  
pp. 284-289 ◽  
Author(s):  
Huan Cheng ◽  
Qi Wang ◽  
Song Zhang ◽  
Rui Guo
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Experimental Conditions

scholarly journals Simulation of the specific surface area of snow using a one-dimensional physical snowpack model: implementation and evaluation for subarctic snow in Alaska

2009 ◽  
Vol 3 (3) ◽  
pp. 681-728 ◽  
Author(s):  
H. W. Jacobi ◽  
F. Domine ◽  
W. R. Simpson ◽  
T. A. Douglas ◽  
M. Sturm
Keyword(s):  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Winter Season ◽  
Data Set ◽  
Thermal Budget ◽  
One Dimensional ◽  
Snow Model ◽  
Physics Model ◽  
Snow Physics

Abstract. The specific surface area (SSA) of the snow constitutes a powerful parameter to quantify the exchange of matter and energy between the snow and the atmosphere. However, currently no snow physics model can simulate the SSA. Therefore, two different types of empirical parameterizations of the specific surface area (SSA) of snow are implemented into the existing one-dimensional snow physics model CROCUS. The parameterizations are either based on diagnostic equations relating the SSA to parameters like snow type and density or on prognostic equations that describe the change of SSA depending on snow age, snowpack temperature, and the temperature gradient within the snowpack. Simulations with the upgraded CROCUS model were performed for a subarctic snowpack, for which an extensive data set including SSA measurements is available at Fairbanks, Alaska for the winter season 2003/2004. While a reasonable agreement between simulated and observed SSA values is obtained using both parameterizations, the model tends to overestimate the SSA. This overestimation is more pronounced using the diagnostic equations compared to the results of the prognostic equations. Parts of the SSA deviations using both parameterizations can be attributed to differences between simulated and observed snow heights, densities, and temperatures. Therefore, further sensitivity studies regarding the thermal budget of the snowpack were performed. They revealed that reducing the heat conductivity of the snow or increasing the turbulent fluxes at the snow surfaces leads to a slight improvement of the simulated thermal budget of the snowpack compared to the observations. However, their impact on further simulated parameters like snow height and SSA remains small. Including additional physical processes in the snow model may have the potential to advance the simulations of the thermal budget of the snowpack and, thus, the SSA simulations.

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