77 research outputs found
An overlooked mechanism underlying the attenuated temperature response of soil heterotrophic respiration
Biogeochemical reactions occurring in soil pore space underpin gaseous emissions measured at macroscopic scales but are difficult to quantify due to their complexity and heterogeneity. We develop a volumetric-average method to calculate aerobic respiration rates analytically from soil with microscopic soil structure represented explicitly. Soil water content in the model is the result of the volumetric-average of the microscopic processes, and it is nonlinearly coupled with temperature and other factors. Since many biogeochemical reactions are driven by oxygen (O2) which must overcome various resistances before reaching reactive microsites from the atmosphere, the volumetric-average results in negative feedback between temperature and soil respiration, with the magnitude of the feedback increasing with soil water content and substrate quality. Comparisons with various experiments show the model reproduces the variation of carbon dioxide emission from soils under different water content and temperature gradients, indicating that it captures the key microscopic processes underpinning soil respiration. We show that alongside thermal microbial adaptation, substrate heterogeneity and microbial turnover and carbon use efficiency, O2 dissolution and diffusion in water associated with soil pore space is another key explanation for the attenuated temperature response of soil respiration and should be considered in developing soil organic carbon models
Parameterization and prediction of nanoparticle transport in porous media : a reanalysis using artificial neural network
The continuing rapid expansion of industrial and consumer processes based on nanoparticles (NP) necessitates a robust model for delineating their fate and transport in groundwater. An ability to reliably specify the full parameter set for prediction of NP transport using continuum models is crucial. In this paper we report the reanalysis of a data set of 493 published column experiment outcomes together with their continuum modeling results. Experimental properties were parameterized into 20 factors which are commonly available. They were then used to predict five key continuum model parameters as well as the effluent concentration via artificial neural network (ANN)-based correlations. The Partial Derivatives (PaD) technique and Monte Carlo method were used for the analysis of sensitivities and model-produced uncertainties, respectively. The outcomes shed light on several controversial relationships between the parameters, e.g., it was revealed that the trend of math formula with average pore water velocity was positive. The resulting correlations, despite being developed based on a âblack-boxâ technique (ANN), were able to explain the effects of theoretical parameters such as critical deposition concentration (CDC), even though these parameters were not explicitly considered in the model. Porous media heterogeneity was considered as a parameter for the first time and showed sensitivities higher than those of dispersivity. The model performance was validated well against subsets of the experimental data and was compared with current models. The robustness of the correlation matrices was not completely satisfactory, since they failed to predict the experimental breakthrough curves (BTCs) at extreme values of ionic strengths
Thank You to Our 2021 Peer Reviewers
The editorial board of AGU Advances thanks the individuals who reviewed for the journal in 2021. © 2022. The Authors. AGU Advances published by Wiley Periodicals LLC on behalf of American Geophysical Union
Seasonal melting and the formation of sedimentary rocks on Mars, with predictions for the Gale Crater mound
A model for the formation and distribution of sedimentary rocks on Mars is
proposed. The rate-limiting step is supply of liquid water from seasonal
melting of snow or ice. The model is run for a O(10^2) mbar pure CO2
atmosphere, dusty snow, and solar luminosity reduced by 23%. For these
conditions snow only melts near the equator, and only when obliquity >40
degrees, eccentricity >0.12, and perihelion occurs near equinox. These
requirements for melting are satisfied by 0.01-20% of the probability
distribution of Mars' past spin-orbit parameters. Total melt production is
sufficient to account for aqueous alteration of the sedimentary rocks. The
pattern of seasonal snowmelt is integrated over all spin-orbit parameters and
compared to the observed distribution of sedimentary rocks. The global
distribution of snowmelt has maxima in Valles Marineris, Meridiani Planum and
Gale Crater. These correspond to maxima in the sedimentary-rock distribution.
Higher pressures and especially higher temperatures lead to melting over a
broader range of spin-orbit parameters. The pattern of sedimentary rocks on
Mars is most consistent with a Mars paleoclimate that only rarely produced
enough meltwater to precipitate aqueous cements and indurate sediment. The
results suggest intermittency of snowmelt and long globally-dry intervals,
unfavorable for past life on Mars. This model makes testable predictions for
the Mars Science Laboratory rover at Gale Crater. Gale Crater is predicted to
be a hemispheric maximum for snowmelt on Mars.Comment: Submitted to Icarus. Minor changes from submitted versio
Arginine Cofactors on the Polymerase Ribozyme
The RNA world hypothesis states that the early evolution of life went through a stage in which RNA served both as genome and as catalyst. The central catalyst in an RNA world organism would have been a ribozyme that catalyzed RNA polymerization to facilitate self-replication. An RNA polymerase ribozyme was developed previously in the lab but it is not efficient enough for self-replication. The factor that limits its polymerization efficiency is its weak sequence-independent binding of the primer/template substrate. Here we tested whether RNA polymerization could be improved by a cationic arginine cofactor, to improve the interaction with the substrate. In an RNA world, amino acid-nucleic acid conjugates could have facilitated the emergence of the translation apparatus and the transition to an RNP world. We chose the amino acid arginine for our study because this is the amino acid most adept to interact with RNA. An arginine cofactor was positioned at ten different sites on the ribozyme, using conjugates of arginine with short DNA or RNA oligonucleotides. However, polymerization efficiency was not increased in any of the ten positions. In five of the ten positions the arginine reduced or modulated polymerization efficiency, which gives insight into the substrate-binding site on the ribozyme. These results suggest that the existing polymerase ribozyme is not well suited to using an arginine cofactor
Violence against women in sex work and HIV risk implications differ qualitatively by perpetrator.
PMC3852292BACKGROUND:
Physical and sexual violence heighten STI/HIV risk for women in sex work. Against this backdrop, we describe the nature of abuse against women in sex work, and its STI/HIV implications, across perpetrators.
METHODS:
Adult women involved in sex work (n = 35) in Baltimore, MD participated in an in-depth interview and brief survey.
RESULTS:
Physical and sexual violence were prevalent, with 43% reporting past-month abuse. Clients were the primary perpetrators; their violence was severe, compromised women's condom and sexual negotiation, and included forced and coerced anal intercourse. Sex work was a factor in intimate partner violence. Police abuse was largely an exploitation of power imbalances for coerced sex.
CONCLUSIONS:
Findings affirm the need to address physical and sexual violence, particularly that perpetrated by clients, as a social determinant of health for women in sex work, as well as a threat to safety and wellbeing, and a contextual barrier to HIV risk reduction.JH Libraries Open Access Fun
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Sensitivity of a Continuum-Scale Porous Media Heat and Mass Transfer Model to the Spatial-Discretization Length-Scale of Applied Atmospheric Forcing Data
Fundamental process understanding and description of heat, mass, and momentum exchanges across the land-atmosphere interface in model boundary forcing parameterizations is critical to the simulation of near-surface soil moisture dynamics (e.g., bare-soil evaporation). This study explores the sensitivity of a continuum-scale porous media heat and mass transfer model to the spatial-discretization length-scales (i.e., spatial-resolution) of near-surface atmospheric data; the goal is to determine how much data are needed to force the model and adequately capture evaporative water losses and subsurface state variable distributions. The requisite atmospheric forcing data were taken from the high-resolution, precision bare-soil evaporation experiments of Trautz et al. (2018, https://doi.org/10.1029/2018WR023102). Simulation results demonstrated that shallow subsurface mass and heat transfer dynamics can be adequately captured with forcing data averaged over large length-scales, or a minimal number of measurements, provided that soil conditions are properly described. The soil moisture spatial distributions were found to be insensitive to horizontal variations in the forcing data. The model failed to capture small-scale trends observed experimentally; this did not impact the accuracy of total evaporative water loss estimates however. These results indicate that in future physical experimental efforts conducted at 1â10-m length-scales, there is no need to focus on the generation of high-spatial resolution atmospheric measurementsâtime and effort would be better spent in characterizing soil conditions and properties. Even though a theoretical foundation was not provided to directly extrapolate this work to the field scale, these findings have practical value in designing field data collection strategies
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Sensitivity of a Continuum-Scale Porous Media Heat and Mass Transfer Model to the Spatial-Discretization Length-Scale of Applied Atmospheric Forcing Data
Fundamental process understanding and description of heat, mass, and momentum exchanges across the land-atmosphere interface in model boundary forcing parameterizations is critical to the simulation of near-surface soil moisture dynamics (e.g., bare-soil evaporation). This study explores the sensitivity of a continuum-scale porous media heat and mass transfer model to the spatial-discretization length-scales (i.e., spatial-resolution) of near-surface atmospheric data; the goal is to determine how much data are needed to force the model and adequately capture evaporative water losses and subsurface state variable distributions. The requisite atmospheric forcing data were taken from the high-resolution, precision bare-soil evaporation experiments of Trautz et al. (2018, https://doi.org/10.1029/2018WR023102). Simulation results demonstrated that shallow subsurface mass and heat transfer dynamics can be adequately captured with forcing data averaged over large length-scales, or a minimal number of measurements, provided that soil conditions are properly described. The soil moisture spatial distributions were found to be insensitive to horizontal variations in the forcing data. The model failed to capture small-scale trends observed experimentally; this did not impact the accuracy of total evaporative water loss estimates however. These results indicate that in future physical experimental efforts conducted at 1â10-m length-scales, there is no need to focus on the generation of high-spatial resolution atmospheric measurementsâtime and effort would be better spent in characterizing soil conditions and properties. Even though a theoretical foundation was not provided to directly extrapolate this work to the field scale, these findings have practical value in designing field data collection strategies
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