254 research outputs found
Influence of Irrigation on the Microclimate and Development of White Mold Disease in Dry Edible Beans
Inelastic electron tunneling via molecular vibrations in single-molecule transistors
In single-molecule transistors, we observe inelastic cotunneling features
that correspond energetically to vibrational excitations of the molecule, as
determined by Raman and infrared spectroscopy. This is a form of inelastic
electron tunneling spectroscopy of single molecules, with the transistor
geometry allowing in-situ tuning of the electronic states via a gate electrode.
The vibrational features shift and change shape as the electronic levels are
tuned near resonance, indicating significant modification of the vibrational
states. When the molecule contains an unpaired electron, we also observe
vibrational satellite features around the Kondo resonance.Comment: 5 pages, 4 figures. Supplementary information available upon reques
Estimating Actual Evapotranspiration from Stony-Soils in Montane Ecosystems
Quantification of evapotranspiration (ET) is crucial for understanding the water balance and for efficient water resources planning. Agricultural settings have received most attention regarding ET measurements while less knowledge is available for actual ET (ETA) in natural ecosystems, many of which have soils containing significant amounts of stones. This study is focused on modelling ETA from stony soil, particularly in montane ecosystems where we estimate the contribution of stone content on water retention properties in soil. We employed a numerical model (HYDRUS-1D) to simulate ETA in natural settings in northern Utah and southern Idaho during the 2015 and 2016 growing seasons based on meteorological and soil moisture measurements at a range of depths. We simulated ETA under three different scenarios, considering soil with (i) no stones, (ii) highly porous stones, and (iii) negligibly porous stones. The simulation results showed significant overestimation of ETA when neglecting stones in comparison to ETA measured by eddy covariance. ETA estimates with negligibly porous stones were lower for all cases due to the decrease in soil water storage compared with estimates made considering highly porous stones. Assumptions of highly porous or negligibly porous stones led to reductions in simulated ETA of between 10% and 30%, respectively, compared with no stones. These results reveal the important role played by soil stones, which can impact the water balance by altering available soil moisture and thus ETA in montane ecosystems
Intercomparison of Nine Micrometeorological Stations during the BEAREX08 Field Campaign
Land–atmosphere interactions play a critical role in regulating numerous meteorological, hydrological, and environmental processes. Investigating these processes often requires multiple measurement sites representing a range of surface conditions. Before these measurements can be compared, however, it is imperative that the differences among the instrumentation systems are fully characterized. Using data collected as a part of the 2008 Bushland Evapotranspiration and Agricultural Remote Sensing Experiment (BEAREX08), measurements from nine collocated eddy covariance (EC) systems were compared with the twofold objective of 1) characterizing the interinstrument variation in the measurements, and 2) quantifying the measurement uncertainty associated with each system. Focusing on the three turbulent fluxes (heat, water vapor, and carbon dioxide), this study evaluated the measurement uncertainty using multiple techniques. The results of the analyses indicated that there could be substantial variability in the uncertainty estimates because of the advective conditions that characterized the study site during the afternoon and evening hours. However, when the analysis was limited to nonadvective, quasi-normal conditions, the response of the nine EC stations were remarkably similar. For the daytime period, both the method of Hollinger and Richardson and the method of Mann and Lenschow indicated that the uncertainty in the measurements of sensible heat, latent heat, and carbon dioxide flux were approximately 13 W m‒2, 27 W m‒2, and 0.10 mg m‒2 s‒1, respectively. Based on the results of this study, it is clear that advection can greatly increase the uncertainty associated with EC flux measurements. Since these conditions, as well as other phenomena that could impact the measurement uncertainty, are often intermittent, it may be beneficial to conduct uncertainty analyses on an ongoing basis
Tower and Aircraft Eddy Covariance Measurements of Water Vapor, Energy, and Carbon Dioxide Fluxes during SMACEX
Abstract
A network of eddy covariance (EC) and micrometeorological flux (METFLUX) stations over corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] canopies was established as part of the Soil Moisture–Atmosphere Coupling Experiment (SMACEX) in central Iowa during the summer of 2002 to measure fluxes of heat, water vapor, and carbon dioxide (CO2) during the growing season. Additionally, EC measurements of water vapor and CO2 fluxes from an aircraft platform complemented the tower-based measurements. Sensible heat, water vapor, and CO2 fluxes showed the greatest spatial and temporal variability during the early crop growth stage. Differences in all of the energy balance components were detectable between corn and soybean as well as within similar crops throughout the study period. Tower network–averaged fluxes of sensible heat, water vapor, and CO2 were observed to be in good agreement with area-averaged aircraft flux measurements
Lidar Based Emissions Measurement at the Whole Facility Scale: Method and Error Analysis
Particulate emissions from agricultural sources vary from dust created by operations and animal movement to the fine secondary particulates generated from ammonia and other emitted gases. The development of reliable facility emission data using point sampling methods designed to characterize regional, well-mixed aerosols are challenged by changing wind directions, disrupted flow fields caused by structures, varied surface temperatures, and the episodic nature of the sources found at these facilities. We describe a three-wavelength lidar-based method, which, when added to a standard point sampler array, provides unambiguous measurement and characterization of the particulate emissions from agricultural production operations in near real time. Point-sampled data are used to provide the aerosol characterization needed for the particle concentration and size fraction calibration, while the lidar provides 3D mapping of particulate concentrations entering, around, and leaving the facility. Differences between downwind and upwind measurements provide an integrated aerosol concentration profile, which, when multiplied by the wind speed profile, produces the facility source flux. This approach assumes only conservation of mass, eliminating reliance on boundary layer theory. We describe the method, examine measurement error, and demonstrate the approach using data collected over a range of agricultural operations, including a swine grow-finish operation, an almond harvest, and a cotton gin emission study
Decoherence in elastic and polaronic transport via discrete quantum states
Here we study the effect of decoherence on elastic and polaronic transport
via discrete quantum states. The calculations are performed with the help of
nonperturbative computational scheme, based on the Green's function theory
within the framework of polaron transformation (GFT-PT), where the many-body
electron-phonon interaction problem is mapped exactly into a single-electron
multi-channel scattering problem. In particular, the influence of dephasing and
relaxation processes on the shape of the electrical current and shot noise
curves is discussed in detail under the linear and nonlinear transport
conditions.Comment: 11 pages, 3 figure
Climate-Ready Landscape Plants: Garden Roses Trialed at Reduced Irrigation Frequency in Utah, USA
Increased urban and suburban populations in the arid western United States have resulted in more water demand; however, water availability in the region has become limited because of inadequate precipitation. Recent droughts have led to restrictions on irrigating landscape plants. Garden rose (Rosa ×hybrida) is commonly used as flowering plants in residential landscapes, but its drought tolerance has not been widely studied. The objective of this study was to determine the impact of reduced irrigation frequency on visual quality, plant growth, and physiology of five garden rose cultivars, including ChewPatout (Oso Easy® Urban Legend®), Meibenbino (Petite Knock Out®), MEIRIFTDAY (Oso Easy® Double Pink), Overedclimb (Cherry Frost™), and Radbeauty (Sitting Pretty™). Twenty-four plants of each rose cultivar were established in a trial plot at Utah Agricultural Experiment Station Greenville Research Farm (North Logan, UT, USA) in Summer 2021. Plants were randomly assigned to one of three deficit irrigation treatments for which irrigation frequencies were calculated using 80% reference evapotranspiration (ETO) (high), 50% ETO (medium), and 20% ETO (low). The total volumes of irrigation water applied to each plant were 345.6, 172.8, and 43.2 L for the high, medium, and low irrigation frequencies, respectively, during the deficit irrigation trial from 12 May to 30 Sep 2022. Root zones were wetted more frequently as irrigation frequency increased from low to high irrigation frequencies. Decreased irrigation frequency increased the number of visibly wilted and damaged leaves on all rose cultivars. However, only ‘Meibenbino’ and ‘MEIRIFTDAY’ exhibited a reduction in overall appearance under decreased irrigation frequency. The relative growth indices of both ‘Meibenbino’ and ‘MEIRIFTDAY’ decreased by 6%, whereas the dry weights of their leaves decreased by 37% and 36%, respectively, as irrigation decreased from high to low frequencies. Roses in this study appeared to decrease stomatal conductance up to 51% when irrigation decreased from high to low frequencies, or when air temperature increased. ‘Meibenbino’ and ‘MEIRIFTDAY’ exhibited unacceptable overall appearance, growth reduction, and higher leaf–air temperature differences, and they were less tolerant to reduced irrigation. Although the ‘Radbeauty’ maintained plant growth under the reduced irrigation frequency, the large leaf size led to a more visibly wilted appearance and the potential for heat stress, thus impairing visual quality. ‘ChewPatout’ and ‘Overedclimb’ were most tolerant to deficit irrigation at 20% ETO and maintained plant growth with acceptable visual quality and lower leaf temperatures when they received one irrigation during the growing season
Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area
Application and validation of many thermal remote sensing-based energy balance models involve the use of local meteorological inputs of incoming solar radiation, wind speed and air temperature as well as accurate land surface temperature (LST), vegetation cover and surface flux measurements. For operational applications at large scales, such local information is not routinely available. In addition, the uncertainty in LST estimates can be several degrees due to sensor calibration issues, atmospheric effects and spatial variations in surface emissivity. Time differencing techniques using multi-temporal thermal remote sensing observations have been developed to reduce errors associated with deriving the surface- air temperature gradient, particularly in complex landscapes. The Dual-Temperature-Difference (DTD) method addresses these issues by utilizing the Two-Source Energy Balance (TSEB) model of Norman et al. (1995) [1], and is a relatively simple scheme requiring meteorological input from standard synoptic weather station networks or mesoscale modeling. A comparison of the TSEB and DTD schemes is performed using LST and flux observations from eddy covariance (EC) flux towers and large weighing lysimeters (LYs) in irrigated cotton fields collected during BEAREX08, a large-scale field experiment conducted in the semi-arid climate of the Texas High Plains as described by Evett et al. (2012) [2]. Model output of the energy fluxes (i.e., net radiation, soil heat flux, sensible and latent heat flux) generated with DTD and TSEB using local and remote meteorological observations are compared with EC and LY observations. The DTD method is found to be significantly more robust in flux estimation compared to the TSEB using the remote meteorological observations. However, discrepancies between model and measured fluxes are also found to be significantly affected by the local inputs of LST and vegetation cover and the representativeness of the remote sensing observations with the local flux measurement footprint
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