Flooding Regime Impacts on Radiation, Evapotranspiration, and Latent Energy Fluxes over Groundwater-Dependent Riparian Cottonwood and Saltcedar Forests

© 2015 James Cleverly et al. Radiation and energy balances are key drivers of ecosystem water and carbon cycling. This study reports on ten years of eddy covariance measurements over groundwater-dependent ecosystems (GDEs) in New Mexico, USA, to compare the role of drought and flooding on radiation, water, and energy budgets of forests differing in species composition (native cottonwood versus nonnative saltcedar) and flooding regime. After net radiation (700-800 W m-2), latent heat flux was the largest energy flux, with annual values of evapotranspiration exceeding annual precipitation by 250-600%. Evaporative cooling dominated the energy fluxes of both forest types, although cottonwood generated much lower daily values of sensible heat flux (<-5 MJ m-2 d-1). Drought caused a reduction in evaporative cooling, especially in the saltcedar sites where evapotranspiration was also reduced, but without a substantial decline in depth-to-groundwater. Our findings have broad implications on water security and the management of native and nonnative vegetation within semiarid southwestern North America. Specifically, consideration of the energy budgets of GDEs as they respond to fluctuations in climatic conditions can inform the management options for reducing evapotranspiration and maintaining in-stream flow, which is legally mandated as part of interstate and international water resources agreements

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

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

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

Greenhouse gas emissions and energy use in UK-grown short-day strawberry (Fragaria xananassa Duch) crops

Original article can be found at: http://journals.cambridge.org/ Copyright Cambridge University PressReducing greenhouse gas emissions and optimizing energy consumption are important for mitigating climate change and improving resource use efficiency. Strawberry (Fragaria xananassa Duch) crops are a key component of the UK soft fruit sector and potentially resource-intensive crops. This is the first study to undertake a detailed environmental impact assessment of all methods of UK strawberry production. A total of 14 systems with six additional sub-systems grown for between 1 and 3 years were identified. They were defined by the growing of short-day (Junebearer) or everbearer varieties, organic production, covering with polytunnels or grown in the open, soil-grown (with or without fumigation) or container-grown (with peat or coir substrate) and summer or spring planted. Pre-harvest, the global warming potential varied between 1·5 and 10·3 t CO2 equiv/ha/crop or 0·13 and 1·14 t CO2 equiv/t of class 1 fruit. Key factors included the use of tunnels, mulch and irrigation, sterilization of soil with fumigants and the use of peat substrate. Seasonal crops without covers grown where rotation of sufficient length reduced Verticillium (system 4) were the most efficient. System 4a (that did not use mulch) emitted 0·13 t CO2 equiv/t of class 1 fruit. A second or third cropping year in soil-grown systems prolonged the effect of mulch and soil fumigants. Greenhouse gases from system 4 (with mulch) averaged 0·30 t CO2 equiv/t of class 1 fruit after 3 years of cropping compared to 0·63 and 0·36 t CO2 equiv/t after 1 and 2 years, respectively.Peer reviewe

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

Integrating Lidar and Atmospheric Boundary Layer Measurements to Determine Fluxes and Dynamics of Particulate Emissions from an Agriculture Facility

Lidar technology offers the ability to quantify concentrations of small particulates in the atmosphere in certain ranges of time and space. While this is a valuable tool to visualize the behavior of plumes emitted from the surface, the actual flux of particles cannot be estimated from such data alone. To determine the mass flux of particles, the concentrations must be properly integrated with wind and turbulence properties. The goal of this study is to utilize a model that uses wind and particle density information to calculate the flux of particles from an animal facility near Ames, Iowa. The model is a simplified conservation equation for particle density in the atmosphere. This approach essentially quantifies fluxes in and out of a box centered over the facility and estimates the surface source by assuming conservation of mass. In addition, we hypothesize that distinct turbulence structures will sometimes interact with the intermittency of the surface emission from the buildings, resulting in episodic changes in emission fluxes from the site. A second objective involves documenting how intermittent the emission plumes are and how they are connected to periodic large scale turbulence events. Lidar data of particle size and density in the vicinity of the site were collected during an intensive field campaign lasting nearly 2 weeks. In addition to the lidar data, turbulence data were measured at several levels on each of three towers, located upwind, inside and downwind of the source area. The model requires measurements of the vertical profiles of both concentrations of particulates and the mean horizontal wind. The concentrations were measured using the lidar, while winds were measured using a combination of cup anemometers and sonic anemometers. This allows the emission fluxes to be calculated during 15 to 30 minute periods when winds are consistent. Flux calculations await the final calibration of the lidar returns using measured particle densities. Flux estimates will be made when distinct plumes are observed under steady-state wind conditions. Current results are presented showing evidence of episodic plumes of CO2 in response to intermittent vertical motions of turbulences