scholarly journals Drivers of diffusive CH<sub>4</sub> emissions from shallow subarctic lakes on daily to multi-year timescales

2020 ◽  
Vol 17 (7) ◽  
pp. 1911-1932 ◽  
Author(s):  
Joachim Jansen ◽  
Brett F. Thornton ◽  
Alicia Cortés ◽  
Jo Snöälv ◽  
Martin Wik ◽  
...  
Keyword(s):  
Wind Speed ◽  
Water Column ◽  
Atmospheric Stability ◽  
Water Concentration ◽  
Gas Transfer ◽  
Air Concentration ◽  
Subarctic Lakes ◽  
Surface Renewal ◽  
Near Surface ◽  
Functional Relations

Abstract. Lakes and reservoirs contribute to regional carbon budgets via significant emissions of climate forcing trace gases. Here, for improved modelling, we use 8 years of floating chamber measurements from three small, shallow subarctic lakes (2010–2017, n=1306) to separate the contribution of physical and biogeochemical processes to the turbulence-driven, diffusion-limited flux of methane (CH4) on daily to multi-year timescales. Correlative data include surface water concentration measurements (2009–2017, n=606), total water column storage (2010–2017, n=237), and in situ meteorological observations. We used the last to compute near-surface turbulence based on similarity scaling and then applied the surface renewal model to compute gas transfer velocities. Chamber fluxes averaged 6.9±0.3 mg CH4 m−2 d−1 and gas transfer velocities (k600) averaged 4.0±0.1 cm h−1. Chamber-derived gas transfer velocities tracked the power-law wind speed relation of the model. Coefficients for the model and dissipation rates depended on shear production of turbulence, atmospheric stability, and exposure to wind. Fluxes increased with wind speed until daily average values exceeded 6.5 m s−1, at which point emissions were suppressed due to rapid water column degassing reducing the water–air concentration gradient. Arrhenius-type temperature functions of the CH4 flux (Ea′=0.90±0.14 eV) were robust (R2≥0.93, p<0.01) and also applied to the surface CH4 concentration (Ea′=0.88±0.09 eV). These results imply that emissions were strongly coupled to production and supply to the water column. Spectral analysis indicated that on timescales shorter than a month, emissions were driven by wind shear whereas on longer timescales variations in water temperature governed the flux. Long-term monitoring efforts are essential to identify distinct functional relations that govern flux variability on timescales of weather and climate change.

scholarly journals Drivers of diffusive lake CH<sub>4</sub> emissions on daily to multi-year time scales

2019 ◽  
Author(s):  
Joachim Jansen ◽  
Brett F. Thornton ◽  
Alicia Cortes ◽  
Jo Snöälv ◽  
Martin Wik ◽  
...  
Keyword(s):  
Water Concentration ◽  
Climate Forcing ◽  
Environmental Drivers ◽  
Gas Transfer ◽  
Subarctic Lakes ◽  
Surface Renewal ◽  
Renewal Model ◽  
Extensive Field ◽  
Lakes And Reservoirs ◽  
Meteorological Observations

Abstract. Lakes and reservoirs are important emitters of climate forcing trace gases. Various environmental drivers of the flux, such as temperature and wind speed, have been identified, but their relative importance remains poorly understood. Here we use an extensive field dataset to disentangle physical and biogeochemical controls on the turbulence-driven diffusive flux of methane (CH4) on daily to multi-year timescales. We compare 8 years of floating chamber fluxes from three small, shallow subarctic lakes (2010–2017, n = 1306) with fluxes computed using 9 years of surface water concentration measurements (2009–2017, n = 606) and a small-eddy surface renewal model informed by in situ meteorological observations. Chamber fluxes averaged 6.9 ± 0.3 mg m−2 d−1 and gas transfer velocities (k600) from the chamber-calibrated surface renewal model averaged 4.0 ± 0.1 cm h−1. We find robust (R2 ≥ 0.93, p 

Diffusion Law and Simulation Analysis of Radon in Uranium Tailings Based on Multiple Gauss Plume Model

2018 ◽  
Author(s):  
Jiaxin Wang ◽  
Guohua Wu ◽  
Liguo Zhang ◽  
Jingyuan Qu ◽  
Jiejuan Tong
Keyword(s):  
Wind Speed ◽  
Radon Concentration ◽  
Single Point ◽  
Atmospheric Stability ◽  
Radiation Hazard ◽  
Downwind Distance ◽  
Average Wind Speed ◽  
Near Surface ◽  
Wide Range ◽  
Uranium Tailings

The radon from uranium tailings spreads fast and has a wide range of pollution, which poses a potential radiation hazard to the environment and the public in downwind region. In this paper, the open and naked uranium tailings are selected as research object. By setting up multiple Gaussian plume models with single point source, the diffusion of radon in the uranium tailings is simulated with different atmospheric stability, average wind speed, height and downwind distance. The results show that the maximum radon concentration increases while the related downwind distance decreases as the atmospheric becoming stable. The higher wind speed does not affect the downwind distance where the maximum radon concentration occurs, but it decreases the maximum radon concentration. The concentration of radon in residential area decreases but the decreasing rate speeds up with height going up. The distribution of radon in vertical and horizontal direction tends to be homogeneous while the near-surface area concentration decreases rapidly as farther downwind distance.

scholarly journals How well does wind speed predict air-sea gas transfer in the sea ice zone? A synthesis of radon deficit profiles in the upper water column of the Arctic Ocean

2017 ◽  
Vol 122 (5) ◽  
pp. 3696-3714 ◽  
Author(s):  
B. Loose ◽  
R. P. Kelly ◽  
A. Bigdeli ◽  
W. Williams ◽  
R. Krishfield ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Water Column ◽  
The Arctic ◽  
Gas Transfer ◽  
The Arctic Ocean

Two Corrections for Turbulent Kinetic Energy Generated by Wind Farms in the WRF Model

2020 ◽  
Vol 148 (12) ◽  
pp. 4823-4835
Author(s):  
Cristina L. Archer ◽  
Sicheng Wu ◽  
Yulong Ma ◽  
Pedro A. Jiménez
Keyword(s):  
Wind Speed ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Wind Farm ◽  
Atmospheric Stability ◽  
Wrf Model ◽  
Wind Farms ◽  
Near Surface ◽  
Large Eddy ◽  
The Way

AbstractAs wind farms grow in number and size worldwide, it is important that their potential impacts on the environment are studied and understood. The Fitch parameterization implemented in the Weather Research and Forecasting (WRF) Model since version 3.3 is a widely used tool today to study such impacts. We identified two important issues related to the way the added turbulent kinetic energy (TKE) generated by a wind farm is treated in the WRF Model with the Fitch parameterization. The first issue is a simple “bug” in the WRF code, and the second issue is the excessive value of a coefficient, called CTKE, that relates TKE to the turbine electromechanical losses. These two issues directly affect the way that a wind farm wake evolves, and they impact properties like near-surface temperature and wind speed at the wind farm as well as behind it in the wake. We provide a bug fix and a revised value of CTKE that is one-quarter of the original value. This 0.25 correction factor is empirical; future studies should examine its dependence on parameters such as atmospheric stability, grid resolution, and wind farm layout. We present the results obtained with the Fitch parameterization in the WRF Model for a single turbine with and without the bug fix and the corrected CTKE and compare them with high-fidelity large-eddy simulations. These two issues have not been discovered before because they interact with one another in such a way that their combined effect is a somewhat realistic vertical TKE profile at the wind farm and a realistic wind speed deficit in the wake. All WRF simulations that used the Fitch wind farm parameterization are affected, and their conclusions may need to be revisited.

Detection and Characterization of Microscale Breaking Waves

2003 ◽  
Author(s):  
M. H. Kamran Siddiqui ◽  
Mark R. Loewen
Keyword(s):  
Wind Speed ◽  
Water Surface ◽  
Air Entrainment ◽  
Breaking Waves ◽  
Skin Layer ◽  
Wave Crest ◽  
Gas Transfer ◽  
Near Surface ◽  
Wind Speeds ◽  
The Waves

Microscale breaking waves are short wind-generated waves that break without air entrainment. At low to moderate wind speeds microscale breaking waves play an important role in enhancing air-water heat and gas transfer. We report on a series of experiments conducted in a wind-wave flume at Harris Hydraulics Laboratory (University of Washington, Seattle) designed to investigate the importance of microscale breaking waves in generating near-surface turbulence and in enhancing air-sea gas and heat transfer rates. Non-invasive experiments were performed at wind speeds ranging from 4.5 m/s to 11 m/s and at a fetch of 5.5 m. The skin-layer or water surface temperature was measured using an infrared (IR) imager and digital particle image velocimetry (DPIV) was used to obtain simultaneous measurements of the two-dimensional velocities immediately below the water surface. Analysis of the simultaneous DPIV and infrared datasets revealed that microscale breaking waves generate strong vortices in their crests that disrupt the cool skin layer at the water surface and create thermal wakes that are visible in the infrared images. While non-breaking waves do not generate strong vortices and hence do not disrupt the skin layer. We developed a scheme based on the magnitude of vorticity in the wave crest to identify microscale breaking waves. The results show that at a wind speed of 4.5 m/s, 11% of the waves broke. The percentage of breaking waves increased with wind speed and at a wind speed of 11 m/s, 91% of the waves were microscale breaking waves. Comparison of different geometric and flow properties of microscale breaking and non-breaking waves revealed that microscale breaking waves are steeper, larger in amplitude and generate more turbulent kinetic energy compared to non-breaking waves.

scholarly journals Natural variability in air–sea gas transfer efficiency of CO2

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mingxi Yang ◽  
Timothy J. Smyth ◽  
Vassilis Kitidis ◽  
Ian J. Brown ◽  
Charel Wohl ◽  
...  
Keyword(s):  
Wind Speed ◽  
Transfer Efficiency ◽  
Gas Transfer ◽  
Transfer Velocity ◽  
Concentration Difference ◽  
Near Surface ◽  
Wind Speeds ◽  
Naturally Occurring ◽  
Surface Active ◽  
The Mean

AbstractThe flux of CO2 between the atmosphere and the ocean is often estimated as the air–sea gas concentration difference multiplied by the gas transfer velocity (K660). The first order driver for K660 over the ocean is wind through its influence on near surface hydrodynamics. However, field observations have shown substantial variability in the wind speed dependencies of K660. In this study we measured K660 with the eddy covariance technique during a ~ 11,000 km long Southern Ocean transect. In parallel, we made a novel measurement of the gas transfer efficiency (GTE) based on partial equilibration of CO2 using a Segmented Flow Coil Equilibrator system. GTE varied by 20% during the transect, was distinct in different water masses, and related to K660. At a moderate wind speed of 7 m s−1, K660 associated with high GTE exceeded K660 with low GTE by 30% in the mean. The sensitivity of K660 towards GTE was stronger at lower wind speeds and weaker at higher wind speeds. Naturally-occurring organics in seawater, some of which are surface active, may be the cause of the variability in GTE and in K660. Neglecting these variations could result in biases in the computed air–sea CO2 fluxes.

scholarly journals Ozone deposition to a coastal sea: comparison of eddy covariance observations with reactive air–sea exchange models

2020 ◽  
Vol 13 (12) ◽  
pp. 6915-6931
Author(s):  
David C. Loades ◽  
Mingxi Yang ◽  
Thomas G. Bell ◽  
Adam R. Vaughan ◽  
Ryan J. Pound ◽  
...  
Keyword(s):  
Wind Speed ◽  
Eddy Covariance ◽  
Friction Velocity ◽  
Limit Of Detection ◽  
Deposition Velocity ◽  
Atmospheric Stability ◽  
Layer Model ◽  
Near Surface ◽  
Wind Speeds ◽  
Ozone Deposition

Abstract. A fast-response (10 Hz) chemiluminescence detector for ozone (O3) was used to determine O3 fluxes using the eddy covariance technique at the Penlee Point Atmospheric Observatory (PPAO) on the south coast of the UK during April and May 2018. The median O3 flux was −0.132 mg m−2 h−1 (0.018 ppbv m s−1), corresponding to a deposition velocity of 0.037 cm s−1 (interquartile range 0.017–0.065 cm s−1) – similar to the higher values previously reported for open-ocean flux measurements but not as high as some other coastal results. We demonstrate that a typical single flux observation was above the 2σ limit of detection but had considerable uncertainty. The median 2σ uncertainty of deposition velocity was 0.031 cm s−1 for each 20 min period, which reduces with the square root of the sample size. Eddy covariance footprint analysis of the site indicates that the flux footprint was predominantly over water (> 96 %), varying with atmospheric stability and, to a lesser extent, with the tide. At very low wind speeds when the atmosphere was typically unstable, the observed ozone deposition velocity was elevated, most likely because the footprint contracted to include a greater land contribution in these conditions. At moderate to high wind speeds when atmospheric stability was near-neutral, the ozone deposition velocity increased with wind speed and showed a linear dependence with friction velocity. This observed dependence on friction velocity (and therefore also wind speed) is consistent with the predictions from the one-layer model of Fairall et al. (2007), which parameterises the oceanic deposition of ozone from the fundamental conservation equation, accounting for both ocean turbulence and near-surface chemical destruction, while assuming that chemical O3 destruction by iodide is distributed over depth. In contrast to our observations, the deposition velocity predicted by the recently developed two-layer model of Luhar et al. (2018) (which considers iodide reactivity in both layers but with molecular diffusivity dominating over turbulent diffusivity in the first layer) shows no major dependence of deposition velocity on wind speed and underestimates the measured deposition velocities. These results call for further investigation into the mechanisms and control of oceanic O3 deposition.

Air–water gas transfer and near-surface motions

2013 ◽  
Vol 733 ◽  
pp. 588-624 ◽  
Author(s):  
Damon E. Turney ◽  
Sanjoy Banerjee
Keyword(s):  
Open Channel ◽  
Breaking Waves ◽  
Capillary Waves ◽  
Gas Transfer ◽  
Water Interface ◽  
Surface Renewal ◽  
Near Surface ◽  
Transfer Rates ◽  
Air Water Interface ◽  
Water Gas

AbstractRates of gas transfer between air and water remain difficult to predict or simulate due to the wide range of length and time scales and lack of experimental observations of near-surface fluid velocity and gas concentrations. The surface renewal model (SR) and surface divergence model (SD) provide the two leading models of the process, yet they remain poorly tested by observation because near-surface velocity is difficult to measure. To contribute to evaluation of these models, we apply new techniques called interfacial particle imaging velocimetry (IPIV) and three-dimensional IPIV (3D-IPIV) for measuring water velocities within a millimetre of a moving deformable air–water interface. The latter technique (3D-IPIV) simultaneously measures the air–water interface topography. We apply these techniques to turbulent open-channel water flows and wind-sheared water flows with microscale breaking waves. Additional measurements made for each flow condition are bulk turbulent length scales, bulk turbulent velocity scales, air–water gas transfer rates, friction velocities, and wave characteristics. We analyse these data to test the surface divergence models for interfacial gas transfer. The first test is of predictions from the Banerjee (Ninth International Heat Transfer Conference, Keynote Lectures, vol. 1, 1990, pp. 395–418, Hemisphere Press) surface divergence model for gas transfer for homogeneous isotropic turbulence interacting with a planar free surface. The second test is of predictions from the McCready, Vassiliadou and Hanratty (AIChE J., vol. 32(7), 1986, pp. 1108–1115) surface divergence model, as applied in both open-channel flow and wind-sheared wavy flows. We find the predictions of the Banerjee and McCreadyet al. models to agree with the experimental data taken for open-channel flow conditions. On the other hand, for wind-driven flows with wind waves we find disagreement between the McCreadyet al. predictions and our direct measurements of the gas transfer coefficient. The cause of the disagreement is investigated by Lagrangian tracking of surface divergence of surface water patches, and by analysis of the corresponding Lagrangian time series with advection–diffusion concepts. A quantitative criterion based on surface divergence strength and lifetime is proposed to distinguish the effectiveness of each near-surface motion toward causing interfacial gas transfer. Capillary waves are found to contribute to surface divergence but to have too short a time scale to cause interfacial gas transfer. As wind speed increases, the presence and intensity on the air–water interface of capillary waves and other ineffective near-surface motions is diminished by the rise of turbulent wakes from microscale breaking waves thus causing the disagreement of the surface divergence model’s predicted transfer rates with measurements. A model of air–water gas transfer that combines the surface renewal and surface divergence models is formulated and found to agree with the data from both open-channel flows and wind-driven flows without requiring an empirical coefficient.

Recurrence Characteristics Analysis of Near-Surface Wind Speed Signal with Different Sampling Frequencies

2014 ◽  
Vol 599-601 ◽  
pp. 1605-1609 ◽  
Author(s):  
Ming Zeng ◽  
Zhan Xie Wu ◽  
Qing Hao Meng ◽  
Jing Hai Li ◽  
Shu Gen Ma
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Recurrence Plot ◽  
Sampling Frequency ◽  
Near Surface ◽  
Gas Leakage ◽  
Time Period ◽  
Characteristics Analysis ◽  
Quantification Analysis

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.

scholarly journals Radiation Dose Calculations for a Hypothetical Accident in Xianning Nuclear Power Plant

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Bo Cao ◽  
Junxiao Zheng ◽  
Yixue Chen
Keyword(s):  
Radiation Dose ◽  
Nuclear Power ◽  
Atmospheric Dispersion ◽  
Harmful Effect ◽  
Atmospheric Stability ◽  
Dispersion Modeling ◽  
Dose Calculations ◽  
Air Concentration ◽  
The Public ◽  
Ground Deposition

Atmospheric dispersion modeling and radiation dose calculations have been performed for a hypothetical AP1000 SGTR accident by HotSpot code 3.03. TEDE, the respiratory time-integrated air concentration, and the ground deposition are calculated for various atmospheric stability classes, Pasquill stability categories A–F with site-specific averaged meteorological conditions. The results indicate that the maximum plume centerline ground deposition value of1.2E+2 kBq/m2occurred at about 1.4 km and the maximum TEDE value of1.41E-05 Sv occurred at 1.4 km from the reactor. It is still far below the annual regulatory limits of 1 mSv for the public as set in IAEA Safety Report Series number 115. The released radionuclides might be transported to long distances but will not have any harmful effect on the public.

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