scholarly journals Improved methane emission estimates using AVIRIS-NG and an Airborne Doppler Wind Lidar

2021 ◽  
Author(s):  
Andrew Thorpe ◽  
Christopher O’Handley ◽  
George Emmitt ◽  
Philip Decola ◽  
Francesca Hopkins ◽  
...  
Keyword(s):  
Wind Speed ◽  
Emission Rate ◽  
Sonic Anemometer ◽  
Surface Measurement ◽  
Emission Rates ◽  
Ch4 Emission ◽  
Near Surface ◽  
Wind Measurements ◽  
Wind Lidar ◽  
Doppler Wind Lidar

<p>This study demonstrates the utility of combining Airborne Doppler Wind Lidar measurements and quantitative methane (CH4) retrievals from the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) to estimate CH4 emission rates. In a controlled release experiment, Twin Otter Doppler Wind Lidar (TODWL) observed wind speed and direction agreed closely with sonic anemometer measurements and CH4 emission rates derived from TODWL observations were more accurate than those using the sonic during periods of stable winds. During periods exhibiting rapid shifts in wind speed and direction, estimating emission rates proved more challenging irrespective of the use of model, sonic, or TODWL wind data. Overall, TODWL was able to provide accurate wind measurements and emission rate estimates despite the variable wind conditions and excessive flight level turbulence which impacted near surface measurement density. TODWL observed winds were also used to constrain CH4 emissions at a refinery, landfill, wastewater facility, and dairy digester. At these sites, TODWL wind measurements agreed well with wind observations from nearby meteorological stations, and when combined with quantitative CH4 plume imagery, yielded emission rate estimates that were similar to those obtained using model winds.</p>

scholarly journals Wind Measurements from Arc Scans with Doppler Wind Lidar

2015 ◽  
Vol 32 (11) ◽  
pp. 2024-2040 ◽  
Author(s):  
H. Wang ◽  
R. J. Barthelmie ◽  
A. Clifton ◽  
S. C. Pryor
Keyword(s):  
Wind Speed ◽  
Sonic Anemometer ◽  
Elevation Angle ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Energy Applications ◽  
Mean Wind Speed ◽  
Wind Measurements ◽  
Wind Lidar ◽  
Doppler Wind Lidar

AbstractDefining optimal scanning geometries for scanning lidars for wind energy applications remains an active field of research. This paper evaluates uncertainties associated with arc scan geometries and presents recommendations regarding optimal configurations in the atmospheric boundary layer. The analysis is based on arc scan data from a Doppler wind lidar with one elevation angle and seven azimuth angles spanning 30° and focuses on an estimation of 10-min mean wind speed and direction. When flow is horizontally uniform, this approach can provide accurate wind measurements required for wind resource assessments in part because of its high resampling rate. Retrieved wind velocities at a single range gate exhibit good correlation to data from a sonic anemometer on a nearby meteorological tower, and vertical profiles of horizontal wind speed, though derived from range gates located on a conical surface, match those measured by mast-mounted cup anemometers. Uncertainties in the retrieved wind velocity are related to high turbulent wind fluctuation and an inhomogeneous horizontal wind field. The radial velocity variance is found to be a robust measure of the uncertainty of the retrieved wind speed because of its relationship to turbulence properties. It is further shown that the standard error of wind speed estimates can be minimized by increasing the azimuthal range beyond 30° and using five to seven azimuth angles.

A comment on scaling methane emissions from vegetation and grazing ruminants in New Zealand

2006 ◽  
Vol 33 (7) ◽  
pp. 613 ◽  
Author(s):  
Francis M. Kelliher ◽  
Harry Clark ◽  
Zheng Li ◽  
Paul C. D. Newton ◽  
Anthony J. Parsons ◽  
...  
Keyword(s):  
New Zealand ◽  
Standard Deviation ◽  
Forest Canopy ◽  
Emission Rate ◽  
Oxidative Capacity ◽  
Emission Rates ◽  
Ch4 Emission ◽  
Ch4 Emissions ◽  
Grazed Pasture ◽  
Indigenous Forest

Keppler et al. (2006, Nature 439, 187–191) showed that plants produce methane (CH4) in aerobic environments, leading Lowe (2006, Nature 439, 148–149) to postulate that in countries such as New Zealand, where grazed pastures have replaced forests, the forests could have produced as much CH4 as the ruminants currently grazing these areas. Estimating CH4 emissions from up to 85 million ruminants in New Zealand is challenging and, for completeness, the capacity of forest and pastoral soils to oxidise CH4 should be included. On average, the CH4 emission rate of grazing ruminants is estimated to be 9.6 ± 2.6 g m–2 year–1 (±standard deviation), six times the corresponding estimate for an indigenous forest canopy (1.6 ± 1.1 g m–2 year–1). The forest’s soil is estimated to oxidise 0.9 ± 0.2 g m–2 year–1 more CH4 than representative soils beneath grazed pasture. Taking into account plant and animal sources and the soil’s oxidative capacity, the net CH4 emission rates of forest and grazed ecosystems are 0.6 ± 1.1 and 9.8 ± 2.6 g m–2 year–1, respectively.

scholarly journals Doppler wind lidar activities at Cabauw

2021 ◽  
Author(s):  
Steven Knoop ◽  
Fred Bosveld ◽  
Marijn de Haij ◽  
Arnoud Apituley
Keyword(s):  
Wind Speed ◽  
Wind Profile ◽  
Continuous Wave ◽  
Wind Farms ◽  
Data Availability ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Low Clouds ◽  
Wind Measurements ◽  
Wind Lidar

<p>Atmospheric motion and turbulence are essential parameters for weather and topics related to air quality. Therefore, wind profile measurements play an important role in atmospheric research and meteorology. One source of wind profile data are Doppler wind lidars, which are laser-based remote sensing instruments that measure wind speed and wind direction up to a few hundred meters or even a few kilometers. Commercial wind lidars use the laser wavelength of 1.5 µm and therefore backscatter is mainly from aerosols while clear air backscatter is minimal, limiting the range to the boundary layer typically.</p><p>We have carried out a two-year intercomparison of the ZephIR 300M (ZX Lidars) short-range wind lidar and tall mast wind measurements at Cabauw [1]. We have focused on the (height-dependent) data availability of the wind lidar under various meteorological conditions and the data quality through a comparison with in situ wind measurements at several levels in the 213m tall meteorological mast. We have found an overall availability of quality-controlled wind lidar data of 97% to 98 %, where the missing part is mainly due to precipitation events exceeding 1 mm/h or fog or low clouds below 100 m. The mean bias in the horizontal wind speed is within 0.1 m/s with a high correlation between the mast and wind lidar measurements, although under some specific conditions (very high wind speed, fog or low clouds) larger deviations are observed. This instrument is being deployed within North Sea wind farms.</p><p>Recently, a scanning long-range wind lidar Windcube 200S (Leosphere/Vaisala) has been installed at Cabauw, as part of the Ruisdael Observatory program [2]. The scanning Doppler wind lidars will provide detailed measurements of the wind field, aerosols and clouds around the Cabauw site, in coordination with other instruments, such as the cloud radar.</p><p>[1] Knoop, S., Bosveld, F. C., de Haij, M. J., and Apituley, A.: A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw, Atmos. Meas. Tech., 14, 2219–2235, 2021</p><p>[2] https://ruisdael-observatory.nl/</p>

scholarly journals Coastal Wind Measurements Using a Single Scanning LiDAR

2020 ◽  
Vol 12 (8) ◽  
pp. 1347 ◽  
Author(s):  
Susumu Shimada ◽  
Jay Prakash Goit ◽  
Teruo Ohsawa ◽  
Tetsuya Kogaki ◽  
Satoshi Nakamura
Keyword(s):  
Wind Speed ◽  
Goodness Of Fit ◽  
Sonic Anemometer ◽  
Data Availability ◽  
Horizontal Wind ◽  
Research Station ◽  
Lidar Measurement ◽  
Wind Speeds ◽  
Wind Measurements ◽  
Scanning Lidar

A wind measurement campaign using a single scanning light detection and ranging (LiDAR) device was conducted at the Hazaki Oceanographical Research Station (HORS) on the Hazaki coast of Japan to evaluate the performance of the device for coastal wind measurements. The scanning LiDAR was deployed on the landward end of the HORS pier. We compared the wind speed and direction data recorded by the scanning LiDAR to the observations obtained from a vertical profiling LiDAR installed at the opposite end of the pier, 400 m from the scanning LiDAR. The best practice for offshore wind measurements using a single scanning LiDAR was evaluated by comparing results from a total of nine experiments using several different scanning settings. A two-parameter velocity volume processing (VVP) method was employed to retrieve the horizontal wind speed and direction from the radial wind speed. Our experiment showed that, at the current offshore site with a negligibly small vertical wind speed component, the accuracy of the scanning LiDAR wind speeds and directions was sensitive to the azimuth angle setting, but not to the elevation angle setting. In addition to the validations for the 10-minute mean wind speeds and directions, the application of LiDARs for the measurement of the turbulence intensity (TI) was also discussed by comparing the results with observations obtained from a sonic anemometer, mounted at the seaward end of the HORS pier, 400 m from the scanning LiDAR. The standard deviation obtained from the scanning LiDAR measurement showed a greater fluctuation than that obtained from the sonic anemometer measurement. However, the difference between the scanning LiDAR and sonic measurements appeared to be within an acceptable range for the wind turbine design. We discuss the variations in data availability and accuracy based on an analysis of the carrier-to-noise ratio (CNR) distribution and the goodness of fit for curve fitting via the VVP method.

Feeding lucerne silage to beef cattle at three allowances and four feeding frequencies affects circadian patterns of methane emissions, but not emissions per unit of intake

2014 ◽  
Vol 54 (9) ◽  
pp. 1350 ◽  
Author(s):  
Arjan Jonker ◽  
German Molano ◽  
Christopher Antwi ◽  
Garry Waghorn
Keyword(s):  
Emission Rate ◽  
Circadian Variation ◽  
Emission Rates ◽  
Ch4 Emission ◽  
Feeding Frequency ◽  
Ch4 Emissions ◽  
Time To Peak ◽  
Ch4 Production ◽  
Ad Libitum ◽  
Circadian Patterns

The objective of this study was to determine the circadian variation in methane (CH4) emissions from cattle fed lucerne silage at different feeding levels and feeding frequencies, to assist with interpretation of short ‘snapshot’ CH4 measurements used for predicting daily emissions. Eight Hereford × Friesian heifers (initially 20 months of age) were used in five consecutive periods (P1–5) of 14 days with CH4 emissions measured using respiration chambers for two consecutive days at the end of each period. Feed was restricted to intakes of ~6, 8, 8, 8 and 11 ± 1.3 (ad libitum) kg lucerne silage dry matter (DM), fed in 2, 2, 3, 4 or ad libitum (refilled twice daily) meals per day in P1–5, respectively. Daily CH4 production (g/day) was lower in P1 than in P2–4 (P < 0.05), which were lower than in P5 (P < 0.05), but CH4 yield (24.3 ± 1.23 g/kg DM) was unaffected by treatment. Among the five periods, CH4 emission rate (g/h) before feeding ranged from 1.8 to 6.5 g/h, time to peak CH4 production after start of feeding ranged from 19 to 40 min and peak CH4 production rate ranged from 11.1 to 17.5 g/h. The range in hourly CH4 emission rates during the day decreased with increasing feed intake level, but was unaffected by feeding frequency. In summary, the circadian pattern of CH4 emissions was affected by feed allowance and feeding frequency, and variation in CH4 emission rate was reduced with increasing intake, without affecting average daily yield (g CH4/kg DM intake).

scholarly journals Performance evaluation of an all-fiber image-reject homodyne coherent Doppler wind lidar

2015 ◽  
Vol 8 (10) ◽  
pp. 4145-4153 ◽  
Author(s):  
C. F. Abari ◽  
A. T. Pedersen ◽  
E. Dellwik ◽  
J. Mann
Keyword(s):  
Continuous Wave ◽  
Sonic Anemometer ◽  
Vertical Component ◽  
Intermediate Frequency ◽  
Heterodyne Receiver ◽  
Front End ◽  
Wind Velocities ◽  
Wind Lidar ◽  
Field Campaigns ◽  
Doppler Wind Lidar

Abstract. The main purpose of this study is to evaluate the near-zero wind velocity measurement performance of two separate 1.5 μm all-fiber coherent Doppler lidars (CDLs). The performance characterization is carried out through the presentation of the results from two separate atmospheric field campaigns. In one campaign, a recently developed continuous wave (CW) CDL benefiting from an image-reject front-end was deployed. The other campaign utilized a different CW CDL, benefiting from a heterodyne receiver with intermediate-frequency (IF) sampling. In both field campaigns the results are compared against a sonic anemometer, as the reference instrument. The measurements clearly show that the image-reject architecture results in more accurate measurements of radial wind velocities close to zero. Close-to-zero velocities are usually associated with the vertical component of the wind and are important to characterize.

Horizontal Wind Speed motion-induced error assessment on a floating Doppler Wind lidar

2021 ◽  
Author(s):  
Andreu Salcedo-Bosch ◽  
Joan Farré-Guarné ◽  
Josep Sala-Álvarez ◽  
Javier Villares-Piera ◽  
Robin Tanamachi ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Profile ◽  
Continuous Wave ◽  
Superposition Principle ◽  
Translational Motion ◽  
Horizontal Wind ◽  
Error Assessment ◽  
Horizontal Wind Speed ◽  
Wind Lidar ◽  
Doppler Wind Lidar

&lt;p&gt;A wind retrieval simulator of a floating Doppler Wind Lidar (DWL) with six Degrees of Freedom (DoF) in its motion is presented. The simulator considers a continuous-wave, conically scanning, floating DWL which retrieves the local wind profile from 50 line of sight (LoS) radial velocity measurements per scan. Rotational and translational motion effects over horizontal wind speed (HWS) measurements are studied parametrically. The 6 DoF motion framework as well as the most important buoy motion equations are based on the model presented in [1].&lt;/p&gt;&lt;p&gt;Each rotational and translational motion is simulated as 1 second sinusoidal signal defined by an amplitude, frequency and motion phase. In order to study the problem of motion-induced error on the retrieved HWS, a dimension reduction is needed (22 variables). A consideration followed in the literature [2] to alleviate the problem is to set the same motional frequency (f=0.3 Hz) for all DoF, a wind vector with constant HWS and null vertical wind speed (VWS). Moreover, the parametric study is carried out under certain constraints in order to finally reduce the problem dimensionality to three, which enables the generation of tri-dimensional colorplots of the error on the retrieved HWS.&lt;/p&gt;&lt;p&gt;Simulation results show that in the presence of motion, HWS error has a strong dependency on FDWL initial scan phase. Moreover, the directions of the rotation axis and translational velocity vector (with respect to wind direction, WD) show great impact on HWS error. For translational motion, a 3 DoF superposition principle is corroborated.&lt;/p&gt;&lt;p&gt;The simulator is as a useful tool for understanding particular lidar motion scenarios and their contributions to HWS measurements error. However, further analysis of the effect of lidar initial scan phase is needed. Additionally, these simulations are conducted under idealized assumptions of horizontally homogeneous wind profiles in the vicinity of the FDWL. Simulations using non-homogeneous wind fields (e.g., turbulence, air mass boundaries) would give insights on how well floating lidars can be expected to retrieve the wind profile in these common scenarios.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Acknowledgements&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;This work was supported via Spanish Government&amp;#8211;European Regional Development Funds project PGC2018-094132-B-I00 and H2020 ACTRIS-IMP (GA-871115). The European Institute of Innovation and Technology (EIT), KIC InnoEnergy project NEPTUNE (Offshore Metocean Data Mea-suring Equipment and Wind, Wave and Current Analysis and ForecastingSoftware, call FP7) supported measurements campaigns. CommSensLab isa Mar&amp;#237;a-de-Maeztu Unit of Excellence funded by the Agencia Estatal de Investigaci&amp;#243;n (Spanish National Science Foundation). The work of Andreu Salcedo-Bosch was supported by the &amp;#8220;Ag&amp;#232;ncia de Gesti&amp;#243; d&amp;#8217;Ajuts Universitaris i de la Recerca (AGAUR)&amp;#8221;, Generalitat de Catalunya, under Grant no. 2020 FISDU 00455.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;[1] F. Kelberlau, V. Neshaug, L. L&amp;#248;nseth, T. Bracchi, and J. Mann, &amp;#8220;Taking the Motion out of Floating Lidar: Turbulence Intensity Estimates with a Continuous-Wave Wind Lidar,&amp;#8221; Remote Sens., vol. 12, no. 898, 2020.&lt;/p&gt;&lt;p&gt;[2] J. Tiana-Alsina, F. Rocadenbosch, and M. A. Gutierrez-Antunano, &amp;#8220;Vertical Azimuth Display simulator for wind-Doppler lidar error assessment,&amp;#8221; in 2017 IEEE Int. Geosci. Remote. Se. (IGARSS). IEEE, Jul. 2017.&lt;/p&gt;

scholarly journals Wind speed measurements using distributed fiber optics: a windtunnel study

2019 ◽  
Author(s):  
Justus G. V. van Ramshorst ◽  
Miriam Coenders-Gerrits ◽  
Bart Schilperoort ◽  
Bas J. H. van de Wiel ◽  
Jonathan G. Izett ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Fiber Optics ◽  
Sonic Anemometer ◽  
Surface Wind ◽  
Turbulent Heat ◽  
Distributed Temperature Sensing ◽  
Near Surface ◽  
Operational Conditions

Abstract. Near-surface wind speed is typically only measured by point observations. The Actively Heated Fiber-Optic (AHFO) technique, however, has the potential to provide high-resolution distributed observations of wind speeds, allowing for better characterization of fine-scale processes. Before AHFO can be widely used, its performance needs to be tested in a range of settings. In this work, experimental results on this novel observational wind-probing technique are presented. We utilized a controlled wind-tunnel setup to assess both the accuracy and the precision of AHFO under a range of operational conditions. The technique allows for wind speed characterization with a spatial resolution of 0.3 m on a 1 s time scale. The flow in the wind tunnel was varied in a controlled manner, such that the mean wind, ranged between 1 and 17 m/s. The AHFO measurements are compared to sonic anemometer measurements and show a high overall correlation (0.85–0.98). Both the precision and accuracy of the AHFO measurements were also greater than 95 %. We conclude that the AHFO has potential to be employed as an outdoor observational technique. It allows for characterization of spatially varying fields of mean wind in complex terrain, such as in canopy flows or in sloping terrain. In the future, the technique could be combined with conventional Distributed Temperature Sensing (DTS) for turbulent heat flux estimation in micrometeorological/hydrological applications.

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