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Relevant bibliographies by topics / Differential absorption

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Academic literature on the topic 'Differential absorption'

Author: Grafiati

Published: 4 June 2021

Last updated: 28 January 2023

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Journal articles on the topic "Differential absorption"

1

Theocharous, E. "Differential absorption displacement transducer." Journal of Physics E: Scientific Instruments 18, no. 3 (March 1985): 253–55. http://dx.doi.org/10.1088/0022-3735/18/3/019.

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Huang, Sheng-Wen, Janet F. Eary, Congxian Jia, Lingyun Huang, Shai Ashkenazi, and Matthew O'Donnell. "Differential-absorption photoacoustic imaging." Optics Letters 34, no. 16 (August 4, 2009): 2393. http://dx.doi.org/10.1364/ol.34.002393.

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Grant, William B., Alan M. Brothers, and James R. Bogan. "Differential absorption lidar signal averaging." Applied Optics 27, no. 10 (May 15, 1988): 1934. http://dx.doi.org/10.1364/ao.27.001934.

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Mei, Liang, and Mikkel Brydegaard. "Continuous-wave differential absorption lidar." Laser & Photonics Reviews 9, no. 6 (October 29, 2015): 629–36. http://dx.doi.org/10.1002/lpor.201400419.

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Virtanen, Simo. "ABSORPTION PATTERNS IN THE DIFFERENTIAL ABSORPTION TEST FOR INFECTIOUS MONONUCLEOSIS." Acta Pathologica Microbiologica Scandinavica 56, no. 1 (August 18, 2009): 57–64. http://dx.doi.org/10.1111/j.1699-0463.1962.tb04163.x.

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Millán, L., M. Lebsock, N. Livesey, S. Tanelli, and G. Stephens. "Differential absorption radar techniques: surface pressure." Atmospheric Measurement Techniques 7, no. 11 (November 27, 2014): 3959–70. http://dx.doi.org/10.5194/amt-7-3959-2014.

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Abstract. Two radar pulses sent at different frequencies near the 60 GHz O2 absorption band can be used to determine surface pressure by measuring the differential absorption on and off the band. Results of inverting synthetic data assuming an airborne radar are presented. The analysis includes the effects of temperature, water vapor, and hydrometeors, as well as particle size distributions and surface backscatter uncertainties. Results show that an airborne radar (with sensitivity of −20 and 0.05 dBZ speckle and relative calibration uncertainties) can estimate surface pressure with a precision of ~ 1.0 hPa and accuracy better than 1.0 hPa for clear-sky and cloudy conditions and better than 3.5 hPa for precipitating conditions. Generally, accuracy would be around 0.5 and 2 hPa for non-precipitating and precipitating conditions, respectively.

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Si Fu-Qi, Xie Pin-Hua, Klaus-Peter Heue, Liu-Cheng, Peng Fu-Min, and Liu Wen-Qing. "Hyperspectral imaging differential optical absorption spectroscopy." Acta Physica Sinica 57, no. 9 (2008): 6018. http://dx.doi.org/10.7498/aps.57.6018.

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CHEN Yafeng, 陈亚峰, 王晓宾 WANG Xiaobin, 刘秋武 LIU Qiuwu, 曹开法 CAO Kaifa, 胡顺星 HU Shunxing, and 黄见 HUANG Jian. "Mobile SO2 Differential Absorption Lidar System." ACTA PHOTONICA SINICA 46, no. 7 (2017): 701004. http://dx.doi.org/10.3788/gzxb20174607.0701004.

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Gorbics, Steven G., and N. R. Pereira. "Differential absorption spectrometer for pulsed bremsstrahlung." Review of Scientific Instruments 64, no. 7 (July 1993): 1835–40. http://dx.doi.org/10.1063/1.1144019.

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Godin, Sophie, Allen I. Carswell, David P. Donovan, Hans Claude, Wolfgang Steinbrecht, I. Stuart McDermid, Thomas J. McGee, et al. "Ozone differential absorption lidar algorithm intercomparison." Applied Optics 38, no. 30 (October 20, 1999): 6225. http://dx.doi.org/10.1364/ao.38.006225.

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Dissertations / Theses on the topic "Differential absorption"

1

McCarthy, Richard Ivor. "GUSTO : a differential UV absorption spectroscopy instrument." Thesis, Imperial College London, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.430743.

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Collar, A. J. "Differential absorption lidar using an optical parametric oscillator source." Thesis, University of Southampton, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.370334.

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Bobrowski, Nicole. "Volcanic gas studies by Multi Axis Differential Absorption Spectroscopy." [S.l. : s.n.], 2006. http://nbn-resolving.de/urn:nbn:de:bsz:16-opus-60521.

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Sinreich, Roman. "Multi-Axis differential optical absorption spectroscopy measurements in polluted environments." [S.l. : s.n.], 2007. http://nbn-resolving.de/urn:nbn:de:bsz:16-opus-80698.

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Kubera, Kimberly. "Evaluation of Upper Atmospheric Ozone Data provided by a Differential-Absorption Lidar." Thesis, Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/6900.

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Ground-level ozone is an environmental and public health issue. Daily ozone forecasts are made to allow people to take precautions to protect their health. For this study, a prototype laser that measures ozone concentrations vertically throughout the atmospheric boundary layer was evaluated as tool for ozone forecasting. To examine this data, three analyses were performed. First, it was determined if stratification, and thus residual layers, could be seen. This was conducted, in part, by examining hourly mixing heights overlaid onto color-coded NEXLASER charts. Each NEXLASER chart shows the horizontal and spatial distribution of the measured ozone concentrations during a twenty-four hour period. In the second analysis, the correlation value between the early morning upper-tropospheric ozone and the maximum 8-hour average surface ozone concentrations was determined. For the third analysis, a case study on two select groups of days was conducted. This study suggested that NEXLASER can be used to detect the presence of residual layers and can be used as an aid in predicting peak daily 8-hour average ground-level ozone concentrations. Specifically, days on which a morning ozone reservoir layer is most prominent have the most potential to lead to high surface ozone concentrations later in the day. While more research should be conducted, this study shows how this data could be useful in explaining ozone events, and thus be an aid to ozone forecasters.

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Jerez, Carlos J. "Measuring Atmospheric Ozone and Nitrogen Dioxide Concentration by Differential Optical Absorption Spectroscopy." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc103336/.

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The main objective was to develop a procedure based on differential optical absorption spectroscopy (DOAS) to measure atmospheric total column of ozone, using the automated instrument developed at the University of North Texas (UNT) by Nebgen in 2006. This project also explored the ability of this instrument to provide measurements of atmospheric total column nitrogen dioxide. The instrument is located on top of UNT’s Environmental Education, Science and Technology Building. It employs a low cost spectrometer coupled with fiber optics, which are aimed at the sun to collect solar radiation. Measurements taken throughout the day with this instrument exhibited a large variability. The DOAS procedure derives total column ozone from the analysis of daily DOAS Langley plots. This plot relates the measured differential column to the airmass factor. The use of such plots is conditioned by the time the concentration of ozone remains constant. Observations of ozone are typically conducted throughout the day. Observations of total column ozone were conducted for 5 months. Values were derived from both DOAS and Nebgen’s procedure and compared to satellite data. Although differences observed from both procedures to satellite data were similar, the variability found in measurements was reduced from 70 Dobson units, with Nebgen’s procedure, to 4 Dobson units, with the DOAS procedure.A methodology to measure atmospheric nitrogen dioxide using DOAS was also investigated. Although a similar approach to ozone measurements could be applied, it was found that such measurements were limited by the amount of solar radiation collected by the instrument. Observations of nitrogen dioxide are typically conducted near sunrise or sunset, when solar radiation experiences most of the atmospheric absorption.

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Smith, Nicola. "A spectroscopic study of the role of the nitrate radical in the troposphere." Thesis, University of East Anglia, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297008.

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Lawrence, James. "Differential absorption LiDAR for the total column measurement of atmospheric CO2 from space." Thesis, University of Leicester, 2012. http://hdl.handle.net/2381/10379.

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Since the beginning of the industrial revolution (1750 to 1800) the Earth’s atmospheric composition has undergone significant change as a result of human activities, in particular the burning of fossil fuels. As a consequence the atmospheric concentrations of a number of gases known to be influential to the Earth’s climate have increased far beyond natural levels. Atmospheric gases such as carbon dioxide which naturally exist in the Earth system have increased in correlation with anthropogenic emissions. The effect of this perturbation on the Earth system has been predicted through computer simulations to have undesirable consequences on the Earth’s future climate. The present measurement systems for atmospheric carbon dioxide have limited spatial coverage and temporal resolution which restricts their ability to accurately attribute observations of atmospheric composition to particular terrestrial sources and sinks. This inability to accurately locate and quantify the key carbon dioxide sources and sinks in the terrestrial and marine biospheres is hindering the understanding of the processes that are driving the Earth’s natural uptake of approximately half of the anthropogenic carbon dioxide emissions. With such uncertainty it is currently unknown precisely how the Earth’s climate will respond to global warming in the future. Through computer simulation it has been demonstrated that improving the spatial distribution of global measurements of atmospheric carbon dioxide is likely to advance the present understanding of the Earth’s terrestrial sources and sinks. Regions that require particular improvement in measurement coverage are the southern oceans owing to a lack of landmass on which to site instruments, and much of the tropics because of difficulties in locating instruments in some of the worlds more politically unstable regions. Satellite remote sensing instruments which measure atmospheric carbon dioxide from low Earth orbit provide some coverage of these sparsely sampled locations, however cloud cover often prevents measurements being made (particularly in the tropics), and limited latitudinal coverage caused by current instruments using passive remote sensing techniques prevents measurements at very high and low latitudes (including much of the southern ocean during local winter). An alternative remote sensing technique has been proposed in the scientific literature for measuring atmospheric carbon dioxide concentrations using laser emissions from a satellite platform known as total column differential absorption LiDAR (TC-DIAL). The TC-DIAL technique has been identified as having the theoretical potential to meet the coverage and precision requirements to greatly aid in identifying and quantifying terrestrial carbon dioxide sources and sinks. The TC-DIAL technique has the potential to achieve these goals largely owing to its unique capabilities of being able to make measurements during both the day and night and at all latitudes with a footprint which may be small enough to see between patchy cloud cover in the tropics. This thesis builds on previous studies of the TC-DIAL measurement technique from a satellite platform to assess its current and future capabilities to meet the observation requirements defined by the atmospheric carbon and modeling scientific communities. Particular investigations are carried out to assess the optimum system configuration in the context of global carbon modeling using up-to-date spectroscopy and instrument parameters for the latest technology. Optimum systems for both direct and heterodyne detection TC-DIAL instruments are defined, and it is found that direct detection provides the lowest retrieval errors under clear sky conditions. For a system based on current technology TC-DIAL retrievals are expected to have errors of approximately 0.68 ppm for direct detection and 1.01 ppm for heterodyne detection over a 50 km surface track. Using global cloud statistics two suitable pulse repetition frequencies (PRF) for a heterodyne detection system have been identified as 5 and 15 kHz. These PRF’s provide the minimum probability of an effect known as cross signal contamination occurring when measurements are made in the presence of cloud. In this thesis it is shown that the retrieval error incurred by cross signal contamination is > 16 ppm for a heterodyne detection TC-DIAL system measuring through cloud with optical depth > 2. The most important retrieval error component in TC-DIAL retrievals has been found to be the uncertainties introduced by the use of numerical weather prediction data for the ancillary atmospheric profiles. The limited spatial resolution of current NWP models (> 20 km) implies the uncertainties associated with the ancillary data are required to be treated as systematic, and as a consequence their errors dominate over other TC-DIAL retrieval errors following multiple pulse integration.

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Nehrir, Amin Reza. "Water vapor profiling using a compact widely tunable diode laser Differential Absorption Lidar (DIAL)." Thesis, Montana State University, 2008. http://etd.lib.montana.edu/etd/2008/nehrir/NehrirA1208.pdf.

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Atmospheric water vapor is an important driver of cloud formation, precipitation, and cloud microphysical structure. Changes in the cloud microphysical structure due to the interaction of aerosols and water vapor can produce more reflective clouds, resulting in more incoming solar radiation being reflected back into space, leading to an overall negative radiative forcing. Water vapor also plays an important role in the atmospheric feedback process that acts to amplify the positive radiative forcing resulting from increasing levels of atmospheric CO2. In the troposphere, where the water vapor greenhouse effect is most important, the situation is harder to quantify. A need exists for tools that allow for high spatial resolution range resolved measurements of water vapor number density up to about 4 km. One approach to obtaining this data within the boundary layer is with the Differential Absorption Lidar (DIAL) that is being developed at Montana State University. A differential absorption lidar (DIAL) instrument for automated profiling of water vapor in the lower troposphere has been designed, tested, and is in routine operation. The laser transmitter for the DIAL instrument uses a widely tunable external cavity diode laser (ECDL) to injection seed two cascaded semiconductor optical amplifiers (SOA) to produce a laser transmitter that accesses the 824-841 nm spectral range. The DIAL receiver utilizes a 28-cm-diameter Schmidt-Cassegrain telescope, an avalanche photodiode (APD) detector, and a narrow band optical filter to collect, discriminate, and measure the scattered light. A technique of correcting for the wavelength-dependent incident angle upon the narrow band optical filter as a function of range has been developed to allow accurate water vapor profiles to be measured down to 225 m above the surface. Data comparisons using the DIAL instrument and co-located radiosonde measurements are presented demonstrating the capabilities of the DIAL instrument.

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Obland, Michael Drew. "Water vapor profiling using a widely tunable amplified diode laser Differential Absorption Lidar (DIAL)." Diss., Montana State University, 2007. http://etd.lib.montana.edu/etd/2007/obland/OblandM0507.pdf.

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Water vapor is one of he most significant constituents of the atmosphere because of its role in cloud formation, precipitation, and interactions with electromagnetic radiation, especially its absorption of longwave infrared radiation. Some details of the role of water and related feedback mechanisms in the Earth system need to be characterized better if local weather, global climate, and the water cycle are to be understood. Water vapor profiles are currently obtained with several remote sensing techniques, such as microwave radiometers, passive instruments like the Atmospheric Emitted Radiance Interferometer (AERI), and Raman lidar. Each of these instruments has some disadvantage, such as only producing column integrated water vapor amounts or being large, overly customized, and costly, making them difficult to use for deployment in networks or onboard satellites to measure water vapor profiles. This thesis work involved the design, construction, and testing of a highly-tunable Differential Absorption Lidar (DIAL) instrument utilizing an all-semiconductor transmitter. It was an attempt to take advantage of semiconductor laser technology to obtain range-resolved water vapor profiles with an instrument that is cheaper, smaller, and more robust than existing field instruments. The eventual goal of this project was to demonstrate the feasibility of this DIAL instrument as a candidate for deployment in multi-point networks or satellite arrays to study water vapor flux profiles. This new DIAL instruments transmitter has, for the first time in any known DIAL instrument, a highly-tunable External Cavity Diode Laser (ECDL) as a seed laser source for two cascaded commercial tapered amplifiers. The transmitter has the capability of tuning over a range of ~17nm to selectively probe several available water vapor absorption lines, depending on current environmental conditions. This capability has been called for in other recent DIAL experiments, Tests of the DIAL instrument to prove the validity of its measurements are presented, Initial water vapor profiles, taken in the Bozeman, MT, area, were taken, analyzed, and compared with co-located radiosonde measurements, Future improvements and directions for the next generation of this DIAL instrument are discussed.

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Books on the topic "Differential absorption"

1

Platt, Ulrich. Differential optical absorption spectroscopy: Principles and applications. Berlin: Springer, 2008.

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2

Allen, Devinatz, ed. The limiting absorption principle for partial differential operators. Providence, R.I., USA: American Mathematical Society, 1987.

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3

Münch, Stefan Walter. Atmospheric water vapour sensing by means of differential absorption spectrometry using solar and lunar radiation. Zürich: Schweizerische Geodätische Kommission, 2014.

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Williamson, Cynthia K. Characterization of a 16-bit digitizer for lidar data acquisition. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 2000.

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Williamson, Cynthia K. Characterization of a 16-bit digitizer for lidar data acquisition. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 2000.

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Harper, David B. Signal-induced noise effects in a photon counting system for stratospheric ozone measurement. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.

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Harper, David B. Signal-induced noise effects in a photon counting system for stratospheric ozone measurement. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.

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Harper, David B. Signal-induced noise effects in a photon counting system for stratospheric ozone measurement. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1998.

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Herrmann, Samuel. Stochastic resonance: A mathematical approach in the small noise limit. Providence, Rhode Island: American Mathematical Society, 2014.

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Differential Optical Absorption Spectroscopy. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-75776-4.

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Book chapters on the topic "Differential absorption"

1

Spuler, Scott M., Matthew Hayman, and Tammy M. Weckwerth. "Water Vapor Differential Absorption Lidar." In Springer Handbook of Atmospheric Measurements, 741–57. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-52171-4_26.

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De Young, Russell. "Aircraft aircraft and Space Atmospheric Measurements Using Differential Absorption Lidar (DIAL) differential absorption lidar (DIAL)." In Encyclopedia of Sustainability Science and Technology, 309–29. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0851-3_878.

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Wirth, Martin. "Measuring Water Vapor with Differential Absorption Lidar." In Atmospheric Physics, 465–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30183-4_28.

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Kölsch, H. J., P. Rairoux, J. P. Wolf, and L. Wöste. "Probing Air Pollutants by Differential Absorption LIDAR." In Laser in der Umweltmeßtechnik / Laser in Remote Sensing, 85–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-50980-3_13.

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Voigt, Jürgen. "Absorption Semigroups, Feller Property, and Kato Class." In Partial Differential Operators and Mathematical Physics, 389–96. Basel: Birkhäuser Basel, 1995. http://dx.doi.org/10.1007/978-3-0348-9092-2_42.

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Galaktionov, Victor A., and Juan Luis Vázquez. "Porous Medium Equation with Critical Strong Absorption." In A Stability Technique for Evolution Partial Differential Equations, 127–67. Boston, MA: Birkhäuser Boston, 2004. http://dx.doi.org/10.1007/978-1-4612-2050-3_5.

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Galaktionov, Victor A., and Juan Luis Vázquez. "Quasilinear Heat Equations with Absorption. The Critical Exponent." In A Stability Technique for Evolution Partial Differential Equations, 81–125. Boston, MA: Birkhäuser Boston, 2004. http://dx.doi.org/10.1007/978-1-4612-2050-3_4.

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De Young, Russell. "Aircraft and Space Atmospheric Measurements Using Differential Absorption Lidar (DIAL)." In Earth System Monitoring, 35–61. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5684-1_3.

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Wolf, J. P., H. J. Kölsch, P. Rairoux, and L. Wöste. "Remote Detection of Atmospheric Pollutants Using Differential Absorption Lidar Techniques." In Applied Laser Spectroscopy, 435–67. Boston, MA: Springer US, 1990. http://dx.doi.org/10.1007/978-1-4684-1342-7_34.

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Shmarev, Sergei. "Interfaces in Solutions of Diffusion-absorption Equations in Arbitrary Space Dimension." In Progress in Nonlinear Differential Equations and Their Applications, 257–73. Basel: Birkhäuser Basel, 2005. http://dx.doi.org/10.1007/3-7643-7317-2_19.

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Conference papers on the topic "Differential absorption"

1

Richter, Peter. "Airborne Differential Absorption Lidar." In 1988 Los Angeles Symposium--O-E/LASE '88, edited by Frank Allario. SPIE, 1988. http://dx.doi.org/10.1117/12.944262.

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Lytkine, A., W. Jäger, and J. Tulip. "Frequency chirped differential absorption LIDAR." In Remote Sensing, edited by Upendra N. Singh. SPIE, 2006. http://dx.doi.org/10.1117/12.689312.

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Powers, Peter E., Thomas J. Kulp, and Randall B. Kennedy. "Differential backscatter absorption gas imaging." In AeroSense '97. SPIE, 1997. http://dx.doi.org/10.1117/12.280320.

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Peczeli, I., Peter I. Richter, Sz Borocz, L. Halasz, and R. C. Herndon. "Nonconventional coherent differential absorption lidar." In Environmental Sensing '92, edited by Richard J. Becherer and Christian Werner. SPIE, 1992. http://dx.doi.org/10.1117/12.138542.

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Ruffoni, M. P., R. F. Pettifer, S. Pascarelli, A. Trapananti, and O. Mathon. "An Introduction to Differential EXAFS." In X-RAY ABSORPTION FINE STRUCTURE - XAFS13: 13th International Conference. AIP, 2007. http://dx.doi.org/10.1063/1.2644679.

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Oh, Choonghoon, Coorg R. Prasad, Victor A. Fromzel, In H. Hwang, John A. Reagan, Hui Fang, and Manuel Rubio. "Water vapor micropulse differential absorption lidar." In AeroSense '99, edited by Gary W. Kamerman and Christian Werner. SPIE, 1999. http://dx.doi.org/10.1117/12.351342.

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Pierrottet, Diego F., and Daniel C. Senft. "CO 2 coherent differential absorption lidar." In AeroSense 2000, edited by Patrick J. Gardner. SPIE, 2000. http://dx.doi.org/10.1117/12.394075.

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Jost, Bradley M., Daniel C. Senft, Diego F. Pierrottet, Mark A. Kovacs, and Joe C. Cardani. "Doppler spectral scanning differential absorption lidar." In International Symposium on Optical Science and Technology, edited by Upendra N. Singh. SPIE, 2002. http://dx.doi.org/10.1117/12.452771.

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Butts, J. James. "Atmospheric tomography using differential absorption lidar." In Satellite Remote Sensing III, edited by Adam D. Devir, Anton Kohnle, and Christian Werner. SPIE, 1997. http://dx.doi.org/10.1117/12.263171.

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Mohebati, Arman, and Terence A. King. "Differential Absorption Fibre-Optic Gas Sensor." In 1988 International Congress on Optical Science and Engineering, edited by Ralf T. Kersten. SPIE, 1989. http://dx.doi.org/10.1117/12.949312.

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Reports on the topic "Differential absorption"

1

Carrico, J. P., K. R. Phelps, J. van der Laan, E. E. Uthe, and P. L. Holland. Infrared Differential Absorption Lidar for Vapor Detection. Fort Belvoir, VA: Defense Technical Information Center, February 1988. http://dx.doi.org/10.21236/ada190600.

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Cannon, Bret D., Warren W. Harper, Tanya L. Myers, Matthew S. Taubman, Richard M. Williams, and John F. Schultz. Progress Report on Frequency - Modulated Differential Absorption Lidar. Office of Scientific and Technical Information (OSTI), December 2001. http://dx.doi.org/10.2172/967023.

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MacKerrow, E. P., J. J. Tiee, and C. B. Fite. Laser speckle effects on hard target differential absorption lidar. Office of Scientific and Technical Information (OSTI), April 1996. http://dx.doi.org/10.2172/219305.

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Weckworth, Tammy M., Scott Spuler, and David D. Turner. Micropulse Differential Absorption Lidar (MPD) Network Demonstration Field Campaign Report. Office of Scientific and Technical Information (OSTI), January 2020. http://dx.doi.org/10.2172/1595264.

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Grund, C. J., R. M. Hardesty, and B. J. Rye. Feasibility of tropospheric water vapor profiling using infrared heterodyne differential absorption lidar. Office of Scientific and Technical Information (OSTI), April 1995. http://dx.doi.org/10.2172/48602.

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Rye, B. J., J. L. Machol, C. J. Grund, and R. M. Hardesty. Evaluation of tropospheric water vapor profiling using eye-safe, infrared differential absorption lidar. Office of Scientific and Technical Information (OSTI), May 1996. http://dx.doi.org/10.2172/244496.

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Nelson, D. H., R. R. Petrin, E. P. MacKerrow, M. J. Schmitt, C. R. Quick, A. Zardecki, W. M. Porch, M. Whitehead, and D. L. Walters. Wave optics simulation of atmospheric turbulence and reflective speckle effects in CO{sub 2} differential absorption LIDAR (DIAL). Office of Scientific and Technical Information (OSTI), September 1998. http://dx.doi.org/10.2172/674893.

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Repasky, Kevin. Development and Deployment of a Compact Eye-Safe Scanning Differential absorption Lidar (DIAL) for Spatial Mapping of Carbon Dioxide for Monitoring/Verification/Accounting at Geologic Sequestration Sites. Office of Scientific and Technical Information (OSTI), March 2014. http://dx.doi.org/10.2172/1155030.

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