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Atmospheric line-of-sight (LOS) wind measurement by means of incoherent Cabannes-Mie lidar with three frequency analyzers with nearly the same maximum transmission of ~80% that could be fielded at different wavelengths is analytically considered. These frequency analyzers are (a) a double-edge Fabry-Perot interferometer (FPI) at 1064 nm (IR-FPI), (b) a double-edge Fabry-Perot interferometer at 355 nm (UV-FPI), and (c) an iodine vapor filter (IVF) at 532 nm with two different methods, using either one absorption edge, single edge (se-IVF), or both absorption edges, double edge (de-IVF). The effect of the backscattered aerosol mixing ratio, R(b), defined as the ratio of the aerosol volume backscatter coefficient to molecular volume backscatter coefficient, on LOS wind uncertainty is discussed. Assuming a known aerosol mixing ratio, R(b), and 100,000 photons owing to Cabannes scattering to the receiver, in shot-noise-limited detection without sky background, the LOS wind uncertainty of the UV-FPI in the aerosol-free air (R(b)=0), is lower by ~16% than that of de-IVF, which has the lowest uncertainty for R(b) between 0.02 and 0.08; for R(b)>0.08, the IR-FPI yielded the lowest wind uncertainty. The wind uncertainty for se-IVF is always higher than that of de-IVF, but by less than a factor of 2 under all aerosol conditions, if the split between the reference and measurement channels is optimized. The design flexibility, which allows the desensitization of either aerosol or molecular scattering, exists only with the FPI system, leading to the common practice of using IR-FPI for the planetary boundary layer and using UV-FPI for higher altitudes. Without this design flexibility, there is little choice but to use a single wavelength IVF system at 532 nm for all atmospheric altitudes.
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http://dx.doi.org/10.1364/ao.46.004434 | DOI Listing |
PLoS One
September 2025
Electrical Engineering Determent, Faculty of Engineering, Minia University, Minia, Egypt.
Renewable energy systems are at the core of global efforts to reduce greenhouse gas (GHG) emissions and to combat climate change. Focusing on the role of energy storage in enhancing dependability and efficiency, this paper investigates the design and optimization of a completely sustainable hybrid energy system. Furthermore, hybrid storage systems have been used to evaluate their viability and cost-benefits.
View Article and Find Full Text PDFJ Air Waste Manag Assoc
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Department of Civil, Environmental & Construction Engineering, University of Central Florida, Orlando, Florida, USA.
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View Article and Find Full Text PDFMath Biosci Eng
July 2025
College of Engineering and Technology, American University of the Middle East, Kuwait.
Short-term wind speed forecasting is essential for enhancing the efficiency and dependability of wind renewable energy installations. Although often used, conventional point predictions generated by machine learning techniques frequently fail to accurately capture the natural uncertainty associated with wind speed variation. Modeling this type of uncertainty is crucial for providing credible information as the level of uncertainty increases.
View Article and Find Full Text PDFBayesian Anal
November 2024
Department of Statistical Science, Duke University.
We propose a class of nonstationary processes to characterize space- and time-varying directional associations in point-referenced data. We are motivated by spatiotemporal modeling of air pollutants in which local wind patterns are key determinants of the pollutant spread, but information regarding prevailing wind directions may be missing or unreliable. We propose to map a discrete set of wind directions to edges in a sparse directed acyclic graph (DAG), accounting for uncertainty in directional correlation patterns across a domain.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109.
An explosion of recent research uses remote imaging spectroscopy from aircraft and spacecraft to detect and quantify methane point source emissions. These instruments first map the methane enhancement field and then combine this information with the effective wind speed to estimate the source emission rate. This wind speed is typically the largest uncertainty in derived emission rates.
View Article and Find Full Text PDF