{"status":"ok","message-type":"work-list","message-version":"1.0.0","message":{"facets":{},"total-results":740501,"items":[{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T17:14:03Z","timestamp":1791306843299,"version":"4.3.1"},"reference-count":77,"publisher":"Copernicus GmbH","issue":"9","license":[{"start":{"date-parts":[[2012,9,20]],"date-time":"2012-09-20T00:00:00Z","timestamp":1348099200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Atmos. Meas. Tech."],"abstract":"<jats:p>Abstract. Droplet size spectra measurements are crucial to obtain a quantitative microphysical description of clouds and fog. However, cloud droplet size measurements are subject to various uncertainties. This work focuses on the error analysis of two key measurement uncertainties arising during cloud droplet size measurements with a conventional droplet size spectrometer (FM-100): first, we addressed the precision with which droplets can be sized with the FM-100 on the basis of the Mie theory. We deduced error assumptions and proposed a new method on how to correct measured size distributions for these errors by redistributing the measured droplet size distribution using a stochastic approach. Second, based on a literature study, we summarized corrections for particle losses during sampling with the FM-100. We applied both corrections to cloud droplet size spectra measured at the high alpine site Jungfraujoch for a temperature range from 0 \u00b0C to 11 \u00b0C. We showed that Mie scattering led to spikes in the droplet size distributions using the default sizing procedure, while the new stochastic approach reproduced the ambient size distribution adequately. A detailed analysis of the FM-100 sampling efficiency revealed that particle losses were typically below 10% for droplet diameters up to 10 \u03bcm. For larger droplets, particle losses can increase up to 90% for the largest droplets of 50 \u03bcm at ambient wind speeds below 4.4 m s\u22121 and even to &gt;90% for larger angles between the instrument orientation and the wind vector (sampling angle) at higher wind speeds. Comparisons of the FM-100 to other reference instruments revealed that the total liquid water content (LWC) measured by the FM-100 was more sensitive to particle losses than to re-sizing based on Mie scattering, while the total number concentration was only marginally influenced by particle losses. Consequently, for further LWC measurements with the FM-100 we strongly recommend to consider (1) the error arising due to Mie scattering, and (2) the particle losses, especially for larger droplets depending on the set-up and wind conditions.<\/jats:p>","DOI":"10.5194\/amt-5-2237-2012","type":"journal-article","created":{"date-parts":[[2012,9,20]],"date-time":"2012-09-20T05:36:52Z","timestamp":1348119412000},"page":"2237-2260","source":"Crossref","is-referenced-by-count":95,"title":["Evaluating the capabilities and uncertainties of droplet measurements for the fog droplet spectrometer (FM-100)"],"prefix":"10.5194","volume":"5","author":[{"given":"J. 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Droplet size spectra measurements are crucial to obtain a quantitative microphysical description of clouds and fog. However, cloud droplet size measurements are subject to various uncertainties. This work focuses on the evaluation of two key measurement uncertainties arising during cloud droplet size measurements with a conventional droplet size spectrometer (FM-100): first, we addressed the precision with which droplets can be sized with the FM-100 on the basis of Mie theory. We deduced error assumptions and proposed how to correct measured size distributions for these errors by redistributing the measured droplet size distribution using a stochastic approach. Second, based on a literature study, we derived corrections for particle losses during sampling with the FM-100. We applied both corrections to cloud droplet size spectra measured at the high alpine site Jungfraujoch for a temperature range from 0 \u00b0C to 11 \u00b0C. We show that Mie scattering led to spikes in the droplet size distributions using the default sizing procedure, while the stochastic approach reproduced the ambient size distribution adequately. A detailed analysis of the FM-100 sampling efficiency revealed that particle losses were typically below 10% for droplet diameters up to 10 \u03bcm. For larger droplets, particle losses can increase up to 90% for the largest droplets of 50 \u03bcm at ambient windspeeds below 4.4 m s\u22121 and even to &gt;90% for larger angles between the instrument orientation and the wind vector (sampling angle) at higher wind speeds. Comparisons of the FM-100 to other reference instruments revealed that the total liquid water content (LWC) measured by the FM-100 was more sensitive to particle losses than to re-sizing based on Mie scattering, while the total number concentration was only marginally influenced by particle losses. As a consequence, for further LWC measurements with the FM-100 we strongly recommend to consider (1) the error arising due to Mie scattering, and (2) the particle losses, especially for larger droplets depending on the set-up and wind conditions.<\/jats:p>","DOI":"10.5194\/amtd-5-3333-2012","type":"posted-content","created":{"date-parts":[[2012,5,7]],"date-time":"2012-05-07T02:33:47Z","timestamp":1336358027000},"source":"Crossref","is-referenced-by-count":3,"title":["Evaluating the capabilities and uncertainties of droplet measurements for the fog droplet spectrometer (FM-100)"],"prefix":"10.5194","author":[{"given":"J. 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This study uses Eulerian\u2013Lagrangian simulations to examine the effects of fog-mesh wire diameter (df 0.2\u20131.0\u2009mm), shade coefficient (SC\u2009=\u20090.3\u20130.7), and freestream velocity (2\u20135\u2009m s\u22121) on the capture of droplets with diameters from 2 to 40\u2009\u03bcm. To interpret the results in a transferable form, droplet behavior is organized by Stokes number into three regimes: regime 1 (low-St and streamline-following droplets with weak capture), regime 2 (intermediate-St droplets that are highly sensitive to mesh geometry and aerodynamics), and regime 3 (high-St droplets dominated by inertial impaction). Large droplets show the highest instantaneous capture across most cases, whereas intermediate droplets govern the sensitivity to SC, df, and U. Fine and intermediate wires (df\u2009=\u20090.2\u20130.6\u2009mm) with SC close to 0.6 provide the best balance between geometric interception and aerodynamic permeability. Increasing velocity enhances impaction until wake formation and flow diversion limit additional gain. The results are interpreted using a nondimensional framework, based on the droplet Stokes number, mesh-fiber Reynolds number, pressure-drop coefficient, and shade coefficient. The reported fog-capture efficiency (\u03b7cap) values should be interpreted as the dry-mesh capture efficiencies (instantaneous capture at the onset of fogging, or under lean fog loading) since the current study excludes the dynamic impact of prolonged wetting, liquid deposition and growth on the fibers, mesh pore-clogging, and droplet re-entrainment effects. 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Geophys. Res."],"published-print":{"date-parts":[[2004,5,27]]},"abstract":"<jats:p>Organic aerosol alters cloud and fog properties through surface tension and solubility effects. This study characterizes the role of organic compounds in affecting fog droplet number concentration by initializing and comparing detailed particle microphysical simulations with two field campaigns in the Po Valley. The size distribution and chemical composition of aerosol were based on the measurements made in the Po Valley Fog Experiments in 1989 and 1998\u20131999. Two types of aerosol with different hygroscopicity were considered: the less hygroscopic particles, composed mainly of organic compounds, and the more hygroscopic particles, composed mainly of inorganic salts. The organic fraction of aerosol mass was explicitly modeled as a mixture of seven soluble compounds [<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"#jgrd11180-bib-0013\"><jats:italic>Fuzzi et al.<\/jats:italic>, 2001<\/jats:ext-link>] by employing a functional group\u2010based thermodynamic model [<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"#jgrd11180-bib-0021\"><jats:italic>Ming and Russell<\/jats:italic>, 2002<\/jats:ext-link>]. Condensable gases in the vapor phase included nitric acid, sulfuric acid, and ammonia. The maximum supersaturation in the simulation is 0.030% and is comparable to the calculation by <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"#jgrd11180-bib-0025\"><jats:italic>Noone et al.<\/jats:italic> [1992]<\/jats:ext-link> inferred from measured residual particle fractions. The minimum activation diameters of the less and more hygroscopic particles are 0.49 \u03bcm and 0.40 \u03bcm, respectively. The predicted residual particle fractions are in agreement with measurements. The organic components of aerosol account for 34% of the droplet residual particle mass and change the average droplet number concentration by \u221210\u20136%, depending on the lowering of droplet surface tension and the interactions among dissolving ions. The hygroscopic growth of particles due to the presence of water\u2010soluble organic compounds enhances the condensation of nitric acid and ammonia due to the increased surface area, resulting in a 9% increase in the average droplet number concentration. Assuming ideal behavior of aqueous solutions of water\u2010soluble organic compounds overestimates the hygroscopic growth of particles and increases droplet numbers by 6%. The results are sensitive to microphysical processes such as condensation of soluble gases, which increases the average droplet number concentration by 26%. 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This paper provides the results of extensive experimental and theoretical studies conducted over several years, coupled with practical aspects learned in the implementation of nearly 500 inlet fogging systems on gas turbines ranging in power from 5 to 250 MW. Part B of the paper treats the practical aspects of fog nozzle droplet sizing, measurement and testing presenting the information from a gas turbine fogging perspective. 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While most devices reported to date rely on advanced photonic integration technologies, here we demonstrate a miniaturization strategy which harnesses unforced mechanisms, such as the evaporation of a liquid droplet on a partially reflective substrate. Based on this principle, we describe a self-operating optofluidic spectrometer and the analysis method to retrieve consistent spectral information in spite of the intrinsically non-reproducible droplet formation and evaporation dynamics. We experimentally realize the device on the tip of an optical fiber and demonstrate quantitative measurements of gas absorption with a 2.6\u2009nm resolution, in a 100\u2009s acquisition time, over the 250\u2009nm span allowed by our setup\u2019s components. A direct comparison with a commercial optical analyzer clearly points out that a simple evaporating droplet can be an efficient small-scale, inexpensive spectrometer, competitive with the most advanced integrated photonic devices.<\/jats:p>","DOI":"10.1038\/s41467-020-16206-8","type":"journal-article","created":{"date-parts":[[2020,5,8]],"date-time":"2020-05-08T10:03:04Z","timestamp":1588932184000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["A self-operating broadband spectrometer on a droplet"],"prefix":"10.1038","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3821-4085","authenticated-orcid":false,"given":"P.","family":"Malara","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"A.","family":"Giorgini","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S.","family":"Avino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V.","family":"Di Sarno","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R.","family":"Aiello","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P.","family":"Maddaloni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"P.","family":"De Natale","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"G.","family":"Gagliardi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,5,8]]},"reference":[{"key":"16206_CR1","doi-asserted-by":"publisher","first-page":"1017","DOI":"10.1126\/science.aax8814","volume":"365","author":"Z Yang","year":"2019","unstructured":"Yang, Z. et al. 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Based on the observation data of fog droplet spectrum monitor, visibility sensor, environmental particle monitoring equipment and meteorological automatic station, the characteristics of fog droplet size distribution and the interaction between the fog droplets and fine particles during dense fog events were analyzed. The results show following characteristics: (1) The average concentration of fog droplets (Na), the average liquid water content (La) and the maximum liquid water content (Lmax) in the strong dense fog process are larger than those in the dense fog. The average spectrum of fog droplet size distribution conforms to Junge distribution, and they are all broad-spectrum fog with a spectrum width of about 45 \u03bcm. The average spectrum is similar to the dense fog of heavily industrialized inland in the world. (2) The maximum of fog droplet diameter during the formation stage have a good indication for the outbreak of strong dense fog. (3) The mass concentration of PM2.5 (CPM2.5) is ranged from 121\u2013375 \u03bcg\/m3, and the interaction between fog droplets and fine particles is analyzed. During the formation, development and maturity stages, fog process can scavenge atmospheric fine particles, and the scavenging efficiency of PM2.5 is more remarkable than PM10. When CPM2.5 does not exceed 350 \u03bcg\/m3, the increase in the concentration of fine particles is conducive to the rapid growth of fog droplets and the sharp drop of visibility. However, when CPM2.5 exceeds the critical value, the increase has a negative feedback effect on the development of the fog process. More investigations and cases are necessary to fully assess the mechanisms related to the dense fog events in Tianjin area and further analysis will be done.<\/jats:p>","DOI":"10.3390\/atmos11030258","type":"journal-article","created":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T07:33:46Z","timestamp":1583480026000},"page":"258","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":42,"title":["Fog Droplet Size Distribution and the Interaction between Fog Droplets and Fine Particles during Dense Fog in Tianjin, China"],"prefix":"10.3390","volume":"11","author":[{"given":"Qing","family":"Liu","sequence":"first","affiliation":[{"name":"Tianjin Weather Modification Office, Tianjin 300074, China"},{"name":"Tianjin Key laboratory of Marine Meteorology, Tianjin 300074, China"},{"name":"Key Laboratory for Cloud Physics of China Meteorological Administration, Beijing 100081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bingui","family":"Wu","sequence":"additional","affiliation":[{"name":"Tianjin Key laboratory of Marine Meteorology, Tianjin 300074, China"},{"name":"Tianjin Meteorology Bureau, Tianjin 300074, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Tianjin Weather Modification Office, Tianjin 300074, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianyi","family":"Hao","sequence":"additional","affiliation":[{"name":"Tianjin Key laboratory of Marine Meteorology, Tianjin 300074, China"},{"name":"Tianjin Meteorology Bureau, Tianjin 300074, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Kulkarni, R., Jenamani, R.K., Pithani, P., Konwar, M., Nigam, N., and Ghude, S.D. 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