AEROSOL GENERATION DURING COUGHING - QUANTITATIVE DEFINITION FOR AEROSOL GENERATING PROCEDURES: OBSERVATIONAL STUDY
Enni SanmarkLotta‐Maria OksanenNoora RantanenMari LahelmaVeli‐Jukka AnttilaLasse LehtonenAntti HyvärinenAhmed Geneid
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ABSTRACT Aim The purpose of the study was to determine aerosol exposure generated by coughing in operation room environments to create a quantitative limit value for high-risk aerosol-generating medical procedures. Background Coughing is known to produce a significant amount of aerosols and is thus commonly used as a best reference for high-risk aerosol-generation. Accordingly, procedures during which aerosol generation exceeds the amount of aerosol generated in instances of coughing are seen as high-risk aerosol generating procedures. However, no reliable quantitative values are available for high-risk aerosol-generation. Methods Coughing was measured from 37 healthy volunteers in the operating room environment. Aerosol particles generated during coughing within the size range of 0.3–10 µm were measured with Optical Particle Sizer from 40cm, 70cm, and 100cm distances. The distances reflected potential exposure distances where personnel are during surgeries. Results A total of 306 coughs were measured. Average aerosol concentration during coughing was 1.580 ± 13.774 particles/cm 3 (range 0.000 – 195.528). Discussion The aerosol concentration measured in this study can be used as a limit for high-risk aerosol generation in the operating room environment when assessing the aerosol generating procedures and the risk of operating room staff’s exposure for aerosol particles.Keywords:
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太陽輻射の波長別測定を用いて大気中のaerosolの粒度分布を求める新しい光学的方法を得た 地上又は高所で測定されるaerosolによる波長刷の減衰係数は大気中にある種々の大きさをもつaerosolの波長別減衰係数の総和である すなわち各波長におけるaerosolによる減衰係数はこれらのaerosolの数(求める未知数)を含む方程式で示される そこでaerosolを大きさに従って幾つかに組分けし その組分けの数に等しい数の種々の波長の所で太陽輻射の減衰を観測すると 未知数(各組のaerosolの数)に等しい数の連立方程式が得られる するとこの式は一般に一義的に解が定まり 従って各組のaerosolの数すなわち粒度分布が求められる ところが一々このような方程式を解くことは極めて煩雑で不便であるので この連立方程式をmatrix表示し 既知係数よりなるmatrixの逆matrixを計算し このmatrixの要素表を作成しておけば この表より観測値を用いて簡単な計算によって aerosolの粒度分布が得られることを示す
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A monoethanolamine (MEA) aerosol growth model was developed to quantify the aerosol growth factor in an amine-based CO2 capture absorber that considers the gas-liquid interactions, and it is empirically validated by measuring the aerosol particle size and concentration. The aerosol growth model, using sucrose as the aerosol nuclei instead of sulfuric acid to prevent the corrosion of the test equipment, accurately predicted that the outlet aerosol size increased to the same level regardless of the sucrose concentration. It also found that particle concentration was the primary factor affecting aerosol growth and amine emissions. We found an inverse relationship between aerosol particle concentration and the aerosol size, while the MEA emissions were proportional to particle concentration.
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There is a growing need to evaluate bioaerosol sensors under relevant operational conditions. New methods are needed that can mimic the temporal fluctuations of ambient aerosol backgrounds and present biological aerosol challenges in a way that simulates a plausible biological agent attack. The Dynamic Concentration Aerosol Generator was developed to address this need. The authors developed a series of aerosol challenges consisting of Bacillus thuringiensis kurstaki (Btk) spores in the presence of background aerosols using a newly developed ramp testing method. Using ramping style tests, 5-min Btk releases were overlaid on top of a background aerosol that fluctuated at varying rates. Background aerosol compositions for different tests were designed to simulate the types of aerosol in the ambient environment. Background aerosol concentration was varied between 7.0 × 103 and 1.5 × 104 particles per liter of air (ppL). Aerosol number concentrations of Btk for the challenges were approximately 2.5 × 103 ppL and the culturable fraction of the collected Btk aerosol was estimated to be 1.25 × 103 colony forming-units (cfu)/L-air. Results of these experiments demonstrate a novel technique for dynamic aerosol generation that can be used to test biological aerosol sensors under controlled conditions designed to reproduce observed fluctuations in the ambient aerosol.
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Abstract. We introduce and evaluate aerosol simulations with the global aerosol–climate model ECHAM6.3–HAM2.3, which is the aerosol component of the fully coupled aerosol–chemistry–climate model ECHAM–HAMMOZ. Both the host atmospheric climate model ECHAM6.3 and the aerosol model HAM2.3 were updated from previous versions. The updated version of the HAM aerosol model contains improved parameterizations of aerosol processes such as cloud activation, as well as updated emission fields for anthropogenic aerosol species and modifications in the online computation of sea salt and mineral dust aerosol emissions. Aerosol results from nudged and free-running simulations for the 10-year period 2003 to 2012 are compared to various measurements of aerosol properties. While there are regional deviations between the model and observations, the model performs well overall in terms of aerosol optical thickness, but may underestimate coarse-mode aerosol concentrations to some extent so that the modeled particles are smaller than indicated by the observations. Sulfate aerosol measurements in the US and Europe are reproduced well by the model, while carbonaceous aerosol species are biased low. Both mineral dust and sea salt aerosol concentrations are improved compared to previous versions of ECHAM–HAM. The evaluation of the simulated aerosol distributions serves as a basis for the suitability of the model for simulating aerosol–climate interactions in a changing climate.
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A general purpose aerosol conditioning device called the Universal Aerosol Conditioner (UAC) has been designed and tested. The device may be used to condition an aerosol in multiple ways: dilute the entire aerosol (gas- and particle-phase), dilute only a gas-phase component of the aerosol without diluting the particle concentration, denude the aerosol by removing semi-volatile material from the particle phase, and humidify or dehumidify an aerosol. The UAC accomplishes these processes by bringing the aerosol into contact with sheath air and allowing enough time for gas-phase components of the aerosol to diffuse into the sheath flow. A model was developed to assess the theoretical performance of the UAC and was solved numerically. From the model it was determined that two parameters dictated the rate of diffusion between the two flows: the Péclet number and the ratio of sheath-to-aerosol flow rates. A prototype was designed and built and the theory of operation was experimentally validated by measuring the particle penetration efficiency and the gas dilution factor at various particle sizes and flow conditions. The results showed that at low aerosol and sheath flows, the prototype behaved closely to the theoretical model but diverged from the theory once the sheath flows were increased, presumably due to mixing between the two flows.Copyright © 2022 American Association for Aerosol Research
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ABSTRACT Aim The purpose of the study was to determine aerosol exposure generated by coughing in operation room environments to create a quantitative limit value for high-risk aerosol-generating medical procedures. Background Coughing is known to produce a significant amount of aerosols and is thus commonly used as a best reference for high-risk aerosol-generation. Accordingly, procedures during which aerosol generation exceeds the amount of aerosol generated in instances of coughing are seen as high-risk aerosol generating procedures. However, no reliable quantitative values are available for high-risk aerosol-generation. Methods Coughing was measured from 37 healthy volunteers in the operating room environment. Aerosol particles generated during coughing within the size range of 0.3–10 µm were measured with Optical Particle Sizer from 40cm, 70cm, and 100cm distances. The distances reflected potential exposure distances where personnel are during surgeries. Results A total of 306 coughs were measured. Average aerosol concentration during coughing was 1.580 ± 13.774 particles/cm 3 (range 0.000 – 195.528). Discussion The aerosol concentration measured in this study can be used as a limit for high-risk aerosol generation in the operating room environment when assessing the aerosol generating procedures and the risk of operating room staff’s exposure for aerosol particles.
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In this study, a monoethanolamine aerosol growth model was developed to investigate the aerosol growth factor. Interactions among the internal conditions in an absorber were considered in this aerosol model. Additionally, an experiment was conducted to measure aerosol particle size, for collecting in-house validation data. Sucrose was used as the aerosol nuclei instead of sulfuric acid to prevent the corrosion of equipment used in the experiment. Experimental results showed that the outlet aerosol sizes increased to the same size regardless of the sucrose concentrations. The aerosol growth model was validated using the in-house experimental data. The aerosol growth model efficiently predicted the aerosol size. For investigating aerosol growth effects, particle number concentration was determined to be the primary factor affecting aerosol growth and amine emissions. When the particle number concentration increased, the aerosol size decreased, whereas the MEA emission increased.
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Бұл зерттеужұмысындaКaно моделітурaлы жәнеоғaн қaтыстытолықмәліметберілгенжәнеуниверситетстуденттерінебaғыттaлғaн қолдaнбaлы (кейстік)зерттеужүргізілген.АхметЯссaуи университетініңстуденттеріүшін Кaно моделіқолдaнылғaн, олaрдың жоғaры білімберусaпaсынa қоятынмaңыздытaлaптaры, яғнисaпaлық қaжеттіліктері,олaрдың мaңыздылығытурaлы жәнесaпaлық қaжеттіліктерінеқaтыстыөз университетінқaлaй бaғaлaйтындығытурaлы сұрaқтaр қойылғaн. Осы зерттеудіңмaқсaты АхметЯсaуи университетіндетуризмменеджментіжәнеқaржы бaкaлaвриaт бaғдaрлaмaлaрыныңсaпaсынa қaтыстыстуденттердіңқaжеттіліктерінaнықтaу, студенттердіңқaнaғaттaну, қaнaғaттaнбaу дәрежелерінбелгілеу,білімберусaпaсын aнықтaу мен жетілдіружолдaрын тaлдaу болыптaбылaды. Осы мaқсaтқaжетуүшін, ең aлдыменКaно сaуaлнaмaсы түзіліп,116 студенткеқолдaнылдыжәнебілімберугежәнеоның сaпaсынa қaтыстыстуденттердіңтaлaптaры мен қaжеттіліктерітоптықжұмыстaрaрқылыaнықтaлды. Екіншіден,бұл aнықтaлғaн тaлaптaр мен қaжеттіліктерКaно бaғaлaу кестесіменжіктелді.Осылaйшa, сaпa тaлaптaры төрт сaнaтқa бөлінді:болуытиіс, бір өлшемді,тaртымдыжәнебейтaрaп.Соңындa,қaнaғaттaну мен қaнaғaттaнбaудың мәндеріесептелдіжәнестуденттердіңқaнaғaттaну мен қaнaғaттaнбaу деңгейлерінжоғaрылaту мен төмендетудеосытaлaптaр мен қaжеттіліктердіңрөліaйқын aнықтaлды.Түйінсөздер:сaпa, сaпaлық қaжеттіліктер,білімберусaпaсы, Кaно моделі.
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Abstract. We introduce and evaluate the aerosol simulations with the global aerosol-climate model ECHAM6.3-HAM2.3, which is the aerosol component of the fully coupled aerosol-chemistry-climate model ECHAM-HAMMOZ. Both the host atmospheric climate model ECHAM6.3 and the aerosol model HAM2.3 were updated from previous versions. The updated version of the HAM aerosol model contains improved parameterizations of aerosol processes such as cloud activation, as well as updated emission fields for anthropogenic aerosol species and modifications in the online computation of sea salt and mineral dust aerosol emissions. Aerosol results from nudged and free running simulations for the 10-year period 2003 to 2012 are compared to various measurements of aerosol properties. While there are regional deviations between model and observations, the model performs well overall in terms of aerosol optical thickness, but may underestimate coarse mode aerosol concentrations to some extent, so that the modeled particles are smaller than indicated by the observations. Sulfate aerosol measurements in the US and Europe are reproduced well by the model, while carbonaceous aerosol species are biased low. Both mineral dust and sea salt aerosol concentrations are improved compared to previous versions of ECHAM-HAM. The evaluation of the simulated aerosol distributions serves as a basis for the suitability of the model for simulating aerosol-climate interactions in a changing climate.
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