Inter-comparison studies of well-characterized fractal soot particles were conducted using the following four instruments: Aerosol Mass Spectrometer-Scanning Mobility Particle Sizer (AMS-SMPS), ...Single Particle Soot Photometer (SP2), Multi-Angle Absorption Photometer (MAAP), and Photoacoustic Spectrometer (PAS). These instruments provided measurements of the refractory mass (AMS-SMPS), incandescent mass (SP2) and optically absorbing mass (MAAP and PAS). The particles studied were in the mobility diameter range from 150 nm to 460 nm and were generated by controlled flames with fuel equivalence ratios ranging between 2.3 and 3.5. The effect of organic coatings (oleic acid and anthracene) on the instrument measurements was determined. For uncoated soot particles, the mass measurements by the AMS-SMPS, SP2, and PAS instruments were in agreement to within 15%, while the MAAP measurement of optically-absorbing mass was higher by ∼ 50%. Thin organic coatings (∼ 10 nm) did not affect the instrument readings. A thicker (∼ 50 nm) oleic acid coating likewise did not affect the instrument readings. The thicker (∼60 nm) anthracene coating did not affect the readings provided by the AMS-SMPS or SP2 instruments but increased the reading of the MAAP instrument by ∼ 20% and the reading of the PAS by ∼ 65%. The response of each instrument to the different particle types is discussed in terms of particle morphology and coating material.
Emissions from motor vehicles are a significant source of fine particulate matter (PM) and gaseous pollutants in urban environments. Few studies have characterized both gaseous and PM emissions from ...individual in-use vehicles under real-world driving conditions. Here we describe chase vehicle studies in which on-road emissions from individual vehicles were measured in real time within seconds of their emission. This work uses an Aerodyne aerosol mass spectrometer (AMS) to provide size-resolved and chemically resolved characterization of the nonrefractory portion of the emitted PM; refractory materials such as elemental carbon (EC) were not measured in this study. The AMS, together with other gas-phase and particle instrumentation, was deployed on the Aerodyne Research Inc. (ARI) mobile laboratory, which was used to "chase" the target vehicles. Tailpipe emission indices of the targeted vehicles were obtained by referencing the measured nonrefractory particulate mass loading to the instantaneous CO
2
measured simultaneously in the plume. During these studies, nonrefractory PM
1.0
(NRPM
1
) emission indices for a representative fraction of the New York City Metropolitan Transit Authority (MTA) bus fleet were determined. Diesel bus emissions ranged from 0.10 g NRPM
1
/kg fuel to 0.23 g NRPM
1
/kg, depending on the type of engine used by the bus. The average NRPM
1
emission index of diesel-powered buses using Continuously Regenerating Technology (CRT™) trap systems was 0.052 g NRPM
1
/kg fuel. Buses fueled by compressed natural gas (CNG) had an average emission index of 0.034 g NRPM
1
/kg Fuel. The mass spectra of the nonrefractory diesel aerosol components measured by the AMS were dominated by lubricating oil spectral signatures. Mass-weighted size distributions of the particles in fresh diesel exhaust plumes peak at vacuum aerodynamic diameters around 90 nm with a typical full width at half maximum of 60 nm.
Two Aerodyne Aerosol Mass Spectrometers (AMS) were deployed at three sites representing urban, semi-rural and rural areas during the Pacific 2001 experiment in the Lower Fraser Valley (LFV), British ...Columbia, Canada in August 2001. The AMS provides on-line quantitative measurements of the size and chemical composition of the non-refractory fraction of submicron aerosol particles. A significant accumulation mode with a peak around 400–500nm was observed at all sites that was principally composed of sulphate, organics, ammonium and some nitrate. Another significant mode with a peak below 200nm was also observed at the urban site and when urban plumes affected the other sites. This paper focuses on the variability of the organic particulate composition and size distribution as a function of location and photochemical activity with a particular emphasis on the urban and rural areas. The small organic mode at the urban site was well correlated with gas phase CO, 1,3-butadiene, benzene and toluene with Pearson's r values of 0.76, 0.71, 0.79 and 0.69, respectively, suggesting that combustion-related emissions are likely to be the main source of the small organic mode at this site. The mass spectra of the urban organic particulate are similar to those of internal combustion engine lubricating oil, and of diesel exhaust aerosol particles, implying that they were composed of a mixture of n-alkanes, branched alkanes, cycloalkanes, and aromatics. In contrast, organic particulate at the rural site was dominated by shorter chain oxidized organic compounds. Correlations between the two organic modes and gas phase compounds at the rural site indicated that a significant part of the small mode originated from combustion sources, while the large accumulation organic mode appeared to be the result of photochemical processing. Processing of organic particulate during a relatively high O3 episode at the rural site appeared to increase the modal diameter of the accumulation mode from about 400 to 600nm and almost doubled its mass loading.
A generalised method for the deconvolution of mass spectral data from the aerodyne aerosol mass spectrometer (AMS) is presented. In this instrument, the sampled ensemble of gas and non-refractory ...particle phase materials interfere with each other in the mass spectra and the data must be systematically analyzed to generate meaningful, quantitative and chemically resolved results. The method presented here is designed to arithmetically separate the raw data into partial mass spectra for distinct chemical species. This technique was developed as part of the AMS analysis tools introduced by Allan et al. (J. Geophys. Res. Atmos. 108 (2003) 4090) and is in use by most groups within the AMS users community. This technique employs a user-definable ‘fragmentation table’ for each chemical species or group of species, and examples of some tables designed for the interpretation of field data are given. The ongoing work being performed to develop and validate the tables will be presented in future publications.
Two Aerodyne aerosol mass spectrometers (AMSs) were deployed at Trinidad Head on the north Californian coast during the National Oceanographic and Atmospheric Administration Intercontinental ...Transport and Chemical Transformation 2002 (ITCT 2K2) experiment, to study the physiochemical properties of submicron aerosol particles within the Pacific marine boundary layer. One AMS was modified to allow the study of sea salt‐based particles, while the other used a temperature cycling system on its inlet. The reported loadings increased by a factor of 2 when the temperature approached the dew point, which is due to the inlet performance and has implications for other AMS experiments and applications. The processed data were compared with those of a particle into liquid sampler‐ion chromatograph and showed that the ammonium, sulfate and organic fractions of the particles were consistently found within a single, normally acidic, accumulation mode at around 300–400 nm. However, when influenced by land‐based sources, vehicle emissions and increased ammonium loadings were seen. The concentrations of nitrate in the accumulation mode were low, but it was also found within sea salt particles in the coarse mode and can be linked to the displacement of chloride. The organic fraction showed a high degree of chemical ageing and evidence of nitrogen‐bearing organics was also observed. The particulate organic data were compared to the volatile organic carbon data derived from an in‐situ gas chromatograph‐mass spectrometer‐flame ionization detector and relationships were found between the gas and particle phase chemicals in both the overall concentrations and the levels of oxidation.
In part 1 of this series, techniques for generating quantitative information on fine airborne particulate‐size and chemically resolved mass concentration from an Aerodyne aerosol mass spectrometer ...were introduced. Presented here are the results generated using these techniques from sampling U.K. urban air with such an instrument in Edinburgh during October 2000 and in Manchester during July 2001 and January 2002. Data on the total mass concentrations and size‐resolved mass distributions of nitrate, sulfate, and organic compounds were obtained for all three campaigns and compared with data from other sources, including a micro‐orifice uniform deposit impactor, total particle numbers, CO and NOx concentrations, local wind speed and temperature, and back trajectory analysis. All three locations showed evidence for emissions from local transport, with a mass modal aerodynamic diameter of around 100–200nm. This mode was dominated by hydrocarbons showing little evidence of oxidization. The three sites also exhibited a larger mode consisting of inorganic chemicals and oxidized organics, which appeared to be governed by sources external to the cities and showed evidence of internal mixing. The mass modal aerodynamic diameter varied between approximately 200–500 nm during the winter and 500–800 nm during the summer. The summer also showed an increased mass loading without an increase in total particle number. Evidence of material building up and ageing in the atmospheric surface layer during periods of low wind speeds was also observed.
A large and increasing fraction of the planet's population lives in megacities, especially in the developing world. These large metropolitan areas generally have very high levels of both gaseous and ...particulate air pollutants that have severe impacts on human health, ecosystem viability, and climate on local, regional, and even continental scales. Emissions fluxes and ambient pollutant concentration distributions are generally poorly characterized for large urban areas even in developed nations. Much less is known about pollutant sources and concentration patterns in the faster growing megacities of the developing world. New methods of locating and measuring pollutant emission sources and tracking subsequent atmospheric chemical transformations and distributions are required. Measurement modes utilizing an innovative van based mobile laboratory equipped with a suite of fast response instruments to characterize the complex and "nastier" chemistry of the urban boundary layer are described. Instrumentation and measurement strategies are illustrated with examples from the Mexico City and Boston metropolitan areas. It is shown that fleet average exhaust emission ratios of formaldehyde (HCHO), acetaldehyde (CH3CHO) and benzene (C6H6) are substantial in Mexico City, with gasoline powered vehicles emitting higher levels normalized by fuel consumption. NH3 exhaust emissions from newer light duty vehicles in Mexico City exceed levels from similar traffic in Boston. A mobile conditional sampling air sample collection mode designed to collect samples from intercepted emission plumes for later analysis is also described.
Deep Transfer Learning Based Stroke Risk Prediction B, Sushma Reddy K; R, Dr. Manjula G; G, Nikhil
International Journal for Research in Applied Science and Engineering Technology,
9/2023, Letnik:
11, Številka:
9
Journal Article
Odprti dostop
Stroke is a medical condition that occurs when there is any blockage or bleeding of the blood vessels either interrupts or reduces the supply of blood to the brain. It causes the disability of ...multiple organs or unexpected death, if that patient’s recognise and address risks at the right time, up to 80% of stroke occurrences can be averted. With the advancement of machine learning in medical science, the early recognition of stroke is very much possible that plays a vital role in diagnosis and getting read of this life taking disease. But it requires large well-labeled data. Due to the strict privacy protection policy in health-care systems, stroke data is usually distributed among different hospitals in small pieces. In addition, the positive and negative instances of such data are extremely imbalanced. Transfer learning can solve small data issue by exploiting the knowledge of a correlated domain, especially when multiple sources of data are available. In this work, deep Transfer Learning based Stroke Risk Prediction scheme is proposed to exploit the knowledge structure from multiple correlated sources and used bayesian optimization for selecting the best parameter. This model is tested in synthetic and real-world scenarios and the random forest gives more accuracy than other models like support vector machines (SVM), decision trees (DT), random forests (RF) and voting classifiers. It also shows the potential of real-world deployment among multiple hospitals aided with 5 G/B5G infrastructures.
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