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Near-Real Time Measurement of Carbonaceous Aerosol Using Microplasma Spectroscopy: Application to Measurement of Carbon Nanomaterials.

ABSTRACT: A sensitive, field-portable microplasma spectroscopy method has been developed for real-time measurement of carbon nanomaterials. The method involves microconcentration of aerosol on a microelectrode tip for subsequent analysis for atomic carbon using laser-induced breakdown spectroscopy (LIBS) or spark emission spectroscopy (SES). The spark-induced microplasma was characterized by measuring the excitation temperature (15,000 - 35,000 K), electron density (1.0 × 1017 - 2.2 × 1017 cm-3), and spectral responses as functions of time and interelectrode distance. The system was calibrated and detection limits were determined for total atomic carbon (TAC) using a carbon emission line at 247.856 nm (C I) for various carbonaceous materials including sucrose, EDTA, caffeine, sodium carbonate, carbon black, and carbon nanotubes. The limit of detection for total atomic carbon was 1.61 ng, equivalent to 238 ng m-3 when sampling at 1.5 L min-1 for 5 min. To improve the selectivity for carbon nanomaterials, which consist of elemental carbon (EC), the cathode was heated to 300 °C to reduce the contribution of organic carbon to the total atomic carbon. Measurements of carbon nanotube aerosol at elevated electrode temperature showed improved selectivity to elemental carbon and compared well with the measurements from thermal optical method (NIOSH Method 5040). The study shows that the SES method to be an excellent candidate for development as a low-cost, hand-portable, real-time instrument for measurement of carbonaceous aerosols and nanomaterials.

SUBMITTER: Zheng L

PROVIDER: S-EPMC5476210 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Near-Real Time Measurement of Carbonaceous Aerosol Using Microplasma Spectroscopy: Application to Measurement of Carbon Nanomaterials.

Zheng Lina L Kulkarni Pramod P Birch M Eileen ME Deye Gregory G Dionysiou Dionysios D DD

Aerosol science and technology : the journal of the American Association for Aerosol Research 20160801 11

A sensitive, field-portable microplasma spectroscopy method has been developed for real-time measurement of carbon nanomaterials. The method involves microconcentration of aerosol on a microelectrode tip for subsequent analysis for atomic carbon using laser-induced breakdown spectroscopy (LIBS) or spark emission spectroscopy (SES). The spark-induced microplasma was characterized by measuring the excitation temperature (15,000 - 35,000 K), electron density (1.0 × 10<sup>17</sup> - 2.2 × 10<sup>17 ...[more]

PMID: 28638174

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Project description:IntroductionElectronic cigarette (e-cigarette) use is increasing worldwide and is highest among both daily and nondaily smokers. E-cigarettes are perceived as a healthier alternative to combustible tobacco products, but their health risk factors have not yet been established, and one of them is lack of data on aerosol size generated by e-cigarettes.MethodsWe applied a real-time, high-resolution aerosol differential mobility spectrometer to monitor the evolution of aerosol size and concentration during puff development. Particles generated by e-cigarettes were immediately delivered for analysis with minimal dilution and therefore with minimal sample distortion, which is critically important given the highly dynamic aerosol/vapor mixture inherent to e-cigarette emissions.ResultsE-cigarette aerosols normally exhibit a bimodal particle size distribution: nanoparticles (11-25nm count median diameter) and submicron particles (96-175nm count median diameter). Each mode has comparable number concentrations (10(7)-10(8) particles/cm(3)). "Dry puff" tests conducted with no e-cigarette liquid (e-liquid) present in the e-cigarette tank demonstrated that under these conditions only nanoparticles were generated. Analysis of the bulk aerosol collected on the filter showed that e-cigarette emissions contained a variety of metals.ConclusionsE-cigarette aerosol size distribution is different from that of combustible tobacco smoke. E-cigarettes generate high concentrations of nanoparticles and their chemical content requires further investigation. Despite the small mass of nanoparticles, their toxicological impact could be significant. Toxic chemicals that are attached to the small nanoparticles may have greater adverse health effects than when attached to larger submicron particles.ImplicationsThe e-cigarette aerosol size distribution is different from that of combustible tobacco smoke and typically exhibits a bimodal behavior with comparable number concentrations of nanoparticles and submicron particles. While vaping the e-cigarette, along with submicron particles the user is also inhaling nano-aerosol that consists of nanoparticles with attached chemicals that has not been fully investigated. The presence of high concentrations of nanoparticles requires nanotoxicological consideration in order to assess the potential health impact of e-cigarettes. The toxicological impact of inhaled nanoparticles could be significant, though not necessarily similar to the biomarkers typical of combustible tobacco smoke.

Project description:Chronic tinnitus is a debilitating condition which affects 10-20% of adults and can severely impact their quality of life. Currently there is no objective measure of tinnitus that can be used clinically. Clinical assessment of the condition uses subjective feedback from individuals which is not always reliable. We investigated the sensitivity of functional near-infrared spectroscopy (fNIRS) to differentiate individuals with and without tinnitus and to identify fNIRS features associated with subjective ratings of tinnitus severity. We recorded fNIRS signals in the resting state and in response to auditory or visual stimuli from 25 individuals with chronic tinnitus and 21 controls matched for age and hearing loss. Severity of tinnitus was rated using the Tinnitus Handicap Inventory and subjective ratings of tinnitus loudness and annoyance were measured on a visual analogue scale. Following statistical group comparisons, machine learning methods including feature extraction and classification were applied to the fNIRS features to classify patients with tinnitus and controls and differentiate tinnitus at different severity levels. Resting state measures of connectivity between temporal regions and frontal and occipital regions were significantly higher in patients with tinnitus compared to controls. In the tinnitus group, temporal-occipital connectivity showed a significant increase with subject ratings of loudness. Also in this group, both visual and auditory evoked responses were significantly reduced in the visual and auditory regions of interest respectively. Naïve Bayes classifiers were able to classify patients with tinnitus from controls with an accuracy of 78.3%. An accuracy of 87.32% was achieved using Neural Networks to differentiate patients with slight/ mild versus moderate/ severe tinnitus. Our findings show the feasibility of using fNIRS and machine learning to develop an objective measure of tinnitus. Such a measure would greatly benefit clinicians and patients by providing a tool to objectively assess new treatments and patients' treatment progress.

Dataset Information

Near-Real Time Measurement of Carbonaceous Aerosol Using Microplasma Spectroscopy: Application to Measurement of Carbon Nanomaterials.

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Near-Real Time Measurement of Carbonaceous Aerosol Using Microplasma Spectroscopy: Application to Measurement of Carbon Nanomaterials.

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