Multispectral Sensor for Chemical Composition Analysis of Ultrafine Aerosols in Air Quality Assessment
用于空气质量评估中超细气溶胶化学成分分析的多光谱传感器
基本信息
- 批准号:10546675
- 负责人:
- 金额:$ 25.96万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-13 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAerosolsAffectAirAir PollutionAutomationAwarenessBiochemical ReactionCOVID-19CarbonCellsChemicalsChemistryChildhoodClinicalClinical ResearchCollaborationsCollectionCommunicable DiseasesComplexCost AnalysisCost SavingsDataDepositionDevelopmentDiesel ExhaustElectrostaticsEngineeringEnvironmentEnvironmental PollutantsEnvironmental and Occupational ExposureEvaluationEvidence based interventionExposure toHealthIn SituIndividualInhalationInstitutional Review BoardsInterventionLaboratoriesLibrariesLinkMachine LearningMeasurementMedicalMethodsMiniaturizationMonitorOpticsOutcomeParticipantParticle SizeParticulate MatterPerformancePhasePreparationResearchResearch DesignResolutionRespiratory SystemSamplingSignal TransductionSolidSolubilitySolventsSourceSpecificitySpectrum AnalysisTechniquesTechnologyTestingTimeTissuesTobacco smokeUltrafineabsorptionair pollution controlbasecommercializationcostcost effectivedesigndetection platformenvironmental agentepidemiology studyimplementation facilitationimprovedinsightinstrumentationmachine learning algorithmminiaturizemonitoring devicemortalitynanomaterialsnovelparticleparticle counterpersonal exposure monitorpollutantpublic health researchpulmonary functionrelating to nervous systemsensorsolvent extractiontoolultrafine particleuptakewood smoke
项目摘要
Project Summary
We propose developing and validating a novel platform technology that combines the collection and
chemical analysis of ultrafine particles using an in-situ multispectral technique. The sample, collected directly
onto the analysis substrate, is analyzed via excitation-emission matrix (EEM) spectroscopy. This approach will
be validated against laboratory combustion-generated aerosols, such as diesel exhaust, wood smoke, tobacco
smoke, and against a mixture of environmental pollutants. Within the respiratory tract, particle size determines
the region of deposition and tissue uptake; the chemistry of the particle also affects solubility and determines the
potential for biochemical reaction with tissues and cells. There is a growing awareness that exposure scenarios
are very complex, consisting of time-varying concentrations and chemical composition over a broad range of
particle sizes. Long-term exposure to air pollution has also been linked to increased mortality rates for infectious
diseases, including COVID-19. The proposed research addresses the need for improved personal exposure
assessment and characterization of ultrafine particles in the environment. Low-cost, miniaturized exposure
monitoring devices can shed insight into the relationships between exposure to pollutants and health impact.
Source apportioned measurements of PM concentration with high temporal and spatial resolution can facilitate
the implementation of optimal air pollution mitigation strategies. The anticipated outcome of this project is the
development of a miniaturized spectroscopic sensor that provides an analysis of the chemical composition of
combustion-generated ultrafine particles, which both reflects the particle sources and determines their toxic
potential. The machine-learning algorithms will enable the deconvolution of the complex spectra and
identification of the PM source from the EEM analysis. The broader applications of the technology are
environmental and regulatory monitoring, personal exposure assessment for the consumer market, and
epidemiological studies.
项目总结
项目成果
期刊论文数量(0)
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{{ truncateString('ALEXANDER V MAMISHEV', 18)}}的其他基金
Multispectral Sensor for Chemical Composition Analysis of Ultrafine Aerosols in Air Quality Assessment
用于空气质量评估中超细气溶胶化学成分分析的多光谱传感器
- 批准号:
10887673 - 财政年份:2022
- 资助金额:
$ 25.96万 - 项目类别:
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