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Integrated Research Observation System for Clean Air (OSCA)

Integrated Research Observation System for Clean Air (OSCA)
清洁空气综合研究观测系统(OSCA)
批准号:
NE/T001909/2
负责人:
David Green
金额:
$49.05万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --

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中文摘要
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英文摘要
"Poor air quality is the largest environmental risk to Public Health in the UK" (DEFRA, 2017) and is consequently a focus of a range of regional and national policy interventions. However, since our transport systems, the way we heat our homes, our energy supply, our use of solvents and our agricultural systems are all changing, we know that profound changes in emissions and trends in air pollutants are likely in the coming years and indeed are already taking place. We need to understand our changing atmospheric composition, to ensure air quality policy has maximum benefit for the protection of human and environmental health.The Clean Air: Analysis and Solutions Programme identifies the need for new capability to predict future changes in the sources, emissions and atmospheric processes responsible for air pollution. The OSCA project addresses this need through a multidisciplinary research activity, combining state-of-the-science atmospheric observations, laboratory studies, new data processing tools and integrated scientific synthesis to deliver new understanding of urban air pollution. OSCA will:-Deliver improved quantification of emissions, combining lab measurements of brake & tyre wear sources, and measurements of the total fluxes of particulate matter (PM) and nitrogen dioxide (NO2) from the BT Tower in London. Nonexhaust emissions comprise up to 70% of traffic-derived PM10, are poorly quantified, and whose relative importance will increase with UK fleet decarbonisation. Real-world emission measurements underpin air quality predictions and avoid dependence upon manufacturer data.-Provide a definitive, state-of-the-science assessment of UK urban air quality through exploitation of the new RCUK-funded urban air quality Supersites in London, Birmingham and Manchester to deliver comprehensive, continuous and long-term measurements of atmospheric composition. These data will characterise the changing UK pollution climate, identify subtle emission trends during implementation of regional air quality policies, and provide a key resource for evaluation of ongoing trends.-Develop new mathematical analyses to identify emergent trends / responses to policies and apply these alongside established methods to address key science uncertainties - e.g.: to assess the trends and changing sources of NO2; to provide definitive quantification of the contributions of non-exhaust traffic, woodsmoke and cooking activities to PM; to identify trends in and contributions to ammonia emissions; to identify changes VOC emissions - precursors to ozone formation.-Provide data and infrastructure to underpin the wider Clean Air Programme, including development and deployment of novel sensor networks (QUANT); data to validate models and health effect calculations (InSPIRE and DREaM); insight into air quality response to policy initiatives (ANTICIPATE); sensor testing and pollutant source identification (APEx).-Enable community mobilisation through intensive field campaigns, targeted at understanding the changing gas-phase reactivity climate of the UK atmosphere (which governs production of secondary PM and ozone), and the sources and chemical composition of atmospheric aerosols.OSCA findings will support policymakers through a range of established relationships the PIs already maintain. These include engagements within the supersite host cities, and links to relevant national bodies, including Defra, DfT, DoH, PHE and the EA. The OSCA deliverables provide important new data and novel scientific approaches central to the assessment of future changes in the sources, emissions and atmospheric processes governing air pollution in the UK - the core of WP1 of the Clean Air programme. OSCA is fully embedded into the wider programme, informing policy decisions, monitoring the impacts of decisions, and feeding public health research and outcomes.
期刊论文(7)
专著(0)
科研奖励(0)
会议论文
The potential of high temporal resolution automatic measurements of PM2.5 composition as an alternative to the filter-based manual method used in routine monitoring
高时间分辨率自动测量 PM2.5 成分作为常规监测中基于过滤器的手动方法的替代方法的潜力
DOI: 10.1016/j.atmosenv.2023.120148
发表时间: 2023
期刊: Atmospheric Environment
影响因子: 5
作者: [Twigg M]
通讯作者: Twigg M
DOI: 10.3390/atmos12020190
发表时间: 2021-02-01
期刊: ATMOSPHERE
影响因子: 2.9
作者: [Hicks, William, Beevers, Sean, Green, David C.]
通讯作者: Green, David C.
DOI: 10.1039/d1em00200g
发表时间: 2021-11
期刊: Environmental science. Processes & impacts
影响因子: --
作者: [K. Ciupek;P. Quincey;D. C. Green;D. Butterfield;G. Fuller]
通讯作者: K. Ciupek;P. Quincey;D. C. Green;D. Butterfield;G. Fuller
Quantifying the change of brake wear particulate matter emissions through powertrain electrification in passenger vehicles
通过乘用车动力总成电气化量化制动器磨损颗粒物排放的变化
DOI: 10.1016/j.envpol.2023.122400
发表时间: 2023
期刊: Environmental Pollution
影响因子: 8.9
作者: [Hicks W]
通讯作者: Hicks W
6
    Linking Particulate Matter Oxidative Potential to Atmospheric Conditions and Particle Composition
    • 批准号:
      EP/X030237/1
    • 项目类别:
      Fellowship
    • 资助金额:
      $24.26万
    • 财政年份:
      2023
    • 负责人:
      David Green
    • 依托单位:
    REU Site: Advanced Materials Synthesis at the University of Virginia
    • 批准号:
      2050867
    • 项目类别:
      Standard Grant
    • 资助金额:
      $41.04万
    • 财政年份:
      2021
    • 负责人:
      David Green
    • 依托单位:
    Integrated Research Observation System for Clean Air (OSCA)
    • 批准号:
      NE/T001909/1
    • 项目类别:
      Research Grant
    • 资助金额:
      $62.6万
    • 财政年份:
      2019
    • 负责人:
      David Green
    • 依托单位:
    Computational and Experimental Investigations of Phase-Separated Monolayers on Ultrasmall Noble Metal Nanoparticles
    • 批准号:
      1904884
    • 项目类别:
      Standard Grant
    • 资助金额:
      $49.0万
    • 财政年份:
      2019
    • 负责人:
      David Green
    • 依托单位:
    国内基金
    海外基金
    Research on Quantum Field Theory without a Lagrangian Description
    • 批准号:
      24ZR1403900
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      SATOSHI NAWATA
    • 依托单位:
    Cell Research
    Cell Research
    Cell Research (细胞研究)