Project Instance

HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "ob_id": 46101,
    "uuid": "a5fd12288d9b4f4fb66f1b1ed56292ad",
    "title": "Secondary Organic Aerosol Prediction in Realistic Atmospheres (SOAPRA) (NE/V012665/1)",
    "abstract": "Aerosol particles are key drivers of reduced air quality and provide significant offsetting of warming by greenhouse gases. The organic fraction is frequently observed to dominate mass of fine particulate matter (PM) and secondary organic aerosol (SOA) is the major contributor. With air pollution responsible for 11 % of global deaths annually and air temperature rise within 0.5 degree C of the target pursued by Paris Agreement signatories, accurate forecasts of organic aerosol particle mass loadings are required to inform policy decisions. Experimental results presented in  recent landmark study to investigate the mechanisms determining SOA formation in atmospheric mixtures will be interrogated. \r\n\r\nNew mechanistic chemical understanding developed from this work will be included into a coupled model of gaseous photochemistry and aerosol formation. Detailed comparison of the model with measured gaseous and aerosol composition will enable unprecedented confidence in our understanding of the interactions that can occur in the real atmosphere. The model will demonstrate the magnitude of interactions to be expected in airmasses containing natural and manmade pollutants that promises to enable reasonable mechanistic interpretation of SOA formation in the real atmosphere for the first time.\r\n\r\nThis project will develop a mechanistic quantitative representation of oxidative chemistry leading to SOA formation in realistic atmospheric mixtures including interactions between biogenic and anthropogenic precursors. The project will demonstrate its predictive capability by comparison with existing and emerging experimental data and use it to evaluate the potential for SOA formation and uncertainty ranges across VOC mixtures at VOC:NOx regimes applicable to the real atmosphere. \r\n\r\nThe recent study (McFiggans et al., 2019) was transformative in that it showed that the formation of particulate mass in mixtures of gaseous precursors cannot be assumed to be the sum of that formed independently from the components of the mixture. The study demonstrated that this resulted from two effects: i) oxidant scavenging; competition of the precursor molecules for the available oxidant and ii) product scavenging; vapour phase interactions between oxidation products that would have otherwise reacted to form condensed particulate mass. These two effects lead to the requirement for a realistic treatment of SOA formation in mixtures in order to predict atmospheric PM loading and its effect on human health and climate. \r\n\r\nData from a large number of published and (as yet) unpublished laboratory and chamber experiments, investigating SOA formation from the oxidation of individual VOC and their mixtures. In each, the project quantifies the formation of highly-oxygenated organic molecules (HOM) found to be major contributors to the condensed SOA mass. The VOC include key species from the major biogenic and anthropogenic classes of SOA precursors. The project will extend the benchmark mechanism for atmospheric VOC oxidation to incorporate the most recent mechanistic understanding of HOM into our chamber model of coupled photochemistry and aerosol microphysics. The project will optimise simulations using this model by comparison with the experimental data and conduct further simulations to establish the critical dependencies of SOA formation in the atmosphere. Large scale air quality and climate models will need to capture these relationships to enable confidence to be placed in their predictions. The project will include a simplified mechanism based on the same framework as our more detailed scheme into the EMEP regional pollution model to demonstrate the impact of interactions in atmospheric mixtures of VOC on regional PM.",
    "keywords": "",
    "status": "ongoing",
    "publicationState": "",
    "identifier_set": [],
    "observationCollection": [],
    "parentProject": null,
    "subProject": [],
    "responsiblepartyinfo_set": [
        "https://catalogue.ceda.ac.uk/api/v2/rpis/220219/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/220220/?format=api",
        "https://catalogue.ceda.ac.uk/api/v2/rpis/220221/?format=api"
    ]
}