Using high complexity analysis to probe the evolution of organic aerosol during pollution events in Beijing
Abstract
There is increasing evidence that exposure to air pollution results in significant impacts on human health. In Beijing, home to over 20 million inhabitants, particulate matter levels are very high by international standards, with official estimates of an annual mean PM2.5 concentration in 2014 of 86 μg m-3, nearly 9 times higher than the WHO guideline. Changes in particle composition during pollution events will provide key information on sources and can be used to inform strategies for pollution mitigation and health benefits. The organic fraction of PM is an extremely complex mixture reflecting the diversity of sources to the atmosphere. In this study we attempt to harness the chemical complexity of OA by developing an extensive database of over 700 mass spectra, built using literature data and sources specific tracers (e.g. diesel emission characterisation experiments and SOA generated in chamber simulations). Using a high throughput analysis method (15 min), involving UHPLC coupled to Orbitrap mass spectrometry, chromatograms are integrated, compared to the library and a list of identified compounds produced. Purpose built software based on R is used to automatically produce time series, alongside common aerosol metrics and data visualisation techniques, dramatically reducing analysis times. Offline measurements of organic aerosol composition were made as part of the Sources and Emissions of Air Pollutants in Beijing project, a collaborative program between leading UK and Chinese research groups. Rather than studying only a small number of 24 hr PM samples, we collected 250 filters samples at a range of different time resolutions, from 30 minutes to 12 hours, depending on the time of day and PM loadings. In total 643 species were identified based on their elemental formula and retention time, with species ranging from C2-C22 and between 1-13 oxygens. A large fraction of the OA species observed were organosulfates and/or nitrates. Here we will present preliminary results on the factors that impact the evolution of organic aerosol in Beijing, highlighting the role of biomass burning in winter and photochemistry in summer. Modern data mining and statistical analysis methods will be used to identify patterns in the OA composition along with co-variances with simultaneous gas and particle measurements.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.A12G..06H
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0317 Chemical kinetic and photochemical properties;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0322 Constituent sources and sinks;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0365 Troposphere: composition and chemistry;
- ATMOSPHERIC COMPOSITION AND STRUCTURE