Understanding the quality of the air we breathe is critical in quantifying the impact that atmospheric chemistry has on health. Poor air quality increases the risk of heart and lung diseases as well as having a detrimental effect on climate, ecology and the built environment. The burning of fossil fuels and plant matter (biomass burning) creates large quantities of gases and particulate matter that impact air quality and the air we breathe. Biomass burning is estimated to contribute 400 Tg of non-methane organic compounds, 40 Tg of methane and 7.1 Tg of nitrogen oxides to the atmosphere each year. This thesis aims to better understand the role of biomass burning on air quality and tropospheric chemistry. The in depth analysis presented here addresses of the impact of boreal biomass burning in North America on air quality, in particular, carbon monoxide (CO) and ozone (O3). By using a number of different modelling techniques along with data collected from a field campaign and satellites the transport and chemistry of biomass burning emissions were analysed and quantified. The first research chapter of the thesis used the GEOS-Chem atmospheric chemistry transport model to interpret aircraft measurements of CO in biomass burning outflow taken during the 2011 BORTAS-B campaign over Canada. The model has some skill reproducing the observed variability, but has a positive bias for observations < 100 ppb and a negative bias for observations > 300 ppb. It was found that observed CO variations are largely due to fires over Ontario, with smaller and less variable contributions from fossil fuel combustion from eastern Asia and NE North America. To help interpret observed variations of CO an effective physical age of emissions (¯A) metric was developed. It was found that during BORTAS-B the age of emissions intercepted over Halifax, Nova Scotia is typically 4–11 days, and on occasion as young as two days. The analysis shows that ¯A is typically 1–5 days older than the associated photochemical ages inferred from co-located measurements of different hydrocarbons. It is argued that a robust observed relationship between CO and black carbon aerosol during BORTAS-B (r² > 0.7), form the basis of indirect evidence that aerosols co-emitted with gases during pyrolysis markedly slowed down the plume photochemistry during BORTAS-B with respect to photochemistry at the same latitude and altitude in clear skies. The second research chapter focuses on O3 production downwind from boreal biomass burning. Using the GEOS-Chem model, the O3 chemistry within a biomass burning plume from a fire on 17 July 2011 in mid-Canada was examined. The model shows a significant positive bias (~20 ppb) in reproducingO3 mixing ratios over North America for July 2011 when compared to observations. Reducing NO emissions from lightning and fossil fuel by 50% and 54% respectively reduced this bias to ~10 ppb. The cause of the remaining bias is uncertain. Using a novel technique with the model, the centre of the biomass burning plume was tracked and O3 concentrations and chemistry was extracted from the centre of the plume. The biomass burning enhanced O3 concentrations throughout the plume by between 1 – 20 ppb when compared with the same plume path with no biomass burning. The plume was characterised as being NOx-rich for the initial four days of transport. The sensitivity of the O3 chemistry to different emissions was calculated and it was found that the O3 is initially highly sensitive to NO emissions from biomass burning and then to NO emissions from fossil fuels as it travels across an urban area surrounding Quebec City. The O3 net production was found to initially decrease with an increase in NO but increase further downwind. The final research chapter of the thesis uses long-term satellite observations to evaluate natural variability in CO concentrations over the North Atlantic. 15 years of MOPITT CO column observations were used along with modelled CO from the GEOS-Chem model. The model was evaluated against the MOPITT overpass and shows a negative bias of between -8% and -24% over the northern mid-latitudes with the largest bias seen in spring. The model has a large positive bias (8% – 40%) over the Amazon,West Africa and Indonesia through all seasons. Using Empirical Orthogonal Function (EOF) analysis on the MOPITT and GEOS-Chem CO columns shows the largest mode of variability seen in the North Atlantic to be the oxidation of methane for winter and spring, biomass burning during summer and fossil fuel combustion from East Asia during autumn.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:739093 |
| Date | January 2017 |
| Creators | Finch, Douglas Peter |
| Contributors | Palmer, Paul ; Nichol, Caroline |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/29536 |
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