Surface ozone (O3) is a toxic air pollutant. In the United States and Europe, among other places, policies and technology have reduced emissions of O3 precursors the last couple decades. As a result, peak levels of O3, quantified by concentration metrics such as maximum daily average over 8 hours (MDA8), the accumulated O3 exposure over a threshold of 40 ppb (AOT40), and the weighted cumulative exposure index (W126) have fallen. Influential past studies have assumed that these improvements in AOT40 and W126 imply reductions in plant injury, even though it is widely recognized that O3 flux into leaves is a better predictor of plant damage than ambient concentration in air. Concentration metrics remain widely used because O3 concentration measurements are more common and because concentration and flux are correlated when the variability of stomatal conductance is limited. We use a new dataset of O3 flux into plants to quantify decadal trends in the cumulative uptake of O3 (CUO) into leaf stomata for the first time. We examine 32 sites in the United States and Europe over 2005-2014 and find that the AOT40 and W126 concentration metrics decreased at 25 and 28 sites, respectively, whereas CUO increased at a majority of sites (18). The divergent trends are due to stomatal control of flux, which is shaped by environmental variability. As a result, there has been no widespread, clear improvement in CUO over 2005-2014 at the sites we can assess. We use several statistical tests to show that temporal trends and variability in CUO are uncorrelated with AOT40, W126, and mean concentration (R2 ≤ 0.15). Decreases in concentration metrics, therefore, give a falsely optimistic picture of the direction and magnitude of O3 impacts on vegetation. Because of this lack of relation between flux and concentration, flux metrics should be preferred over concentration metrics in assessments of plant injury from O3. GEOS-Chem is a 3-D global atmospheric chemistry model that uses meteorological input to simulate atmospheric composition. We evaluate the model’s ability to estimate O3 deposition velocity (V_d) by running a simulation during the same period as the surface O3 trend analysis. By comparing monthly output of V_d from GEOS-Chem to our observations using the SynFlux dataset, we find that GEOS-Chem consistently underestimates V_d. The degree of the underestimation depends on the land class type as well as the time of year. We attempt to improve the model output by prescribing the land class type within the model to match the plant functional types at the FLUXNET sites. This did not lead to a significant improvement and in many cases, this led to a wider gap between the model and observations. We discuss possible reasons for the discrepancy between the model and observations. Improving V_d in the model would better estimate dry deposition of O3, which is important for simulating air quality, and its impacts to humans and plants. / A Thesis submitted to the Department of Earth, Ocean and Atmospheric Science in partial fulfillment of the requirements for the degree of Master of Science. / Spring Semester 2019. / April 3, 2019. / Includes bibliographical references. / Christopher D. Holmes, Professor Directing Thesis; Allison Wing, Committee Member; Mark Bourassa, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_709816 |
| Contributors | Ronan, Allison Christine (author), Holmes, Christopher D. (Professor Directing Thesis), Wing, Allison A. (Committee Member), Bourassa, Mark Allan (Committee Member), Florida State University (degree granting institution), College of Arts and Sciences (degree granting college), Department of Earth, Ocean and Atmospheric Science (degree granting departmentdgg) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text, master thesis |
| Format | 1 online resource (49 pages), computer, application/pdf |
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