Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.782586
Title: Atmospheric inverse modelling of biospheric carbon dioxide fluxes in the UK and Europe
Author: White, Emily
ISNI:       0000 0004 7968 191X
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2019
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Abstract:
Human activity is causing rising atmospheric CO2 concentrations leading to an increase in global mean temperature and a changing climate. Monitoring biospheric CO2 fluxes at global, continental and regional scales is important to track how the biosphere is responding to climate change and to evaulate the success of mitigation policies that involve enhancing sinks of CO2, such as reforestation. The use of atmospheric measurements of CO2 concentrations in a "top-down" inverse modelling set-up is a valuable tool to assess CO2 fluxes. This thesis works towards the first top-down estimates of UK biospheric CO2 fluxes and includes the contribution to a regional inverse modelling comparison project that focusses on European biospheric CO2 fluxes. A hierarchical Bayesian inverse modelling framework is first adapted to some of the unique characteristics of CO2 fluxes, such as the strong diurnal and seasonal cycle, and the mixture of anthropogenic, biospheric and oceanic sources. This framework is then applied to the UK, using atmospheric CO2 concentrations from a relatively dense network of tall-tower and surface sites in and around the UK. The UK biosphere is found to be in balance with a net zero CO2 flux to the atmosphere, according to two separate inversions that use two different models of biospheric flux as prior information. Extending the scope of the study to Europe, with a different measurement network and a more mature model of biospheric fluxes, reveals that European biospheric fluxes are also in balance and estimates found here agree with previous regional inverse modelling studies. Of particular interest in this thesis is the role of the prior biospheric flux model. The inversion process has highlighted some areas where models need to improve, for example in estimating fluxes related to human disturbance.
Supervisor: Rigby, Matthew Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.782586  DOI: Not available
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