Statistical methods for constructing an air pollution indicator for Glasgow

Allison, Katie Jane (2014) Statistical methods for constructing an air pollution indicator for Glasgow. MSc(R) thesis, University of Glasgow.

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Printed Thesis Information: https://eleanor.lib.gla.ac.uk/record=b3082944

Abstract

Air pollution can have both a short term and long term detrimental effect on health. This thesis aims to provide an air quality indicator to be used as a simple and informative tool to track air pollution levels which can be used by both the public and governing bodies.

Chapter 1 discusses the background and motivation of the study. The chapter then moves on to outlining the aims and overall structure of the thesis and provides a description of the data used.

Chapter 2 explores the daily mean monitoring site PM10 data for Glasgow across the years 2010 to 2012. This chapter explores trends and seasonality in the PM10 data using exploratory measures and time series analysis.

Chapter 3 explores the gridded modelled annual mean PM10 map data across the years 2010 to 2012. The spatial aspects of PM10 are first explored using numerical and graphical summaries. A more robust approach is used to then produce a geostatistical model to explain the trend of PM10 across Glasgow.

Chapter 4 then focuses on producing naive indicators building upon the modelling and exploratory analysis conducted in Chapters 2 and 3. This forms the basis of a spatio-temporal model. This results in a final air quality indicator estimate with uncertainty which accounts for spatial and temporal dependence for Glasgow.

Chapter 5 ends the thesis with a discussion of the final indicator and the conclusions with consideration given to improvements which could be made and additional analysis for the future.

Item Type: Thesis (MSc(R))
Qualification Level: Masters
Keywords: Pollution Indicator Spatial Temporal Spatio-temporal Glasgow
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics
Colleges/Schools: College of Science and Engineering > School of Mathematics and Statistics > Statistics
Supervisor's Name: Scott, Professor Marian and Craigmile, Peter
Date of Award: 2014
Depositing User: Miss Katie Jane Allison
Unique ID: glathesis:2014-5558
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 07 Oct 2014 10:06
Last Modified: 08 Oct 2014 13:43
URI: https://theses.gla.ac.uk/id/eprint/5558

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