Impacts of airports on the quality of life of surrounding communities

London Heathrow Airport has both beneficial and detrimental impacts on surrounding communities such as, for example, job creation and noise. The population living in the airport's proximity notices, cares about, and perceives its impacts which have often been studied only partially in literature. This thesis used the concept of Quality of Life to look at impacts multi-dimensionally. A framework was developed and used to systematically analyze Quality of Life impacts of Heathrow Airport using both spatial and regression analysis methods at different spatial resolutions with data collected from statistical authorities and social media. Low spatial resolution analysis found a beneficial impact of proximity to Heathrow Airport for economic conditions, accessibility & connectivity, health, and well-being metrics. Opportunities to verify this analysis with higher-resolution data were sought, but limited data was available. Housing transaction data was available at both low and middle spatial resolutions, and a beneficial impact of proximity to Heathrow Airport was observed at both levels. Counterfactual analysis found that the Heathrow Region performed better than many other regions for housing values and health metrics, and worse for certain well-being/happiness metrics. Additionally, high spatial resolution social media data was collected to analyze perceptions, sentiments, and opinions posted in proximity to Heathrow Airport. This analysis found that aviation and aviation-noise tweets skew negatively as compared to all tweets and that sentiment closer to the airport skews more positively than in the Greater London Region.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Institute for Data, Systems, and Society

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2020

Author dc:creator

• Maddens Toscano, Pedro Manuel.

Advisor dc:contributor.advisor

• R. John Hansman and Florian Allroggen.

• Institute for Data, Systems, and Society.
• Technology and Policy Program.

Statement dc:rights

• MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/127173

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/127173