An exercise in selecting low-cost air quality sensor placements within an urban environment

Air pollution poses the most important environmental health risk to citizens of major cities all over the world. The high cost of current monitoring programs means that enforcement of current regulation, such as the United States Environmental Protection Agency's ambient air quality standards, can be lacking at the individual level. Because of their low cost, sensor networks offer the benefit of providing detailed, high resolution pollutant exposure maps which can inform a number of community and government initiatives aimed at tackling air pollution. The question then arises, what is the optimal configuration of low-cost sensors to measure air pollution within an urban environment? Due to the large number of potential locations in which to measure data, there are difficulties in defining where to place a limited number of sensors. This thesis outlines a proven decision method from spatial statistics: optimal experimental design, and applies the method to a test case in the city of London.

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

2021

Author dc:creator

• Boghozian, Adrianna J.(Adrianna Judith)

Advisor dc:contributor.advisor

• Youssef Marzouk and Stefanie Jegelka.

• Institute for Data, Systems, and Society.
• Technology and Policy Program.
• Electrical Engineering and Computer Science.

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/1721.1/130793

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/130793