An exercise in selecting low-cost air quality sensor placements within an urban environment
Name
1252064693-MIT.pdf
Size
2.69 MB
Format
Adobe PDF
Checksum (MD5)
18053eecb36962dd2851906083f60c29
Author(s)
Boghozian, Adrianna J.(Adrianna Judith)
Advisor(s)
Youssef Marzouk and Stefanie Jegelka.
Date Issued
2021
Publisher
Massachusetts Institute of Technology
Abstract
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.
Description
Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, Technology and Policy Program, February, 2021
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2021
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 69-75).
Subjects
Institute for Data, Systems, and Society.
Technology and Policy Program.
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Technology and Policy Program
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Engineering Systems Division
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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.
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