Masters Theses


"Poor air quality is detrimental to health and is a leading environmental risk factor for early death globally. The massive scale of urbanization and population growth has led urban air quality to become a global concern as the release of air pollutants into the atmosphere continues to increase. Air quality has traditionally been monitored using reference-grade monitoring stations that are expensive and sparsely distributed. Low-cost sensors can complement existing regulatory networks to provide more spatial detail, capturing fine-scale variations. This study investigates spatiotemporal pollutant patterns, exposure disparities and environmental justice using data collected from a two-year (2019-2021) deployment of a multi-pollutant (PM2.5, CO, O3, NO2, NO, SO2, PM10) low-cost sensor network located in the Minneapolis-St Paul metropolitan area. The study focuses on 45 sensors in the network to identify fine-scale spatial variations within an urban region. This study uses several data analysis techniques to investigate the spatiotemporal variability of pollutant concentrations across Twin Cities, MN. Measurement of air quality at a fine-scale can provide insight to pollution hot spots and transient peaks and help improve efforts to protect the health of vulnerable populations. The analyses conducted demonstrate the utility of a dense air quality sensor network and the techniques used can easily be replicated for low-cost networks located elsewhere"--Abstract, p. iii


Wang, Yang

Committee Member(s)

Li, Jiayu
Madria, Sanjay Kumar


Civil, Architectural and Environmental Engineering

Degree Name

M.S. in Environmental Engineering


Missouri University of Science and Technology

Publication Date

Spring 2023


viii, 65 pages

Note about bibliography

Includes_bibliographical_references_(pages 62-64)


© 2023 P. M. Varuni Abhayaratne, All Rights Reserved

Document Type

Thesis - Open Access

File Type




Thesis Number

T 12237

Electronic OCLC #