Date of Award

Summer 2021

Document Type


Degree Name

Master of Science (MS)


Civil, Construction, and Environmental Engineering

First Advisor

McDonald, Walter

Second Advisor

Roy, Somesh

Third Advisor

McNamara, Patrick


Shortly after COVID-19 started spreading across the country, Wisconsin instituted their shutdown on March 23rd, 2020. With large swaths of the population forced to stay at home, this presented a unique case study to evaluate the effects of reduced traffic volumes on vehicle related emissions. To do so, this study measured air quality on a 40-mile route within Milwaukee County on Wednesdays and Saturdays from 4 to 6 PM from the beginning of April until the end of August. Mobile sensors – a Sniffer 4D and micro aethalometer – were attached to a car and collected particulate matter (1.0-10 μm), ammonia (NH3), hydrogen sulfide (H2S), oxidants (O3+NO2), and black and brown carbon. Traffic data were collected using the Streetlight database. Monotonic and abrupt changes in air quality were tested using the Mann-Kendall and Pettitt tests, respectively. Results indicated that 7 out of 8 streets had increasing monotonic trends from the beginning through the end of the lockdown for all particulate matter (1.0, 2.5, & 10) and NH3. In addition, Pettitt tests identified abrupt changes around June 13th, shortly after Milwaukee County reopened on June 11th. Traffic had a similar increasing monotonic trend for the 8 roads with abrupt changes around the middle of May when the statewide order was lifted. Linear regression was used to analyze the relationship between the air pollutants and traffic volume, and it found that traffic explained 1-48% of the variance in particulate matter, 1-46% of the variance in ammonia, and 6-70% of the variance for oxidants. These results indicate that traffic contributes to some, but not all, of the PM (1.0-10), NH3, and O3+NO2 measured in this case study. This study provides data from a unique experiment that demonstrates the direct impact that traffic has on air quality. These results highlight the value of information of traffic emissions at relevant spatial and temporal scales that cannot be captured with typical ground-based sensor systems. This information is also useful for city and traffic planners who are concerned with addressing urban air pollution from traffic sources.

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