Date of Award
2025
Degree Type
Dissertation
Degree Name
Doctor of Philosophy in Civil and Environmental Engineering
Specialization
Environmental Engineering
Department
Civil and Environmental Engineering
First Advisor
Vinka Oyanedel-Craver
Abstract
Stormwater pollution remains a significant environmental concern in urban areas, where impervious surfaces facilitate the accumulation and transport of pollutants into nearby water bodies. Street sweeping, a widely implemented nonstructural best management practice (BMP), offers the potential to mitigate these pollutants, however, its effectiveness is influenced by numerous spatial and temporal factors that are often overlooked in conventional sweeping programs. The objective of this dissertation was to develop a data-driven methodology to enhance street sweeping operations in Rhode Island, with the goal of supporting the Rhode Island Department of Transportation (RIDOT) in reducing stormwater pollution and restoring statewide water quality.
The research presented in this dissertation consisted of four interrelated studies. The first study provided a comprehensive review of street sweeping as a nonstructural BMP, identifying key variables that influence pollutant accumulation and sweeper efficiency, such as land use, canopy coverage, traffic volume, particle size, road characteristics, and sweeper technology. The review concluded that a data-informed approach incorporating these variables is essential for effective sweeping.
The second study involved field sampling in Warwick, RI, to characterize the physical and chemical properties of accumulated street solids and stormwater runoff. Results revealed spatial and seasonal trends in pollutant accumulation, with higher loads observed in commercial areas during spring and in forested areas during fall. Heavy metals (Zn, Cu, Pb) were concentrated in both fine (< 74 µm) and coarse (>840 µm) particle fractions, while nutrients were highest in spring (for TN) and the fall (for TP).
In the third study, a decision-support tool called the Stormwater Pollution Tracker (SWPT) was developed to integrate pollutant transport simulations, geospatial prioritization, and route optimization. Simulation results demonstrated that sweeping prior to forecasted rain events (>0.5 inches) could reduce stormwater pollution by 66%, significantly outperforming fixed-interval or unscheduled sweeping strategies. These findings suggest that weather-informed sweeping schedules are more effective than frequent, routine sweeping.
The fourth study introduced a life cycle assessment (LCA) framework to quantify the environmental trade-offs of street sweeping activities. While sweeping reduced stormwater pollution, it also contributed to vehicle emissions and fuel consumption. Results emphasized the need for standardized metrics to evaluate the net environmental benefits of sweeping strategies.
Collectively, this research supports the development of an enhanced, adaptive street sweeping program for RIDOT. By leveraging environmental data, geospatial analysis, and predictive modeling, this dissertation presents a scalable and cost-effective framework to improve stormwater management in urban areas.
Recommended Citation
Sheerin, Andrew, "DATA-DRIVEN APPROACH TO REDUCING STORMWATER POLLUTION THROUGH ENHANCED STREET SWEEPING" (2025). Open Access Dissertations. Paper 4475.
https://digitalcommons.uri.edu/oa_diss/4475