{"id":1944,"date":"2026-03-04T16:00:44","date_gmt":"2026-03-04T16:00:44","guid":{"rendered":"https:\/\/nasweeper.com\/?p=1944"},"modified":"2026-04-10T18:54:08","modified_gmt":"2026-04-10T18:54:08","slug":"a-sheerin-ph-d-creates-system-to-measure-local-water-quality-effects-from-targeted-sweeping","status":"publish","type":"post","link":"https:\/\/nasweeper.com\/?p=1944","title":{"rendered":"A. Sheerin, Ph.D. Creates System to Measure Local Water Quality Effects from Targeted Sweeping"},"content":{"rendered":"

Today, the street sweeping industry features fully-digital and all-electric sweeper trucks, a variety of off-the-shelf integrated business platforms with full-scope ERPs, including sophisticated CRMs, networked field devices, advanced telecom systems, and more, all adapted to better manage the delivery and performance of street sweeping services. So, the profession is ready for this next-level advancement: Enter Andrew Sheerin, Ph.D. in Environmental Engineering, with emphasis in data analytics software design. Dr. Sheerin’s dissertation focused on building prescriptive systems for custom street sweeping frequency management to protect local waterbodies through stormwater pollution reduction.<\/span><\/span><\/span><\/p>\n

Sheerin’s current study entails the development of a readily replicable platform that integrates sweeping service tracking data, service route characteristics, and weather prediction data, into a system for flagging key areas for sweeping to complement weather conditions for maximal effectiveness in improving water quality from sweeping based on changing conditions. <\/span><\/span><\/span><\/p>\n

Environmental Engineering – Analytical Systems Design<\/strong><\/span><\/span><\/span><\/h2>\n

Sheerin started his academic journey in Systems Engineering at George Washington University before beginning his graduate studies in Civil and Environmental Engineering at the University of Rhode Island (URI). The graduate program, funded by the <\/span><\/span><\/span>Transportation Infrastructure Durability Center, is sponsored by the University of Rhode Island, through a USDOT grant. <\/span><\/span><\/span>The Department was looking to bring in a curriculum around enhanced non-structural Best Management Practices (BMPs). It was supposed to be a 2-year project, and the plan was for Andrew to complete a Master’s degree in that discipline. However, as he explains, things evolved and grew, and with a little convincing from his advisor, Dr. Vinka Oyanedel-Craver, he decided to go for the full Ph.D.: <\/span><\/span><\/span><\/p>\n

“My dissertation started with the evaluation of non-structural BMPs, the current State approach, and determining how that could be enhanced. Looking through all the available data on street sweeping across the country, there have been many great studies. We chose Warwick, Rhode Island as our research base, to focus on the effects of sweeping in urban areas. <\/span><\/span><\/span><\/p>\n

We picked 8 sites, and did street debris collection and water collection for examination of physical and chemical characteristics. I took more classes and furthered aspects of the study through those. I was fairly proficient with Python. Using Geographic Information Systems (GIS), I recognized the layering potential for geographic data sets and started to figure out methods for correlating GIS data with factors like accumulation rates, pollutant concentrations, and a range of others. <\/span><\/span><\/span><\/p>\n

This is not new. People have linked land usage to heavy metals and nutrients in water before, but I wanted to incorporate the specifics of it into the analytical system to generate a clear picture of the compound impacts and the mitigation effects. <\/span><\/span><\/span><\/p>\n

I created a map from existing modification solutions, to defend enhanced street sweeping as a primary cause of reduced pollutants in water. There is a widely used model from the EPA. But it is limited in its ability to reflect sweeping routines, i.e., to program dynamic sweeping schedules based on irregular rainfall events. <\/span><\/span><\/span><\/p>\n

Innovative Geographic Information Systems<\/strong><\/span><\/span><\/span><\/h2>\n

The message is that urban sweeping shouldn’t be managed with a static approach, such as on a weekly schedule that doesn’t consider when it last rained and doesn’t maximize efforts to remove pollution that will otherwise go into waterways via storm drains. I endeavored to create a model to support my research, which took the form of the<\/span><\/span><\/span> <\/span><\/span><\/span>Storm Water Pollution Tracker<\/u><\/span><\/span><\/span><\/a> (SWPT) software application. <\/span><\/span><\/span><\/p>\n

The SWPT app functions with respect to weather forecasting data and a granular assessment of other environmental factors, such as adopted urban activity data sets. For example, land usage, tree cover, traffic volume, watershed characteristics, road slope, road roughness, curbing, and so on. <\/span><\/span><\/span><\/p>\n

Initially, I developed the model based on local field data and did not plan to scale it out to other regions. It’s a big data model, encompassing broad categories of inputs, prioritizing, and optimizing these:<\/span><\/span><\/span><\/p>\n