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The focus of this research was to assess the performance of bioswales in mitigating and treating stormwater runoff from highways and to identify critical parameters that influence the load of pollutants from the drainage area. These bioswales are located in Philadelphia and are part of a project initiated by the Pennsylvania Department of Transportation to upgrade a major roadway (Interstate 95) running through the area. The work included sampling and laboratory analysis of runoff water from 9 storm events to characterize concentrations of contaminants coming from the highway and going in to the bioswales. For one storm event, sampling of vadose-zone and ponded water was included to assess how contaminants move or are retained within the bioswale. The various contaminants include solids, nutrients and metals, which have all been shown to be parameters of concern when dealing with stormwater runoff from highways. In addition, a simulated runoff test was performed to assess the potential risk of a very large storm in mobilizing contaminants within the bioswale. Stepwise linear regression in IBM SPSS was used to analyze the runoff data collected. Characteristics of the rainfall (antecedent dry period, total rainfall, rainfall intensity) were selected as potential explanatory variables to predict contaminant concentration or load. Results of the runoff characterization showed contaminant concentrations that fell within range of literature values from a similar drainage area. Estimated annual loads of contaminants were also in range of what has been observed for highway runoff. Vadose-zone and ponded water sampling showed removal of ammonia, total phosphorus and chemical oxygen demand and build-up of nitrate, total nitrogen and TKN. The build-up was likely due to lack of ion interaction with soil particles, which caused the contaminants to remain in the water. Simulated runoff testing showed no potential for contaminant mobilization within the bioswale but did indicate potential areas of contaminant buildup via observation of a dye tracer. Stepwise linear regressions performed in SPSS showed total rainfall as the most significant predictor of suspended solid, nitrate and total phosphorus load in the bioswales. Results also indicate that there are significant differences between the loads observed for the two bioswales monitored. / Civil Engineering