Characterization and prediction of dissolved heavy metals associated with storm water runoff from elevated roadways

Storm water runoff from highways transports a significant load of contaminants, especially heavy metals and particulate matter, to receiving waters. Heavy metals, either in dissolved or particulate-bound phases, are unique in the fact that unlike organic compounds, they are not degraded in the environment.; The study area for our proposed research was selected at the intersection of the Interstate-10 and Interstate-610, Orleans Parish, New Orleans, Louisiana. Subsequently, a research test site was developed and highway storm water runoff was collected. Volumetric flow rates were taken with every collected sample by measuring the amount of collected water and the collection time. Storm water runoff from the examined elevated roadway section was sampled for 10 discrete events throughout the course of the study, from which hydrologic and water quality data were collected.; One of the primary research objectives in this study was the investigation of the “First Flush” effect that occurs during storm water runoff events. Based on the results of this investigation, the “First Flush” effect in storm water runoff discharges from highways is a runoff volume dependent issue. The first portion of highway storm water runoff volume that is discharged contains the highest concentrations and the highest mass loadings of dissolved heavy metals and decrease with ongoing discharge of storm water runoff volume. As a consequence, it is clearly observable that storm water runoff discharges from roadways exhibit a concentration-based and mass-loading-based “First Flush”.; The development and use of Figure 41 on page 116 made it possible to determine the percentage of dissolved heavy metal mass loading that is contained in a specific portion of highway storm water runoff that is discharged and vice versa.; Another very important achievement in this research was the construction of a prediction model for dissolved heavy metal concentrations based on known TSS concentrations. This model enables the user to predict dissolved heavy metal concentrations with known TSS within a prediction interval of 90% confidence.; However, the validity of the study-developed diagrams and models is geographically dependent and limited to the specific study area.