Stormwater runoff has been known to cause increases in bacterial loadings in urban streams. However, little is known about its impacts on antibiotic resistance genes (ARGs) in urban watersheds. This study was performed to characterize the ARG composition of various environmental compartments of an urban watershed and to quantify their contributions of microbes and ARGs to an urban stream under wet weather conditions. Shotgun metagenomic results showed that the ARG abundance in wet weather flow was significantly higher than in base flow. Multidrug resistance genes were the most common ARG type across environmental samples. Vancomycin resistance genes were abundant in embankment soil and street sweeping samples. Analyses using SourceTracker estimated storm drain outfall water to be the biggest contributor of microbes (54-57%) and ARGs (82-88%) in the urban stream during wet weather flows. Furthermore, results on street sweepings showed that wash-off from streets was the biggest known contributor of microbes (41-45%) and ARGs (92-96%) in storm drain outfall water. Pantoea and Pseudomonas were associated with the highest numbers of ARGs and were most abundant in stormwater-related samples. Results from this study can advance our knowledge about ARGs in urban streams, an important medium linking environmental ARGs to the general public.

Investigating sources of microbial contamination in urban streams, especially when there are no contributions from combined sewer overflows or sewage effluent discharges, can be challenging. The objectives of this study were to identify the sources of microbes in an urban stream and quantify their relative contributions to the microbial community in the stream under dry and wet weather conditions. A microbial source tracking method relying on the 16S rRNA gene was used to investigate the microbial communities in water samples of an urban stream (i.e., from 11 dry and 6 wet weather events), as well as in streambed sediment, soils, street sweepings, sanitary sewage, an upstream lake, and feces of animals and birds collected between 2013 and 2015. The results showed that the levels in the stream were significantly higher in wet weather flow than in dry weather flow. The upstream lake contributed approximately 93% of the microbes in dry weather flows. Water discharged from storm drain outfalls was the biggest source of microbes in wet weather flows, with a median contribution of approximately 90% in the rising limb and peak flow and about 75% in the declining limb of storms. Furthermore, about 70 to 75% of the microbes in the storm drain outfall water came from materials washed off from the street surfaces in the watershed. Fecal samples did not appear to contribute substantially to the microbes in environmental samples. The results highlight the significance of street surfaces in contributing microbial loads to urban streams under wet weather conditions. Identifying the sources of microbial contamination is important for developing best management practices to protect the water quality of urban streams for recreational uses. This study collected a large number of water samples from an urban stream under both dry and wet weather conditions and provided quantitative information on the relative contributions of various environmental compartments to the overall microbial contamination in the stream under the two weather conditions. The watershed in this study represents urban watersheds where no dominant fecal sources are consistently present. The findings highlight the importance of reducing the direct contribution of microbes from street surfaces in the watershed to urban streams under wet weather conditions. The methods and findings from this study are expected to be useful to stormwater managers and regulatory agencies.

Although large (g5 cm) polypropylene packings are frequently used in air stripping towers for environmental applications, few fundamental studies of the mass transfer on these large packing designs have been performed. For small packings, previous research has verified that the Onda correlations are valid for environmental applications. In this research, experimental data for air stripping were obtained using a pilot-scale stripping tower, three test compounds, and four polypropylene packings. Results showed that, in general, Onda is a good predictor of mass transfer for large random packings. However, Onda tended to underpredict mass transfer, with 90% of the data falling between a 16.5% overprediction and a 34.0% underprediction of the observed mass transfer. The underpredictions tended to occur at high gas flow rates and when the gas-film resistance predicted by Onda is large. Further analysis revealed that the functionality of the volumetric gas loading rate is incorrect in the Onda correlations.

Various adsorption column configurations can be used to increase fractional utilization and decrease adsorbent usage rate. This study compared the adsorbent usage rate of different column configurations. Mathematical models simulated chromatographic breakthrough front shapes and determined adsorbent usage rates. A configuration selection diagram based on percent mass‐transfer zone (MTZ) and target C/ C o (effluent concentration/influent concentration) was created to compare the adsorbent usage rate of configurations for single component systems. The target C/ C o determined the column configuration with the lowest adsorbent usage rate when the MTZ was a large percentage of the column (>60%), while all column configurations generally performed similarly at short percent MTZs (<30%). Bypass blending was found to be most effective with a lead‐lag configuration and the maximum amount of bypass. A sensitivity analysis determined that competitive adsorption can significantly change the configuration selection diagram and generally makes lead‐lag more competitive compared with parallel column configurations.

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