Journal of Sustainable Water in the Built Environment最新文献

The U.S. Environmental Protection Agency's Edison Environmental Center (EEC) has a research and demonstration permeable parking lot comprised of three different permeable systems: permeable asphalt, pervious concrete, and permeable interlocking concrete pavers. Water quality and quantity analysis has been ongoing since January 2010. This paper describes analysis of semivolatile organic compounds (SVOCs) to determine if hydrocarbons were in water that infiltrated through the permeable surfaces. SVOCs were analyzed in samples collected from 11 dates over a 3-year period, from February 8, 2010 to April 1, 2013. Results are broadly divided into three categories: 42 chemicals were never detected; 12 chemicals (11 chemical test) were detected at a rate of less than 10% or less; and 22 chemicals were detected at a frequency of 10% or greater (ranging from 10 to 66.5% detections). Fundamental and exploratory statistical analyses were performed on the 22 most observed chemicals. The statistical analyses were limited due to low frequency of detections and dilutions of samples, which impacted detection limits. The infiltrate data through three permeable surfaces were analyzed as nonparametric data by the Kaplan-Meier estimation method for fundamental statistics; there were some statistically observable differences in median concentration between pavement types when using Tarone-Ware comparison hypothesis test. A result was that three groups could be identified based on whether observed porous asphalt infiltrate concentration were greater than, similar to, or less than permeable interlocking concrete pavers infiltrate concentration. Identifying these three groups allowed one-way analysis on chemical attributes; the octonal water partitioning (logK _OW), number of benzene rings, and molecular complexity were all significant. These 22 most observed chemicals in the infiltrate were further tested by Spearman rank order nonparametric for correlations between frequency of detection and chemical attributes; significant correlations were observed for porous asphalt frequency of detection and molecular weight (MW), Henry's constant, log K _OW and molecular complexity, while both permeable concretes did not have any significant correlations between frequency of detection and chemical parameters. Conclusions from the statistical analyses on the 22 most frequently observed SVOCs in the infiltrate indicate that porous asphalt acts as a source for chemicals with low log K _OW and MW and a sink for chemicals with high log K _OW and MW, while no significant pattern was observed in the SVOC infiltrate concentrations of the two types of concrete.

The storm water management model (SWMM) is a widely used tool for urban drainage design and planning. Hundreds of peer-reviewed articles and conference proceedings have been written describing applications of SWMM. This review focuses on collecting information on model performance with respect to calibration and validation in the peer-reviewed literature. The major developmental history and applications of the model are also presented. The results provide utility to others looking for a quick reference to gauge the integrity of their own unique SWMM application. A gap analysis assesses the model's ability to perform water-quality simulations considering green infrastructure (GI)/low impact development (LID) designs and effectiveness. It is concluded that the level of detail underlying the conceptual model of SWMM versus its overall computational parsimony is well balanced-making it an adequate model for large and medium-scale hydrologic applications. However, embedding a new mechanistic algorithm or providing user guidance for coupling with other models will be necessary to realistically simulate diffuse pollutant sources, their fate and transport, and the effectiveness of GI/LID implementation scenarios.