In this study, we explore the use of unsteady transit time distribution (TTD) theory to model solute transport in biofilters, a popular form of nature‐based or “green” storm water infrastructure (GSI). TTD theory has the potential to address many unresolved challenges associated with predicting pollutant fate and transport through these systems, including unsteadiness in the water balance (time‐varying inflows, outflows, and storage), unsteadiness in pollutant loading, time‐dependent reactions, and scale‐up to GSI networks and urban catchments. From a solution to the unsteady age conservation equation under uniform sampling, we derive an explicit expression for solute breakthrough during and after one or more storm events. The solution is calibrated and validated with breakthrough data from 17 simulated storms at a field‐scale biofilter test facility in Southern California, using bromide as a conservative tracer. TTD theory closely reproduces bromide breakthrough concentrations, provided that lateral exchange with the surrounding soil is accounted for. At any given time, according to theory, more than half of the water in storage is from the most recent storm, while the rest is a mixture of penultimate and earlier storms. Thus, key management endpoints, such as the pollutant treatment credit attributable to GSI, are likely to depend on the evolving age distribution of water stored and released by these systems.

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The Asian American community is made up of many different cultural subgroups, all of which deal in different ways with tradition, separatism, and assimilation. Recent surveys are dispelling misconceptions about Asian American giving, suggesting fundraising strategies, and providing a framework for further research.

For many coastal regions around the world, recreational beach water quality is assessed using fecal indicator bacteria (FIB). However, the utility of FIB as indicators of recreational water illness (RWI) risk has been questioned, particularly in coastal settings with no obvious sources of human sewage. In this study we employed a source-apportionment quantitative microbial risk assessment (SA-QMRA) to assess RWI risk at a popular semi-enclosed recreational beach in Southern California (Baby Beach, City of Dana Point) with no obvious point sources of human sewage. Our SA-QMRA results suggest that, during dry weather, the median RWI risk at this beach is below the U.S. EPA recreational water quality criteria (RWQC) of 36 illness cases per 1000 bathers. During wet weather, the median RWI risk predicted by SA-QMRA depends on the assumed level of human waste associated with stormwater; the RWI risk is below the EPA RWQC illness risk benchmark 100% of the time provided that<2% of the FIB in stormwater are of human origin. However, these QMRA outcomes contrast strongly with the EPA RWQC for 30-day geometric mean of enterococci bacteria. Our results suggest that SA-QMRA is a useful framework for estimating robust RWI risk that takes into account local information about possible human and non-human sources of FIB.

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