Molecular tools for bathing water assessment in Europe: Balancing social science research with a rapidly developing environmental science evidence-base.

The use of molecular tools, principally qPCR, versus traditional culture-based methods for quantifying microbial parameters (e.g., Fecal Indicator Organisms) in bathing waters generates considerable ongoing debate at the science-policy interface. Advances in science have allowed the development and application of molecular biological methods for rapid (~2 h) quantification of microbial pollution in bathing and recreational waters. In contrast, culture-based methods can take between 18 and 96 h for sample processing. Thus, molecular tools offer an opportunity to provide a more meaningful statement of microbial risk to water-users by providing near-real-time information enabling potentially more informed decision-making with regard to water-based activities. However, complementary studies concerning the potential costs and benefits of adopting rapid methods as a regulatory tool are in short supply. We report on findings from an international Working Group that examined the breadth of social impacts, challenges, and research opportunities associated with the application of molecular tools to bathing water regulations.

Enterococci predictions from partial least squares regression models in conjunction with a single-sample standard improve the efficacy of beach management advisories.

Beach health advisories are issued if enterococci (ENT) densities exceed the 30-d geometric mean or single-sample water quality criteria. Current ENT enumeration procedures require 1 day of incubation; therefore, beach managers make policy decisions using 1-day-old data. This is tantamount to using a model that assumes ENT density on day t is equal to ENT density on day t-1. Research has shown that ENT densities vary over time scales shorterthan a day, calling into question the usefulness of the current model for decision-making. We created Dynamic Partial Least Square Regression (DPLSR) models for ENT at water quality monitoring stations within two adjacent marine recreational sites, Huntington State Beach (HSB) and Huntington City (HCB) Beach, California, using publicly available environmental data and tested whether these models overcome the drawbacks of the current model. The DPLSR models provide a better prediction of ENT than the current models based on comparisons of root-mean-square errors of prediction and the numbers of type 1 and 2 errors. We compared outcomes in terms of predicted illness, swimmers deterred from entering the water, and net benefits to swimmers for hypothetical management scenarios where beach advisories were issued based on (a) the previously collected sample's ENT density in conjunction with the two water quality criteria, and (b) predictions from DPLSR models in conjunction with the single-sample standard. At both HSB and HCB the DPLSR scenario produced a more favorable balance between illness prevention and recreational access. The results call into question the current method of beach management and show that model-informed decision-making and elimination of the geometric mean standard will aid beach managers in achieving more favorable outcomes in terms of illness and access than are presently achieved using 1-day-old measurements, especially at beaches where water quality problems are chronic.

Economic and health risk trade-offs of swim closures at a Lake Michigan beach.

This paper presents a framework for analyzing the economic, health, and recreation implications of swim closures related to high fecal indicator bacteria (FIB) levels. The framework utilizes benefit transfer policy analysis to provide a practical procedure for estimating the effectiveness of recreational water quality policies. Evaluation criteria include the rates of intended and unintended management outcomes, whether the chosen protocols generate closures with positive net economic benefits to swimmers, and the number of predicted illnesses the policy is able to prevent. We demonstrate the framework through a case study of a Lake Michigan freshwater beach using existing water quality and visitor data from 1998 to 2001. We find that a typical closure causes a net economic loss among would-be swimmers totaling dollars 1274-37,030/day, depending on the value assumptions used. Unnecessary closures, caused by high indicator variability and a 24-h time delay between when samples are taken and the management decision can be made, occurred on 14 (12%) out of 118 monitored summer days. Days with high FIB levels when the swim area is open are also common but do relatively little economic harm in comparison. Also, even if the closure policy could be implemented daily and perfectly without error, only about 42% of predicted illnesses would be avoided. These conclusions were sensitive to the relative values and risk preferences that swimmers have for recreation access and avoiding health effects, suggesting a need for further study of the impacts of recreational water quality policies on individuals.