Assessment of vehicular pollution in Kolkata, India, using CALINE 4 model

Michigan water quality standards for public bathing beaches require local health departments to collect and analyze a minimum of three water samples for Escherichia coli during each sampling event. The geometric mean number of E. coli colonies is then compared to the 300 colonies per 100 ml standard to determine compliance. This article compares the results of the currently mandated procedure to a composite sampling method, whereby the three samples are mixed in equal volumes and analyzed once. This effectively replaces the geometric mean of the individual sample results with an arithmetic mean. Although arithmetic means are more affected by outliers, this sensitivity to high concentrations is more health conservative than the geometric mean. During the 2007 sampling season, nine bathing beaches were monitored once each week. Three individual point samples and a composite sample were analyzed for each sampling event. No statistically significant differences in bacteria concentrations were found between composite sample analysis and the arithmetic mean of individual point sample analyses. No violations were detected in the 2007 sampling season, so using historical data, a retrospective analysis was performed on samples gathered at nine bathing beaches in Kalamazoo County, Michigan during the years 2001–2007. The arithmetic mean of the three samples taken at each site served as a surrogate composite sample. The benefits of compositing the three samples were investigated assuming a 2/3 reduction in analytical costs. In the traditional sampling method, three individual samples were obtained and analyzed once in every 3-week period during the summer season, whereas compositing was simulated by taking the arithmetic mean of each week’s results. The results of this retrospective cost analysis indicates that ten to 14 violations would have been missed using the less frequent traditional sampling and analysis methodology. Composite sampling is a cost-saving alternative to traditional sampling techniques that can be more protective of public health, particularly when the savings are applied to increased numbers of samples in time or space.