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Describes the Worcester Polytechnic Institute in Massachusetts' Pre Qualifying Projects degree course, designed to develop student communication skills in technical presentations. Student presentation of forensic papers and case studies; Aims of the project; Description; Areas of study in the presented papers.

Information about several papers discussed at the national conference of the Division Executive Committee in Boston, Massachusetts in October 2007 is presented. The topic includes implementing a social networking infrastructure, identify professional development and mentoring opportunities for CHED members, and provide access to fully-developed quality resources in the country. The symposium has featured several speakers including Donald Wink, Melanie Cooper, and John Moore.

Historically, the thousands of compounds found in oils constituted an ‘unresolved complex mixture’ that frustrated efforts to analyze oil weathering. Moreover, different weathering processes inflict rich and diverse signatures of compositional change in oil, and conventional methods do not effectively decode this elaborate record. Using comprehensive two-dimensional gas chromatography (GC x GC), we can separate thousands of hydrocarbon components and simultaneously estimate their chemical properties. We investigated 13 weathered field samples collected from the Bouchard 120 heavy fuel oil spill in Buzzards Bay, Massachusetts in 2003. We first mapped hydrocarbon vapor pressures and aqueous solubilities onto the compositional space explored by GC x GC chromatograms of weathered samples. Then we developed methods to quantitatively decouple mass loss patterns associated with evaporation and dissolution. The compositional complexity of oil, traditionally considered an obstacle, was now an advantage. We exploited the large inventory of chemical information encoded in oil to robustly differentiate signatures of mass transfer to air and water. With this new approach, we can evaluate mass transfer models (the Part 2 companion to this paper) and more properly account for evaporation, dissolution, and degradation of oil in the environment. [ABSTRACT FROM AUTHOR]

Environmental data frequently are left censored due to detection limits of laboratory assay procedures. Left censored means that some of the observations are known only to fall below a censoring point (detection limit). This presents difficulties in statistical analysis of the data. In this paper, we examine methods for estimating the correlation between variables each of which is censored at multiple points. Multiple censoring frequently arises due to adjustment of singly censored laboratory results for physical sample size. We discuss maximum likelihood (ML) estimation of the correlation and introduce a new method (cp.mle2) that, instead of using the multiply censored data directly, relies on ML estimates of the covariance of the singly censored laboratory data. We compare the ML methods with Kendall's tau-b (ck.taub) which is a modification Kendall's tau adjusted for ties, and several commonly used simple substitution methods: correlations estimated with nondetects set to the detection limit divided by 2 and correlations based on detects only (cs.det) with nondetects set to missing. The methods are compared based on simulations and real data. In the simulations, censoring levels are varied from 0 to 90%, p from -0.8 to 0.8, and v (variance of physical sample size) is set to 0 and 0.5, for a total of 550 parameter combinations with 1000 replications at each combination. We find that with increasing levels of censoring most of the correlation methods are highly biased. The simple substitution methods in general tend toward zero if singly censored and one if multiply censored. ck.taub tends toward zero. Least biased is cp.mle2, however, it has higher variance than some of the other estimators. Overall, cs.det performs the worst and cp.mle2 the best. [ABSTRACT FROM AUTHOR]

This paper investigates strategic noncompliance with the Total Coliform Rule (TCR) under the U.S. Safe Drinking Water Act. The structure of the TCR provides incentives for some piped drinking water systems to avoid violations by taking additional water quality samples. We estimate the prevalence of this behavior and its potential impact on violations using monthly data for more than 500 Massachusetts water systems, 1993-2003. We find evidence that strategic oversampling is occurring. Water systems most likely to avoid violations by oversampling are most likely to oversample. A significant number of additional violations would have occurred if systems had adhered to legal sampling requirements, rather than oversampling. Our analysis of potential impacts of regulatory avoidance under the current rule suggests that alternative policies for monitoring bacteria in drinking water should be considered.