Mitchell J. Small

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Statistical models are developed for bromine incorporation in the trihalomethane (THM), trihaloacetic acids (THAA), dihaloacetic acid (DHAA), and dihaloacetonitrile (DHAN) subclasses of disinfection byproducts (DBPs) using distribution system samples from plants applying only free chlorine as a primary or residual disinfectant in the Information Collection(More)
Finding patterns in large, real, spatio/temporal data continues to attract high interest (e.g., sales of products over space and time, patterns in mobile phone users; sensor networks collecting operational data from automobiles, or even from humans with wearable computers). In this paper, we describe an interdisciplinary research effort to couple knowledge(More)
A case is made for growth of a new metadiscipline of sustainability science and engineering. This new field integrates industrial, social, and environmental processes in a global context. The skills required for this higher level discipline represent a metadisciplinary endeavor, combining information and insights across multiple disciplines and perspectives(More)
The U.S. Department of Energy has estimated that over 50 GW of offshore wind power will be required for the United States to generate 20% of its electricity from wind. Developers are actively planning offshore wind farms along the U.S. Atlantic and Gulf coasts and several leases have been signed for offshore sites. These planned projects are in areas that(More)
A methodology is presented for assessing the information value of an additional dosage experiment in existing bioassay studies. The analysis demonstrates the potential reduction in the uncertainty of toxicity metrics derived from expanded studies, providing insights for future studies. Bayesian methods are used to fit alternative dose-response models using(More)
Statistical decision theory can be a valuable tool for policy-making decisions. In particular, environmental problems often benefit from the application of Bayesian and decision-theoretic techniques that address the uncertain nature of problems in the environmental and ecological sciences. This paper discusses aspects of implementing statistical(More)
Drinking water disinfection by-product (DBP) occurrence research is important in supporting risk assessment and regulatory performance assessment. Recent DBP occurrence surveys have expanded their scope to include non-regulated priority DBPs as well as regulated DBPs. This study applies a Box-Cox transformed multivariate normal model and data augmentation(More)
Bayesian hierarchical models are built to fit multiple health endpoints from a dose-response study of a toxic chemical, perchlorate. Per-chlorate exposure results in iodine uptake inhibition in the thyroid, with health effects manifested by changes in blood hormone concentrations and histopathological effects on the thyroid. We propose linked empirical(More)