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H. Christopher Frey

Researcher at North Carolina State University

Publications -  191
Citations -  7290

H. Christopher Frey is an academic researcher from North Carolina State University. The author has contributed to research in topics: Diesel fuel & Vehicle-specific power. The author has an hindex of 42, co-authored 184 publications receiving 6466 citations. Previous affiliations of H. Christopher Frey include Hong Kong University of Science and Technology & Carnegie Mellon University.

Papers
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Journal ArticleDOI

Identification and Review of Sensitivity Analysis Methods

TL;DR: Identification and qualitative comparison of sensitivity analysis methods that have been used across various disciplines, and that merit consideration for application to food-safety risk assessment models, are presented.
Book

Probabilistic Techniques in Exposure Assessment: A Handbook for Dealing with Variability and Uncertainty in Models and Inputs

TL;DR: In this article, a basic framework for probabilistic analysis is presented, and a case study of the application of Probabilistic Exposure Assessment is presented. But it does not address the problem of model uncertainty.
Journal ArticleDOI

On-Road Measurement of Vehicle Tailpipe Emissions Using a Portable Instrument

TL;DR: Onboard data demonstrate the importance of accounting for the episodic nature of real-world emissions to help develop appropriate traffic and air quality management strategies.
Journal ArticleDOI

Fuel use and emissions comparisons for alternative routes, time of day, road grade, and vehicles based on in-use measurements.

TL;DR: The results demonstrate that alternative routing can significantly impact trip emissions and vehicle-specific models are needed to capture episodic effects of emissions for near-road short-term human exposure assessment.
Journal ArticleDOI

Uncertainties in predicted ozone concentrations due to input uncertainties for the UAM-V photochemical grid model applied to the July 1995 OTAG domain

TL;DR: In this article, the effect of uncertainties in UAM-V input variables (emissions, initial and boundary conditions, meteorological variables, and chemical reactions) on the uncertainties in ozone predictions was investigated.