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Activity Number: 36 - ENVR Student Paper Awards
Type: Topic Contributed
Date/Time: Monday, August 3, 2020 : 10:00 AM to 11:50 AM
Sponsor: Section on Statistics and the Environment
Abstract #311150
Title: Mechanistic Models for Spatial Data from Ornstein-Uhlenbeck Processes
Author(s): Nathan Wikle* and Ephraim Hanks and Corwin Zigler
Companies: Pennsylvania State University and The Pennsylvania State University and University of Texas at Austin
Keywords: spatial statistics; SDE; Ornstein-Uhlenbeck process; space-time process; sulfate aerosols

We propose a new class of mechanistic models for spatial data observed from a generating spatio-temporal process. A multivariate Ornstein-Uhlenbeck (OU) process is used to approximate the dynamics of space-time processes, and its distributional properties are leveraged to specify novel probability models for data that are viewed as either a snapshot or an average over time of the OU process. We apply this approach to an analysis of the impact of sulfur dioxide emissions from coal-fired power plants on average sulfate concentrations in the U.S., and assess the regulatory impact of flue-gas desulfurization technologies on human exposure to sulfate aerosols.

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