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dc.contributor.authorEnsor, Katherine B.
Ray, Bonnie K.
Charlton, Sarah J.
dc.date.accessioned 2016-02-02T19:17:43Z
dc.date.available 2016-02-02T19:17:43Z
dc.date.issued 2014
dc.identifier.citation Ensor, Katherine B., Ray, Bonnie K. and Charlton, Sarah J.. "Point source influence on observed extreme pollution levels in a monitoring network." Atmospheric Environment, 92, (2014) Elsevier: 191-198. http://dx.doi.org/10.1016/j.atmosenv.2014.04.017.
dc.identifier.urihttps://hdl.handle.net/1911/88300
dc.description.abstract This paper presents a strategy to quantify the influence major point sources in a region have on extreme pollution values observed at each of the monitors in the network. We focus on the number of hours in a day the levels at a monitor exceed a specified health threshold. The number of daily exceedances are modeled using observation-driven negative binomial time series regression models, allowing for a zero-inflation component to characterize the probability of no exceedances in a particular day. The spatial nature of the problem is addressed through the use of a Gaussian plume model for atmospheric dispersion computed at locations of known emissions, creating covariates that impact exceedances. In order to isolate the influence of emitters at individual monitors, we fit separate regression models to the series of counts from each monitor. We apply a final model clustering step to group monitor series that exhibit similar behavior with respect to mean, variability, and common contributors to support policy decision making. The methodology is applied to eight benzene pollution series measured at air quality monitors around the Houston ship channel, a major industrial port.
dc.language.iso eng
dc.publisher Elsevier
dc.rights This is an open access article under the CC BY-NC-ND license.
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/
dc.title Point source influence on observed extreme pollution levels in a monitoring network
dc.type Journal article
dc.contributor.funder National Science Foundation
dc.contributor.funder Houston Endowment
dc.citation.journalTitle Atmospheric Environment
dc.subject.keywordextreme pollution
point source
count regression
zero inflation
model based clustering
dc.citation.volumeNumber 92
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1016/j.atmosenv.2014.04.017
dc.identifier.grantID DMS-0240058 (National Science Foundation)
dc.identifier.grantID DMS-0739420 (National Science Foundation)
dc.type.publication publisher version
dc.citation.firstpage 191
dc.citation.lastpage 198


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