Assessing the uncertainty of emergy analyses with Monte Carlo simulations

Simple item page
dc.contributor.advisorTilley, David Ren_US
dc.contributor.authorHudson, Amyen_US
dc.contributor.departmentEnvironmental Science and Technologyen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2013-04-09T05:32:45Z
dc.date.available2013-04-09T05:32:45Z
dc.date.issued2012en_US
dc.description.abstractCrop production systems were used to show the presence and propagation of uncertainty in emergy analyses and the effect of source variance on the variance of the yield unit emergy value (UEV). Data on energy/masses and UEVs for each source and yield were collected from the emergy literature and considered as inputs for the Monte Carlo simulation. The inputs were assumed to follow normal, lognormal, or uniform probability distributions. Using these inputs and a tabular method, two models ran Monte Carlo simulations to generate yield UEVs. Supplemental excel files elucidate the Monte Carlo simulations' calculations. The nitrogen fertilizer UEV and net topsoil loss energy were the inputs with the largest impact on the variance of the yield's UEV. These two sources also make the largest emergy contributions to the yield and should be the focus of a manager intent on reducing total system uncertainty. The selection of a statistical distribution had an impact on the yield UEV and thus these analyses may need to remain system- or even source- specific.en_US
dc.identifier.urihttp://hdl.handle.net/1903/13863
dc.subject.pqcontrolledEnvironmental scienceen_US
dc.subject.pqcontrolledEcologyen_US
dc.subject.pqcontrolledSystem scienceen_US
dc.subject.pquncontrolledcrop production systemen_US
dc.subject.pquncontrolledemergyen_US
dc.subject.pquncontrolledEnvironmental accountingen_US
dc.subject.pquncontrolledMonte Carlo simulationen_US
dc.subject.pquncontrolledUEVen_US
dc.subject.pquncontrolleduncertaintyen_US
dc.titleAssessing the uncertainty of emergy analyses with Monte Carlo simulationsen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 2 of 2
Thumbnail Image
Name:
Hudson_umd_0117N_13875.pdf
Size:
6.15 MB
Format:
Adobe Portable Document Format
Download
No Thumbnail Available
Name:
ThesisSupplementalMaterial.xlsx
Size:
22.25 KB
Format:
Unknown data format
Download

Collections

UMD Theses and Dissertations
Environmental Science & Technology Theses and Dissertations