Spatial assessment of the economic feasibility of short rotation coppice on radioactively contaminated land in Belarus, Ukraine, and Russia. II. Monte Carlo analysis.
Identifieur interne : 001D85 ( Main/Corpus ); précédent : 001D84; suivant : 001D86Spatial assessment of the economic feasibility of short rotation coppice on radioactively contaminated land in Belarus, Ukraine, and Russia. II. Monte Carlo analysis.
Auteurs : Marcel Van Der Perk ; Jiske Burema ; Hildegarde Vandenhove ; François Goor ; Sergei TimofeyevSource :
- Journal of environmental management [ 0301-4797 ] ; 2004.
English descriptors
- KwdEn :
- Bioelectric Energy Sources (statistics & numerical data), Biomass (MeSH), Cesium Radioisotopes (analysis), Geographic Information Systems (MeSH), Incineration (MeSH), Models, Theoretical (MeSH), Monte Carlo Method (MeSH), Republic of Belarus (MeSH), Russia (MeSH), Salix (growth & development), Ukraine (MeSH).
- MESH :
- chemical , analysis : Cesium Radioisotopes.
- geographic : Republic of Belarus, Russia, Ukraine.
- growth & development : Salix.
- statistics & numerical data : Bioelectric Energy Sources.
- Biomass, Geographic Information Systems, Incineration, Models, Theoretical, Monte Carlo Method.
Abstract
A Monte Carlo analysis of two sequential GIS-embedded submodels, which evaluate the economic feasibility of short rotation coppice (SRC) production and energy conversion in areas contaminated by Chernobyl-derived (137)Cs, was performed to allow for variability of environmental conditions that was not contained in the spatial model inputs. The results from this analysis were compared to the results from the deterministic model presented in part I of this paper. It was concluded that, although the variability in the model results due to within-gridcell variability of the model inputs was considerable, the prediction of the areas where SRC and energy conversion is potentially profitable was robust. If the additional variability in the model input that is not contained in the input maps is also taken into account, the SRC production and energy conversion appears to be potentially profitable at more locations for both the small scale and large scale production scenarios than the model predicted using the deterministic model.
DOI: 10.1016/j.jenvman.2004.05.001
PubMed: 15294355
Links to Exploration step
pubmed:15294355Le document en format XML
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Box 80115, 3508 TC, Utrecht, The Netherlands. m.vanderperk@geog.uu.nl</nlm:affiliation></affiliation></author><author><name sortKey="Burema, Jiske" sort="Burema, Jiske" uniqKey="Burema J" first="Jiske" last="Burema">Jiske Burema</name></author><author><name sortKey="Vandenhove, Hildegarde" sort="Vandenhove, Hildegarde" uniqKey="Vandenhove H" first="Hildegarde" last="Vandenhove">Hildegarde Vandenhove</name></author><author><name sortKey="Goor, Francois" sort="Goor, Francois" uniqKey="Goor F" first="François" last="Goor">François Goor</name></author><author><name sortKey="Timofeyev, Sergei" sort="Timofeyev, Sergei" uniqKey="Timofeyev S" first="Sergei" last="Timofeyev">Sergei Timofeyev</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2004">2004</date><idno type="RBID">pubmed:15294355</idno><idno type="pmid">15294355</idno><idno type="doi">10.1016/j.jenvman.2004.05.001</idno><idno type="wicri:Area/Main/Corpus">001D85</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">001D85</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Spatial assessment of the economic feasibility of short rotation coppice on radioactively contaminated land in Belarus, Ukraine, and Russia. II. Monte Carlo analysis.</title><author><name sortKey="Van Der Perk, Marcel" sort="Van Der Perk, Marcel" uniqKey="Van Der Perk M" first="Marcel" last="Van Der Perk">Marcel Van Der Perk</name><affiliation><nlm:affiliation>Department of Physical Geography, The Netherlands Centre for Geo-ecology, University of Utrecht, P.O. Box 80115, 3508 TC, Utrecht, The Netherlands. m.vanderperk@geog.uu.nl</nlm:affiliation></affiliation></author><author><name sortKey="Burema, Jiske" sort="Burema, Jiske" uniqKey="Burema J" first="Jiske" last="Burema">Jiske Burema</name></author><author><name sortKey="Vandenhove, Hildegarde" sort="Vandenhove, Hildegarde" uniqKey="Vandenhove H" first="Hildegarde" last="Vandenhove">Hildegarde Vandenhove</name></author><author><name sortKey="Goor, Francois" sort="Goor, Francois" uniqKey="Goor F" first="François" last="Goor">François Goor</name></author><author><name sortKey="Timofeyev, Sergei" sort="Timofeyev, Sergei" uniqKey="Timofeyev S" first="Sergei" last="Timofeyev">Sergei Timofeyev</name></author></analytic><series><title level="j">Journal of environmental management</title><idno type="ISSN">0301-4797</idno><imprint><date when="2004" type="published">2004</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Bioelectric Energy Sources (statistics & numerical data)</term><term>Biomass (MeSH)</term><term>Cesium Radioisotopes (analysis)</term><term>Geographic Information Systems (MeSH)</term><term>Incineration (MeSH)</term><term>Models, Theoretical (MeSH)</term><term>Monte Carlo Method (MeSH)</term><term>Republic of Belarus (MeSH)</term><term>Russia (MeSH)</term><term>Salix (growth & development)</term><term>Ukraine (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="analysis" xml:lang="en"><term>Cesium Radioisotopes</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>Republic of Belarus</term><term>Russia</term><term>Ukraine</term></keywords><keywords scheme="MESH" qualifier="growth & development" xml:lang="en"><term>Salix</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Bioelectric Energy Sources</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Biomass</term><term>Geographic Information Systems</term><term>Incineration</term><term>Models, Theoretical</term><term>Monte Carlo Method</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">A Monte Carlo analysis of two sequential GIS-embedded submodels, which evaluate the economic feasibility of short rotation coppice (SRC) production and energy conversion in areas contaminated by Chernobyl-derived (137)Cs, was performed to allow for variability of environmental conditions that was not contained in the spatial model inputs. The results from this analysis were compared to the results from the deterministic model presented in part I of this paper. It was concluded that, although the variability in the model results due to within-gridcell variability of the model inputs was considerable, the prediction of the areas where SRC and energy conversion is potentially profitable was robust. If the additional variability in the model input that is not contained in the input maps is also taken into account, the SRC production and energy conversion appears to be potentially profitable at more locations for both the small scale and large scale production scenarios than the model predicted using the deterministic model.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">15294355</PMID><DateCompleted><Year>2004</Year><Month>12</Month><Day>22</Day></DateCompleted><DateRevised><Year>2010</Year><Month>11</Month><Day>18</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">0301-4797</ISSN><JournalIssue CitedMedium="Print"><Volume>72</Volume><Issue>4</Issue><PubDate><Year>2004</Year><Month>Sep</Month></PubDate></JournalIssue><Title>Journal of environmental management</Title><ISOAbbreviation>J Environ Manage</ISOAbbreviation></Journal><ArticleTitle>Spatial assessment of the economic feasibility of short rotation coppice on radioactively contaminated land in Belarus, Ukraine, and Russia. 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If the additional variability in the model input that is not contained in the input maps is also taken into account, the SRC production and energy conversion appears to be potentially profitable at more locations for both the small scale and large scale production scenarios than the model predicted using the deterministic model.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Van Der Perk</LastName><ForeName>Marcel</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Physical Geography, The Netherlands Centre for Geo-ecology, University of Utrecht, P.O. 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