[object Object]
Short-term prediction of urban NO2 pollution by means of artificial neural networks
Cappa C;Anfossi D;
2001
Abstract
[object Object]| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.ancejournal | INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION | - |
| dc.authority.people | Cappa C | it |
| dc.authority.people | Anfossi D | it |
| dc.authority.people | Grosa M M | it |
| dc.authority.people | Natale P | it |
| dc.collection.id.s | b3f88f24-048a-4e43-8ab1-6697b90e068e | * |
| dc.collection.name | 01.01 Articolo in rivista | * |
| dc.contributor.appartenenza | Istituto di Fisiologia Clinica - IFC | * |
| dc.contributor.appartenenza | Istituto di Scienze dell'Atmosfera e del Clima - ISAC | * |
| dc.contributor.appartenenza.mi | 885 | * |
| dc.contributor.appartenenza.mi | 974 | * |
| dc.date.accessioned | 2024/02/21 00:56:44 | - |
| dc.date.available | 2024/02/21 00:56:44 | - |
| dc.date.issued | 2001 | - |
| dc.description.abstracteng | [object Object] | - |
| dc.description.affiliations | Consiglio Nazionale delle Ricerche | - |
| dc.description.allpeople | Cappa, C; Anfossi, D; Grosa, M M; Natale, P | - |
| dc.description.allpeopleoriginal | Cappa, C.; Anfossi, D.; Grosa, M. M.; Natale, P. | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 4 | - |
| dc.identifier.scopus | 2-s2.0-0034842359 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/310381 | - |
| dc.identifier.url | http://www.scopus.com/record/display.url?eid=2-s2.0-0034842359&origin=inward | - |
| dc.language.iso | eng | - |
| dc.relation.firstpage | 483 | - |
| dc.relation.issue | 5 | - |
| dc.relation.lastpage | 496 | - |
| dc.relation.volume | 15 | - |
| dc.subject.keywords | Artificial neural networks | - |
| dc.subject.keywords | [object Object | - |
| dc.subject.keywords | Urban air pollution | - |
| dc.subject.singlekeyword | Artificial neural networks | * |
| dc.subject.singlekeyword | [object Object | * |
| dc.subject.singlekeyword | Urban air pollution | * |
| dc.title | Short-term prediction of urban NO2 pollution by means of artificial neural networks | en |
| dc.type.driver | info:eu-repo/semantics/article | - |
| dc.type.full | 01 Contributo su Rivista::01.01 Articolo in rivista | it |
| dc.type.miur | 262 | - |
| dc.ugov.descaux1 | 351904 | - |
| iris.orcid.lastModifiedDate | 2024/04/04 15:46:12 | * |
| iris.orcid.lastModifiedMillisecond | 1712238372250 | * |
| iris.scopus.extIssued | 2001 | - |
| iris.scopus.extTitle | Short-term prediction of urban NO2 pollution by means of artificial neural networks | - |
| iris.sitodocente.maxattempts | 1 | - |
| scopus.authority.ancejournal | INTERNATIONAL JOURNAL OF ENVIRONMENT AND POLLUTION###0957-4352 | * |
| scopus.category | 2311 | * |
| scopus.category | 2310 | * |
| scopus.category | 2308 | * |
| scopus.contributor.affiliation | Istituto di Cosmogeofisica del CNR | - |
| scopus.contributor.affiliation | Istituto di Cosmogeofisica del CNR | - |
| scopus.contributor.affiliation | Istituto di Cosmogeofisica del CNR | - |
| scopus.contributor.affiliation | Istituto di Cosmogeofisica del CNR | - |
| scopus.contributor.afid | 60021199 | - |
| scopus.contributor.afid | 60021199 | - |
| scopus.contributor.afid | 60021199 | - |
| scopus.contributor.afid | 60021199 | - |
| scopus.contributor.auid | 24346347000 | - |
| scopus.contributor.auid | 7007151188 | - |
| scopus.contributor.auid | 6506627606 | - |
| scopus.contributor.auid | 7004763362 | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.country | Italy | - |
| scopus.contributor.dptid | - | |
| scopus.contributor.dptid | - | |
| scopus.contributor.dptid | - | |
| scopus.contributor.dptid | - | |
| scopus.contributor.name | C. | - |
| scopus.contributor.name | D. | - |
| scopus.contributor.name | M.M. | - |
| scopus.contributor.name | P. | - |
| scopus.contributor.subaffiliation | - | |
| scopus.contributor.subaffiliation | - | |
| scopus.contributor.subaffiliation | - | |
| scopus.contributor.subaffiliation | - | |
| scopus.contributor.surname | Cappa | - |
| scopus.contributor.surname | Anfossi | - |
| scopus.contributor.surname | Grosa | - |
| scopus.contributor.surname | Natale | - |
| scopus.date.issued | 2001 | * |
| scopus.description.abstracteng | A neural network model for the short-term prediction of concentrations of urban pollutants was developed and applied to the Turin (Northern Italy) air quality network. In particular, the study was focused on NO2 concentrations measured at five stations; t + 3 and t + 24 hour NO2 concentration forecasting based on hourly meteorological and concentration data gave good agreement with observed concentrations. This is particularly true for the mean concentration values and concentration distribution. The time of occurrence of peak values was correctly forecast but the amounts were generally underestimated. To reduce this underestimation, an empirical step function was applied in the t + 24 case. This allowed an accurate estimate to be obtained of the few cases in which 50% of the air quality monitoring stations exceeded the attention level (200 μg m-3) during the following day for at least one hour. | * |
| scopus.description.allpeopleoriginal | Cappa C.; Anfossi D.; Grosa M.M.; Natale P. | * |
| scopus.differences | scopus.subject.keywords | * |
| scopus.differences | scopus.description.allpeopleoriginal | * |
| scopus.differences | scopus.identifier.doi | * |
| scopus.differences | scopus.description.abstracteng | * |
| scopus.document.type | ar | * |
| scopus.document.types | ar | * |
| scopus.identifier.doi | 10.1504/IJEP.2001.004913 | * |
| scopus.identifier.pui | 32839382 | * |
| scopus.identifier.scopus | 2-s2.0-0034842359 | * |
| scopus.journal.sourceid | 23996 | * |
| scopus.language.iso | eng | * |
| scopus.publisher.name | Inderscience Publishers | * |
| scopus.relation.firstpage | 483 | * |
| scopus.relation.issue | 5 | * |
| scopus.relation.lastpage | 496 | * |
| scopus.relation.volume | 15 | * |
| scopus.subject.keywords | Artificial neural networks; NO; 2; concentration predictions; Urban air pollution; | * |
| scopus.title | Short-term prediction of urban NO2 pollution by means of artificial neural networks | * |
| scopus.titleeng | Short-term prediction of urban NO2 pollution by means of artificial neural networks | * |
| Appare nelle tipologie: | 01.01 Articolo in rivista | |
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