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dc.contributor.authorGaßnera, Laura-
dc.contributor.authorBlumendeller, Esther-
dc.contributor.authorMüller, Florian J. Y.-
dc.contributor.authorWiggerd, Maayen-
dc.contributor.authorRettenmeier, Andreas-
dc.contributor.authorCheng, Po Wen-
dc.contributor.authorHübner, Gundula-
dc.contributor.authorRitter, Joachim R. R.-
dc.contributor.authorPohl, Johannes-
dc.date.accessioned2023-03-29T06:32:56Z-
dc.date.available2023-03-29T06:32:56Z-
dc.date.issued2022-
dc.identifier.urihttps://opendata.uni-halle.de//handle/1981185920/103506-
dc.identifier.urihttp://dx.doi.org/10.25673/101548-
dc.description.abstractIn order to advance the expansion of onshore wind energy, wind turbines (WTs) must be erected in often complex terrain. The orography and the associated meteorological conditions, as well as the complex propagation of sound and ground motion waves can lead to increased annoyance of residents. Here a joint investigation of residential noise reports, meteorological, acoustic and ground motion data together with operational parameters of a wind farm in southern Germany is presented, with the objective to assess the annoyance of residents affected by WT emissions. Once strongly annoyed residents had been identified, simultaneous measurements were conducted over a 2-month period while residents used a noise reporting app to document their annoyance. A combination of the data shows that WT-related signals can be detected by acoustic and ground motion measurements in the vicinity of the WTs and, to a lesser extent, at the residential sites. In addition, background noise can be identified well. The app data indicates higher complaint rates in the early morning, evening and night hours. Changes in rotation rate seem to be the cause of annoyance as well as high rotation rates. These findings can be used to adjust WT operation in order to decrease immissions.eng
dc.language.isoeng-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subject.ddc150-
dc.subject.ddc333-
dc.titleJoint analysis of resident complaints, meteorological, acoustic, and ground motion data to establish a robust annoyance evaluation of wind turbine emissionseng
dc.typeArticle-
local.versionTypepublishedVersion-
local.bibliographicCitation.journaltitleRenewable energy-
local.bibliographicCitation.volume188-
local.bibliographicCitation.pagestart1072-
local.bibliographicCitation.pageend1093-
local.bibliographicCitation.publishernameElsevier Science-
local.bibliographicCitation.publisherplaceAmsterdam [u.a.]-
local.bibliographicCitation.doi10.1016/j.renene.2022.02.081-
local.subject.keywordsOnshore wind energy, wind turbine noise, acceptance, annoyance monitoring, sound and vibrations, meteorology-
local.openaccesstrue-
dc.identifier.ppn1796055115-
local.bibliographicCitation.year2022-
cbs.sru.importDate2023-03-29T06:31:04Z-
local.bibliographicCitationEnthalten in Renewable energy - Amsterdam [u.a.] : Elsevier Science, 1991-
local.accessrights.dnbfree-
Enthalten in den Sammlungen:Open Access Publikationen der MLU

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