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dc.contributor.authorMuttoo, Sheena
dc.contributor.authorRamsay, Lisa
dc.contributor.authorBrunekreef, Bert
dc.contributor.authorBeelen, Rob
dc.contributor.authorMeliefste, Kees
dc.contributor.authorNaidoo, Rajen N
dc.date.accessioned2018-01-09T13:43:46Z
dc.date.available2018-01-09T13:43:46Z
dc.date.issued2018-01-01
dc.identifier.citationLand use regression modelling estimating nitrogen oxides exposure in industrial south Durban, South Africa. 2018, 610-611:1439-1447 Sci. Total Environ.en
dc.identifier.issn1879-1026
dc.identifier.pmid28873665
dc.identifier.doi10.1016/j.scitotenv.2017.07.278
dc.identifier.urihttp://hdl.handle.net/10029/621093
dc.description.abstractThe South Durban (SD) area of Durban, South Africa, has a history of air pollution issues due to the juxtaposition of low-income communities with industrial areas. This study used measurements of oxides of nitrogen (NOx) to develop a land use regression (LUR) model to explain the spatial variation of air pollution concentrations in this area.
dc.language.isoenen
dc.rightsArchived with thanks to The Science of the total environmenten
dc.titleLand use regression modelling estimating nitrogen oxides exposure in industrial south Durban, South Africa.en
dc.typeArticleen
dc.identifier.journalSci Total Environ 2017, 610-611:1439-447en
html.description.abstractThe South Durban (SD) area of Durban, South Africa, has a history of air pollution issues due to the juxtaposition of low-income communities with industrial areas. This study used measurements of oxides of nitrogen (NOx) to develop a land use regression (LUR) model to explain the spatial variation of air pollution concentrations in this area.


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