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This paper discusses the relationship between land use composition and the degree of air pollution, specifically PM10, in Iskandar Malaysia. Aspiring to be a low carbon region and a smart city, Iskandar Malaysia has to meet the social and economic needs of its growing population while taking care of all the environmental challenges that come with rapid urbanization. The intermittent regional haze episodes in the past years have shrouded this region with particulate matters including PM10, but the major cause of the haze was extensive agricultural open burning rather than land use change. Since there is no doubt land use change itself can be a significant contributor to local PM10 concentration, separating PM10 caused by the local (land use change) source from that of the regional source would enable us to investigate the trend in local PM10 pollution level. Therefore, a study on the Iskandar Malaysia's PM10 readings for the years 2002, 2006 and 2008 was carried out with the aim to identify the relationship between land use composition and PM10 concentrations. The background concentration of PM10 was extracted by using the base flow separation process commonly used in the hydrograph study. The extracted background concentration was then interpolated with the Terra MODIS level 2 product to identify the PM10 concentration for the whole Iskandar Malaysia region, spatially. Since data for land use changes are compositional data in nature, where the percentages of different land use coverages always add up to unity, the barycentric or ternary plot had been used to investigate the relationship between PM10 concentrations with the land use composition (urban:agriculture:forest) in Iskandar Malaysia. The results show that air quality as represented by PM10 concentrations are inevitably linked to the land use changes at the local level notwithstanding the more noticeable but intermittent influence of the regional haze episodes. The degree of air pollution is noticeably controlled by the percentage of urban land use with PM10 clearly affected by the size of commercial area. © 2016 by MIP.
