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dc.titleCharacterization of aerosol optical depth and Angstrom exponent across Singapore from Sun Photometer measurements
dc.contributor.authorXin, L.
dc.contributor.authorErn, T.W.
dc.contributor.authorKhoo, R.
dc.contributor.authorYong, A.K.
dc.contributor.authorChew, B.N.
dc.contributor.authorSalinas, S.V.
dc.contributor.authorLiew, S.C.
dc.identifier.citationXin, L.,Ern, T.W.,Khoo, R.,Yong, A.K.,Chew, B.N.,Salinas, S.V.,Liew, S.C. (2008). Characterization of aerosol optical depth and Angstrom exponent across Singapore from Sun Photometer measurements. 29th Asian Conference on Remote Sensing 2008, ACRS 2008 3 : 1411-1416. ScholarBank@NUS Repository.
dc.description.abstractSince October 2006, the Center for Remote Imaging, Sensing and Processing (CRISP) of the National University of Singapore has joined the Aerosol Robotic Network, AERONET, to monitoring aerosol optical properties in this region. This initiative complements the already existing activities on satellite remote sensing performed at CRISP. In Singapore, the sources of aerosols are mostly from fossil fuel burning (energy stations, incinerators, cars etc.) and from the industrial and urban areas. The proximity to the sea adds a possible oceanic source and depending on the time of the year, there can be a strong bio-mass component coming from forest fires from various regions of the neighboring countries. In this work, we present a survey of aerosol optical depth (AOD) and Angstrom exponent retrievals at several regions of Singapore. AOD measurements were performed with the help of a hand held Microtops II Sun Photometer, data samples were collected over selected sites across the country. We used CRISP's main Sun Photometer as a benchmark for validation of our results. This study has enabled us to identify possible aerosol sources and understand the nature and physical characteristics of atmospheric aerosols across Singapore.
dc.subjectAtmospheric radiation
dc.subjectSun photometry
dc.typeConference Paper
dc.description.sourcetitle29th Asian Conference on Remote Sensing 2008, ACRS 2008
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