Source profiles by unique ratios (SPUR) analysis: Determination of source profiles from receptor-site streaker samples |
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| Institution: | 1. School of Engineering (FEIS), Department of Biology and Animal Science, São Paulo State University (UNESP), Ilha Solteira, SP 15385-000, Brazil;2. School of Veterinary Medicine and Animal Science (FMVZ), Department of Animal Production,São Paulo State University (UNESP), Botucatu, SP 18618-000, Brazil;3. School of Engineering (FEIS), Graduate Program Animal Science and Technology, São Paulo State University (UNESP), Ilha Solteira, SP 15385-000, Brazil;4. School of Agrarian and Veterinary Sciences (FCAV), Department of Technology, São Paulo State University (UNESP), Jaboticabal, SP 14884-900, Brazil;1. IOT Perception Mine Research Center, China University of Mining and Technology, Xuzhou 221116, China;2. The National and Local Joint Engineering Laboratory of Internet Application Technology on Mine, Xuzhou 221116, China;3. State Key Laboratory of Deep Geomechanics & Underground Engineering, China University of Mining and Technology, Xuzhou 221116, China |
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| Abstract: | A streaker total filter particulate sampler was operated for three weeks at an urban site in Milan, Italy. The filters were analysed by Particle Induced X-ray Emission (PIXE), yielding hourly concentrations of 15 elements. The data are used to extract source elemental profiles using a new method, SPUR (Source Profiles by Unique Ratios). The SPUR technique is a combination of event identification using unique elemental ratios in sources, and correction for background events by identifying events of differing time constants in the time domain. The elemental ratios are identified in plots of log(S]/T])vsT], referred to as SPUR plots, where T is a (non-unique) tracer and S] is an element establishing the unique ratio. Using the SPUR technique, eight distinct sources are identified and profiles established. The sources are: two metallurgical smelters, two crustal sources, a potassium-rich source, automotive, regional crustal and regional sulphur. Results are compared with source profiles derived from Absolute Principal Component Scores analysis. SPUR analysis demonstrates powerful capability for deriving source profiles from receptor samples, including having the capability of distinguishing between sources of similar composition without using a unique tracer element. |
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