Spatial pattern of indoor settled dust in Tel-Aviv Urban area as was monitored by reflectance spectroscopy in the NIR-SWIR region (1.2-2.4 μm)

The aim of this study was to apply a spectral reflectance approach to account for small amounts of sediment dust in occupied homes. We examined the method's ability to predict the gravimetric weight of sediment dust particles solely from the reflectance data (1250-2400 nm). Multivariate data analysis based on Partial Least Squares (PLS) regression was run to predict the dust loads solely from reflectance data. Use of difference spectral index in the PLS analyses was found to demonstrate the best pre-treatment in PLS modeling. In this study, 92 measurements of dust settled on glass traps in living and bed room environments were performed, in 90 buildings within Tel-Aviv city. A map of dust distribution, based both, on the reference gravimetric and spectrally predicted weight values was generated. Reasonable explanation was provided to the found distribution that can be easily used by decision makers to improve the indoor life quality. We conclude that this methodology (simple and rapid in-situ spectral measurements with appropriate analyses), can be employed to assess dust in both indoor and outdoor environments (in small and high dust environment). This information can be used for initial decision making, improving indoor conditions, and tracking dust contamination following environmental change. This method can be further used to assess on-line very small amounts of dust and accordingly to identify shade on the environmental air quality on regular non dusty-days.