Reflectance spectroscopy of indoor settled dust in Tel Aviv, Israel: comparison between the spring and the summer seasons
- 1Remote Sensing and GIS Laboratory, Department of Geography and the Human Environment, Tel-Aviv University, Israel
- 2Unit for Applied Climatology and Environmental Aspects, Department of Geography and the Human Environment, Tel-Aviv University, Israel
Abstract. The influence of mineral and anthropogenic dust components on the VIS-NIR-SWIR spectral reflectance of artificial laboratory dust mixtures was evaluated and used in combination with Partial Least Squares (PLS) regression to construct a model that correlates the dust content with its reflectance. Small amounts of dust (0.018–0.33 mg/cm2) were collected using glass traps placed in different indoor environments in Tel Aviv, Israel during the spring and summer of 2005. The constructed model was applied to reflectance spectroscopy measurements derived from the field dust samples to assess their mineral content. Additionally, field samples were examined using Principal Component Analysis (PCA) to identify the most representative spectral pattern for each season. Across the visible range of spectra two main spectral shapes were observed, convex and concave, though spectra exhibiting hybrid shapes were also seen. Spectra derived from spring season dust samples were characterized mostly by a convex shape, which indicates a high mineral content. In contrast, the spectra generated from summer samples were characterized generally by a concave shape, which indicates a high organic matter content. In addition to this seasonal variation in spectral patterns, spectral differences were observed associated with the dwelling position in the city. Samples collected in the city center showed higher organic content, whereas samples taken from locations at the city margins, near the sea and next to open areas, exhibited higher mineral content. We conclude that mineral components originating in the outdoor environment influence indoor dust loads, even when considering relatively small amounts of indoor settled dust. The sensitive spectral-based method developed here has potentially many applications for environmental researchers and policy makers concerned with dust pollution.