Characterization of the biosolids composting process by hyperspectral analysis

Talli Ilani, Ittai Herrmann, Arnon Karnieli, Gilboa Arye

Research output: Contribution to journalArticlepeer-review

Abstract

Composted biosolids are widely used as a soil supplement to improve soil quality. However, the application of immature or unstable compost can cause the opposite effect. To date, compost maturation determination is time consuming and cannot be done at the composting site. Hyperspectral spectroscopy was suggested as a simple tool for assessing compost maturity and quality. Nevertheless, there is still a gap in knowledge regarding several compost maturation characteristics, such as dissolved organic carbon, NO3, and NH4 contents. In addition, this approach has not yet been tested on a sample at its natural water content. Therefore, in the current study, hyperspectral analysis was employed in order to characterize the biosolids composting process as a function of composting time. This goal was achieved by correlating the reflectance spectra in the range of 400-2400nm, using the partial least squares-regression (PLS-R) model, with the chemical properties of wet and oven-dried biosolid samples. The results showed that the proposed method can be used as a reliable means to evaluate compost maturity and stability. Specifically, the PLS-R model was found to be an adequate tool to evaluate the biosolids' total carbon and dissolved organic carbon, total nitrogen and dissolved nitrogen, and nitrate content, as well as the absorbance ratio of 254/365nm (E2/E3) and C/N ratios in the dry and wet samples. It failed, however, to predict the ammonium content in the dry samples since the ammonium evaporated during the drying process. It was found that in contrast to what is commonly assumed, the spectral analysis of the wet samples can also be successfully used to build a model for predicting the biosolids' compost maturity.

Original languageAmerican English
Pages (from-to)106-114
Number of pages9
JournalWaste Management
Volume48
DOIs
StatePublished - 1 Feb 2016

Keywords

  • Biosolids
  • Compost
  • Hyperspectral spectroscopy
  • PLSR

All Science Journal Classification (ASJC) codes

  • Waste Management and Disposal

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