The effect of reactor scale on biochars and pyrolysis liquids from slow pyrolysis of coffee silverskin, grape pomace and olive mill waste, in auger reactors.

Several studies have addressed the potential biorefinery, through small-scale pyrolysis, of coffee silverskin (CSS), grape pomace (GP) and olive mill waste (OMW), which are respectively the main solid residues from coffee roasting, wine making and olive oil production processes. However, increasing the scale of reactor to bring these studies to an industrial level may affect the properties, and hence applications, of the resulting products. The aim of this study is therefore to perform pilot scale experiments to compare and verify the results of analytical study (TGA) and bench scale reactor runs, in order to understand the fundamental differences and create correlations between pyrolysis runs at different scales.

Chemical stabilization of Cd-contaminated soil using fresh and aged wheat straw biochar.

Metal mining and smelting activities can introduce a substantial amount of potentially toxic elements (PTE) into the environment that can persist for an extended period. That can limit the productivity of the land and creates dangerous effects on ecosystem services. The effectiveness of wheat straw biochar to immobilize Cd in contaminated soil due to metal smelting activities was investigated in this study.

Physical pretreatment of biogenic-rich trommel fines for fast pyrolysis.

Energy from Waste (EfW) technologies such as fluidized bed fast pyrolysis, are beneficial for both energy generation and waste management. Such technologies, however face significant challenges due to the heterogeneous nature, particularly the high ash contents of some municipal solid waste types e.g.

Measurement of key compositional parameters in two species of energy grass by Fourier transform infrared spectroscopy.

Two energy grass species, switch grass, a North American tuft grass, and reed canary grass, a European native, are likely to be important sources of biomass in Western Europe for the production of biorenewable energy. Matching chemical composition to conversion efficiency is a primary goal for improvement programmes and for determining the quality of biomass feed-stocks prior to use and there is a need for methods which allow cost effective characterisation of chemical composition at high rates of sample through-put. In this paper we demonstrate that nitrogen content and alkali index, parameters greatly influencing thermal conversion efficiency, can be accurately predicted in dried samples of these species grown under a range of agronomic conditions by partial least square regression of Fourier transform infrared spectra (R(2) values for plots of predicted vs.

Quantification of hydroxycinnamic acids and lignin in perennial forage and energy grasses by Fourier-transform infrared spectroscopy and partial least squares regression.

Levels of lignin and hydroxycinnamic acid wall components in three genera of forage grasses (Lolium,Festuca and Dactylis) have been accurately predicted by Fourier-transform infrared spectroscopy using partial least squares models correlated to analytical measurements. Different models were derived that predicted the concentrations of acid detergent lignin, total hydroxycinnamic acids, total ferulate monomers plus dimers, p-coumarate and ferulate dimers in independent spectral test data from methanol extracted samples of perennial forage grass with accuracies of 92.8%, 86.