This study presents the first experimental investigation of date palm (Phoenix dactylifera) waste fast pyrolysis in a bubbling fluidized bed reactor. The physiochemical characteristics of the feedstock (from cultivars grown in the Emirate of Sharjah in the UAE), including three anatomical parts of the plant, namely, leaves, leaf stems and empty fruit bunches, have been first analyzed and compared to other popular type of biomass. These components have been subjected to fast pyrolysis and mass balances have been derived. The fast pyrolysis products (bio-oil, and non-condensable gas) have been analyzed in terms of their chemical composition, thermogravimetric profiles, and energy content. The overall product distribution in mass percentage at the pyrolysis temperature of 525 ºC was found to be 38.8% bio-oil (including 10.4% reaction water), 37.2% biochar and 24.0% non-condensable gas. The overall energy conversion efficiency (ratio of energy content in the product to that in the feedstock) was found to be 87.0%, thus indicative of the good potential of converting the date palm waste to energy while eliminating the negative environmental impact and cost associated with waste disposal.

Designing of air pollution control equipment such as biofilters, also known as gas phase biological reactors, for elimination of toxic volatile organic compounds (VOCs) from air streams require accurate modeling and model solutions. In this work, a novel approach is employed to solve a biofilter model and for performance predictions. The approach is based on expressing the particular solution of the governing equations as an integral containing Green’s function. The integral is then tuned to develop a suitable operator in which Krasnoselskii-Mann’s fixed point iteration method is applied. In this work, this technique was utilized to model the biological degradation of methanol and alpha-pinene. The results obtained by the proposed technique were compared against the experimental data adopted from literature and the originally published numerical solution. The comparison showed that the approach is highly accurate and converges fast with a uniformly distributed residual error over the entire domain. Furthermore, the method was used to perform a sensitivity analysis on the model equations to evaluate the performance of the biofilter under various conditions. To the authors’ knowledge, this is the first time Mann’s Green’s embedded method (MGEM) is applied in the solution of biofilter models.