When the shape of single wood spheres was captured and processed under different pyrolysis environments instantaneously, the evolution of sample geometry was obtained and a shrinkage model was proposed in this paper. The proposed shrinkage model was coupled with a one-dimensional unsteady wood pyrolysis model to predict the temperature profiles and mass variation as well as product distribution within wood spheres. A one-step drying mechanism and three parallel primary decomposition reactions as well as three secondary cracking reactions were used to describe the entire pyrolysis process. Experiments were carried out to assess the efficiency of the model prediction, and the effects of volume shrinkage on the temperature, weight loss, and product distribution were analyzed and discussed. Experimental results show that the shrinkage rate is proportional to the furnace temperature, and the average shrinkage rate increases from 0.39 to 0.53 mm/min for 20 mm wood spheres and from 0.26 to 0.55 mm/min for 30 mm wood spheres when the furnace temperature increases from 673 to 973 K. However, the final shrinkage ratio is inversely proportional to the furnace temperature and decreases with the increased sphere diameter. The peaks of simulated temperature profiles are in good agreement with experimental results when shrinkage is considered. Simulated mass loss profiles with shrinkage agree well with experimental data. On the contrary, if a constant particle size is used, the deviation between simulated and measured residual fractions is about 24% for the wood spheres studied in this paper.

Advanced thermal treatment of refuse-derived fuels (RDFs) necessitates accurate determination of the key component fractions and comprehensive understanding of the decomposition characteristics during thermal conversion. In this paper, the linear weighted sum method is employed to retrieve mass fractions of key components in different municipal solid waste (MSW)-derived fuel pellets through thermogravimetric (TG) analysis. A new Gaussian-fitting-based adjusting model is proposed to quantitatively assess the effect of the interaction on the decomposition of individual components based on differential thermogravimetric (DTG) analysis. Results show that the mass fractions of combustible key components can be determined from DTG curves and by applying the Gaussian-fitting-based adjusting model, the effects of the interaction on the decomposition of polyethylene (PE), polypropylene (PP), polystyrene (PS), polyvinyl chloride (PVC), and cellulose can be identified. It is found that, after mixing PE into RDFs, both the reaction time and activation energy of PE are decreased. The degradation of PVC starts at a higher temperature within the temperature range from 200 to 380 °C, and its reaction time is decreased by 50% within the temperature range from 380 to 500 °C. The activation energy of cellulose is slightly increased. The model proposed in this paper could be a promising method to evaluate the interaction between different key components in mixed samples for optimizing the parameters of the thermal conversion system.

This paper introduces a compact and portable sensor based on mid-infrared absorption spectroscopy for NO detection employing a room-temperature continuous wave (CW) distributed feedback quantum cascade laser (DFB-QCL) emitting at 1900.08 c m − 1 . A software-based digital signal generator and lock-in amplifier, in combination with the wavelength modulation spectroscopy (WMS) technique, were used for the concentration measurement of NO. In addition, a Gabor filter denoising method was developed to improve the performance of the measurement system. As a result, a minimum detection limit of 42 ppbv can be achieved at 3 s integration time, and a measurement precision of 450 ppbv can be reached with a time resolution of 0.1 s. The performance of the compact portable sensor was verified by a series of experiments, denoting great potential of field application for sensitive NO sensing.