Mankind consumes as many fossil fuels per year as nature produced during a million years. Furthermore, energy consumption has tripled in the last 60 years, and is expected to be doubled in 2050, due to the technological and economic takeoff of large emerging powers. In light of this scenario, a change in energy policies should be aimed to promote energy efficiency and the use of sustainable energy resources, such as bioenergy, safely and environmental friendly.
Biomass fuels take a main role in the EU's energy and climate policies, aimed at reducing CO2 emissions and combating Climate Change. Quality control of biofuels and knowledge of their characteristics reach a large relevance in any industrial application based on the energy use of biofuels.
NIRS technology (near infrared spectroscopy, Near Infrared Reflectance Spectroscopy) is based on the interaction between electromagnetic radiation and material, and now is presented as an encouraging technological tool for quality testing of solid biofuels, since it is a non-destructive and much faster and cheaper analytical technique than traditional ones, which are based on current ISO standards. That interaction appears as spectral vibrations (energy absorption or absorbance) that are properly processed, allowing to measure the most important physical-chemical properties of solid biofuels in a fast, simple and non-destructive way.
Wood pellet is the highest quality solid biofuel in the current biomass market, which is regulated by ENplus® certification scheme in the European-wide, ensuring the quality of product to consumers. Low heating value is the most important parameter of solid biofuel, and is strongly linked to total moisture content, so the control of moisture is key factor during pelletizing process.
The original research carried out in this work allows to present the development of a NIRS prediction model for total moisture in wood pellets, in the range of values of 5 – 10 %, providing a much faster and more automated methodology for product quality control, both in production plants of wood pellets and in power plants with wood pellets as fuel.
Keywords: near infrared spectroscopy, wood pellets, quality control, moisture, prediction model
Non-destructive and Rapid Prediction of Moisture Content in Red Pepper (Capsicum annuum L.) Powder Using Near-infrared Spectroscopy and a Partial Least Squares Regression Model
