Volatile matter values change according to the standard utilized?

• Autor(a) principal: Silva, Diego Aleixo da
• Data de Publicação: 2021
• Outros Autores: Hansted, Ana Larissa Santiago, Nakashima, Gabriela Tami, Padilla, Elias Ricardo Durango, Pereira, Julio Cesar, Yamaji, Fabio Minoru
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/20476
• topic: Proximate analysis; ASTM; ISO; Biomass.; Análisis Inmediato; ASTM; ISO; Biomasa.; Análise imediata; ASTM; ISO; Biomassa.

In lignocellulosic biomass, the volatile matter can vary from 65 to 85%. Different standards are described in the literature for obtaining this parameter. However, it is observed that some studies of regression models have not considered these differences. They create a volatile matter content database, where the standards for obtaining the same parameter are different. Thus, the objective of the study was to verify whether different standards for volatile matter present statistically equal values. That is if they can be compared with each other, without danger of bias. For this, three types of biomasses of Brazil used were used (eucalyptus chips, pine chips, and sugarcane bagasse). The samples were collected, size reduction, size separation, and stored in the laboratory. Three standards of the American Society for Testing and Materials (ASTM D1762, ASTM E872, ASTM D3175) and one standard of the International Organization for Standardization (ISO 18123) were tested. The experimental design was completely randomized, consisting of four treatments and five replications. The central limit theorem was tested in some literature databases of the volatile matter. The results showed statistical differences when changing the type of standard used. For eucalyptus sawdust, the four standards resulted in methodologies with different averages. Still, the central limit theorem was not observed in some databases of different articles. This was explained by the non-standardization of a single standard when grouping data from different works. Therefore, different volatile content standards produce different results and when comparing values, it is important to take this assumption into account.