New Models Used to Determine the Dioxins Total Amount and Toxicity (TEQ) in Atmospheric Emissions from Thermal Processes
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Título: | New Models Used to Determine the Dioxins Total Amount and Toxicity (TEQ) in Atmospheric Emissions from Thermal Processes |
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Autor/es: | Palmer, Damià | Pou, Josep O. | González Sabaté, Lucinio | Díaz Ferrero, Jordi | Conesa, Juan A. | Ortuño García, Nuria |
Grupo/s de investigación o GITE: | Residuos, Energía, Medio Ambiente y Nanotecnología (REMAN) |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Ingeniería Química |
Palabras clave: | PCDD/F | Dioxins formation | MSW incineration | Linear regression model | Estimation of toxicity | Congener profile |
Área/s de conocimiento: | Ingeniería Química |
Fecha de publicación: | 21-nov-2019 |
Editor: | MDPI |
Cita bibliográfica: | Palmer D, Pou JO, Gonzalez-Sabaté L, Díaz-Ferrero J, Conesa JA, Ortuño N. New Models Used to Determine the Dioxins Total Amount and Toxicity (TEQ) in Atmospheric Emissions from Thermal Processes. Energies. 2019; 12(23):4434. doi:10.3390/en12234434 |
Resumen: | In order to reduce the calculation effort during the simulation of the emission of polychlorinated dibenzo-p-dioxins and furans (PCDD/F) during municipal solid waste incineration, minimizing the number of simulated components is mandatory. For this purpose, two new multilinear regression models capable of determining the dioxins total amount and toxicity of an atmospheric emission have been adjusted based on previously published ones. The new source of data used (almost 200 PCDD/F analyses) provides a wider range of application to the models, increasing also the diversity of the emission sources, from industrial and laboratory scale thermal processes. Only three of the 17 toxic congeners (1,2,3,6,7,8-HxCDD, 2,3,7,8-TCDF and OCDF), whose formation was found to be linearly independent, were necessary as inputs for the models. All model parameters have been statistically validated and their confidence intervals have been calculated using the Bootstrap method. The resulting coefficients of determination (R2) for the models are 0.9711 ± 0.0056 and 0.9583 ± 0.0085; its root mean square errors (RMSE) are 0.2115 and 0.2424, and its mean absolute errors (MAE) are 0.1541 and 0.1733 respectively. |
Patrocinador/es: | Juan A. Conesa and Nuria Ortuño acknowledge the support for this work by the CTQ2016-76608-R project from the Ministry of Economy, Industry and Competitiveness (Spain). Damià Palmer thanks IQS—Universitat Ramon Llull for its financial support. |
URI: | http://hdl.handle.net/10045/102889 |
ISSN: | 1996-1073 |
DOI: | 10.3390/en12234434 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.3390/en12234434 |
Aparece en las colecciones: | INV - REMAN - Artículos de Revistas |
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