A methodology to estimate uncertainty for emission projections through sensitivity analysis

Lumbreras Martin, Julio; Andrés Almeida, Juan Manuel de; Pérez Rodríguez, Javier; Borge García, Rafael; Paz Martín, David de la y Rodríguez Hurtado, María Encarnación (2015). A methodology to estimate uncertainty for emission projections through sensitivity analysis. "Journal of the Air & Waste Management Association", v. 65 (n. 4); pp. 384-394. ISSN 1096-2247. https://doi.org/10.1080/10962247.2014.996268.

Descripción

Título: A methodology to estimate uncertainty for emission projections through sensitivity analysis
Autor/es:
  • Lumbreras Martin, Julio
  • Andrés Almeida, Juan Manuel de
  • Pérez Rodríguez, Javier
  • Borge García, Rafael
  • Paz Martín, David de la
  • Rodríguez Hurtado, María Encarnación
Tipo de Documento: Artículo
Título de Revista/Publicación: Journal of the Air & Waste Management Association
Fecha: 22 Diciembre 2015
Volumen: 65
Materias:
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Ingeniería Química Industrial y del Medio Ambiente
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

Texto completo

[img]
Vista Previa
PDF (Document Portable Format) - Se necesita un visor de ficheros PDF, como GSview, Xpdf o Adobe Acrobat Reader
Descargar (5MB) | Vista Previa

Resumen

Air pollution abatement policies must be based on quantitative information on current and future emissions of pollutants. As emission projections uncertainties are inevitable and traditional statistical treatments of uncertainty are highly time/resources consuming, a simplified methodology for nonstatistical uncertainty estimation based on sensitivity analysis is presented in this work. The methodology was applied to the “with measures” scenario for Spain, concretely over the 12 highest emitting sectors regarding greenhouse gas and air pollutants emissions. Examples of methodology application for two important sectors (power plants, and agriculture and livestock) are shown and explained in depth. Uncertainty bands were obtained up to 2020 by modifying the driving factors of the 12 selected sectors and the methodology was tested against a recomputed emission trend in a low economic-growth perspective and official figures for 2010, showing a very good performance. Implications: A solid understanding and quantification of uncertainties related to atmospheric emission inventories and projections provide useful information for policy negotiations. However, as many of those uncertainties are irreducible, there is an interest on how they could be managed in order to derive robust policy conclusions. Taking this into account, a method developed to use sensitivity analysis as a source of information to derive nonstatistical uncertainty bands for emission projections is presented and applied to Spain. This method simplifies uncertainty assessment and allows other countries to take advantage of their sensitivity analyses.

Más información

ID de Registro: 40440
Identificador DC: http://oa.upm.es/40440/
Identificador OAI: oai:oa.upm.es:40440
Identificador DOI: 10.1080/10962247.2014.996268
Depositado por: Memoria Investigacion
Depositado el: 13 May 2016 09:35
Ultima Modificación: 01 Sep 2017 17:17
  • Open Access
  • Open Access
  • Sherpa-Romeo
    Compruebe si la revista anglosajona en la que ha publicado un artículo permite también su publicación en abierto.
  • Dulcinea
    Compruebe si la revista española en la que ha publicado un artículo permite también su publicación en abierto.
  • Recolecta
  • e-ciencia
  • Observatorio I+D+i UPM
  • OpenCourseWare UPM