IDEAS home Printed from https://ideas.repec.org/a/igg/jaeis0/v3y2012i1p51-71.html
   My bibliography  Save this article

A Generalization of the Orthogonal Regression Technique for Life Cycle Inventory

Author

Listed:
  • Antonino Marvuglia

    (Public Research Centre Henri Tudor, Luxembourg)

  • Maurizio Cellura

    (Università degli Studi di Palermo, Italy)

  • Marcello Pucci

    (Istituto Studi Sistemi Intelligenti per l’Automazione, Italy)

Abstract

Life cycle assessment (LCA) is a method used to quantify the environmental impacts of a product, process, or service across its whole life cycle. One of the problems occurring when the system at hand involves processes delivering more than one valuable output is the apportionment of resource consumption and environmental burdens in the correct proportion amongst the products. The mathematical formulation of the problem is represented by the solution of an over-determined system of linear equations. The paper describes the application of an iterative algorithm for the implementation of least square regression to solve this over-determined system directly in its rectangular form. The applied algorithm dynamically passes from an Ordinary Least Squares (OLS) problem to the regression problems known as Total Least Squares (TLS) and Data Least Squares (DLS). The obtained results suggest further investigations. In particular, the so called constrained least squares method is identified as an interesting development of the methodology.

Suggested Citation

  • Antonino Marvuglia & Maurizio Cellura & Marcello Pucci, 2012. "A Generalization of the Orthogonal Regression Technique for Life Cycle Inventory," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 3(1), pages 51-71, January.
    • Handle: RePEc:igg:jaeis0:v:3:y:2012:i:1:p:51-71
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jaeis.2012010105
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marvuglia, Antonino & Benetto, Enrico & Rios, Gordon & Rugani, Benedetto, 2013. "SCALE: Software for CALculating Emergy based on life cycle inventories," Ecological Modelling, Elsevier, vol. 248(C), pages 80-91.
    2. Brandt, Adam R. & Dale, Michael & Barnhart, Charles J., 2013. "Calculating systems-scale energy efficiency and net energy returns: A bottom-up matrix-based approach," Energy, Elsevier, vol. 62(C), pages 235-247.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jaeis0:v:3:y:2012:i:1:p:51-71. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.