A carbon footprint analysis in the textile supply chain

This research work focuses on the application of life-cycle assessment methodology to determine the carbon footprint of different players involved in a supply chain of the textile sector. A case study of a product by a textile leader company was carried out. This study demonstrates that, in the textile chain, the main contribution to the greenhouse effect is provided by the electrical and thermal energy used and by the transportation (since different production phases are delocalised in a wide range that goes from South Africa, Italy, Romania and all around the world, from the distribution centre to the stores). The Monte Carlo analysis has been used in order to obtain, for each calculated impact, not only the average value but also the distribution curve of the results characterised by uncertainty parameters. Moreover, a sensitivity analysis was carried out to evaluate the impact of management choices such as: • a change in the transportation modality, from aeroplane to boat; • a combination of road and rail transportation; and • a selection among suppliers that allows the firm to cut environmental impacts.

[1]  Patrick Hofstetter,et al.  Perspectives in Life Cycle Impact Assessment: A Structured Approach to Combine Models of the Technosphere, Ecosphere and Valuesphere , 2012 .

[2]  E Roca,et al.  An approach for the application of the Ecological Footprint as environmental indicator in the textile sector. , 2008, Journal of hazardous materials.

[3]  Shang-Lien Lo,et al.  Quantifying and reducing uncertainty in life cycle assessment using the Bayesian Monte Carlo method. , 2005, The Science of the total environment.

[4]  Michael R. Overcash,et al.  Life Cycle Inventory of Refinery Products: Review and Comparison of Commercially Available Databases , 2000 .

[5]  Laurent Lardon,et al.  Inclusion of the variability of diffuse pollutions in LCA for agriculture: the case of slurry application techniques , 2010 .

[6]  Bo Pedersen Weidema,et al.  Data quality management for life cycle inventories—an example of using data quality indicators☆ , 1996 .

[7]  Gerald Rebitzer,et al.  The ecoinvent database system: a comprehensive web-based LCA database , 2005 .

[8]  Herbert Kotzab,et al.  Supply chain management on the crossroad to sustainability: a blessing or a curse? , 2009, Logist. Res..

[9]  Hans-Jürgen Dr. Klüppel,et al.  The Revision of ISO Standards 14040-3 - ISO 14040: Environmental management – Life cycle assessment – Principles and framework - ISO 14044: Environmental management – Life cycle assessment – Requirements and guidelines , 2005 .

[10]  Lynn Downey,et al.  Levi Strauss & Co. , 2007 .

[11]  Richard Y. Wang,et al.  Data Quality , 2000, Advances in Database Systems.

[12]  E. Bucher,et al.  Resistance mechanisms to plant viruses: an overview. , 2003, Virus research.

[13]  Alan C. Brent,et al.  A life cycle impact assessment procedure with resource groups as areas of protection , 2004 .

[14]  H. L. Miller,et al.  Climate Change 2007: The Physical Science Basis , 2007 .

[15]  B. Jin Achieving an optimal global versus domestic sourcing balance under demand uncertainty , 2004 .

[16]  Patrick Hofstetter,et al.  Perspectives in life cycle impact assessment , 1998 .

[17]  Stefan Seuring,et al.  From a literature review to a conceptual framework for sustainable supply chain management , 2008 .

[18]  Marion Tobler,et al.  EU COST Action 628: life cycle assessment (LCA) of textile products, eco-efficiency and definition of best available technology (BAT) of textile processing , 2007 .

[19]  Corinne Le Quéré,et al.  Climate Change 2013: The Physical Science Basis , 2013 .

[20]  J. Minx,et al.  A definition of “carbon footprint” , 2010 .