Premium
Uncertainty and Sensitivity in the Carbon Footprint of Shopping Bags
Author(s) -
Mattila Tuomas,
Kujanpää Marjukka,
Dahlbo Helena,
Soukka Risto,
Myllymaa Tuuli
Publication year - 2011
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/j.1530-9290.2010.00326.x
Subject(s) - carbon footprint , plastic bag , environmental science , sensitivity (control systems) , limiting , life cycle assessment , scenario analysis , uncertainty analysis , ranking (information retrieval) , incineration , polyethylene , waste management , environmental economics , computer science , greenhouse gas , production (economics) , engineering , simulation , statistics , materials science , mathematics , mechanical engineering , ecology , macroeconomics , electronic engineering , machine learning , economics , composite material , biology
Summary Carbon footprints for several shopping bag alternatives (polyethylene, paper, cotton, biodegradable modified starch, and recycled polyethylene) were compared with life cycle assessment. Stochastic uncertainty analysis was used to study the sensitivity of the comparison to scenario and parameter uncertainty. On the basis of the results, we could give only a few robust conclusions without choosing a waste treatment scenario or limiting the parameter space. Given the scenario of current waste infrastructure in Finland, recycled polyethylene bags seem to be the most preferable (−7 to 24 g CO 2 eq./bag) and biodegradable bags the least preferable (38 to 60 g CO 2 eq./bag) option. In each analyzed waste treatment scenario, a few parameters dominated the uncertainty of results. Most of these parameters were downstream of the shopping bag manufacturing (consumer behavior, landfill conditions, method of waste combustion, etc.). The choice of waste treatment scenario had a greater effect on the ranking of bags than parameter uncertainty within scenarios. This result highlights the importance of including several scenarios in comparative life cycle assessments.