Cumulative energy demand as predictor for the environmental burden of commodity production.
Cumulative energy demand has been used as a methodology to assess life cycle environmental impacts of commodity production since the early seventies, but has also been criticized because it focuses on energy only. During the past 30 years there has been much research into the development of more complex single-score life cycle impact assessment methodologies. However, a comprehensive analysis of potential similarities and differences between these methodologies and cumulative energy demand has not been carried out so far. Here we compare the cumulative energy demand of 498 commodities with the results of six frequently applied environmental life cycle impact assessment methodologies. Commodity groups included are metals, glass, paper and cardboard, organic and inorganic chemicals, agricultural products, construction materials, and plastics. We show that all impact assessment methods investigated often provide converging results, in spite of the different philosophies behind these methodologies. Fossil energy use is identified by all methodologies as the most important driver of environmental burden of the majority of the commodities included,with the main exception of agricultural products. We conclude that a wide range of life cycle environmental assessment methodologies point into the same environmental direction for the production of many commodities.
Huijbregts
Mark A J
MA
Department of Environmental Science, Institute for Wetland and Water Research, Faculty of Science, Radboud University Nijmegen, The Netherlands. m.huijbregts@science.ru.nl
Hellweg
Stefanie
S
Frischknecht
Rolf
R
Hendriks
Harrie W M
HW
Hungerbühler
Konrad
K
Hendriks
A Jan
AJ
D003247:Conservation of Natural Resources / Q000379:methods*; D003252:Construction Materials / Q000032:analysis / Q000706:statistics & numerical data; D004777:Environment; D004785:Environmental Pollutants / Q000032:analysis / Q000592:standards; D004787:Environmental Pollution / Q000706:statistics & numerical data*; D007220:Industrial Waste / Q000032:analysis / Q000706:statistics & numerical data; D007221:Industry / Q000191:economics* / Q000706:statistics & numerical data
D004785:Environmental Pollutants; D007220:Industrial Waste