50
The bioenergy debate showed that LCAs may show some fundamental fl aws when
applied as a tool for supporting bioenergy performance-based regulation (PBR). We
distinguish between fl aws related to differences in methods applied between studies
(e.g. related to attributional vs. consequential analysis, data sources, gaps and uncertainties, choices of functional unit, allocation method, impact categories and characterisation method) and fl aws in impacts and mechanisms considered for the systems
analysed. For PBRs, LCA results should be robust and ‘lawsuit proof’, implying that
the freedom of methodological choices for the handling of such issues as biogenic
carbon balances and allocation should be reduced to an absolute minimum, uncertainties should be properly dealt with and it should be realised that there may be a gap
between the translation of results based on a functional unit of a litre of biofuel to
real-world improvements for millions of litres. There are huge differences between
LCA studies on bioenergy systems as identifi ed by Voet et al. ( 2010 ). Besides these
methodological differences, most of these LCA studies have been limited to considering only environmental impacts and not taking into account system effects and consequences such as indirect land use, rebound effects and market mechanisms. These
all play a role in how a large-scale production of bioenergy could affect the food
market, scarcity, social structure, land use, nature and other conditions that are important for society. Large-scale policies to stimulate bioethanol in the USA and Europe
have led to consequences which were not really foreseen and were barely considered
in the preparatory LCA-type studies (Zamagni et al. 2009 ). A framework for deepened analysis – including more of these mechanisms – was lacking so far.
The fact that we may improve the environmental performance of products while
still increasing the global pressure on the environment implies that we cannot simply focus on single product systems only, but also have to broaden our life cyclebased analyses to baskets of products, sectors and whole economies. Referring to
the well-known IPAT equation (Ehrlich and Holdren 1971 ), which decomposes
environmental impact (I) into the separate effects of population size (P), affl uence
(A) and technology (T), LCAs so far have focused on the pollution per functional
unit of product or service. This basically is no more than a ‘supermicro’ analysis of
T. If the total consumption of products and services (increasing affl uence) and the
size of the population keep increasing meanwhile, we may not achieve any improvement in (macro) global sustainability despite signifi cant progresses in (micro) sustainability of (a number of) individual products and services.
Both these arguments resulted in the LCSA defi nition by Guinée et al. ( 2011 )
which added two dimensions to the defi nition by Klöpffer ( 2008 ) and Klöpffer and
Renner ( 2007 ).
4 LCSA Defi nitions Adopted in Practice
In order to fi nd out which defi nition of LCSA practitioners adopt in practice, a bibliometric analysis was carried out of the ISI Web of Science (WoS) published by
Thomson Reuters. The keywords used under ‘topic’ for searching ‘all databases’
J. Guinée
The bioenergy debate showed that LCAs may show some fundamental fl aws when
applied as a tool for supporting bioenergy performance-based regulation (PBR). We
distinguish between fl aws related to differences in methods applied between studies
(e.g. related to attributional vs. consequential analysis, data sources, gaps and uncertainties, choices of functional unit, allocation method, impact categories and characterisation method) and fl aws in impacts and mechanisms considered for the systems
analysed. For PBRs, LCA results should be robust and ‘lawsuit proof’, implying that
the freedom of methodological choices for the handling of such issues as biogenic
carbon balances and allocation should be reduced to an absolute minimum, uncertainties should be properly dealt with and it should be realised that there may be a gap
between the translation of results based on a functional unit of a litre of biofuel to
real-world improvements for millions of litres. There are huge differences between
LCA studies on bioenergy systems as identifi ed by Voet et al. ( 2010 ). Besides these
methodological differences, most of these LCA studies have been limited to considering only environmental impacts and not taking into account system effects and consequences such as indirect land use, rebound effects and market mechanisms. These
all play a role in how a large-scale production of bioenergy could affect the food
market, scarcity, social structure, land use, nature and other conditions that are important for society. Large-scale policies to stimulate bioethanol in the USA and Europe
have led to consequences which were not really foreseen and were barely considered
in the preparatory LCA-type studies (Zamagni et al. 2009 ). A framework for deepened analysis – including more of these mechanisms – was lacking so far.
The fact that we may improve the environmental performance of products while
still increasing the global pressure on the environment implies that we cannot simply focus on single product systems only, but also have to broaden our life cyclebased analyses to baskets of products, sectors and whole economies. Referring to
the well-known IPAT equation (Ehrlich and Holdren 1971 ), which decomposes
environmental impact (I) into the separate effects of population size (P), affl uence
(A) and technology (T), LCAs so far have focused on the pollution per functional
unit of product or service. This basically is no more than a ‘supermicro’ analysis of
T. If the total consumption of products and services (increasing affl uence) and the
size of the population keep increasing meanwhile, we may not achieve any improvement in (macro) global sustainability despite signifi cant progresses in (micro) sustainability of (a number of) individual products and services.
Both these arguments resulted in the LCSA defi nition by Guinée et al. ( 2011 )
which added two dimensions to the defi nition by Klöpffer ( 2008 ) and Klöpffer and
Renner ( 2007 ).
4 LCSA Defi nitions Adopted in Practice
In order to fi nd out which defi nition of LCSA practitioners adopt in practice, a bibliometric analysis was carried out of the ISI Web of Science (WoS) published by
Thomson Reuters. The keywords used under ‘topic’ for searching ‘all databases’
J. Guinée