250
The dynamic model presented by Müller ( 2006 ) is now often used to estimate
future resource demand and waste generation. The feature of this model is that service provided by stocks, determined by population and lifestyle, is the driver of
future service demand and related resource demand (see Chaps. 6 and 7 ). This is a
reasonable assumption when we want to foresee long-term trends of material fl ows.
Modeling future demolition waste generation is one objective of these MFA
studies. However, Hashimoto et al. ( 2007 ) showed that there can be very large discrepancies between the amounts estimated in the studies and the statistical quantities reported. One possible reason is that considerable amounts of construction
materials do not emerge as wastes. Hashimoto et al. ( 2007 ) referred to this as “missing stock” or “dissipated stock” and then proposed a framework for estimating
potential wastes accumulated within an economy (Hashimoto et al. 2009 ). Materials
input into an economy include dissipatively used materials, such as crushed stone
used for leveling the ground and reclaiming ground, and permanent structures, such
as tunnels and dams with a low probability of being demolished. This point should
be considered when we model future generation of demolition waste and its
recyclability.
Demolition waste is also important from the viewpoint of disaster waste management because it is a major portion of the waste to be managed following a disaster.
Tanikawa et al. ( 2014 ) estimated such waste as “lost material stock,” taking the
great east Japan earthquake as a case study. Methodological development for
quickly estimating the amount of disaster waste is important for the IE community,
because planning waste management and recycling is one of the fi rst steps for
recovery from disaster.
2.3 End-of-Life Vehicles and e-Waste
End-of-life vehicles contain many valuable materials that should be recovered (see
Chap. 18 ). An objective of MFA studies is, therefore, to capture fl ows of resources
contained in end-of-life vehicles, such as aluminum (Cheah et al. 2009 ; Mathieux
and Brissaud 2010 ; Modaresi and Müller 2012 ; Hatayama et al. 2012 ), steel, copper, lead, and zinc (Fuse et al. 2009 ; Yano et al. 2014 ). Further, Richa et al. ( 2014 )
analyzed lithium-ion battery waste fl ows from electric vehicles in the future.
Material fl ows of e-waste have been studied in many countries to support its
management and recycling, e.g. Brazil (Araújo et al. 2012 ), China (Liu et al. 2006 ;
Yang et al. 2008 ; Chung 2012 ; Zhang et al. 2012 ; Habuer et al. 2014 ; Li et al. 2015 ),
Chile (Steubing et al. 2010 ), Czech Republic (Polak and Drapalova 2012 ), Germany
(Walk 2009 ), Hong Kong (Chung et al. 2011 ; Lau et al. 2013 ), India (Dwivedy and
Mittal 2010a , b ), Indonesia (Andarani and Goto 2014 ), Iran (Rahmani et al. 2014 ;
Alavi et al. 2015 ), Japan (Yamasue et al. 2007 ; Oguchi et al. 2008 ; Yoshida et al.
2009 ), Nigeria (Osibanjo and Nnorom 2008 ; Nnorom and Osibanjo 2008 ), South
Korea (Lee et al. 2007 ; Kim et al. 2013 ), Spain (Gutierrez et al. 2010 ), USA (Kang
and Schoenung 2006 ; Leigh et al. 2007 ; Kahhat and Williams 2012 ; Lam et al.
Y. Moriguchi and S. Hashimoto
The dynamic model presented by Müller ( 2006 ) is now often used to estimate
future resource demand and waste generation. The feature of this model is that service provided by stocks, determined by population and lifestyle, is the driver of
future service demand and related resource demand (see Chaps. 6 and 7 ). This is a
reasonable assumption when we want to foresee long-term trends of material fl ows.
Modeling future demolition waste generation is one objective of these MFA
studies. However, Hashimoto et al. ( 2007 ) showed that there can be very large discrepancies between the amounts estimated in the studies and the statistical quantities reported. One possible reason is that considerable amounts of construction
materials do not emerge as wastes. Hashimoto et al. ( 2007 ) referred to this as “missing stock” or “dissipated stock” and then proposed a framework for estimating
potential wastes accumulated within an economy (Hashimoto et al. 2009 ). Materials
input into an economy include dissipatively used materials, such as crushed stone
used for leveling the ground and reclaiming ground, and permanent structures, such
as tunnels and dams with a low probability of being demolished. This point should
be considered when we model future generation of demolition waste and its
recyclability.
Demolition waste is also important from the viewpoint of disaster waste management because it is a major portion of the waste to be managed following a disaster.
Tanikawa et al. ( 2014 ) estimated such waste as “lost material stock,” taking the
great east Japan earthquake as a case study. Methodological development for
quickly estimating the amount of disaster waste is important for the IE community,
because planning waste management and recycling is one of the fi rst steps for
recovery from disaster.
2.3 End-of-Life Vehicles and e-Waste
End-of-life vehicles contain many valuable materials that should be recovered (see
Chap. 18 ). An objective of MFA studies is, therefore, to capture fl ows of resources
contained in end-of-life vehicles, such as aluminum (Cheah et al. 2009 ; Mathieux
and Brissaud 2010 ; Modaresi and Müller 2012 ; Hatayama et al. 2012 ), steel, copper, lead, and zinc (Fuse et al. 2009 ; Yano et al. 2014 ). Further, Richa et al. ( 2014 )
analyzed lithium-ion battery waste fl ows from electric vehicles in the future.
Material fl ows of e-waste have been studied in many countries to support its
management and recycling, e.g. Brazil (Araújo et al. 2012 ), China (Liu et al. 2006 ;
Yang et al. 2008 ; Chung 2012 ; Zhang et al. 2012 ; Habuer et al. 2014 ; Li et al. 2015 ),
Chile (Steubing et al. 2010 ), Czech Republic (Polak and Drapalova 2012 ), Germany
(Walk 2009 ), Hong Kong (Chung et al. 2011 ; Lau et al. 2013 ), India (Dwivedy and
Mittal 2010a , b ), Indonesia (Andarani and Goto 2014 ), Iran (Rahmani et al. 2014 ;
Alavi et al. 2015 ), Japan (Yamasue et al. 2007 ; Oguchi et al. 2008 ; Yoshida et al.
2009 ), Nigeria (Osibanjo and Nnorom 2008 ; Nnorom and Osibanjo 2008 ), South
Korea (Lee et al. 2007 ; Kim et al. 2013 ), Spain (Gutierrez et al. 2010 ), USA (Kang
and Schoenung 2006 ; Leigh et al. 2007 ; Kahhat and Williams 2012 ; Lam et al.
Y. Moriguchi and S. Hashimoto