251
2013 ; Schumacher et al. 2014 ), and in the global economy (Yu et al. 2010 ). Some
studies have estimated fl ows of specifi c materials contained in e-waste such as steel,
aluminum, copper, lead, nickel, and zinc (Yamasue et al. 2007 ; Lam et al. 2013 ;
Habuer et al. 2014 ) and parts such as lithium-ion batteries (Chang et al., 2009 ).
Tracking international trade of second-hand e-products is another research objective
of MFA to assess the potential negative impacts on the environment in importing
countries (Kahhat and Williams 2009 , 2012 ; Yoshida and Terazono 2010 ; Breivik
et al. 2014 ).
In many countries, data on e-products and e-waste are limited. Further, consumers tend to store old e-products at home even if they are no longer used. Therefore,
methodological aspects for estimating e-waste fl ows have been discussed (Leigh
et al. 2007 ; Yoshida et al. 2009 ; Gutierrez et al., 2010; Araújo et al. 2012 ; Wang
et al. 2013 ; Li et al. 2015 ). Moreover, Lam et al. ( 2013 ) combined MFA with ecological and human health impact assessment caused by heavy metals in e-waste.
Metals in end-of-life vehicles and e-waste need to be quantifi ed for planning recycling and assessing risks. Streicher-Porte et al. ( 2009 ) integrated MFA, life cycle
assessment (LCA), and multiple attribute utility theory to evaluate scenarios for
computer supplies to schools in Colombia. These methodological developments
and integration of different tools are important next steps for MFAs.
2.4 Metals in Waste
There is a substantial body of research related to metal fl ows and stocks (Chen and
Graedel 2012 ), inevitably including waste and recycling fl ows.
One of the motivations of metal fl ow studies is to estimate recycling rates of
those metals. Graedel et al. ( 2011 ) provide an overview on the current knowledge of
recycling rates for 60 metals and show that many end-of-life recycling ratios (EOLRRs) are very low: only for 18 metals (silver, aluminum, gold, cobalt, chromium,
copper, iron, manganese, niobium, nickel, lead, palladium, platinum, rhenium, rhodium, tin, titanium, and zinc) is the EOL-RR above 50 % at present. We need further
research on recycling fl ows; this should be standardized and institutionalized in the
compilation of statistics.
How many times materials are expected to be recycled is also an interesting and
important question (see Chap. 7 ). Markov chain modeling has been applied to estimate average times of use of steel (Matsuno et al. 2007 ), stainless steel (Hashimoto
et al. 2010 ), nickel (Eckelman et al. 2012 ), and copper (Eckelman and Daigo 2008 ).
Results were, respectively, 2.7, 1.9–4.3, 3, and 1.9 times.
Some studies discuss alloying elements in metal recycling (Nakajima et al. 2011 ,
2013 ; Nakamura et al. 2012 ; Ohno et al. 2014 ). For example, Ohno et al. ( 2014 )
showed that considerable amounts of alloying elements, which correspond to 7–8 %
of the annual consumption in electric arc furnace (EAF) steelmaking, are unintentionally introduced into EAFs. This type of analysis is an interesting application of
MFA to help development of more appropriate recycling systems.
12 Material Flow Analysis and Waste Management
2013 ; Schumacher et al. 2014 ), and in the global economy (Yu et al. 2010 ). Some
studies have estimated fl ows of specifi c materials contained in e-waste such as steel,
aluminum, copper, lead, nickel, and zinc (Yamasue et al. 2007 ; Lam et al. 2013 ;
Habuer et al. 2014 ) and parts such as lithium-ion batteries (Chang et al., 2009 ).
Tracking international trade of second-hand e-products is another research objective
of MFA to assess the potential negative impacts on the environment in importing
countries (Kahhat and Williams 2009 , 2012 ; Yoshida and Terazono 2010 ; Breivik
et al. 2014 ).
In many countries, data on e-products and e-waste are limited. Further, consumers tend to store old e-products at home even if they are no longer used. Therefore,
methodological aspects for estimating e-waste fl ows have been discussed (Leigh
et al. 2007 ; Yoshida et al. 2009 ; Gutierrez et al., 2010; Araújo et al. 2012 ; Wang
et al. 2013 ; Li et al. 2015 ). Moreover, Lam et al. ( 2013 ) combined MFA with ecological and human health impact assessment caused by heavy metals in e-waste.
Metals in end-of-life vehicles and e-waste need to be quantifi ed for planning recycling and assessing risks. Streicher-Porte et al. ( 2009 ) integrated MFA, life cycle
assessment (LCA), and multiple attribute utility theory to evaluate scenarios for
computer supplies to schools in Colombia. These methodological developments
and integration of different tools are important next steps for MFAs.
2.4 Metals in Waste
There is a substantial body of research related to metal fl ows and stocks (Chen and
Graedel 2012 ), inevitably including waste and recycling fl ows.
One of the motivations of metal fl ow studies is to estimate recycling rates of
those metals. Graedel et al. ( 2011 ) provide an overview on the current knowledge of
recycling rates for 60 metals and show that many end-of-life recycling ratios (EOLRRs) are very low: only for 18 metals (silver, aluminum, gold, cobalt, chromium,
copper, iron, manganese, niobium, nickel, lead, palladium, platinum, rhenium, rhodium, tin, titanium, and zinc) is the EOL-RR above 50 % at present. We need further
research on recycling fl ows; this should be standardized and institutionalized in the
compilation of statistics.
How many times materials are expected to be recycled is also an interesting and
important question (see Chap. 7 ). Markov chain modeling has been applied to estimate average times of use of steel (Matsuno et al. 2007 ), stainless steel (Hashimoto
et al. 2010 ), nickel (Eckelman et al. 2012 ), and copper (Eckelman and Daigo 2008 ).
Results were, respectively, 2.7, 1.9–4.3, 3, and 1.9 times.
Some studies discuss alloying elements in metal recycling (Nakajima et al. 2011 ,
2013 ; Nakamura et al. 2012 ; Ohno et al. 2014 ). For example, Ohno et al. ( 2014 )
showed that considerable amounts of alloying elements, which correspond to 7–8 %
of the annual consumption in electric arc furnace (EAF) steelmaking, are unintentionally introduced into EAFs. This type of analysis is an interesting application of
MFA to help development of more appropriate recycling systems.
12 Material Flow Analysis and Waste Management