life cycle assessment 
 ( lca ) practitioners can adopt three types 
 of approach to compile a life cycle inventory ( lci ) : a process approach , 
 an input  output approach , or a combination of the two : a hybrid 
 approach . each has its strengths and weaknesses in 
 terms of data resolution and the completeness and clarity of the system 
 boundaries . in practice , and to a varying extent , all three approaches 
 make use of existing lca databases to reduce the time and resources 
 required to collect raw data from the field . today , there are a wide 
 range of extensive lca databases available suitable for use either 
 in process - based lca or input output 
 lca ( also a recent discussion on international guidance on lca data ) . process - based lca allows sequential 
 inclusion of data on the greenhouse 
 gas ( ghg ) emissions associated with the imports used in a supply chain 
 in order of data availability . some of the existing process - based 
 lca databases can therefore be used to estimate 
 the emissions due to global supply chains . however , process - based 
 lca has difficulty guaranteeing the completeness of global supply 
 chain descriptions and may sometimes even fail to detect key emission 
 sources meriting preferential control in the supply chain input output 
 lca , on the other hand , theoretically guarantees 
 the completeness of global supply chain descriptions by adopting the 
 framework of a multiregional input  output ( mrio ) model . input output 
 lca with mrio is therefore more suitable for identifying global supply 
 chains with high ghg emissions and for prioritizing processes for 
 which inventory data should be elaborated . several case studies employing 
 such a hybrid methodology have recently been published . in reality , however , as can be surmised from recent empirical 
 analyses 
 using mrio , it is no simple matter to build an input  output lca database 
 with mrio in which the system boundary is globally extended to encompass 
 the detailed sectoral classifications readily available for lca . as 
 explained in our previous article , two 
 approaches are available for overcoming the dilemma of high sectoral 
 resolution and the attendant large labor burden . one is to develop 
 a methodology and software that automates as far as possible the process 
 of preparing the economic and environmental data ; the other is to employ a simplified mrio modeling framework tailored 
 to the specific purpose of the analysis . adopting the latter approach , 
 a global link input  output ( glio ) model was developed . in this article , the aim of which is to build an input output 
 lca database of japanese products based on a global system boundary 
 in a manner involving lower time and labor burdens , we calculate the 
 intensities of embodied global environmental burden ( hereafter , global 
 intensities ) of commodities produced in japan using the glio model . the environmental burdens considered here newly include energy consumption 
 and air - pollutant emissions in addition to ghg emissions complied 
 in the previous article . furthermore , 
 given that the glio model is built around a simplified mrio structure , 
 uncertainties in the global intensities deriving from this simplification 
 are quantified using monte carlo simulation . finally , we analyze the 
 characteristics of the derived global intensities focusing particularly 
 on ghg emissions from the perspective of use in lca embracing global 
 supply chains . this study applied the glio model specifying 
 the global supply chains of japanese commodities ( goods and services ) 
 to calculate the intensity of embodied global environmental burden 
 ( energy consumption , ghg , and air - pollutant emissions ) of these commodities . for instance , the embodied global ghg emission intensity ( tco2eq / one million yen : m - jpy ) is a measure of the global ghg 
 emissions ( in japan and abroad ) induced by unit production activity 
 in japan equivalent to one million yen of the commodity in question . 
 because the global intensity of each commodity is derived using input output 
 analysis based on the same system boundary , this approach permits 
 intercommodity comparison of these global intensities . calculating 
 these global intensities is conceptually identical to conducting an 
 lci of the commodity . here , the life cycle stages considered are from 
 cradle to gate , that is from resource mining through to manufacturing , 
 and the functional unit of lci is defined as unit production activity 
 of the commodity in question . as the structure of the glio model 
 has already been described in a previous article , and given space constraints here , the accounting framework and model 
 formulation are set out in detail in the supporting 
 information . here , suffice it to say that from eq 1 below we can ultimately obtain the vectors e = ( ej1jd(i1= ) ) and e = ( epg(i1= ) ) , 
 in which elements ej1jd(i1= ) and epg(i1= ) 
 represent the environmental burden of sector j1 = 1 ... n in 
 japan and in foreign country p = 1 ... n induced by japanese commodity i1 = . eq 2 , summing these elements , 
 then yields the intensity of embodied global environmental burden 
 of the commodity e indicating the global environmental burden induced 
 by unit production ( m - jpy ) of commodity  in japan.12where a11 [ n  n ] is an input coefficient matrix defining 
 the supply chains pertaining to japanese domestic commodities i1 and j1 and 13[n  n ] is 
 an input coefficient matrix defining the export structure of japanese 
 domestic commodity i1 to overseas country q. matrix 31(k ) [ n  n ] is an input coefficient matrix describing the 
 export structure of commodity k from overseas country p used in production of japanese domestic commodity j1 , 32(k ) [ n  n ] represents the export structure of 
 commodity k from overseas country p supplied directly to japanese final demand as import commodity j2 , and 33(k ) [ n  n ] represents international trade of 
 overseas commodity k between overseas countries p and q. vector d[n  1 ] consists of elements indicating the direct environmental 
 burden per unit production of the japanese commodities , and i[n  1 ] is a vector with an element of unity solely for 
 japanese commodity i1 =  and an 
 element of zero for other commodities . the symbol diag in eq 1 means diagonalization of the vector . to set the matrices a11 and 13 in eq 1 the 
 numbers of sectors n and n in eq 2 are thus 406 and 230 . one hundred and eleven foreign 
 commodities ( k = 1 ... 111 ) were considered . with respect 
 to the total domestic ghg emissions per unit production captured in 
 vector d and the total 
 overseas ghg emissions embedded in international trade given by 31(k ) , 32(k ) , and 33(k ) , we also used the ghg emission data compiled 
 in the same previous article . with respect 
 to individual ghgs , that is carbon dioxide ( co2 , both fuel - derived 
 and nonfuel - derived ) , methane ( ch4 ) , nitrous oxide ( n2o ) , perfluorocarbons ( pfcs ) , hydrofluorocarbons ( hfcs ) , and 
 sulfur hexafluoride ( sf6 ) , this study referred to the embodied 
 energy and emission intensity data for japan using input - output tables 
 ( 3eid ) for vector d and the united nation framework convention on climate change 
 ( unfccc ) inventory , international energy 
 agency ( iea ) data , enerdata , the emissions database for global atmospheric 
 research ( edgar ) ver . 4.1 , and the carbon 
 dioxide information analysis center ( cdiac ) for matrices 31(k ) , 32(k ) , and 33(k ) . the global warming potentials 
 for a 100-year time horizon defined in the intergovernmental panel 
 on climate change ( ipcc ) fourth assessment report were applied to convert emissions of ghgs other than co2 into co2 equivalents . as to energy consumption , 
 vector d was estimated 
 by converting the energy consumption on a gross calorific value ( gcv ) 
 basis provided in 3eid to consumption on a net calorific value ( ncv ) 
 basis . values for matrices 31(k ) , 32(k ) , and 33(k ) were estimated using iea 
 data and enerdata . in the case of air pollutants ( nitrogen oxide , nox , and sulfur oxide , sox ) , vector d was 
 calculated by multiplying 
 the sectoral energy consumption data by fuel type reported in 3eid 
 by the respective emission factors for each sector and fuel type . edgar was used to estimate matrices 31(k ) , 32(k ) , and 33(k ) . whereas the energy consumption and emissions associated with international 
 transportation can also be embedded in matrices 31(k ) , 32(k ) , and 33(k ) , these have not been included in the present study . although 
 the method to be used for national allocation of ghg emissions from 
 bunker fuels for international transportation is not specified in 
 the unfccc inventory reporting guidelines , if such emissions were factored in , the values of embodied global 
 ghg intensities ( hereafter , global ghg intensities ) would naturally 
 increase , but the additional contribution to each commodity s 
 global ghg intensity would be relatively insignificant . the same would hold for embodied global energy intensity , too , because 
 fuel consumption stands in direct proportion to co2 emissions . when it comes to nox and sox emissions , however , including those associated with 
 international transportation would have a significant knock - on effect 
 because the share of shipping air - pollutant emissions in the total 
 is far greater . the glio is designed to reduce the time and labor burdens of lci 
 data compilation with a global system boundary by using aggregated 
 multiregional input output structures for countries other than 
 japan , the economy of which is the specific focus here . however , this 
 aggregated description affects the robustness of the global intensities 
 derived in this way . by means of monte carlo simulation , we therefore estimated the coefficients of variation ( % ) vc of 
 the global intensities e to quantify the uncertainties in the global 
 intensities resulting from that description . given space constraints , 
 here too the procedures to determine vc are set out in detail in 
 the supporting information taking the case 
 of total ghg emissions as an example . figure 1 depicts the embodied 
 global ghg intensities ( global ghg intensity ) [ tco2eq / m - jpy ] 
 of commodities produced domestically in japan in 2005 , with the sector 
 numbers ( jd1jd406 ) representing the commodities set out on 
 the horizontal axis . the color composition of each emission indicates 
 the phases in the commodity s supply chain during which ghg 
 emissions occur : ( d ) direct emissions in japan during production , 
 ( s ) induced emissions in japan through the supply chain , and ( f ) induced 
 emissions in foreign countries supply chains . here , the induced 
 emissions mean emissions generated indirectly in the upstream supply 
 chain behind the commodity s production . as figure 1 shows , the global ghg intensities of the vast majority 
 of sectors are below about 30 tco2eq / m - jpy . for most sectors , 
 it is clearly the contributions of emission categories ( s ) and ( f ) 
 that push global ghg intensity values upward , but the magnitude of 
 these contributions varies among sectors . embodied global ghg intensity 
 of goods and services produced in 
 japan in 2005 and breakdown by emission category ( direct emissions 
 ( d ) , induced emissions in japan ( s ) , induced emissions abroad ( f ) ) . the sector numbers and corresponding sector names 
 and global ghg 
 intensities as well as figures for the emission categories ( d ) , ( s ) , 
 and ( f ) are listed in table a2 of the supporting 
 information . given space constraints , here we restrict ourselves 
 to describing the characteristics of the global ghg intensities ; the 
 sectoral intensities for the other environmental pressures considered 
 are listed in tables a1 and a3a10 of the supporting information . table 1 presents the 
 10 sectors with the highest embodied global ghg intensity showing 
 the respective contributions of ( d ) , ( s ) , and ( f ) . the sector with 
 by far the highest global ghg intensity is cement ( jd152 ) , followed 
 by pig iron ( jd161 ) , on - site power generation ( jd294 ) , and crude steel 
 ( converters ) ( jd163 ) . these are the only sectors with a global ghg 
 intensity exceeding 30 tco2eq / m - jpy . with the exception 
 of jd163 , it is the high value of category ( d ) emissions , direct emissions 
 in japan , which engenders the high overall global ghg intensity . in 
 the case of jd163 , the production of jd161 induced in the supply chain 
 is a key emission source , that is the global ghg intensity value is 
 large because of the contribution of category ( s ) emissions , induced 
 emissions in japan . the global ghg intensities of ready - mixed concrete 
 ( jd153 ) and hot rolled steel ( jd166 ) are also due largely to the share 
 of category ( s ) emissions , contributing 95% and 80% , respectively . whereas ocean transport ( jd318 ) and coal products ( jd139 ) have similar 
 global ghg intensities to jd153 and jd166 , these derive mainly from 
 emission categories ( d ) and ( f ) . table 2 identifies the commodities with the highest percentage share 
 of category ( f ) emissions ( induced emissions in foreign countries ) 
 in their global ghg intensity . at the top of the list is rolled and 
 drawn aluminum ( jd183 ) , with 86% of global ghg intensity due to overseas 
 emissions , indicating that production of aluminum products in japan 
 induces substantial emissions abroad . this sector is followed by other 
 nonferrous metal products ( jd186 ) with 83% , animal feed ( jd72 ) with 
 82% , vegetable oils and meal ( jd56 ) with 76% , and other nonferrous 
 metals ( jd178 ) with 76% . these sectors , too , cause substantial emissions 
 in global supply chains through consumption of metal resources and 
 crops for animal feed and forage . an embodied ghg intensity under the domestic technology assumption 
 ( dta ) means that the emissions associated with imports are assumed 
 to be the same as those of equivalent domestic products ( for calculation 
 of this intensity , see the supporting information ) . the commodities with the greatest difference between the global 
 ghg intensity and intensity under dta are presented in table 3 . with dta , the greatest underestimation of sector , 
 66% , is for rolled and drawn aluminum ( jd183 ) . the main reason 
 is that this sector induces large overseas emissions for aluminum 
 primary smelting , but that these emissions are largely avoided under 
 the dta , for although japan carries out secondary aluminum smelting 
 for recycling , there is no domestic primary aluminum smelting , whereas 
 it is this process that requires major inputs of electricity . calculating 
 with dta thus assumes the use of secondary smelting technology for 
 primary smelting leading to a major underestimation for the sector . this sector is followed by several food- and agriculture - related 
 sectors such as seeds and seedlings ( jd11 ) ( 57% ) , flour and 
 other grain mill products ( jd47 ) ( 52% ) , timber ( jd90 ) ( 52% ) , 
 and feeds ( jd72 ) ( 51% ) . in contrast , in certain sectors use 
 of domestic data may lead to overestimation of global ghg emissions , 
 as with tea and roasted coffee ( jd69 ) ( 14% ) , and plasticizers ( jd120 ) 
 ( 3.4% ) . table 4 presents the top 10 sectors with a particularly large coefficient 
 of variation . heading the list is seeds and seedlings ( jd11 ) ( 22% ) . the global ghg intensity of this sector was estimated as 4.36 tco2eq / m - jpy , so that with its coefficient of variation of 22% 
 the true emissions lie between 4.36  ( 1 + 0.22 ) = 5.32 and 4.36 
  ( 10.22 ) = 3.40 tco2eq / m - jpy . this is followed 
 by ocean transport ( jd318 ) ( 17% ) , aircraft repair ( jd262 ) ( 17% ) , vegetable 
 oils and meal ( jd56 ) ( 16% ) , and petroleum refinery products ( incl . , we examined the relationship between 
 the global ghg intensity and the key economic indicators ( domestic 
 output and value added ) of each sector . part a of figure 2 ( an enlarged version of which is included in the supporting information ) is a scatter diagram 
 in which the horizontal axis represents the percentage share of each 
 sector in total japanese domestic output and the vertical axis the 
 global ghg intensity ( tco2eq / m - jpy ) . from this figure , it is immediately apparent that the data points are essentially distributed 
 transversely , and the correlation coefficient is as low as 0.083 . there is thus no linear relationship between the level of domestic 
 output and embodied emission intensity . however , the spearman rank 
 correlation coefficient or spearman s  of the variables 
 is 0.238 pointing to a decreasing monotonic relationship . ( a ) relation 
 between the share of sector s output in total 
 japanese output and embodied global ghg intensity , ( b ) relation between 
 sector s value added ratio and embodied global ghg intensity , 
 ( c ) relation between sector s direct ghg emission and embodied 
 ghg intensity , ( d ) relation between direct ghg emission per unit sectoral 
 output and induced foreign ghg emission per unit sectoral output , 
 ( e ) relation between induced domestic emission per unit sectoral output 
 and induced foreign ghg emission per unit sectoral output , ( f ) relation 
 between share of induced foreign emissions in embodied global ghg 
 intensity and comparison of ghg emissions with and without domestic 
 technology assumption , ( g ) relation between share of induced foreign 
 emissions in embodied global ghg intensity and coefficient of variation 
 of embodied global ghg intensity . part b of figure 2 shows 
 the relationship 
 between the value added ratio ( m - jpy / m - jpy ) of each sector ( the horizontal 
 axis ) and its global ghg intensity ( tco2-eq / m - jpy ) ( the 
 vertical axis ) . from this figure , it is apparent that the global ghg 
 intensity gradually decreases with increasing value added ratio . spearman s  of the variables , 0.399 , 
 means a decreasing monotonic relationship . because value added is 
 a constituent element of total domestic output , the greater its ratio , 
 the lower the relative costs of intermediate inputs such as raw materials . these lower costs of intermediate inputs are presumably associated 
 with lower ghg emissions , so that the higher the value added ratio 
 of a commodity , the lower its embodied emission intensity . however , 
 part c of figure 2 presents the 
 relationship between the share ( % ) of the sector s direct emissions 
 in total japanese emissions ( the horizontal axis ) and its global ghg 
 intensity ( tco2eq / m - jpy ) ( the vertical axis ) . as the figure 
 shows , as the share of direct emission in japan increases , so too 
 does the global ghg intensity . spearman s  of the 
 variables , 0.359 , shows an increasing monotonic relationship . referring 
 to figure 1 , among sectors with a higher global 
 ghg intensity the relatively high contribution of direct emissions 
 ( category ( d ) ) higher overall 
 emissions are thus a factor pushing up unit direct emissions , as reflected 
 in the trend of part c of figure 2 . this article focuses on the 
 relationship between the induced foreign ghg emissions in the global 
 ghg intensity and the emission characteristics ( direct emissions and 
 induced domestic emissions ) of each sector . part d of figure 2 is a scatter diagram with the horizontal axis representing 
 the volume ( tco2eq / m - jpy ) of the unit direct emissions 
 ( d ) of each sector and the vertical axis representing the induced 
 foreign emissions ( f ) ( tco2eq / m - jpy ) component of the global 
 ghg intensity . although the trend is only slight , as the unit direct 
 emission increases so too does the induced foreign emission . in other 
 words , it appears that sectors with higher unit direct emissions in 
 japan do not necessarily avoid similar or greater emissions overseas . the correlation coefficient is 0.192 , signifying a weakly positive 
 correlation , but too weak to establish any definite linear relationship . spearman s  of the variables , 0.365 , confirms an increasing 
 monotonic relationship . part e of figure 2 portrays , for each sector , the relationship between the induced 
 domestic emission ( s ) ( tco2eq / m - jpy ) component of the global 
 ghg intensity ( the horizontal axis ) and the induced foreign emission 
 ( f ) component ( tco2eq / m - jpy ) ( the vertical axis ) . the correlation 
 coefficient is 0.224 indicating a positive correlation that is stronger 
 than in the case of direct emissions described in the previous section . the input coefficient describing 
 the production process of each 
 sector includes inputs of imported commodities . for this reason , if 
 production activities of other sectors are induced in the production 
 supply chainthen the input amounts of imported commodities are simultaneously 
 increased . because ghg are emitted by almost all sectors , the same 
 characteristics will appear even if production activity is expressed 
 based on ghg emissions . a sector inducing greater indirect ghg emissions 
 within the country thus tends to induce greater emissions abroad , 
 too . part f of figure 2 is a scatter diagram with the horizontal axis representing 
 the share of induced foreign emissions ( f ) in the global ghg intensity 
 of each sector and the vertical axis representing the difference ( % ) 
 between the global ghg intensity calculated in the present study and 
 the embodied ghg intensity derived under the dta . if the difference 
 is negative , then the global ghg intensity derived using glio is greater 
 than the intensity under the dta ; if it is positive , the opposite 
 holds . the coefficient of correlation between the share of emissions 
 abroad and the absolute value of the difference is 0.828 signifying 
 a strong correlation . spearman s  of the variables is 
 0.813 signifying a markedly increasing monotonic relationship . in 
 other words , even if japanese domestic technology is assumed for imported 
 commodities , it is unable to accurately duplicate the features of 
 the ghg emissions of imported commodities . the difference from the 
 intensity calculated under the dta is particularly striking in those 
 sectors showing the highest share of induced foreign emissions associated 
 with imported commodities . in part g of figure 2 , the horizontal axis represents the percentage share ( % ) of overseas 
 ( category ( f ) ) emissions in the global ghg intensity and the vertical 
 axis the coefficient of variation ( % ) . as is readily apparent , an 
 increase in the share of overseas emissions in the global ghg intensity 
 tends to increase the coefficient of variation . of the variables is 0.920 , a definite sign of an increasing 
 monotonic relationship . however , although the maximum share of overseas 
 emissions is 86% ( table 2 ) , the maximum value 
 of the coefficient of variation is 22% while remaining below 5% in 
 many sectors . no overall linear relation can consequently be established 
 between the share of induced foreign emissions and the coefficient 
 of variation ( magnitude of uncertainty ) . in addition , the impact 
 of sectoral aggregation on the uncertainty of global ghg intensities 
 was analyzed . table s1 of the supporting information summarizes the weighted average ( wa ) of the global intensities aggregated 
 to 21 broad commodity categories using a weighting coefficient based 
 on the total domestic output of each sector . the table also shows 
 the minimum and maximum global ghg intensity recorded in each category . because the two - capital - letter codes used for the commodity categories 
 in table s1 are the same as those in figure 1 , it can readily be seen from the latter which categories are associated 
 with which global intensities . the range columns in table s1 of the supporting information show the values obtained 
 by dividing the minimum and the maximum by the weighted average and 
 expressing this as a percentage , and this may be taken as the range 
 in which the weighted average is valid . the greater the similarity 
 between the global ghg intensities within a given broad commodity 
 category , the smaller this range becomes . this range is thus an index 
 of the similarity in global intensity within the broad commodity category . the range of the global ghg intensity of ict devices ( it ) and precision 
 machinery ( pm ) is relatively narrow : 85%112% and 90%119% 
 respectively , which indicates broad similarity in the global ghg intensities 
 of the sectors belonging to these two categories . however , certain 
 categories such as services ( sr ) and ceramic , stone and clay products 
 ( cr ) exhibit a far wider range : 5%1350% and 32%726% , 
 respectively . in terms of this range , 10 categories have a lower bound 
 of less than 50% ( half the weighted average ) and 9 categories have 
 an upper bound of more than 200% ( twice the weighted average ) . these 
 results are broadly similar to the spread of global ghg intensities 
 to emerge from process - based lca on the same sector categories as 
 defined here in an input  output table . the range of induced foreign emissions in the global ghg intensity 
 was also computed . similarly to above , ict devices ( it ) and precision 
 machinery ( pm ) again show a relatively narrow range in this respect 
 of 83%115% and 69%123% , respectively . here , there 
 is indeed similarity with the situation for overall global ghg intensity . 
 at the same time though , certain categories such as electric power , 
 gas supply and steam , water supply , and waste disposal ( el ) , corresponding 
 to utilities , exhibit an expanded range of 39%710% with regard 
 to the share of foreign emissions . for eight commodity categories , the lower bound of the range is less than 50% , whereas for six categories 
 the upper bound is over 200% . there are thus fewer categories with 
 a variation extending down to less than half or up to more than twice 
 the weighted average than in the case of overall global ghg intensity . this implies that the emission structure of the global ghg intensity 
 of products belonging to the same broad category do not exhibit any 
 great similarity . finally , we also calculated the range of the 
 coefficient of variation 
 of the global intensity . in this respect , it showed a narrower range 
 of 75%130% , whereas pm showed a wider range of 59%249% . the lower bound of the range is less than 50% for nine categories , 
 whereas the upper bound is over 200% for 11 categories leading to 
 the conclusion that uncertainty of global ghg intensity tends to increase 
 with sectoral aggregation because there is even less similarity in 
 the uncertainty in global ghg intensity of products belonging to the 
 same commodity category than in the case of emission structure just 
 described . for the purposes of input  output lca 
 and hybrid lca , if the lca practitioner knows the 2005 producer price 
 ( m - jpy ) of the commodity under study this price can be multiplied 
 by the global intensity ( tco2eq / m - jpy ) of that commodity 
 to obtain its cradle - to - gate lci with respect to ghg ( tco2eq ) based on a global system boundary . the producer price can be 
 estimated from the physical quantity ( e.g. , kilogram ) of the commodity 
 and its unit price ( e.g. , m - jpy / kg ) in 2005 . in input output 
 lca and hybrid lca on manufacturing processes and technologies with 
 input of high global - ghg - intensity commodities , such as presented 
 in table 1 , or with lower value added ( but 
 no relation to sectoral output level : parts a and b of figure 2 ) , the accuracy of the price or physical amounts 
 of these commodities thus has a significant bearing on the life cycle 
 emissions calculated and , consequently , on the overall reliability 
 of the lci result . in such cases , the lca practitioner should therefore 
 take extra care in quantifying prices and physical quantities giving 
 due consideration to year - to - year differences in prices and/or technologies . in process lca , such high - global ghg intensity commodities should 
 be identified in the screening phase as deserving particularly high 
 priority in terms of collecting detailed process data . for most such 
 commodities , it is direct emissions that are the main contributor 
 to the high global ghg intensity ( part c of figure 2 ) , and the on - site emissions occurring at the commodity s 
 production site should therefore be given greater emphasis than those 
 associated with its global supply chain . a 
 commodity with a high proportion of overseas emissions generates large 
 ghg emissions in the foreign supply chain associated with the imported 
 materials and services used in the domestic supply chain in japan . 
 for commodities with a large share of foreign emissions , as presented 
 in table 2 , the lca practitioner should give 
 priority to collecting process and emission data on the imports used 
 in the supply chain . in process lca , because commodities with large 
 domestic emissions ( both direct and indirect ) tend to show large foreign 
 emissions ( parts d and e of figure 2 ) due effort 
 should be made to identify the foreign emissions associated with such 
 commodities . however , data on processes and emissions in foreign 
 countries are often scarce as well as costly to retrieve . hence , in 
 the case of such commodities , too , input  output lca and hybrid 
 lca using the data described as a result of this study have major 
 benefits over process lca , which generally has no option but to ignore 
 the foreign emissions associated with a commodity for reasons of cost 
 and data availability . for such commodities , an alternative 
 to process lca is to apply 
 domestic ( japanese ) process and emission data for imported materials 
 and services . this substitution assumes that the production technology 
 of an imported commodity is equivalent to that of the corresponding 
 domestic commodity . if an lca of the commodity using domestic emission 
 data rather than those of the imports in question yields a similar 
 result to an lca , that does give due consideration to global supply 
 chain emissions , and then the process lca of the commodity can provide 
 a rough estimate of its global ghg emissions using only domestic data , 
 which are readily obtainable . from the comparison of the global 
 ghg intensities with the intensities 
 under the dta , this study has confirmed that , with relatively few 
 exceptions , presented in table 3 , most sectors 
 show differences between about 40% and 20% ( part f of figure 2 ) . if an lca practitioner defines what degree of 
 under / overestimation is acceptable for the global ghg of a commodity , 
 then use of domestic data as a surrogate for the data on imported 
 commodities used in the supply chain might be deemed a suitable alternative 
 in a process lca . although a simplified method was used 
 to calculate global ghg intensities , the majority of sectors show 
 a coefficient of variation of less than 10% in their global ghg intensity , 
 as presented in part g of figure 2 , and can 
 thus be deemed well amenable to lci data based on an input  output 
 analysis . use of these data thus 
 permits simple estimation of the uncertainty in the results of applying 
 the global ghg intensities obtained in this study to yield an lci . 
 as table s1 of the supporting information shows , however , it should be noted that this uncertainty in global 
 ghg intensity increases markedly if sectors are aggregated . in input output lca , the coefficient of variation of the sector 
 can itself be interpreted as being the uncertainty of the lci . with 
 hybrid lca and particularly tiered hybrid lca , assuming no correlation among the coefficients of variation in the 
 sectors , the possible range of each intensity is calculated from the 
 coefficients of variation and the emissions are calculable for the 
 highest global ghg intensity value and for the lowest . this enables 
 estimation of the range of uncertainty of emissions through the connection 
 with input  output analysis in hybrid lca . in this study , 
 however , the uncertainty was estimated using the 
 input structure of japan s domestic commodities , which does 
 not reflect the characteristics of commodities produced elsewhere 
 ( particularly energy and mineral resources ) . in addition , supply chains 
 that enjoy a geographical advantage to eastern asia , including china as a high carbon emitter , start weighing in on 
 the results , implying a possible overestimation 
 of uncertainty . at the same time , estimating the variation in the 
 input coefficients of overseas sectors in the glio model using monte 
 carlo simulation rested on the extreme assumption that each country 
 except for japan has a production structure in which it produces only 
 one type of commodity ( for details , supporting 
 information ) . however , the glio model aggregates 
 foreign commodities into 111 types leading to a potential underestimate 
 of uncertainty .
to build a life cycle assessment ( lca ) database of japanese 
 products 
 embracing their global supply chains in a manner requiring lower time 
 and labor burdens , this study estimates the intensity of embodied 
 global environmental burden for commodities produced in japan . 
 the 
 intensity of embodied global environmental burden is a measure of 
 the environmental burden generated globally by unit production of 
 the commodity and can be used as life cycle inventory data in lca . 
 the calculation employs an input  output lca method with a global 
 link input  output model that defines a global system boundary 
 grounded in a simplified multiregional input  output framework . 
 as results , 
 the intensities of embodied global environmental burden 
 for 406 japanese commodities are determined in terms of energy consumption , 
 greenhouse - gas emissions ( carbon dioxide , methane , nitrous oxide , 
 perfluorocarbons , hydrofluorocarbons , sulfur hexafluoride , and their 
 summation ) , and air - pollutant emissions ( nitrogen oxide and sulfur 
 oxide ) . 
 the uncertainties in the intensities of embodied global environmental 
 burden attributable to the simplified structure of the global link 
 input  output model are quantified using monte carlo simulation . 
 in addition , by analyzing the structure of the embodied global greenhouse - gas 
 intensities we characterize japanese commodities in the context of 
 lca embracing global supply chains .