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  1. 1. Estimation of Supply Chain Cadmium, Lead, Nickel, and Zinc Intensity with the Mixed-Unit Input-Output Life Cycle Assessment (MUIO-LCA) Model Troy Hawkinsa, Chris Hendricksonb, H. Scott Matthewsc Green Design Institute Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA 15213 USA a trh@andrew.cmu.edu, bcth@andrew.cmu.edu, chsm@andrew.cmu.edu Abstract The risks associated with releases of heavy metals are of great concern for companies, regulators, and society at large. Understanding how and why we use these toxic chemicals can help us use them more efficiently. Here LCA and MFA are combined in the formulation of a mixed-unit, input-output life-cycle assessment (MUIO-LCA) model to help improve environmental decision-making with respect to heavy metals. The 1997 U.S. Benchmark IO Accounts including nearly 500 sectors of the US economy were augmented with additional sectors for explicitly handling physical flows of Cd, Pb, Ni and Zn as described by the US Geological Survey. The model allows for material usage, environmental releases, and other flows of interest to be estimated for the complete supply chains of goods and services. Benefits of using the MUIO-LCA model for evaluating the life-cycle impacts and material flows associated with products include greater detail, explicit tracking of material flows, and the ability to model production of select commodities based on mass units rather than dollars. The inclusion of process sectors based on physical quantity reduces the burden on the model user to calculate the cost associated with these commodities and allows for better estimation of the impacts associated with imported goods by removing the dependence of physical flows on price. We use the MUIO-LCA model to estimate consumption of cadmium, lead, nickel and zinc throughout the entire supply chain of each sector of the economy providing insight into the material intensity of products and processes. By coupling material and economic transaction data the MUIO-LCA model presented here provides a more complete picture of the movement of metals through the economy than either MFA or economic IO techniques alone could provide. Introduction The use of materials and the resultant environmental impacts are important problems. Tracking material flows through industrial processes is vital to understanding of the effects 1
  2. 2. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 of changing consumption patterns and production technologies. A tool for providing information about the flows of environmentally relevant materials would provide valuable guidance for improving efficiency and reducing anthropogenic burdens on natural systems. Approaches that deal with the flows in and out of a specific process are only useful to a limited extent due to the interconnectedness of processes within our economy. National scale input-output models generally rely on national input-output accounts consisting of monetary transactions between sectors of the economy. In this work, national models for the U.S. economy are augmented with sectors representing the physical flow of cadmium, lead, nickel and zinc to create a mixed-unit input-output life-cycle assessment (MUIO-LCA) model. Results from the MUIO-LCA model are provided in dollars for 500 sectors of the economy and mass units for the additional cadmium, lead, nickel, and zinc sectors. Cadmium, lead, nickel, and zinc were chosen as the focus of the Mixed-Unit Input-Output model for a combination of reasons including toxicity, wide-spread use, policy-relevance, and interactions among their material cycles (ATSDR '99, '04a, b, c, Audry '04, EC '83, EPA '90, '93, '97, '05a, b, NRC '80, '93, OSHA '92, Smith '95). Cadmium and lead were chosen primarily due to concerns about their toxicity (EPA '05a, Ui '92). Zinc was added because of its occurrence with cadmium and lead in ore and its prevalence in the economy (Gordon '03, Gordon '04, Graedel '05). All cadmium and much lead is produced as a co- product (or by-product) of zinc production (USGS '98). Nickel was selected because of its relationship to the flows of cadmium and lead. Nickel is used in both nickel-cadmium and nickel-metal hydride batteries. Nickel-cadmium batteries represent the largest cadmium flow, accounting for 80% of cadmium use while nickel-metal hydride batteries are the most common battery technology used in hybrid vehicles (Higgins '07, Stempel '98). The groundwork for the MUIO accounts presented here was laid by many earlier studies. A mixed-unit IO account based on the most appropriate units for measuring the output of each sector was recently suggested by Duchin ('04a). Earlier work by Ayres and Kneese 2
  3. 3. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 ('69) and Kneese et al. ('70) applied the mass-balance principle to input-output analysis forming a basic framework for modeling physical flows. During the energy crises of the 1970s mixed-unit input-output techniques were used in a number of energy analyses (Bullard '75, Bullard '78, Casler '84, Hannon '78, Herendeen '78). Leontief ('70) introduced a pollution sector with mass unit emission flows into a national model. Duchin (Duchin '04b, Weisz '04) presented an extended input-output model based upon physical quantities and prices. Giljum ('04, '05b) provides additional guidance on the development of mixed-unit IO models. Suh ('04a) demonstrated how to integrate process-specific physical flow data with monetary input-output models and noted the advantages of the input-output models in accounting for circularity of flows in environmental life-cycle assessment. Konijn et al. ('97) and Hoekstra ('03) have utilized both physical and monetary units in an input-output table in tracing the resources flows in a national economy introducing the mixed-unit input-output model. Hawkins ('06b) presented a model based on the summary-level US IO tables with added sectors to track flows of cadmium and lead. Lin ('98) provides an example of coke making for an enterprise specific input-output model. Thus the usefulness of input-output models for materials flow analyses, tracking the movements of particular materials or energy through industrial processes, product use and natural reservoirs has been shown to be useful (Ayres '01, Baccini '91, Bailey '04a, '04b, Duchin '91, '92, Giljum '05a, NRC '04, Suh '04b, Suh '04c, Takase '05). Method for Creating a Mixed-Unit Model The MUIO make and use accounts are created by adding rows and columns to the 1997 U.S. Benchmark make and use tables. Existing economic sectors are modified to reflect the movement of activity to these new sectors. Cadmium, lead, nickel, and zinc commodities measured in physical units are represented by an additional column in the make (supply) table and an additional row in the use table. Similarly, industries which produce commodities measured in physical units are represented by an additional row in the make table and an additional column in the use table. 3
  4. 4. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Flows of cadmium, lead, nickel, and zinc used to create MUIO make and use tables are generally based on data published by the U.S. Geological Survey in the annual Minerals Yearbook (USGS '98). The Minerals Yearbook chapter for each mineral generally includes data about the extraction, production, imports, exports and stocks. Data for each mineral are compiled by USGS Commodity Specialists from voluntary surveys, company reports, trade associations publications, journals, international exchanges (such as the New York Mercantile Exchange or the London Metal Exchange), personal communications, and the U.S. Census Bureau. The level of detail of physical flow data published in the Minerals Yearbook differs for each material. In general, the most detailed and most reliable information is available at the early stages of material production. For example, survey data are available for production of zinc ore concentrates and refined slab zinc. In certain cases, such as for lead and zinc, the end use of the material is also well understood. However, the flow of material from refining operations through manufacturing facilities to end use in products is difficult to track. End uses of cadmium and nickel are based on industry association estimates and are considered not as well characterized as those of lead and zinc. In addition to the Minerals Yearbooks, the USGS also publishes a number of materials flow analyses, recycling assessments, and other special reports. All of this data provides an excellent base from which to build models of the flows of individual metals. These data were used to create the metal specific make, use, and final demand tables for cadmium, lead, nickel, and zinc. In many cases missing flows could be imputed from other values provided by the USGS. Additional data gaps were filled with values obtained from peer- reviewed articles (Gordon, et al. '03, Gordon, et al. '04, Graedel, et al. '05, Hawkins '06a), U.S. Census Bureau Industry Reports (USCB '02a, b), and the U.S. Foreign Trade Database (US DoC '99). Figure 1 provides an overview of the normalized MUIO matrices. The make table is made up of the monetary transactions sectors (D’), together with make tables for each of the physical commodities cadmium, lead, nickel, and zinc. Within each of the normalized 4
  5. 5. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 physical transactions make tables, transactions are measured in tonnes metal produced in a commodity per unit output of metal by the industry. Elements outside of the partitions made by the boundaries of the individual metal / monetary transaction industries and commodities are zero. The use matrix is made up of a series of use matrices for each of the metals and one for the dollar transaction sectors. For example, use of nickel commodities by nickel transactions industries is tracked in PNi. Usage of metal commodities by monetary transaction industries is found in the downstream requirements partitions labeled CD. The direct supply chains of metal transaction industries are found in the upstream requirements (or supply chains) partitions labeled CU. Final demand vectors and value added are represented in yellow. Final demand for the monetary transactions sectors is measured in dollars (lower rows) while final demand for the physical transactions sectors is measured in tonnes of metal. Row sums of the use table (before normalization) together with the row sums of the final demand table yields total commodity output (q). Value added is represented in below the use table. In monetary IO tables, value added is generally used to balance the use table. That is the column sums of the use table together with the column sums of value added is equal to total industry output or the row sums of the make table. However, because units in the MUIO model are not consistent across commodities, total industry output cannot be calculated from the use table. Monetary value added includes labor payments, taxes, and other value added. Additional rows representing material flows external to the economy under consideration were used to balance the physical tables. These included metal extraction from the environment, scrap, and other unaccounted for material (generally assumed to be wastes and environmental releases). 5
  6. 6. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 The monetary transactions sectors B’ and D’ are imputed from the values provided in the 1997 U.S. Benchmark IO tables by removing the dollar values of flows that have been replaced by physical flows in the additional metal sectors. Monetary values of physical flows are calculated as the product of the mass of the physical flow and the average 1997 price. The value of metal in compound commodities is assumed to be equal to that of the metal itself. In most cases the physical transaction commodities represented in the model are early in the supply chain of their end use products and so the differences in price should not have a large effect. [Figure 1] Calculation of the total requirements matrix from the make and use tables (BEA '02) was performed following the procedure used by the U.S. Bureau of Economic Analysis for its 1997 Benchmark Model. A special adjustment is made to correct for the production of scrap. Scrap is separated from the make table in order to prevent the use of scrap from stimulating additional activity by the industry in which it was produced. This is accomplished by creating an industry by one vector of scrap output (h) and setting all production of the scrap commodity in the make table equal to zero. After this adjustment the total industry output can be calculated as the sum of the rows of the make table together with the scrap output of each sector. g = Vi + h 1 An industry by one column vector of the ratio of the value of scrap produced by each industry by the total output of the industry is defined. p = g −1 h ˆ 2 The normalized make and use matrices are calculated as before. B = Ug −1 ˆ 3 D = Vq −1 ˆ 4 The normalized make matrix is modified to account for the proportion of the total output of the commodity that is produced by each industry adjusted for the value of scrap. 6
  7. 7. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 W = (I - p) -1 D ˆ 5 Here the adjusted make matrix (W) is used to calculate the industry by commodity total requirements. -1 6 Industry by Commodity Total Requirements = W(I – BW) The MUIO Industry-by-Commodity Total Requirements matrix provides an opportunity to calculate the economy-wide material intensity of material use. In this analysis the MUIO- LCA total requirements matrix is used to provide guidance on supply chain consumption of cadmium, lead, nickel, and zinc per dollar of output for each of the 483 monetary transaction commodities included in the MUIO-LCA model. Results from the MUIO-LCA Model Entries in the rows of the Industry-by-Commodity Total Requirements Matrix corresponding to the output of the physical industries indicate the use of cadmium, lead, nickel, and zinc throughout the supply chain of the 483 commodities of the 1997 Benchmark Model. In Table 1 through Table 4 results are presented for the top ten sectors in terms of material intensity per dollar of additional final demand. [Table 1] [Table 2] [Table 3] [Table 4] Sectors with high material use per dollar of commodity output are a good place to focus efforts to reduce metals use. These sectors offer an opportunity to conserve resources and reduce environmental impacts with the least amount of adverse economic impact. Consider for example lead use per dollar commodity output. A large ratio of lead use per 7
  8. 8. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 dollar commodity output indicates that the contribution of lead to the total value of the commodity is small. Therefore an investment toward reducing the amount of lead used throughout the supply chain of the commodity should not have a large relative impact on the price of the commodity. The application of the material use to dollar value ratio for environmental policy prioritization is most appropriate for resolving problems related to supply availability or the environmental burdens associated with material production. Environmental burdens for primary material are caused by material extraction and processing. Collection, transportation, and remanufacturing are the biggest causes of concern in the case of secondary material. In Table 1, we find that power-driven handtool manufacturing (333991) consistently demonstrates the most intense supply chain use of lead per dollar final demand. Roughly 4.0 grams of lead in ores and base bullion are consumed to produce one dollar of output of power-driven handtools. Of this material, 3.2 grams per dollar enters the supply chain as refined soft lead and lead in alloys produced by primary lead smelters (column 2). An additional 9.3 grams of secondary lead enters the power-driven handtool supply chain per dollar spent. Most of this material, 12 g/$, is contained in lead-acid storage batteries used throughout the supply chain. Presumably the remaining 0.5 grams of lead per dollar is included in other parts of the power-driven handtools, consumed by the processes used to produce them, or disposed of as waste. Upon inspection of Table 1 we find that use of lead in lead-acid batteries dominates lead- use in many products. In fact the US Geological Survey estimates that 88% of lead produced in 1997 was used in the manufacture of lead-acid batteries (USGS '98). Lead in batteries dominates the use of lead in elevator and moving stairway manufacturing (333921), lawn and garden equipment manufacturing (333112), boat building (336612), hand and edge tool manufacturing (332212), motor home manufacturing (336212), and rolling mill and other metalworking machinery (33351A). In addition animal production, except cattle, poultry, and eggs (112A00), sugarcane and sugar beet farming (1119A0), and 8
  9. 9. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 cattle ranching and farming (112100) appear in the top 10 sectors for use of lead in lead- acid storage batteries per dollar. Certain sectors use lead in other forms. Jewelry and silverware manufacturing (339910) likely consumes lead in metal alloys and in solder. Dental laboratories (339116) and dental equipment and supplies manufacturing (339114) both have complicated supply chains in which lead is consumed in the production of equipment and other supplies. Some sectors appear in the use of multiple materials. Jewelry and silverware (339910) appears near the top of the list for all four of the metals described here. Dental laboratories (339116) and dental equipment and supplies manufacturing (339114) are in the top 10 lists for lead, nickel, and zinc. High cadmium and nickel intensity is calculated for the storage battery manufacturing (335911). The highest level of consumption occurred for jewelry and silverware manufacturing which reported an overall zinc consumption rate of 39 grams per dollar. In general smaller values were reported for top cadmium consuming sectors than for lead, nickel, or zinc. Low values are caused by small metal flows or large dollar values of products. Because the IO 1997 commodities include a number of sub-commodities it is likely that low values for cadmium reflect the small fraction of the total flows in each sector made up of products containing cadmium. For example, the flow of cadmium per dollar spent on NiCd batteries should be high. However the supply chain flow of cadmium per dollar spent on storage batteries is small. This is because NiCd batteries only account for a small portion of the total dollar value of storage batteries. This highlights the effect of commodity definitions on MUIO-LCA results. So far we have presented the intensity of material use per dollar spent for the monetary transactions sectors in the MUIO-LCA model. However, many of these sectors include products with which the typical consumer is unfamiliar because they occur early on in the supply chains of more familiar products. We would like to provide guidance on products which consumers choose to purchase directly. This can be done by filtering for products 9
  10. 10. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 with a high percentage of personal consumption expenditures (PCE). Personal consumption expenditure in each sector is tracked in the final demand portion of the 1997 U.S. Benchmark Account. Total domestic consumption (DC) can be calculated as: DC = q + eimports – eexports where DC is Domestic Consumption, q is Total Commodity Output eimports is imports, and eexports is exports. A summary of total material use (primary and secondary) for the top 10 sector in terms of material intensity together with the personal consumption expenditures, domestic consumption, and PCE/DC ratio for each metal can be found in Table 5 through Table 8. We can see that many of the sectors appearing in the top 10 have very small percentages of personal consumption expenditure. [Table 5] [Table 6] [Table 7] [Table 8] In Figure 2 we present the distribution of sectors by their PCE/DC ratio. We find that roughly 65% of the sectors have PCE/DC ratios less than 0.2. The percentage of commodity sectors increases roughly linearly for sectors with PCE/DC ratios between 0.2 and 1.0. Nine sectors have a PCE/DC ratio slightly greater than one. Although this is unexpected, it is likely due to special exceptions in the way monetary transactions are accounted for in these sectors. These 9 sectors are other amusement, gambling, and recreation industries (713A00); other ambulatory health care services (621B00); museums, historical sites, zoos, and parks (712000); funds, trusts, and other financial vehicles (525000); elementary and secondary schools (611100); home health care services (621600) Hospitals (622000); colleges, universities, and junior colleges (611A00); and other accommodations (721A00). 10
  11. 11. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 [Figure 2] The top 10 total material use (primary and secondary) per dollar sectors with PCE/DC ratios greater than 0.2 for cadmium, lead, nickel, and zinc can be found in Table 9. We can see that power-driven handtools (333991) still appear at the top of the list for lead and jewelry and silverware (339910) are still in the top two across the four metals. However, certain sectors appear in these lists which did not appear in the overall top 10. Kitchen utensil, pot, and pan manufacturing (332214) and household cooking appliance manufacturing (335221) appear in the list for zinc. Automobile and light truck manufacturing (336110) appears in the list for lead. Watch, clock, & other measuring & controlling device mfg. (33451A) appears in the lists for zinc, nickel, and cadmium. 11
  12. 12. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 In Figure 3 we present the distribution of supply chain material use per dollar for cadmium, lead, nickel, and zinc overall and for sectors with PCE/DC ratios greater than 0.2. As expected the distributions for the filtered results decrease more steeply with rank than the overall results. However, the top sectors for each metal have material intensities of roughly the same magnitude as the overall results. Overall the material intensity of zinc use is slightly higher for the highest ranked sectors, however near the 50th percentile overall lead and zinc intensity are within the same order of magnitude. The material intensities for lead and zinc consuming sectors with PCE/DC ratios greater than 0.2 are generally within the same order of magnitude across ranks. Material intensities for cadmium and nickel sectors with PCE/DC ratios greater than 0.2 decrease significantly more quickly than the overall results. [Figure 3] The inverse prices of refined cadmium, lead, nickel, and zinc are provided in Table 10 for comparison with the results of our study. We would expect to observe a supply chain consumption of metal in ore per dollar value greater than or equal to the inverse price for the supply chain of the refined metal commodity itself. This is not observed because inputs for the metal commodities themselves in the MUIO-LCA model are measured in tonnes. The inverse price represents an effective limit for the use of refined metal in products. Nickel use in storage battery manufacturing is valued at 7 g/$, roughly 17% of the inverse price of nickel. This indicates that the value of nickel is a large fraction of the value of storage battery output. Recall that a specific physical flow sector has been created in the MUIO-LCA model to account for the flow of lead-acid batteries. Thus the storage battery manufacturing sector represents only flows of storage batteries other than lead- acid. [Table 10] 12
  13. 13. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Limits and Uncertainty in the MUIO-LCA Model Some aspects of the model itself should be discussed. Results of the model are affected by certain assumptions and simplifications made in its development. Two items are important to the results discussed here, aggregation of IO 1997 sectors and the assumptions made in creating the downstream use of physical commodities. The sectors used in the 1997 U.S. Benchmark Accounts are created by aggregating together a number of similar products. In some cases however these sectors include a wider variety of products. For example, iron and steel mills (331111) includes 19 commodities such as coke oven products ; pig iron; slag; iron and steel powders, paste, and flakes; steel ingots; hot rolled steel sheet and strip; steel bars, steel pipes and tubes; and steel rails. In other cases the specific products are difficult to define. For example, 99.5% of primary nonferrous metal, except copper and aluminum (331419) is classified in the 1997 U.S. Benchmark detailed item output as primary nonferrous metals, not elsewhere classified (331419T). This aggregation and uncertainty muddies the connections between material consumption and specific products. Another aspect of the model that introduces error to our results is the assumption we have made in assigning the downstream consumption of physical commodities. In the development of the MUIO account, rows of the 1997 U.S. Benchmark use table were used to estimate downstream consumption of physical commodities. Each physical flow commodity was mapped to the most closely related 1997 U.S. Benchmark commodity. The row was then inspected and modified by zeroing out entries for which no flow of the physical commodity was expected. The dollar transactions remaining in the row (including the final demand sectors) were summed and each was divided by the total remaining transactions to provide a percentage. Physical flows to the monetary sectors of the economy were then distributed according to these percentages. This method relies on our judgements about the flow of materials into the monetary sectors. The strengths of this method are that it captures the complexity of flows in the 13
  14. 14. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 economy and that it matches closely the form of the original 1997 U.S. Benchmark Model. The primary weakness is that when certain flows are not zeroed out for a given metal the distribution of its use becomes more like the average use of the 1997 U.S. Benchmark commodity leading to results which overestimate the use of certain metals in applications which may in fact involve higher consumption of another metal. Thus use of this second group of metals would be underestimated. Another important clarification to make is that the dollar flows associated with the added physical flow sectors have been removed from the monetary transactions portion of the MUIO make and use tables. In the case of lead, the value of lead flows into storage battery manufacturing (335911) has been removed and replaced with a physical flows of lead to a lead-acid battery manufacturing sector whose output is measured in tonnes of lead contained in lead-acid batteries. Thus the remaining value in the storage battery manufacturing sector (335911) pertains primarily to sales of nickel metal hydride, nickel cadmium, and lithium ion battery chemistries. Discussion We have demonstrated how a mixed-unit input-output model could be used to determine the material intensity in terms of material use per unit economic value of a product. Material intensity was calculated for each of the 483 commodities of the 1997 U.S. Benchmark Model. Material intensity can be used as a scoping tool for prioritization of environmental policy. High material use per dollar indicates that a large portion of the overall value of a product is associated with the value of the material from which it is made. In the case of materials for which we would like to decrease use, these products likely offer opportunities to substitute the material currently used with another material. For example, we find that the material intensity of cadmium, lead, nickel, and zinc is high in jewelry and silverware manufacturing. These products are long-lived and purchased relatively infrequently. Policy measures encouraging the substitution of these metals in this sector could reduce material consumption with minimal disruption to the economy. However, it is important to maintain perspective on the magnitude of material flows. 14
  15. 15. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Although this reduction might be made with little disruption, it would have only a small impact on the total flows of these materials. In other cases policy-makers may decide that sectors with high material intensity in fact represent important uses of the material. In these cases action could be taken to encourage proper use and disposal of the material. Knowing the material intensity of certain sectors could also help predict and mitigate the possible consequences of policies which increase the costs associated with the use of a material. For example, we have shown that lead, specifically lead-acid batteries, is important to various agricultural activities. However, policy-actions which increase the cost of storage batteries could have a significant impact on agriculture. Because a large fraction of lead is sourced from recycled material and because the recycle rate is high (~80%), continuing the use of lead-acid batteries in agriculture while it is discouraged elsewhere could reduce the negative impacts of the transition. Calculating material intensities of materials of interest is important to understanding the impacts of policies intended to reduce their use. The simple calculation of material intensity can also be used to predict the sectors which would be impacted most by decreases in the availability or increases in the prices of select materials. For example, we would expect a policy which imposes more stringent regulations on secondary lead smelters to have the greatest effect on the price of power-driven handtools (333991), elevators and moving stairways (333921), jewelry and silverware (339910), and lawn and garden equipment (333112). Similarly a shortage of zinc would have the greatest impact on personal consumption of jewelry and silverware (339910); motorcycles, bicycles, & parts (336991); watch, clock, and other measuring and controlling devices (33451A); electric lamp bulbs and parts (335110); heating equipment, except warm air furnaces (333414); and household laundry equipment (335224). By explicitly representing metal commodities at early stages in the product supply chain the MUIO model provides a clearer picture of the material requirements and intensity for 15
  16. 16. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 sectors of the economy. Care should be taken in interpreting the material intensities calculated using the MUIO model for several reasons. Most of these we have already mentioned. First several metal commodities are often lumped into a single commodity sector, such copper, nickel, lead, and zinc mining (212230) or primary nonferrous metal, except copper and aluminum (331419). Although a list of detailed item output by commodity is available as a supplement to the 1997 U.S. Benchmark Input Output Account, even the detailed information is not specific enough to determine specific materials. For example, 99.5% of primary nonferrous metal, except copper and aluminum (331419) is classified in the 1997 U.S. Benchmark detailed item output as primary nonferrous metals, not elsewhere classified (331419T). Second, the method we have used to create the downstream use of metals assumes that the use of each metal commodity is similar to the dollar transactions for the most closely related 1997 Benchmark sector. In cases where we have improved information flows are manually set to zero. Material is then allocated across the remaining 1997 Benchmark industry and final demand sectors according to the percentages of the total remaining dollar transactions. Allocating in this way causes the model to yield certain metal flows which reflect the average for the associated sector rather than the actual flows which might be slightly higher or lower. Third, the material intensities calculated with the MUIO model do not correspond to the size or hazard associated with each sector. A high material intensity indicates that the amount of material consumed throughout the supply chain of a product is large compared with the producer price of the product. This metric is useful for minimizing the impact of measures to reduce material use. It is also useful for identifying products whose supply chains consume large amounts of material per unit value in the final product. However, in certain cases reducing the overall flow of a material will require reducing flows in low material intensity applications. For example, reducing the use of zinc significantly would necessarily involve reductions in zinc used for galvanizing or protecting steel against corrosion. Galvanizing is included in iron and steel mills (331111) which do not appear in 16
  17. 17. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 the top 10 sectors for zinc intensity. Nonetheless, this sector is important to significantly reducing zinc use. This example also demonstrates the impact of sectoral aggregation. In fact, the material intensity of zinc use in the galvanizing process is likely high. However, because galvanizing accounts for only a small fraction of the total receipts by iron and steel mills the zinc intensity is low. In other cases the hazard associated with a low material intensity is sufficiently high to warrant action. For example, the use of lead as a gasoline additive would not be indicated by a high material intensity, however the risk associated with airborne lead resulting from combustion of leaded fuel is high. Despite these complications, the use of mixed-unit input-output accounts to determine the material intensity of products is an important tool for performing analyses related to resource economics and industrial ecology. By combining monetary input-output accounts with material flow data the MUIO-LCA model is capable of providing a more complete picture of the supply chains of products and processes than either monetary input-output analysis or material flow analysis alone. Reducing material consumption in the supply chains of products targeted based on a high material intensity allows for efficient steps toward dematerialization of an economy. Reduced material use is accompanied by reduced environmental degradation, releases of toxic material, and energy consumption. Identifying and examining material intense sectors allows us to focus our efforts on sectors which consume a large amount of material per unit product value. Focusing on these sectors could help improve the economic efficiency of dematerialization efforts. 17
  18. 18. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 References 1. ATSDR (1999): Toxicological Profile for Cadmium. Agency for Toxic Substances and Disease Registry. City. p 400. 2. ATSDR (2004a): Health Consultation: Bunker Hill Mining and Metallurgical, Kellogg, Shoshone County, Idaho. ATSDR. 3. ATSDR (2004b): Public Health Assessment: Martin Aaron, Incorporated, Camden City, Camden County, New Jersey. ATSDR. 6/23/2004. 4. ATSDR (2004c): Minimal Risk Levels. Agency for Toxic Substances and Disease Registry. <http://www.atsdr.cdc.gov/mrllist_03_04.pdf > 5. Audry S, Blanc G, Schafer J (2004): Cadmium Transport in the Lot-Garonne River System (France) - Temporal Variability and a Model for Flux Estimation. Science of the Total Environment. 319 (1-3) 197-213. 6. Ayres RU, Kneese AV (1969): Production, Consumption and Externalities. American Economic Review. 59 282-97. 7. Ayres RU, Ayres LU (2001): Handbook of Industrial Ecology. Edward Elgar Publishing Ltd.: Cheltenham, UK. 8. Baccini P, Brunner PH (1991): Metabolism of the Anthroposphere. Springer: Berlin. 9. Bailey R, Allen JK, Bras B (2004a): Applying Ecological Input-Output Flow Analysis to Material Flows in Industrial Systems Part I: Tracing Flows. Journal of Industrial Ecology. 8 (1-2) 45-68. 10. Bailey R, Bras B, Allen J (2004b): Applying Ecological Input-Output Flow Analysis to Material Flows in Industrial Systems Part Ii: Flow Metrics. Journal of Industrial Ecology. 8 (1-2) 69-91. 11. BEA (2002): 1997 Benchmark Input-Output Accounts of the United States. <http:// www.bea.gov/bea/dn2/home/benchmark.htm> (Accessed: March 21). 12. Bullard C, Herendeen R (1975): Energy Impact of Consumption Decisions. Proceedings of the IEEE. 63 (3) 484- 93. 13. Bullard C, Penner P, Pilati D (1978): Net Energy Analysis: Handbook for Combining Process and Input-Output Analysis. Resources and Energy. 1 (3) 267-313. 14. Casler S, Wilbur S (1984): Energy Input Output Analysis - a Simple Guide. Resources and Energy. 6 (2) 187-201. 15. Duchin F, Lange G (1991): Strategies for Environmentally Sound Economic Development: An Input-Output Analysis. IEEE Power Engineering Review. June 16-18. 16. Duchin F (1992): Industrial Input-Output Analysis: Implications for Industrial Ecology. Procedings of the National Academy of Science. 89 851-55. 17. Duchin F (2004a): Input-Output Economics and Material Flows. Rensselaer Polytechnic Institute. December 2004. <www.rpi.edu/dept/economics/www/workingpapers/> 18
  19. 19. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 18. Duchin F (2004b): Input-Output Economics and Material Flows. <http://www.economics.rpi.edu/www/workingpapers/rpi0424.pdf> (Accessed: April 2006). 19. EC (1983): Limits on Cadmium Discharges 83/513/Eec. 20. EPA (1990): Clean Air Act. <http://www.epa.gov/air/caa/> (Accessed: 4/9/07). 21. EPA (1993): Locating and Estimating Air Emissions from Sources of Cd and Cd Compounds. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards: Research Triangle Park, NC. 22. EPA (1997): Implementation of the Mercury Containing and Rechargeable Battery Management Act. U.S. Environmental Protection Agency. Washington, D.C. <http://www.epa.gov/epaoswer/hazwaste/recycle/battery.pdf> (Accessed: 4/9/07) 23. EPA (2005a): Priority Chemicals and Fact Sheets Website. <http://www.epa.gov/epaoswer/hazwaste/minimize/chemlist.htm> (Accessed: 1/3/05). 24. EPA (2005b): Integrated Risk Information System. U.S. Environmental Protection Agency. 25. Giljum S, Hubacek K (2004): Alternative Approaches of Physical Input-Output Analysis to Estimate Primary Material Inputs of Production and Consumption Activities. Economic Systems Research. 16 (3) 301-10. 26. Giljum S, Behrens A, Hinterberger F, et al. (2005a): Mosus Project Scenario Evaluation Component: Materials Extraction. Sustainable Europe Research Institute (SERI). Vienna. 27. Giljum S, Hinterberger F, Lutz C, et al. (2005b): Modeling Global Resource Use: Material Flows, Land Use, and Input-Output Models. In Handbook of Input-Output Economics in Industrial Ecology. 28. Gordon R, Graedel T, Bertram M, et al. (2003): The Characterization of Technological Zinc Cycles. Resources Convervation and Recycling. 39 (2) 107-35. 29. Gordon R, Lifset R, Bertram M, et al. (2004): Where Is All the Zinc Going: The Stocks and Flows Project, Part 2. Journal of Minerals. 24-29. 30. Graedel T, et al. (2005): The Multilevel Cycle of Anthropogenic Zinc. Journal of Industrial Ecology. 9 (3) 67-90. 31. Hannon B, Stein RG, Segal BZ, et al. (1978): Energy and Labor in Construction Sector. Science. 202 (4370) 837-47. 32. Hawkins T (2006a): Closing the Loop on Cadmium: An Assessment of the Material Cycle of Cadmium in the U.S. International Journal of Life Cycle Assessment. 11 (1) 38-48. 33. Hawkins T, Hendrickson CT, Higgins C, et al. (2006b): A Mixed-Unit Input- Output Model for Environmental Life-Cycle Assessment and Material Flow Analysis. Environmental Science & Technology. 41 (3) 1024-31. 34. Herendeen RA (1978): Input-Output Techniques and Energy Cost of Commodities. Energy Policy. 6 (2) 162-65. 35. Higgins C, Matthews H, Hendrickson C, et al. (2007): Lead Demand of Future Vehicle Technologies. Transportation Research Part D. 12 103-14. 19
  20. 20. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 36. Hoekstra R (2003): Structural Change of the Physical Economy: Decomposition Analysis of the Physical and Hybrid Input-Output Tables. Free University. Amsterdam. 37. Kneese AV, Ayres RU, d'Arge RC (1970): Economics and the Environment: A Material Balance Approach. Resources for the Future: Washington D.C. 38. Konijn P, de Bohr S, van Dalen J (1997): Input-Output Analysis of Material Flows with Applications to Iron, Steel and Zinc. Structural Change and Economic Dynamics. 8 129-53. 39. Leontief W (1970): Environmental Repercussions and the Economic Structure: An Input-Output Approach. The Review of Economics and Statistics. 52 (3) 262-71. 40. Lin XaKRP (1998): Input-Output Modeling of Production Processes for Business Management. Structural Change and Economic Dynamics. 9 205-26. 41. NRC (1980): Lead in the Human Environment. National Academy Press: Washington, DC. 42. NRC (1993): Measuring Lead Exposure in Infants, Children and Other Sensitive Population. National Academy Press: Washington, DC. 43. NRC (2004): Material Count: The Case for Material Flows Analysis. p 144. 44. OSHA (1992): Occupational Exposure to Cadmium. U.S. Occupational Safety and Health Administration. <http://www.osha.gov/Publications/osha3136.pdf> 45. Smith T (1995): Recycling and Other Regulatory Requirements Affecting Battery Technologies. Proc of the Symp on Electrochemical Technology Applied to Environ Problems. Reno, Nv - Electrochemical Society Pv. In. 46. Stempel R, Ovshinsky S, Gifford P, et al. (1998): Nickel-Metal Hydride: Ready to Serve. IEEE Spectrum. 35 (11) 29-34. 47. Suh S (2004a): Functions, Commodities and Environmental Impacts in an Ecological-Economic Model. Ecological Economics. 48 (4) 451-67. 48. Suh S, et. al. (2004b): System Boundary Selection in Life-Cycle Inventories Using Hybrid Approaches. Environmental Science & Technology. 38 (3) 657-63. 49. Suh S, Huppes G (2004c): Methods for Life Cycle Inventory of a Product. Journal of Cleaner Production. 13 687-97. 50. Takase K, Kondo Y, Washizu A (2005): An Analysis of Sustainable Consumption by Thewaste Input-Output Model. Journal of Industrial Ecology. 9 (1-2) 201-19. 51. Ui J (1992): Industrial Pollution in Japan. United Nations University Press: Tokyo, Japan. 52. US DoC (1999): U.S. Exports History and U.S. Imports History on Cd-Rom. U.S. Department of Commerce, Economic and Statistics Administration, U.S. Census Bureau. Washington, D.C. 53. USCB (2002a): 1997 Economic Census, Mining Industry Reports Series. U.S. Census Bureau. <http://www.census.gov/prod/www/abs/97ecmini.html> 54. USCB (2002b): 1997 Economic Census, Manufacturing Industry Reports Series. U.S. Census Bureau. <http://www.census.gov/prod/www/abs/97ecmini.html> 55. USGS (1998): Minerals Yearbook 1997: Vol. I Metals and Minerals. <http://minerals.usgs.gov/minerals/pubs/commodity/myb/> (Accessed: June 2006). 20
  21. 21. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 56. Weisz H, Duchin F (2004): Physical and Monetary Input-Output Analysis: What Makes the Difference? <http://www.economics.rpi.edu/www/workingpapers/rpi0422.pdf> (Accessed: April 2006). 21
  22. 22. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Tables and Figures 22
  23. 23. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Commodities Industries PNi NORMALIZED CD Total Commodity Output (q) (t Ni/t Ni) USE (t Ni/$) $ Final Demand (e’$) P Final Demand (e’P) PZn CD Commodities (t Zn/t Zn) (t Zn/$) PPb CD (t Pb/t Pb) (t Pb/$) PCd CD (t Cd/t Cd) (t Cd/$) CU CU CU CU B' ($/t Ni) ($/t Zn) ($/t Pb) ($/t Cd) ($/$) DPNi NORMALIZED Total Industry Output (g) t Ni ( /t Ni) MAKE P D Zn (t Zn/t Zn) Industries DPPb t Pb ( /t Pb) DPCd t Cd ( /t Cd) D' ($/$) Value Added Total Commodity Output (q) Figure 1. Structure of make and use accounting framework used for the MUIO-LCA model. 23
  24. 24. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 24
  25. 25. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Table 1. Top 10 lead consuming sectors, all values provided in grams per dollar. Ores & base Primary Lead Secondary Lead New Lead-Acid bullion (mine Storage production) Batteries Power-driven 4 Power-driven 3.2 Power-driven 9.3 Power-driven 12 handtool mfg handtool mfg handtool mfg handtool mfg (333991) (333991) (333991) (333991) Elevator & moving 3.2 Elevator & moving 2.5 Elevator & moving 7.5 Elevator & 9.8 stairway mfg stairway mfg stairway mfg moving stairway (333921) (333921) (333921) mfg (333921) Lawn & garden 2.0 Lawn & garden 1.6 Jewelry & 6.6 Lawn & garden 6.1 equip. mfg (333112) equip. mfg silverware mfg equip. mfg (333112) (339910) (333112) Jewelry & 1.3 Jewelry & 1.0 Lawn & garden 4.7 Boat bldg 2.8 silverware mfg silverware mfg equip. mfg (336612) (339910) (339910) (333112) Boat bldg (336612) 0.9 Boat bldg 0.7 Secondary 4.3 Motor home mfg 2.7 2 (336612) 2 processing of other (336213) nonferrous (331492) Motor home mfg 0.8 Motor home mfg 0.7 Nonferrous metal, 3.9 Hand & edge tool 2.0 (336213) 9 (336213) exc. Cu & Al, mfg (332212) shaping (331491) Secondary 0.8 Secondary 0.6 Dental laboratories 2.7 Rolling mill & 1.9 processing of other 4 processing of other 6 (339116) other nonferrous (331492) nonferrous metalworking (331492) machinery (33351A) Nonferrous metal, 0.7 Nonferrous metal, 0.6 Dental equip. & 2.2 Animal 1.5 exc. Cu & Al, 6 exc. Cu & Al, supplies mfg production, exc. shaping (331491) shaping (331491) (339114) cattle & poultry & eggs (112A00) Hand & edge tool 0.6 Hand & edge tool 0.5 Boat bldg 2.1 Sugarcane & 1.4 mfg (332212) 6 mfg (332212) 2 (336612) sugar beet farming (1119A0) Rolling mill & other 0.6 Rolling mill & 0.5 Motor home mfg 2.1 Cattle ranching & 1.4 metalworking 4 other (336213) farming (112100) machinery (33351A) metalworking machinery (33351A) 25
  26. 26. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Table 2. Top 10 zinc consuming sectors, all values provided in grams per dollar. Zn Mining Primary Zn Secondary Zn Jewelry & silverware 17 Jewelry & silverware 17 Jewelry & silverware 22 mfg (339910) mfg (339910) mfg (339910) Secondary processing 11 Secondary 11 Secondary 14 of other nonferrous processing of other processing of other (331492) nonferrous (331492) nonferrous (331492) Nonferrous metal, exc. 11 Nonferrous metal, 11 Nonferrous metal, 13 Cu & Al, shaping exc. Cu & Al, exc. Cu & Al, (331491) shaping (331491) shaping (331491) Primary nonferrous 8.8 Primary nonferrous 8.8 Primary nonferrous 11 metal, exc. Cu & Al metal, exc. Cu & Al metal, exc. Cu & Al (331419) (331419) (331419) Dental laboratories 6.9 Dental laboratories 6.9 Dental laboratories 8.7 (339116) (339116) (339116) Ferroalloy & related 6.1 Ferroalloy & related 6.1 Dental equip. & 7.2 product mfg (331112) product mfg supplies mfg (331112) (339114) Dental equip. & 5.8 Dental equip. & 5.8 Ferroalloy & related 6.3 supplies mfg (339114) supplies mfg product mfg (339114) (331112) Cu rolling, drawing, & 3.5 Cu rolling, drawing, 3.5 Cu rolling, drawing, 4.7 extruding (331421) & extruding & extruding (331421) (331421) Primary smelting & 3.1 Primary smelting & 3.1 Primary smelting & 4.2 refining of Cu refining of Cu refining of Cu (331411) (331411) (331411) Other Al rolling & 2.5 Other Al rolling & 2.5 Other Al rolling & 2.7 drawing (331319) drawing (331319) drawing (331319) 26
  27. 27. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Table 3. Top 10 nickel consuming sectors, all values provided in grams per dollar. Nickel Mining Primary Nickel Secondary Nickel Storage battery mfg 6.8 Storage battery mfg 6.2 Jewelry & silverware 2.2 (not incl. lead-acid) (not incl. lead-acid) mfg (339910) (335911) (335911) Jewelry & silverware 3.2 Jewelry & silverware 2.9 Secondary 1.4 mfg (339910) mfg (339910) processing of other nonferrous (331492) Secondary processing 2.1 Secondary 1.9 Nonferrous metal, 1.1 of other nonferrous processing of other exc. Cu & Al, (331492) nonferrous (331492) shaping (331491) Nonferrous metal, exc. 1.9 Nonferrous metal, 1.8 Primary nonferrous 1.0 Cu & Al, shaping exc. Cu & Al, metal, exc. Cu & Al (331491) shaping (331491) (331419) Primary nonferrous 1.6 Primary nonferrous 1.5 Dental laboratories 0.87 metal, exc. Cu & Al metal, exc. Cu & Al (339116) (331419) (331419) Ferroalloy & related 1.4 Ferroalloy & related 1.2 Ferroalloy & related 0.84 product mfg (331112) product mfg product mfg (331112) (331112) Dental laboratories 1.3 Dental laboratories 1.2 Dental equip. & 0.72 (339116) (339116) supplies mfg (339114) Dental equip. & 1.1 Dental equip. & 0.9 Ferrous metal 0.26 supplies mfg (339114) supplies mfg 6 foundaries (331510) (339114) Cu rolling, drawing, & 0.7 Cu rolling, drawing, 0.7 Iron & steel mills 0.24 extruding (331421) 8 & extruding 1 (331111) (331421) Primary smelting & 0.7 Primary smelting & 0.6 Al foundries 0.24 refining of Cu 0 refining of Cu 4 (33152A) (331411) (331411) 27
  28. 28. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Table 4. Top 10 cadmium consuming sectors, all values provided in grams per dollar. Cd Mining (together Cd Recovery (from Secondary Cd, with Pb & Zn) primary Zn INMETCO smelting) Storage battery mfg 0.20 Storage battery mfg 0.18 Cutting tool & 0.015 (not incl. lead-acid) (not incl. lead-acid) machine tool (335911) (335911) accessory mfg (333515) Jewelry & silverware 0.078 Jewelry & 7.2E-02 Secondary 0.014 mfg (339910) silverware mfg processing of other (339910) nonferrous (331492) Secondary processing 0.051 Secondary 4.8E-02 Primary battery mfg 5.7E-03 of other nonferrous processing of other (335912) (331492) nonferrous (331492) Nonferrous metal, exc. 0.046 Nonferrous metal, 4.3E-02 All other forging & 2.9E-03 Cu & Al, shaping exc. Cu & Al, stamping (33211A) (331491) shaping (331491) Ferroalloy & related 0.034 Ferroalloy & related 3.1E-02 Metal heat treating 2.3E-03 product mfg (331112) product mfg (332811) (331112) Dental laboratories 0.031 Dental laboratories 2.9E-02 Hardware mfg 1.3E-03 (339116) (339116) (332500) Dental equip. & 0.026 Dental equip. & 2.4E-02 Special tool, die, jig, 1.3E-03 supplies mfg (339114) supplies mfg & fixture mfg (339114) (333514) Ferrous metal 0.01 Ferrous metal 9.7E-03 Al foundries 1.2E-03 foundaries (331510) foundaries (331510) (33152A) Iron & steel mills 9.9E-03 Iron & steel mills 9.2E-03 Oil & gas field 1.2E-03 (331111) (331111) machinery & equip. (333132) Primary battery mfg 9.4E-03 Primary battery mfg 8.8E-03 Lawn & garden 1.1E-03 (335912) (335912) equip. mfg (333112) 28
  29. 29. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Table 5. Total primary and secondary zinc use summary. Description Material Personal Cons. Domestic PCE / Use, g/$ Exp.* (PCE), Consumption DC million $ (DC), million $ Jewelry and silverware manufacturing 39 19,000 21,000 87% (339910) Secondary processing of other nonferrous 25 - 1,200 0% (331492) Nonferrous metal, except copper and 24 57 7,300 1% aluminum, shaping (331491) Primary nonferrous metal, except copper 20 - 10,000 0% and aluminum (331419) Dental laboratories (339116) 16 - 3,000 0% Dental equipment and supplies 13 - 2,300 0% manufacturing (339114) Ferroalloy and related product 12 - 2,300 0% manufacturing (331112) Copper rolling, drawing, and extruding 8.2 - 8,800 0% (331421) Primary smelting and refining of copper 7.3 - 8,100 0% (331411) Other aluminum rolling and drawing 5.2 - 750 0% (331319) 29
  30. 30. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Table 6. Total primary and secondary lead use summary. Description Material Personal Cons. Domestic PCE / Use, g/$ Exp.* (PCE), Consumption DC million $ (DC), million $ Power-driven handtool manufacturing (333991) 13 1,000 4,100 25% Elevator and moving stairway manufacturing (333921) 10 - 1,600 0% Jewelry and silverware manufacturing (339910) 7.6 19,000 21,000 87% Lawn and garden equipment manufacturing (333112) 6.2 620 6,100 10% Secondary processing of other nonferrous (331492) 5 - 1,200 0% Nonferrous metal, except copper and aluminum, shaping (331491) 4.5 57 7,300 1% Dental laboratories (339116) 3.1 - 3,000 0% Boat building (336612) 2.9 4,200 5,400 78% Motor home manufacturing (336213) 2.8 3,200 3,500 90% Dental equipment and supplies manufacturing (339114) 2.5 - 2,300 0% 30
  31. 31. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Table 7. Total primary and secondary nickel use summary. Description Material Personal Cons. Domestic PCE / Use, g/$ Exp.* (PCE), Consumption DC million $ (DC), million $ 2,10 Storage battery manufacturing (335911) 6.4 0 5,100 41% Jewelry and silverware manufacturing 19,00 2 (339910) 5.1 0 1,000 87% Secondary processing of other nonferrous (331492) 3.2 - 1,200 0% Nonferrous metal, except copper and 5 aluminum, shaping (331491) 2.9 7 7,300 1% Primary nonferrous metal, except copper 1 and aluminum (331419) 2.5 - 0,000 0% Ferroalloy and related product manufacturing (331112) 2.1 - 2,300 0% Dental laboratories (339116) 2 - 3,000 0% Dental equipment and supplies manufacturing (339114) 1.7 - 2,300 0% Copper rolling, drawing, and extruding (331421) 0.88 - 8,800 0% Primary smelting and refining of copper (331411) 0.77 - 8,100 0% 31
  32. 32. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Table 8. Total primary and secondary cadmium use summary. Description Material Personal Cons. Domestic PCE / Use, g/$ Exp.* (PCE), Consumption DC million $ (DC), million $ Storage battery manufacturing (335911) 0.18 2,100 5,100 41% Jewelry and silverware manufacturing (339910) 0.073 19,000 21,000 87% Secondary processing of other nonferrous (331492) 0.062 - 1,200 0% Nonferrous metal, except copper and aluminum, shaping (331491) 0.044 57 7,300 1% Ferroalloy and related product manufacturing (331112) 0.032 - 2,300 0% Dental laboratories (339116) 0.029 - 3,000 0% Dental equipment and supplies manufacturing (339114) 0.024 - 2,300 0% Cutting tool and machine tool accessory manufacturing (333515) 0.019 - 5,300 0% Primary battery manufacturing (335912) 0.015 2,000 2,200 91% Ferrous metal foundaries (331510) 0.01 - 17,000 0% 32
  33. 33. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 100% 80% 60% 40% m C P d o n s c e r f t i 20% 0% 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Personal Consumption Expenditure / Domestic Consumption Figure 2. Distribution of commodities by personal consumption expenditure to domestic consumption ratio. 33
  34. 34. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Table 9. Top 10 material consuming sectors by total use of zinc, lead, nickel, and cadmium for sectors with Personal Consumption Expenditures to Domestic Consumption ratio greater than 20%. Zinc Lead Nickel Cadmium 1 Jewelry & silverware mfg. 39 Power-driven handtool mfg. 13 Storage battery mfg. 6.4 Storage battery mfg. 0.18 (339910) (333991) (335911) (335911) 2 Motorcycle, bicycle, & parts 3.2 Jewelry & silverware mfg. 7.6 Jewelry & silverware mfg. 5.1 Jewelry & silverware mfg. 0.073 mfg. (336991) (339910) (339910) (339910) 3 Watch, clock, & other 1.8 Boat bldg. (336612) 2.9 Motorcycle, bicycle, & 0.43 Primary battery mfg. 0.015 measuring & controlling parts mfg. (336991) (335912) device mfg. (33451A) 4 Electric lamp bulb & part 1.5 Motor home mfg. (336213) 2.8 Primary battery mfg. 0.39 Motorcycle, bicycle, & parts 0.0064 mfg. (335110) (335912) mfg. (336991) 5 Heating equip, exc. warm air 1.4 Hand & edge tool mfg. 2.1 Watch, clock, & other 0.24 Power-driven handtool mfg. 0.0055 furnaces (333414) (332212) measuring & controlling (333991) device mfg. (33451A) 6 Household laundry equip. 1.4 Animal, except poultry, 1.1 Power-driven handtool 0.24 Household goods repair & 0.0037 mfg. (335224) slaughtering (311611) mfg. (333991) maintenance (811400) 7 Primary battery mfg. 1.3 Storage battery mfg. 1.0 Household laundry equip. 0.20 Watch, clock, & other 0.0036 (335912) (335911) mfg. (335224) measuring & controlling device mfg. (33451A) 8 Household cooking 1.1 Motorcycle, bicycle, & parts 0.94 Heating equip, exc. warm 0.19 Household laundry equip. 0.0029 appliance mfg. (335221) mfg. (336991) air furnaces (333414) mfg. (335224) 9 Kitchen utensil, pot, & pan 1.1 Automobile & lt. truck mfg. 0.76 Electric lamp bulb & part 0.18 Heating equip, exc. warm 0.0029 mfg (332214) (336110) mfg. (335110) air furnaces (333414) 10 Power-driven handtool mfg. 0.99 Cheese mfg. (311513) 0.76 Household cooking 0.15 Electric lamp bulb & part 0.0026 (333991) appliance mfg. (335221) mfg. (335110) 34
  35. 35. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 10 1 Zn* 0.1 Pb* Zn** Pb** 0.01 Ni* Ni** 0.001 0.0001 Cd** Cd* M U n h p u C $ e a g y S / s r t , i l 0.00001 0.000001 Rank Figure 3. Supply chain material use by sector, g / $. * Overall ** PCE / DC > 0.2 35
  36. 36. Estimation of Supply Chain Cadmium, Lead, Nickel, 16th International Input-Output Conference and Zinc Intensity with the MUIO-LCA Model July 2007 Table 10. Cadmium, Lead, Nickel, Zinc Prices and Their Inverses. Average Price 2006 1 / Price $/kg g/$ Cadmium 2.081,4 481 Lead 1.692, 1.263 593, 794 Nickel 23.93 41.9 Zinc 3.202,5, 3.093,6 313, 324 1 Average New York dealer price 2 North American Producer price 3 London Metals Exchange 4 99.95% purity in 5 short ton lots 5 Special high grade zinc 6 Cash price 36

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