International Construction Specialty Conference of the Canadian Society for Civil Engineering (ICSC) (5th : 2015)

Life cycle analysis of structural steel reuse using the economic input-output method Yeung, Jamie; Walbridge, Scott; Haas, Carl T. Jun 30, 2015

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5th International/11th Construction Specialty Conference 5e International/11e Conférence spécialisée sur la construction    Vancouver, British Columbia June 8 to June 10, 2015 / 8 juin au 10 juin 2015   LIFE CYCLE ANALYSIS OF STRUCTURAL STEEL REUSE USING THE ECONOMIC INPUT-OUTPUT METHOD Jamie Yeung1,4, Scott Walbridge2 and Carl Haas3 1 Graduate Research Assistant, Department of Civil and Environmental Engineering, University of Waterloo, ON, Canada 2 Associate Professor, Department of Civil and Environmental Engineering, University of Waterloo, ON, Canada 3 Professor, Department of Civil and Environmental Engineering, University of Waterloo, ON, Canada 4 j4yeung@uwaterloo.ca Abstract: Reuse of structural steel is not a new concept in civil engineering. However, even though members, and assemblies of members, have been reused for decades, reuse of steel is not a widely implemented practice. Approximately 90% of demolished steel is recycled and only 10% of that steel is reused in its current state. The structural steel reuse that does occur is due to the reuse of very large members or from specialty projects. The reason for these low levels of reuse is because the cost of reusing structural steel is too high. Unfortunately, many decision makers are coming to this conclusion without a comprehensive knowledge of the true cost of reuse and recycling. In order to fully understand the additional costs, or savings, associated with steel reuse, a life cycle analysis needs to be incorporated into an economic analysis. In this study, the economic input-output method was used to perform a life cycle analysis of structural steel reuse as it compares to current practices. The economic input-output method provides the benefit of being able to facilitate a quick analysis but is limited by only being able to perform a generalized analysis across the entire industry. The analysis was performed for several metrics, which can be grouped into four categories: greenhouse gases, energy usage, water usage, and hazardous waste generation. Results from the analysis show that there is a significant decrease, upwards of 65%, for the calculated metrics across each category for reuse. In order to remedy the limitations of the economic input-output method, it is recommended to perform a similar analysis using a process model approach. 1 INTRODUCTION Steel reuse shows great promise to become a more “environmentally friendly” alternative to creating new steel from virgin resources and recycled scrap steel. Current practices result in only about 10% of steel being reused as opposed to the nearly 90% of steel that is recycled, but it is believed that this could increase by up to 150% if economic conditions were to change, technological advances were to be utilized, or externalities affecting life cycle cost were considered (Gorgolewski, 2006 and Ness et al., 2014). The impact of a product, process or activity is not only limited to economic impact; there are also environmental impacts and social impacts. Life cycle analysis is a tool used to assess the entire impact of a product, process or activity throughout its entire life cycle. This analysis is a necessary step in the decision making phase of any project. The complete impact of a decision throughout its entire economic life cycle needs to be quantitatively understood in order to properly and knowledgeably make a 120-1 comparison between proposed alternatives. Performing a life cycle analysis is the only way to truly understand a decision’s full impact, but there are several ways to do this. 2 BACKGROUND Before being able to quantify the environmental benefits of reusing structural steel, the metrics for assessing environmental impact must be established. These metrics often include carbon footprint, water footprint, and energy use. It is important to note that these metrics need to be determined for the entire life cycle of the process or component and are based on direct and, sometimes more importantly, indirect impacts. A more detailed list of life cycle impacts can be seen in the work of Reijnders (1995), where the focus was on limiting resource use, minimizing pollution, and preserving nature. 2.1 Carbon Footprint According to Wiedmann and Minx (2008), “… carbon footprint is a measure of the exclusive total amount of carbon dioxide that is directly and indirectly caused by an activity or is accumulated over the life stages of a product.” This definition of carbon footprint does not include any of the other carbon based pollutants or greenhouse gases, such as methane. Wiedmann and Minx argue that this definition is ideal in spite of its limited scope due to its high level of clarity. When selecting a metric for environmental impact it is important that this metric be of significant contribution, clearly defined, and relatively simple to calculate, especially when implementing practices to reduce environmental impact.  2.2 Water Footprint The industrial sector consumes large volumes of water, but can also pollute even greater volumes downstream (WWAP, 2009). The idea of a ‘water footprint’ associated with each product and process was introduced by Hoekstra (2003) as a very similar concept to ‘virtual water’, originally coined by Allan (1997). Virtual water is the water consumed by the production of every product. It was used in a proposed solution to countries with water shortages by allowing those countries to export their water needs. A water footprint takes this concept a step further by including the water consumed during the entire life cycle of the process or product, rather than just during its production.  2.3 Energy Use Based on the work by Dincer (1999), energy use is a suitable metric for environmental impact because of the wide range of problems that can be associated with it. Increases in energy use can be correlated to acid rain, ozone depletion, global warming, air pollution, forest destruction, and the production of radioactive materials. This is because many of the bi-products of energy creation have negative effects on the environment. Acid rain is a result of excessive amounts of sulfur dioxide (SO2), nitric oxide (NO), and nitrogen dioxide (NO2) being emitted into the atmosphere, which are all released during the combustion of fossil fuels. Ozone depletion is mostly due to chloroflourocarbons (CFCs), which are used in air conditioning and refrigeration units but NO and NO2 also contribute. Other gases produced during energy production, including carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), ozone (O3), and peroxyacetylnitrate, are major contributors to the greenhouse gas effect and global warming.  2.4 The Economic Input-Output Method The economic input-output (EIO) method for life cycle assessment (EIO-LCA) aims to simplify the process of performing a life cycle assessment without having to limit its scope (i.e. exclude minor products and processes). The EIO method takes an aggregate view of a process or product and determines its life cycle impact based on the resulting inputs and outputs into various industry sectors (Hendrickson, Lave, & Matthews, 2006). For example, in order to construct a reinforced concrete building, a certain quantity of steel reinforcing bars will be required. This steel would represent an output from the steel industry and an input to the construction industry. 120-2 The EIO method works by first selecting a product or process to be assessed for its life cycle impact. Next, the entire life cycle requirements for the supply chain of this product or process are determined. These supply chain requirements include everything from extracting raw materials to producing the final product. Once the life cycle supply chain has been established, the discharges associated with each activity in the supply chain are summed and the total life cycle impact is presented. Depending on the desired life cycle analysis output, the aforementioned discharges can be economic activity, environmental, social, etc. (Hendrickson, Lave, & Matthews, 2006). In order for the EIO method to be feasible, the economy needs to be divided into a limited number of distinct sectors. Each sector also needs to have established and quantified relationships with each of the other sectors. This relationship identifies that amount of inputs required from each sector in order to produce one unit of output for the specified sector. Fortunately, these relationships exist because of the work proposed and carried out by Leontief (1970). The discharges per unit of output from each sector are also required in order to convert the supply chain outputs to a specific type of impact, such as environmental impact. For the specific case of environmental impact, these relationships have already been established (Lave et al. 1995, Hendrickson et al. 1998). The limitations of the input-output method result mostly from uncertainty as outlined by Lenzen (2001) who listed seven types: (1) source data uncertainty, (2) import assumption uncertainty, (3) estimation uncertainty for capital flow, (4) proportionality assumption uncertainty, (5) aggregation uncertainty, (6) allocation uncertainty, and (7) gate-to-grave truncation error. The data used in the input-output method is collected from national surveys and while errors can be estimated, they cannot be quantitatively known. This results in source data uncertainty. The uncertainty from imports arises because the data associated with foreign goods does not necessarily follow that of their domestic counterparts but the foreign data is not necessarily known. Worst-case errors are typically used to adjust imports but this is a simplified approximation. If capital flow tables do not exist, they must be constructed from capital expenditure from varied sources. This is an approximation and, as a result, a source of uncertainty. The proportionality assumption states that there is a linear relationship between the inputs and outputs and that price is uniform across the economy (Hendrickson et al. 2006 & Lenzen 2001). This means that doubling the output will require doubled input from each input and that the cost of electricity is the same whether being purchased by the steel industry or the fabrics industry. Aggregation leads to uncertainty because multiple producers are combined into a single industry without any way of differentiating between them. The final uncertainty associated with the input-output method is the uncertainty that results from the truncation of the gate-to-grave portion of the life cycle. The EIO method only accounts for the production discharges and neglects any operation, maintenance and end-of-life processes.  3 METHODOLOGY The life cycle analysis performed in this study was undertaken using the economic input-output life cycle assessment (EIO-LCA) tool, developed by the Green Design Institute at Carnegie Mellon University (CMUGDI, 2008). As discussed previously, the EIO-LCA employs an aggregate overview of the life cycle impacts of a sector of industry based on the desired economic output from that sector. This includes the impacts of other sectors providing inputs to the sector of interest. The methodology for this comparison can be defined by three steps (Figure 1): (1) determining a point of reference, (2) defining appropriate sectors and activities, and (3) equating and comparing equivalent economic activities. 120-3 foundry. The production of new steel components was assumed to come from the “iron, steel pipe and tube manufacturing from purchased steel” sector. This is responsible for the production of welded and rolled structural steel shapes (CMUGDI, 2008). The production of reused steel components was assumed to come from economic activity in the demolition industry. Unfortunately, demolition is not a sector included in the USA 2002 Benchmark data so construction of nonresidential manufacturing structures was selected as a surrogate. It is reasonable to consider construction and deconstruction as equivalent processes performed in an opposite manner. Many of the activities in this sector would be present in the removal of structural steel from buildings at the end of their service life. The main difference is that the deconstruction processes also includes activities for steel and cement manufacturing. The activity in these sectors would be present for the case of construction activity but would likely be absent from reuse activities. An adjustment was made to the impacts of the nonresidential manufacturing structures sector by removing the impacts that result from steel and cement manufacturing. With these sectors removed, the impact results will be more representative of reuse activities. For example, Table 1 displays the five highest total energy using sectors required to produce economic output from the “nonresidential manufacturing structures” sector. It is reasonable to presume that a large majority of the energy usage from “Iron and steel mills” would not be required, and can therefore be disregarded, if the structural steel is being reused. Table 1: Highest energy users from the “nonresidential manufacturing structures” sector  Sector Name  Total Energy Usage (TJ)* Nonresidential manufacturing structures 2.39 Power generation and supply 1.14 Iron and steel mills 0.40 Petroleum refineries 0.26 Truck transportation 0.14 *values are reported per $1,000,000 of economic output The final step was to determine the economic output from each sector required to achieve the desired mass of steel as specified in the first step. In order for a meaningful comparison to be made, the end production of each process needs to be the same. This means that the mass of steel that results from current practices and reuse need to be the same. Unfortunately the EIO-LCA method uses economic activity as the scale defining parameter for the analysis so equivalent economic activities for each production method needed to be calculated. The conversion values used in this study can be found in Table 2. Table 2: Mass to economic activity conversion rates Production Method Conversion Rate Current Practices $3.64 / kg Reuse $4.93 / kg The current practices conversion rate of $3.64 / kg was selected based on the average material price of structural steel sections ranging from 200 mm to 350 mm in depth. The unit prices for these sections were obtained from RSMeans (2009). The reuse conversion rate was selected as $4.93 / kg. This value was based on the average construction cost per unit mass of various industrial steel framing structures. Following similar logic to the selection of the sectors from USA 2002 Benchmark data, the cost of constructing a particular mass of steel is equivalent to deconstructing that same mass. These unit prices were also obtained from RSMeans (2009). Neither price was adjusted for inflation or changes in market value. The accuracy of this study would be increased if current prices were used, but this was deemed unnecessary for this investigation. Together, these values create a new steel to reused steel price ratio of 1:1.35. This comparison is based on the assumption that the steel is in a pre-fabrication state, as 120-5 previously stated. It is expected that reused structural steel closer to the installation stage of the supply chain (PoR2 in Figure 2) would result in a more favourable price ratio. 4 RESULTS The metrics for the previously described comparison were divided into five distinct groups: conventional air pollutants (Figure 3), greenhouse gases (Figure 4), energy consumption (Figure 5), water usage (Figure 6a), and hazardous waste production (Figure 6b). The reported results are based on $1,000,000 of new steel production. A description of each metric can be found in Table 3. Table 3: Definition of metrics used for life cycle analysis Metric Name Description CO - carbon monoxide emissions into the atmosphere NH3 - ammonia emissions into the atmosphere NOx - oxides of nitrogen emissions into the atmosphere PM10 - particulate matter emissions into the atmosphere with diameter less than 10 microns PM2.5 - particulate matter emissions into the atmosphere with diameter less than 2.5 microns SO2 - sulfur dioxide emissions into the atmosphere VOC - volatile organic compound emissions into the atmosphere CO2 Fossil - carbon dioxide emissions into the atmosphere from fossil fuel combustion only CO2 Process - carbon dioxide emissions into the atmosphere from all processes other than fossil fuel combustion CH4 - methane emissions into the environment N2O - nitrous oxide emissions into the atmosphere HFC/PFCs - hydrofluorocarbons, perflourocarbons, and sulphur hexafluoride emissions into the atmosphere Coal - energy consumed from coal sources NatGas - energy consumed from natural gas sources Petrol - energy consumed from petroleum sources Bio/Waste - energy consumed from biomass or waste sources NonFossElec - energy consumed from non-fossil fuel electric sources Water Withdrawals - water withdrawn from the environment Hazardous Waste - the amount of hazardous waste generated as defined by the Resource Conservation and Recovery Act Figure 3 through Figure 6 show that, typically, the analysis for structural steel reuse results in significant life cycle impact reduction. Only four out of the 19 metrics investigated resulted in a significantly increased impact due to the reuse process. Table 4 quantifies the comparison of each metric as the percent reduction that results from applying reuse processes as opposed to current practices. Although a benefit is not demonstrated in all metrics of this study, a generalized decrease in the environmental impact can be seen as a result of reuse. The total mass of conventional air pollutants was reduced by 0.25 t, or 1%, the total mass of greenhouse gases in CO2 equivalent was reduced by over 1500 t, or 75%, and the total energy usage was reduced by over 17 TJ, or 69%.  120-6  Figure 3: Life cycle analysis comparison between current practices and reuse for conventional air pollutants  Figure 4: Life cycle analysis comparison between current practices and reuse for greenhouse gases  Figure 5: Life cycle analysis comparison between current practices and reuse for energy consumption 120-7  Figure 6: Life cycle analysis comparison between current practices and reuse for water usage (a) and hazardous waste generation (b)  Table 4: Percent reduction of life cycle assessment metrics as a result of reuse Life cycle assessment metric Percent reduction as a result of reuse* CO -32% NH3 47% NOx 47% PM10 -32% PM2.5 20% SO2 69% VOC -20% CO2 Fossil 58% CO2 Process 98% CH4 65% N2O 6% HFC/PFCs 77% Coal 90% NatGas 75% Petrol -90% Bio/Waste 36% NonFossElec 78% Water Withdrawals 65% Hazardous Waste 79% *negative percent reductions indicate an increase as a result of reuse                           Figure 7: Percent reduction of life cycle assessment metrics as a result of reuse 5 DISCUSSION AND CONCLUSIONS The economic input-output life cycle analysis results show a clear indication that reuse has the potential to provide significant benefits over current practices. Steel reuse exhibited superior results in nearly every presented metric, given the parameters of this study. When the results are generalized, a 75% reduction in greenhouse gases and a 69% reduction in energy use is expected for steel reuse. a b -100% -50% 0% 50% 100%Hazardous WasteWater WithdrawalsNonFossElecBio/WastePetrolNatGasCoalHFC/PFCsN₂OCH₄CO₂ ProcessCO₂ FossilVOCSO₂PM₂.₅PM₁₀NOₓNH₃COPercent Reduction120-8  The external costs associated with construction decisions, such as material source, are not often considered in current decision making practices. These costs are not considered because they are not accurately understood and they are not associated with direct costs to the decision maker. Introducing direct costs to the decision maker, through carbon credits for example, would encourage practices that incorporate a broader, societal cost into their decision making process. This work makes progress towards achieving accurate quantification of the societal cost of reuse practices but more work is still required. 6 FUTURE WORK One of the main drawbacks of the EIO-LCA method is its aggregate scale. This prevents the specific processes, such as the reuse process, from being examined directly. As a result, a number of assumptions and simplifications needed to be made. These assumptions and simplifications may have an impact on the results. As such, these results should only be treated as preliminary. A more detailed analysis is essential for accurately quantifying the benefits or costs of reusing structural steel. For this analysis, it is recommended to replace the aggregate approach used by the economic input-output method, with a more detailed approach, such as the process model approach. It is also worth investigating how the externalities identified in this EIO-LCA could be monetized, such as carbon credits, so that the opportunity cost to society of not reusing steel could be understand and could influence future reuse decisions. Acknowledgements The authors would like to gratefully acknowledge the financial support provided by National Sciences and Engineering Research Council of Canada through the Graduate Research Studentship (GRS) program in form of a scholarship awarded to the first author. References  Allan, T. 1997. ’Virtual Water’: a long term solution for water short Middle Eastern economies. British Association Festival of Science, University of Leeds, 9 Sept 1997. Carnegie Mellon University Green Design Institute (CMUGDI). 2008. Economic Input-Output Life Cycle Assessment (EIO-LCA). USA 2997 Industry Benchmark Model [Internet], Available from: <http://www.eiolca.net> Accessed Dec 2014. Dincer, I. 1999. Environmental impacts of energy. Energy Policy. 27: 845-854. Gorgolewski, M., Straka, V., Edmonds, J., and Sergio, C. 2006. Facilitating Greater Reuse and Recycling of Structural Steel in the Construction and Demolition Process. Final Report Ryerson University, Toronto ON.  Hendrickson, C. T., Horvath, A., Joshi, S., and Lave, L. 1998. Economic Input-Output Models for Environmental Life-Cycle Assessment. American Chemical Society. 32(7): 184A-191A. Hendrickson, C. T., Lave, L. B., and Matthews, H. S. 2006. Environmental Life Cycle Assessment of Goods and Services: An Input-Output Approach. Washington DC: Resources for the Future. Hoekstra, A. Y. 2003. Virtual Water Trade: Proceedings of the International Expert Meeting on Virtual Water Trade. Value of Water Research Report Series No 12, Delft, Netherlands: UNESCO. Lave, L. B., Cobas-Flores, E., Hendrickson, C. T., and McMichael, F. C. 1995. Using Input-Output Analysis to Estimate Economy-wide Discharges. Environmental Science and Technology. 29(9): 420-426. Lenzen, M. 2001. Errors in Conventional and Input-Output-Based Life-Cycle Inventories. Journal of Industrial Ecology. 4(4): 127-148. Leontief, M. 1970. Environmental Repercussions and the Economic Structure: An Input-Output Approach. The Review of Economics and Statistics. 52(3): 262-271. 120-9 Ness, D., Swift, J., Ranasinghe, D. C., Xing, K., Soebarto, V. 2014. Smart steel: new paradigms for the reuse of steel enabled by digital tracking and modelling, Journal of Cleaner Production. (In Press). Reijnders, L. 1995. Environmentally Improved Production Processes and Products: An Introduction. Berlin: Kluwer Academic Press. RSMeans. 2009. Building Construction Cost Data. R.S. Means Company, Inc. United States of America. Wiedmann, T., and Minx, J. 2008. A Definition of ‘Carbon Footprint’. In: C.C. Perstova, Ecological Economics Research Trends. 1-11. World Water Assessment Programme (WWAP). 2009. The United Nations World Water Report 3: Water in a Changing World. London, England: Earthscan, and Paris, France: UNESCO Publishing.   120-10  5th International/11th Construction Specialty Conference 5e International/11e Conférence spécialisée sur la construction    Vancouver, British Columbia June 8 to June 10, 2015 / 8 juin au 10 juin 2015   LIFE CYCLE ANALYSIS OF STRUCTURAL STEEL REUSE USING THE ECONOMIC INPUT-OUTPUT METHOD Jamie Yeung1,4, Scott Walbridge2 and Carl Haas3 1 Graduate Research Assistant, Department of Civil and Environmental Engineering, University of Waterloo, ON, Canada 2 Associate Professor, Department of Civil and Environmental Engineering, University of Waterloo, ON, Canada 3 Professor, Department of Civil and Environmental Engineering, University of Waterloo, ON, Canada 4 j4yeung@uwaterloo.ca Abstract: Reuse of structural steel is not a new concept in civil engineering. However, even though members, and assemblies of members, have been reused for decades, reuse of steel is not a widely implemented practice. Approximately 90% of demolished steel is recycled and only 10% of that steel is reused in its current state. The structural steel reuse that does occur is due to the reuse of very large members or from specialty projects. The reason for these low levels of reuse is because the cost of reusing structural steel is too high. Unfortunately, many decision makers are coming to this conclusion without a comprehensive knowledge of the true cost of reuse and recycling. In order to fully understand the additional costs, or savings, associated with steel reuse, a life cycle analysis needs to be incorporated into an economic analysis. In this study, the economic input-output method was used to perform a life cycle analysis of structural steel reuse as it compares to current practices. The economic input-output method provides the benefit of being able to facilitate a quick analysis but is limited by only being able to perform a generalized analysis across the entire industry. The analysis was performed for several metrics, which can be grouped into four categories: greenhouse gases, energy usage, water usage, and hazardous waste generation. Results from the analysis show that there is a significant decrease, upwards of 65%, for the calculated metrics across each category for reuse. In order to remedy the limitations of the economic input-output method, it is recommended to perform a similar analysis using a process model approach. 1 INTRODUCTION Steel reuse shows great promise to become a more “environmentally friendly” alternative to creating new steel from virgin resources and recycled scrap steel. Current practices result in only about 10% of steel being reused as opposed to the nearly 90% of steel that is recycled, but it is believed that this could increase by up to 150% if economic conditions were to change, technological advances were to be utilized, or externalities affecting life cycle cost were considered (Gorgolewski, 2006 and Ness et al., 2014). The impact of a product, process or activity is not only limited to economic impact; there are also environmental impacts and social impacts. Life cycle analysis is a tool used to assess the entire impact of a product, process or activity throughout its entire life cycle. This analysis is a necessary step in the decision making phase of any project. The complete impact of a decision throughout its entire economic life cycle needs to be quantitatively understood in order to properly and knowledgeably make a 120-1 comparison between proposed alternatives. Performing a life cycle analysis is the only way to truly understand a decision’s full impact, but there are several ways to do this. 2 BACKGROUND Before being able to quantify the environmental benefits of reusing structural steel, the metrics for assessing environmental impact must be established. These metrics often include carbon footprint, water footprint, and energy use. It is important to note that these metrics need to be determined for the entire life cycle of the process or component and are based on direct and, sometimes more importantly, indirect impacts. A more detailed list of life cycle impacts can be seen in the work of Reijnders (1995), where the focus was on limiting resource use, minimizing pollution, and preserving nature. 2.1 Carbon Footprint According to Wiedmann and Minx (2008), “… carbon footprint is a measure of the exclusive total amount of carbon dioxide that is directly and indirectly caused by an activity or is accumulated over the life stages of a product.” This definition of carbon footprint does not include any of the other carbon based pollutants or greenhouse gases, such as methane. Wiedmann and Minx argue that this definition is ideal in spite of its limited scope due to its high level of clarity. When selecting a metric for environmental impact it is important that this metric be of significant contribution, clearly defined, and relatively simple to calculate, especially when implementing practices to reduce environmental impact.  2.2 Water Footprint The industrial sector consumes large volumes of water, but can also pollute even greater volumes downstream (WWAP, 2009). The idea of a ‘water footprint’ associated with each product and process was introduced by Hoekstra (2003) as a very similar concept to ‘virtual water’, originally coined by Allan (1997). Virtual water is the water consumed by the production of every product. It was used in a proposed solution to countries with water shortages by allowing those countries to export their water needs. A water footprint takes this concept a step further by including the water consumed during the entire life cycle of the process or product, rather than just during its production.  2.3 Energy Use Based on the work by Dincer (1999), energy use is a suitable metric for environmental impact because of the wide range of problems that can be associated with it. Increases in energy use can be correlated to acid rain, ozone depletion, global warming, air pollution, forest destruction, and the production of radioactive materials. This is because many of the bi-products of energy creation have negative effects on the environment. Acid rain is a result of excessive amounts of sulfur dioxide (SO2), nitric oxide (NO), and nitrogen dioxide (NO2) being emitted into the atmosphere, which are all released during the combustion of fossil fuels. Ozone depletion is mostly due to chloroflourocarbons (CFCs), which are used in air conditioning and refrigeration units but NO and NO2 also contribute. Other gases produced during energy production, including carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), ozone (O3), and peroxyacetylnitrate, are major contributors to the greenhouse gas effect and global warming.  2.4 The Economic Input-Output Method The economic input-output (EIO) method for life cycle assessment (EIO-LCA) aims to simplify the process of performing a life cycle assessment without having to limit its scope (i.e. exclude minor products and processes). The EIO method takes an aggregate view of a process or product and determines its life cycle impact based on the resulting inputs and outputs into various industry sectors (Hendrickson, Lave, & Matthews, 2006). For example, in order to construct a reinforced concrete building, a certain quantity of steel reinforcing bars will be required. This steel would represent an output from the steel industry and an input to the construction industry. 120-2 The EIO method works by first selecting a product or process to be assessed for its life cycle impact. Next, the entire life cycle requirements for the supply chain of this product or process are determined. These supply chain requirements include everything from extracting raw materials to producing the final product. Once the life cycle supply chain has been established, the discharges associated with each activity in the supply chain are summed and the total life cycle impact is presented. Depending on the desired life cycle analysis output, the aforementioned discharges can be economic activity, environmental, social, etc. (Hendrickson, Lave, & Matthews, 2006). In order for the EIO method to be feasible, the economy needs to be divided into a limited number of distinct sectors. Each sector also needs to have established and quantified relationships with each of the other sectors. This relationship identifies that amount of inputs required from each sector in order to produce one unit of output for the specified sector. Fortunately, these relationships exist because of the work proposed and carried out by Leontief (1970). The discharges per unit of output from each sector are also required in order to convert the supply chain outputs to a specific type of impact, such as environmental impact. For the specific case of environmental impact, these relationships have already been established (Lave et al. 1995, Hendrickson et al. 1998). The limitations of the input-output method result mostly from uncertainty as outlined by Lenzen (2001) who listed seven types: (1) source data uncertainty, (2) import assumption uncertainty, (3) estimation uncertainty for capital flow, (4) proportionality assumption uncertainty, (5) aggregation uncertainty, (6) allocation uncertainty, and (7) gate-to-grave truncation error. The data used in the input-output method is collected from national surveys and while errors can be estimated, they cannot be quantitatively known. This results in source data uncertainty. The uncertainty from imports arises because the data associated with foreign goods does not necessarily follow that of their domestic counterparts but the foreign data is not necessarily known. Worst-case errors are typically used to adjust imports but this is a simplified approximation. If capital flow tables do not exist, they must be constructed from capital expenditure from varied sources. This is an approximation and, as a result, a source of uncertainty. The proportionality assumption states that there is a linear relationship between the inputs and outputs and that price is uniform across the economy (Hendrickson et al. 2006 & Lenzen 2001). This means that doubling the output will require doubled input from each input and that the cost of electricity is the same whether being purchased by the steel industry or the fabrics industry. Aggregation leads to uncertainty because multiple producers are combined into a single industry without any way of differentiating between them. The final uncertainty associated with the input-output method is the uncertainty that results from the truncation of the gate-to-grave portion of the life cycle. The EIO method only accounts for the production discharges and neglects any operation, maintenance and end-of-life processes.  3 METHODOLOGY The life cycle analysis performed in this study was undertaken using the economic input-output life cycle assessment (EIO-LCA) tool, developed by the Green Design Institute at Carnegie Mellon University (CMUGDI, 2008). As discussed previously, the EIO-LCA employs an aggregate overview of the life cycle impacts of a sector of industry based on the desired economic output from that sector. This includes the impacts of other sectors providing inputs to the sector of interest. The methodology for this comparison can be defined by three steps (Figure 1): (1) determining a point of reference, (2) defining appropriate sectors and activities, and (3) equating and comparing equivalent economic activities. 120-3 foundry. The production of new steel components was assumed to come from the “iron, steel pipe and tube manufacturing from purchased steel” sector. This is responsible for the production of welded and rolled structural steel shapes (CMUGDI, 2008). The production of reused steel components was assumed to come from economic activity in the demolition industry. Unfortunately, demolition is not a sector included in the USA 2002 Benchmark data so construction of nonresidential manufacturing structures was selected as a surrogate. It is reasonable to consider construction and deconstruction as equivalent processes performed in an opposite manner. Many of the activities in this sector would be present in the removal of structural steel from buildings at the end of their service life. The main difference is that the deconstruction processes also includes activities for steel and cement manufacturing. The activity in these sectors would be present for the case of construction activity but would likely be absent from reuse activities. An adjustment was made to the impacts of the nonresidential manufacturing structures sector by removing the impacts that result from steel and cement manufacturing. With these sectors removed, the impact results will be more representative of reuse activities. For example, Table 1 displays the five highest total energy using sectors required to produce economic output from the “nonresidential manufacturing structures” sector. It is reasonable to presume that a large majority of the energy usage from “Iron and steel mills” would not be required, and can therefore be disregarded, if the structural steel is being reused. Table 1: Highest energy users from the “nonresidential manufacturing structures” sector  Sector Name  Total Energy Usage (TJ)* Nonresidential manufacturing structures 2.39 Power generation and supply 1.14 Iron and steel mills 0.40 Petroleum refineries 0.26 Truck transportation 0.14 *values are reported per $1,000,000 of economic output The final step was to determine the economic output from each sector required to achieve the desired mass of steel as specified in the first step. In order for a meaningful comparison to be made, the end production of each process needs to be the same. This means that the mass of steel that results from current practices and reuse need to be the same. Unfortunately the EIO-LCA method uses economic activity as the scale defining parameter for the analysis so equivalent economic activities for each production method needed to be calculated. The conversion values used in this study can be found in Table 2. Table 2: Mass to economic activity conversion rates Production Method Conversion Rate Current Practices $3.64 / kg Reuse $4.93 / kg The current practices conversion rate of $3.64 / kg was selected based on the average material price of structural steel sections ranging from 200 mm to 350 mm in depth. The unit prices for these sections were obtained from RSMeans (2009). The reuse conversion rate was selected as $4.93 / kg. This value was based on the average construction cost per unit mass of various industrial steel framing structures. Following similar logic to the selection of the sectors from USA 2002 Benchmark data, the cost of constructing a particular mass of steel is equivalent to deconstructing that same mass. These unit prices were also obtained from RSMeans (2009). Neither price was adjusted for inflation or changes in market value. The accuracy of this study would be increased if current prices were used, but this was deemed unnecessary for this investigation. Together, these values create a new steel to reused steel price ratio of 1:1.35. This comparison is based on the assumption that the steel is in a pre-fabrication state, as 120-5 previously stated. It is expected that reused structural steel closer to the installation stage of the supply chain (PoR2 in Figure 2) would result in a more favourable price ratio. 4 RESULTS The metrics for the previously described comparison were divided into five distinct groups: conventional air pollutants (Figure 3), greenhouse gases (Figure 4), energy consumption (Figure 5), water usage (Figure 6a), and hazardous waste production (Figure 6b). The reported results are based on $1,000,000 of new steel production. A description of each metric can be found in Table 3. Table 3: Definition of metrics used for life cycle analysis Metric Name Description CO - carbon monoxide emissions into the atmosphere NH3 - ammonia emissions into the atmosphere NOx - oxides of nitrogen emissions into the atmosphere PM10 - particulate matter emissions into the atmosphere with diameter less than 10 microns PM2.5 - particulate matter emissions into the atmosphere with diameter less than 2.5 microns SO2 - sulfur dioxide emissions into the atmosphere VOC - volatile organic compound emissions into the atmosphere CO2 Fossil - carbon dioxide emissions into the atmosphere from fossil fuel combustion only CO2 Process - carbon dioxide emissions into the atmosphere from all processes other than fossil fuel combustion CH4 - methane emissions into the environment N2O - nitrous oxide emissions into the atmosphere HFC/PFCs - hydrofluorocarbons, perflourocarbons, and sulphur hexafluoride emissions into the atmosphere Coal - energy consumed from coal sources NatGas - energy consumed from natural gas sources Petrol - energy consumed from petroleum sources Bio/Waste - energy consumed from biomass or waste sources NonFossElec - energy consumed from non-fossil fuel electric sources Water Withdrawals - water withdrawn from the environment Hazardous Waste - the amount of hazardous waste generated as defined by the Resource Conservation and Recovery Act Figure 3 through Figure 6 show that, typically, the analysis for structural steel reuse results in significant life cycle impact reduction. Only four out of the 19 metrics investigated resulted in a significantly increased impact due to the reuse process. Table 4 quantifies the comparison of each metric as the percent reduction that results from applying reuse processes as opposed to current practices. Although a benefit is not demonstrated in all metrics of this study, a generalized decrease in the environmental impact can be seen as a result of reuse. The total mass of conventional air pollutants was reduced by 0.25 t, or 1%, the total mass of greenhouse gases in CO2 equivalent was reduced by over 1500 t, or 75%, and the total energy usage was reduced by over 17 TJ, or 69%.  120-6  Figure 3: Life cycle analysis comparison between current practices and reuse for conventional air pollutants  Figure 4: Life cycle analysis comparison between current practices and reuse for greenhouse gases  Figure 5: Life cycle analysis comparison between current practices and reuse for energy consumption 120-7  Figure 6: Life cycle analysis comparison between current practices and reuse for water usage (a) and hazardous waste generation (b)  Table 4: Percent reduction of life cycle assessment metrics as a result of reuse Life cycle assessment metric Percent reduction as a result of reuse* CO -32% NH3 47% NOx 47% PM10 -32% PM2.5 20% SO2 69% VOC -20% CO2 Fossil 58% CO2 Process 98% CH4 65% N2O 6% HFC/PFCs 77% Coal 90% NatGas 75% Petrol -90% Bio/Waste 36% NonFossElec 78% Water Withdrawals 65% Hazardous Waste 79% *negative percent reductions indicate an increase as a result of reuse                           Figure 7: Percent reduction of life cycle assessment metrics as a result of reuse 5 DISCUSSION AND CONCLUSIONS The economic input-output life cycle analysis results show a clear indication that reuse has the potential to provide significant benefits over current practices. Steel reuse exhibited superior results in nearly every presented metric, given the parameters of this study. When the results are generalized, a 75% reduction in greenhouse gases and a 69% reduction in energy use is expected for steel reuse. a b -100% -50% 0% 50% 100%Hazardous WasteWater WithdrawalsNonFossElecBio/WastePetrolNatGasCoalHFC/PFCsN₂OCH₄CO₂ ProcessCO₂ FossilVOCSO₂PM₂.₅PM₁₀NOₓNH₃COPercent Reduction120-8  The external costs associated with construction decisions, such as material source, are not often considered in current decision making practices. These costs are not considered because they are not accurately understood and they are not associated with direct costs to the decision maker. Introducing direct costs to the decision maker, through carbon credits for example, would encourage practices that incorporate a broader, societal cost into their decision making process. This work makes progress towards achieving accurate quantification of the societal cost of reuse practices but more work is still required. 6 FUTURE WORK One of the main drawbacks of the EIO-LCA method is its aggregate scale. This prevents the specific processes, such as the reuse process, from being examined directly. As a result, a number of assumptions and simplifications needed to be made. These assumptions and simplifications may have an impact on the results. As such, these results should only be treated as preliminary. A more detailed analysis is essential for accurately quantifying the benefits or costs of reusing structural steel. For this analysis, it is recommended to replace the aggregate approach used by the economic input-output method, with a more detailed approach, such as the process model approach. It is also worth investigating how the externalities identified in this EIO-LCA could be monetized, such as carbon credits, so that the opportunity cost to society of not reusing steel could be understand and could influence future reuse decisions. Acknowledgements The authors would like to gratefully acknowledge the financial support provided by National Sciences and Engineering Research Council of Canada through the Graduate Research Studentship (GRS) program in form of a scholarship awarded to the first author. References  Allan, T. 1997. ’Virtual Water’: a long term solution for water short Middle Eastern economies. British Association Festival of Science, University of Leeds, 9 Sept 1997. Carnegie Mellon University Green Design Institute (CMUGDI). 2008. Economic Input-Output Life Cycle Assessment (EIO-LCA). USA 2997 Industry Benchmark Model [Internet], Available from: <http://www.eiolca.net> Accessed Dec 2014. Dincer, I. 1999. Environmental impacts of energy. Energy Policy. 27: 845-854. Gorgolewski, M., Straka, V., Edmonds, J., and Sergio, C. 2006. Facilitating Greater Reuse and Recycling of Structural Steel in the Construction and Demolition Process. Final Report Ryerson University, Toronto ON.  Hendrickson, C. T., Horvath, A., Joshi, S., and Lave, L. 1998. Economic Input-Output Models for Environmental Life-Cycle Assessment. American Chemical Society. 32(7): 184A-191A. Hendrickson, C. T., Lave, L. B., and Matthews, H. S. 2006. Environmental Life Cycle Assessment of Goods and Services: An Input-Output Approach. Washington DC: Resources for the Future. Hoekstra, A. Y. 2003. Virtual Water Trade: Proceedings of the International Expert Meeting on Virtual Water Trade. Value of Water Research Report Series No 12, Delft, Netherlands: UNESCO. Lave, L. B., Cobas-Flores, E., Hendrickson, C. T., and McMichael, F. C. 1995. Using Input-Output Analysis to Estimate Economy-wide Discharges. Environmental Science and Technology. 29(9): 420-426. Lenzen, M. 2001. Errors in Conventional and Input-Output-Based Life-Cycle Inventories. Journal of Industrial Ecology. 4(4): 127-148. Leontief, M. 1970. Environmental Repercussions and the Economic Structure: An Input-Output Approach. The Review of Economics and Statistics. 52(3): 262-271. 120-9 Ness, D., Swift, J., Ranasinghe, D. C., Xing, K., Soebarto, V. 2014. Smart steel: new paradigms for the reuse of steel enabled by digital tracking and modelling, Journal of Cleaner Production. (In Press). Reijnders, L. 1995. Environmentally Improved Production Processes and Products: An Introduction. Berlin: Kluwer Academic Press. RSMeans. 2009. Building Construction Cost Data. R.S. Means Company, Inc. United States of America. Wiedmann, T., and Minx, J. 2008. A Definition of ‘Carbon Footprint’. In: C.C. Perstova, Ecological Economics Research Trends. 1-11. World Water Assessment Programme (WWAP). 2009. The United Nations World Water Report 3: Water in a Changing World. London, England: Earthscan, and Paris, France: UNESCO Publishing.   120-10  Life Cycle Analysis of Reused Steel Using the Economic Input-Output MethodJamie YeungDr. Scott WalbridgeDr. Carl HaasJune 10th, 2015Motivation• structural steel is relatively easy to salvage for the purposes of reuse• steel reuse is often deemed “too expensive”when compared to conventional methods2ObjectiveQuantitatively compare the life cycle cost of conventional structural steel production with structural steel reuse.3Life Cycle Analysis of Reused Steel• complete cradle-to-grave life cycle• broad spectrum of analysis metrics• the Process Model Approach• the Economic Input-Output Method4Life Cycle Analysis of Reused SteelThe Economic Input-Output Method• simplified LCA method• cradle-to-gate• environmental life cycle metrics• aggregate scale– 428 economic sectors– environmental impact per dollar of production for each sector(Hendrickson, Lave, & Matthews, 2006).5Life Cycle Analysis of Reused Steel• Methodology:SteelReuseMixedProductionSteelIndustryDeconstructionIndustryEconomicActivityEconomicActivityAppropriateSectors andActivitiesPoint ofReferenceEquivalentEconomicActivity6Life Cycle Analysis of Reused Steel• Methodology: Mixed Productiono “Iron, steel pipe and tube manufacturing from purchased steel”o rolled and welded shapes Steel Reuseo “Nonresidential Manufacturing Structures”7• Methodology: absent activities are removed Nonresidential manufacturing structures Power generation and supply Iron and steel mills (removed for reuse) Petroleum refineries Truck transportation Cement manufacturing (removed for reuse) Oil and gas extractionLife Cycle Analysis of Reused Steel8Life Cycle Analysis of Reused Steel• Methodology: equating economic activity:o Mixed Production Price: $3.64 / kg o Reuse Price: $4.93 / kg $1 of Mixed Production = $1.35 of Reuse9Life Cycle Analysis of Reused Steel• Results: Air Pollutants0246810121416CO NH₃ NOₓ PM₁₀ PM₂.₅ SO₂ VOCPollutant Production (t)Conventional Air PollutantCurrent PracticesReuseBased on $1M of Mixed Production46Life Cycle Analysis of Reused Steel• Results: Greenhouse Gases020040060080010001200CO₂ Fossil CO₂ Process CH₄ N₂O HFC/PFCsGas Production (t of CO2Equivalent)Greenhouse GasCurrent PracticesReuseBased on $1M of Mixed Production47Life Cycle Analysis of Reused Steel• Results: Energy Consumption02468101214Coal NatGas Petrol Bio/Waste NonFossElecEnergy Consumption (TJ)Energy Production MethodCurrent PracticesReuseBased on $1M of Mixed Production48Life Cycle Analysis of Reused Steel• Results: Water Usage and Hazardous Waste0246810121416Water WithdrawalsVolume Used (MGal)Water UsageCurrent PracticesReuse0100200300400500600700800Hazerdous WasteWaste Mass (kt)Hazardous Waste GenerationCurrent PracticesReuseBased on $1M of Mixed Production13Life Cycle Analysis of Reused Steel• Results: Summary-100% -50% 0% 50% 100%Hazardous WasteWater WithdrawalsNonFossElecBio/WastePetrolNatGasCoalHFC/PFCsN₂OCH₄CO₂ ProcessCO₂ FossilVOCSO₂PM₂.₅PM₁₀NOₓNH₃COPercent Reduction14Life Cycle Analysis of Reused Steel• Limitations: industry average cradle-to-gate cost ratio assumption15Life Cycle Analysis of Reused Steel• Conclusions: structural steel reuse appears to hold great potential for reducing the life cycle cost of steel construction greater petroleum usage but significant reductions in nearly every other metric16Life Cycle Analysis of Reused Steel• Future Work: Process Model Approach LCA tools for quickly assessing reuse potential17Thank you18

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