Business Intelligence for Sustainable Management Natural Capital Management A briefing on multiregional input–output life cycle assessment and natural capital valuation techniques Rick Betita • Director of Research Dr. James Barrett • Vice President of Environmental Economics November 20, 2013 Modeling GHG, land use, and water use impacts of the global supply chain Determining the natural capital costs of environmental impacts Today’s increasingly complex and globalized economy is rapidly consuming the world’s natural resources and degrading the ecosystem services provided by these resources. The depletion of natural capital – the stock of typically undervalued goods and services provided by nature – is a major threat to a productive global economy. Measuring and managing natural capital is becoming a significant business issue, yet determining the environmental impacts of a deep and sophisticated supply chain remains a challenge. Furthermore, once impacts are calculated, it is difficult to make sense of those impacts and prioritize multiple environmental concerns. To address these issues, Climate Earth has developed the Natural Capital Management System (NCMS): a scalable, web-based system that enables companies to actively manage natural capital assets. (To download our white paper on managing natural capital assets, visit our NCMS webpage at http://www.climateearth.com/ncms.) This paper describes the two methodologies underlying our NCMS technology. The first, multiregional input–output life cycle assessment (MRIO-LCA), measures the environmental impacts throughout a global Business Intelligence for Sustainable Management supply chain and models the location in the value chain where they occur. The second, natural capital valuation (NCV), allows calculated impacts to be valued, compared, and managed using a consistent unit of measure: the financial value of depleted natural capital. In this paper, we discuss our current methods for MRIO-LCA and NCV as applied to the NCMS project completed for Webcor Builders in October 2013. This project assessed the natural capital costs incurred during the construction of the San Francisco Public Utilities Commission headquarters building, completed in June 2012. It is part of a larger strategy to enable Webcor to collaborate with future clients in reducing natural capital costs before and during construction, and to provide post-construction results for all major construction projects. Climate Earth is dedicated to remaining transparent about the application of these emerging technologies. We also strive to partner with leading research organizations and rapidly adopt the most appropriate data and methodologies as they are developed. This strategy of rapid adoption best serves the needs of our clients to go beyond accounting and actively engage in the management of natural capital assets. Business Intelligence for Sustainable Management Methodology overview The calculation of natural capital costs occurs in two steps. First, a multiregional input–output life cycle assessment (MRIO-LCA) model is used to convert company spend data into global supply chain environmental impacts. In the case of the Webcor SFPUC project, we focused on three impact categories: global warming potential (“GHG”) in kg CO2e, forest land use impacts (“land”) in acres of forest land, and water use impacts (“water”) in kg water. Second, natural capital valuation (NCV) factors are applied to convert global supply chain impacts into natural capital costs in financial units. Thus, impacts from GHG, land, and water can be compared using a common unit of dollars of natural capital depletion. The figure below illustrates the higher- level process of calculating the natural capital costs from company spend data. Multiregional input–output life cycle assessment The multiregional input–output life cycle assessment (MRIO-LCA) model can be further broken down into two subprocesses: MRIO analysis, which models global economic activity, and environmentally-extended input– output LCA (EEIO-LCA), which translates global economic activity into environmental impacts. MRIO analysis Traditional input–output analysis methods model the embedded economic activity resulting from direct spend; MRIO analysis extends the results to other countries. Mapping spend The first step in MRIO analysis is to map each element of spend data to the 430 economic sectors used by the United States Bureau of Economic Analysis (BEA) [1]. Once mapped, the spend data is adjusted to the model year of 2002 using the yearly average Producer Price Index (PPI) values [2], based on the mapped sector and spend year. The SFPUC project spanned a time period between 2008 and 2012. NCMS Methodology White Paper www.climateearth.com 3 Business Intelligence for Sustainable Management Modeling economic activity Economic activity is modeled using input–output (I–O) tables from the Comprehensive Environmental Data Archive (CEDA) [3], based on the BEA’s 2002 benchmark input–output accounts. These tables include not only the cost at the final manufacturing facility (the first tier in the supply chain), but also the breakdown of upstream supply chain costs resulting from this first-tier spend. For example, initial demand of architectural metal products involves additional economic activity in upstream sectors – mining metal ores, smelting, making metal parts, and forming subassemblies, as well as energy generation throughout the supply chain – all of which are calculated from these tables. The I–O tables in CEDA, representing economic activity in the United States, are also used to model foreign economies under the “import assumption” [4] (also known as “autonomous regions” [5] and “mirrored economy” [6]). For the SFPUC project, the first tier of spend was assumed to occur entirely within the United States. In subsequent tiers, US spend was split between domestic and imported spend using country recipes. Creating country recipes Country recipes indicate the source of production for the average commodity purchased in a particular country. For the SFPUC project, country recipes were limited to modeling the US supply of commodities under the “uni-directional trade” assumption, which reduces data requirements without introducing large errors [4]. For a particular commodity (sector), the fraction of US purchases originating from other countries is calculated from the import matrix, a supplementary table accompanying the BEA’s 2002 benchmark I–O accounts [7]. Global trade flow data from the United Nations Commodity Trade Statistics database (UN Comtrade) [8] is used to further break down imports into individual countries of origin. For example, according to the BEA’s import matrix, 18.5% of “flat glass manufacturing” originated outside of the US. Of those imports, 22% came from China and 17% came from Germany. Thus, the first three country recipe values for “flat glass manufacturing” in the US are: US: 81.5% (= 100% − 18.5%) China: 4.1% (= 18.5% × 22%) Germany: 3.2% (= 18.5% × 17%) For a particular sector and country (e.g. “flat glass manufacturing” in the US), country recipe values over all source countries sum to unity. Each country recipe contains a “long tail” of countries that contribute very small percentages to the US supply of commodities. To reduce the number of calculations performed, ten countries were selected based on where foreign impacts were likely to occur. As a result, the original country recipes were collapsed into values for the US, the ten selected countries, and the “rest of world” (ROW) containing the sum of values for all other countries. Modeling the international supply chain The basis of traditional I–O models is the ( ) matrix, also known as the Leontief inverse after the Nobel Prize-winning work of Wassily Leontief [9]. It allows for the calculation of economic activity resulting from NCMS Methodology White Paper www.climateearth.com 4 Business Intelligence for Sustainable Management spend in an economy made up of many interdependent sectors, and represents the sum of first-tier purchases, second-tier purchases resulting from first-tier purchases, and so forth. In the MRIO model developed by Climate Earth, this convergent infinite series is broken down into its individual parts, allowing for allocation of domestic spend across countries (representing commodity imports) between each tier of the calculation. These iterative calculations are repeated until total allocated spend reaches a threshold of 99% of the total embedded spend (calculated by multiplying the Leontief inverse by company spend, as in traditional I–O analysis), at which point closed economies are assumed and the remaining economic activity is calculated internally for each individual country using the Leontief inverse. The result of these calculations is the modeled embedded economic activity in each country-sector (e.g. glass manufacturing in China, wood product manufacturing in Canada) resulting from company spend. EEIO-LCA Environmentally-extended input–output life cycle assessment (EEIO-LCA) augments traditional input–output analysis with environmental satellite accounts, which give average impacts per dollar of economic activity in a given sector. These are calculated by dividing the total direct impacts per sector over a given year (in impact units, e.g. the fruit farming sector’s direct water withdrawals in kg of water) by the total output of that sector in that year (in units of model year dollars, e.g. the fruit farming sector’s output in USD2002). The results of MRIO