US I/O Model(s) and the integration with other data sets Gregory A. Norris Sylvatica / Harvard University / U. New Hampshire USA

Development of PLCA data n Total output y i from “unit process” during specified period n Vector z i of total inflows from other processes during period n Vector of total pollution and resource flows f i during period Inflow factors = Pollution, resource flow factors =

Notation Z = transactions matrix (z ij =$/yr) A = direct requirement coefficients matrix (a ij =$/$) F = environmental intervention coefficient matrix (e.g., process inventory flows) (f ij =e.g., kg/$) x = total output ($) y = final demand ($)

Transactions Matrix (Z)

Transactions Matrix (Z)  Direct Requirements Coefficients (A) Direct Requirements Coefficients Input / Total Industrial Output

IO LCA Data Basis n National Accounts n Supply of goods and services by industries n Use of goods and services by industries n Supply/Use framework standardized by Stone, United Nations (1968, current revision 1993) n Industry: “A group of establishments engaged in the same, or similar, kinds of activity” (UN 1993) n ISIC: International Standard Industrial Classification: digit industry “classes”; nations aggregate / disaggregate n Establishment: n Single location n Single main type of productive activity n Enterprise: (e.g., “company”) may own many establishments, which may be in different ISICs

Rectangular Make & Use Matrices… for impact analysis, need symmetric IO matrix (com x com, or ind x ind) Make = commodities inds Use = industries coms

IO matrix creation: math and modeling assumptions – multiple possibilities in practice n Ind x Ind n Negative transfer method (Stone ’61) equivalent to LCI “avoided products” or “system expansion” n Aggregation (value-based allocation) n “Industry Technology Assumption” (value-based allocation plus market share-weighted production) Use coeff’s (per $ ind out) Market shares

IO matrix creation: Commod by Commod n “Commodity technology assumption” n Same input structure used to produce a given commodity, regardless of industry n Use technology or survey data n Use data from primary producing industry n Can lead to negative coefficients in IO matrix n Requires invertible square Make matrix (generally via commodity aggregation)

Given IO matrix, Adding pollution (or any impact) data is basic, and equivalent to PLCA system x i = sector i economic output ($/yr) p ij = sector i pollutant j release (kg/yr) p ij = f ij = sector i pollution intensity (kg/$) yiyi Given IO matrix and pollution coefficients, Computations are equivalent to PLCA system

US IO Data: 2 Main Sources n Bureau of Economic Analysis (BEA), of US Department of Commerce n Bureau of Labor Statistics (BLS), of US Department of Labor

BEA I/O Accounts n The “Benchmark” National I/O Accounts n Released every 5 years, as result of economic census n Summary tables (~80 sectors) n Detailed tables (~500 sectors) (SIC4) n 1992 is most recent census data year n Annual updates (detailed available upon request; ) n Soon will see major new census-based tables for 1997

BLS I/O Accounts n Less sector detail n ~300 sectors, corresponding to SIC3 n Annual and consistent time series data from ; projection for 2010 n Annual and consistent final demand time series data

Environmental Data for Integration 1 n Toxic Release Inventory (EPA) n Annual, n SIC4 basis n >400 pollutants, air/water/land/underground n Self-reported, various bases n Sector and pollutant coverage evolving n Reporting thresholds within reporting sectors n Chemical use n Number of employees

Environmental Data for Integration 2 n Criteria Air Pollutants n PM10, PM2.5, SOx, NOx, VOCs, CO n Inventory Approach n Expenditure Approach

Inventory Approach n US EPA National Emission Trends db n Annual, 2000 most recent n Point, Area, Mobile sources n Point by SIC4, state n Area and Mobile by “source classification code” (SCC) n Partial allocation of area and mobile sources to SIC4 possible

Expenditure Approach Expenditures ($/yr) Price ($/MJ, $/liter) Quantity (MJ/yr) Emission factor (kg/MJ) Emissions (kg/yr)

Expenditure Approach Expenditures ($/yr) Price ($/MJ, $/liter) Quantity (MJ/yr) Emission factor (kg/MJ) Emissions (kg/yr) IO Tables, “work files” Energy Information Administration (EIA) Prices vary by sector US EPA “AP 42” Factors vary by technology Process emissions not addressed

Work Files Data

Price Data n State Energy Price and Expenditure Report n Annual n Industrial / Commercial / Transportation / Electric Utilities / Residential n Manufacturing Energy Consumption Survey (MECS) n 1991, 1994, 1998 n Various SICs (SIC4, SIC3, SIC2)

Sector Fuel Price Variability EIA Price (Industrial), 98 Average (91, 94) Ratio of sector to EIA Industrial price By sector, by fuel Estimated Prices, 98

Summary Regarding Estimation n n Inventory approach n n Misses mobile and area sources unless partially allocated n n Captures process emissions n n Uncertainties unknown n n Expenditure approach n n Uncertainties in price (sector, year, fuel) n n Uncertainties in emission factor (sector, technology, fuel, yr) n n Uncertainty lower bound estimable

Other Environmental Data n Water pollution from point sources (EPA) n Pesticides (CML, CMU) n Hazardous waste (CML, CMU) n Expenditures on disposal of solid and hazardous waste (Economic census) n Occupational injuries and fatalities (BLS)

Summary n Data integration = modeling n Transparency and open exchange needed for IO as with Process LCA n Uncertainty analysis needed