Disaggregate State Level Freight Data to County Level October 2013 Shih-Miao Chin, Ph.D. Ho-Ling Hwang, Ph.D. Francisco Moraes Oliveira Neto, Ph.D. Center for Transportation Analysis Oak Ridge National Laboratory

Outline  Background  Freight Analysis Framework (FAF)  Major data sources  Methodology  Disaggregation process  Example  Results & Validations  FAF Ton-miles  Comparison with other freight data programs  Remarks

Background: Freight Analysis Framework (FAF)  Manages by the Office of Freight Management and Operations, Federal Highway Administration (FHWA)  Provides a comprehensive picture of freight movement among states and major metropolitan areas by all modes  Most current release is FAF3.4 database South, Central & Western Asia Eastern Asia Mexico Europe Africa Canada Rest of Americas Mexico SE Asia & Oceania Eastern Asia SW & Central Asia  Geography  123 domestic regions  8 foreign regions  Modes of transportation  Truck  Rail  Water  Air/air-truck  Multiple mode/mail  Pipeline  Others/unknown  43 Commodities

Background: Major Data Sources  Commodity Flow Survey (CFS)  Conducted under the partnership of U.S. Census and Bureau of Transportation Statistics (BTS)  Sample survey of business U.S. establishments & classified according to North American Industry Classification System (NAICS) codes  Latest available data: 2007 (i.e., base year data for FAF3)  County Business Patterns (CBP)  An annual data series from U.S. Census  Provides economic data by industry (# establishments, employment, payroll)  Latest available data: 2011  Industry Input-Output (I-O) Accounts  Annual I-O tables produced by the Bureau of Economic Analysis (BEA)  Make and Use Tables, by industry according to NAICS codes  Latest available data: 2011

FAF3 Disaggregation: Estimation of Ton-Miles  Tonnage and value of goods moved are important measures of the freight activity, but they do not necessarily reflect the usage of transportation systems  Environmental impact (emissions and fuel efficiency) of freight activity can be assessed using measures normalized by ton-miles  The revenue of transportation firms is related to the amount of freight in tones transported per mile  Main disaggregation steps  Linking freight activities with economic activities  Disaggregate FAF3 database (ODCM tonnage matrix) to county level  Estimate average shipment distance by mode on the multimodal network systems

Freight Flow Disaggregation Approach ω Origin county / Commodity, Mode ω Destination county / Commodity, Mode ω county-to-county by commodity & mode Production CBP Information theory o d i j Where (o, d) – FAF OD pair & (i, j) – County pair f FAF zone-to-zone, Commodity, Mode Attraction CBP BEA I-O Accounts (a pq ) ω O/ C, M = ∑ω O / I ω I / C, M ω D/ C, M = ∑ω D / I ω I / C, M

Methodologies/Models  Log-linear regression models for linking freight activity with economic activity by industry sector at state  Production: freight tonnage shipped & payroll of producing industry  Attraction: freight tonnage received & payroll of receiving industry  Estimates of county-level production/attraction shares by industry  Spatial distribution by matrix balancing procedures (or doubly constraint gravity model)

Distance Matrices Highway: Contains 500,000 miles of roadway in the US, Canada, and Mexico Railway: Contains every railroad route in the US, Canada, and Mexico that has been active since 1993 Waterway: Contains inland and off-shore links Intermodal Network

9Managed by UT-Battelle for the U.S. Department of Energy Estimated using the highway network system in GIS Baltimore Example: Destination County FIPS Origin County FIPS D =

10Managed by UT-Battelle for the U.S. Department of Energy FAF O-D Flow (short tons) t 242,241,truck = 171,747 FAF O-D Flow (short tons) t 242,241,truck = 171,747 FAF zone to county disaggregation – generation and attraction by county Annual payroll ($ 1000) in the origin counties Share of annual payroll ($ 1000) in the destination counties NAICS 311 FIPSTotal , , , Attraction Model (Attraction Share) Attraction Model (Attraction Share) Production Model (Production Share) Production Model (Production Share) NAICS 311 FIPSTotal , , , , , , ,440 PRODUCTIONS FIPSTons , , , Total171,747 ATTRACTIONS FIPSTons , , , , , , ,755 Total171,747

11Managed by UT-Battelle for the U.S. Department of Energy FAF to county disaggregation – distribution and spatial interaction ,54816,8932,0732,2634, ,312 3,8688, ,2052, ,697 12,09624,9632,1503,5746, , NAICS 311 FIPSTons , , , FIPS 22,61451,0595,1697,07112,9221,15671,755Tons

12Managed by UT-Battelle for the U.S. Department of Energy Matrix of Total Tons by Truck Destination County FIPS Origin County FIPS Total Tons ,84233,7443,9787,52416,0942,23226, , ,06690,1968,74718,27037,5554,55465, , ,845445,228102,33369,463180,52910,952302,784 1,314, ,372613,635102,795106,944342,45222,376482,374 2,055, ,469436,77645,59987,047206,27119,945361,597 1,520, ,79278,8096,42913,99128,1733,92257, ,699 Total Tons 1,122,3861,698,387269,881303,239811,07463,9811,296,0545,565,002 Matrix of Tons * Distance MatrixMatrix of Ton-miles

FAF Ton-miles Estimates Value/ Ton-miles ($) Include all domestic, exported, and imported shipments transported within the U.S.

Comparisons with Other Freight Data Programs U.S. Network Sub-system Data source / Modes Ton-miles (billions) HighwayFAF3 (Truck single mode only)2, CFS (Truck single mode only)1,342 Railway FAF3 (Rail single mode plus rail portion of multiple modes) 1, CFS (Rail single mode and portion of multiple modes which includes rail) 1, AAR report (all rail activities)1,820 Waterway FAF3 (water and the water portion of multiple modes) CFS (water and the portion of multiple modes which includes water) USACE waterborne commerce (all water activities) 506

Concluding Remarks  To carry out national transportation freight analysis and planning at a level of detail  The disaggregation methodology will provide more data at a more geographic detailed level for:  Environmental impact assessment  Vulnerability and resilience of freight multimodal network  Modal shift analysis  Truck weight and size studies  Further work is required to estimate freight flow models through FAF regions, by commodity, by mode.