1. presented to presented by Cambridge Systematics, Inc. Transportation leadership you can trust. State and Local Freight Data Using National Freight Data for Local Planning FHWA Talking Freight Seminar May 2010 Dike Ahanotu, Ph.D.

2. Topics National freight data sources – CFS, FAF, TRANSEARCH »Considerations for local freight planning efforts »NCFRP 20 – preliminary findings and next steps Developing local freight data »Potato production example »Diesel production example 2

3. National Data BTS Commodity Flow Survey - Overview Why focus on CFS? »Basis of FHWA FAF2 »Dominant source for short-distance truck trips in TRANSEARCH Shipper survey of select industry sectors »Over 100,000 responses across most significant industries »Survey data expanded to 117 regions, 7 modes, and 23 commodities Very useful for freight planning efforts 3

4. National Data BTS Commodity Flow Survey – Missing Data Sectors included in the survey »Mining, manufacturing, wholesale trade, select retail trade industries, auxiliary establishments Sectors not included in the survey »Farms, forestry, fishing, utilities, construction, government- owned entities, transportation, most retail and services industries, foreign-based businesses importing into the U.S. Missing data due to »Cells with small or zero values »Proprietary concerns when a single firm dominates a particular O-D-M-C combination 4

5. National Data BTS Commodity Flow Survey – Survey Mechanism 40 shipments requested from each shipper »Shipments reported at regular intervals (e.g., every 20 th shipment) »Multistop tours recorded as single shipments from shipper to each stop along the tour 5

6. National Data BTS Commodity Flow Survey – Summary of Issues Several sectors not included – many are local truck trips Trip chaining not captured Full supply chain of import flows not included Open questions »How are firms handled that cross industries (e.g., Hewlett Packard)? »How did individual firms interpret shipment information requests? For example, did they include parcels? »How did firms respond when they had incomplete information? »How did firms respond when they had unsophisticated shipment record storage systems? 6

7. National Data FHWA Freight Analysis Framework Key features »Built entirely from public data sources »Transforms CFS data to complete freight flow database »Log-linear modeling and IPF used to fill in “zero” cells »Employment, population, and VIUS truck VMT data used for out-of-scope CFS sectors Biggest issues »Technique to fill in zero cells is somewhat problematic for data suppressed for proprietary reasons »No field data used to validate methods used for out-of-scope sectors »Relationships will not hold true for all localities 7

8. National Data TRANSEARCH Privately maintained freight flow database Off-the-shelf, county-level freight flow data available relatively quickly Key features of methodology »Heavier reliance on economic data »Motor carrier data exchange used to distribute truck trips »CFS still heavily used for shorter distance truck trips Biggest issues »Similar issues to CFS at local level 8

9. NCFRP 20 Summary of Preliminary Findings Several attempts to disaggregate FHWA FAF Less frequent efforts to develop ground-up freight flow data to supplement or substitute other sources Very few efforts to validate the relationship between socioeconomic data and freight flows »Limited data indicate that this method works better for some commodities rather than others 9

10. NCFRP 20 FAF2 Disaggregation Example Method to correlate economic data to commodity tonnage flows (production data) 10 SCTG Commodity Being Estimated Employment Data Used to Estimate the Commodity “Fit” 20-23Various*Chemical Manufacturing11% 10-15Various**Mining (except oil and gas)13% 9Tobacco ProductsBeverage and Tobacco Product Manufacturing15% 1Live Animals/FishSupport Activities for Agriculture and Forestry17% 16Crude PetroleumOil and Gas Extraction21% 38Precision InstrumentsMiscellaneous Manufacturing34% 24Plastics/RubberPlastics and Rubber Products Manufacturing43% 2Cereal GrainsFood Manufacturing, Farm Acres48% 8Alcoholic BeveragesBeverage and Tobacco Product Manufacturing50% 39FurnitureFurniture and Related Product Manufacturing56% 4Animal FeedSupport Activities for Agriculture and Forestry60% * SCTG 20-23 is Basic Chemicals, Pharmaceutical Products, Fertilizers, and Chemical Products and Preparations n.e.c. ** SCTG 10-15 is Monumental or Building Stone, Natural Sands, Gravel and Crushed Stone, and Nonmetallic Minerals n.e.c.

11. NCFRP 20 Next Steps (Preliminary) Identify freight planning applications Develop generic supply chain descriptions »High value, high volume, highly problematic Assess methods for compiling subnational commodity flow data in terms of »Meeting needs of freight planning applications »Filling in gaps of existing commodity flow databases »Describing important supply chains Collect small sample of new data to validate methods »May involve analysis of existing local databases Develop guidebook on subnational commodity flow data 11

12. Developing Local Freight Data General methodology »Estimate value of commodity generated based on economic output data from public sources or trade associations »Convert value to tonnages using sources such as CFS »Identify mode share from state or national data or industry experts »Convert modal tonnage to vehicle data using sources such as VIUS Two Washington examples show range of applications for this methodology 12

13. Washington Potato Example Production Potato production identified based on USDA and Washington State Potato Commission 13 Source: WSDOT Development and Analysis of a GIS-Based Statewide Freight Data Flow Network; Goodchild, Jessup et al, 2009

14. Washington Potato Example Production (continued) Supply chain and potato processors identified by Washington State Potato Commission 14 Source: WSDOT Development and Analysis of a GIS-Based Statewide Freight Data Flow Network; Goodchild, Jessup et al, 2009

15. Washington Potato Example Production (continued) Potato distribution identified by Commission survey Freight flows were ultimately assigned to trucks and routed on the Washington highway network 15 Major Destinations Lower Basin Skagit Valley Upper Basin Eastern Washington12.48%2.03%6.22% Western Washington14.29%6.81%6.40% Oregon2.31%4.35%1.25% California14.58%40.72%11.85% Idaho0.00% 34.33% States West of the Mississippi22.01%13.30%12.76% States East of the Mississippi24.26%23.58%11.99% Canada8.85%7.04%2.91% Mexico0.14%1.96%0.25% Other International1.09%0.20%12.03% Source: WSDOT Development and Analysis of a GIS-Based Statewide Freight Data Flow Network; Goodchild, Jessup et al, 2009

16. Washington Diesel Supply Chain Example Diesel distribution data held in a multitude of locations by a number of agencies and private sector companies WA DOA – regulates quality and quantity of fuel delivered at gas stations WA Department of Ecology – regulates active underground storage tanks, publishes vessel entry data U.S. EPA – regulates above-ground storage tanks WA DOR – responsible for assessing and collecting fuel taxes at terminal locations Other agencies monitor mode-specific activity (e.g., pipeline, waterborne activity, railroads) 16 Source: WSDOT Development and Analysis of a GIS-Based Statewide Freight Data Flow Network; Goodchild, Jessup et al, 2009

17. Washington Potato Example Production Data stitched together from several different sources produced a multimodal freight flow picture 17 Source: WSDOT Development and Analysis of a GIS-Based Statewide Freight Data Flow Network; Goodchild, Jessup et al, 2009

18. Conclusions on Collecting Local Freight Data Some commodities will be much easier than others May require a mix of actual data and estimated data »For example, could have good production data, but poor distribution data »Trade associations and industry experts are critical Likely cost-effective only for a select number of commodities or industries »Not cost-effective for developing entire commodity flow databases 18