Use of FAF Data for Florida Multimodal Freight Analysis

Use of FAF Data for Florida Multimodal Freight Analysis

Report

prepared for

Systems Planning Office, Florida Department of Transportation

prepared by

Cambridge Systematics, Inc.

September 2008

report

prepared for

Systems Planning Office, Florida Department of Transportation

prepared by

Cambridge Systematics, Inc.

2457 Care Drive, Suite 101

Tallahassee, Florida 32308

date

October 2008

Use of FAF Data for Florida Multimodal Freight Analysis

Report

Use of FAF Data for Florida Multimodal Freight Analysis

Table of Contents

1.0Introduction

1.1Background and Need

2.0FAF2 Data

2.1Florida FAF2 Data

3.0Commodity Based OD Data

3.1Commodity Flow Survey (CFS)

Industry Coverage

Shipment Coverage

CFS Strengths and Weaknesses

3.2Global Insight TRANSEARCH

4.0Mode Specific Freight Data

4.1Vehicle Inventory and Use Survey

4.2Carload Waybill Sample

4.3Waterborne Commerce Statistics Database

5.0Economic/Industry Data

5.1Input – Output Data

Analytical uses

Statistical uses

5.2County Business Patterns

Industry Classification of Establishments

Geographic Classification of Establishments

Reliability of Data

6.0Disaggregation Methods

6.1Regression Methods

6.2Multinomial Logit Models

Truck VMT Approach

TransCAD O-D Matrix estimation

7.0Methodology for Disaggregating Florida FAF2 Data

7.1Development of Regression Equations

7.2Development of expansion factors

7.3Incorporating Import Data

7.4Future Year Forecast

8.0Future Work

Systems Planning Office, FDOT1

Use of FAF Data for Florida Multimodal Freight Analysis

List of Tables

Table 2.12002 Commodity Flow by Mode (thousands of tons)

Table 2.22035 Commodity Flow by Mode (thousands of tons)

Table 7.1Two Digit SCTG Commodity Classification

Table 7.2Production Equations (2002 thousands of tons)

Table 7.3Attraction Equations (2002 thousands of tons)

Table 7.4Matrix Expansion Results

Table 7.5Sample Shipment from the FAF2 That Has an International Origin

Table 7.6Share of Import Tonnage in 2002 among Ports in the FL Miami FAF2 Region

Table 7.7Sample Shipment from the FAF2 That Has an International Origin and disaggregated to US Counties by Port

Systems Planning Office, FDOT1

Use of FAF Data for Florida Multimodal Freight Analysis

List of Figures

Figure 1.1Vehicle-Mile Traveled (VMT) and Lane-Miles: 1980-2000

Figure 1.2Florida VMT and Lane Miles (1981 - 2006)

Figure 2.1FAF2 Methodology

Figure 2.2FAF2 Network

Figure 2.3FAF2 Regions

Figure 2.4Florida FAF2 Regions

Figure 6.1Factors Affecting Freight Transportation Demand

Systems Planning Office, FDOT1

Use of FAF Data for Florida Multimodal Freight Analysis

1.0Introduction

The last several decades have witnessed steady growth in the demand for freight transportationin the United States, driven by economic expansion and global trade. But today,the nation is entering the early stages of a capacity crisis. Freight transportation capacityis expanding too slowly to keep up with demand, and the freight productivity improvementsgained though investment in the Interstate highway system and economic deregulationof the freight transportation industry in the 1980s are showing diminishing returns.

The effects of growing demand and limited capacity are felt as congestion, upward pressureon freight transportation prices, and less reliable trip times as freight carriers struggleto meet delivery windows. Higher transportation prices and lower reliability can meanincreased supply costs for manufacturers, higher import prices, and a need for businessesto hold more expensive inventory to prevent stock outs. The effect on individual shipmentsand transactions is usually modest, but over time the costs can add up to a highercost of doing business for firms, a higher cost of living for consumers, and a less productiveand competitive economy.

1.1Background and Need

Increases in the volume of freight have strained the transportation network in some locations and exacerbated conflicts between the traveling public and freight carriers. Recent growth in international trade has placed greater pressure on gateways, ports, airports, and border crossings—nodes in the system that are potential bottlenecks for the movement of freight. Between 1990 and 2000, U.S. international trade more than doubled (in inflation-adjusted terms), rising from about $900 billion to $2.2 trillion. Nearly one-third of U.S. merchandise trade in 2000 was with Canada and Mexico[1]. Many gateways already suffer from congestion, which has intensified by heightened security following the terrorist attacks of September 11, 2001.

Additionally, the creation of NAFTA (North American Free Trade Agreement) has fostered north-south traffic, placing more demands on the domestic freight transportation system. Since NAFTA went into effect in 1994, U.S. trade with Canada and Mexico has risen by about 90 percent[2]. As a result, the Nation's highway and rail networks—initially developed for the traditional east-west trade—are now strained, especially at border crossings. In the future, trade with NAFTA and Latin American countries is expected to grow along both north-south corridors and east-west corridors running through the northern and southern border regions. The anticipated growth in trade and changes in the character of freight flows present many challenges to America’s transportation system and highlight the importance of international gateways to the U.S. economy and security.

To further exacerbate the situation, the transportation network has not increased at a rate commensurate with growth in travel and commerce. In the highway sector, for example, vehicle-miles traveled (VMT) increased by 80 percent while lane-miles of public roads increased by only 2 percent between 1980 and 2000. Growth in truck-miles traveled was even more dramatic, exceeding the growth in passenger VMT over the last few years [3](USDOT FHWA 2001a). Clearly, more traffic is moving over essentially the same highway infrastructure. Other surface transportation networks are witnessing a similar overburdening of their systems as well. Figure 1.1 shows the growth in VMT and lane miles added over time.

Figure 1.1Vehicle-Mile Traveled (VMT) and Lane-Miles: 1980-2000

In Florida, while truck VMT does not exceed passenger VMT, the impact of trucks on the highway system is more acute in terms of congestion and pavement decay. Between 1981 and 2006 Florida saw passenger VMT grow by 168 percent and truck VMT growth by 95 percent. Figure 1.2 shows these trends along with the growth in lane miles. The figure also shows the annual and truck VMT in millions for 1990, 2000, and 2006 to give a sense of the growth over time. This historical growth along with growth projections that the population and employment growth between 2001 and 2030 is expected to be 46.5 percent[4]and 110 percent [5]respectively makes it important for Florida to get a better understanding of the factors that account for freight flow. The Freight Analysis Framework, version 2 (FAF2) provides a possible tool for understanding and evaluating the impact of freight on the transportation network. However, since the FAF2 datafocuses on national policy and planning issues, is not directly useful for state DOTs or Metropolitan Planning Organizations (MPOs). The focus of this research effort will be to develop models and approaches that can effectively allocate FAF2 data to smaller geographical areas in Florida. Doing so will allow assignment of the resulting Origin-Destination (OD) matrices to the Statewide Transportation Freight Model (STFM) transportation network.

Figure 1.2Florida VMT and Lane Miles (1981 - 2006) [6]

Systems Planning Office, FDOT1

Use of FAF Data for Florida Multimodal Freight Analysis

2.0FAF2 Data

The Freight Analysis Framework (FAF)[7]estimates commodity flows and related freight transportation activity among states, sub-state regions, and major international gateways. It also forecasts future flows among regions and relates those flows to the transportation network. FAF includes an origin-destination database of commodity flows among regions, and a network database in which flows are converted to truck payloads and related to specific routes.

The FAF commodity origin-destination database includes tons and value of commodity movements among regions by mode of transportation and type of commodity. Specific differences between Version 2.2 and 2.1 are:

• FAF2.2 contains projected commodity flow data ranging from 2010 to 2035 in five-year intervals as well as corrected 2002 base case data from Version 2.1.
• FAF2.2excludes all foreign-to-foreign shipments via the United States. These in-transit flows were partially covered in the "sea" file of Version 2.1.

Neither version includes international air cargo data, which will be added later.

The FAF2.2 2002 base year database is built entirely from public data sources. Key sources include the 2002 Commodity Flow Survey (CFS), developed by the Census Bureau, U.S. Department of Commerce, and the Bureau of Transportation Statistics (BTS), U.S. Department of Transportation; Foreign Waterborne Cargo data, developed by the U.S. Army Corps of Engineers; and a host of other sourcesthat are documented here[8]. FAF statistics do not match those in mode-specific publications primarily due to different definitions that were used to avoid double counting. FAF2.2 statistics should not be compared with original FAF data because different methods and coverage are employed. Methods in developing the 2002 base year data are transparent; and it has been expanded to cover all modes and significant sources of shipments. Future projected data covering years from 2010 to 2035 with a five-year interval are based on Global Insight's proprietary economic and freight modeling packages.

The 2002 FAF2.2 Commodity Origin-Destination Database is a product of the Federal Highway Administration (FHWA), developed in cooperation with the Bureau of Transportation Statistics (BTS) through contracts with Oak Ridge National Laboratory, MacroSys Research and Technology, Global Insight, and Battelle. Because the scope and methods have changed significantly, statistics from FAF2 and the original FAF should not be compared.

Figure 2.1 shows the methodology[9] used to derive FAF2 flow tables and figure 2.2 shows how the FAF2 network is derived. Figure 2.3 shows the 138 FAF regions.

Figure 2.1FAF2 Methodology

Figure 2.2FAF2 Network

Figure 2.3FAF2 Regions

FAF2 has seven modes and 43 commodities. The 43 commodities are classified as per the Standard Classification for Transported Goods (SCTG) code at the 2-digit level. Of the 43 commodities, 42 are known and one is unknown. The seven modes include:

Truck
Rail
Water
Air / Pipeline
Intermodal
Others

2.1Florida FAF2Data

Florida has five FAF2 regions – Jacksonville, Miami, Orlando, Tampa and “rest of Florida” (Figure 2.4). Tables 2.1 and 2.2 show the 2002 and 2035 distribution of commodity flows by mode respectively. As can be from Tables 2.1 and 2.2, the majority of commodities are transported via trucks (more than 85 percent) and most of the commodities are being distributed within the state and come from outside the state.

Figure 2.4Florida FAF2 Regions

Table 2.12002 Commodity Flow by Mode (thousands of tons)

2002
Mode / Within State / From State / To State
Number / Percent / Number / Percent / Number / Percent
Truck / 487 / 85 / 50 / 68 / 85 / 42
Rail / 60 / 11 / 17 / 23 / 37 / 18
Water (Domestic only) / <0.1 / <1 / 1 / <1 / 37 / 18
Air, air & truck (Domestic only) / <0.1 / <1 / 0 / <1 / 0 / <1
Truck & rail / <0.1 / <1 / 0 / <1 / 1 / <1
Other intermodal / 0 / <1 / 1 / 1 / 5 / 3
Pipeline & unknown / 27 / 5 / 5 / 7 / 36 / 18
Total / 575 / 100 / 74 / 100 / 202 / 100

Table 2.22035 Commodity Flow by Mode (thousands of tons)

2035
Mode / Within State / From State / To State
Number / Percent / Number / Percent / Number / Percent
Truck / 928 / 88 / 67 / 72 / 300 / 56
Rail / 56 / 5 / 14 / 15 / 113 / 21
Water / <0.1 / <1 / 0 / <1 / 18 / 3
Air, air & truck / <0.1 / <1 / 0 / <1 / 1 / <1
Truck & rail / 0 / <1 / 0 / <1 / 3 / <1
Other intermodal / 1 / 0 / 1 / 1 / 17 / 3
Pipeline & unknown / 64 / 6 / 10 / 10 / 85 / 16
Total / 1049 / 100 / 94 / 100 / 538 / 100

There is very little commodity flowing outside of Florida, which given the dominance of the service industry is to be expected. Also, total commodity flows are expected to grow by 98 percent between 2002 and 2035 with truck commodity flows increasing by 108 percent. Water, on the other hand, as a mode for carrying commodities is estimated to fall by 51 percent. These findings suggest the following:

• Over the next 35 years, there is going to be a substantial increase in truck trips in Florida;
• Rail commodity flow will increase by 61 percent; and
• Water as a mode for commodity transportation is underutilized and steps can be taken by policy makers to remedy this situation.

Given the increase in truck commodity flows over the next 30 plus years, it is important that policy makers address the issue of congestion on highway networks. In order to understand the impacts of congestion, it is necessary to determine how freight traffic is distributed on the transportation network and the FAF2 database offers a potential rich source of information to achieve this purpose. However, given the large geography of these FAF2 regions, it is necessary to disaggregate the FAF2 flows to county and TAZ geographies. The next section documents the various data sources for freight data analysis and describes in more detail the specific data sources that will be used for disaggregation.

Systems Planning Office, FDOT1

Use of FAF Data for Florida Multimodal Freight Analysis

3.0Commodity Based OD Data

3.1Commodity Flow Survey (CFS)

The CFS is a national survey of business establishments in selected industries, namely, mining, manufacturing, wholesale trade, and certain retail establishments. The survey captures data on shipments of goods originating from a sample of such establishments located in the 50 states of the United States and the District of Columbia. BTS and the Census Bureau of the U.S. Department of Commerce conduct the CFS. The Census Bureau administers the survey as part of the 5-yearly Economic Census.

The purpose of the CFS is to supply information on the flow of goods by mode of transport within the United States. Data are provided on tons, miles, ton-miles, value, shipment distance, commodity, and weight. All major modes of freight transportation (air, motor carrier, rail, water, and pipeline) and intermodal combinations are covered. Despite gaps in shipment and industry coverage, the CFS is the only Federal government data source that recognizes the need for such comprehensive information on freight flows.

Industry Coverage

The 2002 CFS covers business establishments with paid employees that are located in the United States and are classified using the 1997 North American Industry Classification System (NAICS) in mining, manufacturing, wholesale trade, and select retail trade industries, namely, electronic shopping and mail-order houses. Establishments classified in services, transportation, construction, and most retail industries are excluded from the survey. Farms, fisheries, foreign establishments, and most government-owned establishments also are excluded. The survey also covers auxiliary establishments (i.e., warehouses and managing offices) of multi-establishment companies, which have non-auxiliary establishments that are in-scope to the CFS or are classified in retail trade. The coverage of managing offices has been expanded in the 2002 CFS, compared to the 1997 CFS. For the 1997 CFS, the number of in scope managing offices was reduced to a large extent based on the results of the 1992 Economic Census. A managing office was considered in-scope to the 1997 CFS only if it had sales or end-of-year inventories in the 1992 Census. However, research conducted prior to the 2002 CFS showed that not all managing offices with shipping activity in the 1997 CFS indicated sales or inventories in the 1997 Economic Census. Therefore, the 1997 Economic Census results were not used in the determination of scope for managing offices in the 2002 CFS.

Shipment Coverage

The CFS captures data on shipments originating from select types of business establishments located in the 50 states and the District of Columbia. The data do not cover shipments originating from business establishments located in Puerto Rico and other U.S. possessions and territories. Shipments traversing the United States from a foreign location to another foreign location (e.g., from Canada to Mexico) are not included, nor are shipments from a foreign location to a U.S. location. Imported products are included in the CFS at the point that they left the importer’s domestic location for shipment to another location. Shipments that are shipped through a foreign territory with both the origin and destination in the United States are included in the CFS data. The mileages calculated for these shipments exclude the international segments (e.g., shipments from New York to Michigan through Canada do not include any mileages for Canada). Export shipments are included, with the domestic destination defined as the U.S. port, airport, or border crossing of exit from the United States.

CFS Strengths and Weaknesses[10]

The CFS strengths include:

• Fully national in scope;
• Covers all the major surface transportation modes (truck, rail, water, petroleum pipelines), as well as shipments of air freight;
• Identifies the true geographic O-D of each shipment (and therefore also provides estimates of “door-to-door” shipment distances);
• Collects data on both the weight and dollar value of all in-scope shipments;
• Has a time series in the form of the 1993, 1997, and 2002 surveys; and
• Is done in conjunction with the Economic Census, providing concurrency with other data sets.

Particular weaknesses include:

• Not all commodities are covered by the CFS;
• The survey does not, in theory, capture imports;
• The spatial detail available to its mode-specific O-D matrices is limited to a small number of rather large geographic regions;
• The volume of intermodal freight reported may be low, due at least in part to definitional issues;
• The shipment length detail available from non-geographically disaggregated products is very limited in its supporting commodity-level detail;
• The surveys have seen some content changes, and a 4 to 1 reduction in sample size between 1993 and 2002 that makes for some large coefficients of variation in reported estimates; and
• There are discrepancies in the estimates generated by the CFS and the U.S. Army Corps of Engineers’ waterborne commerce data, the latter based on industry-wide carrier reporting that produces larger ton and ton-mileage figures.

3.2Global Insight TRANSEARCH

TRANSEARCH is a privately maintained comprehensive market research database for intercity freight traffic flows compiled by Global Insight. The development of the TRANSEARCH database involves the fusion of various freight traffic data sources into a common framework for planning and analysis. The database provides detailed U.S. and cross-border origin-destination freight shipment data at the state, Business Economic Area (BEA), county, metropolitan area, and zip-code level detail by commodity type (by Standard Transportation Commodity Classification (STCC) code) and major modes of transportation. Forecasts of commodity flows up to 25 years are available for the following four modes– air, truck, water, and rail.