The nation’s transit industry carried about 1 percent more trips and passenger miles in 2014 than in 2013. But to carry that many, industry operating costs grew by 7 percent and maintenance costs grew by 2 percent. For that increase in operating costs, vehicle revenue miles grew by less than 3 percent.
Transit is thus becoming increasingly expensive to operate and maintain per rider: the operating cost of single trip grew from $3.81 to $4.04, a 6 percent increase. Fares, meanwhile, grew by just 2 percent, and the industry as a whole collected just $15.1 billion in fares while spending $42.4 billion on operations, $11.0 billion on maintenance, and $6.0 billion on capital improvements.
These numbers are from the 2014 National Transit Database that the Federal Transit Administration posted last week. The numbers are only tentative, however, as the FTA took the numbers down this week (though some of the data are still available if you know where to look for them–see below). Moreover, a few key spreadsheets were missing from the data that were posted.
Since at least 1997, the FTA has posted the database in two forms: data tables and database. The data tables are easier to read with more explanatory heading, but the database is easier to use for industry-wide calculations. For example, many of the data tables have subtotals for each transit agency, so if you try to sum all the data in the table, you will double count. Another difference is that most numbers in the data tables are in thousands while in the database they are in units, so the data table numbers must be multiplied by 1,000 to make them comparable to the database.
FTA’s database for 2014 included only 20 of the 25 spreadsheets that were posted in 2013. Missing were the service spreadsheet (showing such things as annual riders, weekday riders, passenger miles, and vehicle revenue miles), operating expense spreadsheet, and vehicle inventory spreadsheet. Fortunately, most of these data, though not the weekday riders or vehicle inventory, can be found in the data tables, keeping in mind that all those numbers are in thousands.
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This week, links to both the database and data tables were removed from the National Transit Database web site, suggesting that last week’s posting may have been a mistake. The database page is no longer available, but the data table page can still be read, though this is the only link to it you are likely to find today.
Considering Monday’s discussion of energy consumption, it is worth noting that transit’s energy efficiency improved by 2.8 percent in 2014. The energy efficiency of light rail, streetcars, and hybrid rail (meaning Diesel-multiple units such as Austin and Portland’s commuter-rail lines) all got worse, but the efficiency of buses and heavy rail both improved.
Transit agencies only reported energy consumption for about 92 percent of the vehicle miles travelled in 2014, so the rest of the industry may not be as efficient. For those that reported, the average energy cost was 3,141 BTUs per passenger mile, which is almost identical to the average energy cost per passenger mile for cars in 2013 (which was 3,144).
As usual, the Antiplanner has compiled the data into a single spreadsheet (0.5-MB) showing trips, passenger miles, fares, operating costs, capital and maintenance costs, rail miles, energy consumption, greenhouse gas emissions, and similar data for each transit agency and mode of transit. I’ve corrected for the numbers that were in thousands, and left blanks for such things as average weekday ridership and average number of seats per vehicle to be filled in when the FTA posts the rest of the data.
The raw data in the table fill 28 columns and 1894 rows. The energy consumption in BTUs and carbon-dioxide emissions in grams are calculated using standard conversions such as one gallon of Diesel fuel produces 138,700 BTUs and emits 22.384 pounds of carbon dioxide. The only other calculations I’ve made in the spreadsheet are mode totals at the bottom, both for all transit and for transit for which BTUs can be calculated. I’ll repost the spreadsheet with some additional calculations such as urban area totals when the rest of the data become available.
Maybe they realized the numbers were too accurate and withdrew them to massage everything a little.