US Airport-Pair Fares & Route Traffic — DOT DB1B Benchmarks

Official source. No API key. Pay per record.

Who this is for and the decision it supports

Airline network planners, travel-analytics and pricing teams benchmarking average fares and traffic on US city-pair markets (US DOT DB1B).

One record answers: for this origin-destination market and quarter, what were the average fare, traffic and the largest/lowest-fare carrier shares — a route-economics and competitive benchmark.

Sample output

Real rows from a live run of this actor (first 5 rows, selected columns).

One full record from the same run, exactly as delivered:

{
  "record_id": "202611013514112ABEPIE",
  "tbl": "Table1a",
  "year": 2026,
  "quarter": 1,
  "citymarketid_1": 30135,
  "citymarketid_2": 33195,
  "city1": "Allentown/Bethlehem/Easton, PA",
  "city2": "Tampa, FL (Metropolitan Area)",
  "airportid_1": 10135,
  "airportid_2": 14112,
  "airport_1": "ABE",
  "airport_2": "PIE",
  "nsmiles": 970,
  "passengers": 208.8888889,
  "fare": 121.8280319,
  "carrier_lg": "G4",
  "large_ms": 1,
  "fare_lg": 121.8280319,
  "carrier_low": "G4",
  "lf_ms": 1,
  "fare_low": 121.8280319,
  "tbl1apk": "202611013514112ABEPIE",
  "source": "U.S. DOT / Bureau of Transportation Statistics",
  "source_dataset": "tfrh-tu9e",
  "licence": "U.S. DOT / Bureau of Transportation Statistics. Public-domain U.S. Government work (17 U.S.C. 105). Reproduced verbatim; no third-party content or logos.",
  "attribution": "U.S. DOT, Office of the Assistant Secretary for Aviation and International Affairs",
  "caveat": "Fares are average market fares over a quarter, not bookable or current prices, and exclude taxes/ancillary fees per the DOT methodology. City geocode/address columns are intentionally excluded. Values reproduced verbatim.",
  "observed_at": "2026-09-25T17:27:36Z"
}

What one record is

Each record is one DB1B city-pair market x quarter: city and airport ids, distance, passengers, average fare, and largest/lowest-fare carrier and their market shares and fares.

Your first run

Paste this input and run it — the last 10 quarters of the New York JFK – Los Angeles LAX market:

{
  "airportPairs": ["JFK-LAX"],
  "maxRecords": 10
}

Here is the first record that input returned when checked (Sep 2026; newest quarter first):

{
  "record_id": "202611289212478LAXJFK",
  "year": 2026,
  "quarter": 1,
  "city1": "Los Angeles, CA (Metropolitan Area)",
  "city2": "New York City, NY (Metropolitan Area)",
  "airport_1": "LAX",
  "airport_2": "JFK",
  "nsmiles": 2510,
  "passengers": 5780.111111,
  "fare": 508.3078641,
  "carrier_lg": "DL",
  "large_ms": 0.4315026624,
  "fare_lg": 609.068748,
  "carrier_low": "B6",
  "lf_ms": 0.3040637435,
  "fare_low": 357.6894239
}

fare is DOT's overall average fare (US dollars) for the quarter, with the largest carrier's and the lowest-fare carrier's averages and market shares; passengers is passengers per day. These are published historical averages, not bookable or current prices.

DOT aggregates these as directionless markets: traffic in both directions is added together and each pair is listed once per quarter, in one fixed order (here LAX first), so JFK-LAX and LAX-JFK return the same rows.

Coverage limit (from DOT): this table only lists airport markets where the origin or destination airport shares its city market with another commercial airport. In 2026 Q1 that meant 2,080 markets touching 17 multi-airport city markets: Boston, Chicago, Cleveland, Columbus, Dallas/Fort Worth, Denver, Houston, Los Angeles, Miami, New York, Norfolk, Phoenix, San Francisco, Seattle, Spokane, Tampa and Washington (checked: every row has at least one such end). A route with neither end in one of them is not in this table; a search for it returns nothing and costs nothing. Other searches: {"airports": ["SEA"], "year": "2026"} for every Seattle market in 2026; {"cities": ["Seattle"], "airports": ["JFK"]} for JFK to any airport in the Seattle market.

What the sample costs: $0.05 per record. The sample above delivers 10 records, so it costs at most $0.50.

Pulling in bulk

Raise Maximum records to pull the full historical panel of US city-pair markets. A buyer pulls the full multi-decade panel to model fare trends, market concentration and route economics.

To expand from the sample: raise Maximum records, and widen any filters shown in the input. You are billed only for records actually delivered, so a sample stays cheap and a full pull is predictable.

When to run it again

US DOT publishes DB1B quarterly; the actor returns the full series (earliest quarters first).

Update schedule: Quarterly — US DOT releases DB1B each quarter with a lag. Verified live: records carry year and quarter; the source is the official DB1B market table.

How this is different

US airport-PAIR (route/market) fares and traffic — distinct from the country-level EU Air Passenger Flow actor. This is route-level economics.

Limitations (source coverage vs product coverage)

• ROUTE/MARKET level (city-pair), and fares are AVERAGE market fares over a quarter — not bookable, current, or itinerary-level prices.
• By default the newest available quarter is returned first (currently 2026 Q1). Use the year (and optional quarter) inputs for a historical window; the full multi-decade panel back to 1993 stays reachable. Each record is one market-quarter, unique on the source key (tbl1apk).
• Excludes some ticket types per DB1B methodology.
• Table 1a only covers airport markets where the origin or destination airport shares its city market with another commercial airport (DOT's own scope note; 17 such city markets in 2026 Q1, e.g. New York, Chicago, Los Angeles, San Francisco, Washington, Seattle SEA/BFI).

FAQ

Are these current bookable fares?

No. They are quarterly average market fares from US DOT DB1B, historical by design.

Can I pull only the latest quarter?

Yes. Leave year blank for the newest quarter first; set year (and optional quarter) for a historical window, e.g. year=1993, quarter=1. An unavailable period returns an honest empty result.

Route or country level?

Route/market (city-pair) level.

How much does it cost? You pay $0.05 per fare record delivered to your dataset (less on higher Apify plans). Set the record limit in the input to cap what a run can cost. Records that are not delivered are never charged.

How do I get the data out? Every run saves its records to an Apify dataset. You can download it as JSON, CSV, Excel, XML or HTML from the run page, or read it through the Apify API.

Can I run it on a schedule? Yes. Use Apify Schedules to run it daily, weekly or monthly, with the same input each time.

Can I call it from my own code? Yes. Call nexgensignal/us-airport-pair-fare-records through the Apify API or the Apify Python and JavaScript clients, pass the same JSON input as the form, and read the dataset when the run finishes.

What happens if the source is down? The run ends with a clear status message, and nothing is charged for records that were not delivered.

Input fields

Every input this actor accepts, read from its input schema:

Field	Type	Default	Description
airportPairs	array		Airport pairs like JFK-LAX; either order matches (DOT lists each pair once).
airports	array		3-character airport codes as DOT publishes them; matches either end of the market.
cities	array		Text in DOT's city-market name at either end, e.g. Seattle.
maxRecords	integer	10	Maximum records delivered and billed. You are billed only for records actually delivered. Raise it to pull the full set.
year	string		Leave blank for the latest available quarter first. Set a 4-digit year (e.g. 2026) for a historical window.
quarter	string		Optional quarter within the chosen year.

Default changed on 30 Sep 2026: if you leave maxRecords out, a run now returns up to 10 records (it was 500). Set maxRecords yourself to get more — the maximum is unchanged.

Output fields

Every field in each delivered record, read from its output schema:

Field	Type	Meaning
record_id	string	Composite source-native key.
tbl	string	Source table id, verbatim.
year	number	Year of the quarterly market observation.
quarter	number	Calendar quarter (1-4).
citymarketid_1	number	DOT city-market id, endpoint 1.
citymarketid_2	number	DOT city-market id, endpoint 2.
city1	string	City-market name, endpoint 1.
city2	string	City-market name, endpoint 2.
airportid_1	number	DOT airport id, endpoint 1.
airportid_2	number	DOT airport id, endpoint 2.
airport_1	string	Airport code, endpoint 1.
airport_2	string	Airport code, endpoint 2.
nsmiles	number	Non-stop market distance in statute miles.
passengers	number	Average daily passengers in the market.
fare	number	Average market fare (USD).
carrier_lg	string	Carrier with the largest market share (code).
large_ms	number	Largest-carrier market share (fraction).
fare_lg	number	Average fare of the largest carrier (USD).
carrier_low	string	Lowest-fare carrier (code).
lf_ms	number	Lowest-fare carrier market share (fraction).
fare_low	number	Lowest carrier fare (USD).
tbl1apk	string	Source-native primary key for the market-quarter row.
source	string	Data source.
source_dataset	string	Socrata resource id.
licence	string	Licence / public-domain notice.
attribution	string	Required attribution string.
caveat	string	Interpretation caveat.
observed_at	string	UTC timestamp the record was retrieved.

Related actors

• eu-air-passenger-flow-records — country-level EU air passenger volumes
• company-data-enrichment-api — resolve carriers to legal entities
• world-bank-project-records — transport-sector development projects

Source, licence and how it is built

Source and licence are carried on every record (source, licence, attribution, observed_at). The actor reads only the official public endpoint, honours the source's robots and licence terms, and emits values unmodified with full provenance. Records are keyed on a stable id so re-runs upsert cleanly into a table you keep. Row delivery and billing are exactly equal: you are charged once per record delivered (push-then-charge), so an empty run costs nothing.

Part of NexGen Signal — official-source data products.