In 2019, Singapore was the most efficient country in air transport services with a *** rating, which is measured based on the scale of one to seven. Singapore is known internationally for its leading position in the transportation industry. Singapore Changi Airport Singapore Changi Airport is one of the largest transportation hubs in Asia. The airport was ranked by Skytrax as the world’s best airport between 2013 and 2018. Between 2010 and 2019, the number of passengers arriving at Changi Airport increased continuously, reaching over ** million people. During that same period, the number of passengers in transit at Changi Airport declined from over *** million travelers to roughly *** million people. The number of aircraft departures from Changi Airport in Singapore grew from over ******* in 2010 to over ******* aircraft in 2019. This indicates how well the Changi Airport has kept the quality of transportation while achieving higher efficiency in handling passengers or cargo. Global air cargo Between 2004 and 2018, the worldwide air freight traffic increased by roughly ** percent, reaching over ** million metric tons in 2018. During the same period, the worldwide revenue of cargo airlines grew exponentially, up from ** billion U.S. dollars in 2004 to *** billion U.S. dollars in 2018. Except for the Middle East, the growth in cargo traffic worldwide was positive in 2018. For instance, cargo traffic growth rate at African airports was the highest globally, around *** percent. As an international high export-oriented country, China’s air cargo volume between 2008 and 2018 increased continuously, almost doubled in size. In 2019, North American air cargo fleet held the most air freighters globally. When it comes to the leading firms, DHL Supply Chain & Global Forwarding was the leading airfreight forwarder based on the volume of freight.

The average for 2019 based on 141 countries was 4.55 points. The highest value was in Singapore: 6.7 points and the lowest value was in Lesotho: 1.4 points. The indicator is available from 2006 to 2019. Below is a chart for all countries where data are available.

This statistic ranks the most connected countries in the aviation industry in 2019, based on airport connectivity. The United States was at the top of the list, with an airport connectivity score of **** million.

Italy Passenger Air Transport was up 3.9% in 2019, from a year earlier. Need to compare country statistics and get a global overview? Find all data easily.

Monthly number of passengers carried (arrivals plus departures), by type of transport (national, international, intra- and extra-EU). Passengers carried are (1) all passengers on a particular flight (with one flight number) counted once only and not repeatedly on each individual stage of that flight, (2) all revenue and non-revenue passengers whose journey begins or terminates at the reporting airport and transfer passengers joining or leaving the flight at the reporting airport. Excludes direct transit passengers. National aggregates, total intra-EU aggregates and total EU aggregates exclude any double counting.

The Air transport domain contains national and international intra and extra-EU data. This provides air transport data for passengers (in number of passengers) and for freight and mail (in 1 000 tonnes) as well as air traffic data by airports, airlines and aircraft. Data are transmitted to Eurostat by EU Member States, EFTA countries and some other reporting countries. Data are compiled following the provisions of the Regulation (EC) N°1358/2003, implementing Regulation N°437/2003 of the European Parliament and of the Council on statistical returns in respect of the carriage of passengers, freight and mail by air. The air transport data are collected at airport level. As from 2003 reference year the data are provided according to the legal act (some countries were given derogation until 2005). Until 2002 partial information (passenger transport only) are available for some countries and airports.

Airports handling less than 15 000 passenger units annually are excluded from the scope of the Regulation. Datasets A1 and B1 are provided on monthly basis, while dataset C1 can be provided either on monthly or annual basis. For some countries optional variable - total number of transfer passengers - is provided as well.

The data are disseminated by Eurostat in on-line database in four sub-domains:

• Air Transport measurement - Passengers
• Air Transport measurement - Freight and mail
• Air Transport measurement - Traffic data by airports, aircraft and airlines
• Air Transport measurement - Data aggregated at standard regional levels (NUTS).

The two first domains contain several data collections:

• Overview of the air transport by country and airport,
• National air transport by country and airport,
• International intra-EU air transport by country and airport,
• International extra-EU air transport by country and airport,
• Detailed air transport by reporting country and routes.

In the tables of the sub-domain "Transport measurement - Passengers", data are broken down by passengers on board (arrivals, departures and total), passengers carried (arrivals, departures and total) and passenger commercial air flights (arrival, departures and total). Additionally, the tables of collection "Detailed air transport by reporting country and routes" provide data on seats available (arrival, departures and total). The data is presented at monthly, quarterly and annual level.

In the tables of the sub-domain "Transport measurement - Freight and mail", data are broken down by freight and mail on board (arrival, departures and total), freight and mail loaded/unloaded (loaded, unloaded and total) and all-freight and mail commercial air flights (arrival, departures and total). The data is presented at monthly, quarterly and annual level.

In the tables of the sub-domain "Transport measurement - Traffic by airports, aircraft and airlines":

• Data by type of aircraft are broken down by total passengers on board, total freight and mail on board in tonnes, total passengers seats available, total commercial air flights (passengers + all-freight and mail), passenger commercial air flights, all-freight and mail commercial air flights. The data is presented at annual level since 2003.
• Data by type of airline are broken down by total passengers on board, total passengers carried, total freight and mail on board, total freight and mail loaded/unloaded, total passengers seats available, total commercial air flights (passengers + all-freight and mail), passenger commercial air flights, all-freight and mail commercial air flights. The data is presented at annual level since 2003.
• Data by airport are broken down by total passengers carried, total transit passengers, total transfer passengers, total freight and mail loaded/unloaded, total commercial aircraft movements, total aircrafts movements. The data is presented at monthly, quarterly and annual level.

The sub-domain "Transport measurement - Data aggregated at standard regional levels (NUTS)", contains two tables:

• Air transport of passengers at regional level
• Air transport of freight at regional level

The tables present the evolution of the number of passengers carried (if not available passengers on board) and the volume of freight and mail loaded or unloaded (if not available freight and mail on board) to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. The air transport regional data have been calculated using data collected at the airport level in the frame of the regulatory data collection on air transport.

For more details on datasets, data validation and dissemination refer also to Reference Manual on Air Transport Statistics available in the Annex part of the metadata.

Finnair Oyj ranked first in the ranking of air transport companies in the Nordic countries as of August 2021, by net profit. The net profit of Finnair Oyj amounted to roughly *** million euros.

Due to the nature of transport, a spatial reference is built into most legal acts dealing with transport statistics. In a few cases, these sources can be directly used for the derivation of regional transport indicators, while other indicators are collected on a voluntary basis. This is the case of the regional transport data collection in which both data types are used.

Three types of regional data can be distinguished depending on their source: two are based on data collections performed on the basis of legal acts (the Maritime and Aviation data) and one is a voluntary data collection (infrastructures, vehicles and road accidents).

Regional data collected on voluntary basis: The current regional data collection taking place on a voluntary basis comprises a set of transport indicators at NUTS 0, 1 and 2^[1] levels for the road, railways, inland waterways (infrastructure), vehicle stocks and road accidents. The information collected is then disseminated in Eurostat's dissemination database (Eurobase) under “General and regional statistics/Regional statistics by NUTS classification/Regional transport statistics” theme and also mirrored under “Transport/Multimodal data/Regional transport statistics” theme. The annual data collection for infrastructure, vehicle stocks and road accidents was first launched at the beginning of 2002 covering both EU Member States and Candidate countries. Since 2007, it includes EFTA countries as well. Starting from 2023, data on stock of electric vehicles are also collected.

Regional data are collected directly from the countries using a questionnaire: data on transport infrastructure, vehicle stocks and road accidents. Currently, regional datasets are provided via the EDAMIS application. For the voluntary data collection via the EDAMIS portal, the definitions from the 5^th edition of the Illustrated Glossary for Transport Statistics (jointly elaborated by Eurostat, ITF, UNECE) were proposed and countries should use them when reporting the data.

All the methodological issues reported by countries for the Regional data collection (e.g. breaks in time series, data availability and comparability, differences in definitions) are collected and presented in the document Country Specific Notes (See Annex).

Regional data based on legal acts: For the collection based on legal acts, regional data are actually derived from the information provided by the participating countries in the frame of the legal data collections at port and airport level. Maritime transport data collection is legally based – Directive 2009/42/EC of the European Parliament and of the Council of 6 May 2009 on statistical returns in respect of carriage of goods and passengers by sea (OJ L141 of 6 June 2009, page 29), which is the recast of the original Council Directive 95/64/EC of 8 December 1995. The air transport regional data have been calculated using data collected at the airport level in the context of the Council and Parliament Regulation (Regulation (EC) No 437/2003 of the European Parliament and of the Council of 27 February 2003 on statistical returns in respect of the carriage of passengers, freight and mail by air).

Within the collection Maritime transport - data aggregated at standard regional levels (NUTS) there are two tables:

• Maritime transport of passengers by NUTS 2 regions (tran_r_mapa_nm);
• Maritime transport of freight by NUTS 2 regions (tran_r_mago_nm).

Within the collection Air transport - data aggregated at standard regional levels (NUTS) there are two tables:

• Air transport of passengers by NUTS 2 regions (tran_r_avpa_nm)
• Air transport of freight by NUTS 2 regions (tran_r_avgo_nm)

The tables present the evolution of the number of passengers carried and the volume of freight and mail loaded or unloaded to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. Before the legal act on air transport statistics was introduced (2003 with 3 years transitional period), air transport statistics were collected using the statistical questionnaire (voluntary basis). Some countries provided figures for passenger transport taking into account “passengers on board” and some “passenger carried”. Until 2007 reference year, the disseminated numbers of passengers aggregated at regional level are actually a mixture of passengers on board and passengers carried data.
Since 2008, the air transport regional data are being calculated only by using data collected at the airport level in the frame of the regulatory data collection on air transport. Only airports with more than 150 000 passenger units serviced annually are required to report this data, however some countries also provide detailed information for smaller airports.
To solve the problem of double counting, it is necessary to start at the airport level for each aggregate in order to identify the mirror declarations, i.e. the airport routes for which both airports report the volume, since these constitute the routes where the problem of double counting occurs. When calculating the total volume in such cases, only the departure declarations of the concerned airports have been taken into account. The problem of the double counting only appears for the calculation of the total passengers but not for the total arrivals (respectively total departures), which corresponds to the sum of the arrivals (respectively departures) at each domestic airport.

For the tables presenting maritime data at regional level the same aggregation method (exclusion of double counting) is applied taking into account main ports only. Only for these ports (handling more than one million tonnes of goods or recording more than 200 000 passenger movements annually) the detailed statistics allow such aggregation.

For some Member States (up to 1998 data) and for others that joint the EU later (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are available in separate tables (listed below) and are no longer updated:

• Maritime transport of passengers by NUTS 2 regions (questionnaire) (tran_r_mapa_om).
• Maritime transport of freight by NUTS 2 regions (questionnaire) (tran_r_mago_om).
• Air transport of passengers by NUTS 2 regions (questionnaire) (tran_r_avpa_om).
• Air transport of freight by NUTS 2 regions (questionnaire) (tran_r_avgo_om).

[1] Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS) and its amendments. More information on NUTS classification can be found under the following website.

Due to the nature of transport, a spatial reference is built into most legal acts dealing with transport statistics. In a few cases, these sources can be directly used for the derivation of regional transport indicators, while other indicators are collected on a voluntary basis. This is the case of the regional transport data collection in which both data types are used.

Three types of regional data can be distinguished depending on their source: two are based on data collections performed on the basis of legal acts (the Maritime and Aviation data) and one is a voluntary data collection (infrastructures, vehicles and road accidents).

Regional data collected on voluntary basis: The current regional data collection taking place on a voluntary basis comprises a set of transport indicators at NUTS 0, 1 and 2^[1] levels for the road, railways, inland waterways (infrastructure), vehicle stocks and road accidents. The information collected is then disseminated in Eurostat's dissemination database (Eurobase) under “General and regional statistics/Regional statistics by NUTS classification/Regional transport statistics” theme and also mirrored under “Transport/Multimodal data/Regional transport statistics” theme. The annual data collection for infrastructure, vehicle stocks and road accidents was first launched at the beginning of 2002 covering both EU Member States and Candidate countries. Since 2007, it includes EFTA countries as well. Starting from 2023, data on stock of electric vehicles are also collected.

Regional data are collected directly from the countries using a questionnaire: data on transport infrastructure, vehicle stocks and road accidents. Currently, regional datasets are provided via the EDAMIS application. For the voluntary data collection via the EDAMIS portal, the definitions from the 5^th edition of the Illustrated Glossary for Transport Statistics (jointly elaborated by Eurostat, ITF, UNECE) were proposed and countries should use them when reporting the data.

All the methodological issues reported by countries for the Regional data collection (e.g. breaks in time series, data availability and comparability, differences in definitions) are collected and presented in the document Country Specific Notes (See Annex).

Regional data based on legal acts: For the collection based on legal acts, regional data are actually derived from the information provided by the participating countries in the frame of the legal data collections at port and airport level. Maritime transport data collection is legally based – Directive 2009/42/EC of the European Parliament and of the Council of 6 May 2009 on statistical returns in respect of carriage of goods and passengers by sea (OJ L141 of 6 June 2009, page 29), which is the recast of the original Council Directive 95/64/EC of 8 December 1995. The air transport regional data have been calculated using data collected at the airport level in the context of the Council and Parliament Regulation (Regulation (EC) No 437/2003 of the European Parliament and of the Council of 27 February 2003 on statistical returns in respect of the carriage of passengers, freight and mail by air).

Within the collection Maritime transport - data aggregated at standard regional levels (NUTS) there are two tables:

• Maritime transport of passengers by NUTS 2 regions (tran_r_mapa_nm);
• Maritime transport of freight by NUTS 2 regions (tran_r_mago_nm).

Within the collection Air transport - data aggregated at standard regional levels (NUTS) there are two tables:

• Air transport of passengers by NUTS 2 regions (tran_r_avpa_nm)
• Air transport of freight by NUTS 2 regions (tran_r_avgo_nm)

The tables present the evolution of the number of passengers carried and the volume of freight and mail loaded or unloaded to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. Before the legal act on air transport statistics was introduced (2003 with 3 years transitional period), air transport statistics were collected using the statistical questionnaire (voluntary basis). Some countries provided figures for passenger transport taking into account “passengers on board” and some “passenger carried”. Until 2007 reference year, the disseminated numbers of passengers aggregated at regional level are actually a mixture of passengers on board and passengers carried data.
Since 2008, the air transport regional data are being calculated only by using data collected at the airport level in the frame of the regulatory data collection on air transport. Only airports with more than 150 000 passenger units serviced annually are required to report this data, however some countries also provide detailed information for smaller airports.
To solve the problem of double counting, it is necessary to start at the airport level for each aggregate in order to identify the mirror declarations, i.e. the airport routes for which both airports report the volume, since these constitute the routes where the problem of double counting occurs. When calculating the total volume in such cases, only the departure declarations of the concerned airports have been taken into account. The problem of the double counting only appears for the calculation of the total passengers but not for the total arrivals (respectively total departures), which corresponds to the sum of the arrivals (respectively departures) at each domestic airport.

For the tables presenting maritime data at regional level the same aggregation method (exclusion of double counting) is applied taking into account main ports only. Only for these ports (handling more than one million tonnes of goods or recording more than 200 000 passenger movements annually) the detailed statistics allow such aggregation.

For some Member States (up to 1998 data) and for others that joint the EU later (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are available in separate tables (listed below) and are no longer updated:

• Maritime transport of passengers by NUTS 2 regions (questionnaire) (tran_r_mapa_om).
• Maritime transport of freight by NUTS 2 regions (questionnaire) (tran_r_mago_om).
• Air transport of passengers by NUTS 2 regions (questionnaire) (tran_r_avpa_om).
• Air transport of freight by NUTS 2 regions (questionnaire) (tran_r_avgo_om).

[1] Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS) and its amendments. More information on NUTS classification can be found under the following website.

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The Airlines Reviews and Ratings dataset is a comprehensive collection of passenger feedback on various aspects of their flight experiences across different airlines. This dataset aims to provide insights into passenger satisfaction and airlines' service quality, offering valuable data for analysis in the travel and hospitality industry, customer service improvement, and predictive modeling for customer satisfaction. Airlines Reviews and Ratings Dataset, a rich collection designed to explore the multifaceted aspects of air travel experiences across various airlines worldwide. This dataset encompasses a broad range of data points, from aircraft types and user reviews to detailed service ratings, offering a unique lens through which to analyze and predict airline performance from a passenger perspective.

Column Details:

• Aircraft Type: Type of aircraft used for the flight.
• Users Reviews: Textual reviews provided by the users.
• Country: The country of the airline or the flight origin/destination.
• Type of Travellers: Categorizes travellers (e.g., Solo, Family, Business...).
• Route: The flight route taken.
• Seat Types: Class of the seat (Economy, Business, First Class...).
• Seat Comfort: Rating of the seat comfort.
• Date Flown: When the flight took place./The flight date.
• Cabin Staff Service: Rating of the service provided by the cabin staff.
• Ground Service/Floor: Rating of the ground service, including check-in and boarding.
• Food & Beverages: Rating of the food and beverage quality.
• Wifi & Connectivity: Rating of the wifi and connectivity options available.
• Inflight Entertainment: Rating of the inflight entertainment options.
• Value For Money: Overall value for money rating.
• Recommended: Whether the reviewer recommends the airline or not.

Time series data for the statistic Air transport, registered carrier departures worldwide and country Iceland. Indicator Definition:Registered carrier departures worldwide are domestic takeoffs and takeoffs abroad of air carriers registered in the country.The indicator "Air transport, registered carrier departures worldwide" stands at 24.52 Thousand as of 12/31/2021. Regarding the One-Year-Change of the series, the current value constitutes an increase of 80.36 percent compared to the value the year prior.The 1 year change in percent is 80.36.The 3 year change in percent is -55.14.The 5 year change in percent is -40.23.The 10 year change in percent is 0.1225.The Serie's long term average value is 19.06 Thousand. It's latest available value, on 12/31/2021, is 28.65 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2003, to it's latest available value, on 12/31/2021, is +151.47%.The Serie's change in percent from it's maximum value, on 12/31/2018, to it's latest available value, on 12/31/2021, is -55.14%.

Norwegian Air Shuttle ranked first in the ranking of air transport companies in the Nordic countries as of ***********, by number of employees. The number of employees of Norwegian amounted to approximately *****.

The Henley Passport Index is a global ranking of countries according to the travel freedom their citizens enjoy. It is based on exclusive data from the International Air Transport Association (IATA) and measures how many destinations a passport holder can access without a prior visa.

Country name

Rank

Number of visa-free destinations

Visa-free, visa-on-arrival, eVisa, and visa-required destinations (if applicable)

The data is valuable for research in global mobility, international relations, travel, visa policy, and economic development.

Due to the nature of transport, a spatial reference is built into most legal acts dealing with transport statistics. In a few cases, these sources can be directly used for the derivation of regional transport indicators, while other indicators are collected on a voluntary basis. This is the case of the regional transport data collection in which both data types are used.

Three types of regional data can be distinguished depending on their source: two are based on data collections performed on the basis of legal acts (the Maritime and Aviation data) and one is a voluntary data collection (infrastructures, vehicles and road accidents).

Regional data collected on voluntary basis: The current regional data collection taking place on a voluntary basis comprises a set of transport indicators at NUTS 0, 1 and 2^[1] levels for the road, railways, inland waterways (infrastructure), vehicle stocks and road accidents. The information collected is then disseminated in Eurostat's dissemination database (Eurobase) under “General and regional statistics/Regional statistics by NUTS classification/Regional transport statistics” theme and also mirrored under “Transport/Multimodal data/Regional transport statistics” theme. The annual data collection for infrastructure, vehicle stocks and road accidents was first launched at the beginning of 2002 covering both EU Member States and Candidate countries. Since 2007, it includes EFTA countries as well. Starting from 2023, data on stock of electric vehicles are also collected.

Regional data are collected directly from the countries using a questionnaire: data on transport infrastructure, vehicle stocks and road accidents. Currently, regional datasets are provided via the EDAMIS application. For the voluntary data collection via the EDAMIS portal, the definitions from the 5^th edition of the Illustrated Glossary for Transport Statistics (jointly elaborated by Eurostat, ITF, UNECE) were proposed and countries should use them when reporting the data.

All the methodological issues reported by countries for the Regional data collection (e.g. breaks in time series, data availability and comparability, differences in definitions) are collected and presented in the document Country Specific Notes (See Annex).

Regional data based on legal acts: For the collection based on legal acts, regional data are actually derived from the information provided by the participating countries in the frame of the legal data collections at port and airport level. Maritime transport data collection is legally based – Directive 2009/42/EC of the European Parliament and of the Council of 6 May 2009 on statistical returns in respect of carriage of goods and passengers by sea (OJ L141 of 6 June 2009, page 29), which is the recast of the original Council Directive 95/64/EC of 8 December 1995. The air transport regional data have been calculated using data collected at the airport level in the context of the Council and Parliament Regulation (Regulation (EC) No 437/2003 of the European Parliament and of the Council of 27 February 2003 on statistical returns in respect of the carriage of passengers, freight and mail by air).

Within the collection Maritime transport - data aggregated at standard regional levels (NUTS) there are two tables:

• Maritime transport of passengers by NUTS 2 regions (tran_r_mapa_nm);
• Maritime transport of freight by NUTS 2 regions (tran_r_mago_nm).

Within the collection Air transport - data aggregated at standard regional levels (NUTS) there are two tables:

• Air transport of passengers by NUTS 2 regions (tran_r_avpa_nm)
• Air transport of freight by NUTS 2 regions (tran_r_avgo_nm)

The tables present the evolution of the number of passengers carried and the volume of freight and mail loaded or unloaded to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. Before the legal act on air transport statistics was introduced (2003 with 3 years transitional period), air transport statistics were collected using the statistical questionnaire (voluntary basis). Some countries provided figures for passenger transport taking into account “passengers on board” and some “passenger carried”. Until 2007 reference year, the disseminated numbers of passengers aggregated at regional level are actually a mixture of passengers on board and passengers carried data.
Since 2008, the air transport regional data are being calculated only by using data collected at the airport level in the frame of the regulatory data collection on air transport. Only airports with more than 150 000 passenger units serviced annually are required to report this data, however some countries also provide detailed information for smaller airports.
To solve the problem of double counting, it is necessary to start at the airport level for each aggregate in order to identify the mirror declarations, i.e. the airport routes for which both airports report the volume, since these constitute the routes where the problem of double counting occurs. When calculating the total volume in such cases, only the departure declarations of the concerned airports have been taken into account. The problem of the double counting only appears for the calculation of the total passengers but not for the total arrivals (respectively total departures), which corresponds to the sum of the arrivals (respectively departures) at each domestic airport.

For the tables presenting maritime data at regional level the same aggregation method (exclusion of double counting) is applied taking into account main ports only. Only for these ports (handling more than one million tonnes of goods or recording more than 200 000 passenger movements annually) the detailed statistics allow such aggregation.

For some Member States (up to 1998 data) and for others that joint the EU later (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are available in separate tables (listed below) and are no longer updated:

• Maritime transport of passengers by NUTS 2 regions (questionnaire) (tran_r_mapa_om).
• Maritime transport of freight by NUTS 2 regions (questionnaire) (tran_r_mago_om).
• Air transport of passengers by NUTS 2 regions (questionnaire) (tran_r_avpa_om).
• Air transport of freight by NUTS 2 regions (questionnaire) (tran_r_avgo_om).

[1] Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS) and its amendments. More information on NUTS classification can be found under the following website.

This record is a global open-source passenger air traffic dataset primarily dedicated to the research community. It gives a seating capacity available on each origin-destination route for a given year, 2019, and the associated aircraft and airline when this information is available. Context on the original work is given in the related article (https://journals.open.tudelft.nl/joas/article/download/7201/5683) and on the associated GitHub page (https://github.com/AeroMAPS/AeroSCOPE/).A simple data exploration interface will be available at www.aeromaps.eu/aeroscope.The dataset was created by aggregating various available open-source databases with limited geographical coverage. It was then completed using a route database created by parsing Wikipedia and Wikidata, on which the traffic volume was estimated using a machine learning algorithm (XGBoost) trained using traffic and socio-economical data. 1- DISCLAIMER The dataset was gathered to allow highly aggregated analyses of the air traffic, at the continental or country levels. At the route level, the accuracy is limited as mentioned in the associated article and improper usage could lead to erroneous analyses. Although all sources used are open to everyone, the Eurocontrol database is only freely available to academic researchers. It is used in this dataset in a very aggregated way and under several levels of abstraction. As a result, it is not distributed in its original format as specified in the contract of use. As a general rule, we decline any responsibility for any use that is contrary to the terms and conditions of the various sources that are used. In case of commercial use of the database, please contact us in advance. 2- DESCRIPTION Each data entry represents an (Origin-Destination-Operator-Aircraft type) tuple. Please refer to the support article for more details (see above). The dataset contains the following columns:

"First column" : index airline_iata : IATA code of the operator in nominal cases. An ICAO -> IATA code conversion was performed for some sources, and the ICAO code was kept if no match was found. acft_icao : ICAO code of the aircraft type acft_class : Aircraft class identifier, own classification.

WB: Wide Body NB: Narrow Body RJ: Regional Jet PJ: Private Jet TP: Turbo Propeller PP: Piston Propeller HE: Helicopter OTHER seymour_proxy: Aircraft code for Seymour Surrogate (https://doi.org/10.1016/j.trd.2020.102528), own classification to derive proxy aircraft when nominal aircraft type unavailable in the aircraft performance model. source: Original data source for the record, before compilation and enrichment.

ANAC: Brasilian Civil Aviation Authorities AUS Stats: Australian Civil Aviation Authorities BTS: US Bureau of Transportation Statistics T100 Estimation: Own model, estimation on Wikipedia-parsed route database Eurocontrol: Aggregation and enrichment of R&D database OpenSky World Bank seats: Number of seats available for the data entry, AFTER airport residual scaling n_flights: Number of flights of the data entry, when available iata_departure, iata_arrival : IATA code of the origin and destination airports. Some BTS inhouse identifiers could remain but it is marginal. departure_lon, departure_lat, arrival_lon, arrival_lat : Origin and destination coordinates, could be NaN if the IATA identifier is erroneous departure_country, arrival_country: Origin and destination country ISO2 code. WARNING: disable NA (Namibia) as default NaN at import departure_continent, arrival_continent: Origin and destination continent code. WARNING: disable NA (North America) as default NaN at import seats_no_est_scaling: Number of seats available for the data entry, BEFORE airport residual scaling distance_km: Flight distance (km) ask: Available Seat Kilometres rpk: Revenue Passenger Kilometres (simple calculation from ASK using IATA average load factor) fuel_burn_seymour: Fuel burn per flight (kg) when seymour proxy available fuel_burn: Total fuel burn of the data entry (kg) co2: Total CO2 emissions of the data entry (kg) domestic: Domestic/international boolean (Domestic=1, International=0)

3- Citation Please cite the support paper instead of the dataset itself.

Salgas, A., Sun, J., Delbecq, S., Planès, T., & Lafforgue, G. (2023). Compilation of an open-source traffic and CO2 emissions dataset for commercial aviation. Journal of Open Aviation Science. https://doi.org/10.59490/joas.2023.7201

Latvia Hours Worked: TS: Air Transport data was reported at 714,130.000 Hour in Mar 2018. This records an increase from the previous number of 712,383.000 Hour for Dec 2017. Latvia Hours Worked: TS: Air Transport data is updated quarterly, averaging 583,864.000 Hour from Mar 2005 (Median) to Mar 2018, with 53 observations. The data reached an all-time high of 775,394.000 Hour in Dec 2010 and a record low of 345,823.000 Hour in Mar 2005. Latvia Hours Worked: TS: Air Transport data remains active status in CEIC and is reported by Central Statistical Bureau of Latvia. The data is categorized under Global Database’s Latvia – Table LV.G022: Hours Paid and Hours Worked: Statistical Classification of Economic Activities Revision 2.

This Dataset is an enhanced version of the original Busiest Airports by Passenger Traffic (2022) dataset by Raj Kumar Pandey. The modifications include: *Added Latitude and Longitude columns: These columns provide the geographical coordinates of each airport, enabling advanced visualizations such as mapping and spatial analysis. *Removed unnecessary columns: Columns that did not contribute to the visualizations were removed for clarity and simplicity. This dataset provides valuable insights into the passenger traffic of the busiest airports globally in 2022. It is ideal for data analysis, visualization projects, and geospatial studies. Column Descriptors

1. Rank: The ranking of the airport based on the total number of passengers in 2022.
2. lat: Latitude coordinate of the airport, used for geospatial visualizations.
3. long: Longitude coordinate of the airport, used for geospatial visualizations.
4. Airport: The official name of the airport.
5. Location: The city and state (or equivalent) where the airport is located.
6. Country: The country where the airport is located.
7. Code (IATA/ICAO): The IATA (International Air Transport Association) and ICAO (International Civil Aviation Organization) codes for the airport.
8. Total passengers: The total number of passengers that traveled through the airport in 2022.

Due to the nature of transport, a spatial reference is built into most legal acts dealing with transport statistics. In a few cases, these sources can be directly used for the derivation of regional transport indicators, while other indicators are collected on a voluntary basis. This is the case of the regional transport data collection in which both data types are used.

Three types of regional data can be distinguished depending on their source: two are based on data collections performed on the basis of legal acts (the Maritime and Aviation data) and one is a voluntary data collection (infrastructures, vehicles and road accidents).

Regional data collected on voluntary basis: The current regional data collection taking place on a voluntary basis comprises a set of transport indicators at NUTS 0, 1 and 2^[1] levels for the road, railways, inland waterways (infrastructure), vehicle stocks and road accidents. The information collected is then disseminated in Eurostat's dissemination database (Eurobase) under “General and regional statistics/Regional statistics by NUTS classification/Regional transport statistics” theme and also mirrored under “Transport/Multimodal data/Regional transport statistics” theme. The annual data collection for infrastructure, vehicle stocks and road accidents was first launched at the beginning of 2002 covering both EU Member States and Candidate countries. Since 2007, it includes EFTA countries as well. Starting from 2023, data on stock of electric vehicles are also collected.

Regional data are collected directly from the countries using a questionnaire: data on transport infrastructure, vehicle stocks and road accidents. Currently, regional datasets are provided via the EDAMIS application. For the voluntary data collection via the EDAMIS portal, the definitions from the 5^th edition of the Illustrated Glossary for Transport Statistics (jointly elaborated by Eurostat, ITF, UNECE) were proposed and countries should use them when reporting the data.

All the methodological issues reported by countries for the Regional data collection (e.g. breaks in time series, data availability and comparability, differences in definitions) are collected and presented in the document Country Specific Notes (See Annex).

Regional data based on legal acts: For the collection based on legal acts, regional data are actually derived from the information provided by the participating countries in the frame of the legal data collections at port and airport level. Maritime transport data collection is legally based – Directive 2009/42/EC of the European Parliament and of the Council of 6 May 2009 on statistical returns in respect of carriage of goods and passengers by sea (OJ L141 of 6 June 2009, page 29), which is the recast of the original Council Directive 95/64/EC of 8 December 1995. The air transport regional data have been calculated using data collected at the airport level in the context of the Council and Parliament Regulation (Regulation (EC) No 437/2003 of the European Parliament and of the Council of 27 February 2003 on statistical returns in respect of the carriage of passengers, freight and mail by air).

Within the collection Maritime transport - data aggregated at standard regional levels (NUTS) there are two tables:

• Maritime transport of passengers by NUTS 2 regions (tran_r_mapa_nm);
• Maritime transport of freight by NUTS 2 regions (tran_r_mago_nm).

Within the collection Air transport - data aggregated at standard regional levels (NUTS) there are two tables:

• Air transport of passengers by NUTS 2 regions (tran_r_avpa_nm)
• Air transport of freight by NUTS 2 regions (tran_r_avgo_nm)

The tables present the evolution of the number of passengers carried and the volume of freight and mail loaded or unloaded to/from the NUTS regions (level 2, 1 and 0) since 1999. The data is presented at annual level. Before the legal act on air transport statistics was introduced (2003 with 3 years transitional period), air transport statistics were collected using the statistical questionnaire (voluntary basis). Some countries provided figures for passenger transport taking into account “passengers on board” and some “passenger carried”. Until 2007 reference year, the disseminated numbers of passengers aggregated at regional level are actually a mixture of passengers on board and passengers carried data.
Since 2008, the air transport regional data are being calculated only by using data collected at the airport level in the frame of the regulatory data collection on air transport. Only airports with more than 150 000 passenger units serviced annually are required to report this data, however some countries also provide detailed information for smaller airports.
To solve the problem of double counting, it is necessary to start at the airport level for each aggregate in order to identify the mirror declarations, i.e. the airport routes for which both airports report the volume, since these constitute the routes where the problem of double counting occurs. When calculating the total volume in such cases, only the departure declarations of the concerned airports have been taken into account. The problem of the double counting only appears for the calculation of the total passengers but not for the total arrivals (respectively total departures), which corresponds to the sum of the arrivals (respectively departures) at each domestic airport.

For the tables presenting maritime data at regional level the same aggregation method (exclusion of double counting) is applied taking into account main ports only. Only for these ports (handling more than one million tonnes of goods or recording more than 200 000 passenger movements annually) the detailed statistics allow such aggregation.

For some Member States (up to 1998 data) and for others that joint the EU later (up to 2002) transport flows through ports and airports had been collected, via questionnaire. Because of the difference in the methodologies applied, the data for air and maritime transport at regional level up to 2002 reference year are available in separate tables (listed below) and are no longer updated:

• Maritime transport of passengers by NUTS 2 regions (questionnaire) (tran_r_mapa_om).
• Maritime transport of freight by NUTS 2 regions (questionnaire) (tran_r_mago_om).
• Air transport of passengers by NUTS 2 regions (questionnaire) (tran_r_avpa_om).
• Air transport of freight by NUTS 2 regions (questionnaire) (tran_r_avgo_om).

[1] Regulation (EC) No 1059/2003 of the European Parliament and of the Council of 26 May 2003 on the establishment of a common classification of territorial units for statistics (NUTS) and its amendments. More information on NUTS classification can be found under the following website.

Czech Republic Electricity Consumption: Air Transport data was reported at 2,136.254 MWh in 2022. This records an increase from the previous number of 1,547.452 MWh for 2021. Czech Republic Electricity Consumption: Air Transport data is updated yearly, averaging 1,573.733 MWh from Dec 2007 (Median) to 2022, with 16 observations. The data reached an all-time high of 14,813.000 MWh in 2007 and a record low of 492.810 MWh in 2018. Czech Republic Electricity Consumption: Air Transport data remains active status in CEIC and is reported by Czech Statistical Office. The data is categorized under Global Database’s Czech Republic – Table CZ.RB005: Energy Consumption: Electricity: by Industry: Statistical Classification of Economic Activities Rev. 2.

Lithuania LT: Foreign Direct Investment Income: Inward: USD: Total: Air Transport data was reported at 48.951 USD mn in 2023. This records an increase from the previous number of 11.719 USD mn for 2022. Lithuania LT: Foreign Direct Investment Income: Inward: USD: Total: Air Transport data is updated yearly, averaging 0.571 USD mn from Dec 2006 (Median) to 2023, with 17 observations. The data reached an all-time high of 48.951 USD mn in 2023 and a record low of -28.387 USD mn in 2020. Lithuania LT: Foreign Direct Investment Income: Inward: USD: Total: Air Transport data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Lithuania – Table LT.OECD.FDI: Foreign Direct Investment Income: USD: by Industry: OECD Member: Annual. Reverse investment: Netting of reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) and reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. Treatment of debt FDI transactions and positions between fellow enterprises: directional basis according to the residency of the ultimate controlling parent (extended directional principle). FDI transactions and positions by partner country and/or by industry are available excluding and including resident Special Purpose Entities (SPEs). The dataset 'FDI statistics by parner country and by industry - Summary' contains series including resident SPEs only. Valuation method used for listed inward and outward equity positions: Market value. Valuation method used for unlisted inward and outward equity positions: Own funds at book value. Valuation method used for inward and outward debt positions: Market and Nominal values. .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the non resident direct investment enterprise. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.