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Cited by 16Aviation Industry Analysis and TrendsTransportation Planning and OptimizationEnergy, Environment, and Transportation Policies

Agent-Based Simulation of Long-Distance Travel: Strategies to Reduce CO2 Emissions from Passenger Aviation

Open access
Pukhova, Alona, Moreno, Ana Tsui, Llorca, Carlos, Huang, Wei-Chieh, Moeckel, Rolf·2021·Urban Planning
DOI 10.17645/up.v6i2.4021
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Abstract

Every sector needs to minimize GHG emissions to limit climate change. Emissions from transport, however, have remained mostly unchanged over the past thirty years. In particular, air travel for short-haul flights is a significant contributor to transport emissions. This article identifies factors that influence the demand for domestic air travel. An agent-based model was implemented for domestic travel in Germany to test policies that could be implemented to reduce air travel and CO 2 emissions. The agent-based long-distance travel demand model is composed of trip generation, destination choice, mode choice and CO 2 emission modules. The travel demand model was estimated and calibrated with the German Household Travel Survey, including socio-demographic characteristics and area type. Long-distance trips were differentiated by trip type (daytrip, overnight trip), trip purpose (business, leisure, private) and mode (auto, air, long-distance rail and long-distance bus). Emission factors by mode were used to calculate CO 2 emissions. Potential strategies and policies to reduce air travel demand and its CO 2 emissions are tested using this model. An increase in airfares reduced the number of air trips and reduced transport emissions. Even stronger effects were found with a policy that restricts air travel to trips that are longer than a certain threshold distance. While such policies might be difficult to implement politically, restricting air travel has the potential to reduce total CO 2 emissions from transport by 7.5%.

AI snapshot

Written from the paper’s full text.

TL;DR

This paper implements an agent-based long-distance travel demand model for Germany and couples it with CO2 emission factors to test policies that reduce domestic air travel. It finds that restricting air travel below a distance threshold is more effective than airfare increases, with a 900 km minimum distance reducing total transport CO2 by 7.5%.

Key findings

  • The base scenario simulated 4,512,610 domestic long-distance trips on an average day; air accounted for 0.39% of daytrips and 3.96% of overnight trips but 8.54% of daytrip CO2 emissions and 43.30% of overnight-trip CO2 emissions.
  • Restricting air travel below 900 km reduced air emissions by 93.1% and air trips to 4,917, increased ground-mode emissions by 3.6%, and reduced overall emissions by 24.2%; the best scenario achieved almost 33,000 tons CO2 per day reduction and would reduce Germany’s total transport sector emissions by 7.5%.
  • Airfare increases reduced aviation CO2 by 28.42% at +100% (11,086.95 tons CO2 per day) and 53.2% at +500% (equivalent to 20,745.64 tons CO2), with total emissions reduced by up to 13.8%.
  • Auto was the dominant long-distance mode (83.54% modeled total vs. 81.11% survey), while air was 2.23% modeled vs. 3.26% survey.

Methods

  • Agent-based, trip-based long-distance travel demand model for all of Germany with 11,717 zones; modules for trip generation, destination choice, mode choice, and CO2 emissions; synthetic population of about 80 million persons in 53 million households.
  • Estimated and calibrated with the German Household Travel Survey: 316,361 people and 960,619 trip records; after cleaning, 293,216 person records; 12,451 long-distance trip records for destination choice; 7,098 records for mode choice. Long-distance threshold was 40 km for non-commute trips; modes were auto, air, long-distance rail, and bus; purposes were business, leisure, and private; separate daytrip and overnight mode choice models were estimated.
  • Scenario analysis tested air distance thresholds of 300, 500, 700, and 900 km and airfare increases of 100%, 300%, and 500%; each scenario was run 8 times with different random seeds and averaged. Emission factors included auto 170.89 gCO2/km divided by 2.25 occupancy, bus 44.55 g/passenger-km, rail 14 g/passenger-km, and a distance-dependent air factor multiplied by 1.9 for radiative forcing.

Limitations

  • The paper states road-network congestion was not considered; the sequential trip-based model does not account for interaction between steps; joint destination and mode choice/copula models were unfeasible with 11,717 zones; mode choice logsums were not included; and induced or dampened demand is not considered.
  • The paper states CO2 equivalent emissions were not feasible because CH4 and N2O per km by flight distance were unavailable; the 1.9 radiative forcing factor is an overestimate for short-distance air trips and an underestimate for long-distance trips; and agent-based stochasticity required multiple model runs.
  • Evident from the text: the model underpredicted air share (2.23% modeled vs. 3.26% survey) and overpredicted auto share (83.54% vs. 81.11%), and destination-choice standard deviations were smaller than observed, indicating underestimation of very short and very long long-distance trips; international travel was not included.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.17645/up.v6i2.4021

Cites

46 of 46 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 25 cited sources checked · 0 supported · 0 flagged

  • Findingnone given

    Restricting air travel has the potential to reduce total CO2 emissions from transport by 7.5%.

    “restricting air travel has the potential to reduce total CO 2 emissions from transport by 7.5%.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.
    • The authors state this as an assumption: The decision of choosing a mode is influenced by the duration of the trip.
  • Findingreasoning

    Employed people tend to be less likely to conduct long-distance private and leisure trips than non-employed.

    “Employed people tend to be less likely to conduct long-distance private and leisure trips than non-employed”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.
  • Findingown data

    Bus and train tend to be preferred by low-income households.

    “Bus and train tend to be preferred by low-income households.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.
    • The authors state this as an assumption: The decision of choosing a mode is influenced by the duration of the trip.
  • Findingown data

    Car ownership has a negative impact on private overnight trips.

    “but it has a negative impact on private overnight trips”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.
  • Findingown data

    The average error of all controlled attributes by municipalities in the synthetic population ranges between 0% and 30%.

    “The average error by municipalities ranges between 0% and 30%.”
    Quote in the paperNot a substantial claim
  • May combine two claims. 21
  • Classified as probably not a substantial claim. 16

  • May combine two claims.

    Findingown data

    An increase in airfares reduced the number of air trips and reduced transport emissions.

    “An increase in airfares reduced the number of air trips and reduced transport emissions.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.
    • The authors state this as an assumption: The decision of choosing a mode is influenced by the duration of the trip.

  • May combine two claims.

    Findingown data

    Females and persons of single-person households are more likely to choose rail.

    “we generally observed that females and persons of single-person households are more likely to choose rail.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.
    • The authors state this as an assumption: The decision of choosing a mode is influenced by the duration of the trip.

  • May combine two claims.

    Findingown data

    Air trips accounted for 0.39% of daytrips in Germany and for 3.96% of overnight trips.

    “Air trips accounted for 0.39% of daytrips in Germany and for 3.96% of overnight trips.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    When the distance threshold is 900 km, air travel is strongly reduced and emissions drop by 93.1%, with the number of air trips dropping to 4,917 trips.

    “When the dis-tance threshold is 900 km, air travel is strongly reduced and emissions drop by 93.1% with the number of air trips dropping to 4,917 trips.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The modeled standard deviation of one-way distance is slightly smaller than observed, indicating the model tends to slightly underestimate rather short and very long long-distance trips.

    “The modeled standard deviation is slightly smaller than observed, which indicates that the model has a tendency to slightly underestimate rather short and very long long-distance trips.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.

  • May combine two claims.

    Findingown data

    The emissions of the remaining long-distance ground modes increase due to the shift from the air mode, with the highest increase of 3.6% in the 900 km scenario.

    “At the same time, the emissions of the remaining long-distance ground modes increase due to the shift from the air mode, with the highest increase of 3.6% in the 900 km scenario.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    As airfare was increased by 500%, the reduction in CO2 emissions was 53.2%, equivalent to 20,745.64 tons of CO2.

    “As airfare was increased by 500%, the reduction in CO 2 emissions was 53.2% (equivalent to 20,745.64 tons of CO 2 ).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingnone given

    Smaller municipalities tend to be more difficult to match in the synthetic population.

    “Smaller municipalities tend to be more difficult to match.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    An increase of 100% in airfare reduced CO2 emissions from aviation by 28.42% compared to the base scenario, equivalent to 11,086.95 tons of CO2 per day.

    “With respect to the scenarios with higher airfares, an increase of 100% already reduced CO 2 emissions from aviation by 28.42% compared to the base scenario (11,086.95tons of CO 2 per day), as seen in Figure 4.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The total amount of CO2 emissions released by aviation was 8.54% of daytrip CO2 emissions and 43.30% of overnight trip emissions.

    “However, the total amount of CO 2 emissions released by aviation was significantly larger: 8.54% of daytrip CO 2 emissions and 43.30% of overnight trip emissions.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    Total population, employment, and number of hotels at a destination have a positive impact on utility, meaning destinations with more population, employment, and hotels are more likely to be chosen.

    “Total population and employment and the number of hotels have a positive impact on the utility, which means destinations with more population, employment and hotels are more likely to be chosen.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.

  • Classified as probably not a substantial claim.

    Premisecitation

    Agent-based models introduce a lot of flexibility to design scenarios.

    “Agent-based models introduce a lot of flexibility to design scenarios (Donnelly, Erhardt, Moeckel, & Davidson, 2010).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Donnelly, Erhardt, Moeckel, & Davidson, 2010

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisereasoning

    The differences between model runs are marginal if a large number of agents is simulated or if a lot of choices of these agents are simulated, as a large number of events averages out.

    “The differences between model runs are marginal if a large number of agents is simulated or if a lot of choices of these agents are simulated, as a large number of events averages out.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Explanatory variables that were highly correlated were excluded from the models; if two variables correlated by more than R2 = 0.5, only one was retained.

    “Explanatory variables that were highly correlated were excluded from the models.If two variables correlated by more than R 2 = 0.5, only one of the two was retained.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.

  • May combine two claims.

    Interpretationnone given

    The factor of 1.9 used to account for radiative forcing is an overestimate for short-distance air trips and an underestimate for long-distance trips.

    “We recognize that this factor of 1.9 is an overestimate for short-distance air trips and an underestimate for the long-distance trips.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Aviation generated 2.4% of all CO2 emissions in 2018, with a growth rate of 32% over the past five years.

    “Aviation generated 2.4% of all CO 2 emissions in 2018 (Graver, Zhang, & Rutherford, 2019), with a growth rate of 32% over the past five years.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Graver, Zhang, & Rutherford, 2019

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim.

    Premisecitation

    Emissions need to be reduced by 7.6% every year from 2020 to 2030 to limit global warming to 1.5°C.

    “emissions need to be reduced by 7.6% every year from 2020 to 2030 to limit global warming to 1.5°C.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites UN Environment Programme, 2019

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisereasoning

    Agent-based models require a random number generator to simulate choices of individual agents, so every model run produces slightly different results.

    “Such models require a random number generator to simulate choices of individual agents.Depending on the random numbers chosen, every model run produces slightly different results.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Passenger air travel in Europe dropped by 89% during the pandemic.

    “Passenger air travel in Europe dropped by 89% (Nižetić, 2020), and emissions were reduced accordingly.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Nižetić, 2020 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The destination choice model was calibrated to match the average one-way distance between survey and model.

    “The model was implemented and calibrated to match the average one-way distance between survey and model.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The model was run 8 times with different random seeds and the average was calculated to obtain more reliable results.

    “We run the model 8 times with different random seeds and calculated the average to obtain more reliable results.”
    • Also stated in: § 8. Conclusion · plain
      “Therefore, the model had to be run multiple times to calculate the average of every scenario presented in this article.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    In Germany, CO2 equivalent emissions from international aviation increased 2.5-times over the last 30 years, while emissions from domestic aviation showed a 10% reduction in CO2eq.

    “In Germany alone, the amount of CO 2 equivalent emissions (CO 2 eq) from international aviation increased 2.5-times over the last 30 years, while emissions from domestic aviation showed a 10% reduction in CO 2eg (Umwelt Bundesamt, 2020).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Umwelt Bundesamt, 2020

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    IATA predicts that air travel will recover by 2024 with an annual global growth rate of 3.7% over the next 20 years.

    “IATA predicts, however, that air travel will recover by 2024 with an annual global growth rate of 3.7% over the next 20 years (IATA, 2020).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites IATA, 2020

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    The share of gasoline and diesel-powered vehicles was 65.9% and 31.7%, respectively.

    “The share of gasoline and dieselpowered vehicles was 65.9% and 31.7%,respectively (Kraftfahrt-Bundesamt, 2020).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Kraftfahrt-Bundesamt, 2020

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    75% of all trips are shorter than 15 km, but they account for only around 30% of the vehicle-distance travelled.

    “According to Shiffer (2012), 75% of all trips are shorter than 15 km, but they account for only around 30% of the vehicle-distance travelled.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Shiffer (2012)

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The number of long-distance auto trips in Germany is expected to grow further by 13-16% by 2030, depending on the purpose of the trips.

    “Moreover, the number of long-distance auto trips in Germany is expected to grow further by 13-16% by 2030, depending on the purpose of the trips.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Federal Ministry of Transport and Digital Infrastructure, 2014

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Distances are expected to grow by 12% by 2030.

    “Similarly, distances are expected to grow by 12% (Federal Ministry of Transport and Digital Infrastructure, 2014).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Federal Ministry of Transport and Digital Infrastructure, 2014

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductreasoning

    Induced demand due to new modes or dampened travel demand due to restrictive scenarios are not considered in this model, as they are difficult to quantify.

    “Last but not least, induced demand due to new modes or dampened travel demand due to restrictive scenarios are not considered in this model, as they are difficult to quantify.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Whenever a small number of agents or rare events are studied, agent-based models need to be run many times and the average across many model runs needs to be calculated.

    “Whenever a small number of agents or rare events are studied, agent-based models need to be run many times and the average across many model runs needs to be calculated (Wegener, 2011).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Wegener, 2011 source

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    Long-distance travel is not so rare that it would be difficult to study it with an agent-based model, at least not for common destinations and modes.

    “Long-distance travel is not as rare that it would be difficult to study it with an agent-based model, at least not for common destinations and modes.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductreasoning

    The application of copula models could better account for the interaction issue, but a study area with 11,717 zones makes a joint destination and mode choice unfeasible.

    “The application of copula models could better account for this issue, but a study area with 11,717 zones makes a joint destination and mode choice unfeasible.”
    Quote in the paperSubstantial claim
31 of 31

  • The authors state this as an assumption.

    In the multinomial logit model, the alternatives are irrelevant and independent from each other, and people can make rational choices by differentiating the utility of each alternative.

    “The main assumption of the multinomial logit model is that the alternatives are irrelevant and independent from each other and that people can make rational choices by differentiating the utility of each alternative (Ortuzar, Hensher, & Jara-Diaz, 1999).”

  • The authors state this as an assumption.

    The decision of choosing a mode is influenced by the duration of the trip.

    “Two separate mode choice models were estimated for domestic day and overnight trips, assuming that a decision of choosing a mode is influenced by the duration of the trip.”

  • The paper relies on this without support.

    Many domestic air trips in Germany are business trips for which the employer covers the travel costs, which tends to reduce price sensitivity.

    “Also, many domestic air trips in Germany are business trips for which the employer covers the travel costs, which tends to reduce price sensitivity.”

  • The paper relies on this without support.

    Traveling by auto is often more economical than other public ground modes, particularly when traveling with more than one person.

    “Traveling by auto is often more economical than other public ground modes, particularly when traveling with more than one person.”
4 of 4

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

  • Bus-emissions total does not add up

    Major

    The day-trip and overnight bus emissions sum to 2,307.10 tons, not 3,937.06 tons. The reported grand total is consequently 1,629.96 tons higher than the sum of its day-trip and overnight totals.

    Reported 3937.06 · recomputed 2307.1

1 of 1

Cites

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1 of the 47 references couldn’t be matched to a known paper.

Cited by

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Related

Authors
Pukhova, A., Moreno, A. T., Llorca, C., Huang, W.-C., & Moeckel, R.
Affiliations
Technical University of Munich (DE)
ORCID
Venue
Urban Planning
Publisher
Cogitatio
Published
2021-06-09
Volume
6
Issue
2
Pages
271-284
ISSN
2183-7635 (ISSN-L)
DOI
10.17645/up.v6i2.4021
OpenAlex
W3172597124
Cited by
16
References
47
Citations by year
2026: 3 · 2025: 8 · 2024: 2 · 2023: 1 · 2022: 1 · 2021: 1
FWCI
1.86
Type
journal article
Language
en
Open access
Licence
Locations
  • Urban Planning (publishedVersion, cc-by)
  • Social Science Open Access Repository (GESIS – Leibniz Institute for the Social Sciences) (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • mediaTUM (Technical University of Munich) (submittedVersion)
  • mediaTUM (Technical University of Munich) (submittedVersion, other-oa)
  • Cogitatio (Cogitatio) (submittedVersion, cc-by)
Funders
  • European Commission (291763)
  • Deutsche Forschungsgemeinschaft (291763)
  • Technische Universität München (291763)
  • International Graduate School of Science and Engineering
Topics
  • Social Sciences › Economics, Econometrics and Finance › General Economics, Econometrics and Finance › Aviation Industry Analysis and Trends
  • Social Sciences › Transportation › Transportation Planning and Optimization
  • Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Energy, Environment, and Transportation Policies
Keywords
domestic air travel, travel demand modeling, agent-based modeling, mode choice, destination choice, trip generation, transport emissions reduction

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Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-13.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-13.

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