Journal Papers

Slashing warming pollution to the near-zero levels needed to stop global climate change will require massive investments in nearly every industry. However, nearly all of today’s clean industrial investment is focused on a few sectors where technologies and business strategies are relatively mature and thus risks are relatively low: renewable energy, electric grids with battery storage, and electric vehicles (1). In other industries that lag behind, investment in new technologies and business practices involves much larger risks that are harder for investors to fathom. The aviation sector is emblematic of the challenge. A new approach is needed that is more realistic about what is achievable and better aligned with how real-world investors balance risk and reward. We outline an approach that could help guide a pioneer group of research and development (R&D) programs alongside investors and airlines who are motivated to deploy new technology.

Models of air freight are often constrained by a lack of available data. This study brings together different sources of air freight supply and demand data to address this gap. To study air freight operations, we combine schedules, flight tracking data and country-level databases of passenger and freight movements to produce estimates of global flight segment-level capacity and load factors in freighter aircraft and passenger holds for 2019–2021. To study true origin-ultimate destination air freight demand, a freight mode choice model by commodity group is developed for 2019 to fill gaps in mode information in international and national trade datasets, and estimates are made for 2019 and 2021. Initial comparisons of supply and demand data demonstrate that air freight journeys differ significantly from passenger journeys, typically including more flight legs (roughly, around 2, compared to 1.2 for passengers) and greater leg distances (2.2–2.5 times average passenger distance), with significant asymmetry in commodity flows and operations to and from individual countries and regions. These differences persist in 2021, despite COVID-19 induced shifts towards carrying more air freight in freighter aircraft. This research forms a first step towards making available an integrated database of estimated global air freight flows by commodity.

Aviation emissions that are dispersed into the Earth's atmosphere affect the climate and air pollution, with significant spatiotemporal variation owing to heterogeneous aircraft activity. In this paper, we use historical flight trajectories derived from Automatic Dependent Surveillance–Broadcast (ADS-B) telemetry and reanalysis weather data for 2019–2021 to develop the Global Aviation emissions Inventory based on ADS-B (GAIA). In 2019, 40.2 million flights collectively travelled 61 billion kilometres using 283 Tg of fuel, leading to CO₂, NO_x and non-volatile particulate matter (nvPM) mass and number emissions of 893 Tg, 4.49 Tg, 21.4 Gg and 2.8 × 1026 respectively. Global responses to COVID-19 led to reductions in the annual flight distance flown and CO₂ and NO_x emissions in 2020 (−43 %, −48 % and −50 % respectively relative to 2019) and 2021 (−31 %, −41 % and −43 % respectively), with significant regional variability. Short-haul flights with durations < 3 h accounted for 83 % of all flights but only for 35 % of the 2019 CO₂ emissions, while long-haul flights with durations > 6 h (5 % of all flights) were responsible for 43 % of CO₂ and 49 % of NO_x emissions. Globally, the actual flight trajectories flown are, on average, ∼ 5 % greater than the great circle path between the origin and destination airports, but this varies by region and flight distance. An evaluation of 8705 unique flights between London and Singapore showed large variabilities in the flight trajectory profile, fuel consumption and emission indices. GAIA captures the spatiotemporal distribution of aviation activity and emissions and is provided for use in future studies to evaluate the negative externalities arising from global aviation.

Aviation emissions are not on a trajectory consistent with Paris Climate Agreement goals. We evaluate the extent to which fuel pathways–synthetic fuels from biomass, synthetic fuels from green hydrogen and atmospheric CO₂, and the direct use of green liquid hydrogen – could lead aviation towards net-zero climate impacts. Together with continued efficiency gains and contrail avoidance, but without offsets, such an energy transition could reduce lifecycle aviation CO₂ emissions by 89–94% compared with year-2019 levels, despite a 2–3-fold growth in demand by 2050. The aviation sector could manage the associated cost increases, with ticket prices rising by no more than 15% compared with a no-intervention baseline leading to demand suppression of less than 14%. These pathways will require discounted investments on the order of US$0.5–2.1 trillion over a 30 yr period. However, our pathways reduce aviation CO₂-equivalent emissions by only 46–69%; more action is required to mitigate non-CO₂ impacts.

The COVID-19 pandemic had a dramatic impact on aviation in 2020, and the industry’s future is uncertain. In this paper, we consider scenarios for recovery and ongoing demand, and discuss the implications of these scenarios for aviation emissions-related policy, including the Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) and the EU Emissions Trading Scheme (ETS). Using the Aviation Integrated Model (AIM2015), a global aviation systems model, we project how long-term demand, fleet, and emissions projections might change. Depending on recovery scenario, we project cumulative aviation fuel use to 2050 might be up to 9% below that in scenarios not including the pandemic. The majority of this difference arises from reductions in relative global income levels. Around 40% of modeled scenarios project no offset requirement in either the CORSIA pilot or first phases; however, because of its more stringent emissions baseline (based on reductions from year 2004–2006 CO₂, rather than constant year-2019 CO₂), the EU ETS is likely to be less affected. However, if no new policies are applied and technology developments follow historical trends, year-2050 global net aviation CO₂ is still likely to be well above industry goals, including the goal of carbon-neutral growth from 2019, even when the demand effects of the pandemic are accounted for.

Airport capacity limitations have been suggested to lead to reduced pass-through of airline cost changes, and increased airline profits. Theoretically, these outcomes arise from limited supply leading to profit-optimal passenger fares, determined only by available capacity. Practically, however, outcomes depend on real-world airline networks, fleet, and costs. We model airline competition across an existing network (Australian intercity domestic flights) with endogenously generated fares and frequency to investigate this. Consistent with theory, we find less pass-through at airports with more stringent capacity constraints and where airlines are unequally affected by cost changes. Per-passenger airline profit increases roughly linearly with constraint stringency.

Theoretical analyses of the impact of airport capacity expansion must model or make assumptions about the effect of capacity on demand, airline competition, aircraft types, fares and other characteristics of a given airport. In this paper, we use empirical data on historical schedules, fares, delays and demand for the busiest 150 airports in 2015 to examine the typical impact of historical capacity expansions. We find significant diversity in outcomes, with over half the expanded airports either using less than their pre-expansion capacity or remaining constrained even at post-expansion capacity by 2016. Many of the expected impacts, such as reductions in typical aircraft size, either do not materialise or are dominated by other effects (for example, recessions; airlines beginning or ending operations at an airport; changes in regulation). Behaviour on expansion is affected by slot control regulations and whether the airport is initially capacity-constrained. In particular, slot-controlled airports typically add new destinations and carriers on expansion rather than making significant changes to existing schedules.

The inherently global, connected nature of aviation means that carbon leakage from aviation policy does not necessarily behave similarly to leakage from other sectors. We model carbon leakage from a range of aviation policy test cases applied to a specific country (the United Kingdom), motivated by a desire to reduce aviation CO₂ faster than achievable by currently-planned global mitigation efforts in pursuit of a year-2050 net zero CO₂ target. We find that there are two main components to leakage: one related to passenger behaviour, which tends to result in emissions reductions outside the policy area (negative leakage), and one related to airline behaviour, which tends to result in emissions increases outside the policy area (positive leakage). The overall leakage impact of a policy, and whether it is positive or negative, depends on the balance of these two components and the geographic scope used, and varies for different policy types. In our simulations, carbon pricing-type policies were associated with leakage of between +50 and −150% depending on what is assumed about scope and the values of uncertain parameters. Mandatory biofuel use was associated with positive leakage of around 0–40%, and changes in airport landing costs to promote more fuel-efficient aircraft were associated with positive leakage of 50–150%.

Policies aimed at influencing air transportation must operate in a complex, interacting global system of passengers, airlines, airports and other stakeholders. Tools which are capable of assessing policy outcomes in this situation are vital. Given the high uncertainty about future demand, costs and technology characteristics on policy-relevant timescales, such tools also need to allow the evaluation of outcomes from a wide range of plausible futures. This paper presents the validation study and initial baseline results from a comprehensive, open source update of the global AIM aviation systems model. We show that running the model from 2005 to 2015 using 2005 base year data reproduces well the observed demand levels and patterns of growth. Running from a 2015 base year, we project global demand in 2050 of between 13,800 billion and 46,000 billion revenue passenger kilometres (RPK), respectively 2.2 and 7.4 times year 2015 values, depending primarily on the future scenario for population, income and oil price assumed. Absent any radical change in aircraft technology, this would lead to global direct CO₂ emissions from aviation of between 876 and 2500 Mt, or 1.5 to 4.4 times the year-2015 level. This wide level of baseline variation may present a challenge for long-term aviation policy and its adaptability to different futures.

This paper demonstrates the ability of a model, which simulates competition between airlines in a domestic aviation market, to accurately reproduce real-world behavior. The Australian market was chosen as a test case as it is a geographically isolated region with significant demand and complexity, including one of the busiest routes in the world, where connecting international passengers do not significantly skew the market. The model is based on an n-player noncooperative game, in which each airline represents a player within the game. The primary assumption is that each airline attempts to maximize profits by adjusting the decision variables of airfares, flight frequency, and choice of aircraft on routes within its network. The approach works iteratively, allowing each airline to respond to the decisions made by other airlines during each successive optimization. The model is said to reach convergence when there is no significant change in any airline’s profit from one iteration to the next. Once this occurs, the predictions of each airline’s decision variables can be compared with real data. The model gives highly detailed predictions of airline specific airfares, flight frequencies on segments, passenger flows, and airline market share, which strongly correlate with observed values.

This paper examines the beneficial impact of high-speed rail (HSR) on reducing aviation CO₂ emissions in China. As a fast-growing economy and the world’s largest CO₂ emitter, China has made massive infrastructure investments but has also committed to reducing emissions across all sectors. This study demonstrates that investments in China’s HSR can effectively contribute to reduction of emissions from domestic aviation, a sector that is particularly challenging to decarbonize. Although a wide body of literature has assessed the competition between HSR and air transport, little attention has been paid to the climate implications of this phenomenon. It is estimated that, through mode substitution for air transport, HSR generated a cumulative net saving of between 1.76 and 2.76 million tons of CO₂ from 2012 to 2015. This was equivalent to 3.2%–5.1% of 2015 domestic aviation emissions. Importantly, it is also demonstrated that by not taking into account the electricity consumption of HSR, its environmental benefits could be overestimated. Lastly, through analysis of future energy mix scenarios this study highlights that HSR has a great potential to reduce CO₂ emissions even further if China achieved its climate pledge in the Paris Agreement in terms of decarbonizing its electricity generation sector by 2030.

Ever since the Wright brothers’ first powered flight in 1903, commercial aircraft have relied on liquid hydrocarbon fuels. However, the need for greenhouse gas emission reductions along with recent progress in battery technology for automobiles has generated strong interest in electric propulsion in aviation. This Analysis provides a first-order assessment of the energy, economic and environmental implications of all-electric aircraft. We show that batteries with significantly higher specific energy and lower cost, coupled with further reductions of costs and CO₂ intensity of electricity, are necessary for exploiting the full range of economic and environmental benefits provided by all-electric aircraft. A global fleet of all-electric aircraft serving all flights up to a distance of 400–600 nautical miles (741–1,111 km) would demand an equivalent of 0.6–1.7% of worldwide electricity consumption in 2015. Although lifecycle CO₂ emissions of all-electric aircraft depend on the power generation mix, all direct combustion emissions and thus direct air pollutants and direct non-CO₂ warming impacts would be eliminated.

We analyze the costs of CO₂ emissions mitigation measures available to aviation using a global aviation systems model. In that context, we discuss the relationship between mitigation potential and scenario characteristics, and how these interact with policy measures that increase the effective price of fuel, for example, ICAO’s CORSIA emissions offset scheme. We find that global fuel lifecycle CO₂ emissions per revenue passenger km could be reduced by 1.9% to 3.0% per year on average by the use of a combination of cost-effective measures, for oil prices which reach $75 to $185 per barrel by 2050. Smaller additional emissions reductions, of the order of 0.1% per year, are possible if carbon prices of $50 to $150/tCO₂ are assumed by 2050. These outcomes strongly depend on assumptions about biofuels, which account for about half of the reduction potential by 2050. Absolute reductions in emissions are limited by the relative lack of mitigation options for long-haul flights, coupled with strong demand growth.

Studies assessing the impact of market-based environmental policies in aviation rely on various scenarios of airline cost pass-through, because there is little empirical evidence with respect to the impacts of airline costs on airfares. Instead, the costs effect has been indirectly measured by proxy variables such as distance, fuel price, and aircraft sizes. This paper provides empirical evidence of airline cost pass-through by developing an airfare model that explicitly captures airline operating costs. Using a feasible generalized two-stage least squares (FG2SLS) approach, we obtained coefficients of airline fuel costs per passenger, non-fuel costs per passenger, and non-fuel costs per flight modeling for seven world regions (20 region-pair markets). A comparison of the estimated cost pass-through elasticities conducted across regional markets suggests that airlines may respond to the cost increases differently, depending on the cost types and the markets they operate in. Based on the estimated coefficients, we systematically evaluate the potential impacts of introducing a carbon tax policy within two major regional markets with distinct cost pass-through elasticities.

An investigation was made into whether passenger delays and airline costs due to disruptive events affecting European airports could be reduced by a coordinated strategy of using alternative flights and ground transportation to help stranded passengers reach their final destination using airport collaborative decision-making concepts. Optimizing for airline cost for hypothetical disruptive events suggests that, for airport closures of up to 10 h, airlines could benefit from up to a 20% reduction in passenger delay-related costs. The mean passenger delay could be reduced by up to 70%, mainly via a reduction in very long delays.

In response to strong growth in air transportation CO₂ emissions, governments and industry began to explore and implement mitigation measures and targets in the early 2000s. However, in the absence of rigorous analyses assessing the costs for mitigating CO₂ emissions, these policies could be economically wasteful. Here we identify the cost-effectiveness of CO₂ emission reductions from narrow-body aircraft, the workhorse of passenger air transportation. We find that in the US, a combination of fuel burn reduction strategies could reduce the 2012 level of life cycle CO₂ emissions per passenger kilometre by around 2% per year to mid-century. These intensity reductions would occur at zero marginal costs for oil prices between US$50–100 per barrel. Even larger reductions are possible, but could impose extra costs and require the adoption of biomass-based synthetic fuels. The extent to which these intensity reductions will translate into absolute emissions reductions will depend on fleet growth.

Carbon-fibre-reinforced polymers (CFRP) have been developed by the aviation industry to reduce aircraft fuel burn and emissions of greenhouse gases. This study presents a life cycle assessment (LCA) of an all-composite airplane, based on a Boeing 787 Dreamliner. The global transition of aircraft to those of composite architecture is estimated to contribute 20–25% of industry CO₂ reduction targets. A secondary stage of the cradle-to-grave analysis expands the study from an individual aircraft to the global fleet.

In this paper we use simulation to analyze how flight routing network structure may change in different world regions, and how this might impact future traffic growth and emissions. We compare models of the domestic Indian and US air transportation systems, representing developing and mature air transportation systems respectively. We explicitly model passenger and airline decision-making, capturing passenger demand effects and airline operational responses, including airline network change. The models are applied to simulate air transportation system growth for networks of 49 airports in each country from 2005 to 2050. In India, the percentage of connecting passengers simulated decreases significantly (from over 40% in 2005 to under 10% in 2050), indicating that a shift in network structure towards increased point-to-point routing can be expected. In contrast, very little network change is simulated for the US airport set modeled. The simulated impact of network change on system CO₂ emissions is very small, although in the case of India it could enable a large increase in demand, and therefore a significant reduction in emissions per passenger (by nearly 25%). NO_x emissions at major hub airports are also estimated, and could initially reduce relative to a case in which network change is not simulated (by nearly 25% in the case of Mumbai in 2025). This effect, however, is significantly reduced by 2050 because of frequency competition effects. We conclude that network effects are important when estimating CO₂ emissions per passenger and local air quality effects at hub airports in developing air transportation systems.

This special issue of air transportation and the environment brings together analyses carried out by the integrated aviation modeling teams at the Massachusetts Institute of Technology and the University of Cambridge over the past 5–8 years. All contributions directly or indirectly relate to the challenges of measuring and/or responding to the environmental impact of air transportation in terms of noise, air pollution, and climate change. The contributors to this special issue identify several promising mitigation opportunities. However, in light of an anticipated continued growth in global aviation demand in the order of 5–6% per year, the identified opportunities are likely to only mitigate the growth in environmental impacts, at least over the next 20–30 years.

Between 1960 and 2011, worldwide scheduled passenger air travel grew by more than 7% per year. Most projections suggest that the demand for air travel will continue to increase strongly, by around 5% per year over the coming decades. This strong anticipated growth, however, does not account for any air transport infrastructure constraints. Airport and airspace capacity may not be expanded at a rate sufficiently high to enable the projected demand growth, which may lead to lower than anticipated growth in aviation. This paper describes and applies a recently developed model that predicts airline operational responses to airport capacity constraints. It does this by simulating a Nash best-response game between competing airlines, in which each airline maximizes its profit by adjusting flight frequencies and passenger routing, attempting to gain market share by increasing flight frequencies, but at the cost of the added flights. The model is validated for a network of airports in the United States in 2005 and applied to simulate airline operational changes through 2030 under two capacity-constrained scenarios: frozen 2005 capacity levels on (i) a system-wide scale, and (ii) only at Chicago O׳Hare International, a primary hub airport. Simulated passenger demand, air traffic, flight delays, system CO₂ emissions and Chicago O׳Hare NO_x emissions are compared to a case in which airport capacity is expanded according to existing airport expansion plans. The simulation results indicate that the air transport system would adjust operations within a constrained network in such way as to avoid airports with high delays. While most system-wide implications for operations and environmental impact seem to be manageable, local impacts at congested hub-airports may be significant.

We describe the current status of knowledge regarding the contribution of aviation to anthropogenic climate forcing. The emissions and associated radiative forcings from aviation are compared to those from other modes of transport. The different analytical metrics used to quantify climate forcing are presented showing their relevancies and uncertainties. The discussion then focuses on the use of radiative forcing, one of the most commonly used metric, in accounting for the climate change contribution from aviation with a particular look at how the contribution from CO₂ and non-CO₂ greenhouse gases can be compared.

If all aircraft in the global fleet were replaced with the most fuel-efficient present-day substitute technology, global aviation CO₂ emissions could be reduced by as much as 10%. However, the long lifetimes both of individual aircraft and of aircraft models in production mean that, in reality, any technology-based methods of emissions reduction will take a significant time to percolate into the fleet. The timescale over which new technology enters the fleet depends on a number of factors, most notably the demand for new aircraft, and is a potential barrier for technology-based (as opposed to economic or operational) policy measures. In this paper we evaluate aviation CO₂ emissions for the US, Europe and the world, discuss the theoretical reductions possible by substituting newer technology, assess the timescales on which these emission reductions are achievable, and discuss other timescales which may affect policy outcomes.

The negative external impacts of aviation are currently under unprecedented scrutiny. In response, a number of studies into future prospects for improvement have recently been carried out. This paper reviews these studies and discusses their combined implications for emissions of carbon dioxide, oxides of nitrogen, and noise. The results are also compared with targets for emissions reduction proposed by ACARE and NASA. It is concluded that significant future gains are achievable, but not to the extent implied by the ACARE and NASA targets, which represent an unrealistically optimistic view of technological potential over the next 20–40 years. The focus on technological advance also deflects attention from the substantial benefits available from combining present-day technology with behavioural change. Finally, difficult policy decisions will be necessary; the greatest benefits are associated with technological developments that will require major, and long-term, investment for their realisation, and there will be increasing conflict between environmental and noise goals.

Air traffic management has a fundamentally important role in reducing the environmental impacts of air transportation by reducing the inefficiencies in the paths flown by aircraft. The potential causes of flight inefficiency are discussed in this paper, followed by the development of flight inefficiency metrics to quantify the performance of the system. Metrics based on track extensions and fuel inefficiency are used with operational data to illustrate how quantifying inefficiencies in different flight phases can be used to indicate where the largest potential scope exists for improving the system and hence can be used to guide policy-makers as they evolve the air traffic management system. For example, the analyses presented here highlight the relative importance of allowing aircraft to fly closer to their optimal four-dimensional trajectories and reducing inefficiencies in high fuel burn phases of flight. It also discusses what operational and technical enablers might be appropriate to help achieve fuel burn and environmental impact reduction.

Stimulating fleet renewal and attaching a price to carbon dioxide emissions have both been suggested as ways of reducing aviation׳s environmental impact. One potential route for emissions reduction is to combine these policy options, by applying a carbon tax which is used to subsidize fleet renewal. Such a policy would have impacts on many aspects of the aviation system, including demand, fleet composition, traffic delays, and airfares. Therefore, its impacts need to be considered holistically, taking into account likely interaction and feedback effects. In this paper, we apply a model of the global aviation system, the Aviation Integrated Model (AIM), to assess the demand and emissions response from passenger aviation following the application of such an aviation sector policy. We find that by 2050, aviation lifecycle carbon dioxide emissions may be reduced by up to 34% compared to the no-policy case for a policy aimed at retiring aircraft over 20 years old.

This paper analyzes energy intensities of ships, diesel-fuelled railways, trucks, and aircraft, using publicly available data. The analysis suggests that differences in operation, not technology, explain most of the variation in energy intensity within and across modes. Among the operational characteristics, most important is the amount of cargo weight transported per vehicle and therefore the scale of the respective transportation system. It is found that each mode has a characteristic envelope in an average energy intensity versus average cargo weight diagram, and estimates of the elasticities of energy intensity with respect to load size are made.

We model global aviation biofuel uptake under a future emissions trading policy, and compare aviation CO₂ emission reductions with climate impact reductions (CO₂ and non-CO₂). We find that climate impacts in terms of global warming potential are less favourable than CO₂ climate impacts for biofuel use, dependent on the time horizon of the chosen output climate metric. Results indicate that widespread use of aviation biofuel may lead to a scenario in which aviation growth is accompanied by flat or decreasing carbon emissions but an increasing total climate impact.

The rebound effect, i.e., the (partial) offset of the energy efficiency improvement potential due to a reduction in marginal usage costs and the associated increase in consumer demand, has been extensively studied for residential energy demand and automobile travel. This study presents a quantitative estimate of the rebound effect for an air traffic network including the 22 busiest airports, which serve 14 of the highest O–D cities within the domestic U.S. aviation sector. To satisfy this objective, passenger flows, aircraft operations, flight delays and the resulting energy use are simulated. Our model results indicate that the average rebound effect in this network is about 19%, for the range of aircraft fuel burn reductions considered. This is the net impact of an increase in air transportation supply to satisfy the rising passenger demand, airline operational effects that further increase supply, and the mitigating effects of an increase in flight delays. Although the magnitude of the rebound effect is small, it can be significant for a sector that has comparatively few options for reducing greenhouse gas emissions.

Many options for mitigating aviation's environmental impact rely on introduction of new aircraft technology, retrofits or early retirement of older aircraft. Using a global fleet database, we analyse aircraft lifecycles and their interaction with fuel price, demand, policy and economic cycles. Simple relationships, including aircraft retirement curves, are estimated to allow insight into the effectiveness and timescales of emissions reductions from these measures. We find variations in retirement age and retrofits have historically had little effect on global emissions. The design and purchasing stages offer a more promising target, subject to long timescales and demand growth rates.

Using a new data set describing the techno-economic characteristics of current and projected future transport technologies and a synthesis of existing transport demand models, lifecycle CO₂ emissions from 27 EU countries (EU27) were estimated in the absence and presence of new policy interventions to 2050. Future CO₂ emissions are strongly dependent on geographical scope and economic growth assumptions, and to a lesser extent on uncertainties in technology characteristics, but in the absence of new policy intervention they continue to rise from present-day values in all three scenarios examined. Consequently, EU27 emissions goals, which may require a 60% decrease in transport sector greenhouse gas emissions from year-1990 values by 2050, will be difficult to meet. This is even the case under widespread adoption of the most promising technologies for all modes, due primarily to limitations in biofuel production capacity and a lack of technologies that would drastically reduce CO₂ emissions from heavy trucks and intercontinental aviation.

This paper simulates airline strategic decision making and its impact on passenger demand, flight delays and aircraft emissions. Passenger flows, aircraft operations, flight delays and aircraft emissions are simulated for 22 airports in the US, under three airport capacity scenarios. The simulation results indicate that most system-wide implications for operations and environmental impact seem to be manageable, but local impacts at congested hub airports may be significant. The response of the air transportation system to avoid airports with high delays could significantly impact passenger demand and air traffic for these and directly dependent airports. The simulations also suggest that frequency competition effects could maintain flight frequencies at high levels, preventing a significant shift toward larger aircraft, which would otherwise reduce the impact of the capacity constraints.

Aircraft emissions impact human health though degradation of air quality. The majority of previous analyses of air quality impacts from aviation have considered only landing and takeoff emissions. We show that aircraft cruise emissions impact human health over a hemispheric scale and provide the first estimate of premature mortalities attributable to aircraft emissions globally. We estimate ∼8000 premature mortalities per year are attributable to aircraft cruise emissions. This represents ∼80% of the total impact of aviation (where the total includes the effects of landing and takeoff emissions), and ∼1% of air quality-related premature mortalities from all sources. However, we note that the impact of landing and takeoff emissions is likely to be under-resolved. Secondary H₂SO₄–HNO₃–NH₃ aerosols are found to dominate mortality impacts. Due to the altitude and region of the atmosphere at which aircraft emissions are deposited, the extent of transboundary air pollution is particularly strong. For example, we describe how strong zonal westerly winds aloft, the mean meridional circulation around 30–60°N, interaction of aircraft-attributable aerosol precursors with background ammonia, and high population densities in combination give rise to an estimated ∼3500 premature mortalities per year in China and India combined, despite their relatively small current share of aircraft emissions. Subsidence of aviation-attributable aerosol and aerosol precursors occurs predominantly around the dry subtropical ridge, which results in reduced wet removal of aviation-attributable aerosol. It is also found that aircraft NO_x emissions serve to increase oxidation of nonaviation SO₂, thereby further increasing the air quality impacts of aviation. We recommend that cruise emissions be explicitly considered in the development of policies, technologies and operational procedures designed to mitigate the air quality impacts of air transportation.

A new computational method has been developed that simulates the performance of an aircraft and determines the fuel consumption and emissions throughout the flight trajectory by linking the main aircraft aerodynamic characteristics with a model of engine performance. The Performance Emission Simulation of aircraft Operations (PESO) model responds to the needs of the Aviation Integrated Modelling (AIM) project by delivering a computationally fast and reliable model able to simulate aircraft performance, fuel use and emissions. The method is novel in that the airframe aerodynamic characteristics and the performance of the engine are modelled by generic non-dimensional relationships. These non-dimensional characteristics are sufficient to enable accurate determination of the forces acting on the aircraft, the fuel burn of the engine and the key parameters that determine the emissions of pollutants such as nitrous oxides. Within this paper, this new non-dimensional approach is demonstrated and validated using comparisons with flight data from commercial aircraft operations. The results show that the methodology used is sound and that the model can accurately simulate aircraft performance for a range of flight conditions and operating procedures. In future work with the AIM project the method will be applied to investigate novel aircraft technologies, new operating procedures and alternative fuels.

This paper investigates the interaction between economic, technological and operational measures intended to reduce air transport-related CO₂ emissions. In particular, the introduction of aviation to the European Emissions Trading Scheme (ETS) in 2012 may prompt increased uptake of presently-available emission reduction options (e.g. retrofitting winglets, expanding maintenance programs) by airlines operating in Europe. In the future, carbon prices may also determine the usage of new options currently under development (e.g. open rotor engines, second-generation biofuels and improved air traffic management (ATM)). We apply the results of a number of studies analyzing the airline costs and emission reductions possible from different mitigation options to a systems model of European aviation. Using a set of nine scenarios (three internally-consistent projections for future population, gross domestic product, oil and carbon prices, each run with three policy cases), we analyze technology uptake and the resulting effect on fuel lifecycle CO₂ emissions with and without an ETS. We find that some options are rapidly taken up under all scenarios (e.g. improved ATM), others are taken up more slowly by specific aircraft classes depending on the scenario (e.g. biofuels) and others have negligible impact in the cases studied. High uptake of one mitigation option may also reduce the uptake of other options. Finally, it is observed that European aviation fuel lifecycle emissions could be reduced below 2005 levels before 2050 if cellulosic biomass fuels are made available from 2020. However, the land use requirements in this scenario may limit its practicality at currently-projected cellulosic biomass yields.

Predicting long-term mean pollutant concentrations in the vicinity of airports, roads and other industrial sources are frequently of concern in regulatory and public health contexts. Many emissions are represented geometrically as ground-level line or area sources. Well developed modelling tools such as AERMOD and ADMS are able to model dispersion from finite (i.e. non-point) sources with considerable accuracy, drawing upon an up-to-date understanding of boundary layer behaviour. Due to mathematical difficulties associated with line and area sources, computationally expensive numerical integration schemes have been developed. For example, some models decompose area sources into a large number of line sources orthogonal to the mean wind direction, for which an analytical (Gaussian) solution exists. Models also employ a time-series approach, which involves computing mean pollutant concentrations for every hour over one or more years of meteorological data. This can give rise to computer runtimes of several days for assessment of a site. While this may be acceptable for assessment of a single industrial complex, airport, etc., this level of computational cost precludes national or international policy assessments at the level of detail available with dispersion modelling. In this paper, we extend previous work [S.R.H. Barrett, R.E. Britter, 2008. Development of algorithms and approximations for rapid operational air quality modelling. Atmospheric Environment 42 (2008) 8105–8111] to line and area sources. We introduce approximations which allow for the development of new analytical solutions for long-term mean dispersion from line and area sources, based on hypergeometric functions. We describe how these solutions can be parameterized from a single point source run from an existing advanced dispersion model, thereby accounting for all processes modelled in the more costly algorithms. The parameterization method combined with the analytical solutions for long-term mean dispersion are shown to produce results several orders of magnitude more efficiently with a loss of accuracy small compared to the absolute accuracy of advanced dispersion models near sources. The method can be readily incorporated into existing dispersion models, and may allow for additional computation time to be expended on modelling dispersion processes more accurately in future, rather than on accounting for source geometry.

In regulatory and public health contexts the long-term average pollutant concentration in the vicinity of a source is frequently of interest. Well-developed modelling tools such as AERMOD and ADMS are able to generate time-series air quality estimates of considerable accuracy, applying an up-to-date understanding of atmospheric boundary layer behaviour. However, such models incur a significant computational cost with runtimes of hours to days. These approaches are often acceptable when considering a single industrial complex, but for widespread policy analyses the computational cost rapidly becomes intractable. In this paper we present some mathematical techniques and algorithmic approaches that can make air quality estimates several orders of magnitude faster. We show that, for long-term average concentrations, lateral dispersion need not be accounted for explicitly. This is applied to a simple reference case of a ground-level point source in a neutral boundary layer. A scaling law is also developed for the area in exceedance of a regulatory limit value.