Search

We report on an inconsistency in the latitudinal distribution of aviation emissions between the data products of phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP). Emissions in the CMIP6 data occur at higher latitudes than in the CMIP5 data for all scenarios, years, and emitted species. A comparative simulation with the chemistry–climate model ECHAM/MESSy Atmospheric Chemistry (EMAC) reveals that the difference in nitrogen oxide emission distribution leads to reduced overall ozone changes due to aviation in the CMIP6 scenarios because in those scenarios the distribution of emissions is partly shifted towards the chemically less active higher latitudes. The radiative forcing associated with aviation ozone is 7.6 % higher, and the decrease in methane lifetime is 5.7 % larger for the year 2015 when using the CMIP5 latitudinal distribution of emissions compared to when using the CMIP6 distribution. We do not find a statistically significant difference in the radiative forcing associated with aviation aerosol emissions. In total, future studies investigating the effects of aviation emissions on ozone and climate should consider the inconsistency reported here.

The optimization of aircraft trajectories involves balancing operating costs and climate impact, which are often conflicting objectives. To achieve compromise optimal solutions, higher-level information such as preferences of decision-makers must be taken into account. This paper introduces the SolFinder 1.0 module, a decision-making tool designed to identify eco-efficient aircraft trajectories, which allow to reduce the flights climate impact with limited cost penalties compared to cost-optimal solutions. SolFinder 1.0 offers flexible decision-making options that allow users to select trade-offs between different objective functions, including fuel use, flight time, NOx emissions, contrail distance, and climate impact. The module is included in the AirTraf 3.0 submodel, which optimizes trajectories under atmospheric conditions simulated by the ECHAM/MESSy Atmospheric Chemistry model. This paper focuses on the ability of the module to identify eco-efficient trajectories while solving a bi-objective optimization problem that minimizes climate impact and operating costs. SolFinder 1.0 enables users to explore trajectory properties at varying locations of the Pareto fronts without prior knowledge of the problem results and to identify solutions that limit the cost of reducing the climate impact of a single flight.

The climate impact of non-CO2 emissions, which are responsible for two-thirds of aviation radiative forcing, highly depends on the atmospheric chemistry and weather conditions. Hence, by planning aircraft trajectories to reroute areas where the non-CO2 climate impacts are strongly enhanced, called climate-sensitive regions, there is a potential to reduce aviation-induced non-CO2 climate effects. Weather forecast is inevitably uncertain, which can lead to unreliable determination of climate-sensitive regions and aircraft dynamical behavior and, consequently, inefficient trajectories. In this study, we propose robust climate-optimal aircraft trajectory planning within the currently structured airspace considering uncertainties in standard weather forecasts. The ensemble prediction system is employed to characterize uncertainty in the weather forecast, and climate-sensitive regions are quantified using the prototype algorithmic climate change functions. As the optimization problem is constrained by the structure of airspace, it is associated with hybrid decision spaces. To account for discrete and continuous decision variables in an integrated and more efficient manner, the optimization is conducted on the space of probability distributions defined over flight plans instead of directly searching for the optimal profile. A heuristic algorithm based on the augmented random search is employed and implemented on graphics processing units to solve the proposed stochastic optimization computationally fast. An open-source Python library called ROOST (V1.0) is developed based on the aircraft trajectory optimization technique. The effectiveness of our proposed strategy to plan robust climate-optimal trajectories within the structured airspace is analyzed through two scenarios: a scenario with a large contrail climate impact and a scenario with no formation of persistent contrails. It is shown that, for a nighttime flight from Frankfurt to Kyiv, a 55 % reduction in climate impact can be achieved at the expense of a 4 % increase in the operating cost.

Emissions of land transport and anthropogenic non-traffic emissions (e.g. industry, households and power generation) are significant sources of nitrogen oxides, carbon monoxide, and volatile organic compounds. These emissions are important precursors of tropospheric ozone and affect air quality. The contribution of emission sectors to ozone cannot be mea- sured directly, but calculated with sophisticated models of atmospheric chemistry only. For this study we apply a the MECO(n) model system (MESSy-fied ECHAM and COSMO models nested n times) equipped with a source attribution method to investigate the contribution of anthropogenic (land transport and non-traffic) and biogenic emissions to ozone in Europe. This model system couples a global chemistry-climate mode with a regional chemistry-climate model. Our source attribution (tag- ging) method fully decomposes the budgets of ozone and ozone precursors into contributions from various emission sources and regions. To estimate also the contributions of regional versus long-range transported contributions we distinguish four different source regions: Europe, North America, East Asia and Rest of the World. We performed one simulation covering 2 years with two regional refinements, one covering Europe (50 km resolution), and one covering Central Europe (12 km resolution). The model results are evaluated with data from European air quality stations and in situ data from the flight campaign Effect of Megacities on the Transport and Transformation of Pollutants on the Regional to Global Scales (EMeRGe) Europe in Summer 2017. Two study areas with large anthropogenic emissions, Benelux and Po Valley, are compared in detail. The absolute contributions of European land transport emissions to ground-level ozone for JJA 2017 in the Po Valley are larger than in the Benelux region (7 nmol mol−1 and ≈ 3 nmol mol−1), the same applies for the relative contributions with 12 % in the Po Valley and 7 % in the Benelux regions. Similar results are found for the contribution of European anthropogenic non-traffic emissions. Here, absolute contributions are larger in the Po Valley with 11 nmol mol−1 (19 %) than 5 nmol mol−1 (15 %) in the Benelux regions. The relative contributions to ozone from long-range transported land transport emissions in both regions in the range of 5–6 %, and the relative contributions from long-range transported non-traffic emissions are 9 % in the Po Valley and 13 % in the Benelux region. Contributions to ozone from long-range transported emissions are clearly more homogeneously distributed throughout Europe, whereas the distribution of contributions to ozone from European emissions is notably in-homogeneous. During periods of high ozone, contributions of European land transport and anthropogenic non-traffic emissions increase in particular over the Po Valley and in the Benelux. Especially in the Po Valley the increase is very strong and extreme ozone values could be mitigated in the Po Valley by reducing anthropogenic emissions.

As aviation's contribution to anthropogenic climate change is increasing, industry aims at reducing the aviation climate effect. However, the large contribution of non-CO2 effects to the total climate effect of aviation and their large variability for each individual flight inhibit finding appropriate guidance. Here, we present a method for the simplified calculation of CO2 equivalent emissions, expressed using the physical climate metrics ATR100 or AGWP100, from CO2 and non-CO2 effects for a given flight, exclusively based on the aircraft seat category as well as the origin and destination airports. The simplified calculation method estimates non-CO2 climate effects of air traffic as precisely as possible, without detailed information on the actual flight route, actual fuel burn, and current weather situation. For this purpose, we evaluate a global data set containing detailed flight trajectories, flight emissions, and climate responses, and derive a set of regression formulas for climate effects, which we call climate effect functions, as well as regression formulas for fuel consumption and NOx emissions. Compared to previous studies, this method is available for a larger number of aircraft types, including most commercial airliners with seat capacities starting from 101 passengers, and delivers more specific results through a clustering approach. The climate effects calculated using the climate effect functions derived in this study exhibit a mean absolute relative error of 15.0 % and a root mean square error of 1.24 nK with respect to results from the climate response model AirClim. The climate effect functions are designed for climate footprint assessments, but would not create an incentive in an emission trading system, for which detailed information on the current weather as well as the actual flight route and profile would be required.

The aviation industry has set an ambitious goal of reducing its climate impacts. Accordingly, airlines must balance their plans according to this goal with financial considerations. We developed a multi-objective framework to facilitate climate-aware network design by incorporating the objective to minimise the flight average temperature response (ATR) when optimising the airline network. We also assessed the operational improvements (OIs) which are introduced to improve sustainability in airline operations. In particular, we considered intermediate stop-overs (ISOs) and lower flight altitudes as OIs in our case studies. We analysed the impact of considering the climate impact in the planning of operations of three different airline types: one main-hub-and-spoke (KLM), one smaller multi-hub airline (TAP), and one low-cost carrier (EasyJet). The results show that airlines could also lower their environmental impact by 10–36% when considering the ATR as an objective. However, this would require an 8–20% reduction in profits. Adopting lower-altitude flying with ISO could mitigate their climate impact by 27–49% while reducing profits by approximately 6%. Our study highlights the importance of considering the airline network as a whole and demonstrates the potential benefits of operational improvements from a network perspective.