Predicting the climate impact of aviation for en-route emissions: the algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53

Abstract

Abstract. Using climate-optimized flight trajectories is one essential measure to reduce aviation's climate impact. Detailed knowledge of temporal and spatial climate sensitivity for aviation emissions in the atmosphere is required to realize such a climate mitigation measure. The algorithmic Climate Change Functions (aCCFs) represent the basis for such purposes. This paper presents the first version of the Algorithmic Climate Change Function submodel (ACCF 1.0) within the European Centre HAMburg general circulation model (ECHAM) and Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model framework. In the ACCF 1.0, we implement a set of aCCFs (version 1.0) to estimate the average temperature response over 20 years (ATR20) resulting from aviation CO2 emissions and non-CO2 impacts, such as NOx emissions (via ozone production and methane destruction), water vapour emissions, and contrail cirrus. While the aCCF concept has been introduced in previous research, here, we publish a consistent set of aCCF formulas in terms of fuel scenario, metric, and efficacy for the first time. In particular, this paper elaborates on contrail aCCF development, which has not been published before. ACCF 1.0 uses the simulated atmospheric conditions at the emission location as input to calculate the ATR20 per unit of fuel burned, per NOx emitted, or per flown kilometre. In this research, we perform quality checks of the ACCF 1.0 outputs in two aspects. Firstly, we compare climatological values calculated by ACCF 1.0 to previous studies. The comparison confirms that in the Northern Hemisphere between 150–300 hPa altitude (flight corridor), the vertical and latitudinal structure of NOx-induced ozone and H2O effects are well represented by the ACCF model output. The NOx-induced methane effects increase towards lower altitudes and higher latitudes, which behaves differently from the existing literature. For contrail cirrus, the climatological pattern of the ACCF model output corresponds with the literature, except that contrail-cirrus aCCF generates values at low altitudes near polar regions, which is caused by the conditions set up for contrail formation. Secondly, we evaluate the reduction of NOx-induced ozone effects through trajectory optimization, employing the tagging chemistry approach (contribution approach to tag species according to their emission categories and to inherit these tags to other species during the subsequent chemical reactions). The simulation results show that climate-optimized trajectories reduce the radiative forcing contribution from aviation NOx-induced ozone compared to cost-optimized trajectories. Finally, we couple the ACCF 1.0 to the air traffic simulation submodel AirTraf version 2.0 and demonstrate the variability of the flight trajectories when the efficacy of individual effects is considered. Based on the 1 d simulation results of a subset of European flights, the total ATR20 of the climate-optimized flights is significantly lower (roughly 50 % less) than that of the cost-optimized flights, with the most considerable contribution from contrail cirrus. The CO2 contribution observed in this study is low compared with the non-CO2 effects, which requires further diagnosis.

Decision-making strategies implemented in SolFinder 1.0 to identify eco-efficient aircraft trajectories: application study in AirTraf 3.0

“…where TIME i and FUEL i represent the flight time and fuel used at the i th flight segment, respectively, while c t = 0.75 $/s and c f = 0.51 $/kg are the unit time and unit fuel costs (Burris, 2015;Yamashita et al, 2020). The climate impact of each aircraft trajectory is measured in terms of Average Temperature Response over 20 years (ATR20), as provided by the ACCF submodel (van Manen and Grewe, 2019;Yin et al, 2023). The total climate impact ATR20 tot of each aircraft trajectory is determined summing the contribution from the main climate effects:…”

“…water vapour (H 2 O), (3) ozone (O 3 ) from emission of NO x , (4) methane (CH 4 ) from emission of NO x , and (5) contrails. The term ATR20 NOx-CH4,i includes the changes in primary mode ozone induced by the reduced CH 4 atmospheric concentration, while it neglects the feedback from stratospheric water vapour (Yin et al, 2023). The present study uses ATR20 as climate metric, assuming a business-as-usual Future emission scenario (F-ATR20).…”

“…Fig. 1 illustrates the relation between the EMAC model and the three submodels that have a major relevance in our experiments: CONTRAIL (Frömming et al, 2014), ACCF (Yin et al, 2023), and AirTraf (Yamashita et al, 2020). The EMAC model provides the atmospheric conditions at a specific time and location.…”

Feasibility of contrail avoidance in a commercial flight planning system: an operational analysis

“…Many studies have modeled the formation and avoidance of contrails based on weather and climate models, such as the CoCiP model [9,13], the APCEMM model [11], aGCMs [14][15][16], or the aCCFs [17,18], to name a few. Contrail formation and evolution can also be observed directly from ground and satellite imagery [19][20][21].…”

“…Several studies have analyzed the feasibility of contrail-optimal trajectory generation in different airspace scenarios using historical flight data [17,[31][32][33][34][35][36]. It was not until [37] that a commercial flight planning system was used to evaluate the actual operational risks of pre-tactical avoidance.…”