China\'s rapid expansion of civil aviation has led to an increase in pollution-related issues, causing adverse health effects on populations near airports and downwind. Accurately quantifying aviation emissions is essential for effective emission management. Here, we developed a high-resolution aviation emissions inventory for China by employing a bottom-up approach that relied on daily flight schedules. By using the Aeronautical Information Publication (AIP) to reproduce real-world flight routes rather than conventional great-circle routes, we improved the accuracy of emissions and investigated the potential for reducing these emissions. Our findings demonstrated substantial variations in domestic civil aviation emissions both spatially and temporally. Emissions peaked in most provinces during Chinese holidays, particularly the Chinese Lunar New Year and summer holidays, highlighting the importance of detailed activity data for accurate emissions calculations. Therefore, we recommend extensive utilization of real-world flight routes, particularly in areas with limited Automatic Dependent Surveillance-Broadcast (ADS-B) coverage since they provide more accurate representations of actual flight trajectories. Our study also identified regions like Shaanxi, Sichuan, Beijing, and their surroundings having considerable potential for emission reduction due to substantial deviations from great-circle routes. This approach can enhance the accuracy and spatiotemporal resolution of aviation emissions at national and global scales throughout the year, without relying on extensive, long-term real-time flight trajectories. Additionally, it provides a unique way to quantify the potential for emission reductions across provinces in civil aviation, ultimately contributing to mitigating pollution-related health impacts from aviation emissions and promoting a more sustainable aviation industry.

Reducing aviation emissions is important as they contribute to air pollution and climate change. Several alternative aviation fuels that may reduce life cycle emissions have been proposed. Comparative life cycle assessments (LCAs) of fuels are useful for inspecting individual fuels, but systemwide analysis remains difficult. Thus, systematic properties like fleet composition, performance, or emissions and changes to them under alternative fuels can only be partially addressed in LCAs. By integrating the geospatial fuel and emission model, AviTeam, with LCA, we can assess the mitigation potential of a fleetwide use of alternative aviation fuels on 210 000 shorter haul flights. In an optimistic case, liquid hydrogen (LH2) and power-to-liquid fuels, when produced with renewable electricity, may reduce emissions by about 950 GgCO2eq when assessed with the GWP100 metric and including non-CO2 impacts for all flights considered. Mitigation potentials range from 44% on shorter flights to 56% on longer flights. Alternative aviation fuels\' mitigation potential is limited because of short-lived climate forcings and additional fuel demand to accommodate LH2 fuel. Our results highlight the importance of integrating system models into LCAs and are of value to researchers and decision-makers engaged in climate change mitigation in the aviation and transport sectors.

In recent years, there has been an increasing amount of research on nitrogen oxides (NOx) emissions, and the environmental impact of aviation NOx emissions at cruising altitudes has received widespread attention. NOx may play a crucial role in altering the composition of the atmosphere, particularly regarding ozone formation in the upper troposphere. At present, the ground emission database based on the landing and takeoff (LTO) cycle is more comprehensive, while high-altitude emission data is scarce due to the prohibitively high cost and the inevitable measurement uncertainty associated with in-flight sampling. Therefore, it is necessary to establish a comprehensive NOx emission database for the entire flight envelope, encompassing both ground and cruise phases. This will enable a thorough assessment of the impact of aviation NOx emissions on climate and air quality. In this study, a prediction model has been developed via convolutional neural network (CNN) technology. This model can predict the ground and cruise NOx emission index for turbofan engines and mixed turbofan engines fueled by either conventional aviation kerosene or sustainable aviation fuels (SAFs). The model utilizes data from the engine emission database (EEDB) released by the International Civil Aviation Organization (ICAO) and results obtained from several in-situ emission measurements conducted during ground and cruise phases. The model has been validated by comparing measured and predicted data, and the results demonstrate its high prediction accuracy for both the ground (R2 > 0.95) and cruise phases (R2 > 0.9). This surpasses traditional prediction models that rely on fuel flow rate, such as the Boeing Fuel Flow Method 2 (BFFM2). Furthermore, the model can predict NOx emissions from aircrafts burning SAFs with satisfactory accuracy, facilitating the development of a more complete and accurate aviation NOx emission inventory, which can serve as a basis for aviation environmental and climatic research. SYNOPSIS: The utilization of the ANOEPM-CNN offers a foundation for establishing more precise emission inventories, thereby reducing inaccuracies in assessing the impact of aviation NOx emissions on climate and air quality.

There has been a continuously growing trend in international commercial air traffic, with the exception of COVID-19 crises; however, after the recovery, the trend is expected to even sharpen. The consequences of released emissions and by-products in the environment range from human health hazards, low air quality and global warming. This study is aimed to investigate the role of aviation emissions in global warming. For this purpose, data on different variables including global air traffic and growth rate, air traffic in different continents, total global CO2 emissions of different airlines, direct and indirect emissions, air traffic in various UK airports and fuel-efficient aircraft was collected from various sources like EU member states, Statista, Eurostat, IATA, CAA and EUROCONTROL. The results indicated that in 2019, commercial airlines carried over 4.5 × 109 passengers on scheduled flights. However, due to the COVID-19 pandemic in 2020, the global number of passengers was reduced to 1.8 × 109, representing around a 60% reduction in air traffic. Germany was the largest contributor to greenhouse gas (GHG) from the EU, releasing 927 kt of emissions in 3 years. In the UK, Heathrow airport had the highest number of passengers in 2019 with over 80 million, and the study of monthly aircraft movement revealed that Heathrow Airport also had the highest number of EU and International flights, while Edinburgh had the domestic flights in 2018. These research findings could be beneficial for airlines, policymakers and governments targeting the reduction of aircraft emissions.

Nonvolatile particulate matter (nvPM) emissions from aircraft turbine engines deteriorate air quality and contribute to climate change. These emissions can be reduced using sustainable aviation fuels (SAFs). Here, we investigate the effects of a 32% SAF blend with fossil fuel on particle size distributions and nvPM emission indices of a widely used turbofan engine. The experiments were conducted in a test cell using a standardized sampling and measurement system. The geometric mean diameter (GMD) increased with thrust from ∼8 nm at idle to ∼40 nm at take-off, and the geometric standard deviation (GSD) was in the range of 1.74-2.01. The SAF blend reduced the GMD and GSD at each test point. The nvPM emission indices were reduced most markedly at idle by 70% in terms of nvPM mass and 60% in terms of nvPM number. The relative reduction of nvPM emissions decreased with the increasing thrust. The SAF blend reduced the nvPM emissions from the standardized landing and take-off cycle by 20% in terms of nvPM mass and 25% in terms of nvPM number. This work will help develop standardized models of fuel composition effects on nvPM emissions and evaluate the impacts of SAF on air quality and climate.

Aviation emissions contribute to the radiative forcing (RF) of climate. Of importance are emissions of carbon dioxide (CO2), nitrogen oxides (NO x ), aerosols and their precursors (soot and sulphate), and increased cloudiness in the form of persistent linear contrails and induced-cirrus cloudiness. The recent Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) quantified aviation\'s RF contribution for 2005 based upon 2000 operations data. Aviation has grown strongly over the past years, despite world-changing events in the early 2000s; the average annual passenger traffic growth rate was 5.3% yr-1 between 2000 and 2007, resulting in an increase of passenger traffic of 38%. Presented here are updated values of aviation RF for 2005 based upon new operations data that show an increase in traffic of 22.5%, fuel use of 8.4% and total aviation RF of 14% (excluding induced-cirrus enhancement) over the period 2000-2005. The lack of physical process models and adequate observational data for aviation-induced cirrus effects limit confidence in quantifying their RF contribution. Total aviation RF (excluding induced cirrus) in 2005 was ∼55 mW m-2 (23-87 mW m-2, 90% likelihood range), which was 3.5% (range 1.3-10%, 90% likelihood range) of total anthropogenic forcing. Including estimates for aviation-induced cirrus RF increases the total aviation RF in 2005-78 mW m-2 (38-139 mW m-2, 90% likelihood range), which represents 4.9% of total anthropogenic forcing (2-14%, 90% likelihood range). Future scenarios of aviation emissions for 2050 that are consistent with IPCC SRES A1 and B2 scenario assumptions have been presented that show an increase of fuel usage by factors of 2.7-3.9 over 2000. Simplified calculations of total aviation RF in 2050 indicate increases by factors of 3.0-4.0 over the 2000 value, representing 4-4.7% of total RF (excluding induced cirrus). An examination of a range of future technological options shows that substantive reductions in aviation fuel usage are possible only with the introduction of radical technologies. Incorporation of aviation into an emissions trading system offers the potential for overall (i.e., beyond the aviation sector) CO2 emissions reductions. Proposals exist for introduction of such a system at a European level, but no agreement has been reached at a global level.

In this study, we modeled concentrations of fine particulate matter (PM2.5) and ozone (O3) attributable to precursor emissions from individual airports in the United States, developing airport-specific health damage functions (deaths per 1000t of precursor emissions) and physically-interpretable regression models to explain variability in these functions. We applied the Community Multiscale Air Quality model using the Decoupled Direct Method to isolate PM2.5- or O3-related contributions from precursor pollutants emitted by 66 individual airports. We linked airport- and pollutant-specific concentrations with population data and literature-based concentration-response functions to create health damage functions. Deaths per 1000t of primary PM2.5 emissions ranged from 3 to 160 across airports, with variability explained by population patterns within 500km of the airport. Deaths per 1000t of precursors for secondary PM2.5 varied across airports from 0.1 to 2.7 for NOx, 0.06 to 2.9 for SO2, and 0.06 to 11 for VOCs, with variability explained by population patterns and ambient concentrations influencing particle formation. Deaths per 1000t of O3 precursors ranged from -0.004 to 1.0 for NOx and 0.03 to 1.5 for VOCs, with strong seasonality and influence of ambient concentrations. Our findings reinforce the importance of location- and source-specific health damage functions in design of health-maximizing emissions control policies.