The Impact of COVID-19 on Civil Aviation Emissions: A High-Resolution Inventory Study in Eastern China’s Industrial Province

Abstract

Emissions from civil aviation not only degrade the environmental quality around airports but also have the significant effects on climate change. According to the flight schedules, aircraft/engine combination information and revised emission factors from the International Civil Aviation Organization (ICAO) Aircraft Engine Emission Databank (EEDB) based on meteorological data, the emissions of climate forcers (CFs: BC, CH₄, CO₂, H₂O, and N₂O), conventional air pollutants (CAPs: CO, HC, NO_X, OC, PM_2.5, and SO₂), and hazardous heavy metals (HMs: As, Cu, Ni, Se, Cr, Cd, Hg, Pb, and Zn) from flights of civil aviation of eight airports in Shandong in 2018 and 2020 are estimated in this study. Moreover, the study quantifies the impact of COVID-19 on civil aviation emissions (CFs, CAPs, and HMs) in Shandong, revealing reductions of 47.45%, 48.03%, and 47.45% in 2020 compared to 2018 due to flight cuts. By 2020, total emissions reach 9075.44 kt (CFs), 35.57 kt (CAPs), and 0.51 t (HMs), with top contributors being Qingdao Liuting International Airport (ZSQD) (39.60–40.37%), Shandong Airlines (26.56–28.92%), and B738 aircraft (42.98–46.70%). As byproducts of incomplete fuel combustion, the shares of CO (52.40%) and HC (47.76%) emissions during taxi/ground idle mode are significant. In contrast, emissions during cruise phase are the dominant contributor of other species with a share of 74.67–95.61% of the associated total emissions. The findings highlight the disproportionate role of specific airlines, aircraft, and operational phases in regional aviation pollution. By bridging gaps in localized emission inventories and flight-phase analyses, this research supports targeted mitigation strategies, such as fleet modernization and ground operation optimization, to improve air quality in Shandong. The study highlights how sudden shifts in demand, such as those caused by pandemics, can significantly alter emission profiles, providing insights for sustainable aviation planning.

1. Introduction

The civil aviation industry of China has achieved leapfrog development, driven by both sustained macroeconomic growth and the new urbanization strategy. As the world’s second-largest aviation market, followed by the U.S., China’s civil aviation passenger traffic volume in 2024 reached 1291.50 billion passenger-kilometers, an increase of 325.47 times over the 1980 baseline. The related growth rate is found to significantly exceed traditional modes of transport, such as highways (6.01 times) and railways (10.42 times) [1]. However, the adverse environmental effects accompanying industrial expansion are gradually becoming apparent. In particular, emissions from aviation fuel combustion (e.g., CO₂, CO, HC, NO_X, SO₂, and PM_2.5) pose a multidimensional threat to air quality, ecosystems, and public health [2,3]. Specially, the global average impact of aviation emissions on surface O₃ is estimated at 0.6 ppb. Of this, landing and takeoff (LTO) emissions contribute approximately 2% (10.7 ppt) of the aviation-induced surface O₃ perturbation. Aviation emissions also lead to an average ground-level PM₂.₅ concentration increase of 6.2 ng/m³ [4]. Nitrate (NO₃⁻) and sulfate (SO₄²⁻) dominate the composition of aviation-attributable PM_2.5, accounting for 42% and 38% of the total mass, respectively [4,5]. Notably, aircraft NO_X emissions can deplete radical species near airports, inhibiting the oxidation of organic aerosol precursors [6]. Consequently, black carbon (BC) and organic carbon (OC) collectively contribute only ~1% to aviation-related PM_2.5 on average [4,6]. Emissions from aviation can degrade the environmental quality around airports [7], potentially exacerbating conditions of haze. Primary PM_2.5 from aviation emissions accounts for 44–61% of total aviation-attributable PM_2.5 concentrations within 2 km of airports [4]. This percentage decreases with increasing distance from airports, declining to less than 6% at 20 km [7]. Globally, aviation emissions contribute an average PM_2.5 concentration of 44.2 ng/m³ within a 20 km radius of all airports [4]. Prolonged exposure to harmful air pollutants from aviation emissions poses a threat to human health [8], particularly affecting cardiac and pulmonary function. Global aviation emissions cause 74,300 premature deaths per year due to population exposure to aviation-attributable PM_2.5 and O₃ [4]. Of the total premature deaths, 87% and 13% are due to PM_2.5 and O₃, respectively, while 25% is attributable to the LTO portion of emissions [4,5,9]. Furthermore, the negative impact of civil aviation on climate change is escalating, encompassing not only direct CO₂ emissions from fuel combustion but also emissions of BC, NO_X, soot, and water vapor (H₂O) at high flight altitudes [10,11]. According to statistical data, the CO₂ emission contribution from civil aviation reaches 2.9% of global total emission [12]. Non-CO₂ emissions, particularly short-lived climatic pollutants from engine exhaust, also play a role in atmospheric disturbances, exerting both positive and negative effects on radiative forcing.

Given the above background, numerous researchers have been designing multiple methods to accurately estimate aviation emissions of species, such as the International Civil Aviation Organization (ICAO) method [13,14,15], the Aviation Environmental Design Tool (AEDT) method [14,15], and the Environmental Protection Agency (EPA) method [16,17]. The emission results from these methods often differ from one another. One reason is that the discrepancies of fuel flow rate estimation during climb/cruise/descent (CCD) mode among above methods [18,19]. As we know, one accurate and high-resolution emission inventory is critical for civil aviation industry to reduce emissions and realize low-carbon transition. Presently, according to key parameters (e.g., the number of landing and take-off (LTO) processes, fuel flow rates, times of different operating modes, and emission factors of species), the emissions per flight are estimated by domestic and foreign researchers [20,21]. While this method enables rapid estimation of aviation sector emissions, it is subject to significant uncertainties due to its failure to account for emission variations across different aircraft types [22]. Furthermore, it lacks phase-specific emission insights (e.g., take-off, climb-out, and cruise), limiting its utility for policymakers in designing targeted emission reduction strategies.

Focusing on Beijing–Tianjin–Hebei and its surrounding areas (BTHSA), the frequent occurrence of compound air pollution in autumn and winter has led to joint prevention and control for air pollution becoming a regular governance mechanism [23]. As the province with the largest economic scale (GDP: RMB 9856.58 billion) and population (100.8 million permanent residents) in BTHSA, the average proportion of days with the good air quality in 2024 is 72.2% [24]. Thus, there are still substantial refined control work to be implemented to improve local air quality. Therein, the establishment of emission inventory of civil aviation is one of effective measures [25,26]. Although national and regional aviation emission inventories have been established, comprehensive emission inventories for the aviation industry in key industrial provinces with severe air pollution, such as Shandong, have not been publicly released to date [27]. The LTO cycle (as defined by ICAO) and the high-altitude cruise phase represent two key sources of aviation emissions [28]. Therein, cruise phase is the dominant contributor of fuel consumption and species emissions during the whole flight compared with LTO cycle [2,15]. For instance, the fuel consumption, BC, and NO_X of flights account for 56–59%, 63–89%, and 51–79% in the cruise phase [18]. However, the emission characteristics of species from civil aviation during CCD phase are often overlooked in published studies [29]. Therefore, developing an integrated emission inventory for civil aviation in Shandong that includes various species (e.g., climate forcers (CFs), conventional air pollutants (CAPs), and hazardous heavy metals (HMs)) and considers both the LTO cycle and the cruise phase between airports is essential.

COVID-19-related travel restrictions lead to a 66% decrease in global revenue passenger-kilometers (RPKs) in 2020. Nevertheless, aviation activity is projected to rebound to pre-pandemic levels by 2023 and is expected to increase at an annual rate of 4% until 2040 [30]. In terms of emission reductions, global responses to COVID-19 bring about a decrease in the annual flight distance flown and the emissions of CO₂ and NO_X in 2020 (−43%, −48%, and −50% respectively compared to 2019), with significant regional variability. For instance, the reductions in flight distance and fuel consumption for civil aviation in the North Atlantic are −61% and −64%, while East China recorded growth in both metrics (21% and 9%, respectively) [19]. Despite the growing body of research on aviation emissions, significant gaps remain in understanding the provincial-scale impacts of civil aviation on air quality and climate change, particularly in industrial provinces such as Shandong. Current studies often fail to offer a comprehensive evaluation of emissions throughout both the LTO cycle and the CCD phase, leading to incomplete emission inventories. Additionally, the effects of disruptive events such as the COVID-19 pandemic on provincial aviation emissions have not been thoroughly quantified, nor have the contributions of specific aircraft types, airlines, and operating modes been systematically analyzed. These gaps hinder the development of targeted mitigation strategies for the aviation sector.

This study addresses these gaps by constructing a high-resolution emission inventory for civil aviation in Shandong Province, encompassing CFs (e.g., BC, CH₄, CO₂, H₂O, and N₂O), CAPs (e.g., CO, HC, NO_X, OC, PM_2.5, and SO₂), and HMs (e.g., As, Cu, Ni, Se, Cr, Cd, Hg, Pb, and Zn) for 2018 and 2020. Key research questions include the following: (1) How did COVID-19-induced flight reductions alter emission patterns? (2) What are the dominant contributors (e.g., airports, airlines, and aircraft types) to provincial aviation emissions? (3) How do emissions vary across different operating modes? The novelty of this work lies in its integration of refined information on airports’ flight schedules, civil aviation aircraft/engine comparison list, revised emission factors from ICAO database under cruise conditions to provide a spatially and temporally resolved inventory for China’s typical industrial province. By analyzing these dimensions, the study aims to offer actionable insights for policymakers to prioritize emission reduction measures, supporting Shandong’s low-carbon transition and aligning with China’s net-zero goals.

2. Methodology

2.1. Study Area and Base Years

Shandong Province is selected for this study due to its representative aviation profile, robust data availability, and policy relevance. Specifically, as the second most populous province in China (100.8 million) and one of China’s top three provincial economies [1], Shandong processes over 25 million passengers annually at major hubs such as Qingdao and Jinan, making it an ideal case for analyzing aviation emissions in high-growth regions. Moreover, the province’s diverse fleet mix, which includes narrow-body, wide-body, and regional aircraft, along with varying airport sizes, allows for a comprehensive assessment of emission patterns. While focusing on Shandong, our methodology—integrating flight schedules, aircraft information, and ICAO emission factors—is adaptable for other regions. This study provides a robust case and methodological framework for developing localized emission inventories and mitigation strategies in other provinces in China and beyond. In summary, Shandong serves as a strategic case study. The systematic methods and policy insights derived from it offer direct transferability to other provinces, thereby advancing air quality improvements and China’s aviation decarbonization.

There are eight civil aviation airports in Shandong Province (see Figure 1), including Jinan Yaoqiang International Airport (ZSJN), Jining Qufu Airport (ZSJG), Linyi Qiyang Airport (ZSLY), Weifang Nanyuan Airport (ZSWF), Rizhao Shanzihe Airport (ZSRZ), Yantai Penglai International Airport (ZSYT), Qingdao Liuting International Airport (ZSQD), and Weihai Dashuibo International Airport (ZSWH).

This study selects 2018 (pre-pandemic) and 2020 (peak pandemic) for the following three key reasons: Firstly, these years provide the most reliable and complete aviation activity data, essential for accurate emission inventories. Secondly, the drastic flight reductions in 2020 create a clear natural experiment to assess the impact of COVID-19 on emissions, while post-pandemic years feature volatile recovery patterns that will introduce uncertainty. Thirdly, the prolonged and non-linear recovery of the aviation sector since 2021 involves structural changes, such as the variation in fleet compositions, which will complicate direct comparisons. Focusing on the immediate pre-/mid-pandemic contrast best reveals the crisis’ pure effects before subsequent market adaptations.

2.2. Calculation Methods for Civil Aviation Emissions

2.2.1. Data Sources

Flight Schedule Database

The aviation schedules applied in this study are extracted from the airline schedules of eight airports situated in Shandong Province. The data for each flight meticulously includes the airline’s designation, flight identifier, aircraft model, flight date, and precise departure and arrival times and locales. The flights are presented in the form of city-to-city pairs to avoid double-counting and misclassification of data.

Aircraft/Engine Combinations

Airbus and Boeing aircraft are the primary types utilized at airports in Shandong Province. Especially, different models of aircrafts are produced by different manufacturers. However, an identical type of aircraft maybe equipped with different types of engines [15]. For instance, there are three models of engines that can be adopted for A330 aircraft, including Trent 772B-60, CF6-80E1A3, and PW4168A. Consequently, it is challenging to fully describe the engine details for each aircraft. To simplify calculations, emission factors for species from the representative type of engine are selected to estimate the emission inventory of species from civil aviation in general [31]. The matching relationship between aircraft and engine types is listed in Supplementary Information (SI) Table S1 [15,32]. Fuel consumption of civil aviation transportation industry in 2018 from Shandong province (aircraft-dependent) can be seen in SI Table S2.

Emission Factors of Species from Civil Aviation

The emission factors of CO, HC, and NO_X of LTO cycle for different types of engines at sea level ISA (International Standard Atmosphere) conditions are obtained from the ICAO Aircraft Engine Emission Databank (EEDB) [33]. The emissions of CO₂, H₂O, SO₂, HMs from aircraft are dependent on the fuel only and not on the technology [34]. Liu et al. and Zhang et al. indicate that the emissions of these species are directly proportional to fuel consumption [13,18]. The fuel consumption-specific emission factors of CO₂, SO₂, and H₂O based on fuel are 3149 g/kg, 0.84 g/kg, and 1230 g/kg, respectively [34,35]. For HMs, the emission factors of As, Cu, Ni, Se, Cr, Cd, Hg, Pb, Zn are cited from EEA air pollutant emission inventory guidebook [34], due to the limited measured data for China’s civil aviation. The specific values can be see SI Table S3 for more details.

The emissions of PM are aircraft and payload dependent. Presently, there is little information on PM emission from aircraft. Döpelheuer and Lecht [36] provide emission factor of PM for different phases of the flight for A300. The values are 0.05 g/kg, 0.01 g/kg, 0.01 g/kg, and 0.0067 g/kg for take-off, climb, descent, and cruise, respectively. In addition to HC, CO and NO_X, EEDB also contains emission factors for smoke at the different thrust settings. In this study, we apply the First Order Approximation version 3 (FOA3) to estimate the PM emissions from smoke [37]. EEA assume that all PM emissions from aircraft can be viewed as PM₁₀ [34]. From combustion science principles, it is reasonable to assume that for aircraft their PM emissions can be considered as PM_2.5. These are mainly because the PM_2.5 to PM₁₀ ratio for aircraft engines will be similar to, or higher than, that for internal combustion engines (about 94%).

Black carbon (BC) and organic carbon (OC) are important components of atmospheric particulate matter. The absorption and scattering properties of BC can warm the atmosphere at high altitudes and reduce surface temperatures, which makes the near-surface inversion more stable and provides conditions for the accumulation of pollutants [38]. BC fractions (f_BC) of PM emissions for take-off, climb, approach-landing, and taxi/ground idle are determined to 0.54, 0.48, 0.33, and 0.30 [34]. While OC, mainly from combustion processed, has an impact on the radiative properties of clouds and precipitation processes [39]. The emission factors of HC, CO, NO_X, PM_2.5 and BC from different types of engine for five operating modes are shown in SI Table S4. The emission factors of CH₄ and N₂O according to the percentage of the maximum rated engine thrust condition are taken from Santoni et al. [40]. The OC emission factors were obtained by multiplying the LTO different stage fixing factors by the HC different stage emission factors [18]. All data used in Section 2.2.1 are listed in SI Table S5.

2.2.2. Key Assumptions

In this study, the emissions of multiple species from civil aviation aircraft during the typical phases of flight, including LTO phase and CCD phase, are estimated. To simplify the calculation, certain key assumptions for emission estimation are defined as follows:

(1)

The operating modes of LTO for civil aviation in Shandong are in accordance with the standard LTO cycles, as follows: 0.7 min for the take-off mode with 100% engine thrust, 2.2 min for the climb-out mode with 85% engine thrust; 4 min for the approach-landing mode with 30% engine thrust; and 26 min for the taxi/ground idle mode with 7% engine thrust. The engine thrust is set as 70% of total thrust for cruise mode [34,41], of which time consumed is calculated with the distance and cruise speed of the flight.

(2)

The aircraft’s operating route between two cities is assumed to be a great circle, with the starting and finishing airports as the endpoints, and aircrafts fly in a straight line between two points.

(3)

All flights are adequately fueled, and all civil aviation flights fly as planned.

(4)

The actual cruising altitudes of major aircrafts are roughly 9–13 km, and species emitted at around 11 km account for a substantial part of total emissions [42,43]. For cruise emissions, the values for domestic flights are concentrated at 8000–10,000 m, while those for international flights are predominantly at 10,000–12,000 m [18]. Take NO_X emissions for example, approximately 60% of NO_X the global is emitted at cruise altitude of 10–12 km [15,44]. According to above discussion, the cruise altitude is set to 11 km in this study.

(5)

The emissions of aircraft during CCD mode are divided according to travel demand, with the starting and finishing airports each accounting for half of the emissions during CCD mode.

(6)

All flights operate within the standard atmosphere.

(7)

The load factor of all flights is assumed to be 70%. Aircrafts are loaded with passengers’ luggage, but no other cargo.

(8)

Wind, as well as fluctuations in temperature and humidity throughout the day, are overlooked.

(9)

At the same cruise altitude and speed, the reduction in fuel flow due to the aircraft’s weight lightening from fuel consumption is not considered.

(10)

The emissions are simply summed up, disregarding the chemical reactions, drift, and diffusion of pollutants in the atmosphere.

2.2.3. Calculation Methods

Emission Calculations for LTO Cycles

We used the fuel flow method to estimate the aircraft emissions for each aircraft type, flight phase (taxi-off, climb-out, approach-landing, and taxi/ground idle) and flight route. The fuel consumption is calculated by the fuel flow and time in different operating modes. This is mainly because the the ICAO EEDB provides fuel flow and emission factors for every flight phase except the cruise phase retrieved from aircraft tests and engine manufacturers for all types of engines [33], and this method has been widely used in previous studies [2,45]. Especially, the fuel flow data from EEDB need to be revised due to the neglect of installation effects [18]. The correction coefficients of the fuel flow for take-off, climb-out, approach-landing, and taxi/ground idle modes are 1.010, 1.013, 1.020, and 1.100, respectively. The emissions of aircraft at different stages of the LTO cycle can be calculated by the following equation [46,47,48].

$$E_{i,m}={\displaystyle \sum _j{\displaystyle \sum _{k}LT{O}_{j,k}}}\cdot N_k\cdot F_{j,m}\cdot E{F}_{i,j,k,m}\cdot T_m$$

(1)

where, E_i,m is the annual emission of species i (BC, CH₄, CO₂, H₂O, N₂O, CO, HC, NO_X, OC, PM_2.5, SO₂, As, Cu, Ni, Se, Cr, Cd, Hg, Pb, and Zn) for operating mode m (take-off, climb-out, approach-landing and taxi/ground idle), kg; LTO_j,k is the number of annual LTO cycles for aircraft type j equipped with engine type k; N_k is the number of engine type k per aircraft; F_j,m is the fuel flow rate for aircraft type j and operating mode m, kg/s; EF_i,j,k,m is the emission factor of specie i for aircraft type j equipped with engine type k at the operating mode m, g/kg; T_m is the time for operating mode m, s.

Previous studies roughly divide OC by using unified mass fractions, rather than employing the FOA3 method, due to limited activity data. Zhang et al. provide a basis for introducing the more specific FOA3 method by using the high-quality aircraft performance data [18].

$$E{F}_{OC,m}={\partial }_m\times E{F}_{HC,CCD}$$

(2)

where, EF_OC,m is the emission factor of OC in operating mode m, g/kg; $\partial$ is the mode-specific ratio, which is 115, 76, 56.3, and 6.2 for take-off, climb-out, approach-landing, and taxi/ground idle, respectively.

Emission Calculations for CCD Mode

The emissions of species from civil aircraft during the LTO cycles can be calculated directly based on the EEDB. However, it is necessary to revise fuel flow rates and emission factors under actual cruise conditions with emission data from EEDB. These are mainly because the reference emission factors of species from civil aircraft provided by EEDB are measured under the ISA (International Standard Atmosphere) condition at sea level. The substantial variations in engine performance can bring about enormous discrepancies on emission of jet engine under different ambient conditions (e.g., pressure, temperature, humidity). In this study, Boeing method 2 is applied to estimate the emissions of civil aviation during the CCD mode [15,18,49]. Specifically, the reference emission factors for each species from each aircraft type under sea level against thrust setting for different operating modes are plotted on the Cartesian coordinate system (see SI Figure S1 for more details). Subsequently, the emission factor of each species under 70% thrust setting on sea level according to the fitting equations are obtained. Then, we use the revised equations to calculate the fuel flow rate and the emission factors of species for each aircraft type under actual cruise conditions. The specific formulas of fuel flow rate are as follows.

$$F_f={\displaystyle \frac{F_{ff}\times {\delta }_{amb}}{{\theta }_{amb}^{3.8}\times \exp {\left(0.2Ma\right)}^2}}$$

(3)

$${\theta }_{amb}={\displaystyle \frac{T_{amb}+273.15}{288.15}}$$

(4)

$${\delta }_{amb}={\displaystyle \frac{P_{amb}}{101.325}}$$

(5)

where, F_f and F_ff are the fuel flow rate at flight altitude and sea level standard respectively, kg/s; ${\theta }_{amb}$ is the ratio of the ambient temperature to the sea level standard temperature (288.15 K); ${\delta }_{amb}$ is the ratio of the ambient atmospheric pressure to the sea level standard pressure (101.325 kPa); Ma is the cruise Mach number of aircrafts; T_amb and P_amb are the ambient temperature (°C) and ambient pressure (kPa), respectively.

The flowchart of civil aviation emissions are listed in SI Figure S2.

2.2.4. Revision of Emission Factors

As discussion above, the reference emission factors given in EEDB are the emission factors under ISA condition at the sea level standard. It is required to revise the emission factors with existing data to obtain emission factors under actual cruise conditions.

$$EF\left(CO\right)=REF\left(CO\right)\cdot {\displaystyle \frac{{\theta }_{amb}^{3.3}}{{\delta }_{amb}^{1.02}}}$$

(6)

$$EF\left(HC\right)=REF\left(HC\right)\cdot {\displaystyle \frac{{\theta }_{amb}^{3.3}}{{\delta }_{amb}^{1.02}}}$$

(7)

$$EF\left(N{O}_X\right)=REF\left(N{O}_X\right)\cdot \exp \left(H\right)\cdot {\left({\displaystyle \frac{{\theta }_{amb}^{3.3}}{{\delta }_{amb}^{3.02}}}\right)}^{-0.5}$$

(8)

where, EF(HC), EF(CO), and EF(NO_X) are emission factors of HC, CO, and NO_X at high altitude, respectively, g/kg; REF(HC), REF(CO), and REF(NO_X) are reference emission factors of HC, CO, and NO_X at the sea level standard, respectively, g/kg.

The parameter of H appearing in Equation (8) can be calculated by the following equations:

$$H=-19.0\times \left(\omega -0.0063\right)$$

(9)

$$\omega ={\displaystyle \frac{0.62198\cdot \left(\phi \right)\cdot P_v}{P_{amb}-\left(\phi \right)\cdot P_v}}$$

(10)

$$P_v=\left(0.014504\right)\times {10}^{\beta }$$

(11)

$$\begin{array}{l}\beta =7.90298\times \left(1-{\displaystyle \frac{373.16}{T_{amb}+273.16}}\right)+3.00571\\ +(5.02808)\times \lg \left({\displaystyle \frac{373.16}{T_{amb}+273.16}}\right)+(1.3816\times {10}^{-7})\times \left(1-{10}^{11.344\times (1-{\displaystyle \frac{T_{amb}+273.16}{273.16}})}\right)\\ +\left(8.1328\times {10}^{-3}\right)\times \left({10}^{3.49149\times \left(1-{\displaystyle \frac{373.16}{T_{amb}+273.16}}\right)}-1\right)\end{array}$$

(12)

where, $\omega$ and $\phi$ are the specific and relative humidity at the cruise altitude, respectively; $P_{amb}$ and $P_v$ are the ambient and saturated vapor pressures at the cruise altitude, respectively, kPa.

The formulae for species from civil aircraft during the CCD mode is as follows:

$$E_i={\displaystyle \sum _j{\displaystyle \sum _{k}CC{D}_{j,k}\cdot N_k\cdot F_{f_i}\cdot E{F}_{i,j,k}\cdot T}}$$

(13)

where, E_i is the annual emission of species i at the CCD mode, kg; CCD_j,k is the number of annual CCD mode for aircraft type j equipped with engine type k; N_k is the number of engine type k per aircraft; $F_{f_i}$ is the fuel flow rate for aircraft type j at the CCD mode, kg/s; EF_i,j,k is the emission factor of species i for aircraft type j equipped with engine type k at the CCD mode, g/kg; T is the time of CCD mode, s.

3. Results and Discussion

3.1. Temporal Variations in Civil Aviation Emissions in Shandong: Impacts of the COVID-19 Pandemic

3.1.1. Aviation Emissions Comparison: 2018 vs. 2020

The emissions of CFs (BC, CH₄, CO₂, H₂O, and N₂O), CAPs (CO, HC, NO_X, OC, PM_2.5, and SO₂) and HMs (As, Cu, Ni, Se, Cr, Cd, Hg, Pb, and Zn) from civil aviation of Shandong in 2018, 2020, and 2020 (expected) are illustrated in Figure 2.

As can be seen, the total emissions of CFs from civil aviation of Shandong in 2018 and 2020 are 16.27 Mt and 9.08 Mt, respectively. Therein, CO₂ emissions from civil aviation reach 11.70 Mt in 2018 and 6.53 Mt in 2020, representing the highest levels of climate-forcing emissions in those respective years. This finding is consistent with previous studies [50]. Notably, aircraft emissions account for approximately 2 percent of global anthropogenic CO₂ emissions.

For the CAPs, the annual emissions of CO, HC, NO_X, OC, PM_2.5, and SO₂ are 3.45 kt, 0.21 kt, 29.67 kt, 6.74 t, 0.49 kt, and 1.74 kt in 2020, which are 42.62%, 46.00%, 45.38%, 47.43%, 44.44%, and 44.23% lower than those in 2018. NO_X constitute the largest proportion of emissions among CAPs, representing 83.91% and 83.42% of the total emissions in 2018 and 2020, respectively. It should be noted that the aviation NO_X emissions bring about 0.3% increase in the global annual ozone load [51]. Emissions from civil aviation should be given extra attention because of their adverse impact on the global environment. Specifically, the majority of aviation-attributable PM_2.5 at surface level is secondary sulfate–ammonium–nitrate aerosol formed from neutralization of NH₄⁺ with either SO₄^2- or NO₃^-_, about 90% of which is emitted during non LTO phases of flight [52,53]. Previous studies have proven that the consistent increase in tropospheric O₃ from aviation NO_X cruise emissions is observed [54]. Aerosol precursors emitted at cruise altitudes influence surface air quality through the following two principal pathways: (1) vertical transport of pollutants and (2) enhanced oxidation of precursors at the surface, promoting aerosol formation. This process contributes to an intercontinental mechanism of PM_2.5 exposure [55]. Furthermore, O₃ produced at cruise altitudes exhibits a longer atmospheric lifetime than NO_X emitted near the surface, thereby exerting a more pronounced global-scale influence [56]. These findings demonstrate that, even when accounting for non-aviation anthropogenic emissions (e.g., automobile, agriculture, industry)—which, unlike aviation-related emissions, originate primarily at ground level—the inter-regional impacts remain substantial. Specifically, aviation emissions contribute to 20–50% of O₃-related premature mortalities and 2–5% of PM_2.5-attributable mortalities [52].

Furthermore, the annual emissions of HMs are calculated in this study. Specifically, the annual total emissions of HMs from civil aviation of Shandong in 2018 and 2020 are 0.92 t and 0.51 t, respectively. Therein, the annual emissions of As, Cu, Ni, Se, Cr, Cd, Hg, Pb, and Zn contribute about 0.02%, 8.12%, 12.36%, 49.44%, 3.53%, 3.53%, 0.04%, 19.42%, and 3.53% of the total HMs emission from civil aviation in 2020, for instance. The specific emissions of nine HMs from civil aviation of Shandong in 2018 and 2020 can be seen SI Table S6 for more details.

3.1.2. Aviation Emissions Comparison: 2020 vs. 2020 (Expected)

Since the outbreak of COVID-19 in Wuhan, China, on 23 January 2020, the Chinese government has escalated its epidemic control measures to the highest level and has implemented containment and mitigation activities, such as school closures, travel restrictions, and the suspension of industrial activities. In response to the evolving epidemic situation, the Shandong Provincial People’s Government successively activates the Level I (particularly significant), Level II (grave), and Level III (major) public health emergency responses, as stipulated by the Shandong Provincial Emergency Plan for Public Health Emergencies, on 25 January, 7 March, and 6 May 2020, respectively [57]. These measures have significantly impacted air passenger transport. For example, data released by the Civil Aviation Administration of China (CAAC) indicate that the number of take-offs and landings for civil aviation in Shandong in 2018 is estimated at about 254,772, which is 1.65 times that of 2020 [58].

To quantify the negative impacts of COVID-19 on emissions from civil aviation, this study estimates the emissions from Shandong province’s airports in 2020 under the counterfactual scenario that the COVID-19 pandemic had not occurred (abbreviated as 2020 expected). The analysis is based on airlines strictly adhering to their published flight schedules at all Shandong airports. Flight data, including aircraft type, departure/arrival times, and operational phases (take-off, climb-out, approach-landing, taxi/ground idle, CCD), are collected from official schedules. Emissions are calculated using the methodology described earlier, incorporating fuel flow rates and emission factors for species to each aircraft model. In this study, activity data (i.e., the number of take-offs and landings) and species emissions are compared with those in 2018 to ensure consistency and accuracy. Specifically, the number of take-offs and landings for civil aviation in Shandong in 2020 expected is 9.34% higher than that in 2018 [58]. Correspondingly, the emissions of CFs, CAPs, and HMs in 2020 expected are 6.13%, 5.71%, and 6.13% higher than those in 2018. Emissions exhibit a strong positive correspondence with the increase in take-off and landing number. This implies that aviation-related emissions would have continued to increase in the absence of the COVID-19 pandemic. The actual number of take-offs and landings of aviation aircrafts in Shandong is 123,923 fewer than the projected number in 2020, representing a reduction of 44.48%. Correspondingly, the projected emissions of CFs, CAPs, and HMs from civil aviation in Shandong in 2020 are 17.27 Mt, 68.44 kt, and 0.98 t, which are 90.29%, 92.40%, and 90.29% higher than those of actual emissions, respectively. The significant reduction in civil aviation activities, primarily due to lockdowns and social distancing measures, is the main reason for the discrepancy between projected and actual emissions.

3.1.3. Monthly Emission Characteristics for Civil Aviation

The monthly emissions of CFs, CAPs, and HMs from civil aviation of Shandong in 2018 and 2020 are shown in Figure 3. As can be seen, the COVID-19 pandemic significantly influences the monthly emissions of civil aviation pollutants in 2020, leading to distinct temporal variations. Generally, the monthly emissions of CFs (excluding CH₄), CAPs, and HMs from civil aviation exhibit a sharp decrease followed by a gradual increase. Emissions of above species in January remain at their highest level, plummeting to their lowest levels in February (for instance, the emissions of CO₂, NO_X, and HMs dropped from 710.00 kt, 3.23 kt, and 0.06 t in January to 295.98 kt, 1.35 kt, 0.02 t in February, respectively), and then gradually increase from March onward. The second highest emissions occur in October (for instance, the emissions of CO₂, NO_X, and HMs are estimated at 663.22 kt, 3.02 kt, and 0.05 t, respectively) due to the deregulation of air traffic and the increased travel demand during National Day holiday, yet the emission levels of civil aviation in 2020 are still significantly lower than those in 2018 or the projected values for 2020, indicating a limited recovery post-pandemic. Notably, the slow recovery of civil aviation emissions in Shandong suggests regional economic and policy factors may have delayed the rebound in air travel. Moreover, all pollutants’ emissions (excluding CH₄) demonstrate synchronized fluctuations, indicating that the pandemic uniformly affected emissions due to reduced aviation activity. This finding aligns with global observations of decreased transportation-related emissions during lockdowns [59].

Besides, the projected emissions of CFs, CAPs, and HMs of civil aviation in 2020 are also estimated in the absence of the pandemic. As can be seen from Figure 3, the monthly species emissions from civil aviation (excluding CH₄) will remain stable with minor seasonal fluctuations, peaking in May and October (take emissions in May for example, CO₂: 1.10 Mt, NO_X: 5.07 kt, HMs: 0.09 t) and dipping slightly in winter months (e.g., December, January, and February). Furthermore, similar monthly variation characteristics are observed between the projected emissions for 2020 and the actual emissions for 2018. This implies that, in the absence of external disruptions, emission growths in the civil aviation sector may follow a linear trajectory that is tied to economic expansion.

The pandemic brings about substantial deviations from projected emissions. For example, the monthly averaged emissions of CO₂, NO_X, and HMs is estimated at about 543.84 kt, 2.47 kt, and 0.04 t in 2020, which are 47.45%, 48.22%, and 47.45% less than projected emission of corresponding species, respectively. Maximum emission reductions in civil aviation are found in February. These are mainly because of the remarkable decrease in the number of take-offs and landings of civil aviation aircraft in February 2020 compared with the corresponding projected value (decrease from 21,067 to 7014). As a result, the actual emissions are only 30.18–37.49% of projected emissions (e.g., CO₂: 295.98 vs. 939.11 kt, NO_X: 1.35 vs. 4.33 kt, HMs: 0.02 vs. 0.07 t), illustrating the immediate effect of aviation shutdowns. By December, the emissions of species from civil aviation reach merely 61.37–76.22% of projected emission levels (e.g., CO₂: 645.46 vs. 1007.27 kt, NO_X: 2.93 vs. 4.65 kt, HMs: 0.05 vs. 0.08 t), indicating prolonged suppression due to pandemic. The pandemic-induced emission reductions serve as a proxy for assessing the potential of demand-side mitigation strategies. However, the transient nature of these gains underscores the urgency of transitioning to low-carbon aviation technologies to achieve permanent reductions without economic sacrifice—a critical direction for future research.

Unlike the emission characteristics of other species, the monthly emission values of CH₄ is negative, which indicates that the amount of atmospheric CH₄ consumed by civil aviation engines during flight is much higher than its emission. For instance, in February 2020, the difference between the consumption of atmospheric CH₄ and the emission of CH₄ from civil aviation aircraft in Shandong is estimated at 4.80 t. The oxidation reaction of CH₄ (CH₄ + 2O₂ → CO₂ + 2H₂O) will be promoted during the high temperature environment of combustion chamber (>1500 °C) (e.g., take-off and climb-out modes), resulting in net absorption effect [60]. However, during the low-speed taxi/ground idle mode, net CH₄ emissions are produced due to the low combustion efficiency of engine (the combustion temperature is less than 800 °C under this condition).

3.2. Emission Characteristics of Different Civil Airports

3.2.1. Emissions from Eight Airport in 2018 and 2020

The emissions of CFs, CAPs and HMs from the eight airports of Shandong in 2018 and 2020 show significant differences (see Figure 4). The airports ranked by civil aviation emissions from largest to smallest are the following: ZSQD, ZSJN, ZSYT, ZSWH, ZSLY, ZSJG, ZSRZ, and ZSWF. Specifically, the emissions of BC, CH₄, CO₂, H₂O, N₂O, CO, HC, NO_X, OC, PM_2.5, SO₂, and HMs from ZSQD in 2018 is estimated at 131.99 t, −73.13 t, 4.50 Mt, 1.76 Mt, 59.37 t, 2413.96 t, 161.19 t, 21,254.86 t, 5.13 t, 306.94 t, 1201.16 t, and 0.35 t, accounting for 34.78–41.88% of provincial corresponding emissions of civil aviation, respectively. Compared to the emissions in 2018, the emissions of CFs, CAPs, and HMs from ZSQD in 2020 decrease by 42.60%, 43.35%, and 42.60%, respectively, which are lower than the provincial average decrease rates (CFs: 44.23%; CAPs: 45.06%; HMs: 44.23%). This discrepancy may be attributed to the increased proportion of cargo flights, which leads to a higher emission factor per flight. The significant emission disparities between airports (e.g., ZSQD) highlight the need for targeted mitigation strategies. For instance, airports with higher emissions can prioritize the adoption of cleaner technologies, such as sustainable aviation fuels (SAFs) or electrification of ground support equipment.

As the second largest emission airport in Shandong, ZSJN contributes 25.87%, 24.59%, 24.47%, 24.47%, 24.19%, 22.19%, 21.70%, 24.71%, 22.97%, 25.87%, 24.47%, and 24.47% of the provincial emissions of corresponding species in 2018. Meanwhile, the emission intensity per aircraft (71.78 tons/aircraft) of ZSJN is 19.38% higher than this of ZSQD. The variations in emission intensity per aircraft suggest that optimizing flight schedules and ground operations could further reduce emissions. For instance, encouraging airlines to use more fuel-efficient aircraft on high-frequency routes can yield substantial benefits. However, the total emission of species from ZSJN in 2020 is 33.76% lower than this in 2018, which is significantly lower than the average emission reduction rate of species from ZSYT (61.49%). This regional heterogeneity may be attributed to the stable share of domestic mainline flights (>85%) at ZSJN, whereas the civil emissions from ZSYT is more influenced by the suspension of international flights.

3.2.2. Emissions from Different Airlines

Shandong Airlines, China Eastern Airlines, and China Southern Airlines are consistent ranked among the top three in terms of provincial civil aviation emission contributions in 2018 and 2020. For instance, the emissions of BC, CH₄, CO₂, H₂O, N₂O, CO, HC, NO_X, OC, PM_2.5, SO_2, and HMs from Shandong Airlines in 2018 are estimated at about 112.62 t, −54.03 t, 3.31 Mt, 1.29Mt, 42.88 t, 1596.00 t, 95.43 t, 14,376.43 t, 3.00 t, 262.10 t, 882.14 t, and 0.26 t, accounting for 23.33–29.70% of provincial total emissions of corresponding species, respectively. By 2020, the emissions of above species from Shandong Airlines decrease by 42.03–50.33%, compared with those in 2018. Compared with those in 2018, the contribution rate of Shandong Airlines to the corresponding species emissions in the province remained stable in 2020, ranging from 22.04% to 30.45%. However, its actual number of take-offs and landings sharply drops from 76,011 to 47,012, a decline of 38%. These imply that compared to Shandong Airlines, the COVID-19 pandemic has a greater impact on the business operations of other airlines. Furthermore, despite the significant contraction in industry scale caused by public health emergencies, the dual stability of airline market shares and emission structures confirm the deep coupling characteristics between regional air transport networks and regional economic linkages.

In order to further explore the emission characteristics of civil aviation, the emission contributions of primary airlines operated in the eight airports are discussed (see Figure 5). As can be seen, the emission contributions of different airlines varies remarkable in the eight airports. For instance, Shandong Airlines, Beibu Gulf Airlines, Shenzhen Airlines, Hainan Airlines, China Eastern Airlines, Shandong Airlines, Shandong Airlines, and China Eastern Airlines are the top CO₂-emitting airlines in ZSJN, ZSJG, ZSLY, ZSWF, ZSRZ, ZSYT, ZSQD, and ZSWH, contributing 42.41%, 34.52%, 21.32%, 83.94%, 21.48%, 24.10%, 31.22%, and 28.55% to the total emissions, respectively.

According to statistics from the ICAO, the COVID-19 pandemic has severely impacted the global air transport system. For instance, more than twenty airlines worldwide have completely suspended their international flight operations by the end of March 2020. The sharp decline in air transport volume during the first quarter of 2020 leads to a reduction in global GDP growth by 0.02–0.12%, highlighting the systemic influence of the civil aviation industry on the macro-economy [61]. In this context, China’s civil aviation transport system has also experienced significant disruptions. The proportion of international flights in 2020 plummets to 4.31%, down from 8.59% in 2018. Correspondingly, the number of international flight operations drastically decrease from 21,882 to 6660, marking a decline of 69.56%. The emission contributions of CFs, CAPs, and HMs for international flight in 2018 are estimated at 11.74%, 12.13%, and 11.74%, which are 2.53, 2.46, and 2.53 times of those in 2020 (see SI Figure S3 for more details).

3.2.3. Emissions from Different Aircraft Types

Variations in CFs, CAPs, and HMs emissions are significantly influenced by differences in aircraft types, particularly those equipped with distinct engine configurations. In Shandong, the aviation fleet is predominantly composed of Airbus and Boeing aircraft, with twin-engine models representing the majority. The emission contributions of CFs, CAPs, and HMs vary significantly across different aircraft types at the eight airports in Shandong (see Figure 6). However, these values of the emission contributions of CFs, CAPs, and HMs across various aircraft types at the eight airports in Shandong Province in 2018 and 2020 exhibit no significant changes. Therefore, this study explores the emission contributions of different aircraft types, with analysis limited to the year 2020. For example, B738, B738, A320, B738, A320, A320, B738, and A320 are the primary emission aircraft types of CFs at ZSJN, ZSJG, ZSLY, ZSWF, ZSRZ, ZSYT, ZSQD, and ZSWH, accounting for about 70.73%, 40.03%, 59.58%, 82.44%, 46.60%, 48.45%, 42.60%, and 40.65% of total CFs emissions from corresponding airports, respectively.

In term of the annual civil aviation emissions from Shandong, the largest annual emissions of BC (103.39 t), CO₂ (3044.74 kt), H₂O (1189.28 kt), N₂O (39.88 t), CO (1401.26 t), HC (78.50 t), NO_X (12.53 kt), OC (2.32 t), PM_2.5 (240.65 t), SO₂ (812.19 t), and HMs (0.24 t) are produced by the B738 aircrafts equipped with CFM56-7B26 engines in 2020. Furthermore, the largest net consumption of atmospheric CH₄ (49.52 t) from B738 aircraft is found. The related conclusion is consistent with Fan et al. [32]. These are mainly because the majority types of aircraft in Shandong are B738, which execute a large number of domestic and international flights (e.g., 71,107 flights in 2020, accounting for about 46.08% of the provincial total flights) and have the longest total flight duration. The annual civil aviation emissions of CFs, CAPs, and HMs from A320 aircrafts rank the second. This is because A320s owned by Chinese airlines are also quite numerous, and have a long total flight duration. As discussion above, the B738 and A320 aircraft types are the primary contributors to emissions in Shandong. Which imply that the environmental burden associated with older engine models (e.g., CFM56-7B26) should be paid more attention. We recommend the phased retirement of high-emission aircraft and incentivizing the adoption of newer, fuel-efficient models (e.g., Boeing 737 MAX or Airbus A320neo) to align with global decarbonization goals and improve air quality. More details of the annul emissions of BC, CH₄, CO₂, H₂O, N₂O, CO, HC, NO_X, OC, PM_2.5, SO₂, and HMs for different aircraft types from eight airports in Shandong are illustrated in SI Figures S4 and S5.

3.3. Emission Characteristics of Different Operating Modes in Flying Circulation

Emission characteristics of different operating modes in flying circulation are summarized in Figure 7. Emissions of multiple pollutants show great discrepancy among different operation modes (see Figure 7a). For BC, CH₄, CO₂, H₂O, N₂O, NO_X, OC, PM_2.5, SO₂, and HMs, the emissions from cruise phase are regarded to be the dominant contributor with a share of 95.61%, 84.57%, 86.79%, 86.79%, 74.67%, 88.03%, 81.70%, 95.45%, 86.78%, and 86.79% of the associated total emissions, respectively. It should be noted that PM_2.5 and BC emissions from flight processes are calculated based on engine types, engine number and time in operating mode, using emission values (kg/s/engine) as referenced from the EEA guidebook [34]. The ratios of PM_2.5 and BC emission factors from the LTO phase to the cruise phase are lower than those of other pollutants. Due to the limitation of available data, the emissions of CO₂, H₂O, SO₂, and HMs from different operating modes are calculated by using the same emission factors of corresponding discharges. As a result, the proportions of CO₂, H₂O, SO₂, and HMs emissions from different operating modes are consistent. Overall, the emissions for each atmospheric emission are closely related to combustion states and flight duration. Furthermore, the airports and surrounding areas are thought to be the most affected regions by CO and HC emissions from civil aviation industry due to the significant emission contributions of LTO phase [15]. The identical conclusion is obtained in this study. Concretely, as the byproducts of incomplete fuel combustion, the shares of CO and HC emissions from cruise process are 43.87% and 49.51% of the total emissions of CO and HC. For CH₄, the net emissions of CH₄ in the four modes of take-off, climb-out, approach-landing, and cruise are negative, which indicates that the absorption effect on ambient CH₄ for aviation engine is dominant during the modes with the high engine thrust [40]. Moreover, the net emission of CH₄ is found in the taxiing phase (7% of the maximum engine thrust).

For emission characteristics of CFs, CAPs, and HMs at different operating modes of the LTO cycle, the separate contribution to total emissions from take-off, climb-out, approach-landing, and taxi/ground idle are shown in Figure 7b. It is noteworthy that emissions contributions of those species are proportional to fuel consumption, emission factors and flight duration for different operation modes. The interplay of these elements leads to substantial disparities in the emission contributions from aviation throughout different operating modes. For instance, the contributions to N₂O (72.8%), CO (93.36%), and HC (94.59%) emission of LTO cycle from taxi/ground idle mode are much higher than those from other operating modes, which are quite different from other pollutants. The consistent results are also obtained by Winther et al. [62]. This is primarily because HC and CO are produced by the incomplete combustion of aviation fuel, and the taxi/ground idle process requires up to 26 min as well as 7% engine thrust. In contrast, the engine thrust settings for take-off, climb-out, and approach-landing are 100%, 85%, and 30%, respectively [32,33]. Furthermore, the trend of decreasing N₂O emissions with increasing thrust is observed at alternative aviation fuel experiment [40]. A potential explanation for this trend is that NO_X can convert to N₂O in these engine plumes, particularly in the presence of acid aerosols. Such a mechanism can account for the differences at lower thrusts, as these plumes have longer lifetimes compared to those sampled at higher powers where advection is facilitated by larger engine exit velocities.

The emission of NO_X from jet engine are primary produced through thermal oxidation reaction of nitrogen (N₂) and oxygen (O₂). Consequently, the formation of NO_X is closely related to factors such as combustion chamber temperature. As we know, there is a linear relationship between engine thrust and combustion chamber temperature, resulting in highly contribution to the total NO_X emissions of LTO cycle while climb-out process is setting 85% engine thrust and takes 2.2 min [33]. Specifically, four different operating modes (take-off, climb-out, approach-landing, and taxi/ground idle) contribute about 24.68%, 51.29%, 10.77%, and 13.26% of total NO_X emission of LTO cycle for the year 2018, respectively. The results are well consistent with the previous studies, showing that NO_X emissions of LTO cycle are mainly released from climb-out and take-off modes [15,35,62]. It can be concluded that NO_X emissions from civil aviation industry are associated with thrust setting of engine and flight duration.

To mitigate aviation emissions effectively, targeted strategies must address the dominant phases of flight. Our findings reveal that the cruise phase accounts for 74.67–95.61% of total emissions for key pollutants, highlighting the critical need for optimizing flight trajectories and altitudes to reduce fuel consumption and radiative forcing impacts. Simultaneously, the disproportionate contribution of taxi/ground idle operations to CO (52.40%) and HC (47.76%) emissions underscores the importance of adopting ground-level interventions, such as electrifying auxiliary power units (APUs) and minimizing idle times through operational adjustments. Furthermore, we emphasize the integration of real-world flight data (e.g., ADS-B telemetry) into emission inventories to improve spatial-temporal resolution, enabling dynamic policy formulation and evidence-based decision-making for sustainable aviation management.

3.4. Comparative Analysis with Other Studies

Until now, the comprehensive and refined research on CFs, CAPs, and HMs emissions from civil aviation in the typical industrial provinces of China (e.g., Shandong) is still quite limited. Therefore, only emissions of certain CFs, CAPs, and HMs from typical airports (e.g., ZSQD and ZSJN) are compared with those from previous studies [2,14,15,63] (see

Table 1. Civil aviation emissions from LTO process in this study compared with other studies and other sectors.

Airports/Emission Sources	BC/t	CO2/kt	CO/t	HC/t	NOX/t	SO2/t	OC/t	PM2.5/t	HMs/kg	Year	Data Sources
Beijing (ZBAA)	/	/	2597.6	351.1	7995.2	306.2	/	38.9	/	2018	[63]
Beijing (ZBAA)	/	690	2230	130	2970	160	/	10	/	2019	[2]
Beijing (ZBAA)	15.9	1312.8	4143.9	338.1	6416.7	416.8	10.6	33.1	119.1	2015	[13]
Qingdao (ZSQD)	2.7	211.1	749.3	55.1	775.1	67	1.8	5.6	19.2	2015	[13]
Qingdao (ZSQD)	4.6	416.9	1017.4	62.5	1931.6	111.2	0.7	10.7	32.9	2018	this study
Tianjin (ZBTJ)	/	/	706.5	91.7	1250.4	52.9	/	7.6	/	2018	[63]
Tianjin (ZBTJ)	2.2	170.7	605.8	44.6	626.6	54.2	1.5	4.6	15.5	2015	[13]
Zhengzhou (ZHCC)	/	/	577	56.3	969.4	268.3	/	26.9	/	2019	[14]
Zhengzhou (ZHCC)	2.7	209.8	744.4	54.8	770	66.6	1.8	5.6	19	2015	[13]
Jinan (ZSJN)	1.4	145.2	501.7	24.5	539.3	38.7	0.2	3.5	11.4	2018	this study
Activation LTO emission from Shandong	8.5	827.8	2346.6	130.0	3458.1	220.9	1.3	20.5	65.2	2018	this study
Industrial processes	/	/	10,749,500	1,599,700	109,800	25,500	/	547,500	/	2016	[64]
Anthropogenic emissions in Shandong	/	/	19,618,800	3,257,100	1,430,600	/	/	5,136,800	/	2016	[64]
Mobile sources	4236	176,971.0	536,121	111,845	452,702		974	17,059		2020	[65]
Fossil fuel combustion	/	/	1961,400	57,600	1,622,200	1,015,500	/	237,300	/	2017	[66]
Biomass burning	/	/	1,283,600	130,000	35,200	13,700	/	125,300	/	2017	[66]
Mobile sources	/	/	2,297,000	379,900	773,700	51,700	/	54,100	/	2017	[66]
Anthropogenic emissions in Shandong	/	/	9,250,700	2,254,700	2,488,600	1,387,800	/	3,193,000	/	2017	[66]

).

Overall, the results of the individual studies varied considerably due to differences in base year, data sources, estimation methodology, adopted emission factors, and study regions. For example, the LTO emissions of HC, CO, NO_X, SO₂, and PM_2.5 for ZBAA airport from An et al. [2] are 62.97%, 14.15%, 62.85%, 47.75%, and 74.29% lower than those from Han et al. [63], respectively. However, most of our study results are comparable with those of other studies on emissions from identical city. For ZSQD airport, emissions of CFs, CAPs, and HMs represent a remarkable upward trend except OC in this study, compared with those in Liu et al. [13]. The main important factors causing the discrepancy is the difference of number of LTO and calculation method of OC emission from LTO cycle. Liu et al. divide OC by unified mass fraction (f_oc = 0.32) instead of using the FOA3 method due to limited activity data [13], which is discussed in details by Zhang et al. [18]. If the same base years of emissions are assumed, our results (except for OC) would be closer to those of Liu et al. [13].

Additionally, although the number of take-offs and landings at ZHCC airport is higher than those at ZSQD airport, the emissions of CO, HC, and NO_X from ZSQD airport, as estimated by this study, are higher than those from ZHCC airport, as estimated by Han et al. [12]. These partly occur because the significant difference of composition of aircraft types among above airports. For instance, the aircraft usage shares of the B738 and A320 at ZHCC airport are 56.5% and 22.7%, respectively. However, the corresponding shares are 43.32% and 36.65% at ZSQD airport, respectively. The analysis results of CO, HC and NO_X emissions difference between ZSQD and ZHCC airports are also applicable to ZBTJ and ZHCC airports [63]. Finally, the airports with CO, HC, NO_X, SO₂, and PM_2.5 emissions from large to small are ZBAA, ZSQD, ZBTJ, and ZSJN, which are consistent with the order of number of aircraft taking-off and landing at these four airports [67]. Moreover, these are the same result as the study of Liu et al. [13].

The aviation emissions from LTO process in Shandong Province are also compared with other primary emission sources, including industrial processes, mobile sources, fossil fuel combustion, biomass burning, and provincial totals of anthropogenic sources. The results indicate that aviation emissions from LTO process account for a relatively small proportion of total emissions, yet they display unique characteristics for specific species emissions. For example, aviation CO₂ emission from LTO process (827.8 kt) are significantly lower than those from mobile sources (176,971.0 kt) [64]. However, aviation NO_X emissions from LTO process (3458.1 tons) are significant, representing ~0.2% of provincial total NO_X emissions (1,430,600 t in 2016 and 2,488,600 t in 2017) [65,66]. As discussed above, ground-level aviation NO_X emissions, such as those from take-off and approach-landing, contribute to local O₃ formation. However, NO_X emissions from the cruise phase, which account for approximately 88% of total aviation NO_X emissions, have a more pronounced global impact. Moreover, unlike emissions from non-aviation sources, NO_X released at high altitudes triggers O₃ production in the upper troposphere, where its atmospheric lifetime is significantly longer than the NO_X directly emitted near the ground. This enhancement of radiative forcing exacerbates climate warming. Additionally, cruise NO_X promotes the formation of secondary aerosols and contrails, further influencing cloud dynamics and Earth’s energy balance. Thus, aviation-attributable air quality degradation is a significant contributor to aviation’s environmental impacts and that mitigation of full-flight NO_X emissions should be considered alongside ongoing efforts to reduce the effects of aviation on the climate.

3.5. Pathways to Reducing Emissions and Enhancing Efficiency for Sustainable Aviation

The aviation industry plays a critical role in global connectivity and economic growth, yet its environmental impact, particularly in terms of greenhouse gas emissions and air pollutants, poses significant challenges. To address these issues, sustainable aviation strategies must integrate technological innovations, operational improvements, and policy frameworks. One promising approach is the adoption of continuous descent operations (CDOs), which can reduce fuel consumption by an average of 139 kg per flight compared to conventional step-down approaches. These are mainly because CDOs minimize level-off segments during descent, enabling engines to operate at idle or near-idle thrust, which not only cuts fuel use but also reduces emissions of CO₂, NO_X, CO, and PM [25].

Beyond operational optimizations, the transition to sustainable aviation fuels (SAFs) offers a viable near-term solution, with the potential to reduce lifecycle CO₂ emissions by up to 80% compared to conventional fuels. However, widespread SAF adoption requires advancements in feedstock efficiency, cost reduction, and supply chain scalability. Complementing these efforts, zero-emission technologies, such as hydrogen-powered and electric aircraft, are emerging as long-term solutions, though their deployment hinges on breakthroughs in energy storage and infrastructure development [26].

Policy measures are equally critical. The ICAO’s Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) and regional initiatives such as the EU’s emission trading system provide frameworks for incentivizing decarbonization. Furthermore, digital technologies, including artificial intelligence (AI)-driven air traffic management and predictive analytics, can further optimize fuel efficiency and reduce emissions [25,26].

Moving forward, a holistic approach—encompassing CDOs, SAFs, advanced propulsion, and robust policies—will be essential to achieving net-zero aviation by 2050. Collaborative efforts among governments, airlines, and researchers are imperative to ensure a sustainable and resilient aviation sector.

4. Conclusions

This study provides a comprehensive analysis of civil aviation emissions in Shandong Province for 2018 and 2020, highlighting the impact of COVID-19 and key emission characteristics. The main findings are summarized as follows: (1) The emissions of CFs, CAPs, and HMs decreased by 42.62–47.43% compared to those in 2018, a result of COVID-19 impact. Moreover, the pandemic cause the most significant reductions in February 2020, with emissions dropping to 30.18–37.49% of projected levels. (2) ZSQD is the largest emitter, contributing 34.78–41.88% of provincial emissions in 2018. (3) Shandong Airlines, China Eastern Airlines, and China Southern Airlines are the top three airlines with the highest emissions in Shandong, accounting for 26.56–28.92%, 16.17–17.36%, and 8.30–8.69% of the provincial emissions of CFs, CAPs, and HMs in 2020, respectively. (4) B738 and A320 are the primary emission aircraft types, contributing 42.98–46.70% and 35.38–36.93% of provincial civil emissions of CFs, CAPs, and HMs. (5) Taxi and ground idle modes significantly contribute to CO (52.40%) and HC (47.76%) emissions due to incomplete combustion at low engine thrust. The cruise phase, however, dominates emissions for other species, accounting for 74.67–95.61% of total emissions.

Considering the practicality of the data, the results of the Shandong’s civil aviation emission inventory we have established align with relevant research conclusions. However, the localization characteristics of activity levels and emission factors require further enhancement. Consequently, to build one more accurate emission inventory of civil aviation and improve assessments of the environmental impacts of aviation, future research should focus on the emission characteristics of civil aviation engines during the different operating modes and the application of actual trajectory records.