Aircraft take-off and landing cycle stage emission estimation method based on historical data modeling

Abstract

The invention discloses an aircraft take-off and landing cyclic emission estimation method based on historical data modeling. The method comprises the steps that S1, historical flight data, actual flight data and meteorological detection data are acquired; s2, counting the aircraft shift arrangement number per hour, and determining the local daily maximum mixing layer height of the airport; s3, constructing a function relationship between the taxiing time and the aircraft shift arrangement number, obtaining the taxiing time in each take-off and landing sortie, constructing a function relationship between the climbing / approaching time and the flight height, and obtaining the climbing / approaching time in each take-off and landing sortie; s4, estimating daily LTO cycle stage pollutant discharge of the historical flights; s5, function relation fitting of daily LTO rising and landing sorties and daily pollutant emission is carried out on various pollutants; and S6, substituting the daily LTO takeoff and landing sortie of the airport to be estimated into the fitted functional relationship between the daily LTO takeoff and landing sortie and the daily pollutant emission, and obtaining the daily LTO cycle stage pollutant emission. According to the method, rapid and accurate estimation of airport pollutant emission is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of air pollution prevention and control, and in particular to a method for estimating aircraft take-off and landing cycle emissions based on historical data modeling. Background Art

[0002] The aviation industry is rapidly developing. Aircraft engines burning aviation fuel emit greenhouse gases and pollutants such as hydrocarbons (HC), carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), carbon dioxide (CO2), and particulate matter (PM). These emissions have direct and indirect negative impacts on environmental quality and human health. Pollutants generated during the LTO cycle, in particular, come into close contact with residents near airports, garnering widespread attention. A refined inventory of pollutant emissions during the aircraft LTO cycle provides a crucial data foundation for studying the impact of aircraft near-ground activities on air quality and is crucial for incorporating environmental benefits into airport flight planning and management.

[0003] Currently, there are two main approaches for estimating pollutant emissions during the LTO cycle. One is the engine factor method, which combines the operating time of each stage with the Engine Emission Databank (EEDB) recommended by the International Civil Aviation Organization (ICAO) to account for variations in fuel flow rates and emission factors during the different LTO cycle phases. However, this method uses a single aircraft as the unit, requiring extensive and complex data processing. Another approach is the LTO cycle unit emission factor method. In 2014, my country issued the "Technical Guidelines for the Compilation of Emission Inventories for Non-Road Mobile Pollution Sources (Trial)," which provides guidance on calculating aircraft LTO cycle emissions. This method does not distinguish between aircraft types; total emissions can be calculated simply by combining the total number of LTO cycles and the unit emission factor. This method is simple and easy to implement and is often used to quickly estimate aircraft emissions during the LTO cycle. However, the fixed emission factors can differ significantly from the actual values, resulting in significant uncertainty in the resulting emissions inventory.

[0004] Therefore, it is urgent to establish a fast and accurate method for estimating the pollutant emission inventory of the aircraft LTO cycle stage to provide timely and accurate basic data for the formulation of relevant environmental protection policies. Summary of the Invention

[0005] In response to the shortcomings of the existing technology, the present invention provides an aircraft take-off and landing cycle emissions estimation method based on historical data modeling. The modeling is based on historical flight data and refined aircraft emission estimation results. The modeling results are applied to the rapid and accurate estimation of pollutant emissions in the aircraft LTO cycle stage, reducing the complexity of the estimation process and the uncertainty of the estimation results.

[0006] The present invention provides a method for estimating aircraft take-off and landing cycle emissions based on historical data modeling, the method comprising:

[0007] S1. Obtain historical flight data, actual flight data and weather detection data;

[0008] S2. Counting the number of aircraft scheduled per hour based on the actual LTO takeoffs and landings per hour at the airport in the historical flight data, and determining the local daily maximum mixing layer height at the airport based on the meteorological detection data;

[0009] S3. Based on the actual taxi time in the actual flight data and the aircraft schedule number, a functional relationship between the taxi time and the aircraft schedule number is constructed to obtain the taxi time for each take-off and landing operation. Based on the actual climb / approach time in the actual flight data and the daily maximum mixed layer altitude, a functional relationship between the climb / approach time and the flight altitude is constructed to obtain the climb / approach time for each take-off and landing operation.

[0010] S4. Estimate the daily LTO cycle pollutant emissions of historical flights based on the LTO operation time and engine emission database;

[0011] S5. Based on the historical flight data and the daily LTO cycle pollutant emissions of the historical flights, fitting the functional relationship between the daily LTO take-off and landing number and the daily pollutant emissions for each type of pollutant;

[0012] S6. Substitute the daily LTO take-offs and landings of the airport to be estimated into the fitted functional relationship between the daily LTO take-offs and landings and the daily pollutant emissions to obtain the daily LTO cycle stage pollutant emissions.

[0013] Preferably, step S1 includes:

[0014] Obtain historical flight data from flight data service companies, including LTO takeoff and landing numbers, aircraft types, takeoff and landing times, and takeoff and landing airports;

[0015] Obtain actual flight data through aircraft meteorological observation data, including actual aircraft altitude and actual flight time data of some historical flights;

[0016] Obtain meteorological detection data through the China Meteorological Administration, including historical vertical meteorological detection data at the airport.

[0017] Preferably, step S2 includes:

[0018] Based on the actual LTO takeoffs and landings per hour at the airport in the historical flight data, the number of aircraft schedules per hour is calculated; the number of aircraft schedules represents the number of aircraft taking off or landing at a certain airport in a certain hour, indicating the cumulative flow of aircraft taking off / landing per hour;

[0019] Based on the vertical meteorological detection data, the dry adiabatic method is used to determine the local daily maximum mixing layer height at the airport.

[0020] Preferably, step S3 includes:

[0021] S31. Constructing a functional relationship between the taxiing time and the number of scheduled aircraft based on the actual taxiing time and the number of scheduled aircraft in the actual flight time data of the portion of historical flights;

[0022] S32. Substituting the aircraft schedule number of the airport in all historical flights into the functional relationship between taxiing time and aircraft schedule number to obtain the taxiing time for each take-off and landing;

[0023] S33. Constructing a functional relationship between the climb / approach time and the flight altitude based on the actual climb / approach time and the daily maximum mixed layer altitude data in the actual flight time data of the portion of historical flights;

[0024] S34. Substitute the local daily maximum mixed layer altitude data of the airport in all historical flights into the functional relationship between the climb / approach time and the flight altitude to obtain the climb / approach time in each take-off and landing.

[0025] Preferably, in step S31, the functional relationship between the taxiing time and the number of aircraft scheduled is expressed by a linear equation, as follows:

[0026] T taxi,h,n =α×N sh,n +β(α≥0)

[0027] Among them, T taxi,h,n Ns represents the taxi-in / out mode time at airport n at time h, in seconds; h,n represents the number of aircraft scheduled at airport n at time h; α represents the slope of the linear equation, which means that every Ns h,n The increased taxi-in / out time, in seconds; β is the intercept of the linear equation, which represents the initial taxi-in / out time when there are no aircraft in the queue, in seconds.

[0028] Preferably, in step S32, the functional relationship between the climb / approach time and the flight altitude is expressed by a linear or quadratic function equation, as follows:

[0029] H n,d =aT n,d 2 +bT n,d +c(a≥0,T≥0)

[0030]

[0031] Among them, H n,drepresents the flight altitude of aircraft taking off and landing at airport n on day d, in meters; T n,d represents the duration of an aircraft taking off or landing at airport n on day d, crossing from the ground to a given altitude (climb) or crossing from a specific altitude to the ground (approach), in seconds; a, b, c are constants in the equation; T n,cd,limb T represents the time of climb mode at airport n on day d, in seconds; n,d,approach represents the time of the approach mode at airport n on day d, in seconds; H0 represents the fixed takeoff stage altitude of 152m; Indicates the time from the ground to 152m high; H m,n,d It represents the actual mixing layer height at the geographical location of airport n on day d, in meters; It represents the time it takes for an aircraft taking off or landing at airport n to travel from the ground to the top of the mixing layer or vice versa on day d.

[0032] Preferably, step S4 includes:

[0033] Based on the operating time of each LTO stage, the emission factors and fuel flow rate in the engine emissions, the daily LTO cycle pollutant emissions of historical flights are estimated using the following formula:

[0034]

[0035] Among them, E j,n represents the emission of pollutant j during the LTO cycle at airport n, in g; EI l,m,j FF represents the emission factor of pollutant j in mode m of the lth LTO, in g / kg; l,m,j represents the fuel flow rate of pollutant j in the m mode of the lth LTO, in kg / s; T l,m,n It indicates the operation time in mode M of the lth LTO at airport n, in seconds. The mode M of LTO includes takeoff, climb, approach and taxi.

[0036] Preferably, step S5 includes:

[0037] Based on the daily emissions of various pollutants and the daily LTO take-offs and landings in the historical flight data, as well as the daily aircraft LTO cycle pollutant emissions of the historical flights, the functional relationship between the LTO take-offs and landings and the pollutant emissions of each pollutant is fitted respectively, and the functional relationship between the daily LTO take-offs and landings and the daily pollutant emissions of each pollutant is obtained respectively.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] The present invention constructs a functional relationship between taxi time and aircraft schedule number based on actual flight data, thereby obtaining taxi time for each takeoff and landing. Based on the actual climb / approach time and daily maximum mixed layer altitude in actual flight data, a functional relationship between climb / approach time and flight altitude is constructed to obtain climb / approach time for each takeoff and landing, thereby obtaining the aircraft's LTO cycle operation time. Based on historical flight data and daily LTO cycle pollutant emissions from historical flights, a functional relationship between daily LTO takeoffs and landings and daily pollutant emissions is fitted for each type of pollutant. The daily LTO takeoffs and landings of the airport to be estimated are then substituted into the fitted functional relationship between daily LTO takeoffs and landings and daily pollutant emissions to obtain daily LTO cycle pollutant emissions.

[0040] The present invention constructs various functional relationships based on historical emission estimation data and aircraft takeoff and landing data, and ultimately estimates the daily LTO cycle stage pollutant emissions through various functional relationships, reducing the complexity of the estimation process and the inaccuracy of the estimation results, and achieving rapid and accurate estimation of airport pollutant emissions. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart of a method for estimating aircraft takeoff and landing cycle emissions based on historical data modeling provided by the present invention;

[0042] Figure 2 This is a schematic diagram of the fitting relationship between the daily LTO take-off and landing times and daily pollutant emissions at all airports in China from 2019 to 2022, provided by the present invention;

[0043] Figure 3 This is a comparison chart of the estimated atmospheric pollutant emissions during the LTO cycle stage of Beijing Capital International Airport, a typical Chinese airport in 2023, provided by the present invention. DETAILED DESCRIPTION

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0045] The present invention is described in further detail below with reference to the accompanying drawings:

[0046] Example 1:

[0047] Embodiment 1 of the present invention provides a method for estimating emissions from aircraft takeoff and landing cycles based on historical data modeling, comprising:

[0048] S1. Obtain historical flight data, actual flight data and weather detection data;

[0049] In the embodiment of the present invention, step S1 includes:

[0050] Obtain historical flight data from flight data service companies, including LTO takeoff and landing numbers, aircraft types, takeoff and landing times, and takeoff and landing airports;

[0051] Obtain actual flight data through aircraft meteorological observation data, including actual aircraft altitude and actual flight time data of some historical flights;

[0052] Obtain meteorological detection data through the China Meteorological Administration, including historical vertical meteorological detection data at the airport.

[0053] S2. Based on the actual LTO takeoffs and landings per hour at the airport in historical flight data, the number of aircraft scheduled per hour is calculated, and based on meteorological detection data, the local daily maximum mixing layer height at the airport is determined;

[0054] In the embodiment of the present invention, step S2 includes:

[0055] Based on the actual LTO takeoffs and landings per hour at the airport in the historical flight data, the number of aircraft schedules per hour is calculated; the number of aircraft schedules represents the number of aircraft taking off or landing at a certain airport in a certain hour, indicating the cumulative flow of aircraft taking off / landing per hour;

[0056] Based on vertical meteorological detection data, the dry adiabatic method is used to determine the local maximum daily mixing layer height at the airport.

[0057] S3. Based on the actual taxi time and aircraft schedule number in the actual flight data, a functional relationship between taxi time and aircraft schedule number is constructed to obtain the taxi time for each takeoff and landing. Based on the actual climb / approach time and daily maximum mixed layer altitude in the actual flight data, a functional relationship between climb / approach time and flight altitude is constructed to obtain the climb / approach time for each takeoff and landing.

[0058] In the embodiment of the present invention, step S3 includes:

[0059] S31. Constructing a functional relationship between the taxiing time and the number of scheduled aircraft based on the actual taxiing time and the number of scheduled aircraft in the actual flight time data of some historical flights;

[0060] S32. Substituting the aircraft schedule number of the airport in all historical flights into the functional relationship between taxi time and aircraft schedule number to obtain the taxi time for each take-off and landing;

[0061] S33. Based on the actual climb / approach time and daily maximum mixed layer altitude data in the actual flight time data of some historical flights, construct a functional relationship between the climb / approach time and the flight altitude;

[0062] S34. Substitute the local daily maximum mixed layer altitude data of the airport for all historical flights into the functional relationship between the climb / approach time and the flight altitude to obtain the climb / approach time for each take-off and landing.

[0063] In the embodiment of the present invention, in step S31, the functional relationship between the taxiing time and the number of aircraft scheduled is expressed by a linear equation, as follows:

[0064] T taxi,h,n =α×Ns h,n +β(α≥0)

[0065] Among them, T taxi,h,n Ns represents the taxi-in / out mode time at airport n at time h, in seconds; h,n represents the number of aircraft scheduled at airport n at time h; α represents the slope of the linear equation, which means that every Ns h,n The increased taxi-in / out time, in seconds; β is the intercept of the linear equation, which represents the initial taxi-in / out time when there are no aircraft in the queue, in seconds.

[0066] In the embodiment of the present invention, in step S32, the functional relationship between the climb / approach time and the flight altitude is expressed by a linear or quadratic function equation, as shown in the following formula:

[0067] H n,d =aT n,d 2 +bT n,d +c(a≥0,T≥0)

[0068]

[0069] Among them, H n,d represents the flight altitude of aircraft taking off and landing at airport n on day d, in meters; T n,d represents the duration of an aircraft taking off or landing at airport n on day d, crossing from the ground to a given altitude (climb) or crossing from a specific altitude to the ground (approach), in seconds; a, b, c are constants in the equation; T n,cd,limb T represents the time of climb mode at airport n on day d, in seconds; n,d,approach represents the time of the approach mode at airport n on day d, in seconds; H0 represents the fixed takeoff stage altitude of 152m; Indicates the time from the ground to 152m high; H m,n,dIt represents the actual mixing layer height at the geographical location of airport n on day d, in meters; It represents the time it takes for an aircraft taking off or landing at airport n to travel from the ground to the top of the mixing layer or vice versa on day d.

[0070] S4. Estimate the daily LTO cycle pollutant emissions of historical flights based on the LTO operation time and engine emission database;

[0071] In the embodiment of the present invention, step S4 includes:

[0072] Based on the operating time of each LTO stage, as well as the emission factors and fuel flow in engine emissions, the daily LTO cycle pollutant emissions of historical flights are estimated using the following formula:

[0073]

[0074] Among them, E j,n represents the emission of pollutant j during the LTO cycle at airport n, in g; EI l,m,j FF represents the emission factor of pollutant j in mode m of the lth LTO, in g / kg; l,m,j represents the fuel flow rate of pollutant j in the m mode of the lth LTO, in kg / s; T l,m,n It indicates the operation time in mode M of the lth LTO at airport n, in seconds. The mode M of LTO includes takeoff, climb, approach and taxi.

[0075] S5. Based on historical flight data and daily LTO cycle pollutant emissions of historical flights, the functional relationship between daily LTO take-offs and landings and daily pollutant emissions of various pollutants is fitted;

[0076] In the embodiment of the present invention, step S5 includes:

[0077] Based on the daily emissions of various pollutants and the daily LTO take-offs and landings in historical flight data, as well as the pollutant emissions in the daily aircraft LTO cycle stage of historical flights, the functional relationship between the LTO take-offs and landings and pollutant emissions of various pollutants was fitted respectively, and the functional relationship between the daily LTO take-offs and landings and daily pollutant emissions of various pollutants was obtained respectively.

[0078] S6. Substitute the daily LTO take-offs and landings of the airport to be estimated into the fitted functional relationship between the daily LTO take-offs and landings and the daily pollutant emissions to obtain the daily LTO cycle stage pollutant emissions.

[0079] Example 2:

[0080] like Figure 1As shown, Example 2 of the present invention provides an aircraft takeoff and landing cycle emissions estimation method based on historical data modeling. Taking Beijing Capital International Airport as the research object, and using five pollutants as target pollutants, a rapid and accurate estimation of aircraft LTO cycle pollutant emissions at Beijing Capital International Airport in 2023 is implemented, including the following steps:

[0081] S1-1. Obtain flight data for all airports in China from 2019 to 2022 through flight data service companies, including takeoff and landing numbers, aircraft types, takeoff and landing times, and takeoff and landing airports; obtain aircraft altitude and flight time data for various operational phases of some flights in 2019 through aircraft monitoring data; and obtain vertical meteorological detection data for 2019 through the China Meteorological Administration.

[0082] S1-2. Based on the take-off and landing data of all airports in China in 2019, the hourly aircraft schedules for each airport are counted; based on the 2019 vertical meteorological detection data, the dry adiabatic method is used to determine the local daily maximum mixing layer height at the airport.

[0083] S2-1. Based on the taxi time and aircraft schedule number in the actual flight data of some flights in 2019, construct a taxi time and aircraft schedule number function:

[0084] T taxi,h,n =α×Ns h,n +β(α≥0)

[0085] in,

[0086] T taxi,h,n represents the taxi-in / out time (s) of airport n at time h;

[0087] Ns h,n represents the number of aircraft scheduled at airport n at time h;

[0088] α represents the slope of the linear model, which indicates the increase in slide-in / slide-out time (s) per Ns;

[0089] β is the intercept of the linear model representing the initial taxi-in / out time (s) when there is no aircraft in the queue.

[0090] S2-2. Substitute the airport schedule numbers from 2019 to 2022 into the taxi time and aircraft schedule number function constructed in S2-1 to obtain the taxi time for each take-off and landing from 2019 to 2022.

[0091] S2-3. Construct a function of climb / approach time and flight altitude based on the actual climb / approach time and daily maximum mixed layer altitude of some flights in 2019:

[0092] H n,d =aTn,d 2 +bT n,d +c(a≥0,T≥0)

[0093]

[0094] in,

[0095] H n,d represents the flight altitude (m) of aircraft taking off and landing at airport n on day d;

[0096] T n,d represents the duration (s) of an aircraft taking off or landing at airport n on day d to traverse a given altitude from the ground (climb) or to traverse from a specific altitude to the ground (approach);

[0097] a, b, c represent constants in the equation;

[0098] T n,cd,limb represents the time (s) of the climb mode at airport n on day d;

[0099] T n,d,approach represents the time (s) of the approach mode at airport n on day d;

[0100] H0 represents 152m;

[0101] Indicates the time from the ground to an altitude of 152m;

[0102] H m,n,d represents the actual mixing layer height (m) at the geographical location of airport n on day d;

[0103] It represents the time it takes for an aircraft taking off or landing at airport n to travel from the ground to the top of the mixing layer or vice versa on day d.

[0104] S2-4. Substitute the local daily maximum mixed layer altitude at each airport from 2019 to 2022 into the climb / approach time and flight altitude function constructed in S2-3 to obtain the climb / approach time for each take-off and landing from 2019 to 2022.

[0105] S3. Based on the emission factor (EI), fuel flow rate (FF) in the EEDB, and the operating time (T) of different flight phases estimated in S2, a refined estimate of daily aircraft LTO cycle pollutant emissions at Chinese airports from 2019 to 2022 is made using the following formula:

[0106]

[0107] in,

[0108] E j,nThe LTO cycle pollutants j (including HC, CO, NO x , SO2, PM) daily emissions (g);

[0109] EI l,n,j represents the emission factor of pollutant j in mode m (takeoff, climb, approach and taxi) of the lth LTO (g / kg);

[0110] FF l,m,j represents the fuel flow rate of pollutant j in mode m of the lth LTO (kg / s);

[0111] T l,m,n represents the operating time (s) of airport n in mode m during the lth LTO.

[0112] S4, based on the daily emissions of various pollutants and daily LTO take-offs and landings of various airports in China from 2019 to 2022 calculated in S3, for HC, CO, NO x , SO2, and PM pollutants were fitted with the functional relationship between LTO take-off and landing flights and pollutant emissions, and HC, CO, NO x The functional relationship between the daily LTO take-off and landing times and daily pollutant emissions of SO2 and PM. Figure 2 shown.

[0113] S5. Based on the functional relationship between the daily LTO take-offs and landings and daily pollutant emissions of the airport obtained by the modeling in S4, obtain the flight data of Beijing Capital International Airport in 2023 and make a rapid estimate of the pollutant emissions in the LTO cycle stage of Beijing Capital International Airport in 2023. Figure 3 shown.

[0114] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for estimating aircraft take-off and landing cycle emissions based on historical data modeling, characterized in that: The method comprises: S1. Obtain historical flight data, actual flight data and weather detection data; S2. Counting the number of aircraft scheduled per hour based on the actual LTO takeoffs and landings per hour at the airport in the historical flight data, and determining the local daily maximum mixing layer height at the airport based on the meteorological detection data; S3. Based on the actual taxi time in the actual flight data and the aircraft schedule number, a functional relationship between the taxi time and the aircraft schedule number is constructed to obtain the taxi time for each take-off and landing operation. Based on the actual climb / approach time in the actual flight data and the daily maximum mixed layer altitude, a functional relationship between the climb / approach time and the flight altitude is constructed to obtain the climb / approach time for each take-off and landing operation. S4. Estimate the daily LTO cycle pollutant emissions of historical flights based on the LTO operation time and engine emission database; S5. Based on the historical flight data and the daily LTO cycle pollutant emissions of the historical flights, fitting the functional relationship between the daily LTO take-off and landing number and the daily pollutant emissions for each type of pollutant; S6. Substitute the daily LTO take-offs and landings of the airport to be estimated into the fitted functional relationship between the daily LTO take-offs and landings and the daily pollutant emissions to obtain the daily LTO cycle stage pollutant emissions.

2. The method according to claim 1, characterized in that Step S1 includes: Obtain historical flight data from flight data service companies, including LTO takeoff and landing numbers, aircraft types, takeoff and landing times, and takeoff and landing airports; Obtain actual flight data through aircraft meteorological observation data, including actual aircraft altitude and actual flight time data of some historical flights; Obtain meteorological detection data through the China Meteorological Administration, including historical vertical meteorological detection data at the airport.

3. The method according to claim 2, characterized in that Step S2 includes: Based on the actual LTO takeoffs and landings per hour at the airport in the historical flight data, the number of aircraft schedules per hour is calculated; the number of aircraft schedules represents the number of aircraft taking off or landing at a certain airport in a certain hour, indicating the cumulative flow of aircraft taking off / landing per hour; Based on the vertical meteorological detection data, the dry adiabatic method is used to determine the local daily maximum mixing layer height at the airport.

4. The method according to claim 2, characterized in that Step S3 includes: S31. Constructing a functional relationship between the taxiing time and the number of scheduled aircraft based on the actual taxiing time and the number of scheduled aircraft in the actual flight time data of the portion of historical flights; S32. Substituting the aircraft schedule number of the airport in all historical flights into the functional relationship between taxiing time and aircraft schedule number to obtain the taxiing time for each take-off and landing; S33. Constructing a functional relationship between the climb / approach time and the flight altitude based on the actual climb / approach time and the daily maximum mixed layer altitude data in the actual flight time data of the portion of historical flights; S34. Substitute the local daily maximum mixed layer altitude data of the airport in all historical flights into the functional relationship between the climb / approach time and the flight altitude to obtain the climb / approach time in each take-off and landing.

5. The method according to claim 4, characterized in that In step S31, the functional relationship between the taxiing time and the number of aircraft scheduled is expressed using a linear equation, as follows: T taxi,h,n =α×Ns h,n +β(α≥0) Among them, T taxi,h,n Ns represents the taxi-in / out mode time at airport n at time h, in seconds; h,n represents the number of aircraft scheduled at airport n at time h; α represents the slope of the linear equation, which means that every Ns h,n The increased taxi-in / out time, in seconds; β is the intercept of the linear equation, which represents the initial taxi-in / out time when there are no aircraft in the queue, in seconds.

6. The method according to claim 4, characterized in that In step S32, the functional relationship between the climb / approach time and the flight altitude is expressed using a linear or quadratic function equation, as shown in the following formula: H n,d =aT n,d 2 +bT n,d +c(a≥0,T≥0) Among them, H n,d represents the flight altitude of aircraft taking off and landing at airport n on day d, in meters; T n,d represents the duration of an aircraft taking off or landing at airport n on day d, crossing from the ground to a given altitude (climb) or crossing from a specific altitude to the ground (approach), in seconds; a, b, c are constants in the equation; T n,cd,limb T represents the time of climb mode at airport n on day d, in seconds; n,d,approach represents the time of the approach mode at airport n on day d, in seconds; H0 represents the fixed takeoff stage altitude of 152m; Indicates the time from the ground to 152m high; H m,n,d It represents the actual mixing layer height at the geographical location of airport n on day d, in meters; It represents the time it takes for an aircraft taking off or landing at airport n to travel from the ground to the top of the mixing layer or vice versa on day d.

7. The method according to claim 1, characterized in that Step S4 includes: Based on the operating time of each LTO stage, the emission factors and fuel flow rate in the engine emissions, the daily LTO cycle pollutant emissions of historical flights are estimated using the following formula: Among them, E j,n represents the emission of pollutant j during the LTO cycle at airport n, in g; EI l,m,j FF represents the emission factor of pollutant j in mode m of the lth LTO, in g / kg; l,m,j represents the fuel flow rate of pollutant j in the m mode of the lth LTO, in kg / s; T l,m,n It indicates the operation time in mode M of the lth LTO at airport n, in seconds. The mode M of LTO includes takeoff, climb, approach and taxi.

8. The method according to claim 1, characterized in that Step S5 includes: Based on the daily emissions of various pollutants and the daily LTO take-offs and landings in the historical flight data, as well as the daily aircraft LTO cycle pollutant emissions of the historical flights, the functional relationship between the LTO take-offs and landings and the pollutant emissions of each pollutant is fitted respectively, and the functional relationship between the daily LTO take-offs and landings and the daily pollutant emissions of each pollutant is obtained respectively.

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