Ship emission telemetering method based on multiband spectrum inversion

Abstract

The invention relates to the technical field of ship emission monitoring, in particular to a ship emission telemetering method based on multiband spectrum inversion, which comprises the following steps of: acquiring O4 differential inclined column concentration along the horizontal direction by utilizing shore-based multiband telemetering, calculating effective light path lengths of different bands, dividing the NO2 horizontal column concentration subjected to synchronous inversion by the effective light path lengths, and calculating the ship emission telemetering result. The average concentration on the horizontal path is obtained, and NO2 concentrations of different horizontal layers are separated based on multiband inversion; the method comprises the following steps: constructing a ship plume model in which a ship navigation trajectory is coupled with a Gaussian plume model on the basis of ship AIS (Automatic Identification System) data in combination with wind direction and wind speed information, matching plume trajectories of different ships with passed concentration layers, and quantifying the concentration of NO2 discharged by a single ship in combination with plume width information calculated by the ship plume model. According to the method, the emission condition of the in-flight ship is evaluated based on a telemetering means, monitoring can be carried out under the condition that normal navigation of the ship is not interfered, and powerful technical means and data support are provided for ship emission supervision.

Description

Technical Field

[0001] The present invention relates to the technical field of ship emission monitoring, and in particular to a ship emission remote sensing method based on multi-band spectral inversion. Background Art

[0002] my country will account for 7 of the top 10 ports in terms of global container throughput in 2023. In addition, my country has a large network of inland waterways. my country's marine and inland shipping industries are developing rapidly and are large in scale. The rapid development of the shipping industry is also accompanied by environmental pollution problems. Ship emissions are aerosol particles (such as PM2.5) in the atmosphere. 10 、PM 2.5 ) and gaseous pollutants (such as SO2, NO X 、VOCs、CO X ), which has a great impact on air quality, and will also cause harm to human health, climate change and other aspects. In order to reduce the impact of ship emissions on air quality and public health, many legal provisions have been established at the global and local levels, such as the International Maritime Organization's global sulfur limit order, which strictly restricts ship emissions. Ship emission monitoring can comprehensively grasp and deeply analyze the types and concentrations of pollutants emitted by ships, can determine whether ship emissions meet relevant standards, and also provide data support for further supervision and law enforcement. Existing ship emission technologies include online monitoring, sniffing monitoring and other technologies. Among them, online monitoring sensors need to be calibrated regularly and the accuracy is difficult to guarantee, while sniffing monitoring requires contact monitoring, which may have certain safety risks. In recent years, a series of methods based on optical telemetry have also been developed at home and abroad. The optical telemetry method has the advantage of long-distance monitoring, but the optical telemetry method has certain difficulties in quantitative monitoring of ship emissions. The present invention is based on a ship emission telemetry method based on multi-band spectral inversion to achieve quantification of ship emissions of NO2.

[0003] The patent application with publication number CN118425075A discloses a drone-mounted imaging spectral tracking detection method for ship pollutant gas emissions, including a drone, an imaging detection system, a computer, etc. The detection and inversion of ship emission plumes are achieved by hovering the drone near the ship or following the movement of the ship. This method adopts a tracking telemetry method based on a drone platform, which is significantly different from the method of the present invention that uses multi-band telemetry based on a shore-based platform to obtain ship position and concentration quantification.

[0004] The patent application with publication number CN113960042B discloses a remote sensing monitoring system for ship emissions, including an upper lock head, an upper lock head miter gate, a lower lock head, a lower lock head miter gate, a left wall of a ship lock, a right wall of a ship lock, a ship, and a ship monitoring device. By simply modifying the side wall of the ship lock at a checkpoint such as a ship lock that ships must pass through, the ship monitoring device is simplified to capture the background of the ship's exhaust gas. On this basis, a hull occlusion recognition algorithm and an exhaust gas blackness grading algorithm are designed and utilized to achieve efficient and accurate supervision capabilities for the phenomenon of black smoke from ships. This method only monitors the smoke plume of ships passing through the ship lock, and cannot identify the types of pollutants and pollutant concentration information in the propagating smoke plume.

[0005] Therefore, this application proposes a ship emission remote sensing method based on multi-band spectral inversion to solve the above problems. Summary of the invention

[0006] The purpose of the present invention is to provide a ship emission remote sensing method based on multi-band spectral inversion, which is used to solve the problem of emission monitoring of ships at sea, realize monitoring without interfering with the normal navigation of the ship, effectively evaluate the actual emission of the ship, provide a powerful technical means for ship emission monitoring, and provide necessary data support for further ship emission supervision.

[0007] The technical solution of the present invention is a ship emission remote sensing method based on multi-band spectral inversion, comprising the following steps:

[0008] S1. Based on the principle of differential absorption spectroscopy, the least squares method is used to fit the multi-band spectral data of shore-based observations to obtain the differential slant column concentration (DSCD) of NO2 and O4 on the horizontal path;

[0009] S2. Calculate the effective optical path length of the corresponding band, that is, the effective horizontal path length, by dividing the differential oblique column concentration of O4 by the number density of O4;

[0010] S3, using the calculated effective horizontal path length to calculate the average volume mixing ratio concentration of NO2 in the horizontal path;

[0011] S4, based on the O4 and NO2 horizontal column concentrations inverted by multi-band, obtain the effective horizontal path length information corresponding to different bands, and separate the NO2 concentrations in different horizontal layers;

[0012] S5. Based on the ship AIS data combined with wind direction and wind speed information, a ship plume model coupling the ship's forward trajectory with the Gaussian plume model is constructed;

[0013] S6. Obtain the plume shape based on the ship plume model and match it with the different horizontal concentration layers actually observed to obtain the NO2 concentration data of the horizontal layer corresponding to the single plume. Finally, determine the single ship emission concentration based on the plume width calculated by the ship plume model.

[0014] Optionally, in S1, the multi-band spectral data of shore-based observations are solar scattering spectral data covering multiple bands.

[0015] Optionally, in S1, based on the difference between the observed spectrum at a horizontal elevation angle of 0° and the reference spectrum at a vertical elevation angle of 90°, the light intensity loss caused by the absorption process of atmospheric trace gas molecules is obtained, and based on the linear least squares fitting of multi-component absorption in a specific band, the differential oblique column concentration results of NO2 and O4 in the corresponding band are inverted to obtain.

[0016] Optionally, in S2, O4 has the same band range as NO2 in the multi-band inversion, and the effective horizontal path length L is calculated by combining the O4 differential oblique column concentration with the following formula:

[0017]

[0018] in, is the number density of O2, and is solved based on the proportion of oxygen in the air, which is 20.9%:

[0019]

[0020] n air is the number density of air, which can be calculated based on the observed temperature (T air ) and atmospheric pressure (P air ) is calculated using the ideal gas state equation:

[0021]

[0022] Among them, N A is Avogadro's constant, and R is the molar gas constant.

[0023] Optionally, in S3, the differential oblique column concentration of NO2 is divided by the effective horizontal path length L to obtain the average concentration of NO2 along the horizontal light path, and further divided by the concentration of air to obtain the average mixing ratio concentration on the effective horizontal path length L, expressed as:

[0024]

[0025] Optionally, in S4, the concentrations and effective horizontal path lengths of different bands are obtained by detecting different bands, and the horizontal stratification of NO2 concentration is achieved by detecting two adjacent bands:

[0026]

[0027] Among them, L long and L short The effective horizontal path lengths corresponding to the long-wave and short-wave bands, DSCD long and DSCD short The NO2 differential oblique column concentrations corresponding to the long-wave band and the short-wave band, ΔDSCD is the difference in differential oblique column concentrations between two adjacent bands, and ΔL is the effective horizontal path difference between two adjacent bands.

[0028] Optionally, in S5, assuming that the ship is at a fixed position, two Gaussian curves can be used to describe the diffusion process of the ship plume in the vertical and horizontal directions, and the pollutant emission rate Q, the average wind speed U in the x direction, and the horizontal diffusion coefficient σ y and the vertical diffusion coefficient σ z Coupled with the concentration C at point (x, y, z), it is expressed as:

[0029]

[0030] The vertical coordinate z is the sum of the effective plume height H, the plume height and the initial plume height after correction. The wind speed and wind direction data are derived from the synchronous meteorological observation data or the wind field data simulated by the meteorological model.

[0031] Optionally, in S5, the Gaussian plume model needs to be further coupled with the ship's navigation track information, and the ship's latitude and longitude, speed, heading and other information involved can be obtained through the ship's AIS data.

[0032] Optionally, in S6, the concentration layer passed by a single smoke plume and the corresponding plume width b are determined according to the ship plume model, and the emission concentration of a single ship can be calculated by the following formula:

[0033]

[0034] Where ΔDSCD plume is the differential slant column concentration of the NO2 concentration layer where the plume is located, DSCD background is the background concentration value contained in the plume layer concentration, DSCD no-plume is the concentration layer that has not passed through the plume, L no-plume is the effective path length corresponding to the concentration layer that does not pass through the plume, ΔL plume is the thickness of the concentration layer where the smoke plume is located.

[0035] Compared with the prior art, the present invention has at least one of the following beneficial technical effects:

[0036] 1. Based on shore-based multi-band telemetry, obtain the effective horizontal path of multi-band inversion and NO2 differential oblique column concentration data. Further, based on the different path lengths of different bands, realize the horizontal stratification of NO2 concentration.

[0037] 2. A ship plume model that couples the ship's navigation trajectory and the Gaussian plume diffusion model was constructed to characterize the plume trajectory and quantify the plume width.

[0038] 3. The concentration layer was matched with the plume trajectory, and the plume width information at the corresponding position was calculated. Finally, the NO2 concentration information in a single plume was accurately calculated.

[0039] 4. Establish a ship emission remote sensing method based on shore-based multi-band spectral inversion to realize emission monitoring of ships at sea. It can carry out monitoring without interfering with the normal navigation of ships, provide powerful technical means for ship emission monitoring, and provide necessary data support for further supervision. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 The flowchart of a ship emission remote sensing method based on multi-band spectral inversion is shown in Figure 2. DETAILED DESCRIPTION

[0041] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and specific embodiments.

[0042] like Figure 1 As shown, the present invention proposes a ship emission remote sensing method based on multi-band spectral inversion, which specifically comprises the following steps:

[0043] Step 1: Based on the principle of differential absorption spectroscopy, the trace gas slant column concentration (SCD) is inverted from the measured spectrum, that is, the integrated concentration absorbed along the atmospheric light path. In order to measure the NO2 absorption in the ship plume emitted on the waterway, the instrument points to 0° (horizontal elevation angle). The zenith sky measurement spectrum collected synchronously is used as the reference spectrum, so only the absorption along the horizontal effective light path is inverted, while the absorption at higher positions in the atmosphere is offset, thus generating the differential slant column concentration (DSCD) on the horizontal path.

[0044] In the embodiment of the present invention, the above-mentioned trace gases are nitrogen dioxide (NO2) and a dimer of oxygen (O4).

[0045] In an embodiment of the present invention, the multi-band spectral data of shore-based observations are solar scattering spectra covering multiple bands, and illustratively, may be solar scattering spectra covering 340-370nm, 430-490nm, and 540-590nm.

[0046] During the implementation process, the light intensity loss caused by the absorption process of atmospheric trace gas molecules is obtained based on the difference between the observed spectrum in the horizontal direction (observed spectrum at 0° elevation angle) and the reference spectrum in the vertical direction (measured spectrum at 90° elevation angle). Based on the linear least squares fitting of multi-component absorption in a specific band, the differential oblique column concentration results of NO2 and O4 in the corresponding band are inverted to obtain.

[0047] Step 2: Divide the DSCD of O4 by the number density of O4 To calculate the effective optical path length of the corresponding band, that is, the effective horizontal path length.

[0048] The absorption band of O2 dimer O4 in the ultraviolet and visible light bands is consistent with that of NO2. Since the concentration of O4 near the surface is known, the effective horizontal path length can be calculated using the following formula:

[0049]

[0050] in, is the number density of O2, and is solved based on the proportion of oxygen in the air, which is 20.9%:

[0051]

[0052] n air is the number density of air, which can be calculated based on the observed temperature (T air ) and atmospheric pressure (P air ) is calculated using the ideal gas state equation:

[0053]

[0054] Among them, N A is Avogadro's constant, and R is the molar gas constant.

[0055] Step 3: Use the effective horizontal path to calculate the average volume mixing ratio concentration along the horizontal path.

[0056] When the horizontal optical path length is known, that is, the effective horizontal path length is L, the differential oblique column concentration of NO2 can be divided by L to obtain the average concentration (number density) of NO2 along the horizontal optical path. Further divided by the concentration of air, the average mixing ratio concentration on the effective horizontal path length L is obtained, expressed as:

[0057]

[0058] Step 4: Use the multi-band inverted O4 and NO2 horizontal column concentrations to obtain the effective horizontal path length information corresponding to different bands and separate the NO2 concentrations in different horizontal layers.

[0059] In the embodiment of the present invention, the concentration and effective horizontal path length of different bands can be obtained by detecting different bands, and the horizontal stratification of NO2 concentration can be achieved by detecting two adjacent bands:

[0060]

[0061] Among them, L long and L short The effective horizontal path lengths corresponding to the long-wave and short-wave bands, DSCD long and DSCD short The NO2 differential oblique column concentrations corresponding to the long-wave and short-wave bands, respectively. The wavelength dependence of Rayleigh scattering leads to the wavelength dependence of the optical path length after the last scattering point, so the detection of air masses at different locations can be achieved through spectral detection in different bands.

[0062] Step 5: Based on the ship AIS data (latitude and longitude, speed, heading and other information), the auxiliary observed wind direction and wind speed information is used to construct a ship plume model that couples the ship's forward trajectory with the Gaussian plume model.

[0063] Assuming that the ship is at a fixed position, two Gaussian curves can be used to describe the vertical and horizontal ship plume diffusion process, and the pollutant emission rate Q, average wind speed U (x direction), horizontal and vertical diffusion coefficients σ y and σ z Relate to the concentration C at point (x,y,z):

[0064]

[0065] The vertical coordinate z is the sum of the effective plume height H (the effective height of the plume centerline), the plume height, and the initial plume height. Diffusion coefficient σ y and σ z is the standard deviation of the Gaussian shaping function and is related to atmospheric stability.

[0066] Considering that the ship is a moving point source, the path of the plume is not only related to the wind direction, but also to the ship's navigation route. The ship moves in a certain direction and speed. Therefore, it is not enough to run a Gaussian plume model for each ship position, because each plume air mass is emitted at a different location, and it is necessary to further couple the ship's navigation track. The information involved, such as the ship's longitude and latitude, speed, and heading, can be obtained through the ship's AIS data. The ship plume model is constructed according to the stability category of the weather conditions during the observation period, and a plume width and height lookup table is created based on the distance from the emission point. For each plume air mass on the navigation track, the plume width b at the observation location is evaluated based on the distance the plume air mass has traveled since it was discharged. By introducing the normalization method, the specific values ​​of the emission rate Q and wind speed U are made irrelevant to the calculation.

[0067] For example, wind speed and direction data may be obtained through synchronously constructed meteorological observation instruments, or calculated through model-simulated wind field data.

[0068] Step 6: Based on the ship plume model, the plume shape can be obtained and matched with the different horizontal concentration layers actually observed to obtain the NO2 concentration data of the horizontal layer corresponding to a single plume. Finally, the plume width b is calculated based on the ship plume model to accurately calculate the emission concentration of a single ship.

[0069]

[0070] Where, ΔDSCD plume is the differential slant column concentration of the NO2 concentration layer where the plume is located, DSCD background is the background concentration value contained in the plume layer concentration, which can be obtained through the concentration layer DSCD that does not pass through the plume no-plume and its effective horizontal path length L no-plume And the thickness of the concentration layer where the plume is located ΔL plume And the plume width b is calculated.

[0071] In order to further verify the accuracy of the quantification results of the plume concentration, the ship plume can be sniffed and observed based on the sampling instrument carried by the UAV flying platform, and the consistency analysis of the two observation results can be performed. In the experiment, the above scheme of the embodiment of the present invention achieved a higher accuracy.

[0072] The ship emission remote sensing method based on multi-band spectral inversion provided by the embodiment of the present invention uses shore-based multi-band remote sensing to obtain the differential oblique column concentration results along the horizontal direction, and calculates the effective optical path length of different wavelengths based on the wavelength dependence of the optical path length after the last scattering point caused by the wavelength dependence of Rayleigh scattering. By using O4 to calculate the effective horizontal path length, the inverted NO2 horizontal column concentration is divided by the effective horizontal path to obtain the average concentration on the horizontal path. Based on the multi-band inverted O4 and NO2 horizontal column concentrations, the effective horizontal path lengths of different lengths are obtained, and the NO2 concentrations of different horizontal layers are separated. Further, based on the ship AIS data (latitude and longitude information, speed, heading, etc.), wind direction and wind speed information, a ship plume model combining the ship's forward trajectory with the Gaussian plume model is constructed to match the trajectories of different ships with the concentration layers passed. Finally, based on the plume width calculated by the ship plume model, the emission concentration of a single ship is accurately calculated. This method evaluates the emissions of ships at sea based on remote sensing. It can carry out monitoring without interfering with the normal navigation of ships, providing a powerful technical means for ship emission monitoring and the necessary data support for further supervision.

[0073] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above embodiments can be implemented by software, or by means of software plus necessary general hardware platforms. Based on such an understanding, the technical solutions of the above embodiments can be embodied in the form of software products, which can be stored in a non-volatile storage medium (which can be a USB flash drive, a mobile hard disk, etc.), including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0074] The above specific embodiments are only several optional embodiments of the present invention. Based on the technical solutions of the present invention and the relevant inspirations of the above embodiments, those skilled in the art can make various alternative improvements and combinations to the above specific embodiments.

Claims

1. A ship emission remote sensing method based on multi-band spectral inversion, characterized in that: The following steps are involved: S1. Based on the principle of differential absorption spectroscopy, the least squares method is used to fit the multi-band spectral data of shore-based observations to obtain the differential oblique column concentrations of NO2 and O4 on the horizontal path; S2. Calculate the effective optical path length of the corresponding band, that is, the effective horizontal path length, by dividing the differential oblique column concentration of O4 by the number density of O4; S3, using the calculated effective horizontal path length to calculate the average volume mixing ratio concentration of NO2 on the horizontal path; S4, based on the O4 and NO2 horizontal column concentrations inverted by multi-band, obtain the effective horizontal path length information corresponding to different bands, and separate the NO2 concentrations in different horizontal layers; S5. Based on the ship AIS data combined with wind direction and wind speed information, a ship plume model coupling the ship's navigation trajectory with the Gaussian plume model is constructed; S6. Obtain the plume shape based on the ship plume model and match it with the different horizontal concentration layers actually observed to obtain the NO2 concentration data of the horizontal layer where the single plume is located. Finally, determine the single ship emission concentration based on the plume width calculated by the ship plume model.

2. A ship emission remote sensing method based on multi-band spectral inversion according to claim 1, characterized in that: In S1, the multi-band spectral data observed on the shore is solar scattering spectral data covering multiple bands.

3. The ship emission remote sensing method based on multi-band spectral inversion according to claim 1 is characterized in that: In S1, based on the difference between the observed spectrum at a horizontal elevation angle of 0° and the reference spectrum at a vertical elevation angle of 90°, the light intensity loss caused by the absorption of atmospheric trace gas molecules is obtained, and based on the linear least squares fitting of multi-component absorption in a specific band, the differential oblique column concentration results of NO2 and O4 in the corresponding band are inverted to obtain.

4. A ship emission remote sensing method based on multi-band spectral inversion according to claim 3, characterized in that: In S2, O4 has the same band range as NO2 in the multi-band inversion. Combined with the near-surface concentration of O4, the effective horizontal path length L is calculated using the following formula: in, is the number density of O2, and is solved based on the proportion of oxygen in the air, which is 20.9%: n air is the number density of air, according to the observed temperature T air and atmospheric pressure P air Calculated using the ideal gas state equation: Among them, N A is Avogadro's constant, and R is the molar gas constant.

5. A ship emission remote sensing method based on multi-band spectral inversion according to claim 4, characterized in that: In S3, the differential oblique column concentration of NO2 is divided by the effective horizontal path length L to obtain the average concentration of NO2 along the effective horizontal path, which is further divided by the concentration of air to obtain the average mixing ratio concentration on the effective horizontal path length L, expressed as:

6. A ship emission remote sensing method based on multi-band spectral inversion according to claim 4, characterized in that: In S4, the concentration and effective horizontal path length of different bands are obtained by detecting different bands, and the horizontal stratification of NO2 concentration is achieved by detecting two adjacent bands: Among them, L long and L short The effective horizontal path lengths corresponding to the adjacent long-wave and short-wave bands, DSCD long and DSCD short The differential slant column concentrations of NO2 corresponding to the long-wave band and the short-wave band respectively, ΔDSCD is the difference in differential slant column concentrations between two adjacent bands, and ΔL is the effective horizontal path difference between two adjacent bands.

7. A ship emission remote sensing method based on multi-band spectral inversion according to claim 1 or 6, characterized in that: In S5, it is assumed that the ship is at a fixed position, and two Gaussian curves are used to describe the diffusion process of the ship plume in the vertical and horizontal directions. The pollutant emission rate Q, the average wind speed U in the x direction, and the horizontal diffusion coefficient σ y and the vertical diffusion coefficient σ z Coupled with the concentration C at point (x, y, z), it is expressed as: Among them, the vertical coordinate z is the sum of the effective plume height H, the plume height and the initial plume height corrected.

8. A ship emission remote sensing method based on multi-band spectral inversion according to claim 7, characterized in that: In S5, the Gaussian plume model is coupled with the ship's navigation track information, and the information of the ship's latitude and longitude, speed, and heading is obtained through the ship's AIS data.

9. The ship emission remote sensing method based on multi-band spectral inversion according to claim 7 is characterized in that: In S6, the concentration layer passed by a single smoke plume and the corresponding plume width b are determined according to the ship plume model, and the emission concentration of a single ship is calculated by the following formula: Where, ΔDSCD plume is the differential slant column concentration of the NO2 concentration layer where the plume is located, DSCD background is the background concentration value contained in the plume layer concentration, DSCD no-plume is the concentration layer that has not passed through the plume, L no-plume is the effective path length corresponding to the concentration layer that does not pass through the plume, ΔL plume is the thickness of the concentration layer where the smoke plume is located.

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