A ship emission remote sensing method based on multi-band spectral inversion

Abstract

The present application relates to the technical field of ship emission monitoring, and particularly relates to a ship emission remote sensing method based on multi-band spectral inversion, which uses shore-based multi-band remote sensing to obtain O4 differential slant column density in the horizontal direction, calculates the effective optical path length of different bands, divides the synchronously inverted NO2 horizontal column density by the effective optical path length to obtain the average concentration on the horizontal path, separates the NO2 concentration of different horizontal layers based on multi-band inversion; constructs a ship plume model coupled with the ship sailing track and Gaussian plume model based on ship AIS data combined with wind direction and wind speed information, matches the plume track of different ships with the concentration layer passed, and quantifies the NO2 concentration of single ship emission combined with the plume width information calculated by the ship plume model. The present application evaluates the emission of ships at sea based on remote sensing means, can carry out monitoring without interfering with the normal sailing of ships, and provides strong technical means and data support for ship emission supervision.

Description

Technical Field

[0001] This invention relates to the field of ship emission monitoring technology, and in particular to a ship emission telemetry method based on multi-band spectral inversion. Background Technology

[0002] In 2023, my country accounted for 7 of the world's top 10 container ports. Furthermore, my country boasts a vast inland waterway network, and its maritime and inland waterway shipping industries have developed rapidly and on a massive scale. However, this rapid development has also brought environmental pollution problems. Ship emissions contribute to the release of aerosol particles (such as PM2.5) into the atmosphere. 10 PM 2.5 ) and gaseous pollutants (such as SO2, NO) X VOCs, CO X NO2 is a major source of pollution from ships, significantly impacting air quality and posing risks to human health and climate change. To reduce the impact of ship emissions on air quality and public health, numerous laws have been established at the global and local levels, such as the International Maritime Organization's global sulfur cap, strictly limiting ship emissions. Ship emission monitoring can comprehensively understand and deeply analyze the types and concentrations of pollutants emitted by ships, determining whether ship emissions comply with relevant standards and providing data support for further supervision and enforcement. Existing ship emission technologies include online monitoring and sniffing monitoring. Online monitoring sensors require regular calibration, making accuracy difficult to guarantee, while sniffing monitoring requires contact monitoring, potentially posing safety risks. In recent years, a series of optical remote sensing methods have been developed both domestically and internationally. Optical remote sensing methods have the advantage of long-distance monitoring; however, they face certain difficulties in quantitative monitoring of ship emissions. This invention utilizes a multi-band spectral inversion-based ship emission remote sensing method to quantify NO2 emissions from ships.

[0003] Patent application CN118425075A discloses an unmanned aerial vehicle (UAV)-based imaging spectral tracking and detection method for ship pollutant emissions, including a UAV, an imaging detection system, and a computer. This method detects and retrieves ship emission plumes by hovering near the ship or following its movement. This method employs a UAV-based tracking telemetry approach, which differs significantly from the shore-based multi-band telemetry method of this invention, which uses a shore-based platform to acquire ship location and concentration quantification.

[0004] Patent application 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 side wall of the lock, a right side wall of the lock, a ship, and a ship monitoring device. By making simple modifications to the lock sidewalls at a crucial point for ships to pass through, the system simplifies the process of the ship monitoring device capturing the background of ship exhaust. Based on this, a hull obstruction recognition algorithm and an exhaust opacity classification algorithm are designed and utilized to achieve efficient and accurate monitoring of black smoke emitted by ships. However, this method only monitors plumes emitted by ships passing through the lock and cannot identify the types and concentrations of pollutants in the propagating plumes.

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

[0006] The purpose of this invention is to provide a ship emission telemetry method based on multi-band spectral inversion to solve the problem of monitoring emissions from ships at sea, enabling monitoring without interfering with normal ship navigation, effectively assessing the actual emissions of ships, providing a powerful technical means for ship emission monitoring, and providing necessary data support for further ship emission regulation.

[0007] The technical solution of this invention: A method for remote sensing of ship emissions 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 and perform spectral analysis to obtain the differential oblique column concentration (DSCD) of NO2 and O4 on the horizontal path.

[0009] S2. Calculate the effective optical path length, i.e. the effective horizontal path length, by dividing the differential oblique column concentration of O4 by the number density of O4.

[0010] S3. Calculate the average volumetric mixing ratio concentration of NO2 in the horizontal path using the calculated effective horizontal path length;

[0011] S4. Based on the O4 and NO2 horizontal column concentrations retrieved from multiple bands, obtain the effective horizontal path length information corresponding to different bands, and separate the NO2 concentration of different horizontal layers.

[0012] S5. Based on ship AIS data and wind direction and speed information, construct a ship plume model that couples the ship's forward trajectory with the Gaussian plume model.

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

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

[0015] Optionally, in S1, the light intensity loss caused by the absorption process of atmospheric trace gas molecules is obtained 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°. 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 obtained by inversion.

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

[0017]

[0018] in, Given the number density of O2, calculate based on the fact that oxygen accounts for 20.9% of the air:

[0019]

[0020] n air The number density of air can be determined based on the observed temperature (T). air ) and atmospheric pressure (P) air The following calculations were performed using the ideal gas law:

[0021]

[0022] Where, N A Let R be Avogadro's constant, and R be the molar gas constant.

[0023] Optionally, in step 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 optical path. This average concentration is then further divided by the concentration of air to obtain the average mixing ratio concentration along the effective horizontal path length L, expressed as:

[0024]

[0025] Optionally, in step S4, the concentration and effective horizontal path length of different bands are obtained through detection in different bands, and horizontal stratification of NO2 concentration is achieved through detection in two adjacent bands.

[0026]

[0027] Among them, L long and L short Corresponding to the effective horizontal path lengths of the long-wave band and short-wave band respectively, DSCD long and DSCD short The values ​​represent the NO2 differential column concentrations for the long-wave and short-wave bands, respectively. ΔDSCD represents the difference in differential column concentrations between two adjacent bands, and ΔL represents the difference in effective horizontal path between two adjacent bands.

[0028] Optionally, in S5, assuming the ship is at a fixed position, two Gaussian curves can be used to describe the vertical and horizontal ship plume diffusion process, incorporating pollutant emission rate Q, average wind speed U in the x-direction, and horizontal diffusion coefficient σ. y and 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 represents the effective plume height H, and the sum of the plume height and the initial plume height has been corrected. Wind speed and direction data are derived from concurrent meteorological observations or wind field data simulated by meteorological models.

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

[0032] Optionally, in step S6, the concentration layer through which a single plume passes and the corresponding plume width b are determined based on the ship plume model. The emission concentration of a single ship can be calculated using the following formula:

[0033]

[0034] Wherein, ΔDSCD plume The differential oblique column concentration of the NO2 concentration layer containing the plume, DSCD background The background concentration value included in the plume concentration, DSCD no-plume For the concentration layer that has not passed through the plume, L no-plume ΔL represents the effective path length corresponding to the concentration layer that does not pass through the plume. plume The thickness of the concentration layer where the plume is located.

[0035] Compared with the prior art, this application includes at least one of the following beneficial technical effects:

[0036] 1. Based on shore-based multi-band telemetry, obtain effective horizontal paths retrieved from multiple bands, and NO2 differential oblique column concentration data. Further, based on different path lengths in different bands, achieve horizontal stratification of NO2 concentration.

[0037] 2. A ship plume model was constructed that couples the ship's navigation trajectory with the Gaussian plume diffusion model, enabling the representation of the plume trajectory and the quantification of the plume width.

[0038] 3. The concentration layer and plume trajectory were matched, 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 telemetry method based on shore-based multi-band spectral inversion to enable emission monitoring of ships navigating in waterways. This method can conduct monitoring without interfering with normal ship navigation, providing a powerful technical means for ship emission monitoring and necessary data support for further supervision. Attached Figure Description

[0040] Figure 1 This is a flowchart of a ship emission telemetry method based on multi-band spectral inversion. Detailed Implementation

[0041] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

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

[0043] Step 1: Based on the principle of differential absorption spectroscopy, the trace gas column concentration (SCD) is obtained by inversion from the measured spectrum, which is the integrated concentration absorbed along the atmospheric optical path. To measure NO2 absorption in ship plumes emitted over waterways, the instrument is pointed to 0° (horizontal elevation angle). Using the synchronously acquired zenith sky measurement spectrum as the reference spectrum, only the absorption along the effective horizontal optical path is inverted, while absorption at higher positions in the atmosphere is canceled out, thus generating the differential column concentration (DSCD) along the horizontal path.

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

[0045] In this embodiment of the invention, the multi-band spectral data of shore-based observation is a solar scattering spectrum covering multiple bands. For example, it can be a solar scattering spectrum covering 340-370nm, 430-490nm, and 540-590nm.

[0046] In the implementation process, the light intensity loss caused by the absorption process of atmospheric trace gas molecules is obtained by the difference between the horizontal observation spectrum (0° elevation angle observation spectrum) and the vertical reference spectrum (90° elevation angle measurement spectrum). 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 obtained by inversion.

[0047] Step 2: Divide the O4-based DSCD by the number density of O4. To calculate the effective optical path length, i.e. the effective horizontal path length, for the corresponding band.

[0048] The O2 dimer O4 absorbs light in the same wavelength range in the ultraviolet and visible light bands as NO2. Since the near-surface concentration of O4 is known, the effective horizontal path length can be calculated using the following formula:

[0049]

[0050] in, Given the number density of O2, calculate based on the fact that oxygen accounts for 20.9% of the air:

[0051]

[0052] n air The number density of air can be determined based on the observed temperature (T). air ) and atmospheric pressure (P) air The following calculations were performed using the ideal gas law:

[0053]

[0054] Where, N A Let R be Avogadro's constant, and R be the molar gas constant.

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

[0056] Given the horizontal optical path length, i.e., the effective horizontal path length 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 dividing by the concentration of air yields the average mixing ratio concentration along the effective horizontal path length L, expressed as:

[0057]

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

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

[0060]

[0061] Among them, L long and L short Corresponding to the effective horizontal path lengths of the long-wave band and short-wave band respectively, DSCD long and DSCD short These correspond to the NO2 differential oblique column concentrations in the long-wavelength and short-wavelength bands, respectively. Based on the wavelength dependence of Rayleigh scattering, the optical path length after the last scattering point becomes wavelength dependent; therefore, different locations of air masses can be detected through spectral probing in different bands.

[0062] Step 5: Based on ship AIS data (latitude, longitude, speed, heading, etc.), construct a ship plume model that couples the ship's trajectory with the Gaussian plume model using wind direction and speed information obtained from auxiliary observations.

[0063] Assuming the ship is in a fixed position, the vertical and horizontal ship plume diffusion process can be described by two Gaussian curves, which incorporate the pollutant emission rate Q, average wind speed U (x-direction), and horizontal and vertical diffusion coefficients σ. y and σ z Relating to the concentration C at point (x,y,z):

[0064]

[0065] The vertical coordinate z represents the effective plume height H (effective height of the plume centerline), which has been corrected for the sum of the plume height and the initial plume height. The diffusion coefficient σ... y and σ z It is the standard deviation of the Gaussian shaping function, which is related to atmospheric stability.

[0066] Considering ships as moving point sources, the plume path depends not only on wind direction but also on the ship's navigation route. Ships move in a certain direction and at a certain speed. Therefore, running a Gaussian plume model for every ship location is insufficient, as each plume is emitted from a different location. It is necessary to further couple the model with the ship's navigation trajectory, using information such as latitude, longitude, speed, and heading, which can be obtained from the ship's AIS data. A ship plume model is constructed based on the stability category of weather conditions during the observation period, and a lookup table for plume width and height is created based on the distance from the emission point. For each plume on the navigation trajectory, the plume width *b* at the observation location is evaluated based on the distance the plume has traveled since its emission. By introducing a normalization method, the specific values ​​of the emission rate *Q* and wind speed *U* are made independent of the calculation.

[0067] For example, wind speed and direction data can be obtained through synchronously constructed meteorological observation instruments or calculated from wind field data simulated by models.

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

[0069]

[0070] Wherein, ΔDSCD plume The differential oblique column concentration of the NO2 concentration layer containing the plume, DSCD background The background concentration value contained in the plume layer can be obtained by using DSCD of the concentration layer that has not passed through the plume. no-plume and its effective horizontal path length L no-plume and the thickness ΔL of the concentration layer where the plume is located plume The width of the plume, b, is calculated from this.

[0071] To further verify the accuracy of the plume concentration quantification results, a sampling instrument mounted on an unmanned aerial vehicle (UAV) flight platform can be used to sniff out and observe the ship plume, and a consistency analysis can be performed on the two observation results. In the experiment, the above-mentioned scheme in the embodiment of the present invention achieved high accuracy.

[0072] The ship emission telemetry method based on multi-band spectral inversion provided in this invention utilizes shore-based multi-band telemetry to obtain differential oblique column concentration results along the horizontal direction. Based on the wavelength dependence of Rayleigh scattering, which leads to the wavelength dependence of the optical path length after the last scattering point, the effective optical path length for different wavelengths is calculated. The effective horizontal path length is calculated using O4, and the inverted NO2 horizontal column concentration is divided by the effective horizontal path to obtain the average concentration along 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. Furthermore, based on ship AIS data (latitude and longitude information, speed, heading, etc.), wind direction, and wind speed information, a ship plume model combining the ship's trajectory and a Gaussian plume model is constructed to match the trajectories of different ships with the concentration layers they pass through. Finally, based on the plume width calculated by the ship plume model, the emission concentration of a single ship is accurately calculated. This method assesses the emissions of ships in transit based on telemetry, enabling monitoring without interfering with normal navigation. It provides a powerful technical means for ship emission monitoring and necessary data support for further regulation.

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

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

Claims

1. A method for remote sensing of ship emissions based on multi-band spectral inversion, characterized in that, Includes the following steps: 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 and perform spectral analysis to obtain the differential oblique column concentrations of NO2 and O4 on the horizontal path. S2. Calculate the effective optical path length, i.e. the effective horizontal path length, by dividing the differential oblique column concentration of O4 by the number density of O4. S3. Calculate the average volumetric mixing ratio concentration of NO2 on the horizontal path using the calculated effective horizontal path length; S4. Based on the O4 and NO2 horizontal column concentrations retrieved from multiple bands, obtain the effective horizontal path length information corresponding to different bands, and separate the NO2 concentration of different horizontal layers. S5. Based on ship AIS data and wind direction and speed information, construct a ship plume model that couples ship navigation trajectory with Gaussian plume model; S6. Obtain the plume shape based on the ship plume model and match it with different horizontal concentration layers observed in actual operation to obtain the NO2 concentration data of the horizontal layer where a single plume is located. Finally, determine the emission concentration of a single ship based on the plume width calculated by the ship plume model. Based on the ship plume model, the concentration layer through which a single plume passes and the corresponding plume width b are determined. The emission concentration of a single ship is then calculated using the following formula: ， ,in, The concentration of the NO2 concentration layer containing the plume is represented by the differential oblique column. This represents the background concentration value included in the plume concentration. This is the concentration layer that has not passed through the plume. This represents the effective path length corresponding to the concentration layer that does not pass through the plume. The thickness of the concentration layer where the plume is located.

2. The ship emission telemetry method based on multi-band spectral inversion according to claim 1, characterized in that, In S1, the multi-band spectral data from shore-based observations are solar scattering spectral data covering multiple bands.

3. The ship emission telemetry method based on multi-band spectral inversion according to claim 1, characterized in that, In S1, the light intensity loss caused by the absorption of atmospheric trace gas molecules is obtained 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°. Based on the linear least squares fitting of the multi-component absorption in specific bands of 340-370 nm, 430-490 nm, and 540-590 nm, the differential oblique column concentration results of NO2 and O4 in the corresponding bands are obtained by inversion.

4. The ship emission telemetry 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. Based on the near-surface concentration of O4, the effective horizontal path length L is calculated using the following formula: ,in, Given the number density of O2, calculate based on the fact that oxygen accounts for 20.9% of the air: , The number density of air, based on the observed temperature. and atmospheric pressure Calculations using the ideal gas law yielded the following: ,in, Let R be Avogadro's constant, and R be the molar gas constant.

5. The ship emission telemetry method based on multi-band spectral inversion according to claim 4, characterized in that, In step 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. This average concentration is then further divided by the concentration of air to obtain the average mixing ratio concentration along the effective horizontal path length L, expressed as: 。 6. The ship emission telemetry method based on multi-band spectral inversion according to claim 4, characterized in that, In step S4, the concentration and effective horizontal path length of different bands are obtained through detection in different bands, and the horizontal stratification of NO2 concentration is achieved through detection in two adjacent bands. ,in, and These correspond to the effective horizontal path lengths of adjacent longwave and shortwave bands, respectively. and The NO2 differential oblique column concentrations correspond to the long-wavelength and short-wavelength bands, respectively. This represents the concentration difference of the differential oblique column between two adjacent bands. This represents the effective horizontal path difference between two adjacent bands.

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

8. The ship emission telemetry 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 trajectory information, and the ship's latitude, longitude, speed, and heading information are obtained through the ship's AIS data.

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