A method and system for real-time measurement of ship exhaust emission rates based on ground-based doas

Abstract

The present application relates to the technical field of ship emission monitoring, and particularly relates to a method and system for measuring ship exhaust emission rate in real time based on ground-based DOAS. The technical scheme comprises installation and calibration of the instrument, real-time data acquisition and processing, and optimal estimation method based on Monte Carlo radiation transfer model simulation. The present application collects spectral information and distribution information of ship emission plume in real time, establishes a discrete Gaussian plume model and inputs it into the Monte Carlo radiation transfer model, reconstructs the radiation transfer process of the plume in the atmosphere, simulates the radiance data in the field of view of the spectrometer, compares it with the actually collected spectral information, and infers the ship exhaust emission rate through the optimal estimation method, so as to fully exert the characteristics of passive DOAS instrument measurement, such as rapidness and flexibility.

Description

Technical Field

[0001] The present invention relates to the technical field of ship emission monitoring, and in particular to a method and system for real-time measurement of ship exhaust emission rate based on ground-based DOAS. Background Art

[0002] Ship exhaust emissions are a growing environmental concern, primarily consisting of harmful substances such as sulfur dioxide (SO2), nitrogen oxides (NOx), particulate matter (PM), and carbon dioxide (CO2). These pollutants not only degrade air quality but also pose a threat to human health. Ship exhaust emissions can even directly impact ocean water quality, harming marine life and the ecological balance. Furthermore, the increase in greenhouse gases contributes to global warming and climate change. Consequently, the shipping industry faces increasingly stringent environmental regulations, necessitating the adoption of more environmentally friendly technologies and management measures to achieve sustainable development.

[0003] Until now, fuel compliance checks have been conducted by inspection agencies. These agencies enter ships at anchor, review fuel logbooks and fuel quality certificates, and, if suspected, take fuel samples for analysis in certified laboratories. Based on the results of these analyses, compliance can be verified and, if necessary, legal action can be taken. However, these controls can only be applied to a small number of vessels.

[0004] For monitoring ship emissions, some simple but effective methods are to use on-site instruments to directly measure trace pollutant gases. Current ship emission monitoring technologies are mainly divided into sniffer technology and optical principle technology. Sniffer technology is widely used to collect and analyze exhaust emissions transmitted by wind. This technology captures the gas components flowing in the environment through a series of sensors and instrument systems. The sniffer is usually located far away from the emission source in order to collect and analyze the components of the gas propagated by the wind. Some scholars also install sniffers on drones or aircraft, and use the airborne platform to enter the ship's smoke plume to collect exhaust gas. Sniffer technology is currently the most widely used and convenient type of equipment, with flexible installation and low cost. However, it is greatly affected by environmental conditions, and the exhaust gas emitted by ships must be transmitted to the instrument before it can be detected.

[0005] Optical techniques are theoretically less susceptible to environmental influences and provide more reliable measurement results. Optical techniques are generally categorized as DOAS instruments, laser radar (LIDAR), and UV cameras. LiDAR technology is an active optical method that emits short laser pulses into the atmosphere. Differential absorption lidar (DIAL) can measure atmospheric gas concentrations by emitting two or more pulses of different wavelengths, chosen so that one wavelength is more strongly absorbed by the gas being measured than the other. Distance information along the laser beam path is still available, allowing the instrument to measure the concentration at a known location in the atmosphere. A UV camera consists of a UV charge-coupled array (CCD) and a UV lens. For example, for SO₂ detection, SO₂ in the camera's field of view causes attenuation of the recorded light intensity. By calibrating the camera using a gas chamber containing a known amount of SO₂, the recorded light intensity can be directly correlated to the path concentration. The camera's rapid sampling allows it to track features in the image and derive wind speed and gas flux within the plume. The DOAS principle analyzes gas concentration by measuring the difference in gas absorption of light within a specific wavelength range. Since its proposal in 1979, it has been widely used in remote sensing monitoring of atmospheric pollutants.

[0006] DOAS instruments are categorized as passive and active. Passive DOAS instruments rely on natural light sources for gas measurement and generally consist of an optical system and a detector. Active DOAS instruments, such as long-path DOAS (LP-DOAS), use active light sources. They combine DOAS with lidar technology, illuminating the target area with an artificial laser light source and measuring the reflection or scattering of the light signal to analyze gas concentrations. They generally consist of a laser, a reflector, and a detector. Passive DOAS uses natural light sources and is affected by weather, but they are low-cost and suitable for large-scale monitoring. Active DOAS instruments are not affected by weather and offer higher measurement accuracy than passive DOAS.

[0007] The main purpose of applying DOAS instruments to ship emission regulation is to measure the emission rate of ship exhaust gas and determine whether the ship is in violation of regulations. Therefore, the identity of the ship must be identified and the measurement results of the DOAS instrument must be assigned to the specific ship. The current common ship identification technology is the Automatic Identification System (AIS). AIS is a system based on wireless communication between ships and between ships and shores, which is used to improve the safety of maritime traffic. AIS broadcasts its position, speed, heading and other information through equipment on the ship, and receives relevant data from other ships. On the other hand, the measurement of wind speed and direction is crucial for ship identification. The ship's smoke plume is affected by the transmission of natural wind. The position of the ship's smoke plume is generally the resultant force of the relative wind generated by the ship's running speed and the real wind (natural wind).

[0008] For monitoring of ship emissions during navigation, existing monitoring methods cannot guarantee that the observation position is always at the ship's chimney outlet. Therefore, monitoring of the emission rate of a specific ship is often done by measuring the old smoke plume emitted by the ship and then combining it with wind speed or Gaussian smoke plume model to estimate the emission rate at the chimney outlet.

[0009] As mentioned above, differential optical absorption spectroscopy (DOAS) technology is of great value in ship exhaust monitoring. This non-contact monitoring method is suitable for real-time monitoring of ship emissions, especially in open water and port environments, and has broad application prospects. However, because ships are mobile emission sources and the exhaust gas they emit is usually transparent and invisible, it is difficult for DOAS instruments to determine the location of the observation target. At the same time, the measurement of ship exhaust emission rates is affected by factors such as the ship's own emission factors, fuel type, meteorological conditions (especially wind speed), background interference, and optical path uncertainty. Therefore, existing passive DOAS instruments are not very useful in the field of ship exhaust measurement, and the advantages of DOAS instruments in terms of real-time performance and accuracy cannot be fully utilized.

[0010] Therefore, we propose a method and system for real-time measurement of ship exhaust emission rate based on ground-based DOAS. Summary of the Invention

[0011] The purpose of the present invention is to provide a ground-based DOAS observation system that combines an imaging spectrometer with a visual camera, an AIS receiver, and a meteorological sensor to collect the spectral information and distribution information of ship exhaust plumes in real time, establish a discrete Gaussian plume model and input it into a Monte Carlo radiation transfer model, reconstruct the radiation transfer process of the plume in the atmosphere, simulate the radiance data in the spectrometer field of view, and compare it with the actual collected spectral information, and infer the exhaust emission rate of the ship through the optimal estimation method.

[0012] In one aspect, the present invention provides a method for real-time measurement of ship exhaust emission rate based on ground-based DOAS, comprising the following steps:

[0013] Installation and calibration of instruments: installation of optical lens, DOAS imaging spectrometer, visual camera, and AIS receiver, matching of visual camera and spectrometer fields of view, and selection of observation sight lines;

[0014] Real-time data collection and processing: retrieval of pollutant emissions from the light intensity values ​​collected by the DOAS imaging spectrometer, aggregation of the collected data, and construction of the spatial distribution of the ship's emission plume;

[0015] Based on the optimal estimation method of Monte Carlo radiation transfer model simulation, the Gaussian plume model is added to the Monte Carlo radiation transfer model as an inhomogeneous medium, the collected radiance is simulated and compared with the actual collected radiance value, the source concentration parameters of the Gaussian plume are adjusted, and the actual emission concentration value is inferred.

[0016] Optionally, the DOAS imaging spectrometer is an ultraviolet DOAS imaging spectrometer with a wavelength band of 300nm to 400nm.

[0017] Optionally, the optical lens adopts a rectangular field of view of 5.5°×5.5°, and transmits the light signal to the slit of the DOAS imaging spectrometer through an optical fiber.

[0018] Optionally, the field of view of the visual camera is 60°×30°.

[0019] Optionally, the light intensity values ​​collected by the DOAS imaging spectrometer are inverted to form concentration changes in the time dimension to retrieve whether passing ships have pollution emissions, and the spectral data corresponding to the peak concentration is converted into radiance data collected by the DOAS imaging spectrometer through radiation calibration.

[0020] Optionally, the inversion of the spectral data is automatically performed using the QDOAS tool, and the reference spectrum is the zenith spectrum when no ship passes. After inversion, each piece of spectral data generates 49 concentration values ​​corresponding to 49 optical fibers. The concentration values ​​at different times constitute a concentration change curve in the time dimension, and the concentration curve in the time dimension is low-pass filtered to extract its peak change, and at the same time, the peak change below the gas concentration detection line of the DOAS imaging spectrometer is eliminated.

[0021] Optionally, there are 49 optical fibers, which are arranged as 7×7 at the optical lens end and 1×49 at the slit end. The optical fibers transpose the two-dimensional spatial image in the optical lens into a one-dimensional spatial image collected by the DOAS imaging spectrometer.

[0022] Optionally, the image position captured by the visual camera includes the position of the ship's chimney. The effective height of the smoke plume emitted by the ship is related to the height of the chimney and the initial vertical velocity of the smoke plume. The calculation formula is as follows:

[0023]

[0024] Among them, h eff is the effective height of the plume, h stack is the chimney height, is the initial vertical velocity of the plume, and g is the acceleration due to gravity.

[0025] Optionally, the calculation formula of the Gaussian plume model is as follows:

[0026]

[0027] Where C(x, y, z) represents the pollutant concentration at a point x meters downwind, y meters horizontally, and z meters high from the emission source, Q is the emission rate of the emission source, and σ yis the lateral diffusion coefficient, σ z is the longitudinal diffusion coefficient, U is the wind speed at the emission height H, and H is the effective height of the emission source.

[0028] On the other hand, the present invention proposes a system for real-time measurement of ship exhaust emission rates based on ground-based DOAS, using the above-mentioned method. The system includes an industrial computer for controlling and processing data of each subsystem, and is characterized by also including:

[0029] An optical lens and a DOAS imaging spectrometer connected to the optical lens, wherein the optical lens collects spectral information of the target and transmits it to an imaging circuit in the DOAS imaging spectrometer, and transmits the received optical signal to the industrial computer;

[0030] A visual camera mounted on a pan-tilt head is used to identify the ship's position, collect information about the ship's shape, and determine the field of view of the DOAS imaging spectrometer;

[0031] AIS receiver, which receives AIS data broadcast by nearby ships through an antenna;

[0032] Meteorological data system, obtains data related to wind direction, wind speed, temperature and air pressure in the observation area.

[0033] In summary, this application includes at least one of the following beneficial technical effects:

[0034] This paper proposes a ground-based DOAS observation system that combines an imaging spectrometer with a visual camera, an AIS receiver, and a meteorological sensor. This system collects the spectral and distribution information of ship exhaust plumes in real time, establishes a discrete Gaussian plume model, and inputs it into a Monte Carlo radiative transfer model. This system reconstructs the radiative transfer process of the plume in the atmosphere, simulates the radiance data in the spectrometer's field of view, and compares it with the actual spectral information collected. This system then infers the ship's exhaust emission rate using an optimal estimation method. This system is unaffected by the optical path when calculating the ship's emission rate, leveraging the fast and flexible measurement capabilities of passive DOAS instruments.

[0035] Furthermore, a smoke plume model of ship emissions and realistic instrument parameters are defined in the Monte Carlo radiative transfer model to simulate the radiance under actual observation conditions. The emission rate of pollutant gases from ships is inferred by comparing it with the actual observation value through the optimal estimation method. This method can be applied to experimental scenarios under various observation conditions, avoiding measurement errors caused by the uncertainty of the integral path, and is suitable for more flexible experimental optical path design. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic diagram of a system for real-time measurement of ship exhaust emission rates based on ground-based DOAS according to the present invention;

[0037] Figure 2 This is a flow chart of the present invention for real-time monitoring of ship pollutant gas emission rates;

[0038] Figure 3 Schematic diagram of the relationship between the field of view of the optical lens and the field of view of the DOAS imaging spectrometer;

[0039] Figure 4 Schematic diagram of the field of view correction process and results;

[0040] Figure 5 This is a diagram of the peak matching process in real-time data acquisition and processing;

[0041] Figure 6 This is a schematic diagram of the plume orientation;

[0042] Figure 7 Flowchart for setting specific parameters in the MCARaTs tool. DETAILED DESCRIPTION

[0043] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0044] The components of the embodiments of the present invention generally described and shown in the drawings herein may be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of the invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention.

[0045] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

[0046] like Figure 1As shown, the present invention proposes a system for real-time measurement of ship exhaust emission rates based on ground-based DOAS, which is mainly composed of an industrial computer, a DOAS imaging spectrometer, an optical lens, a visual camera, a pan-tilt platform, an AIS receiver, a meteorological data system and related supporting software. The industrial computer completes the control and data processing of each subsystem; the DOAS imaging spectrometer is connected to an optical lens through an optical fiber to complete the spectral information acquisition of the target, and the imaging circuit in the DOAS imaging spectrometer transmits the optical signal received by the detector to the industrial computer. In practical applications, the DOAS imaging spectrometer used in the present invention is an ultraviolet DOAS imaging spectrometer with a wavelength of 300nm to 400nm, which is used to invert the NO2 and SO2 concentration information in ship emissions; the visual camera is used to identify the position of the ship, collect the ship's appearance information and determine the field of view of the DOAS imaging spectrometer; the visual camera and the optical lens are fixedly mounted on the pan-tilt platform, and the rotation of the pan-tilt platform drives the change of the optical lens's line of sight to complete the adjustment of the system's optical path.

[0047] In practical applications of the present invention, the visual camera has a field of view of 60°×30°, and the optical lens has a field of view of 5.5°×5.5°; the AIS receiver receives AIS data broadcast by nearby ships through an antenna; the meteorological data system obtains data such as wind direction, wind speed, temperature, and air pressure in the observation area. In practical applications, data can be obtained through the API provided by the online meteorological model or from the local weather station.

[0048] The flow chart of this system for real-time monitoring of ship pollutant gas emission rate is as follows Figure 2 As shown. The overall test process can be divided into three parts: instrument installation and calibration, real-time data acquisition and processing, and optimal estimation method based on Monte Carlo radiation transfer model simulation. The instrument installation and calibration part mainly completes the matching of the visual camera and spectrometer field of view and the selection of the observation line of sight of this system, which is carried out before the field experiment begins. Real-time data acquisition and processing mainly retrieves whether there is pollutant gas emission from the light intensity value collected by the DOAS imaging spectrometer, summarizes the collected data and constructs the spatial distribution of the ship emission plume. The optimal estimation method based on Monte Carlo radiation transfer model simulation mainly adds the Gaussian plume model as a non-uniform medium to the Monte Carlo radiation transfer model to simulate the radiance collected by this system and compares it with the actual collected radiance value, adjusts the source concentration parameters of the Gaussian plume, and infers the actual emission concentration value.

[0049] Specifically, due to the existence of assembly errors, the field of view calibration is first performed after the instrument is installed to ensure that the field of view of the DOAS imaging spectrometer is accurately positioned in the field of view of the visual camera, helping to select the observation area of ​​the DOAS imaging spectrometer and providing a reliable foundation for subsequent data processing and the establishment of the forward transmission model. The optical lens used in the present invention has a rectangular field of view of 5.5°×5.5°. The optical signal is transmitted to the slit of the imaging spectrometer through an optical fiber. There are 49 optical fibers, which are arranged in 7×7 at the optical lens end and 1×49 at the slit end. Figure 3 As shown, the optical fiber transposes the two-dimensional spatial image in the optical lens into a one-dimensional spatial image collected by the DOAS imaging spectrometer. The specific method of field of view correction is to use the instrument to observe a specific target pattern or a target with obvious light and dark distribution characteristics, and select the light intensity value of a single wavelength from the one-dimensional spatial image collected by the spectrometer and reconstruct the two-dimensional image to form a low-resolution pattern of 7×7 pixels. The image collected by the visible camera is then converted into a grayscale image, and a rectangle with a range of 5.5°×5.5° and divided into 7×7 grids is used to reduce the resolution in the collected visible camera grayscale image and compare it with the low-resolution pattern collected by the DOAS imaging spectrometer to finally determine the exact position of the DOAS imaging spectrometer in the field of view of the visible camera. The field of view correction process and results are shown in the figure. Figure 4 Figure 1 shows an image captured by a visible camera, with the white rectangle indicating the approximate location of the DOAS imaging spectrometer within the visible camera. Figure 1 shows a downscaled image of the grayscale image captured by the visible camera, and Figure 1 shows a two-dimensional spatial image captured by the DOAS imaging spectrometer. Comparing (b) with (c) determines the location of the DOAS imaging spectrometer's field of view within the visible camera's field of view.

[0050] The system's observation line of sight is determined by the experimental plan. The system determines whether a passing ship is emitting pollutants by detecting transient peaks in target gas concentrations as the vessel passes. Therefore, the observation line of sight is always pre-positioned at the location of the vessel's plume, enabling the system to retrieve peaks from the background concentration of the detected gas. After field of view correction, the instrument's line of sight is controlled by the pan / tilt (PTZ). Typically, the instrument's line of sight is perpendicular to the vessel's course. For measurements on inland rivers and ports, the instrument is mounted on either bank, with the line of sight perpendicular to the river. To maximize the instrument's line of sight through the vessel's plume, the system adjusts the pan / tilt angle based on the vessel's navigation information received by the AIS receiver. Therefore, the vessel's size and position in the AIS information are crucial, and the system pre-positions the line of sight above the passing vessel.

[0051] After the line of sight is adjusted, the system starts to collect data and analyze it. The light intensity data generated by the DOAS imaging spectrometer is mainly used to retrieve whether the passing ships have pollution emissions through the concentration changes in the time dimension after inversion, and the spectral data corresponding to the peak concentration is converted into radiance data collected by the instrument through radiation calibration. The specific process is as follows: The spectral data is automatically inverted using the QDOAS tool, and the reference spectrum selects the zenith spectrum when no ship passes by. After inversion, each spectral data generates 49 concentration values ​​corresponding to 49 optical fibers. The concentration values ​​at different times constitute the concentration change curve in the time dimension. Due to the existence of inversion errors, the background value of the concentration (when no ship passes) always fluctuates. Therefore, low-pass filtering is used for the concentration curve in the time dimension to extract its peak changes, and at the same time, the peak changes below the instrument gas concentration detection line are eliminated. The process is as follows: Figure 5 shown.

[0052] When a ship passes by and an effective peak concentration occurs, the raw spectral data collected by the DOAS imaging spectrometer at that moment is matched with relevant data collected by other parts of the system for subsequent plume modeling and concentration calculation. The image position collected by the visual camera mainly provides the location of the ship's chimney. The effective height of the ship's exhaust plume is related to the height of the chimney and the initial vertical velocity of the plume, which is calculated as follows:

[0053]

[0054] Among them, h eff is the effective height of the plume, h stack is the chimney height, is the initial vertical velocity of the plume, and g is the acceleration due to gravity.

[0055] The size and propagation direction of the smoke plume are determined by the ship speed and direction provided by AIS data and the wind speed and direction provided by meteorological data, such as Figure 6 shown.

[0056] The plume model is approximated by the Gaussian plume model. The calculation formula of the standard three-dimensional Gaussian plume model is as follows:

[0057]

[0058] Where C(x, y, z) represents the pollutant concentration at a point x meters downwind, y meters horizontally, and z meters high from the emission source, Q is the emission rate of the emission source, and σ y is the lateral diffusion coefficient, σ z is the longitudinal diffusion coefficient, U is the wind speed at the emission height H, and H is the effective height of the emission source.

[0059] In reality, the shape of a Gaussian plume is affected by atmospheric stability and can be categorized as a looping plume, coning plume, fanning plume, lofting plume, trapped plume, and fumigation plume. The level of atmospheric stability is related to meteorological factors such as wind speed, temperature, and pressure.

[0060] After the three-dimensional Gaussian plume model is established, the relationship between the emission rate of the emission source and the concentration at any spatial position of the plume can be obtained. This relationship is continuous. In order to further serve as the input of numerical simulation, this Gaussian plume model is discretized. The size of the spatial grid is related to the spatial grid scale defined by the Monte Carlo radiation transfer model. In the present invention, the MCARaTs tool is used as the Monte Carlo radiation transfer model as a solution tool, and the minimum grid is defined as 1×1×1 meter.

[0061] In the optimal estimation method based on Monte Carlo radiative transfer model simulation, a three-dimensional grid scene close to the actual observation conditions is established, the gas absorption coefficient is set according to the space-concentration relationship in the discretized Gaussian plume model, and the radiance observed from the instrument perspective is simulated. After comparison with the actual observed radiance, the emission source concentration of the Gaussian plume model is further adjusted to infer the actual emission concentration of the ship. The specific parameter setting process in the MCARaTs tool of the present invention is as follows: Figure 7 shown.

[0062] The parameters related to the Monte Carlo radiation transfer model mainly include the phase function related to the calculation, the order of photon scattering, etc., atmospheric parameters, surface reflection parameters, and radiance simulation parameters. The most core of these is the atmospheric parameter setting. In the MCARaTs software, the atmosphere is divided into three-dimensional grids, and each layer is regarded as a homogeneous layer. Parameters such as temperature, pressure, extinction coefficient, and gas absorption coefficient are set for each layer. At the same time, a three-dimensional extinction coefficient and a gas absorption coefficient scaling function are provided to modify the homogeneous layer into a non-homogeneous layer to simulate the actual atmospheric state. In the present invention, the scaling factor of the gas absorption coefficient is set according to the space-concentration relationship in the established discrete Gaussian plume model to simulate the plume emitted by the ship. The surface reflection parameters can simulate the actual reflection parameters of the channel and the ground combination. The position parameters of the light source and radiance calculation are set according to the actual observation time and the instrument design parameters to simulate the radiance data under the actual observation conditions.

[0063] After the Monte Carlo radiative transfer model simulates the radiance, the spectral data collected by the spectrometer under these observation conditions is converted to radiance data through a radiometric calibration experiment. This radiometric calibration experiment is usually completed in advance and the relationship between radiance and light intensity is determined for the same instrument. An optimal estimation method is used to compare the simulated radiance with the actual measured radiance. The gas absorption coefficient scaling factor of the smoke plume is adjusted in the radiative transfer model to minimize the error between the simulated and measured radiances, thereby inferring the actual smoke plume concentration distribution information. The emission rate of the pollutant gas is then determined based on the established Gaussian smoke plume model.

[0064] The above specific embodiments are merely 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 may make various alternative improvements and combinations to the above specific embodiments.

Claims

1. A method for real-time measurement of ship exhaust emission rate based on ground-based DOAS, characterized in that: The following steps are involved: Installation and calibration of instruments: installation of optical lens, DOAS imaging spectrometer, visual camera, and AIS receiver, matching of visual camera and spectrometer fields of view, and selection of observation sight lines; Real-time data collection and processing: retrieval of pollutant emissions from the light intensity values ​​collected by the DOAS imaging spectrometer, aggregation of the collected data, and construction of the spatial distribution of the ship's emission plume; The light intensity values ​​collected by the DOAS imaging spectrometer are inverted to form concentration changes in the time dimension to retrieve whether the passing ship has discharged pollution, and the spectral data corresponding to the peak concentration is converted into radiance data collected by the DOAS imaging spectrometer through radiometric calibration; Based on the optimal estimation method of Monte Carlo radiative transfer model simulation, the Gaussian plume model is added as an inhomogeneous medium to the Monte Carlo radiative transfer model, the simulated collected radiance is compared with the actual collected radiance value, the source concentration parameters of the Gaussian plume are adjusted, and the actual emission concentration value is inferred; The image position captured by the visual camera includes the position of the ship's chimney. The effective height of the ship's smoke plume is related to the height of the chimney and the initial vertical velocity of the smoke plume. The calculation formula is as follows: ； in, is the effective height of the plume, is the chimney height, is the initial vertical velocity of the plume, is the acceleration due to gravity.

2. The method for real-time measurement of ship exhaust emission rate based on ground-based DOAS according to claim 1 is characterized in that: The DOAS imaging spectrometer is an ultraviolet DOAS imaging spectrometer with a wavelength range of 300nm to 400nm.

3. The method for real-time measurement of ship exhaust emission rate based on ground-based DOAS according to claim 1 is characterized in that: The optical lens adopts a rectangular field of view of 5.5°×5.5° and transmits the light signal to the slit of the DOAS imaging spectrometer through an optical fiber.

4. The method for real-time measurement of ship exhaust emission rate based on ground-based DOAS according to claim 1 is characterized in that: The field of view of the visual camera is 60°×30°.

5. The method for real-time measurement of ship exhaust emission rate based on ground-based DOAS according to claim 1 is characterized in that: The spectral data is automatically inverted using the QDOAS tool. The reference spectrum is the zenith spectrum when no ship passes. After inversion, each spectral data generates 49 concentration values ​​corresponding to 49 optical fibers. The concentration values ​​at different times constitute a concentration change curve in the time dimension. The concentration curve in the time dimension is low-pass filtered to extract its peak change, and the peak change below the gas concentration detection line of the DOAS imaging spectrometer is eliminated.

6. The method for real-time measurement of ship exhaust emission rate based on ground-based DOAS according to claim 5 is characterized in that: There are 49 optical fibers, which are arranged in 7×7 at the optical lens end and 1×49 at the slit end. The optical fibers transpose the two-dimensional spatial image in the optical lens into a one-dimensional spatial image collected by the DOAS imaging spectrometer.

7. The method for real-time measurement of ship exhaust emission rate based on ground-based DOAS according to claim 1 is characterized in that: The calculation formula of the Gaussian plume model is as follows: ； Where, It represents the pollutant concentration at a distance of x meters downwind, y meters horizontally, and z meters in height from the emission source. Q is the emission rate of the emission source. is the lateral diffusion coefficient, is the longitudinal diffusion coefficient, U is the wind speed at the emission height H, and H is the effective height of the emission source.

8. A system for real-time measurement of ship exhaust emission rates based on ground-based DOAS, using the method according to any one of claims 1 to 7, wherein the system includes an industrial computer for controlling and processing data of each subsystem, characterized in that: Also includes: An optical lens and a DOAS imaging spectrometer connected to the optical lens, wherein the optical lens collects spectral information of the target and transmits it to an imaging circuit in the DOAS imaging spectrometer, and transmits the received optical signal to the industrial computer; A visual camera mounted on a pan-tilt head is used to identify the ship's position, collect information about the ship's shape, and determine the field of view of the DOAS imaging spectrometer; AIS receiver, which receives AIS data broadcast by nearby ships through an antenna; Meteorological data system, obtains data related to wind direction, wind speed, temperature and air pressure in the observation area.

Images