Multi-component greenhouse gas detection method and system based on infrared absorption spectrum

Abstract

The invention discloses a multi-component greenhouse gas detection method and system based on an infrared absorption spectrum. The method comprises the following steps: obtaining the infrared absorption spectrum of a detected gas sample through measurement by a detection system; processing the infrared absorption spectrum of the detected gas sample by adopting mean filtering to obtain a background spectrum; calculating the greenhouse gas transmittance by using the background spectrum and the infrared absorption spectrum of the detected gas sample; calculating to obtain a greenhouse gas reference calibration spectrum by using a greenhouse gas standard absorption cross section provided by an HITRAN database; and carrying out iterative fitting on the transmittance and the reference calibration spectrum by adopting a nonlinear least square algorithm to invert the concentration of the greenhouse gas so as to realize the detection of the concentration of the multi-component gas in the greenhouse gas. The method can be used for greenhouse gas content monitoring in various different scenes.

Description

Technical Field

[0001] The present invention belongs to the field of gas detection technology and spectrum measurement technology, and specifically relates to a multi-component greenhouse gas detection method and system based on infrared absorption spectroscopy. Background Art

[0002] Greenhouse gas emissions have led to global temperature rise, climate warming, and sea level rise. From the perspective of the contribution to global temperature rise, CO2, CH4, and N2O are the three main greenhouse gases with the largest proportion, accounting for about 77% of global warming, and are still increasing year by year. Greenhouse gas spectroscopy detection technologies mainly include non-dispersive infrared spectroscopy (NDIR), Fourier transform spectroscopy (FTIR), cavity ring-down spectroscopy (CRDS), off-axis integral cavity output spectroscopy (OA-ICOS), laser heterodyne spectroscopy (LHS), differential absorption spectroscopy (DOAS), and tunable semiconductor laser absorption spectroscopy (TDLAS). Among them, FTIR spectroscopy is an infrared spectroscopy technology developed based on the principle of optical coherence. It has the advantages of high resolution, fast response speed, no need for gas separation, wide measurement band, the ability to complete multi-component quantification while decomposing gas components qualitatively, and short detection time, so it can form an online real-time monitoring system.

[0003] When using FTIR spectroscopy to measure atmospheric greenhouse gases, in principle, it is required to measure a spectrum that does not include the absorption signal of the target gas at the same time as measuring the spectrum, that is, the background spectrum, which is used to calculate the transmittance of the target gas. Under laboratory conditions, if the measurement time is not long, the measurement of the background spectrum is not difficult. It only needs to be filled with nitrogen in the closed sample cell and then measured to obtain a relatively ideal reference spectrum. However, under actual atmospheric observation conditions, since the measurement time is as long as weeks or even months, it is not practical to prepare a large amount of nitrogen. In addition, during long-term continuous monitoring, the actual background spectrum will fluctuate due to changes in environmental conditions. When using the single background spectrum obtained by the system in advance to invert the gas concentration, measurement errors will be introduced.

[0004] FTIR quantitative analysis methods based on Beer's law include peak height or peak area analysis, difference spectrum method, traditional least squares method and partial least squares method, but strictly speaking, Beer's law is only valid at infinite resolution. Beer's law does not hold when the actual absorption characteristic line width is comparable to or narrower than the spectral resolution. The typical line width of a single spectral line at 1 atm pressure is 0.05 to 0.15 cm -1 In order to avoid the nonlinearity of Beer's law, a high-resolution spectrum is required, while the typical resolution commonly used in atmospheric measurements is 0.5 to 4 cm. -1This is done by a spectrometer, which makes it impossible to ignore the deviation of Beer's law in quantitative analysis. In addition, greenhouse gases have cross absorption in the mid-infrared band, such as 2100-2500cm -1 The band includes CO2, N2O and CO absorption, 2900~3100cm -1 The band includes CH4 and H2O absorption. Therefore, when using the traditional FTIR quantitative analysis method for multi-component gas detection, it is difficult to overcome the problem of low greenhouse gas concentration inversion accuracy caused by multi-component cross-absorption and instrument linear influence. Summary of the invention

[0005] In view of the shortcomings of existing greenhouse gas online detection technology, the present invention provides a multi-component greenhouse gas detection method and system based on infrared absorption spectroscopy to solve the problems of difficulty in real-time acquisition of background spectrum during infrared spectrum measurement, multiple greenhouse gas components and cross-absorption interference in the infrared band, and difficulty in accurate inversion of multi-component gas concentrations, thereby realizing long-term continuous monitoring and accurate measurement of multi-component greenhouse gas concentrations, and providing reliable technical methods and equipment for greenhouse gas detection.

[0006] The present invention adopts the following technical solutions to solve the technical problems:

[0007] The multi-component greenhouse gas detection method based on infrared absorption spectrum of the present invention comprises: obtaining the infrared absorption spectrum of the measured gas sample by measuring through a detection system; processing the infrared absorption spectrum of the measured gas sample by a mean filtering method to obtain a background spectrum; calculating and obtaining the greenhouse gas transmittance by using the background spectrum and the infrared absorption spectrum of the measured gas sample; setting the initial value C0 of the greenhouse gas concentration according to the measurement temperature T, the measurement pressure P and the measurement optical path L, and according to the toe-cut function, spectral resolution and field angle of the detection system by using the standard absorption cross section of the greenhouse gas provided by the HITRAN database, and calculating and obtaining the greenhouse gas reference calibration spectrum; iteratively fitting the transmittance and the reference calibration spectrum by using a nonlinear least squares algorithm to invert the greenhouse gas concentration, updating the initial value C0 of the greenhouse gas concentration to a greenhouse gas concentration adjustment value, until the residual square sum between the transmittance and the reference calibration spectrum reaches a set minimum value, and taking the finally updated greenhouse gas concentration adjustment value as the detection result, so as to realize the detection of the greenhouse gas multi-component gas concentration; the measured gas sample is ambient air or atmospheric greenhouse gas of pollution source, and the greenhouse gas includes methane, water vapor, carbon dioxide, carbon monoxide and nitrous oxide.

[0008] The multi-component greenhouse gas detection method based on infrared absorption spectrum of the present invention uses the mean filtering method to process the infrared absorption spectrum to obtain the background spectrum in the following steps:

[0009] Step 2.1, set the size of the filter window and the upper limit of the number of filtering times, and take the infrared absorption spectrum as the filtering object I1;

[0010] Step 2.2, use a moving mean filter to smooth the filter object I1 to obtain a filter return column vector I2 of the same length as the filter object I1, compare the filter return column vector I2 with the filter object I1, and use the part of the filter return column vector I2 that is greater than or equal to the filter object I1 and the part of the filter object I1 that is greater than the filter return column vector I2 to form an update column vector I3;

[0011] Step 2.3, use the updated column vector I3 as the filtering object I1, repeat step 2.2 until the filtering return column vector I2 is greater than the infrared absorption spectrum by 95% or more, or the filtering times reaches the upper limit of the filtering times to complete the filtering, and the filtering return column vector I2 when the filtering is completed is the background spectrum.

[0012] The multi-component greenhouse gas detection method based on infrared absorption spectroscopy of the present invention comprises the following steps of calculating the greenhouse gas reference calibration spectrum:

[0013] According to the standard absorption cross sections of methane, water vapor, carbon dioxide, carbon monoxide and nitrous oxide at a standard atmospheric pressure and a temperature of 296K provided by the HITRAN database, the line intensity is corrected to the measurement temperature T and the measurement pressure P as shown in formula (1):

[0014]

[0015] In formula (1):

[0016] S ηη′ (T) represents the molecular spectral line intensity under the measurement temperature T; c2 is the second radiation constant;

[0017] ν ηη′ is the absorption line frequency; E η is the energy of the low-energy state of the absorption line, m is the temperature-dependent parameter of the partition function;

[0018] Using equation (2), the spectral line intensity is corrected for pressure broadening according to the Lorentz line type;

[0019]

[0020] In formula (2):

[0021] f L (ν) is the pressure broadening function; v is the frequency of the spectrum line; ν0 is the center position of the spectrum line;

[0022] α L is the half-width at half-height of the Lorentz line peak, n is the broadening temperature dependence parameter, p is the pressure, p s is the partial pressure of the absorbed gas, both in atm, γ air is the half-width at half-height of the air broadening of the absorption line, γ self is the half-height half-width of the absorption line self-broadening;

[0023] Use equation (3) to make Doppler broadening correction for the spectral line intensity according to the Gaussian line shape:

[0024]

[0025] In formula (3):

[0026] f G (ν) is the Doppler broadening function;

[0027] α G is the half-height half-width of the Gaussian line peak,

[0028] c is the speed of light, k is the Boltzmann constant, and M is the molecular mass;

[0029] According to the apodization function, spectral resolution and field of view of the detection system, the detection instrument line shape ILS (ν) is obtained as shown in formula (4):

[0030]

[0031] In formula (4):

[0032] δ is the optical path difference, sinc is the Sigmoid function;

[0033] Convolution is performed according to formula (5) to obtain the absorption cross section σ(ν) of a single spectral line under the same conditions as the measured spectrum:

[0034]

[0035] The greenhouse gas reference calibration spectrum τ′(ν) is calculated by formula (6):

[0036] τ′(ν)=exp[-σ(ν)·C0·L] (6)

[0037] The greenhouse gas reference calibration spectrum τ′(ν) is a greenhouse gas reference calibration spectrum that is identical to actual measurement environmental conditions and includes the linear influence of an actual measurement instrument.

[0038] The multi-component greenhouse gas detection method based on infrared absorption spectroscopy of the present invention uses a nonlinear least squares algorithm to iteratively fit the transmittance with a reference calibration spectrum, and includes the following steps:

[0039] The reference calibration spectrum is compared with the transmittance, and the residual square sum χ between the two is calculated according to formula (7):2 ;

[0040]

[0041] The Levenberg-Marquardt nonlinear least squares algorithm was used to adjust the greenhouse gas concentration values ​​and perform iterative fitting. This process was repeated until the residual sum of squares between the transmittance and the reference calibration spectrum was χ 2 When the set minimum value min is reached, the iteration is stopped. At this time, the greenhouse gas concentration is the measurement result. The root mean square error RMS calculated by formula (8) is used to evaluate the spectrum fitting effect to achieve quantitative inversion of greenhouse gas multi-component gas concentration.

[0042]

[0043] In formula (8), i represents the fitting data point, i=1, 2, ... N, and N is the total number of fitting data points.

[0044] The multi-component greenhouse gas detection system based on infrared absorption spectroscopy of the present invention comprises:

[0045] an infrared light source, which emits an infrared light signal;

[0046] An interferometer, used for modulating the infrared light signal into an interference signal;

[0047] A sample pool, into which the measured gas sample is introduced, the interference signal passes through the sample pool and is selectively absorbed by the measured gas sample, and a sample interference signal is output, wherein a temperature and pressure sensor for obtaining a measured temperature and a measured pressure is arranged in the sample pool;

[0048] A detector, which is used to receive a sample interference signal;

[0049] A signal acquisition circuit, used for acquiring a sample interference signal output by the detector;

[0050] A computer demodulates and restores the sample interference signal to obtain spectrum detection data, and processes the spectrum detection data according to the multi-component greenhouse gas detection method of the present invention to achieve concentration detection of multi-component greenhouse gases.

[0051] The multi-component greenhouse gas detection system based on infrared absorption spectroscopy of the present invention also includes: a sampling head for introducing the measured gas sample into the sample pool; and a vacuum pump for making the measured gas sample form a continuous flow through the sample pool to achieve online detection of the measured gas sample.

[0052] The invention discloses a multi-component greenhouse gas detection system based on infrared absorption spectroscopy. The sample pool adopts a multiple reflection structure and utilizes three spherical mirrors to realize multiple reflections of infrared light.

[0053] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0054] The present invention obtains a background spectrum by filtering the measured infrared absorption spectrum, and obtains a relatively accurate real-time background spectrum without stopping the measurement, thereby solving the problem of the difficulty in obtaining the background spectrum in the traditional method. Therefore, the present invention is very suitable for long-term continuous monitoring, and uses a reference calibration spectrum including the influence of instrument linearity and environmental parameters to perform quantitative inversion of multi-component gas concentrations, effectively solving the problem of low inversion accuracy of target gas concentration caused by changes in the environment, instrument linearity, etc. when the traditional infrared spectrum measurement method is applied, and can realize accurate measurement of multi-component greenhouse gas concentrations, providing a reliable technical method and equipment for greenhouse gas detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic diagram of the detection method process of the present invention;

[0056] Figure 2 A flow chart of obtaining a background spectrum by mean filtering in the method of the present invention;

[0057] Figure 3 A comparison diagram of the background spectrum and the measured greenhouse gas infrared absorption spectrum in the method of the present invention;

[0058] Figure 4 is the greenhouse gas permeability in the method of the present invention;

[0059] Figure 5 A reference calibration spectrum for greenhouse gases in the method of the present invention;

[0060] Figure 6 The transmittance of the CO2, CO, and N2O analysis bands in the method of the present invention and the fitting results of the reference calibration spectrum;

[0061] Figure 7 The transmittance of CH4 and H2O analysis bands in the method of the present invention is fitted with the reference calibration spectrum;

[0062] Figure 8 It is a schematic diagram of the structure of the detection system in the present invention. DETAILED DESCRIPTION

[0063] The multi-component greenhouse gas detection method based on infrared absorption spectroscopy in this embodiment includes: the detection system obtains the infrared absorption spectrum of the measured gas sample through measurement; the infrared absorption spectrum of the measured gas sample is processed by the mean filtering method to obtain the background spectrum; the greenhouse gas transmittance is calculated using the background spectrum and the infrared absorption spectrum of the measured gas sample; the greenhouse gas standard absorption cross section provided by the HITRAN database is used to set the initial value C0 of the greenhouse gas concentration according to the measurement temperature T, the measurement pressure P and the measurement optical path L, and according to the toe-cutting function, spectral resolution and field angle of the detection system, and the greenhouse gas reference calibration spectrum is calculated; the transmittance and the reference calibration spectrum are iteratively fitted by the nonlinear least squares algorithm to invert the greenhouse gas concentration, and the initial value C0 of the greenhouse gas concentration is updated to the greenhouse gas concentration adjustment value until the residual sum of squares between the transmittance and the reference calibration spectrum reaches the set minimum value, and the final updated greenhouse gas concentration adjustment value is used as the detection result to realize the detection of the multi-component greenhouse gas concentration; the measured gas sample is ambient air or atmospheric greenhouse gas from pollution sources, and the greenhouse gases include methane, water vapor, carbon dioxide, carbon monoxide and nitrous oxide. See the detection method flow. Figure 1 .

[0064] In this embodiment, the implementation process of using the mean filtering method to process the infrared absorption spectrum to obtain the background spectrum is shown in Figure 2 , follow the steps below:

[0065] Step 2.1, set the size of the filter window to 5 and the upper limit of the filter times to 100, and take the infrared absorption spectrum as the filter object I1;

[0066] Step 2.2, use a moving mean filter to smooth the filter object I1 to obtain a filter return column vector I2 of the same length as the filter object I1, compare the filter return column vector I2 with the filter object I1, and use the part of the filter return column vector I2 that is greater than or equal to the filter object I1 and the part of the filter object I1 that is greater than the filter return column vector I2 to form an update column vector I3;

[0067] Step 2.3, update the column vector I3 as the filtering object I1, repeat step 2.2 until the filter return column vector I2 is greater than the infrared absorption spectrum by 95% or more, or the filtering times reaches the upper limit of the filtering times to complete the filtering. The filter return column vector I2 when the filtering is completed is the background spectrum. Figure 3 As shown. The greenhouse gas transmittance is further calculated using the infrared absorption spectrum and the background spectrum as follows Figure 4 shown.

[0068] In this embodiment, calculating the greenhouse gas reference calibration spectrum includes the following steps:

[0069] According to the standard absorption cross sections of methane, water vapor, carbon dioxide, carbon monoxide and nitrous oxide at a standard atmospheric pressure and a temperature of 296K provided by the HITRAN database, the line intensity is corrected to the measurement temperature T and the measurement pressure P as shown in formula (1):

[0070]

[0071] In formula (1):

[0072] S ηη′ (T) represents the molecular spectral line intensity at the measurement temperature T, and its unit is cm 2 / (mol·cm);

[0073] c2 is the second radiation constant, which is 1.4388 cm·K;

[0074] ν ηη′ is the absorption line frequency, its unit is cm -1 ;

[0075] E η is the low-energy state energy of the absorption line, and its unit is cm -1 ,

[0076] m is the temperature dependence parameter of the partition function, for linear molecules, m = 1; for nonlinear molecules, m = 1.5;

[0077] Using equation (2), the spectral line intensity is corrected for pressure broadening according to the Lorentz line type;

[0078]

[0079] In formula (2):

[0080] f L (ν) is the pressure broadening function;

[0081] v is the spectral line frequency, its unit is cm -1 ; ν0 is the center position of the spectral line, and its unit is cm -1 ;

[0082] α L is the half-width at half-height of the Lorentz line peak, n is the broadening temperature dependence parameter, p is the pressure, p s is the partial pressure of the absorbed gas, both in atm, γ air is the half-width at half-height of the air broadening of the absorption line, γ self is the half-height half-width of the absorption line self-broadening;

[0083] Use equation (3) to make Doppler broadening correction for the spectral line intensity according to the Gaussian line shape:

[0084]

[0085] In formula (3):

[0086] f G (ν) is the Doppler broadening function, c is the speed of light;

[0087] α G is the half-height half-width of the Gaussian line peak,

[0088] k is the Boltzmann constant, which is 1.381×10 -23 JK -1 ;

[0089] M is the molecular mass, in kg;

[0090] According to the apodization function, spectral resolution and field of view of the detection system, the detection instrument line shape ILS (ν) is obtained as shown in formula (4):

[0091]

[0092] In formula (4):

[0093] δ is the optical path difference, and sinc is the Sigmoid function.

[0094] Convolution is performed according to formula (5) to obtain the absorption cross section σ(ν) of a single spectral line under the same conditions as the measured spectrum:

[0095]

[0096] The greenhouse gas reference calibration spectrum τ′(ν) is calculated by formula (6):

[0097] τ′(ν)=exp[-σ(ν)·C0·L] (6)

[0098] The greenhouse gas reference calibration spectrum τ′(ν) is the greenhouse gas reference calibration spectrum with the same environmental conditions as the actual measurement and includes the influence of the actual measurement instrument line shape. The temperature is 298K, the pressure is 1atm, the absorption path is 10m, the measurement system apodization function is a rectangular window function, and the spectral resolution is 0.5cm -1 The calculated reference calibration spectra of 10 ppm methane, 100 ppm water vapor, 10 ppm carbon dioxide, 10 ppm carbon monoxide and 10 ppm nitrous oxide are as follows: Figure 5 shown.

[0099] In this embodiment, the nonlinear least squares algorithm is used to iteratively fit the transmittance with the reference calibration spectrum, including the following steps:

[0100] Compare the reference calibration spectrum with the transmittance and calculate the residual sum of squares between the two using formula (7): 2 ;

[0101]

[0102] The Levenberg-Marquardt nonlinear least squares algorithm was used to adjust the greenhouse gas concentration values ​​and perform iterative fitting. This process was repeated until the residual sum of squares between the transmittance and the reference calibration spectrum was χ 2 Reach the set minimum value of 1×10 -5 The iteration stops when , and the greenhouse gas concentration is the measurement result. The root mean square error RMS calculated by formula (8) is used to evaluate the spectrum fitting effect, and the quantitative inversion of greenhouse gas multi-component gas concentration is realized;

[0103]

[0104] In formula (8), i represents the fitting data point, i=1, 2, ... N, and N is the total number of fitting data points.

[0105] When conducting quantitative analysis of greenhouse gas concentrations, the inversion band should avoid the water vapor absorption band or select a band with relatively small water vapor absorption. In addition, it is necessary to avoid the absorption saturation band of the target gas. Considering the contribution of water vapor in spectral absorption, the analysis algorithm will fit water vapor as a component to be measured together with the target gas to remove the interference of water vapor absorption. The analysis bands of CO2, CO, and N2O are 2100-2250cm -1 , the number of fitted data points is 313, and the RMS is equal to 0.15%, see Figure 6 ; CH4 and H2O analysis band is 2900~3140cm -1 , the number of fitting data points is 499, and the RMS is equal to 1.34%. Figure 7 shown.

[0106] See also Figure 8 In this embodiment, the multi-component greenhouse gas detection system based on infrared absorption spectroscopy includes:

[0107] Infrared light source, which emits infrared light signals, uses silicon carbide rods, has a power of 24W, and a radiation band range of 1 to 25μm;

[0108] Interferometer, which is used to modulate infrared light signals into interference signals, adopts a double-angle mirror swing structure to ensure the stability of the optical path in long-term operation;

[0109] A sample pool, into which the measured gas sample is introduced, the interference signal passes through the sample pool and is selectively absorbed by the measured gas sample, and a sample interference signal is output, and a sensor for obtaining a measured temperature and a measured pressure is arranged in the sample pool;

[0110] The detector is used to receive the sample interference signal, and adopts a mercury cadmium telluride photoconductive detector, with a response band of 2 to 16 μm and a window material of zinc selenide;

[0111] Signal acquisition circuit, used to collect sample interference signals output by the detector, 16-channel 16-bit 200KHz AD acquisition;

[0112] A computer demodulates and restores the sample interference signal to obtain spectral detection data, processes the spectral detection data according to the multi-component greenhouse gas detection method based on infrared absorption spectroscopy in this embodiment, and realizes the concentration detection of multi-component greenhouse gases.

[0113] In the specific implementation, the detection system also includes: a sampling head, used to introduce the measured gas sample into the sample pool; an air pump, used to make the measured gas sample form a continuous flow through the sample pool to realize online detection of the measured gas sample; the sample pool adopts a multiple reflection structure, using three spherical mirrors to realize multiple reflections of infrared light.

[0114] The above content is a further detailed description of the implementation mode of the present invention. It cannot be determined that the specific implementation mode of the present invention is limited to this. For ordinary technicians in the technical field to which the present invention belongs, they can make several simple deductions or substitutions without departing from the concept of the present invention, which should be regarded as belonging to the scope of patent protection determined by the claims submitted by the present invention.

Claims

1. A multi-component greenhouse gas detection method based on infrared absorption spectroscopy, characterized in that: The detection method comprises: obtaining an infrared absorption spectrum of a measured gas sample by a detection system through measurement; processing the infrared absorption spectrum of the measured gas sample by a mean filtering method to obtain a background spectrum; calculating and obtaining greenhouse gas transmittance by using the background spectrum and the infrared absorption spectrum of the measured gas sample; setting an initial value C0 of greenhouse gas concentration by using a standard absorption cross section of greenhouse gases provided by a HITRAN database according to a measurement temperature T, a measurement pressure P and a measurement optical path L, and according to a toe-cutting function, a spectral resolution and a field angle of the detection system, and calculating and obtaining a reference calibration spectrum of greenhouse gases; performing iterative fitting inversion of greenhouse gas concentration by using a nonlinear least squares algorithm between the transmittance and the reference calibration spectrum, updating the initial value C0 of greenhouse gas concentration to a greenhouse gas concentration adjustment value, until the residual sum of squares between the transmittance and the reference calibration spectrum reaches a set minimum value, and using the finally updated greenhouse gas concentration adjustment value as a detection result, thereby realizing detection of greenhouse gas multi-component gas concentration; the measured gas sample is ambient air or atmospheric greenhouse gases from pollution sources, and the greenhouse gases include methane, water vapor, carbon dioxide, carbon monoxide and nitrous oxide.

2. The multi-component greenhouse gas detection method based on infrared absorption spectroscopy according to claim 1 is characterized in that: The process of processing the infrared absorption spectrum by the mean filtering method to obtain the background spectrum is performed according to the following steps: Step 2.1, set the size of the filter window and the upper limit of the number of filtering times, and take the infrared absorption spectrum as the filtering object I1; Step 2.2, use a moving mean filter to smooth the filter object I1 to obtain a filter return column vector I2 of the same length as the filter object I1, compare the filter return column vector I2 with the filter object I1, and use the part of the filter return column vector I2 that is greater than or equal to the filter object I1 and the part of the filter object I1 that is greater than the filter return column vector I2 to form an update column vector I3; Step 2.3, use the updated column vector I3 as the filtering object I1, repeat step 2.2 until the filtering return column vector I2 is greater than the infrared absorption spectrum by 95% or more, or the filtering times reaches the upper limit of the filtering times to complete the filtering, and the filtering return column vector I2 when the filtering is completed is the background spectrum.

3. The multi-component greenhouse gas detection method based on infrared absorption spectroscopy according to claim 1 is characterized in that: The calculation of greenhouse gas reference calibration spectrum comprises the following steps: According to the standard absorption cross sections of methane, water vapor, carbon dioxide, carbon monoxide and nitrous oxide at a standard atmospheric pressure and a temperature of 296K provided by the HITRAN database, the line intensity is corrected to the measurement temperature T and the measurement pressure P as shown in formula (1): In formula (1): S ηη′ (T) represents the molecular spectral line intensity under the measurement temperature T; c2 is the second radiation constant; ν ηη′ is the absorption line frequency; E η is the energy of the low-energy state of the absorption line, m is the temperature-dependent parameter of the partition function; Using equation (2), the spectral line intensity is corrected for pressure broadening according to the Lorentz line type; In formula (2): f L (ν) is the pressure broadening function; v is the frequency of the spectrum line; ν0 is the center position of the spectrum line; α L is the half-width at half-height of the Lorentz line peak, n is the broadening temperature dependence parameter, p is the pressure, p s is the partial pressure of the absorbed gas, both in atm, γ air is the half-width at half-height of the air broadening of the absorption line, γ self is the half-height half-width of the absorption line self-broadening; Use equation (3) to make Doppler broadening correction for the spectral line intensity according to the Gaussian line shape: In formula (3): f G (ν) is the Doppler broadening function; α G is the half-height half-width of the Gaussian line peak, c is the speed of light, k is the Boltzmann constant, and M is the molecular mass; According to the apodization function, spectral resolution and field of view of the detection system, the detection instrument line shape ILS (ν) is obtained as shown in formula (4): In formula (4): δ is the optical path difference, sinc is the Sigmoid function; Convolution is performed according to formula (5) to obtain the absorption cross section σ(ν) of a single spectral line under the same conditions as the measured spectrum: The greenhouse gas reference calibration spectrum τ′(ν) is calculated by formula (6): τ′(ν)=exp[-σ(ν)·C0·L] (6) The greenhouse gas reference calibration spectrum τ′(ν) is a greenhouse gas reference calibration spectrum that is identical to actual measurement environmental conditions and includes the linear influence of an actual measurement instrument.

4. The multi-component greenhouse gas detection method based on infrared absorption spectroscopy according to claim 1 is characterized in that: The iterative fitting of the transmittance and the reference calibration spectrum using a nonlinear least squares algorithm comprises the following steps: The reference calibration spectrum is compared with the transmittance, and the residual square sum χ between the two is calculated according to formula (7): 2 ; The Levenberg-Marquardt nonlinear least squares algorithm was used to adjust the greenhouse gas concentration values ​​and perform iterative fitting. This process was repeated until the residual sum of squares between the transmittance and the reference calibration spectrum was χ 2 When the set minimum value min is reached, the iteration is stopped. At this time, the greenhouse gas concentration is the measurement result. The root mean square error RMS calculated by formula (8) is used to evaluate the spectrum fitting effect to achieve quantitative inversion of greenhouse gas multi-component gas concentration. In formula (8), i represents the fitting data point, i=1, 2, ... N, and N is the total number of fitting data points.

5. A multi-component greenhouse gas detection system based on infrared absorption spectroscopy, characterized in that include: an infrared light source, which emits an infrared light signal; An interferometer, used for modulating the infrared light signal into an interference signal; A sample pool, into which the measured gas sample is introduced, the interference signal passes through the sample pool and is selectively absorbed by the measured gas sample, and a sample interference signal is output, wherein a temperature and pressure sensor for obtaining a measured temperature and a measured pressure is arranged in the sample pool; A detector, which is used to receive a sample interference signal; A signal acquisition circuit, used for acquiring a sample interference signal output by the detector; A computer obtains spectrum detection data by demodulating and restoring the sample interference signal, and processes the spectrum detection data according to the multi-component greenhouse gas detection method of claim 1 to realize the concentration detection of the multi-component greenhouse gas.

6. The multi-component greenhouse gas detection system based on infrared absorption spectroscopy according to claim 5 is characterized in that The detection system further comprises: a sampling head for introducing the measured gas sample into the sample pool; and a vacuum pump for making the measured gas sample flow continuously through the sample pool to realize online detection of the measured gas sample.

7. The multi-component greenhouse gas detection system based on infrared absorption spectroscopy according to claim 5 is characterized in that The sample pool adopts a multiple reflection structure and utilizes three spherical mirrors to realize multiple reflections of infrared light.

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