Comprehensive screening method for background concentration of CO2 and CH4 in atmosphere

Abstract

The invention discloses a comprehensive screening method for background concentration of CO2 and CH4 in atmosphere, which is characterized by comprising the following steps of: firstly collecting greenhouse gas observation data and meteorological observation data, then processing the data, and finally carrying out background screening on effective observation data of CO2 or CH4 by adopting a robust local regression algorithm based on the processed data, setting a bandwidth value in combination with the seasonal change of the atmospheric CO2 concentration, carrying out iterative calculation to enable a fitting curve to converge, calculating to obtain a scale parameter delta, screening observation data between the fitting value + / -delta as a background value, and taking other data as local values; after robust local regression screening, the influence of the atmospheric stability condition, the wind speed and the wind direction on the greenhouse gas source sink is comprehensively considered, and atmospheric CO2 and CH4 concentration screening is achieved. The method is suitable for screening main greenhouse gases such as CO2 and CH4 in the region, and can provide support for constructing a carbon-to-peak carbon neutralization policy system in the region and formulating an emission reduction policy.

Description

Technical Field

[0001] The invention belongs to the technical field of atmospheric background concentration screening, and in particular relates to a comprehensive screening method for atmospheric CO2 and CH4 background concentrations. Background Art

[0002] The greenhouse gas atmospheric background in the World Meteorological Organization's Global Atmosphere Watch (GAW) refers to the situation where it is not affected by local and anthropogenic activities and is mixed well. The global background is generally manifested as large-scale and long-term changes directly related to the global climate, and the concentration value is not affected by local and regional sources and sinks; the regional background represents the concentration value of a region that is well mixed and not affected by local sources and sinks. Global atmospheric background stations (such as the Waliguan Station in Qinghai, my country) and regional atmospheric background stations (such as the Lin'an Station in Zhejiang, my country) are mostly located in areas with little impact from anthropogenic activities. With the establishment of a large number of greenhouse gas monitoring stations, the observation environment is complex and changeable due to high anthropogenic activities. For example, the Yangtze River Delta, the Pearl River Delta, and the Beijing-Tianjin-Hebei region have dense cities, developed economies, dense populations, and numerous emission sources, and there are greater fluctuations in the temporal and spatial changes in atmospheric CO2 and CH4 concentrations. The greenhouse gas background screening schemes of global and regional atmospheric background stations are not fully applicable in areas with high anthropogenic activities.

[0003] At present, there are no technical specifications or relevant standards for screening background concentrations of greenhouse gases in areas with high anthropogenic activities in China. The implementation of background concentration screening technology for atmospheric greenhouse gases in economically developed, densely populated areas with numerous emission sources has become an indispensable technical tool for accurately analyzing the changing patterns of regional greenhouse gas concentrations. It helps to objectively and accurately measure the dynamic changes of greenhouse gas emission sources and sinks, and can provide a scientific basis for formulating emission reduction paths and verifying emission reduction effects.

[0004] Therefore, it is particularly necessary to develop a method for screening background concentrations of atmospheric CO2 and CH4. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a comprehensive screening method for the background concentrations of atmospheric CO2 and CH4, which can realize the screening of the background concentrations of atmospheric greenhouse gases in economically developed, densely populated areas and areas with numerous emission sources, and become an indispensable technical tool for accurately analyzing the changing laws of regional greenhouse gas concentrations. It helps to objectively and accurately measure the dynamic changes of greenhouse gas emission sources and absorption sinks, and can provide a scientific basis for the formulation of emission reduction paths and the verification of emission reduction effects.

[0006] In order to achieve the above technical effects, the technical solution adopted by the present invention is:

[0007] A comprehensive screening method for atmospheric CO2 and CH4 background concentrations comprises the following steps:

[0008] S1. Data collection: Collect greenhouse gas observation data and meteorological observation data;

[0009] S2. Data processing: Processing the collected greenhouse gas observation data and meteorological data, including eliminating the collected abnormal data and processing the greenhouse gas concentration observation data after elimination for data completeness, monthly average greenhouse gas concentration by wind direction, monthly average greenhouse gas concentration in sixteen wind directions, monthly standard deviation of greenhouse gas concentration in sixteen wind directions, monthly average greenhouse gas concentration and monthly standard deviation of greenhouse gas concentration;

[0010] S3, comprehensive background screening: Based on the data processed in step S2, the robust local regression screening method and meteorological screening method are used to comprehensively screen the atmospheric CO2 and CH4 background concentrations, which includes:

[0011] S31, robust local regression screening method: Use robust local regression algorithm to screen the effective observation data of CO2 or CH4 for background. Combined with the seasonal variation of atmospheric CO2 concentration, the bandwidth value is set. After iterative calculation, the fitting curve converges and the scale parameter δ is calculated. The observation data between the fitting value ±δ is screened as the background value, and the remaining data is the local value.

[0012] S32. Meteorological screening method: After robust local regression screening, the influence of atmospheric stability, wind speed and wind direction on the sources and sinks of greenhouse gases is comprehensively considered; atmospheric stability judgment, wind direction and concentration judgment, wind speed judgment and outlier judgment are carried out in sequence to finally achieve the screening of atmospheric CO2 and CH4 concentrations.

[0013] Furthermore, the calculation process of the data integrity rate in step S2 is that the time resolution of the CO2 and CH4 concentration observation data is hourly, and the total data and monthly data integrity rates must reach more than 95%; and the missed measurements due to instrument failure, shutdown, and system maintenance are not counted when calculating the data integrity rate.

[0014] Furthermore, the monthly average concentration of greenhouse gases in each wind direction in step S2 is calculated monthly based on the CO2 or CH4 concentration observation data and wind direction data during the observation period, and the average concentration of CO2 or CH4 corresponding to the sixteen azimuth wind directions is calculated by the following method:

[0015]

[0016] Where:

[0017] It indicates the average concentration of CO2 or CH4 in a specific wind direction in a specific month, m indicates January to December, and n indicates wind directions from 1 to 16;

[0018] Indicates the hourly CO2 or CH4 concentration in a specific wind direction in a specific month;

[0019] N m,n Indicates the number of CO2 or CH4 observations participating in the statistics for a specific wind direction in a specific month.

[0020] Furthermore, the atmospheric stability determination in step S32 is a determination of the remaining CO2 or CH4 concentration observations after robust local regression screening, which is to first classify the atmospheric stability based on the calculation of the gradient Richardson number and the stability determination scheme, and then use the Pasquier-Ternaud method to classify the stability when the meteorological data cannot satisfy the calculation of the gradient Richardson number; if the stability grade is neutral, relatively stable and stable, the CO2 or CH4 observation data at the corresponding time is screened as a local value; finally, when the meteorological data cannot satisfy the Pasquier-Ternaud stability and gradient Richardson number calculation, the CO2 or CH4 observation data of the period with relatively uniform mixing is directly screened empirically to participate in the background screening, and the CO2 or CH4 observation data of the period other than the daily period with relatively uniform mixing is screened as a local value.

[0021] Furthermore, the wind direction and concentration determination in step S32 is a determination made on the remaining CO2 or CH4 concentration observations after robust local regression screening and atmospheric stability determination, which is based on the hourly wind direction data of the CO2 or CH4 observation period, and the monthly average concentration of CO2 or CH4 by wind direction is calculated. Average wind direction concentration for the 16th day of each month Standard deviation of wind direction concentration for the 16th day of each month σ m,1-16 , for m month n wind direction, if The observed CO2 or CH4 concentration values ​​in that wind direction for that month are screened as local values.

[0022] Furthermore, in step S32, the wind speed is determined after robust local regression screening, atmospheric stability determination, and wind direction and concentration determination, and the remaining CO2 or CH4 concentration observation values ​​are further determined based on the wind speed threshold, which is to combine the hourly wind speed data of the same period of CO2 or CH4 observation, and screen the CO2 or CH4 observation concentration values ​​corresponding to the moments when the wind speed is less than 1.5 m / s as local values.

[0023] Furthermore, the abnormal value determination in step S32 is to calculate the average value on a monthly basis for the remaining CO2 or CH4 concentration observations after robust local regression screening, atmospheric stability determination, wind direction and concentration determination, and wind speed determination. Calculate the standard deviation σ month by month m , for a certain moment, if The data at that moment is screened into local values, and the remaining data is the background value of CO2 or CH4 concentration.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] The present invention combines the scheme of mathematical statistics robust local regression screening method and meteorological screening method to form a screening algorithm suitable for major greenhouse gases such as regional CO2 and CH4, which is suitable for evaluating the spatiotemporal variation of greenhouse gases and their impact on climate. It is recommended for use by meteorological, ecological and environmental, colleges and universities and other business and research departments engaged in greenhouse gas concentration observation and analysis. This screening method fills the gap in greenhouse gas background concentration screening technology and can provide scientific technical support for relevant departments to formulate effective development plans and action plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of background screening of the present invention. DETAILED DESCRIPTION

[0027] The following is a detailed description of the implementation of the present invention in conjunction with the accompanying drawings, but they do not constitute a limitation of the present invention and are only given as examples. At the same time, the advantages of the present invention are made clearer and easier to understand through the description.

[0028] like Figure 1 As shown, a comprehensive screening method for atmospheric CO2 and CH4 background concentrations comprises the following steps:

[0029] S1. Data collection: Collect greenhouse gas observation data and meteorological observation data;

[0030] S2. Data processing: Processing the collected greenhouse gas observation data and meteorological data, including eliminating the collected abnormal data and processing the greenhouse gas concentration observation data after elimination for data completeness, monthly average greenhouse gas concentration by wind direction, monthly average greenhouse gas concentration in sixteen wind directions, monthly standard deviation of greenhouse gas concentration in sixteen wind directions, monthly average greenhouse gas concentration and monthly standard deviation of greenhouse gas concentration;

[0031] S21. Data completeness rate: The time resolution of CO2 and CH4 concentration observation data used for background screening is hourly, and the total data and monthly data completeness rates must reach more than 95%; and the missed measurements due to instrument failure, shutdown, and system maintenance are not counted when calculating the data completeness rate.

[0032] S22. Average concentration of greenhouse gases by wind direction on a monthly basis: Based on the CO2 or CH4 concentration observation data and wind direction data during the observation period, the average concentration of CO2 or CH4 corresponding to the 16 wind directions is calculated on a monthly basis. The azimuths, symbols, center angles, angle ranges and calm wind standards corresponding to the 16 wind directions are shown in Table 1. The calculation method for the average concentration of greenhouse gases by wind direction on a monthly basis is shown in Formula (1):

[0033]

[0034] Where:

[0035] It indicates the average concentration of CO2 or CH4 in a specific wind direction in a specific month, m indicates January to December, and n indicates wind directions from 1 to 16;

[0036] Indicates the hourly CO2 or CH4 concentration in a specific wind direction in a specific month;

[0037] N m,n Indicates the number of CO2 or CH4 observations participating in the statistics for a specific wind direction in a specific month.

[0038] Table 1 Wind direction and parameter comparison table

[0039]

[0040]

[0041] Note: Wind speed less than or equal to 0.2m / s is treated as calm wind and is not taken into account in the 16 wind directions.

[0042] S23, monthly average concentration of greenhouse gases in sixteen wind directions: Based on the monthly average concentration of CO2 or CH4 in each wind direction calculated in S22, the monthly average concentration of greenhouse gases in sixteen wind directions is calculated. The calculation method is shown in formula (2):

[0043]

[0044] Where:

[0045] Indicates the average concentration of CO2 or CH4 in sixteen wind directions in a specific month.

[0046] S24, monthly greenhouse gas concentration standard deviation in 16 wind directions: Based on the monthly average concentration of CO2 or CH4 in each wind direction calculated by S23, the monthly standard deviation of the concentration in 16 wind directions is calculated. The calculation method is shown in formula (3):

[0047]

[0048] Where:

[0049] σ m,1-16 Indicates the standard deviation of CO2 or CH4 concentration in sixteen wind directions in a specific month.

[0050] S25. Monthly average greenhouse gas concentration: Based on the CO2 or CH4 concentration observation data during the observation period, the monthly average CO2 or CH4 concentration is calculated. The calculation method is shown in formula (4):

[0051]

[0052] Where:

[0053] Indicates the average concentration of CO2 or CH4 participating in the statistics in a specific month;

[0054] Indicates the hourly CO2 or CH4 concentration participating in the statistics for a specific month;

[0055] N m Indicates the number of CO2 or CH4 observations participating in the statistics in a specific month.

[0056] S26. Monthly greenhouse gas concentration standard deviation: Based on the CO2 or CH4 concentration observation data during the observation period, the CO2 or CH4 concentration standard deviation is calculated monthly. The calculation method is shown in formula (5):

[0057]

[0058] Where:

[0059] σ m Indicates the standard deviation of CO2 or CH4 concentration in a specific month.

[0060] S3, comprehensive background screening: Based on the data processed in step S2, the robust local regression screening method and meteorological screening method are used to comprehensively screen the atmospheric CO2 and CH4 background concentrations, which includes:

[0061] S31. Robust local regression screening method: Based on the robust local regression algorithm, the effective observation data of CO2 or CH4 are screened for background, and the observed concentration value is defined as formula (6). Assume that C obs is continuous, a local linear regression model can be used to obs So at any given time t0, in a small enough neighborhood, we can assume that C obs (t i ) is a straight line, and the number near t0 can be obtained by the least square method. Considering the seasonal variation of atmospheric CO2 concentration, the bandwidth is set to 60 days (1440 hours). After iterative calculation, the fitting curve converges, and the scale parameter δ is calculated. The observation data between the fitting value ±δ is screened as background value, and the rest of the data is local value.

[0062] C obs (t i )=C bg (t i )+C Δ (t i )+E i (6)

[0063] Where:

[0064] C obs (t i ) represents the observed value of CO2 or CH4 concentration;

[0065] C bg (t i ) represents the background concentration value of CO2 or CH4;

[0066] C Δ (t i ) represents the contribution of local sources and sinks;

[0067] E i represents the observation error.

[0068] S32. Meteorological screening method: After robust local regression screening, the influence of atmospheric stability, wind speed and wind direction on greenhouse gas sources and sinks is comprehensively considered; the four steps of atmospheric stability determination, wind direction and concentration determination, wind speed determination and outlier determination are carried out in sequence to finally achieve the screening of atmospheric CO2 and CH4 concentrations.

[0069] S321. Atmospheric stability determination: After robust local regression screening, the atmospheric stability determination is performed on the remaining CO2 or CH4 concentration observations. Based on the meteorological data of the same period of CO2 or CH4 observation, the atmospheric mixing capacity can be determined by using the gradient Richardson number, Pasquier-Ternaud or mixing period determination method according to the data conditions. Specifically:

[0070] S3211. Determination of gradient Richardson number: The gradient Richardson number Ri at each moment is calculated using the temperature, air pressure, wind speed and wind direction on the ground and within the atmospheric boundary layer, and the atmospheric stability is graded according to the atmospheric stability grade classification based on the gradient Richardson number in Table 2 below. A, B, C, D, E and F represent strong instability, instability, weak instability, neutral, relatively stable and stable, respectively. The calculation method of the gradient Richardson number is shown in formula (7) and formula (8):

[0071]

[0072] Where:

[0073] g represents the acceleration due to gravity, which is 9.8 m / s 2 ;

[0074] Z1 represents the low-level observation height (m);

[0075] Z2 represents the high-level observation height (m);

[0076] θ1 represents the lower layer potential temperature (K);

[0077] θ2 represents the high-level potential temperature (K);

[0078] V1 represents the low-level wind speed (m / s);

[0079] V2 represents the upper-level wind speed (m / s);

[0080] θ a Indicates the average potential temperature of the lower and upper layers (K);

[0081] θ represents potential temperature (K);

[0082] T represents the temperature (K);

[0083] P represents air pressure (hPa);

[0084] P O Indicates standard atmospheric pressure, 1000hPa;

[0085] k d represents a constant, taking 0.286.

[0086] Table 1 Classification of atmospheric stability based on gradient Richardson number

[0087] Stability level Ri range A Ri<-3.433 B -3.433≤Ri<-1.375 C -1.375≤Ri<-0.233 D -0.233≤Ri<0.145 E 0.145≤Ri<0.636 F 0.636≤Ri

[0088] S3212, Pasquier-Ternaud stability: If the meteorological data cannot meet the calculation of the gradient Richardson number, the Pasquier-Ternaud stability is calculated and classified according to the method in GB / T 3840. If the stability level is D, E, or F, the CO2 or CH4 observation data at the corresponding time is screened as a local value. The Pasquier-Ternaud stability classification method is used to classify the atmospheric stability level using the hourly cloud cover and wind speed data. First, the solar altitude angle at each moment is calculated, and the solar radiation level is determined in combination with the cloud cover data; then the atmospheric stability level is determined in combination with the solar radiation level and the ground wind speed. It can be divided into six levels: strongly unstable, unstable, weakly unstable, neutral, relatively stable, and stable, represented by A, B, C, D, E, and F, respectively.

[0089] S3213, Mixing period determination: If the meteorological data cannot meet the Pasquier-Turnell stability and gradient Richardson number calculations, then the CO2 or CH4 observation data of the mixing period with relatively uniform mixing can be directly screened to participate in the background screening, and the CO2 or CH4 observation data of the period outside the daily mixing period with relatively uniform mixing can be screened as local values. For example, in southern Jiangsu and other regions of my country, the period from 08:00 to 18:00 Beijing time can be used as the direct screening period for relatively uniform mixing. This period takes into account the basic characteristics of the daily variation of the atmospheric boundary layer in different seasons under the subtropical monsoon conditions, and can retain the observation data with relatively strong turbulent exchange and relatively uniform greenhouse gas mixing to participate in the background screening to the greatest extent, and the CO2 or CH4 observation data from 18:00 to 8:00 the next day Beijing time can be screened as local values.

[0090] S322. Wind direction and concentration determination: After robust local regression screening and atmospheric stability determination, the remaining CO2 or CH4 concentration observations are further determined based on wind direction and concentration.

[0091] Combined with the hourly wind direction data of CO2 or CH4 observation during the same period, calculate the monthly average concentration of CO2 or CH4 by wind direction according to step S22 According to step S23, the average concentration of the sixteen wind directions per month is calculated According to step S24, the standard deviation σ of the wind direction concentration for each month is calculated. m,1-16 , for m month n wind direction, if The observed CO2 or CH4 concentration values ​​in that wind direction for that month are screened as local values.

[0092] S323, wind speed determination: After robust local regression screening, atmospheric stability determination, and wind direction and concentration determination, the remaining CO2 or CH4 concentration observations are further determined based on the wind speed threshold.

[0093] Combined with the hourly wind speed data during the CO2 or CH4 observation period, the CO2 or CH4 observation concentration values ​​corresponding to the moments when the wind speed was less than 1.5 m / s (level 1 wind) were screened as local values.

[0094] S324, outlier determination: After robust local regression screening, atmospheric stability determination, wind direction and concentration determination, and wind speed determination, the remaining CO2 or CH4 concentration observations are averaged based on the monthly calculation. Calculate the standard deviation σ month by month m , for a certain moment, if The data at that moment is screened into local values, and the remaining data is the background value of CO2 or CH4 concentration.

[0095] In this embodiment, the wind direction and concentration determination and wind speed determination are intended to further eliminate the influence of local sources and sinks. The wind direction and concentration determination is based on the concentration of greenhouse gases in the wind direction of the sixteen directions to determine the possible sources and sinks around the observation position, and all data on the high-impact wind direction are eliminated. The wind speed determination is based on the basic theory that CO2 and CH4 concentrations are more susceptible to local influences under calm and light wind conditions, and the concentration observation data of wind speeds below level 0 to 1 are eliminated. The data processing window is monthly, which is based on the existing and future long-term series monitoring needs and the seasonal variation laws of natural vegetation in many parts of my country, in order to cope with more complex agricultural farming, industrial production and energy consumption and other human activities that affect the concentration of atmospheric CO2 and CH4. The time variation characteristics of these income and expenditure items are significantly shorter than the seasonal variation of natural terrestrial ecosystems. The outlier determination is formulated to eliminate a small number of high concentration values ​​that appear under higher wind speeds. These values ​​are often hidden in the low-concentration directions in summer. Atmospheric stability determination, wind direction and concentration determination, and wind speed determination may occasionally miss the situation of identification.

[0096] The screening method of the present invention combines the scheme of mathematical statistical robust local regression screening method and meteorological screening method to form a screening algorithm suitable for major greenhouse gases such as regional carbon dioxide and methane, which is suitable for evaluating the spatiotemporal variation of greenhouse gases and their impact on climate. It is recommended for use by business and research departments such as meteorology, ecological environment, and colleges and universities engaged in greenhouse gas concentration observation and analysis. This screening method fills the gap in greenhouse gas background concentration screening technology and can provide scientific technical support for relevant departments to formulate effective development plans and action plans.

[0097] It should be pointed out that the scale parameter δ is calculated in the robust local regression screening method mentioned in step S31 of the present invention. The detailed calculation method can be found in the document Ruckstuhl AF, Henne S, Reimann S, et al. Robustextraction of baseline signal of atmospheric trace species using localregression. Atmospheric Measurement Techniques, 2012, 5: 2613–2624.

[0098] The present invention is not limited to the above-mentioned specific implementation modes. For ordinary technicians in this field, various changes made based on the above-mentioned conception without creative work all fall within the protection scope of the present invention.

Claims

1. A comprehensive screening method for atmospheric CO2 and CH4 background concentrations, characterized in that: The following steps are involved: S1. Data collection: Collect greenhouse gas observation data and meteorological observation data; S2. Data processing: Processing the collected greenhouse gas observation data and meteorological data, including eliminating the collected abnormal data and processing the greenhouse gas concentration observation data after elimination for data completeness, monthly average greenhouse gas concentration by wind direction, monthly average greenhouse gas concentration in sixteen wind directions, monthly standard deviation of greenhouse gas concentration in sixteen wind directions, monthly average greenhouse gas concentration and monthly standard deviation of greenhouse gas concentration; S3, comprehensive background screening: Based on the data processed in step S2, the robust local regression screening method and meteorological screening method are used to comprehensively screen the atmospheric CO2 and CH4 background concentrations, which includes: S31, robust local regression screening method: Use robust local regression algorithm to screen the effective observation data of CO2 or CH4 for background. Combined with the seasonal variation of atmospheric CO2 concentration, the bandwidth value is set. After iterative calculation, the fitting curve converges and the scale parameter δ is calculated. The observation data between the fitting value ±δ is screened as the background value, and the remaining data is the local value. S32. Meteorological screening method: After robust local regression screening, the influence of atmospheric stability, wind speed and wind direction on the sources and sinks of greenhouse gases is comprehensively considered; atmospheric stability judgment, wind direction and concentration judgment, wind speed judgment and outlier judgment are carried out in sequence to finally achieve the screening of atmospheric CO2 and CH4 concentrations.

2. A comprehensive screening method for atmospheric CO2 and CH4 background concentrations according to claim 1, characterized in that: The calculation process of the data integrity rate in step S2 is that the time resolution of the CO2 and CH4 concentration observation data is hourly, and the total data and monthly data integrity rates must reach more than 95%; and the missed measurements due to instrument failure, shutdown, and system maintenance are not counted when calculating the data integrity rate.

3. A comprehensive screening method for atmospheric CO2 and CH4 background concentrations according to claim 1, characterized in that: The monthly average concentration of greenhouse gases in each wind direction in step S2 is calculated based on the CO2 or CH4 concentration observation data and wind direction data during the observation period, and the average concentration of CO2 or CH4 corresponding to the sixteen azimuth wind directions is calculated monthly. The calculation method is: Where: It indicates the average concentration of CO2 or CH4 in a specific wind direction in a specific month, m indicates January to December, and n indicates wind directions from 1 to 16; Indicates the hourly CO2 or CH4 concentration in a specific wind direction in a specific month; N m,n Indicates the number of CO2 or CH4 observations participating in the statistics for a specific wind direction in a specific month.

4. A comprehensive screening method for atmospheric CO2 and CH4 background concentrations according to claim 1, characterized in that: The atmospheric stability determination in step S32 is a determination of the remaining CO2 or CH4 concentration observations after robust local regression screening, which is to first classify the atmospheric stability based on the calculation of the gradient Richardson number and the stability determination scheme, and then use the Pasquier-Ternaud method to classify the stability when the meteorological data cannot satisfy the calculation of the gradient Richardson number; if the stability level is neutral, relatively stable, and stable, the CO2 or CH4 observation data at the corresponding time is screened as a local value; finally, when the meteorological data cannot satisfy the Pasquier-Ternaud stability and gradient Richardson number calculation, the CO2 or CH4 observation data of the period with relatively uniform mixing is directly screened empirically to participate in the background screening, and the CO2 or CH4 observation data of the period other than the daily period with relatively uniform mixing is screened as a local value.

5. A comprehensive screening method for atmospheric CO2 and CH4 background concentrations according to claim 1, characterized in that: The wind direction and concentration determination in step S32 is a determination made on the remaining CO2 or CH4 concentration observations after robust local regression screening and atmospheric stability determination. It is based on the hourly wind direction data of the CO2 or CH4 observation period, and the monthly average wind direction concentration of CO2 or CH4 is calculated. Average wind direction concentration for the 16th day of each month Standard deviation of wind direction concentration for the 16th day of each month σ m,1-16 , for m month n wind direction, if The observed CO2 or CH4 concentration values ​​in that wind direction for that month are screened as local values.

6. A comprehensive screening method for atmospheric CO2 and CH4 background concentrations according to claim 1, characterized in that: In step S32, the wind speed is determined by robust local regression screening, atmospheric stability determination, and wind direction and concentration determination, and the remaining CO2 or CH4 concentration observation values ​​are further determined based on the wind speed threshold; combined with the hourly wind speed data of the same period of CO2 or CH4 observation, the CO2 or CH4 observation concentration values ​​corresponding to the moments when the wind speed is less than 1.5 m / s are screened as local values.

7. A comprehensive screening method for atmospheric CO2 and CH4 background concentrations according to claim 1, characterized in that: The abnormal value determination in step S32 is to calculate the average value of the remaining CO2 or CH4 concentration after robust local regression screening, atmospheric stability determination, wind direction and concentration determination and wind speed determination. Calculate the standard deviation σ month by month m , for a certain moment, if The data at that moment is screened into local values, and the remaining data is the background value of CO2 or CH4 concentration.

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