Fine particulate matter concentration calculation method based on actually measured visibility and relative humidity

Abstract

The embodiment of the invention provides a fine particulate matter concentration calculation method based on actually measured visibility and relative humidity, and is applied to the technical field of meteorological prediction. The method comprises the following steps: determining an aerosol extinction coefficient of a visible light wave band based on historical data; extracting particle size spectrum distribution characteristics of dry aerosol particles on a site corresponding to the numerical mode chemical field and a hygroscopic parameter kappa of fine particle aerosol; aiming at the dry and wet parts, the complex refractive index of the environmental aerosol particles is obtained; on the basis of the Mie scattering theory and the aerosol extinction coefficient of the visible light wave band, the actually measured visibility is obtained, and the aerosol fine particle mass concentration corresponding to the site is obtained through inversion. Development of aerosol extinction coefficient tangent linearity and adjoint operators in an assimilation system is avoided, the calculation efficiency is improved, existing aerosol particle size spectrum distribution in a mode chemical field is comprehensively utilized, it is ensured that the relation between aerosol chemical components and extinction coefficients in actual measurement and modes is kept consistent, and the accuracy of aerosol particle size spectrum distribution is improved. And more reasonable assimilation and forecasting effects are realized.

Description

Technical Field

[0001] The present disclosure relates to the technical field of meteorological forecasting, and in particular to a method, device, equipment and storage medium for calculating fine particulate matter concentration based on measured visibility and relative humidity. Background Art

[0002] Atmospheric aerosols have a significant impact on air quality, climate change and human health. Accurate simulation and forecasting of aerosols play a very important role in the analysis of the spatiotemporal evolution characteristics of atmospheric pollution processes, the study of internal mechanisms, the tracing of pollutants, and the support of prevention and control.

[0003] Most of the aerosol models in the current atmospheric chemistry models are constructed based on aerosol chemical components (the total mass is the aerosol mass concentration). In order to realize the conversion between directly observed variables and model control variables, the variational assimilation model will include "observation operators" to realize the conversion between aerosol optical property observations and chemical components.

[0004] In order to achieve the assimilation of aerosol optical property observation data, the conversion relationship between the measured aerosol extinction coefficient and the measured aerosol fine particle mass concentration is often established by measuring the aerosol optical property and chemical property in situ at the same site. The measured aerosol extinction coefficient is converted into the aerosol fine particle mass concentration. The aerosol fine particle mass concentration is then used for the assimilation of the atmospheric chemical variational assimilation model.

[0005] However, in the above existing processing process, the required computing resources are relatively high, and there are also problems with the regional applicability of the obtained aerosol mass concentration inversion results. Summary of the invention

[0006] The present disclosure provides a method, device, equipment and storage medium for calculating fine particulate matter concentration based on measured visibility and relative humidity.

[0007] According to a first aspect of the present disclosure, a method for calculating fine particulate matter concentration based on measured visibility and relative humidity is provided, the method comprising:

[0008] Based on the historical data of visibility observation and humidity observation at the site, the aerosol extinction coefficient in the visible light band is determined;

[0009] Extract the particle size spectrum distribution characteristics of dry aerosol particles at the corresponding station of the numerical model chemical field, and determine the fine particle aerosol hygroscopicity parameter κ based on the particle size spectrum distribution characteristics of dry aerosol particles;

[0010] Based on the preset single-parameter κ-Kora equation, the measured relative humidity is selected and the aerosol particle size after moisture absorption growth of multiple particle size segments is iteratively obtained;

[0011] Based on the preset complex refractive index of dry aerosol particles and the complex refractive index of water, a volume-weighted average is performed on the dry and wet parts to obtain the complex refractive index of the ambient aerosol particles;

[0012] Based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, according to the preset algorithm corresponding to the Mie scattering theory and the aerosol extinction coefficient of the visible light band, the visibility based on the measured relative humidity is obtained. Combined with the fine particle mass concentration of the model and the measured visibility, the aerosol fine particle mass concentration corresponding to the site is iteratively obtained.

[0013] In some implementations of the first aspect, determining the fine particle aerosol hygroscopicity parameter κ based on the particle size spectrum distribution characteristics of the dry aerosol particles includes:

[0014] Based on the particle size distribution characteristics of dry aerosol particles, combined with the hygroscopicity parameter κ corresponding to each aerosol chemical component i The mass concentration of chemical components C i Take the weighted average to obtain the aerosol hygroscopic parameter κ, which satisfies the formula:

[0015]

[0016] Where n is the number of chemical components in the aerosol.

[0017] In some implementations of the first aspect, based on the aerosol particle size after moisture absorption growth and the complex refractive index of the ambient aerosol particles, according to a preset algorithm corresponding to the Mie scattering theory and the aerosol extinction coefficient of the visible light band, visibility based on the measured relative humidity is obtained, and the fine particle mass concentration of the model and the measured visibility are combined to iteratively obtain the aerosol fine particle mass concentration corresponding to the site, including:

[0018] Based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, the extinction coefficient cross sections of multiple particle sizes are calculated according to the algorithm corresponding to the preset Mie scattering theory, the number of particles is integrated to obtain the extinction coefficients of multiple particle sizes, and the extinction coefficients of multiple particle sizes are summed to obtain the aerosol extinction coefficient b on the corresponding model grid point under the actual humidity conditions of the site. model ;

[0019] Based on the aerosol extinction coefficient in the visible light band and the aerosol extinction coefficient b on the model grid point model , visibility based on the measured relative humidity is obtained, and the aerosol fine particle mass concentration corresponding to the station is iteratively obtained by combining the model's fine particle mass concentration and the measured visibility.

[0020] In some implementations of the first aspect, based on the aerosol extinction coefficient in the visible light band and the aerosol extinction coefficient b on the pattern grid pointmodel , obtain the visibility based on the measured relative humidity, combine the model fine particle mass concentration and the measured visibility, and iterate to obtain the aerosol fine particle mass concentration corresponding to the station, including:

[0021] Under the assumption that the aerosol density remains constant, the number of particles in each particle size segment is iterated in equal proportion so that the extinction coefficient b on the model grid point model The difference between the aerosol extinction coefficient in the visible light band and the aerosol extinction coefficient in the visible light band is less than a preset value, and the mass concentration of aerosol fine particles corresponding to the inverted site is obtained.

[0022] In some implementations of the first aspect, the method further includes:

[0023] By iterating the number of particles in each particle size segment in equal proportion, the extinction coefficient b on the pattern grid point is model The difference between the aerosol extinction coefficient in the visible light band and the aerosol extinction coefficient in the visible light band is less than a preset value, and the model aerosol mass concentration is determined based on the number of aerosol particles according to a preset transformation rule to obtain the inverted aerosol fine particle mass concentration.

[0024] In some implementations of the first aspect, the aerosol extinction coefficient in the visible light band is obtained by measuring visibility, and factors affecting visibility include the sum of the extinction coefficients of atmospheric aerosol particles, gas molecules, fog droplets, and raindrops.

[0025] In some implementations of the first aspect, the aerosol chemical components include at least one of black carbon, organic carbon, sulfate, nitrate, ammonium salt, sodium salt and chloride salt.

[0026] According to a second aspect of the present disclosure, there is provided a device for calculating fine particulate matter concentration based on measured visibility and relative humidity, the device comprising:

[0027] A determination module is used to determine the aerosol extinction coefficient in the visible light band based on the historical data of the site visibility observation and humidity observation;

[0028] The determination module is also used to extract the particle size spectrum distribution characteristics of the dry aerosol particles at the corresponding station of the numerical model chemical field, and determine the fine particle aerosol hygroscopicity parameter κ based on the particle size spectrum distribution characteristics of the dry aerosol particles;

[0029] An iterative module is used to select the measured relative humidity based on the preset single-parameter κ-Kolla equation, and iteratively obtain the aerosol particle size after moisture absorption growth of multiple particle size segments;

[0030] A processing module, configured to perform volume weighted averaging on the dry and wet parts based on the preset complex refractive index of the dry aerosol particles and the complex refractive index of water, so as to obtain the complex refractive index of the ambient aerosol particles;

[0031] The processing module is also used to obtain visibility based on the measured relative humidity based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, according to the algorithm corresponding to the preset Mie scattering theory and the aerosol extinction coefficient of the visible light band, and iteratively obtain the aerosol fine particle mass concentration corresponding to the site in combination with the model's fine particle mass concentration and the measured visibility.

[0032] According to a third aspect of the present disclosure, an electronic device is provided. The electronic device includes: a memory and a processor. The memory stores a computer program. When the processor executes the program, the method of the first aspect of the present disclosure is implemented.

[0033] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method of the first aspect of the present disclosure is implemented.

[0034] The present disclosure determines the aerosol extinction coefficient in the visible light band based on historical data; extracts the particle size spectrum distribution characteristics of dry aerosol particles at the corresponding station of the numerical model chemical field, as well as the fine particle aerosol hygroscopicity parameter κ; obtains the complex refractive index of environmental aerosol particles for the dry and wet parts; obtains the visibility based on the measured relative humidity based on the Mie scattering theory and the aerosol extinction coefficient in the visible light band, and iteratively obtains the aerosol fine particle mass concentration corresponding to the station by combining the fine particle mass concentration of the model and the measured visibility. It avoids developing the aerosol extinction coefficient tangent and adjoint operator in the assimilation system, improves the calculation efficiency, comprehensively utilizes the existing aerosol particle size spectrum distribution in the model chemical field, ensures that the relationship between the aerosol chemical components and the extinction coefficient in the measured and model is consistent, improves the initial aerosol field of the model, and improves the aerosol forecast level, thereby achieving a more reasonable assimilation and forecasting effect.

[0035] It should be understood that the contents described in the summary of the invention are not intended to limit the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, among which:

[0037] Figure 1 A schematic flow chart of a method for calculating fine particulate matter concentration based on measured visibility and relative humidity according to an embodiment of the present disclosure is shown;

[0038] Figure 2 A block diagram of a device for calculating fine particulate matter concentration based on measured visibility and relative humidity according to an embodiment of the present disclosure is shown;

[0039] Figure 3 A block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0041] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0042] In the present disclosure, in order to solve the above technical problems, the aerosol extinction coefficient in the visible light band is determined based on historical data; the particle size spectrum distribution characteristics of dry aerosol particles at the corresponding station of the numerical model chemical field and the fine particle aerosol hygroscopicity parameter κ are extracted; for the dry and wet parts, the complex refractive index of the environmental aerosol particles is obtained; based on the Mie scattering theory and the aerosol extinction coefficient in the visible light band, the visibility based on the measured relative humidity is obtained, and the fine particle mass concentration of the model and the measured visibility are combined to iteratively obtain the aerosol fine particle mass concentration corresponding to the station. It avoids the development of aerosol extinction coefficient tangent and adjoint operators in the assimilation system, improves the calculation efficiency, and comprehensively utilizes the existing aerosol particle size spectrum distribution in the model chemical field, ensuring that the relationship between the aerosol chemical components and the extinction coefficient in the measured and model remains consistent, achieving a more reasonable assimilation and forecasting effect.

[0043] Figure 1 FIG. 1 is a flow chart of a method for calculating fine particulate matter concentration based on measured visibility and relative humidity according to an embodiment of the present disclosure, as shown in FIG. Figure 1 As shown, the method 100 for calculating the concentration of fine particulate matter based on measured visibility and relative humidity may include:

[0044] S101, determine the aerosol extinction coefficient in the visible light band based on the historical data of site visibility observations and humidity observations.

[0045] It should be noted that visibility is the sum of the extinction effects of aerosols, clouds / fog droplets, and gas molecules in the atmosphere. Under normal circumstances, the scattering effect of dry and clean atmospheric molecules and the absorption effect of nitrogen dioxide can be ignored compared with the extinction effect of aerosols. Under certain relative humidity conditions, the presence of cloud droplets can be ignored. Therefore, under certain conditions, the main factor causing the decrease in atmospheric visibility is aerosols. The aerosol extinction coefficient is specifically the sum of the scattering coefficient and the absorption coefficient. In general areas, the particle scattering coefficient is much larger than the absorption coefficient, that is, relative to the aerosol scattering coefficient, the absorption effect contributes less to the extinction effect of aerosols. Therefore, at present, in the meteorological visibility observation business, a forward scattering visibility meter is used to measure the scattered light intensity at a specific angle, and the total scattering coefficient is determined based on the relationship between it and the total scattering. Since light propagates in a short distance, the effect of absorption is ignored, and visibility is obtained using total scattering. Therefore, according to Koschmieder's law:

[0046]

[0047] In formula (1), V is visibility in km, and the unit of scattering coefficient is km -1 . The extinction coefficient is the sum of the extinction coefficients of atmospheric aerosol particles, gas molecules, fog droplets / raindrops, etc. Excluding precipitation weather, when the relative humidity is lower than a certain threshold (such as 80%-95%, depending on the measurement accuracy and representativeness of the relative humidity), the possibility of fog droplets appearing in the atmosphere is very small. Compared with the aerosol extinction coefficient, the extinction effect of gas molecules can be ignored. Therefore, when the relative humidity is lower than a certain threshold, the atmospheric extinction is mainly caused by aerosol particles. At this time, in a specific embodiment, b(550nm) can be regarded as the aerosol extinction coefficient.

[0048] S102, extracting the particle size spectrum distribution characteristics of the dry aerosol particles at the corresponding station of the numerical model chemical field, and determining the fine particle aerosol hygroscopicity parameter κ based on the particle size spectrum distribution characteristics of the dry aerosol particles.

[0049] In some embodiments, in order to accurately obtain the fine particle aerosol hygroscopicity parameter κ, the above-mentioned determination of the fine particle aerosol hygroscopicity parameter κ based on the particle size spectrum distribution characteristics of the dry aerosol particles may specifically include:

[0050] Based on the particle size distribution characteristics of dry aerosol particles, combined with the hygroscopicity parameter κ corresponding to each aerosol chemical component i The mass concentration of chemical components C i Taking the weighted average, we get the aerosol hygroscopic parameter κ, which satisfies formula (2):

[0051]

[0052] In formula (2), n is the number of chemical components in the aerosol.

[0053] In the above embodiment, based on the particle size spectrum distribution characteristics of the dry aerosol particles, combined with the hygroscopicity parameter κ corresponding to each aerosol chemical component, the above formula is used. i The mass concentration of chemical components C i By taking the weighted average, the fine particle aerosol hygroscopicity parameter κ can be accurately obtained.

[0054] It should also be noted that the aerosol module in the atmospheric chemistry model generally gives an assumption on the aerosol particle size spectrum distribution, and each grid point has a corresponding aerosol chemical component. If the longitude and latitude of the station are known, the grid point corresponding to the measured station can be obtained by the nearest distance method. For example, the MOSAIC aerosol scheme uses particle size segment (bin) aerosol particle size spectrum distribution, such as 4 bins (0.039-0.1, 0.1-1.0, 1.0-2.5, and 2.5-10μm). Each particle size segment can contain 8 aerosol chemical components (black carbon, organic carbon, sulfate, nitrate, ammonium salt, sodium salt, chloride salt, and other inorganic salts), that is, the above n can be 8. In addition, each bin has a specific particle size and number of particles, which can describe the aerosol particle size spectrum distribution characteristics of the grid point. Each specific aerosol chemical component has a specific hygroscopicity parameter κ i , the mass concentration of chemical components C i By taking the weighted average, the aerosol hygroscopic parameter κ of the grid point can be obtained, as shown in formula (2).

[0055] Afterwards, based on the above description and formula (2), multiple particle sizes and corresponding particle numbers corresponding to the measured visibility sites can be extracted, that is, S103-S105 are executed.

[0056] S103, based on the preset single-parameter κ-Kolla equation, the measured relative humidity is selected, and the aerosol particle sizes after moisture absorption growth of multiple particle size segments are obtained by iteration.

[0057] It should be noted that the aerosol particle size after moisture absorption growth of multiple particle size segments iteratively obtained in S103 is one of the important input variables for the subsequent calculation of the aerosol extinction coefficient based on the algorithm corresponding to the Mie scattering theory.

[0058] S104, based on the preset complex refractive index of dry aerosol particles and the complex refractive index of water, a volume weighted average is performed on the dry and wet parts to obtain the complex refractive index of the ambient aerosol particles.

[0059] Specifically, the preset complex refractive index of dry aerosol particles can be selected from empirical reference values ​​such as 1.55-0.04i; the preset complex refractive index of water can be selected from empirical reference values ​​1.33-0.0i. For the dry and wet parts, the volume-weighted average is taken to obtain the complex refractive index of the ambient aerosol particles, so as to obtain another important input variable for the subsequent calculation of the aerosol extinction coefficient based on the algorithm corresponding to the Mie scattering theory.

[0060] After obtaining the two input variables for calculating the aerosol extinction coefficient, the calculation can be performed, that is, S105 is executed.

[0061] S105, based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, according to the preset algorithm corresponding to the Mie scattering theory and the aerosol extinction coefficient in the visible light band, obtains the visibility based on the measured relative humidity, combines the fine particle mass concentration of the model and the measured visibility, and iteratively obtains the aerosol fine particle mass concentration corresponding to the site.

[0062] In some embodiments, in order to accurately invert the mass concentration of aerosol fine particles corresponding to the site, the above-mentioned aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles are obtained according to the preset algorithm corresponding to the Mie scattering theory and the aerosol extinction coefficient in the visible light band, and the visibility based on the measured relative humidity is obtained. The fine particle mass concentration of the model and the measured visibility are combined to iteratively obtain the mass concentration of aerosol fine particles corresponding to the site, which may include:

[0063] Based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, the extinction coefficient cross-sections of multiple particle sizes are calculated according to the preset algorithm corresponding to the Mie scattering theory. The extinction coefficients of multiple particle sizes are integrated over the number of particles, and the extinction coefficients of multiple particle sizes are summed to obtain the aerosol extinction coefficient b at the corresponding model grid point under the actual humidity conditions of the site. model , wherein the multiple particle sizes may specifically be 4 particle sizes;

[0064] Aerosol extinction coefficient based on visible light band and aerosol extinction coefficient b on model grid model , visibility based on the measured relative humidity is obtained, and the aerosol fine particle mass concentration corresponding to the station is iteratively obtained by combining the model's fine particle mass concentration and the measured visibility.

[0065] In the above embodiment, the extinction coefficient cross sections of multiple particle sizes are calculated according to the algorithm corresponding to the preset Mie scattering theory, the number of particles is integrated to obtain the extinction coefficients of multiple particle sizes, and the extinction coefficients of multiple particle sizes are summed to obtain the aerosol extinction coefficient b at the corresponding model grid point under the actual humidity conditions of the site. model, and then based on the aerosol extinction coefficient in the visible light band, the measured visibility is iterated to obtain the mass concentration of fine aerosol particles by combining the model to simulate the mass concentration of fine aerosol particles corresponding to the station, and the mass concentration of fine aerosol particles can be accurately inverted.

[0066] In some embodiments, in order to accurately iterate the measured visibility and thus obtain the accurate mass concentration of aerosol fine particles, the aerosol extinction coefficient based on the visible light band and the aerosol extinction coefficient on the model grid are model , obtain the visibility based on the measured relative humidity, combine the fine particle mass concentration of the model and the measured visibility, iterate to obtain the aerosol fine particle mass concentration corresponding to the station, which can include:

[0067] Under the assumption that the aerosol density remains unchanged, the number of particles in each particle size segment is iterated in equal proportion to ensure that the shape of the particle size spectrum remains unchanged, so that the extinction coefficient b on the model grid point model When the difference between the aerosol extinction coefficient in the visible light band and the inverted mass concentration of aerosol fine particles is less than the preset value, the inverted mass concentration of aerosol fine particles is obtained.

[0068] In the above embodiment, the extinction coefficient b on the model grid point is obtained by iterating the number of particles in each particle size segment in equal proportion under the assumption that the aerosol density is constant. model The difference between the aerosol extinction coefficient in the visible light band and the measured visibility is smaller than the preset value, so that the measured visibility can be accurately iterated to obtain the accurate mass concentration of aerosol fine particles.

[0069] In order to obtain the inverted aerosol fine particle mass concentration more accurately, in some embodiments, the number of particles in each particle size segment can be iterated in proportion so that the extinction coefficient b on the pattern grid point is model When the difference between the aerosol extinction coefficient in the visible light band and the model aerosol mass concentration is less than a preset value, the model aerosol mass concentration is determined based on the number of aerosol particles according to a preset transformation rule to obtain the inverted aerosol fine particle mass concentration.

[0070] Among them, the model aerosol mass concentration is determined based on the number of aerosol particles according to a preset transformation rule to obtain the inverted aerosol fine particle mass concentration. Specifically, the model aerosol mass concentration can be amplified accordingly based on the proportional amplification of the aerosol particle number, or reduced accordingly based on the proportional reduction, that is, the inversion result of the aerosol fine particle concentration constrained by the model aerosol chemical composition and particle size spectrum is obtained.

[0071] In the above embodiment, in the process of obtaining the inverted aerosol fine particle mass concentration, the model aerosol mass concentration is determined according to a preset transformation rule based on the number of aerosol particles, so that the inverted aerosol fine particle mass concentration can be accurately obtained.

[0072] In addition, in the actual inversion process, in order to obtain better aerosol fine particle mass concentration inversion products, the optimal chemical component forecast field can be selected, or the analysis field after assimilating the ground aerosol mass concentration can be used.

[0073] In some embodiments, the aerosol extinction coefficient in the visible light band is obtained by measuring visibility, and factors affecting visibility include the sum of the extinction coefficients of atmospheric aerosol particles, gas molecules, fog droplets and raindrops.

[0074] In some embodiments, the aerosol extinction coefficient in the visible light band includes the sum of the scattering coefficient and the absorption coefficient of the atmospheric aerosol particles.

[0075] In some embodiments, the aerosol chemical components include at least one of black carbon, organic carbon, sulfate, nitrate, ammonium salt, sodium salt and chloride salt.

[0076] In the process of S101-S105, the aerosol extinction coefficient in the visible light band is determined based on historical data; the particle size spectrum distribution characteristics of dry aerosol particles at the corresponding station of the numerical model chemical field and the fine particle aerosol hygroscopicity parameter κ are extracted; the complex refractive index of environmental aerosol particles is obtained for the dry and wet parts; based on the Mie scattering theory and the aerosol extinction coefficient in the visible light band, the visibility based on the measured relative humidity is obtained, and the fine particle mass concentration of the model and the measured visibility are combined to iteratively obtain the aerosol fine particle mass concentration corresponding to the station. The development of aerosol extinction coefficient tangent and adjoint operators in the assimilation system is avoided, the calculation efficiency is improved, the existing aerosol particle size spectrum distribution in the model chemical field is comprehensively utilized, and the relationship between the measured and model aerosol chemical components and extinction coefficients is ensured to be consistent, the initial aerosol field of the model is improved, and the aerosol forecast level is improved, thereby achieving a more reasonable assimilation and forecasting effect.

[0077] Moreover, through the scheme disclosed in the present invention, in the air quality detection mode, it is not necessary to develop an aerosol extinction coefficient observation operator, and the aerosol extinction coefficient data can be inverted into aerosol fine particle mass concentration, and the variational assimilation model directly assimilates the aerosol fine particle mass concentration data. In addition, not only the visibility observation data, but also the observation results of other optical property observation equipment, such as laser ceilometer, aerosol lidar, turbidity meter and other optical property observation equipment, combined with the humidity observation data (value or profile) at the same site, can also be used to invert the aerosol fine particle concentration (value or profile) using this method.

[0078] The above is an introduction to the method embodiment. The following is a further explanation of the disclosed solution through an apparatus embodiment.

[0079] Figure 2A block diagram of a device for calculating fine particulate matter concentration based on measured visibility and relative humidity according to an embodiment of the present disclosure is shown.

[0080] like Figure 2 As shown, the fine particulate matter concentration calculation device 200 based on the measured visibility and relative humidity may include:

[0081] A determination module 201 is used to determine the aerosol extinction coefficient in the visible light band based on the site visibility observation and humidity observation history data;

[0082] The determination module 201 is also used to extract the particle size spectrum distribution characteristics of the dry aerosol particles at the corresponding station of the numerical model chemical field, and determine the fine particle aerosol hygroscopicity parameter κ based on the particle size spectrum distribution characteristics of the dry aerosol particles;

[0083] An iteration module 202 is used to select the measured relative humidity based on a preset single-parameter κ-Kolla equation, and iteratively obtain the aerosol particle sizes after moisture absorption growth of multiple particle size segments;

[0084] A processing module 203 is used to perform volume weighted averaging on the dry and wet parts based on the preset complex refractive index of the dry aerosol particles and the complex refractive index of water to obtain the complex refractive index of the ambient aerosol particles;

[0085] The processing module 203 is also used to obtain visibility based on the measured relative humidity based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, according to the preset algorithm corresponding to the Mie scattering theory and the aerosol extinction coefficient in the visible light band, and iteratively obtain the aerosol fine particle mass concentration corresponding to the site in combination with the model fine particle mass concentration and the measured visibility.

[0086] In some embodiments, determining the fine particle aerosol hygroscopicity parameter κ based on the particle size spectrum distribution characteristics of the dry aerosol particles comprises:

[0087] Based on the particle size distribution characteristics of dry aerosol particles, combined with the hygroscopicity parameter κ corresponding to each aerosol chemical component i The mass concentration of chemical components C i Take the weighted average to obtain the aerosol hygroscopic parameter κ, which satisfies the formula:

[0088]

[0089] Where n is the number of chemical components in the aerosol.

[0090] In some embodiments, based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, according to the preset algorithm corresponding to the Mie scattering theory and the aerosol extinction coefficient in the visible light band, the visibility based on the measured relative humidity is obtained, and the fine particle mass concentration of the model and the measured visibility are combined to iteratively obtain the aerosol fine particle mass concentration corresponding to the site, including:

[0091] Based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, the extinction coefficient cross-sections of multiple particle sizes are calculated according to the preset algorithm corresponding to the Mie scattering theory. The extinction coefficients of multiple particle sizes are integrated over the number of particles, and the extinction coefficients of multiple particle sizes are summed to obtain the aerosol extinction coefficient b at the corresponding model grid point under the actual humidity conditions of the site. model ;

[0092] Aerosol extinction coefficient based on visible light band and aerosol extinction coefficient b on model grid model , visibility based on the measured relative humidity is obtained, and the aerosol fine particle mass concentration corresponding to the station is iteratively obtained by combining the model's fine particle mass concentration and the measured visibility.

[0093] In some embodiments, based on the aerosol extinction coefficient in the visible light band and the aerosol extinction coefficient b on the model grid point model , obtain the visibility based on the measured relative humidity, combine the model fine particle mass concentration and the measured visibility, and iterate to obtain the aerosol fine particle mass concentration corresponding to the station, including:

[0094] Under the assumption that the aerosol density remains constant, the number of particles in each particle size segment is iterated in equal proportion so that the extinction coefficient b on the model grid point model If the difference between the aerosol extinction coefficient in the visible light band and the aerosol extinction coefficient in the visible light band is less than the preset value, the mass concentration of aerosol fine particles corresponding to the inverted station is obtained.

[0095] In some embodiments, the processing module 203 is further used to iterate the number of particles in each particle size segment in equal proportion so that the extinction coefficient b on the pattern grid point is model When the difference between the aerosol extinction coefficient in the visible light band and the model aerosol mass concentration is less than a preset value, the model aerosol mass concentration is determined based on the number of aerosol particles according to a preset transformation rule to obtain the inverted aerosol fine particle mass concentration.

[0096] In some embodiments, the aerosol extinction coefficient in the visible light band is obtained by measuring visibility, and factors affecting visibility include the sum of the extinction coefficients of atmospheric aerosol particles, gas molecules, fog droplets and raindrops.

[0097] In some embodiments, the aerosol extinction coefficient in the visible light band includes the sum of the scattering coefficient and the absorption coefficient of the atmospheric aerosol particles.

[0098] In some embodiments, the aerosol chemical components include at least one of black carbon, organic carbon, sulfate, nitrate, ammonium salt, sodium salt and chloride salt.

[0099] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present disclosure is not limited by the order of the actions described, because according to the present disclosure, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present disclosure.

[0100] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0101] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0102] Figure 3 A block diagram of an exemplary electronic device capable of implementing an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0103] The device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0104] A number of components in the device 300 are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0105] The computing unit 301 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 301 performs the various methods and processes described above, such as method 100. For example, in some embodiments, the method 100 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the computing unit 301, one or more steps of the method 100 described above may be performed.

[0106] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0107] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0108] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0109] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0110] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0111] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0112] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of this disclosure can be achieved, and this document is not limited here.

[0113] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for calculating fine particulate matter concentration based on measured visibility and relative humidity, characterized in that: The method comprises: Based on the historical data of visibility observation and humidity observation at the site, the aerosol extinction coefficient in the visible light band is determined; Extract the particle size spectrum distribution characteristics of dry aerosol particles at the corresponding station of the numerical model chemical field, and determine the fine particle aerosol hygroscopicity parameter κ based on the particle size spectrum distribution characteristics of dry aerosol particles; Based on the preset single-parameter κ-Kora equation, the measured relative humidity is selected and the aerosol particle size after moisture absorption growth of multiple particle size segments is iteratively obtained; Based on the preset complex refractive index of dry aerosol particles and the complex refractive index of water, a volume-weighted average is performed on the dry and wet parts to obtain the complex refractive index of the ambient aerosol particles; Based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, according to the preset algorithm corresponding to the Mie scattering theory and the aerosol extinction coefficient of the visible light band, the visibility based on the measured relative humidity is obtained. Combined with the fine particle mass concentration of the model and the measured visibility, the aerosol fine particle mass concentration corresponding to the site is iteratively obtained.

2. The method according to claim 1, characterized in that The method of determining the fine particle aerosol hygroscopicity parameter κ based on the particle size spectrum distribution characteristics of the dry aerosol particles comprises: Based on the particle size distribution characteristics of dry aerosol particles, combined with the hygroscopicity parameter κ corresponding to each aerosol chemical component i The mass concentration of chemical components C i Take the weighted average to obtain the aerosol hygroscopic parameter κ, which satisfies the formula: Where n is the number of chemical components in the aerosol.

3. The method according to claim 1, characterized in that The aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles are obtained according to the preset algorithm corresponding to the Mie scattering theory and the aerosol extinction coefficient of the visible light band, and the visibility based on the measured relative humidity is obtained. The fine particle mass concentration of the model and the measured visibility are combined to iteratively obtain the aerosol fine particle mass concentration corresponding to the site, including: Based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, the extinction coefficient cross sections of multiple particle sizes are calculated according to the algorithm corresponding to the preset Mie scattering theory, the number of particles is integrated to obtain the extinction coefficients of multiple particle sizes, and the extinction coefficients of multiple particle sizes are summed to obtain the aerosol extinction coefficient b on the corresponding model grid point under the actual humidity conditions of the site. model ; Based on the aerosol extinction coefficient in the visible light band and the aerosol extinction coefficient b on the model grid point model , visibility based on the measured relative humidity is obtained, and the aerosol fine particle mass concentration corresponding to the station is iteratively obtained by combining the model's fine particle mass concentration and the measured visibility.

4. The method according to claim 3, characterized in that Based on the aerosol extinction coefficient in the visible light band and the aerosol extinction coefficient b on the model grid point model , obtain the visibility based on the measured relative humidity, combine the model fine particle mass concentration and the measured visibility, and iterate to obtain the aerosol fine particle mass concentration corresponding to the station, including: Under the assumption that the aerosol density remains constant, the number of particles in each particle size segment is iterated in equal proportion so that the extinction coefficient b on the model grid point model The difference between the aerosol extinction coefficient in the visible light band and the aerosol extinction coefficient in the visible light band is less than a preset value, and the mass concentration of aerosol fine particles corresponding to the inverted site is obtained.

5. The method according to claim 4, characterized in that The method further comprises: By iterating the number of particles in each particle size segment in equal proportion, the extinction coefficient b on the pattern grid point is model The difference between the aerosol extinction coefficient in the visible light band and the aerosol extinction coefficient in the visible light band is less than a preset value, and the model aerosol mass concentration is determined based on the number of aerosol particles according to a preset transformation rule to obtain the inverted aerosol fine particle mass concentration.

6. The method according to claim 1, characterized in that The aerosol extinction coefficient in the visible light band is obtained by measuring visibility, and factors affecting visibility include the sum of the extinction coefficients of atmospheric aerosol particles, gas molecules, fog droplets and raindrops.

7. The method according to claim 2, characterized in that The aerosol chemical components include at least one of black carbon, organic carbon, sulfate, nitrate, ammonium salt, sodium salt and chloride salt.

8. A device for calculating the concentration of fine particulate matter based on measured visibility and relative humidity, characterized in that: The device comprises: A determination module is used to determine the aerosol extinction coefficient in the visible light band based on the historical data of the site visibility observation and humidity observation; The determination module is also used to extract the particle size spectrum distribution characteristics of the dry aerosol particles at the corresponding station of the numerical model chemical field, and determine the fine particle aerosol hygroscopicity parameter κ based on the particle size spectrum distribution characteristics of the dry aerosol particles; An iterative module is used to select the measured relative humidity based on the preset single-parameter κ-Kolla equation, and iteratively obtain the aerosol particle size after moisture absorption growth of multiple particle size segments; A processing module, configured to perform volume weighted averaging on the dry and wet parts based on the preset complex refractive index of the dry aerosol particles and the complex refractive index of water, so as to obtain the complex refractive index of the ambient aerosol particles; The processing module is also used to obtain visibility based on the measured relative humidity based on the aerosol particle size after hygroscopic growth and the complex refractive index of the ambient aerosol particles, according to the algorithm corresponding to the preset Mie scattering theory and the aerosol extinction coefficient of the visible light band, and iteratively obtain the aerosol fine particle mass concentration corresponding to the site in combination with the model's fine particle mass concentration and the measured visibility.

9. An electronic device, characterized in that: include: at least one processor; and a memory communicatively coupled to the at least one processor; It is characterized in that the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

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