Air quality evaluation method

Abstract

The invention discloses an air quality assessment method, which comprises the following steps: acquiring hyperspectral satellite data and meteorological data of a to-be-assessed area, and acquiring trace gas plume structures from the hyperspectral satellite data and the meteorological data; determining trace gas linear density based on the trace gas plume structure; fitting the trace gas linear density and the constructed transmission diffusion model to obtain parameter information of the transmission diffusion model, and constructing the transmission diffusion model; and estimating the effective emission amount and the effective life of the trace gas based on the constructed transmission diffusion model. The atmospheric trace gas emission can be effectively monitored in real time on the basis of data acquisition of a hyperspectral satellite, and large-scale global observation and evaluation of the atmospheric environment are realized, so that pollution emission caused by hot spots and hot events can be evaluated, and corresponding instant data can be obtained in time.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent environmental monitoring, and particularly to an air quality assessment method. Background Art

[0002] The assessment of the emissions of urban air pollutants is the key to controlling urban pollution and air quality. Moreover, some of the atmospheric trace gases will also pose a serious health threat, leading to respiratory diseases and infant diseases, etc., thus seriously endangering the health of urban residents.

[0003] In order to assess the emissions of urban air pollutants, the currently adopted traditional methods for estimating urban air pollutant emissions mainly rely on the annually updated emission inventory. However, since the corresponding emission inventory is often updated slowly, it is difficult to meet the emissions changes caused by sudden hot events or human activities. That is to say, there is currently no method that can monitor and evaluate in real time the emissions changes caused by sudden hot events or human activities, and then effectively monitor the air pollution situation in real time.

[0004] In view of this, the present invention is specifically proposed. Summary of the Invention

[0005] The object of the present invention is to provide an air quality assessment method for effectively monitoring in real time the emissions changes caused by sudden hot events or human activities and solving the problems existing in the prior art.

[0006] The object of the present invention is achieved by the following technical solutions:

[0007] An air quality assessment method, comprising:

[0008] Obtaining hyperspectral satellite data and meteorological data of the area to be evaluated, and obtaining the trace gas plume structure from the hyperspectral satellite data and meteorological data;

[0009] Determining the trace gas line density based on the trace gas plume structure;

[0010] Fitting the trace gas line density and the constructed transport and diffusion model to obtain the transport and diffusion model parameter information of the transport and diffusion model;

[0011] Assessing the air quality based on the transport and diffusion model parameter information.

[0012] The hyperspectral satellite data includes: concentration information of glyoxal, formaldehyde, sulfur dioxide and nitrogen dioxide, and the concentration information is the tropospheric column concentration.

[0013] Before the hyperspectral satellite data is applied, it is also subjected to screening processing, and the screening processing includes:

[0014] The quality assurance value should meet the reference value provided by the trace gas inversion algorithm. The regular grid size, i.e., the spatial resolution, of the satellite data should meet a value better than the predetermined value, and the time resolution should meet the requirement of daily or monthly global coverage.

[0015] The meteorological data includes:

[0016] The wind field data of the area to be evaluated, where the wind field data includes the average grid wind field and wind speed data, and the wind field data contains zonal wind and meridional wind, and the average grid wind field and wind speed data correspond one-to-one with the latitude and longitude of the satellite data.

[0017] The processing process for obtaining the trace gas plume structure includes:

[0018] Determine the central latitude and longitude of the area to be evaluated, and take the central latitude and longitude as the center, and rotate with a set distance value as the radius to determine the rotated trace gas grid result as the trace gas plume structure;

[0019] Among them, the rotation is calculated by the following formula:

[0020] lat a =lat b cos(-θ)+lon b sin(-θ);

[0021] lon a =-lat b sin(-θ)+lon b cos(-θ);

[0022] Among them, lat a and lon a are the rotated latitude and longitude, lat b and lon b are the latitude and longitude before rotation, and θ is the angle between the wind direction at the central latitude and longitude grid and the due east direction.

[0023] The processing process for determining the trace gas line density based on the trace gas plume structure includes:

[0024] Based on the rotated trace gas grid result, intercept part of the rotated concentration distribution data, and obtain the trace gas line density along the wind direction with reference to a predetermined distance.

[0025] The calculation formula for constructing the transport and diffusion model M(x) includes:

[0026]

[0027] Among them, E is the emission factor, B is the background concentration, and e is the truncated exponential function; and the corresponding truncated exponential function e is expressed as:

[0028]

[0029] Among them, X is the central longitude and latitude, and x 0 is the distance when the line density of the trace gas drops to 1 / e, and x is the predetermined distance for obtaining the line density of the trace gas;

[0030] In the transport and diffusion model M(x), e is also convolved with the Gaussian function G(x), and the Gaussian function G(x) is expressed as:

[0031]

[0032] Among them, σ is the standard deviation of the Gaussian function.

[0033] The processing process for obtaining the parameter information of the transport and diffusion model includes:

[0034] Performing least squares fitting on the line density L(x) of the trace gas and the transport and diffusion model M(x) to obtain the parameter information of the transport and diffusion model M(x); and the parameter information of the transport and diffusion model includes:

[0035] Emission factor E, background concentration B, distance x when the line density of the trace gas drops to 1 / e 0 and the standard deviation σ of the Gaussian function.

[0036] The process of evaluating air quality based on the parameter information of the transport and diffusion model includes: estimating the effective emission amount and effective lifetime of the trace gas based on the parameter information of the transport and diffusion model.

[0037] The processing process for estimating the effective emission amount and effective lifetime of the trace gas includes:

[0038] The calculation formulas for the effective emission amount P and effective lifetime τ of the trace gas are:

[0039] P = E / τ, τ = x 0 / w;

[0040] Among them, E is the emission factor as the parameter information of the transport and diffusion model, and x 0 is the distance when the line density of the trace gas drops to 1 / e as the parameter information of the transport and diffusion model, and w is the wind speed at the central longitude and latitude.

[0041] Compared with the prior art, an air quality assessment method provided by the present invention can perform real-time and effective monitoring of atmospheric trace gas emissions based on hyperspectral satellite data collection, realizing large-scale global observation and assessment of the atmospheric environment, so as to obtain corresponding immediate data in a timely manner for evaluating pollution emissions caused by hot spots and hot events. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0043] Figure 1 It is a schematic diagram of the implementation process of the method provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments, which do not constitute a limitation to the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present invention.

[0045] First, the following explanations will be given to the terms that may be used in this article:

[0046] The term "and / or" means that either or both of the two can be realized. For example, X and / or Y means that it includes both the case of "X" or "Y" and the three cases of "X and Y".

[0047] Descriptions with semantic meanings such as "including", "comprising", "containing", "having" or other similar ones should be interpreted as non-exclusive inclusion. For example: including a certain technical feature element (such as raw materials, components, ingredients, carriers, dosage forms, materials, dimensions, parts, components, mechanisms, devices, steps, processes, methods, reaction conditions, processing conditions, parameters, algorithms, signals, data, products or articles, etc.) should be interpreted as not only including the clearly listed certain technical feature element, but also including other well-known technical feature elements in the art that are not clearly listed.

[0048] The term "consisting of" means excluding any technical feature elements not expressly listed. If this term is used in a claim, it will make the claim closed-ended, so that it does not include technical feature elements other than those expressly listed, except for conventional impurities related thereto. If this term only appears in a certain clause of a claim, then it only limits the elements expressly listed in that clause, and the elements recited in other clauses are not excluded from the overall claim.

[0049] The term "parts by mass" represents the mass ratio relationship between multiple components. For example: if component X is described as x parts by mass and component Y is described as y parts by mass, then it means the mass ratio of component X to component Y is x:y; 1 part by mass can represent any mass. For example: 1 part by mass can be represented as 1 kg or 3.1415926 kg, etc. The sum of the parts by mass of all components is not necessarily 100 parts, and can be greater than 100 parts, less than 100 parts or equal to 100 parts. Unless otherwise specified, the parts, ratios and percentages described herein are by mass.

[0050] Unless otherwise expressly specified or limited, terms such as "installed", "connected", "joined", "fixed", etc. shall be understood in a broad sense. For example: it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in this text can be understood according to specific circumstances.

[0051] When a concentration, temperature, pressure, size or other parameter is expressed in the form of a numerical range, this numerical range should be understood as specifically disclosing all ranges formed by the pairing of any upper limit value, lower limit value, and preferred value within this numerical range, regardless of whether this range is expressly recited; for example, if the numerical range "2 - 8" is recited, then this numerical range should be interpreted as including ranges such as "2 - 7", "2 - 6", "5 - 7", "3 - 4 and 6 - 7", "3 - 5 and 7", "2 and 5 - 7", etc. Unless otherwise specified, the numerical ranges recited in this text include both their end values and all integers and fractions within this numerical range.

[0052] The terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. They are only for convenience of description and simplification of description, rather than explicitly or implicitly indicating that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be construed as a limitation to this article.

[0053] The following provides a detailed description of an air quality assessment method provided by the present invention. The content not described in detail in the embodiments of the present invention belongs to the prior art well-known to those skilled in the art. For those conditions not specified in the embodiments of the present invention, they are carried out according to the conventional conditions in the art or the conditions recommended by the manufacturer. For the reagents or instruments not specified in the embodiments of the present invention for the manufacturer, they are all conventional products that can be obtained through commercial purchase.

[0054] The air quality assessment method provided by the present invention can be realized based on multi-source satellite data observed by hyperspectral satellites. For example, corresponding assessments are carried out based on satellite data of atmospheric pollutants such as glyoxal, formaldehyde, sulfur dioxide, and nitrogen dioxide. Based on hyperspectral satellites, it is usually possible to achieve daily large-scale global observations of the atmospheric environment to obtain the observed multi-source satellite data; then, the multi-source satellite data observed is used to estimate the pollutant emissions in hot spot cities and regions, that is, the corresponding observed multi-source satellite data can provide immediate data support for the assessment of pollution emissions in hot spot regions and hot spot events.

[0055] Specifically, the purpose of the implementation of the embodiments of the present invention is to provide a remote sensing algorithm capable of realizing air quality assessment. This remote sensing algorithm can calculate the pollutant emissions of hot spot events or regions by using multi-source satellite data retrieved by hyperspectral satellite instruments, so as to monitor and evaluate the pollution emissions in the atmospheric environment in real time.

[0056] An air quality assessment method provided by an embodiment of the present invention is specifically a satellite remote sensing method for calculating pollutant emissions, and the implementation process of this method refers to Figure 1 as shown, and may include the following steps:

[0057] Step 11, acquisition of hyperspectral satellite data;

[0058] The hyperspectral satellite data may include concentration information of glyoxal, formaldehyde, sulfur dioxide, nitrogen dioxide, etc.; in the embodiments of the present invention, the pollutant emissions in hot spot events and hot spot regions are mainly evaluated based on the data of atmospheric trace gases retrieved from hyperspectral satellite data (that is, the concentration information of glyoxal, formaldehyde, sulfur dioxide, nitrogen dioxide, etc. contained in the atmosphere).

[0059] Generally, the corresponding glyoxal and formaldehyde can be used to evaluate the emissions of volatile organic compounds, sulfur dioxide is used to evaluate the emissions of sulfides, and nitrogen dioxide is used to evaluate the emissions of nitrogen oxides; thus, by obtaining the concentration information of pollutants such as glyoxal, formaldehyde, sulfur dioxide, and nitrogen dioxide, the emissions of atmospheric pollutants in the atmospheric environment can be evaluated, and then the air quality can be effectively evaluated;

[0060] It should be noted that the data of atmospheric trace gases applied in the embodiments of the present invention are all tropospheric column concentrations to reduce the influence of the background value of the stratosphere on the evaluation results.

[0061] Step 12, screening the hyperspectral satellite data;

[0062] In this step, the three-level data retrieved from the hyperspectral satellite (i.e., the data of atmospheric trace gases) need to be screened before application, and the screening conditions include:

[0063] The quality assurance value should meet the official reference value provided by the trace gas retrieval algorithm. The regular grid size of the satellite data, i.e., the spatial resolution, should be better than 5 km, and the time resolution should meet daily or monthly global coverage;

[0064] Among them, the quality assurance value QA is usually a number between 0 and 1. For example, it is stipulated that when QA is greater than 0.5, it indicates that the data result is reliable, and when QA is less than 0.5, it indicates that the data result is unreliable; of course, there are also data with QA values of 0, 1, 2. When QA is 0, it is good (the data result is reliable), when QA is 1, it means the data is bad (the data result is unreliable), and when QA is 2, it means high-reflection pixels with large errors; the QAs of different data products are different and there are certain differences; therefore, in the present invention, it is required that the corresponding quality assurance value should meet the official reference value provided by the trace gas retrieval algorithm;

[0065] The corresponding spatial resolution should be better than 5 km, which refers to the spatial resolution of the smallest grid of the satellite pixels. Usually, the smallest pixel can be 5 km, 2 km, 1 km. Therefore, when studying urban emissions, the corresponding spatial resolution should be better than 5 km, that is, <5 km.

[0066] Step 13, obtaining auxiliary meteorological data;

[0067] In this step, the corresponding meteorological data need to be obtained for application; mainly obtain the plume structure of atmospheric trace gases in hot events or regions, which mainly includes wind field data;

[0068] For example, it is possible to obtain the average grid wind field and wind speed data of the near-surface area (e.g., the pressure range is from 1000 hPa to 900 hPa) with a fixed range (e.g., 200 km) centered around a hot event or region; the wind field and wind speed data should correspond one-to-one with the satellite grid longitude and latitude, and the wind field data includes zonal wind and meridional wind.

[0069] Step 14, obtaining the trace gas plume structure;

[0070] In this step, it is necessary to obtain the trace gas plume structure from the hyperspectral satellite data and meteorological data. The specific process of obtaining the corresponding trace gas plume structure can include:

[0071] First, determine the central longitude and latitude of the hot event or hot region under study;

[0072] Among them, when the research target is urban emissions, the central longitude and latitude are the central longitude and latitude of the city; when the research target is a biomass burning event, the central longitude and latitude are the longitude and latitude of the maximum radiance of the fire point; when the research target is an instantaneous industrial activity, the central longitude and latitude are the longitude and latitude where the event occurs;

[0073] Then, rotate the longitude and latitude corresponding to the trace gas concentration distribution grid of the regional grid with the determined central longitude and latitude as the center and a fixed range (e.g., 200 km) as the radius to obtain the rotated longitude and latitude grid, that is, obtain the rotated trace gas grid result as the corresponding trace gas plume structure;

[0074] The rotation process is calculated by the following formula:

[0075] lat a =lat b cos(-θ)+lon b sin(-θ);

[0076] lon a =-lat b sin(-θ)+lon b cos(-θ);

[0077] Among them, lat a and lon a are the rotated latitude and longitude, lat b and lon b are the latitude and longitude before rotation, and θ is the angle between the wind direction at the central longitude and latitude grid and the due east direction.

[0078] Step 15, obtaining the trace gas linear density and constructing the transport and diffusion model M(x);

[0079] This step is to intercept part of the rotated concentration distribution data based on the rotated trace gas grid results, and obtain the trace gas line density along the wind direction with reference to a predetermined distance. The specific implementation process may include:

[0080] First, intercept part of the rotated concentration distribution data from the rotated trace gas grid results (i.e., the trace gas plume structure) obtained through the above step 14; for example, the data within a range of 50 km upwind, 150 km downwind, and 100 km perpendicular to the wind direction at the central longitude and latitude;

[0081] After that, along the wind direction, obtain the trace gas line density L(x), where x is the distance. For example, intercept a line density point every 5 km. This line density point is the sum of the concentrations of all grids within a range of 100 km perpendicular to the wind direction. Based on the corresponding line density points, the trace gas line density can be determined;

[0082] Finally, obtain the parameter information of the transport diffusion model by performing a least squares fit on the line density L(x) and the transport diffusion model M(x);

[0083] Among them, the transport diffusion model M(x) is constructed by the following formula:

[0084]

[0085] Among them, E is the emission factor, B is the background concentration value, and e is the truncated exponential function; and the corresponding truncated exponential function e is expressed as:

[0086]

[0087] Among them, X is the central longitude and latitude, and x 0 is the distance when the trace gas line density drops to 1 / e.

[0088] In addition, in the construction formula of the transport diffusion model M(x), e also needs to be convolved with a Gaussian function G(x), and the corresponding G(x) can be expressed as:

[0089]

[0090] Among them, σ is the standard deviation of the Gaussian function.

[0091] Based on the above formula, the parameter information E, B, x 0 , σ, etc. of the transport diffusion model M(x) can be obtained by performing a least squares fit on the line density L(x) and the transport diffusion model M(x);

[0092] Among the obtained parameter information:

[0093] The corresponding parameter information E is the emission factor in the corresponding transmission and diffusion model parameter information;

[0094] The corresponding parameter information B is the background value concentration. Based on this B value, it is beneficial to understand the background value of pollutants in the research area;

[0095] The corresponding parameter information x0 is the distance required for the pollutant line density to drop to 1 / e, which can characterize the pollution diffusion ability of the area;

[0096] Therefore, after obtaining the above corresponding E, B, x 0 , σ parameter information, the corresponding assessment of the pollution information in the research area can be performed, that is, the air quality can be evaluated based on the parameter information of the transmission and diffusion model; for example, the subsequent step 16 can be performed to estimate the effective emission amount and effective lifetime of trace gases, etc.

[0097] Step 16, estimating the effective emission amount and effective lifetime of trace gases based on the parameter information of the transmission and diffusion model;

[0098] Specifically, the effective emission amount P and effective lifetime τ of trace gases in hot spots or events can be estimated through the model parameters calculated in step 15 (i.e., the parameter information of the transmission and diffusion model);

[0099] Furthermore, the estimation calculation can be performed through the following formula:

[0100] τ = x 0 / w, P = E / τ;

[0101] where w is the wind speed at the central longitude and latitude, E is the emission factor in the corresponding transmission and diffusion model parameter information, and x 0 is the distance when the trace gas line density in the corresponding transmission and diffusion model parameter information drops to 1 / e.

[0102] After calculating the effective emission amount P and effective lifetime τ of trace gases in the corresponding hot spots or events, the real-time monitoring and evaluation of the air quality of the atmospheric environment corresponding to the hot spots or events are achieved.

[0103] In summary, in the implementation process of the above technical solution provided by the present invention, it can perform real-time and effective monitoring of the atmospheric trace gas emission amount based on the data collection of hyperspectral satellites, so as to achieve a large-scale global observation and evaluation of the atmospheric environment, so as to obtain corresponding instant data in a timely manner for the pollution emissions caused by evaluation hot spots and hot events, providing reliable technical support for the real-time monitoring of the atmospheric environment.

[0104] As described above, it is only the preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims. The information disclosed in the background art part of this article is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as an admission or any form of implication that this information constitutes the prior art known to those skilled in the art.

Claims

1. An air quality assessment method, characterized in that: include: Acquire hyperspectral satellite data and meteorological data of the area to be evaluated, and obtain trace gas plume structure from the hyperspectral satellite data and meteorological data; determining a trace gas linear density based on the trace gas plume structure; Fitting the trace gas linear density and the constructed transmission diffusion model to obtain transmission diffusion model parameter information of the transmission diffusion model; Air quality is evaluated based on the transmission diffusion model parameter information.

2. The method according to claim 1, characterized in that The hyperspectral satellite data includes concentration information of glyoxal, formaldehyde, sulfur dioxide and nitrogen dioxide, and the concentration information is tropospheric column concentration.

3. The method according to claim 2, characterized in that The hyperspectral satellite data is further subjected to screening processing before application, and the screening processing includes: The quality assurance value should meet the reference value provided by the trace gas inversion algorithm, the regular grid size of the satellite data, that is, the spatial resolution should be better than the predetermined value, and the temporal resolution should meet daily or monthly global coverage.

4. The method according to claim 1, characterized in that: The meteorological data include: The wind field data of the area to be evaluated includes average grid wind field and wind speed data, and the wind field data includes latitudinal wind and meridional wind, and the average grid wind field and wind speed data correspond to the longitude and latitude of the satellite data one by one.

5. The method according to any one of claims 1 to 4, characterized in that: The processing process of obtaining the trace gas plume structure includes: Determine the central longitude and latitude of the area to be evaluated, and rotate the trace gas grid result after rotation with the central longitude and latitude as the center and the set distance value as the radius as the trace gas plume structure; The rotation is calculated by the following formula: years a =years b cos(-θ)+lon b sin(-θ); lon a =-lat b sin(-θ)+long b cos(−θ); Among them, lat a and lon a is the latitude and longitude after rotation, lat b and lon b is the latitude and longitude before rotation, and θ is the angle between the wind direction at the center longitude and latitude grid and the due east direction.

6. The method according to claim 5, characterized in that The process of determining the trace gas linear density based on the trace gas plume structure includes: Based on the rotated trace gas grid result, a portion of the rotated concentration distribution data is intercepted, and the trace gas linear density is obtained along the wind direction with reference to a predetermined distance.

7. The method according to claim 5, characterized in that The calculation formula for constructing the transmission diffusion model M(x) includes: Where E is the emission factor, B is the background concentration, and e is the truncated exponential function; and the corresponding truncated exponential function e is expressed as: Wherein, X is the center longitude and latitude, x0 is the distance when the trace gas linear density drops to 1 / e, and x is the predetermined distance for obtaining the trace gas linear density; In the transmission diffusion model M(x), e is also convolved with a Gaussian function G(x), and the Gaussian function G(x) is expressed as: Here, σ is the standard deviation of the Gaussian function.

8. The method according to claim 5, characterized in that The process of obtaining the transmission diffusion model parameter information includes: The trace gas linear density L(x) and the transmission diffusion model M(x) are subjected to least square fitting to obtain transmission diffusion model parameter information of the transmission diffusion model M(x); and the transmission diffusion model parameter information includes: Emission factor E, background concentration B, distance x0 at which the trace gas linear density drops to 1 / e, and standard deviation σ of the Gaussian function.

9. The method according to claim 5, characterized in that The process of evaluating air quality based on the transmission diffusion model parameter information includes: The effective emission amount and effective life of trace gases are estimated based on the transmission diffusion model parameter information.

10. The method according to claim 9, characterized in that The process of estimating the effective emission and effective life of trace gases includes: The calculation formula for trace gas effective emission P and effective life τ is: P = E / τ, τ = x0 / w; Among them, E is the emission factor as the parameter information of the transmission diffusion model, x0 is the distance when the trace gas linear density drops to 1 / e as the parameter information of the transmission diffusion model, and w is the wind speed at the central longitude and latitude.

Images