CN117495637A - Atmospheric pollutant assessment method and system based on meteorological factors and pollution transmission - Google Patents
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Abstract
The invention provides an atmospheric pollutant assessment method and an atmospheric pollutant assessment system based on meteorological factors and pollution transmission, wherein the method comprises the following steps: s1: extracting the atmospheric pollution concentration data of the test area on a preset time sequence, and constructing data as a model; s2: filtering the influence of the meteorological factors in the model construction data to construct a meteorological factor influence model; s3: calculating external transmission contribution influence in the model construction data, and constructing an external transmission contribution influence model; s4: performing relational coupling on the model construction data and the meteorological factor influence model and the external transmission contribution influence model, and constructing an atmospheric pollution concentration relational coupling model; s5: and estimating the influence of the atmospheric pollutant concentration of the region to be detected according to the atmospheric pollutant concentration relation coupling model. According to the method, the regional atmosphere pollution concentration can be comprehensively studied and judged according to the meteorological factors and the external transmission contribution influence by combining the meteorological factors and the external transmission contribution influence.
Description
Technical Field
The invention belongs to the technical field of atmospheric environment, and particularly relates to an atmospheric pollutant evaluation method, an atmospheric pollutant evaluation system and an atmospheric pollutant evaluation system based on meteorological factors and pollution transmission.
Background
The observation of the atmospheric pollution refers to the process of measuring the type and concentration of pollutants in the atmosphere and observing the time-space distribution and change rule of the pollutants. The atmospheric pollution monitoring aims to identify pollutant in the atmosphere, master the distribution and diffusion rule of the pollutant, and monitor the emission and control conditions of an atmospheric pollution source.
The time series of the observed concentration of the atmospheric pollutants is unsteady, is mainly influenced by the double effects of an emission source and an atmospheric condition, and simultaneously superimposes external transmission contributions.
At present, for the research of the influence of the concentration of the atmospheric pollutants, only the influence of the meteorological conditions or the pollution transmission influence on the concentration of the atmospheric pollutants is independently researched by domestic and foreign experts and scholars for a long time, the relation between the meteorological conditions or the pollution transmission influence is not comprehensively considered, and the comprehensive influence of the meteorological conditions or the pollution transmission influence on the concentration of the atmospheric pollutants is not quantitatively researched and judged.
Disclosure of Invention
According to the atmospheric pollutant evaluation method and system based on the meteorological factors and the pollution transmission, the atmospheric pollutant concentration of the area can be comprehensively researched and judged by combining the meteorological factors and the external transmission contribution influence, so that the technical problem is solved.
The technical scheme for solving the technical problems is as follows:
in a first aspect, the present invention provides a method of atmospheric contaminant assessment based on meteorological factors and pollution transmission, comprising the steps of:
s1: extracting the atmospheric pollution concentration data of the test area on a preset time sequence, and constructing data as a model;
s2: filtering the influence of the meteorological factors in the model construction data to construct a meteorological factor influence model;
s3: calculating external transmission contribution influence in the model construction data, and constructing an external transmission contribution influence model;
s4: performing relational coupling on the model construction data and the meteorological factor influence model and the external transmission contribution influence model, and constructing an atmospheric pollution concentration relational coupling model;
s5: and estimating the influence of the atmospheric pollutant concentration of the region to be detected according to the atmospheric pollutant concentration relation coupling model.
In some embodiments, the "filtering out meteorological factor effects in model building data" in S2 includes:
and filtering out the influence of the meteorological factors in the model construction data by using a numerical simulation method, or filtering out the influence of the meteorological factors in the model construction data by using a KZ filtering method.
In some embodiments, the "filtering out meteorological factor effects in model building data with KZ filtering" includes:
s21: performing KZ filtering on the model construction data, and decomposing the filtered model construction data according to a long-term component, a short-term component, a seasonal component and a baseline component;
s22: filtering the influence of meteorological factors in the long-term component by utilizing multiple linear regression fitting to obtain the sum of the regression residual error of the short-term component and the regression residual error of the baseline component as a total residual error;
s23: and carrying out KZ filtering on the total residual error to obtain the atmospheric pollution concentration data after the meteorological factors are filtered.
In some embodiments, the specific calculation process of "KZ filtering model construction data" in S21 is:；/>；
wherein,for the filtered time series, +.>Constructing data for a model->For sliding window +.>For the length of the sliding window before and after filtering, < >>Is a filtering parameter.
In some embodiments, the specific calculation process of S23 is:；
wherein,represents the atmospheric pollution concentration after filtering the meteorological factors, < +.>Mean value of long-term component +.>Representing the residual long-term component.
In some embodiments, the "calculating the extraneous transmission contribution effect in the model building data" in S3 includes: background station calculation or numerical simulation;
the background station calculation method comprises the following steps:
s31: taking the test area as a station to be researched, and taking the area with the lowest concentration of atmospheric pollutants in the upwind direction or downwind direction of the test area as a background observation station;
s32: and acquiring the air pollution concentration of the background observation station, taking the air pollution concentration of the station to be researched as the concentration of the station to be researched, and calculating external transmission contribution according to the concentration of the background station and the concentration of the station to be researched.
In some embodiments, the specific calculation process of S32 is:；
where P represents the extrinsic transport contribution, B is the background station concentration, and A is the station concentration to be studied.
In a second aspect, the present invention provides an atmospheric pollutant assessment system based on meteorological factors and pollution transmission, comprising:
the data acquisition module is used for extracting the atmospheric pollution concentration data of the test area on a preset time sequence and taking the atmospheric pollution concentration data as model construction data;
the meteorological factor filtering module is used for filtering meteorological factor influences in the model construction data and constructing a meteorological factor influence model;
the transmission contribution model construction module is used for calculating external transmission contribution influences in model construction data and constructing an external transmission contribution influence model;
the model coupling module is used for carrying out relation coupling on model construction data, a meteorological factor influence model and an external transmission contribution influence model, and constructing an atmospheric pollution concentration relation coupling model;
and the estimation module is used for estimating the influence of the atmospheric pollutant concentration of the area to be measured according to the atmospheric pollutant concentration relation coupling model.
In some embodiments, the meteorological factor filtering module comprises:
the data decomposition sub-module is used for carrying out KZ filtering on the model construction data and decomposing the filtered model construction data according to the long-term component, the short-term component, the seasonal component and the baseline component;
the residual calculation sub-module is used for filtering the influence of meteorological factors in the long-term component by utilizing multiple linear regression fitting to obtain the sum of the regression residual of the short-term component and the regression residual of the baseline component as a total residual;
and the residual filtering sub-module is used for carrying out KZ filtering on the total residual to obtain the atmospheric pollution concentration data after the meteorological factors are filtered.
In some embodiments, the transmission contribution model building module comprises:
the station classifying sub-module is used for taking the test area as a station to be researched, and taking the area with the lowest concentration of the atmospheric pollutants in the upwind direction or the downwind direction of the test area as a background observation station;
the external transmission calculation sub-module is used for acquiring the air pollution concentration of the background observation station, taking the air pollution concentration of the station to be researched as the concentration of the background station, and calculating external transmission contribution according to the concentration of the background station and the concentration of the station to be researched.
The beneficial effects of this application are:
according to the atmospheric pollutant evaluation method and system based on the meteorological factors and the pollution transmission, the meteorological factors and the external transmission contribution influence are combined, so that the relationship between the meteorological factors or the external transmission influence is comprehensively considered, and the regional atmospheric pollutant concentration can be comprehensively researched and judged.
Drawings
FIG. 1 is a flow chart of an atmospheric contaminant assessment method and system based on meteorological factors and pollution transmission of the present application;
FIG. 2 is a sub-flowchart of step S2 of the present application;
FIG. 3 is a sub-flowchart of step S3 of the present application;
fig. 4 is a conceptual diagram of the relationship of model coupling of the present application.
Detailed Description
The principles and features of the present invention are described below with reference to the drawings, the examples are illustrated for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention.
In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and examples. It is to be understood that the described embodiments are some, but not all, of the embodiments of the present application. The specific embodiments described herein are to be considered in an illustrative rather than a restrictive sense. All other embodiments obtained by a person of ordinary skill in the art based on the described embodiments of the present application are within the scope of the protection of the present application.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
Fig. 1 is a flow chart of the method of the present application. An atmospheric contaminant assessment method based on meteorological factors and contaminant transmission, in combination with fig. 1, comprises the steps of:
s1: extracting the atmospheric pollution concentration data of the test area on a preset time sequence, and constructing data as a model;
specifically, the time series of the observed concentration of the atmospheric pollutants is a non-steady time series, and is mainly influenced by the double effects of an emission source and an meteorological factor, and simultaneously, external transmission contributions are superimposed. The time series change of the observed concentration of the atmospheric pollutants comprises pollution source information and meteorological information; the change of meteorological factors seriously affects and interferes with the real change of the concentration of atmospheric pollutants; certain meteorological factors can cause external transmission and sedimentation, and how to clear the influence of atmospheric pollutant meteorological factors and pollution transmission on the concentration of atmospheric pollutants is particularly important to filter and analyze the atmospheric pollutant concentration time sequence meteorological factors and quantitatively calculate pollution transmission contribution. And firstly, the air pollution concentration data of the test area on a preset time sequence needs to be extracted and used as model construction data for subsequent model construction.
S2: filtering the influence of the meteorological factors in the model construction data to construct a meteorological factor influence model;
specifically, in order to clear the influence of atmospheric pollutant meteorological factors and pollution transmission on the atmospheric pollutant concentration, firstly, the acquired atmospheric pollutant concentration data of the test area, namely, the meteorological factors in the model construction data, need to be filtered.
In some embodiments, in conjunction with fig. 2, which is a sub-flowchart of step S2 of the present application, the S2 includes:
s21: performing KZ filtering on the model construction data, and decomposing the filtered model construction data according to a long-term component, a short-term component, a seasonal component and a baseline component;
s22: filtering the influence of meteorological factors in the long-term component by utilizing multiple linear regression fitting to obtain the sum of the regression residual error of the short-term component and the regression residual error of the baseline component as a total residual error;
s23: and carrying out KZ filtering on the total residual error to obtain the atmospheric pollution concentration data after the meteorological factors are filtered.
Specifically, the specific process of filtering meteorological factors by using a KZ filtering method comprises the steps of firstly carrying out KZ filtering on model construction data, and decomposing the filtered model construction data according to long-term components, short-term components, seasonal components and baseline components, wherein the long-term components are mainly influenced by pollution sources, climate changes and other factors, the seasonal components are caused by seasonal changes of seasonal pollution sources and meteorological conditions, and short-term variables are residual errors and are mainly influenced by small-scale weather systems and short-term pollution emission changes. In an ideal case, the 3 components of the time series decomposition short-term, seasonal and long-term components are independent of each other, i.e. the covariance between them is zero.
And secondly, the influence of the weather factors in the long-term components is filtered by utilizing multiple linear regression fitting, the sum of the regression residual error of the short-term components and the regression residual error of the baseline components is obtained and used as the total residual error, and the total residual error is subjected to KZ filtering to obtain the atmospheric pollution concentration data after the weather factors are filtered.
In some embodiments, the specific calculation process of "KZ filtering model construction data" in S21 is:；/>；
wherein,for the filtered time series, +.>Constructing data for a model->For sliding window +.>For the length of the sliding window before and after filtering, < >>Is a filtering parameter;
specifically, for the KZ filtering method and the data decomposition, the present scheme is represented by the above formula.
In some embodiments, the specific calculation process of S23 is:；
wherein,represents the atmospheric pollution concentration after filtering the meteorological factors, < +.>Mean value of long-term component +.>Representing the residual long-term component.
Specifically, the long-term component E (t) after KZ filtering and decomposition still comprises the influence of weather factors, the influence of the weather factors can be further eliminated by utilizing a multiple linear regression fitting method, the short-term component and the baseline component of the long-term sequence of pollutants are respectively established with weather factors with strong correlation (the short-term component and the baseline component of the corresponding weather sequence), and the total residual error comprises the short-term influence of local pollution sources, the influence of the weather factors which are not considered in regression and noise.
And then, carrying out KZ filtering on the total residual, and adding the obtained residual long-term component and the average value of the long-term component of the pollutant sequence data to obtain the atmospheric pollutant sequence with meteorological factors filtered.
S3: calculating external transmission contribution influence in the model construction data, and constructing an external transmission contribution influence model;
in some embodiments, in conjunction with the sub-flowchart of fig. 3, i.e., S3, the "calculating the extraneous transmission contribution effect in the model construction data" in S3 includes: background station calculation or numerical simulation;
the background station calculation method comprises the following steps:
s31: taking the test area as a station to be researched, and taking the area with the lowest concentration of atmospheric pollutants in the upwind direction or downwind direction of the test area as a background observation station;
s32: and acquiring the air pollution concentration of the background observation station, taking the air pollution concentration of the station to be researched as the concentration of the station to be researched, and calculating external transmission contribution according to the concentration of the background station and the concentration of the station to be researched.
In some embodiments, the specific calculation process of S32 is:；
where P represents the extrinsic transport contribution, B is the background station concentration, and A is the station concentration to be studied.
Specifically, if the relationship between the background station and the station to be studied is used to calculate the extraneous transmission contribution, the calculation process is as described in the above formula.
In some possible embodiments, the CMAQ and CAMx are used to construct an atmospheric model to simulate and calculate the atmospheric pollution conditions of the test area and the surrounding area, and to track the atmospheric physical and chemical processes performed by the atmospheric pollutants in each area.
In addition to the above method of calculating the extraneous transmission contribution using the relationship between the background station and the station to be studied, the extraneous transmission contribution can also be simulated by atmospheric simulation software. Specifically, the CMAQ and CAMx are utilized to construct an atmosphere model, the atmosphere pollution conditions of the test area and the peripheral area are simulated and calculated, the pollutants discharged by different areas are marked exclusively, and the atmosphere physical and chemical processes carried out by the atmosphere pollutants of each area are tracked, so that the aim of tracing the pollutant sources of a certain place is fulfilled.
S4: and carrying out relational coupling on the model construction data, the meteorological factor influence model and the external transmission contribution influence model, and constructing an atmospheric pollution concentration relational coupling model.
In some possible embodiments, S4 comprises:
and generating a model coupling relation graph according to the relation among the atmospheric pollution concentration data, the weather effect duty ratio and the external transmission contribution effect duty ratio on the same time sequence.
Specifically, the weather effect size and the external transmission effect size can be calculated through the factor effect model and the external transmission contribution effect model, for example, for a certain time of data, the weather effect proportion is calculated to be 60%, the external transmission effect proportion is calculated to be 40%, the corresponding PM2.5 atmospheric pollutant concentration is 50 micrograms, and a plurality of groups of data on a certain time sequence are calculated to be represented by a three-dimensional drawing of x, y and z, so that three-dimensional distribution is obtained, and the three relations are nonlinear. For example, another z=atmospheric contaminant concentration=30 micrograms, from which x weather effect duty cycles, and y extraneous transmission effect duty cycles can be found.
S5: and estimating the influence of the atmospheric pollutant concentration of the region to be detected according to the atmospheric pollutant concentration relation coupling model.
Specifically, after the weather factor filtering model and the external transmission contribution influence model are built, the original atmospheric pollution concentration data are coupled with the two models, so that the atmospheric pollution concentration can be more accurately described by the weather factor and the external transmission contribution. For example, where a weather factor favors contaminant concentration diffusion, the extraneous transport contribution has less effect on PM2.5 concentration, i.e., the greater extraneous transport contribution and the smaller extraneous transport contribution correspond to less difference in PM2.5 concentration, the favorable weather factor will favor further dissipation of the extraneous transported contaminant. The greater the extraneous transport contribution, the higher the PM2.5 concentration when meteorological factors are detrimental to contaminant diffusion. When the meteorological factor influence is greater than 60%, there is a tendency for the extraneous transmission contribution to decrease in the PM2.5 concentration influence difference, i.e., the PM2.5 concentration becomes insensitive to the extraneous transmission contribution. It is seen that the meteorological factors are dominant factors restricting the change of the PM2.5 concentration, and the regional transmission plays an aggravating role.
The second aspect of the present invention also provides an atmospheric pollutant assessment system based on meteorological factors and pollution transmission, comprising:
the data acquisition module is used for extracting the atmospheric pollution concentration data of the test area on a preset time sequence and taking the atmospheric pollution concentration data as model construction data;
the meteorological factor filtering module is used for filtering meteorological factor influences in the model construction data and constructing a meteorological factor influence model;
the transmission contribution model construction module is used for calculating external transmission contribution influences in model construction data and constructing an external transmission contribution influence model;
the model coupling module is used for carrying out relation coupling on model construction data, a meteorological factor influence model and an external transmission contribution influence model, and constructing an atmospheric pollution concentration relation coupling model;
and the estimation module is used for estimating the influence of the atmospheric pollutant concentration of the area to be measured according to the atmospheric pollutant concentration relation coupling model.
In some embodiments, the meteorological factor filtering module comprises:
the data decomposition sub-module is used for carrying out KZ filtering on the model construction data and decomposing the filtered model construction data according to the long-term component, the short-term component, the seasonal component and the baseline component;
the residual calculation sub-module is used for filtering the influence of meteorological factors in the long-term component by utilizing multiple linear regression fitting to obtain the sum of the regression residual of the short-term component and the regression residual of the baseline component as a total residual;
and the residual filtering sub-module is used for carrying out KZ filtering on the total residual to obtain the atmospheric pollution concentration data after the meteorological factors are filtered.
In some embodiments, the transmission contribution model building module comprises:
the station classifying sub-module is used for taking the test area as a station to be researched, and taking the area with the lowest concentration of the atmospheric pollutants in the upwind direction or the downwind direction of the test area as a background observation station;
the external transmission calculation sub-module is used for acquiring the air pollution concentration of the background observation station, taking the air pollution concentration of the station to be researched as the concentration of the background station, and calculating external transmission contribution according to the concentration of the background station and the concentration of the station to be researched.
Those skilled in the art will appreciate that while some embodiments described herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the present application and form different embodiments.
Those skilled in the art will appreciate that the descriptions of the various embodiments are each focused on, and that portions of one embodiment that are not described in detail may be referred to as related descriptions of other embodiments.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and alterations without departing from the spirit and scope of the present invention, and such modifications and alterations fall within the scope of the appended claims, which are to be construed as merely illustrative of this invention, but the scope of the invention is not limited thereto, and various equivalent modifications and substitutions will be readily apparent to those skilled in the art within the scope of the present invention, and are intended to be included within the scope of the invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
The present invention is not limited to the above embodiments, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and these modifications and substitutions are intended to be included in the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. The atmospheric pollutant assessment method based on meteorological factors and pollution transmission is characterized by comprising the following steps of:
s1: extracting the atmospheric pollution concentration data of the test area on a preset time sequence, and constructing data as a model;
s2: filtering the influence of the meteorological factors in the model construction data to construct a meteorological factor influence model;
s3: calculating external transmission contribution influence in the model construction data, and constructing an external transmission contribution influence model;
s4: performing relational coupling on the model construction data and the meteorological factor influence model and the external transmission contribution influence model, and constructing an atmospheric pollution concentration relational coupling model;
s5: and estimating the influence of the atmospheric pollutant concentration of the region to be detected according to the atmospheric pollutant concentration relation coupling model.
2. The atmospheric contaminant assessment method based on meteorological factors and pollution transfer of claim 1, wherein "filtering out meteorological factor effects in model build data" in S2 comprises:
and filtering out the influence of the meteorological factors in the model construction data by using a numerical simulation method, or filtering out the influence of the meteorological factors in the model construction data by using a KZ filtering method.
3. The atmospheric contaminant assessment method based on meteorological factors and pollution transfer of claim 2, wherein said filtering out meteorological factor effects in model building data with KZ filtering comprises:
s21: performing KZ filtering on the model construction data, and decomposing the filtered model construction data according to a long-term component, a short-term component, a seasonal component and a baseline component;
s22: filtering the influence of meteorological factors in the long-term component by utilizing multiple linear regression fitting to obtain the sum of the regression residual error of the short-term component and the regression residual error of the baseline component as a total residual error;
s23: and carrying out KZ filtering on the total residual error to obtain the atmospheric pollution concentration data after the meteorological factors are filtered.
4. The atmospheric pollution assessment method based on meteorological factors and pollution transmission according to claim 3, wherein the specific calculation process of "KZ filtering model construction data" in S21 is:
；
；
wherein,for the filtered time series, +.>Constructing data for a model->For sliding window +.>For the length of the sliding window before and after filtering, < >>Is a filtering parameter.
5. The atmospheric pollutant assessment method based on meteorological factors and pollution transmission according to claim 4, wherein the specific calculation process of S23 is:
；
wherein,represents the atmospheric pollution concentration after filtering the meteorological factors, < +.>Representing the average value of the long-term component,representing the residual long-term component.
6. The atmospheric contaminant assessment method based on meteorological factors and pollution transport according to claim 1, wherein "calculating extraneous transmission contribution effects in model construction data" in S3 comprises: background station calculation or numerical simulation;
the background station calculation method comprises the following steps:
s31: taking the test area as a station to be researched, and taking the area with the lowest concentration of atmospheric pollutants in the upwind direction or downwind direction of the test area as a background observation station;
s32: the method comprises the steps of obtaining the air pollution concentration of a background observation station, taking the air pollution concentration of a station to be researched as the concentration of the station to be researched, and calculating external transmission contribution according to the concentration of the background station and the concentration of the station to be researched;
the numerical simulation method comprises the following steps: and constructing an atmosphere model by using CMAQ and CAMx, simulating and calculating the atmosphere pollution conditions of the test area and the peripheral area, and tracking the atmosphere physical and chemical processes carried out by the atmosphere pollutants of each area.
7. The atmospheric contaminant assessment method based on meteorological factors and pollution transfer of claim 6, wherein the specific calculation process of S32 is:
；
where P represents the extrinsic transport contribution, B is the background station concentration, and A is the station concentration to be studied.
8. An atmospheric pollutant assessment system based on meteorological factors and pollution transmission, comprising:
the data acquisition module is used for extracting the atmospheric pollution concentration data of the test area on a preset time sequence and taking the atmospheric pollution concentration data as model construction data;
the meteorological factor filtering module is used for filtering meteorological factor influences in the model construction data and constructing a meteorological factor influence model;
the transmission contribution model construction module is used for calculating external transmission contribution influences in model construction data and constructing an external transmission contribution influence model;
the model coupling module is used for carrying out relation coupling on model construction data, a meteorological factor influence model and an external transmission contribution influence model, and constructing an atmospheric pollution concentration relation coupling model;
and the estimation module is used for estimating the influence of the atmospheric pollutant concentration of the area to be measured according to the atmospheric pollutant concentration relation coupling model.
9. The atmospheric pollutant assessment system based on meteorological factors and pollution transmission of claim 8, wherein the meteorological factor filtering module comprises:
the data decomposition sub-module is used for carrying out KZ filtering on the model construction data and decomposing the filtered model construction data according to the long-term component, the short-term component, the seasonal component and the baseline component;
the residual calculation sub-module is used for filtering the influence of meteorological factors in the long-term component by utilizing multiple linear regression fitting to obtain the sum of the regression residual of the short-term component and the regression residual of the baseline component as a total residual;
and the residual filtering sub-module is used for carrying out KZ filtering on the total residual to obtain the atmospheric pollution concentration data after the meteorological factors are filtered.
10. The atmospheric pollution assessment system based on meteorological factors and pollution transmission of claim 8, wherein said transmission contribution model building module comprises:
the station classifying sub-module is used for taking the test area as a station to be researched, and taking the area with the lowest concentration of the atmospheric pollutants in the upwind direction or the downwind direction of the test area as a background observation station;
the external transmission calculation sub-module is used for acquiring the air pollution concentration of the background observation station, taking the air pollution concentration of the station to be researched as the concentration of the background station, and calculating external transmission contribution according to the concentration of the background station and the concentration of the station to be researched.
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| CN117875576B (en) * | 2024-03-13 | 2024-05-24 | 四川国蓝中天环境科技集团有限公司 | Urban atmosphere pollution analysis method based on structured case library |
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