CN112505254B - Method and device for analyzing atmospheric pollution source, storage medium and terminal - Google Patents
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Abstract
The invention discloses an analysis method, a device, a storage medium and a terminal of an atmospheric pollution source, wherein the method comprises the following steps: acquiring atmospheric environment monitoring data of a selected area within a preset time period; inputting atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on empirical results for analysis, and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the composition of atmospheric pollution sources in a selected area within a preset time period; the analysis result is pushed to the terminal equipment of the appointed user, so that by adopting the embodiment of the application, the analysis result is presented in an image mode, and thus, the composition of the atmospheric pollution source in the selected area in the preset time period can be visually seen through the analysis result presented in the image mode, so that the user experience degree is improved; in addition, the analysis result is pushed to the terminal of the appointed user, so that the appointed user who customizes the push service can acquire the latest analysis result in real time.
Description
Technical Field
The invention relates to the technical field of computers, in particular to an analysis method, an analysis device, a storage medium and a terminal for an atmospheric pollution source.
Background
In recent years, as air pollution has become increasingly serious with urban development, PM2.5 has attracted considerable attention worldwide as a major air pollutant. PM2.5 means that the aerodynamic equivalent diameter in the ambient air is smallThe 2.5 μm particles have complex chemical compositions, contain various chemical components such as water-soluble ions, carbon components, elements of the crust of the earth, various trace elements and the like, have influence on human health, solar radiation, visibility, cloud and mist formation, particle growth, particle conversion process and the like, and also directly or indirectly influence stratospheric ozone and climate environment. At present, the research on carbon-containing components, heavy metal elements, nitrogen oxides and sulfur oxides is common and deep in domestic and overseas research. In recent years, attention has been paid to the analysis of the kind, content and source of the secondary inorganic water-soluble ion in PM 2.5. The water-soluble ion is an important component of PM2.5, and the secondary inorganic ion SO42-、NO3-And NH4+The compound is an important chemical species in the process of particulate pollution, the proportion sum of the three is up to 40-57% in east cities of China, and the compound has higher share rate for the extinction coefficient of atmosphere, which is a main reason for reducing visibility of many cities. The concentration of sulfate ions and nitrate ions is also an important reason for influencing the pH value of precipitation. Atmospheric particulate pollution is increasingly serious, and the contribution of a particulate source analysis technology for identifying and evaluating a pollution source provides scientific support for atmospheric pollution prevention and control. With the development of monitoring technology, the online monitoring instrument with high time resolution is widely applied to the observation of atmospheric pollutants, and the obtained online monitoring data is combined with a receptor model to be applied to the analysis research of the atmospheric pollutants.
The classical receptor model PMF (orthogonal matrix factorization) is mostly used for source resolution studies of offline sampled data. The positive definite matrix factor PMF model is firstly proposed by Paatero and the like, is a multivariate factor analysis tool, and divides a matrix of specific sample data into two matrixes by a least square method by utilizing the constraint condition that no obvious negative source exists: factor contribution (G) and factor summary (F). These factors are summarised and need to be judged, identified and interpreted by the user in order to get contributions from the particulate matter emission sources. The basic principle is that firstly, the error of each chemical component in the particulate matter is calculated by using weight, and then the main pollution source and the contribution rate thereof are determined by a least square method: assuming that X is an n × m matrix, n is the number of samples, and m is the number of chemical components, the matrix X is decomposed into a matrix G and a matrix F: wherein G is a contribution matrix of the particulate matter emission source of nxp, F is a composition spectrum matrix of the pollutant source of p x m, and p is the number of main pollution sources. The basic formula is as follows:
X＝G×F+E (1)
in the above formula (1), E represents uncertainty of model calculation. Where E is a residual matrix representing the difference between X and GF, and Q represents the difference between the actual data and the analysis result. In order to resolve G and F, the positive matrix factor mode resolution process requires Q to be minimized:
in the above formula (2), sijIs the standard deviation of X; xij、gij、fkj、eijX, G, F, E matrix elements, respectively, at gij≥0、fkjAnd under the constraint condition that the Q value is more than or equal to 0, solving the Q value through an iterative minimization algorithm.
The geometric growth of online monitoring data has urgent need for deep analysis and fusion analysis of data. Limited and high requirements of environment required by air quality mode analysis, PMF of a mathematical method becomes a breakthrough for online realization of source analysis software. Currently, many software manufacturers have successfully improved and have mature PMF online data source parsing software and run online on multiple platforms.
In the existing analysis method for the air pollution source, the form of the obtained analysis result is often a large amount of documents or data, a user cannot intuitively know the local air pollution source and the pollution conditions of different air pollution sources through the obtained analysis result, and the user experience degree is poor.
Disclosure of Invention
The embodiment of the application provides an analysis method and device for an atmospheric pollution source, a storage medium and a terminal. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
In a first aspect, an embodiment of the present application provides a method for resolving an atmospheric pollution source, where the method includes:
acquiring atmospheric environment monitoring data of a selected area within a preset time period;
inputting the atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on an empirical result for analysis, and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the atmospheric pollution source composition of the selected area in the preset time period;
and pushing the analysis result to the terminal equipment of the appointed user.
In one embodiment, the inputting the atmospheric monitoring data into an empirical result-based PMF orthogonal matrix factorization model for parsing further includes: and automatically adjusting parameters of each parameter in the PMF orthogonal matrix factorization model.
In one embodiment, the automatically tuning parameters of the PMF orthogonal matrix factorization model comprises:
inputting pollutant components of a monitoring area meeting a first preset condition into the PMF orthogonal matrix factorization model for operation to obtain each characteristic value;
determining the number of each inflection point factor according to each characteristic value;
determining the number of each factor which is in line with the number of each inflection point factor, taking the number of the factor with the minimum inter-species residual difference in the number of each factor as the selected factor, wherein the judgment condition for determining the number of each factor which is in line with the number of each factor comprises that the inter-species residual difference corresponding to each factor is less than or equal to a certain residual difference standard value;
and screening each selected factor number according to a preset configured factor-source matching relation and a second preset condition to obtain each screened factor number, and automatically adjusting parameters of the PMF model according to each screened factor number, wherein the second preset condition is an incidence relation between each screened factor and a corresponding source.
In one embodiment, the method further comprises:
judging whether the actually measured components are related to the model fitting result or not according to the correlation between the actually measured components of the pollutants in the monitoring area and the model fitting result and a third preset condition, if the correlation meets the third preset condition, judging that the actually measured components are related to the model fitting result, otherwise, judging that the actually measured components are not related to the model fitting result, and deleting the actually measured components.
In one embodiment, the third preset condition includes:
the correlation of the measured component with the model fitting result is close to 1, the fitted line slope is close to 1, and the intercept is close to zero.
In one embodiment, before the components meeting the first preset condition are input into the PMF orthogonal matrix factorization model for operation, the method further includes:
and acquiring detection limit and uncertainty of pollutant components in the monitored area.
In one embodiment, prior to said obtaining the detection limit and uncertainty of contaminant components in the monitored area, the method further comprises:
taking the lower threshold limit of the monitoring factor in the quality control data as the detection limit of the pollutant component in the monitoring area; or,
and reading the detection limit of the pollutant component in the monitoring area from the instrument end.
In a second aspect, an embodiment of the present application provides an apparatus for resolving an atmospheric pollution source, the apparatus including:
the acquisition unit is used for acquiring atmospheric environment monitoring data of a selected area within a preset time period;
the analysis unit is used for inputting the atmospheric environment monitoring data acquired by the acquisition unit into a PMF orthogonal matrix factorization model based on empirical results for analysis and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the atmospheric pollution source composition of the selected area in the preset time period;
and the pushing unit is used for pushing the analysis result analyzed by the analysis unit to the terminal equipment of the appointed user.
In a third aspect, embodiments of the present application provide a computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the above-mentioned method steps.
In a fourth aspect, an embodiment of the present application provides a terminal, which may include: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the above-mentioned method steps.
The technical scheme provided by the embodiment of the application can have the following beneficial effects:
in the embodiment of the application, atmospheric environment monitoring data of a selected area in a preset time period are obtained; inputting atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on empirical results for analysis, and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the composition of atmospheric pollution sources in a selected area within a preset time period; the analysis result is pushed to the terminal equipment of the appointed user, so that by adopting the embodiment of the application, the analysis result is presented in an image mode, and thus, the composition of the atmospheric pollution source in the selected area in the preset time period can be visually seen through the analysis result presented in the image mode, so that the user experience degree is improved; in addition, the analysis result is pushed to the terminal of the appointed user, so that the appointed user who customizes the push service can acquire the latest analysis result in real time.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic flow chart of a method for analyzing an atmospheric pollution source according to an embodiment of the present disclosure;
fig. 2 is a schematic flow chart illustrating automatic parameter adjustment in an analysis process of an atmospheric pollution source according to an embodiment of the present disclosure;
fig. 3 is a schematic flowchart of an automatic parameter adjusting method of a PMF model in a specific application scenario according to an embodiment of the present application;
fig. 4 is a schematic diagram of an analysis result presented in an image manner in a specific application scenario provided in the embodiment of the present application;
fig. 5 is a schematic structural diagram of an apparatus for analyzing an atmospheric pollution source according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of a terminal according to an embodiment of the present application.
Detailed Description
The following description and the drawings sufficiently illustrate specific embodiments of the invention to enable those skilled in the art to practice them.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Based on the existing method, the local air pollution source and the pollution conditions of different air pollution sources can not be intuitively obtained through the obtained analysis result. Therefore, the present application provides an analysis method, an apparatus, a storage medium, and a terminal for analyzing an atmospheric pollution source, so as to solve the above problems in the related art. According to the technical scheme, atmospheric environment monitoring data of a selected area in a preset time period are obtained; inputting atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on empirical results for analysis, and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the composition of atmospheric pollution sources in a selected area within a preset time period; the analysis result is pushed to the terminal equipment of the appointed user, so that by adopting the embodiment of the application, the analysis result is presented in an image mode, and thus, the composition of the atmospheric pollution source in the selected area in the preset time period can be visually seen through the analysis result presented in the image mode, so that the user experience degree is improved; in addition, pushing the analysis result to the terminal of the designated user enables the designated user who customizes the push service to obtain the latest analysis result in real time, which is described in detail below with an exemplary embodiment.
The method for analyzing the source of atmospheric pollution provided by the embodiments of the present application will be described in detail with reference to fig. 1 to 4. The method for analyzing the atmospheric pollution source can be realized by depending on a computer program and can be operated on an analyzing device of the atmospheric pollution source. The computer program may be integrated into the application or may run as a separate tool-like application. The user terminal in the embodiment of the present application includes, but is not limited to: personal computers, tablet computers, handheld devices, in-vehicle devices, wearable devices, computing devices or other processing devices connected to a wireless modem, and the like. The user terminals may be called different names in different networks, for example: user equipment, access terminal, subscriber unit, subscriber station, mobile station, remote terminal, mobile device, user terminal, wireless communication device, user agent or user equipment, cellular telephone, cordless telephone, Personal Digital Assistant (PDA), terminal equipment in a 5G network or future evolution network, and the like.
Fig. 1 is a schematic flow chart of a method for analyzing an atmospheric pollution source according to an embodiment of the present disclosure; as shown in fig. 1, the method for analyzing an atmospheric pollution source according to the embodiment of the present application may include the following steps:
s101, acquiring atmospheric environment monitoring data of a selected area in a preset time period;
in the embodiment of the present application, the preset time period and the selected area may be configured according to different application scenarios, and are not described herein again.
S102, inputting atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on an empirical result for analysis, and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the composition of atmospheric pollution sources in a selected area within a preset time period; the composition of the atmospheric pollution sources in the selected area within the preset time period can be visually seen through the analysis result presented in an image mode, so that the user experience degree is improved.
S103, pushing the analysis result to the terminal equipment of the appointed user; the analysis result is pushed to the terminal of the appointed user, so that the appointed user who customizes the push service can obtain the latest analysis result in real time.
In the embodiment of the application, the step of inputting the atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on empirical results for analysis comprises the following steps:
and automatically adjusting parameters of each parameter in the PMF orthogonal matrix factorization model.
Please refer to fig. 2, which is a schematic flow chart illustrating automatic parameter adjustment in an analysis process of an atmospheric pollution source according to an embodiment of the present disclosure. As shown in fig. 2, the automatically tuning parameters of the PMF orthogonal matrix factorization model in the analytic method provided in the embodiment of the present application may include the following steps:
s201, inputting the pollutant components of the monitoring area meeting the first preset condition into a PMF orthogonal matrix factorization model for operation to obtain each characteristic value.
In the embodiment of the present application, each feature value may be a Q/Qexp value of each factor, each feature value may also be a component residual, or each feature value is a time series corresponding to the Q/Qexp value.
In the embodiment of the present application, for a detailed description of the Q/Qexp value of each factor, see the related description on pages 35 to 36 of the official website of the national environmental protection agency with the file name "EPA PMF5.0USER GUIDE FINAL FINAL", the website of the official website of the national environmental protection agency is specifically as follows: "https://cfpub.epa.gov/si/si_ public_record_report.cfmLab＝NERL&count＝10000&dirEntryId＝308292&searchall ＝&showcriteria＝2&simplesearch＝0&timstype＝”And will not be described herein.
In the embodiment of the present application, the first preset condition includes: and the component which is within a preset time period and has the data effective rate greater than a preset effective rate threshold value.
For example, a preset time period capable of automatically recognizing the validity of data may be configured in advance, that is: only within the preset time period, the data efficiency can be automatically identified.
Under a specific application scene, the components with the effective rate of more than eighty percent of the pre-configured data can be input into the PMF orthogonal matrix factorization model, so that various characteristic values obtained through operation are more matched with the actual situation, and the accuracy of automatic parameter adjustment is improved.
As shown in fig. 3, a flowchart of an automatic parameter adjusting method of a PMF model in a specific application scenario of the embodiment of the present application is shown; starting to select M pieces of data, judging the number of effective data, and determining the number of factors from at least N pieces of effective data if the number of effective data is greater than N pieces of effective data; if the number of the effective data is less than or equal to N, reselecting M + X data until the number of the effective data is greater than N, and determining the factor number from the M + X data, wherein M, N, X is a natural number, M can be 200, 300, 400, 500 and the like, N can be 50, 100, 150 and the like, X can be 50, 100, 150 and the like, and preferably M, N, X is 300, 100 respectively.
In the embodiment of the application, the factor number is used for referring to the number of several types of important sources of a certain type of atmospheric pollution at present. For example, in a specific application scenario, it is determined that the current factor of a certain type of atmospheric pollution is 7, and there are mainly 7 types of pollutant sources of the current certain type of atmospheric pollution. Here, this is merely an example, and different factors may be determined according to different application scenarios, which is not described herein again.
In a possible implementation manner, before inputting the components meeting the first preset condition into the PMF orthogonal matrix factorization model for operation to obtain each feature value, the method further includes the following steps:
and acquiring detection limit and uncertainty of pollutant components in the monitored area.
In the embodiment of the present application, the detection limit of the component may be determined in two ways, specifically as follows:
taking the lower limit of the monitoring factor threshold in the quality control data as the detection limit of pollutant components in the monitoring area; alternatively, the detection limit of the contaminant component in the monitored area is read from the instrument side. The above lists only two common ways of determining the detection limits of the components, and can also be determined or read by other methods, which are not described herein again.
In the embodiment of the present application, the uncertainty of a component is generated according to the monitoring principle of the component and the conventional method, or configured manually, and is not described herein again.
Under a certain application scene, for the condition that the source contribution degree is zero, the following processing is carried out:
and for the condition that the source contribution degree is zero, automatically re-performing automatic parameter adjustment on the data in the preset time period, and reducing the uncertainty of the source indication species until the source contribution degree is greater than zero.
In the embodiment of the application, several types of sources of a certain type of current atmospheric pollution are configured in advance, and preset conditions are respectively configured for different types of sources in advance. For example, in a specific application scenario, a type of main source, source a, of a current type of atmospheric pollution is preconfigured, and a preset condition a is preconfigured for source a. The condition that the source contribution degree in the above step is zero means that the uncertainty of the source indicator species is reduced until the obtained source is not matched with the preset condition a configured in advance. The condition that the source contribution degree is zero means that the uncertainty of the source indicator species is reduced, and the obtained source does not accord with the preset condition A configured in advance.
S202, determining the number of each inflection factor according to each characteristic value.
In the embodiment of the present application, each inflection factor number is the inflection factor number corresponding to each factor number Q/Qexp value.
For a detailed description of the Q/Qexp values of the respective factors, see the related description of pages 35 to 36 of the official document name "EPAPMF5.0USERGUIDEFINALFINAL" of the national environmental protection agency, the website of the official document of the national environmental protection agency is specifically as follows:
“https://cfpub.epa.gov/si/si_public_record_report.cfmLab＝NERL&count ＝10000&dirEntryId＝308292&searchall＝&showcriteria＝2&simplesearch＝0& timstype＝", will not be described in detail herein.
In the embodiment of the present application, the inflection factor number refers to a numerical value of a factor causing data mutation, for example, in a certain application scenario, the current factor number of a certain type of atmospheric pollution is 7, that is: currently, the main sources of a certain type of atmospheric pollution are 7 types, and the corresponding factor value of a point where data (e.g., component concentration data) is mutated is the inflection factor number, for example, the corresponding factor value of a point where data is mutated is 6, that is: the sixth major source, namely: in this application scenario, the number of inflection factors determined is 6.
As shown in fig. 3, a method for determining each inflection point factor number of each factor number Q/Qexp value is shown, if each component difference in the component residual corresponding to the inflection point factor number of any factor number Q/Qexp value is less than or equal to a certain residual difference standard value (the residual difference standard value is an empirical value obtained from a plurality of tests), the inflection point factor number is an available inflection point factor number, if each component difference in the component residual corresponding to the inflection point factor number of any factor number Q/Qexp value is greater than a certain residual difference standard value (the residual difference is an empirical value obtained from a plurality of tests), another inflection point factor number is selected for the above-mentioned determination process, if all inflection point factor numbers do not meet the requirements, the uncertainty of the residual with the greater difference of other components is increased, by operating a certain number of uncertainty setting strategies (the number is related to the number of components to be adjusted), until a matching factor number is obtained.
In the embodiment of the present application, for a detailed description of the Q/Qexp value of each factor, see the related description of pages 35 to 36 of the official website of the national environmental protection agency with the file name "EPAPMF5.0USERGUIDEFINALFINAL", the website of the official website of the national environmental protection agency is specifically as follows:
“https://cfpub.epa.gov/si/si_public_record_report.cfmLab＝NERL&count ＝10000&dirEntryId＝308292&searchall＝&showcriteria＝2&simplesearch＝0& timstype＝", will not be described in detail herein.
In the embodiment of the present application, the process of determining the certain residual difference standard value is described as follows:
considering the residual values or the magnitude order differences of each species, the setting of a "standard value for a residual difference" is determined by taking the logarithm of the residual result of each component and then performing a difference method, and in addition, the judgment is performed by combining sample data, which is not described herein again.
S203, determining the number of the factors according to the number of the inflection points, taking the number of the factors with the minimum inter-species residual difference as the selected number of the factors, wherein the judgment condition for determining the number of the factors comprises that the inter-species residual difference corresponding to each number of the factors is less than or equal to a certain residual difference standard value.
And S204, screening each selected factor number according to a preset configured factor-source matching relation and a second preset condition to obtain each screened factor number, and automatically adjusting parameters of the PMF model according to each screened factor number, wherein the second preset condition is an incidence relation between each screened factor and a corresponding source.
In the embodiment of the application, the pre-configured factor-source matching relationship can be configured according to different application scenarios. For example, in a specific application scenario, the factor-source matching relationship may be: the factor is nitrate and the source is secondary pollution. The above are merely examples, and other factor-source relationships may also be configured according to different application scenarios, which are not described herein again.
In a specific application scenario, the association relationship between each screened factor in the second preset condition and the corresponding source may be: for example, one of the factors after screening is calcium ion, and the association relationship between the calcium ion and the corresponding source in the second preset condition is specifically: the source of calcium ion can be crusta, and the source of calcium ion can also be sea.
In the embodiment of the present application, the preset configured factor-source matching relationship is often a matching relationship obtained according to a large number of big data statistics results, and the matching relationship can be found from an existing database and is not described herein again.
In the embodiment of the application, for the condition that the tracer species indicates multiple sources simultaneously, the source indicated by different components of the factor together is selected; thus, the mapping relation between the screened factor number and the corresponding source identification can be ensured to have one-to-one correspondence.
In the embodiment of the present application, in order to further ensure the accuracy of automatic parameter adjustment, the automatic parameter adjustment method provided in the embodiment of the present application may further perform judgment and screening on actually measured components, and the specific steps are as follows:
and judging whether the actual measurement component is related to the model fitting result or not according to the correlation between the actual measurement component of the pollutant in the monitoring area and the model fitting result and a third preset condition, if the correlation meets the third preset condition, judging that the actual measurement component is related to the model fitting result, otherwise, judging that the actual measurement component is not related to the model fitting result, and deleting the actual measurement component.
In the embodiment of the application, the model fitting result refers to a fitting result obtained by operating a PMF orthogonal matrix factorization model based on an empirical result according to a preconfigured factor number, and the fitting result includes pollutant simulation component concentration data of each monitoring area.
In the method for analyzing the atmospheric pollution source provided by the embodiment of the application, different factors can be configured, namely; if the current factor of a certain type of atmospheric pollution is set to be 7, namely: and if 7 types of main sources of certain type of atmospheric pollution exist currently, the corresponding model fitting result is obtained by operating a PMF orthogonal matrix factorization model based on empirical results according to the number of preconfigured factors 7, and the fitting result comprises pollutant simulation component concentration data of each monitoring area.
After the pollutant simulation component concentration data of each monitoring area are obtained, comparing the pollutant simulation component concentration of each monitoring area with the pollutant actual measurement component concentration of the same monitoring area, judging whether the pollutant simulation component concentration of each monitoring area is close to the pollutant actual measurement component concentration of the same monitoring area, and if the pollutant simulation component concentration of each monitoring area is close to the pollutant actual measurement component concentration of the same monitoring area, judging that the actual measurement component is related to the model fitting result if the pollutant simulation component concentration of each monitoring area is within the preset difference threshold range.
In practical application, the difference between the two may be configured according to different application scenarios, and here, the difference between the two is not specifically limited.
In this embodiment of the present application, in a specific application scenario, the third preset condition includes: the correlation of the measured component with the model fitting result is close to 1, the fitted line slope is close to 1, and the intercept is close to zero. In addition to the listed third preset conditions, other third preset conditions may be configured according to the requirements of different application scenarios, and are not described herein again.
If the correlation between the actual measurement component of the pollutant in the monitoring area and the model fitting result meets the third preset condition, judging that the actual measurement component of the pollutant in the monitoring area is correlated with the model fitting result, and judging whether the next actual measurement component is correlated with the model fitting result; if the correlation between the actual measurement component of the pollutant in the monitoring area and the model fitting result does not meet the third preset condition, judging that the actual measurement component of the pollutant in the monitoring area and the model fitting result do not have the correlation, and deleting the actual measurement component; therefore, through the judgment process, the fact that each screened monitored area pollutant actual measurement component has correlation with the model fitting result and the correlation between the screened monitored area pollutant actual measurement component and the model fitting result meets the third preset condition can be guaranteed.
According to the analysis method for the atmospheric pollution source, the automatic parameter adjusting process is introduced, so that the manual parameter adjusting time can be effectively reduced, and the data processing speed is increased.
Fig. 3 is a schematic flow chart of an automatic parameter adjusting method of a PMF model in a specific application scenario according to an embodiment of the present application.
The steps of the method for automatically adjusting the parameters as shown in fig. 3 are as follows:
selecting effective data from M pieces of data, further determining the number of factors if the number of the effective data is greater than N pieces of data, reselecting nearly M + X pieces of data if the number of the effective data is less than or equal to N pieces of data, and selecting the effective data from the M + X pieces of data until the number of the effective data is greater than N pieces of data; wherein M, N, X are all natural numbers, M can be 200, 300, 400, 500, etc., N can be 50, 100, 150, etc., X can be 50, 100, 150, etc., preferably M, N, X is 300, 100, respectively. After determining the factor number, further determining the component; after the components are determined, further determining detection limit and uncertainty; when the pre-configured data efficiency is more than the preset data efficiency (for example, the preset data efficiency is more than eighty percent), the components can be input into the PMF orthogonal matrix factorization model, and the PMF orthogonal matrix factorization model is operated; the process of determining the number of each inflection point factor of each factor number Q/Qexp value refers to the related or similar description in fig. 1, and is not repeated herein; selecting the number of factors with minimum residual difference among species; and judging whether the correlation R2 of the fitting result of the actual measurement component and the model is close to 1, the slope of the fitted line is close to 1 and the intercept is close to zero, if the correlation R2 of the fitting result of the actual measurement component and the model is close to 1, the slope of the fitted line is close to 1 and the intercept is close to zero, performing factor-source matching to obtain the number of each screened factor, and automatically adjusting the parameter of the PMF model according to the number of each screened factor.
In the embodiment of the present application, for a detailed description of the Q/Qexp value of each factor, see the related description on pages 35 to 36 of the official website of the national environmental protection agency with the file name "EPA PMF5.0USER GUIDE FINAL FINAL", the website of the official website of the national environmental protection agency is specifically as follows: "https://cfpub.epa.gov/si/si_ public_record_report.cfmLab＝NERL&count＝10000&dirEntryId＝308292&searchall ＝&showcriteria＝2&simplesearch＝0&timstype＝", will not be described in detail herein.
For the description of the automatic reference adjusting method in fig. 3, refer to the related or similar description in fig. 2, and will not be described herein again.
According to actual test results, the automatic parameter adjusting method provided by the embodiment of the disclosure can successfully realize a source analysis result with a data acquisition time frequency of 5min (monitoring of the navigation vehicle), and can further shorten the updating time by adjusting computing resources; according to the acquired hour monitoring data, the workload of manual parameter adjustment can be reduced by 80%. Compared with the artificial parameter adjustment result, the error range is between 13.4 percent below zero and 21.3 percent below zero. The following table 1 is a comparison table of the automatic parameter adjusting result and the manual parameter adjusting result provided in the embodiments disclosed in the present application, and specifically includes the following steps:
table 1: comparison table of automatic parameter adjusting result and manual parameter adjusting result
The comments in table 1 above are explained as follows:
note 1: taking a 24-hour daily result of a sample;
note 2:
Fig. 4 is a schematic diagram of an analysis result presented in an image manner in a specific application scenario according to an embodiment of the present application. As shown in the schematic diagram of the analysis result shown in fig. 4, the composition of the atmospheric pollution source in the selected area within the preset time period can be visually seen through the analysis result presented in the form of an image, thereby improving the user experience.
In the embodiment of the application, atmospheric environment monitoring data of a selected area in a preset time period are obtained; inputting atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on empirical results for analysis, and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the composition of atmospheric pollution sources in a selected area within a preset time period; the analysis result is pushed to the terminal equipment of the appointed user, so that by adopting the embodiment of the application, the analysis result is presented in an image mode, and thus, the composition of the atmospheric pollution source in the selected area in the preset time period can be visually seen through the analysis result presented in the image mode, so that the user experience degree is improved; in addition, the analysis result is pushed to the terminal of the appointed user, so that the appointed user who customizes the push service can acquire the latest analysis result in real time.
The following is an embodiment of the analyzing apparatus for analyzing a source of atmospheric pollution according to the present invention, which can be used to perform an embodiment of the analyzing method for a source of atmospheric pollution according to the present invention. For details not disclosed in the embodiments of the analysis apparatus for sources of atmospheric pollution of the present invention, please refer to the embodiments of the analysis method for sources of atmospheric pollution of the present invention.
Fig. 5 is a schematic structural diagram of an atmospheric pollution source analysis device according to an exemplary embodiment of the present invention. The analyzing device for the atmospheric pollution source may be implemented as all or a part of the terminal by software, hardware, or a combination of both. The analysis device for the atmospheric pollution source comprises an acquisition unit 10, an analysis unit 20 and a pushing unit 30.
Specifically, the acquiring unit 10 is configured to acquire atmospheric environment monitoring data of a selected area within a preset time period;
the analysis unit 20 is configured to input the atmospheric environment monitoring data acquired by the acquisition unit 10 into a PMF orthogonal matrix factorization model based on an empirical result for analysis, and output an analysis result presented in an image manner, where the analysis result is used to represent an atmospheric pollution source composition of a selected area within a preset time period;
a pushing unit 30, configured to push the analysis result analyzed by the analysis unit 20 to the terminal device of the specified user.
Optionally, the parsing unit 20 is configured to automatically tune parameters of each parameter in the PMF orthogonal matrix factorization model.
Optionally, the parsing unit 20 is specifically configured to:
inputting pollutant components of a monitoring area meeting a first preset condition into a PMF orthogonal matrix factorization model for operation to obtain each characteristic value;
determining the number of each inflection point factor according to each characteristic value;
determining the number of each factor which is in line with the number of each inflection point factor, taking the number of the factor with the minimum inter-species residual difference in the number of each factor as the selected factor, wherein the judgment condition for determining the number of each factor which is in line with the number of each factor comprises that the inter-species residual difference corresponding to each factor is less than or equal to a certain residual difference standard value;
and screening each selected factor number according to a preset configured factor-source matching relation and a second preset condition to obtain each screened factor number, and automatically adjusting parameters of the PMF model according to each screened factor number, wherein the second preset condition is an incidence relation between each screened factor and a corresponding source.
Optionally, the apparatus further comprises:
a determining unit (not shown in fig. 5) configured to determine, according to a correlation between an actually measured component of a pollutant in the monitoring area and a model fitting result and a third preset condition, whether the actually measured component is related to the model fitting result, if the correlation satisfies the third preset condition, determine that the actually measured component is related to the model fitting result, otherwise, determine that the actually measured component is not related to the model fitting result;
and a deleting unit (not shown in fig. 5) for deleting the measured component when the judging unit judges that the measured component is not related to the model fitting result.
Optionally, the third preset condition includes: the correlation of the measured component with the model fitting result is close to 1, the fitted line slope is close to 1, and the intercept is close to zero.
Optionally, the obtaining unit 10 is further configured to: before the analysis unit 20 inputs the components meeting the first preset condition into the PMF orthogonal matrix factorization model for operation to obtain each characteristic value, the detection limit and uncertainty of the pollutant components in the monitoring area are obtained.
Optionally, the apparatus further comprises:
a detection limit determining unit (not shown in fig. 5) configured to use a lower threshold limit of the monitoring factor in the quality control data as a detection limit of the pollutant component in the monitoring area before the obtaining unit 10 obtains the detection limit and the uncertainty of the pollutant component in the monitoring area; alternatively, the detection limit of the contaminant component in the monitored area is read from the instrument side.
It should be noted that, when the analysis device for an air pollution source provided in the foregoing embodiment executes an analysis method for an air pollution source, the above-mentioned division of each functional module is merely used as an example, and in practical applications, the above-mentioned function distribution may be completed by different functional modules according to needs, that is, the internal structure of the equipment is divided into different functional modules, so as to complete all or part of the above-mentioned functions. In addition, the analyzing device for the source of atmospheric pollution provided by the above embodiments and the analyzing method for the source of atmospheric pollution belong to the same concept, and the implementation process is detailed in the analyzing method for the source of atmospheric pollution, which is not described herein again.
In the embodiment of the application, the acquisition unit is used for acquiring atmospheric environment monitoring data of a selected area within a preset time period; the analysis unit is used for inputting the atmospheric environment monitoring data acquired by the acquisition unit into a PMF orthogonal matrix factorization model based on empirical results for analysis and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the composition of atmospheric pollution sources in a selected area within a preset time period; and the pushing unit is used for pushing the analysis result analyzed by the analysis unit to the terminal equipment of the appointed user. According to the analysis method for the atmospheric pollution source, the analysis result obtained by analysis is presented in an image mode, so that the composition of the atmospheric pollution source in the selected area in the preset time period can be visually seen through the analysis result presented in the image mode, and the user experience degree is improved; in addition, the analysis result is pushed to the terminal of the appointed user, so that the appointed user who customizes the push service can acquire the latest analysis result in real time.
The present invention also provides a computer readable medium, on which program instructions are stored, which program instructions, when executed by a processor, implement the method for analyzing an atmospheric pollution source provided by the above-mentioned method embodiments.
The invention also provides a computer program product containing instructions which, when run on a computer, cause the computer to perform the method for resolving a source of atmospheric pollution as described in the various method embodiments above.
Please refer to fig. 6, which provides a schematic structural diagram of a terminal according to an embodiment of the present application. As shown in fig. 6, terminal 1000 can include: at least one processor 1001, at least one network interface 1004, a user interface 1003, memory 1005, at least one communication bus 1002.
Wherein a communication bus 1002 is used to enable connective communication between these components.
The user interface 1003 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.
The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Alternatively, the processor 1001 may be implemented in at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 1001 may integrate one or more of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. Wherein, the CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It is understood that the modem may not be integrated into the processor 1001, but may be implemented by a single chip.
The Memory 1005 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable medium. The memory 1005 may be used to store an instruction, a program, code, a set of codes, or a set of instructions. The memory 1005 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the various method embodiments described above, and the like; the storage data area may store data and the like referred to in the above respective method embodiments. The memory 1005 may optionally be at least one memory device located remotely from the processor 1001. As shown in fig. 6, the memory 1005, which is a type of computer storage medium, may include an operating system, a network communication module, a user interface module, and an analysis application of an atmospheric pollution source.
In the terminal 1000 shown in fig. 6, the user interface 1003 is mainly used as an interface for providing input for a user, and acquiring data input by the user; the processor 1001 may be configured to call an analysis application of the atmospheric pollution source stored in the memory 1005, and specifically perform the following operations:
acquiring atmospheric environment monitoring data of a selected area within a preset time period;
inputting atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on empirical results for analysis, and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the composition of atmospheric pollution sources in a selected area within a preset time period;
and pushing the analysis result to the terminal equipment of the appointed user.
In one embodiment, the processor 1001, in performing the parsing of the atmospheric environmental monitoring data into the empirical result based PMF orthogonal matrix factorization model, performs the following operations:
and automatically adjusting parameters of each parameter in the PMF orthogonal matrix factorization model.
In one embodiment, processor 1001, in performing the auto-parameterization of the parameters of the PMF orthonormal matrix factorization model, performs the following operations:
inputting pollutant components of a monitoring area meeting a first preset condition into a PMF orthogonal matrix factorization model for operation to obtain each characteristic value;
determining the number of each inflection point factor according to each characteristic value;
determining the number of each factor which is in line with the number of each inflection point factor, taking the number of the factor with the minimum inter-species residual difference in the number of each factor as the selected factor, wherein the judgment condition for determining the number of each factor which is in line with the number of each factor comprises that the inter-species residual difference corresponding to each factor is less than or equal to a certain residual difference standard value;
and screening each selected factor number according to a preset configured factor-source matching relation and a second preset condition to obtain each screened factor number, and automatically adjusting parameters of the PMF model according to each screened factor number, wherein the second preset condition is an incidence relation between each screened factor and a corresponding source.
In one embodiment, the processor 1001 also performs the following operations:
and judging whether the actual measurement component is related to the model fitting result or not according to the correlation between the actual measurement component of the pollutant in the monitoring area and the model fitting result and a third preset condition, if the correlation meets the third preset condition, judging that the actual measurement component is related to the model fitting result, otherwise, judging that the actual measurement component is not related to the model fitting result, and deleting the actual measurement component.
In one embodiment, the third preset condition includes: the correlation of the measured component with the model fitting result is close to 1, the fitted line slope is close to 1, and the intercept is close to zero.
In one embodiment, before performing the operation of inputting the components satisfying the first preset condition into the PMF orthogonal matrix factorization model to obtain the feature values, the processor 1001 further performs the following operations:
and acquiring detection limit and uncertainty of pollutant components in the monitored area.
In one embodiment, processor 1001, prior to performing the steps of obtaining the detection limit and uncertainty of the contaminant component in the monitored area, further performs the following:
taking the lower limit of the monitoring factor threshold in the quality control data as the detection limit of pollutant components in the monitoring area; alternatively, the detection limit of the contaminant component in the monitored area is read from the instrument side.
In the embodiment of the application, atmospheric environment monitoring data of a selected area in a preset time period are obtained; inputting atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on empirical results for analysis, and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the composition of atmospheric pollution sources in a selected area within a preset time period; and pushing the analysis result to the terminal equipment of the appointed user. The analysis result obtained by the analysis method is presented in an image mode, so that the composition of the atmospheric pollution source in the selected area in the preset time period can be visually seen through the analysis result presented in the image mode, and the user experience degree is improved; in addition, the analysis result is pushed to the terminal of the appointed user, so that the appointed user who customizes the push service can acquire the latest analysis result in real time.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present application and is not to be construed as limiting the scope of the present application, so that the present application is not limited thereto, and all equivalent variations and modifications can be made to the present application.
Claims (8)
1. A method for resolving a source of atmospheric pollution, the method comprising:
acquiring atmospheric environment monitoring data of a selected area within a preset time period;
inputting the atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on an empirical result for analysis, and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the atmospheric pollution source composition of the selected area in the preset time period;
the inputting the atmospheric environment monitoring data into a PMF orthogonal matrix factorization model based on empirical results for analysis comprises:
automatically adjusting parameters of each parameter in the PMF orthogonal matrix factorization model;
the automatically adjusting parameters of each parameter in the PMF orthogonal matrix factorization model comprises:
inputting pollutant components of a monitoring area meeting a first preset condition into the PMF orthogonal matrix factorization model for operation to obtain each characteristic value; the first preset condition includes: the component which is in a preset time period and has the data effective rate greater than a preset effective rate threshold value;
determining the number of each inflection point factor according to each characteristic value;
determining the number of each factor which is in line with the number of each inflection point factor, taking the number of the factor with the minimum inter-species residual difference in the number of each factor as the selected factor, wherein the judgment condition for determining the number of each factor which is in line with the number of each factor comprises that the inter-species residual difference corresponding to each factor is less than or equal to a certain residual difference standard value;
screening each selected factor number according to a preset configured factor-source matching relation and a second preset condition to obtain each screened factor number, and automatically adjusting parameters of the PMF orthogonal matrix factorization model according to each screened factor number, wherein the second preset condition is an incidence relation between each screened factor and a corresponding source;
and pushing the analysis result to the terminal equipment of the appointed user.
2. The method of claim 1, further comprising:
judging whether the actually measured components are related to the model fitting result or not according to the correlation between the actually measured components of the pollutants in the monitoring area and the model fitting result and a third preset condition, if the correlation meets the third preset condition, judging that the actually measured components are related to the model fitting result, otherwise, judging that the actually measured components are not related to the model fitting result, and deleting the actually measured components.
3. The method according to claim 2, wherein the third preset condition comprises:
the correlation of the measured component with the model fitting result is close to 1, the fitted line slope is close to 1, and the intercept is close to zero.
4. The method according to claim 1, wherein before the components satisfying the first predetermined condition are input to the PMF orthogonal matrix factorization model for operation, the method further comprises:
and acquiring detection limit and uncertainty of pollutant components in the monitored area.
5. The method of claim 4, wherein prior to said obtaining a detection limit and uncertainty of a contaminant component in the monitored area, the method further comprises:
taking the lower threshold limit of the monitoring factor in the quality control data as the detection limit of the pollutant component in the monitoring area; or,
and reading the detection limit of the pollutant component in the monitoring area from the instrument end.
6. An apparatus for resolving a source of atmospheric pollution, said apparatus comprising:
the acquisition unit is used for acquiring atmospheric environment monitoring data of a selected area within a preset time period;
the analysis unit is used for inputting the atmospheric environment monitoring data acquired by the acquisition unit into a PMF orthogonal matrix factorization model based on empirical results for analysis and outputting an analysis result presented in an image mode, wherein the analysis result is used for representing the atmospheric pollution source composition of the selected area in the preset time period;
the analysis unit is used for: automatically adjusting parameters of each parameter in the PMF orthogonal matrix factorization model;
the analysis unit is specifically configured to: inputting pollutant components of a monitoring area meeting a first preset condition into the PMF orthogonal matrix factorization model for operation to obtain each characteristic value; the first preset condition includes: the component which is in a preset time period and has the data effective rate greater than a preset effective rate threshold value;
determining the number of each inflection point factor according to each characteristic value;
determining the number of each factor which is in line with the number of each inflection point factor, taking the number of the factor with the minimum inter-species residual difference in the number of each factor as the selected factor, wherein the judgment condition for determining the number of each factor which is in line with the number of each factor comprises that the inter-species residual difference corresponding to each factor is less than or equal to a certain residual difference standard value;
screening each selected factor number according to a preset configured factor-source matching relation and a second preset condition to obtain each screened factor number, and automatically adjusting parameters of the PMF orthogonal matrix factorization model according to each screened factor number, wherein the second preset condition is an incidence relation between each screened factor and a corresponding source;
and the pushing unit is used for pushing the analysis result analyzed by the analysis unit to the terminal equipment of the appointed user.
7. A computer storage medium, characterized in that it stores a plurality of instructions adapted to be loaded by a processor and to carry out the method steps according to any one of claims 1 to 5.
8. A terminal, comprising: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the method steps of any of claims 1 to 5.
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| CN117129638B (en) * | 2023-10-26 | 2024-01-12 | 江西怡杉环保股份有限公司 | Regional air environment quality monitoring method and system |
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Application publication date: 20210316 Assignee: Beijing Zhongke Sanqing Environmental Technology Co.,Ltd. Assignor: 3CLEAR TECHNOLOGY Co.,Ltd. Contract record no.: X2022980012305 Denomination of invention: A method, device, storage medium and terminal for analyzing the source of air pollution Granted publication date: 20210921 License type: Common License Record date: 20220815 |