CN116089771A - Particulate matter source analysis method, device, terminal and storage medium - Google Patents

Abstract

The application provides a particulate matter source analysis method, a particulate matter source analysis device, a particulate matter source analysis terminal and a particulate matter source storage medium. Comprising the following steps: acquiring the number concentration data of the particles with different particle diameters of at least one pollution source, and establishing a particle size spectrum library of a typical particle emission source; monitoring the number concentration data of the particulate matters of the target environmental receptor for a preset period of time; identifying first contribution rates of different particle size sections of different pollution sources in a target environmental receptor in a preset period based on an orthogonal matrix factor analysis model according to the number concentration data of the particles of the target environmental receptor in the preset period; and searching a pollution source of atmospheric particulates in the target environmental receptor of the preset time period from a typical particulate matter emission source particle size spectrum library based on the first contribution rate of particulates of different particle size segments of different pollution sources in the target environmental receptor of the preset time period. The method and the device can improve the accuracy of the pollutant source analysis result of the particulate matters in the environmental receptor.

Description

Particulate matter source analysis method, device, terminal and storage medium

Technical Field

The present disclosure relates to the field of atmospheric particulate source analysis technologies, and in particular, to a particulate source analysis method, a particulate source analysis device, a particulate source terminal, and a particulate source storage medium.

Background

Aiming at the problems that the emission sources of primary particles, especially coarse particles of 2.5-10 mu m, in urban atmosphere are complex, construction sites, bare soil, road dust, storage yards, industrial emission and the like are complicated, and pollution emission caused by different sources due to the difference of engineering stages or control degrees is also changed, so that the coarse particles have unique characteristics in space-time distribution. With the increasing demands of the atmospheric environmental management for refinement, analyzing the source of PM2.5 based solely on the receptor resolution technique has not been able to meet the demands of the primary particulate emission source for refinement management.

At present, the method for analyzing the source of the particulate matters mainly comprises an active list method, a diffusion model method, a receptor model method and the like, the receptor model method is most popular, the source of the particulate matters is rich, and the source of PM10 or PM2.5 is analyzed only based on a receptor analysis technology, so that the requirement of fine management of the emission source of the primary particulate matters cannot be met. In the aspect of fine source analysis of particulate matters, a method based on hierarchical sampling and laboratory analysis can be adopted, and the defects are long sampling period and low time resolution; in addition, based on the single-particle scanning electron microscope SEM/TEM-EDS technology, the morphology, the composition, the particle size, the mixing state and other information of the particles can be obtained, and the particle source analysis is carried out through the particle morphology analysis.

In the face of the current particulate matter management demands, the comprehensive application of various tracing and analyzing technologies is urgently needed to be enhanced, so that a finer particulate matter source analyzing result with a divided particle size is obtained, and data support is provided for carrying out comprehensive supervision, prevention and control of primary particulate matters.

Disclosure of Invention

The application provides a method, a device, a terminal and a storage medium for analyzing a particulate matter source, which are used for solving the problem that a pollution source analysis result of particulate matters in an environment receptor is not fine enough in the prior art.

In a first aspect, the present application provides a method of analyzing a source of particulate matter, comprising:

acquiring data of the number concentration of the particles with different particle diameters of at least one pollution source, and establishing a particle size spectrum library of a typical particle emission source, wherein the pollution source comprises road dust, construction dust, tail gas dust, combustion source dust and process dust Cheng Chen; the library of typical particulate emission source particle size spectra includes a first contribution rate of particulate matter of different particle size segments of any source of pollution; the first contribution rate is the ratio of the number concentration data of the particulate matters in any particle size section to the number concentration data of the particulate matters in the pollution source;

monitoring the number concentration data of the particulate matters of the target environmental receptor for a preset period of time;

Identifying first contribution rates of different particle size sections of different pollution sources in the target environmental receptor in the preset period based on an orthogonal matrix factor analysis model according to the number concentration data of the particulate matters of the target environmental receptor in the preset period;

and searching the pollution sources of the atmospheric particulates in the target environmental acceptors of the preset time period from the typical particulate emission source particle size spectrum library based on the first contribution rate of the particulates of different particle size segments of different pollution sources in the target environmental acceptors of the preset time period.

In a second aspect, the present application provides a particulate matter source analysis device comprising:

the system comprises a building module, a control module and a control module, wherein the building module is used for obtaining the number concentration data of the particles with different particle diameters of at least one pollution source and building a particle diameter spectrum library of a typical particle emission source, wherein the pollution source comprises road dust, construction dust, tail gas dust, combustion source dust and process dust Cheng Chen; the library of typical particulate emission source particle size spectra includes a first contribution rate of particulate matter of different particle size segments of any source of pollution; the first contribution rate is the ratio of the number concentration data of the particulate matters in any particle size section to the number concentration data of the particulate matters in the pollution source;

The monitoring module is used for monitoring the number concentration data of the particulate matters of the target environmental receptor in a preset period;

the identification module is used for identifying first contribution rates of different particle size sections of different pollution sources in the target environmental receptor in the preset period based on an orthogonal matrix factor analysis model according to the number concentration data of the particulate matters of the target environmental receptor in the preset period;

the matching module is used for searching the pollution sources of the atmospheric particulates in the target environmental acceptors of the preset time period from the typical particulate matter emission source particle size spectrum library based on the first contribution rates of the particulates of different particle size segments of different pollution sources in the target environmental acceptors of the preset time period.

In a third aspect, the present application provides a terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method according to the first aspect or any one of the possible implementations of the first aspect when the computer program is executed.

In a fourth aspect, the present application provides a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method as described above in the first aspect or any one of the possible implementations of the first aspect.

The application provides a particle source analysis method, a device, a terminal and a storage medium, wherein the distribution condition of first contribution rates of particles in different particle size sections of different pollution sources can be better displayed according to a typical particle emission source particle size spectrum library; according to finer division of particle diameter sections in a typical particle emission source particle diameter spectrum library, the accuracy of a pollution source analysis result of the particles in an environmental receptor is improved; in addition, the method and the device do not need to carry out off-line test by means of chemical instruments, and are low in cost and high in efficiency.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required for the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart illustrating an implementation of a method for analyzing a particulate source according to an embodiment of the present disclosure;

FIG. 2 is a graph showing the partitioning of different particle size fractions provided in the examples herein;

FIG. 3 is a graph of a first contribution ratio of different particle size segments for different sources of contamination provided in an embodiment of the present application;

FIG. 4 is a graph showing the duty ratio of the source analysis result of PM10 under the scanning electron microscope according to the embodiment of the present application;

FIG. 5 is a graph of the duty cycle of the source analysis result of the particle size spectrum PM10 provided in the example of the present application;

FIG. 6 is a plot of the duty cycle of the source resolution results for PM2.5 for a component station provided in an embodiment of the present application;

FIG. 7 is a plot of a first contribution rate of PM2.5 for a component station provided by an embodiment of the present application;

FIG. 8 is a plot of the duty cycle of the source resolution results for particle size spectrum PM2.5 provided in the examples of the present application;

FIG. 9 is a graph of a first contribution rate of particle size spectrum PM2.5 provided in an embodiment of the present application;

FIG. 10 is a schematic diagram of a particulate matter source analysis device according to an embodiment of the present disclosure;

fig. 11 is a schematic diagram of a terminal provided in an embodiment of the present application.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the following description will be made with reference to the accompanying drawings by way of specific embodiments.

Fig. 1 is a flowchart of an implementation of a method for analyzing a particulate matter source according to an embodiment of the present application, which is described in detail below:

in step 101, acquiring data of the number concentration of the particulate matters with different particle diameters of at least one pollution source, and establishing a typical particulate matter emission source particle diameter spectrum library, wherein the pollution source comprises road dust, construction dust, tail gas dust, combustion source dust and process dust Cheng Chen; a typical particulate emissions source particle size spectrum library includes a first contribution rate of particulate matter of different particle size segments of any source of pollution; the first contribution ratio is a ratio of the number concentration data of the particulate matters in any particle size section to the number concentration data of the particulate matters in the pollution source.

In a practical environment, the pollution source can generate atmospheric pollution, and mainly comprises road dust, construction dust, tail gas dust, combustion source dust and process dust Cheng Chen.

In the embodiment of the application, the data of the number concentration of the particles with different particle diameters of road dust, construction dust, tail gas dust, combustion source dust and process dust are required to be obtained, and each type of pollution source can only collect one pollution source, for example, when collecting the road dust, only collect the road dust with high speed, for example, when collecting the construction dust, only collect the construction dust of a certain removed site; each type of pollution source can also collect a plurality of pollution sources, for example, road dust of various road types such as expressways, branches and the like can be collected, and construction dust of a plurality of removed sites can be collected when construction dust is collected, so that in the embodiment of the application, each type of pollution source is required to collect at least one type of pollution source dust.

In this embodiment, the number concentration data of the particulate matters with different particle diameters of at least one pollution source are obtained by each type of pollution source, the particle diameter sections are divided according to the different particle diameters, then a typical particulate matter emission source particle diameter spectrum library is established according to the divided particle diameter sections, the division situation of the particle diameter section of any pollution source is referred to fig. 2, the particle diameter of the particulate matters of each type of pollution source is divided into 58 sections, and the first contribution rate of the particulate matters with different particle diameter sections of each type of pollution source is included in the typical particulate matter emission source particle diameter spectrum library.

For the calculation of the first contribution ratio, exemplary, referring to fig. 2, the collected data of the number concentration of the particulate matters of the road dust is N, and the data of the number concentration of the particulate matters of the particle size section numbered P10 is N ₁ The first contribution rate of the P10 particle size section to the road dust is N ₁ /N。

In one possible implementation, step 101 may include:

classifying the number concentration data of the particulate matters of each pollution source according to the particle size ranges of different particle size sections to obtain particle size section data corresponding to each particle size section, wherein the particle size section data comprises the number concentration data of the particulate matters and a first contribution rate;

for any pollution source, if the first contribution rate of all particle size sections of the pollution source meets a first condition, determining the pollution source of the particle size section as road dust, wherein the first condition is as follows:

wherein ,

is of particle diameter section P _n P of the first contribution rate of (2) _n The number of the particle size sections is n, and n is the total number of the particle size sections;

if the first contribution rate of all particle size sections of the pollution source meets a second condition, determining the pollution source of the particle size section as construction dust, wherein the second condition is as follows:

if the first contribution rate of all particle size sections of the pollution source meets a third condition, determining the pollution source of the particle size section as tail gas dust, wherein the third condition is that:

if the first contribution rate of all particle size sections of the pollution source meets a fourth condition, determining that the pollution source of the particle size section is combustion source dust and process dust Cheng Chen, wherein the fourth condition is that:

and constructing a typical particle emission source particle size spectrum library according to the first contribution rate of the particles of each pollution source and the different particle size sections corresponding to the pollution sources.

Setting sampling points for different pollution sources according to relevant standard specifications, and acquiring the number concentration data of the particulate matters with different particle diameters of the different pollution sources by using a high-precision particle size spectrum monitor, wherein the pollution sources comprise road dust, construction dust, tail gas dust, combustion source dust and process dust Cheng Chen; then classifying and numbering the collected number concentration data of the particulate matters of each pollution source according to the particle size ranges of different particle size sections to obtain particle size section data corresponding to each particle size section, wherein the particle size section data comprises a first contribution rate, and the classification result of the particle size ranges of the different particle size sections is shown in fig. 2; and respectively calculating the distribution situation of the first contribution rates of the particles in all particle size sections of different pollution sources according to the analysis results of the orthogonal matrix factor analysis model, and constructing a typical particle size spectrum library of the particle emission sources according to the first contribution rates of the particles in different particle size sections corresponding to each pollution source and the pollution source.

For a typical particle emission source particle size spectrum library, wherein the particle size range comprises 0.154-10 μm, each type of pollution source emits particles with the particle size range of 0.154-10 μm, but the ratio of the data of the number concentration of the particles in different particle size sections is different for different pollution sources, and the ratio is the first contribution rate, so that the first contribution rate is included in the typical particle emission source particle size spectrum library.

In one possible implementation, after determining that the pollution source of the particle size segment is combustion source dust and process pass Cheng Chen if the first contribution rates of all particle size segments of the pollution source meet the fourth condition, the method may further include:

calculating two values of the particle size section numbers meeting the fourth condition, and taking the two values as a first value and a second value;

if the first value is larger than the second value, the pollution source of the particle size section corresponding to the first value is combustion source dust, and the pollution source of the particle size section corresponding to the second value is process dust;

if the first value is smaller than the second value, the pollution source of the particle size section corresponding to the first value is process dust, and the pollution source of the particle size section corresponding to the second value is combustion dust.

In this embodiment, two values with different particle size segment numbers, i.e., the first value n, may be obtained according to the fourth condition ₁ And a second value n ₂ And judging the first value n ₁ And a second value n ₂ If the first value is greater than the second value, i.e. n ₁ >n ₂ Determining a pollution source of the particle size section corresponding to the first value as combustion source dust, and determining a pollution source of the particle size section corresponding to the second value as process dust; if the first value is smaller than the second value, n ₁ <n ₂ And determining the pollution source of the particle size section corresponding to the first value as process dust, and determining the pollution source of the particle size section corresponding to the second value as combustion source dust.

According to the method and the device, through the established typical particle emission source particle size spectrum library, finer division of the number concentration data of the particles in different pollution sources is achieved, a reference basis is provided for subsequent analysis of the pollution sources, the number concentration data of the particles with different particle sizes of the different pollution sources are divided according to particle size segments, and a chemical detection instrument is not needed, so that operation is more convenient.

In step 102, the number concentration data of the particulate matter of the target environmental receptor for a preset period of time is monitored.

The environmental receptor includes a plurality of pollution sources, and according to step 101, at least one pollution source of road dust, construction dust, tail gas dust, combustion source dust and process dust is known, and in general, the environmental receptor includes the above dust, and the number of the pollution sources included in the environmental receptor is not limited in the embodiment of the present application.

In the embodiment of the present application, the number concentration data of the particulate matters of the target environmental receptor within the preset period is monitored, and according to the typical particulate matter emission source particle size spectrum library established in step 101, the monitored number concentration data of the particulate matters of the target environmental receptor is divided according to the distribution condition of the particle size segments in the typical particulate matter emission source particle size spectrum library.

In one possible implementation, the preset time period may include a plurality of time periods, and the number concentration data of the particulate matter of the target environmental receptor may include the number concentration data of the particulate matter corresponding to each time period.

In this embodiment of the present application, the monitored preset period may include a plurality of time periods, for example, the preset period is 1 hour, and divided according to minutes, and then the preset period includes 60 time periods, and correspondingly, the monitored data of the number concentration of the particulate matters of the target environmental receptor is also divided according to the time periods, and divided into the data of the number concentration of the particulate matters corresponding to the 60 time periods.

In step 103, according to the number concentration data of the particulate matters of the target environmental receptor in the preset period, the first contribution rates of different particle size segments of different pollution sources in the target environmental receptor in the preset period are identified based on the orthogonal matrix factor analysis model.

In the embodiment of the application, the number concentration data of the particulate matters of the target environmental receptor, which is monitored in the step 102 for a preset period, is input into an orthogonal matrix factor analysis model, and the first contribution rates of different particle size segments of different pollution sources in the target environmental receptor for the preset period are identified.

The orthogonal matrix factor analysis model (Positive Matrix Factorization, PMF) is a multi-element factor analysis model, and is used for decomposing a matrix (X) of sample data into a factor contribution matrix (G) and a factor spectrum matrix (F), identifying the factor spectrum matrix and quantitatively calculating the factor contribution of a sample.

The principle of the analytic calculation of the particle source by using the PMF model is to make the concentration matrix X of the receptor particle component _(n×m) Factorization, decomposition into two factor matrices, F _(p×m) and G_(n×p) And a "residual matrix" E _(n×m) As shown in formula (1):

X _(n×m) ＝G _(n×p) F _(p×m) +E _(n×m) (1)

wherein ,X_(n×m) For the concentration matrix of the receptor particulate matter component, G _(n×p) Contribution matrix for factor F _(p×m) The factor spectrum matrix is formed by the steps of, n is the number of samples, m is the chemical component type, and p is the number of resolved factors (pollution sources).

The PMF model defines that the components in both matrices G and F are positive, i.e., non-negative limits. The PMF model resolves equation (1) by defining an "objective function" Q and minimizing the value of this objective function; when the objective function Q is minimum, the model decomposes the receptor concentration matrix X into a factor contribution matrix and a factor spectrum matrix.

In the embodiment of the application, the orthogonal matrix factor analysis model is used for identifying the first contribution rates of different particle size segments of different pollution sources in a target environment receptor in a preset period, and mainly identifying the ratio of the number concentration data of the particulate matters of different particle size segments of a certain pollution source to the number concentration data of the particulate matters of the pollution source.

In one possible implementation, step 103 may include:

for the data of the number concentration of the particulate matters corresponding to any time period, monitoring whether abnormal data occur in the data of the number concentration of the particulate matters corresponding to the time period, wherein the abnormal data comprise zero values, negative values and blank values;

if abnormal data appear and the abnormal rate of the number concentration data of the particles corresponding to the time period is larger than a first preset threshold value, deleting the number concentration data of the particles corresponding to the time period;

if abnormal data occur and the abnormal rate of the number concentration data of the particulate matters corresponding to the time period is not greater than a first preset threshold value, correcting the abnormal data through a first formula to obtain corrected number concentration data of the particulate matters;

according to the corrected data of the number concentration of the particles, carrying out correlation comparison on the sum of the data of the number concentration of the particles in different particle size sections corresponding to each time section and the data of the number concentration of the particles corresponding to the time section, and obtaining comparison results of the particles in different particle size sections in each time section;

Determining weight coefficients of the particles with different particle sizes in a preset period according to comparison results of the particles with different particle sizes in each period, and summing the corrected number concentration data of the particles with the particle sizes in each period in the preset period according to any particle size to obtain the number concentration data of the particles with the particle sizes in the preset period;

inputting the number concentration data and the weight coefficient of the particles corresponding to each particle size section in a preset period into an orthogonal matrix factor analysis model, and outputting the first contribution rates of the particles in different particle size sections of different pollution sources in a target environment receptor in the preset period;

wherein, the first formula is:

wherein ,

to be corrected afterParticle size section P _n Particle size monitoring data of>

Is of particle diameter section P _n Is the particle size monitoring data of the particles, n is the particle size section P _n Is a number of (3).

After monitoring the number concentration data of the particulate matters of the target environmental receptor in the preset time period, first, for the number concentration data of the particulate matters corresponding to any time period, monitoring and judging whether abnormal data occurs in the number concentration data of the particulate matters corresponding to the time period, if the abnormal data occurs and the abnormal rate of the number concentration data of the particulate matters corresponding to the time period is greater than a first preset threshold, deleting the number concentration data of the particulate matters corresponding to the time period, if the abnormal data occurs and the abnormal rate of the number concentration data of the particulate matters corresponding to the time period is not greater than the first preset threshold, correcting the abnormal data through a first formula to obtain corrected number concentration data of the particulate matters, in the embodiment of the application, when the first preset threshold is set to be 20%, namely greater than 20%, deleting the number concentration data of the particulate matters corresponding to the time period, and when the abnormal data is not greater than 20%, correcting the first preset threshold according to different requirements, and in the embodiment of the application, setting of the first preset threshold is not limited.

Exemplary, a first preset threshold is set to c ₀ Calculating the abnormality rate of the number concentration data of the particulate matters corresponding to each time period as c, and if the abnormality rate is greater than a first preset threshold value, namely c>c ₀ Deleting the data of the number concentration of the particles corresponding to the time period; if the abnormality rate is not greater than a first preset threshold, i.e. c is less than or equal to c ₀ Then adopt the first formula

Correcting abnormal data in the particulate matters corresponding to the time period, namely respectively calculating the number concentration data of the three particulate matters before and after the abnormal data to average, wherein the obtained average is the correction data of the abnormal data, namely the corrected number concentration of the particulate mattersAnd (5) degree data.

And secondly, on the basis of the corrected data of the number concentration of the particles, carrying out correlation comparison on the sum of the data of the number concentration of different particle sizes of each particle corresponding to each time period and the data of the number concentration of the particles corresponding to the time period, and obtaining the comparison result of the particles with different particle sizes in each time period.

In one possible implementation manner, according to the corrected number concentration data of the particulate matters, performing correlation comparison on the sum of the number concentration data of each particulate matter in different particle size segments corresponding to each time segment and the number concentration data of the particulate matters corresponding to the time segment to obtain a comparison result of the particulate matters in different particle size segments in each time segment, and may include:

Calculating the comparison result of the particulate matters in different particle size sections in each time section by a pearson correlation calculation formula:

wherein r is the comparison result of the particles with different particle sizes in the i time period,

is the P in the i time period _n Number concentration data of particulate matter of particle size section, < ->

For the P in the i time period after correction _n Number concentration data of particulate matter of particle size section, < ->

For PM in i time period ₁₀ Digital concentration data of>

For PM in corrected i time period ₁₀ Is a digital concentration data of (a).

In this embodiment of the present application, correlation comparison is performed on the sum of the number concentration data of different particle size segments of each particulate matter corresponding to each time segment and the number concentration data of particulate matter corresponding to the time segment, and a pearson correlation calculation formula is adopted to obtain comparison results of particulate matters of different particle size segments in each time segment, and according to the comparison results, weight coefficients of particulate matters of different particle size segments in a preset time segment are determined.

In one possible implementation manner, determining the weight coefficient of the particulate matters in the different particle size segments in the preset time period according to the comparison result of the particulate matters in the different particle size segments in each time period may include:

Judging whether the comparison result of the particles in each particle size section in each time section is smaller than a second preset threshold value or not according to the particles in each particle size section in each time section; if the comparison result of the particulate matters in the particle size section in the time period is smaller than a second preset threshold value, setting a first initial weight coefficient for the particulate matters in the particle size section; if the comparison result of the particulate matters in the particle size section in the time period is not smaller than a second preset threshold value, setting a second initial weight coefficient for the particulate matters in the particle size section; wherein the first initial weight coefficient is smaller than the second initial weight coefficient;

calculating a first weight coefficient of the particulate matters of each particle size section in a preset time period based on the first initial weight coefficient of the particulate matters of each particle size section in each time period in the preset time period;

and calculating the second weight coefficient of the particulate matters of each particle size section in the preset time period based on the second initial weight coefficient of the particulate matters of each particle size section in each time period in the preset time period.

In this embodiment, a weighted sum is used to average the first weight coefficient and the second weight coefficient of the particulate matter in each particle size section within a preset time, and since the first initial weight coefficient is smaller than the second initial weight coefficient, the first weight coefficient is obtained by calculating the weighted sum for the first initial weight coefficient, and the second weight coefficient is obtained by calculating the weighted sum for the second initial weight coefficient, the first weight coefficient is smaller than the second weight coefficient.

In the embodiment of the application, for the particulate matters in each particle size section in each time section, whether the comparison result of the particulate matters in the particle size section in the time section is smaller than a second preset threshold value is judged, if the comparison result is smaller than the second preset threshold value, a first initial weight coefficient is set for the particulate matters in the particle size section, and the first weight coefficient of the particulate matters in each particle size section in the time section is calculated through weighted summation and average; if the comparison result is not smaller than a second preset threshold value, setting a second initial weight coefficient for the particles in the particle size section, and calculating the second weight coefficient of the particles in each particle size section in the time through weighted summation and averaging.

The purpose of the embodiment of the present application is to more highlight the data of the number concentration of the particulate matters in the particle size section in each time zone, or to weaken the data of the number concentration of the particulate matters in the particle size section in the time zone, by setting a weight coefficient for the particulate matters in each particle size section in each time zone, for example: if the comparison result is smaller than a second preset threshold value, the comparison result shows that the number concentration data of the particles in the particle size section in the time is not standard, a first initial weight coefficient is set, and the occupation ratio condition of the number concentration data of the particles in the particle size section in the time section in the pollution source is weakened more; if the comparison result is not smaller than the second preset threshold value, the comparison result shows that the number concentration data of the particles in the particle size section in the time period is compared with the standard, and a second initial weight coefficient is set to more highlight the ratio of the number concentration data of the particles in the particle size section in the time period to the pollution source.

The setting of the second preset threshold may be set to 0.7 in the embodiment of the present application, or may be set to different values according to different requirements, which is not limited in the setting of the second preset threshold.

For example, referring to fig. 2, the particle size section of each particle corresponding to each time period is divided into 1-58 sections, and a second preset threshold is set to 0.7, for any particle, a pearson correlation calculation formula is adopted to calculate the comparison result of the particles in different particle size sections in each time period, taking the particle size section P10 as an example, if the correlation of the number concentration data of the collected particles in the particle size section P10 is less than 0.7, it is indicated that the number concentration data of the collected particles in the particle size section P10 is not standard, a first initial weight coefficient is set for the particles in the particle size section, and a weighted sum averaging method is adopted to calculate the first weight coefficient of the particles in each particle size section in the preset time period for the first initial weight coefficient of the particles in each particle size section in the preset time period; if the correlation of the collected number concentration data of the particles in the particle size section P10 is not less than 0.7, the comparison standard of the number concentration data of the particles collected in the particle size section P10 is indicated, a second initial weight coefficient is set for the particles in the particle size section, a weighted sum averaging method is adopted, and the second weight coefficient of the particles in each particle size section in a preset time period is calculated for the second initial weight coefficient of the particles in each particle size section in each time period in the preset time period.

Thirdly, based on the first and second operations, summing the corrected particle number concentration data of the particle size section in each of the preset time periods to obtain the particle number concentration data of the particle size section in the preset time period.

Fourth, the number concentration data of the particulate matters corresponding to each particle size section in the third preset time period and the weight coefficient obtained in the second preset time period are input into an orthogonal matrix factor analysis model, and the first contribution rates of the particulate matters of different particle size sections of different pollution sources in a target environment receptor in the preset time period are output.

In step 104, the pollution sources of the atmospheric particulates in the target environmental acceptors for the preset period are searched from the typical particulate emissions source particle size spectrum library based on the first contribution rates of the particulates for the different particle size segments of the different pollution sources in the target environmental acceptors for the preset period.

And (3) according to the particle size spectrum library of the typical particle emission source, which is established in the step (101), matching the first contribution rate of the particles with different particle sizes of different pollution sources in the target environmental receptor in the preset time period obtained in the step (103) with the particle size spectrum library of the typical particle emission source to obtain the pollution sources of the atmospheric particles in the target environmental receptor in the preset time period.

For example, in step 103, the first contribution rates of the particles in the different particle size segments corresponding to the A, B, C, D, E five pollution sources in the target environmental receptor in the preset period are obtained, referring to fig. 3, the first contribution rates of the particles in the different particle size segments corresponding to the A, B, C, D, E five different pollution sources are obtained from top to bottom, then the distribution situation of the first contribution rates of the particles in the different particle size segments of the five pollution sources is matched with the first contribution rates of the particles in the different particle size segments of the different pollution sources in the typical particle emission source particle size spectrum library, so as to obtain the pollution source a as process dust, the pollution source B as road dust, the pollution source C as tail gas dust (motor dust), the pollution source D as construction dust, and the pollution source E as combustion source dust (fixed combustion dust).

In one possible implementation, after searching the pollution source of the atmospheric particulates in the target environmental receptor for a preset period of time from the typical particulate emission source particle size spectrum library, the method may further include:

and identifying a second contribution rate of the particulate matters of different pollution sources in the target environmental receptor in a preset period based on the orthogonal matrix factor analysis model, wherein the second contribution rate is the ratio of the sum of the number concentration data of the particulate matters of any pollution source in the number concentration data of the target environmental receptor.

In this embodiment of the present application, based on step 103, several types of pollution sources of the orthogonal matrix factor analysis model may be further set based on the orthogonal matrix factor analysis model, and a second contribution rate of the particulate matters of different pollution sources in the target environmental receptor in a preset period is identified, where the second contribution rate is a ratio of a sum of the number concentration data of the particulate matters of any pollution source in the number concentration data of the target environmental receptor.

The method comprises the steps of obtaining second contribution rates of particulate matters of different pollution sources in a target environment receptor in a preset period, obtaining first contribution rates of data of the number concentration of the particulate matters of different particle size sections of each pollution source at the same time, and then respectively matching the first contribution rates of the data of the number concentration of the particulate matters of different particle size sections of each pollution source with a typical particulate matter emission source particle size spectrum library established in the step 101 to accurately determine the types of the pollution sources so as to obtain the ratio situation of the different pollution sources in the target environment receptor in the preset period.

Illustratively, referring to fig. 3, based on the orthogonal matrix factor analysis model, a pollution source a accounts for 25% of the number concentration data of the target environmental receptor, a pollution source B accounts for 15% of the number concentration data of the target environmental receptor, a pollution source C accounts for 20% of the number concentration data of the target environmental receptor, a pollution source D accounts for 10% of the number concentration data of the target environmental receptor, and a pollution source E accounts for 30% of the number concentration data of the target environmental receptor are obtained respectively; then, according to a typical particle size spectrum library of the particulate matter emission source, it was determined that the pollution source a was process dust, the pollution source B was road dust, the pollution source C was tail gas dust (motor dust), the pollution source D was construction dust, and the pollution source E was combustion source dust (fixed combustion dust), thereby determining that the process dust was 25% in the target environmental acceptor, the road dust was 15% in the target environmental acceptor, the pollution source was 20% in the target environmental acceptor, the construction dust was 10% in the target environmental acceptor, and the combustion source dust was 30% in the target environmental acceptor.

According to the particle size spectrum library of the typical particle emission source, the distribution condition of the first contribution rate of the particles in different particle size sections of different pollution sources can be better displayed; according to finer division of particle diameter sections in a typical particle emission source particle diameter spectrum library, the accuracy of a pollution source analysis result of the particles in an environmental receptor is improved; in addition, the method and the device do not need to carry out off-line test by means of chemical instruments, and are low in cost and high in efficiency.

The method for analyzing the source of particulate matter will be described below with reference to the comparative results of the source analysis and electron microscope analysis of PM10 as the particle size spectrum data of the examples.

The type and the source of each particle can be divided and summarized and analyzed by a scanning electron microscope (according to the EPA SEM-EDS particle sample analysis technical guidelines and the national standard GB/T35099-2018 scanning electron microscope-energy spectrometer atmospheric fine particle single particle morphology and element analysis). Mass concentration data of the target environmental receptor at the time of 3 months, 24 days, 9 days, 40 minutes to 4 months, 6 days and 10 days are collected, and an electron microscope scanning result shows that the soil dust accounts for 40.1 percent, the building dust accounts for 21.5 percent, the combustion source (including fixed combustion, motor vehicles and biomass combustion) accounts for 28.4 percent, the other sources account for 10.0 percent, and the specific proportion situation is shown in fig. 4. Performing source analysis on the PM10 concentration at the same time period based on particle size spectrum data, wherein the contribution of a dust source is 44.2%, and the construction dust and the road dust are 33.0% and 18.2% respectively; the vehicle, stationary combustion source and process source are 14.0%, 24.1% and 10.7% respectively, with specific ratios as described with reference to fig. 5.

The analytical results of both methods indicated that the dust source (including road dust and construction dust) contributed most to the PM10, followed by the combustion source (motor vehicle, stationary combustion, etc.). The analytical results were substantially consistent, indicating that analytical results in the examples of the present application may substantially reflect the primary source of PM 10.

The method for analyzing the source of particulate matter will be described below by comparing the source analysis and the component analysis results for the particle size spectrum data of PM2.5 in the examples.

PM2.5 sources can be analyzed by means of a PMF model through anion and cation, OC/EC and heavy metal concentration monitoring data of the grouping station. Mass concentration data of particles of target environmental acceptors from 18 days to 27 days in 4 months are collected, PM2.5 analysis results based on the component data show that the secondary inorganic salt accounts for 29.9 percent, the dust source accounts for 28.5 percent, the fixed combustion source accounts for 22.1 percent, the motor vehicle accounts for 11.0 percent, the process source accounts for 8.5 percent, the specific account is shown in fig. 6, and the distribution situation of corresponding particle size segments is shown in fig. 7. The PM2.5 concentration in the same time period is subjected to source analysis based on particle size spectrum data, the contribution of secondary inorganic salt and other sources is 27.0%, the dust source accounts for 26.6%, the fixed combustion source accounts for 22.9%, the motor vehicle accounts for 15.0%, the process source accounts for 8.5%, the specific account is shown in fig. 8, and the corresponding particle size distribution is shown in fig. 9.

The analysis results of the two methods indicate that besides the secondary inorganic salt, the dust source has the highest contribution to PM2.5 in the period, and the analysis results are basically consistent with the fixed combustion source, the motor vehicle and the process source, so that the analysis results in the embodiment of the application can basically reflect the main source of PM 2.5.

It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.

The following are device embodiments of the present application, for details not described in detail therein, reference may be made to the corresponding method embodiments described above.

Fig. 10 is a schematic structural diagram of a particulate matter source analysis device according to an embodiment of the present application, and for convenience of explanation, only a portion related to the embodiment of the present application is shown, and the details are as follows:

as shown in fig. 10, the particulate matter source analysis device 10 includes:

a building module 101, configured to obtain data of a number concentration of particulate matters with different particle diameters of at least one pollution source, and build a typical particulate matter emission source particle diameter spectrum library, where the pollution source includes road dust, construction dust, tail gas dust, combustion source dust and process dust Cheng Chen; a typical particulate emissions source particle size spectrum library includes a first contribution rate of particulate matter of different particle size segments of any source of pollution; the first contribution rate is the ratio of the number concentration data of the particulate matters in any particle size section to the number concentration data of the particulate matters in the pollution source;

A monitoring module 102 for monitoring the number concentration data of the particulate matters of the target environmental receptor for a preset period of time;

the identifying module 103 is configured to identify, based on the orthogonal matrix factor analysis model, first contribution rates of different particle size segments of different pollution sources in the target environmental receptor in a preset period according to the number concentration data of the particulate matters in the target environmental receptor in the preset period;

the matching module 104 is configured to search a typical particulate matter emission source particle size spectrum library for a pollution source of atmospheric particulate matters in a target environmental acceptor in a preset period based on a first contribution rate of particulate matters in different particle size segments of different pollution sources in the target environmental acceptor in the preset period.

The application provides a particulate matter source analysis device, which can better show the distribution condition of first contribution rates of particulate matters in different particle size sections of different pollution sources according to a typical particulate matter emission source particle size spectrum library; according to finer division of particle diameter sections in a typical particle emission source particle diameter spectrum library, the accuracy of a pollution source analysis result of the particles in an environmental receptor is improved; in addition, the method and the device do not need to carry out off-line test by means of chemical instruments, and are low in cost and high in efficiency.

In one possible implementation manner, the establishing module specifically includes:

the classification module is used for classifying the number concentration data of the particulate matters of each pollution source according to the particle size ranges of different particle size sections to obtain particle size section data corresponding to each particle size section, wherein the particle size section data comprises the number concentration data of the particulate matters and a first contribution rate;

the first calculation module is configured to determine, for any pollution source, that the pollution source of the particle size section is road dust if the first contribution rates of all particle size sections of the pollution source meet a first condition, where the first condition is:

wherein ,

is of particle diameter section P _n P of the first contribution rate of (2) _n The number of the particle size sections is n, and n is the total number of the particle size sections;

the second calculation module is configured to determine that the pollution source of the particle size section is construction dust if the first contribution rates of all particle size sections of the pollution source meet a second condition, where the second condition is:

the third calculation module is configured to determine that the pollution source of the particle size section is exhaust dust if the first contribution rates of all particle size sections of the pollution source meet a third condition, where the third condition is:

a fourth calculation module, configured to determine that the pollution source of the particle size section is combustion source dust and process dust Cheng Chen if the first contribution rates of all particle size sections of the pollution source meet a fourth condition, where the fourth condition is:

The construction module is used for constructing a typical particle emission source particle size spectrum library according to each pollution source and the first contribution rate of the particles of different particle size sections corresponding to the pollution sources.

In one possible implementation, the fourth computing module is further configured to:

calculating two values of the particle size section numbers meeting the fourth condition, and taking the two values as a first value and a second value;

if the first value is larger than the second value, the pollution source of the particle size section corresponding to the first value is combustion source dust, and the pollution source of the particle size section corresponding to the second value is process dust;

if the first value is smaller than the second value, the pollution source of the particle size section corresponding to the first value is process dust, and the pollution source of the particle size section corresponding to the second value is combustion dust.

In one possible implementation, the preset time period may include a plurality of time periods, and the number concentration data of the particulate matter of the target environmental receptor may include the number concentration data of the particulate matter corresponding to each time period.

In one possible implementation manner, the identification module specifically may include:

the judging module is used for monitoring whether abnormal data are generated in the data of the number concentration of the particles corresponding to any time period, wherein the abnormal data comprise zero values, negative values and blank values;

The deleting module is used for deleting the data of the number concentration of the particles corresponding to the time period if the abnormal data occur and the abnormal rate of the data of the number concentration of the particles corresponding to the time period is larger than a first preset threshold value;

the correction module is used for correcting the abnormal data through a first formula to obtain corrected data of the number concentration of the particulate matters if the abnormal data occur and the abnormal rate of the data of the number concentration of the particulate matters corresponding to the time period is not greater than a first preset threshold value;

the comparison module is used for carrying out correlation comparison on the sum of the number concentration data of each particle in different particle size sections corresponding to each time section and the number concentration data of the particle corresponding to the time section according to the corrected number concentration data of the particle, so as to obtain comparison results of the particle in different particle size sections in each time section;

the weight determining module is used for determining weight coefficients of the particles with different particle sizes in the preset time period according to the comparison result of the particles with different particle sizes in each time period, and summing the corrected number concentration data of the particles with the particle sizes in each time period in the preset time period according to any particle size in the preset time period to obtain the number concentration data of the particles with the particle sizes in the preset time period;

The output module is used for inputting the number concentration data and the weight coefficient of the particulate matters corresponding to each particle size section in the preset period into the orthogonal matrix factor analysis model and outputting the first contribution rates of the particulate matters in different particle size sections of different pollution sources in the target environment receptor in the preset period;

wherein, the first formula is:

wherein ,

for the corrected particle size section P _n Particle size monitoring data of>

Is of particle diameter section P _n Is the particle size monitoring data of the particles, n is the particle size section P _n Is a number of (3).

In one possible implementation, the comparison module may be specifically configured to:

calculating the comparison result of the particulate matters in different particle size sections in each time section by a pearson correlation calculation formula:

wherein r is the comparison result of the particles with different particle sizes in the i time period,

is the P in the i time period _n Number concentration data of particulate matter of particle size section, < ->

For the P in the i time period after correction _n Number concentration data of particulate matter of particle size section, < ->

For PM in i time period ₁₀ Digital concentration data of>

For PM in corrected i time period ₁₀ Is a digital concentration data of (a).

In one possible implementation, the weight determination module may be configured to:

Judging whether the comparison result of the particles in each particle size section in each time section is smaller than a second preset threshold value or not according to the particles in each particle size section in each time section; if the comparison result of the particulate matters in the particle size section in the time period is smaller than a second preset threshold value, setting a first initial weight coefficient for the particulate matters in the particle size section; if the comparison result of the particulate matters in the particle size section in the time period is not smaller than a second preset threshold value, setting a second initial weight coefficient for the particulate matters in the particle size section; wherein the first initial weight coefficient is smaller than the second initial weight coefficient;

calculating a first weight coefficient of the particulate matters of each particle size section in a preset time period based on the first initial weight coefficient of the particulate matters of each particle size section in each time period in the preset time period;

and calculating the second weight coefficient of the particulate matters of each particle size section in the preset time period based on the second initial weight coefficient of the particulate matters of each particle size section in each time period in the preset time period.

In one possible implementation, after the matching module, the apparatus may further be configured to:

and identifying a second contribution rate of the particulate matters of different pollution sources in the target environmental receptor in a preset period based on the orthogonal matrix factor analysis model, wherein the second contribution rate is the ratio of the sum of the number concentration data of the particulate matters of any pollution source in the number concentration data of the target environmental receptor.

Fig. 11 is a schematic diagram of a terminal provided in an embodiment of the present application. As shown in fig. 11, the terminal 11 of this embodiment includes: a processor 110, a memory 111 and a computer program 112 stored in said memory 111 and executable on said processor 110. The processor 110, when executing the computer program 112, performs the steps of the various embodiments of the particulate matter source analysis method described above, such as steps 101 through 104 shown in fig. 1. Alternatively, the processor 110 may implement the functions of the modules in the above-described apparatus embodiments, such as the functions of the modules 101 to 104 shown in fig. 10, when executing the computer program 112.

By way of example, the computer program 112 may be partitioned into one or more modules that are stored in the memory 111 and executed by the processor 110 to complete the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 112 in the terminal 11. For example, the computer program 112 may be partitioned into modules 101-104 shown in fig. 10.

The terminal 11 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The terminal 11 may include, but is not limited to, a processor 110, a memory 111. It will be appreciated by those skilled in the art that fig. 11 is merely an example of a terminal 11 and is not intended to limit the terminal 11, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the terminal may further include input-output devices, network access devices, buses, etc.

The processor 110 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The storage 111 may be an internal storage unit of the terminal 11, for example, a hard disk or a memory of the terminal 11. The memory 111 may be an external storage device of the terminal 11, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal 11. Further, the memory 111 may also include both an internal storage unit and an external storage device of the terminal 11. The memory 111 is used for storing the computer program and other programs and data required by the terminal. The memory 111 may also be used to temporarily store data that has been output or is to be output.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal and method may be implemented in other manners. For example, the apparatus/terminal embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.

The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each embodiment of the method of analyzing a particulate matter source. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium may include content that is subject to appropriate increases and decreases as required by jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is not included as electrical carrier signals and telecommunication signals.

The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims (10)

1. A method for analyzing a source of particulate matter, comprising:

acquiring data of the number concentration of the particles with different particle diameters of at least one pollution source, and establishing a particle size spectrum library of a typical particle emission source, wherein the pollution source comprises road dust, construction dust, tail gas dust, combustion source dust and process dust Cheng Chen; the library of typical particulate emission source particle size spectra includes a first contribution rate of particulate matter of different particle size segments of any source of pollution; the first contribution rate is the ratio of the number concentration data of the particulate matters in any particle size section to the number concentration data of the particulate matters in the pollution source;

Monitoring the number concentration data of the particulate matters of the target environmental receptor for a preset period of time;

identifying first contribution rates of different particle size sections of different pollution sources in the target environmental receptor in the preset period based on an orthogonal matrix factor analysis model according to the number concentration data of the particulate matters of the target environmental receptor in the preset period;

and searching the pollution sources of the atmospheric particulates in the target environmental acceptors of the preset time period from the typical particulate emission source particle size spectrum library based on the first contribution rate of the particulates of different particle size segments of different pollution sources in the target environmental acceptors of the preset time period.

2. The method of claim 1, wherein the obtaining the data of the concentration of the number of the particles of the different particle sizes of the at least one pollution source and creating the library of particle size spectra of the typical emission source comprises:

classifying the number concentration data of the particulate matters of each pollution source according to the particle size ranges of different particle size sections to obtain particle size section data corresponding to each particle size section, wherein the particle size section data comprises the number concentration data of the particulate matters and the first contribution rate;

for any pollution source, if the first contribution rate of all particle size sections of the pollution source meets a first condition, determining the pollution source of the particle size section as road dust, wherein the first condition is as follows:

wherein ,

is of particle diameter section P _n P of the first contribution rate of (2) _n The number of the particle size sections is n, and n is the total number of the particle size sections;

if the first contribution rate of all particle size sections of the pollution source meets a second condition, determining the pollution source of the particle size section as construction dust, wherein the second condition is as follows:

if the first contribution rate of all particle size sections of the pollution source meets a third condition, determining the pollution source of the particle size section as tail gas dust, wherein the third condition is as follows:

if the first contribution rate of all particle size sections of the pollution source meets a fourth condition, determining that the pollution source of the particle size section is combustion source dust and process dust Cheng Chen, wherein the fourth condition is that:

and constructing a particle size spectrum library of the typical particulate matter emission source according to each pollution source and the first contribution rate of the particulate matters of different particle size sections of the corresponding pollution source.

3. The method of claim 2, further comprising, after determining that the pollution source of the particle size fraction is combustion source dust and process Cheng Chen if the first contribution of all particle size fractions of the pollution source meets a fourth condition:

calculating two values of the particle size section numbers meeting the fourth condition, and taking the two values as a first value and a second value;

If the first value is larger than the second value, the pollution source of the particle size section corresponding to the first value is combustion source dust, and the pollution source of the particle size section corresponding to the second value is process dust;

and if the first value is smaller than the second value, the pollution source of the particle size section corresponding to the first value is process dust, and the pollution source of the particle size section corresponding to the second value is combustion source dust.

4. The method of claim 1, wherein the predetermined period of time comprises a plurality of periods of time, and the data of the number concentration of the particulate matter of the target environmental receptor comprises data of the number concentration of the particulate matter corresponding to each period of time;

the identifying, based on the orthogonal matrix factor analysis model, the first contribution rates of different particle size segments of different pollution sources in the target environmental receptor in the preset period according to the number concentration data of the particulate matters of the target environmental receptor in the preset period includes:

monitoring whether abnormal data are generated in the data of the number concentration of the particles corresponding to any time period according to the data of the number concentration of the particles corresponding to the time period, wherein the abnormal data comprise zero values, negative values and blank values;

If abnormal data appear and the abnormal rate of the number concentration data of the particulate matters corresponding to the time period is larger than the first preset threshold value, deleting the number concentration data of the particulate matters corresponding to the time period;

if abnormal data occur and the abnormal rate of the number concentration data of the particulate matters corresponding to the time period is not greater than the first preset threshold value, correcting the abnormal data through a first formula to obtain corrected number concentration data of the particulate matters;

according to the corrected data of the number concentration of the particles, carrying out correlation comparison on the sum of the data of the number concentration of the particles in different particle size sections corresponding to each time section and the data of the number concentration of the particles corresponding to the time section, and obtaining comparison results of the particles in different particle size sections in each time section;

determining weight coefficients of the particles with different particle sizes in the preset time period according to the comparison result of the particles with different particle sizes in each time period, and summing the corrected number concentration data of the particles with the particle sizes in each time period in the preset time period according to any particle size in the preset time period to obtain the number concentration data of the particles with the particle sizes in the preset time period;

Inputting the number concentration data and the weight coefficient of the particulate matters corresponding to each particle size section of the preset time period into the orthogonal matrix factor analysis model, and outputting the first contribution rates of the particulate matters of different particle size sections of different pollution sources in a target environment receptor of the preset time period;

wherein, the first formula is:

wherein ,

for the corrected particle size section P _n Particle size monitoring data of>

Is of particle diameter section P _n Is the particle size monitoring data of the particles, n is the particle size section P _n Is a number of (3).

5. The method according to claim 4, wherein the step of performing correlation comparison between the number concentration data of each particle in each time zone and the sum of the number concentration data of each particle in each different particle size zone according to the corrected number concentration data of the particles, to obtain a comparison result of the particles in each different particle size zone, comprises:

calculating the comparison result of the particulate matters in different particle size sections in each time section by a pearson correlation calculation formula:

wherein r is the comparison result of the particles with different particle sizes in the i time period,

is the P in the i time period _n Number concentration data of particulate matter of particle size section, < ->

For the P in the i time period after correction _n Number concentration data of particulate matter of particle size section, < ->

For PM in i time period ₁₀ Digital concentration data of>

For PM in corrected i time period ₁₀ Is a digital concentration data of (a).

6. The method according to claim 5, wherein determining the weight coefficient of the particulate matter of the different particle size segments in the preset time period according to the comparison result of the particulate matter of the different particle size segments in each time period comprises:

judging whether the comparison result of the particles in each particle size section in each time section is smaller than a second preset threshold value or not according to the particles in each particle size section in each time section; if the comparison result of the particulate matters in the particle size section in the time period is smaller than the second preset threshold value, setting a first initial weight coefficient for the particulate matters in the particle size section; if the comparison result of the particulate matters in the particle size section in the time period is not smaller than the second preset threshold value, setting a second initial weight coefficient for the particulate matters in the particle size section; wherein the first initial weight coefficient is smaller than the second initial weight coefficient;

calculating a first weight coefficient of the particulate matters of each particle size section in the preset time period based on the first initial weight coefficient of the particulate matters of each particle size section in each time period in the preset time period;

And calculating the second weight coefficient of the particulate matters of each particle size section in the preset time period based on the second initial weight coefficient of the particulate matters of each particle size section in each time period in the preset time period.

7. The particulate matter source analysis method of claim 1, wherein after the searching for a pollution source of atmospheric particulates in a target environmental acceptor for the preset period of time from the library of typical particulate matter emission source particle size spectra, the method further comprises:

and identifying a second contribution rate of the particulate matters of different pollution sources in the target environmental receptor in the preset period based on the orthogonal matrix factor analysis model, wherein the second contribution rate is the ratio of the sum of the number concentration data of the particulate matters of any pollution source in the number concentration data of the target environmental receptor.

8. A particulate matter source analyzing apparatus, comprising:

the system comprises a building module, a control module and a control module, wherein the building module is used for obtaining the number concentration data of the particles with different particle diameters of at least one pollution source and building a particle diameter spectrum library of a typical particle emission source, wherein the pollution source comprises road dust, construction dust, tail gas dust, combustion source dust and process dust Cheng Chen; the library of typical particulate emission source particle size spectra includes a first contribution rate of particulate matter of different particle size segments of any source of pollution; the first contribution rate is the ratio of the number concentration data of the particulate matters in any particle size section to the number concentration data of the particulate matters in the pollution source;

The monitoring module is used for monitoring the number concentration data of the particulate matters of the target environmental receptor in a preset period;

the identification module is used for identifying first contribution rates of different particle size sections of different pollution sources in the target environmental receptor in the preset period based on an orthogonal matrix factor analysis model according to the number concentration data of the particulate matters of the target environmental receptor in the preset period;

the matching module is used for searching the pollution sources of the atmospheric particulates in the target environmental acceptors of the preset time period from the typical particulate matter emission source particle size spectrum library based on the first contribution rates of the particulates of different particle size segments of different pollution sources in the target environmental acceptors of the preset time period.

9. A terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method for analysing a source of particulate matter according to any one of claims 1 to 7 when the computer program is executed.

10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the particulate matter source analysis method according to any one of the preceding claims 1 to 7.

Images