A particulate matter source analysis method, device, terminal and storage medium

Abstract

The application provides a particle source analysis method and device, a terminal and a storage medium. The method comprises the following steps: acquiring the number concentration data of particles of different particle sizes of at least one pollution source, and establishing a typical particle emission source particle size spectrum library; monitoring the number concentration data of particles of a target environmental receptor in a preset period; identifying the first contribution rate 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 particles of the target environmental receptor in the preset period; and finding the pollution source of atmospheric particles in the target environmental receptor in the preset period from the typical particle emission source particle size spectrum library based on the first contribution rate of particles of different particle size sections of different pollution sources in the target environmental receptor in the preset period. The application can improve the accuracy of the pollution source analysis result of particles in the environmental receptor.

Description

Technical Field

[0001] This application relates to the field of atmospheric particulate matter source analysis technology, and in particular to a particulate matter source analysis method, apparatus, terminal and storage medium. Background Technology

[0002] The sources of primary particulate matter (PM2.5), especially coarse particulate matter (PPM2.5) in the 2.5-10 μm range, in urban atmospheres are complex, including construction sites, bare soil, road dust, stockpiles, and industrial emissions. Furthermore, the pollution emissions from different sources vary due to differences in their engineering stages or levels of control, resulting in unique spatiotemporal distribution characteristics for PPM2.5. With the increasing demands for refined atmospheric environmental management, relying solely on receptor apportionment technology to analyze PM2.5 sources is no longer sufficient to meet the needs of sophisticated management of primary particulate matter emission sources.

[0003] Currently, methods for analyzing particulate matter sources mainly include source inventory methods, diffusion modeling methods, and receptor modeling methods, with receptor modeling being the most widely used. However, given the abundance of particulate matter sources, relying solely on receptor analysis to determine the sources of PM10 or PM2.5 is insufficient for the refined management of primary particulate matter emission sources. For refined particulate matter source apportionment, methods based on tiered sampling and laboratory analysis can be used, but these methods suffer from long sampling cycles and low temporal resolution. Alternatively, single-particle scanning electron microscopy (SEM / TEM-EDS) can also obtain information on particle morphology, composition, particle size, and mixing state, allowing for source apportionment through particulate matter morphology analysis. While this method allows for source analysis by particle size, it suffers from long sampling times and poor timeliness, making it equally difficult to effectively support refined management and control efforts.

[0004] In response to the current needs of particulate matter management, there is an urgent need to strengthen the comprehensive application of various source tracing and analysis technologies to obtain more refined source analysis results for particulate matter by particle size, and to provide data support for carrying out comprehensive supervision and control of particulate matter. Summary of the Invention

[0005] This application provides a method, apparatus, terminal, and storage medium for particulate matter source analysis to address the problem that the prior art does not provide sufficiently refined results for the analysis of particulate matter pollution sources in environmental receptors.

[0006] In a first aspect, this application provides a method for analyzing the source of particulate matter, including:

[0007] Acquire number concentration data of particulate matter of different sizes from at least one pollution source and establish a typical particulate matter emission source size spectrum library, wherein the pollution source includes road dust, construction dust, exhaust dust, combustion source dust, and process dust; the typical particulate matter emission source size spectrum library includes a first contribution rate of particulate matter of different size segments from any pollution source; the first contribution rate is the proportion of the number concentration data of particulate matter of any size segment in the number concentration data of particulate matter of that pollution source.

[0008] Monitor the number concentration data of particulate matter in the target environmental receptor during a preset time period;

[0009] Based on the number concentration data of particulate matter in the target environmental receptor during the preset time period, and using an orthogonal matrix factor analysis model, the first contribution rate of different particle size segments of different pollution sources in the target environmental receptor during the preset time period is identified.

[0010] Based on the first contribution rate of particulate matter of different particle size ranges from different pollution sources in the target environmental receptor during the preset time period, the pollution sources of atmospheric particulate matter in the target environmental receptor during the preset time period are searched from the typical particulate matter emission source particle size spectrum library.

[0011] Secondly, this application provides a particulate matter source analysis device, comprising:

[0012] A module is established to acquire number concentration data of particulate matter of different sizes from at least one pollution source and to establish a typical particulate matter emission source size spectrum library. The pollution sources include road dust, construction dust, exhaust dust, combustion source dust, and process dust. The typical particulate matter emission source size spectrum library includes a first contribution rate of particulate matter of different size segments from any pollution source. The first contribution rate is the proportion of the number concentration data of particulate matter of any size segment in the total number concentration data of particulate matter from that pollution source.

[0013] The monitoring module is used to monitor the number concentration data of particulate matter in the target environmental receptor during a preset time period;

[0014] The identification module is used to identify the first contribution rate of different particle size segments of different pollution sources in the target environmental receptor based on the number concentration data of particulate matter in the target environmental receptor during the preset time period and an orthogonal matrix factor analysis model.

[0015] The matching module is used to search for the pollution sources of atmospheric particulate matter in the target environmental receptor during the preset time period from the typical particulate matter emission source particle size spectrum library based on the first contribution rate of particulate matter of different particle size ranges of different pollution sources in the target environmental receptor during the preset time period.

[0016] Thirdly, this application provides a terminal including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method as described in the first aspect or any possible implementation of the first aspect above.

[0017] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any possible implementation thereof.

[0018] This application provides a method, apparatus, terminal, and storage medium for particulate matter source analysis. Based on a typical particulate matter emission source particle size spectrum library, this application can better demonstrate the distribution of the first contribution rate of particulate matter in different particle size ranges from different pollution sources. The more refined division of particle size ranges in the typical particulate matter emission source particle size spectrum library improves the accuracy of pollution source analysis results for particulate matter in environmental receptors. Furthermore, this application does not require offline testing using chemical instruments, resulting in low cost and high efficiency. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the implementation of the particulate matter source analysis method provided in the embodiments of this application;

[0021] Figure 2 This is a distribution diagram showing the division of different particle size segments provided in the embodiments of this application;

[0022] Figure 3 This is a distribution diagram of the first contribution rate of different pollution sources and different particle size ranges provided in the embodiments of this application;

[0023] Figure 4 This is a percentage chart showing the source analysis results of PM10 under a scanning electron microscope provided in the embodiments of this application;

[0024] Figure 5 This is a percentage chart of the source apportionment results of PM10 in the particle size distribution provided in the embodiments of this application;

[0025] Figure 6 This is a graph showing the percentage of PM2.5 source apportionment results for the component stations provided in the embodiments of this application;

[0026] Figure 7 This is a distribution map of the first contribution rate of PM2.5 of the component stations provided in the embodiments of this application;

[0027] Figure 8 This is a percentage chart of the source apportionment results of PM2.5 particle size distribution provided in the embodiments of this application;

[0028] Figure 9 This is a distribution diagram of the first contribution rate of PM2.5 in the particle size spectrum provided in the embodiments of this application;

[0029] Figure 10 This is a schematic diagram of the particulate matter source analysis device provided in the embodiments of this application;

[0030] Figure 11 This is a schematic diagram of the terminal provided in the embodiments of this application. Detailed Implementation

[0031] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0032] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0033] Figure 1 The implementation flowchart of the particulate matter source analysis method provided in the embodiments of this application is described in detail below:

[0034] In step 101, number concentration data of particulate matter of different sizes from at least one pollution source are obtained, and a typical particulate matter emission source size spectrum library is established. The pollution sources include road dust, construction dust, exhaust dust, combustion source dust, and process dust. The typical particulate matter emission source size spectrum library includes the first contribution rate of particulate matter of different size segments from any pollution source. The first contribution rate is the proportion of the number concentration data of particulate matter of any size segment in the number concentration data of particulate matter of that pollution source.

[0035] In real-world environments, pollution sources generate air pollution. These sources mainly include road dust, construction dust, exhaust dust, combustion source dust, and process dust.

[0036] In this embodiment of the application, it is necessary to obtain the number concentration data of particulate matter of different particle sizes for road dust, construction dust, exhaust dust, combustion source dust, and process dust. Only one pollution source can be collected for each type of pollution source. For example, when collecting road dust, only road dust at high speeds can be collected, and when collecting construction dust, only construction dust from a certain demolition site can be collected. Multiple pollution sources can also be collected for each type of pollution source. For example, when collecting road dust, road dust from various road types such as expressways and branch roads can be collected, and when collecting construction dust, construction dust from multiple demolition sites can be collected. Therefore, in this embodiment of the application, it is required that at least one type of pollution source dust be collected for each type of pollution source.

[0037] In this embodiment, number concentration data of particulate matter of different sizes from at least one pollution source are obtained for each type of pollution source. The particle size is then divided into segments based on these segments, and a typical particulate matter emission source particle size spectrum library is established according to these segments. The particle size segmentation for any pollution source is described in reference to... Figure 2 The particle size of particulate matter from each type of pollution source is divided into 58 segments. The typical particulate matter emission source particle size spectrum library includes the first contribution rate of particulate matter from different particle size segments of each type of pollution source.

[0038] For the calculation of the first contribution rate, as an example, refer to... Figure 2 If the number concentration data of road dust particles is N, and the number concentration data of particles in the particle size range P10 is N1, then the first contribution rate of the P10 particle size range of road dust is N1 / N.

[0039] In one possible implementation, step 101 may include:

[0040] The number concentration data of particulate matter from each pollution source are classified according to the particle size range of different particle size segments to obtain the particle size segment data corresponding to each particle size segment. The particle size segment data includes the number concentration data of particulate matter and the first contribution rate.

[0041] For any pollution source, if the first contribution rate of all particle size segments of that pollution source satisfies a first condition, then the pollution source of that particle size segment is determined to be road dust. The first condition is:

[0042]

[0043] in, For particle size range P n First contribution rate, P n For particle size segment numbered n, where n is the total number of particle size segment numbers;

[0044] If the first contribution rate of all particle size ranges of the pollution source meets the second condition, then the pollution source of that particle size range is determined to be construction dust. The second condition is:

[0045]

[0046] If the first contribution rate of all particle size ranges of the pollution source satisfies the third condition, then the pollution source of that particle size range is determined to be exhaust dust. The third condition is:

[0047]

[0048] If the first contribution rate of all particle size ranges of the pollution source satisfies the fourth condition, then the pollution source of that particle size range is determined to be combustion source dust and process dust. The fourth condition is:

[0049]

[0050] Based on the first contribution rate of particulate matter from each pollution source and the corresponding particle size range of the pollution source, a typical particulate matter emission source particle size spectrum library is constructed.

[0051] In this embodiment, sampling points are set up for different pollution sources according to relevant standards and specifications. A high-precision particle size distribution monitor is used to collect the number concentration data of particulate matter of different sizes from different pollution sources. The pollution sources include road dust, construction dust, exhaust dust, combustion source dust, and process dust. Then, the collected number concentration data of particulate matter from each pollution source is classified and numbered according to different particle size ranges to obtain the particle size range data corresponding to each range. The particle size range data includes a first contribution rate. The classification results of the particle size ranges for different ranges are referenced... Figure 2 Based on the analytical results of the orthogonal matrix factor analysis model, the distribution of the first contribution rate of particulate matter in all particle size ranges of different pollution sources is calculated. Based on each pollution source and the first contribution rate of particulate matter in different particle size ranges corresponding to that pollution source, a typical particulate matter emission source particle size spectrum library is constructed.

[0052] For a typical particulate matter emission source particle size spectrum library, the particle size range includes 0.154-10μm. Each type of pollution source will emit particulate matter involving a particle size range of 0.154-10μm. However, for different pollution sources, the proportion of number concentration data of particulate matter in different particle size ranges is different. This proportion is the first contribution rate. Therefore, the typical particulate matter emission source particle size spectrum library includes the first contribution rate.

[0053] In one possible implementation, after determining that the pollution source of a certain particle size range is combustion source dust and process dust if the first contribution rate of all particle size ranges of the pollution source satisfies the fourth condition, the method may further include:

[0054] Calculate two possible values ​​for the particle size range number that satisfy the fourth condition, and use them as the first and second values;

[0055] If the first value is greater than the second value, the pollution source of the particle size range corresponding to the first value is combustion source dust, and the pollution source of the particle size range corresponding to the second value is process dust;

[0056] If the first value is less than the second value, the pollution source of the particle size range corresponding to the first value is process dust, and the pollution source of the particle size range corresponding to the second value is combustion source dust.

[0057] In the embodiment of the present application, according to the fourth condition, two values with different particle size range numbers can be obtained, that is, the first value n1 and the second value n2, and the magnitudes of the first value n1 and the second value n2 are judged. If the first value is greater than the second value, that is, n1>n2, then the pollution source of the particle size range corresponding to the first value is determined as combustion source dust, and the pollution source of the particle size range corresponding to the second value is determined as process dust; if the first value is less than the second value, that is, n1<n2, then the pollution source of the particle size range corresponding to the first value is determined as process dust, and the pollution source of the particle size range corresponding to the second value is determined as combustion source dust.

[0058] In the embodiment of the present application, through the established typical particulate matter emission source particle size spectrum library, the number concentration data of particulate matter in different pollution sources is more refinedly divided, providing a reference basis for subsequent analysis of the sources of pollution sources. Moreover, according to the number concentration data of particulate matter with different particle sizes in different pollution sources divided by particle size range, chemical detection instruments do not need to be used, making the operation more convenient.

[0059] In step 102, monitor the number concentration data of particulate matter of the target environmental receptor in the preset time period.

[0060] Among them, the environmental receptor includes multiple pollution sources. According to step 101, it includes at least one pollution source such as road dust, construction dust, tail gas dust, combustion source dust, and process dust. Generally, the above-mentioned types of dust are included in the environmental receptor. In the embodiment of the present application, the number of pollution sources included in the environmental receptor is not limited.

[0061] In the embodiment of the present application, monitor the number concentration data of particulate matter of the target environmental receptor in the preset time period, and divide the monitored number concentration data of particulate matter of the target environmental receptor according to the particle size range distribution in the established typical particulate matter emission source particle size spectrum library in step 101.

[0062] In a possible implementation manner, the preset time period may include multiple time periods, and the number concentration data of particulate matter of the target environmental receptor may include the number concentration data of particulate matter corresponding to each time period.

[0063] In this embodiment of the application, the preset monitoring period may include multiple time periods. For example, if the preset period is 1 hour and divided into minutes, the preset period includes 60 time periods. Correspondingly, the number concentration data of the target environmental receptor particles are also divided according to this time period, into the number concentration data of particles corresponding to the 60 time periods.

[0064] In step 103, based on the number concentration data of particulate matter in the target environmental receptor during a preset time period, and using an orthogonal matrix factor analysis model, the first contribution rate of different particle size segments of different pollution sources in the target environmental receptor during the preset time period is identified.

[0065] In this embodiment of the application, the number concentration data of particulate matter of the target environmental receptor monitored in step 102 for a preset time period is input into the orthogonal matrix factor analysis model to identify the first contribution rate of different particle size segments of different pollution sources in the target environmental receptor for the preset time period.

[0066] Among them, the Orthogonal Matrix Factorization (PMF) model is a multivariate factor analysis model that decomposes the sample data matrix (X) into a factor contribution matrix (G) and a factor spectrum matrix (F), identifies the factor spectrum matrix, and quantitatively calculates the factor contribution of the sample.

[0067] The principle of using the PMF model for particulate matter source apportionment calculations is to use the receptor particulate matter component concentration matrix X (n×m) Factorization, decomposed into two factor matrices, F (p×m) and G (n×p) and a "residual matrix" E (n×m) As shown in formula (1):

[0068] X (n×m) =G (n×p) F (p×m) +E (n×m) (1)

[0069] Among them, X (n×m) G is the concentration matrix of receptor particulate components. (n×p) For the factor contribution matrix, F (p×m) is the factor spectrum matrix, where n is the number of samples, m is the number of chemical components, and p is the number of factors (pollution sources) analyzed.

[0070] The PMF model restricts the components in matrices G and F to be positive, i.e., non-negative. The analytical formula (1) of the PMF model is derived by defining an "objective function" Q and minimizing its value. When the objective function Q is minimized, the model decomposes the receptor concentration matrix X into a factor contribution matrix and a factor spectrum matrix.

[0071] In this embodiment of the application, the orthogonal matrix factor analysis model is used to identify the first contribution rate of different particle size segments of different pollution sources in the target environmental receptor during a preset time period. The main identification is the proportion of the number concentration data of different particle size segments of a certain pollution source in the number concentration data of the particulate matter of that pollution source.

[0072] In one possible implementation, step 103 may include:

[0073] For particulate matter number concentration data corresponding to any time period, monitor whether there are abnormal data in the particulate matter number concentration data corresponding to that time period. Abnormal data includes zero values, negative values ​​and blank values.

[0074] If abnormal data is found and the abnormality rate of the particulate matter number concentration data for that time period is greater than the first preset threshold, then the particulate matter number concentration data for that time period will be deleted.

[0075] If abnormal data is found and the abnormality rate of the particulate matter number concentration data corresponding to that time period is not greater than the first preset threshold, the abnormal data is corrected by the first formula to obtain the corrected particulate matter number concentration data.

[0076] Based on the corrected number concentration data of particulate matter, the correlation between the number concentration data of each particulate matter in different particle size ranges for each time period and the sum of the number concentration data of particulate matter in that time period is compared to obtain the comparison results of particulate matter in different particle size ranges within each time period.

[0077] Based on the comparison results of particulate matter of different particle size ranges in each time period, the weighting coefficients of particulate matter of different particle size ranges in the preset time period are determined. For any particle size range, the corrected number concentration data of particulate matter of that particle size range in each time period in the preset time period are summed to obtain the number concentration data of particulate matter of that particle size range in the preset time period.

[0078] Input the number concentration data and weighting coefficients of particulate matter corresponding to each particle size range in the preset time period into the orthogonal matrix factor analysis model, and output the first contribution rate of particulate matter of different particle size ranges of different pollution sources in the target environmental receptor in the preset time period.

[0079] The first formula is:

[0080]

[0081] in, For the corrected particle size range P n Particulate matter particle size monitoring data, For particle size range P n The particulate matter particle size monitoring data, where n is the particle size range Pn The number.

[0082] In this embodiment, after monitoring the number concentration data of particulate matter in the target environmental receptor for a preset time period, firstly, for any time period, the number concentration data of particulate matter in that time period is monitored and it is determined whether abnormal data appears. If abnormal data appears and the abnormality rate of the number concentration data of particulate matter in that time period is greater than a first preset threshold, the number concentration data of particulate matter in that time period is deleted. If abnormal data appears and the abnormality rate of the number concentration data of particulate matter in that time period is not greater than the first preset threshold, the abnormal data is corrected by a first formula to obtain corrected number concentration data of particulate matter. In this embodiment, the first preset threshold can be set to 20%, that is, if it is greater than 20%, the number concentration data of particulate matter in that time period is deleted, and if it is not greater than 20%, it is corrected. Alternatively, the first preset threshold can be set according to different requirements. In this embodiment, the setting of the first preset threshold is not limited.

[0083] For example, if the first preset threshold is set to c0, then the anomaly rate c in the particulate matter number concentration data corresponding to each time period is calculated. If the anomaly rate is greater than the first preset threshold (i.e., c > c0), then the particulate matter number concentration data corresponding to that time period is deleted; if the anomaly rate is not greater than the first preset threshold (i.e., c ≤ c0), then the first formula is used. The abnormal data of particulate matter in the corresponding time period is corrected by averaging the number concentration data of the three particulate matter before and after the abnormal data. The average value is the corrected data of the abnormal data, that is, the corrected number concentration data of particulate matter.

[0084] Second, based on the corrected number concentration data of particulate matter, the number concentration data of each particulate matter of different particle size ranges corresponding to each time period and the sum of the number concentration data of particulate matter corresponding to that time period are compared to obtain the comparison results of particulate matter of different particle size ranges in each time period.

[0085] In one possible implementation, based on the corrected particulate matter number concentration data, the correlation between the number concentration data of each particulate matter in different particle size ranges for each time period and the sum of the number concentration data of particulate matter in that time period is compared to obtain the comparison results of particulate matter in different particle size ranges within each time period, which may include:

[0086] The comparison results of particulate matter of different particle sizes within each time period were calculated using the Pearson correlation formula, which is as follows:

[0087]

[0088] Where r represents the comparison results of particulate matter of different particle sizes within time period i. For the Pth time interval of time i n Number concentration data for particles in the specified particle size range. For the Pth time segment within the corrected time period i n Number concentration data for particles in the specified particle size range. PM within time period i 10 Number concentration data, PM within the corrected time period i 10 The number concentration data.

[0089] In this embodiment of the application, the number concentration data of each particle with different particle size ranges corresponding to each time period and the sum of the number concentration data of the particles corresponding to that time period are compared for correlation. The Pearson correlation calculation formula is used to obtain the comparison results of particles with different particle size ranges in each time period, and the weight coefficient of particles with different particle size ranges in the preset time period is determined based on the comparison results.

[0090] In one possible implementation, determining the weighting coefficients of particulate matter in different size ranges within a preset time period based on the comparison results of particulate matter in different size ranges within each time period may include:

[0091] For each particle size segment within each time period, determine whether the comparison result of the particle size segment within that time period is less than a second preset threshold; if the comparison result of the particle size segment within that time period is less than the second preset threshold, then set a first initial weighting coefficient for the particle size segment; if the comparison result of the particle size segment within that time period is not less than the second preset threshold, then set a second initial weighting coefficient for the particle size segment; wherein, the first initial weighting coefficient is less than the second initial weighting coefficient.

[0092] Based on the first initial weighting coefficient of particulate matter in each particle size range within each time period within the preset time period, calculate the first weighting coefficient of particulate matter in each particle size range within the preset time period.

[0093] Based on the second initial weighting coefficient of particulate matter in each particle size range within the preset time period, the second weighting coefficient of particulate matter in each particle size range within the preset time period is calculated.

[0094] In this embodiment of the application, a weighted summation and averaging method is used to calculate the first weight coefficient and the second weight coefficient of particles in each particle size range within a preset time. Since the first initial weight coefficient is less than the second initial weight coefficient, and the first weight coefficient is obtained by weighted summation and averaging of the first initial weight coefficient, and the second weight coefficient is obtained by weighted summation and averaging of the second initial weight coefficient, the first weight coefficient is less than the second weight coefficient.

[0095] In this embodiment of the application, for particulate matter of each particle size segment within each time period, the comparison result of the particulate matter of that particle size segment within that time period is determined to be less than a second preset threshold. If the comparison result is less than the second preset threshold, a first initial weighting coefficient is set for the particulate matter of that particle size segment, and the first weighting coefficient of the particulate matter of each particle size segment within that time period is calculated by weighted summation and averaging. If the comparison result is not less than the second preset threshold, a second initial weighting coefficient is set for the particulate matter of that particle size segment, and the second weighting coefficient of the particulate matter of each particle size segment within that time period is calculated by weighted summation and averaging.

[0096] This application embodiment sets a weighting coefficient for particulate matter of each particle size range within each time period. The purpose is to either highlight the number concentration data of particulate matter of that particle size range within that time period, or to reduce the number concentration data of particulate matter of that particle size range within that time period. For example, if the comparison result is less than a second preset threshold, it indicates that the number concentration data of particulate matter of that particle size range within that time period is not standard. In this case, a first initial weighting coefficient is set to further reduce the proportion of the number concentration data of particulate matter of that particle size range in the pollution source within that time period. If the comparison result is not less than the second preset threshold, it indicates that the number concentration data of particulate matter of that particle size range within that time period is standard. In this case, a second initial weighting coefficient is set to further highlight the proportion of the number concentration data of particulate matter of that particle size range in the pollution source within that time period.

[0097] In this embodiment, the second preset threshold can be set to 0.7, or different values ​​can be set according to different needs. This application does not restrict the setting of the second preset threshold.

[0098] For example, refer to Figure 2The particle size range of each particulate matter in each time period is divided into 1-58 segments, and a second preset threshold of 0.7 is set. For any particulate matter, the Pearson correlation formula is used to calculate the comparison results of particulate matter in different size segments within each time period. Taking particle size segment P10 as an example, if the correlation of the number concentration data of the collected particulate matter in particle size segment P10 is less than 0.7, it indicates that the number concentration data of the collected particulate matter in particle size segment P10 is not standardized. In this case, a first initial weighting coefficient is set for the particulate matter in this particle size segment, and a weighted summation and averaging method is used to compare the number concentration data of each particulate matter in the preset time period. The first initial weighting coefficient of particulate matter in each particle size segment within a time period is calculated. If the correlation of the number concentration data of particulate matter collected in particle size segment P10 is not less than 0.7, it indicates that the number concentration data of particulate matter collected in particle size segment P10 is relatively standard. Then, a second initial weighting coefficient is set for particulate matter in particle size segment P10, and a weighted summation and averaging method is used to calculate the second initial weighting coefficient of particulate matter in each particle size segment within the preset time period.

[0099] Third, based on the operations of the first and second steps, for any particle size segment, the corrected number concentration data of the particle size segment in each time period within the preset time period are summed to obtain the number concentration data of the particle size segment in the preset time period.

[0100] Fourth, the number concentration data of particulate matter corresponding to each particle size segment in the preset time period in the third step and the weight coefficients obtained in the second step are input into the orthogonal matrix factor analysis model, and the first contribution rate of particulate matter of different particle size segments of different pollution sources in the target environmental receptor in the preset time period is output.

[0101] In step 104, based on the first contribution rate of particulate matter of different particle size ranges from different pollution sources in the target environmental receptor during a preset time period, the pollution sources of atmospheric particulate matter in the target environmental receptor during the preset time period are searched from the typical particulate matter emission source particle size spectrum library.

[0102] Based on the typical particulate matter emission source particle size spectrum library established in step 101, the first contribution rate of different particle size segments of different pollution sources in the target environmental receptor obtained in step 103 for a preset time period is matched with the typical particulate matter emission source particle size spectrum library to obtain the pollution sources of atmospheric particulate matter in the target environmental receptor for a preset time period.

[0103] For example, in step 103, the first contribution rate of particulate matter of different particle size ranges corresponding to five pollution sources A, B, C, D, and E in the target environmental receptor during a preset time period is obtained, with reference to... Figure 3From top to bottom, the first contribution rates of particulate matter in different particle size ranges corresponding to five different pollution sources, namely A, B, C, D, and E, are shown. Then, the distribution of the first contribution rates of particulate matter in different particle size ranges of these five pollution sources is matched with the first contribution rates of particulate matter in different particle size ranges of different pollution sources in the typical particulate matter emission source particle size spectrum library. It is found that pollution source A is process dust, pollution source B is road dust, pollution source C is exhaust dust (motor dust), pollution source D is construction dust, and pollution source E is combustion source dust (stationary combustion dust).

[0104] In one possible implementation, after identifying the sources of atmospheric particulate matter pollution in the target environmental receptor for a predetermined time period from a typical particulate matter emission source size spectrum library, the method may further include:

[0105] Based on the orthogonal matrix factor analysis model, the second contribution rate of particulate matter from different pollution sources in the target environmental receptor during a preset time period is identified. The second contribution rate is the proportion of the sum of the number concentration data of particulate matter from any pollution source in the number concentration data of the target environmental receptor.

[0106] In this embodiment of the application, based on step 103, several types of pollution sources can be set based on the orthogonal matrix factor analysis model, and the second contribution rate of particulate matter from different pollution sources in the target environmental receptor during a preset time period can be identified. The second contribution rate is the proportion of the sum of the number concentration data of particulate matter from any pollution source in the number concentration data of the target environmental receptor.

[0107] In this process, while obtaining the second contribution rate of particulate matter from different pollution sources in the target environmental receptor during a preset time period, the first contribution rate of the number concentration data of particulate matter in different particle size ranges of each pollution source is also obtained. Then, the first contribution rate of the number concentration data of particulate matter in different particle size ranges of each pollution source is matched with the typical particulate matter emission source particle size spectrum library established in step 101 to accurately determine the types of pollution sources, thereby obtaining the proportion of different pollution sources in the target environmental receptor during the preset time period.

[0108] For example, refer to Figure 3Based on the orthogonal matrix factor analysis model, the number concentration data of pollution source A, B, C, D, and E in the target environmental receptors were obtained as follows: 25% for pollution source A, 15% for pollution source B, 20% for pollution source C, 10% for pollution source D, and 30% for pollution source E. Then, according to the particle size spectrum library of typical particulate matter emission sources, pollution source A was identified as process dust, pollution source B as road dust, pollution source C as exhaust dust (motorized dust), pollution source D as construction dust, and pollution source E as combustion source dust (stationary combustion dust). Thus, the proportions of process dust, road dust, pollution source dust, construction dust, and combustion source dust in the target environmental receptors were determined to be 25%, 15%, 20%, 10%, and 30%, respectively.

[0109] This application provides a method for analyzing particulate matter sources. Based on a typical particulate matter emission source particle size spectrum library, this application can better demonstrate the distribution of the first contribution rate of particulate matter in different particle size ranges from different pollution sources. The more refined division of particle size ranges in the typical particulate matter emission source particle size spectrum library improves the accuracy of pollution source analysis results for particulate matter in environmental receptors. Furthermore, this application does not require offline testing using chemical instruments, resulting in low cost and high efficiency.

[0110] The above-mentioned particulate matter source analysis method is illustrated below by comparing the source apportionment and electron microscopy results of PM10 particle size distribution data in the examples.

[0111] Scanning electron microscopy (SEM) allows for the classification and summarization of the type and source of each particulate matter (based on the US EPA's "Technical Guidelines for SEM-EDS Particulate Matter Sample Analysis" and the national standard GB / T 35099-2018 "Scanning Electron Microscopy-Energy Spectroscopy - Morphology and Elemental Analysis of Fine Atmospheric Particles"). Mass concentration data of particulate matter from the target environmental receptor were collected from 9:40 AM on March 24th to 10:00 AM on April 6th. SEM results showed that soil dust accounted for 40.1%, construction dust for 21.5%, combustion source dust (including stationary combustion, motor vehicle combustion, and biomass combustion) for 28.4%, and other sources for 10.0%. Specific percentages are detailed in [reference needed]. Figure 4 Based on particle size distribution data, the sources of PM10 concentration during the same period were analyzed. Dust sources contributed the most, accounting for 44.2%, with construction dust and road dust accounting for 33.0% and 18.2%, respectively. Motor vehicles, stationary combustion sources, and industrial process sources accounted for 14.0%, 24.1%, and 10.7%, respectively. For specific percentages, please refer to [reference needed]. Figure 5 .

[0112] The analysis results of both methods indicate that dust sources (including road dust and construction dust) contribute the most to PM10, followed by combustion sources (motor vehicles, stationary combustion, etc.). The analysis results are basically consistent, indicating that the analysis results in the embodiments of this application can basically reflect the main sources of PM10.

[0113] The above-mentioned particulate matter source analysis method will be further explained below by comparing the source apportionment and component apportionment results of PM2.5 particle size distribution data in the examples.

[0114] By analyzing the concentration data of anions and cations, OC / EC, and heavy metals from group stations, the sources of PM2.5 can be analyzed using a PMF model. Mass concentration data of particulate matter from target environmental receptors were collected from April 18th to 27th. Based on the component data, the PM2.5 analysis results show that secondary inorganic salts accounted for 29.9%, dust sources for 28.5%, stationary combustion sources for 22.1%, motor vehicles for 11.0%, and process sources for 8.5%. For detailed percentages, please refer to [reference needed]. Figure 6 The distribution of the corresponding particle size range is shown in the reference. Figure 7 Based on particle size distribution data, the sources of PM2.5 concentration during the same period were analyzed. Secondary inorganic salts and other sources contributed a total of 27.0%, dust sources accounted for 26.6%, stationary combustion sources accounted for 22.9%, motor vehicles accounted for 15.0%, and process sources accounted for 8.5%. For detailed percentages, please refer to [reference needed]. Figure 8 The distribution of the corresponding particle size range is shown in the reference. Figure 9 .

[0115] The analysis results of the two methods mentioned above indicate that, apart from secondary inorganic salts, dust sources contribute the most to PM2.5 during this period, followed by stationary combustion sources, motor vehicles, and process sources. The analysis results are basically consistent, indicating that the analysis results in the embodiments of this application can basically reflect the main sources of PM2.5.

[0116] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0117] The following are device embodiments of this application. For details not described in detail, please refer to the corresponding method embodiments described above.

[0118] Figure 10 A schematic diagram of the particulate matter source analysis device provided in an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown, and are described in detail below:

[0119] like Figure 10 As shown, the particulate matter source analysis device 10 includes:

[0120] Module 101 is established to acquire number concentration data of particulate matter of different sizes from at least one pollution source and to establish a typical particulate matter emission source size spectrum library. The pollution sources include road dust, construction dust, exhaust dust, combustion source dust, and process dust. The typical particulate matter emission source size spectrum library includes the first contribution rate of particulate matter of different size segments from any pollution source. The first contribution rate is the proportion of the number concentration data of particulate matter of any size segment in the number concentration data of particulate matter of that pollution source.

[0121] Monitoring module 102 is used to monitor the number concentration data of particulate matter in the target environmental receptor during a preset time period;

[0122] The identification module 103 is used to identify the first contribution rate of different particle size segments of different pollution sources in the target environmental receptor based on the number concentration data of particulate matter in the target environmental receptor during the preset time period and an orthogonal matrix factor analysis model.

[0123] The matching module 104 is used to search for the pollution sources of atmospheric particulate matter in the target environmental receptor during the preset time period from the typical particulate matter emission source particle size spectrum library based on the first contribution rate of particulate matter of different particle size ranges of different pollution sources in the target environmental receptor during the preset time period.

[0124] This application provides a particulate matter source analysis device. Based on a typical particulate matter emission source particle size spectrum library, this application can better display the distribution of the first contribution rate of particulate matter in different particle size segments of different pollution sources. Based on the more refined division of particle size segments in the typical particulate matter emission source particle size spectrum library, the accuracy of pollution source analysis results of particulate matter in environmental receptors is improved. Furthermore, this application does not require offline testing with the aid of chemical instruments, which is low in cost and high in efficiency.

[0125] In one possible implementation, building the module specifically includes:

[0126] The classification module is used to classify the number concentration data of particulate matter from various pollution sources according to different particle size ranges, and obtain the particle size range data corresponding to each particle size range. The particle size range data includes the number concentration data of particulate matter and the first contribution rate.

[0127] The first calculation module is used to determine that for any pollution source, if the first contribution rate of all particle size segments of the pollution source meets a first condition, then the pollution source of that particle size segment is road dust. The first condition is:

[0128]

[0129] in, For particle size range P n First contribution rate, P nFor particle size segment numbered n, where n is the total number of particle size segment numbers;

[0130] The second calculation module is used to determine that the pollution source of a certain particle size range is construction dust if the first contribution rate of all particle size ranges of the pollution source meets the second condition. The second condition is:

[0131]

[0132] The third calculation module is used to determine that the pollution source of a certain particle size range is exhaust dust if the first contribution rate of all particle size ranges of the pollution source meets the third condition. The third condition is:

[0133]

[0134] The fourth calculation module is used to determine the pollution source of a particle size range as combustion source dust and process dust if the first contribution rate of all particle size ranges of the pollution source meets the fourth condition. The fourth condition is:

[0135]

[0136] The module is used to construct a typical particulate matter emission source size spectrum library based on the first contribution rate of particulate matter from each pollution source and the corresponding different particle size ranges of the pollution source.

[0137] In one possible implementation, the fourth computation module is also used for:

[0138] Calculate two possible values ​​for the particle size range number that satisfy the fourth condition, and use them as the first and second values;

[0139] If the first value is greater than the second value, then the pollution source for the particle size range corresponding to the first value is combustion source dust, and the pollution source for the particle size range corresponding to the second value is process dust.

[0140] If the first value is less than the second value, then the pollution source for the particle size range corresponding to the first value is process dust, and the pollution source for the particle size range corresponding to the second value is combustion source dust.

[0141] In one possible implementation, the preset time period may include multiple time periods, and the number concentration data of particulate matter in the target environmental receptor may include the number concentration data of particulate matter corresponding to each time period.

[0142] In one possible implementation, the identification module may specifically include:

[0143] The judgment module is used to monitor whether there are abnormal data in the number concentration data of particulate matter for any given time period. Abnormal data includes zero values, negative values, and blank values.

[0144] The deletion module is used to delete the number concentration data of particulate matter in the corresponding time period if abnormal data is found and the abnormality rate of the number concentration data of particulate matter in the corresponding time period is greater than a first preset threshold.

[0145] The correction module is used to correct abnormal data by using a first formula if abnormal data occurs and the abnormality rate of the number concentration data of particulate matter in the corresponding time period is not greater than a first preset threshold, so as to obtain the corrected number concentration data of particulate matter.

[0146] The comparison module is used to perform correlation comparison between the number concentration data of each particulate matter in different particle size ranges for each time period and the sum of the number concentration data of the particulate matter in that time period, based on the corrected number concentration data of particulate matter, to obtain the comparison results of particulate matter in different particle size ranges within each time period.

[0147] The weight determination module is used to determine the weight coefficients of particles of different particle sizes in a preset time period based on the comparison results of particles of different particle sizes in each time period, and to sum the corrected number concentration data of particles of that particle size in each time period in the preset time period for any particle size, so as to obtain the number concentration data of particles of that particle size in the preset time period.

[0148] The output module is used to input the number concentration data and weighting coefficients of particulate matter corresponding to each particle size segment in the preset time period into the orthogonal matrix factor analysis model, and output the first contribution rate of particulate matter of different particle size segments of different pollution sources in the target environmental receptor in the preset time period.

[0149] The first formula is:

[0150]

[0151] in, For the corrected particle size range P n Particulate matter particle size monitoring data, For particle size range P n Particulate matter particle size monitoring data, where n is the particle size range P n The number.

[0152] In one possible implementation, the comparison module can specifically be used for:

[0153] The comparison results of particulate matter of different particle sizes within each time period were calculated using the Pearson correlation formula, which is as follows:

[0154]

[0155] Where r represents the comparison results of particulate matter of different particle sizes within time period i. For the Pth time interval of time in Number concentration data for particles in the specified particle size range. For the Pth time segment within the corrected time period i n Number concentration data for particles in the specified particle size range. PM within time period i 10 Number concentration data, PM within the corrected time period i 10 The number concentration data.

[0156] In one possible implementation, the weight determination module can be used to:

[0157] For each particle size segment within each time period, determine whether the comparison result of the particle size segment within that time period is less than a second preset threshold; if the comparison result of the particle size segment within that time period is less than the second preset threshold, then set a first initial weighting coefficient for the particle size segment; if the comparison result of the particle size segment within that time period is not less than the second preset threshold, then set a second initial weighting coefficient for the particle size segment; wherein, the first initial weighting coefficient is less than the second initial weighting coefficient.

[0158] Based on the first initial weighting coefficient of particulate matter in each particle size range within each time period within the preset time period, calculate the first weighting coefficient of particulate matter in each particle size range within the preset time period.

[0159] Based on the second initial weighting coefficient of particulate matter in each particle size range within the preset time period, the second weighting coefficient of particulate matter in each particle size range within the preset time period is calculated.

[0160] In one possible implementation, after the matching module, the device can also be used for:

[0161] Based on the orthogonal matrix factor analysis model, the second contribution rate of particulate matter from different pollution sources in the target environmental receptor during a preset time period is identified. The second contribution rate is the proportion of the sum of the number concentration data of particulate matter from any pollution source in the number concentration data of the target environmental receptor.

[0162] Figure 11 This is a schematic diagram of the terminal provided in an embodiment of this application. For example... Figure 11 As shown, the terminal 11 in this embodiment includes: a processor 110, a memory 111, and a computer program 112 stored in the memory 111 and executable on the processor 110. When the processor 110 executes the computer program 112, it implements the steps in the various particulate matter source analysis method embodiments described above, for example... Figure 1 Steps 101 to 104 are shown. Alternatively, when the processor 110 executes the computer program 112, it implements the functions of each module in the above-described device embodiments, for example... Figure 10 The functions of modules 101 to 104 are shown.

[0163] For example, the computer program 112 can be divided into one or more modules, which are stored in the memory 111 and executed by the processor 110 to complete this application. The one or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 112 in the terminal 11. For example, the computer program 112 can be divided into... Figure 10 Modules 101 to 104 are shown.

[0164] The terminal 11 can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. The terminal 11 may include, but is not limited to, a processor 110 and a memory 111. Those skilled in the art will understand that... Figure 11 This is merely an example of terminal 11 and does not constitute a limitation on terminal 11. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal may also include input / output devices, network access devices, buses, etc.

[0165] The processor 110 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0166] The memory 111 can be an internal storage unit of the terminal 11, such as a hard disk or memory of the terminal 11. The memory 111 can also be an external storage device of the terminal 11, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or FlashCard equipped on the terminal 11. Furthermore, the memory 111 can include both internal storage units and external storage devices of the terminal 11. The memory 111 is used to store the computer program and other programs and data required by the terminal. The memory 111 can also be used to temporarily store data that has been output or will be output.

[0167] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0168] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0169] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0170] In the embodiments provided in this application, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0171] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0172] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0173] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various particulate matter source analysis method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately added to or subtracted from the content as required by the legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium may not include electrical carrier signals and telecommunication signals.

[0174] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for analyzing the source of particulate matter, characterized in that, include: Acquire number concentration data of particulate matter of different sizes from at least one pollution source and establish a typical particulate matter emission source size spectrum library, wherein the pollution source includes road dust, construction dust, exhaust dust, combustion source dust, and process dust; the typical particulate matter emission source size spectrum library includes a first contribution rate of particulate matter of different size segments from any pollution source; the first contribution rate is the proportion of the number concentration data of particulate matter of any size segment in the number concentration data of particulate matter of that pollution source. Monitor the number concentration data of particulate matter in the target environmental receptor during a preset time period; Based on the number concentration data of particulate matter in the target environmental receptor during the preset time period, and using an orthogonal matrix factor analysis model, the first contribution rate of different particle size segments of different pollution sources in the target environmental receptor during the preset time period is identified. Based on the first contribution rate of particulate matter of different particle size ranges from different pollution sources in the target environmental receptor during the preset time period, the pollution sources of atmospheric particulate matter in the target environmental receptor during the preset time period are searched from the typical particulate matter emission source particle size spectrum library. The preset time period includes multiple time periods, and the number concentration data of particulate matter in the target environmental receptor includes the number concentration data of particulate matter corresponding to each time period. The step of identifying the first contribution rate of different particle size ranges from different pollution sources in the target environmental receptor based on the number concentration data of particulate matter in the target environmental receptor during the preset time period, using an orthogonal matrix factor analysis model, includes: For particulate matter number concentration data corresponding to any time period, monitor whether there are abnormal data in the particulate matter number concentration data corresponding to that time period. The abnormal data includes zero value, negative value and blank value. If abnormal data is found and the abnormality rate of the particulate matter number concentration data for that time period is greater than the first preset threshold, then the particulate matter number concentration data for that time period will be deleted. If abnormal data is found and the abnormality rate of the particulate matter number concentration data corresponding to that time period is not greater than the first preset threshold, the abnormal data is corrected by the first formula to obtain the corrected particulate matter number concentration data. Based on the corrected number concentration data of particulate matter, the correlation between the number concentration data of each particulate matter in different particle size ranges for each time period and the sum of the number concentration data of particulate matter in that time period is compared to obtain the comparison results of particulate matter in different particle size ranges within each time period. Based on the comparison results of particles of different particle sizes in each time period, the weighting coefficients of particles of different particle sizes in the preset time period are determined, and for any particle size, the corrected number concentration data of particles of that particle size in each time period in the preset time period are summed to obtain the number concentration data of particles of that particle size in the preset time period. The number concentration data and weighting coefficients of particulate matter corresponding to each particle size segment in the preset time period are input into the orthogonal matrix factor analysis model, and the first contribution rate of particulate matter of different particle size segments of different pollution sources in the target environmental receptor in the preset time period is output. The first formula is: ， in, For the corrected particle size range Particulate matter particle size monitoring data, Particle size range Particulate matter particle size monitoring data, Particle size range The number.

2. The particulate matter source analysis method according to claim 1, characterized in that, The acquisition of number concentration data of particulate matter of different sizes from at least one pollution source, and the establishment of a typical particulate matter emission source size spectrum library, includes: The number concentration data of particulate matter from each pollution source are classified according to the particle size range of different particle size segments to obtain the particle size segment data corresponding to each particle size segment. The particle size segment data includes the number concentration data of particulate matter and the first contribution rate. For any pollution source, if the first contribution rate of all particle size segments of the pollution source satisfies a first condition, then the pollution source of that particle size segment is determined to be road dust. The first condition is: ， in, Particle size range First contribution rate For the number Particle size range, The total number of particle size ranges; If the first contribution rate of all particle size ranges of the pollution source meets the second condition, then the pollution source of that particle size range is determined to be construction dust. The second condition is: ； If the first contribution rate of all particle size ranges of the pollution source meets the third condition, then the pollution source of that particle size range is determined to be exhaust dust. The third condition is: ； If the first contribution rate of all particle size ranges of the pollution source satisfies the fourth condition, then the pollution source of that particle size range is determined to be combustion source dust and process dust. The fourth condition is: ； Based on the first contribution rate of particulate matter from each pollution source and the corresponding particle size range of the pollution source, a typical particulate matter emission source particle size spectrum library is constructed.

3. The method for analyzing the source of particulate matter according to claim 2, characterized in that, After determining that the pollution source of a certain particle size range is combustion source dust and process dust if the first contribution rate of all particle size ranges of the pollution source satisfies the fourth condition, the method further includes: Calculate two values ​​for the particle size segment number that satisfy the fourth condition, and use them as the first value and the second value; If the first value is greater than the second value, then the pollution source of the particle size segment corresponding to the first value is combustion source dust, and the pollution source of the particle size segment corresponding to the second value is process dust. If the first value is less than the second value, then the pollution source for the particle size range corresponding to the first value is process dust, and the pollution source for the particle size range corresponding to the second value is combustion source dust.

4. The particulate matter source analysis method according to claim 1, characterized in that, The process involves comparing the number concentration data of each particulate matter in different particle size ranges within each time period with the sum of the number concentration data of the particulate matter in that time period, based on the corrected particulate matter number concentration data, to obtain the comparison results of particulate matter in different particle size ranges within each time period, including: The comparison results of particulate matter of different particle size ranges within each time period were calculated using the Pearson correlation formula, which is as follows: ， in, for Comparison results of particulate matter of different particle sizes within a time period. for The first time period Number concentration data for particles in the specified particle size range. For the revised version The first time period Number concentration data for particles in the specified particle size range. for within the time period Number concentration data, For the revised version within the time period The number concentration data.

5. The method for analyzing the source of particulate matter according to claim 4, characterized in that, The step of determining the weighting coefficients of particulate matter of different size ranges within the preset time period based on the comparison results of particulate matter of different size ranges within each time period includes: For each particle size segment within each time period, determine whether the comparison result of the particle size segment within that time period is less than a second preset threshold; if the comparison result of the particle size segment within that time period is less than the second preset threshold, then set a first initial weighting coefficient for the particle size segment; if the comparison result of the particle size segment within that time period is not less than the second preset threshold, then set a second initial weighting coefficient for the particle size segment; wherein, the first initial weighting coefficient is less than the second initial weighting coefficient. Based on the first initial weighting coefficient of particulate matter in each particle size segment within each time period within the preset time period, calculate the first weighting coefficient of particulate matter in each particle size segment within the preset time period. Based on the second initial weighting coefficient of particulate matter in each particle size segment within each time period of the preset time period, the second weighting coefficient of particulate matter in each particle size segment within the preset time period is calculated.

6. The method for analyzing the source of particulate matter according to claim 1, characterized in that, After searching the typical particulate matter emission source library for the target environmental receptor during the preset time period for the pollution source of atmospheric particulate matter, the method further includes: Based on the orthogonal matrix factor analysis model, the second contribution rate of particulate matter from different pollution sources in the target environmental receptor during the preset time period is identified. The second contribution rate is the proportion of the sum of the number concentration data of particulate matter from any pollution source in the number concentration data of the target environmental receptor.

7. A particulate matter source analysis device, characterized in that, include: A module is established to acquire number concentration data of particulate matter of different sizes from at least one pollution source and to establish a typical particulate matter emission source size spectrum library. The pollution sources include road dust, construction dust, exhaust dust, combustion source dust, and process dust. The typical particulate matter emission source size spectrum library includes a first contribution rate of particulate matter of different size segments from any pollution source. The first contribution rate is the proportion of the number concentration data of particulate matter of any size segment in the total number concentration data of particulate matter from that pollution source. The monitoring module is used to monitor the number concentration data of particulate matter in the target environmental receptor during a preset time period; The identification module is used to identify the first contribution rate of different particle size segments of different pollution sources in the target environmental receptor based on the number concentration data of particulate matter in the target environmental receptor during the preset time period and an orthogonal matrix factor analysis model. The matching module is used to search for the pollution sources of atmospheric particulate matter in the target environmental receptor during the preset time period from the typical particulate matter emission source particle size spectrum library based on the first contribution rate of particulate matter of different particle size ranges of different pollution sources in the target environmental receptor during the preset time period. The preset time period includes multiple time periods, and the number concentration data of particulate matter in the target environmental receptor includes the number concentration data of particulate matter corresponding to each time period. The identification module includes: The judgment module is used to monitor whether there are abnormal data in the number concentration data of particulate matter for any given time period. The abnormal data includes zero values, negative values, and blank values. The deletion module is used to delete the number concentration data of particulate matter in the corresponding time period if abnormal data is found and the abnormality rate of the number concentration data of particulate matter in the corresponding time period is greater than a first preset threshold. The correction module is used to correct the abnormal data by a first formula if abnormal data occurs and the abnormal rate of the number concentration data of particulate matter in the corresponding time period is not greater than the first preset threshold, so as to obtain the corrected number concentration data of particulate matter. The comparison module is used to perform correlation comparison between the number concentration data of each particulate matter in different particle size ranges for each time period and the sum of the number concentration data of the particulate matter in that time period, based on the corrected number concentration data of particulate matter, to obtain the comparison results of particulate matter in different particle size ranges within each time period. The weight determination module is used to determine the weight coefficient of the particles in different particle size segments within the preset time period based on the comparison results of particles in different particle size segments within each time period, and to sum the corrected number concentration data of particles in that particle size segment in each time period within the preset time period for any particle size segment, so as to obtain the number concentration data of particles in that particle size segment within the preset time period. The output module is used to input the number concentration data and weight coefficients of particulate matter corresponding to each particle size segment in the preset time period into the orthogonal matrix factor analysis model, and output the first contribution rate of particulate matter of different particle size segments of different pollution sources in the target environmental receptor in the preset time period. The first formula is: ， in, For the corrected particle size range Particulate matter particle size monitoring data, Particle size range Particulate matter particle size monitoring data, Particle size range The number.

8. A terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the particulate matter source analysis method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the particulate matter source analysis method as described in any one of claims 1 to 6.

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