GB2624745A - Method and system for online source apportionment of PM based on isotopes, device, and medium - Google Patents

Method and system for online source apportionment of PM based on isotopes, device, and medium Download PDF

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GB2624745A
GB2624745A GB2313535.3A GB202313535A GB2624745A GB 2624745 A GB2624745 A GB 2624745A GB 202313535 A GB202313535 A GB 202313535A GB 2624745 A GB2624745 A GB 2624745A
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characteristic
target
isotope
particle
isotopes
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Li Mei
Pei Chenglei
Zhang Qianhua
Chen Mubai
Lian Xiufeng
Cheng Chunlei
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Guangzhou Sub Branch Of Guangdong Ecological And Env Monitoring Center
Jinan University
University of Jinan
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Guangzhou Sub Branch Of Guangdong Ecological And Env Monitoring Center
Jinan University
University of Jinan
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    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/1031—Investigating individual particles by measuring electrical or magnetic effects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/06—Investigating concentration of particle suspensions
    • G01N15/0656—Investigating concentration of particle suspensions using electric, e.g. electrostatic methods or magnetic methods
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • H—ELECTRICITY
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    • H01J49/00—Particle spectrometers or separator tubes
    • H01J49/26—Mass spectrometers or separator tubes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N2015/0042—Investigating dispersion of solids
    • G01N2015/0046—Investigating dispersion of solids in gas, e.g. smoke
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N2015/1021—Measuring mass of individual particles
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
    • H01J49/00—Particle spectrometers or separator tubes
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
    • Y02A50/20—Air quality improvement or preservation, e.g. vehicle emission control or emission reduction by using catalytic converters
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
    • Y02A50/20—Air quality improvement or preservation, e.g. vehicle emission control or emission reduction by using catalytic converters
    • Y02A50/2351—Atmospheric particulate matter [PM], e.g. carbon smoke microparticles, smog, aerosol particles, dust

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Abstract

A method of online source apportionment of a particulate matter (PM) based on isotopes includes: performing 110 online monitoring on atmospheric PMs at a target site using a single particle aerosol mass spectrometer to obtain mass spectrum information of a target PM; determining 120 a characteristic element particle (lead, copper, zinc or chlorine) in the target PM based on the mass spectrum information of the target PM using a tracer ion retrieval approach; determining 130 isotope ratios of characteristic isotopes at the target site based on the mass spectrum information of all characteristic element particles at the target site to obtain a plurality of sets of target characteristic data values; and determining 140 a source apportionment result of the target PM based on a pollution source characteristic database and the target characteristic data values.

Description

METHOD AND SYSTEM FOR ONLINE SOURCE APPORTIONMENT OF PM BASED ON ISOTOPES, DEVICE, AND MEDIUM
TECHNICAL FIELD
[0001] The present disclosure relates to the technical field of source apportionment, and in particular, to a method and system for online source apportionment of a particulate matter (PM) based on isotopes, a device, and a medium.
BACKGROUND
[0002] Atmospheric particulate matter (PM) pollution is one of serious environmental pollutions that trouble the world urban environment and development. With increasing global urbanization level, the effects of human activities have been intensified, leading to increasingly serious urban atmospheric pollution. The atmospheric PM pollution caused during urbanization has become an important factor influencing the health of residents. Identifying a pollution source of a PM in the atmosphere to provide data and scientific data for pollution control is of great significance for carrying out atmospheric PM pollution treatment and improving the quality of the urban atmospheric environment.
[0003] A source of atmospheric PM pollution is extremely complicated and its identification is a difficult process. There are three common methods for identifying a pollution source: a chemical method in combination with a "receptor model" and various multivariate statistical analysis methods, a microscopic analysis method, and an isotopic tracing method. The chemical method requires large-area sampling, leading to heavy workload, and is mainly to perform statistical analysis on the contents of various elements and various chemical species in atmospheric dust fall and to perform quality assessment. The microscopic analysis method has the disadvantages of long analysis time, high expense, insensitivity to uncertain organic components accounting for a large proportion in a PM, large errors in observations of a particle density and volume, and the like. The isotopic tracing method may use a natural stable isotopic composition as fingerprint information for a different source to trace a source by making a natural stable isotopic composition range of each source have a significant difference based on an isotopic fractionation behavior in a different formation process of a particular source.
[0004] Many studies on tracing sources and formulation processes of atmospheric PMs based on traditional stable isotopes (carbon, nitrogen, hydrogen, oxygen, and sulfur) have been reported at present, but due to the limitations of analysis techniques, there are few studies on non-traditional stable isotopes in atmospheric PMs. In recent years, with the rapid development of an isotope mass spectrometry technique, in particular the development of an inductively coupled plasma-mass spectrometer (ICP-MS), more compositions of non-traditional stable isotopes (such as lithium, boron, magnesium, silicon, calcium, titanium, alum, chromium, iron, nickel, copper, zinc, germanium, selenium, strontium, molybdenum, silver, cadmium, tin, antimony, tellurium, barium, tungsten, platinum, mercury, thallium, and uranium) can be accurately detected. The non-traditional stable isotopes such as silicon, strontium, iron, zinc, copper, neodymium, lead, mercury, and iodine have been applied in source apportionment studies on atmospheric PMs and heavy metal components thereof 100051 Isotope detection is most commonly used in an inductively coupled plasma-mass spectrometry (ICP-MS) detection technique. A sample is monitored using an ICPMS device after being digested through pretreatment, and contents of various elements and isotopes thereof in the sample can be obtained. However, this technique needs to be implemented in a laboratory through complex detection steps, requires an investment of lots of time and money costs, and has high technical arid economical requirements. In practical work, it is hard to conduct multiple isotopic tracing experiments simultaneously, in a large batch, and online.
[0006] With increasing attention to accurate pollution control, scientific pollution control, and lawful pollution control in ecological environmental protection, techniques and methods for real-time rapid online apportionment of element sources in the atmosphere have become a new trend.
SUMMARY
[0007] An objective of the present disclosure is to provides a method and system for online source apportionment of a PM based on isotopes, a device, and a medium to realize rapid and efficient online source apportionment of a PM with good operability and a low overall operation cost.
100081 To achieve the above objective, the present disclosure provides the following technical solutions, 100091 A method for online source apportionment of a PM based on isotopes includes: 100101 performing online monitoring on atmospheric PMs at a target site using a single particle aerosol mass spectrometer to obtain mass spectrum information of a target PM, where the target PM is an atmospheric PM within the target site in a unit time; and the mass spectrum information characterizes a peak area variation from a mass number of -300 to a mass number of +300; 10011] determining a characteristic element particle in the target PM based on the mass spectrum information of the target PM using a tracer ion retrieval approach, where the characteristic element particle includes at least one of a lead-bearing particle, a copper-bearing particle, a zinc-bearing particle, and a chlorine-bearing particle; 100121 determining isotope ratios of characteristic isotopes of all characteristic element particles at the target site based on the mass spectrum information of all characteristic element particles at the target site to obtain a plurality of sets of target characteristic data values, where the isotope ratios are obtained by taking any isotope of a characteristic element corresponding to the characteristic element particle as a reference isotope and dividing peak areas of other isotopes of the characteristic element corresponding to the characteristic element particle by a peak area of the reference isotope; the characteristic isotopes are characteristic element isotopes except the reference isotope; and a total number of the sets of target characteristic data values is equal to a total number of the characteristic element particles in the target PM; and [0013] determining a source apportionment result of the target PM based on a pollution source characteristic database and the target characteristic data values, where the source apportionment result of the target PM includes a contribution ratio of each atmospheric pollution source to the target PM; and the pollution source characteristic database is established based on mass spectrum information of PM samples of a plurality of atmospheric pollution sources.
[0014] Alternatively, the pollution source characteristic database may be specifically established by: [0015] sampling PMs emitted by a plurality of atmospheric pollution sources, respectively, to obtain PM samples of the plurality of atmospheric pollution sources; [0016] performing composition detection on the PM samples separately using the single particle aerosol mass spectrometer to obtain mass spectrum information of the PM sample of each atmospheric pollution source; 100171 determining a characteristic element particle in the PM sample of each atmospheric pollution source based on the mass spectrum information of the PM sample using the tracer ion retrieval approach, and [0018] determining isotope ratios of characteristic isotopes of each atmospheric pollution source based on the mass spectrum information of all characteristic element particles of each atmospheric pollution source to obtain the pollution source characteristic database.
[0019] Alternatively, the determining a source apportionment result of the target PM based on a pollution source characteristic database and the target characteristic data values may specifically include: [0020] determining a pollution source element characteristic data matrix and a pollution source element characteristic probability distribution function based on the pollution source characteristic database, where each element in the pollution source element characteristic data matrix represents a range of an isotope ratio corresponding to a characteristic isotope in an atmospheric pollution source; a size of the pollution source element characteristic data matrix is k*N, where k is a number of atmospheric pollution sources, and N is a number of characteristic isotopes; and the pollution source element characteristic probability distribution function includes a probability distribution function of the isotope ratios of all characteristic isotopes of each atmospheric pollution source; [0021] establishing a homogeneous linear model based on the pollution source element characteristic data matrix and the target characteristic data values, [0022] solving the homogeneous linear model using a Gaussian elimination approach to obtain apportionment coefficients of the homogeneous linear model; [0023] determining an initial contribution ratio of each atmospheric pollution source to the target PM based on the apportionment coefficients of the homogeneous linear model, 100241 determining a characteristic isotope occurrence probability of each atmospheric pollution source based on the pollution source element characteristic probability distribution function; [0025] determining a weight correction coefficient based on the characteristic isotope occurrence probability; and [0026] determining the source apportionment result of the target PM based on the weight correction coefficient and the initial contribution ratio.
100271 Alternatively, the determining a pollution source element characteristic data matrix and a pollution source element characteristic probability distribution function based on the pollution source characteristic database may specifically include: [0028] determining the pollution source element characteristic data matrix based on the pollution source characteristic database; 100291 for any element in the pollution source element characteristic data matrix, performing equal division to obtain m interval ranges; and for all elements in the pollution source element characteristic data matrix, obtaining a total of k*N*m interval ranges, where in is greater than 2; 100301 for any characteristic isotope in any atmospheric pollution source, calculating probabilities of the isotope ratios of the PM sample falling within the m interval ranges, respectively, to obtain m statistical data sets; and for all characteristic isotopes in all atmospheric pollution sources, obtaining a total of k*N*m statistical data sets; and [0031] establishing k*N*m (m-2)th-order polynomials based on the k*N*m statistical data sets, respectively, and performing polynomial fitting to determine the pollution source element characteristic probability distribution function.
[0032] Alternatively, the establishing a homogeneous linear model based on the pollution source element characteristic data matrix and the target characteristic data values may specifically include.
[0033] determining k*N*(m+ I) interval boundary values based on the k*N*m interval ranges; [0034] determining (m+1) boundary value data matrices based on the k*N*(m+1) interval boundary values, where each element in the boundary value data matrix represents an interval boundary value corresponding to a characteristic isotope in an atmospheric pollution source, and a serial number of the interval boundary value corresponds to a serial number of the boundary value data matrix, and a size of the boundary value data matrix is k*N; [0035] for any boundary value data matrix, arbitrarily selecting k characteristic isotopes from N characteristic isotopes, and establishing T* ek homogeneous equations with corresponding elements in the boundary value data matrix as independent variables of the homogeneous equations and the isotope ratios of corresponding k characteristic isotopes in each set of target characteristic data values as respective dependent variables of the homogeneous equations; and for the (m+1) boundary value data matrices, establishing a total of T*(m+1)m dk homogeneous equations, where T is a total number of the sets of target characteristic data values, and T is greater than or equal to 1; and [0036] determining the T*( m+1)* 0, homogeneous equations as the homogeneous linear model.
[0037] Alternatively, the determining a characteristic element particle in the target PM based on the mass spectrum information of the target PM using a tracer ion retrieval approach may specifically include: [0038] for any target PM: 100391 if peak areas at positions with mass numbers of 206, 207, and 208 in the mass spectrum information of the target PM are not 0, determining that the target PM is the lead-bearing particle; [0040] if peak areas at positions with mass numbers of 63 and 65 in the mass spectrum information of the target PM are not 0 while peak areas at positions with mass numbers of 43 51, 63, and 77 are 0, determining that the target PM is the copper-bearing particle; [0041] if peak areas at positions with mass numbers of 64 and 66 in the mass spectrum information of the target PM are not 0 while peak areas at positions with mass numbers of 43, 51, 63, and 77 are 0, determining that the target PM is the zinc-bearing particle; and [0042] if peak areas at positions with mass numbers of -35 and -37 in the mass spectrum information of the target PM are not 0, determining that the target PM is the chlorine-bearing particle.
[0043] Alternatively, the determining isotope ratios of characteristic isotopes of all characteristic element particles at the target site based on the mass spectrum information of all characteristic element particles at the target site to obtain a plurality of sets of target characteristic data values may specifically include: [0044] for any characteristic element particle at the target site: [0045] if the characteristic element particle is the lead-bearing particle, taking a lead isotope having a mass number of 206 as a reference isotope, and separately dividing peak areas at positions with mass numbers of 204, 207, and 208 in the mass spectrum information of the characteristic element particle by a peak area of the reference isotope to obtain the isotope ratios of lead isotopes; [0046] if the characteristic element particle is the copper-bearing particle, taking a copper isotope having a mass number of 65 as the reference isotope, and dividing a peak area at a position with a mass number of 63 in the mass spectrum information of the characteristic element particle by the peak area of the reference isotope to obtain the isotope ratio of copper isotopes; [0047] if the characteristic element particle is the zinc-bearing particle, taking a zinc isotope having a mass number of 66 as the reference isotope, and dividing a peak area at a position with a mass number of 64 in the mass spectrum information of the characteristic element particle by the peak area of the reference isotope to obtain the isotope ratio of zinc isotopes; [0048] if the characteristic element particle is the chlorine-bearing particle, taking a chlorine isotope having a mass number of -37 as the reference isotope, and dividing a peak area at a position with a mass number of -35 in the mass spectrum information of the characteristic element particle by the peak area of the reference isotope to obtain the isotope ratio of chlorine isotopes; and [0049] determining the isotope ratio(s) of each characteristic element particle within the target site as a set of target characteristic data values, thereby obtaining the plurality of sets of target characteristic data values.
[0050] A system for online source apportionment of a PM based on isotopes includes: [0051] a mass spectrum information acquisition module configured to perform online monitoring on atmospheric PMs at a target site using a single particle aerosol mass spectrometer to obtain mass spectrum information of a target PM, where the target PM is an atmospheric PM within the target site in a unit time; and the mass spectrum information characterizes a peak area variation from a mass number of -300 to a mass number of +300; [0052] a characteristic particle determination module configured to determine a characteristic element particle in the target PM based on the mass spectrum information of the target PM using a tracer ion retrieval approach, where the characteristic element particle includes at least one of a lead-bearing particle, a copper-bearing particle, a zinc-bearing particle, and a chlorine-bearing particle; [0053] a characteristic data determination module configured to determine isotope ratios of characteristic isotopes of all characteristic element particles at the target site based on the mass spectrum information of all characteristic element particles at the target site to obtain a plurality of sets of target characteristic data values, where the isotope ratios are obtained by taking any isotope of a characteristic element corresponding to the characteristic element particle as a reference isotope and dividing peak areas of other isotopes of the characteristic element corresponding to the characteristic element particle by a peak area of the reference isotope; the characteristic isotopes are characteristic element isotopes except the reference isotope, a total number of the sets of target characteristic data values is equal to a total number of the characteristic element particles in the target PM; and [0054] a PM source apportionment module configured to determine a source apportionment result of the target PM based on a pollution source characteristic database and the target characteristic data values, where the source apportionment result of the target PM includes a contribution ratio of each atmospheric pollution source to the target PM; and the pollution source characteristic database is established based on mass spectrum information of PM samples of a plurality of atmospheric pollution sources.
[0055] An electronic device includes a memory and a processor, where the memory is configured to store a computer program, and the processor is configured to run the computer program to cause the electronic device to perform the method for online source apportionment of a PM based on isotopes described above.
100561 A computer-readable storage medium stores a computer program which, when executed by a processor, implements the method for online source apportionment of a PM based on isotopes described above.
[0057] According to specific embodiments provided in the present disclosure, the present disclosure has the following technical effects.
100581 The method for online source apportionment of a PM based on isotopes provided in the present disclosure uses the single particle aerosol mass spectrometer to directly perform online monitoring on the atmospheric PMs at the target site to obtain the mass spectrum information of the target PM, and thus can obtain single particle isotope data with a minute-level resolution. By performing receptor source analysis, the method can realize rapid and efficient source apportionment of the atmospheric PMs at the target site. Secondly, since no consumable is required during detection in the present disclosure and a complicated offline detection process can be avoided, the method is good in operability and low in overall operation cost.
BRIEF DESCRIPTION OF THE DRAWINGS
100591 To describe the technical solutions in embodiments of the present disclosure or in the prior art more clearly, the accompanying drawings required in the embodiments are briefly described below. Apparently, the accompanying drawings in the following description show merely some embodiments of the present disclosure, and other drawings can be derived from these accompanying drawings by those of ordinary skill in the art without creative efforts.
[0060] FIG. 1 is a flowchart of a method for online source apportionment of a PM based on isotopes provided in the present disclosure; 100611 FIG. 2 is a specific flowchart of a method for online source apportionment of a PM based on isotopes provided by an example of the present disclosure; and [0062] FIG. 3 is a module diagram of a system for online source apportionment of a PM based on isotopes provided in the present disclosure.
[0063] List of Reference Numerals: [0064] 1-mass spectrum information acquisition module, 2-characteristic particle determination module, 3-characteristic data determination module, and 4-PM source apportionment module.
DETAILED DESCRIPTION OF THE EMBODIMENTS
[0065] The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Apparently, the described embodiments are merely a part rather than all the embodiments of the present disclosure. All other embodiments derived from the embodiments in the present disclosure by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of the present disclosure.
[0066] An objective of the present disclosure is to provides a method and system for online source apportionment of a PM based on isotopes, a device, and a medium to realize rapid and efficient online source apportionment of a PM with good operability and a low overall operation cost.
[0067] In order to make the above objective, features, and advantages of the present disclosure clearer and more comprehensible, the present disclosure will be further described in detail below in combination with the accompanying drawings and the specific embodiments.
[0068] Example 1
100691 As shown in FIG. 1, the present disclosure provides a method for online source apportionment of a PM based on isotopes, including: [0070] Step 110: online monitoring is performed on atmospheric PMs at a target site using a single particle aerosol mass spectrometer to obtain mass spectrum information of a target PM, where the target PM is an atmospheric PM within the target site in a unit time; and the mass spectrum information characterizes a peak area variation from a mass number of -300 to a mass number of +300. The single particle aerosol mass spectrometer is capable of acquiring a mass spectrum composition of each particle with a minute-level time resolution.
[0071] Step 120: a characteristic element particle in the target PM is determined based on the mass spectrum information of the target PM using a tracer ion retrieval approach, where the characteristic element particle includes at least one of a lead-bearing particle, a copper-bearing particle, a zinc-bearing particle, and a chlorine-bearing particle. Characteristic elements corresponding to the above characteristic element particles are lead element, copper element, zinc element, and chlorine element, respectively. It needs to be noted that the above characteristic elements are only used as examples and other characteristic elements that can be conceived of by a person skilled in the art without creative efforts should also fall within the protection scope of the present disclosure.
100721 Step 130: isotope ratios of characteristic isotopes of all characteristic element particles at the target site are determined based on the mass spectrum information of all characteristic element particles at the target site to obtain a plurality of sets of target characteristic data values, where the isotope ratios are obtained by taking any isotope of a characteristic element corresponding to the characteristic element particle as a reference isotope and dividing peak areas of other isotopes of the characteristic element corresponding to the characteristic element particle by a peak area of the reference isotope; the characteristic isotopes are characteristic element isotopes except the reference isotope; and a total number of the sets of target characteristic data values is equal to a total number of the characteristic element particles in the target PM.
[0073] Step 140: a source apportionment result of the target PM based is determined on a pollution source characteristic database and the target characteristic data values, where the source apportionment result of the target PM includes a contribution ratio of each atmospheric pollution source to the target PM; and the pollution source characteristic database is established based on mass spectrum information of PM samples of a plurality of atmospheric pollution sources.
[0074] As shown in FIG. 2, the above steps are separately discussed in detail below.
100751 Firstly, the pollution source characteristic database needs to be established. That is, the method further includes: [0076] Step 100, the pollution source characteristic database is established based on mass spectrum information of PM samples of a plurality of atmospheric pollution sources. This step specifically includes: [0077] Step 101: PMs emitted by a plurality of atmospheric pollution sources are sampled, respectively, to obtain PM samples of the plurality of atmospheric pollution sources.
[0078] Specifically, the PMs emitted by the plurality of atmospheric pollution sources are collected using gas bags or vacuum bottles.
[0079] Step 102: composition detection is performed on the PM samples separately using the single particle aerosol mass spectrometer to obtain mass spectrum information of the PM sample of each atmospheric pollution source.
[0080] Specifically, a pollution source sample does not need to be pretreated, and a sample container is directly connected to the single particle aerosol mass spectrometer using a hose. After being turned on for detection, the device can automatically perform composition detection on the particles of the pollution source to obtain the mass spectrum information of each particle of the pollution source. The mass spectrum information refers to peak area data from a mass number of -300 to a mass number of +300.
[0081] Step 103: a characteristic element particle in the PM sample of each atmospheric pollution source is determined based on the mass spectrum information of the PM sample using the tracer ion retrieval approach.
100821 Specifically, to eliminate the interference of other components on the mass spectrum signal of the target element and to remain more characteristic information, source spectrum particles need to be purified, and particular retrieval rules are established using the tracer ion retrieval approach to find out the characteristic element particles such as the lead-bearing particle, the copper-bearing particle, the zinc-bearing particle, and the chlorine-bearing particle. For example, the retrieval rule for the lead-bearing particle is that signals need to be simultaneously detected at positions with mass numbers of 206, 207, and 208 in a mass spectrum. The retrieval rule for the zinc-bearing particle is that signals need to be simultaneously detected at positions with mass numbers of 64 and 66 in a mass spectrum and no signal can be detected at positions with mass numbers of 43, 51, 63, and 77 in the mass spectrum. The retrieval rule for the copper-bearing particle is that signals need to be simultaneously detected at positions with mass numbers of 63 and 65 in a mass spectrum and no signal can be detected at positions with mass numbers of 43, 51, 63, and 77 in the mass spectrum. The retrieval rule for the chlorine-bearing particle is that signals need to be simultaneously detected at positions with mass numbers of -35 and -37 in a mass spectrum. The characteristic element particle is obtained after performing retrieval on other elements.
[0083] Step 104: isotope ratios of characteristic isotopes of each atmospheric pollution source are determined based on the mass spectrum information of all characteristic element particles of each atmospheric pollution source to obtain the pollution source characteristic database.
100841 In the characteristic element particle, the isotope ratios of the characteristic isotopes are further obtained. Specifically, peak area values of element isotopes are obtained and then division calculation is performed on the peak area values to obtain the isotope ratios. For example, for the lead-bearing particle, the peak area with a mass number of 208 is divided by the peak area with a mass number of 206, the peak area with a mass number of 207 is divided by the peak area with the mass number of 206, and the peak area with a mass number of 204 is divided by the peak area with the mass number of 206. For the copper-bearing particle, the peak area with a mass number of 63 is divided by the peak area with a mass number of 65. For the zinc-bearing particle, the peak area with a mass number of 64 is divided by the peak area with a mass number of 66. For the chlorine-bearing particle, the peak area with a mass number of -35 is divided by the peak area with a mass number of -37. Since a plurality of particles are collected for each category of pollution source, a range may be obtained for the isotope ratios of the characteristic element of each category of pollution source. This range is specifically a closed interval from a minimum of the isotope ratios to a maximum of the isotope ratios under this category. For ease of discussion, the isotope ratio of the characteristic element of the pollution source is referred to as an element characteristic (i.e., the isotope ratio of the characteristic isotope to the reference isotope).
100851 At this point, the isotope ratio information of the characteristic element particles in all PM samples may be obtained, namely the pollution source characteristic database.
100861 Further, assuming that there are k pollution sources each haying N sets of element characteristics, the isotope ratio data of the characteristic elements of the pollution sources is gathered to form a pollution source element characteristic data matrix. A format of the pollution source element characteristic data matrix is as shown in Table 1 and a specific example thereof is as shown in Table 2.
[0087] Table 1 Format of Pollution source element characteristic data matrix [0088] Element Isotope Pollution Source Pollution Source kl Pollution Source k2 Pollution Source k Element Characteristic Isotope Ratio Isotope Ratio Isotope Ratio NI Range Range Range Element Characteristic Isotope Ratio Isotope Ratio Isotope Ratio N2 Range b Range b Range Element Characteristic Isotope Ratio Isotope Ratio Isotope Ratio N3 Range Range Range Isotope Ratio Range Element Characteristic N Isotope Ratio Isotope Ratio Isotope Ratio Range Range Range [0089] Table 2 Example of Pollution source element characteristic data matrix [0090] Element Isotope Pollution Source Coal-Fired Source Tail Gas Source Industrial Source Pb: 208/206 1-1.5 1.3-2 Value Range Pb: 207/206 1.2-1.4 Value Range Value Range Pb: 204/206 0.7-0.8 Value Range Value Range Cu: 63/65 1.3-1.6 Possibly no Value Range Zn: 64/66 0.3-1.5 Value Range Value Range Cl: -35/-37 0.3-20 Value Range Value Range 100911 Corresponding to the above establishment process of the pollution source characteristic database, the source apportionment process of the atmospheric PMs at the target site also includes the steps of determining the characteristic element particle and the isotope ratios, namely step 120 and step 130.
[0092] Preferably, step 120 specifically includes: for any target PM, if peak areas at positions with mass numbers of 206, 207, and 208 in the mass spectrum information of the target PM are not 0, determine that the target PM is the lead-bearing particle, if peak areas at positions with mass numbers of 63 and 65 in the mass spectrum information of the target PM are not 0 while peak areas at positions with mass numbers of 43, 51, 63, and 77 are 0, determine that the target PM is the copper-bearing particle; if peak areas at positions with mass numbers of 64 and 66 in the mass spectrum information of the target PM are not 0 while peak areas at positions with mass numbers of 43, 51, 63, and 77 are 0, determine that the target PM is the zinc-bearing particle; and if peak areas at positions with mass numbers of -35 and -37 in the mass spectrum information of the target PM are not 0, determine that the target PM is the chlorine-bearing particle.
100931 Preferably, step 130 specifically includes: for any characteristic element particle at the target site if the characteristic element particle is the lead-bearing particle, take a lead isotope having a mass number of 206 as a reference isotope, and separately divide peak areas at positions with mass numbers of 204, 207, and 208 in the mass spectrum information of the characteristic element particle by a peak area of the reference isotope to obtain the isotope ratios of lead isotopes, if the characteristic element particle is the copper-bearing particle, take a copper isotope having a mass number of 65 as the reference isotope, and divide a peak area at a position with a mass number of 63 in the mass spectrum information of the characteristic element particle by the peak area of the reference isotope to obtain the isotope ratio of copper isotopes; if the characteristic element particle is the zinc-bearing particle, take a zinc isotope having a mass number of 66 as the reference isotope, and divide a peak area at a position with a mass number of 64 in the mass spectrum information of the characteristic element particle by the peak area of the reference isotope to obtain the isotope ratio of zinc isotopes; if the characteristic element particle is the chlorine-bearing particle, take a chlorine isotope having a mass number of -37 as the reference isotope, and divide a peak area at a position with a mass number of -35 in the mass spectrum information of the characteristic element particle by the peak area of the reference isotope to obtain the isotope ratio of chlorine isotopes; and determine the isotope ratio(s) of each characteristic element particle within the target site as a set of target characteristic data values, thereby obtaining the plurality of sets of target characteristic data values.
100941 It needs to be noted that, if the characteristic element particle only contains partial characteristic elements, the isotope ratios of other characteristic elements of the characteristic element particle are 0. For example, if the characteristic element particle is merely the lead-bearing particle and contains no other characteristic element, in the target characteristic data values corresponding to the characteristic element particle, the isotope ratios of the characteristic isotopes of the lead element are calculated normally as above, and the isotope ratios of the characteristic isotopes of other elements are all set to 0.
100951 Specifically, step 120 and step 130 are both implemented by software programming.
[0096] Further, Step 140 specifically includes [0097] Step 141: a pollution source element characteristic data matrix and a pollution source element characteristic probability distribution function are determined based on the pollution source characteristic database.
[0098] Each element in the pollution source element characteristic data matrix represents a range of an isotope ratio corresponding to a characteristic isotope in an atmospheric pollution source; a size of the pollution source element characteristic data matrix is k*N, where k is a number of atmospheric pollution sources, and N is a number of characteristic isotopes; and the pollution source element characteristic probability distribution function includes a probability distribution function of the isotope ratios of all characteristic isotopes of each atmospheric pollution source.
[0099] Step 141 specifically includes: [0100] Step 141.1: the pollution source element characteristic data matrix is determined based on the pollution source characteristic database.
[0101] Step 141.2: for any element in the pollution source element characteristic data matrix, equal division is performed to obtain in interval ranges; and for all elements in the pollution source element characteristic data matrix, a total of k*N*m interval ranges are obtained, where m is greater than 2.
[0102] Specifically, each element characteristic range in k pollution sources is equally divided into m portions. Taking the first element characteristic N1 of the first pollution source ki for example, assuming that the element characteristic range thereof is [dko " ekvvi] , an equal rm elc1N1-,11(11 71.
division formula is The element characteristic will be divided into m equally divided rn intervals, where the range of interval m1 (the first interval) is [dkiN,,dkikk, + ek1N1-41N1, and yrz eki -dki ivi eki -d the range of interval m2 (the second interval) is [dkiNi + dk1N1 + 2 * and so on. Finally, for each set of element characteristics, m interval ranges and (m+1) interval boundary values are obtained.
[0103] Step 141.3: for any characteristic isotope in any atmospheric pollution source, probabilities of the isotope ratios of the PM sample falling within the m interval ranges are calculated, respectively, to obtain m statistical data sets; and for all characteristic isotopes in all atmospheric pollution sources, a total of k*N*m statistical data sets are obtained.
[0104] Step 141.4: k*N*m (m-2)th-order polynomials are established based on the k*N*m statistical data sets, respectively, and polynomial fitting is performed to determine the pollution source element characteristic probability distribution function.
101051 Specifically, the probability of the element characteristic of each particle falling within the m intervals is calculated, denoted as Ii, and a (m-2)th-order polynomial is established using the data set [(1, h1), (2, h2),..., (m, h,,,)] by the following formula: 101061 h = ani_2x"2-2 + ar1_3xm-3 + + ax + b 1111071 The data set is substituted into the polynomial for polynomial fitting to obtain polynomial coefficients (am_2, a1_3..... a, b) ; and the probability distribution function of the k*N sets of element characteristics based on the obtained coefficients, respectively.
1111081 Step 142: a homogeneous linear model is established based on the pollution source element characteristic data matrix and the target characteristic data values.
101091 Step 142 specifically includes: 101101 Step 1421: k*N*(m+1) interval boundary values are determined based on the k*N*rn interval ranges.
101111 Step 142.2: (m+1) boundary value data matrices are determined based on the k*N*(m+1) interval boundary values, where each element in the boundary value data matrix represents an interval boundary value corresponding to a characteristic isotope in an atmospheric pollution source, and a serial number of the interval boundary value corresponds to a serial number of the boundary value data matrix; and a size of the boundary value data matrix is k*N.
101121 Specifically, (m+1) element characteristic data matrices are established with the (m+1) interval boundary values obtained for each set of element characteristics in step 142.1, where the minimum of the first interval range (i.e., the first interval boundary value) is taken for the first set of data, and the minimum of the second interval range (i.e., the second interval boundary value) is taken for the second set of data, and so on; the minimum of the mth interval range (i.e., the mth interval boundary value) is taken for the mth set of data, and the maximum (i.e., the (m+l)th interval boundary value) of the mth interval range is taken for the (m+l)th set of data. 101131 Step 142.3: for any boundary value data matrix, k characteristic isotopes are arbitrarily selected from N characteristic isotopes, and T* dk homogeneous equations are established with (a total of k*k) corresponding elements in the boundary value data matrix as independent variables (i.e., xnd to xnkk) of the homogeneous equations and the isotope ratios of corresponding k characteristic isotopes in each set of target characteristic data values (for a set of target characteristic data values, there are k corresponding isotope ratios; for T sets of target characteristic data values, there are a total of T*1( corresponding isotope ratios, where T is a total number of the sets of target characteristic data values, and T is greater than or equal to 1) as respective dependent variables (i.e., for any homogeneous equation, yn, to ynk) of the homogeneous equations; and for the (m+1) boundary value data matrices, a total of T*(m+1)*ghomogeneous equations are established.
[0114] Step 142.4: the T*(m+1)* CIA, homogeneous equations are determined as the homogeneous linear model.
[0115] Specifically, for (m+1) data matrices, in combination with the element characteristic values of the target atmospheric PM (i.e., a set of target characteristic data values corresponding to any characteristic element particle in the target PM), the homogeneous equations are established and solved separately. Taking the first set of data for example, a total of CIA/ homogeneous equations are established. The homogeneous equations are expressed as: [0116] aix,ii + bix"i2 + + kixnik = [0117] a1x,21 + bix,22 + + = [0118] [0119] aixnki + bixnk2 + + kixnkk = y"k [0120] where 1 5 n1 <n2 < < nk 5 N (n1, n2..... rik are any k numbers from 1 to N) ; (cti, b1,c1...,k1) represents solution coefficients for the ith homogeneous equation; (3,74, y,22, , ynk) represents values of different element characteristics (here referring to corresponding isotope ratios) of the target atmospheric PM; x",i represents a value of pollution source I under an element characteristic proportion, and x12 represents a value of pollution source 2 under an element characteristic proportion, and so on.
[0121] Step 143: the homogeneous linear model is solved using a Gaussian elimination approach to obtain apportionment coefficients of the homogeneous linear model.
[0122] Specifically, for Of homogeneous equations corresponding to a characteristic element particle established based on the first boundary value data matrix, the equations are solved using the Gaussian elimination approach. The CIAT homogeneous equations are solved to obtain respective apportionment coefficients (a1, b1... k1), (a2, b2 k2), , ticik k). The apportionment result of a negative value is removed.
[0123] Step 144: an initial contribution ratio (i.e., a one-dimensional pollution source apportionment result) of each atmospheric pollution source to the target PM is determined based on the apportionment coefficients of the homogeneous linear model.
[0124] Specifically, equally weighted arithmetic average calculation is performed on the apportionment coefficients of each pollution source to obtain a contribution coefficient of each a1+a2+...+a k
CN
pollution source aa"g bavg
CN k CN
kavgl The
CAT k CN
contribution coefficient of each pollution source is further normalized to obtain the initial a"v contribution ratio of each pollution source: b'avgl havgl naugl+baugl+-+Icaugl leavgl avvgl+bvvgl+-±kaugl where a'avgl is the initial kayo contribution ratio of pollution source 1, and b' avgi the initial contribution ratio of pollution source 2, ..., and k'a"githe initial contribution ratio of pollution source k.
[0125] For any characteristic element particle in the target PM, the homogeneous equation calculation is performed on the (m+1) element characteristic data matrices to obtain (m+1) one-dimensional pollution source apportionment results respectively: (a' a"gi, a"g1, avg1), (alavy2, avy2, * * * Ktvy2), (alavy(m+1), Ifavg(m+1), * * * leavy(m+1)* [0126] Step 145: a characteristic isotope occurrence probability of each atmospheric pollution source is determined based on the pollution source element characteristic probability distribution function.
[0127] Step 146: a weight correction coefficient is determined based on the characteristic isotope occurrence probability.
[0128] Specifically, the (m+1) interval boundary values for each of N element characteristics of k pollution sources are substituted into the pollution source element characteristic probability distribution function to obtain corresponding pollution source element characteristic occurrence probabilities. Taking the first set of data for example, k*N pollution source element characteristic occurrence probability values TkN Prl can be obtained. The probability values calculated for different element characteristics of the same pollution source are added up to obtain two-dimensional weight correction coefficients of the pollution source: (To, Tb, [0129] (m+1) correction coefficients are calculated in a same way: (Ta, ..., TOP°, . (Ta, Tb, TOP"-1).
[0130] Step 147: the source apportionment result of the target PM is determined based on the weight correction coefficient and the initial contribution ratio.
[0131] Specifically, the correction coefficient calculated in step 146 is multiplied by the initial contribution ratio of the corresponding pollution source in step 144. For any characteristic element particle in the target PM, weights Ta P* alavg, Tapr2* ctiav92 for the contribution ratios of the pollution sources are corrected based on the element characteristic probability distribution to obtain weighted pollution source contribution coefficients (cewri.* Wino * * lewd)T* (a' wt2, b'wt2, * * * wt2)T, * * *, (cliwom+1), wqm+1), * * * wom+.0)1* The weighted coefficient coefficients of the pollution sources are averaged to obtain weighted averaged pollution source contribution coefficients by the following formulas ±F,T kT -m+1 le "tiT+le2T+ +lc\ +1.1T a T 'wt2T+...-Fa'wt(",±1)T aT mu [0132] Finally, the above calculation results are normalized to obtain a two-dimensional source apportionment result ( a'T, b'T, k'T) of the target atmospheric PM, where a'T is the contribution ratio of pollution source 1, and b'T the contribution ratio of pollution source 2, and k'T the contribution ratio of pollution source k. The two-dimensional source apportionment results for all characteristic element particles in the target PM are determined as the source apportionment result of the target PM.
[0133] In this example, the one-dimensional pollution source apportionment results are subjected to weighting correction based on the occurrence frequencies of element characteristics of the pollution sources so that the two-dimensional source apportionment results more in line with the generation of the pollution sources can be obtained.
[0134] Example 2
[0135] To perform the corresponding method of Example 1 so as to implement corresponding functions and technical effects, a system for online source apportionment of a PM based on isotopes is provided below. As shown in FIG. 3, the system includes: [0136] a mass spectrum information acquisition module I configured to perform online monitoring on atmospheric PMs at a target site using a single particle aerosol mass spectrometer to obtain mass spectrum information of a target PM, where the target PM is an atmospheric PM within the target site in a unit time; and the mass spectrum information characterizes a peak area variation from a mass number of -300 to a mass number of +300; [0137] a characteristic particle determination module 2 configured to determine a characteristic element particle in the target PM based on the mass spectrum information of the target PM using a tracer ion retrieval approach, where the characteristic element particle includes at least one of a lead-bearing particle, a copper-bearing particle, a zinc-bearing particle, and a chlorine-bearing particle; [0138] a characteristic data determination module 3 configured to determine isotope ratios of characteristic isotopes at the target site based on the mass spectrum information of all characteristic element particles at the target site to obtain a plurality of sets of target characteristic data values, where the isotope ratios are obtained by taking any isotope of a characteristic element corresponding to the characteristic element particle as a reference isotope and dividing peak areas of other isotopes of the characteristic element corresponding to the characteristic element particle by a peak area of the reference isotope; the characteristic isotopes are characteristic element isotopes except the reference isotope; and a total number of the sets of target characteristic data values is equal to a total number of the characteristic element particles in the target PM; and [0139] a PM source apportionment module 4 configured to determine a source apportionment result of the target PM based on a pollution source characteristic database and the target characteristic data values, where the source apportionment result of the target PM includes a contribution ratio of each atmospheric pollution source to the target PM; and the pollution source characteristic database is established based on mass spectrum information of PM samples of a plurality of atmospheric pollution sources.
[0140] Example 3
101411 An embodiment of the present disclosure further provides an electronic device. The electronic device includes a memory and a processor, where the memory is configured to store a computer program, and the processor is configured to run the computer program to enable the electronic device to perform the method for online source apportionment of a PM based on isotopes in Example 1. The electronic device may be a server.
101421 In addition, the present disclosure further provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method for online source apportionment of a PM based on isotopes in Example I. [0143] The method and system for online source apportionment of a PM based on isotopes, the device, and the medium provided in the present disclosure have the following advantages: [0144] (I) According to the present disclosure, the single particle aerosol mass spectrometry is utilized to directly measure the composition information of the target atmospheric PM to obtain the online monitoring data of the element isotopes of a single particle, and receptor source analysis is performed based on the isotope data of the single particle with a minute-level resolution, therefore, the present disclosure can realize implements rapid and efficient element source apportionment of the target atmospheric PM 101451 (2) According to the present disclosure, since online measurement is performed on the element isotopes of the target atmospheric PM with no need for a consumable during detection and a complicated offline detection process can be avoided, the present disclosure is good in operability and low in overall operation cost.
[0146] (3) The present disclosure innovatively combines the homogeneous linear model with the probability distribution model to form a two-dimensional isotope ratio source apportionment model based on a mass spectrum of a single particle, and online calculation may be carried out to obtain real-time source apportionment results of elements of atmospheric PMs. Therefore, the present disclosure is capable of obtaining comprehensive and reasonable source apportionment results to provide technical support for coping with atmospheric pollution.
101471 Based on the above advantages, the present disclosure can be extensively applied to atmospheric PM pollution control.
101481 The embodiments are described herein in a progressive manner. Each embodiment focuses on the difference from another embodiment, and the same and similar parts between the embodiments may refer to each other. Since the system disclosed in an embodiment corresponds to the method disclosed in an embodiment, the description is relatively simple, and for related contents, references can be made to the description of the method.
101491 Specific examples are used herein to explain the principles and embodiments of the present disclosure. The foregoing description of the embodiments is merely intended to help understand the method of the present disclosure and its core ideas; besides, various modifications may be made by a person of ordinary skill in the art to specific embodiments and the scope of application in accordance with the ideas of the present disclosure. In conclusion, the contents of the present description shall not be construed as limitations to the present disclosure.

Claims (10)

  1. WHAT IS CLAIMED IS: 1. A method for online source apportionment of a particulate matter (PM) based on isotopes, comprising: performing online monitoring on atmospheric PMs at a target site using a single particle aerosol mass spectrometer to obtain mass spectrum information of a target PM, wherein the target PM is an atmospheric PM within the target site in a unit time; and the mass spectrum information characterizes a peak area variation from a mass number of -300 to a mass number of +300; determining a characteristic element particle in the target PM based on the mass spectrum information of the target PM using a tracer ion retrieval approach, wherein the characteristic element particle comprises at least one of a lead-bearing particle, a copper-bearing particle, a zinc-bearing particle, and a chlorine-bearing particle, determining isotope ratios of characteristic isotopes at the target site based on the mass spectrum information of all characteristic element particles at the target site to obtain a plurality of sets of target characteristic data values, wherein the isotope ratios are obtained by taking any isotope of a characteristic element corresponding to the characteristic element particle as a reference isotope and dividing peak areas of other isotopes of the characteristic element corresponding to the characteristic element particle by a peak area of the reference isotope; the characteristic isotopes are characteristic element isotopes except the reference isotope, and a total number of the sets of target characteristic data values is equal to a total number of the characteristic element particles in the target PM; and determining a source apportionment result of the target PM based on a pollution source characteristic database and the target characteristic data values, wherein the source apportionment result of the target PM comprises a contribution ratio of each atmospheric pollution source to the target PM, and the pollution source characteristic database is established based on mass spectrum information of PM samples of a plurality of atmospheric pollution sources.
  2. 2. The method for online source apportionment of a PM based on isotopes according to claim 1, wherein the pollution source characteristic database is specifically established by: sampling PMs emitted by a plurality of atmospheric pollution sources, respectively, to obtain PM samples of the plurality of atmospheric pollution sources; performing composition detection on the PM samples separately using the single particle aerosol mass spectrometer to obtain mass spectrum information of the PM sample of each atmospheric pollution source; determining a characteristic element particle in the PM sample of each atmospheric pollution source based on the mass spectrum information of the PM sample using the tracer ion retrieval approach; and determining isotope ratios of characteristic isotopes of each atmospheric pollution source based on the mass spectrum information of all characteristic element particles of each atmospheric pollution source to obtain the pollution source characteristic database.
  3. 3. The method for online source apportionment of a PM based on isotopes according to claim 2, wherein the determining a source apportionment result of the target PM based on a pollution source characteristic database and the target characteristic data values specifically comprises determining a pollution source element characteristic data matrix and a pollution source element characteristic probability distribution function based on the pollution source characteristic database, wherein each element in the pollution source element characteristic data matrix represents a range of an isotope ratio corresponding to a characteristic isotope in an atmospheric pollution source; a size of the pollution source element characteristic data matrix is k*N, wherein k is a number of atmospheric pollution sources, and N is a number of characteristic isotopes, and the pollution source element characteristic probability distribution function comprises a probability distribution function of the isotope ratios of all characteristic isotopes of each atmospheric pollution source; establishing a homogeneous linear model based on the pollution source element characteristic data matrix and the target characteristic data values; solving the homogeneous linear model using a Gaussian elimination approach to obtain apportionment coefficients of the homogeneous linear model; determining an initial contribution ratio of each atmospheric pollution source to the target PM based on the apportionment coefficients of the homogeneous linear model; determining a characteristic isotope occurrence probability of each atmospheric pollution source based on the pollution source element characteristic probability distribution function; determining a weight correction coefficient based on the characteristic isotope occurrence probability; and determining the source apportionment result of the target PM based on the weight correction coefficient and the initial contribution ratio.
  4. 4. The method for online source apportionment of a PM based on isotopes according to claim 3, wherein the determining a pollution source element characteristic data matrix and a pollution source element characteristic probability distribution function based on the pollution source characteristic database specifically comprises: determining the pollution source element characteristic data matrix based on the pollution source characteristic database; for any element in the pollution source element characteristic data matrix, performing equal division to obtain m interval ranges; and for all elements in the pollution source element characteristic data matrix, obtaining a total of k*N*m interval ranges, wherein m is greater than 2; for any characteristic isotope in any atmospheric pollution source, calculating probabilities of the isotope ratios of the PM sample falling within the m interval ranges, respectively, to obtain m statistical data sets; and for all characteristic isotopes in all atmospheric pollution sources, obtaining a total of k*N*m statistical data sets; and establishing k*N*m (m-2)th-order polynomials based on the k*N*m statistical data sets, respectively, and performing polynomial fitting to determine the pollution source element characteristic probability distribution function.
  5. 5. The method for online source apportionment of a PM based on isotopes according to claim 4, wherein the establishing a homogeneous linear model based on the pollution source element characteristic data matrix and the target characteristic data values specifically comprises: determining k*N*(m+1) interval boundary values based on the k*N*m interval ranges; determining (m+1) boundary value data matrices based on the k'N*(m+1) interval boundary values, wherein each element in the boundary value data matrix represents an interval boundary value corresponding to a characteristic isotope in an atmospheric pollution source, and a serial number of the interval boundary value corresponds to a serial number of the boundary value data matrix, and a size of the boundary value data matrix is k*N; for any boundary value data matrix, arbitrarily selecting k characteristic isotopes from N characteristic isotopes, and establishing T* Clk homogeneous equations with corresponding elements in the boundary value data matrix as independent variables of the homogeneous equations and the isotope ratios of corresponding k characteristic isotopes in each set of target characteristic data values as respective dependent variables of the homogeneous equations; and for the (m+1) boundary value data matrices, establishing a total of T*(m+1)m Or homogeneous equations, wherein T is a total number of the sets of target characteristic data values, and T is greater than or equal to 1; and determining the T*(m+1)*Clk homogeneous equations as the homogeneous linear model.
  6. 6. The method for online source apportionment of a PM based on isotopes according to claim 1, wherein the determining a characteristic element particle in the target PM based on the mass spectrum information of the target PM using a tracer ion retrieval approach specifically comprises: for any target PM: if peak areas at positions with mass numbers of 206, 207, and 208 in the mass spectrum information of the target PM are not 0, determining that the target PM is the lead-bearing particle; if peak areas at positions with mass numbers of 63 and 65 in the mass spectrum information of the target PM are not 0 while peak areas at positions with mass numbers of 43, 51, 63, and 77 are 0, determining that the target PM is the copper-bearing particle; if peak areas at positions with mass numbers of 64 and 66 in the mass spectrum information of the target PM are not 0 while peak areas at positions with mass numbers of 43, 51, 63, and 77 are 0, determining that the target PM is the zinc-bearing particle; and if peak areas at positions with mass numbers of -35 and -37 in the mass spectrum information of the target PM are not 0, determining that the target PM is the chlorine-bearing particle.
  7. 7. The method for online source apportionment of a PM based on isotopes according to claim 1, wherein the determining isotope ratios of characteristic isotopes of an characteristic element particles at the target site based on the mass spectrum information of all characteristic element particles at the target site to obtain a plurality of sets of target characteristic data values specifically comprises: for any characteristic element particle at the target site: if the characteristic element particle is the lead-bearing particle, taking a lead isotope having a mass number of 206 as a reference isotope, and separately dividing peak areas at positions with mass numbers of 204, 207, and 208 in the mass spectrum information of the characteristic element particle by a peak area of the reference isotope to obtain the isotope ratios of lead isotopes; if the characteristic element particle is the copper-bearing particle, taking a copper isotope having a mass number of 65 as the reference isotope, and dividing a peak area at a position with a mass number of 63 in the mass spectrum information of the characteristic element particle by the peak area of the reference isotope to obtain the isotope ratio of copper isotopes; if the characteristic element particle is the zinc-bearing particle, taking a zinc isotope having a mass number of 66 as the reference isotope, and dividing a peak area at a position with a mass number of 64 in the mass spectrum information of the characteristic element particle by the peak area of the reference isotope to obtain the isotope ratio of zinc isotopes, if the characteristic element particle is the chlorine-bearing particle, taking a chlorine isotope having a mass number of -37 as the reference isotope, and dividing a peak area at a position with a mass number of -35 in the mass spectrum information of the characteristic element particle by the peak area of the reference isotope to obtain the isotope ratio of chlorine isotopes; and determining the isotope ratio(s) of each characteristic element particle within the target site as a set of target characteristic data values, thereby obtaining the plurality of sets of target characteristic data values.
  8. 8. A system for online source apportionment of a PM based on isotopes, comprising: a mass spectrum information acquisition module configured to perform online monitoring on atmospheric PMs at a target site using a single particle aerosol mass spectrometer to obtain mass spectrum information of a target PM, wherein the target PM is an atmospheric PM within the target site in a unit time; and the mass spectrum information characterizes a peak area variation from a mass number of -300 to a mass number of +300; a characteristic particle determination module configured to determine a characteristic element particle in the target PM based on the mass spectrum information of the target PM using a tracer ion retrieval approach, wherein the characteristic element particle comprises at least one of a lead-bearing particle, a copper-bearing particle, a zinc-bearing particle, and a chlorine-bearing particle; a characteristic data determination module configured to determine isotope ratios of characteristic isotopes of all characteristic element particles at the target site based on the mass spectrum information of all characteristic element particles at the target site to obtain a plurality of sets of target characteristic data values, wherein the isotope ratios are obtained by taking any isotope of a characteristic element corresponding to the characteristic element particle as a reference isotope and dividing peak areas of other isotopes of the characteristic element corresponding to the characteristic element particle by a peak area of the reference isotope; the characteristic isotopes are characteristic element isotopes except the reference isotope; and a total number of the sets of target characteristic data values is equal to a total number of the characteristic element particles in the target PM; and a PM source apportionment module configured to determine a source apportionment result of the target PM based on a pollution source characteristic database and the target characteristic data values, wherein the source apportionment result of the target PM comprises a contribution ratio of each atmospheric pollution source to the target PM; and the pollution source characteristic database is established based on mass spectrum information of PM samples of a plurality of atmospheric pollution sources.
  9. 9. An electronic device, comprising a memory and a processor, wherein the memory is configured to store a computer program, and the processor is configured to run the computer program to cause the electronic device to perform the method for online source apportionment of a PM based on isotopes according to any one of claims 1 to 7.
  10. 10. A computer-readable storage medium, storing a computer program which, when executed by a processor, implements the method for online source apportionment of a PM based on isotopes according to any one of claims 1 to 7
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