CN114252463A - Urban atmospheric particulate source analysis method - Google Patents
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Abstract
The invention relates to the technical field of atmospheric particulate source analysis, in particular to an urban atmospheric particulate source analysis method, which comprises the following specific steps of S1, setting a sampling point, and setting a sampler at the sampling point to collect atmospheric particulate from different sources; s2, carrying out chemical composition analysis on the collected atmospheric particulates, and calculating errors of chemical components in the particulates by using weights; s3, identifying key pollution components and sources thereof in the atmospheric particulates by adopting an orthogonal matrix factor analysis (PMF) model; and S4, observing the microstructure attributes of the particles by adopting a transmission electron microscope-energy spectrum analysis method, and classifying and judging the sources of the particles according to the main morphology types of the atmospheric particles.
Description
Technical Field
The invention relates to the technical field of atmospheric particulate source analysis, in particular to an urban atmospheric particulate source analysis method.
Background
The atmospheric particulate is complex in source and extremely harmful. The atmospheric particulate sources can be divided into natural sources and artificial sources, wherein the artificial sources are the main sources. There are mainly six types of sources of urban atmospheric particulates: dust emission, coal burning, industrial emission, motor vehicle emission, biomass combustion, and secondary particles generated by oxidation of SO2, NOx, VOCs (hurian swallow et al, 2004). The particle source analysis technology starts from a diffusion model with a pollution source as a target, and in the 70 s of the 20 th century, a receptor model with a pollution area (receptor) as a target is proposed and rapidly developed. The diffusion model is also called a source-oriented model (SM), and is based on a pollutant source emission list and a meteorological field, processes of transmission, diffusion, chemical conversion, sedimentation and the like of pollutants in the atmosphere are simulated by a numerical method, and the contribution conditions of different pollutant sources to the pollutant concentration of a receptor site are estimated on the basis. In the 60's of the 20 th century, Blifford and Meeker first proposed a Receptor Model (RM) (Blifford and Meeker 1967) which focused on the pollution area and studied the contribution of the emission source to the receptor, and analyzed the characteristics of the pollutants at the sampling point to reversely deduce the contribution of the pollution source to the pollutants.
A receptor model without a source component spectrum, such as a multivariate statistical model, needs to acquire a large amount of sample data to obtain a more accurate result, and meanwhile, the method is greatly influenced by the change of meteorological factors and is not suitable for source analysis with more emission sources. The domestic PM2.5 source analysis work is the same as PM2.5 monitoring, starting is late, only sporadic research is distributed in different areas, and systematicness and integrity are lacked. Most PM2.5 source analysis work carried out by utilizing a Chemical Mass Balance (CMB) model method in a receptor model method is more or less lack of a local source component spectrum, so that a source analysis result has great uncertainty; the work of combination, comparison and coupling of different models is rarely carried out; the verification work for the model result is not enough; based on the model simulation result, there is little situation analysis, and the research result lacks guidance opinions on policies.
In order to solve the problems, the application provides an urban atmospheric particulate source analysis method.
Disclosure of Invention
Objects of the invention
In order to solve the technical problems in the background art, the invention provides an urban atmospheric particulate source analysis method which has the characteristics of preventing the blindness of PMF model rotation, avoiding the complete dependence of a chemical mass balance method (CMB) on a local source component spectrum and increasing the known exploration space.
(II) technical scheme
In order to solve the technical problem, the invention provides a method for analyzing urban atmospheric particulate sources, which is characterized by comprising the following specific steps of:
s1, setting sampling points, and setting samplers at the sampling points to collect atmospheric particulates from different sources;
s2, carrying out chemical composition analysis on the collected atmospheric particulates, and calculating errors of chemical components in the particulates by using weights;
s3, identifying key pollution components and sources thereof in the atmospheric particulates by adopting an orthogonal matrix factor analysis (PMF) model;
and S4, observing the microstructure attributes of the particles by adopting a transmission electron microscope-energy spectrum analysis method, and classifying and judging the sources of the particles according to the main morphology types of the atmospheric particles.
Preferably, the sampler uses a four-channel atmospheric particulate intelligent sampler of a rainbow TH-16A type.
Preferably, two channels of each sampler are provided with Teflon films for weighing and ion and metal element analysis; the other two were equipped with quartz membranes for Organic Carbon (OC) and Elemental Carbon (EC) analysis; each sample was taken 24 hours long.
Preferably, when the orthogonal matrix factor analysis (PMF) model is used to identify the pollutant components in the atmospheric particulates in S3:
firstly, calculating errors of chemical components in the particles by using weight, and then determining a main pollution source and a contribution rate of the particles by using a least square method;
assuming that X is an n × m matrix, n is the number of samples, m is the number of chemical components, the matrix X can be decomposed into X ═ GF + E, where G is an n × p matrix, F is a p × m matrix, p is the number of major contamination sources, and E is a residue matrix, defined as follows:
in the formula:
xij-the concentration of substance j on day i in the recipient;
gik-contribution of day i factor k to the receptor;
fkj-fraction of jth substance at kth factor;
eij-residue of j material on day i;
sij-standard deviation of X.
The technical scheme of the invention has the following beneficial technical effects:
and a multivariate linear model (ME-2) model is adopted, so that the blindness of PMF model rotation is avoided. The ME-2 model is also called a multivariate linear model, the basic principle and the equation of the multivariate linear model are the same as those of a PMF model, the main difference is that the ME-2 model enhances the control of rotation, one or more selected factors can be integrally introduced or removed as constraint information without changing the whole output matrix, the blindness of PMF model rotation is prevented, the complete dependence of a Chemical Mass Balance (CMB) method on a local source component spectrum is avoided, and the exploration space of understanding is increased. To add reasonable constraints, the ME-2 model may add acquired a priori information, such as known rows of the factor profile or known columns of factor contributions, to the limits of the model when solving the PMF problem, while still obtaining a mathematically good solution.
The microstructure attribute of the particles is observed by adopting a transmission electron microscope-energy spectrum analysis method, so that the purpose of assisting in determining the source of the key pollution components in the atmospheric particles can be achieved.
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FIG. 1 is a schematic view of the step structure of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
The invention provides a method for analyzing urban atmospheric particulate sources, which comprises the following specific steps:
s1, setting sampling points, and setting samplers at the sampling points to collect atmospheric particulates from different sources;
s2, carrying out chemical composition analysis on the collected atmospheric particulates, and calculating errors of chemical components in the particulates by using weights;
s3, identifying key pollution components and sources thereof in the atmospheric particulates by adopting an orthogonal matrix factor analysis (PMF) model;
and S4, observing the microstructure attributes of the particles by adopting a transmission electron microscope-energy spectrum analysis method, and classifying and judging the sources of the particles according to the main morphology types of the atmospheric particles.
In this embodiment, the PMF optimization objective is to minimize Q towards the degree of freedom value, i.e. the sum of squares. Under the constraint condition that gik is more than or equal to 0 and fkj is more than or equal to 0, the contribution G (relative value) of the pollution source and the component spectrum F (relative concentration value of chemical components) of the pollution source can be simultaneously determined by solving Q through an iterative minimization algorithm. If the pattern matches the data and if the specified deviation does reflect uncertainty in the data, then the number of data points in the concentration data should be approximately equal at Q, and this is used as the basic setting for optimization.
The basic inputs to the PMF model are: mass concentration and uncertainty of each chemical component in the sample. The basic outputs of the PMF model are: the share and uncertainty of each chemical component in a source spectrum; contribution of various factors (sources) to the overall concentration of the particulate matter; time series of contributions of various types of factors (sources).
And a multivariate linear model (ME-2) model is adopted, so that the blindness of PMF model rotation is avoided. The ME-2 model is also called a multivariate linear model, the basic principle and the equation of the multivariate linear model are the same as those of a PMF model, the main difference is that the ME-2 model enhances the control of rotation, one or more selected factors can be integrally introduced or removed as constraint information without changing the whole output matrix, the blindness of PMF model rotation is prevented, the complete dependence of a Chemical Mass Balance (CMB) method on a local source component spectrum is avoided, and the exploration space of understanding is increased. To add reasonable constraints, the ME-2 model may add acquired a priori information, such as known rows of the factor profile or known columns of factor contributions, to the limits of the model when solving the PMF problem, while still obtaining a mathematically good solution. The ME-2 model is defined as follows:
X＝G×F+E
in the formula:
x-sample species concentration matrix;
g is a decomposed non-negative constant matrix and a factor contribution matrix;
f, decomposing the non-negative constant matrix and the factor profile matrix;
e-residual matrix, which is the difference between the measured concentration value and the fitting output value;
eij-residue of j material on day i;
standard deviation of uij-X;
q-uncertainty data based on sample concentration, and the working principle of the ME-2 model is to fit through a multivariate linear model to minimize an objective function, thereby generating the optimal solution of the model.
In the embodiment, the purpose of assisting in determining the source of the key pollution components in the atmospheric particulates can be achieved by observing the microstructure attributes of the particulates by using a transmission electron microscope-energy spectrum analysis method; the particulate morphology and physical properties are shown in the following table:
the working principle and the using process of the invention are as follows: setting sampling points, and setting samplers at the sampling points to collect atmospheric particulates from different sources; a plurality of groups of sampling points are arranged, and the sampling points comprise an industrial area, a road, a seaside, a residential area and a park green land; the sampler adopts a rainbow TH-16A type four-channel intelligent sampler for atmospheric particulates; two channels of each sampler are provided with Teflon films for weighing and analyzing ions and metal elements; the other two were equipped with quartz membranes for Organic Carbon (OC) and Elemental Carbon (EC) analysis; each sample was taken 24 hours long. Then, carrying out chemical composition analysis on the collected atmospheric particulate matters, and calculating errors of all chemical components in the particulate matters by using weights;
then identifying key pollution components and sources thereof in the atmospheric particulates by adopting an orthogonal matrix factor analysis (PMF) model; when PMF model analysis is carried out, further multivariate linear model (ME-2) can be adopted for analysis, and the multivariate linear model (ME-2) can avoid blindness of PMF model rotation
And finally, observing the microstructure attributes of the particles by adopting a transmission electron microscope-energy spectrum analysis method, and classifying and judging the sources of the particles according to the main appearance types of the atmospheric particles.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (5)
1. The urban atmospheric particulate source analysis method is characterized by comprising the following specific steps:
s1, setting sampling points, and setting samplers at the sampling points to collect atmospheric particulates from different sources;
s2, carrying out chemical composition analysis on the collected atmospheric particulates, and calculating errors of chemical components in the particulates by using weights;
s3, analyzing the PMF model by adopting an orthogonal matrix factor, and identifying key pollution components and sources thereof in the atmospheric particulates;
and S4, observing the microstructure attributes of the particles by adopting a transmission electron microscope-energy spectrum analysis method, and classifying and judging the sources of the particles according to the main morphology types of the atmospheric particles.
2. The urban atmospheric particulate source analysis method according to claim 1, wherein the sampler uses an iridescent TH-16A type four-channel atmospheric particulate intelligent sampler.
3. The urban atmospheric particulate source analysis method according to claim 2, wherein two channels of each sampler are provided with Teflon films for weighing and ion and metal element analysis; the other two were equipped with quartz membranes for organic carbon OC and elemental carbon EC analysis; each sample was taken 24 hours long.
4. The urban atmospheric particulate source analysis method according to claim 1, wherein in the step S3, when identifying the pollutant components in the atmospheric particulate by using the orthogonal matrix factor analysis PMF model:
firstly, calculating errors of chemical components in the particles by using weight, and then determining a main pollution source and a contribution rate of the particles by using a least square method;
assuming that X is an n × m matrix, n is the number of samples, m is the number of chemical components, the matrix X can be decomposed into X ═ GF + E, where G is an n × p matrix, F is a p × m matrix, p is the number of major contamination sources, and E is a residue matrix, defined as follows:
in the formula:
xij-the concentration of substance j on day i in the recipient;
gik-contribution of day i factor k to the receptor;
fkj-fraction of jth substance at kth factor;
eij-residue of j material on day i;
sij-standard deviation of X.
5. The urban atmospheric particulate source analysis method according to claim 1, wherein a multivariate linear model ME-2 model is used to optimize the accuracy of a PMF model solution.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114974452A (en) * | 2022-05-24 | 2022-08-30 | 北京中科三清环境技术有限公司 | Method and device for determining control target of secondary conversion source |
| CN116128421A (en) * | 2022-09-23 | 2023-05-16 | 北京清创美科环境科技有限公司 | Atmospheric pollution control scheme generation method coupled with pollution source emission and analysis |
| CN116128421B (en) * | 2022-09-23 | 2023-10-20 | 北京清创美科环境科技有限公司 | Atmospheric pollution control scheme generation method coupled with pollution source emission and analysis |
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