CN111855915A - Atmospheric pollutant tracing method - Google Patents

Atmospheric pollutant tracing method Download PDF

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CN111855915A
CN111855915A CN202010750663.0A CN202010750663A CN111855915A CN 111855915 A CN111855915 A CN 111855915A CN 202010750663 A CN202010750663 A CN 202010750663A CN 111855915 A CN111855915 A CN 111855915A
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刘娟娟
王吉麟
王斌
成巍
张季平
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Abstract

The invention discloses an atmospheric pollutant tracing method, which comprises the following steps: 1) obtaining a source-sink sensitivity matrix by utilizing an atmospheric chemical mode; 2) calculating a correlation coefficient between the simulated concentration generated by releasing pollutants on each grid point of the atmospheric chemical mode and the observed concentration or the residual concentration through the source sink sensitivity matrix obtained in the step 1), and determining the position of the maximum correlation coefficient as the position of the polluted source; 3) calculating the emission intensity of the pollution source determined in the step 2); 4) judging whether all pollution sources are identified or not by using the correlation coefficient obtained in the step 2) and the emission intensity obtained in the step 3), and if so, outputting the number of the pollution sources, the position of each pollution source and the emission intensity; if not, repeating the steps 2) -3) until all pollution sources are identified. The invention can deal with sudden air pollution accidents and reduce the harm of the accidents to the ecological environment and the health of people.

Description

Atmospheric pollutant tracing method
Technical Field
The invention relates to the technical field of pollutant tracing, and relates to a tracing method for atmospheric pollutants.
Background
The current pollutant tracing method mainly combines an atmospheric chemical mode and observation concentration information to invert the characteristics of a pollution source, and researchers at home and abroad have proposed more source item estimation methods, such as a simpler backward trajectory method and a more complex probability method.
And the backward trajectory method directly reverses the wind field of the atmospheric chemical mode, calculates backward Lagrange trajectories of all observed data, and determines the intersection point of all the trajectories as the position of the pollution source. The method has the advantages of simplicity, easiness in implementation, low calculation cost, capability of only performing qualitative analysis and incapability of estimating the intensity of the pollution source, and the estimation result depends on the accuracy degree of a wind field to a great extent because only the advection effect and the diffusion process are considered in the process of calculating the backward track.
The probability method combines available concentration observation data with prior information based on Bayesian inference, considers errors (such as observation errors, mode errors and prior errors) of input data, and finally obtains uncertainty and confidence interval of posterior parameters through sampling estimation. While this method can provide uncertainty information for the estimated parameters, such methods are often time consuming due to the relatively cumbersome sampling process and require a priori information of known sources of contamination, which is difficult to implement in an atmospheric emergency response.
The above methods focus primarily on the estimation of a single source of pollution, while tracing to multiple sources of pollution is less. However, in real conditions, such as factory stack emissions, and sudden leakage of toxic gases, are generally multi-point source emission events. When there are multiple point sources, the observed concentration is a summation of the concentration fields produced by the multiple sources, it is difficult to distinguish the contribution of each source, and weak emission sources near the observation point may have the same effect on the observation site as strong emission sources further away from the observation point, making multi-point source estimation more challenging than single-point source estimation.
In the prior art, only a few methods can realize accurate estimation of the number, the position and the intensity of a plurality of pollution sources, wherein some prior information needs to be given in advance, or the calculation cost is obviously increased along with the increase of the number of the pollution sources, so that the method is difficult to be directly applied to emergency response of atmospheric pollution.
Therefore, a fast and accurate multi-point pollution source estimation method needs to be established to deal with the occurrence of sudden pollution accidents, provide reference for making emergency decisions and guarantee the life health of people.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide a relatively quick and accurate tracing method for atmospheric pollutants, so as to deal with sudden atmospheric pollution accidents and reduce the harm of the accidents to the ecological environment and the health of people.
In order to achieve the purpose, the invention provides the following technical scheme:
an atmospheric pollutant tracing method comprises the following steps:
1) obtaining a source-sink sensitivity matrix by utilizing an atmospheric chemical mode;
2) calculating a correlation coefficient between the simulated concentration generated by releasing pollutants on each grid point of the atmospheric chemical mode and the observed concentration or the residual concentration through the source sink sensitivity matrix obtained in the step 1), and determining the position of the maximum correlation coefficient as the position of the polluted source;
3) calculating the emission intensity of the pollution source determined in the step 2);
4) judging whether all pollution sources are identified or not by using the correlation coefficient obtained in the step 2) and the emission intensity obtained in the step 3),
if so, outputting the number of the pollution sources, the position of each pollution source and the emission intensity;
if not, repeating the steps 2) -3) until all pollution sources are identified.
Further, in the step 1), the position of each observation data is used as a starting point, wind field information of weather forecast is input, the atmospheric chemical mode is operated backwards, a group of source-sink sensitivity matrixes H can be obtained, and each element H in the matrixesijSensitivity of data representing ith observed concentration to pollutant emission flux at jth pattern lattice pointAnd (4) sex.
Further, in step 2), the number n of potential contamination sources is set to 1 at the time of the first calculation.
Further, in step 2), the source-sink sensitivity matrix H obtained in step 1) is multiplied by the pollution source emission matrix to obtain the simulated concentration generated by the released pollutants at each grid point of the atmospheric chemical mode.
Further, in step 2), all grid points of the atmospheric chemical pattern are taken as potential pollution sources.
Further, in step 2), the correlation coefficient between the simulated concentration and the observed concentration generated by the release of the pollutant at each potential pollution source is as follows:
Figure BDA0002609917850000031
wherein j is the number of the atmospheric chemical mode grid points, N is the total number of grid points, i is the number of the observed concentration, m is the total number of the observed data,
Figure BDA0002609917850000032
for the i-th observed concentration data, HijFor the elements, q, in the source-sink sensitivity matrix obtained in step 1)sIs a vector containing the emission intensity of the pollution source, HijAnd q issThe product of (a) is the simulated concentration of the contaminant released at the jth grid point corresponding to the ith observation.
Further, in the step 2), the maximum value of the obtained N correlation coefficients is recorded as Rmax，nAnd the grid point where it is located is determined as the nth pollution source position.
Further, in step 2), the method also comprises the step of storing the maximum correlation coefficient R in each calculationmax，nAnd its location (x)n，yn) And recording the maximum value of all the calculated maximum correlation coefficients as Rmax，Rmax＝MAX(Rmax，p)，p＝1，2，...，n。
Further, in step 3), the emission intensity of all n identified pollution sources is calculated by minimizing a cost function, which is defined as:
Figure BDA0002609917850000033
wherein HeThe method is an m x n dimensional matrix which represents the source-sink relationship between the emission of n pollution sources and m observed concentrations, q is the emission intensity vector of the n pollution sources to be solved, and C DEG is an m x 1 dimensional observed concentration vector.
Further, the step 3) and the step 4) further include calculating residual concentration between the observed concentration and the simulated concentration, wherein the residual concentration is as follows:
Figure BDA0002609917850000034
wherein q iseThe emission intensity of the n pollution sources obtained in the step 3).
Further, in step 4), the judgment conditions for judging that all the pollution sources are identified are as follows:
if the maximum value R among the N correlation coefficients obtained in the nth calculationmax，nLess than the maximum correlation coefficient R in all previous calculationsmaxOr the maximum value of the calculated emission intensity of the pollution source
Figure BDA0002609917850000041
And minimum value
Figure BDA0002609917850000042
By an order of magnitude.
Further, in step 4), when all the contamination sources are not recognized and the next calculation is performed, the number n of the contamination sources is set to n +1, and the residual concentration is used instead of the observed concentration when the correlation coefficient is calculated.
The method can quickly and accurately position the pollution sources, estimates the number of the pollution sources and the corresponding emission intensity of the pollution sources, only needs an atmospheric chemical mode and observation data in the estimation process, does not need any initial guess information, is very suitable for emergency response of sudden pollution accidents, can quickly position the sources, and helps decision makers to make reasonable evacuation measures so as to guarantee the life and property safety of people.
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FIG. 1 is a system flow chart of the tracing method for atmospheric pollutants according to the present invention.
Detailed Description
The technical solution of the present invention will be described in further detail with reference to specific embodiments.
The atmospheric pollutant tracing method mainly comprises the following steps:
1) obtaining a source-sink sensitivity matrix by utilizing an atmospheric chemical mode;
2) calculating a correlation coefficient between the simulated concentration and the observed concentration or the residual concentration generated by releasing the pollutants at each grid point in the atmospheric chemical mode, and determining the position of the maximum correlation coefficient as the estimated position of the pollution source;
3) calculating the emission intensity of the determined pollution source by using a minimum cost function J;
4) judging whether all main pollution sources are identified or not by using the correlation coefficient obtained by calculation and the emission intensity of the pollution sources, if so, finishing iterative calculation, and outputting the number of the pollution sources, the positions of the pollution sources and the emission intensity of each pollution source; if not, repeating the steps 2) -3), continuing the next iterative computation, estimating the unrecognized pollution sources by using the residual concentration, correspondingly increasing the number of the pollution sources until all the pollution sources are recognized, outputting, and finishing the iterative computation.
The system flow of the above steps in the present invention is shown in fig. 1.
The following explains the above steps starting from the first calculation:
obtaining a source-sink sensitivity matrix by using an atmospheric chemical mode:
inputting wind field information of weather forecast by using the position of each observation data as a starting point, and then operating an atmospheric chemical mode to obtain a group of source-sink sensitivity matrixes H, wherein each element H in the matrixesijRepresenting the sensitivity of the ith observed concentration data to the pollutant emission flux at the jth mode lattice point.
In the subsequent calculation process, the matrix is directly multiplied by the pollution source emission matrix to obtain the simulated concentration generated by corresponding emission, so that the time-consuming operation of a forward atmospheric chemical mode is avoided, and the calculation efficiency can be greatly improved.
Calculating the correlation coefficient of the simulated concentration generated by releasing the pollutants on each grid point of the atmospheric chemical mode and the observed concentration or residual concentration:
first, setting the number n of initial pollution sources to 1, and since it is generally difficult to provide location information of potential pollution sources in emergency response, all grid points of the atmospheric chemical model are directly used as potential pollution sources, and a correlation coefficient between a simulated concentration and an observed concentration generated by pollutant release at each grid point is calculated as follows:
Figure BDA0002609917850000051
wherein j is the number of the atmospheric chemical mode grid points, N is the total number of grid points, i is the number of the observed concentration, m is the total number of the observed data,
Figure BDA0002609917850000052
for the i-th observed concentration data, HijElements in the Source-sink sensitivity matrix, q, obtained for atmospheric chemistry mode Back-runningsIs a vector containing the emission intensity of the pollution source, HijAnd q issThe product of (a) is the simulated concentration corresponding to the i-th observed data resulting from the release of the contaminant at the j-th grid point.
It is to be noted that q is released regularly, since it is considered here that the source of contamination is constantly releasedsIs a constant whose value does not affect the correlation coefficient between two sets of variables, so that q can be directly used in the implementation of the methodsThe elements in (b) are set to unit emission intensity to simplify the calculation.
Finding out the simulated concentration and the observed concentration generated by the released pollutants on all the grid pointsThe maximum correlation coefficient between degrees, i.e. the maximum value R of the N correlation coefficients foundmaxnSetting the grid point as the estimated position of the 1 st pollution source, and storing the maximum correlation coefficient R calculated in the first iterationmax，1And its location (x)1，y1)。
Calculating the emission intensity of the determined pollution source:
the emission intensity (source intensity) of the 1 st pollution source is calculated by minimizing a cost function, which is defined as the sum of the squares of the residuals between the simulated and observed concentrations, i.e. the cost function
Figure BDA0002609917850000061
Wherein HeAnd the matrix is an m multiplied by 1 dimension matrix and represents the source-sink relationship between the emission of the 1 st pollution source and the m observed concentrations, q is the emission intensity vector of the 1 st pollution source to be estimated, and C DEG is the observed concentration vector of the m multiplied by 1 dimension.
In the minimization process, unreasonable negative values in the estimated emission intensity q can be avoided by applying positive constraints to the L-BFGS-B algorithm (constrained BFGS algorithm in limited memory, which is a local minimization algorithm proposed by Broyden, Fletcher, Goldfarb, Shanno quadbist).
So far, the position and emission intensity information of the 1 st pollution source are estimated, the simulated concentration generated by the 1 st pollution source and the residual concentration between the observed concentration and the simulated concentration, namely the residual concentration, are quickly calculated by using the obtained source-sink sensitivity matrix
Figure BDA0002609917850000062
Wherein q ise1In order to estimate the emission intensity of the 1 st pollution source when calculating the emission intensity of the pollution source,
Figure BDA0002609917850000063
the residual concentration is used.
Performing second iterative calculation to determine whether there is 2 nd pollution source signal, calculating correlation coefficient and maximum value of N correlation coefficientsUsing the residual concentration
Figure BDA0002609917850000064
Instead of observing the concentration C.
Storing the maximum correlation coefficient R calculated in the second iterationmax，2And the position (x) where it is located2，y2)。
And calculating the determined emission intensity of the 2 nd pollution source, and judging whether all the pollution sources are identified or not after obtaining the emission intensity of the 2 nd pollution source. If the maximum correlation coefficient R obtained in the second iteration calculationmax，2Less than the maximum correlation coefficient R obtained in the first iterationmax，1One-half of, or the estimated pollutant emission intensity qe2And q ise1And if the difference is one order of magnitude, ending the operation, and outputting information such as the number of the pollution sources, the positions of the pollution sources, the emission intensity of the pollution sources and the like, wherein the number of the pollution sources is 1.
If the termination condition is not met, the second pollution source is also important pollution, the number of the pollution sources is added by 1, and meanwhile, the emission intensity of all the identified pollution sources is estimated again through a least square optimization algorithm according to the positions of the newly identified pollution sources.
So far, the position and emission intensity information of 2 pollution sources are estimated, and the simulated concentration generated by the 2 pollution sources and the residual concentration between the observed concentration and the simulated concentration, namely the residual concentration, are quickly calculated by using the obtained source-sink sensitivity matrix
Figure BDA0002609917850000071
Wherein q iseIn order to estimate the emission intensities of 2 pollution sources when calculating the emission intensities of the pollution sources,
Figure BDA0002609917850000072
the residual concentration is used.
Using the obtained residual concentration
Figure BDA0002609917850000073
Then, the nth iteration calculation is carried out to determine whether the nth pollution source existsSignal, i.e. identification of the nth source of pollution is performed.
So far, the positions and the emission intensities of n pollution sources are estimated, the simulated concentrations generated by the n pollution sources are quickly calculated by using the obtained source-sink sensitivity matrix, and the residual concentration between the observed concentration and the simulated concentration is observed, namely
Figure BDA0002609917850000074
Wherein q iseIn order to estimate the emission intensities of the n pollution sources when calculating the emission intensities of the pollution sources,
Figure BDA0002609917850000075
the residual concentration is used.
If the maximum correlation coefficient R is calculated in this iterationmax，nLess than the maximum correlation coefficient R in all previous iterationsmaxOne-half of, or the maximum of, the estimated emission intensity of the pollution source
Figure BDA0002609917850000076
And minimum value
Figure BDA0002609917850000077
And if the difference is one order of magnitude, ending the operation, and outputting the information of the number n of the pollution sources, the position of each pollution source, the emission intensity of the pollution sources and the like.
If the termination condition is not met, which indicates that the important pollution source is still not successfully identified, n is equal to n +1, the calculation is repeated, and the next iteration is continued. In the position estimation of the next iteration, the residual is used
Figure BDA0002609917850000078
Instead of observing the concentration C ° to check whether the residual contains further contamination source signals, the location of the newly identified contamination source is determined if so. In addition, in order to better estimate the pollution source characteristics, when a new pollution source is identified, the emission intensity of all the identified pollution sources is re-estimated through a least square optimization algorithm.
The atmospheric pollutant tracing method solves the problem of multipoint source estimation with less research at present, can estimate the number, the position and the source strength information of pollution sources simultaneously, and has the advantage that the calculation cost cannot be obviously increased along with the increase of the number of point sources due to the use of the source-sink relationship.
The method adopts a backward atmosphere chemical mode to calculate the source-sink relationship, and can greatly improve the calculation efficiency. The method does not need any initial guess information and is very suitable for emergency response of accidents.
It is important to point out that the present invention provides a fast and accurate multi-point source estimation method to deal with sudden air pollution accidents and reduce the harm of the accidents to the ecological environment and the health of people. The method mainly adopts an iterative process to gradually estimate the position and intensity information of each pollution source, in the estimation of each pollution source, a correlation coefficient between simulated concentration and observed concentration generated by releasing pollutants at all potential pollution sources is calculated by using a traversal method and an atmospheric chemical mode, the position of the maximum value of the correlation coefficient is determined as the position of the pollution source, and then the source intensity at the position is estimated by using a least square optimization method. In each iteration, whether the maximum correlation coefficient and the estimated pollution source intensity in the iteration are large enough needs to be judged, if the maximum correlation coefficient and the estimated pollution source intensity in the iteration are smaller than the preset standard, all the main pollution sources are identified at the moment, the loop iteration process can be ended, and the estimated number, position and intensity information of the pollution sources is output.
It should be noted that the iteration ending criterion set in the invention can be adjusted according to the actual situation, so that a decision maker can conveniently make more reasonable emergency measures.
While the preferred embodiments of the present invention have been described in detail, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those skilled in the art.

Claims (10)

1. An atmospheric pollutant tracing method is characterized by comprising the following steps:
1) obtaining a source-sink sensitivity matrix by utilizing an atmospheric chemical mode;
2) calculating a correlation coefficient between the simulated concentration generated by releasing pollutants on each grid point of the atmospheric chemical mode and the observed concentration or the residual concentration through the source sink sensitivity matrix obtained in the step 1), and determining the position of the maximum correlation coefficient as the position of the polluted source;
3) calculating the emission intensity of the pollution source determined in the step 2);
4) judging whether all pollution sources are identified or not by using the correlation coefficient obtained in the step 2) and the emission intensity obtained in the step 3),
if so, outputting the number of the pollution sources, the position of each pollution source and the emission intensity;
if not, repeating the steps 2) -3) until all pollution sources are identified.
2. The atmospheric pollutant tracing method according to claim 1, wherein in step 1), wind field information of weather forecast is input by taking the position of each observation data as a starting point, an atmospheric chemical mode is operated backwards to obtain a source-sink sensitivity matrix H, and each element H in the matrix isijRepresenting the sensitivity of the ith observed concentration data to the pollutant emission flux at the jth mode lattice point.
3. The atmospheric pollutant tracing method according to claim 2, wherein in step 2), the simulated concentration generated by pollutant release at each grid point of the atmospheric chemical model is obtained by multiplying the source-sink sensitivity matrix H obtained in step 1) by the pollutant source-drain matrix H.
4. The atmospheric pollutant tracing method of claim 2, wherein in step 2), the correlation coefficient between the simulated concentration and the observed concentration generated by pollutant release at each grid point is as follows:
Figure FDA0002609917840000011
wherein j is the number of the atmospheric chemical mode grid points, N is the total number of grid points, i is the number of the observed concentration, m is the total number of the observed data,
Figure FDA0002609917840000012
for the i-th observed concentration data, HijFor the elements, q, in the source-sink sensitivity matrix obtained in step 1)sIs a vector containing the emission intensity of the pollution source, HijAnd q issThe product of (a) is the simulated concentration of the contaminant released at the jth grid point corresponding to the ith observation.
5. The atmospheric pollutant tracing method according to claim 4, wherein in step 2), the maximum value of the obtained N correlation coefficients is recorded as Rmax，nAnd the grid point where it is located is determined as the nth pollution source position.
6. The atmospheric pollutant tracing method of claim 5, wherein in step 2), the method further comprises storing the maximum correlation coefficient R in each calculationmax，nAnd its location (x)n，yn) And recording the maximum value of all the calculated maximum correlation coefficients as Rmax，Rmax＝MAX(Rmax，p)，p＝1，2，...，n。
7. The atmospheric pollutant tracing method according to claim 6, wherein in step 3), the emission intensity of all n identified pollution sources is calculated by minimizing a cost function, wherein the cost function is defined as:
Figure FDA0002609917840000021
wherein HeIs an m x n dimensional matrix which represents the source-sink relationship between the emission of n pollution sources and m observed concentrations, q is the emission intensity vector of the n pollution sources to be solved,Cois an observed concentration vector of dimension m × 1.
8. The atmospheric pollutant tracing method of claim 7, wherein the steps between step 3) and step 4) further comprise calculating a residual concentration between the observed concentration and the simulated concentration, the residual concentration being:
Figure FDA0002609917840000022
wherein q iseThe emission intensity of the n pollution sources obtained in the step 3).
9. The atmospheric pollutant tracing method according to claim 8, wherein in step 4), the judgment conditions for judging that all pollution sources are identified are as follows:
if the maximum value R among the N correlation coefficients obtained in the nth calculationmax，nLess than the maximum correlation coefficient R in all previous calculationsmaxOr the maximum value of the calculated emission intensity of the pollution source
Figure FDA0002609917840000023
And minimum value
Figure FDA0002609917840000024
By an order of magnitude.
10. The atmospheric pollutant tracing method according to claim 9, wherein in step 4), when all the pollution sources are not identified and the next calculation is performed, the number n of the pollution sources is set to n +1, and the residual concentration is used to replace the observed concentration when the correlation coefficient is calculated.
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CN112733419B (en) * 2020-11-27 2023-10-31 北京工业大学 Method for improving inversion accuracy of sudden atmospheric pollution accident source
CN113063897A (en) * 2021-03-23 2021-07-02 淄博青禾检测科技有限公司 Air pollutant tracing method and device
CN113063897B (en) * 2021-03-23 2023-05-09 淄博青禾检测科技有限公司 Air pollutant tracing method and device
CN113533445A (en) * 2021-06-17 2021-10-22 北京工业大学 Two-dimensional water pollution tracing method considering parameter uncertainty
CN113533445B (en) * 2021-06-17 2024-04-12 北京工业大学 Two-dimensional water pollution tracing method considering parameter uncertainty

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