CN114757807A - Multi-mode fused online accounting method for actual emission of atmospheric pollutants - Google Patents

Multi-mode fused online accounting method for actual emission of atmospheric pollutants Download PDF

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CN114757807A
CN114757807A CN202210660280.3A CN202210660280A CN114757807A CN 114757807 A CN114757807 A CN 114757807A CN 202210660280 A CN202210660280 A CN 202210660280A CN 114757807 A CN114757807 A CN 114757807A
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王经顺
赵瀚森
陆晓波
徐向凯
栗鹏辉
侯鹏
沈宁航
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Abstract

The invention discloses an online accounting method for actual emission of atmospheric pollutants with multi-mode fusion, which comprises the steps of constructing a multi-mode atmospheric pollution diffusion model to obtain a visual contribution matrix of pollution source intensity and a monitoring station in a current park; constructing a source parameter inversion algorithm, and evaluating the effectiveness of the constructed multi-mode atmospheric pollution diffusion model; and calculating the total amount of the pollutant emission of the park based on the source intensity of the pollution source obtained through optimization estimation. The invention integrates the advantages of multiple models through the fusion of the multiple models and the dynamic distribution of the model weight, and improves the accuracy, universality and stability of the set model.

Description

Multi-mode fused online accounting method for actual emission of atmospheric pollutants
Technical Field
The invention relates to the technical field of environmental monitoring and environmental protection, in particular to an online accounting method for actual emission of atmospheric pollutants with multi-mode fusion.
Background
The industrial park is a centralized place of industrial production, plays a vital role in the development of local economy and is also a large household for pollutant emission.
In the ecological civilization construction process, the key point for stably improving the local air environment level is to control the emission intensity and the total amount of atmospheric pollutants in an industrial park.
Accurate accounting of pollutant emission amount of an industrial park is the basis for formulating reasonable emission indexes and scientifically formulating emission reduction plans for the park.
At present, although online monitoring instruments are installed on most organized sewage outlets of key enterprises in an industrial park, the discharge forms such as organized discharge and the like are still difficult to monitor through an online monitoring means.
In view of the above, it is urgently needed to design and develop a set of scientific method and accounting system for calculating the total amount of the discharged air of the park through the local air quality change monitoring data of the park.
Disclosure of Invention
The invention aims to provide a multimode-fused online accounting method for actual emission of atmospheric pollutants, which is characterized in that a mode of calculating contribution scores of pollution sources to monitoring sites by acquiring comprehensive meteorological data information, park pollution sources, monitoring sites and topographic building information of a park and a mode of calculating emission intensity of the pollution sources and total emission of a nucleic acid park in a certain time are realized, so that a mode of directly calculating the total emission of the park through local air quality change monitoring data of the park is realized, and the problems in the prior art are solved. In order to achieve the purpose, the invention provides the following technical scheme:
the online accounting method for the actual emission of the atmospheric pollutants with multi-mode fusion comprises the following steps:
Rolling simulation is carried out to obtain meteorological environment data in a garden area; constructing a simulation grid comprising park information, wherein the park information comprises park monitoring station basic information, park pollution source basic information and park elevation information;
constructing a multi-mode atmospheric pollution diffusion model, simulating and acquiring the concentration distribution relation between the garden pollution source intensity and the position of a garden monitoring station under the diffusion and atmosphere transmission effects according to meteorological environment data and real-time data of the garden monitoring station, and obtaining a contribution matrix of the pollution source intensity in the current garden to the monitoring station so as to obtain the influence of pollution source emission on the monitoring station;
constructing a source parameter inversion algorithm, and carrying out optimization estimation on the pollution source intensity according to the acquired park monitoring station data and the simulation result output by the multi-mode atmospheric pollution diffusion model so as to carry out effectiveness evaluation on the constructed multi-mode atmospheric pollution diffusion model;
and calculating the total amount of the pollutant emission of the park based on the source intensity of the pollution source obtained through optimization estimation.
As an improvement of the multi-mode fused online accounting method for the actual emission of the atmospheric pollutants, the meteorological environment data in the park area are acquired and comprise meteorological field data which can be directly extracted from a simulation result and meteorological field data which cannot be directly calculated; the simulation grids include a weather simulation grid and a campus simulation grid, wherein,
Before acquiring the data of the meteorological environment of the campus, the position index of the campus position in the meteorological simulation grid needs to be calculated firstly:
Figure 425178DEST_PATH_IMAGE001
Figure 348135DEST_PATH_IMAGE002
in the formula, i represents a grid corresponding to a pollution source in the meteorological simulation gridIndexing; j represents a grid index corresponding to a monitoring station in the meteorological simulation grid; x and y are respectively expressed as longitude and latitude information of the park or UTM coordinates x and y;
Figure 657893DEST_PATH_IMAGE003
and
Figure 728617DEST_PATH_IMAGE004
respectively representing longitude and latitude or UTM coordinates of a starting point of the meteorological simulation grid;
Figure 719707DEST_PATH_IMAGE005
represents rounding down; d is expressed as the grid resolution.
As an improvement of the multi-mode integrated online accounting method for the actual emission of the atmospheric pollutants, before simulating the concentration distribution relationship between the source intensity of the pollution source of the park and the position of the park monitoring station, the acquired data of the park monitoring station needs to be subjected to unit conversion, and the validity of the acquired data of the park monitoring station is verified, and the method specifically comprises the following steps:
Figure 559487DEST_PATH_IMAGE006
Figure 977830DEST_PATH_IMAGE007
Figure 270271DEST_PATH_IMAGE008
in the formula (I), the compound is shown in the specification,
Figure 127369DEST_PATH_IMAGE009
and
Figure 257874DEST_PATH_IMAGE010
respectively representing the monitoring concentration after unit conversion and before conversion, and MIN _ NSITE and MIN _ RSITE are used for setting the minimum number and minimum number of effective monitoring sites for the configuration fileEffectively monitoring the site proportion, wherein Vflag represents whether the site is effective or not;
Figure 909435DEST_PATH_IMAGE011
is a conversion factor;
Figure 892434DEST_PATH_IMAGE011
the calculation formula of (2) is as follows:
Figure 287644DEST_PATH_IMAGE012
Wherein P is a standard atmospheric pressure (Pa); r is an ideal gas constant with the unit of J/mol.K; t is the ambient temperature (K); wmRelative molecular mass (g/mol);
Figure 836437DEST_PATH_IMAGE013
the conversion ratio of the final mass unit and the gram after conversion;
Figure 862162DEST_PATH_IMAGE014
unit proportion before conversion; e.g. from ppm to mg/m3When the temperature of the water is higher than the set temperature,
Figure 129195DEST_PATH_IMAGE013
value of 103，
Figure 328095DEST_PATH_IMAGE014
Value of 106；
Figure 669078DEST_PATH_IMAGE015
Identifying the data validity of the ith monitoring station; and N is the total number of the monitored stations.
As an improvement of the multi-mode integrated online accounting method for the actual emission of the atmospheric pollutants, the specific method for constructing the park simulation grid is as follows:
Figure 928021DEST_PATH_IMAGE016
Figure 118568DEST_PATH_IMAGE017
in the formula, nx is the number of grids of the park simulation grid in the x direction,
Figure 855580DEST_PATH_IMAGE018
and
Figure 378965DEST_PATH_IMAGE019
maximum and minimum UTM-X coordinates of a pollution source and a monitoring point of the park respectively; offset is the amount of expansion of the grid, usually equal to the grid resolution;
Figure 746493DEST_PATH_IMAGE020
representing the UTM area in which the longitude and latitude information is located; lng denotes longitude.
As an improvement of the multi-mode fused online accounting method for the actual emission of the atmospheric pollutants, the specific method for constructing the multi-mode atmospheric pollution diffusion model comprises the following steps:
s1, customizing a linear superposition hypothesis that the data of a single monitoring station of the garden are strong relative to pollution sources in a plurality of gardens to reduce the calculation difficulty:
Figure 722539DEST_PATH_IMAGE021
In the formula (I), the compound is shown in the specification,
Figure 263242DEST_PATH_IMAGE022
as a result of monitoring site j, b is background concentration,
Figure 844396DEST_PATH_IMAGE023
in order to be the emission intensity of the pollution source i,
Figure 179562DEST_PATH_IMAGE024
representing the contribution of the pollution source i to the monitored site j;
and S11, establishing the data of the N monitoring stations of the garden and an M x N x K three-dimensional contribution matrix of the M pollution sources based on a linear superposition hypothesis, wherein K represents the number of the multi-mode atmospheric pollution diffusion models participating in calculation so as to reduce the repeated calling of the multi-mode atmospheric pollution diffusion models in the optimization process, for example, for a Sutton model:
Figure 846167DEST_PATH_IMAGE025
wherein u is the average wind speed; z and h are the height of the receptor site and the height of the source respectively;
Figure 924981DEST_PATH_IMAGE026
and
Figure 422959DEST_PATH_IMAGE027
the diffusion coefficient is related to meteorological conditions, and the relative size of contribution degrees is shown by the change of brightness of the M, N and K three-dimensional contribution matrix.
As an improvement of the multi-mode fused online accounting method for the actual emission of the atmospheric pollutants, the method for optimally estimating the source intensity of the pollution source based on the source parameter inversion algorithm comprises the following steps:
s2, estimating the environmental background concentration of the park according to the pollution source intensity and the distribution condition of the monitoring stations and by combining the current wind field data, wherein the specific estimation steps are as follows:
vector pointing to any pollution source i from monitoring site j
Figure 365245DEST_PATH_IMAGE028
Unit vector with real-time wind direction
Figure 581462DEST_PATH_IMAGE029
Performing dot product calculation to obtain vector
Figure 401651DEST_PATH_IMAGE028
In that
Figure 754135DEST_PATH_IMAGE029
Projection in the direction;
when the concentration of the contaminant in the sample is low for any contamination source i, if,
Figure 696683DEST_PATH_IMAGE030
if the monitoring station is a windward station, the monitoring station is considered as an upwind station;
when a plurality of upwind direction sites appear, averaging corresponding monitoring data to be used as the environmental background concentration of the park;
s21, calculating the pseudo inverse of the contribution matrix, obtaining an initial guess of the source intensity of the pollution source, performing distribution optimization on the source intensity of the pollution source to obtain a reliable initial guess, and then performing optimization on the source intensity distribution of the pollution source, wherein the specific calculation mode is as follows:
Figure 72301DEST_PATH_IMAGE031
in the formula (I), the compound is shown in the specification,
Figure 492918DEST_PATH_IMAGE032
is a 1 x M row vector of the image,
Figure 965487DEST_PATH_IMAGE033
is a row vector of 1 x N,
Figure 751041DEST_PATH_IMAGE034
is that
Figure 676271DEST_PATH_IMAGE035
Pseudo-inverse of the matrix;
Figure 172735DEST_PATH_IMAGE036
is an initial guess of the source strength of the pollution source;
s22, calculating the average relative deviation between the pollution source intensity and the measured value, taking the average relative deviation as the accuracy measurement of the multi-mode atmospheric pollution diffusion model calculation, dynamically generating the weight of the integration of the multi-mode atmospheric pollution diffusion model to avoid the subjective interference caused by artificially setting the integration weight of the multi-mode atmospheric pollution diffusion model, and the specific calculation mode is as follows:
Figure 499811DEST_PATH_IMAGE037
Figure 784162DEST_PATH_IMAGE038
in the formula (I), the compound is shown in the specification,
Figure 134372DEST_PATH_IMAGE039
is the average relative deviation of the multi-mode atmospheric pollution diffusion model K,
Figure 896792DEST_PATH_IMAGE040
is a configurable constant.
As an improvement of the online accounting method for the actual emission of the atmospheric pollutants fused in multiple modes, the specific steps for calculating the total emission of the pollution in the park are as follows:
S3, marking the attribute of the pollution source to eliminate the influence of the pollution source outside the park:
Figure 16057DEST_PATH_IMAGE041
Figure 471310DEST_PATH_IMAGE042
in the formula, Q represents the total amount of the pollutant source emission outside the garden.
As an improvement of the online accounting method for the actual emission of the atmospheric pollutants fused in multiple modes, when the total emission of pollutants in a park is calculated, the maximum total emission Q _ MAX and the maximum relative deviation RME _ MAX are set through a configuration file to carry out validity verification on an accounting result of a multiple-mode atmospheric pollution diffusion model:
Figure 308816DEST_PATH_IMAGE043
Figure 874926DEST_PATH_IMAGE044
when the fitting result of the multi-mode atmospheric pollution diffusion model is consistent with the park monitoring data, the simulation accounting of the multi-mode atmospheric pollution diffusion model is proved to be effective.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the method, the advantages of multiple models are integrated through fusion of the multiple models and dynamic distribution of model weights, and the accuracy, universality and stability of the set model are improved;
2. by adding the linear superposition assumption and the algorithm design of the contribution matrix, the calling of an atmospheric pollution diffusion model with large calculation amount is reduced, the optimization process is simplified, and the timeliness of the algorithm is improved;
3. according to the invention, through setting the virtual source which does not participate in statistics, the influence of factors such as irregular range of the park, pollution sources outside the park boundary and the like on the accounting is reduced.
Drawings
FIG. 1 is a flow chart of a multi-mode fusion accounting framework according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a campus information configuration interface according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a plot simulated pollutant diffusion contour map (left) and a contribution matrix (right) according to an embodiment of the present invention;
fig. 4 is a graph showing the relative magnitude of the emission intensity of the pollution source obtained by the simulation of the park according to an embodiment of the present invention (upper) and the comparison of the simulation result with the monitored value (lower).
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments, and all other embodiments obtained by a person skilled in the art without making creative efforts based on the embodiments of the present invention belong to the protection scope of the present invention.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like, are used in the orientations and positional relationships indicated in the drawings, which are based on the orientations and positional relationships indicated in the drawings, and are used for convenience of description and simplicity of description, but do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
The present invention will be described in further detail below with reference to the accompanying drawings, but the present invention is not limited thereto.
Referring to fig. 1-4, as an embodiment of the present invention, the method for on-line accounting actual emission of atmospheric pollutants with multi-mode fusion includes a weather simulation module, a park information configuration module, a base station data collection module, a multi-mode atmospheric pollution diffusion model module, a source parameter inversion algorithm module, and a total accounting module, it should be noted that,
the meteorological simulation module is used for rolling and simulating and calculating the atmospheric physical environment characteristics of the campus area according to the initial field data of the campus; the park information configuration module is used for converting longitude and latitude coordinates of a park pollution source and a monitoring station into local coordinates, processing the terrain of the park, and dividing to form simulation grids of the park, wherein the simulation grids comprise a meteorological simulation grid and a park simulation grid; a base station data aggregation module: collecting and verifying the effectiveness of the monitoring data of the monitoring station; the multi-mode atmospheric pollution diffusion model module is used for constructing a multi-mode atmospheric pollution diffusion model to simulate the influence of pollution source emission on a monitoring station; the source parameter inversion algorithm module is used for optimizing and estimating to obtain the source intensity information of the pollution source of the industrial park by combining monitoring data of the monitoring station and a simulation result of the multi-mode atmospheric pollution diffusion model module; a total amount accounting module: and calculating the total amount of pollution emission in the garden area in the time period based on the pollution source intensity obtained through optimization estimation.
The method comprises the following steps:
firstly, on the basis of a meteorological simulation module, responding to an API request and returning meteorological environment data of any park place in a simulation range to establish a meteorological simulation grid, wherein the acquired meteorological environment data comprise meteorological field data which can be directly extracted from a simulation result, such as temperature, air pressure, wind direction, wind speed and the like; and data which needs to be further calculated and obtained, such as sunshine intensity, rainfall amount per unit time and the like, wherein the sunshine intensity netRad and the accumulated rainfall raining amount rainCum are calculated in the following way:
Figure 911015DEST_PATH_IMAGE045
Figure 973387DEST_PATH_IMAGE046
in the formula, SW and LW respectively represent short wave and long wave radiation, RAINC and RAINSH respectively represent accumulative clouding precipitation, accumulative grid precipitation and accumulative shallow clouding precipitation, and it needs to be explained that a meteorological simulation module can adopt a WRF mode to simulate campus meteorology, especially high altitude meteorology, and when the module is specifically implemented, the module can be independently arranged in a high-performance Linux server, the calculation efficiency is improved through parallel calculation, and the whole-day meteorological simulation of the same day is completed in a plurality of hours in the early morning to support the operation of a total calculation model;
when a user acquires meteorological environment data based on a meteorological simulation module, a form is made according to specifications, a park information configuration module reads in the form, a local coordinate system is automatically established, longitude and latitude information (the longitude and latitude information of a pollution source and the longitude and latitude information of a monitoring station) is converted into local coordinates, a simulation grid is generated according to grid resolution input by the user, visually displaying on a map, exporting the json file configured in the park by one key when in actual use, copying the json file configured in the park to a formulated directory of an accounting system by a user, and modifying the configuration file of the accounting system, after the park name, the ID and the configuration file name are indicated, the park information can be configured and added into a real-time accounting system, and can be understood to comprise park monitoring station basic information, park pollution source basic information and park elevation information; the basic information of the park monitoring station comprises longitude and latitude and height of the monitoring station, data of the park monitoring station is an atmospheric pollutant concentration value obtained through a monitoring instrument of the monitoring station, and the basic information of the park pollution source comprises data of the position, height, discharge port temperature and the like of the pollution source; the elevation information of the park refers to the elevation information of each position of the park.
In an embodiment of the present invention, it should be noted that, when the weather simulation module responds to the API request and returns the weather environment data of any campus location in the simulation range, when the weather simulation module constructs the simulation grid, the longitude and latitude information (the longitude and latitude information of the pollution source and the longitude and latitude information of the monitoring station) in the API needs to be converted into the UTM coordinate
Figure 360506DEST_PATH_IMAGE047
Then, calculating the grid index in the meteorological simulation grid corresponding to the campus information (campus position):
Figure 402411DEST_PATH_IMAGE001
Figure 558586DEST_PATH_IMAGE002
in the formula, i represents a grid index corresponding to a pollution source in a meteorological simulation grid; j represents a grid index corresponding to a monitoring station in the meteorological simulation grid; x and y are respectively expressed as longitude and latitude information of the park or UTM coordinates x and y;
Figure 355641DEST_PATH_IMAGE003
and
Figure 902160DEST_PATH_IMAGE004
respectively representing longitude and latitude or UTM coordinates of a starting point of the meteorological simulation grid;
Figure 75652DEST_PATH_IMAGE005
represents rounding down; d is the grid resolution, it can be understood that the value "0.5" in the above formula is the offset of the UTM coordinates x, yThe displacement is used for accurately calculating; it can be understood that the method can decouple the meteorological simulation data with large calculation amount and long time consumption from the total accounting data with small calculation amount and high real-time requirement on software and hardware deployment, and the mode of carrying out meteorological simulation calculation by using the high-performance server in the period from sub-night to early morning makes the required total accounting part directly obtain the required meteorological data from the high-performance server through the API, thereby reducing the calculation amount.
Meanwhile, after acquiring the grid index in the meteorological simulation grid corresponding to the campus information (campus position), the campus information configuration module automatically generates the campus simulation grid according to the position of the campus pollution source and the position of the monitoring station and synchronously acquires the geographical elevation information:
Figure 86333DEST_PATH_IMAGE016
Figure 991973DEST_PATH_IMAGE017
Figure 88105DEST_PATH_IMAGE048
Figure 534129DEST_PATH_IMAGE049
in the formula, nx is the number of grids of the garden simulation grid in the x direction,
Figure 101115DEST_PATH_IMAGE018
and
Figure 239972DEST_PATH_IMAGE019
maximum and minimum UTM-X coordinates of a pollution source and a monitoring point of the park respectively; offset is the amount of expansion of the grid, usually equal to the grid resolution;
Figure 761083DEST_PATH_IMAGE020
representing the UTM area in which the longitude and latitude information is located; r and c are indexes for searching the geographical elevation file of the park; long and lat respectively represent longitude and latitude, and it can be understood that the value "31" in the above formula is an offset to be added when longitude zone partition is calculated through east longitude in UTM projection; constants such as 36, 60 and the like are offset when the SRTM elevation data file is indexed through longitude and latitude; and 5, dividing the range for the longitude and latitude of the elevation file. It can be understood that the automation level of the park configuration process can be improved through the method, and in practical application, a user only needs to collect routine data such as park range, pollution sources, monitoring site longitude and latitude and the like, and can automatically convert the data into professional parameters of models such as calculation grid information, elevation information and the like through an accounting system.
The second step, for the simulation result deviation that factors such as effectual reduction garden monitoring facilities off-line lead to, the stability of reinforcing accounting system, consequently, still need carry out the unit conversion through garden information configuration module to the garden monitoring station data of acquireing to carry out validity verification to the garden monitoring station data of acquireing, its concrete processing mode is:
Figure 10799DEST_PATH_IMAGE006
Figure 996072DEST_PATH_IMAGE007
Figure 243514DEST_PATH_IMAGE008
in the formula (I), the compound is shown in the specification,
Figure 314238DEST_PATH_IMAGE009
and
Figure 367645DEST_PATH_IMAGE010
representing the monitored concentration after unit conversion and before conversion, respectively, and MIN _ NSITE and MIN _ RSITE are configuredThe number of the minimum effective monitoring sites and the proportion of the minimum effective monitoring sites are set by the file, and the Vflag indicates whether the minimum effective monitoring sites are effective or not;
Figure 145108DEST_PATH_IMAGE011
is a conversion factor; it should be noted that, in the following description,
Figure 625768DEST_PATH_IMAGE011
the calculation formula of (2) is as follows:
Figure 918209DEST_PATH_IMAGE012
wherein P is a standard atmospheric pressure (Pa); r is an ideal gas constant; t is the ambient temperature (K); wmRelative molecular mass (g/mol);
Figure 211525DEST_PATH_IMAGE013
the conversion ratio of the final mass unit and the gram after conversion;
Figure 905811DEST_PATH_IMAGE014
unit proportion before conversion; e.g. from ppm to mg/m3When the temperature of the water is higher than the set temperature,
Figure 557373DEST_PATH_IMAGE013
value of 103，
Figure 540372DEST_PATH_IMAGE014
Value of 106；
Figure 935581DEST_PATH_IMAGE015
Identifying the data validity of the ith monitoring station; and N is the total number of the monitored stations.
Thirdly, constructing a multi-mode atmospheric pollution diffusion model, wherein topographic and meteorological factors need to be considered when constructing the multi-mode atmospheric pollution diffusion model, the concentration distribution relationship between the source intensity of the park pollution source and the position of the park monitoring station under the diffusion and atmospheric transmission actions needs to be simulated and obtained according to meteorological environment data and real-time data of the park monitoring station, for any monitoring station in the simulation range, the contribution degree of the pollution source intensity and the local concentration of the position of the monitoring station can be calculated according to the relationship between the pollution source intensity and the local concentration of the position of the monitoring station set by the multi-mode atmospheric pollution diffusion model, and then forming a contribution matrix by the contribution degree relation of a plurality of pollution sources and a plurality of monitoring stations, (namely obtaining the contribution matrix of the pollution source intensity and the monitoring stations in the current park) in order to obtain the influence of the pollution source emission on the monitoring stations, so that the specific steps of constructing the multi-mode atmospheric pollution diffusion model are as follows:
Firstly (S1), in order to solve the problem that the superposition influence of multiple sources in the campus on the monitoring site is converted into the solution of the multivariate linear equation set, on the premise of definitely optimizing the target and reducing the calculation difficulty, it is necessary to define the linear superposition assumption that the data of a single monitoring station in the campus is strong relative to the pollution sources in multiple campuses, so as to reduce the calculation difficulty proposed in the above problem:
Figure 484374DEST_PATH_IMAGE021
in the formula (I), the compound is shown in the specification,
Figure 510099DEST_PATH_IMAGE022
as a result of monitoring site j, b is background concentration,
Figure 777133DEST_PATH_IMAGE023
in order to be the emission intensity of the pollution source i,
Figure 648137DEST_PATH_IMAGE024
the method is represented as the contribution of a pollution source i to a monitoring station j, and can be understood that the calling of an atmospheric pollution diffusion model with large calculation amount is reduced, the optimization process is simplified, and the timeliness of the algorithm is improved through the algorithm design of a linear superposition hypothesis and a contribution matrix;
and secondly (S11), establishing N monitoring station data of the garden and M N K three-dimensional contribution matrixes of M pollution sources based on the linear superposition assumption proposed in the step S1, wherein K is the number of the multi-mode atmospheric pollution diffusion models participating in calculation so as to reduce repeated calling of the multi-mode atmospheric pollution diffusion models in the optimization process.
It should be noted that, in an embodiment of the present invention, the present invention preferably takes a Sutton model as an example, that is,
Figure 317015DEST_PATH_IMAGE024
The calculation is as follows:
Figure 575958DEST_PATH_IMAGE025
wherein u is the average wind speed; z and h are the height of the receptor site and the height of the source respectively;
Figure 500927DEST_PATH_IMAGE026
and
Figure 503518DEST_PATH_IMAGE027
the diffusion coefficients are related to meteorological conditions, and the relative sizes of the light and shade change display contribution degrees of the M, N, K three-dimensional contribution matrixes are different, so that the repeated calling of the multi-mode atmospheric pollution diffusion model in the optimization process is reduced, and the algorithm efficiency is improved;
in order to solve the existing problems that the multi-mode atmospheric pollution diffusion model is called repeatedly in the optimization process and the algorithm efficiency is improved, besides the Sutton model, the method can also adopt AERMOD, CALPUFF, Gaussian models and the like, and the reason that the optimized Sutton model is directly calculated through a group of data to obtain the contribution of the pollution source i to the monitoring station j is understood to improve the algorithm efficiency.
Fourthly, constructing a source parameter inversion algorithm, and carrying out optimization estimation on the pollution source intensity according to the acquired data of the park monitoring station and the simulation result output by the multi-mode atmospheric pollution diffusion model so as to evaluate the effectiveness of the constructed multi-mode atmospheric pollution diffusion model,
the method for carrying out optimization estimation on the source intensity of the pollution source based on the source parameter inversion algorithm comprises the following steps:
S2, estimating the environmental background concentration of the park according to the initial guess of the pollution source intensity, the distribution situation of the pollution source intensity and the monitoring station and the combination of the current wind field data, wherein the specific estimation steps are as follows:
firstly, starting from a monitoring site j, a vector pointing to any pollution source i
Figure 26903DEST_PATH_IMAGE028
Unit vector with real-time wind direction
Figure 128851DEST_PATH_IMAGE029
Performing dot product calculation to obtain vector
Figure 370477DEST_PATH_IMAGE028
In that
Figure 911180DEST_PATH_IMAGE029
Projection in the direction;
second, when for any contamination source i, if,
Figure 226754DEST_PATH_IMAGE030
if the monitoring station is a windward station, the monitoring station is considered as an upwind station;
finally, when a plurality of upwind sites appear, averaging corresponding monitoring data to be used as the environmental background concentration of the park, and it can be understood that by the method, an accounting system can rapidly identify the upwind sites according to the real-time main wind direction through mathematical operation so as to dynamically acquire the background concentration;
s21, calculating a pseudo-inverse of a contribution matrix (M x N x K three-dimensional contribution matrix), after obtaining an initial guess of the source intensity of the pollution source, performing distribution optimization on the source intensity of the pollution source to obtain a reliable initial guess, and then performing optimization on the source intensity distribution of the pollution source, wherein the specific calculation mode is as follows:
Figure 827500DEST_PATH_IMAGE031
in the formula (I), the compound is shown in the specification,
Figure 228525DEST_PATH_IMAGE032
is a row vector of 1 x M,
Figure 572919DEST_PATH_IMAGE033
is a row vector of 1 x N,
Figure 70897DEST_PATH_IMAGE034
is that
Figure 13183DEST_PATH_IMAGE035
Pseudo-inverse of the matrix;
Figure 229400DEST_PATH_IMAGE036
The initial guess of the pollution source strength is adopted, and it can be understood that through the method, a more reliable initial guess can be obtained, the time required by optimization is reduced, and the situation that the optimization effect is poor due to the fact that the optimization falls into a local optimal solution is reduced;
s22, calculating the average relative deviation between the pollution source intensity and the measured value, taking the average relative deviation as the accuracy measurement of the multi-mode atmospheric pollution diffusion model calculation, dynamically generating the weight of the integration of the multi-mode atmospheric pollution diffusion model, avoiding the subjective interference caused by artificially setting the integration weight of the multi-mode atmospheric pollution diffusion model, and fully utilizing the characteristics of different models in different conditions, wherein the specific calculation mode is as follows:
Figure 111906DEST_PATH_IMAGE037
Figure 402073DEST_PATH_IMAGE038
in the formula (I), the compound is shown in the specification,
Figure 79042DEST_PATH_IMAGE039
is the average relative deviation of the multimode atmospheric pollution diffusion model K,
Figure 516976DEST_PATH_IMAGE040
the set model is a configurable constant, and can be understood that the advantages of multiple models are integrated through fusion of the multiple models and dynamic distribution of model weights, so that the accuracy, universality and stability of the set model are improved;
fifthly, calculating the total pollutant discharge amount of the park based on the pollutant source intensity obtained through optimization estimation, wherein the influence of the pollutant source outside the park is required to be eliminated by marking the pollutant source attribute when the total pollutant discharge amount of the park is estimated due to the problems of irregular park boundary, influence of the pollutant sources outside the park, such as enterprises outside the park, living quarters and the like,
S3, the specific estimation steps are:
Figure 140856DEST_PATH_IMAGE041
Figure 347846DEST_PATH_IMAGE042
in the formula, Q represents the total discharge amount of pollution sources outside the garden;
based on the above technical concept, it should be noted that, when the total amount of the pollutant emissions of the park is calculated, the maximum total amount of the pollutant emissions Q _ MAX and the maximum relative deviation RME _ MAX are set through the configuration file to perform validity verification on the calculation result of the multi-mode atmospheric pollution diffusion model:
Figure 461295DEST_PATH_IMAGE043
Figure 324209DEST_PATH_IMAGE044
it can be understood that, because the pollution source is usually associated with an enterprise district, the relative magnitude estimation of the emission intensity in different areas of the garden can also be indirectly obtained, and the evaluation of the model on the interpretability of the monitoring data can be obtained through the consistency analysis of the simulation result and the monitoring result, that is, when the fitting result of the model is more consistent with the monitoring data of the garden, the simulation core of the model is proved to be effective, and when the simulation of the model is proved to be effective, it can be understood that the model simulation result is not determined to be effective if the model simulation result is consistent with the monitoring data, but the model is effective if the model simulation result is consistent with the monitoring data, and meanwhile, the model result is unlikely to be completely consistent with the actual monitoring result.
In the actual calculation, the result of the total discharge amount of the park is the product of the intensity of the pollution source and the discharge time, and the interference of the park external source needs to be considered and eliminated, so that the influence of the factors such as irregular park range, the pollution source outside the park boundary and the like on the calculation is reduced by setting the virtual source which does not participate in the statistics.
As an embodiment of the present invention, it should be noted that, in the above technical solution provided by the present invention, except that the park information configuration module in the first step requires a user to perform a survey and check according to the actual situation of the park to obtain accurate information to generate the configuration file, the steps processed by other modules are automatically performed by the accounting system through a timing task, so as to implement hourly accounting and statistics of the actual emission total amount of the atmospheric pollutants in the park.
As an embodiment of the present invention, as shown in fig. 2, a schematic diagram of basic information configuration of an industrial park is shown, where a dot represents a position of a pollution source of the park, an inverted triangle represents a position of a monitoring site, a white dotted line frame represents a boundary of a park simulation grid, and the park grid should cover all the pollution sources and the monitoring sites; at the same time, the user can select the required time,
as shown in fig. 3, a contour diagram (left) of the result of the campus atmospheric pollution diffusion simulation is shown, and it is understood that the horizontal and vertical coordinates in fig. 3 are X and Y coordinates of the UTM coordinate system; a pollution concentration contribution matrix (right) of a pollution source to the monitored site is displayed, and the contribution degree is in the form of thermodynamic diagrams;
as shown in fig. 4, a plot of the emissions of pollution from a campus is plotted (up), wherein the ordinate is the distance of the pollution source from the geographic center of the campus in the east-west and north-south directions, and the size of the plot indicates the relative magnitude of the emission intensity, and the four largest emissions sources at the current time are plotted; the plot (bottom) of figure 4 is a plot of simulated versus actual concentration of atmospheric pollutants for a campus.
While there have been shown and described what are at present considered to be the basic principles and essential features of the invention and advantages thereof, it will be apparent to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, but is capable of other embodiments without departing from the spirit or essential characteristics thereof; the present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein, and any reference signs in the claims are not to be construed as limiting the claims.
Furthermore, it should be understood that although the present specification describes embodiments, not every embodiment includes only a single embodiment, and such description is for clarity purposes only, and it is to be understood that all embodiments may be combined as appropriate by one of ordinary skill in the art to form other embodiments as will be apparent to those of skill in the art from the description herein.

Claims (8)

1. The online accounting method for the actual emission of the atmospheric pollutants with multi-mode fusion is characterized by comprising the following steps of:
rolling simulation is carried out to obtain meteorological environment data in a garden area; constructing a simulation grid comprising park information, wherein the park information comprises park monitoring station basic information, park pollution source basic information and park elevation information;
constructing a multi-mode atmospheric pollution diffusion model, simulating and acquiring the concentration distribution relation between the garden pollution source intensity and the position of a garden monitoring station under the diffusion and atmosphere transmission effects according to meteorological environment data and real-time data of the garden monitoring station, and obtaining a contribution matrix of the pollution source intensity in the current garden to the monitoring station so as to obtain the influence of pollution source emission on the monitoring station;
constructing a source parameter inversion algorithm, and carrying out optimization estimation on the pollution source intensity according to the acquired park monitoring station data and the simulation result output by the multi-mode atmospheric pollution diffusion model so as to carry out effectiveness evaluation on the constructed multi-mode atmospheric pollution diffusion model;
and calculating the total amount of the pollutant emission of the park based on the source intensity of the pollution source obtained through optimization estimation.
2. The multi-mode fused online accounting method for the actual emission of atmospheric pollutants as claimed in claim 1, wherein the meteorological environment data comprises directly calculable meteorological field data and indirectly calculable meteorological field data; the simulation grids comprise a meteorological simulation grid and a campus simulation grid,
Wherein, before extracting the campus meteorological environment data, need calculate the position index of campus position in meteorological simulation grid earlier:
Figure 552354DEST_PATH_IMAGE001
Figure 536491DEST_PATH_IMAGE002
in the formula, i is expressed as a grid index corresponding to a pollution source in the meteorological simulation grid; j represents a grid index corresponding to a monitoring station in the meteorological simulation grid; x and y are respectively expressed as longitude and latitude information or UTM coordinates of the park;
Figure 115240DEST_PATH_IMAGE003
and
Figure 893840DEST_PATH_IMAGE004
respectively representing longitude and latitude or UTM coordinates of a starting point of the meteorological simulation grid; d is the grid resolution;
Figure 315898DEST_PATH_IMAGE005
indicating a rounding down.
3. The multi-mode fused online accounting method for the actual emission of the atmospheric pollutants according to claim 1, wherein before simulating the concentration distribution relationship between the pollution source intensity of the park and the location of the park monitoring station, the unit transformation of the acquired data of the park monitoring station is required, and the validity of the acquired data of the park monitoring station is verified, and the method specifically comprises the following steps:
Figure 103725DEST_PATH_IMAGE006
Figure 536981DEST_PATH_IMAGE007
Figure 486482DEST_PATH_IMAGE008
in the formula (I), the compound is shown in the specification,
Figure 372398DEST_PATH_IMAGE009
and
Figure 698338DEST_PATH_IMAGE010
respectively representing the monitoring concentration after unit conversion and before unit conversion, wherein MIN _ NSITE and MIN _ RSITE are the minimum effective monitoring site number and the minimum effective monitoring site proportion set for the configuration file, and Vflag represents whether the monitoring concentration is effective or not;
Figure 986099DEST_PATH_IMAGE011
is a conversion factor;
Figure 106502DEST_PATH_IMAGE011
The calculation formula of (c) is:
Figure 745294DEST_PATH_IMAGE012
wherein, P is standard atmospheric pressure (Pa); r is an ideal gas constant with the unit of J/mol.K; t is the ambient temperature (K); w is a group ofmRelative molecular mass (g/mol);
Figure 609345DEST_PATH_IMAGE013
the conversion ratio of the final converted mass unit to the gram;
Figure 751613DEST_PATH_IMAGE014
unit proportion before conversion; e.g. from ppm to mg/m3When the utility model is used, the water is discharged,
Figure 308496DEST_PATH_IMAGE013
value of 103，
Figure 309950DEST_PATH_IMAGE014
Value of 106；
Figure 102326DEST_PATH_IMAGE015
Identifying the data validity of the ith monitoring station; and N is the total number of the monitored stations.
4. The multimode-fused online accounting method for the actual emission of the atmospheric pollutants according to claim 1 or 2, wherein the park simulation grid is constructed by the following specific method:
Figure 974467DEST_PATH_IMAGE016
Figure 826885DEST_PATH_IMAGE017
in the formula, nx is the number of grids of the park simulation grid in the x direction,
Figure 315636DEST_PATH_IMAGE018
and
Figure 646123DEST_PATH_IMAGE019
maximum and minimum UTM-X coordinates of a pollution source and a monitoring point of the park respectively; offset is the amount of expansion of the grid, usually equal to the grid resolution;
Figure 638349DEST_PATH_IMAGE020
representing the UTM area in which the longitude and latitude information is located; lng denotes longitude.
5. The multi-mode fused online accounting method for the actual emission of the atmospheric pollutants as claimed in claim 1, wherein the specific way of constructing the multi-mode atmospheric pollution diffusion model is as follows:
s1, customizing a linear superposition hypothesis that the data of a single monitoring station of the garden are strong relative to pollution sources in a plurality of gardens to reduce the calculation difficulty:
Figure 661669DEST_PATH_IMAGE021
In the formula (I), the compound is shown in the specification,
Figure 106557DEST_PATH_IMAGE022
as a result of monitoring site j, b is background concentration,
Figure 381680DEST_PATH_IMAGE023
in order to be the emission intensity of the pollution source i,
Figure 618627DEST_PATH_IMAGE024
representing the contribution of the pollution source i to the monitored site j;
s11, establishing data of N monitoring stations of the park and an M x N x K three-dimensional contribution matrix of M pollution sources based on a linear superposition hypothesis, wherein K is expressed as the number of the multi-mode atmospheric pollution diffusion models participating in calculation so as to reduce the repeated calling of the multi-mode atmospheric pollution diffusion models in the optimization process:
Figure 422635DEST_PATH_IMAGE025
wherein u is the average wind speed; z and h are the height of the receptor site and the height of the source respectively;
Figure 745032DEST_PATH_IMAGE026
and
Figure 292688DEST_PATH_IMAGE027
the diffusion coefficient is related to meteorological conditions, and the brightness change of the M x N x K three-dimensional contribution matrix shows the difference of the relative size of the contribution degree.
6. The multi-mode fused online accounting method for the actual emission of the atmospheric pollutants according to claim 1, wherein the source intensity of the pollution source is optimally estimated based on the source parameter inversion algorithm by:
s2, estimating the environmental background concentration of the park according to the pollution source intensity and the distribution condition of the monitoring stations and by combining the current wind field data, wherein the specific estimation steps are as follows:
vector pointing to any pollution source i from monitoring site j
Figure 649720DEST_PATH_IMAGE028
Unit vector with real-time wind direction
Figure 624629DEST_PATH_IMAGE029
Performing dot product calculation to obtain vector
Figure 575267DEST_PATH_IMAGE028
In that
Figure 51248DEST_PATH_IMAGE029
Projection in the direction;
when the concentration of the contaminant in the sample is low for any contamination source i, if,
Figure 872574DEST_PATH_IMAGE030
if the monitoring station is a windward station, the monitoring station is considered as an upwind station;
when a plurality of upwind direction sites appear, averaging corresponding monitoring data to be used as the environmental background concentration of the park;
s21, calculating the pseudo inverse of the contribution matrix, obtaining an initial guess of the source intensity of the pollution source, optimizing the distribution of the source intensity of the pollution source to obtain a reliable initial guess, and optimizing the strong distribution of the pollution source, wherein the specific calculation mode is as follows:
Figure 408597DEST_PATH_IMAGE031
in the formula (I), the compound is shown in the specification,
Figure 315373DEST_PATH_IMAGE032
is a 1 x M row vector of the image,
Figure 329466DEST_PATH_IMAGE033
is a row vector of 1 x N,
Figure 270877DEST_PATH_IMAGE034
is that
Figure 712222DEST_PATH_IMAGE035
Pseudo-inverse of the matrix;
Figure 371874DEST_PATH_IMAGE036
is an initial guess of the source strength of the pollution source;
s22, calculating the average relative deviation between the pollution source intensity and the measured value, taking the average relative deviation as the accuracy measurement of the multi-mode atmospheric pollution diffusion model calculation, dynamically generating the weight of the integration of the multi-mode atmospheric pollution diffusion model to avoid the subjective interference caused by artificially setting the integration weight of the multi-mode atmospheric pollution diffusion model, and the specific calculation mode is as follows:
Figure 189657DEST_PATH_IMAGE037
Figure 985575DEST_PATH_IMAGE038
in the formula (I), the compound is shown in the specification,
Figure 4346DEST_PATH_IMAGE039
is the average relative deviation of the multi-mode atmospheric pollution diffusion model K,
Figure 10349DEST_PATH_IMAGE040
is a configurable constant.
7. The multimode-fused online accounting method for the actual emission of the atmospheric pollutants according to claim 1, wherein the specific steps of calculating the total emission of the pollution in the park are as follows:
S3, marking the attribute of the pollution source to eliminate the influence of the pollution source outside the park:
Figure 241610DEST_PATH_IMAGE041
Figure 282247DEST_PATH_IMAGE042
in the formula, Q represents the total amount of the pollutant source emission outside the garden.
8. The multi-mode fused online accounting method for the actual emission of the atmospheric pollutants as claimed in claim 1 or 7, wherein when the total emission of the pollution in the park is calculated, the validity of the accounting result of the multi-mode atmospheric pollution diffusion model is further verified by setting a maximum total emission Q _ MAX and a maximum relative deviation RME _ MAX through a configuration file:
Figure 206341DEST_PATH_IMAGE043
Figure 699639DEST_PATH_IMAGE044
when the fitting result of the multi-mode atmospheric pollution diffusion model is consistent with the park monitoring data, the simulation accounting of the multi-mode atmospheric pollution diffusion model is proved to be effective.
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