CN115146859A - Raise dust simulation forecasting method, device and system - Google Patents
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Abstract
The invention discloses a raise dust simulation forecasting method, device and system. The method comprises the following steps: dividing the covered area into grid areas, collecting a soil data set of each grid area in the covered area, and determining a dust emission characteristic value of each grid area; collecting weather forecast data corresponding to each grid area in a forecasting system; inputting the raise dust characteristic value and the meteorological forecast data of each grid area into a simulated raise dust data model, and outputting a raise dust concentration value of each grid area; and outputting a gridding data result of the dust influence area and the severity according to the dust concentration value. The invention realizes the accurate and comprehensive output of the dust emission forecast by applying the computer simulation technology, carries out multi-point multi-face flexible and accurate monitoring forecast on the dust emission distribution condition and the change trend in the coverage area, carries out the comprehensive implementation of the project, can bring all areas in the coverage area into the supervision area in the form of grid division, really realizes the effective management and the standardized management, and provides a decision basis for the prevention and treatment of the dust emission.
Description
Technical Field
The invention relates to the field of pollutant forecasting, in particular to a method, a device and a system for simulating and forecasting flying dust.
Background
The traditional raise dust monitoring system realizes monitoring of the concentration of particulate matters through a light scattering online monitor, meteorological five-parameter acquisition equipment, acquisition transmission equipment and the like; and the acquired data is transmitted back to the rear management platform through a network.
The field monitoring device is internally integrated with data acquisition devices such as a particulate matter concentration monitor, a meteorological five-parameter monitor, a noise monitor and the like, and samples are acquired according to the field environment. And the sample data is processed by the field equipment and then transmitted to the background through the network layer. And the rear data service platform is used for carrying out system analysis according to data returned by the raise dust field monitoring platform, and then transmitting the analysis result to client systems of different environmental authorities, construction sites and the like, so that the online monitoring of real-time data of pollution sources, the monitoring of field images and videos, the exceeding alarm of the pollution sources and various management and statistics facing different management layers based on Web are realized.
The current raise dust monitoring system can realize the monitoring task in a local range. There are still a number of significant drawbacks. The method is characterized by comprising the following aspects:
1) The existing system is difficult to ensure the comprehensiveness of the monitoring result: the raise dust monitoring system who adopts at present only sets up an on-the-spot monitoring equipment in every monitoring area, because regional area scope is great, and meteorological parameter such as regional wind direction is changeable, and the position that the raise dust takes place can not only be restricted to in one place, consequently, single-point monitoring both can't judge the position that the raise dust produced, also can't confirm the position of raise dust fall point.
2) The existing system is difficult to reflect the authenticity of monitoring data: data acquired by the existing system are generally displayed on a terminal after a series of corrections are carried out on the data through a front field monitoring platform, a rear data service platform and other self-contained platforms, and the accuracy of the data is influenced by a correction method, so that a large error always exists between the displayed data and a true value.
3) The existing system is difficult to realize the universality of data transmission: the raise dust monitoring system of different enterprise productions uses respective communication protocol, though can satisfy the data transmission of equipment to monitor platform separately, but data transmission standard is not unified each other, can't form effectual information sharing each other, has also increased environmental protection department's the supervision degree of difficulty, is unfavorable for forming standardized, normalized raise dust supervision system.
4) The information output is delayed, and an intelligent processing mechanism is lacked. Data that field monitoring equipment collected are through a series of data that handle transmission to industry owner's end, compare in the raise dust environmental change that is going on and have certain hysteresis quality, more can't in time predict the development trend of raise dust environment, artificial intelligence disappearance.
5) The operation and maintenance cost is high, and the economy is great. The traditional raise dust monitoring system is limited by field equipment, if the monitoring area is large, in order to ensure the authenticity of the monitoring result, the field monitoring equipment must be arranged in a multipoint scattered manner, so that the stability system of the system operation and the later operation and maintenance cost are quite worried.
Disclosure of Invention
The invention provides a raise dust simulation forecasting method, which comprises the following steps:
dividing the coverage area into grid areas, collecting a soil data set of each grid area in the coverage area, and determining the dust characteristic value of each grid area;
collecting weather forecast data corresponding to each grid area in a forecasting system;
inputting the raise dust characteristic value and meteorological forecast data of each grid area into a simulated raise dust data model, and outputting a raise dust concentration value of each grid area;
and outputting a gridding data result of the dust influence area and the severity according to the dust concentration value.
The method for simulating and forecasting the flying dust comprises the step of performing grid area division on a coverage area, specifically performing grid division according to a preset area division standard, wherein the grid area division is performed according to a standard of 0.25 degree or 0.5 degree, or the grid area division is performed according to an integer multiple of 0.25 degree or 0.5 degree or is divided into n-dimensional matrixes by cutting.
A method for simulated forecast of dust emission as described above, wherein the weather forecast data in the forecast system is from the gfs global forecast system, and the system also provides 0.25 degree or 0.5 degree grid data accordingly.
The method for simulating and forecasting the flying dust is characterized in that the divided grid areas are numbered.
The method for forecasting raise dust simulation as described above, wherein the collecting the soil data set of each grid area in the coverage area includes: collecting land utilization and soil texture data, and acquiring a dust raising coefficient corresponding to each grid area and a corresponding dust raising influence resisting purification coefficient.
A raise dust simulation forecasting method as described above, wherein the collected weather forecast data includes:
(1) acquiring air pressure gridding data, namely air pressure data of each grid area, wherein dust is in direct proportion to air pressure;
(2) acquiring temperature gridding data, namely the temperature data of each grid area, wherein the temperature data comprises more than-10, -10 to 10, and more than 10 according to temperature grades, the corresponding three coefficient values are respectively 0.9,1 and 1.1, and the coefficient values are reset and adjusted according to the training simulation result;
(3) acquiring humidity gridding data, namely humidity data of each grid area, wherein the raised dust is in inverse proportion to the humidity;
(4) acquiring wind speed and wind direction gridding data, namely the wind speed and the wind direction of each grid area, wherein the dust flying size is in direct proportion to the wind speed, and the distance between the level image and the grid close to the wind direction is in direct proportion to the wind speed.
The raise dust simulation forecasting method specifically comprises the following steps:
wherein, Y i For the output value of the dust concentration of the ith grid area, K i For the obtained dust emission coefficient, P, corresponding to the ith grid area i For the atmospheric pressure corresponding to the ith grid area, W i For the temperature of the ith grid area, F i For the acquired wind speed corresponding to the ith grid area, L i To obtain the ithDust impact resistance purification coefficient, S, corresponding to grid area i And in order to obtain the humidity corresponding to the ith grid area, the value of i is 1 to N, and N is the total number of the grid areas.
In the method for forecasting the dust emission simulation, after the dust emission concentration value of each grid area is calculated, different dust emission severity degrees are output for the grid areas with different dust emission concentration values by referring to the pm2.5/pm10 standard.
The invention also provides a raise dust simulation forecasting device, which is characterized by comprising the following components: the device executes a raise dust simulation forecasting method of any one of the above.
The invention also provides a raise dust simulation and prediction system which is characterized by comprising the raise dust simulation and prediction device, soil data acquisition equipment and a prediction system; the soil data acquisition equipment provides a collected soil data set for the raise dust simulation and forecast device, and the forecast system provides meteorological forecast data for the raise dust simulation and forecast device.
The invention has the following beneficial effects: the invention realizes the accurate and comprehensive output of the flying dust forecast by applying the computer simulation technology, and can carry out multi-point and multi-surface flexible accurate monitoring and forecast on the flying dust distribution condition and the variation trend in the coverage area by collecting the corresponding land utilization and soil texture data of the target area, carrying out grid division on the coverage area, extracting the flying dust coefficient of each grid, acquiring the key data of the flying dust calculation by collecting the meteorological data, and carrying out comprehensive implementation of the project by carrying out comprehensive simulation calculation analysis on the computer, so that all areas in the coverage area can be brought into the supervision area in the form of grid division, thereby really realizing effective management and standardized management and providing a decision basis for the prevention and treatment of the flying dust.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained by those skilled in the art according to these drawings.
Fig. 1 is a flow chart of a method for simulating and forecasting a dust emission according to an embodiment of the present invention;
fig. 2 is a diagram of a raise dust simulation forecast grid result output by applying the raise dust simulation forecast method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are 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 some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
As shown in fig. 1, an embodiment of the present invention provides a method for simulating and forecasting flying dust, including:
step 110, carrying out grid area division on the coverage area, collecting a soil data set of each grid area in the coverage area, and determining a raise dust characteristic value of each grid area;
in the embodiment of the present application, the coverage area is divided into grids according to a preset area division standard, preferably, the grids are divided according to a 0.25 degree or 0.5 degree standard, and also divided into n-dimensional matrixes according to integer multiples of 0.25 degree or 0.5 degree or cut into n-dimensional matrixes, where 1 degree is about 110 km and 0.25 degree is about 28 km × 28 km according to a geographic standard. In addition, the area division may be performed according to actual needs, for example, the area division may be performed according to administrative division of the target coverage area, or the soil geology division of the target area, and the like, and is not limited herein. The method and the device have the advantages that the forecasting effect is presented in a grid mode through the comprehensive application of the digital simulation technology, the full coverage of the forecasting area is realized, the defect of insufficient comprehensiveness of the traditional single-point monitoring method is overcome, and the method and the device can be applied to the calculation and simulation of the dust emission of the world, the country and the city, and the building site and the factory area.
The divided mesh regions are numbered, for example, to obtain the mesh regions as shown in the following table:
| 1 | 2 | 3 | 4 | 5 | 6 | 7 |
| 8 | 9 | 10 | 11 | 12 | 13 | 14 |
| 15 | 16 | 17 | 18 | 19 | 20 | 21 |
| 22 | 23 | 24 | 25 | 26 | 27 | 28 |
| 29 | 30 | 31 | 32 | 33 | 34 | 35 |
| 36 | 37 | 38 | 39 | 40 | 41 | 42 |
| 43 | 44 | 45 | 46 | 47 | 48 | 49 |
collecting soil data sets for each grid area within the coverage area comprises: collecting land utilization and soil texture data, and acquiring a dust raising coefficient corresponding to each grid area and a corresponding dust raising influence resisting purification coefficient. The dust emission coefficient and the anti-dust emission influence purification coefficient are preset values related to soil data, for example, the soil texture type is sand, the land utilization is forest land, and the dust emission coefficient and the anti-dust emission influence purification coefficient are larger than those of the soil texture type which is sand and the land utilization which is bare land.
Step 120, collecting weather forecast data corresponding to each grid area in a forecast system;
weather forecast data in forecast systems is typically from the gfs global forecast system, which also provides 0.25 degrees or 0.5 degrees of grid data accordingly.
Wherein, the weather forecast data collected includes:
(1) acquiring air pressure gridding data, namely air pressure data of each grid area, wherein dust is in direct proportion to air pressure;
(2) acquiring temperature gridding data, namely the temperature data of each grid area, wherein the temperature data comprises more than-10, -10 to 10, and more than 10 according to temperature grades, the corresponding three coefficient values are respectively 0.9,1,1.1, and the coefficient values can be reset and adjusted according to the training simulation result;
(3) acquiring humidity gridding data, namely humidity data of each grid area, wherein the raised dust is in inverse proportion to the humidity;
(4) acquiring wind speed and wind direction gridding data, namely the wind speed and the wind direction of each grid area, wherein the dust flying size is in direct proportion to the wind speed, and the distance between the level image and the grid close to the wind direction is in direct proportion to the wind speed.
Step 130, inputting the raise dust characteristic value and meteorological forecast data of each grid area into a simulated raise dust data model, and outputting a raise dust concentration value of each grid area;
in the embodiment of the application, the simulation raise dust data model is obtained by AI according to the wind direction, temperature, humidity and other coefficients combined with the aerodynamic principle, and the simulation raise dust data model is specifically:
wherein, Y i For the output value of the dust concentration of the ith grid area, K i For the obtained dust emission coefficient, P, corresponding to the ith grid area i For the atmospheric pressure, W, corresponding to the ith grid area i For the temperature of the ith grid area, F i For the acquired wind speed corresponding to the ith grid area, L i For obtaining the dust-impact-resistant purification coefficient corresponding to the ith grid area, S i For the ith acquired grid areaAnd (3) corresponding humidity, wherein the value of i is 1 to N, and N is the total number of the grid areas.
Inputting the dust characteristic values (including dust coefficient and dust-influence-resisting purification coefficient) and meteorological forecast data (atmospheric pressure, temperature, wind speed and humidity) corresponding to the soil data sets collected in each grid area into the simulated dust data model, and outputting the dust concentration values of each grid area. According to the method, on the basis of different soil data of each grid area and 0.25/0.5-degree grid data provided by a forecasting system, various dust-raising influence factors are comprehensively considered, the AI data model is used for calculating dust-raising data, the authenticity of a forecasting result is greatly increased, on-site acquisition equipment is not required to be arranged for data acquisition of the forecasting system, a large amount of equipment cost, site cost and equipment later-stage operation maintenance cost are saved, and the method is more economical.
Step 140, outputting a gridding data result of the dust influence area and the severity according to the dust concentration value;
in the embodiment of the application, after calculating the dust concentration value of each grid area, refer to pm2.5/pm10 standard, to the grid area output different dust severity of different dust concentration values, for example, clearly show the dust severity of different grid areas according to modes such as color marking or icon marking, make the dust forecast more have authenticity and predictability, fig. 2 is the grid achievement diagram that this application actually carries out the output of dust simulation forecast, the number of each grid area in the diagram represents the dust concentration value of this grid area, the darker colour in the grid represents that the dust concentration of this area is higher, then this area pollution degree is more serious.
Example two
The second embodiment of the invention provides a raise dust simulation and prediction system, which comprises a raise dust simulation and prediction device, soil data acquisition equipment and a prediction system; the soil data acquisition equipment provides the collected soil data set for the raise dust simulation and forecast device, and the forecast system provides weather forecast data for the raise dust simulation and forecast device. The dust simulation forecasting device executes a dust simulation forecasting method according to the soil data acquisition equipment and the forecasting system.
The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only examples of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made on the basis of the technical solutions of the present invention should be included in the scope of the present invention.
Claims (10)
1. A raise dust simulation forecasting method is characterized by comprising the following steps:
dividing the coverage area into grid areas, collecting a soil data set of each grid area in the coverage area, and determining the dust characteristic value of each grid area;
collecting weather forecast data corresponding to each grid area in a forecasting system;
inputting the raise dust characteristic value and meteorological forecast data of each grid area into a simulated raise dust data model, and outputting a raise dust concentration value of each grid area;
and outputting a gridding data result of the dust influence area and the severity according to the dust concentration value.
2. A method as claimed in claim 1, wherein the coverage area is divided into grids according to a predetermined area division standard, the grid division is performed according to a standard of 0.25 degrees or 0.5 degrees, or divided into n-dimensional matrixes according to an integer multiple of 0.25 degrees or 0.5 degrees or cut into n-dimensional matrixes.
3. A method as claimed in claim 2, wherein the weather forecast data in the forecast system is from the gfs global forecast system, which also provides 0.25 degree or 0.5 degree grid data.
4. A method as claimed in claim 1, wherein the divided grid areas are numbered.
5. A method as claimed in claim 1, wherein collecting soil data sets for grid areas in the coverage area comprises: collecting land utilization and soil texture data, and acquiring a dust raising coefficient corresponding to each grid area and a corresponding dust raising influence resisting purification coefficient.
6. A method as claimed in claim 1, wherein the collected weather forecast data comprises:
(1) acquiring air pressure gridding data, namely air pressure data of each grid area, wherein dust is in direct proportion to air pressure;
(2) acquiring temperature gridding data, namely the temperature data of each grid area, wherein the temperature gridding data comprises more than-10, -10 to 10, and more than 10 according to temperature grades, the corresponding three coefficient values are respectively 0.9,1 and 1.1, and the coefficient values are reset and adjusted according to the training simulation result;
(3) acquiring humidity gridding data, namely humidity data of each grid area, wherein the raised dust is in inverse proportion to the humidity;
(4) acquiring wind speed and wind direction gridding data, namely the wind speed and the wind direction of each grid area, wherein the dust flying size is in direct proportion to the wind speed, and the distance between the level image and the grid close to the wind direction is in direct proportion to the wind speed.
7. The method according to claim 1, wherein the simulated dust data model is specifically:
wherein, Y i For the output value of the dust concentration of the ith grid area, K i For obtaining the dust raising coefficient, P, corresponding to the ith grid area i For the atmospheric pressure, W, corresponding to the ith grid area i For the temperature of the ith grid area, F i For the acquired wind speed corresponding to the ith grid area, L i For obtaining the dust-impact-resistant purification coefficient corresponding to the ith grid area, S i And in order to obtain the humidity corresponding to the ith grid area, the value of i is 1 to N, and N is the total number of the grid areas.
8. A method as claimed in claim 1, wherein after the values of the dust concentration in each grid area are calculated, different levels of dust severity are output for grid areas with different values of the dust concentration, with reference to pm2.5/pm10 standard.
9. A raise dust simulation forecasting apparatus, comprising: the device performs a dust emission simulation forecasting method as claimed in any one of claims 1 to 8.
10. A dust emission simulation forecasting system comprising the dust emission simulation forecasting apparatus as claimed in claim 9, and a soil data collecting device and forecasting system; the soil data acquisition equipment provides the collected soil data set for the raise dust simulation and forecast device, and the forecast system provides weather forecast data for the raise dust simulation and forecast device.
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