Simulation area setting method and equipment based on fine particulate matter source analysis result

Abstract

The embodiment of the invention discloses a simulation area setting method and device based on a fine particulate matter source analysis result. Respectively determining the concentration contributions of the n different buffer areas to the fine particulate matters in the region of interest; quantificationally representing an accuracy influence value of the ith buffer area on the fine particulate matter simulation of the concerned area; according to the quantized accuracy influence value, eliminating a buffer area with a relatively small accuracy influence value; and determining a new boundary of the target simulation area according to the residual buffer area so as to determine the optimal simulation range of the air quality mode for the area of interest. Compared with a mode range set according to experience, the optimal simulation range has the advantages that on the basis of ensuring the fine particle simulation accuracy of the region of interest, the calculation time consumption is remarkably reduced, and the calculation resources are saved.

Description

Technical Field

[0001] This specification relates to the field of atmospheric numerical simulation, and particularly to a method and device for setting a simulation area based on the results of source apportionment of fine particulate matter. Background Art

[0002] In the field of atmospheric numerical simulation, the size of the simulation area can affect the numerical simulation process in multiple aspects. For example, if the simulation / forecast area range of the air quality model is set too small, the simulation / forecast value of fine particulate matter (PM2.5) will be significantly underestimated due to insufficient consideration of long-distance pollutant transport; if the simulation / forecast area range of the air quality model is set too large, it will increase the unnecessary computing time of the model, thereby wasting computing resources. Currently, when conducting regional air quality simulation research and forecasting, the setting of the simulation range of the air quality model is mostly based on empirical judgment, without specific quantitative criteria.

[0003] Based on this, there is a need for a simulation area setting scheme that can be accurately quantified. Summary of the Invention

[0004] Embodiments of this specification provide a method and device for setting a simulation area based on the results of source apportionment of fine particulate matter, to solve the following technical problem: there is a need for a simulation area setting scheme that can be accurately quantified.

[0005] To solve the above technical problem, one or more embodiments of this specification are implemented as follows:

[0006] In a first aspect, embodiments of this specification provide a method for setting a simulation area based on the results of source apportionment of fine particulate matter, which is applied to an original simulation area including a concerned area and n buffer areas, and includes: respectively determining the concentration contribution of the n different buffer areas to the fine particulate matter in the concerned area; quantitatively representing the influence value of the accuracy of the simulation of the fine particulate matter in the concerned area by the i-th buffer area; removing the buffer areas with smaller influence values of accuracy according to the quantitatively represented influence value of accuracy; and determining the new boundary of the target simulation area according to the remaining buffer areas.

[0007] In a second aspect, one or more embodiments of this specification provide an electronic device, including:

[0008] At least one processor; and,

[0009] A memory communicatively connected to the at least one processor; wherein,

[0010] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method as described in the first aspect.

[0011] The above at least one technical solution adopted by one or more embodiments of this specification can achieve the following beneficial effects: By respectively determining the concentration contributions of the n different buffer zones to the fine particulate matter in the area of concern; quantitatively representing the influence value of the accuracy of the simulation of the fine particulate matter in the i-th buffer zone on the area of concern; eliminating the buffer zones with relatively small influence values of accuracy according to the quantitatively determined influence values of accuracy; and determining the new boundary of the target simulation area based on the remaining buffer zones, so as to determine the best simulation range of the air quality model for the area of concern. Compared with the model range set empirically, the best simulation range can significantly reduce the calculation time consumption and save computing resources while ensuring the accuracy of the fine particulate matter simulation in the area of concern. Description of the Drawings

[0012] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in this specification. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0013] Figure 1 It is a schematic flowchart of a method for setting a simulation area based on the source analysis result of fine particulate matter provided by an embodiment of this specification;

[0014] Figure 2 It is a schematic diagram of the area of concern and buffer zones in atmospheric numerical simulation provided by an embodiment of this specification;

[0015] Figure 3 It is a schematic diagram of the marking setting of multiple source areas provided by an embodiment of this specification;

[0016] Figure 4 It is a schematic diagram of delimiting a target simulation area provided by an embodiment of this specification;

[0017] Figure 5 It is a schematic diagram of the structure of an electronic device provided by an embodiment of this specification. Detailed Embodiments

[0018] Embodiments of this specification provide a method and device for setting a simulation area based on the source analysis result of fine particulate matter.

[0019] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0020] As Figure 1 shown, Figure 1 This is a schematic flowchart of a method for setting a simulation area based on the source analysis result of fine particulate matter provided by the embodiment of this specification.

[0021] Figure 1 The process in

[0022] S102: Determine the concentration contributions of the n different buffer zones to the fine particulate matter in the area of interest respectively.

[0023] In numerical simulation, usually a primary simulation area (the primary simulation area is usually rectangular) is first set, and 1 area of interest, an air quality model, and n buffer zones are set in this area. At the same time, for the n buffer zones, they can also be respectively set as an eastern buffer zone, a western buffer zone, a southern buffer zone, and a northern buffer zone based on their orientations relative to the area of interest. The number of buffer zones in each orientation can be 1 or more. The area of interest and the buffer zones are usually irregular figures obtained based on the actual administrative region division.

[0024] As Figure 2 shown, Figure 2 This is a schematic diagram of the area of interest and buffer zones in atmospheric numerical simulation provided by the embodiment of this specification.

[0025] For the convenience of subsequent calculations, ID numbers of different source areas can also be set within the simulation area. As Figure 3 shown, Figure 3 This is a schematic diagram of the marking setting of multiple source areas provided by the embodiment of this specification.

[0026] For example, the area of interest is set as a local area. The northern buffer is divided into three local areas successively from south to north starting from the area adjacent to the area of interest, namely North-1, North-2, and North-3 local areas. Similarly, the western buffer is divided into three local areas successively from east to west, namely West-1, West-2, and West-3 local areas. The eastern buffer is divided into three local areas successively from west to east, namely East-1, East-2, and East-3 local areas. The southern buffer is divided into two local areas successively from north to south, namely South-1 and South-2 local areas.

[0027] Furthermore, the particulate matter source apportionment technology can be used to calculate the concentration contributions of the n different buffers to the particulate matter in the area of interest respectively. The Particulate Source Apportionment Technology (PSAT) is developed from the Ozone Source Apportionment Technology (OSAT) in the regional air quality model CAMx. As one of the most commonly used particulate matter source apportionment methods at present, the CAMx-PSAT model is widely used in the research on particulate matter source apportionment in specific local areas or specific industries.

[0028] By adding reactive tracer "labels" to pollutants of different source areas and different emission types to track the target pollutants, and statistically analyzing the contribution amounts of tracer species at receptor points, the pollutant concentration contribution results of different source areas and different emission types to the receptor points can be obtained. In this application, the particulate matter source apportionment technology is mainly used to obtain the particulate matter concentration contributions of different buffers to the area of interest.

[0029] S104, quantitatively represent the influence value of the accuracy of the particulate matter simulation in the i-th buffer on the area of interest.

[0030] There can be multiple quantification indicators. For example, the influence value of the accuracy of the i-th buffer, ΔRMSE, is quantitatively represented in the following way i :

[0031] where RMSE all represents the mean square error between the particulate matter concentration contributions of all areas and the observed values, and RMSE i represents the mean square error between the sum of the particulate matter concentration contributions of the remaining areas (including n - 1 buffers and the area of interest) and the observed values after removing the i-th buffer, and ΔRMSE iFor the accuracy impact of the i-th buffer on the simulation accuracy of fine particulate matter in the area of interest, M_all represents the sum of the contributions of fine particulate matter concentrations in all areas (including n buffers and the area of interest), M_part represents the sum of the contributions of fine particulate matter concentrations in the remaining areas (including n - 1 buffers and the area of interest) after removing the i-th buffer, O represents the observed value, m represents the number of pairs of valid samples (note: the number of pairs of valid samples m has no relation with the number of buffers n), M loacl represents the contribution of the fine particulate matter concentration in the area of interest, and M i represents the contribution of the fine particulate matter concentration of the i-th buffer.

[0032] The specific steps are as follows: First, calculate the root mean square error RMSE between the sum of the contributions of all buffer concentrations and the observed value. all Then, successively remove the contribution of the fine particulate matter concentration of a single buffer one by one, and calculate the root mean square error RMSE between the sum of the contributions of the fine particulate matter concentrations of the remaining buffers and the observed value. i Finally, by calculating the difference between the two, quantify the impact of removing the buffer on the simulation accuracy of fine particulate matter. If ΔRMSE i is larger, it indicates that the buffer has a greater impact on the simulation accuracy of fine particulate matter in the area of interest and is not suitable to be removed from the original simulation area; conversely, the smaller the difference, the smaller the impact of the buffer on the simulation accuracy of fine particulate matter in the area of interest, and it can be considered to be removed from the original simulation area.

[0033] S106. Remove the buffer with a smaller accuracy impact value according to the quantified accuracy impact value.

[0034] The specific removal method can be various, and several are exemplarily given below. For example:

[0035] The first type: The buffer with an accuracy impact value less than a preset threshold. The preset threshold can be set according to actual needs or according to the observed value. For example, it is set to 0.5 μg·m -3 , or it is set to 1% of the observed value. Thus, after removing the area, the simulation accuracy of fine particulate matter in the area of interest can still be guaranteed.

[0036] Still taking Figure 3 as an example. Set the preset threshold to 0.5 μg·m -3 . Using the source analysis technology of fine particulate matter, it is determined that the North-3, West-3, and South-2 buffers in this example have relatively small contributions to the fine particulate matter concentration in Henan Province, and the ΔRMSE values are 0.1 μg·m -3 , 0.3 μg·m -3 , 0.4 μg·m -3, these areas need to be removed from the original simulation areas.

[0037] Second, remove the top K buffers with the smallest to largest accuracy impact values in the sorted order. In this way, even if the absolute value of the accuracy impact value is relatively large, it may still be removed.

[0038] Third, sequentially remove the buffers according to the accuracy impact value from smallest to largest until the area of the remaining buffers and the area of the concerned area meet the preset condition. The preset condition can be that the sum of the area of the buffers and the area of the concerned area shall not be lower than a certain ratio, or the ratio of the area of the buffers to the area of the concerned area shall not be lower than a certain ratio, so as to ensure the number of grids in the numerical simulation process and avoid simulation instability caused by too few grids.

[0039] S108, determine the new boundary of the target simulation area according to the remaining buffers.

[0040] As mentioned above, whether it is the original simulation area or the target simulation area, they are both rectangles. While the buffers are irregular in shape. It is impossible to directly apply the remaining area after removing them to the numerical simulation. Therefore, it is also necessary to convert it into a regular area.

[0041] Specifically, determine the remaining buffers in each direction; for any one of the four directions of east, south, west, and north, determine the maximum and minimum points of the remaining buffers in this direction in this direction; define the reference line passing through the maximum and minimum points and parallel to the boundary of the original simulation area in this direction as the new boundary of the target simulation area in this direction.

[0042] For example, when determining the boundary of the target simulation area in Fig. 3, when determining the north boundary of the optimal range, use the northernmost point of the northern Sub-source Area 2 as the reference point (Northern Sub-source Area 3 has been removed), and define the north boundary with a reference line parallel to the north boundary of the original simulation range; similarly, when determining the south boundary, use the southernmost point of the southern Sub-source Area 1 as the reference point (Southern Sub-source Area 2 has been removed), and define the south boundary with a reference line parallel to the south boundary of the original simulation range; when determining the west boundary, use the westernmost point of the western Sub-source Area 2 as the reference point (Western Sub-source Area 3 has been removed), and define the west boundary with a reference line parallel to the west boundary of the original simulation range; the east boundary remains the same as the east boundary of the original simulation area (there is no removed buffer in the east, so the boundary remains unchanged). As Figure 4 shown, Figure 4 is a schematic diagram of a method for defining a target simulation area provided by an embodiment of this specification. In this schematic diagram, the boundary line marked by the dashed box is the boundary line of the new target simulation area.

[0043] By separately determining the concentration contributions of the n different buffers to the fine particulate matter in the area of interest; quantifying the impact value of the accuracy of the simulation of the fine particulate matter in the i-th buffer on the area of interest; removing the buffers with smaller accuracy impact values according to the quantified accuracy impact values; and determining the new boundary of the target simulation area based on the remaining buffers, so as to determine the best simulation range of the air quality model for the area of interest. Compared with the model range set empirically, the best simulation range significantly reduces the calculation time and saves computing resources while ensuring the accuracy of the fine particulate matter simulation in the area of interest.

[0044] Table 1 shows the comparison of the indexes of numerical simulation calculations for the empirically set range (original simulation area) and the target simulation area (i.e., the rectangular range set by the dashed line in Figure 3 ). Under the setting of the target simulation area, the simulation accuracy of the fine particulate matter only increases from 52.2 μg m-3 to 53.1 μg m-3, a decrease of 3.1%, but the number of calculation grids decreases from 3.092 million to 2.2 million, the total number of grids decreases by 42.3%, and the calculation time is reduced from 20.3 minutes to 14.8 minutes, a reduction of 39.6%.

[0045] Table 1: Comparison of the indexes of numerical simulation calculations for the empirically set area and the target simulation area.

[0046] Empirical setting area Target simulation area Number of grids 478*462*14, approximately 3.092 million 428*367*14, approximately 2.2 million Simulation accuracy (RMSE) 52.2 μg m-3 53.1 μg m-3 Computation time 20.3 minutes 14.8 minutes

[0047] It can also be seen from Table 1 that the best simulation range of the air quality model determined by the present invention can be applied to the provincial- and municipal-level air quality operational forecasting system, which can significantly reduce the forecasting time, ensure the timeliness of the forecast, and save computing resources while ensuring the accuracy of the fine particulate matter forecast.

[0048] In a second aspect, based on the same idea, the embodiments of this specification also provide an electronic device. As Figure 5 shown, Figure 5 is a schematic structural diagram of an electronic device provided by the embodiments of this specification. The device includes:

[0049] At least one processor; and,

[0050] A memory communicatively connected to the at least one processor; wherein,

[0051] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method as described in the first aspect.

[0052] Based on the same idea, the embodiments of this specification also provide a non-volatile computer storage medium corresponding to the above method, storing computer-executable instructions. When a computer reads the computer-executable instructions in the storage medium, the instructions cause one or more processors to execute the method described in the first aspect.

[0053] The embodiments in this specification are all described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, equipment, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, reference can be made to the partial description of the method embodiments.

[0054] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0055] The above is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, there can be various modifications and changes to one or more embodiments of this specification. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A simulation area setting method based on the results of fine particulate matter source analysis is applied to an original simulation area including a focus area and n buffer areas, the method comprising: Determining respectively the concentration contribution of the n different buffer zones to the fine particulate matter in the area of ​​interest; Quantitatively represents the impact of the i-th buffer zone on the accuracy of fine particle simulation in the area of ​​concern; Eliminating a buffer zone with a smaller accuracy impact value according to the quantified accuracy impact value; Determine the new boundaries of the target simulation area based on the remaining buffer.

2. The method of claim 1, wherein: Quantify the impact of the i-th buffer zone on the accuracy of fine particle simulation in the area of ​​interest, including: The accuracy impact value ΔRMSE of the i-th buffer is quantified as follows: i : Among them, RMSE all Represents the mean square error between the fine particle concentration contribution of all regions and the observed value, RMSE i It represents the mean square error between the sum of the fine particulate matter concentration contribution in the remaining area and the observed value after removing the i-th buffer zone, ΔRMSE i is the impact of the ith buffer zone on the accuracy of the fine particle simulation in the area of ​​interest, M_all represents the sum of the fine particle concentration contributions of n buffer zones and the area of ​​interest, M_part represents the sum of the fine particle concentration contributions of the remaining n-1 buffer zones and the area of ​​interest after the ith buffer zone is removed, O represents the observed value, m represents the number of valid sample logarithms, m is independent of n, and M loacl Indicates the contribution of fine particulate matter concentration in the area of ​​concern, M i represents the fine particle concentration contribution of the i-th buffer zone.

3. The method of claim 1, wherein: Eliminating a buffer zone with a smaller accuracy impact value according to the quantified accuracy impact value includes: Eliminate the buffer zone whose accuracy impact value is less than a preset threshold; Alternatively, the K buffers that are ranked first in the ascending order of the accuracy impact values ​​are eliminated; Alternatively, the buffers are eliminated in order from small to large according to the accuracy impact values ​​until the areas of the remaining buffers and the focus area meet a preset condition.

4. The method of claim 1, wherein: The boundaries of the simulation area are determined based on the remaining buffer, including: Determine the remaining buffer in each direction; For any direction of east, south, west or north, determine the maximum point of the remaining buffer zone in that direction; A reference line passing through the maximum point and parallel to the boundary of the original simulation area in this direction is defined as a new boundary of the target simulation area in this direction.

5. The method of claim 1, wherein: Determining respectively the concentration contribution of the n different buffer zones to the fine particulate matter in the area of ​​interest, including: Ozone source tracking technology is used to determine the concentration contribution of the n different buffer zones to the fine particulate matter in the area of ​​interest.

6. An electronic device comprising: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

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