Method, apparatus and electronic device for determining a monitoring station location

Abstract

The present disclosure relates to a method, device and electronic equipment for determining a monitoring station position, the method comprising: obtaining first meteorological information and first concentration information of an air pollutant of N target sub-regions at T time, and second meteorological information and second concentration information of an air pollutant of M preset sub-regions at T time; determining the concentration information of the air pollutant of a second target sub-region at a first time according to the first meteorological information and the first concentration information; determining the concentration information of the air pollutant of a first target sub-region at the first time according to the second meteorological information and the second concentration information; and determining a monitoring station of the air pollutant from the N target sub-regions according to the concentration information of the air pollutant of the N target sub-regions at the first time. Through the above technical solution, the influence of the air pollutant outside the target region on the boundary is considered, and the accuracy and rationality of the determined monitoring station are improved.

Description

Technical Field

[0001] This disclosure relates to the field of air quality monitoring technology, and more specifically, to a method, apparatus, and electronic equipment for determining the location of monitoring stations. Background Technology

[0002] With the rapid development of industrialization and urbanization in my country, air pollution has become an increasingly prominent problem. Establishing a scientifically sound monitoring network is crucial for the effective monitoring and control of air pollution. The selection of monitoring station locations is a key aspect of building this network, directly affecting the representativeness and accuracy of air pollutant monitoring data. Therefore, setting up appropriate monitoring stations is beneficial to improving the effectiveness of air pollution control. Summary of the Invention

[0003] The purpose of this disclosure is to provide a method, apparatus, and electronic equipment for determining the location of monitoring stations, taking into account the impact of air pollutants outside the target area on the boundary, thereby improving the accuracy and rationality of the determined monitoring stations.

[0004] To achieve the above objectives, in a first aspect, this disclosure provides a method for determining the location of a monitoring station, the method comprising:

[0005] Acquire first meteorological information and first concentration information of air pollutants for each of N target sub-regions at time T, and second meteorological information and second concentration information of air pollutants for each of M preset sub-regions at time T. The target region is divided into the N target sub-regions, and the preset region is divided into the M preset sub-regions. The range of the preset region is greater than and includes the range of the target region. There is no overlapping area between the first target sub-region and the preset sub-region located at the boundary of the preset region. The first target sub-region includes the target sub-region located at the boundary of the target region.

[0006] Based on the first meteorological information and the first concentration information, the air pollutant concentration information of the second target sub-region at the first time is determined. The first time includes every time from time T+1 to time T+K. The second target sub-region includes the target sub-regions other than the first target sub-region in the target region.

[0007] Based on the second meteorological information and the second concentration information, determine the air pollutant concentration information of the first target sub-region at the first time.

[0008] Based on the air pollutant concentration information of the N target sub-regions at the first time, the monitoring stations for the air pollutants are determined from the N target sub-regions.

[0009] Optionally, determining the air pollutant concentration information of the second target sub-region at the first moment based on the first meteorological information and the first concentration information includes:

[0010] Based on the first meteorological information, a first Markov matrix is ​​determined. The first Markov matrix has N rows and N columns. The element in the i-th row and j-th column of the first Markov matrix represents the probability that air pollutants in the i-th target sub-region will transfer to the j-th target sub-region after a preset time interval. The time interval between time T+1 and time T, as well as the time interval between each two adjacent first times, are the preset time intervals.

[0011] Based on the first concentration information and the first Markov matrix, determine the air pollutant concentration information of the second target sub-region at time T+1;

[0012] Based on whether the third meteorological information of each of the N target sub-regions at time T+1 is obtained, the air pollutant concentration information of the second target sub-region at time T+2 is determined;

[0013] Take time T+2 as the new time T+1, and return to the step of determining the air pollutant concentration information of the second target sub-region at time T+2 based on whether the third meteorological information of each of the N target sub-regions at time T+1 is obtained, until the air pollutant concentration information of the second target sub-region at time T+K is obtained.

[0014] Optionally, determining the air pollutant concentration information of the second target sub-region at time T+2 based on whether the third meteorological information of each of the N target sub-regions at time T+1 is obtained includes:

[0015] If the third meteorological information is not obtained, the air pollutant concentration information of the second target sub-region at time T+2 is determined based on the first concentration information and the first Markov matrix.

[0016] If the third meteorological information is obtained, a second Markov matrix is ​​determined based on the third meteorological information. Based on the first concentration information, the first Markov matrix, and the second Markov matrix, the air pollutant concentration information of the second target sub-region at time T+2 is determined, wherein the size of the second Markov matrix is ​​the same as the size of the first Markov matrix.

[0017] Optionally, determining the air pollutant concentration information of the first target sub-region at the first time based on the second meteorological information and the second concentration information includes:

[0018] Based on the second meteorological information, a third Markov matrix is ​​determined. The third Markov matrix has M rows and M columns. The element in the i-th row and j-th column of the third Markov matrix represents the probability that air pollutants in the i-th preset sub-region will transfer to the j-th preset sub-region after a preset time interval. The time interval between time T+1 and time T, as well as the time interval between each two adjacent first times, are the preset time intervals.

[0019] Based on the second concentration information and the third Markov matrix, determine the air pollutant concentration information of the M preset sub-regions at time T+1;

[0020] Based on the air pollutant concentration information of the first preset sub-region at time T+1, the air pollutant concentration information of the first target sub-region at time T+1 is determined. The first preset sub-region is the sub-region corresponding to the first target sub-region among the M preset sub-regions.

[0021] Based on whether the fourth meteorological information of each of the M preset sub-regions at time T+1 is obtained, the air pollutant concentration information of each of the M preset sub-regions at time T+2 is determined.

[0022] Based on the air pollutant concentration information of the first preset sub-region at time T+2, determine the air pollutant concentration information of the first target sub-region at time T+2.

[0023] Take time T+2 as the new time T+1, and return to the step of determining the air pollutant concentration information of the M preset sub-regions at time T+2 based on whether the fourth meteorological information of each of the M preset sub-regions at time T+1 is obtained, until the air pollutant concentration information of the first target sub-region at time T+K is obtained.

[0024] Optionally, determining the air pollutant concentration information of the M preset sub-regions at time T+2 based on whether the fourth meteorological information of each of the M preset sub-regions at time T+1 is obtained includes:

[0025] If the fourth meteorological information is not obtained, then the air pollutant concentration information of the M preset sub-regions at time T+2 is determined according to the second concentration information and the third Markov matrix.

[0026] If the fourth meteorological information is obtained, then a fourth Markov matrix is ​​determined based on the fourth meteorological information. Based on the second concentration information, the third Markov matrix, and the fourth Markov matrix, the air pollutant concentration information of the M preset sub-regions at time T+2 is determined, wherein the size of the fourth Markov matrix is ​​the same as the size of the third Markov matrix.

[0027] Optionally, the area of ​​the first preset sub-region is larger than and includes the area of ​​the first target sub-region;

[0028] The air pollutant concentration information of the first target sub-region at the first time time is determined based on the air pollutant concentration information of the first preset sub-region at the first time time in the following manner:

[0029] If the position of the first target sub-region corresponds to the first vertex of the first preset sub-region, then the average value of the air pollutant concentration information of the preset sub-region with the first vertex as the vertex at the first time shall be used as the air pollutant concentration information of the first target sub-region at the first time.

[0030] If the position of the first target sub-region corresponds to the first edge of the first preset sub-region, then the average value of the air pollutant concentration information of the preset sub-region with the first edge as the edge at the first time shall be used as the air pollutant concentration information of the first target sub-region at the first time.

[0031] Optionally, the time interval between time T+1 and time T, as well as the time interval between any two adjacent first times, are preset time intervals, wherein the preset time interval is less than or equal to the upper limit of the time interval.

[0032] The N target sub-regions are square grid regions with equal side lengths, and the upper limit of the time interval is obtained based on the side length and the historical average wind speed of the N target sub-regions.

[0033] Optionally, the method further includes:

[0034] Taking time T+K+1 as the new time T, the steps of obtaining the first meteorological information and the first concentration information of air pollutants for each of the N target sub-regions at time T, and the second meteorological information and the second concentration information of air pollutants for each of the M preset sub-regions at time T, are repeated until the step of determining the air pollutant concentration information of the first target sub-region at the first time based on the second meteorological information and the second concentration information is performed, until the first time includes the preset end time, and the air pollutant monitoring station is determined from the N target sub-regions based on the air pollutant concentration information of the N target sub-regions at the first time.

[0035] Wherein, the first meteorological information and the second meteorological information include wind speed in the horizontal direction, the concentration information of air pollutants in the target sub-region at time T+K+1 is determined based on the chemical change process, deposition change process and vertical change process of the air pollutants in the target sub-region, and the concentration information of air pollutants in the preset sub-region at time T+K+1 is determined based on the chemical change process, deposition change process and vertical change process of the air pollutants in the preset sub-region.

[0036] Secondly, this disclosure provides an apparatus for determining the location of a monitoring station, the apparatus comprising:

[0037] A memory on which computer programs are stored;

[0038] A processor for executing the computer program in the memory to implement the method for determining the location of a monitoring station provided in the first aspect.

[0039] Thirdly, this disclosure provides an electronic device, including the means for determining the location of a monitoring station provided in the second aspect.

[0040] The above technical solution addresses the issue that determining the air pollutant concentration information of the first target sub-region at its boundary based solely on the first meteorological and first concentration information of the target sub-region would fail to account for the impact of air pollutants outside the target region on the boundary. Therefore, a pre-defined area is delineated around the target region. This pre-defined area is larger than and includes the target region, and there is no overlap between the first target sub-region and the pre-defined sub-region located at the boundary of the pre-defined area. In this way, determining the air pollutant concentration information of the first target sub-region at the first moment based on the second meteorological and second concentration information of the pre-defined sub-region allows for consideration of the impact of air pollutants outside the target region on the boundary. This makes the determined air pollutant concentration information of the first target sub-region more accurate, improving the accuracy and rationality of determining air pollutant monitoring stations from N target sub-regions.

[0041] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0042] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings:

[0043] Figure 1 This is a flowchart illustrating a method for determining the location of a monitoring station according to an exemplary embodiment.

[0044] Figure 2 This is a schematic diagram illustrating the target area.

[0045] Figure 3 This is a schematic diagram of a preset area as an example.

[0046] Figure 4 This is an illustrative diagram showing the transfer of air pollutants.

[0047] Figure 5 This is a schematic diagram illustrating the area of ​​the transfer region as an example.

[0048] Figure 6 This is a flowchart of a method for determining the air pollutant concentration information of a second target sub-region at a first moment based on first meteorological information and first concentration information.

[0049] Figure 7 This is a flowchart of a method for determining the air pollutant concentration information of the first target sub-region at a first moment based on second meteorological information and second concentration information.

[0050] Figure 8 Based on Figure 2 The target area shown and Figure 3 The preset area shown is a schematic diagram illustrating the relationship between the preset sub-region and the target sub-region.

[0051] Figure 9 This is a block diagram illustrating an electronic device according to an exemplary embodiment. Detailed Implementation

[0052] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0053] As described in the background section, setting up reasonable monitoring stations is beneficial to improving the effectiveness of air pollution control. In related technologies, monitoring stations are usually selected near pollution sources or densely populated areas, or based on historical monitoring data of pollutants. However, the methods in related technologies do not fully consider the spatial distribution characteristics and transfer characteristics of air pollutants, making it difficult to guarantee the representativeness of the monitoring data.

[0054] This disclosure provides a method, apparatus, and electronic equipment for determining the location of monitoring stations, thereby improving the rationality of site selection for air pollutant monitoring stations.

[0055] Figure 1 This is a flowchart illustrating a method for determining the location of a monitoring site according to an exemplary embodiment. This method can be applied to an electronic device, such as a server. Figure 1 As shown, the method for determining the location of monitoring stations includes steps 11 to 14.

[0056] Step 11: Obtain the first meteorological information and the first concentration information of air pollutants for each of the N target sub-regions at time T, and the second meteorological information and the second concentration information of air pollutants for each of the M preset sub-regions at time T.

[0057] The target area is divided into N target sub-regions, and the preset area is divided into M preset sub-regions. The range of the preset area is greater than and includes the range of the target area. There is no overlapping area between the first target sub-region and the preset sub-region located at the boundary of the preset area. The first target sub-region includes the target sub-region located at the boundary of the target area.

[0058] The boundary of the target region can be a first target sub-region with at least one edge serving as the boundary of the target region. The boundary of the preset region can be a preset sub-region with at least one edge serving as the boundary of the preset region.

[0059] Figure 2 This is a schematic diagram illustrating the target area. Figure 3 This is a schematic diagram illustrating a preset area as an example. Figure 2 As shown, the target area is divided into N target sub-regions, which can be square grid regions with the same side length. Among them, the target sub-region filled with gray is the first target sub-region, that is, the first target sub-region includes target sub-regions A1 to A32 located at the boundary of the target area. The target sub-region not filled with gray is the second target sub-region, that is, the second target sub-region includes the target sub-regions in the target area other than the first target sub-region.

[0060] like Figure 3As shown, the preset area is divided into M preset sub-areas, which include preset sub-areas B1 to preset sub-areas B30. Among them, the area filled with diagonal lines is the target area, that is, the area formed by preset sub-areas B8 to B10, preset sub-areas B14 to B16, and preset sub-areas B20 to B22 is the target area. That is, the range of the preset area is greater than and includes the range of the target area.

[0061] Furthermore, referring to Figure 3 Preset sub-regions B1 to B6, B25 to B30, B7, B13, B19, B12, B18, and B24 are located at the boundaries of the preset regions. The first target sub-region, namely target sub-regions A1 to A32, does not overlap with the preset sub-regions located at the boundaries of the preset regions.

[0062] The first meteorological information for the target sub-region may include the wind speed of the target sub-region at time T. The second meteorological information for the preset sub-region may include the wind speed of the preset sub-region at time T.

[0063] Air pollutants can be any of the following: PM (Particulate Matter) 2.5 (particulate matter with a diameter of 2.5 micrometers or less), PM10 (particulate matter with a diameter of 10 micrometers or less), NO2 (nitrogen dioxide), SO2 (sulfur dioxide), CO (carbon monoxide), and O3 (ozone).

[0064] Step 12: Based on the first meteorological information and the first concentration information, determine the air pollutant concentration information of the second target sub-region at the first time point. The first time point includes every time point from T+1 to T+K.

[0065] Step 13: Determine the air pollutant concentration information of the first target sub-region at the first moment based on the second meteorological information and the second concentration information.

[0066] Among them, based on the first meteorological information and first concentration information of each of the N target sub-regions at time T, the second target sub-region (i.e., Figure 2 Air pollutant concentration information for the target sub-region (not filled in gray) at each time point from T+1 to T+K.

[0067] Based on the second meteorological information and second concentration information of each of the M preset sub-regions at time T, predict the first target sub-region (i.e., Figure 2 The air pollutant concentration information for each time period from time T+1 to time T+K in the target sub-regions A1 to A32 filled in gray.

[0068] Taking target sub-region A1 as an example, air pollutants outside the target region may transfer to target sub-region A1. Therefore, this disclosure takes into account that the first target sub-region is located at the boundary of the target region, and determines the air pollutant concentration information of the first target sub-region at the boundary by delineating a larger preset area.

[0069] The time interval between time T+1 and time T, as well as the time interval between any two adjacent first times, are preset time intervals. There is no limit to the length of the preset time intervals; they can be set as needed.

[0070] Step 14: Based on the air pollutant concentration information of the N target sub-regions at the first moment, determine the air pollutant monitoring stations from the N target sub-regions.

[0071] For example, air pollutant monitoring stations can be determined from N target sub-regions based on the amount of change in air pollutant concentration information in the target sub-regions and / or the total amount of air pollutant concentration information in the target sub-regions.

[0072] The above technical solution addresses the issue that determining the air pollutant concentration information of the first target sub-region at its boundary based solely on the first meteorological and first concentration information of the target sub-region would fail to account for the impact of air pollutants outside the target region on the boundary. Therefore, a pre-defined area is delineated around the target region. This pre-defined area is larger than and includes the target region, and there is no overlap between the first target sub-region and the pre-defined sub-region located at the boundary of the pre-defined area. In this way, determining the air pollutant concentration information of the first target sub-region at the first moment based on the second meteorological and second concentration information of the pre-defined sub-region allows for consideration of the impact of air pollutants outside the target region on the boundary. This makes the determined air pollutant concentration information of the first target sub-region more accurate, improving the accuracy and rationality of determining air pollutant monitoring stations from N target sub-regions.

[0073] First, we introduce the implementation method for determining the Markov matrix in this disclosure. The Markov matrix can also be called the Markov transition probability matrix or transition matrix. Figure 4 This is an exemplary schematic diagram illustrating the transfer of air pollutants. Figure 4 The grid regions 1 to 9 shown can represent the target sub-region and the preset sub-region. All grid regions 1 to 9 can be square grid regions. The first Markov matrix, the second Markov matrix, the third Markov matrix and the fourth Markov matrix mentioned below can be determined with reference to this implementation method.

[0074] like Figure 4As shown, since only air pollutants in the near-surface layer (i.e., layer=0) need to be considered when selecting the location of the monitoring station, the grid area can be simplified to a two-dimensional plane. The meteorological information of the grid area at time t can include the wind speed of each boundary of the grid area at time t. The wind speed can include the vector magnitude of the wind speed in the horizontal east-west direction and the vector magnitude of the wind speed in the horizontal north-south direction.

[0075] Figure 4 Taking grid region 5 as an example, the points on the four edges of grid region 5 are the boundary points of grid region 5. Taking boundary point a of grid region 5 as an example, based on the wind speed at boundary point a at time t, it can be determined that the air pollutants at boundary point a will be present after a preset time interval. The location subsequently moved to, such as Figure 4 As shown, for example, air pollutants at boundary point a pass through Then it moves to point b. Taking boundary point c of grid region 5 as an example, based on the wind speed at boundary point c at time t, it can be determined that the air pollutants at boundary point c pass through... The location subsequently moved to, such as Figure 4 As shown, for example, air pollutants at boundary point c pass through Then it moves to point d.

[0076] Wind speed is a vector, which can also represent the direction of the wind. The method of determining the direction and distance of air pollutant transfer based on wind speed can refer to relevant technologies. For example, the direction and distance of transfer can be determined based on wind speed, as well as the mass and transfer characteristics of air pollutants.

[0077] Air pollutants at other boundary points of grid area 5 after passing through The location to which it was subsequently moved can be referred to Figure 4 As shown by the solid gray dots, connecting the positions to which each boundary point has been transferred forms a transfer region. Figure 4 The region 5' formed by the line connecting the solid gray dots can be considered as the transfer region of grid region 5. This transfer region is a virtual region, representing the air pollutants in grid region 5 after passing through... The area subsequently transferred to.

[0078] Figure 5 This is a schematic diagram illustrating the area of ​​the transfer region as an example. For example... Figure 5 As shown, S represents the area of ​​region 5'. 52 S represents the area where region 5' overlaps with grid region 2. 53 S represents the area where region 5' overlaps with grid region 3. 55 S represents the area where region 5' overlaps with grid region 5. 56This represents the area where region 5' overlaps with grid region 6. . This can represent the probability that air pollutants in grid region 5 will transfer to grid region 2. This can represent the probability that air pollutants in grid region 5 will transfer to grid region 3. This can represent the probability that air pollutants in grid region 5 remain in grid region 5. This can represent the probability that air pollutants in grid region 5 will transfer to grid region 6. Furthermore, the probability that air pollutants in grid region 5 will transfer to grid regions 1, 4, 7, 8, or 9 can be 0.

[0079] Figure 4 and Figure 5 Using grid region 5 as an example, the probability calculation for other grid regions can be referenced from the example in grid region 5.

[0080] The element in the i-th row and j-th column of a Markov matrix , indicating that the air pollutants in the i-th grid area pass through The probability of moving to the j-th grid region. ,in, This represents the area where region i' overlaps with the j-th grid region. This represents the area of ​​region i', where region i' is the transition region of the i-th grid region.

[0081] Figure 6 This is a flowchart illustrating a method for determining the air pollutant concentration information of a second target sub-region at a first moment based on first meteorological information and first concentration information, as shown below. Figure 6 As shown, step 12 includes steps 121 to 128.

[0082] Step 121: Determine the first Markov matrix based on the first meteorological information.

[0083] The first Markov matrix has N rows and N columns. The element in the i-th row and j-th column of the first Markov matrix represents the probability that air pollutants from the i-th target sub-region will move to the j-th target sub-region after a preset time interval starting from time T. This can be expressed as shown in formula (1):

[0084] (1)

[0085] Step 122: Determine the air pollutant concentration information of the second target sub-region at time T+1 based on the first concentration information and the first Markov matrix.

[0086] The first concentration information of each of the N target sub-regions at time T can be formed into a matrix with one row and N columns. ,matrix The element in the first row and i-th column represents the first concentration information of the i-th target sub-region, and the matrix can be obtained by the following formula (2). :

[0087] (2)

[0088] Among them, matrix The matrix includes air pollutant concentration information for N target sub-regions at time T+1. The element in the first row and i-th column of the matrix represents the air pollutant concentration information of the i-th target sub-region at time T+1. From the matrix... The matrix provides information on air pollutant concentrations in each secondary target sub-region at time T+1. The air pollutant concentration information of the first target sub-region at time T+1 is not accurate enough because it does not take into account the influence of air pollutants outside the target region, and therefore it can not be used to determine the monitoring station.

[0089] Step 123: Determine whether the third meteorological information for each of the N target sub-regions at time T+1 has been obtained. If not, proceed to step 124; if yes, proceed to steps 125 and 126.

[0090] Step 124: Based on the first concentration information and the first Markov matrix, determine the air pollutant concentration information of the second target sub-region at time T+2.

[0091] Step 125: Determine the second Markov matrix based on the third meteorological information. The size of the second Markov matrix is ​​the same as that of the first Markov matrix.

[0092] Step 126: Determine the air pollutant concentration information of the second target sub-region at time T+2 based on the first concentration information, the first Markov matrix, and the second Markov matrix.

[0093] In this disclosure, considering that the target area is not a closed area like a room, but an open area, the meteorological information of the target area is not constant. In order to take into account the changing characteristics of the meteorological information of the target area, this disclosure can continuously update the meteorological information of the target sub-area. The update interval of the meteorological information of the target sub-area can be a preset time interval. It can also be greater than .

[0094] If third meteorological information is not obtained, it indicates that the meteorological information of the target sub-region was not updated at time T+1, and the first Markov matrix is ​​still used. The matrix can be obtained by performing calculations using the following formula (3). :

[0095] (3)

[0096] matrix It contains air pollutant concentration information for N target sub-regions at time T+2, from the matrix. The concentration information of air pollutants in each second target sub-region at time T+2 can be obtained.

[0097] If third meteorological information is obtained, a new Markov matrix is ​​determined, and based on the third meteorological information, a second Markov matrix is ​​determined. The method can be referred to the above description. Second Markov Matrix The number of rows and columns is N. The element in the i-th row and j-th column of the second Markov matrix represents the probability that air pollutants from the i-th target sub-region will transfer to the j-th target sub-region after a preset time interval starting from time T+1. If third meteorological information is obtained, the matrix can be obtained by the following formula (4). :

[0098] (4)

[0099] Step 127: Determine whether the air pollutant concentration information for the second target sub-region at time T+K has been obtained. If yes, end; otherwise, proceed to step 128.

[0100] Step 128: Set time T+2 as the new time T+1. Then, return to step 123.

[0101] Specifically, treating T+2 as the new T+1 can be understood as continuing the process of determining the air pollutant concentration information of the second target sub-region at T+3 based on whether the third meteorological information of each of the N target sub-regions at T+2 has been obtained. Increasing the time number by 1 can be understood as entering the next time moment, that is, continuing to determine the air pollutant concentration information of the second target sub-region at the next time moment, until the air pollutant concentration information of the second target sub-region at T+K is obtained.

[0102] With the above technical solution, the second target sub-region is not located at the boundary of the target region. Therefore, by combining the meteorological information and the first concentration information of the target sub-region, and considering the transfer characteristics of air pollutants between the various target sub-regions, that is, by combining the spatial distribution characteristics and transfer characteristics of air pollutants, the air pollutant concentration information of the second target sub-region at the first moment can be predicted. Furthermore, when the meteorological information of the target sub-region is updated, a new Markov matrix can be re-determined to participate in the prediction of air pollutant concentration information, which conforms to the changing characteristics of the meteorological information of the target region and can be applied to the processing of pollutant concentration information in open flow fields.

[0103] Figure 7 This is a flowchart illustrating a method for determining the air pollutant concentration information of a first target sub-region at a first moment based on second meteorological information and second concentration information, as shown below. Figure 7 As shown, step 13 includes steps 1301 to 1310.

[0104] Step 1301: Determine the third Markov matrix based on the second meteorological information.

[0105] The third Markov matrix has M rows and M columns. The element in the i-th row and j-th column of the third Markov matrix represents the probability that air pollutants in the i-th preset sub-region will move to the j-th preset sub-region after a preset time interval starting from time T. This can be represented as shown in formula (5):

[0106] (5)

[0107] Step 1302: Based on the second concentration information and the third Markov matrix, determine the air pollutant concentration information of M preset sub-regions at time T+1.

[0108] The second concentration information of each of the M preset sub-regions at time T can form a matrix with one row and M columns. ,matrix The element in the first row and i-th column represents the second concentration information of the i-th preset sub-region, and the matrix can be obtained by the following formula (6). :

[0109] (6)

[0110] Among them, matrix It includes air pollutant concentration information for M preset sub-regions at time T+1. Matrix The element in the first row and i-th column represents the air pollutant concentration information of the i-th preset sub-region at time T+1.

[0111] Step 1303: Based on the air pollutant concentration information of the first preset sub-region at time T+1, determine the air pollutant concentration information of the first target sub-region at time T+1. The first preset sub-region is the sub-region corresponding to the first target sub-region among M preset sub-regions.

[0112] Figure 8 Based on Figure 2 The target area shown and Figure 3 The diagram shown illustrates the relationship between the preset sub-region and the target sub-region. The first preset sub-region may be a preset sub-region that includes the first target sub-region. For example... Figure 8 As shown, taking target sub-regions A1 to A3, A10, and A12 as examples, the first preset sub-region corresponding to these first target sub-regions is preset sub-region B8. The first preset sub-regions corresponding to other first target sub-regions are similarly defined.

[0113] Step 1304: Determine whether the fourth meteorological information for each of the M preset sub-regions at time T+1 has been obtained. If not, proceed to step 1305; if yes, proceed to steps 1306 and 1307.

[0114] Step 1305: Based on the second concentration information and the third Markov matrix, determine the air pollutant concentration information of the M preset sub-regions at time T+2.

[0115] Step 1306: Based on the fourth meteorological information, determine the fourth Markov matrix. The size of the fourth Markov matrix is ​​the same as that of the third Markov matrix.

[0116] Step 1307: Based on the second concentration information, the third Markov matrix, and the fourth Markov matrix, determine the air pollutant concentration information of the M preset sub-regions at time T+2.

[0117] The updates of meteorological information in the target sub-region and the preset sub-region can be synchronized, or both can be predicted meteorological information output by the WRF (Weather Research and Forecasting) model.

[0118] If the fourth meteorological information is not obtained, it indicates that the meteorological information of the preset sub-region has not been updated at time T+1, and the third Markov matrix is ​​still used. The matrix can be obtained by performing calculations using the following formula (7). :

[0119] (7)

[0120] matrix It contains air pollutant concentration information for M preset sub-regions at time T+2.

[0121] If the fourth meteorological information is obtained, a new Markov matrix is ​​determined. Based on the fourth meteorological information, the fourth Markov matrix is ​​determined. The method can be referred to the above introduction. Fourth Markov Matrix The matrix has M rows and M columns. The element in the i-th row and j-th column of the fourth Markov matrix represents the probability that air pollutants from the i-th preset sub-region will transfer to the j-th preset sub-region after a preset time interval starting from time T+1. If the fourth meteorological information is obtained, the matrix can be obtained by the following formula (8). :

[0122] (8)

[0123] Step 1308: Determine the air pollutant concentration information of the first target sub-region at time T+2 based on the air pollutant concentration information of the first preset sub-region at time T+2.

[0124] Step 1309: Determine whether the air pollutant concentration information for the first target sub-region at time T+K has been obtained. If yes, end; otherwise, proceed to step 1310.

[0125] Step 1310: Set time T+2 as the new time T+1. Then, return to step 1304.

[0126] Similar to step 128, incrementing the time number by 1 can be understood as the next time, which means continuing to determine the air pollutant concentration information of the first target sub-region at the next time until the air pollutant concentration information of the first target sub-region at time T+K is obtained.

[0127] In one embodiment, to improve data computation efficiency, the side length of the preset sub-region can be greater than the side length of the target sub-region; that is, the preset sub-region can be a coarse grid, and the target sub-region can be a fine grid, thereby reducing the computational load for determining the air pollutant concentration information of each preset sub-region. The area of ​​the first preset sub-region can be greater than and include the area of ​​the first target sub-region.

[0128] In this disclosure, in steps 1303 and 1308, the air pollutant concentration information of the first target sub-region at the first moment can be determined based on the air pollutant concentration information of the first preset sub-region at the first moment in the following manner:

[0129] If the location of the first target sub-region corresponds to the first vertex of the first preset sub-region, then the average value of the air pollutant concentration information of the preset sub-region with the first vertex as the vertex at the first time moment will be used as the air pollutant concentration information of the first target sub-region at the first time moment.

[0130] like Figure 8 As shown, taking target sub-region A1 as an example, target sub-region A1 corresponds to the first vertex of the upper left corner of preset sub-region B8. The preset sub-regions with the vertex of the upper left corner of preset sub-region B8 as the vertex include preset sub-region B1, preset sub-region B2, preset sub-region B7 and preset sub-region B8. The average value of the air pollutant concentration information of these four preset sub-regions at the first moment can be used as the air pollutant concentration information of target sub-region A1 at the first moment.

[0131] The target sub-region A3 corresponds to the first vertex of the upper right corner of the preset sub-region B8. The preset sub-regions with the vertex of the upper right corner of the preset sub-region B8 as the vertex include preset sub-regions B2, B3, B8 and B9. The average value of the air pollutant concentration information of these four preset sub-regions at the first moment can be used as the air pollutant concentration information of the target sub-region A3 at the first moment.

[0132] Similarly, the average of the air pollutant concentration information of the preset sub-regions B7, B8, B13 and B14 at the first moment is used as the air pollutant concentration information of the target sub-region A12 at the first moment.

[0133] If the location of the first target sub-region corresponds to the first edge of the first preset sub-region, then the average value of the air pollutant concentration information of the preset sub-region with the first edge as the edge at the first time shall be used as the air pollutant concentration information of the first target sub-region at the first time.

[0134] Taking target sub-region A2 as an example, target sub-region A2 corresponds to the first edge line on the upper side of preset sub-region B8. The preset sub-regions with the first edge line as the edge line include preset sub-region B2 and preset sub-region B8. The average value of the air pollutant concentration information of these two preset sub-regions at the first moment can be used as the air pollutant concentration information of target sub-region A2 at the first moment.

[0135] Similarly, since the first edge of the left side of the target sub-region A10 corresponds to the preset sub-region B8, the average value of the air pollutant concentration information of the preset sub-regions B7 and B8 at the first moment can be used as the air pollutant concentration information of the target sub-region A10 at the first moment.

[0136] The determination of air pollutant concentration information for other first target sub-regions at the first moment can refer to the above example.

[0137] In addition, when both the target sub-region and the preset sub-region are square grid regions, the position of the first target sub-region corresponds to the vertex of the first preset sub-region. This can also be seen as the first target sub-region having two edges that overlap with the edge of the first preset sub-region. The position of the first target sub-region corresponds to the edge of the first preset sub-region. This can also be seen as the first target sub-region having one edge that overlaps with the edge of the first preset sub-region.

[0138] The above technical solution calculates the air pollutant concentration information of the first target sub-region based on a preset area, taking into account the impact of air pollutants outside the target area on the boundary, thus making the determined air pollutant concentration information of the first target sub-region more accurate. Furthermore, when the meteorological information of the preset sub-region is updated, a new Markov matrix can be re-determined for calculation, conforming to the changing characteristics of the meteorological information in the preset area.

[0139] In addition, the area of ​​the first preset sub-region can be the same as the area of ​​the first target sub-region, that is, the side length of the preset sub-region is the same as the side length of the target sub-region. In this embodiment, the air pollutant concentration information of the first preset sub-region at the first moment can be used as the air pollutant concentration information of the first target sub-region at the first moment.

[0140] In one embodiment, a preset time interval The time interval is less than or equal to the upper limit; the N target sub-regions are square grid regions with equal side lengths, and the upper limit of the time interval is obtained based on the side length and the historical average wind speed of the N target sub-regions.

[0141] Among them, the preset time interval The time step can be used as the time step in the Markov matrix solution process. The determination of the time step affects the accuracy of concentration prediction. If the time step is too long, after one time step, pollutants in the grid area will cross the surrounding grids to transfer to grid areas further away, which can easily cause prediction errors. Therefore, the upper limit of the time interval can be determined by the following formula (9). :

[0142] (9)

[0143] Where h represents the side length of the target sub-region. This represents the historical average wind speed of N target sub-regions. The historical period for which the average wind speed is used can be preset.

[0144] The preset time interval can be set manually, that is, set to a value less than or equal to the upper limit of the time interval.

[0145] Therefore, setting a reasonable preset time interval, which is the time step in the Markov matrix solution process, can reduce calculation errors and improve the accuracy of concentration information prediction.

[0146] In one embodiment, the method for determining the location of a monitoring station provided in this disclosure may further include:

[0147] Take time T+K+1 as the new time T, and repeat steps 11 to 13 until the first time includes the preset end time, then execute step 14.

[0148] The first and second meteorological information include wind speed in the horizontal direction, namely the vector magnitude of wind speed in the horizontal east-west direction and the vector magnitude of wind speed in the horizontal north-south direction. In addition to the horizontal diffusion of air pollutants, the chemical change process, deposition process and vertical change process of air pollutants also need to be considered.

[0149] Therefore, in this disclosure, the concentration information of air pollutants in the target sub-region and the concentration information of air pollutants in the preset sub-region can be continuously updated, for example, by using the concentration information of air pollutants predicted and output by the CMAQ (Community Multiscale Air Quality Modeling System) numerical air quality model.

[0150] The concentration information of air pollutants output by the numerical air quality model covers the effects of chemical changes, deposition processes, and vertical changes of air pollutants, thus contributing to the accuracy of air pollutant concentration prediction.

[0151] For example, the concentration information of air pollutants in the target sub-region at time T+K+1 is determined based on the chemical change process, sedimentation change process, and vertical change process of air pollutants in the target sub-region, and the concentration information of air pollutants in the preset sub-region at time T+K+1 is determined based on the chemical change process, sedimentation change process, and vertical change process of air pollutants in the preset sub-region.

[0152] Specifically, taking time T+K+1 as the new time T and re-executing steps 11 to 13 can be understood as, after obtaining the updated air pollutant concentration information of the target sub-region at time T+K+1, and the air pollutant concentration information of the preset sub-region at time T+K+1, continuing to determine the air pollutant concentration information of the target sub-region at time T+K+2 and multiple subsequent times. In this case, time T+K+2 and multiple subsequent times are taken as the new first time. This cycle of taking time T+K+1 as the new time T can be repeated multiple times. If the first time includes the preset end time, it can be considered that the prediction of air pollutant concentration information at each preset first time has been completed.

[0153] Taking the determination of air pollutant concentration information in the second target sub-region as an example, an embodiment will be used for explanation and illustration.

[0154] For time T, the first concentration information of each of the N target sub-regions at time T constitutes a matrix with one row and N columns. The first Markov matrix is ​​represented as .

[0155] For time T+1, through the matrix The air pollutant concentration information for the second target sub-region at time T+1 is obtained. .

[0156] For time T+2, through the matrix The air pollutant concentration information for the second target sub-region at time T+2 is obtained. .

[0157] For time T+3, through the matrix The air pollutant concentration information for the second target sub-region at time T+3 is obtained. .

[0158] Based on the meteorological information of each of the N target sub-regions at time T+3, the Markov matrix is ​​determined, represented as follows: .

[0159] For time T+4, through the matrix The air pollutant concentration information for the second target sub-region at time T+4 was obtained. .

[0160] For time T+5, through the matrix The air pollutant concentration information for the second target sub-region at time T+5 is obtained. .

[0161] For time T+6, through the matrix The air pollutant concentration information for the second target sub-region at time T+6 was obtained. .

[0162] At time T+7, the concentration information of air pollutants in N target sub-regions is updated, and the updated concentration information forms a matrix with one row and N columns. Furthermore, based on the meteorological information of each of the N target sub-regions at time T+7, the Markov matrix is ​​determined, represented as follows: .

[0163] For time T+8, through the matrix The concentration information of air pollutants in the second target sub-region at time T+8 was obtained. .

[0164] The concentration information of air pollutants in the second target sub-region at other times, as well as the concentration information of air pollutants in the first target sub-region, can be found in the above embodiments.

[0165] In one embodiment, the method for determining air pollutant monitoring stations from N target sub-regions based on their air pollutant concentration information at a first time step can be as follows:

[0166] Based on the air pollutant concentration information of N target sub-regions at the first moment, determine the change in air pollutant concentration of each of the N target sub-regions.

[0167] Based on the air pollutant concentration information of N target sub-regions at the first moment, determine the total air pollutant concentration of each of the N target sub-regions;

[0168] The monitoring sites are determined based on the change and / or the total amount.

[0169] Among them, with This represents the first concentration information of air pollutants in the m-th target sub-region at time T, in order to... This represents the air pollutant concentration information for the m-th target sub-region after k state transitions. This represents the change in air pollutant concentration in the m-th target sub-region after a total step size of n steps, expressed as... This represents the total concentration of air pollutants in the m-th target sub-region after a total of n steps. It can be determined using formula (10). It can be determined by formula (11) :

[0170] (10)

[0171] (11)

[0172] For example, the changes in air pollutant concentrations in each target sub-region can be sorted from largest to smallest, or the total air pollutant concentrations in each target sub-region can be sorted from largest to smallest. Alternatively, the results of a weighted sum of the changes and total concentrations can be sorted from largest to smallest. The target sub-regions that are ranked first by a predetermined number of positions in any sorting method are identified as monitoring stations.

[0173] The aforementioned k-step state transition can be understood as having gone through k preset time intervals, and the total number of n steps can be understood as having gone through a total of n preset time intervals.

[0174] This disclosure also provides an apparatus for determining the location of a monitoring station, the apparatus comprising:

[0175] A memory on which computer programs are stored;

[0176] A processor is configured to execute the computer program in the memory to implement the steps of the method for determining the location of a monitoring station provided in the above embodiments.

[0177] Figure 9 This is a block diagram illustrating an electronic device 1900 according to an exemplary embodiment. For example, the electronic device 1900 may be provided as a server. (Refer to...) Figure 9 The electronic device 1900 includes a processor 1922, which may be one or more, and a memory 1932 for storing computer programs executable by the processor 1922. The computer program stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processor 1922 may be configured to execute the computer program to perform the aforementioned method for determining the location of monitoring stations.

[0178] Additionally, the electronic device 1900 may also include a power supply component 1926 and a communication component 1950. The power supply component 1926 can be configured to perform power management of the electronic device 1900, and the communication component 1950 can be configured to enable communication of the electronic device 1900, such as wired or wireless communication. Furthermore, the electronic device 1900 may also include an input / output (I / O) interface 1958. The electronic device 1900 can operate on an operating system, such as Windows Server, stored in memory 1932. TM Mac OS X TM Unix TM Linux TM etc.

[0179] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the method for determining the location of a monitoring station described above. For example, the computer-readable storage medium may be the memory 1932 including the program instructions described above, which may be executed by the processor 1922 of the electronic device 1900 to complete the method for determining the location of a monitoring station described above.

[0180] In another exemplary embodiment, a computer program product is also provided, which includes a computer program executable by a processor, which, when executed by the processor, implements the steps of the method for determining the location of a monitoring station as described above.

[0181] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings. However, this disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of this disclosure, various simple modifications can be made to the technical solutions of this disclosure, and these simple modifications all fall within the protection scope of this disclosure.

[0182] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0183] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

Claims

1. A method for determining the location of a monitoring station, characterized in that, The method includes: Acquire first meteorological information and first concentration information of air pollutants for each of N target sub-regions at time T, and second meteorological information and second concentration information of air pollutants for each of M preset sub-regions at time T. The target region is divided into the N target sub-regions, and the preset region is divided into the M preset sub-regions. The range of the preset region is greater than and includes the range of the target region. There is no overlapping area between the first target sub-region and the preset sub-region located at the boundary of the preset region. The first target sub-region includes the target sub-region located at the boundary of the target region. Based on the first meteorological information and the first concentration information, the air pollutant concentration information of the second target sub-region at the first time is determined. The first time includes every time from time T+1 to time T+K. The second target sub-region includes the target sub-regions other than the first target sub-region in the target region. Based on the second meteorological information and the second concentration information, determine the air pollutant concentration information of the first target sub-region at the first time. Based on the air pollutant concentration information of the N target sub-regions at the first time, the monitoring stations for the air pollutants are determined from the N target sub-regions; The step of determining the air pollutant concentration information of the first target sub-region at the first time based on the second meteorological information and the second concentration information includes: Based on the second meteorological information, a third Markov matrix is ​​determined. The third Markov matrix has M rows and M columns. The element in the i-th row and j-th column of the third Markov matrix represents the probability that air pollutants in the i-th preset sub-region will transfer to the j-th preset sub-region after a preset time interval. The time interval between time T+1 and time T, as well as the time interval between each two adjacent first times, are the preset time intervals. Based on the second concentration information and the third Markov matrix, determine the air pollutant concentration information of the M preset sub-regions at time T+1; Based on the air pollutant concentration information of the first preset sub-region at time T+1, the air pollutant concentration information of the first target sub-region at time T+1 is determined. The first preset sub-region is the sub-region among the M preset sub-regions that corresponds to the first target sub-region. Based on whether the fourth meteorological information of each of the M preset sub-regions at time T+1 is obtained, the air pollutant concentration information of each of the M preset sub-regions at time T+2 is determined. Based on the air pollutant concentration information of the first preset sub-region at time T+2, determine the air pollutant concentration information of the first target sub-region at time T+2. Take time T+2 as the new time T+1, and return to the step of determining the air pollutant concentration information of the M preset sub-regions at time T+2 based on whether the fourth meteorological information of each of the M preset sub-regions at time T+1 is obtained, until the air pollutant concentration information of the first target sub-region at time T+K is obtained.

2. The method according to claim 1, characterized in that, The step of determining the air pollutant concentration information of the second target sub-region at a first moment based on the first meteorological information and the first concentration information includes: Based on the first meteorological information, a first Markov matrix is ​​determined. The first Markov matrix has N rows and N columns. The element in the i-th row and j-th column of the first Markov matrix represents the probability that air pollutants in the i-th target sub-region will transfer to the j-th target sub-region after a preset time interval. Based on the first concentration information and the first Markov matrix, determine the air pollutant concentration information of the second target sub-region at time T+1; Based on whether the third meteorological information of each of the N target sub-regions at time T+1 is obtained, the air pollutant concentration information of the second target sub-region at time T+2 is determined; Take time T+2 as the new time T+1, and return to the step of determining the air pollutant concentration information of the second target sub-region at time T+2 based on whether the third meteorological information of each of the N target sub-regions at time T+1 is obtained, until the air pollutant concentration information of the second target sub-region at time T+K is obtained.

3. The method according to claim 2, characterized in that, The step of determining the air pollutant concentration information of the second target sub-region at time T+2 based on whether the third meteorological information of each of the N target sub-regions at time T+1 is obtained includes: If the third meteorological information is not obtained, the air pollutant concentration information of the second target sub-region at time T+2 is determined based on the first concentration information and the first Markov matrix. If the third meteorological information is obtained, a second Markov matrix is ​​determined based on the third meteorological information. Based on the first concentration information, the first Markov matrix, and the second Markov matrix, the air pollutant concentration information of the second target sub-region at time T+2 is determined, wherein the size of the second Markov matrix is ​​the same as the size of the first Markov matrix.

4. The method according to claim 1, characterized in that, The step of determining the air pollutant concentration information of the M preset sub-regions at time T+2 based on whether the fourth meteorological information of each of the M preset sub-regions at time T+1 is obtained includes: If the fourth meteorological information is not obtained, then the air pollutant concentration information of the M preset sub-regions at time T+2 is determined according to the second concentration information and the third Markov matrix. If the fourth meteorological information is obtained, then a fourth Markov matrix is ​​determined based on the fourth meteorological information. Based on the second concentration information, the third Markov matrix, and the fourth Markov matrix, the air pollutant concentration information of the M preset sub-regions at time T+2 is determined, wherein the size of the fourth Markov matrix is ​​the same as the size of the third Markov matrix.

5. The method according to claim 1, characterized in that, The area of ​​the first preset sub-region is larger than and includes the area of ​​the first target sub-region; The air pollutant concentration information of the first target sub-region at the first time time is determined based on the air pollutant concentration information of the first preset sub-region at the first time time in the following manner: If the position of the first target sub-region corresponds to the first vertex of the first preset sub-region, then the average value of the air pollutant concentration information of the preset sub-region with the first vertex as the vertex at the first time shall be used as the air pollutant concentration information of the first target sub-region at the first time. If the position of the first target sub-region corresponds to the first edge of the first preset sub-region, then the average value of the air pollutant concentration information of the preset sub-region with the first edge as the edge at the first time shall be used as the air pollutant concentration information of the first target sub-region at the first time.

6. The method according to claim 1, characterized in that, The time interval between time T+1 and time T, as well as the time interval between any two adjacent first times, are all preset time intervals, and the preset time intervals are less than or equal to the upper limit of the time interval. The N target sub-regions are square grid regions with equal side lengths, and the upper limit of the time interval is obtained based on the side length and the historical average wind speed of the N target sub-regions.

7. The method according to claim 1, characterized in that, The method further includes: Taking time T+K+1 as the new time T, the steps of obtaining the first meteorological information and the first concentration information of air pollutants for each of the N target sub-regions at time T, and the second meteorological information and the second concentration information of air pollutants for each of the M preset sub-regions at time T, are repeated until the step of determining the air pollutant concentration information of the first target sub-region at the first time based on the second meteorological information and the second concentration information is performed, until the first time includes the preset end time, and the air pollutant monitoring station is determined from the N target sub-regions based on the air pollutant concentration information of the N target sub-regions at the first time. Wherein, the first meteorological information and the second meteorological information include wind speed in the horizontal direction, the concentration information of air pollutants in the target sub-region at time T+K+1 is determined based on the chemical change process, deposition change process and vertical change process of the air pollutants in the target sub-region, and the concentration information of air pollutants in the preset sub-region at time T+K+1 is determined based on the chemical change process, deposition change process and vertical change process of the air pollutants in the preset sub-region.

8. A device for determining the location of a monitoring station, characterized in that, The device includes: A memory on which computer programs are stored; A processor for executing the computer program in the memory to implement the steps of the method according to any one of claims 1 to 7.

9. An electronic device, characterized in that, Includes the apparatus for determining the location of monitoring stations as described in claim 8.

Images