CN109345004B - Air pollutant data acquisition method based on hot spot grid - Google Patents
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Abstract
The invention relates to an air pollutant data acquisition method based on a hot spot grid, which comprises the following steps: acquiring first air pollutant concentration data of a plurality of first hotspot grids; generating a ranked list of a plurality of first air pollutant concentration data from high to low according to concentration; selecting second air contaminant concentration data for a plurality of second hotspot grids in the ordered list; collecting a plurality of air pollutant data samples by using monitoring equipment in the area corresponding to each second hot spot grid; dividing each second hotspot grid into a plurality of third hotspot grids; performing interpolation calculation according to the air pollutant data samples to obtain third pollutant concentration data of all third hot spot grids; calculating an average of all third contaminant concentration data within the second hotspot grid; the concentration data of each third pollutant is differed from the average value to obtain a compensation value; and carrying out compensation processing on the third pollutant concentration data according to the compensation value to obtain fourth pollutant concentration data.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an air pollutant data acquisition method based on a hot spot grid.
Background
In 2016, the Ministry of environmental protection cooperates with scientific and technological enterprises to divide the Beijing Ji and the surrounding key areas of "2+26" cities (2 refers to Beijing city and Tianjin city, 26 refers to Hebei Jizhuang, tangshan, baoding, jifang, cangzhou, heshui, zhuang, chen, shanxi Taiyuan, yangquan, changzhi, jincheng, shandong Jinan, bobo, chacheng, texas, binzhou, jining, ganzze, henan Zheng, new county, henan Jibi, anyang, jiang, puyang and Kakai 26 cities) into grids according to 3km×3km, and 36793 in total. And according to the divided grids, encrypting and distributing the atmospheric monitoring points. The hot spot grids with higher air pollution degree are regularly screened out through big data and sent to relevant local governments and environmental protection departments, so that accurate law enforcement is promoted to be implemented.
The hot spot grid focuses on pollution control of 2+26 cities nationwide, and places the pollution control on 36793 grids divided by 3km multiplied by 3km, so that one-step focusing on pollution is realized. However, 3km×3km is still not fine enough for a micro-environment.
Thus, there is a need for a finer grained atmosphere pollution monitoring solution.
Disclosure of Invention
The invention aims at overcoming the defects in the prior art and provides an air pollutant data acquisition method based on a hot spot grid.
To achieve the above object, in a first aspect, the present invention provides an air pollutant data acquisition method based on a hotspot grid, including:
acquiring first air pollutant concentration data of a plurality of first hot spot grids in a preset time period;
sequencing a plurality of first air pollutant concentration data according to the concentration from high to low to generate a sequencing list;
selecting second air pollutant concentration data of a plurality of second hot spot grids with preset proportions from the ordered list;
collecting a plurality of air pollutant data samples in the area corresponding to each second hot spot grid by using monitoring equipment;
dividing each second hot spot grid according to a preset mode to obtain a plurality of corresponding third hot spot grids;
performing interpolation calculation according to the air pollutant data samples to obtain third pollutant concentration data of all third hot spot grids;
calculating an average of all of the third contaminant concentration data within the second hotspot grid;
each third pollutant concentration data is subjected to difference with the average value, and a compensation value of the third pollutant concentration data is obtained;
and carrying out compensation processing on the third pollutant concentration data according to the compensation value to obtain fourth pollutant concentration data.
Further, the collecting, by using a monitoring device, a plurality of air pollutant data samples in the area corresponding to each of the second hotspot grids specifically includes:
and moving and collecting a plurality of air pollutant data samples in the area corresponding to each second hot spot grid according to a spiral route by using monitoring equipment.
Further, the dividing each second hotspot grid according to a preset manner to obtain a plurality of corresponding third hotspot grids specifically includes:
dividing each second hot spot grid into a plurality of third hot spot grids according to the hundred-meter level.
Further, performing interpolation calculation according to the air pollutant data samples to obtain third pollutant concentration data of all third hotspot grids specifically includes:
acquiring sample pollutant concentration data corresponding to the air pollutant data sample;
and performing interpolation calculation on the sample pollutant concentration data by using a Kriging interpolation method to obtain third pollutant concentration data of all third hot spot grids.
Further, the compensating the third pollutant concentration data according to the compensation value to obtain fourth pollutant concentration data specifically includes:
and adding the corresponding compensation value to the third pollutant concentration data to obtain the four pollutant concentration data.
Further, before acquiring the first air pollutant concentration data of the plurality of first hotspot grids in the preset time period, the method further includes:
and equally dividing the monitoring area into a plurality of first hot spot grids according to a preset size.
Further, the acquiring the first air pollutant concentration data of the plurality of first hotspot grids within the preset time period specifically includes:
and calculating the annual average PM2.5 concentration of the areas corresponding to the first hot spot grids according to the satellite remote sensing data, the air quality ground observation data and the meteorological observation data.
In a second aspect, the present invention provides an apparatus comprising a memory for storing a program and a processor for performing the method of the first aspect and various implementations of the first aspect.
In a third aspect, the present invention provides a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of the first aspect and the various implementations of the first aspect.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of the first aspect and the various implementations of the first aspect.
According to the air pollutant data acquisition method based on the hot spot grids, a part of second hot spot grids with higher air pollutant concentration are extracted from the first hot spot grids, a plurality of air pollutant data samples are acquired by using monitoring equipment in the area corresponding to each second hot spot grid, each second hot spot grid is further divided into a plurality of third hot spot grids, interpolation and compensation are carried out on the air pollutant concentration in the third hot spot grids according to the acquired air pollutant data samples, and therefore air pollutant concentration data of the area corresponding to all the third hot spot grids are obtained. According to the method provided by the invention, the pollution distribution in the focus hot spot grid with finer granularity is further focused by further dividing the hot spot grid and interpolating and compensating, so that the pollution monitoring is more targeted.
Drawings
FIG. 1 is a flowchart of a method for acquiring air pollutant data based on a hot spot grid according to an embodiment of the present invention;
FIG. 2 is a diagram of a mobile data acquisition path provided in accordance with a first embodiment of the present invention;
fig. 3 is a schematic diagram of a distribution of variance of a half-variance function according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Fig. 1 is a flowchart of a method for acquiring air pollutant data based on a hotspot grid according to an embodiment of the present invention. As shown in fig. 1, the method specifically comprises the following steps:
step 101, acquiring first air pollutant concentration data of a plurality of first hot spot grids in a preset time period.
Before step 101, the monitoring area is divided into a plurality of first hotspot grids according to a preset size. The hot spot grid is used for dividing the pollution monitoring area into a plurality of grids, so that accurate monitoring is facilitated. For example, the city of jingjin and the surrounding key areas "2+26" (2 means beijing and Tianjin, 26 means Hebei province stone house, tangshan, baoding, gallery, cang state, heshui, kan tai, shanxi province taiyuan, yangquan, chang, jin city, shandong province jinan, zibo, chat city, texas, coast state, jining, joze, henan province Zheng, new country, crane wall, an yang, coke, puyang, and unsealed 26 cities) are meshed according to 3km×3km, and 36793 total.
The first hotspot grid is to extract a part or all of the hotspot grids from the divided hotspot grids, for example, 10 hotspot grids with the highest PM2.5 concentration in each city are screened out from the '2+26' cities to be taken as the first hotspot grid, and 280 hotspot grids are taken as the first hotspot grid. And encoding each hot spot grid, wherein each hot spot grid code uniquely corresponds to one divided monitoring area unit. Historical monitoring data of first air pollutant concentration of a region corresponding to the first hot spot grid is obtained. For example, annual average PM2.5 concentration of the region corresponding to the plurality of first hotspot grids is calculated according to satellite remote sensing data, air quality ground observation data and meteorological observation data. The pollutant concentration data can be obtained through monitoring equipment, and can also be obtained from a public database, and the first air pollutant can be specifically all pollutants which can be discharged into the air to cause air pollution, and can be PM2.5, PM10 and the like. The preset time period is a historical time which can be selected according to specific needs, for example, an average value of the PM2.5 concentration of the corresponding areas of the first hotspot grids in the past year is obtained.
Step 102, sorting the plurality of first air pollutant concentration data according to the concentration from high to low to generate a sorted list.
Specifically, the air pollutant concentrations of the monitoring areas corresponding to the selected plurality of first hotspot grids are ordered according to the order of the concentrations from high to low, for example, the area codes corresponding to the hotspot grids and the annual average PM2.5 concentrations are A1/b1, A2/b2, A3/b3, A4/b4 and A5/b5 respectively, wherein the annual average PM2.5 concentration b5 > b4 > b3 > b2 > b1, and the generated ordered list is shown in table 1:
TABLE 1
Step 103, selecting second air pollutant concentration data of a plurality of second hot spot grids with preset proportions in the ordered list.
And selecting a part of key hot spot grids with the top pollutant concentration rank from the ranked first hot spot grids as second hot spot grids, for example, selecting the first hot spot grid with the top pollutant concentration rank of 20% as the second hot spot grid according to the 'twenty-eight principle'. The preset ratio is not limited thereto, and may be set according to specific needs.
And 104, acquiring a plurality of air pollutant data samples by using the monitoring equipment in the area corresponding to each second hot spot grid.
Specifically, the monitoring device is carried, and for each area corresponding to the second hot spot grid of 3km×3km, a plurality of air pollutant data samples are collected along the spiral moving route shown in fig. 2, and each line is spaced by 100 meters.
And 105, dividing each second hot spot grid according to a preset mode to obtain a plurality of corresponding third hot spot grids.
Specifically, each second hotspot grid is divided into a plurality of third hotspot grids with dimensions of 100 meters×100 meters. The purpose of dividing the second hot spot grid into a plurality of third hot spot grids in a finer manner is to accurately position the pollution monitoring area, so that pollution monitoring is performed more effectively.
The specific division mode and the specific division size for dividing the second hot spot grid into the third hot spot grid can be determined according to the existing monitoring conditions of manpower and material resources.
And 106, carrying out interpolation calculation according to the air pollutant data samples to obtain third pollutant concentration data of all third hot spot grids.
Specifically, calculating corresponding sample pollutant concentration data according to the acquired air pollutant data sample; and performing interpolation calculation on the sample pollutant concentration data by using a Kriging interpolation method to obtain third pollutant concentration data of all third hot spot grids.
Performing Kriging interpolation in a third hotspot grid after the second hotspot grid is thinned, starting with a graph of an empirical half-variation function in the spatial modeling of the monitoring point structure, and for all position pairs separated by a distance h, knowing the half-variation function of the monitoring point as follows:
Semivariogram(distance h)＝0.5*average((value i –value j ) 2 )(i、j＝1，2，…，n)
by analyzing the distribution characteristics of the variance of the semi-variation function, as shown in fig. 3, an exponential model is used to fit, and an exponential equation S (h) is obtained as in equation (1).
Wherein c is a base station value, a is a variation, and h is a hysteresis distance.
The contaminant concentration data for each unknown grid is calculated using equation (2).
Wherein Z (x) i ) Is the concentration of the contaminant in the region corresponding to the known grid point, Z (x 0 ) Is the unknown point x 0 And finally obtaining the pollutant concentration data of the corresponding areas of all the third hot spot grids. Lambda (lambda) i For the undetermined weight coefficients, Z (x) i ) There is a certain correlation between them, and this correlation is related to the distance and the relative direction change, and can obtain undetermined weight coefficient lambda for unbiased and minimum variance condition of Kerling method i Satisfy formula (3);
on the premise of unbiased, the Crigy variance is the minimum to obtain the undetermined weight coefficient lambda i Formula (4) of (2);
wherein C (x) i ,x j ) Is Z (x) i ) And Z (x) j ) And μ is a determined trend value.
At step 107, an average of all third contaminant concentration data within the second hotspot grid is calculated.
For example, from 10 interpolation results within the second hotspot grid: c1, c2, c3, c4, c5, c6, c7, c8, c9, c10, the average value is calculated as
Step 108, the third pollutant concentration data are each different from the average value, and a compensation value of the third pollutant concentration data is obtained.
As an example in step 107, 10 interpolation results within the second hotspot grid: the compensation values corresponding to c1, c2, c3, c4, c5, c6, c7, c8, c9 and c10 are in turn
And step 109, performing compensation processing on the third pollutant concentration data according to the compensation value to obtain fourth pollutant concentration data.
Specifically, according to the third pollutant concentration data, the interpolation points in each third hot spot grid are translated, and the compensation value is added, so that a compensated interpolation result is obtained, and the fourth pollutant concentration data is the pollutant concentration data after compensation.
According to the technical scheme, the pollutant concentration data of all finer areas after the corresponding areas of the 3km multiplied by 3km hot spot grids are subdivided are obtained, so that a user can be assisted in searching a pollutant source according to the pollutant concentration data, and the problem related to pollutant emission is solved.
According to the air pollutant data acquisition method based on the hot spot grids, a part of second hot spot grids with higher air pollutant concentration are extracted from the first hot spot grids, a plurality of air pollutant data samples are acquired by using monitoring equipment in the area corresponding to each second hot spot grid, each second hot spot grid is further divided into a plurality of third hot spot grids, interpolation and compensation are carried out on the air pollutant concentration in the third hot spot grids according to the acquired air pollutant data samples, and therefore air pollutant concentration data of the area corresponding to all the third hot spot grids are obtained. According to the method provided by the invention, the pollution distribution in the focus hot spot grid with finer granularity is further focused by further dividing the hot spot grid and interpolating and compensating, so that the pollution monitoring is more targeted.
The second embodiment of the invention provides a device, which comprises a memory and a processor, wherein the memory is used for storing programs, and the memory can be connected with the processor through a bus. The memory may be non-volatile memory, such as a hard disk drive and flash memory, in which software programs and device drivers are stored. The software program can execute various functions of the method provided by the embodiment of the invention; the device driver may be a network and interface driver. The processor is configured to execute a software program, where the software program is executed to implement the method provided by the embodiment of the present invention.
A third embodiment of the present invention provides a computer program product containing instructions, which when executed on a computer, cause the computer to perform the method provided by the first embodiment of the present invention.
The fourth embodiment of the present invention provides a computer readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the method provided in the first embodiment of the present invention is implemented.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of function in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (8)
1. An air pollutant data acquisition method based on a hotspot grid, which is characterized by comprising the following steps:
acquiring first air pollutant concentration data of a plurality of first hot spot grids in a preset time period;
sequencing a plurality of first air pollutant concentration data according to the concentration from high to low to generate a sequencing list;
selecting second air pollutant concentration data of a plurality of second hot spot grids with preset proportions from the ordered list;
collecting a plurality of air pollutant data samples in the area corresponding to each second hot spot grid by using monitoring equipment;
dividing each second hot spot grid according to a preset mode to obtain a plurality of corresponding third hot spot grids, wherein the method specifically comprises the following steps:
dividing each second hot spot grid into a plurality of third hot spot grids according to hundred-meter levels;
performing interpolation calculation according to the air pollutant data samples to obtain third pollutant concentration data of all third hot spot grids;
calculating an average of all of the third contaminant concentration data within the second hotspot grid; each third pollutant concentration data is subjected to difference with the average value, and a compensation value of the third pollutant concentration data is obtained;
and carrying out compensation processing on the third pollutant concentration data according to the compensation value to obtain fourth pollutant concentration data, wherein the method specifically comprises the following steps of:
and translating interpolation points in each third hot spot grid, adding the corresponding compensation value to the third pollutant concentration data to obtain a compensated interpolation result, wherein the fourth pollutant concentration data is the pollutant concentration data after compensation.
2. The method according to claim 1, wherein the collecting a plurality of air contaminant data samples with the monitoring device in the area corresponding to each of the second hotspot grids specifically comprises:
and moving and collecting a plurality of air pollutant data samples in the area corresponding to each second hot spot grid according to a spiral route by using monitoring equipment.
3. The method of claim 1, wherein the interpolating according to the air contaminant data samples to obtain third contaminant concentration data of all third hotspot grids specifically includes:
acquiring sample pollutant concentration data corresponding to the air pollutant data sample; and performing interpolation calculation on the sample pollutant concentration data by using a Kriging interpolation method to obtain third pollutant concentration data of all third hot spot grids.
4. The method of claim 1, wherein prior to acquiring the first air contaminant concentration data for the plurality of first hotspot grids over the preset time period, the method further comprises:
and equally dividing the monitoring area into a plurality of first hot spot grids according to a preset size.
5. The method of claim 1, wherein the acquiring the first air contaminant concentration data of the plurality of first hotspot grids within the preset time period specifically comprises:
and calculating the annual average PM2.5 concentration of the areas corresponding to the first hot spot grids according to the satellite remote sensing data, the air quality ground observation data and the meteorological observation data.
6. An apparatus comprising a memory for storing a program and a processor for performing the method of any of claims 1-5.
7. A computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of any of claims 1-5.
8. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the method according to any of claims 1-5.
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