CN112525787A - Method for inverting PM2.5 all-weather fine grid data based on surface high-density meteorological data - Google Patents
Method for inverting PM2.5 all-weather fine grid data based on surface high-density meteorological data Download PDFInfo
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Abstract
The invention discloses a method for inverting PM2.5 all-weather fine grid data based on surface high-density meteorological data, which utilizes high-density surface visibility and relative humidity meteorological observation data to construct ground PM2.5 all-weather time-by-time high-resolution grid data.
Description
Technical Field
The invention relates to a method for inverting PM2.5 all-weather fine grid data based on surface high-density meteorological data.
Background
The ground PM2.5 monitoring is limited to equipment and operation and maintenance cost, the number of sites is limited, the space distribution is uneven (the urban area is many and suburbs are few), how to acquire all-weather time-by-time fine grid PM2.5 data makes up the problem that the sites are rare or even blank in the suburbs in remote areas is always a hot scientific problem concerned by the academic community, and the method is also an urgent demand for air quality evaluation, PM2.5 human health influence research, air pollution treatment decision and the like; the general spatial interpolation algorithm is limited in that the error is large in a region with rare sites. The academic world provides a plurality of algorithms for fusing earth surface data and performing satellite remote sensing (AOD) inversion to obtain earth surface refined PM2.5, and the effects are good. The algorithm is limited in that satellite remote sensing AOD data are only 1-2 times per day, even existing high-resolution stationary satellites monitor time by time, the PM2.5 on the earth surface can not be monitored when clouds exist, and the cloud interference problem is particularly serious in southern areas. It is necessary to find a method for inverting ground PM2.5 time-by-time fine grid data, which does not depend on remote sensing data and has available precision quality.
The current automatic meteorological station is fast in construction and development, the ground visibility and relative humidity observation station point density which are closely related to PM2.5 are more than 10 times higher than that of the PM2.5 station point, and therefore a feasible basis is provided for establishing a method which only depends on high-density ground observation data.
Disclosure of Invention
According to the method, the ground PM2.5 all-weather time-by-time high-resolution grid data are constructed by utilizing meteorological observation data of high-density earth surface visibility and relative humidity, the problem that the conventional interpolation method has a large error in a rare area of a site is solved, and the problem of data loss caused by cloud interference based on a remote sensing method is also solved.
The technical scheme provided by the invention specifically comprises the following steps:
a method for inverting PM2.5 all-weather fine grid data based on surface high-density meteorological data comprises the following steps:
(1) calculating surface extinction delta from time-to-time or day-to-day visibility (V/km) data of a ground meteorological station in a target area, and performing spatial interpolation by adopting an inverse distance method to obtain delta lattice point data of a target resolution;
(2) performing spatial interpolation on the relative humidity (RH/%) data of the earth surface weather station time by time or day by adopting an inverse distance method to obtain RH lattice point data of a target resolution;
(3) according to PM2.5 observation stations in the target area, matching delta and RH data of corresponding positions, fitting an equation (1) one by one to obtain K and gamma parameters of each station;
RH in formula (1)0Taking 40% and delta being 3.912/V;
(4) adopting inverse distance spatial interpolation to obtain K and gamma lattice point data of target resolution for K and gamma parameters of PM2.5 observation stations in the region;
(5) the obtained K, gamma, delta and RH lattice point data are substituted for the formula (1) to obtain PM2.5 lattice point data with the target resolution.
As an improvement, the visibility data in the step (1) is collected from national stations and regional stations.
The invention has the following advantages: according to the method, the meteorological observation data of high-density earth surface visibility and relative humidity are utilized, the problem of data loss caused by cloud interference based on a remote sensing AOD method is solved, and all-weather time-by-time fine grid data of ground PM2.5 are constructed.
The beneficial effects include: (1) the method is beneficial to improving the capability of an air quality numerical prediction mode; (2) the PM2.5 evaluation precision level of the environmental air quality is improved, more accurate decision reference is provided for the government department to make an accurate atmospheric pollution control strategy, and the method has remarkable social and ecological benefits. (3) And key data support is provided for developing PM2.5 human health influence research.
Drawings
Fig. 1 is a schematic structural view of the present invention.
Detailed Description
With the combination of the attached drawings, the method for inverting PM2.5 all-weather fine grid data based on surface high-density meteorological data is characterized by comprising the following steps:
(1) calculating surface extinction delta from time-to-time or day-to-day visibility (V/km) data of a ground meteorological station in a target area, and performing spatial interpolation by adopting an inverse distance method to obtain delta lattice point data of a target resolution;
(2) performing spatial interpolation on the relative humidity (RH/%) data of the earth surface weather station time by time or day by adopting an inverse distance method to obtain RH lattice point data of a target resolution;
(3) according to PM2.5 observation stations in the target area, matching delta and RH data of corresponding positions, fitting an equation (1) one by one to obtain K and gamma parameters of each station;
RH in formula (1)0Taking 40% and delta being 3.912/V;
(4) adopting inverse distance spatial interpolation to obtain K and gamma lattice point data of target resolution for K and gamma parameters of PM2.5 observation stations in the region;
(5) the obtained K, gamma, delta and RH lattice point data are substituted for the formula (1) to obtain PM2.5 lattice point data with the target resolution.
The visibility data in the step (1) is collected from national stations and regional stations.
The present invention and its embodiments have been described above, and the description is not intended to be limiting, and the drawings are only one embodiment of the present invention, and the actual structure is not limited thereto. In summary, those skilled in the art should appreciate that they can readily use the disclosed conception and specific embodiments as a basis for designing or modifying other structures for carrying out the same purposes of the present invention without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (2)
1. The method for inverting PM2.5 all-weather fine grid data based on the surface high-density meteorological data is characterized by comprising the following steps:
(1) calculating surface extinction delta from time-to-time or day-to-day visibility (V/km) data of a ground meteorological station in a target area, and performing spatial interpolation by adopting an inverse distance method to obtain delta lattice point data of a target resolution;
(2) performing spatial interpolation on the relative humidity (RH/%) data of the earth surface weather station time by time or day by adopting an inverse distance method to obtain RH lattice point data of a target resolution;
(3) according to PM2.5 observation stations in the target area, matching delta and RH data of corresponding positions, fitting an equation (1) one by one to obtain K and gamma parameters of each station;
RH in formula (1)0Taking 40% and delta being 3.912/V;
(4) adopting inverse distance spatial interpolation to obtain K and gamma lattice point data of target resolution for K and gamma parameters of PM2.5 observation stations in the region;
(5) the obtained K, gamma, delta and RH lattice point data are substituted for the formula (1) to obtain PM2.5 lattice point data with the target resolution.
2. The method for inverting PM2.5 all-weather fine grid data based on surface high-density meteorological data as claimed in claim 1, wherein the visibility data in the step (1) is collected from national stations and regional stations.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113111309A (en) * | 2021-03-25 | 2021-07-13 | 中国气象局广州热带海洋气象研究所（广东省气象科学研究所） | Method for evaluating influence of artificial and meteorological factors on concentration of atmospheric pollutants |
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| CN101504353A (en) * | 2008-02-06 | 2009-08-12 | 香港科技大学 | Method and system for providing near ground suspending particulate distribution |
| CN103942439A (en) * | 2014-04-24 | 2014-07-23 | 中国科学院遥感与数字地球研究所 | Inhalable particle concentration estimating method based on meteorological observation data |
| CN108426815A (en) * | 2018-04-20 | 2018-08-21 | 中国科学院遥感与数字地球研究所 | A kind of fine particle concentration of component evaluation method near the ground |
| CN111912754A (en) * | 2020-07-23 | 2020-11-10 | 安徽省气象科学研究所 | Remote sensing inversion method for near-surface particulate matter concentration |
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Patent Citations (4)
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| CN101504353A (en) * | 2008-02-06 | 2009-08-12 | 香港科技大学 | Method and system for providing near ground suspending particulate distribution |
| CN103942439A (en) * | 2014-04-24 | 2014-07-23 | 中国科学院遥感与数字地球研究所 | Inhalable particle concentration estimating method based on meteorological observation data |
| CN108426815A (en) * | 2018-04-20 | 2018-08-21 | 中国科学院遥感与数字地球研究所 | A kind of fine particle concentration of component evaluation method near the ground |
| CN111912754A (en) * | 2020-07-23 | 2020-11-10 | 安徽省气象科学研究所 | Remote sensing inversion method for near-surface particulate matter concentration |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113111309A (en) * | 2021-03-25 | 2021-07-13 | 中国气象局广州热带海洋气象研究所（广东省气象科学研究所） | Method for evaluating influence of artificial and meteorological factors on concentration of atmospheric pollutants |
| CN113111309B (en) * | 2021-03-25 | 2022-10-14 | 中国气象局广州热带海洋气象研究所（广东省气象科学研究所） | Method for evaluating influence of artificial and meteorological factors on concentration of atmospheric pollutants |
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