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Regional PM2.5 remote sensing inversion model fusing fine particulate matter concentration data

A PM2.5, remote sensing inversion technology, applied in particle suspension analysis, measurement device, suspension and porous material analysis, etc., can solve the problem of limiting the accuracy of the estimation model, and achieve the effect of accurate product data and overcoming dispersion.

Active Publication Date: 2020-06-23
CENT SOUTH UNIV
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Problems solved by technology

However, there is a large uncertainty in the relationship between the above factors and the concentration of ground particulate matter, which will limit the accuracy of the estimation model. Therefore, a solution with better performance and better accuracy is needed in the prior art to solve this problem. question

Method used

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  • Regional PM2.5 remote sensing inversion model fusing fine particulate matter concentration data
  • Regional PM2.5 remote sensing inversion model fusing fine particulate matter concentration data
  • Regional PM2.5 remote sensing inversion model fusing fine particulate matter concentration data

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Embodiment Construction

[0038] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but the present invention can be implemented in various ways defined and covered by the claims.

[0039] Such as figure 1 The regional PM2.5 remote sensing inversion model fused with fine particle concentration data shown is obtained through the following steps S1-S3,

[0040] S1. Select PM2.5 product data with the same time resolution as Himawari-8 / AHI aerosol optical depth data from MASINGAR’s PM2.5 products, and interpolate the selected MASINGAR’s PM2.5 product data to the Himawari-8 / AHI aerosol optical depth data. 8 / AHI aerosol optical depth data have the same spatial resolution; select the topographic factor data of the observation area, and interpolate the data to have the same spatial resolution as the Himawari-8 / AHI aerosol optical depth data; select from ERA5 products Meteorological analysis data within the observation area; select NDVI produ...

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Abstract

The invention provides a regional PM2.5 remote sensing inversion model fusing fine particulate matter concentration data. PM2.5 product data of MASINGAR is introduced into an existing basic model to serve as a newly added prediction factor; space-time matching is performed on the newly added prediction factor, the prediction factor in the basic model and the foundation observation data; a linear regression coefficient of each prediction factor including the increased prediction factor is calculated in combination with ground observation data; an improved model which is simultaneously associated with the prediction factor of the basic model and PM2.5 product data of MASINGAR is established by using the calculated linear regression coefficient; the improved model is used for estimating the PM2.5 concentration of the earth surface, PM2.5 concentration data obtained through calculation is more accurate than concentration data obtained only based on a basic model and is also more accurate than PM2.5 product data of MASINGAR additionally referenced, and the defects that foundation observation data is scattered and discontinuous are overcome.

Description

technical field [0001] The invention relates to the technical field of atmospheric environment monitoring, in particular to a regional PM2.5 remote sensing inversion model fused with fine particle concentration data. Background technique [0002] PM2.5 generally refers to particulate matter suspended in the air with an aerodynamic equivalent diameter of less than or equal to 2.5, also known as fine particulate matter. Although PM2.5 is only a small component of the earth’s atmospheric composition, it is harmful to human health and Air quality has an important impact. Compared with coarse atmospheric particulate matter, PM2.5 has a small particle size, strong activity, is easy to attach toxic and harmful substances, and stays in the atmosphere for a long time, so it has a greater impact on human health and the quality of the atmospheric environment. PM2.5 can directly affect visibility, and visibility directly affects urban traffic, and in severe cases, it will cause traffic...

Claims

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Application Information

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IPC IPC(8): G01N15/06G01W1/10
CPCG01N15/06G01W1/10
Inventor 王威张仪潇
Owner CENT SOUTH UNIV
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