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Regional PM2.5 Remote Sensing Retrieval Model Fused with Fine Particle Concentration Data

A PM2.5, remote sensing inversion technology, applied in particle suspension analysis, suspension and porous material analysis, meteorology, etc., can solve problems such as limiting the accuracy of estimation models, achieve accurate product data, and overcome dispersion effects

Active Publication Date: 2021-08-24
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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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 Retrieval Model Fused with Fine Particle Concentration Data
  • Regional PM2.5 Remote Sensing Retrieval Model Fused with Fine Particle Concentration Data
  • Regional PM2.5 Remote Sensing Retrieval Model Fused with Fine Particle 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 present invention provides a regional PM2.5 remote sensing inversion model that integrates fine particle concentration data. The PM2.5 product data of MASINGAR is introduced into the existing basic model as a new predictive factor, and the new predictive factor, basic model After the predictors in and the ground-based observation data are matched in time and space, the linear regression coefficients of each predictor including the added predictors are calculated in combination with the ground-based observation data, and a simultaneous correlation basic model is established with the calculated linear regression coefficients The improved model of predictors and MASINGAR's PM2.5 product data, the improved model is used to estimate the surface PM2.5 concentration, the calculated PM2.5 concentration data is more accurate than the concentration data obtained based on the basic model only Adding the PM2.5 product data of MASINGAR cited is more accurate, and overcomes the defects of scattered and discontinuous ground-based observation data.

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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Patent Type & Authority Patents(China)
IPC IPC(8): G01N15/06G01W1/10
CPCG01N15/06G01W1/10
Inventor 王威张仪潇
Owner CENT SOUTH UNIV