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A pm2.5 inversion method and monitoring area segmentation method

A monitoring area and inversion technology, which is applied in the monitoring of particulate matter in the air and in the field of PM2.5 inversion, can solve the problems of increasing the missing rate of satellite AOD and low accuracy of AOD inversion, so as to improve the spatial coverage and better anti-noise Ability to ensure stability

Active Publication Date: 2021-10-12
天津珞雍空间信息研究院有限公司
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

In addition, the inversion of AOD is related to the albedo of the surface. When the albedo of the surface is high, the surface is highlighted. The inversion accuracy of AOD is low, and the missing rate of satellite AOD will be increased when the quality control and screening of data are carried out.

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  • A pm2.5 inversion method and monitoring area segmentation method
  • A pm2.5 inversion method and monitoring area segmentation method
  • A pm2.5 inversion method and monitoring area segmentation method

Examples

Experimental program
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Embodiment 2

[0073] Example 2 The PM2.5 inversion method is provided, on the basis of the monitoring area segmentation method of the first example one, the monitoring area is divided into a number sub-area, and then the PM2.5 inversion is performed according to the following steps:

[0074] S410. Establish a random forest regression model to each sub-region, and the weather dynamic indicators and satellite AODs are entered into the random forest network. After the random forest network, the random forest regression model is optimally model, in the optimal model, inversion to find each sub-area PM2.5 concentration satellite estimation value In the meteorological dynamic indicator, for example, a surface temperature, a surface pressure, a wind speed, and a relative humidity and the boundary layer height.

[0075] The AOD is an aerosol optical thickness, and the integral of the aerosol extinction coefficient in the vertical direction, quantitatively describes the physical quantity of the gas sol...

Embodiment 3

[0086] Based on the second embodiment, the following steps further include:

[0087] S460, establish PM2.5 concentration satellite estimation value And space interpolation Fit function.

[0088] The corresponding site data of the PM2.5 concentration estimation value of the corresponding ground site data is calculated according to the fit function.

[0089] Satellite observations exist data missing, and interpolation interpolation Since the site is sparse and distributed uneven, the interpolation accuracy is also fluctuated in space, and the results of the two can be combined, and the error can be reduced to a certain extent, and the spatial coverage of the inversion results can be increased. The specific implementation process is divided into two steps, first establishing the fitting functions between the two, and there is no satellite observation, but there is space interpolation The pixels are rebuilt for satellite inversion results to fill the missing data.

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Abstract

This application discloses a monitoring area segmentation method and a PM2.5 inversion method for PM2.5 inversion. The monitoring area segmentation method includes the following steps: taking the geographical static indicators in the monitoring area and the measured concentration of PM2.5 as samples , and calculate the correlation coefficient between each static index and the measured concentration of PM2.5; use the correlation coefficient as a weight to normalize each static index to obtain the normalized parameter N_index, and the normalized parameter N_index is displayed in grid data ; Carry out multi-scale segmentation on the raster data with the normalization parameter N_index, determine the optimal segmentation method and divide the monitoring area into several sub-areas with the optimal segmentation method. This application uses a multi-scale segmentation algorithm to segment the monitoring area to reduce the interference of spatial heterogeneity on parameter estimation, and establishes its own particle concentration inversion model for different research sub-areas.

Description

Technical field [0001] The present disclosure generally relates to the field of environmental monitoring technology, and more particularly to the monitoring techniques of particulate matter in air, and more particularly to a monitoring region segmentation method for PM2.5 inversion and PM2.5 inversion method. Background technique [0002] In the past few decades, due to the rapid urban expansion and industrialization, a large amount of particulate matter (PM, the diameter of 1 nanometer to 100 micrometers) is discharged into the air, resulting in frequent China's ash incidents, especially the economy. The developed and population-intensive metropolitan areas are particularly prominent, including the Beijing-Tianjin-Hebei, the Yangtze River Delta, Huazhong and Sichuan Basin. [0003] Atmospheric particulate matter is the most important component of aerosol, the weather and climate system are affected by direct or indirect effects. Specifically, on the one hand, aerosol can directl...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N15/06
Inventor 宋沙磊徐宝马昕李治平莫云龙
Owner 天津珞雍空间信息研究院有限公司