Method for indicating high-pollution area around emission source and number of healthy exposure risk people through satellite remote sensing

Abstract

The invention provides a method for indicating a high-pollution area around an emission source and the number of healthy exposure risk people through satellite remote sensing. The method comprises the following steps: firstly, acquiring a long-term emission plume data set of a large emission source through satellite remote sensing monitoring, further acquiring an accumulated pollution emission coverage area of the emission source through a resampling technology, and calculating the number of population exposed in a high pollution risk area; and a more accurate coverage range of pollution emission of the large pollution source and the number of people exposed in a high-risk area are provided.

Description

Technical Field

[0001] The invention belongs to the field of atmospheric pollution emission monitoring and relates to a method for indicating high-pollution areas around emission sources and the number of people at health exposure risks through satellite remote sensing. Background Art

[0002] Identifying the polluted areas of large-scale atmospheric pollution emission sources is an important means of controlling atmospheric pollution and a key measure to protect the health of residents. At present, most ground-based detection instruments are mainly deployed in densely populated areas, using ground-based point-type concentration monitoring, which can only represent the concentration of polluted gases at specific locations. Although ground-based concentration imaging instruments can visualize the smoke plumes at the emission outlets of emission sources (such as chimney outlets), they cannot track the horizontal coverage area of ​​such emission plumes. In the past, studies on the exposure risks of large emission sources to human health mainly relied on emission inventories combined with model simulations to determine the exposure risks of pollution emissions from emission sources to people, but the lag of the inventory led to inaccurate results. High-resolution polar orbit satellite remote sensing monitoring can provide the spatial distribution of global atmospheric gas concentrations and identify and obtain emission plume data from large emission sources. Human health exposure risk research based on satellite remote sensing usually relies on the long-term average concentration spatial distribution results to analyze the population exposure risks in high-concentration areas. However, this method can only derive the exposure risks of high-concentration areas averaged over a long period of time, and cannot specifically analyze the specific impact of pollution emissions from a large emission source on the health of surrounding residents. It is crucial to analyze the impact of pollution emissions from specific large emission sources on residents' health, because many large emission sources often emit pathogenic pollutants, which seriously threaten residents' health. Summary of the invention

[0003] In order to more accurately provide the pollution coverage of large emission sources and the number of people exposed to different degrees of pollution in the cumulative coverage area, thereby providing important data support for environmental protection and public health, the present invention provides a method for long-term monitoring of emission plume datasets of large emission sources using satellite remote sensing. The cumulative pollution emission coverage area of ​​the emission source is obtained through resampling technology, and the number of people exposed in the high pollution risk area is evaluated. This method is applicable to emission plume datasets obtained from kilometer-level satellite remote sensing monitoring data, which can make up for the limitations of traditional ground-based monitoring, provide more accurate coverage of pollution emissions from large pollution sources and the number of people exposed in high-risk areas, and aims to provide important data support for environmental protection and public health.

[0004] The objective of the present invention is achieved through the following technical solutions: A method for indicating high pollution areas around emission sources and the number of people at health exposure risk by satellite remote sensing, comprising the following steps: Step 1: Based on satellite remote sensing observations, obtain the emission plume of the specified emission source; the emission plume refers to a group of continuous concentration-enhanced pixels with a plume shape, and the concentration enhancement is the result of deducting the background concentration from the original observed concentration; Step 2: Based on the observation data from long-term monitoring, obtain the emission plume dataset of the specified emission source; Step 3: Through resampling technology, the emission plume data sets with different pixel shapes are unified into the same resolution grid to obtain the concentration distribution of cumulative pollution emissions, grid coverage frequency distribution, and grid average concentration distribution; Step 4, combining the concentration distribution map of cumulative pollution emissions with the population data, setting different thresholds in the concentration distribution results of cumulative pollution emissions, selecting a data range greater than the threshold as a mask, and calculating the population size in the population density data based on the mask area.

[0005] The present invention first extracts the emission plume dataset of large emission sources obtained through long-term monitoring of high-resolution satellite remote sensing, and extracts the emission plume dataset of different pixel shapes into a grid of uniform resolution through resampling technology, and obtains the cumulative concentration distribution results, average concentration distribution results and coverage frequency distribution results of pollution emissions. Furthermore, according to the different concentration levels in the cumulative emission pollution coverage area, the pollution areas exposed to different risk levels are divided, and the population of different risk level areas is obtained according to the mask of the area.

[0006] The present invention has the following beneficial effects: The present invention provides a method for satellite remote sensing to indicate the number of people at risk of health exposure in the high-pollution areas around emission sources. Based on the emission plume data set of large emission sources monitored by high-resolution satellite remote sensing for a long time, the coverage area of ​​different pollution emission accumulation levels around the emission source is obtained, and the population of different risk level areas is calculated, providing important data support for environmental protection and public health. Compared with other methods (based on national control point monitoring results, ground-based point layout monitoring results, long-term average satellite column concentration distribution, etc.), the present invention has the following advantages and benefits: It can provide the concentration distribution of accumulated pollution emissions around large emission sources: Since the national control points are mainly located in the main urban areas of various cities in my country to meet the needs of monitoring changes in urban air quality in my country, but these points are rarely located around large emission sources, it is difficult to monitor the pollution emissions of emission sources in real time. Satellite remote sensing can track the spatial coverage of pollution emissions from emission sources based on long-term top-down observations, thereby identifying high-concentration areas around emission sources that pose a high risk to residents' health.

[0007] Based on long-term satellite monitoring, it can provide low-cost and large-scale cumulative pollution emission concentration distribution results around large emission sources: due to regulatory or scientific research requirements, regulatory departments and scientific research teams will deploy concentration detection instruments or measure the concentration in the area where the large emission sources are located or around them, but this concentration is a point distribution and it is difficult to visualize the spatial distribution. And because there are a lot of large emission sources, the deployment of ground monitoring instruments will consume huge manpower and material resources, so it is difficult to obtain the regional distribution of high pollution concentrations that pose health risks to residents from all large emission sources.

[0008] Based on the emission plume dataset, the research object can be constrained to the distribution of pollution concentrations generated by specific large emission sources: in the past, the high-value areas were further locked as potential health risks based on the long-term average concentration results of satellite monitoring. This method can only focus on the scope of high-concentration areas and their population from the perspective of satellites, and cannot analyze the cumulative high-concentration area scope and population exposure risk of pollution emissions from large emission sources alone. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 It is an example in the present invention, where satellite observations are used to obtain emission plume images of large emission sources after background deduction; Figure 2 It is an example of applying the present invention, and is a map of emission plume data sets obtained based on long-term satellite observation results; Figure 3 It is an example of applying the present invention to obtain a cumulative pollution emission concentration distribution map of the area where the emission source is located; Figure 4 It is an example of applying the present invention to obtain a frequency distribution map of pollution emission coverage in the area where the emission source is located; Figure 5 It is an example of applying the present invention to obtain the average concentration distribution map of pollution emissions in the area where the emission source is located; Figure 6 It is an example of the present invention, a population distribution map of the area where a certain emission source is located; Figure 7 This is an example of the present invention, a population map of different concentration coverage areas in the area where the emission source is located. DETAILED DESCRIPTION

[0010] The present invention is described in detail below in conjunction with the accompanying drawings and specific implementation cases. However, the following embodiments are limited to explaining the present invention, and the protection scope of the present invention should include the entire contents of the claims, and through the description of the following embodiments, those skilled in the art can fully implement the entire contents of the claims of the present invention.

[0011] The present invention proposes a method for indicating the high pollution area around the emission source and the number of people at health exposure risk by satellite remote sensing, comprising the following steps: Step 1: Based on satellite remote sensing observations, obtain the emission plume of the specified emission source; the emission plume refers to a group of continuous concentration-enhanced pixels with a plume shape, and the concentration enhancement is the result of deducting the background concentration from the original observed concentration; Step 2: Based on the observation data from long-term monitoring, obtain the emission plume dataset of the specified emission source; Step 3: Through resampling technology, the emission plume data sets with different pixel shapes are unified into the same resolution grid to obtain the concentration distribution of cumulative pollution emissions, grid coverage frequency distribution, and grid average concentration distribution; Step 4: Combine the concentration distribution map of cumulative pollution emissions with population data, set different thresholds in the concentration distribution results of cumulative pollution emissions, select the data range greater than the threshold as a mask, and calculate the population size in the population density data based on the mask area. Use the large-scale emission source emission plume data set obtained through long-term monitoring of high-resolution satellite remote sensing to obtain the cumulative emission pollution coverage area through resampling technology, and calculate the number of people exposed to different risk areas.

[0012] High-resolution satellite remote sensing refers to polar orbit satellites or geostationary satellites with kilometer-level spatial resolution. Through the long-term monitoring of kilometer-level spatial distribution data of pollutant concentrations by satellite remote sensing, the emission plume data set of large emission sources can be obtained. The emission plume of a large emission source refers to the continuous concentration-enhanced pixels with strips starting from the emission source location observed by the satellite. Its concentration can be expressed as: molecules / cm 2 ).

[0013] The resampling technique described refers to re-extracting emission plume datasets of different pixel shapes into a concentration grid of uniform resolution.

[0014] The cumulative emission pollution coverage area refers to the cumulative concentration distribution of all emission plumes at the same grid resolution after resampling. In addition, the average concentration distribution results and coverage frequency distribution results in the coverage area of ​​all emission plumes are obtained through synchronous processing.

[0015] The number of people exposed in different risk areas refers to selecting areas with concentrations greater than different thresholds in the cumulative emission pollution coverage area as areas with different exposure risk levels, generating a data mask, and combining the population grid data to calculate the number of people exposed in areas with different risk levels.

[0016] The present invention first extracts the emission plume dataset of large emission sources obtained through long-term monitoring of high-resolution satellite remote sensing, and extracts the emission plume dataset of different pixel shapes into a grid of uniform resolution through resampling technology, and obtains the cumulative concentration distribution results, average concentration distribution results and coverage frequency distribution results of pollution emissions. Furthermore, according to the different concentration levels in the cumulative emission pollution coverage area, the pollution areas exposed to different risk levels are divided, and the population of different risk level areas is obtained according to the mask of the area.

[0017] Specifically, a method of using satellite remote sensing to indicate the number of people with high pollution areas and health exposure risks around emission sources of the present invention comprises the following steps: First, based on satellite remote sensing observations, the emission plume of a designated large emission source is obtained. An emission plume refers to a group of continuous concentration-enhanced pixels with a plume shape. The concentration enhancement is the result of deducting the background concentration from the original observed concentration. The results of a single emission plume observed by satellite remote sensing are as follows: Figure 1 shown.

[0018] Furthermore, based on the observation data of long-term monitoring, the emission plume dataset of the specified large emission source is obtained. The emission plume dataset here includes multiple emission plumes obtained by long-term observation, such as Figure 2 .

[0019] Then, through the resampling technology, the emission plume data sets with different pixel shapes are unified into the same resolution grid to obtain the concentration distribution of cumulative pollution emissions, grid coverage frequency distribution and grid average concentration distribution, such as Figure 3 , 4 and 5. The resampling technique is to create an empty two-dimensional grid (X, Y) covering the plume area. For each pixel of the emission plume, calculate which specific grids in the empty grid each pixel should be filled into, and count the number of times it is filled in. The calculation of the cumulative pollution emission concentration distribution is as shown in formula (1): (1) in, represents the cumulative concentration of the grid in the i-th row and j-th column, n is the number of plumes, represents the concentration of the plx-th pixel of the plu-th plume, represents the plu-th plume, represents the pixth pixel, Represents the grid at row i and column j.

[0020] The calculation of grid coverage frequency distribution is shown in formula (2): (2) in, represents the coverage frequency of the grid in row i and column j; The calculation of the grid average concentration distribution is shown in formula (3): (3) The concentration distribution map of cumulative pollution emissions refers to the cumulative pollutant distribution of all emission plumes around the emission sources obtained during the long-term satellite remote sensing observation period (such as Figure 3 ), the grid coverage frequency distribution diagram refers to the distribution of the number of coverage times of each grid in the grid (such as Figure 4 ), the grid average concentration distribution is obtained by dividing the cumulative pollutant concentration at each location in the grid by the number of coverage times (e.g. Figure 5 ).

[0021] Furthermore, the concentration distribution map of cumulative pollution emissions is combined with population data, such as Figure 6 Different thresholds are set in the concentration distribution results of cumulative pollution emissions. The thresholds in the present invention are set at 50%, 75%, 90%, 95%, 99%, 99.5% and 99.9% percentiles as thresholds, and the data range greater than the threshold is selected as a mask, and the population in the population density data is calculated based on the mask area, as shown in FIG. Figure 7 shown.

[0022] The final result is Figure 7 As shown, there are 440,066 people in the long-term observed emission plume area of ​​the emission source, and when the screening concentration threshold is at the 50% percentile, that is, the concentration is greater than 6.1142E+17 molecules / cm2, there are 282,684 people, and when it is greater than the 90% percentile, that is, the concentration is greater than 3.7323E+18 molecules / cm2, there are 81,658 people. When it is greater than the 99% percentile, that is, the concentration is greater than 1.323E+19 molecules / cm2, there are 9,133 people. The higher the cumulative concentration, the higher the health risk that residents may face.

Claims

1. A method for using satellite remote sensing to indicate high pollution areas around emission sources and the number of people at risk of health exposure. It is characterized in that The following steps are involved: Step 1: Obtain the emission plume of the designated emission source based on satellite remote sensing; The emission plume refers to a group of continuous concentration-enhanced pixels with the shape of a smoke plume, and the concentration enhancement is the result of deducting the background concentration from the original observed concentration; Step 2: Based on the observation data from long-term monitoring, obtain the emission plume dataset of the specified emission source; Step 3: Unify the emission plume data sets of different pixel shapes into the same resolution grid through resampling technology to obtain the concentration distribution of cumulative pollution emissions, grid coverage frequency distribution, and grid average concentration distribution; Step 4, combining the concentration distribution map of cumulative pollution emissions with the population data, setting different thresholds in the concentration distribution results of cumulative pollution emissions, selecting a data range greater than the threshold as a mask, and calculating the population size in the population density data based on the mask area.

2. The method according to claim 1, It is characterized in that Satellite remote sensing refers to polar-orbiting satellites or geostationary satellites with a spatial resolution of kilometers. Through satellite remote sensing, the spatial distribution data of pollutant gas concentrations at the kilometer level can be monitored over a long period of time, and emission plume data sets of large emission sources can be obtained.

3. The method according to claim 1, It is characterized in that The emission plume of an emission source refers to the continuous strip-shaped concentration-enhanced pixels starting from the emission source location observed by the satellite, and its concentration is expressed as: number of molecules / square centimeter.

4. The method according to claim 1, It is characterized in that The specific resampling is as follows: create an empty two-dimensional grid (X, Y) covering the plume area. For each pixel of the emission plume, calculate which specific grids in the empty grid each pixel should be filled into, and count the number of fillings accordingly. The calculation of the cumulative pollution emission concentration distribution is as shown in formula (1): （1） in, represents the cumulative concentration of the grid in the i-th row and j-th column, n is the number of plumes, represents the concentration of the plx-th pixel of the plu-th plume, represents the plu-th plume, represents the pixth pixel, Represents the grid at row i and column j; The calculation of grid coverage frequency distribution is shown in formula (2): （2） in, represents the coverage frequency of the grid in row i and column j; The calculation of the grid average concentration distribution is shown in formula (3): （3）。

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