Natural source and artificial source contribution concentration calculation method based on leaf area index

Abstract

The invention discloses a natural source and artificial source contribution concentration calculation method based on a leaf area index, and belongs to the technical field of atmospheric pollutant source analysis. The method comprises the following steps: firstly, dividing a target area into a plurality of grid areas, determining the grid contribution concentration of each grid area, and calculating the natural source contribution concentration of each grid in different seasons by combining leaf area index data in different seasons; and finally, subtracting the contribution concentration of the natural source from the grid region concentration to obtain the contribution concentration of the artificial source, thereby realizing accurate identification and evaluation of the natural source and the artificial source.

Description

Technical Field

[0001] The present invention relates to the technical field of atmospheric pollutant source analysis, and in particular to a method for calculating the contribution concentrations of natural sources and anthropogenic sources based on leaf area index. Background Art

[0002] The formation mechanism of ozone in the atmospheric environment is relatively complex, mainly related to pollutants such as NOx and VOCs released by human activities. These pollutants and VOCs from natural sources such as vegetation generate ozone through complex photochemical reactions under the influence of environmental factors such as sunlight, temperature changes and humidity. In related technologies, since pollutants emitted by human and natural sources act synergistically in the atmosphere, only their combined contribution to ozone concentration can be evaluated.

[0003] Analysis of the sources of atmospheric pollutants is an important research topic in environmental science. In particular, how to accurately distinguish the contributions of natural sources from anthropogenic sources is of great significance for formulating effective pollution prevention and control measures.

[0004] At present, the HYSPLIT model, as a mature air mass trajectory simulation tool, is widely used in the calculation of potential contribution concentration (CWT). However, traditional methods mainly focus on the contribution assessment of overall pollution sources and fail to effectively distinguish the impact of natural sources and anthropogenic sources. Therefore, a method for calculating the contribution concentration of natural and anthropogenic sources based on leaf area index is proposed. Summary of the invention

[0005] The technical problem to be solved by the present invention is how to effectively distinguish the influence of natural sources and anthropogenic sources in the process of analyzing the sources of air pollutants, and provides a method for calculating the contribution concentrations of natural sources and anthropogenic sources based on leaf area index.

[0006] The present invention solves the above technical problems through the following technical solutions, and the present invention comprises the following steps:

[0007] S100: Divide the target area into a plurality of grid areas, and obtain leaf area index data of the corresponding grid areas by remote sensing technology;

[0008] S200: Using the HYSPLIT model, the backward movement trajectory of the air mass is calculated based on the emission source location of the target pollutant and atmospheric conditions;

[0009] S300: Based on the backward movement trajectory calculated by the HYSPLIT model and the pollutant concentration data of the observation point, the potential contribution concentration WHCWT of each grid area is calculated;

[0010] S400: Calculate the leaf area index weight coefficient K of each grid area according to the leaf area index data of the selected season;

[0011] S500: The natural source contribution concentration bio of each grid area is obtained by multiplying the leaf area index weight coefficient K of each grid area with the potential contribution concentration WHCWT of each grid area. ij ;

[0012] S600: Based on the natural source contribution concentration bio ij Calculate the concentration of anthropogenic contribution chem ij .

[0013] Furthermore, in step S100, leaf area index data of the corresponding grid area in spring, summer, autumn and winter are obtained by remote sensing technology, and the specific process is as follows:

[0014] According to the time span of spring, summer, autumn and winter, the leaf area index data corresponding to each season are extracted. The leaf area index data comes from the LAI dataset provided by MODIS and is downloaded according to the required data time range and geographical area.

[0015] Furthermore, in step S200, the trajectory data includes the latitude, longitude and altitude information of the trajectory at each time step.

[0016] Furthermore, in step S300, the calculation process of the potential contribution concentration WHCWT of each grid area is as follows:

[0017] S301: Calculate the CWT contribution value, the formula is as follows:

[0018]

[0019] Among them, C ij is the contribution concentration of the grid area in row i and column j, i.e., the CWT contribution value; C l is the pollutant concentration when the backward moving trajectory passes through the grid area, that is, the pollutant concentration of a single node on the backward moving trajectory; τ ijl is the length of time that the backward moving trajectory stays in the grid area of ​​the i-th row and j-th column. The length of time is represented by the number of nodes of the backward moving trajectory in the grid area of ​​the i-th row and j-th column. The more nodes there are, the longer the length of time that the backward moving trajectory stays in the grid area.

[0020] S302: Calculate the concentration weighted trajectory HCWT value integrated into the air mass height and boundary layer height:

[0021]

[0022] Among them, C ij is the contribution concentration of the grid area in row i and column j; height ijis the air mass height in the grid area of ​​row i and column j; PBLH ij is the boundary layer height of the grid area in the i-th row and j-th column;

[0023] S303: Using the weight function W(n ij ) The HCWT value is corrected, and the concentration weighted trajectory WHCWT value integrated into the air mass height and boundary layer height after correction is as follows:

[0024] WHCWT=HCWT ij *W(n ij );

[0025] Among them, the weight function W(n ij )The formula is as follows:

[0026]

[0027] Among them, n ave is the average number of nodes per grid area within the target area; n ij is the number of nodes in the grid area of ​​row i and column j that the backward moving trajectory passes through.

[0028] Furthermore, in step S400, the calculation formula of the leaf area index weight coefficient K of each grid area is as follows:

[0029]

[0030] Among them, K ij is the leaf area index weight coefficient of the grid area in the i-th row and j-th column of the selected season, LAI ij is the leaf area index of the grid area in the i-th row and j-th column; LAI min is the minimum leaf area index in all grid areas; LAI max is the maximum leaf area index among all grid regions.

[0031] Furthermore, in step S500, the natural source contribution concentration bio of each grid area is ij The calculation formula is as follows:

[0032]

[0033] Among them, K ij is the leaf area index weight coefficient of the i-th row and j-th column grid in the selected season; WHCWT ij is the potential contribution concentration of the grid area in row i and column j; LAI ij is the leaf area index of the grid area in the i-th row and j-th column; LAI min is the minimum leaf area index in all grid areas; LAImax is the maximum leaf area index among all grid regions.

[0034] Furthermore, in step S600, the artificial source contribution concentration chem ij The calculation formula is as follows:

[0035] chem ij =(1-bio ij )*WHCWT ij .

[0036] Compared with the prior art, the present invention has the following advantages: the method for calculating the contribution concentrations of natural sources and anthropogenic sources based on the leaf area index first divides the target area into multiple grid areas, determines the grid contribution concentration of each grid area, and then calculates the natural source contribution concentration of each grid in different seasons in combination with the leaf area index data of different seasons; finally, the natural source contribution concentration is subtracted from the grid area concentration to obtain the anthropogenic source contribution concentration, thereby achieving accurate identification and evaluation of natural sources and anthropogenic sources respectively. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic flow chart of a method for calculating the concentration contribution of natural sources and anthropogenic sources based on seasonal leaf area index in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiment.

[0039] Considering that at present, the analysis of atmospheric pollutant sources mainly focuses on the contribution assessment of the overall pollution source, and fails to effectively distinguish the impact of natural sources and anthropogenic sources. The present invention first uses the HYSPLIT model to calculate the WHCWT, and then combines the LAI data of different seasons to calculate the contribution concentration of natural sources in each grid in different seasons. Finally, the contribution concentration of anthropogenic sources is obtained by subtracting the contribution concentration of natural sources from the WHCWT, thereby realizing the accurate identification and assessment of natural sources and anthropogenic sources respectively.

[0040] like Figure 1 As shown, the method for calculating the concentration of natural and anthropogenic sources based on the seasonal leaf area index in this embodiment includes the following steps:

[0041] Step S100, divide the target area into multiple grid areas, for example, the grid area has i rows and j columns; determine the leaf area index (LAI) data of the corresponding grid area. Specifically, determine the leaf area index (LAI) data of the corresponding grid area in spring, summer, autumn and winter. The leaf area index reflects the vegetation coverage in different seasons, usually counted by month, quarter or season. In addition, the leaf area index (LAI) is an important parameter to describe the vegetation coverage, and LAI has significant seasonal changes. Spring and summer are usually the periods with the highest LAI values ​​because plants grow vigorously in these seasons; in autumn and winter, the LAI value usually decreases with the falling of leaves and the withering of vegetation.

[0042] In this step, remote sensing technology is used to obtain the leaf area index data of the corresponding grid area in spring, summer, autumn and winter. The specific process is as follows:

[0043] S101: Extract the leaf area index data corresponding to each season according to the time span of spring (March-May), summer (June-August), autumn (September-November), and winter (December-February of the following year). The leaf area index data comes from the LAI dataset provided by MODIS (Moderate Resolution Imaging Spectroradiometer) and is downloaded according to the required data time range and geographical area.

[0044] Step S200: Use the HYSPLIT trajectory model to calculate and obtain a large number of backward moving trajectories of the air mass; the trajectory data includes the latitude, longitude and altitude information of the trajectory at each time step. The details are as follows:

[0045] The prepared meteorological data is input into the HYSPLIT trajectory model to obtain a large number of backward trajectories of air masses passing through the grid area to reach the receptor point (such as an air quality monitoring station); during the trajectory calculation process, the position (latitude, longitude and altitude) information of each trajectory at different time steps is recorded; at the same time, the influence of terrain on the trajectory should be considered, especially in areas with complex terrain, to ensure the accuracy of trajectory calculation.

[0046] Among them, meteorological data are collected with high temporal and spatial resolution, such as wind speed, wind direction, temperature, air pressure, humidity, etc. These data come from the Global Data Assimilation System (GDAS) reanalysis data.

[0047] Step S300: Calculate the potential contribution concentration (WHCWT) of each grid area using the trajectory data calculated by the HYSPLIT model and the pollutant concentration data of the observation point.

[0048] In this step, the calculation process of the potential contribution concentration WHCWT of each grid area is as follows:

[0049] S301: Calculate the CWT contribution value, the formula is as follows:

[0050]

[0051] Among them, C ij is the contribution concentration of the grid area in row i and column j, i.e., the CWT contribution value; C l is the pollutant concentration when the backward moving trajectory passes through the grid area, that is, the pollutant concentration of a single node on the backward moving trajectory; τ ijl is the length of time that the backward moving trajectory stays in the grid area of ​​the i-th row and j-th column. The length of time is represented by the number of nodes of the backward moving trajectory in the grid area of ​​the i-th row and j-th column. The more nodes there are, the longer the length of time that the backward moving trajectory stays in the grid area.

[0052] S302: Calculate the concentration weighted trajectory HCWT value integrated into the air mass height and boundary layer height:

[0053]

[0054] Among them, C ij is the contribution concentration of the grid area in row i and column j; height ij is the air mass height in the grid area of ​​row i and column j; PBLH ij is the boundary layer height of the grid area in the i-th row and j-th column;

[0055] S303: Using the weight function W(n ij ) The HCWT value is corrected, and the concentration weighted trajectory WHCWT value integrated into the air mass height and boundary layer height after correction is as follows:

[0056] WHCWT=HCWT ij *W(n ij );

[0057] Among them, the weight function W(n ij )The formula is as follows:

[0058]

[0059] Among them, n ave is the average number of nodes per grid area within the target area; n ij is the number of nodes in the grid area of ​​row i and column j that the backward moving trajectory passes through.

[0060] Step S400: Calculate the leaf area index weight coefficient K of each grid according to the LAI data of the selected season.

[0061] In this step, the calculation formula of the leaf area index weight coefficient K of each grid is as follows:

[0062]

[0063] Among them, K ij is the leaf area index weight coefficient of the grid area in the i-th row and j-th column of the selected season, LAI ij is the leaf area index of the grid area in the i-th row and j-th column; LAI min is the minimum leaf area index in all grid areas; LAI max is the maximum leaf area index among all grid regions.

[0064] Step S500: According to the above leaf area index weight coefficient, adjust the WHCWT of each grid to obtain the natural source contribution concentration bio of each grid. ij The expression is:

[0065]

[0066] Among them, K ij is the leaf area index weight coefficient of the grid area in the i-th row and j-th column of the selected season; WHCWT ij is the potential contribution concentration of the grid area in row i and column j; LAI ij LAI is the leaf area index of the grid area in the i-th row and j-th column; min is the minimum leaf area index in all grid areas; LAI max is the maximum leaf area index among all grid regions.

[0067] Step S600: according to the natural source contribution concentration bio ij Get the concentration of anthropogenic contribution chem ij The expression is:

[0068] chem ij =(1-bio ij )*WHCWT ij

[0069] To summarize, the method for calculating the contribution concentrations of natural and anthropogenic sources based on the leaf area index in the above embodiment first divides the target area into multiple grid areas, determines the grid contribution concentration of each grid area, and then calculates the natural source contribution concentration of each grid in different seasons in combination with the leaf area index data of different seasons; finally, the natural source contribution concentration is subtracted from the grid area concentration to obtain the contribution concentration of anthropogenic sources, thereby achieving accurate identification and evaluation of natural and anthropogenic sources respectively.

[0070] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for calculating the contribution concentration of natural sources and anthropogenic sources based on leaf area index, characterized in that: The following steps are involved: S100: Divide the target area into a plurality of grid areas, and obtain leaf area index data of the corresponding grid areas by remote sensing technology; S200: Using the HYSPLIT model, the backward movement trajectory of the air mass is calculated based on the emission source location of the target pollutant and atmospheric conditions; S300: Based on the backward movement trajectory calculated by the HYSPLIT model and the pollutant concentration data of the observation point, the potential contribution concentration WHCWT of each grid area is calculated; S400: Calculate the leaf area index weight coefficient K of each grid area according to the leaf area index data of the selected season; S500: The natural source contribution concentration bio of each grid area is obtained by multiplying the leaf area index weight coefficient K of each grid area with the potential contribution concentration WHCWT of each grid area. ij ; S6 00: According to the natural source contribution concentration bio ij Calculate the concentration of anthropogenic contribution chem ij .

2. The method for calculating the contribution concentration of natural sources and anthropogenic sources based on leaf area index according to claim 1, characterized in that: In step S100, the leaf area index data of the corresponding grid area in spring, summer, autumn and winter are obtained by remote sensing technology. The specific process is as follows: According to the time span of spring, summer, autumn and winter, the leaf area index data corresponding to each season are extracted. The leaf area index data comes from the LAI dataset provided by MODIS and is downloaded according to the required data time range and geographical area.

3. The method for calculating the contribution concentration of natural sources and anthropogenic sources based on leaf area index according to claim 1, characterized in that: In step S200, the trajectory data includes the latitude, longitude and altitude information of the trajectory at each time step.

4. The method for calculating the contribution concentration of natural sources and anthropogenic sources based on leaf area index according to claim 1, characterized in that: In step S300, the calculation process of the potential contribution concentration WHCWT of each grid area is as follows: S301: Calculate the CWT contribution value, the formula is as follows: Among them, C ij is the contribution concentration of the grid area in row i and column j, i.e., the CWT contribution value; C l is the pollutant concentration when the backward moving trajectory passes through the grid area, that is, the pollutant concentration of a single node on the backward moving trajectory; τ ijl is the length of time that the backward moving trajectory stays in the grid area of ​​the i-th row and j-th column. The length of time is represented by the number of nodes of the backward moving trajectory in the grid area of ​​the i-th row and j-th column. The more nodes there are, the longer the length of time that the backward moving trajectory stays in the grid area. S302: Calculate the concentration weighted trajectory HCWT value integrated into the air mass height and boundary layer height: Among them, C ij is the contribution concentration of the grid area in row i and column j; height ij is the air mass height in the grid area of ​​row i and column j; PBLH ij is the boundary layer height of the grid area in the i-th row and j-th column; S303: Using the weight function W(n ij ) The HCWT value is corrected, and the concentration weighted trajectory WHCWT value integrated into the air mass height and boundary layer height after correction is as follows: WHCWT=HCWT ij *W(n ij ); Among them, the weight function W(n ij )The formula is as follows: Among them, n ave is the average number of nodes per grid area within the target area; n ij is the number of nodes in the grid area of ​​row i and column j that the backward moving trajectory passes through.

5. The method for calculating the contribution concentration of natural sources and anthropogenic sources based on leaf area index according to claim 1, characterized in that: In step S400, the calculation formula of the leaf area index weight coefficient K of each grid area is as follows: Among them, K ij is the leaf area index weight coefficient of the grid area in the i-th row and j-th column of the selected season, LAI ij is the leaf area index of the grid area in the i-th row and j-th column; LAI min is the minimum leaf area index in all grid areas; LAI max is the maximum leaf area index among all grid regions.

6. The method for calculating the contribution concentration of natural sources and anthropogenic sources based on leaf area index according to claim 1, characterized in that: In step S500, the natural source contribution concentration bio in each grid area ij The calculation formula is as follows: Among them, K ij is the leaf area index weight coefficient of the i-th row and j-th column grid in the selected season; WHCWT ij is the potential contribution concentration of the grid area in row i and column j; LAI ij is the leaf area index of the grid area in the i-th row and j-th column; LAI min is the minimum leaf area index in all grid areas; LAI max is the maximum leaf area index among all grid regions.

7. The method for calculating the contribution concentration of natural sources and anthropogenic sources based on leaf area index according to claim 6, characterized in that: In step S600, the artificial source contribution concentration chem ij The calculation formula is as follows: chem ij =(1-bio ij )*WHCWT ij 。

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