Ozone control mechanism dynamic identification method and device fusing satellite and ground observation
By integrating satellite and ground observation data, the ozone control mechanism dynamically recognizes the ozone control mechanism, the difficulty in identifying the ozone control mechanism caused by the scarcity of ground observation stations is solved, and accurate identification of ozone pollution sources and the provision of prevention and control measures are achieved.
Patent Information
- Application Number
- CN202411308682.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-19
- Publication Date
- 2025-02-18
AI Technical Summary
Since there are relatively few ground observation sites, especially VOCs, the ozone control mechanism cannot be refined, which increases the difficulty of identifying pollution sources.
Using a dynamic identification method of ozone control mechanism that integrates satellites and ground observations, the ozone pollution areas are determined by obtaining satellite inversion HCHO and column concentration data and ground ozone concentration observation data, and fusing these data to conduct preliminary identification of ozone control mechanisms. and the key control area of precursor objects, and finally identify the main pollution sources.
The refined identification of the ozone control mechanism is achieved, the high uncertainty brought about by using only satellite inversion data is reduced, and the accurate data basis is provided, and scientific countermeasures are provided for the prevention and control of ozone pollution.
Smart Images
Figure CN119474773A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of environmental monitoring and control, and in particular to a method and device for dynamically identifying an ozone control mechanism by integrating satellite and ground observations. Background Art
[0002] Surface ozone ( ) is one of the major air pollutants that adversely affect air quality, human health and ecosystem productivity.
[0003] Ground-level ozone is mainly generated by photochemical reactions of precursors such as nitrogen oxides (NOx) and volatile organic compounds (VOCs). NOx and VOCs released by industrial enterprises, transportation, residents' lives, agricultural production, energy consumption, vegetation and soil, etc., undergo a series of photochemical reactions and eventually generate high concentrations of ozone. However, there is an obvious nonlinear relationship between the photochemical generation of ozone and its precursors. The photochemical generation of ozone produces different changing characteristics as the concentrations of NOx and VOCs change. Therefore, identifying the photochemical generation mechanism of ozone, that is, the ozone control mechanism, through technical means is a key issue in controlling ozone pollution.
[0004] The determination of ozone control mechanisms can be done through observation, model simulation, satellite remote sensing, etc. Although observation-based methods are the most intuitive and reliable, due to the relatively small number of ground observation sites, especially VOCs observation sites, it is impossible to finely identify ozone control mechanisms, which makes it more difficult to identify pollution sources. Summary of the invention
[0005] In order to solve the problem that due to the relatively small number of ground observation sites, especially VOCs observation sites, it is impossible to finely identify the ozone control mechanism, thereby increasing the difficulty in identifying pollution sources, the present invention provides a method and device for dynamically identifying the ozone control mechanism by integrating satellite and ground observations.
[0006] In a first aspect, the present invention provides a method for dynamically identifying ozone control mechanisms by integrating satellite and ground observations, which adopts the following technical solutions: A method for dynamically identifying ozone control mechanisms by integrating satellite and ground observations includes the following steps:
[0007] S1, obtain the satellite inverted HCHO and Column concentration data and ground-level ozone concentration observations; S2, fusion of HCHO and Column concentration data and ground-level ozone concentration observations for preliminary identification of ozone control mechanisms; S3, determine ozone pollution areas based on ground ozone concentration observation data, and determine key control areas for precursors in ozone pollution areas based on preliminary identification of ozone control mechanisms; S4, identify the main pollution sources based on the precursor key control areas.
[0008] Optionally, in step S1, HCHO and Column concentration data and ground ozone concentration observation data specifically include: Determine the scope of the target area and obtain the HCHO and Column concentration data, and clearly HCHO and Latitude and longitude information of column concentration data; Based on the column concentration data, the area to be monitored is divided into multiple grid points, each of which includes its own geographical coordinates and the corresponding HCHO and Column concentration data; Obtain ground ozone concentration observation data from ground-based urban air quality monitoring stations, determine the ozone concentration at the monitoring station based on the satellite transit time, and retrieve the latitude and longitude information of the monitoring station.
[0009] Optionally, when dividing the grid, HCHO and Column concentration is less than 1×10 15 molec / cm 2 data.
[0010] Optionally, in step S2, the HCHO and Column concentration data and ground-level ozone concentration observation data include: Match each air quality monitoring site with the grid points based on the latitude and longitude information to obtain the HCHO and Column concentration data; Calculate HCHO and The ratio of Within a preset time, a polynomial fitting curve is constructed based on the analysis and calculation of the ozone concentration corresponding to the contrast value and the ratio, and a first threshold value and a second threshold value are obtained through the polynomial fitting curve; When the ratio of the target grid point is less than the second threshold, the target grid point is a VOC control mechanism; When the target grid point ratio is greater than the second threshold and less than the first threshold, the target grid point is a VOC and NOx mixed control mechanism; When the ratio of the target grid point is greater than the first threshold, the target grid point is a NOx control mechanism.
[0011] Optionally, the specific steps of constructing a polynomial fitting curve based on the analysis and calculation of the ozone concentration corresponding to the contrast value and the ratio, and obtaining the first threshold and the second threshold through the polynomial fitting curve include: All ratios are divided into multiple intervals based on a preset division interval; Obtain the ozone concentration corresponding to the ratio in each interval, and calculate the mean ozone concentration in each interval; The ratio of each interval was used as the independent variable, and the mean ozone concentration of each interval was used as the dependent variable to construct a fitting curve of a cubic polynomial. The critical ratio corresponding to the cubic polynomial when the ozone maximum occurs is calculated, the derivatives of the curves on both sides of the cubic polynomial maximum point are obtained as -a and a, and the corresponding first threshold and second threshold are obtained.
[0012] Optionally, in step S3, determining the ozone pollution area specifically includes: Based on the ground ozone concentration observation data, the maximum eight-hour daily ozone concentration MDA8 is calculated for the target period. ; MDA8 Concentration higher than 160 μg / areas as ozone polluted areas; And obtain the spatial distribution characteristics of ozone concentration in ozone polluted areas.
[0013] Optionally, in step S3, determining the key control area of precursors in the ozone polluted area in combination with the preliminary identification of the ozone control mechanism specifically includes: Identify the ozone control mechanism in the ozone polluted area based on the dynamic identification method in step S2; In ozone polluted areas, The part in the VOC control mechanism is determined as the first area, and the first concentration area in which the HCHO column concentration is above the 80th percentile in the first area is identified, and the first concentration area is the VOC key control area; The part in the NOx control mechanism is determined as the second area, and the second area is identified. The second concentration area where the column concentration is above the 80th percentile, and the first concentration area is the key NOx control area; The part in the mixed control area is determined as the third area, and the third area is identified and a third concentration region where the HCHO column concentration is above the 80th percentile, and the third concentration region is a mixed precursor control region.
[0014] Optionally, before identifying the ozone control mechanism of the ozone polluted area based on the dynamic identification method in step S2: Determine land cover type data based on satellite remote sensing and geographic information database; The ozone pollution areas not caused by human emissions are eliminated in combination with the land cover type data, and the ozone pollution areas affected by human influence are retained as the final ozone pollution areas.
[0015] Optionally, step S4 specifically includes: The main pollution sources in the key control areas of precursors identified based on sub-meter high-resolution images; In the VOC key control area, focus on identifying industrial enterprises in the area as the main pollution sources; In key NOx control areas, focus on identifying energy-consuming enterprises in the area as the main pollution sources; Mixed precursor control areas, identifying all significant sources of contamination.
[0016] In the second aspect, a method and device for dynamically identifying ozone control mechanisms integrating satellite and ground observations includes: Satellite remote sensing module, obtains HCHO and Column concentration data; The ground observation module is equipped with multiple air quality monitoring stations to obtain ground ozone concentration observation data; Identification processing module, fusion of satellite inversion HCHO and Column concentration data and ground ozone concentration observation data are used to make a preliminary identification of the ozone control mechanism; ozone pollution areas are determined based on ground ozone concentration observation data, and precursor key control areas are determined in ozone pollution areas in combination with the preliminary identification of ozone control mechanisms; major pollution sources are identified based on precursor key control areas.
[0017] In summary, the present invention has the following beneficial technical effects: HCHO and Column concentration, while using the ozone concentration of the target city's ground air quality monitoring station. The method of ozone control mechanism used takes into account regional and temporal differences, and reduces the high uncertainty caused by using only satellite inversion data, making full use of the existing urban air quality monitoring network and high-resolution satellite inversion data. A dynamic identification technology has been created to timely identify the ozone control mechanism in the target area, which is more scientific than the current technology of determining the ozone control mechanism in a certain area during a fixed period of time. And through dynamic identification technology, a data basis is provided for precise prevention and control, which is more accurate than the identification of fixed ozone control mechanisms, and realizes high-precision and dynamic identification of ozone control mechanisms. And determine the dominant precursor pollution area, find the pollution source for the dominant precursor pollution area, so as to propose scientific prevention and control countermeasures in the future. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] Figure 1It is a flow chart of a method for dynamically identifying an ozone control mechanism by integrating satellite and ground observations according to an embodiment of the present invention.
[0019] Figure 2 The HCHO and Schematic diagram of example column concentrations and ozone concentration data for ground-based observing stations.
[0020] Figure 3 In one embodiment of the present invention, the area to be tested is and HCHO / Fitting curve of the ratio and schematic diagram of the ozone control zone division standard.
[0021] Figure 4 MDA8 of the embodiment of the present invention Schematic diagram of spatial distribution of concentration.
[0022] Figure 5 The red part of the embodiment of the present invention is a schematic diagram of the area where the HCHO column concentration in the ozone polluted area is above the 80th percentile.
[0023] Figure 6 It is a structural schematic diagram of a device for dynamically identifying ozone control mechanisms that integrates satellite and ground observations according to an embodiment of the present invention. DETAILED DESCRIPTION
[0024] The following is combined with Figure 1-6 The present invention is described in further detail.
[0025] Example 1 Reference Figure 1 , a method for dynamically identifying ozone control mechanisms by integrating satellite and ground observations in this embodiment includes the following steps: S1, obtain satellite-derived formaldehyde (HCHO) and nitrogen dioxide ( ) Column concentration data and ground-level ozone concentration observation data; Specifically include: Determine the scope of the target area and obtain the HCHO and Column concentration data, and clearly HCHO and The latitude and longitude information of the column concentration data; the preset time in this embodiment is the last 15 days, and in other embodiments, a time similar to the current weather conditions can also be selected as the preset time, and the satellite inversion data is mapped to ARCGIS according to the latitude and longitude information; this embodiment uses TROPOMI inversion The data of HCHO column concentration can be obtained from https: / / developers.google.cn / earth-engine / . By sorting out the satellite data of the monitoring area, the corresponding and HCHO column concentration data.
[0026] Based on the column concentration data, the area to be monitored is divided into multiple grid points, each of which includes its own geographical coordinates and the corresponding HCHO and Column concentration data; In this embodiment, the area to be monitored is divided into grid points of approximately 1 km in size (approximately 0.009°); Obtain the ground ozone concentration observation data of the ground urban air quality monitoring station, and determine the ozone concentration of the monitoring station according to the satellite transit time, and retrieve the longitude and latitude information of the monitoring station. In this embodiment, according to the satellite transit time, the one-hour average of ozone concentrations at 13:00 and 14:00 local time is taken as the ozone concentration at the station; the above data should be accompanied by longitude and latitude and time information to facilitate time and space matching. The data of the air quality monitoring network in this embodiment can be obtained from ecological and environmental departments at all levels. This embodiment selects the air quality monitoring network of the ecological and environmental bureau of the target area. The hourly average of ozone at 13:00 and 14:00 in the target period is selected as the ozone concentration. Figure 2 shown.
[0027] The latitude and longitude information of the collected satellite remote sensing data and ground observation data are matched and input into ARCGIS to form a dataset with temporal and spatial distribution. Column concentration is less than 1×10 15 molec / cm 2 The data is removed to reduce the interference of systematic errors on the analysis and facilitate subsequent use.
[0028] S2, fusion of HCHO and Column concentration data and ground-level ozone concentration observations for preliminary identification of ozone control mechanisms; Fusion of HCHO and Column concentration data and ground-level ozone concentration observation data include: S2-1, match each air quality monitoring site with the grid points according to the latitude and longitude information, and obtain the HCHO and Column concentration data; S2-2, calculate HCHO and The ratio of S2-3, within a preset time, construct a polynomial fitting curve based on the analysis and calculation of the ozone concentration corresponding to the comparison value and the ratio, and obtain the first threshold and the second threshold through the polynomial fitting curve; the specific steps include: Reference Figure 3 , all ratios are divided into multiple intervals based on a preset segmentation interval; Obtain the ozone concentration corresponding to the ratio in each interval, and calculate the mean ozone concentration in each interval; The ratio of each interval is used as the independent variable, and the mean ozone concentration of each interval is used as the dependent variable to construct a fitting curve of a cubic polynomial. In this embodiment, the least squares method is used to fit the optimal cubic polynomial parameters: Calculate the critical ratio corresponding to the ozone maximum in the cubic polynomial, find the derivatives of the curve on both sides of the cubic polynomial maximum point as -a and a, and obtain the corresponding first threshold and second threshold. In this embodiment, by analyzing the different slopes of the curve, a is defined as 3.5, and different first thresholds and second thresholds are found in different curves according to the definition of a. Figure 3 One situation is shown in .
[0029] If the time period of the identification target changes, such as seasonal or weather changes, the concentrations of HCHO and NO2 may fluctuate significantly, which will affect the mechanism of ozone generation. In this case, the previously fitted curve may no longer be applicable, so the polynomial fitting needs to be re-performed based on the new data; Different geographic regions may have different pollutant emission patterns and concentrations. For example, some regions may be dominated by VOCs emissions, while other regions are dominated by NOx emissions. Therefore, whenever the identification area changes, especially across regions, the new regional data needs to be fitted to ensure the accuracy of the fitting curve; Therefore, by analyzing the weather and other factors affecting the current area to be tested, a period of time that best fits the current situation is selected as the preset time, a curve is fitted to the historical data of the preset time, and then the precursor control area is judged to make the judgment more standardized.
[0030] S2-4, when the ratio of the target grid point is less than a second threshold, the target grid point is a volatile organic compound (VOC) control mechanism; When the target grid point ratio is greater than the second threshold and less than the first threshold, the target grid point is a mixed control mechanism of VOC and nitrogen oxides (NOx); When the ratio of the target grid point is greater than the first threshold, the target grid point is a NOx control mechanism.
[0031] S3, determine the ozone pollution area based on the ground ozone concentration observation data, and determine the key control areas of precursors in the ozone pollution area in combination with the preliminary identification of the ozone control mechanism; The ozone pollution areas are as follows: Based on the ground ozone concentration observation data, the maximum eight-hour daily ozone concentration MDA8 is calculated for the target period. ; MDA8 Concentration higher than 160 μg / Areas with 160μg / It is the second level standard of national air quality standard; And obtain the spatial distribution characteristics of ozone concentration in the ozone pollution area. And use ARCGIS interpolation analysis to interpolate the ozone concentration and obtain the spatial distribution characteristics of regional ozone concentration. Figure 4 As shown, the embodiment shows an interpolation map of the spatial distribution of ozone in the target area and its surrounding areas.
[0032] Combined with the preliminary identification of ozone control mechanisms, key control areas for precursors are identified in ozone polluted areas, including: Determine land cover type data based on satellite remote sensing and geographic information database; Combined with the land cover type data, the ozone pollution areas not caused by human emissions are eliminated, and the ozone pollution areas affected by human influence are retained as the final ozone pollution areas. The ozone pollution areas not caused by human emissions include farmland, forest land, grassland, water area and unused land.
[0033] Identify the ozone control mechanism in the ozone polluted area based on the dynamic identification method in step S2; In ozone polluted areas, Reference Figure 5 , the part in the VOC control mechanism is determined as the first area, and the first concentration area in the first area where the HCHO column concentration is above the 80th percentile is identified. The first concentration area is the VOC key control area; it is displayed in red in the figure; The part in the NOx control mechanism is determined as the second area, and the second area is identified. The second concentration area where the column concentration is above the 80th percentile, and the first concentration area is the key NOx control area; The part in the mixed control area is determined as the third area, and the third area is identified and a third concentration region where the HCHO column concentration is above the 80th percentile, and the third concentration region is a mixed precursor control region.
[0034] S4, identify the main pollution sources based on the precursor key control areas.
[0035] The main pollution sources in the key control areas of precursors identified based on sub-meter high-resolution images; In the VOC key control area, focus on identifying industrial enterprises such as petrochemicals, solvent use, and chemical synthesis in the area as major pollution sources; In the NOx key control area, energy-consuming enterprises such as transportation and thermal power plants in the area are identified as the main pollution sources; Mixed precursor control areas, identify all important pollution sources. Integrate the identified pollution sources to provide basic data for further precise control of ozone pollution. For areas within the target area that are not included in the key control area, the HCHO / The ratio of VOC and NOx emission reduction in the area is determined by the ratio of
[0036] In summary, the present invention relates to a precise dynamic identification technology for ozone control mechanism, which is based on the tropospheric HCHO and The column concentration and the ozone concentration observed by the ground air quality monitoring network are determined by establishing a functional relationship. The control type of photochemically generated precursors. Combined with high-resolution satellite remote sensing data and land use type data, the main precursor control areas are accurately identified and precursor control countermeasures are given.
[0037] Example 2 The difference between this embodiment and embodiment 1 is that this embodiment provides a method and device for dynamically identifying an ozone control mechanism integrating satellite and ground observations, including: Satellite remote sensing module, obtains HCHO and Column concentration data; The ground observation module is equipped with multiple air quality monitoring stations to obtain ground ozone concentration observation data; Identification processing module, fusion of satellite inversion HCHO and Column concentration data and ground ozone concentration observation data are used to make a preliminary identification of ozone control mechanisms; ozone pollution areas are determined based on ground ozone concentration observation data, and precursor key control areas are determined in ozone pollution areas in combination with the preliminary identification of ozone control mechanisms; major pollution sources are identified based on precursor key control areas.
[0038] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the method disclosed in the embodiment, since it corresponds to the system disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.
[0039] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.
[0040] The above disclosure is only a preferred embodiment of the present invention, but the present invention is not limited thereto. Any non-creative changes that can be thought of by a person skilled in the art, as well as several improvements and modifications made without departing from the principle of the present invention, should fall within the protection scope of the present invention.
Claims
1. A method for dynamic identification of ozone control mechanisms integrating satellite and ground observations, characterized in that: The following steps are involved: S1, obtain the satellite inverted HCHO and Column concentration data and ground-level ozone concentration observations; S2, fusion of HCHO and Column concentration data and ground-level ozone concentration observations for preliminary identification of ozone control mechanisms; S3, determine ozone pollution areas based on ground ozone concentration observation data, and determine key control areas for precursors in ozone pollution areas based on preliminary identification of ozone control mechanisms; S4, identify the main pollution sources based on the precursor key control areas.
2. The method for dynamic identification of ozone control mechanisms integrating satellite and ground observations according to claim 1 is characterized in that: In step S1, the HCHO and Column concentration data and ground ozone concentration observation data specifically include: Determine the scope of the target area and obtain the HCHO and Column concentration data, and clearly HCHO and Latitude and longitude information of column concentration data; Based on the column concentration data, the area to be monitored is divided into multiple grid points, each of which includes its own geographical coordinates and the corresponding HCHO and Column concentration data; Obtain ground ozone concentration observation data from ground-based urban air quality monitoring stations, determine the ozone concentration at the monitoring station based on the satellite transit time, and retrieve the latitude and longitude information of the monitoring station.
3. The method for dynamically identifying ozone control mechanisms by integrating satellite and ground observations according to claim 2 is characterized in that: When dividing the grid, remove HCHO and Column concentration is less than 1×10 15 molec / cm 2 data.
4. The method for dynamically identifying ozone control mechanisms by integrating satellite and ground observations according to claim 2, characterized in that: In step S2, the HCHO and Column concentration data and ground-level ozone concentration observation data include: Match each air quality monitoring site with the grid points based on the latitude and longitude information to obtain the HCHO and Column concentration data; Calculate HCHO and The ratio of Within a preset time, a polynomial fitting curve is constructed based on the analysis and calculation of the ozone concentration corresponding to the contrast value and the ratio, and a first threshold value and a second threshold value are obtained through the polynomial fitting curve; When the ratio of the target grid point is less than the second threshold, the target grid point is a VOC control mechanism; When the target grid point ratio is greater than the second threshold and less than the first threshold, the target grid point is a VOC and NOx mixed control mechanism; When the ratio of the target grid point is greater than the first threshold, the target grid point is a NOx control mechanism.
5. The method for dynamic identification of ozone control mechanisms integrating satellite and ground observations according to claim 4 is characterized in that: The specific steps of constructing a polynomial fitting curve based on the analysis and calculation of the ozone concentration corresponding to the contrast value and the ratio, and obtaining the first threshold and the second threshold through the polynomial fitting curve include: All ratios are divided into multiple intervals based on a preset division interval; Obtain the ozone concentration corresponding to the ratio in each interval, and calculate the mean ozone concentration in each interval; The ratio of each interval was used as the independent variable, and the mean ozone concentration of each interval was used as the dependent variable to construct a fitting curve of a cubic polynomial. The critical ratio corresponding to the cubic polynomial when the ozone maximum occurs is calculated, the derivatives of the curves on both sides of the cubic polynomial maximum point are obtained as -a and a, and the corresponding first threshold and second threshold are obtained.
6. The method for dynamic identification of ozone control mechanisms integrating satellite and ground observations according to claim 1, characterized in that: In step S3, determining the ozone pollution area specifically includes: Based on the ground ozone concentration observation data, the maximum eight-hour daily ozone concentration MDA8 is calculated for the target period. ; MDA8 Concentration higher than 160 μg / areas as ozone polluted areas; And obtain the spatial distribution characteristics of ozone concentration in ozone polluted areas.
7. The method for dynamically identifying ozone control mechanisms by integrating satellite and ground observations according to claim 6, characterized in that: In step S3, the key control area for precursors is determined in the ozone pollution area in combination with the preliminary identification of the ozone control mechanism, specifically including: Identify the ozone control mechanism in the ozone polluted area based on the dynamic identification method in step S2; In ozone polluted areas, The part in the VOC control mechanism is determined as the first area, and the first concentration area in which the HCHO column concentration is above the 80th percentile in the first area is identified, and the first concentration area is the VOC key control area; The part in the NOx control mechanism is determined as the second area, and the second area is identified. The second concentration area where the column concentration is above the 80th percentile, and the first concentration area is the key NOx control area; The part in the mixed control area is determined as the third area, and the third area is identified and a third concentration region where the HCHO column concentration is above the 80th percentile, and the third concentration region is a mixed precursor control region.
8. The method for dynamically identifying ozone control mechanisms by integrating satellite and ground observations according to claim 7, characterized in that: Before the ozone control mechanism of the ozone polluted area is identified based on the dynamic identification method in step S2: Determine land cover type data based on satellite remote sensing and geographic information database; The ozone pollution areas not caused by human emissions are eliminated in combination with the land cover type data, and the ozone pollution areas affected by human influence are retained as the final ozone pollution areas.
9. The method for dynamically identifying ozone control mechanisms by integrating satellite and ground observations according to claim 7, characterized in that: Step S4 specifically includes: The main pollution sources in the key control areas of precursors identified based on sub-meter high-resolution images; In the VOC key control area, focus on identifying industrial enterprises in the area as the main pollution sources; In key NOx control areas, focus on identifying energy-consuming enterprises in the area as the main pollution sources; Mixed precursor control areas, identifying all significant sources of contamination.
10. A method and device for dynamically identifying ozone control mechanisms by integrating satellite and ground observations, characterized in that: include: Satellite remote sensing module, obtains HCHO and Column concentration data; The ground observation module is equipped with multiple air quality monitoring stations to obtain ground ozone concentration observation data; Identification processing module, fusion of satellite inversion HCHO and Column concentration data and ground ozone concentration observation data are used to make a preliminary identification of ozone control mechanisms; ozone pollution areas are determined based on ground ozone concentration observation data, and precursor key control areas are determined in ozone pollution areas in combination with the preliminary identification of ozone control mechanisms; major pollution sources are identified based on precursor key control areas.