Urban air pollution early warning method based on meteorological and environmental monitoring data

Abstract

The invention discloses an urban air pollution early warning method based on meteorological and environmental monitoring data, which relates to the technical field of environmental monitoring, and comprises the following steps: setting a monitoring period and a monitoring area, and establishing an air pollution early warning model according to historical data characteristics; establishing an urban air pollution early warning strategy of the current monitoring period according to the data characteristics predicted by the air pollution early warning model; when the real-time data characteristics of the monitoring area do not conform to the urban air pollution early warning strategy of the current monitoring period, a sentinel node is arranged in the monitoring area, the sentinel node sends detection data to the adjacent monitoring area at regular time, and a real-time data sharing channel is established between the monitoring area and the adjacent monitoring area; the quantitative data of migration and diffusion of pollutants in the atmospheric environment are obtained through the real-time data sharing channel, the air pollution early warning model of the current monitoring period is dynamically adjusted, the urban air pollution early warning strategy of the remaining time period of the current monitoring period is updated, and the early warning accuracy of dynamic environmental pollution is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and specifically to an urban air pollution early warning method based on meteorological and environmental monitoring data. Background Art

[0002] The atmospheric environment is one of the material conditions for human production and life. The quality of the atmospheric environment is closely related to the development of social economy and human health. Therefore, the quality and change trend of the large environment have always been concerned by people, and the theories and methods of evaluation and prediction have been continuously developed and improved in long-term research and practice. In recent years, the theories and methods of early warning have been gradually introduced into environmental science and become a hot spot in contemporary environmental science research.

[0003] Due to the time lag effect of meteorological elements, it is difficult to comprehensively reflect the impact of meteorological conditions on the change of pollutant concentration only with the data of the current moment. The existing forecasting models are obtained on the basis of a large number of long-term experiments, tests and investigations under the conditions of stable weather and relatively fixed pollution sources. Therefore, they have a certain long-term stability and static nature of prediction, and it is very difficult to make timely and effective early warning strategies for real-time dynamic pollution situations. How to use reasonable technical means and theoretical basis to demonstrate and achieve short-term prediction of heavy air pollution events is an urgent problem for us to solve. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide an urban air pollution early warning method based on meteorological and environmental monitoring data, including the following steps: Step S1: Set a monitoring period and several monitoring areas, establish an air pollution early warning model according to the historical data characteristics in the database, the data characteristics include environmental parameters, pollutant types and pollutant quantities, and establish an urban air pollution early warning strategy for the current monitoring period according to the data characteristics predicted by the air pollution early warning model; Step S2: Collect the real-time data characteristics of meteorological and environmental monitoring data in each monitoring area and mark the collection time; when the real-time data characteristics of the monitoring area do not conform to the urban air pollution early warning strategy of the current monitoring period, set a sentinel node in the monitoring area, the sentinel node regularly sends detection data to adjacent monitoring areas of the monitoring area, and establish a real-time data sharing channel between the monitoring area and adjacent monitoring areas, and predict the type cumulative amount of pollutants and the cumulative amount of each type of pollutant in the remaining different time periods of the current monitoring period and the transmission path in the remaining time period of the current monitoring period through the real-time data sharing channel; Step S3: Predict the key characteristic data of the monitoring area and the monitoring area types in the remaining different time periods of the current monitoring period, and dynamically adjust the air pollution early warning model of the current monitoring period, and update the urban air pollution early warning strategy in the remaining time period of the current monitoring period.

[0005] Further, the process of establishing the urban air pollution warning strategy for the current monitoring period based on the data characteristics predicted by the air pollution warning model includes: Set the upper limit of the total number of pollutant types and the upper limit of the number of pollutants of each type; obtain the total number of predicted pollutant types and the number of predicted pollutants of each type in the monitoring area, and compare the total number of predicted pollutant types in the monitoring area with the upper limit of the total number of pollutant types. When the total number of predicted pollutant types in the monitoring area is greater than the upper limit of the total number of pollutant types, mark this monitoring area as a pollution warning monitoring area; when the total number of predicted pollutant types in the monitoring area is less than or equal to the upper limit of the total number of pollutant types, mark this monitoring area as a to-be-detected monitoring area; then compare the number of predicted pollutants of each type in the to-be-detected monitoring area with the corresponding upper limit of the number of pollutants of each type. If there is a pollutant type in the to-be-detected monitoring area whose predicted pollutant quantity is greater than the upper limit of the number of pollutants, mark this to-be-detected monitoring area as a pollution warning monitoring area; if there is no pollutant type in the to-be-detected monitoring area whose predicted pollutant quantity is greater than the upper limit of the number of pollutants, mark this to-be-detected monitoring area as a safety monitoring area.

[0006] Further, the process by which the sentinel node establishes a real-time data sharing channel and obtains the cumulative quantity of pollutant types and the cumulative quantity of pollutants of each type in the remaining different time periods of the current monitoring period through the real-time data sharing channel includes: The sentinel node periodically sends detection data to adjacent monitoring areas in the monitoring area. The detection data determines whether there is a transmission path indicator pointing to this monitoring area in its adjacent monitoring area. If there is a transmission path indicator pointing to this monitoring area, then determine whether this adjacent monitoring area is a pollution warning monitoring area. If this adjacent monitoring area is a pollution warning monitoring area, establish a real-time data sharing channel between the monitoring area and the adjacent monitoring area, obtain the number of pollutant types and the number of pollutants of each type at the current monitoring time in the safety monitoring area, and obtain the type transfer quantity and the transfer quantity of pollutants of each type in the remaining different time periods in the safety monitoring area, and the type transfer-in quantity and the transfer-in quantity of pollutants of each type in the remaining different time periods in the adjacent monitoring area; obtain the cumulative quantity of pollutant types and the cumulative quantity of pollutants of each type in the remaining different time periods of the current monitoring period in the monitoring area based on the type transfer quantity, the transfer quantity of pollutants of each type, the number of pollutant types and the number of pollutants of each type in the safety monitoring area in the remaining different time periods, and the type transfer-in quantity and the transfer-in quantity of pollutants of each type in each adjacent monitoring area in the remaining different time periods.

[0007] Further, the process by which the sentinel node establishes a transmission path indicator and obtains the transmission path through the real-time data sharing channel includes: Predict the pollutant diffusion and transmission route in the current monitoring period based on the environmental parameters, pollutant types, and pollutant quantities in the monitoring area. When the diffusion and transmission route of the pollutants in the monitoring area points to an adjacent monitoring area in the current monitoring period, a transmission path indicator pointing to the adjacent monitoring area is established in the monitoring area; when the monitoring area has a transmission path indicator, it is determined whether the adjacent monitoring area pointed to by the transmission path indicator of the monitoring area has a transmission path indicator. If the adjacent monitoring area has a transmission path indicator, the adjacent monitoring area is marked as a transmission area. The transmission area repeatedly determines whether the adjacent monitoring area pointed to by the transmission path indicator of the transmission area has a transmission path indicator until the adjacent monitoring area pointed to by the transmission path indicator of the transmission area has no transmission path indicator. Connect all the transmission areas and mark them as the transmission path of the monitoring area.

[0008] Further, the process by which the sentinel node obtains the type transfer amount of pollutants and the transfer amount of each type of pollutant in the remaining different time periods of the current monitoring period in the monitoring area includes: Establish a multiple linear regression model of the type transfer amount of pollutants, the transfer amount of each type of pollutant under different environmental parameters based on the type transfer amount of pollutants, the transfer amount of each type of pollutant, and environmental parameters in the monitoring area of several historical monitoring periods. Obtain a multiple linear regression model consistent with the environmental parameters of the remaining different time periods of the current monitoring period and predict the type transfer amount of pollutants and the transfer amount of each type of pollutant in the remaining different time periods of the current monitoring period.

[0009] Further, the process of predicting the monitoring area type in the remaining different time periods of the current monitoring period in the monitoring area includes: The monitoring area types include pollution warning monitoring areas and safety monitoring areas. Compare the type cumulative amount of pollutants and the cumulative amount of each type of pollutant in the remaining different time periods of the current monitoring period in the monitoring area with the upper limit of the total number of pollutant types and the upper limit of the quantity of each type of pollutant to obtain the monitoring area type in the remaining different time periods of the current monitoring period in the monitoring area.

[0010] Further, the process of predicting the key feature data of each monitoring area includes: Obtain the average value of the type cumulative amount of pollutants and the average value of the cumulative amount of each type of pollutant in the remaining different time periods of the current monitoring period, and obtain the quantity of each type of pollutant in the current monitoring area. Perform a weighted average calculation on the average value of the type cumulative amount of pollutants, the average value of the cumulative amount of each type of pollutant, and the quantity of each type of pollutant to obtain the data key score of each type of pollutant in the monitoring area, and mark the pollutant with the highest data key score as the key feature data.

[0011] Further, dynamically adjust the air pollution warning model for the current monitoring period, and update the urban air pollution warning strategy for the remaining time period of the current monitoring period: Set the environmental pollution threshold for the entire region; use the transmission path of the monitoring region, key feature data, the type of the monitoring region at the current monitoring time, and the types of the monitoring regions in different remaining time periods within the current monitoring period as new parameters of the air pollution warning model, and predict the environmental pollution value for the entire region of pollutants in the monitoring region according to the adjusted air pollution warning model. When the environmental pollution value for the entire region of the monitoring region is greater than or equal to the environmental pollution threshold for the entire monitoring region, if the monitoring region is a pollution warning monitoring region, mark the monitoring region as a red air pollution warning monitoring region; if the monitoring region is a safety warning monitoring region, mark the monitoring region as an orange air pollution warning monitoring region; when the environmental pollution value for the entire region of the monitoring region is less than the environmental pollution threshold for the entire monitoring region, if the monitoring region is a pollution warning monitoring region, mark the monitoring region as a yellow air pollution warning monitoring region.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention establishes an air pollution warning model regarding historical data and time based on historical meteorological and environmental data, predicts the future air pollution data of each region of the city, and establishes an urban air pollution warning strategy for the current monitoring period according to the future air pollution data. When the real-time data characteristics of the monitoring region do not conform to the urban air pollution warning strategy for the current monitoring period, the present invention establishes a spatio-temporal trend model regarding historical data and time and space according to the relevant characteristics of historical data and time and space, obtains the future atmospheric environmental pollution transmission paths of each monitoring region, predicts the development trend of environmental pollution based on the growth and reduction laws of environmental pollution in each future period under different meteorological conditions, and provides a scientific basis for pollution source planning decision-making and quality management. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a schematic diagram of a method for warning urban air pollution based on meteorological and environmental monitoring data according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] Next, in combination with the drawings in the embodiments of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0015] As Figure 1 shown, a method for warning urban air pollution based on meteorological and environmental monitoring data includes the following steps: Step S1: Set a monitoring period and several monitoring areas, establish an air pollution early warning model based on the historical data characteristics in the database, where the data characteristics include environmental parameters, pollutant types, and pollutant quantities, and establish an urban air pollution early warning strategy for the current monitoring period based on the data characteristics predicted by the air pollution early warning model; Step S2: Collect the real-time data characteristics of meteorological and environmental monitoring data in each monitoring area and mark the collection time; when the real-time data characteristics of the monitoring area do not conform to the urban air pollution early warning strategy for the current monitoring period, set sentinel nodes in the monitoring area. The sentinel nodes regularly send detection data to adjacent monitoring areas of the monitoring area, and establish a real-time data sharing channel between this monitoring area and the adjacent monitoring areas, and predict the type cumulative amount of pollutants and the cumulative amount of each type of pollutant in the remaining different time periods of the current monitoring period as well as the transmission path in the remaining time periods of the current monitoring period through the real-time data sharing channel; Step S3: Predict the key feature data of the monitoring area and the types of monitoring areas in the remaining different time periods of the current monitoring period, and dynamically adjust the air pollution early warning model for the current monitoring period, and update the urban air pollution early warning strategy for the remaining time periods of the current monitoring period.

[0016] It should be further noted that in the specific implementation process, the process of establishing an urban air pollution early warning strategy for the current monitoring period based on the data characteristics predicted by the air pollution early warning model includes: Set the upper limit of the total number of pollutant types and the upper limit of the quantity of each type of pollutant; obtain the total predicted number of pollutant types and the predicted quantity of each type of pollutant in the monitoring area, compare the total predicted number of pollutant types in the monitoring area with the upper limit of the total number of pollutant types. When the total predicted number of pollutant types in the monitoring area is greater than the upper limit of the total number of pollutant types, mark this monitoring area as a pollution warning monitoring area; when the total predicted number of pollutant types in the monitoring area is less than or equal to the upper limit of the total number of pollutant types, mark this monitoring area as a to-be-detected monitoring area; then compare the predicted quantity of each type of pollutant in the to-be-detected monitoring area with the corresponding upper limit of the quantity of each type of pollutant. If there is a pollutant type in the to-be-detected monitoring area whose predicted quantity is greater than the upper limit of the quantity of the pollutant, mark this to-be-detected monitoring area as a pollution warning monitoring area; if there is no pollutant type in the to-be-detected monitoring area whose predicted quantity is greater than the upper limit of the quantity of the pollutant, mark this to-be-detected monitoring area as a safety monitoring area.

[0017] It should be further noted that in the specific implementation process, the process in which the sentinel nodes establish a real-time data sharing channel and obtain the type cumulative amount of pollutants and the cumulative amount of each type of pollutant in the remaining different time periods of the current monitoring period through the real-time data sharing channel includes: The sentinel node periodically sends detection data to adjacent monitoring areas in the monitoring area. The detection data is used to determine whether there are transmission path indicators pointing to this monitoring area in its adjacent monitoring areas. If there are transmission path indicators pointing to this monitoring area, it is then determined whether the adjacent monitoring area is a pollution warning monitoring area. If the adjacent monitoring area is a pollution warning monitoring area, a real-time data sharing channel is established between the monitoring area and the adjacent monitoring area, and the type quantity of pollutants and the quantity of each type of pollutant at the current monitoring time of the safety monitoring area are obtained. Also, the type transfer quantity of pollutants and the transfer quantity of each type of pollutant in the remaining different time periods of the safety monitoring area, the type transfer-in quantity of pollutants and the transfer-in quantity of each type of pollutant in the remaining different time periods of the adjacent monitoring area are obtained; based on the type transfer quantity of pollutants, the transfer quantity of each type of pollutant, the type quantity of pollutants and the quantity of each type of pollutant in the remaining different time periods of the safety monitoring area, and the type transfer-in quantity of pollutants and the transfer-in quantity of each type of pollutant in the remaining different time periods of each adjacent monitoring area, the type cumulative quantity of pollutants and the cumulative quantity of each type of pollutant in the remaining different time periods of the current monitoring cycle of the monitoring area are obtained.

[0018] It should be further noted that, in the specific implementation process, the process by which the sentinel node establishes a transmission path indicator and obtains the transmission path through the real-time data sharing channel includes: Predict the pollutant diffusion and transmission route of the current monitoring cycle based on the environmental parameters, pollutant types and pollutant quantities in the monitoring area. The environmental parameters include temperature, air pressure, wind direction, wind speed, precipitation, and evaporation. When the diffusion and transmission route of the pollutants in the monitoring area in the current monitoring cycle points to an adjacent monitoring area, a transmission path indicator pointing to the adjacent monitoring area is established in the monitoring area; when the monitoring area has a transmission path indicator, it is determined whether there is a transmission path indicator in the adjacent monitoring area pointed to by the transmission path indicator of this monitoring area. If there is a transmission path indicator in the adjacent monitoring area, the adjacent monitoring area is marked as a transmission area. The transmission area repeatedly determines whether there is a transmission path indicator in the adjacent monitoring area pointed to by the transmission path indicator of this transmission area until there is no transmission path indicator in the adjacent monitoring area pointed to by the transmission path indicator of the transmission area. All the transmission areas are connected and marked as the transmission path of the monitoring area.

[0019] It should be further noted that, in the specific implementation process, the process by which the sentinel node obtains the type transfer quantity of pollutants and the transfer quantity of each type of pollutant in the remaining different time periods of the current monitoring cycle of the monitoring area includes: A multiple linear regression model of the type transfer amount of pollutants, the transfer amount of each type of pollutant under different environmental parameters is established based on the type transfer amount of pollutants, the transfer amount of each type of pollutant and environmental parameters in several historical monitoring periods, and a multiple linear regression model consistent with the environmental parameters in different time periods of the remaining current monitoring period is obtained to predict the type transfer amount of pollutants and the transfer amount of each type of pollutant in different time periods of the remaining current monitoring period.

[0020] It should be further noted that in the specific implementation process, the process of predicting the type of the monitoring area in different time periods of the remaining current monitoring period of the monitoring area includes: The type of the monitoring area includes a pollution warning monitoring area and a safety monitoring area. The cumulative amount of the type of pollutants and the cumulative amount of each type of pollutant in different time periods of the remaining current monitoring period of the monitoring area are compared with the upper limit of the total number of pollutant types and the upper limit of the number of each type of pollutant to obtain the type of the monitoring area in different time periods of the remaining current monitoring period of the monitoring area.

[0021] It should be further noted that in the specific implementation process, the process of predicting the key feature data of each monitoring area includes: Obtain the average value of the cumulative amount of the type of pollutants and the average value of the cumulative amount of each type of pollutant in different time periods of the remaining current monitoring period, and obtain the number of each type of pollutant in the current monitoring area. The weighted average calculation of the average value of the cumulative amount of the type of pollutants, the average value of the cumulative amount of each type of pollutant and the number of each type of pollutant is used to obtain the key score of the data of each type of pollutant in the monitoring area, and the pollutant with the highest key score of the data is marked as the key feature data.

[0022] It should be further noted that in the specific implementation process, the air pollution warning model in the current monitoring period is dynamically adjusted, and the urban air pollution warning strategy in the remaining time period of the current monitoring period is updated: Set the environmental pollution threshold for the whole region; take the transmission path of the monitoring area, the key feature data, the type of the monitoring area at the current monitoring time, and the type of the monitoring area in different time periods of the remaining current monitoring period as the new parameters of the air pollution warning model, and predict the environmental pollution value of the whole region of the pollutants in the monitoring area according to the adjusted air pollution warning model. When the environmental pollution value of the whole region of the monitoring area is greater than or equal to the environmental pollution threshold of the whole monitoring area, if the monitoring area is a pollution warning monitoring area, mark the monitoring area as a red air pollution warning monitoring area; if the monitoring area is a safety warning monitoring area, mark the monitoring area as an orange air pollution warning monitoring area; when the environmental pollution value of the whole region of the monitoring area is less than the environmental pollution threshold of the whole monitoring area, if the monitoring area is a pollution warning monitoring area, mark the monitoring area as a yellow air pollution warning monitoring area.

[0023] It should be further noted that, in the specific implementation process, the monitoring period is usually set as 1 day, and 1 h is used as the fixed time period. When the real-time data characteristics at the 12th hour do not conform to the air pollution warning strategy of the day, the air pollution warning model within the remaining 12 hours of the day is dynamically adjusted and the air pollution warning strategy is updated. When the real-time data characteristics within the remaining 12 hours do not conform to the updated air pollution warning strategy, the fixed time period of 1 h is adjusted to 0.5 h as the fixed time period, and new parameters of the air pollution warning model are established with the characteristic data of a shorter fixed time period, and the air pollution warning strategy is updated until the real-time data characteristics of the remaining time period conform to the updated air pollution warning strategy; Subsequently, the pollution warning model adjusted for this 1 day is sent to the historical database, the pollution warning models of this 1 day and the previous 2 days are obtained, and the pollution warning models of these 3 days are used as the rolling update prediction model, and the time series method is used to predict the next 3 days using the pollution warning model in the rolling update prediction model. When the pollution warning model in the rolling update prediction model within the next 1 day does not conform to the air pollution warning strategy of the day, the pollution warning model in the rolling update prediction model is deleted, and then the pollution warning model adjusted for this 1 day is sent to the rolling update prediction model.

[0024] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An urban air pollution early warning method based on meteorological and environmental monitoring data, characterized in that, Including the following steps: Step S1: Set a monitoring period and a number of monitoring areas, establish an air pollution early warning model based on the historical data characteristics in the database, where the data characteristics include environmental parameters, pollutant types, and pollutant quantities, and establish an urban air pollution early warning strategy for the current monitoring period according to the data characteristics predicted by the air pollution early warning model; Step S2: Collect the real-time data characteristics of meteorological and environmental monitoring data in each monitoring area and mark the collection time; when the real-time data characteristics of the monitoring area do not conform to the urban air pollution early warning strategy for the current monitoring period, set sentinel nodes in the monitoring area. The sentinel nodes regularly send detection data to adjacent monitoring areas of the monitoring area, and establish a real-time data sharing channel between this monitoring area and adjacent monitoring areas. Predict the type cumulative amount of pollutants and the cumulative amount of each type of pollutant in the remaining different time periods of the current monitoring period and the transmission path in the remaining time periods of the current monitoring period through the real-time data sharing channel; Step S3: Predict the key characteristic data of the monitoring area and the monitoring area types in the remaining different time periods of the current monitoring period, and dynamically adjust the air pollution early warning model for the current monitoring period, and update the urban air pollution early warning strategy for the remaining time periods of the current monitoring period.

2. The urban air pollution early warning method based on meteorological and environmental monitoring data according to claim 1, wherein, The process of establishing an urban air pollution early warning strategy for the current monitoring period according to the data characteristics predicted by the air pollution early warning model includes: Set the upper limit of the total number of pollutant types and the upper limit of the quantity of each type of pollutant; obtain the total number of predicted pollutant types and the predicted quantity of each type of pollutant in the monitoring area, and compare the total number of predicted pollutant types in the monitoring area with the upper limit of the total number of pollutant types. When the total number of predicted pollutant types in the monitoring area is greater than the upper limit of the total number of pollutant types, mark this monitoring area as a pollution early warning monitoring area; when the total number of predicted pollutant types in the monitoring area is less than or equal to the upper limit of the total number of pollutant types, mark this monitoring area as a to-be-detected monitoring area; then compare the predicted quantity of each type of pollutant in the to-be-detected monitoring area with the corresponding upper limit of the quantity of each type of pollutant. If there is a pollutant type in the to-be-detected monitoring area with a predicted quantity greater than the upper limit of the quantity of the pollutant, mark this to-be-detected monitoring area as a pollution early warning monitoring area; if there is no pollutant type in the to-be-detected monitoring area with a predicted quantity greater than the upper limit of the quantity of the pollutant, mark this to-be-detected monitoring area as a safety monitoring area.

3. The urban air pollution early warning method based on meteorological and environmental monitoring data according to claim 2, characterized in that, The process by which the sentinel node establishes a real-time data sharing channel and obtains the type cumulative amount of pollutants and the cumulative amount of each type of pollutant in the remaining different time periods of the current monitoring period through the real-time data sharing channel includes: The sentinel node periodically sends detection data to adjacent monitoring areas in the monitoring area. The detection data is used to determine whether there are transmission path indicators pointing to this monitoring area in its adjacent monitoring areas. If there are transmission path indicators pointing to this monitoring area, it is then determined whether the adjacent monitoring area is a pollution warning monitoring area. If the adjacent monitoring area is a pollution warning monitoring area, a real-time data sharing channel is established between the monitoring area and the adjacent monitoring area. The type quantity of pollutants and the quantity of each type of pollutant at the current monitoring time of the safety monitoring area are obtained, and the type transfer quantity of pollutants and the transfer quantity of each type of pollutant in the remaining different time periods of the safety monitoring area, the type transfer-in quantity of pollutants and the transfer-in quantity of each type of pollutant in the remaining different time periods of the adjacent monitoring area are obtained; based on the type transfer quantity of pollutants, the transfer quantity of each type of pollutant, the type quantity of pollutants and the quantity of each type of pollutant in the remaining different time periods of the safety monitoring area, and the type transfer-in quantity of pollutants and the transfer-in quantity of each type of pollutant in the remaining different time periods of each adjacent monitoring area, the type cumulative quantity of pollutants and the cumulative quantity of each type of pollutant in the remaining different time periods of the current monitoring cycle of the monitoring area are obtained.

4. The urban air pollution warning method based on meteorological and environmental monitoring data according to claim 3, characterized in that, The process by which the sentinel node establishes a transmission path indicator and obtains the transmission path through the real-time data sharing channel includes: Predict the pollutant diffusion transmission route of the current monitoring cycle according to the environmental parameters, pollutant types and pollutant quantities of the monitoring area. When the diffusion transmission route of the pollutants in the monitoring area in the current monitoring cycle points to an adjacent monitoring area, a transmission path indicator pointing to the adjacent monitoring area is established in the monitoring area; when the monitoring area has a transmission path indicator, it is determined whether there is a transmission path indicator in the adjacent monitoring area pointed to by the transmission path indicator of this monitoring area. If there is a transmission path indicator in the adjacent monitoring area, the adjacent monitoring area is marked as a transmission area. The transmission area repeatedly determines whether there is a transmission path indicator in the adjacent monitoring area pointed to by the transmission path indicator of this transmission area until there is no transmission path indicator in the adjacent monitoring area pointed to by the transmission path indicator of the transmission area. All transmission areas are connected and marked as the transmission path of the monitoring area.

5. The urban air pollution warning method based on meteorological and environmental monitoring data according to claim 4, characterized in that, The process by which the sentinel node obtains the type transfer quantity of pollutants and the transfer quantity of each type of pollutant in the remaining different time periods of the current monitoring cycle of the monitoring area includes: Establish a multiple linear regression model of the type transfer quantity of pollutants and the transfer quantity of each type of pollutant under different environmental parameters based on the type transfer quantity of pollutants, the transfer quantity of each type of pollutant and environmental parameters of the monitoring area in several historical monitoring cycles. Obtain the multiple linear regression model consistent with the environmental parameters of the remaining different time periods of the current monitoring cycle and predict the type transfer quantity of pollutants and the transfer quantity of each type of pollutant in the remaining different time periods of the current monitoring cycle.

6. The urban air pollution warning method based on meteorological and environmental monitoring data according to claim 5, characterized in that, The process of predicting the monitoring area type in the remaining different time periods of the current monitoring cycle of the monitoring area includes: The types of the monitored areas include pollution early warning monitoring areas and safety monitoring areas. The cumulative amounts of pollutant types in the remaining different time periods of the current monitoring cycle of the monitored area and the cumulative amounts of each type of pollutant are compared with the upper limit of the total number of pollutant types and the upper limit of the quantity of each type of pollutant to obtain the types of the monitored areas in the remaining different time periods of the current monitoring cycle.

7. The urban air pollution warning method based on meteorological and environmental monitoring data according to claim 6, wherein The process of predicting the key feature data of each monitored area includes: Obtaining the average value of the cumulative amount of pollutant types and the average value of the cumulative amount of each type of pollutant in the remaining different time periods of the current monitoring cycle, and obtaining the quantity of each type of pollutant in the current monitored area. The weighted average calculation is performed on the average value of the cumulative amount of pollutant types, the average value of the cumulative amount of each type of pollutant, and the quantity of each type of pollutant to obtain the key data scores of each type of pollutant in the monitored area, and the pollutant with the highest data key score is marked as the key feature data.

8. A method for urban air pollution early warning based on meteorological and environmental monitoring data according to claim 7, characterized in that, Dynamically adjust the air pollution early warning model for the current monitoring cycle and update the urban air pollution early warning strategy for the remaining time period of the current monitoring cycle: Set the environmental pollution threshold for the entire area; use the transmission path of the monitored area, the key feature data, the type of the monitored area at the current monitoring time, and the types of the monitored areas in the remaining different time periods within the current monitoring cycle as the new parameters of the air pollution early warning model, and predict the environmental pollution value of the entire area of pollutants in the monitored area according to the adjusted air pollution early warning model. When the environmental pollution value of the entire area of the monitored area is greater than or equal to the environmental pollution threshold of the entire monitored area, if the monitored area is a pollution early warning monitoring area, mark the monitored area as a red air pollution early warning monitoring area; if the monitored area is a safety early warning monitoring area, mark the monitored area as an orange air pollution early warning monitoring area; when the environmental pollution value of the entire area of the monitored area is less than the environmental pollution threshold of the entire monitored area, if the monitored area is a pollution early warning monitoring area, mark the monitored area as a yellow air pollution early warning monitoring area.

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