Real-time monitoring system and method based on urban air pollutants

Abstract

The present invention relates to the field of atmospheric monitoring technology, specifically to a real-time monitoring system and method based on urban atmospheric pollutants, wherein the system includes a pollution real-time monitoring module, a pollution source tracking module, a pollution trend analysis module, and an early warning and health analysis module. In the present invention, by combining real-time pollution data with a geographic information system, the tracking accuracy of pollution sources and the visualization of dynamic changes are enhanced, and the integrated technology improves the practicality of environmental monitoring data, making the update of pollution distribution more real-time and accurate. By statistically analyzing historical and real-time data, the diffusion trend of future pollutants can be more effectively predicted, thereby providing more targeted health warnings and protective measures. Automated alarm technology enables rapid response at the early stage of pollution events, reducing potential health risks, and predictive analysis provides a scientific basis for decision-making, optimizes urban air quality management strategies, and significantly enhances the ability of the public and policy makers to respond to future environmental changes.

Description

Technical Field

[0001] The present invention relates to the field of air monitoring technology, and in particular to a real-time monitoring system and method based on urban air pollutants. Background Art

[0002] The field of atmospheric monitoring technology focuses on the development and application of a variety of methods and equipment for the detection and analysis of pollutants in the atmosphere, including but not limited to real-time monitoring of particulate matter, hazardous gases (such as sulfur dioxide, carbon monoxide and nitrogen oxides), and volatile organic compounds. It covers a variety of monitoring systems from ground stations to satellite remote sensing, as well as the use of portable and fixed sensors, which can provide a continuous stream of data for environmental policy making, public health protection and air quality management.

[0003] Among them, the real-time monitoring system of urban air pollutants involves a specific technical configuration and method, which is designed to monitor the level of air pollution in real time in the urban environment. The main purpose of the system is to provide accurate air quality data in order to respond promptly to possible environmental health risks, improve urban air quality management, and support environmental regulatory agencies in making decisions on the formulation and implementation of air quality standards. The monitoring system helps the public understand the current air quality conditions and enhance public awareness of air pollution problems and response measures.

[0004] Although existing technologies provide extensive monitoring from the ground to satellites, they have obvious shortcomings in real-time data processing and accurate dynamic tracking. Existing methods focus more on data collection rather than in-depth analysis and real-time application of data. Especially in rapidly changing urban environments, this processing delay leads to an untimely response to pollution peaks. In addition, existing systems are not sufficient in integrating and analyzing collected data, especially in predicting future pollution events and formulating emergency response measures, which limits their effectiveness in environmental management and public health protection. For example, when high-value pollution areas are not quickly located and responded to, critical opportunities for preventing and mitigating serious pollution incidents may be missed, increasing environmental and health risks. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a real-time monitoring system and method based on urban air pollutants.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: A real-time monitoring system based on urban air pollutants comprises:

[0007] The pollution real-time monitoring module collects data from air quality monitors and meteorological sensors, performs signal synchronization and filtering, corrects data time series, standardizes environmental parameters, and generates real-time pollution data;

[0008] The pollution source tracking module identifies high-value pollution areas based on the real-time pollution data and the pollution threshold, analyzes the concentration trend of high-value pollution areas, uses GIS to match pollution points with actual geographical locations according to the analysis results, updates the pollution distribution map in real time, tracks the dynamic changes of pollution sources, and draws a dynamic tracking map of pollution sources;

[0009] The pollution trend analysis module uses the pollution source dynamic tracking diagram to analyze the impact range of the pollution source, calculate the pollution propagation speed, and use statistical analysis to compare historical data of the same period based on the calculation results to predict the future diffusion direction of pollutants and the potential highest concentration area, and generate pollution trend prediction records;

[0010] The early warning and health analysis module evaluates the pollution level reached in the city based on the pollution trend prediction records, sets health risk thresholds, automatically issues alarms for areas exceeding the threshold, formulates health protection measures, and generates health protection guidelines.

[0011] As a further solution of the present invention, the step of acquiring the real-time pollution data is:

[0012] Collect raw data from air quality monitors and meteorological sensors, using the formula,

[0013] ,

[0014] Calculate the synchronized signal value , generate synchronization signal data, where, Represents the signal strength of the air quality monitor, Represents the signal strength of the meteorological sensor, represents the attenuation coefficient, which is used to adjust the impact of the two data sources, and t represents the time point;

[0015] The synchronization signal data is filtered using the formula:

[0016] ,

[0017] Generate filtered signal data ,in, is the weight coefficient, which ensures the filtering effect and the data characteristics of the matching difference time point. represent The first N data points of , where N is the window size of the filter;

[0018] The filtered signal data is time corrected using the formula:

[0019] ,

[0020] Generate time-corrected data ,in, represents the time deviation, is the adjustment factor used to refine the effect of time correction;

[0021] The time-corrected data is standardized using the formula,

[0022] ,

[0023] Generate real-time pollution data ,in, and They are The mean and standard deviation of , f is a small positive number to avoid division by zero errors.

[0024] As a further solution of the present invention, the steps for analyzing the central tendency of the high-pollution area are:

[0025] Based on the real-time pollution data, a pollution threshold is defined, using the formula:

[0026] ,

[0027] Filter the pollution readings that exceed the pollution threshold to form a high pollution data set H, where D represents the pollution data monitored in real time, d is a single data point, and T is the set pollution threshold;

[0028] Statistical analysis is performed on the highly polluted data set to analyze the degree of pollution concentration, using the formula,

[0029] ,

[0030] and

[0031] ,

[0032] Calculate the average and standard deviation , generate pollution trend analysis results, where is the element in the highly polluted data set, n is the number of elements in H;

[0033] Based on the pollution trend analysis results, cluster analysis of polluted areas is performed using the formula:

[0034] ,

[0035] Calculate the weighted central location value C and generate the cluster analysis results.

[0036] As a further solution of the present invention, the steps of drawing the pollution source dynamic tracking diagram are:

[0037] Based on the cluster analysis results, GIS is connected with the geographic coordinate database and the formula is used.

[0038] ,

[0039] Calculate the mapping value M between the cluster center and the geographic location, and output the geographic mapping result, where m is the number of clustering results. and Respectively represent the cluster center value and the corresponding geographic coordinate point;

[0040] According to the geographic mapping results, dynamic update is performed using the formula:

[0041] ,

[0042] Calculate the updated pollution data U and output a real-time updated pollution distribution map, where H is the new real-time pollution data;

[0043] The real-time updated pollution distribution map is used to continuously track the dynamic changes of pollution sources, display the real-time changes of pollution, and draw and output a dynamic tracking map of pollution sources.

[0044] As a further solution of the present invention, the steps for calculating the pollution propagation speed are:

[0045] Based on the pollution source dynamic tracking map, the real-time location, intensity and type data of the pollution source are collected, and the formula is used.

[0046] ,

[0047] Get the actual information of the i-th pollution source , generate detailed information table for each pollution source, where and Represents geographic coordinates, represents the pollution intensity, Represents the pollutant type, Represents monitoring time;

[0048] Based on the detailed information table for each pollution source, using the formula,

[0049] ,

[0050] Calculate the impact intensity of the i-th pollution source on the surrounding environment , draw an impact range diagram, where and is the attenuation coefficient, is the distance from pollution source i to observation point q, represents the natural exponential function;

[0051] Based on the impact range diagram, a dynamic simulation is performed using the formula:

[0052] ,

[0053] Calculate the propagation velocity V of pollutants and generate pollution propagation velocity analysis records, where: and Represent the changes in pollution intensity at consecutive time points, is the time interval, and Q represents the number of time points.

[0054] As a further solution of the present invention, the steps for obtaining the pollution trend prediction record are:

[0055] Using the pollution transmission speed analysis records, compared with the historical pollution data of the same period, the formula is adopted.

[0056] ,

[0057] Calculate the correlation coefficient X, evaluate the similarity between historical and current data, and generate historical data comparison results, where K represents the pollution transmission speed during the same period in history. is the cross-mean, and is the average value;

[0058] According to the historical data comparison results, combined with the current environmental parameters, the formula is used:

[0059] ,

[0060] Calculate the environmental impact prediction value F and output the future pollution diffusion direction map, where: is the adjustment factor, It is an environmental factor The weight of, Z represents the number of environmental factors;

[0061] Using the future pollution diffusion direction map, the formula is adopted,

[0062] ,

[0063] Calculate the predicted value G of the highest pollution concentration area, predict the potential highest pollution concentration area, and generate pollution trend prediction records, where: is the sensitivity factor of region j, J represents the total number of regions, Indicates the maximum value.

[0064] As a further solution of the present invention, the steps for obtaining the health protection guide are:

[0065] Based on the pollution trend prediction records, the real-time monitoring data of the city and the historical pollution records are integrated, and the formula is adopted.

[0066] ,

[0067] Calculate the weighted average pollution level for a city , generating a comprehensive record of pollution levels, where Indicates the weight of the corresponding days, reflecting the reliability and importance of the data. is the pollution index on the i-th day, and A represents the total number of days;

[0068] Based on the comprehensive record of pollution levels, the formula is used.

[0069] ,

[0070] Calculate the health risk threshold Y, automatically issue an alarm when the threshold is exceeded, and generate an over-threshold alarm record, where k is a coefficient adjusted based on health research, which is used to identify areas that exceed this threshold and automatically issue an alarm, is the natural logarithm, which is used to adjust the sensitivity of the threshold to high pollution levels;

[0071] Based on the above-threshold alarm records, health protection measures are formulated and issued, and health protection guidelines are generated.

[0072] The real-time monitoring method based on urban air pollutants includes the following steps:

[0073] S1: Collect data from air quality monitors and meteorological sensors, perform signal synchronization and filtering, perform time correction and standardization on the filtered signal data, and generate real-time pollution data;

[0074] S2: Based on the real-time pollution data, a pollution threshold is defined, pollution readings exceeding the pollution threshold are screened, statistical analysis is performed, the degree of pollution concentration is analyzed, a weighted central position value is calculated, and a cluster analysis result is generated;

[0075] S3: Based on the cluster analysis results, connect with the geographic coordinate library, calculate the mapping value between the cluster center and the geographic location, update the pollution distribution map in real time, continuously track the dynamic changes of the pollution source, draw and output the dynamic tracking map of the pollution source;

[0076] S4: Based on the pollution source dynamic tracking diagram, collect the real-time location, intensity and type data of the pollution source, calculate the impact intensity of the pollution source on the surrounding environment, and perform dynamic simulation to calculate the propagation speed of pollutants and generate pollution propagation speed analysis records;

[0077] S5: using the pollution propagation speed analysis record, comparing it with the historical pollution data of the same period, evaluating the similarity between historical and current data, combining it with current environmental parameters, calculating the environmental impact prediction value, predicting the potential highest pollution concentration area, and generating a pollution trend prediction record;

[0078] S6: Based on the pollution trend forecast records, the city’s real-time monitoring data and historical pollution records are integrated to calculate the city’s weighted average pollution level and health risk threshold. When the threshold is exceeded, an alarm is automatically issued, health protection measures are formulated and issued, and health protection guidelines are generated.

[0079] Compared with the prior art, the advantages and positive effects of the present invention are:

[0080] In the present invention, by combining real-time pollution data with geographic information systems, the tracking accuracy of pollution sources and the visualization of dynamic changes are enhanced, and the integrated technology improves the practicability of environmental monitoring data, making the update of pollution distribution more real-time and accurate. By statistically analyzing historical and real-time data, the diffusion trend of future pollutants can be more effectively predicted, thereby providing more targeted health warnings and protective measures. Automated alarm technology enables rapid response in the early stages of pollution events, reducing potential health risks. Predictive analysis provides a scientific basis for decision-making, optimizes urban air quality management strategies, and significantly enhances the ability of the public and policy makers to respond to future environmental changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 is a system flow chart of the present invention;

[0082] Figure 2 This is a flowchart for obtaining real-time pollution data of the present invention;

[0083] Figure 3 The flowchart of the analysis of the concentration trend of the high-value pollution area of ​​the present invention;

[0084] Figure 4 A flow chart for drawing a dynamic tracking diagram of pollution sources according to the present invention;

[0085] Figure 5 is a flow chart for calculating the pollution propagation speed of the present invention;

[0086] Figure 6 A flowchart for obtaining pollution trend prediction records of the present invention;

[0087] Figure 7 The figure is a flow chart for obtaining the health protection guide of the present invention. DETAILED DESCRIPTION

[0088] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0089] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0090] See also Figure 1 , the real-time monitoring system based on urban air pollutants includes:

[0091] The pollution real-time monitoring module collects data from air quality monitors and meteorological sensors, performs signal synchronization and filtering, corrects data time series, standardizes environmental parameters, and generates real-time pollution data;

[0092] The pollution source tracking module is based on real-time pollution data and pollution thresholds to identify high-value pollution areas, analyze the concentration trend of high-value pollution areas, use GIS to match pollution points with actual geographical locations based on the analysis results, update pollution distribution maps in real time, track the dynamic changes of pollution sources, and draw dynamic tracking maps of pollution sources;

[0093] The pollution trend analysis module uses the pollution source dynamic tracking map to analyze the impact range of the pollution source, calculate the pollution propagation speed, and use statistical analysis to compare historical data of the same period based on the calculation results to predict the future diffusion direction of pollutants and the potential highest concentration area, and generate pollution trend prediction records;

[0094] The early warning and health analysis module evaluates the pollution level reached in the city based on pollution trend forecast records, sets health risk thresholds, automatically issues alarms for areas exceeding the threshold, formulates health protection measures, and generates health protection guidelines.

[0095] Real-time pollution data includes signal synchronization data, filtered data, time series correction data and environmental parameter standardization data. The dynamic tracking map of pollution sources includes the matching results of high-value pollution areas, real-time pollution distribution maps and dynamic change tracking maps. The pollution trend prediction records include the assessment results of the pollution impact range, the calculation results of the pollution propagation speed, the analysis records of the future pollutant diffusion direction and the identification results of potential highest concentration areas. The health protection guidelines include the assessment results of urban pollution levels, health risk thresholds, alarm issuance records and health protection measures.

[0096] See also Figure 2 ,The steps to obtain real-time pollution data are:

[0097] Collect raw data from air quality monitors and meteorological sensors, using the formula,

[0098] ,

[0099] Calculate the synchronized signal value , generate synchronization signal data, where, Represents the signal strength of the air quality monitor, Represents the signal strength of the meteorological sensor, represents the attenuation coefficient, which is used to adjust the impact of the two data sources, and t represents the time point;

[0100] The synchronous signal data is filtered using the formula:

[0101] ,

[0102] Generate filtered signal data ,in, is the weight coefficient, which ensures the filtering effect and the data characteristics of the matching difference time point. represent The first N data points of , where N is the window size of the filter;

[0103] The filtered signal data is time corrected using the formula,

[0104] ,

[0105] Generate time-corrected data ,in, represents the time deviation, is the adjustment factor used to refine the effect of time correction;

[0106] The time-corrected data were standardized using the formula,

[0107] ,

[0108] Generate real-time pollution data ,in, and They are The mean and standard deviation of , f is a small positive number to avoid division by zero errors.

[0109] : The signal strength of the air quality monitor, the value collected at t=0 is 150 units;

[0110] : Signal strength of meteorological sensor, the value at the same time t is 100 units;

[0111] : Attenuation coefficient, used to balance the weights of the two signals, adjusted according to historical data, set to 0.1;

[0112] t: time variable, the specific time considered is t=0.

[0113] calculate The value of when t = 0 and =1:

[0114] ,

[0115] Substitution and , calculated: ,

[0116] Indicates the signal value after synchronization. At this time, the synchronization signal at t=0 is 150 units;

[0117] N: filter window size, set to 5;

[0118] : Dynamic weight coefficient, adjusted according to position i, set , , , ;

[0119] : The signals of the previous N moments are collected , , , , ;

[0120] Sum calculation:

[0121] ,

[0122] but: ;

[0123] : represents the filtered signal. At this time, the filtered signal at t=0 is 28.2 units;

[0124] : Time deviation, set according to the system synchronization error, is +1 second;

[0125] :Adjustment coefficient, set to ;

[0126] :The above calculation The value of delaying 1 second is 30;

[0127] Since t=0, then:

[0128] ,

[0129] ,

[0130] : is the signal after time correction, at this time t=0 the correction signal is 30 units;

[0131] and : Mean and standard deviation, the calculated mean is 25 and the standard deviation is 5;

[0132] f: A small positive number to avoid division by zero errors, set to 0.001.

[0133] Combining the above calculation results, substituting them into the formula, we get:

[0134] ,

[0135] It represents the standardized real-time pollution data. At this time, the standardized value of t=0 is about 0.999, which can be used for environmental quality assessment.

[0136] See also Figure 3 , the analysis steps of the central tendency of high pollution value areas are:

[0137] Based on real-time pollution data, the pollution threshold is defined and the formula is used.

[0138] ,

[0139] Filter the pollution readings that exceed the pollution threshold to form a high pollution data set H, where D represents the pollution data monitored in real time, d is a single data point, and T is the set pollution threshold;

[0140] Statistical analysis of highly polluted data sets was performed to analyze the degree of pollution concentration, using the formula,

[0141] ,

[0142] and

[0143] ,

[0144] Calculate the average and standard deviation , generate pollution trend analysis results, where is the element in the highly polluted data set, n is the number of elements in H;

[0145] Based on the results of pollution trend analysis, cluster analysis of polluted areas was carried out using the formula:

[0146] ,

[0147] Calculate the weighted central location value C and generate the cluster analysis results.

[0148] The monitored data set D is .

[0149] Set T = 75 micrograms / cubic meter for screening, the result is , that is, these three values ​​exceed the threshold T=75;

[0150] Calculate the average :

[0151] ,

[0152] Calculating the standard deviation :

[0153] ,

[0154] Indicates that the pollution data is scattered relative to the mean within the range.

[0155] set up , , ;

[0156] calculate :

[0157] For each Calculate weights:

[0158] ,

[0159] ,

[0160] ,

[0161] Calculation of weighted average:

[0162] ,

[0163] The weighted center location value is calculated to be 55.08. This value represents the estimated location where the pollution is most concentrated after taking into account the difference in distance from the average value, which helps to accurately identify and locate the most polluted areas.

[0164] See also Figure 4 , the steps for drawing the pollution source dynamic tracking map are:

[0165] Based on the cluster analysis results, GIS is connected with the geographic coordinate database and the formula is used.

[0166] ,

[0167] Calculate the mapping value M between the cluster center and the geographic location, and output the geographic mapping result, where m is the number of clustering results. and Respectively represent the cluster center value and the corresponding geographic coordinate point;

[0168] According to the results of geographic mapping, dynamic updates are performed using the formula:

[0169] ,

[0170] Calculate the updated pollution data U and output a real-time updated pollution distribution map, where H is the new real-time pollution data;

[0171] Utilize the pollution distribution map updated in real time to continuously track the dynamic changes of pollution sources, display the real-time changes of pollution, draw and output the dynamic tracking map of pollution sources.

[0172] When connecting with the geographic coordinate library through GIS, first select GIS software, including ArcGIS or QGIS. The geographic coordinate library is a geographic data set provided by government agencies or public data sources. Directly import the acquired geographic coordinate library into the GIS system, integrate multiple data sources in the GIS system, perform coordinate conversion, data cleaning, and spatial data indexing, and then directly obtain geographic coordinate points.

[0173] Set cluster centers for , geographic coordinate library for ;

[0174] Substitute into the formula to calculate M:

[0175] ,

[0176] The M value reflects the mapping strength between the cluster center and the geographic location, and a larger value indicates a closer match.

[0177] Continue to use the M=15500 obtained in the previous calculation, the high pollution data set .

[0178] Substituting into the formula, we get: ;

[0179] The results show that the update operation basically keeps the original contaminated data unchanged.

[0180] Simultaneously and continuously track the dynamic changes of pollution sources and draw dynamic tracking maps of pollution sources to reveal real-time changes in pollution.

[0181] See also Figure 5 , the calculation steps of pollution propagation speed are:

[0182] Based on the pollution source dynamic tracking map, the real-time location, intensity and type data of pollution sources are collected, and the formula is used.

[0183] ,

[0184] Get the actual information of the i-th pollution source , generate detailed information table for each pollution source, where and Represents geographic coordinates, represents the pollution intensity, Represents the pollutant type, Represents monitoring time;

[0185] Based on the detailed information table of each pollution source, the formula is used.

[0186] ,

[0187] Calculate the impact intensity of the i-th pollution source on the surrounding environment , draw an impact range diagram, where and is the attenuation coefficient, is the distance from pollution source i to observation point q, represents the natural exponential function;

[0188] Based on the impact range diagram, dynamic simulation is performed using the formula:

[0189] ,

[0190] Calculate the propagation velocity V of pollutants and generate pollution propagation velocity analysis records, where: and Represent the changes in pollution intensity at consecutive time points, is the time interval, and Q represents the number of time points.

[0191] , : The geographical coordinates of the pollution source are obtained from the monitoring site data through the Geographic Information System (GIS). The location of the pollution source is (longitude), (latitude);

[0192] : Pollution intensity, directly measured by air quality monitoring instruments, in micrograms per cubic meter, to obtain pollution intensity =150 μg / m3;

[0193] : Type of contaminant, determined by chemical analysis, ;

[0194] The monitoring time is provided by the timestamp of the data acquisition system in the format of a time string; specifically .

[0195] but: ;

[0196] The records show that a certain monitoring point captured a high concentration of PM2.5 at a specified time and at a specified longitude and latitude. This information will be used for further environmental impact analysis.

[0197] : Attenuation coefficient, determined based on historical data analysis, usually set in the range of 0.1 to 0.3. =0.2;

[0198] : The distance from pollution source i to observation point j can be directly obtained as =5 km;

[0199] : Secondary attenuation coefficient, adjusted according to environmental variables, set =0.5.

[0200] Combining the above data and substituting it into the formula, we get:

[0201] ,

[0202] result =24.52 means the impact intensity at a distance of 5 km is 24.52 units. When the observation point is 5 km away from the pollution source, the impact intensity of the pollution on the point is 24.52 units. This shows that pollutants decay rapidly with increasing distance. This data can be used for environmental planning and health risk assessment.

[0203] : Time interval, calculated by the data collection timestamp, data is updated every hour. =1 hour.

[0204] According to the above calculation, the previous hour , current hour , =1, then:

[0205] ,

[0206] The result V=4.52 means that the pollution spread speed is 4.52 units of pollution intensity per hour. It indicates that the pollution is intensifying or the activity of the pollution source is increasing. This information is crucial for emergency response and further environmental monitoring.

[0207] See also Figure 6 , the steps to obtain pollution trend prediction records are:

[0208] Using the pollution transmission speed analysis records, compared with the historical pollution data of the same period, the formula is used.

[0209] ,

[0210] Calculate the correlation coefficient X, evaluate the similarity between historical and current data, and generate historical data comparison results, where K represents the pollution transmission speed during the same period in history. is the cross-mean, and is the average value;

[0211] According to the historical data comparison results, combined with the current environmental parameters, the formula is used.

[0212] ,

[0213] Calculate the environmental impact prediction value F and output the future pollution diffusion direction map, where: is the adjustment factor, It is an environmental factor The weight of, Z represents the number of environmental factors;

[0214] Using the future pollution diffusion direction map, the formula is adopted.

[0215] ,

[0216] Calculate the predicted value G of the highest pollution concentration area, predict the potential highest pollution concentration area, and generate pollution trend prediction records, where: is the sensitivity factor of region j, J represents the total number of regions, Indicates the maximum value.

[0217] Collect the following sample data:

[0218] Current pollution rate ,

[0219] Pollution rate during the same period in history ,

[0220] calculate and :

[0221] ,

[0222] ,

[0223] calculate :

[0224] ,

[0225] calculate :

[0226] ,

[0227] but: ;

[0228] calculate and :

[0229] ,

[0230] ,

[0231] calculate and :

[0232] ,

[0233] ,

[0234] but: ;

[0235] Calculate the correlation coefficient: ,

[0236] Correlation coefficient This means that the current data has a high degree of positive correlation with the historical data, indicating that the speed of pollution spread is increasing over time and is consistent with the historical data pattern.

[0237] Set the environmental factors (taking temperature and humidity as examples) and weights as follows:

[0238] temperature , weight ;

[0239] humidity: , weight ;

[0240] set up =0.2.

[0241] Use the maximum values ​​of X and V from the previous calculation results: V=5.01, X=0.993;

[0242] Calculate the impact of environmental factors:

[0243] ,

[0244] Calculate F: .

[0245] The calculated prediction value F=12.0643 indicates that the future diffusion direction of pollutants is affected by the current speed and environmental factors, indicating that temperature has a significant enhancing effect on pollution diffusion.

[0246] Setting the Area Sensitivity Factor The values ​​are:

[0247] Region 1: , Region 2: , Region 3: ;

[0248] Substituting into the formula, we get:

[0249] ,

[0250] G = 12.0643 means that in area 2, the predicted pollution concentration is the highest, which may reach 12.0643 units, indicating that environmental monitoring and pollution control measures in this area should be given priority.

[0251] See also Figure 7 , the steps to obtain the health protection guide are:

[0252] Based on the pollution trend prediction records, the real-time monitoring data of the city and the historical pollution records are integrated, and the formula is adopted.

[0253] ,

[0254] Calculate the weighted average pollution level for a city , generating a comprehensive record of pollution levels, where Indicates the weight of the corresponding days, reflecting the reliability and importance of the data. is the pollution index on the i-th day, and A represents the total number of days;

[0255] Based on comprehensive records of pollution levels, the formula

[0256] ,

[0257] Calculate the health risk threshold Y, automatically issue an alarm when the threshold is exceeded, and generate an over-threshold alarm record, where k is a coefficient adjusted based on health research, which is used to identify areas that exceed this threshold and automatically issue an alarm, is the natural logarithm, which is used to adjust the sensitivity of the threshold to high pollution levels;

[0258] Based on the threshold alarm records, formulate and issue health protection measures and generate health protection guidelines.

[0259] Collect three days of pollution data and set corresponding weights:

[0260] Day 1: , ;

[0261] Day 2: , ;

[0262] Day 3: , ;

[0263] Substituting into the formula, we get:

[0264] ,

[0265] The results show that taking into account the weights of different days; the average pollution index of the city is 104.44.

[0266] k: A coefficient adjusted based on health research, usually set based on public health research and set to k=10 to provide a reasonable alarm threshold.

[0267] Combined with the above calculation results, ,but:

[0268] ,

[0269] The threshold means that pollution levels above 46.6 will be considered to pose a higher risk to health and automatically trigger an alert.

[0270] Based on the alert, relevant departments and personnel can formulate and issue health protection measures, such as

[0271] Mild pollution: Sensitive people are advised to reduce the time spent exercising outdoors.

[0272] Moderate pollution: It is recommended that all people avoid prolonged outdoor activities, and sensitive people should stay indoors.

[0273] Severe pollution: It is recommended that all people stay indoors, use air purifiers, and close doors and windows to prevent outdoor polluted air from entering.

[0274] Hazardous pollution: It is recommended to stop all outdoor activities, activate emergency plans, and seek medical help if necessary.

[0275] This will then generate customized health protection guidelines to protect people’s safety.

[0276] The real-time monitoring method based on urban air pollutants includes the following steps:

[0277] S1: Collect data from air quality monitors and meteorological sensors, perform signal synchronization and filtering, perform time correction and standardization on the filtered signal data, and generate real-time pollution data;

[0278] S2: Based on real-time pollution data, define the pollution threshold, filter the pollution readings that exceed the pollution threshold, perform statistical analysis, analyze the degree of pollution concentration, calculate the weighted center position value, and generate cluster analysis results;

[0279] S3: Based on the cluster analysis results, connect with the geographic coordinate library, calculate the mapping value between the cluster center and the geographic location, update the pollution distribution map in real time, continuously track the dynamic changes of pollution sources, draw and output the dynamic tracking map of pollution sources;

[0280] S4: Based on the pollution source dynamic tracking map, collect the real-time location, intensity and type data of the pollution source, calculate the impact intensity of the pollution source on the surrounding environment, and perform dynamic simulation to calculate the propagation speed of pollutants and generate pollution propagation speed analysis records;

[0281] S5: Use the pollution propagation speed analysis records to compare with historical pollution data of the same period, evaluate the similarity between historical and current data, combine with current environmental parameters, calculate the environmental impact prediction value, predict the potential highest pollution concentration area, and generate pollution trend prediction records;

[0282] S6: Based on pollution trend forecast records, integrate the city's real-time monitoring data and historical pollution records, calculate the city's weighted average pollution level and health risk threshold, automatically issue an alarm when the threshold is exceeded, formulate and issue health protection measures, and generate health protection guidelines.

[0283] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A real-time monitoring system based on urban air pollutants, characterized by: The system comprises: The pollution real-time monitoring module collects data from air quality monitors and meteorological sensors, performs signal synchronization and filtering, corrects data time series, standardizes environmental parameters, and generates real-time pollution data; The pollution source tracking module identifies high-value pollution areas based on the real-time pollution data and the pollution threshold, analyzes the concentration trend of high-value pollution areas, uses GIS to match pollution points with actual geographical locations according to the analysis results, updates the pollution distribution map in real time, tracks the dynamic changes of pollution sources, and draws a dynamic tracking map of pollution sources; The pollution trend analysis module uses the pollution source dynamic tracking diagram to analyze the impact range of the pollution source, calculate the pollution propagation speed, and use statistical analysis to compare historical data of the same period based on the calculation results to predict the future diffusion direction of pollutants and the potential highest concentration area, and generate pollution trend prediction records; The early warning and health analysis module evaluates the pollution level reached in the city based on the pollution trend prediction record, sets health risk thresholds, automatically issues alarms for areas exceeding the threshold, formulates health protection measures, and generates health protection guidelines; The steps for obtaining the real-time pollution data are as follows: Collect raw data from air quality monitors and meteorological sensors, using the formula, ， Calculate the synchronized signal value , generate synchronization signal data, where, Represents the signal strength of the air quality monitor, Represents the signal strength of the meteorological sensor, represents the attenuation coefficient, which is used to adjust the impact of the two data sources, and t represents the time point; The synchronization signal data is filtered using the formula: ， Generate filtered signal data ,in, is the weight coefficient, which ensures the filtering effect and the data characteristics of the matching difference time point. represent The first N data points of , where N is the window size of the filter; The filtered signal data is time corrected using the formula: ， Generate time-corrected data ,in, represents the time deviation, is the adjustment factor used to refine the effect of time correction; The time-corrected data is standardized using the formula, ， Generate real-time pollution data ,in, and They are The mean and standard deviation of , f is a small positive number to avoid zero division errors; The analysis steps of the central tendency of the high pollution value area are as follows: Based on the real-time pollution data, a pollution threshold is defined, using the formula: ， Filter the pollution readings that exceed the pollution threshold to form a high pollution data set H, where D represents the pollution data monitored in real time, d is a single data point, and T is the set pollution threshold; Statistical analysis is performed on the highly polluted data set to analyze the degree of pollution concentration, using the formula, ， and ， Calculate the average and standard deviation , generate pollution trend analysis results, where is the element in the highly polluted data set, n is the number of elements in H; Based on the pollution trend analysis results, cluster analysis of polluted areas is performed using the formula: ， Calculate the weighted central location value C and generate cluster analysis results; The steps for drawing the pollution source dynamic tracking diagram are as follows: Based on the cluster analysis results, GIS is connected with the geographic coordinate database and the formula is used. ， Calculate the mapping value M between the cluster center and the geographic location, and output the geographic mapping result, where m is the number of clustering results. and Respectively represent the cluster center value and the corresponding geographic coordinate point; According to the geographic mapping results, dynamic update is performed using the formula: ， Calculate the updated pollution data U and output a real-time updated pollution distribution map, where H is the new real-time pollution data; Using the real-time updated pollution distribution map, the dynamic changes of pollution sources are continuously tracked, the real-time changes of pollution are displayed, and a dynamic tracking map of pollution sources is drawn and output; The calculation steps of the pollution propagation speed are: Based on the pollution source dynamic tracking map, the real-time location, intensity and type data of the pollution source are collected, and the formula is used. ， Get the actual information of the i-th pollution source , generate detailed information table for each pollution source, where and Represents geographic coordinates, represents the pollution intensity, Represents the pollutant type, Represents monitoring time; Based on the detailed information table for each pollution source, using the formula, ， Calculate the impact intensity of the i-th pollution source on the surrounding environment , draw an impact range diagram, where and is the attenuation coefficient, is the distance from pollution source i to observation point q, represents the natural exponential function; Based on the impact range diagram, a dynamic simulation is performed using the formula: ， Calculate the propagation velocity V of pollutants and generate pollution propagation velocity analysis records, where: and Represent the changes in pollution intensity at consecutive time points, is the time interval, Q represents the number of time points; The steps for obtaining the pollution trend prediction record are: Using the pollution transmission speed analysis records, compared with the historical pollution data of the same period, the formula is adopted. ， Calculate the correlation coefficient X, evaluate the similarity between historical and current data, and generate historical data comparison results, where K represents the pollution transmission speed during the same period in history. is the cross-mean, and is the average value; According to the historical data comparison results, combined with the current environmental parameters, the formula is used: ， Calculate the environmental impact prediction value F and output the future pollution diffusion direction map, where: is the adjustment factor, It is an environmental factor The weight of, Z represents the number of environmental factors; Using the future pollution diffusion direction map, the formula is adopted, ， Calculate the predicted value G of the highest pollution concentration area, predict the potential highest pollution concentration area, and generate pollution trend prediction records, where: is the sensitivity factor of region j, J represents the total number of regions, Indicates the maximum value; The steps for obtaining the health protection guidelines are: Based on the pollution trend prediction records, the real-time monitoring data of the city and the historical pollution records are integrated, and the formula is adopted. ， Calculate the weighted average pollution level for a city , generating a comprehensive record of pollution levels, where Indicates the weight of the corresponding days, reflecting the reliability and importance of the data. is the pollution index on the i-th day, and A represents the total number of days; Based on the comprehensive record of pollution levels, the formula is used. ， Calculate the health risk threshold Y, automatically issue an alarm when the threshold is exceeded, and generate an over-threshold alarm record, where k is a coefficient adjusted based on health research, which is used to identify areas that exceed this threshold and automatically issue an alarm, is the natural logarithm, which is used to adjust the sensitivity of the threshold to high pollution levels; Based on the above-threshold alarm records, health protection measures are formulated and issued, and health protection guidelines are generated.

2. A real-time monitoring method based on urban air pollutants, characterized in that: According to claim 1, the real-time monitoring system based on urban air pollutants is implemented, comprising the following steps: Collect data from air quality monitors and meteorological sensors, perform signal synchronization and filtering, time correct the filtered signal data, and perform standardization to generate real-time pollution data; Based on the real-time pollution data, a pollution threshold is defined, pollution readings exceeding the pollution threshold are screened, statistical analysis is performed, the degree of pollution concentration is analyzed, a weighted central position value is calculated, and a cluster analysis result is generated; Based on the cluster analysis results, the cluster center is connected to the geographic coordinate library to calculate the mapping value between the cluster center and the geographic location, the pollution distribution map is updated in real time, the dynamic changes of the pollution source are continuously tracked, and a dynamic tracking map of the pollution source is drawn and output; Based on the pollution source dynamic tracking diagram, collect the real-time location, intensity and type data of the pollution source, calculate the impact intensity of the pollution source on the surrounding environment, and perform dynamic simulation to calculate the propagation speed of pollutants and generate pollution propagation speed analysis records; Utilize the pollution propagation speed analysis record to compare with historical pollution data of the same period, evaluate the similarity between historical and current data, calculate the environmental impact prediction value in combination with current environmental parameters, predict the area with the highest pollution concentration that may be reached, and generate pollution trend prediction records; Based on the pollution trend forecast records, the city's real-time monitoring data and historical pollution records are integrated to calculate the city's weighted average pollution level and health risk threshold. When the threshold is exceeded, an alarm is automatically issued, health protection measures are formulated and issued, and health protection guidelines are generated.

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