Environment pollution monitoring system and method based on big data

Abstract

The invention discloses an environmental pollution monitoring system and method based on big data, and relates to the technical field of environmental pollution monitoring. Three algorithm units cooperate with one another to jointly form a core architecture of the environmental pollution monitoring system based on the big data; a plurality of factors such as population density Pd, air pollution and water quality pollution are comprehensively considered, the comprehensive environmental pollution index ECi of different monitoring areas is calculated, the air pollution and the water quality pollution can be uniformly evaluated through the analyzed comprehensive environmental pollution index ECi value, the environmental pollution conditions of the different monitoring areas are comprehensively reflected, and the method is suitable for popularization and application. An environment monitoring department can timely discover environmental problems by evaluating the environmental comprehensive pollution index ECi values of different monitoring areas, and increases the monitoring frequency and takes corresponding treatment measures for the monitoring area with the low environmental comprehensive pollution index ECi. Scientific and reliable data support is provided for an environment monitoring department to formulate an environment protection policy and plan an environment governance project.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental pollution monitoring, and particularly to an environmental pollution monitoring system and method based on big data. Background Art

[0002] Environmental monitoring refers to the activities of environmental monitoring agencies to monitor and measure the environmental quality status. Environmental monitoring is to monitor and measure the indicators reflecting environmental quality to determine the environmental pollution status and the level of environmental quality. The content of environmental monitoring mainly includes the monitoring of physical indicators, chemical indicators and ecological systems. Environmental monitoring is the basis for scientific environmental management and environmental law enforcement supervision, and is an essential basic work for environmental protection. The core goal of environmental monitoring is to provide data on the current status and change trends of environmental quality, judge environmental quality, evaluate the current major environmental problems, and serve environmental management.

[0003] Big data, also known as massive data, refers to the data volume involved is so huge that it cannot be captured, managed, processed and sorted into information that helps enterprises or relevant departments make more proactive business decisions through mainstream software tools within a reasonable time.

[0004] After retrieval:

[0005] Chinese invention CN116757311B discloses an ecological environmental pollution monitoring method and system based on big data. The invention obtains the geographical location information where the air pollution monitoring base station is located, predicts the meteorological characteristic data of the air pollution monitoring base station according to the geographical location information where the air pollution monitoring base station is located, obtains the meteorological characteristic prediction result, further obtains the working characteristic data information of the air pollution monitoring base station, and determines the pollution monitoring period of the air monitoring base station by combining the meteorological characteristic prediction result with the working characteristic data information, and constructs a monitoring plan for the air pollution monitoring base station according to the pollution monitoring period of the air monitoring base station.

[0006] Chinese invention CN114935637A discloses an environmental pollution monitoring system based on big data, including a water quality data acquisition module, a water pollution data analysis module and a real-time operation monitoring module. The water quality data acquisition module is used to acquire the water quality information of the water area, the water pollution data analysis module is used to analyze the acquired water quality data information, and the real-time operation monitoring module is used to monitor the water pollution of the water area in real time. The real-time operation monitoring module and the water pollution data analysis module are both network-connected to the water quality data acquisition module. This invention has the characteristics of automatic data analysis and intelligent monitoring.

[0007] In existing environmental pollution monitoring systems such as the above-cited documents, they often only focus on air pollution or water pollution, ignoring factors such as population density in different regions, wind speed, rainfall, etc. during the detection of air pollutant content, which can also affect the environmental monitoring results. Moreover, air pollution monitoring and water pollution monitoring are carried out separately, making it difficult to conduct a unified assessment in the environmental monitoring system, and the monitoring results are accidental and not conducive to use.

[0008] And since the total monitoring resources are limited, it is difficult for the environmental pollution monitoring systems in the existing technology to scientifically and reasonably allocate monitoring resources according to the operation of the detection system, reducing the monitoring efficiency of the monitoring system.

[0009] Therefore, there is an urgent need for an environmental pollution monitoring system and method based on big data to solve the above problems. Summary of the Invention

[0010] The purpose of the present invention is to provide an environmental pollution monitoring system and method based on big data to solve the problems raised in the above background technology.

[0011] To achieve the above purpose, the present invention provides the following technical solutions: An environmental pollution monitoring system and method based on big data, including:

[0012] A data collection module, used to detect air through an air detector to obtain the PM2.5 concentration Pm, carbon monoxide concentration Ca, and nitrogen dioxide concentration Nit in the air, which are the three pollutants that have the greatest impact on air quality, and detect the water source in the monitoring area through a water quality detector to obtain the turbidity Wt, pH value Ph, and dissolved oxygen concentration Wd of the water body and upload them to the database;

[0013] A data processing module, used to decode and preprocess the data information in the database to obtain the parameters participating in the calculation in the calculation processing module;

[0014] A calculation processing module, used to calculate the obtained parameter values through an air pollution value algorithm unit and a water pollution value algorithm unit to obtain an air pollution value API and a water pollution value WQi, and calculate the different environmental comprehensive pollution indices ECi of different monitoring areas through an environmental comprehensive pollution index algorithm unit and upload them to the database. Set the warning threshold Y1 of the environmental comprehensive pollution index ECi in the database to 30%, and set the danger threshold Y2 of the environmental comprehensive pollution index ECi to 70%;

[0015] A resource allocation module, used to allocate monitoring resources:

[0016] In the database, compare the different environmental comprehensive pollution indices ECi of different monitoring areas with the warning threshold Y1 and the danger threshold Y2;

[0017] For the monitoring areas where the comprehensive environmental pollution index ECi is less than the warning threshold Y1, maintain the monitoring frequency of once every quarter.

[0018] For the monitoring areas where the comprehensive environmental pollution index ECi is greater than 30% of the warning threshold Y1 and less than the danger threshold Y2, increase the monitoring frequency from once every quarter to once a month.

[0019] For the monitoring areas where the comprehensive environmental pollution index ECi is greater than the danger threshold Y2, increase the monitoring frequency to once a week and remind the environmental monitoring department to take corresponding environmental governance measures.

[0020] Optionally, the data collection module includes an air detector and a water quality detector.

[0021] Optionally, the calculation and processing module includes an air pollution value algorithm unit, a water quality pollution value algorithm unit, and a comprehensive environmental pollution index algorithm unit.

[0022] Optionally, the air pollution value algorithm unit is as follows:

[0023]

[0024] Where:

[0025] API represents the air pollution value;

[0026] Pm represents the concentration of PM2.5 in the air;

[0027] Ca represents the concentration of carbon monoxide in the air;

[0028] Nit represents the concentration of nitrogen dioxide in the air;

[0029] Ws represents the wind speed during the detection of the pollutant content in the air;

[0030] Wref represents the reference wind speed, which is the maximum wind speed in the past year in the monitored city and is obtained from the meteorological bureau report;

[0031] Ra represents the total rainfall from the previous monitoring time to the current time in the monitoring area;

[0032] Rref represents the reference rainfall, which is the total rainfall in the time period with the most rainfall among all monitoring time periods in the past five years;

[0033] In the formula calculation:

[0034] This part represents the square root of the sum of squares of the concentrations of three major air pollutants: the PM2.5 concentration Pm in the air, the carbon monoxide concentration Car in the air, and the square of the nitrogen dioxide concentration Nit in the air. By comprehensively considering the relative contributions of the three pollutants that can best reflect air pollution, the total concentration index of multiple pollutants in the air is obtained. Calculating the square root of the sum of squares can avoid the excessive influence on the calculation of the air pollution value API when one of the three pollution concentrations is too large;

[0035] This part represents the enhancement factor of the wind speed Ws during the detection of the pollutant content in the air relative to the reference wind speed Wref. Excessive wind speed will affect the diffusion of pollutants. As the wind speed Ws during the detection of the pollutant content in the air increases, the diffusion of pollutants will increase, thereby increasing the calculated air pollution value API. As the wind speed Ws during the detection of the pollutant content in the air decreases, the diffusion of pollutants will decrease to reduce the air pollution value API;

[0036] This part monitors the reduction factor of the total rainfall Ra from the previous monitoring time to the current time in the monitoring area relative to the reference rainfall Rref. Rainfall can affect the sedimentation of pollutants and wash the pollutants in the air. As the total rainfall Ra from the previous monitoring time to the current time in the monitoring area increases, it will reduce the calculated value of this part, thereby reducing the air pollution value API. As the total rainfall Ra from the previous monitoring time to the current time in the monitoring area decreases, it will increase the calculated value of this part, thereby increasing the air pollution value API.

[0037] Optionally, the water pollution value algorithm unit is as follows:

[0038]

[0039] Where:

[0040] WQi represents the water pollution value;

[0041] Wt represents the turbidity of the water body;

[0042] Ph represents the pH value of the water body;

[0043] Wd represents the dissolved oxygen concentration in the water body;

[0044] α 1 、α 2 、and α 3 respectively represent the weight coefficients of the turbidity Wt of the water body, the pH value Ph of the water body, and the dissolved oxygen concentration Wd in the water body, and always satisfy α 1 +α 2 +α 3= 1;

[0045] In the formula calculation:

[0046] α 1 × Wt 2 This part represents the contribution of the turbidity Wt of the water body to the water quality pollution value. The higher the turbidity, the more suspended solids in the water body. As the turbidity Wt of the water body increases, the calculated water quality pollution value WQi will also increase. After squaring the turbidity Wt of the water body and multiplying by the weight coefficient α 1 it then affects the water quality pollution value WQi, emphasizing the degree of influence of turbidity on the water quality pollution value;

[0047] α 2 × |Ph - 7| This part represents the contribution of the pH value Ph of the water body to the water quality pollution value WQi. Ph - 7 represents the degree of deviation of the pH value from the neutral value, and both acidic and alkaline deviations are taken into account. After multiplying by the weight coefficient α 2 it reflects the influence of the pH value on the water quality pollution value WQi. As the pH value Ph of the water body deviates more from the neutral value, the calculated water quality pollution value WQi is larger;

[0048] This part represents the contribution of the dissolved oxygen concentration Wd in the water body to the water quality pollution value. The lower the concentration, the more serious the organic pollution in the water body. After taking the reciprocal square of the dissolved oxygen concentration Wd in the water body and multiplying by the weight coefficient α 3 it emphasizes the influence of the dissolved oxygen concentration on the water quality pollution value. When the dissolved oxygen concentration Wd in the water body decreases, the calculated value of this part will increase, indicating that as the dissolved oxygen concentration Wd decreases, the organic pollution in the water body becomes more serious, increasing the calculated water quality pollution value WQi.

[0049] Optionally, the environmental comprehensive pollution index algorithm unit is as follows:

[0050]

[0051] Where:

[0052] ECi represents the environmental comprehensive pollution index;

[0053] API represents the air pollution value;

[0054] WQI represents the water quality pollution value;

[0055] Pd represents the population density, indicating the number of people per unit area in the monitoring area;

[0056] Ser represents the soil erosion rate, which is a measure of the speed of soil erosion and water and soil loss;

[0057] APImax represents the maximum value of the air pollution index API in multiple monitorings of all monitored areas recorded in the database;

[0058] WQ max represents the maximum value of the water quality pollution index WQI in multiple monitorings of all monitored areas recorded in the database;

[0059] Pd max represents the maximum value of the population density Pd in all monitored areas;

[0060] Ser max represents the maximum value of the soil erosion rate Ser in all monitored areas.

[0061] k1 and k2 respectively represent the weight coefficients of the population density Pd and the soil erosion rate Ser, which are used to adjust the contribution degrees of the population density Pd and the soil erosion rate Ser to the environmental comprehensive pollution index ECi, and always satisfy k1 + k2 = 1;

[0062] In the formula calculation:

[0063] This part represents the normalized squared value of the air pollution index API, which reflects the ratio of the air pollution degree to the maximum pollution degree, and enhances the influence of this ratio through squaring, emphasizing the influence degree of the air pollution index API on the environmental comprehensive pollution index ECi. As the air pollution index API increases, the environmental comprehensive pollution index ECi also increases;

[0064] This part represents the normalized squared value of the water quality pollution index WQI, which reflects the ratio of the water quality pollution degree to the maximum pollution degree, and enhances the influence of this ratio through squaring, emphasizing the influence degree of the water quality pollution index WQI on the environmental comprehensive pollution index ECi. As the water quality pollution index WQI increases, the environmental comprehensive pollution index ECi also increases;

[0065] This part represents the normalized squared value of the population density Pd, which reflects the ratio of the population density Pd to the maximum population density, and affects the calculation of the environmental comprehensive pollution index ECi value after multiplying by the weight coefficient k1. As the population density Pd increases, the environmental comprehensive pollution index ECi also increases;

[0066] This part represents the normalized squared value of the soil erosion rate Ser, which reflects the ratio of the soil erosion rate Ser to the maximum soil erosion rate, and affects the calculation of the environmental comprehensive pollution index ECi value after multiplying by the weight coefficient k2. As the soil erosion rate Ser increases, the environmental comprehensive pollution index ECi also increases;

[0067] After adding the above four product terms and dividing by a fixed value of 3, the comprehensive environmental pollution index ECi of the monitoring area is obtained. Setting the constant 3 in the denominator can prevent the value of the comprehensive environmental pollution index ECi from being greater than 1 when the numerators in the product terms all take the maximum values, ensuring that the value of the comprehensive environmental pollution index ECi is always ∈(0,1).

[0068] Optionally, the decoding preprocessing includes data cleaning and data standardization.

[0069] Optionally, a big data-based environmental pollution monitoring method includes the following steps:

[0070] Data is collected through a data collection module. The PM2.5 concentration Pm, carbon monoxide concentration Ca, and nitrogen dioxide concentration Nit in the air, which are the three pollutants with the greatest impact on air quality, are detected by an air detector. The wind speed Ws at the time of detecting the air pollutant content and the total rainfall Ra from the previous monitoring time to the current time in the monitoring area are obtained through the meteorological bureau of the monitored city and uploaded to the database;

[0071] The water turbidity Wt, water acidity and alkalinity Ph, and dissolved oxygen concentration Wd in the water body are detected by a water quality detector for the water source in the monitoring area. The population density Pd and soil erosion rate Ser of the monitored city are obtained through an Internet platform and uploaded to the database;

[0072] Data preprocessing is performed through a data processing module. The data information in the database is transmitted to the data processing module for decoding preprocessing to obtain the parameters participating in the calculation in the calculation processing module;

[0073] The parameter values obtained after decoding preprocessing are substituted into the air pollution value algorithm unit and water pollution value algorithm unit of the calculation processing module to calculate the air pollution value API and water pollution value WQi;

[0074] The calculated air pollution value API and water pollution value WQi are used as input parameters and input into the comprehensive environmental pollution index algorithm unit of the calculation processing module to calculate the comprehensive environmental pollution indexes ECi of different monitoring areas and upload them to the database. The warning threshold Y1 of the comprehensive environmental pollution index ECi in the database is set to 30%, and the danger threshold Y2 of the comprehensive environmental pollution index ECi is set to 70%;

[0075] Monitoring resource allocation is performed through a resource allocation module:

[0076] The comprehensive environmental pollution indexes ECi of different monitoring areas are compared with the warning threshold Y1 and the danger threshold Y2;

[0077] For the monitoring areas where the comprehensive environmental pollution index ECi is less than the warning threshold Y1, maintain the monitoring frequency of once every quarter.

[0078] For the monitoring areas where the comprehensive environmental pollution index ECi is greater than 30% of the warning threshold Y1 and less than the danger threshold Y2, increase the monitoring frequency from once every quarter to once a month.

[0079] For the monitoring areas where the comprehensive environmental pollution index ECi is greater than the danger threshold Y2, increase the monitoring frequency to once a week, and remind the environmental monitoring department to take corresponding environmental governance measures.

[0080] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0081] First, through the mutual cooperation of three algorithm units, the present invention jointly constitutes the core architecture of the environmental pollution monitoring system based on big data. By comprehensively considering multiple factors such as population density Pd and wind speed Ws during the detection of air pollutant content, the comprehensive environmental pollution index ECi of different monitoring areas is calculated, which can uniformly evaluate air pollution and water pollution, and comprehensively reflect the environmental pollution status of different monitoring areas. Through evaluating the different comprehensive environmental pollution indices ECi of different monitoring areas, the environmental monitoring department can timely discover which detection areas have environmental problems, increase the monitoring frequency of the monitoring areas with lower comprehensive environmental pollution index ECi, and timely take corresponding governance measures, providing scientific and reliable data support for the environmental monitoring department to formulate environmental protection policies and plan environmental governance projects.

[0082] Second, in the database of the environmental pollution monitoring system of the present invention, the warning threshold Y1 of the comprehensive environmental pollution index ECi is set at 30%, and the danger threshold Y2 of the comprehensive environmental pollution index ECi is set at 70%. The different comprehensive environmental pollution indices ECi of different monitoring areas are compared with the warning threshold Y1 and the danger threshold Y2. For the monitoring areas where the comprehensive environmental pollution index ECi is less than the warning threshold Y1, maintain the monitoring frequency of once every quarter. For the monitoring areas where the comprehensive environmental pollution index ECi is greater than 30% of the warning threshold Y1 and less than the danger threshold Y2, increase the monitoring frequency to once a month. For the monitoring areas where the comprehensive environmental pollution index ECi is greater than the danger threshold Y2, increase the monitoring frequency to once a week, and remind the environmental monitoring department to take corresponding environmental governance measures. It can increase the monitoring frequency of the areas with low comprehensive environmental pollution index ECi under the total amount of effective monitoring resources, more scientifically and reasonably complete the allocation of monitoring resources, enhance the monitoring efficiency of the environmental pollution monitoring system, and is worthy of popularization and use. Description of the Drawings

[0083] Figure 1It is a flowchart of an environmental pollution monitoring system and method based on big data;

[0084] Figure 2 It is a schematic diagram of the overall structure of an environmental pollution monitoring system and method based on big data. Specific implementation manner

[0085] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0086] Example 1, please refer to Figures 1 to 2 , the present invention provides an environmental pollution monitoring system and method based on big data, including:

[0087] A data collection module, which is used to detect the air through an air detector to obtain three pollutants that have the greatest impact on air quality, namely the PM2.5 concentration Pm in the air, the carbon monoxide concentration Ca in the air, and the nitrogen dioxide concentration Nit in the air, and detect the water source in the monitoring area through a water quality detector to obtain the turbidity Wt of the water body, the pH value Ph of the water body, and the dissolved oxygen concentration Wd in the water body and upload them to the database;

[0088] A data processing module, which is used to decode and preprocess the data information in the database to obtain the parameters participating in the calculation in the calculation processing module;

[0089] A calculation processing module, which is used to calculate the obtained parameter values through an air pollution value algorithm unit and a water pollution value algorithm unit to obtain an air pollution value API and a water pollution value WQi, and calculate different environmental comprehensive pollution indices ECi of different monitoring areas through an environmental comprehensive pollution index algorithm unit and upload them to the database. In the database, the warning threshold Y1 of the environmental comprehensive pollution index ECi is set to 30%, and the danger threshold Y2 of the environmental comprehensive pollution index ECi is set to 70%;

[0090] A resource allocation module, which is used to allocate monitoring resources:

[0091] In the database, compare the different environmental comprehensive pollution indices ECi of different monitoring areas with the warning threshold Y1 and the danger threshold Y2;

[0092] For the monitoring areas where the environmental comprehensive pollution index ECi is less than the warning threshold Y1, maintain a monitoring frequency of once every quarter;

[0093] For the monitoring areas where the comprehensive environmental pollution index ECi is greater than the warning threshold Y1 of 30% and less than the danger threshold Y2, increase the monitoring frequency from once a quarter to once a month;

[0094] For the monitoring areas where the comprehensive environmental pollution index ECi is greater than the danger threshold Y2, increase the monitoring frequency to once a week and remind the environmental monitoring department to take corresponding environmental governance measures.

[0095] In this embodiment:

[0096] Through the mutual cooperation of three algorithm units, the present invention jointly constitutes the core architecture of the environmental pollution monitoring system based on big data. By comprehensively considering multiple influencing factors such as population density Pd, wind speed Ws during the detection of air pollutant content, and rainfall, the comprehensive environmental pollution index ECi of different monitoring areas is calculated, which more comprehensively reflects the environmental pollution status of different monitoring areas. Through evaluating the differences in the comprehensive environmental pollution index ECi of different monitoring areas, the environmental monitoring department can quickly understand the changing trend of environmental pollution, formulate targeted environmental protection measures, and by continuously monitoring the change of the comprehensive environmental pollution index ECi value, it can timely discover which detection areas have environmental problems, increase the monitoring frequency of the monitoring areas with a lower comprehensive environmental pollution index ECi, and timely take corresponding governance measures, providing scientific and reliable data support for the environmental monitoring department to formulate environmental protection policies and plan environmental governance projects.

[0097] Please refer to Figures 1 to 2 , the air pollution value algorithm unit is as follows:

[0098]

[0099] Where:

[0100] API represents the air pollution value;

[0101] Pm represents the concentration of PM2.5 in the air. PM2.5 refers to particulate matter with an aerodynamic equivalent diameter less than or equal to 2.5 microns in ambient air, also known as fine particulate matter, which has an important impact on air quality and visibility, etc.;

[0102] Ca represents the concentration of carbon monoxide in the air, which is one of the main gaseous pollutants in the atmosphere;

[0103] Nit represents the concentration of nitrogen dioxide in the air. Nitrogen dioxide is one of the main gaseous pollutants in the atmosphere, mainly from vehicle exhaust and industrial emissions;

[0104] Ws represents the wind speed during the detection of air pollutant content, and the wind speed will affect the diffusion of pollutants;

[0105] Wref represents the reference wind speed, which is the maximum wind speed in the monitored city in the past year and is obtained from the meteorological bureau's report;

[0106] Ra represents the total rainfall from the previous monitoring time to the current time in the monitored area. Rainfall can affect the settlement and washing of pollutants;

[0107] Rref represents the reference rainfall, which is the total rainfall in the time period with the most rainfall among all monitoring time periods in the past five years.

[0108] In the formula calculation:

[0109] This part represents the square root of the sum of the squares of the concentrations of three main air pollutants: the PM2.5 concentration Pm in the air, the carbon monoxide concentration Car in the air, and the nitrogen dioxide concentration Nit in the air. The combination can best reflect the relative contributions of the three pollutants that can most reflect air pollution, and obtain the total concentration index of multiple pollutants in the air. In mathematical calculations, taking the square root of the sum of squares can avoid the situation where when one of the three pollution concentrations is too large, it has too much influence on the calculation of the air pollution value API, making the calculated air pollution value API mathematically reasonable and accurate;

[0110] This part represents the enhancement factor of the wind speed Ws during the detection of the air pollutant content relative to the reference wind speed Wref. Since too high a wind speed will affect the diffusion of pollutants, as the wind speed Ws during the detection of the air pollutant content increases, it will increase the diffusion of pollutants, thereby increasing the calculated air pollution value API. As the wind speed Ws during the detection of the air pollutant content decreases, it will reduce the diffusion of pollutants to reduce the air pollution value API;

[0111] This part is the reduction factor of the total rainfall Ra from the previous monitoring time to the current time in the monitored area relative to the reference rainfall Rref. Since rainfall can affect the settlement of pollutants and wash the pollutants in the air, as the total rainfall Ra from the previous monitoring time to the current time in the monitored area increases, it will reduce the calculated value of this part, thereby reducing the air pollution value API. As the total rainfall Ra from the previous monitoring time to the current time in the monitored area decreases, it will increase the calculated value of this part, thereby increasing the air pollution value API.

[0112] In this embodiment:

[0113] Taking into account multiple influencing factors such as the PM2.5 concentration Pm in the air, the carbon monoxide concentration Ca in the air, and the nitrogen dioxide concentration Nit in the air, the air pollution value API is calculated, which can give a comprehensive air pollutant concentration index in environmental pollution monitoring to comprehensively reflect the air quality status of the monitoring area. This comprehensive evaluation method can more accurately reflect the actual situation of air pollution than monitoring a single pollutant alone, and helps the environmental monitoring department to more comprehensively understand the air pollution situation.

[0114] Wind speed can affect the diffusion of pollutants, and rainfall can affect the sedimentation of pollutants and wash the pollutants in the air. In addition to the pollutant concentration in the air, the air pollution value algorithm unit also considers the influence of two meteorological factors, wind speed and rainfall, making the calculated air pollution value API more accurate and comprehensive in evaluating air pollution, which helps to better predict and respond to air pollution events and provides scientific and reliable data support for the environmental monitoring department to evaluate environmental quality and formulate environmental protection decisions.

[0115] Please refer to Figures 1 to 2 , the water pollution value algorithm unit is as follows:

[0116]

[0117] Where:

[0118] WQi represents the water pollution value;

[0119] Wt represents the turbidity of the water body;

[0120] Ph represents the pH value of the water body;

[0121] Wd represents the dissolved oxygen concentration in the water body;

[0122] α 1 、α 2 、and α 3 represent the weight coefficients of the turbidity Wt of the water body, the pH value Ph of the water body, and the dissolved oxygen concentration Wd in the water body respectively, and always satisfy α 1 +α 2 +α 3 =1. The weight coefficients α 1 、α 2 、and α 3 can be self-adjusted within the environmental pollution monitoring system. For example:

[0123] When the main pollution source of the monitored water source changes from agricultural pollution to industrial pollution, the discharged industrial polluted wastewater will seriously affect the pH value of the monitored water source. At this time, the system will reduce the value of the weight coefficient α 2 to prevent the pH value Ph of the water body from having too much influence on the water pollution value WQi.

[0124] In formula calculation:

[0125] α 1 ×Wt 2 This part represents the contribution of the turbidity Wt of the water body to the water quality pollution value. Turbidity is an index to measure the clarity of the water body. The higher the turbidity, the more suspended solids there are in the water body. As the turbidity Wt of the water body increases, the calculated water quality pollution value WQi increases. After squaring the turbidity Wt of the water body and multiplying it by the weighting coefficient α 1 it further affects the water quality pollution value WQi, emphasizing the degree of influence of turbidity on the water quality pollution value;

[0126] α 2 ×|Ph - 7| This part represents the contribution of the pH value Ph of the water body to the water quality pollution value WQi. Ph - 7 represents the degree of deviation of the pH value from the neutral value. Both acidic deviation and alkaline deviation will be calculated. After multiplying by the weighting coefficient α 2 it reflects the influence of the pH value on the water quality pollution value WQi. As the pH value Ph of the water body deviates more from the neutral value, the calculated water quality pollution value WQi is larger;

[0127] This part represents the contribution of the dissolved oxygen concentration Wd in the water body to the water quality pollution value. Dissolved oxygen is an important index to measure the self - purification ability of the water body. The lower the concentration, the more serious the organic pollution in the water body. After taking the reciprocal square of the dissolved oxygen concentration Wd in the water body and multiplying it by the weighting coefficient α 3 it emphasizes the influence of the dissolved oxygen concentration on the water quality pollution value. When the dissolved oxygen concentration Wd in the water body decreases, the calculated value of this part will increase, indicating that as the dissolved oxygen concentration Wd decreases, the organic pollution in the water body is more serious, and thus the calculated water quality pollution value WQi will increase.

[0128] In this embodiment:

[0129] By comprehensively considering multiple influencing factors such as the turbidity Wt of the water body, the pH value Ph of the water body, and the dissolved oxygen concentration Wd in the water body, the water quality pollution value WQi is calculated. The environmental monitoring department can enable the monitoring personnel to quickly understand the pollution status of the water bodies in different monitoring areas by continuously monitoring and analyzing the different water quality pollution values WQi in different monitoring areas. In environmental pollution monitoring, monitoring resources and environmental maintenance resources are limited. By evaluating the different water quality pollution values WQi in different monitoring areas, the allocation of monitoring resources can be optimized, and the limited resources can be invested in the areas that most need monitoring and protection. This helps to improve the monitoring efficiency, ensure the rational use of resources, and can formulate targeted environmental protection measures and pollution control plans for areas with serious water quality pollution, providing scientific and reliable data support for the formulation of environmental protection policies.

[0130] Please refer to Figures 1 to 2 , the environmental comprehensive pollution index algorithm unit is as follows:

[0131]

[0132] Where:

[0133] ECi represents the environmental comprehensive pollution index; it is an indicator that comprehensively reflects multiple environmental factors such as air pollution, water pollution, population density, and soil erosion rate.

[0134] API represents the air pollution value;

[0135] WQI represents the water pollution value;

[0136] Pd represents the population density, which represents the number of people per unit area in the monitoring area and is obtained from the information released by the government statistics department through the Internet;

[0137] Ser represents the soil erosion rate, which is a measure of the speed of soil erosion and water loss and is obtained from the meteorological bureau of the monitored city through the Internet;

[0138] API max represents the maximum value of the air pollution value API in multiple monitors of all monitoring areas recorded in the database;

[0139] WQ max represents the maximum value of the water pollution value WQI in multiple monitors of all monitoring areas recorded in the database;

[0140] Pd max represents the maximum value of the population density Pd in all monitoring areas;

[0141] Ser max represents the maximum value of the soil erosion rate Ser in all monitoring areas;

[0142] k1 and k2 respectively represent the weight coefficients of the population density Pd and the soil erosion rate Ser, which are used to adjust the contribution degree of the population density Pd and the soil erosion rate Ser to the environmental comprehensive pollution index ECi, and always satisfy k1 + k2 = 1;

[0143] The values of k1 and k2 can be self-adjusted within the environmental pollution monitoring system. For example:

[0144] When the monitoring area is located in a first-tier city with a large population density Pd, the system will lower the value of k1 to prevent the value of the population density Pd from being too large and having too much impact on the environmental comprehensive pollution index ECi.

[0145] In the formula calculation:

[0146] This part represents the normalized square value of the air pollution value API, which reflects the ratio of the air pollution level to the maximum pollution level, and enhances the impact of this ratio through squaring, emphasizing the influence degree of the air pollution value API on the environmental comprehensive pollution index ECi. As the air pollution value API increases, the environmental comprehensive pollution index ECi also increases;

[0147] This part represents the normalized square value of the water quality pollution value WQI, which reflects the ratio of the water quality pollution level to the maximum pollution level, and enhances the impact of this ratio through squaring, emphasizing the influence degree of the water quality pollution value WQI on the environmental comprehensive pollution index ECi. As the water quality pollution value WQI increases, the environmental comprehensive pollution index ECi also increases;

[0148] This part represents the normalized square value of the population density Pd, which reflects the ratio of the population density Pd to the maximum population density, and affects the calculation of the environmental comprehensive pollution index ECi value after multiplying by the weight coefficient k1. As the population density Pd increases, the environmental comprehensive pollution index ECi also increases;

[0149] This part represents the normalized square value of the soil erosion rate Ser, which reflects the ratio of the soil erosion rate Ser to the maximum soil erosion rate, and affects the calculation of the environmental comprehensive pollution index ECi value after multiplying by the weight coefficient k2. As the soil erosion rate Ser increases, the environmental comprehensive pollution index ECi also increases;

[0150] Add the above four product terms and then divide by a fixed value 3 to obtain the environmental comprehensive pollution index ECi of the monitoring area. Setting the constant 3 in the denominator can prevent the numerical value of the environmental comprehensive pollution index ECi from being greater than 1 when the numerators in the product terms all take the maximum values (an extreme phenomenon, almost non-existent), ensuring that the numerical value of the environmental comprehensive pollution index ECi is always ∈(0,1).

[0151] In this embodiment:

[0152] Traditional environmental monitoring systems often only focus on air pollution or water pollution, ignoring factors such as population density Pd in different regions and wind speed Ws during the detection of air pollutants, which can also affect the environmental monitoring results. Moreover, air pollution monitoring and water pollution monitoring are carried out separately, unable to conduct a unified assessment in the environmental monitoring system, and the monitoring results are accidental and not conducive to use. The environmental comprehensive pollution index algorithm unit comprehensively considers multiple aspects such as air, water quality, wind speed during detection, population density, and soil erosion in the calculation, and can more comprehensively reflect the environmental pollution situation. By evaluating the differences in the environmental comprehensive pollution index ECi of different monitoring regions, the environmental monitoring department can quickly understand the changing trend of environmental pollution and formulate targeted environmental protection measures. By continuously monitoring the changes in the value of the environmental comprehensive pollution index ECi, it is possible to timely discover which detection regions have environmental problems and take corresponding treatment measures in a timely manner, providing scientific and reliable data support for the environmental monitoring department to formulate environmental protection policies and plan environmental governance projects.

[0153] Moreover, in the environmental pollution monitoring based on big data, the monitoring system can record and analyze the value of the environmental comprehensive pollution index ECi of different regions in real time through big data. When the environmental comprehensive pollution index ECi of a certain monitoring area is too high, it reminds relevant departments and personnel to take measures for manual intervention in a timely manner, which helps to reduce the risk of environmental pollution deterioration and protect the ecological environment.

[0154] An environmental pollution monitoring method based on big data includes the following steps:

[0155] Collect data through the data collection module. Detect the PM2.5 concentration Pm, carbon monoxide concentration Ca, and nitrogen dioxide concentration Nit in the air, which have the greatest impact on air quality, through an air detector, and obtain the wind speed Ws during the detection of air pollutants and the total rainfall Ra from the previous monitoring time to the current time in the monitoring area from the meteorological bureau of the monitored city and upload them to the database.

[0156] Detect the water source in the monitoring area through a water quality detector to obtain the turbidity Wt, pH value Ph, and dissolved oxygen concentration Wd of the water body, and obtain the population density Pd and soil erosion rate Ser of the monitored city through the Internet platform and upload them to the database.

[0157] Perform data preprocessing through the data processing module. Transmit the data information in the database to the data processing module for decoding and preprocessing to obtain the parameters participating in the calculation in the calculation processing module.

[0158] Substitute the parameter values obtained after decoding preprocessing into the air pollution value algorithm unit and water quality pollution value algorithm unit of the calculation and processing module, and calculate the air pollution value API and water quality pollution value WQi;

[0159] Take the calculated air pollution value API and water quality pollution value WQi as input parameters and input them into the environmental comprehensive pollution index algorithm unit of the calculation and processing module to calculate the different environmental comprehensive pollution indices ECi of different monitoring areas and upload them to the database. Set the warning threshold Y1 of the environmental comprehensive pollution index ECi in the database to 30%, and set the danger threshold Y2 of the environmental comprehensive pollution index ECi to 70%;

[0160] Perform monitoring resource allocation through the resource allocation module:

[0161] Compare the different environmental comprehensive pollution indices ECi of different monitoring areas with the warning threshold Y1 and the danger threshold Y2;

[0162] For the monitoring areas where the environmental comprehensive pollution index ECi is less than the warning threshold Y1, maintain the monitoring frequency of once every quarter;

[0163] For the monitoring areas where the environmental comprehensive pollution index ECi is greater than the warning threshold Y1 of 30% and less than the danger threshold Y2, increase the monitoring frequency from once every quarter to once a month;

[0164] For the monitoring areas where the environmental comprehensive pollution index ECi is greater than the danger threshold Y2, increase the monitoring frequency to once a week and remind the environmental monitoring department to take corresponding environmental governance measures.

[0165] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A system and method for monitoring environmental pollution based on big data, characterized in that: include: The data collection module is used to detect the air through an air detector to obtain the three pollutants that have the greatest impact on air quality, namely, the PM2.5 concentration Pm, the carbon monoxide concentration Ca, and the nitrogen dioxide concentration Nit in the air. The water quality detector is used to detect the water source in the monitoring area to obtain the turbidity Wt, the pH value Ph, and the dissolved oxygen concentration Wd of the water body and upload them to the database; The data processing module is used to decode and preprocess the data information in the database to obtain the parameters involved in the calculation in the calculation processing module; A calculation processing module is used to calculate the parameter values ​​obtained after decoding preprocessing through an air pollution value algorithm unit and a water quality pollution value algorithm unit to obtain an air pollution value API and a water quality pollution value WQi, and to calculate different environmental comprehensive pollution indexes ECi of different monitoring areas through an environmental comprehensive pollution index algorithm unit and upload them to a database, and to set a warning threshold value Y1 of the environmental comprehensive pollution index ECi to 30% and a danger threshold value Y2 of the environmental comprehensive pollution index ECi to 70% in the database; Resource allocation module, used to allocate monitoring resources: In the database, the different comprehensive environmental pollution indexes ECi of different monitoring areas are compared with the warning threshold Y1 and the danger threshold Y2; For monitoring areas where the comprehensive environmental pollution index ECi is less than the warning threshold Y1, the monitoring frequency is maintained at once a quarter; For monitoring areas where the comprehensive environmental pollution index ECi is greater than the warning threshold Y1 by 30% and less than the danger threshold Y2, the monitoring frequency will be increased from once a quarter to once a month; For monitoring areas where the comprehensive environmental pollution index ECi is greater than the danger threshold Y2, the monitoring frequency will be increased to once a week, and the environmental monitoring department will be reminded to take corresponding environmental governance measures.

2. The big data-based environmental pollution monitoring system and method according to claim 1, characterized in that: The data collection module includes an air detector and a water quality detector.

3. The environmental pollution monitoring system and method based on big data according to claim 2 is characterized by: The calculation and processing module includes an air pollution value algorithm unit, a water quality pollution value algorithm unit and an environmental comprehensive pollution index algorithm unit.

4. The environmental pollution monitoring system and method based on big data according to claim 3 is characterized by: The air pollution value algorithm unit is as follows: in: API stands for Air Pollution Index; Pm represents the concentration of PM2.5 in the air; Ca represents the concentration of carbon monoxide in the air; Nit represents the concentration of nitrogen dioxide in the air; Ws represents the wind speed when the pollutant content in the air is detected; Wref stands for reference wind speed, which is the maximum wind speed of the monitored city in the past year and is obtained from the meteorological bureau report; Ra represents the total rainfall in the monitoring area from the last monitoring time to the current time; Rref stands for reference rainfall, which is the total rainfall in the period with the highest rainfall among all monitoring periods in the past five years; In the calculation formula: This part represents the square root of the sum of squares of three major air pollutants: PM2.5 concentration Pm in the air, carbon monoxide concentration Car in the air, and nitrogen dioxide concentration Nit in the air. It comprehensively reflects the relative contributions of the three pollutants that best reflect air pollution, and obtains the total concentration index of multiple pollutants in the air. Calculating the square sum and then taking the square root can avoid excessive impact on the calculation of the air pollution value API when one of the three pollution concentrations is too large; This part indicates the enhancement factor of the wind speed Ws when detecting the pollutant content in the air relative to the reference wind speed Wref. Too high wind speed will affect the diffusion of pollutants. As the wind speed Ws when detecting the pollutant content in the air increases, the diffusion of pollutants will increase, thereby increasing the calculated air pollution value API. As the wind speed Ws when detecting the pollutant content in the air decreases, the diffusion of pollutants will decrease, thereby reducing the air pollution value API. The reduction factor of the total rainfall Ra in this monitoring area from the last monitoring time to the current time relative to the reference rainfall Rref. Rainfall can affect the deposition of pollutants and clean pollutants in the air. As the total rainfall Ra in the monitoring area from the last monitoring time to the current time increases, it will decrease. The calculated value of this part will reduce the air pollution value API. As the total rainfall Ra in the monitoring area from the last monitoring time to the current time decreases, it will increase. The calculated value of this part increases the air pollution value API.

5. The big data-based environmental pollution monitoring system and method according to claim 4 is characterized by: The water pollution value algorithm unit is as follows: in: WQi represents the water pollution value; Wt represents the turbidity of the water body; Ph represents the pH of water; Wd represents the dissolved oxygen concentration in the water body; α1, α2, and α3 represent the weight coefficients of the turbidity Wt of the water body, the pH value Ph of the water body, and the dissolved oxygen concentration Wd in the water body, respectively, and always satisfy α1+α2+α3=1; In the calculation formula: α1×Wt 2 This part indicates the contribution of the turbidity Wt of the water body to the water pollution value. The higher the turbidity, the more suspended solids there are in the water body. As the turbidity Wt of the water body increases, the calculated water pollution value WQi will also increase. The water pollution value WQi is affected by the square of the turbidity Wt of the water body multiplied by the weight coefficient α1, emphasizing the influence of turbidity on the water pollution value. α2×|Ph-7| represents the contribution of the pH value Ph of the water body to the water quality pollution value WQi. Ph-7 represents the degree of deviation of pH value from the neutral value. Both acidic deviation and alkaline deviation are calculated. After multiplying by the weight coefficient α2, it reflects the influence of pH value on the water quality pollution value WQi. As the pH value Ph of the water body deviates from the neutral value, the calculated water quality pollution value WQi will be larger. This part indicates the contribution of dissolved oxygen concentration Wd in the water body to the water pollution value. The lower the concentration, the more serious the organic pollution in the water body. The influence of dissolved oxygen concentration on water pollution value is emphasized by multiplying the reciprocal square of dissolved oxygen concentration Wd in the water body by weight coefficient α3. When dissolved oxygen concentration Wd in the water body decreases, The calculated value of this part will increase, indicating that as the dissolved oxygen concentration Wd decreases, the organic pollution in the water body becomes more serious, increasing the calculated water quality pollution value WQi.

6. The big data-based environmental pollution monitoring system and method according to claim 5, characterized in that: The environmental comprehensive pollution index algorithm unit is as follows: in: ECi stands for Comprehensive Environmental Pollution Index; API stands for Air Pollution Index; WQI stands for water quality index; Pd represents population density, which indicates the number of people per unit area in the monitoring area; Ser stands for soil erosion rate, which is a measure of the speed of soil erosion and water loss; API max Represents the maximum value of the air pollution value API in multiple monitorings of all monitoring areas recorded in the database; WQ max Represents the maximum value of water quality pollution value WQI in multiple monitoring of all monitoring areas recorded in the database; Pd max Represents the maximum value of population density Pd in ​​all monitoring areas; Ser max Represents the maximum value of the soil and water loss rate Ser in all monitoring areas. k1 and k2 represent the weight coefficients of population density Pd and soil erosion rate Ser, respectively, which are used to adjust the contribution of population density Pd and soil erosion rate Ser to the comprehensive environmental pollution index ECi, and always satisfy k1+k2=1; In the calculation formula: This part represents the normalized square value of the air pollution value API, which reflects the ratio of the air pollution level to the maximum pollution level, and enhances the influence of this ratio through the square, emphasizing the influence of the air pollution value API on the comprehensive environmental pollution index ECi. As the air pollution value API increases, the comprehensive environmental pollution index ECi will also increase. This part represents the normalized square value of the water quality pollution value WQI, which reflects the ratio of the water quality pollution degree to the maximum pollution degree, and enhances the influence of this ratio through the square, emphasizing the influence of the water quality pollution value WQI on the comprehensive environmental pollution index ECi. As the water quality pollution value WQI increases, the comprehensive environmental pollution index ECi will also increase; This part represents the normalized square value of population density Pd, reflecting the ratio of population density Pd to the maximum population density, and multiplying it by the weight coefficient k1 affects the calculation of the comprehensive environmental pollution index ECi. As population density Pd increases, the comprehensive environmental pollution index ECi will also increase. This part represents the normalized square value of the soil and water loss rate Ser, reflecting the ratio of the soil and water loss rate Ser to the maximum soil and water loss rate, and multiplying it by the weight coefficient k2 affects the calculation of the comprehensive environmental pollution index ECi. As the soil and water loss rate Ser increases, the comprehensive environmental pollution index ECi will also increase. The sum of the above four product terms is divided by a fixed value of 3 to obtain the comprehensive environmental pollution index ECi of the monitored area. Setting a constant 3 in the denominator can prevent the value of the calculated comprehensive environmental pollution index ECi from being greater than 1 when the numerators in the product terms all reach the maximum value, thereby ensuring that the value of the comprehensive environmental pollution index ECi is always ∈(0,1).

7. The big data-based environmental pollution monitoring system and method according to claim 1, characterized in that: The decoding preprocessing includes data cleaning and data standardization.

8. The big data-based environmental pollution monitoring system and method according to claim 1, characterized in that: The method comprises the following steps: The data collection module is used to collect data. The air detector is used to detect the three pollutants that have the greatest impact on air quality: PM2.5 concentration Pm, carbon monoxide concentration Ca, and nitrogen dioxide concentration Nit. The wind speed Ws during the air pollutant content detection and the total rainfall Ra in the monitoring area from the last monitoring time to the current time are obtained through the meteorological bureau of the monitoring city and uploaded to the database; The water source in the monitoring area is tested by a water quality detector to obtain the turbidity Wt, the pH value Ph and the dissolved oxygen concentration Wd of the water body, and the population density Pd and the soil erosion rate Ser of the monitored city are obtained through the Internet platform and uploaded to the database; The data processing module performs data preprocessing, transmits the data information in the database to the data processing module for decoding preprocessing, and obtains the parameters involved in the calculation in the calculation processing module; Substitute the parameter values ​​obtained after decoding preprocessing into the air pollution value algorithm unit and the water pollution value algorithm unit of the calculation processing module to calculate the air pollution value API and the water pollution value WQi; The calculated air pollution value API and water pollution value WQi are input as input parameters to the environmental comprehensive pollution index algorithm unit of the calculation processing module to calculate different environmental comprehensive pollution indexes ECi for different monitoring areas and upload them to the database, and the warning threshold value Y1 of the environmental comprehensive pollution index ECi is set to 30% in the database, and the danger threshold value Y2 of the environmental comprehensive pollution index ECi is set to 70%; Monitor resource allocation through the resource allocation module: Compare the different comprehensive environmental pollution indexes ECi of different monitoring areas with the warning threshold Y1 and the danger threshold Y2; For monitoring areas where the comprehensive environmental pollution index ECi is less than the warning threshold Y1, the monitoring frequency is maintained at once a quarter; For monitoring areas where the comprehensive environmental pollution index ECi is greater than the warning threshold Y1 and less than the danger threshold Y2, the monitoring frequency will be increased from once a quarter to once a month; For monitoring areas where the comprehensive environmental pollution index ECi is greater than the danger threshold Y2, the monitoring frequency will be increased to once a week, and the environmental monitoring department will be reminded to take corresponding environmental governance measures.

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