Bulk cargo wharf pollution source intelligent monitoring system and method based on meteorological sensing

Abstract

The invention discloses a meteorological sensing-based bulk cargo terminal pollution source intelligent monitoring system and method. The system comprises a sensor monitoring network; a data acquisition module; a data fusion evaluation module; according to the system, meteorological sensing data and multi-source pollution indexes are organically combined, a sum evaluation index system covering flying dust, noise, air pollution and water resource utilization efficiency is constructed, the spatial position of a pollution source can be rapidly positioned, the emission intensity can be quantified, and data support is provided for subsequent prevention and treatment measures.

Description

Technical Field

[0001] This invention relates to the field of pollution source monitoring technology, and in particular to an intelligent monitoring system and method for pollution sources at bulk cargo terminals based on meteorological sensors. Background Technology

[0002] Bulk cargo terminals undertake the loading, unloading, storage, and operation of large quantities of bulk cargo such as coal, ore, and grain. However, the operations of bulk cargo terminals are often accompanied by serious environmental pollution problems, which seriously affect the surrounding ecological environment and human health. Traditional bulk cargo terminal monitoring has relatively single dimensions and cannot comprehensively evaluate the overall environmental conditions of the terminal area. For example, patent application CN117092300A uses laser scanning radar and air detectors to obtain data for air quality evaluation. However, the monitoring elements are single and lack simultaneous monitoring of multiple elements such as dust, noise, air pollutants, and water resource utilization. Moreover, the traceability capability is weak. Many monitoring systems stop at displaying monitoring data and issuing alarms, failing to effectively trace the pollution source and failing to effectively guide dust suppression, noise reduction, and water cycle management. Summary of the Invention

[0003] The present invention aims to address the shortcomings of the prior art by providing an intelligent monitoring system and method for pollution sources at bulk cargo terminals based on meteorological sensors.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A smart monitoring system for pollution sources at a bulk cargo terminal based on meteorological sensors includes:

[0006] Sensor monitoring network: including meteorological sensors, particulate matter sensors, noise sensors, air quality sensors and water volume sensors, to collect environmental data of bulk cargo terminals in real time;

[0007] Data acquisition module: Summarizes environmental data collected by the sensor monitoring network and performs formatting and verification;

[0008] Pollution source identification module: Identifies the type, location, and emission intensity of pollution sources based on environmental data;

[0009] Data fusion and evaluation module: Based on environmental data and pollution source information, calculate the dust pollution index, noise pollution index, air pollution comprehensive index and water resource utilization efficiency index, and calculate the comprehensive monitoring index after fusion;

[0010] Early warning and visualization module: It compares the comprehensive monitoring index with the preset threshold, and determines the abnormal situation of environmental monitoring based on the comparison results. When the comprehensive monitoring index exceeds the preset threshold, an early warning is issued, and the pollution distribution, source tracing results and early warning information are displayed on the map interface of the visualization terminal.

[0011] The pollution source identification module includes a transport and diffusion analysis unit, a chemical reaction analysis unit, and a source apportionment unit. The transport and diffusion analysis unit is used to simulate the diffusion path and concentration distribution of pollutants in the dock area based on environmental data and pollution source parameters. The chemical reaction analysis unit is used to simulate the chemical reaction process of pollutants in the atmosphere based on pollutant type and meteorological data. The source apportionment unit is used to analyze the pollution source contribution value and composition spectrum based on the pollutant concentration matrix and source configuration matrix.

[0012] The formula for calculating the comprehensive monitoring index in the data fusion evaluation module is as follows: Among them, EMCI is the comprehensive monitoring index; DPI is the dust pollution index; NPI is the noise pollution index; AQCI is the comprehensive air pollution index; and WUEI is the water resource utilization efficiency index.

[0013] The aforementioned early warning and visualization module includes an interface for displaying the spatial distribution of pollution concentration; an interface for analyzing the spatiotemporal evolution of pollution; an interface for analyzing pollution sources; an interface for early warning and alarm; and an interface for predicting and assessing air quality.

[0014] The formula for calculating the dust pollution index (DPI) is as follows:

[0015] ,in, The surface area of ​​the storage yard; Average wind speed; , These are surface humidity and internal humidity, respectively. PM10 concentration; This represents the maximum humidity level in the air.

[0016] The formula for calculating the Noise Pollution Index (NPI) is as follows:

[0017] ,in: Noise from dock operations; Average traffic noise at the dock; This represents the average background noise at the dock. The maximum noise level specified for bulk cargo terminals;

[0018] Among them, dock operation noise Where m is the number of dockside machines; Let i be the operating time of the i-th machine within the monitoring cycle; The average noise level within the specified operating area of ​​the i-th machine is obtained by averaging the values ​​of K noise sensors. Average operating time of all operating machinery; The average noise level of all operating machinery;

[0019] Average traffic noise at the dock Where k1 is the number of noise sampling points in the dock traffic area; This is the sum of the noise levels at all k1 noise sampling points in the port traffic area;

[0020] Average background noise at the dock Where k2 is the number of noise sampling points in the non-operational and non-traffic areas of the dock; This is the sum of the noise levels at all k2 noise sampling points in the area;

[0021] The formula for calculating the Air Quality Index (AQCI) is as follows:

[0022] Where AQCI is the comprehensive air pollution index; N is the number of types of air pollutants in the target bulk cargo terminal area; Let be the weighting coefficient of the i-th air pollutant, satisfying ; Let be the air pollution sub-index for the i-th pollutant; Let be the measured concentration value of the i-th pollutant;

[0023] Among them, the air pollution sub-index for each pollutant The calculation formula is: ,in This represents the lower limit of the concentration limit range for the i-th pollutant. This represents the upper limit of the concentration limit range for the i-th pollutant; For corresponding The lower limit of the air pollution index; For corresponding The upper limit of the air pollution index.

[0024] The formula for calculating the Water Resources Utilization Efficiency Index (WUEI) is as follows:

[0025] ,in, Water consumption during the monitoring period at the wharf; For the port's cargo throughput; To improve the rainwater collection and utilization rate of the dock; The rate of wastewater treatment and reuse at the dock; , The amount of rainwater collected is measured by sensors in the dock's rainwater harvesting system. This refers to the total rainfall during the monitoring period, obtained from meteorological data. , The amount of wastewater treated and reused is collected by sensors in the dock wastewater treatment system. This refers to the total wastewater volume within the monitoring period obtained from the dock wastewater discharge records.

[0026] A method for intelligent monitoring of pollution sources at bulk cargo terminals based on meteorological sensors, comprising the following steps:

[0027] Step S1: Collect environmental data of the bulk cargo terminal in real time through a sensor monitoring network, obtain wind speed, humidity and precipitation data using preset meteorological sensors, obtain surface area data of the bulk cargo terminal yard through drones, and obtain concentration data of one or more pollutants among PM10, SO2, NO2, CO and O3 using air quality sensors.

[0028] Step S2: Format and validate the environmental data, and store it in the database;

[0029] Step S3: Identify pollution source types, locations, and emission intensity based on environmental data;

[0030] Step S4: Calculate the dust pollution index, noise pollution index, comprehensive air pollution index, and water resource utilization efficiency index from the acquired data on wind speed, humidity, precipitation, storage yard surface area, and pollutant concentration, and then calculate the comprehensive monitoring index after merging them.

[0031] Step S5: When the comprehensive monitoring index exceeds the preset threshold, an early warning is triggered and pollution information is displayed on the visual map interface.

[0032] The warning judgment condition in step S4 is as follows: ,in, This represents the preset threshold of the comprehensive monitoring index. If EPC < 1, it is determined to be an environmental monitoring anomaly.

[0033] The beneficial effects of this invention are: This invention organically combines meteorological sensor data with multi-source pollution indicators to construct a comprehensive evaluation index system covering dust, noise, air pollution and water resource utilization efficiency, which can quickly locate the spatial location of pollution sources and quantify emission intensity, providing data support for subsequent prevention and control measures. Attached Figure Description

[0034] Figure 1 This is a framework diagram of the intelligent monitoring system for pollution sources at bulk cargo terminals based on meteorological sensors, as presented in this invention.

[0035] The following will describe in detail, with reference to the accompanying drawings, embodiments of the invention. Detailed Implementation

[0036] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0037] A smart monitoring system for pollution sources at a bulk cargo terminal based on meteorological sensors includes:

[0038] Sensor monitoring network: including meteorological sensors, particulate matter sensors, noise sensors, air quality sensors and water volume sensors, to collect environmental data of bulk cargo terminals in real time;

[0039] Data acquisition module: Summarizes environmental data collected by the sensor monitoring network and performs formatting and verification;

[0040] Pollution Source Identification Module: Based on environmental data, this module identifies the type, location, and emission intensity of pollution sources. It includes a transport and diffusion analysis unit, a chemical reaction analysis unit, and a source apportionment unit. The transport and diffusion analysis unit simulates the diffusion path and concentration distribution of pollutants in the dock area based on environmental data and pollution source parameters. The chemical reaction analysis unit simulates the chemical reaction process of pollutants in the atmosphere based on pollutant type and meteorological data. The source apportionment unit analyzes the pollution source contribution value and composition spectrum based on the pollutant concentration matrix and source configuration matrix.

[0041] Data fusion and evaluation module: Based on environmental data and pollution source information, calculate the dust pollution index, noise pollution index, air pollution comprehensive index and water resource utilization efficiency index, and calculate the comprehensive monitoring index after fusion;

[0042] The formula for calculating the comprehensive monitoring index in the data fusion evaluation module is as follows: Among them, EMCI is the comprehensive monitoring index; DPI is the dust pollution index; NPI is the noise pollution index; AQCI is the comprehensive air pollution index; and WUEI is the water resource utilization efficiency index.

[0043] The formula for calculating the dust pollution index (DPI) is as follows:

[0044] ,in, The surface area of ​​the storage yard; Average wind speed; , These are surface humidity and internal humidity, respectively. PM10 concentration; This represents the maximum humidity level in the air.

[0045] The formula for calculating the Noise Pollution Index (NPI) is as follows:

[0046] ,in: Noise from dock operations; Average traffic noise at the dock; This represents the average background noise at the dock. The maximum noise level specified for bulk cargo terminals;

[0047] Among them, dock operation noise Where m is the number of dockside machines; Let i be the operating time of the i-th machine within the monitoring cycle; The average noise level within the specified operating area of ​​the i-th machine is obtained by averaging the values ​​of K noise sensors. Average operating time of all operating machinery; The average noise level of all operating machinery;

[0048] Average traffic noise at the dock Where k1 is the number of noise sampling points in the dock traffic area; This is the sum of the noise levels at all k1 noise sampling points in the port traffic area;

[0049] Average background noise at the dock Where k2 is the number of noise sampling points in the non-operational and non-traffic areas of the dock; This is the sum of the noise levels at all k2 noise sampling points in the area;

[0050] The formula for calculating the Air Quality Index (AQCI) is as follows:

[0051] Where AQCI is the comprehensive air pollution index; N is the number of types of air pollutants in the target bulk cargo terminal area; Let be the weighting coefficient of the i-th air pollutant, satisfying ; Let be the air pollution sub-index for the i-th pollutant; Let be the measured concentration value of the i-th pollutant;

[0052] Among them, the air pollution sub-index for each pollutant The calculation formula is: ,in This represents the lower limit of the concentration limit range for the i-th pollutant. This represents the upper limit of the concentration limit range for the i-th pollutant; For corresponding The lower limit of the air pollution index; For corresponding The upper limit of the air pollution index.

[0053] The formula for calculating the Water Resources Utilization Efficiency Index (WUEI) is as follows:

[0054] ,in, Water consumption during the monitoring period at the wharf; For the port's cargo throughput; To improve the rainwater collection and utilization rate of the dock; The rate of wastewater treatment and reuse at the dock; , The amount of rainwater collected is measured by sensors in the dock's rainwater harvesting system. This refers to the total rainfall during the monitoring period, obtained from meteorological data. , The amount of wastewater treated and reused is collected by sensors in the dock wastewater treatment system. This refers to the total wastewater volume within the monitoring period obtained from the dock wastewater discharge records.

[0055] Early warning and visualization module: It compares the comprehensive monitoring index with the preset threshold, and determines the abnormal situation of environmental monitoring based on the comparison results. When the comprehensive monitoring index exceeds the preset threshold, an early warning is issued, and the pollution distribution, source tracing results and early warning information are displayed on the map interface of the visualization terminal.

[0056] The aforementioned early warning and visualization module includes an interface for displaying the spatial distribution of pollution concentration; an interface for analyzing the spatiotemporal evolution of pollution; an interface for analyzing pollution sources; an interface for early warning and alarm; and an interface for predicting and assessing air quality.

[0057] A method for intelligent monitoring of pollution sources at bulk cargo terminals based on meteorological sensors, comprising the following steps:

[0058] Step S1: Collect environmental data of the bulk cargo terminal in real time through a sensor monitoring network, obtain wind speed, humidity and precipitation data using preset meteorological sensors, obtain surface area data of the bulk cargo terminal yard through drones, and obtain concentration data of one or more pollutants among PM10, SO2, NO2, CO and O3 using air quality sensors.

[0059] Step S2: Format and validate the environmental data, and store it in the database;

[0060] Step S3: Identify pollution source types, locations, and emission intensity based on environmental data;

[0061] Step S4: Calculate the dust pollution index, noise pollution index, comprehensive air pollution index, and water resource utilization efficiency index from the acquired data on wind speed, humidity, precipitation, storage yard surface area, and pollutant concentration, and then calculate the comprehensive monitoring index after merging them.

[0062] Step S5: When the comprehensive monitoring index exceeds the preset threshold, an early warning is triggered and pollution information is displayed on the visual map interface.

[0063] Early warning judgment conditions are ,in, This represents the preset threshold of the comprehensive monitoring index. If EPC < 1, it is determined to be an environmental monitoring anomaly.

[0064] Example 1

[0065] Sensor selection and deployment planning: Choose sensors with industrial-grade protection, high precision, and support for wireless transmission.

[0066] At least one set of six-element micro-weather station shall be deployed on both the upwind and downwind sides of the prevailing wind at the wharf to monitor wind speed, wind direction, temperature, humidity, air pressure and rainfall, etc.

[0067] Particulate matter sensors are deployed in a grid pattern around the storage yard, transfer station, dock boundary, and both sides of main road, with denser deployment in key areas.

[0068] Noise sensors are deployed in the work area around large machinery such as stacker-reclaimers, ship loaders, and ship unloaders; in the traffic area around the dock's heavy truck lanes and intersections; and in the background area around the dock's return work area and green areas, which are far from the work and traffic.

[0069] Air quality sensors and particulate matter sensors are deployed at the same or adjacent locations to monitor SO2, NO2, CO, O3, etc.

[0070] Water sensor: Rainwater harvesting: Install a flow meter at the inlet of the rainwater harvesting tank. Wastewater reuse: Install a flow meter at the reuse outlet of the wastewater treatment system. Total water consumption: Install smart water meters at the main water inlet of the dock. .

[0071] A time-series database is used to store real-time data collected by sensors to meet the high-frequency data read and write requirements, while a relational database is used to store business data, model parameters, and calculation results.

[0072] Pollution Identification Module: Transport and Diffusion Analysis Unit: Integrates an AERMOD diffusion model, inputs meteorological data, and the system initially estimates source strength and topographic data, then outputs a pollutant concentration analysis grid map; Chemical Reaction Analysis Unit: Contains a simple chemical mechanism library to simulate the secondary transformation process of pollutants in the atmosphere; Source Apportionment Unit: Employs the Chemical Mass Balance (CMB) model, pre-establishes a localized "source composition spectrum" database, such as coal dust, road dust, and ship exhaust, fits the real-time monitored pollutant concentration matrix with the source composition spectrum matrix, and calculates the contribution value of cadmium pollution sources.

[0073] Data Fusion Evaluation Module: Index Calculation Engine: A microserver is written to periodically calculate DPI, NPI, AQCI, and WUEI according to preset formulas, configure key parameters, and set... Pollutant weighting coefficient Concentration limits and Parameters, call the result of the exponent calculation engine, according to the formula Calculate the comprehensive monitoring index.

[0074] Early Warning and Visualization Module: Early Warning Trigger: Settings in the early warning system threshold Calculate on a timed basis ;when When the interface displays green, it indicates normal operation. When this happens, the interface will display red, automatically triggering an audible and visual alarm.

[0075] In this invention, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a connection that allows communication between them; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0076] The invention has been described above with reference to the accompanying drawings. Obviously, the specific implementation of the invention is not limited to the above-described manner. Any improvements made using the inventive concept and technical solution, or direct application to other situations without modification, are all within the scope of protection of the invention.

Claims

1. An intelligent monitoring system for pollution sources at bulk cargo terminals based on meteorological sensors, characterized in that, include: Sensor monitoring network: including meteorological sensors, particulate matter sensors, noise sensors, air quality sensors and water volume sensors, to collect environmental data of bulk cargo terminals in real time; Data acquisition module: Summarizes environmental data collected by the sensor monitoring network and performs formatting and verification; Pollution source identification module: Identifies the type, location, and emission intensity of pollution sources based on environmental data; Data fusion and evaluation module: Based on environmental data and pollution source information, calculate the dust pollution index, noise pollution index, air pollution comprehensive index and water resource utilization efficiency index, and calculate the comprehensive monitoring index after fusion; Early warning and visualization module: It compares the comprehensive monitoring index with the preset threshold, and determines the abnormal situation of environmental monitoring based on the comparison results. When the comprehensive monitoring index exceeds the preset threshold, an early warning is issued, and the pollution distribution, source tracing results and early warning information are displayed on the map interface of the visualization terminal.

2. The intelligent monitoring system for pollution sources at bulk cargo terminals based on meteorological sensors according to claim 1, characterized in that, The pollution source identification module includes a transport and diffusion analysis unit, a chemical reaction analysis unit, and a source apportionment unit. The transport and diffusion analysis unit is used to simulate the diffusion path and concentration distribution of pollutants in the dock area based on environmental data and pollution source parameters. The chemical reaction analysis unit is used to simulate the chemical reaction process of pollutants in the atmosphere based on pollutant type and meteorological data. The source apportionment unit is used to analyze the pollution source contribution value and composition spectrum based on the pollutant concentration matrix and source configuration matrix.

3. The intelligent monitoring system for pollution sources at bulk cargo terminals based on meteorological sensors according to claim 2, characterized in that, The formula for calculating the comprehensive monitoring index in the data fusion evaluation module is as follows: Among them, EMCI is the comprehensive monitoring index; DPI is the dust pollution index; NPI is the noise pollution index; AQCI is the comprehensive air pollution index; and WUEI is the water resource utilization efficiency index.

4. The intelligent monitoring system for pollution sources at a bulk cargo terminal based on meteorological sensors according to claim 3, characterized in that, The aforementioned early warning and visualization module includes an interface for displaying the spatial distribution of pollution concentration; an interface for analyzing the spatiotemporal evolution of pollution; an interface for analyzing pollution source tracing; an early warning and alarm interface; and an interface for predicting and assessing air quality.

5. The intelligent monitoring system for pollution sources at a bulk cargo terminal based on meteorological sensors according to claim 3, characterized in that, The formula for calculating the dust pollution index (DPI) is as follows: ,in, The surface area of ​​the storage yard; Average wind speed; , These are surface humidity and internal humidity, respectively. PM10 concentration; This represents the maximum humidity level in the air.

6. The intelligent monitoring system for pollution sources at a bulk cargo terminal based on meteorological sensors according to claim 3, characterized in that, The formula for calculating the Noise Pollution Index (NPI) is as follows: ,in: Noise from dock operations; Average traffic noise at the dock; This represents the average background noise at the dock. The maximum noise level specified for bulk cargo terminals; Among them, dock operation noise Where m is the number of dockside machines; Let i be the operating time of the i-th machine within the monitoring cycle; Let be the average noise level within the specified operating area of ​​the i-th machine; Average operating time of all operating machinery; The average noise level of all operating machinery; Average traffic noise at the dock Where k1 is the number of noise sampling points in the dock traffic area; This is the sum of the noise levels at all k1 noise sampling points in the port traffic area; Average background noise at the dock Where k2 is the number of noise sampling points in the non-operational and non-traffic areas of the dock; This is the sum of the noise levels at all k2 noise sampling points in the area.

7. The intelligent monitoring system for pollution sources at a bulk cargo terminal based on meteorological sensors according to claim 3, characterized in that, The formula for calculating the Air Quality Index (AQCI) is as follows: Where AQCI is the comprehensive air pollution index; N is the number of types of air pollutants in the target bulk cargo terminal area; Let be the weighting coefficient of the i-th air pollutant, satisfying ; Let be the air pollution sub-index for the i-th pollutant; Let be the measured concentration value of the i-th pollutant; Among them, the air pollution sub-index for each pollutant The calculation formula is: ,in This represents the lower limit of the concentration limit range for the i-th pollutant. This represents the upper limit of the concentration limit range for the i-th pollutant; For corresponding The lower limit of the air pollution index; For corresponding The upper limit of the air pollution index.

8. The intelligent monitoring system for pollution sources at a bulk cargo terminal based on meteorological sensors according to claim 3, characterized in that, The formula for calculating the Water Resources Utilization Efficiency Index (WUEI) is as follows: ,in, Water consumption during the monitoring period at the wharf; For the port's cargo throughput; To improve the rainwater collection and utilization rate of the dock; The rate of wastewater treatment and reuse at the dock; , The amount of rainwater collected is measured by sensors in the dock's rainwater harvesting system. This refers to the total rainfall during the monitoring period, obtained from meteorological data. , The amount of wastewater treated and reused is collected by sensors in the dock wastewater treatment system. This refers to the total wastewater volume within the monitoring period obtained from the dock wastewater discharge records.

9. The application method of the intelligent monitoring system for pollution sources at bulk cargo terminals based on meteorological sensors according to claim 4, characterized in that, The steps are as follows: Step S1: Collect environmental data of the bulk cargo terminal in real time through a sensor monitoring network, obtain wind speed, humidity and precipitation data using preset meteorological sensors, obtain surface area data of the bulk cargo terminal yard through drones, and obtain concentration data of one or more pollutants among PM10, SO2, NO2, CO and O3 using air quality sensors. Step S2: Format and validate the environmental data, and store it in the database; Step S3: Identify pollution source types, locations, and emission intensity based on environmental data; Step S4: Calculate the dust pollution index, noise pollution index, comprehensive air pollution index, and water resource utilization efficiency index from the acquired data on wind speed, humidity, precipitation, storage yard surface area, and pollutant concentration, and then calculate the comprehensive monitoring index after merging them. Step S5: When the comprehensive monitoring index exceeds the preset threshold, an early warning is triggered and pollution information is displayed on the visual map interface.

10. The intelligent monitoring method for pollution sources at bulk cargo terminals based on meteorological sensors according to claim 9, characterized in that, The warning judgment condition in step S5 is as follows: ,in, This represents the preset threshold of the comprehensive monitoring index. If EPC < 1, it is determined to be an environmental monitoring anomaly.

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