Atmospheric environment bearing capacity monitoring and early warning system

Abstract

The invention discloses an atmospheric environment bearing capacity monitoring and early warning system which comprises a sensor network, a data transmission network and a data processing center. The sensor network is composed of sensors deployed in a monitoring area and is used for collecting atmospheric environment data in real time; the data transmission network rapidly and stably transmits data collected by the sensor network to the data processing center by using the Internet of Things technology; the data processing center is used for carding, analyzing and storing the received data and providing basic data for subsequent big data analysis; the big data analysis and early warning comprises the following steps: (1) data integration; (2) data mining; (3) predicting a model; (4) judging whether the atmospheric environment reaches an early warning threshold value or not, and triggering an early warning mechanism; according to the invention, through utilization of the Internet of Things technology and big data analysis, real-time monitoring of the atmospheric environment quality and prediction of the future trend are realized, early warning information is issued in time, and a scientific basis can be provided for decision making of government competent departments.

Description

Technical Field

[0001] The present invention belongs to the technical field related to atmospheric environment monitoring and early warning, and specifically relates to an atmospheric environment carrying capacity monitoring and early warning system which realizes real-time monitoring of atmospheric environment quality and prediction of future trends, timely releases early warning information, and can provide a scientific basis for decision-making by government departments by utilizing Internet of Things technology and big data analysis. Background Art

[0002] With the acceleration of industrialization and the expansion of urban scale, atmospheric environmental problems have become increasingly prominent, causing serious impacts on human health and the ecological environment. In order to effectively manage the atmospheric environment, it is necessary to monitor the atmospheric environmental quality in real time and issue early warnings for potential environmental risks. However, existing monitoring methods often have problems such as delays in data collection and analysis, and the lack of intelligence in the early warning system.

[0003] To this end, we have developed an atmospheric environment carrying capacity monitoring and early warning system that uses Internet of Things technology and big data analysis to achieve real-time monitoring of atmospheric environmental quality and prediction of future trends, as well as timely release of early warning information, and can provide a scientific basis for decision-making by government departments. Summary of the invention

[0004] The purpose of the present invention is to provide an atmospheric environment carrying capacity monitoring and early warning system that can realize real-time monitoring of atmospheric environmental quality and prediction of future trends, timely release of early warning information, and provide a scientific basis for decision-making by government departments by utilizing Internet of Things technology and big data analysis.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an atmospheric environment carrying capacity monitoring and early warning system, comprising a sensor network, a data transmission network and a data processing center; the sensor network is composed of sensors deployed in the monitoring area, and is used to collect atmospheric environment data in real time; the data transmission network uses the Internet of Things technology to quickly and stably transmit the data collected by the sensor network to the data processing center; the data processing center sorts, analyzes and stores the received data, and provides basic data for subsequent big data analysis; The big data analysis and early warning include the following steps: ⑴Data integration: Integrate the real-time online monitoring data and historical data of the sensor network to build a regional atmospheric environment database; ⑵Data mining: Use big data analysis technology to analyze the data in the database and discover the laws and trends of atmospheric environmental changes; ⑶ Prediction model: Based on the results of data mining, a prediction model for atmospheric environmental changes is established; (4) The data processing center can determine whether the atmospheric environment has reached the warning threshold and trigger the warning mechanism based on the prediction model and real-time online monitoring data; if the warning is triggered, the warning information will be issued to government departments and relevant personnel through mobile applications, text messages, emails, etc.

[0006] Preferably, in the atmospheric environment carrying capacity monitoring and early warning system, if the data analysis shows that the law and trend of atmospheric environment changes are developing in a one-way direction for the worse, the prediction model should respond in advance and trigger an early warning; if the data analysis shows that the law and trend of atmospheric environment changes are developing in a one-way direction for the better, the prediction model should delay responding before triggering an early warning; if the data analysis shows that the law and trend of atmospheric environment changes are cyclical, the prediction model should respond in a timely manner and trigger an early warning.

[0007] Preferably, in the atmospheric environment carrying capacity monitoring and early warning system, the data processing center adopts the A-value method to calculate the atmospheric environment capacity to obtain the atmospheric environment carrying capacity of a certain place; the data processing center also adopts the CMAQ model simulation method to simulate and evaluate the air quality; the CMAQ model simulation method can comprehensively consider the transmission, diffusion, transformation and sedimentation processes of various pollutants in the atmosphere, thereby realizing the refined simulation and prediction of air quality; the data processing center compares the atmospheric environment capacities obtained by the A-value method and the CMAQ model simulation method, and takes the smaller value to determine the optimal atmospheric environment carrying capacity.

[0008] Compared with the prior art, the present invention provides an atmospheric environment carrying capacity monitoring and early warning system, which has the following beneficial effects: The atmospheric environment carrying capacity monitoring and early warning system described in the present invention compares the atmospheric environment capacities obtained by the A value method and the CMAQ model simulation method, takes the smaller value, to determine the optimal atmospheric environment carrying capacity, and provides a scientific basis for the decision-making of the government department in charge; at the same time, it can judge whether the atmospheric environment reaches the early warning threshold according to the prediction model and real-time online monitoring data, and trigger the early warning mechanism; if the early warning is triggered, the early warning information is issued to the government department in charge and relevant personnel through mobile applications, text messages, emails, etc. DETAILED DESCRIPTION

[0009] The technical solutions in the embodiments of the present invention are clearly and completely described below. Obviously, the described embodiments are only 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 ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0010] The present invention provides a technical solution: an atmospheric environment carrying capacity monitoring and early warning system, comprising a sensor network, a data transmission network and a data processing center; the sensor network is composed of sensors deployed in a monitoring area, and is used to collect atmospheric environment data in real time, such as pollutant concentrations, meteorological parameters, etc.; the data transmission network uses the Internet of Things technology to quickly and stably transmit the data collected by the sensor network to the data processing center; the data processing center sorts, analyzes and stores the received data, and provides basic data for subsequent big data analysis; The big data analysis and early warning include the following steps: ⑴Data integration: Integrate the real-time online monitoring data and historical data of the sensor network to build a regional atmospheric environment database; ⑵Data mining: Use big data analysis technology to analyze the data in the database and discover the laws and trends of atmospheric environmental changes; ⑶ Prediction model: Based on the results of data mining, a prediction model for atmospheric environmental changes is established; (4) The data processing center can determine whether the atmospheric environment has reached the warning threshold and trigger the warning mechanism based on the prediction model and real-time online monitoring data; if the warning is triggered, the warning information will be issued to government departments and relevant personnel through mobile applications, text messages, emails, etc.

[0011] In this embodiment, if the data analysis shows that the law and trend of atmospheric environment changes are developing in a unidirectional direction for the worse, the prediction model should respond in advance, such as when the real-time online monitoring data approaches the warning threshold of 90%, an early warning is triggered; if the data analysis shows that the law and trend of atmospheric environment changes are developing in a unidirectional direction for the better, the prediction model should delay the response, such as when the real-time online monitoring data approaches the warning threshold of 110%, an early warning is triggered; if the data analysis shows that the law and trend of atmospheric environment changes are cyclical, the prediction model should respond in a timely manner, such as when the real-time online monitoring data approaches the warning threshold of 100%, an early warning is triggered.

[0012] In this embodiment, the data processing center uses the A-value method to calculate the atmospheric environment capacity to obtain the atmospheric environment carrying capacity of a certain place; the atmospheric environment capacity includes the annual allowable total emission limits of various pollutants; the data processing center also uses the CMAQ model simulation method to simulate and evaluate air quality; the CMAQ model simulation method can comprehensively consider the transmission, diffusion, transformation and sedimentation processes of various pollutants in the atmosphere, thereby realizing refined simulation and prediction of air quality; the data processing center compares the atmospheric environment capacities obtained by the A-value method and the CMAQ model simulation method, and takes the smaller value to determine the optimal atmospheric environment carrying capacity.

[0013] The A-value method for calculating atmospheric environmental capacity is an existing technology and will not be repeated here.

[0014] The Community Multiscale Air Quality Model (CMAQ) model is a complex model developed by the U.S. Environmental Protection Agency (EPA) for simulating and evaluating air quality. The CMAQ model can simulate a variety of pollutants, including ozone, particulate matter, toxic substances, and acid deposition, and is suitable for multi-scale, multi-pollution air quality forecasting, assessment, and decision-making research.

[0015] The basic principles and functions of the CMAQ model: The CMAQ model is based on the Chemical Transport Model (CTM) and can simulate chemical reactions and transport processes in the atmosphere; it contains multiple chemical mechanisms, such as CB4, CB5, SAPRC99 and RADM2, which are used to describe the reaction processes of different chemical substances; the biggest feature of the CMAQ model is its "one atmosphere" concept, which can comprehensively deal with complex air pollution conditions, such as tropospheric ozone, PM, toxicants, acid deposition and visibility issues.

[0016] 1. Installation, configuration and operation of CMAQ model: To install the CMAQ model, follow these steps: ‌Environment configuration‌: Install necessary library files and environment settings; Meteorological field processing module: install and run MCIP (Meteorological Component Interface Program); ‌Pre-processing module‌: Install and run ICON or BCON.

[0017] ‌ Polluted source file update processing module‌: install and run related modules; ‌Main module‌: Install CCTM (Community Multiscale Air Quality Model); 2. Analysis and interpretation of CMAQ simulation results: Understanding CMAQ simulation results requires the following steps: ‌Result extraction and data visualization‌: Extract simulation results and perform visualization; ‌Physical interpretation‌: Provide physical interpretation of simulation results to understand the impact of different parameters on air quality; Uncertainty analysis: Uncertainty transfer analysis is performed through Monte Carlo method and random response surface method to improve the prediction accuracy and computational efficiency of the model; 3. CMAQ Air Quality Forecast and Assessment System The third-generation air quality forecasting and assessment system (Models-3) developed by the U.S. Environmental Protection Agency. Models-3 is the general name for the third-generation air quality modeling system, and its core is the Community Multiscale Air Quality (CMAQ) model system, so it can also be generally referred to as the Models-3 / CMAQ model; the biggest feature of CMAQ is that it breaks through the concept of one-atmosphere, breaking through the traditional model's simulation of single species and single-phase species, and comprehensively handles complex air pollution conditions such as tropospheric ozone, PM, toxic substances, acid deposition and visibility, and is used for multi-scale, multi-pollution air quality forecasting, assessment and decision-making research and other purposes; in terms of spatial scope, users can choose multi-scale scopes such as local, urban, and regional according to their own model requirements; the model can predict a variety of pollutants, with more than 80 types; in the chemical transport mode of Models-3, four chemical mechanisms can be selected: CB4, CB5, SAPRC99 and RADM2.

[0018] Application 1 of the present invention: (1) Use the sensor network to collect pollutant data from key industrial sources in the study area, and after analysis by the data processing center, obtain the types and composition of air pollution sources in Manas County; (2) The sensor network was used to collect environmental quality data of basic pollutants in the atmospheric environment of the study area. The data processing center used mathematical statistics to determine whether each factor met the standard. At the same time, additional monitoring of characteristic factors was carried out, and environmental quality analysis of characteristic pollutants was performed. (3) The data processing center used the A value method to estimate and analyze the environmental capacity of conventional basic pollutants SO2, NO2 and characteristic pollutants VOCS in Manas County; at the same time, based on the CMAQ model baseline scenario simulation results, the environmental capacity of the main conventional basic pollutants SO2, NO2 and characteristic pollutants VOCS in Manas County was simulated and analyzed to quantify the atmospheric environmental capacity of Manas County with different analysis methods; (4) The data processing center compares the atmospheric environmental capacity obtained by the two methods and takes the smaller value to determine the atmospheric environmental carrying capacity of Manas County. Based on this, it makes plans and suggestions for the land space planning and industrial optimization layout of the Tahe Industrial Zone in Manas County; Furthermore, if data analysis shows that the rules and trends of atmospheric environmental changes are developing in a unidirectional direction for the worse, the prediction model should respond in advance, such as triggering a warning when the real-time online monitoring data approaches the warning threshold of 90%; if data analysis shows that the rules and trends of atmospheric environmental changes are developing in a unidirectional direction for the better, the prediction model should respond later, such as triggering a warning when the real-time online monitoring data approaches the warning threshold of 110%; if data analysis shows that the rules and trends of atmospheric environmental changes are cyclical, the prediction model should respond in a timely manner, such as triggering a warning when the real-time online monitoring data approaches the warning threshold of 100%.

[0019] This application mainly uses the A value method in the environmental capacity assessment method and analyzes the atmospheric environmental carrying capacity of Manas County. Based on the analysis results, it proposes plans and suggestions for the land space planning and industrial optimization layout of the Tahe Industrial Zone in Manas County.

[0020] Compared with the prior art, the present invention has the following beneficial effects: The atmospheric environment carrying capacity monitoring and early warning system described in the present invention compares the atmospheric environment capacities obtained by the A value method and the CMAQ model simulation method, takes the smaller value, to determine the optimal atmospheric environment carrying capacity, and thereby provides a scientific basis for government decision-making; at the same time, it can determine whether the atmospheric environment reaches the early warning threshold based on the prediction model and real-time online monitoring data, and trigger the early warning mechanism; if the early warning is triggered, the early warning information is issued to the government departments and relevant personnel through mobile applications, text messages, emails, etc.

[0021] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An atmospheric environment carrying capacity monitoring and early warning system, characterized in that: It includes a sensor network, a data transmission network and a data processing center; the sensor network is composed of sensors deployed in the monitoring area and is used to collect atmospheric environment data in real time; the data transmission network uses the Internet of Things technology to quickly and stably transmit the data collected by the sensor network to the data processing center; the data processing center sorts, analyzes and stores the received data to provide basic data for subsequent big data analysis; The big data analysis and early warning include the following steps: ⑴Data integration: Integrate the real-time online monitoring data and historical data of the sensor network to build a regional atmospheric environment database; ⑵Data mining: Use big data analysis technology to analyze the data in the database and discover the laws and trends of atmospheric environmental changes; ⑶ Prediction model: Based on the results of data mining, a prediction model for atmospheric environmental changes is established; (4) The data processing center can determine whether the atmospheric environment has reached the warning threshold and trigger the warning mechanism based on the prediction model and real-time online monitoring data; if the warning is triggered, the warning information will be issued to government departments and relevant personnel through mobile applications, text messages, emails, etc.

2. The atmospheric environment carrying capacity monitoring and early warning system according to claim 1, characterized in that: If the data analysis shows that the law and trend of atmospheric environmental change is developing in a one-way direction, the prediction model should respond in advance and trigger an early warning; If the data analysis shows that the law and trend of atmospheric environmental change is a one-way positive development, the prediction model will delay the response before triggering the warning; If data analysis shows that the patterns and trends of atmospheric environmental changes are cyclical, the prediction model must respond promptly and trigger an early warning.

3. The atmospheric environment carrying capacity monitoring and early warning system according to claim 1 or 2, characterized in that: The data processing center uses the A-value method to calculate the atmospheric environmental capacity to obtain the atmospheric environmental carrying capacity of a certain place; the data processing center also uses the CMAQ model simulation method to simulate and evaluate air quality; the CMAQ model simulation method can comprehensively consider the transmission, diffusion, transformation and sedimentation processes of various pollutants in the atmosphere, thereby realizing refined simulation and prediction of air quality; the data processing center compares the atmospheric environmental capacities obtained by the A-value method and the CMAQ model simulation method, takes the smaller value, and determines the optimal atmospheric environmental carrying capacity.