CN111145064B - Dynamic emergency early warning assessment and decision support method and system for sudden air pollution accidents - Google Patents
Dynamic emergency early warning assessment and decision support method and system for sudden air pollution accidents Download PDFInfo
- Publication number
- CN111145064B CN111145064B CN201911320897.5A CN201911320897A CN111145064B CN 111145064 B CN111145064 B CN 111145064B CN 201911320897 A CN201911320897 A CN 201911320897A CN 111145064 B CN111145064 B CN 111145064B
- Authority
- CN
- China
- Prior art keywords
- emergency
- monitoring
- accident
- dynamic
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000003915 air pollution Methods 0.000 title claims abstract description 21
- 238000012544 monitoring process Methods 0.000 claims abstract description 80
- 238000009826 distribution Methods 0.000 claims abstract description 33
- 230000036541 health Effects 0.000 claims abstract description 31
- 238000004088 simulation Methods 0.000 claims abstract description 20
- 238000012502 risk assessment Methods 0.000 claims abstract description 18
- 238000005516 engineering process Methods 0.000 claims abstract description 14
- 238000011156 evaluation Methods 0.000 claims abstract description 14
- 238000005457 optimization Methods 0.000 claims abstract description 11
- 239000003344 environmental pollutant Substances 0.000 claims abstract description 8
- 231100000719 pollutant Toxicity 0.000 claims abstract description 8
- 238000009792 diffusion process Methods 0.000 claims description 30
- 238000007726 management method Methods 0.000 claims description 10
- 230000001154 acute effect Effects 0.000 claims description 8
- 230000008821 health effect Effects 0.000 claims description 8
- 231100000331 toxic Toxicity 0.000 claims description 8
- 230000002588 toxic effect Effects 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000004891 communication Methods 0.000 claims description 7
- 231100000614 poison Toxicity 0.000 claims description 6
- 239000002341 toxic gas Substances 0.000 claims description 6
- 238000011161 development Methods 0.000 claims description 5
- 230000004044 response Effects 0.000 claims description 5
- 238000012876 topography Methods 0.000 claims description 5
- 231100000569 acute exposure Toxicity 0.000 claims description 4
- 230000008878 coupling Effects 0.000 claims description 4
- 238000010168 coupling process Methods 0.000 claims description 4
- 238000005859 coupling reaction Methods 0.000 claims description 4
- 239000002574 poison Substances 0.000 claims description 4
- 238000011160 research Methods 0.000 claims description 4
- 239000000126 substance Substances 0.000 claims description 4
- 230000001502 supplementing effect Effects 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 230000007613 environmental effect Effects 0.000 claims description 3
- 241000282412 Homo Species 0.000 claims description 2
- 238000004422 calculation algorithm Methods 0.000 claims description 2
- 238000005094 computer simulation Methods 0.000 claims description 2
- 238000001514 detection method Methods 0.000 claims description 2
- 230000004927 fusion Effects 0.000 claims description 2
- 238000011065 in-situ storage Methods 0.000 claims description 2
- 238000012905 input function Methods 0.000 claims description 2
- 230000003993 interaction Effects 0.000 claims description 2
- 238000012806 monitoring device Methods 0.000 claims description 2
- 239000002245 particle Substances 0.000 claims description 2
- 238000005070 sampling Methods 0.000 claims description 2
- 238000012216 screening Methods 0.000 claims description 2
- 238000012163 sequencing technique Methods 0.000 claims description 2
- 230000008569 process Effects 0.000 abstract description 3
- 230000008859 change Effects 0.000 abstract description 2
- 238000012937 correction Methods 0.000 abstract description 2
- 230000002093 peripheral effect Effects 0.000 description 4
- 239000007789 gas Substances 0.000 description 2
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 231100000206 health hazard Toxicity 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000007096 poisonous effect Effects 0.000 description 1
- 231100000816 toxic dose Toxicity 0.000 description 1
- 239000003440 toxic substance Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Educational Administration (AREA)
- Entrepreneurship & Innovation (AREA)
- Tourism & Hospitality (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Primary Health Care (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
A dynamic emergency early warning assessment and decision support method and system for sudden air pollution accidents belong to the field of sudden air pollution emergency early warning assessment and emergency decision. The method comprises the following steps: (1) accident capturing and identifying; (2) decision support basic data information query retrieval; (3) simulation prediction and health risk assessment; (4) optimizing monitoring distribution points; (5) on-site integrated monitoring (weather, pollutants); (6) source strong dynamic update feedback; (7) expert consultation. The emergency method steps are integrated by utilizing a network information technology, and finally a complete dynamic emergency early warning evaluation and decision support system is formed. The invention provides a key emergency technical process framework of 'source intensity-simulation-monitoring distribution', realizes mutual feedback correction of the data streams of pollution emission-simulation-monitoring, and can systematically solve the problems of dynamic change of the source intensity of sudden accidents, rapid early warning and updating of micro-scale pollution, emergency optimization monitoring selection and the like.
Description
Technical Field
The invention belongs to the field of emergency early warning evaluation and emergency decision support of sudden air pollution, and relates to a method for emergency early warning evaluation and decision support of sudden air pollution accidents, in particular to a dynamic emergency early warning evaluation and decision support system which is built by integrating an optimization traceability technology, a model simulation forecasting technology, an emergency monitoring point distribution technology, a health risk evaluation criterion, a database information management system and an emergency monitoring system so as to realize rapid and scientific dynamic emergency early warning evaluation and decision support of sudden air pollution accidents.
Background
With the rapid development of the economy in China, sudden atmospheric pollution accidents (explosion, fire, leakage, malodor and the like) caused by various production and living activities are rapidly increased, and the accidents suddenly and rapidly emit a large amount of toxic and harmful pollutants in a short time, the dynamic change of emission rules and the pollution degree are difficult to control, so that the pollution degree is a great threat to human health, ecological environment and economic development. The rapid and accurate early warning and emergency evaluation treatment of the sudden accident are researched, and the method has important significance for improving the scientificity and the effectiveness of the sudden air pollution accident emergency and reducing the human health hazard and the economic loss.
At present, some researches are carried out on emergency systems of sudden accidents at home and abroad, such as an ALOHA early warning system recommended by the U.S. environmental protection agency, a GASTRAR system developed by Cambridge environment research consultation company in England, a GIS-SLAB dangerous gas diffusion real-time prediction early warning system, an MM5/WRF-HYSPLIT prediction system and a sudden air pollution monitoring and forecasting integrated mobile platform in China. In general, some research has been done, but the above emergency systems mostly focus on only one aspect of the emergency process. The existing system lacks of effective integration of multiple technologies and of an emission-monitoring-simulation-emergency treatment linkage coupling emergency early warning assessment method, and rapid and dynamic early warning assessment of sudden accidents is not realized.
Disclosure of Invention
Aiming at emergency requirements of sudden accidents, the invention solves the problems of pollution emission, monitoring, simulation, dynamic update and feedback of emergency treatment information and the like in the real sudden accident emergency management and treatment process, and provides a set of dynamic emergency early warning evaluation and decision support method and system, thereby realizing rapid and dynamic early warning evaluation of sudden accidents and providing more scientific and perfect technical support for emergency decisions.
The technical scheme adopted by the invention is as follows:
a dynamic emergency early warning assessment and decision support method for sudden air pollution accidents comprises the following steps:
(1) Sudden accident catching and identifying method
After the sudden air pollution accident occurs, emergency personnel input and record the basic information of the sudden accident according to the alarm receiving information;
(2) Automatic retrieval of underlying database information
Inquiring basic database information according to the accident alarm receiving information and calling information about the displayed accident;
(3) Simulation prediction and health risk assessment
The method comprises the steps of realizing the normalized operation of a weather forecast model and the dynamic display of a forecast result; according to accident alarm receiving information, dynamic simulation prediction is carried out on toxic gas pollution diffusion space-time distribution to obtain pollution influence range, and the concentration standard of human acute health effect is combined on the basis; defining a health risk area, generating a dynamic health risk forecasting field and displaying the dynamic health risk forecasting field;
(4) Optimizing monitoring distribution point
Based on the diffusion simulation-health risk assessment result and combining with actual emergency monitoring resources and geographic information (peripheral sensitive points, traffic, population density, topography, rivers and the like), obtaining and displaying an optimized monitoring point distribution proposal;
(5) In-situ integrated monitoring
According to the optimized point distribution proposal, real-time monitoring data are obtained by utilizing on-line monitoring equipment;
(6) Dynamic update feedback of source strength
The on-site real-time monitoring data and the diffusion model are utilized to dynamically update the accident source intensity, and the source intensity updating result is transmitted and fed back to the diffusion model to dynamically update the pollution prediction result;
(7) Expert consultation
Establishing audio connection between the emergency command center and the accident emergency site by using a network communication technology, and realizing information interaction feedback between the command center and the accident site; the network communication technology is utilized to realize the audio connection between the command center and the expert in the emergency field, and scientific and effective suggestions are provided for the accident scene treatment decision.
The emergency technical support module formed by applying the method comprises a sudden accident capturing and identifying module, a basic information management module, a simulation prediction and health risk assessment module, an optimized monitoring point distribution module, a field comprehensive monitoring module, a source strong dynamic updating feedback module and an expert consultation module which are all connected with the same network platform, and a sudden air pollution accident dynamic emergency early warning assessment and decision support system based on multi-technology fusion is established. Each system can independently operate, and can also carry out cooperative work through data transmission among different technical modules.
The dynamic emergency early warning assessment and decision support method and system for the sudden air pollution accident, provided by the invention, are used for coupling an integrated basic information data system, a prediction simulation system, an emergency point distribution system, a field comprehensive monitoring system and a traceability system into a whole from actual emergency demands, and constructing a dynamic emergency early warning assessment and decision support system, wherein the system covers the functions of automatic acquisition of database information, dynamic prediction of future accident pollution development state, real-time comprehensive monitoring of an accident field, and interactive feedback of information between a command center and the accident field, and can realize rapid and scientific emergency early warning assessment and decision support for the sudden air pollution accident.
Drawings
FIG. 1 is a schematic flow diagram of a dynamic emergency early warning evaluation and decision support system structure and main use method for sudden air pollution accidents;
Detailed Description
The invention is further described below based on the case assumption scenario of sudden accidents in combination with the main handling flow of sudden accidents:
the method for dynamic emergency early warning and decision support of sudden accidents provided by the invention is used for emergency response under the assumption that a poisonous gas leakage accident occurs in a certain chemical enterprise, and the system is used for operation, and comprises the following specific steps:
(1) Sudden accident catching
The emergency personnel receives the accident alarming telephone, inputs and records the basic information of the accident according to the information provided by the alarming personnel, and starts an emergency system; meanwhile, immediately notifying a department leader, and enabling related emergency personnel to rush to the scene;
the incident basic information input content mainly comprises: the method comprises the steps of dealing with enterprise names, accident occurrence time, toxic names, information sources, alarm persons and contact modes, alarm receiving personnel and alarm receiving time.
(2) Basic data information inquiry and call
Inquiring and supplementing basic database information according to the accident alarm receiving information and calling information about the displayed accident;
further supplementing and subdividing the basic information base, specifically comprising: a risk source basic information database (including information such as enterprise names, positions, responsible persons, contact ways, emergency resources and the like), a geographic information database (including information such as surrounding sensitive points, traffic, topography, population density and the like), an emergency equipment management database (field sampling equipment, field monitoring equipment, communication lighting, personal protection equipment and the like), an emergency expert information database (including expert information in aspects such as medical treatment, chemical industry, environment, accident scene rescue and the like), a toxic emergency treatment information database (including information such as related toxic physicochemical properties, influence on the environment, environmental standards, field and laboratory detection methods, emergency treatment methods and the like), and an emergency plan database (government emergency plans, comprehensive emergency plans, special emergency plans and field treatment plans).
Risk source information, emergency plans, surrounding sensitive point information and toxic emergency disposal information of the involved enterprises.
The emergency system automatically retrieves and retrieves information about accidents according to accident information input by emergency personnel, and at least comprises information about enterprises involved in the accidents, information about physical and chemical properties and treatment methods of toxic substances, information about sensitive points around the accidents, information about emergency specialists, information about emergency plans of the accidents and the like, so that preliminary information support is provided for leading and commanding decisions of emergency departments.
(3) Simulation prediction and health risk assessment
Adopting and realizing the normalized operation of a weather forecast model and predicting a dynamic diffusion result;
according to accident alarm receiving information, adopting a weather forecast model to dynamically simulate and predict the space-time distribution of toxic gas pollution diffusion to obtain a pollution influence range, and combining the concentration standard of the human acute health effect on the basis; defining a health risk area, generating a dynamic health risk forecasting field and displaying the dynamic health risk forecasting field;
when emergency personnel arrive at the scene, model prediction and health risk assessment in an emergency system enter a background running state and give out calculation results in a short time, the obtained toxic gas pollution influence range and health risk area division prediction results are displayed in a superposition dynamic manner by adopting a GIS system, and advice and reference are provided for the rapid operation of accident handling command;
the weather forecast model adopts a WRF-CALMET coupling model, the pollution diffusion forecast adopts a WRF-CALMET weather forecast field as weather drive, and is coupled with the diffusion model to realize pollution dynamic forecast, and the diffusion model is selected from any one of CALPUFF, AERMOD, gaussian plume model (Gaussian Plume Model) and SLAB diffusion model.
The concentration criteria for acute health effects in humans include: acute exposure guide concentrations (Acute Exposure Guideline Levels, AEGLs); emergency response plan guidance concentration (Emergency Response Planning Guidelines, ERPG); short emergency exposure limit (Temporary Emergency Exposure Limits, tel).
(4) Emergency monitoring point location optimization
After the pollution prediction result is obtained, emergency system operators mobilize emergency monitoring resources, peripheral sensitive points, health risk assessment results and geographic information according to the actual scene, an optimal point distribution proposal scheme is obtained through calculation by using an optimal point distribution technology module, and the commander is helped to make a quick decision in the aspect of monitoring point selection;
based on the diffusion simulation-health risk assessment result obtained in the step (3) and combining with actual emergency monitoring resources and geographic information (peripheral sensitive points, traffic, population density, topography, rivers and the like), obtaining and displaying an optimal monitoring point distribution proposal;
the optimization monitoring distribution comprises the following specific steps:
step 1), primarily judging a distribution range by utilizing a pollution concentration field result of a numerical model meshing;
step 2) determining a poison hazard zone based on a concentration standard of an acute health effect of a human body;
step 3) sorting pollution concentration prediction results according to concentration outside the poison dangerous area;
step 4) according to the concentration sequencing result, screening the grid point positions with the N large values before concentration by taking the number N of monitoring devices which can be actually called in the accident scene as a constraint condition, and taking the grid point positions as suggested monitoring point distribution positions;
and 5) comprehensively evaluating the point distribution scheme by combining geographic information (peripheral sensitive points, traffic, population density, topography, rivers and the like), and determining a final optimized monitoring point distribution scheme.
(5) On-site comprehensive observation
According to the optimized point distribution proposal, real-time monitoring data are obtained by utilizing on-line monitoring equipment;
the on-site integrated monitoring comprises the following steps: and acquiring real-time data of the wind direction, the wind speed and the pollutant qualitative and quantitative of the accident site by using on-line monitoring equipment.
(6) Dynamic update feedback of source strength
Comparing the on-site real-time monitoring data with the prediction result of the diffusion model to judge whether to dynamically update the accident source intensity, if so, performing source intensity updating calculation by using the monitoring data, and transmitting and feeding back the calculation result to the simulation prediction in the step (3), namely updating the pollution prediction and the risk area division result by using the diffusion model;
the step of dynamically updating the source intensity comprises the following steps:
step 1) utilizing concentration data of site monitoring points, firstly carrying out dynamic update judgment on the source intensity of pollutants, and if the update condition is met; step 2) is executed, and if the condition is not met, no update is executed;
step 2) taking the field concentration data as input into a source intensity inversion model, establishing a minimized objective function, and solving the minimized objective function by using an optimization method, wherein the obtained solution results are the pollution source position and the release rate of pollution source pollutants;
the dynamic update judgment conditions are as follows:
r represents a correlation coefficient, sigma o 、σ p Representing the standard deviation of the actual monitoring concentration value at all the monitoring positions and the standard deviation of the model simulation concentration value at all the positions corresponding to the actual monitoring respectively, C p 、C o Representing the analog concentration and the actual monitoring concentration output by the diffusion model at a certain monitoring point,concentration mean value representing all actual monitoring points, +.>The average value of the analog concentration, which represents the output of all diffusion models, is updated when R is greater than 0.6.
The source intensity inversion model is in the form of:
i represents field concentration monitoring points, n represents the number of monitoring points, and C p 、C o As above.
The source intensity inversion solving method is a standard particle swarm optimization algorithm.
(7) Expert consultation
When the accident development scale and pollution influence are large, the audio connection is required to be quickly established with emergency personnel at the accident scene and related experts in the emergency expert information base automatically called in the step (2), the accident scene, the command center and the off-site experts are connected through an emergency system, the accident is scientifically researched and judged, and finally the command center issues a reasonable disposal command for the accident scene.
The sudden accident capturing and identifying module (1) has the functions of model operation parameter input and intelligent starting including (2) a basic information management module and (3) two technical modules of a simulation prediction and health risk assessment module besides the alarm receiving information input function, and realizes the automatic operation of the system modules (2) and (3).
And (6) the source intensity dynamic updating feedback module can directly utilize the monitoring data of the (5) on-site comprehensive monitoring module to carry out source intensity inversion updating and automatically feed information back to the (3) simulation prediction and health risk assessment module.
Based on the on-line monitoring equipment, the meteorological elements and the toxic concentration of sensitive points around the accident are monitored in real time, and the on-site data is transmitted to an emergency system of a command center for real-time dynamic display by utilizing a network communication technology.
The systems can work independently, and can also work cooperatively through data transmission among different technical modules, so that dynamic feedback correction of data flow of pollution emission-mode prediction-on-site monitoring is formed, and important support is provided for dynamic emergency early warning and decision of sudden air pollution accidents.
Claims (6)
1. The method for dynamically and emergently warning, evaluating and supporting decision of the emergency system for sudden air pollution accidents is characterized in that the adopted emergency system comprises the following steps: the system comprises a sudden accident capturing and identifying module, a basic information management module, a simulation prediction and health risk assessment module, an optimization monitoring point distribution module, a field comprehensive monitoring module, a source intensity dynamic updating feedback module, and an expert consultation module, wherein the sudden accident capturing and identifying module, the basic information management module, the simulation prediction and health risk assessment module, the optimization monitoring point distribution module, the field comprehensive monitoring module, the source intensity dynamic updating feedback module and the expert consultation module are connected to the same network platform, and meanwhile, the source intensity dynamic updating feedback module can directly utilize the monitoring data of the field comprehensive monitoring module to carry out source intensity inversion updating and automatically feed information back to the simulation prediction and health risk assessment module; the emergency system is a dynamic emergency early warning evaluation and decision support system for sudden air pollution accidents based on multi-technology fusion;
the method comprises the following steps:
(1) Sudden accident catching and identifying method
After the sudden air pollution accident occurs, emergency personnel input and record the basic information of the sudden accident according to the alarm receiving information; the emergency personnel receives the accident alarming telephone, inputs and records the basic information of the accident according to the information provided by the alarming personnel, and starts an emergency system; meanwhile, immediately notifying a department leader, and enabling related emergency personnel to rush to the scene;
the incident basic information input content mainly comprises: the method comprises the steps of a, a related business name, accident occurrence time, a toxic name, an information source, an alarm person, a contact mode, an alarm receiving person and alarm receiving time;
(2) Automatic retrieval of underlying database information
Inquiring basic database information according to the accident alarm receiving information and calling information about the displayed accident; inquiring and supplementing basic database information according to the accident alarm receiving information and calling information about the displayed accident;
the method also comprises the steps of further supplementing and subdividing the basic information base, and specifically comprises the following steps: 1): the risk source basic information database comprises risk source enterprise names, positions, responsible persons, contact ways and emergency resource information; 2) Geographic information database, including surrounding sensitive points, traffic, topography, population density information; 3) An emergency equipment management library, on-site sampling equipment, on-site monitoring equipment, communication lighting and personal protection equipment; 4) The emergency expert information base comprises medical treatment, chemical industry, environment and accident scene rescue expert information; 5) The toxic emergency treatment information base comprises information of related toxic physicochemical properties, influence on environment, environmental standards, on-site and laboratory detection methods and emergency treatment methods; 6) An emergency plan library, government emergency plans, comprehensive emergency plans, special emergency plans and on-site disposal plans;
(3) Simulation prediction and health risk assessment
The method comprises the steps of realizing the normalized operation of a weather forecast model and the dynamic display of a forecast result; according to accident alarm receiving information, dynamic simulation prediction is carried out on toxic gas pollution diffusion space-time distribution to obtain pollution influence range, and the concentration standard of human acute health effect is combined on the basis; defining a health risk area, generating a dynamic health risk forecasting field and displaying the dynamic health risk forecasting field;
the method comprises the following steps: according to accident alarm receiving information, adopting a weather forecast model to dynamically simulate and predict the space-time distribution of toxic gas pollution diffusion to obtain a pollution influence range, and combining the concentration standard of the human acute health effect on the basis; defining a health risk area, generating a dynamic health risk forecasting field and displaying the dynamic health risk forecasting field;
when emergency personnel arrive at the scene, model prediction and health risk assessment in an emergency system enter a background running state and give out calculation results in a short time, the obtained toxic gas pollution influence range and health risk area division prediction results are displayed in a superposition dynamic manner by adopting a GIS system, and advice and reference are provided for the rapid operation of accident handling command;
(4) Optimizing monitoring distribution point
Based on the diffusion simulation-health risk assessment result and combining with actual emergency monitoring resources and geographic information, obtaining and displaying an optimal monitoring point distribution proposal;
the specific steps in the optimizing monitoring distribution point are as follows:
step 1), primarily judging a distribution range by utilizing a pollution concentration field result of a numerical model meshing;
step 2) determining a poison hazard zone based on a concentration standard of an acute health effect of a human body;
step 3) sorting pollution concentration prediction results according to concentration outside the poison dangerous area;
step 4) according to the concentration sequencing result, screening the grid point positions with the N large values before concentration by taking the number N of monitoring devices which can be actually called in the accident scene as a constraint condition, and taking the grid point positions as suggested monitoring point distribution positions;
step 5) comprehensively evaluating the point distribution scheme by combining the geographic information, and determining a final optimized monitoring point distribution scheme;
(5) In-situ integrated monitoring
According to the optimized point distribution proposal, real-time monitoring data are obtained by utilizing on-line monitoring equipment;
(6) Dynamic update feedback of source strength
The on-site real-time monitoring data and the diffusion model are utilized to dynamically update the accident source intensity, and the source intensity updating result is transmitted and fed back to the diffusion model to dynamically update the pollution prediction result;
the source intensity comprises a pollution source position and a pollution source pollutant release rate, the source intensity dynamic update feedback refers to comparing on-site real-time monitoring data with a diffusion model prediction result, judging whether to perform dynamic update of the accident source intensity, if the source intensity is required to be updated, performing source intensity update calculation by using the monitoring data, and transmitting and feeding back a calculation result to the simulation prediction in the step (3), namely updating the pollution prediction and the risk area division result by using the diffusion model;
the step of dynamically updating the source intensity comprises the following steps:
step 1) utilizing concentration data of site monitoring points, firstly carrying out dynamic update judgment on the source intensity of pollutants, and if the update condition is met; step 2) is executed, and if the condition is not met, no update is executed;
step 2) taking the field concentration data as input into a source intensity inversion model, establishing a minimized objective function, and solving the minimized objective function by using an optimization method, wherein the obtained solution results are the pollution source position and the release rate of pollution source pollutants;
the dynamic update judgment conditions are as follows:
r represents a correlation coefficient, sigma o 、σ p Representing the standard deviation of the actual monitoring concentration value at all the monitoring positions and the standard deviation of the model simulation concentration value at all the positions corresponding to the actual monitoring respectively, C p 、C o Representing the analog concentration and the actual monitoring concentration output by the diffusion model at a certain monitoring point,concentration mean value representing all actual monitoring points, +.>Representing the average value of the simulation concentration output by all diffusion models, and updating when R is more than 0.6;
the source intensity inversion model is in the form of:
i represents field concentration monitoring points, n represents the number of monitoring points, and C p 、C o As above;
the source intensity inversion model solving method is a standard particle swarm optimization algorithm;
(7) Expert consultation
Establishing audio connection between the emergency command center and the accident emergency site by using a network communication technology, and realizing information interaction feedback between the command center and the accident site; the network communication technology is utilized to realize the audio connection between the command center and the expert in the emergency field, and scientific and effective suggestions are provided for the accident scene treatment decision.
2. The method for dynamically and emergently evaluating and supporting decision of emergency system to sudden atmospheric pollution accident according to claim 1, wherein in step (3) the weather forecast model adopts a WRF-CALMET coupling model, pollution diffusion forecast adopts a WRF-CALMET weather forecast field as weather drive, and is coupled with a diffusion model to realize pollution dynamic forecast, and the diffusion model is selected from any one of CALPUFF, AERMOD, gaussian plume model (Gaussian Plume Model) and SLAB diffusion model;
the concentration criteria for acute health effects in humans include: acute exposure guide concentrations (Acute Exposure Guideline Levels, AEGLs); emergency response plan guidance concentration (Emergency Response Planning Guidelines, ERPG); short emergency exposure limit (Temporary Emergency Exposure Limits, tel).
3. The method for dynamic emergency early warning assessment and decision support of an emergency system for sudden air pollution accidents according to claim 1, wherein the following steps (4): and (3) obtaining and displaying an optimal monitoring distribution proposal scheme based on the diffusion simulation-health risk assessment result obtained in the step (3) and by combining with actual emergency monitoring resources and geographic information.
4. The method for dynamic emergency early warning assessment and decision support of sudden atmospheric pollution accidents by an emergency system according to claim 1 is characterized in that when the accident development scale and pollution influence are large, audio connection is required to be quickly established with emergency personnel at the accident scene and related experts in an emergency expert information base automatically called in the step (2), the accident scene, a command center and off-site experts are connected through the emergency system, scientific research and judgment are carried out on the accidents, and finally the command center gives a reasonable disposal command for the accident scene.
5. The method for dynamic emergency early warning evaluation and decision support of the emergency system to the sudden atmospheric pollution accident is characterized in that the sudden accident capturing and recognition of the step (1) corresponds to the sudden accident capturing and recognition module of the setting (1), and the basic database information of the step (2) automatically calls the basic information management module of the corresponding setting (2); the method comprises the steps of setting (3) a simulation prediction and health risk evaluation corresponding module (3), setting (4) an optimization monitoring distribution module (5) a field comprehensive monitoring corresponding module (5) and setting (6) a source intensity dynamic updating feedback module (6) a source intensity dynamic updating feedback corresponding module; step (7), expert consultation correspondingly sets (7) an expert consultation module; all modules are connected to the same network platform, and a multi-technology integrated dynamic emergency early warning evaluation and decision support system for sudden air pollution accidents is established; each module can independently operate, and can also carry out cooperative work through data transmission among different technical modules.
6. The method of claim 1, wherein (1) the accident capturing and identifying module has the functions of (2) a basic information management module and (3) a simulation prediction and health risk assessment module besides the alarm receiving information input function, and further has the functions of model operation parameter input and intelligent starting, so that the automatic operation of the system modules (2) and (3) is realized.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911320897.5A CN111145064B (en) | 2019-12-19 | 2019-12-19 | Dynamic emergency early warning assessment and decision support method and system for sudden air pollution accidents |
| PCT/CN2020/117448 WO2021120765A1 (en) | 2019-12-19 | 2020-09-24 | Dynamic emergency early-warning assessment and decision-making support method and system for sudden atmospheric pollution accident |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911320897.5A CN111145064B (en) | 2019-12-19 | 2019-12-19 | Dynamic emergency early warning assessment and decision support method and system for sudden air pollution accidents |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111145064A CN111145064A (en) | 2020-05-12 |
| CN111145064B true CN111145064B (en) | 2024-03-29 |
Family
ID=70519035
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911320897.5A Active CN111145064B (en) | 2019-12-19 | 2019-12-19 | Dynamic emergency early warning assessment and decision support method and system for sudden air pollution accidents |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN111145064B (en) |
| WO (1) | WO2021120765A1 (en) |
Families Citing this family (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111145064B (en) * | 2019-12-19 | 2024-03-29 | 北京工业大学 | Dynamic emergency early warning assessment and decision support method and system for sudden air pollution accidents |
| CN112462603B (en) * | 2020-10-13 | 2021-11-16 | 中科三清科技有限公司 | Optimal regulation and control method, device, equipment and medium for regional atmosphere heavy pollution emergency |
| CN112733419B (en) * | 2020-11-27 | 2023-10-31 | 北京工业大学 | Method for improving inversion accuracy of sudden atmospheric pollution accident source |
| CN112598392A (en) * | 2020-12-28 | 2021-04-02 | 江苏汇环环保科技有限公司 | Emergency early warning assessment and decision support system for atmospheric environmental pollution accident |
| CN113449918B (en) * | 2021-05-13 | 2023-01-31 | 深圳中兴网信科技有限公司 | Emergency command aid decision-making method and system for sudden major pollution event |
| CN113177731B (en) * | 2021-05-20 | 2022-01-07 | 中山大学 | Water resource decision management system based on intelligent contracts |
| CN113624921B (en) * | 2021-08-04 | 2024-03-29 | 杭州谱育科技发展有限公司 | Multi-mode comprehensive pollution tracing method |
| CN113990043A (en) * | 2021-10-19 | 2022-01-28 | 北京伟瑞迪科技有限公司 | Atmospheric pollution monitoring alarm system, method, electronic equipment and storage medium |
| CN114155129B (en) * | 2021-11-29 | 2023-08-29 | 中科三清科技有限公司 | Atmospheric environment tracing and evaluating method and system based on industrial park |
| CN114266404B (en) * | 2021-12-24 | 2023-07-14 | 江苏省环境科学研究院 | Chemical industry garden place pollution early warning system |
| CN114819517A (en) * | 2022-03-30 | 2022-07-29 | 国网福建省电力有限公司 | 365-quantity cheap intelligent supervision platform and early warning method for collaborative professional supervision |
| CN115062990B (en) * | 2022-06-27 | 2023-10-20 | 清云智通(北京)科技有限公司 | Industrial park emergency management coping method, device and system |
| CN117196309A (en) * | 2023-09-15 | 2023-12-08 | 中国疾病预防控制中心环境与健康相关产品安全所 | Public winter chill health risk full-stage grading early warning management system and method |
| CN117057590B (en) * | 2023-10-11 | 2024-02-02 | 国网山东省电力公司博兴县供电公司 | Power grid overhaul management system and method |
| CN117310101A (en) * | 2023-10-31 | 2023-12-29 | 湖北凌创环保有限公司 | Atmospheric pollutant concentration monitoring system |
| CN117953995A (en) * | 2024-01-25 | 2024-04-30 | 北京争上游科技有限公司 | Intelligent Internet of things air quality monitoring system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102567808A (en) * | 2010-12-31 | 2012-07-11 | 北京工业大学 | Method for forecasting and warning accident consequence of major hazard installation by combining with real-time meteorological information |
| CN103984310A (en) * | 2014-05-12 | 2014-08-13 | 华迪计算机集团有限公司 | Chemical industry park environment pollution detection method and device based on multi-source remote sensing data |
| CN104280789A (en) * | 2014-10-29 | 2015-01-14 | 清华大学 | Locating method, locating device, treatment device and system for chemical leakage source |
| CN104573978A (en) * | 2015-01-23 | 2015-04-29 | 长江勘测规划设计研究有限责任公司 | Emergency disposal decision support system for sudden water contamination accident |
| CN110084418A (en) * | 2019-04-21 | 2019-08-02 | 北京工业大学 | A kind of monitoring point optimization distribution method of burst atmosphere pollution accident emergency monitoring |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102456091A (en) * | 2010-10-15 | 2012-05-16 | 中国石油化工股份有限公司 | Emergency system for atmospheric environmental risks |
| US8655806B2 (en) * | 2010-12-09 | 2014-02-18 | Sungeun JUNG | Disaster analysis and decision system |
| CN111145064B (en) * | 2019-12-19 | 2024-03-29 | 北京工业大学 | Dynamic emergency early warning assessment and decision support method and system for sudden air pollution accidents |
-
2019
- 2019-12-19 CN CN201911320897.5A patent/CN111145064B/en active Active
-
2020
- 2020-09-24 WO PCT/CN2020/117448 patent/WO2021120765A1/en active Application Filing
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102567808A (en) * | 2010-12-31 | 2012-07-11 | 北京工业大学 | Method for forecasting and warning accident consequence of major hazard installation by combining with real-time meteorological information |
| CN103984310A (en) * | 2014-05-12 | 2014-08-13 | 华迪计算机集团有限公司 | Chemical industry park environment pollution detection method and device based on multi-source remote sensing data |
| CN104280789A (en) * | 2014-10-29 | 2015-01-14 | 清华大学 | Locating method, locating device, treatment device and system for chemical leakage source |
| CN104573978A (en) * | 2015-01-23 | 2015-04-29 | 长江勘测规划设计研究有限责任公司 | Emergency disposal decision support system for sudden water contamination accident |
| CN110084418A (en) * | 2019-04-21 | 2019-08-02 | 北京工业大学 | A kind of monitoring point optimization distribution method of burst atmosphere pollution accident emergency monitoring |
Non-Patent Citations (1)
| Title |
|---|
| 栗小东 等.突发大气污染事故辅助决策系统设计探讨.上海环境科学.2018,(第6期),正文第1-3节. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111145064A (en) | 2020-05-12 |
| WO2021120765A1 (en) | 2021-06-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111145064B (en) | Dynamic emergency early warning assessment and decision support method and system for sudden air pollution accidents | |
| CN112530119B (en) | Forest fire emergency drilling evaluation and analysis system and method and computer equipment | |
| Xiaojun et al. | IOT-based air pollution monitoring and forecasting system | |
| Zhao et al. | Reprint of: Regional risk assessment for urban major hazards based on GIS geoprocessing to improve public safety | |
| CN108490889B (en) | The safe big data data source method for generation of intelligent plant and device based on TE model | |
| CN106991633A (en) | The computer simulation system and emulation mode of a kind of public safety emergency management | |
| CN114155129B (en) | Atmospheric environment tracing and evaluating method and system based on industrial park | |
| CN111489006A (en) | Fire development situation prediction method and device and computer-readable storage medium | |
| CN109543919A (en) | A kind of fire-fighting dynamic Decision System of Emergency and its implementation to be developed based on accident | |
| CN113313387B (en) | Intelligent management and control method and system for major security risk classification of enterprise | |
| CN113706355A (en) | Method for building intelligent emergency system of chemical industry park | |
| CN114723133A (en) | City emergency early warning and evacuation command method and system under emergency | |
| CN113554318A (en) | Three-dimensional visual risk intelligent management and control integrated system and method for chemical industry park | |
| CN102456091A (en) | Emergency system for atmospheric environmental risks | |
| CN107392459A (en) | A kind of emergency preplan generation method, apparatus and system | |
| CN101582192A (en) | Establishing method of water body environment early warning system | |
| CN112598392A (en) | Emergency early warning assessment and decision support system for atmospheric environmental pollution accident | |
| CN110490361A (en) | The digital emergency planning system and its design method of urban distribution network contingency management | |
| CN114943428A (en) | Emergency comprehensive management system for safety production of hazardous chemical substances | |
| Riebau et al. | The new smoke management | |
| CN114841660A (en) | Enterprise intelligent safety management and control cloud platform based on field information | |
| CN114118847A (en) | Chemical industry park danger source on-line monitoring platform | |
| Ghasemi et al. | Simulation of fire stations resources considering the downtime of machines: A case study | |
| CN111932100A (en) | Urban public safety emergency rescue platform | |
| Jiang et al. | Emergency response for tackling major accidental toxic gas releases: What should be done and when? |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |