CN111145064A - Dynamic emergency early warning assessment and decision support method and system for sudden atmospheric pollution accident - Google Patents
Dynamic emergency early warning assessment and decision support method and system for sudden atmospheric pollution accident Download PDFInfo
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Abstract
A dynamic emergency early warning assessment and decision support method and system for sudden atmospheric pollution accidents belong to the field of sudden atmospheric pollution emergency early warning assessment and emergency decision. The method comprises the following steps: (1) capturing and identifying sudden accidents; (2) the decision supports basic data information query and retrieval; (3) simulating prediction and health risk assessment; (4) optimizing monitoring distribution points; (5) on-site integrated monitoring (weather, pollutants); (6) source strength dynamic update feedback; (7) the experts consult. 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 firstly provides a key emergency technical process frame of 'source intensity-simulation-monitoring distribution', realizes mutual feedback correction of data streams of pollution emission-simulation-monitoring, and can systematically solve the problems of dynamic change of source intensity of sudden accidents, rapid early warning and updating of micro-scale pollution, emergency optimization monitoring and point selection and the like.
Description
Technical Field
The invention belongs to the field of emergent early warning evaluation and emergent decision support for sudden atmospheric pollution accidents, and relates to a method for the emergent early warning evaluation and decision support for sudden atmospheric pollution accidents.
Background
With the rapid development of economy in China, sudden air pollution accidents (explosion, fire, leakage, stink and the like) caused by various production and living activities are increased rapidly, and because a large amount of toxic and harmful pollutants are discharged suddenly in a short time, the discharge rule is changed dynamically, the pollution degree is difficult to control, and the method has great threat to human health, ecological environment and economic development. The rapid and accurate early warning and emergency assessment and disposal for the research of the sudden accident have important significance for improving the emergency scientificity and effectiveness of the sudden atmospheric pollution accident and reducing the harm to human health and the economic loss.
At present, some researches are carried out at home and abroad aiming at emergency systems of sudden accidents, such as an ALOHA early warning system recommended by the United states environmental protection agency, a GASTRAR system developed by Cambridge environmental research and 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 atmospheric pollution monitoring and prediction integrated mobile platform in China. In general, some results have been obtained in the research, but most of the above emergency systems only focus on one aspect of the emergency process. The handling of accidents such as Tianjin explosion and the like shows that the conventional system is lack of effective integration of multiple technologies, and an emergency early warning and evaluation method of linkage coupling of emission-monitoring-simulation-emergency handling is lacked, so that rapid and dynamic early warning and evaluation of sudden accidents are not realized.
Disclosure of Invention
The invention aims to solve the problems of pollution emission, monitoring, simulation, dynamic update and feedback of emergency disposal information and the like in the process of real emergency management and disposal aiming at emergency requirements of emergency accidents, and provides a set of dynamic emergency early warning assessment and decision support method and system, thereby realizing rapid and dynamic early warning assessment of the emergency accidents and providing more scientific and perfect technical support for emergency decision.
To solve the technical problems, the technical scheme adopted by the invention is as follows:
a dynamic emergency early warning assessment and decision support method for sudden atmospheric pollution accidents comprises the following steps:
(1) sudden accident capturing and identifying method
After the sudden air pollution accident occurs, emergency personnel input and record basic information of the sudden accident according to alarm receiving information;
(2) automatic retrieval of base database information
Inquiring basic database information according to the accident alarm receiving information and calling and displaying accident related information data;
(3) simulation prediction and health risk assessment
Realizing the normalized operation of the meteorological forecasting model and the dynamic display of the forecasting result; according to the accident alarm receiving information, dynamically simulating and predicting the time-space 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;
(4) optimized monitoring stationing
Obtaining and displaying an optimized monitoring stationing suggestion scheme based on a diffusion simulation-health risk assessment result and in combination with actual emergency monitoring resources and geographic information (surrounding sensitive points, traffic, population density, terrain, rivers and the like);
(5) on-site integrated monitoring
Obtaining real-time monitoring data by using on-line monitoring equipment according to an optimized stationing suggestion scheme;
(6) source-intensive dynamic update feedback
Carrying out dynamic update of accident source intensity by utilizing the on-site real-time monitoring data and the diffusion model, and transmitting and feeding back a source intensity update result to the diffusion model to carry out dynamic update of a pollution prediction result;
(7) expert consultation
The audio connection between the emergency command center and the accident emergency site is established by utilizing a network communication technology, so that the information interaction feedback between the command center and the accident site is realized; the network communication technology is utilized to realize audio connection between the command center and experts in the emergency field, and scientific and effective suggestions are provided for accident site disposal decisions.
A dynamic emergency early warning assessment and decision support system for sudden atmospheric pollution accidents is characterized in that an emergency technical support module developed by applying the steps of the method comprises a sudden accident capturing and identifying module (1), a basic information management module (2), a simulation prediction and health risk assessment module (3), an optimized monitoring and point placement module (4), a field comprehensive monitoring module (5), a source intensity dynamic updating feedback module (6) and an expert consultation module (7), wherein the source intensity dynamic updating feedback module and the expert consultation module are all connected into the same network platform, and the dynamic emergency early warning assessment and decision support system for sudden atmospheric pollution accidents based on multi-technology fusion is established. Each system can operate independently, and can also carry out cooperative work through data transmission among different technical modules.
The dynamic emergency early warning evaluation and decision support method and system for the sudden atmospheric pollution accident, provided by the invention, are based on actual emergency requirements, are integrated with a basic information data system, a prediction simulation system, an emergency distribution system, an on-site comprehensive monitoring system and a traceability system in a coupling mode to construct a dynamic emergency early warning evaluation and decision support system, and the system covers the functions of automatic database information acquisition, dynamic prediction of future accident pollution development situation, real-time comprehensive monitoring of an accident site and interactive feedback of information between a command center and the accident site, and can realize rapid and scientific emergency early warning evaluation and decision support for the sudden atmospheric pollution accident.
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FIG. 1 is a schematic flow chart of a dynamic emergency early warning evaluation and decision support system structure and a main using method for sudden atmospheric pollution accidents according to the present invention;
Detailed Description
The invention is further explained by combining the main handling process of the sudden accident based on the case hypothesis situation of the sudden accident:
assuming that a certain chemical enterprise has toxic gas leakage accidents, the dynamic emergency early warning and decision support method for sudden accidents provided by the invention is adopted to carry out emergency response, and the system is used for operation, and the specific steps are as follows:
(1) sudden accident capture
Emergency personnel receive the accident alarm call, input and record basic information of the emergency accident according to the information provided by the alarm personnel, and start an emergency system; meanwhile, immediately informing a department leader to rush to a site by related emergency personnel;
the basic information input content of the emergency mainly comprises the following steps: the name of the enterprise involved in the accident, the accident occurrence time, the name of the poisonous substance, the information source, the alarm person and the contact way, the alarm receiving person and the alarm receiving time.
(2) Basic data information query invocation
Inquiring information of a supplementary basic database according to the accident alarm receiving information and calling and displaying accident related information data;
the further supplement and subdivision of the basic information base specifically comprise: risk source basic information database (including information such as enterprise names, positions, responsible persons, contact ways and emergency resources), geographic information database (including information such as peripheral sensitive points, traffic, terrain, population density and the like), emergency equipment management database (field sampling equipment, field monitoring equipment, communication lighting, personal protection equipment and the like), emergency expert information database (including expert information in the aspects of medical treatment, chemical engineering, environment, accident scene rescue and the like), toxic emergency disposal information database (including information such as related toxic physicochemical properties, influences on the environment, environmental standards, scene and laboratory detection methods, emergency treatment disposal methods and the like), emergency plan database (government emergency plans, comprehensive emergency plans, special emergency plans and scene disposal plans).
Risk source information of related enterprises, emergency plans, peripheral sensitive point information and poisonous emergency disposal information.
The emergency system automatically retrieves and calls accident related information data at least comprising information of affair-related enterprises, information of physicochemical properties and disposal methods of poisons, information of sensitive points around accidents, information of emergency experts, information of accident emergency plans and the like according to accident information input by emergency personnel, and provides preliminary information support for leaders in emergency departments to command decisions.
(3) Simulation prediction and health risk assessment
Realizing the normalized operation of the meteorological forecasting model and predicting the dynamic diffusion result;
according to the accident alarm receiving information, a weather forecast model is adopted to carry out space-time distribution dynamic simulation prediction on toxic gas pollution diffusion, a pollution influence range is obtained, and on the basis, the concentration standard of the human body acute health effect is combined; defining a health risk area, generating a dynamic health risk forecasting field and displaying the dynamic health risk forecasting field;
when an emergency worker arrives at the site, model prediction and health risk assessment in the emergency system enter a background operation state and give a calculation result in a short time, the obtained toxic gas pollution influence range and health risk area division prediction results are displayed dynamically in a superposition mode by a GIS (geographic information system) system, and suggestions and references are provided for rapid accident handling and commanding work;
the weather forecasting Model adopts a WRF-CALMET coupling Model, the pollution diffusion forecasting adopts a WRF-CALMET weather forecasting field as weather drive, the WRF-CALMET weather forecasting field is coupled with a diffusion Model, and the dynamic pollution forecasting is realized, and the diffusion Model is selected from any one of CALPUFF, AERMOD, Gaussian Plume Model (Gaussian Plume Model) and SLAB diffusion Model.
The human acute health effect concentration standard comprises: acute exposure guidance concentrations (Acute ExposureGuideline Levels, AEGLs); emergency Response program guidelines concentrations (Emergency Response plantanningguidelines, ERPG); short Time Emergency Exposure Limits (TEEL).
(4) Emergency monitoring point location optimization
After the pollution prediction result is obtained, emergency system operators transfer emergency monitoring resources, peripheral sensitive points, health risk assessment results and geographic information according to actual site, an optimized stationing technical module is used for calculating to obtain an optimized stationing suggestion scheme, and commanders are helped to make quick decisions in the aspect of monitoring point location selection;
obtaining and displaying an optimized monitoring stationing suggestion scheme based on the diffusion simulation-health risk assessment result obtained in the step (3) and in combination with actual emergency monitoring resources and geographic information (surrounding sensitive points, traffic, population density, terrain, rivers and the like);
the optimization monitoring stationing method comprises the following specific steps:
step 1) preliminarily judging a point distribution range by using a numerical model gridded pollution concentration field result;
step 2) determining a poison danger area based on the concentration standard of the acute health effect of the human body;
step 3) sorting the prediction results of the pollution concentration according to the concentration outside the toxic hazard area;
step 4) according to the concentration sorting result, taking the number N of monitoring equipment which can be actually called in an accident site as a constraint condition, and screening the grid point position with the N large values before concentration as a suggested monitoring point distribution position;
and 5) comprehensively evaluating the stationing scheme by combining geographic information (surrounding sensitive points, traffic, population density, terrain, rivers and the like) to determine a final optimized monitoring stationing scheme.
(5) On-site comprehensive observation
Obtaining real-time monitoring data by using on-line monitoring equipment according to an optimized stationing suggestion scheme;
the field comprehensive monitoring comprises the following steps: and acquiring qualitative and quantitative real-time data of wind direction and wind speed and pollutants of the accident site by using on-line monitoring equipment.
(6) Source-intensive dynamic update feedback
Comparing the on-site real-time monitoring data with the diffusion model prediction result to judge whether to perform dynamic updating of accident source intensity, if the source intensity is required to be updated, performing source intensity updating calculation by using the monitoring data, and transmitting and feeding back the calculation result to the simulation prediction of the step (3), namely updating the pollution prediction and risk area division result of the diffusion model;
the source intensity dynamic updating step comprises the following steps:
step 1) utilizing concentration data of site monitoring point positions, firstly, dynamically updating and judging the source intensity of pollutants, and if the concentration data meets the updating condition; executing the step 2), if the condition is not met, not executing the updating;
step 2) taking 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 result is the position of the pollution source and the release rate of pollutants of the pollution source;
the dynamic update judgment condition is as follows:
r represents a correlation coefficient, σo、σpRespectively representing the standard deviation of the actually monitored concentration values at all the monitored positions and the standard deviation of the model simulated concentration values at all the positions corresponding to the actual monitoring, Cp、CoRepresenting the simulated concentration and the actual monitored concentration output by the diffusion model at a certain monitoring point,
represents the average of the concentrations at all the actual monitoring points,
represents the mean value of the simulated concentration of all diffusion model outputs, and is updated when R is greater than 0.6.
The source strength inversion model is in the form of:
i represents the site concentration monitoring points, n represents the number of monitoring points, Cp、CoAs above.
The source intensity inversion solving method is a standard particle swarm optimization algorithm.
(7) Expert consultation
When the accident development scale and the pollution influence are large, audio connection needs to be rapidly established between emergency personnel on the accident site and relevant experts in the emergency expert information base automatically called in the step (2), the accident site, the command center and off-site experts are connected through an emergency system to scientifically study and judge the accident, and finally the command center issues a reasonable disposal command on the accident site.
The emergency capturing and identifying module in the step (1) has the functions of inputting the alarm receiving information, inputting the model operation parameters and intelligently starting two technical modules including a basic information management module (2) and a simulation prediction and health risk assessment module (3), 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 field comprehensive monitoring module in the step (5) to carry out source intensity inversion updating and automatically feed back the information to the simulation prediction and health risk assessment module in the step (3).
Based on the on-line monitoring equipment, real-time monitoring is carried out on meteorological elements and toxic substance concentration of sensitive points around the accident, and the field data is transmitted to an emergency system of a command center by utilizing a network communication technology for real-time dynamic display.
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-field monitoring is formed, and important support is provided for dynamic emergency early warning and decision making of sudden atmospheric pollution accidents.
Claims (10)
1. A dynamic emergency early warning assessment and decision support method for sudden atmospheric pollution accidents is characterized by comprising the following steps:
(1) sudden accident capturing and identifying method
After the sudden air pollution accident occurs, emergency personnel input and record basic information of the sudden accident according to alarm receiving information;
(2) automatic retrieval of base database information
Inquiring basic database information according to the accident alarm receiving information and calling and displaying accident related information data;
(3) simulation prediction and health risk assessment
Realizing the normalized operation of the meteorological forecasting model and the dynamic display of the forecasting result; according to the accident alarm receiving information, dynamically simulating and predicting the time-space 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;
(4) optimized monitoring stationing
Obtaining and displaying an optimized monitoring stationing suggestion scheme based on a diffusion simulation-health risk evaluation result and in combination with actual emergency monitoring resources and geographic information;
(5) on-site integrated monitoring
Obtaining real-time monitoring data by using on-line monitoring equipment according to an optimized stationing suggestion scheme;
(6) source-intensive dynamic update feedback
Carrying out dynamic update of accident source intensity by utilizing the on-site real-time monitoring data and the diffusion model, and transmitting and feeding back a source intensity update result to the diffusion model to carry out dynamic update of a pollution prediction result;
(7) expert consultation
The audio connection between the emergency command center and the accident emergency site is established by utilizing a network communication technology, so that the information interaction feedback between the command center and the accident site is realized; the network communication technology is utilized to realize audio connection between the command center and experts in the emergency field, and scientific and effective suggestions are provided for accident site disposal decisions.
2. The dynamic emergency early warning assessment and decision support method for the sudden atmospheric pollution accident based on multi-technology fusion as claimed in claim 1, wherein, in the step (1), the emergency personnel receives an accident alarm call, inputs and records basic information of the sudden accident according to the information provided by the alarm personnel, and starts an emergency system; meanwhile, immediately informing a department leader to rush to a site by related emergency personnel;
the basic information input content of the emergency mainly comprises the following steps: the name of the enterprise involved in the accident, the accident occurrence time, the name of the poisonous substance, the information source, the alarm person and the contact way, the alarm receiving person and the alarm receiving time.
3. The dynamic emergency early warning assessment and decision support method for sudden atmospheric pollution accidents according to claim 1, characterized in that the step (2) queries information of a supplementary basic database according to accident alarm receiving information and retrieves and displays information data related to accidents;
further supplement and subdivision for the basic information base are also included, and the method specifically comprises the following steps: risk source basic information database (including information such as enterprise names, positions, responsible persons, contact ways and emergency resources), geographic information database (including information such as peripheral sensitive points, traffic, terrain, population density and the like), emergency equipment management database (field sampling equipment, field monitoring equipment, communication lighting, personal protection equipment and the like), emergency expert information database (including expert information in the aspects of medical treatment, chemical engineering, environment, accident scene rescue and the like), toxic emergency disposal information database (including information such as related toxic physicochemical properties, influences on the environment, environmental standards, scene and laboratory detection methods, emergency treatment disposal methods and the like), emergency plan database (government emergency plans, comprehensive emergency plans, special emergency plans and scene disposal plans).
4. The dynamic emergency early warning assessment and decision support method for sudden atmospheric pollution accidents according to claim 1, characterized in that, in the step (3), according to the accident alarm receiving information, a weather forecast model is adopted to perform space-time distribution dynamic simulation prediction on toxic gas pollution diffusion, so as to obtain a pollution influence range, and on the basis, the concentration standard of the human body acute health effect is combined; defining a health risk area, generating a dynamic health risk forecasting field and displaying the dynamic health risk forecasting field;
when an emergency worker arrives at the site, model prediction and health risk assessment in the emergency system enter a background operation state and give a calculation result in a short time, the obtained toxic gas pollution influence range and health risk area division prediction results are displayed dynamically in a superposition mode by a GIS (geographic information system) system, and suggestions and references are provided for rapid accident handling and commanding work;
the weather forecasting Model adopts a WRF-CALMET coupling Model, the pollution diffusion forecasting adopts a WRF-CALMET weather forecasting field as weather drive, the WRF-CALMET weather forecasting field is coupled with a diffusion Model, and the pollution dynamic prediction is realized, wherein the diffusion Model is selected from any one of CALPUFF, AERMOD, Gaussian Plume Model (Gaussian Plume Model) and SLAB diffusion Model;
the human acute health effect concentration standard comprises: acute Exposure guidance concentrations (Acute Exposure guidelines, AEGLs); emergency Response plan guidance concentration (ERPG); short Time Emergency Exposure Limits (TEEL).
5. The method for dynamic emergency early warning assessment and decision support for sudden atmospheric pollution accidents according to claim 1, wherein the emergency monitoring point location optimization in the step (4): after the pollution prediction result is obtained, emergency system operators transfer emergency monitoring resources, peripheral sensitive points, health risk assessment results and geographic information according to actual site, an optimized stationing technical module is used for calculating to obtain an optimized stationing suggestion scheme, and commanders are helped to make quick decisions in the aspect of monitoring point location selection;
and (4) obtaining and displaying an optimized monitoring stationing suggestion scheme based on the diffusion simulation-health risk assessment result obtained in the step (3) and in combination with actual emergency monitoring resources and geographic information.
6. The dynamic emergency early warning assessment and decision support method for sudden atmospheric pollution accidents according to claim 1, characterized in that the optimization monitoring stationing in the step (4) comprises the following specific steps:
step 1) preliminarily judging a point distribution range by using a numerical model gridded pollution concentration field result;
step 2) determining a poison danger area based on the concentration standard of the acute health effect of the human body;
step 3) sorting the prediction results of the pollution concentration according to the concentration outside the toxic hazard area;
step 4) according to the concentration sorting result, taking the number N of monitoring equipment which can be actually called in an accident site as a constraint condition, and screening the grid point position with the N large values before concentration as a suggested monitoring point distribution position;
and 5) comprehensively evaluating the stationing scheme by combining the geographic information to determine the final optimized monitoring stationing scheme.
7. The method for dynamic emergency early warning assessment and decision support of sudden atmospheric pollution accident according to claim 1, wherein the source strength in step (6) includes the source position of the pollution source and the pollutant release rate of the pollution source, the source strength dynamic update feedback means that whether dynamic update of the accident source strength is performed is judged by comparing the on-site real-time monitoring data with the diffusion model prediction result, if the source strength update is required, the source strength update calculation is performed by using the monitoring data, and the calculation result is transmitted and fed back to the simulation prediction, i.e. the diffusion model in step (3) to perform the update of the pollution prediction and the risk area division result;
the source intensity dynamic updating step comprises the following steps:
step 1) utilizing concentration data of site monitoring point positions, firstly, dynamically updating and judging the source intensity of pollutants, and if the concentration data meets the updating condition; executing the step 2), if the condition is not met, not executing the updating;
step 2) taking 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 result is the position of the pollution source and the release rate of pollutants of the pollution source;
the dynamic update judgment condition is as follows:
r represents a correlation coefficient, σo、σpRespectively representing the standard deviation of the actually monitored concentration values at all the monitored positions and the standard deviation of the model simulated concentration values at all the positions corresponding to the actual monitoring, Cp、CoRepresenting the simulated concentration and the actual monitored concentration output by the diffusion model at a certain monitoring point,
represents the average of the concentrations at all the actual monitoring points,
representing the average value of the simulated concentration output by all the diffusion models, and updating when R is more than 0.6;
the source strength inversion model is in the form of:
i represents the site concentration monitoring points, n represents the number of monitoring points, Cp、CoThe same as above;
the source intensity inversion model solving method is a standard particle swarm optimization algorithm.
8. The dynamic emergency early warning assessment and decision support method for sudden atmospheric pollution accidents according to claim 1, characterized in that when the scale of the accident development and the pollution influence are large, audio connection is required to be rapidly established with emergency personnel at the accident site and related experts in the emergency expert information base automatically retrieved in the step (2), the accident site, a command center and off-site experts are connected through an emergency system to scientifically study and judge the accident, and finally the command center issues a reasonable handling command for the accident site.
9. The system corresponding to the sudden atmospheric pollution accident dynamic emergency early warning assessment and decision support method according to claim 1, is characterized in that the sudden accident capturing and identifying of step (1) corresponds to the setting of the sudden accident capturing and identifying module, and the basic database information automatic calling of step (2) corresponds to the setting of step (2) corresponds to the automatic calling of basic database information; step (3) simulation prediction and health risk assessment are correspondingly set, step (4) an optimized monitoring point distribution module is correspondingly set, step (5) a field comprehensive monitoring data module is correspondingly set, step (6) a source intensity dynamic updating feedback module is correspondingly set, and step (6) a source intensity dynamic updating feedback module is correspondingly set; step (7) the expert consultation is correspondingly provided with (7) an expert consultation module; all modules are connected to the same network platform, and a multi-technology fused dynamic emergency early warning evaluation and decision support system for sudden atmospheric pollution accidents is established; each module can independently operate and can also carry out cooperative work through data transmission among modules with different technologies.
10. The system according to claim 9, characterized in that (1) the emergency capturing and identifying module has functions of inputting model operation parameters and intelligently starting two technical modules including (2) a basic information management module and (3) a simulation prediction and health risk assessment module besides the function of inputting alarm receiving information, so as to realize the automatic operation of the system modules (2) and (3);
(6) the source intensity dynamic updating feedback module can directly utilize the monitoring data of the field comprehensive monitoring module in the step (5) to carry out source intensity inversion updating and automatically feed back the information to the simulation prediction and health risk assessment module in the step (3).
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