CN114693166A - Method and device for monitoring execution condition of emergency emission reduction measure on line and electronic equipment - Google Patents
Method and device for monitoring execution condition of emergency emission reduction measure on line and electronic equipment Download PDFInfo
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Abstract
The invention provides a method, a device and electronic equipment for online monitoring of execution conditions of emergency emission reduction measures, wherein the method comprises the following steps: acquiring and analyzing emergency emission reduction list data to obtain a production limit enterprise and a production limit production line or a working procedure thereof in a target area; determining a discharge monitoring point corresponding to a production limit line or a process according to the incidence relation between the production line or the process and the discharge monitoring point; for each emission monitoring point: acquiring historical monitoring emission amount of a plurality of days when an emission monitoring point does not start early warning; determining the daily average value of the historical monitoring discharge amount as a reference value of a discharge monitoring point; acquiring the online monitoring discharge amount of a discharge monitoring point on a target date; judging whether the online monitoring discharge is lower than a reference value or not; if not, determining that the corresponding production limit line or working procedure does not execute emission reduction measures; and outputting a detection result. By the method and the system, the limited production enterprises which do not execute the emission reduction measures can be determined from a large number of enterprises, and the limited production lines or processes which do not execute the emission reduction measures can be refined.
Description
Technical Field
The invention relates to the technical field of execution monitoring of emergency emission reduction measures, in particular to a method and a device for monitoring execution conditions of the emergency emission reduction measures on line and electronic equipment.
Background
With the advent of the big data age, more and more enterprises have installed automatic atmospheric pollutant monitoring equipment and electricity consumption monitoring equipment, are networked and can upload the equipment to an environment management platform. In order to guarantee the air quality of a city, when early warning of different degrees is started, the implementation situation of emission reduction measures of industrial enterprises needs to be concerned.
In the related technology, when different levels of early warning are started in a city, in order to determine the implementation situation of emission reduction measures of enterprises, the enterprises are divided into production stopping enterprises and production limiting enterprises according to the production situation of the enterprises. For a production stopping enterprise, comparison and check are generally performed through enterprise online data, for example, whether the enterprise is in production stopping or not can be checked through enterprise power consumption monitoring data or enterprise online emission data. For a limited-production enterprise, a common method is to go to the enterprise for field inspection, and due to the fact that the number of enterprises is large, early warning is short, time and labor cost are high, the early warning time is sometimes over, and the enterprise with early warning measures which are not implemented is not found yet.
Disclosure of Invention
According to an aspect of the invention, a method for online monitoring of execution conditions of emergency emission reduction measures is provided, which is applied to electronic equipment and comprises the following steps:
acquiring emergency emission reduction list data;
analyzing the emergency emission reduction list data to obtain a production limit enterprise and a production limit production line or a working procedure thereof in the target area;
determining emission monitoring points corresponding to the production limiting line or the working procedure according to the association relationship between the production line or the working procedure and the emission monitoring points, wherein each emission monitoring point is configured to monitor the emission amount of atmospheric pollutants of the associated production line or the working procedure;
for each emission monitoring point:
acquiring historical monitoring emission amount of a plurality of days when an emission monitoring point does not start early warning;
determining the daily average value of historical monitoring emission of multiple days, and taking the daily average value as a reference value of an emission monitoring point;
acquiring online monitoring emission of an emission monitoring point on a target date, wherein the target date belongs to an early warning period;
judging whether the online monitoring discharge amount of the discharge monitoring point is lower than a reference value; and
if the online monitoring emission amount of the emission monitoring point is not less than the reference value, determining that the production limit line or the working procedure corresponding to the emission monitoring point does not execute emission reduction measures; and
and outputting the limited production enterprises of which the target dates do not execute the emission reduction measures in the target area and the limited production lines or processes of which the target dates do not execute the emission reduction measures.
In some possible embodiments, obtaining the online monitored emission amount of the emission monitoring point on the target date comprises:
acquiring online monitoring data of a target date in a target area, wherein the online monitoring data comprises enterprise information in the target area, emission monitoring point information related to the enterprise information and online monitoring emission of the emission monitoring point information in the target date;
determining second enterprise information of the production-limited enterprise in the online monitoring data according to first enterprise information of the production-limited enterprise in the emergency emission reduction list data;
determining second emission monitoring point information of the emission monitoring points in the online monitoring data according to the second enterprise information and the first emission monitoring point information of the emission monitoring points in the emergency emission reduction list data;
and acquiring the online monitoring emission corresponding to the second emission monitoring point information as the online monitoring emission of the emission monitoring point.
In some possible embodiments, the method further comprises:
for each emission monitoring point: if the online discharge amount of the discharge monitoring point is not lower than the reference value, determining the increase amount of the online discharge amount of the discharge monitoring point relative to the reference value;
and for all emission monitoring points, sequencing the production limit enterprises which do not execute emission reduction measures and the production limit lines or processes which do not execute the emission reduction measures according to the increasing amounts corresponding to the monitoring points.
In some possible embodiments, obtaining historical monitored emissions for a plurality of days when the emissions monitoring point did not initiate the warning includes: and taking the target date as a starting point, and acquiring historical monitoring discharge of preset days when the discharge monitoring point does not start early warning before the target date.
In some possible embodiments, the production-limited enterprises which do not execute emission reduction measures on the target date in the target area and the production-limited enterprises or processes which do not execute emission reduction measures are output in a list form according to the sorting result.
According to another aspect of the invention, there is provided an apparatus for online monitoring of emergency emission reduction measure execution, comprising:
the acquisition module is used for acquiring emergency emission reduction list data;
the analysis module is used for analyzing the emergency emission reduction list data to obtain a production-limiting enterprise and a production-limiting production line or a working procedure thereof in the target area;
the device comprises a first determining module, a second determining module and a monitoring module, wherein the first determining module is used for determining emission monitoring points corresponding to a production limit line or a working procedure according to the incidence relation between the production line or the working procedure and the emission monitoring points, and each emission monitoring point is configured to monitor the emission amount of atmospheric pollutants of the associated production line or the working procedure;
a second determination module to, for each emission monitoring point: acquiring historical monitoring emission amount of a plurality of days when an emission monitoring point does not start early warning; determining the daily average value of historical monitoring emission of multiple days, and taking the daily average value as a reference value of an emission monitoring point; acquiring online monitoring emission of an emission monitoring point on a target date, wherein the target date belongs to an early warning period; judging whether the online monitoring discharge amount of the discharge monitoring point is lower than a reference value; if the online monitoring emission amount of the emission monitoring point is not lower than the reference value, determining that the production line or the process corresponding to the emission monitoring point does not execute emission reduction measures; and
and the output module is used for outputting the limited production enterprises of which the target dates do not execute the emission reduction measures in the target area and the limited production lines or processes of which the target dates do not execute the emission reduction measures.
In some possible embodiments, the second determining module is configured to:
acquiring online monitoring data of the target date in a target area, wherein the online monitoring data comprises enterprise information in the target area, emission monitoring point information related to the enterprise information and online monitoring emission of the emission monitoring point information on the target date;
determining second enterprise information of the production-limited enterprise in the online monitoring data according to first enterprise information of the production-limited enterprise in the emergency emission reduction list data;
determining second emission monitoring point information of the emission monitoring points in the online monitoring data according to the second enterprise information and the first emission monitoring point information of the emission monitoring points in the emergency emission reduction list data;
and acquiring the online monitoring discharge amount corresponding to the second emission monitoring point information as the online monitoring discharge amount of the emission monitoring point.
In some possible embodiments, the second determining module is further configured to:
for each emission monitoring point: if the online discharge amount of the discharge monitoring point is not lower than the reference value, determining the increase amount of the online discharge amount of the discharge monitoring point relative to the reference value;
and for all emission monitoring points, sequencing the limited production enterprises which do not execute emission reduction measures and the limited production lines or processes which do not execute emission reduction measures according to the increasing amounts corresponding to the monitoring points.
According to still another aspect of the present invention, there is provided an electronic apparatus including:
a processor; and
a memory for storing a program, wherein the program is stored in the memory,
wherein the program comprises instructions which, when executed by the processor, cause the processor to perform the method of the invention.
According to yet another aspect of the present invention, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of the present invention.
According to one or more technical schemes provided by the embodiment of the invention, the production-limited enterprises and the production-limited lines or processes thereof in the target area are obtained by analyzing the emergency emission reduction list data, the emission monitoring points corresponding to the production-limited lines or processes are determined according to the association relationship between the production lines or processes and the emission monitoring points, and the execution condition of the emergency emission reduction measures is monitored on line based on the online emission of the emission monitoring points. The method comprises the steps of obtaining historical monitoring discharge amount of a plurality of days when the discharge monitoring point does not start early warning, taking the daily average value of the historical monitoring discharge amount of the plurality of days as the reference value of the discharge monitoring point, and taking the daily average value of the historical monitoring discharge amount as the comparison reference, so that the method is more accurate. And obtaining the online monitoring emission of the emission monitoring point on a target date, judging whether the online monitoring emission of the emission monitoring point is lower than a reference value of the emission monitoring point, and if the online monitoring emission of the emission monitoring point is not lower than the reference value, indicating that the corresponding production line or working procedure does not execute emission reduction measures, so that the production line or working procedure limited by the emission monitoring point is determined not to execute the emission reduction measures. And outputting the limited production enterprises of which the target dates do not execute the emission reduction measures in the target area and the limited production lines or processes of which the target dates do not execute the emission reduction measures. Therefore, the limited production enterprises which do not execute the emission reduction measures can be determined from a large number of enterprises, the enterprises can be checked on site, and the limited production lines or processes which do not execute the emission reduction measures can be refined.
Drawings
Further details, features and advantages of the invention are disclosed in the following description of exemplary embodiments with reference to the accompanying drawings, in which:
FIG. 1 illustrates a flow chart of a method for online monitoring of emergency emission reduction measure performance in accordance with an exemplary embodiment of the present invention;
FIG. 2 shows a schematic block diagram of an apparatus for online monitoring of emergency emission abatement measure performance in accordance with an exemplary embodiment of the present invention;
FIG. 3 illustrates a block diagram of an exemplary electronic device that can be used to implement an embodiment of the invention.
Detailed Description
Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and the embodiments of the present invention are illustrative only and are not intended to limit the scope of the present invention.
It should be understood that the various steps recited in the method embodiments of the present invention may be performed in a different order and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the invention is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description. It should be noted that the terms "first", "second", and the like in the present invention are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in the present invention are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that reference to "one or more" unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present invention are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
Compared with on-site inspection, online automatic monitoring is beneficial to reducing the time cost and the labor cost for determining the implementation situation of the enterprise emission reduction measures. For a production-stopping enterprise, the online emission amount is almost zero, so whether the enterprise is stopped to meet the emission reduction measures can be determined based on whether the online emission amount of the enterprise during the early warning period is zero or not.
However, for a production-limited enterprise, emission reduction measures are set in the emergency emission reduction list, correspond to a production line or a working procedure, and are explicitly detailed to the working procedure, equipment and the like, for example, a continuous rolling production line stops 1 heating furnace, a wire rod stops one heating furnace and the like, instead of setting a target emission reduction amount. Therefore, the implementation situation of emission reduction measures of the production stopping enterprises cannot be determined based on whether the online emission amount during early warning reaches the target emission reduction amount or not. In addition, in the online monitoring data of the enterprise, whether the equipment is stopped in the production line/process is not monitored online by taking the emission monitoring point as a reference, so that online monitoring cannot be performed based on whether the equipment is stopped.
Meanwhile, different production lines/processes and different early warning levels of different enterprises have different emission reduction measures, the production lines/processes of each enterprise are automatically and finely judged, if detection is carried out based on whether the online emission reaches the target emission reduction amount, judgment rules need to be set for each production line/process and each early warning level of each enterprise, emission reduction measures and emission data of the enterprises are constantly changed, and therefore the judgment rules need to be constantly modified, and the problems of high time cost and high labor cost exist.
Therefore, no feasible solution is provided at present how to realize online monitoring of the execution situation of the emergency emission reduction measures.
The embodiment of the invention provides a method for monitoring the execution condition of an emergency emission reduction measure on line, which is used for monitoring the execution condition of the emergency emission reduction measure on line. The method can quickly process the implementation situation of enterprise emission reduction measures in special periods (such as the period of important activity guarantee) in batches, can be accurate to specific discharge ports and production procedures, greatly saves the cost, further continuously improves the refinement level of environmental management, and reduces the occurrence frequency and the pollution degree of heavily polluted weather.
According to the embodiment of the invention, the production-limited enterprises and the production-limited lines or processes thereof in the target area are obtained by analyzing the emergency emission reduction list data, the emission monitoring points corresponding to the production-limited lines or processes are determined according to the incidence relation between the production lines or processes and the emission monitoring points, and the execution condition of the emergency emission reduction measures is monitored on line based on the online emission of the emission monitoring points. The method comprises the steps of obtaining historical monitoring emission of a plurality of days when an emission monitoring point does not start early warning, taking the daily average of the historical monitoring emission of the plurality of days as a reference value of the emission monitoring point, and taking the daily average of the historical monitoring emission as a comparison reference, so that the method is more accurate. And obtaining the online monitoring emission of the emission monitoring point on a target date, judging whether the online monitoring emission of the emission monitoring point is lower than a reference value of the emission monitoring point, and if the online monitoring emission of the emission monitoring point is not lower than the reference value, indicating that the corresponding production line or working procedure does not execute emission reduction measures, so that the production line or working procedure limited by the emission monitoring point is determined not to execute the emission reduction measures. And outputting the limited production enterprises of which the target dates in the target area do not execute the emission reduction measures and the limited production lines or processes of which the target dates do not execute the emission reduction measures. Therefore, the limited production enterprises which do not execute the emission reduction measures can be determined from a large number of enterprises, the enterprises can be checked on site, and the limited production lines or processes which do not execute the emission reduction measures can be refined.
Fig. 1 shows a flowchart of a method for online monitoring of performance of an emergency emission reduction measure according to an exemplary embodiment of the present invention, and as shown in fig. 1, the method includes steps S101 to S105.
And S101, acquiring emergency emission reduction list data.
Typically, the emergency emission reduction inventory data is provided by a user (e.g., an environmental protection department or organization). And configuring production stopping enterprises and production limiting enterprises by the emergency emission reduction list. And configuring a production line or a working procedure of the limited production enterprise.
As an embodiment, the emergency emission reduction inventory data may be a spreadsheet, such as Excel or the like. The present embodiment does not limit the form of the quick-decrease clearance data.
And S102, analyzing the emergency emission reduction list data to obtain the production-limited enterprises and the production-limited production lines or processes thereof in the target area.
The target area may include one or more cities.
As an example, in the emergency emission reduction inventory data, enterprise information, production line or process information associated with the enterprise information, and emission reduction measures corresponding to the production line or process information are configured. The emission reduction measure is described by natural language, for example, a continuous rolling production line stops 1 heating furnace, a wire rod stops one heating furnace and the like, but target emission reduction amount is not set. Since the target reduced displacement amount is not set, it is not possible to determine whether to execute the emission reduction measure based on the comparison of the target reduced displacement amount with the actual emission amount. In addition, since the emission reduction measures are described in natural language, it is difficult to realize automated processing.
As one embodiment, the limited production enterprise may be screened based on one or more conditions, including but not limited to enterprise, regulatory type, and/or industry type, among others. Thus, the data processing amount can be reduced.
When the control type is used as the screening condition, the enterprise corresponding to the control type can be selected from all the enterprises. As an example, the management and control types include a class a enterprise, a class B enterprise, a class C enterprise, a class D enterprise, a performance-guided enterprise, a non-performance-guided enterprise, a long-term production-suspended enterprise, a civil-exempt enterprise, and the like, and each management and control type of enterprise corresponds to a different degree of management and control. For example, an enterprise with a high degree of control may be selected for online monitoring.
In the case of the business type as the filtering condition, the business type of the business may be selected from all the businesses. As an example, industry types include: long run combined steel, short run steel, ferroalloy, coking industry, alumina, electrolytic aluminum, carbon, copper smelting, lead, zinc smelting, recycled copper aluminum lead zinc, cement, brick and tile kilns, ceramics, refractories, glass, rock wool, lime kilns, foundry industry, oil refining and petrochemical industry, coal nitrogen fertilizer, pharmaceutical industry, pesticide manufacturing, paint manufacturing, ink manufacturing, furniture manufacturing, packaging printing, artificial board manufacturing, plastic manufacturing, rubber product manufacturing, industrial coating, and others. For example, one or more industry-type businesses may be selected for online monitoring.
In some possible embodiments, the emergency emissions manifest configures multiple warning levels, with different warning levels corresponding to different emission reduction measures, such as different warning levels limiting emissions for different production lines or processes. In step S102, a corresponding production limit line or process and production limit measure are determined based on the warning level of the target date. As an example, the alert level may include: a yellow warning period, an orange warning period and a red warning period.
And S103, determining emission monitoring points corresponding to the production limit line or the process according to the association relationship between the production line or the process and the emission monitoring points, wherein each emission monitoring point is configured to monitor the emission amount of the atmospheric pollutants of the associated production line or process.
Based on the incidence relation between the production line or the working procedure and the emission monitoring points, the emission monitoring points corresponding to the production line or the working procedure with limited production can be determined, and further, the emission can be monitored on line based on the emission monitoring points, and the execution condition of emission reduction measures executed on the relevant production line or the working procedure with limited production can be monitored on line.
The production line or process may be associated with one or more emission monitoring points, and one emission monitoring point may be associated with one or more production lines or processes, which is not limited in this embodiment.
Generally, in the case of shutdown of a portion of the equipment in a production line or process, such that the capacity of the production line or process is reduced, the amount of atmospheric pollutants emitted from the production line or process is reduced, and the amount of online emissions monitored from at least some of its associated one or more emission monitoring points is reduced.
Generally, in the case that one emission monitoring point is associated with a plurality of production lines or processes, in the case that at least part of the production lines or processes associated with the emission monitoring point shut down part of the equipment, the capacity of the at least part of the production lines or processes is reduced, the emission amount of the atmospheric pollutants of the at least part of the production lines or processes is reduced, and the emission amount of the online monitoring of the emission monitoring point is generally kept unchanged.
The process of step S104 is performed for each emission monitoring point, and as shown in fig. 1, step S104 includes steps S1041 to S1045.
And step S1041, acquiring historical monitoring emission amount of a plurality of days when the emission monitoring point does not start early warning.
Before step S1041, emission data of the atmospheric pollutants of the emission monitoring point is collected, and the emission amount of the emission monitoring point may be determined based on the emission data of the atmospheric pollutants. The atmospheric pollutant emission data may include emission data for one or more pollutants. As one example, emission data may include: and (4) discharging the emission amount, concentration, flow and discharge time of the atmospheric pollutants at the monitoring point. The typical emissions are daily emissions.
In this embodiment, the plurality of days when the warning is not activated may be consecutive days (for example, 15 consecutive days from 1 month and 1 day to 1 month and 15 days), or non-consecutive days (for example, non-consecutive days such as 1 month and 1 day, 1 month and 5 days to 1 month and 10 days). This embodiment does not limit this.
The amount of emissions closer to the target date can represent the actual amount of emissions. In some possible embodiments, the target date is taken as a starting point, and the historical monitoring emission amount of the emission monitoring point for a preset number of days when the early warning is not started before the target date is obtained. As an example, the target date is 4 months and 30 days, the historical monitoring emission amount of 2 weeks when the early warning is not started before 4 months and 30 days can be acquired, and when the early warning is not started during 4 months and 16 days to 29 days, the acquired historical monitoring emission amount can be the monitoring emission amount of 4 months and 16 days to 29 days; and if the early warning is started for one or more days between the days 16 and 29 of 4 months, the monitoring emission of the corresponding days before the day 16 of 4 months can be obtained.
As an example, the daily average monitored emission of half a month in which the warning is not activated is selected as a reference value.
And step S1042, determining the daily average value of historical monitoring emission for multiple days, and taking the daily average value as the reference value of the emission monitoring point.
As one embodiment, the daily average may be a daily arithmetic average, i.e., the sum of the historical monitored emissions per day divided by the number of days. As another example, the daily average may be a weighted average, with emissions closer to the target date corresponding to higher weights.
And step S1043, acquiring the online monitoring emission of the emission monitoring point on a target date, wherein the target date belongs to the early warning period.
In some possible embodiments, obtaining the online monitored emission amount of the emission monitoring point on the target date comprises:
and acquiring online monitoring data of a target date in the target area, wherein the online monitoring data comprises enterprise information in the target area, emission monitoring point information related to the enterprise information and online monitoring emission of the emission monitoring point information on the target date.
And determining second enterprise information of the production-limited enterprise in the online monitoring data according to the first enterprise information of the production-limited enterprise in the emergency emission reduction list data. Wherein the first enterprise information and the second enterprise information may include enterprise names, unified social credit codes, and the like. As one embodiment, the business names are first matched, and if the business names do not match, the business names can be matched through the social credit codes, and if the social credit codes do not match, the business names can be matched through the keywords. For example, XX thermodynamic and XX thermodynamic Limited companies may be matched by "XX thermodynamics".
And determining second emission monitoring point information of the emission monitoring points in the online monitoring data according to the second enterprise information and the first emission monitoring point information of the emission monitoring points in the emergency emission reduction list data.
And acquiring the online monitoring discharge amount corresponding to the second emission monitoring point information as the online monitoring discharge amount of the emission monitoring point.
And step S1044, judging whether the online monitoring discharge amount of the discharge monitoring point is lower than the reference value.
And S1045, if the online monitoring emission amount of the emission monitoring point is not lower than the reference value, determining that the production limiting line or the working procedure corresponding to the emission monitoring point does not execute emission reduction measures.
In this embodiment, whether the production limit line or the process corresponding to the emission monitoring point executes the emission reduction measure is determined based on whether the online monitoring emission amount of the emission monitoring point is lower than the reference value thereof, so that the difficulty in automatically processing the emission reduction measure described in natural language is avoided.
And S105, outputting the limited production enterprises of which the target dates do not execute the emission reduction measures in the target area and the limited production lines or processes of which the target dates do not execute the emission reduction measures.
As an embodiment, the output information further includes: online monitoring data of emission monitoring points of a production limit line or a process which does not execute emission reduction measures, and corresponding early warning levels and emission reduction measures.
As an example, the output information is: in the orange early warning period of XX aluminum industry Co., Ltd, the upper furnace and the lower furnace of the double-chamber reverberatory furnace are respectively stopped, 1 casting machine stops production, but the pollutant emission amount in X month and X day is not reduced or increased reversely compared with the reference value without starting the early warning, and the suspected emission reduction measures are not implemented in place.
In some possible embodiments, the method further comprises: for each emission monitoring point: if the online discharge amount of the discharge monitoring point is not lower than the reference value, determining the increase amount of the online discharge amount of the discharge monitoring point relative to the reference value; and for all emission monitoring points, sequencing the production limit enterprises which do not execute emission reduction measures and the production limit lines or processes which do not execute the emission reduction measures according to the increasing amounts corresponding to the monitoring points. Wherein a larger rise indicates that the corresponding production line or process has not performed an emission abatement measure.
In some possible embodiments, the production limiting enterprises which do not execute the emission reduction measures on the target date in the target area and the production limiting lines or processes which do not execute the emission reduction measures are output in a list form according to the sorted results. The severity of the problems of the limited production enterprises which do not execute emission reduction measures can be displayed, and then the limited production enterprises with serious problems are treated preferentially.
The embodiment of the invention also provides a device for monitoring the execution condition of the emergency emission reduction measures on line.
Fig. 2 shows a schematic block diagram of an apparatus for online monitoring of performance of emergency emission reduction measures according to an exemplary embodiment of the present invention, as shown in fig. 2, including: an obtaining module 210, configured to obtain emergency emission reduction inventory data; the analysis module 220 is used for analyzing the emergency emission reduction list data to obtain a production limit enterprise and a production limit line or a working procedure thereof in the target area; a first determining module 230, configured to determine, according to an association relationship between a production line or a process and a discharge monitoring point, a discharge monitoring point corresponding to the production line or the process, where each discharge monitoring point is configured to monitor an amount of atmospheric pollutants discharged by its associated production line or process; a second determination module 240 for, for each emission monitoring point: acquiring historical monitoring emission amount of a plurality of days when an emission monitoring point does not start early warning; determining the daily average value of historical monitoring emission of multiple days, and taking the daily average value as a reference value of an emission monitoring point; acquiring online monitoring emission of an emission monitoring point on a target date, wherein the target date belongs to an early warning period; judging whether the online monitoring discharge amount of the discharge monitoring point is lower than a reference value; if the online monitoring emission amount of the emission monitoring point is not lower than the reference value, determining that the production line or the process corresponding to the emission monitoring point does not execute emission reduction measures; and the output module 250 is used for outputting the limited production enterprises of which the target dates do not execute the emission reduction measures in the target area and the limited production lines or processes of which the target dates do not execute the emission reduction measures.
In some possible embodiments, the second determining module 240 is configured to:
acquiring online monitoring data of the target date in a target area, wherein the online monitoring data comprises enterprise information in the target area, emission monitoring point information related to the enterprise information and online monitoring emission of the emission monitoring point information on the target date;
determining second enterprise information of the production-limited enterprise in the online monitoring data according to first enterprise information of the production-limited enterprise in the emergency emission reduction list data;
determining second emission monitoring point information of the emission monitoring points in the online monitoring data according to the second enterprise information and the first emission monitoring point information of the emission monitoring points in the emergency emission reduction list data;
and acquiring the online monitoring discharge amount corresponding to the second emission monitoring point information as the online monitoring discharge amount of the emission monitoring point.
In some possible embodiments, the second determining module 240 is further configured to:
for each emission monitoring point: if the online emission of the emission monitoring point is not lower than the reference value, determining the increase of the online emission of the emission monitoring point relative to the reference value;
and for all emission monitoring points, sequencing the production limit enterprises which do not execute emission reduction measures and the production limit lines or processes which do not execute the emission reduction measures according to the increasing amounts corresponding to the monitoring points.
An exemplary embodiment of the present invention also provides an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor. The memory stores a computer program executable by the at least one processor, the computer program, when executed by the at least one processor, is for causing the electronic device to perform a method according to an embodiment of the invention.
Exemplary embodiments of the present invention also provide a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is operable to cause the computer to perform a method according to an embodiment of the present invention.
Exemplary embodiments of the present invention also provide a computer program product comprising a computer program, wherein the computer program is operative, when executed by a processor of a computer, to cause the computer to perform a method according to an embodiment of the present invention.
Referring to fig. 3, a block diagram of a structure of an electronic device 300, which may be a server or a client of the present invention, which is an example of a hardware device that may be applied to aspects of the present invention, will now be described. Electronic device is intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 3, the electronic device 300 includes a computing unit 301 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)302 or a computer program loaded from a storage unit 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The calculation unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
A number of components in the electronic device 300 are connected to the I/O interface 305, including: an input unit 306, an output unit 307, a storage unit 308, and a communication unit 309. The input unit 306 may be any type of device capable of inputting information to the electronic device 300, and the input unit 306 may receive input numeric or character information and generate key signal inputs related to user settings and/or function controls of the electronic device. Output unit 307 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, a video/audio output terminal, a vibrator, and/or a printer. The storage unit 308 may include, but is not limited to, a magnetic disk, an optical disk. The communication unit 309 allows the electronic device 300 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth devices, WiFi devices, WiMax devices, cellular communication devices, and/or the like.
The computing unit 301 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 301 performs the respective methods and processes described above. For example, in some embodiments, the method of online monitoring of emergency emission abatement measure performance may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 300 via the ROM 302 and/or the communication unit 309. In some embodiments, the computing unit 301 may be configured to perform the method of online monitoring of emergency emission abatement measure performance by any other suitable means (e.g., by way of firmware).
Program code for implementing the methods of the present invention may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
Claims (10)
1. A method for monitoring execution conditions of emergency emission reduction measures on line is applied to electronic equipment, and is characterized by comprising the following steps:
acquiring emergency emission reduction list data;
analyzing the emergency emission reduction list data to obtain a production limit enterprise and a production limit production line or a working procedure thereof in a target area;
determining emission monitoring points corresponding to the production limit line or the working procedure according to the incidence relation between the production line or the working procedure and the emission monitoring points, wherein each emission monitoring point is configured to monitor the emission amount of the atmospheric pollutants of the associated production line or the working procedure;
for each of the emission monitoring points:
acquiring historical monitoring emission amount of the emission monitoring point for multiple days when early warning is not started;
determining the daily average value of the historical monitoring emission of the multiple days, and taking the daily average value as the reference value of the emission monitoring point;
acquiring the online monitoring emission of the emission monitoring point on a target date, wherein the target date belongs to an early warning period;
judging whether the online monitoring discharge amount of the discharge monitoring point is lower than a reference value; and
if the online monitoring emission amount of the emission monitoring point is not lower than the reference value, determining that the production line or the working procedure corresponding to the emission monitoring point does not execute emission reduction measures; and
and outputting the limited production enterprises which do not execute the emission reduction measures on the target date in the target area and the limited production lines or processes which do not execute the emission reduction measures.
2. The method of claim 1, wherein obtaining the online monitored emissions for the emission monitoring point on a target date comprises:
acquiring online monitoring data of a target date in the target area, wherein the online monitoring data comprises enterprise information in the target area, emission monitoring point information related to the enterprise information and online monitoring emission of the emission monitoring point information on the target date;
determining second enterprise information of the production-limited enterprise in the online monitoring data according to first enterprise information of the production-limited enterprise in the emergency emission reduction list data;
determining second emission monitoring point information of the emission monitoring points in the online monitoring data according to the second enterprise information and first emission monitoring point information of the emission monitoring points in the emergency emission reduction list data;
and acquiring the online monitoring emission corresponding to the second emission monitoring point information to serve as the online monitoring emission of the emission monitoring point.
3. The method of claim 1, further comprising:
for each of the emission monitoring points: if the online emission of the emission monitoring point is not lower than the reference value, determining the increase of the online emission of the emission monitoring point relative to the reference value;
and for all the emission monitoring points, sequencing the production limit enterprises which do not execute emission reduction measures and the production limit lines or processes which do not execute the emission reduction measures according to the increasing amounts corresponding to the monitoring points.
4. The method of claim 1, wherein obtaining historical monitored emissions over a plurality of days when the emissions monitoring point has not activated an early warning comprises:
and taking the target date as a starting point, and acquiring historical monitoring emission of the emission monitoring point for preset days when early warning is not started before the target date.
5. The method of claim 3, wherein a production limit facility in which no emission reduction measure is performed on the target date in the target area and a production limit facility or process in which no emission reduction measure is performed are output in a list according to the result of the sorting.
6. A device for online monitoring of emergency emission reduction measure execution conditions is characterized by comprising:
the acquisition module is used for acquiring emergency emission reduction list data;
the analysis module is used for analyzing the emergency emission reduction list data to obtain a production limit enterprise and a production limit production line or a working procedure thereof in a target area;
the device comprises a first determining module, a second determining module and a control module, wherein the first determining module is used for determining emission monitoring points corresponding to the production limit line or the working procedure according to the incidence relation between the production line or the working procedure and the emission monitoring points, and each emission monitoring point is configured to monitor the emission amount of atmospheric pollutants of the associated production line or the working procedure;
a second determination module to, for each of the emission monitoring points: acquiring historical monitoring emission amount of the emission monitoring point for multiple days when early warning is not started; determining the daily average value of the historical monitoring emission of the multiple days, and taking the daily average value as the reference value of the emission monitoring point; acquiring the online monitoring emission of the emission monitoring point on a target date, wherein the target date belongs to an early warning period; judging whether the online monitoring discharge amount of the discharge monitoring point is lower than a reference value; if the online monitoring emission amount of the emission monitoring point is not lower than the reference value, determining that the production line or the working procedure corresponding to the emission monitoring point does not execute emission reduction measures; and
and the output module is used for outputting the limited production enterprises which do not execute the emission reduction measures on the target date in the target area and the limited production lines or processes which do not execute the emission reduction measures.
7. The apparatus of claim 6, wherein the second determining module is to:
acquiring online monitoring data of the target date in the target area, wherein the online monitoring data comprises enterprise information in the target area, emission monitoring point information related to the enterprise information and online monitoring emission of the emission monitoring point information on the target date;
determining second enterprise information of the production-limited enterprise in the online monitoring data according to first enterprise information of the production-limited enterprise in the emergency emission reduction list data;
determining second emission monitoring point information of the emission monitoring points in the online monitoring data according to the second enterprise information and first emission monitoring point information of the emission monitoring points in the emergency emission reduction list data;
and acquiring the online monitoring emission corresponding to the second emission monitoring point information to serve as the online monitoring emission of the emission monitoring point.
8. The apparatus of claim 6, wherein the second determining module is further configured to:
for each of the emission monitoring points: if the online discharge amount of the discharge monitoring point is not lower than the reference value, determining the increase amount of the online discharge amount of the discharge monitoring point relative to the reference value;
and for all the emission monitoring points, sequencing the production limit enterprises which do not execute emission reduction measures and the production limit lines or processes which do not execute the emission reduction measures according to the increasing amounts corresponding to the monitoring points.
9. An electronic device, comprising:
a processor; and
a memory for storing a program, wherein the program is stored in the memory,
wherein the program comprises instructions which, when executed by the processor, cause the processor to carry out the method according to any one of claims 1-5.
10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116070923A (en) * | 2023-02-15 | 2023-05-05 | 中科三清科技有限公司 | Atmospheric pollution scene simulation method and device and electronic equipment |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110991848A (en) * | 2019-11-26 | 2020-04-10 | 浙江省环境科技有限公司 | Enterprise environment information management system |
| CN111046922A (en) * | 2019-11-25 | 2020-04-21 | 中国环境监测总站 | Method for making self-monitoring emission monitoring scheme |
| CN113030562A (en) * | 2021-03-29 | 2021-06-25 | 河南中济智控工业互联网技术有限公司 | Environment-friendly facility power consumption monitoring system |
| CN113393178A (en) * | 2021-08-18 | 2021-09-14 | 北京清创美科环境科技有限公司 | Management system for rapid coupling of emergency emission reduction list and emission list of atmospheric pollution source |
| CN113487212A (en) * | 2021-06-07 | 2021-10-08 | 广联达科技股份有限公司 | Risk monitoring method and device |
| CN113792988A (en) * | 2021-08-24 | 2021-12-14 | 河北先河环保科技股份有限公司 | Online monitoring data anomaly identification method for enterprise |
| CN113988711A (en) * | 2021-11-22 | 2022-01-28 | 国网江苏省电力有限公司连云港供电分公司 | Power consumption data-based monitoring method for stopping or limiting production of sewage disposal enterprises in control state |
-
2022
- 2022-04-22 CN CN202210427193.3A patent/CN114693166A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111046922A (en) * | 2019-11-25 | 2020-04-21 | 中国环境监测总站 | Method for making self-monitoring emission monitoring scheme |
| CN110991848A (en) * | 2019-11-26 | 2020-04-10 | 浙江省环境科技有限公司 | Enterprise environment information management system |
| CN113030562A (en) * | 2021-03-29 | 2021-06-25 | 河南中济智控工业互联网技术有限公司 | Environment-friendly facility power consumption monitoring system |
| CN113487212A (en) * | 2021-06-07 | 2021-10-08 | 广联达科技股份有限公司 | Risk monitoring method and device |
| CN113393178A (en) * | 2021-08-18 | 2021-09-14 | 北京清创美科环境科技有限公司 | Management system for rapid coupling of emergency emission reduction list and emission list of atmospheric pollution source |
| CN113792988A (en) * | 2021-08-24 | 2021-12-14 | 河北先河环保科技股份有限公司 | Online monitoring data anomaly identification method for enterprise |
| CN113988711A (en) * | 2021-11-22 | 2022-01-28 | 国网江苏省电力有限公司连云港供电分公司 | Power consumption data-based monitoring method for stopping or limiting production of sewage disposal enterprises in control state |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116070923A (en) * | 2023-02-15 | 2023-05-05 | 中科三清科技有限公司 | Atmospheric pollution scene simulation method and device and electronic equipment |
| CN116070923B (en) * | 2023-02-15 | 2024-05-07 | 中科三清科技有限公司 | Atmospheric pollution scene simulation method and device and electronic equipment |
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