Method for determining the intensity of air pollution processes and equipment for calculating it

Abstract

The disclosed embodiments provide a method and a computing device for determining the intensity of an atmospheric pollution process. The method for determining the comprehensive index of the intensity of an atmospheric pollution process includes: obtaining the pollutant concentration sequence of each point affected by the atmospheric pollution process to determine the impact duration index, the impact range index, and the average pollution degree index, and performing harmonic averaging based on the impact duration index, the impact range index, the average pollution degree index, and the corresponding weight coefficients to obtain a comprehensive index for evaluating the intensity of the atmospheric pollution process. The aforementioned comprehensive index judges the overall intensity of the atmospheric pollution process in a single way, which is convenient for relevant policy makers to intuitively understand the severity of the atmospheric pollution process and make reasonable policy guidance countermeasures.

Description

Technical Field

[0001] The present disclosure relates to the technical field of environmental monitoring data processing, and in particular to a method for determining the intensity of an atmospheric pollution process and a computing device. Background Art

[0002] The atmospheric pollution process is a process in which the concentration of pollutants exceeds the target concentration within a certain time and space range. The atmospheric pollution process includes the accumulation, persistence and removal stages of pollutants, and has the characteristics of regionality, continuity and high concentration of pollutants. In the case of atmospheric pollution processes (especially large-area heavy pollution processes), in order to achieve peak reduction and value reduction of pollutant processes and avoid the impact of long-term pollution on residents' health and the ecological environment, it is necessary to reasonably formulate pollution reduction measures such as suspension of production and restriction of vehicles by pollution source enterprises.

[0003] The premise for formulating reasonable pollution reduction measures is to have a reasonable forecast and estimate of the intensity of the atmospheric pollution process. At present, although there are methods such as the ambient air quality index (AQI) to conduct regional quantitative assessments of the degree of atmospheric pollution, the aforementioned methods can only quantitatively assess the degree of atmospheric pollution in local areas (city scale and site scale), and cannot achieve rapid quantitative assessments of atmospheric pollution processes that affect larger areas. In the prior art, in order to provide reasonable decision-making basis for emission reduction measure formulaters, experienced environmental experts are required to estimate the intensity of the entire pollution process based on the pollution impact range, pollution intensity, pollution duration and future weather conditions of each region, and it is impossible to achieve reasonable and objective assessment results. Summary of the invention

[0004] In order to solve the problem that it is impossible to provide reasonable comprehensive evaluation indicators to achieve reasonable comprehensive evaluation of the air pollution process, the embodiments of the present disclosure provide a method for determining the intensity of the air pollution process and a computing device.

[0005] In a first aspect, an embodiment of the present disclosure provides a method for determining a comprehensive index of air pollution process intensity, comprising:

[0006] Obtain the pollutant concentration series of each point affected by the atmospheric pollution process;

[0007] Determine the duration of the air pollution process based on the pollutant concentration monitoring data sequence of each point, and determine the affected time of each point and the pollutant concentration within the affected time based on the pollutant concentration monitoring data sequence of each point;

[0008] Calculate the impact duration index of the air pollution process according to the duration, calculate the impact range index of the air pollution process according to the duration and the affected duration of each point, and calculate the average pollution degree index of the air pollution process according to the pollutant concentration of each point within the corresponding affected duration;

[0009] Based on the harmonic average of the impact duration index, the impact range index, the average pollution degree index and the corresponding weight coefficients, a comprehensive index for evaluating the intensity of the air pollution process is obtained.

[0010] Optionally, determining the duration of the air pollution process based on the pollutant concentration monitoring data sequence at each point includes:

[0011] Based on the pollutant concentration sequence of each point, the point where the pollutant concentration of the air pollution process is greater than the excessive concentration for the first continuous set time is taken as the trigger point, and a moment within the first continuous set time is determined as the start timing moment of the air pollution process;

[0012] Based on the pollutant concentration sequence of each point, the point where the pollutant concentration is less than the excessive concentration within the second continuous set time period in the air pollution process is taken as the end point, and the end timing moment of the air pollution process is determined based on the moment when the end point corresponds to the second continuous set time period; or, the current moment of the air pollution process is taken as the end timing moment;

[0013] The duration of the air pollution process is determined based on the start timing time and the end timing time.

[0014] Optionally, calculating the impact duration index of the air pollution process according to the duration includes:

[0015] The impact duration index is determined by performing normalization processing based on the duration, a predetermined maximum experience duration, and a predetermined shortest experience duration.

[0016] Optionally, the calculating the impact range index of the air pollution process according to the duration and the duration of time each point is affected includes:

[0017] The affected time of each point is accumulated to obtain the accumulated affected time;

[0018] The accumulated impact duration is compared with the impact duration to obtain an impact range ratio;

[0019] The influence range index is determined according to the influence range ratio.

[0020] Optionally, determining the influence range index according to the influence range ratio includes:

[0021] The influence range index is determined by performing normalization processing based on the influence range ratio, a predetermined maximum experience ratio and a predetermined minimum experience ratio.

[0022] Optionally, the calculating the average pollution degree index of the air pollution process according to the pollutant concentrations at each point within the corresponding affected time period includes:

[0023] Accumulate the pollutant concentrations at each point within the corresponding affected time to obtain a cumulative sum value; compare the cumulative sum value with the duration to obtain a cumulative average concentration;

[0024] The average pollution degree index is determined based on the accumulated average concentration.

[0025] Optionally, the calculating the average pollution degree index of the air pollution process according to the pollutant concentrations at each point within the corresponding affected time period includes:

[0026] The pollutant concentrations at each point within the corresponding affected time are averaged to obtain the point mean concentration; the point mean concentrations of all points are averaged again to obtain the overall mean concentration;

[0027] The average pollution degree index is determined based on the overall mean concentration.

[0028] Optionally, determining the average pollution degree index based on the overall mean concentration includes:

[0029] The average pollution degree index is determined by performing normalization processing based on the overall mean concentration, a predetermined maximum mean concentration and a minimum mean concentration.

[0030] Optionally, the comprehensive index for evaluating the intensity of the air pollution process is obtained by performing harmonic averaging based on the impact duration index, the impact range index, the average pollution degree index and corresponding weight coefficients, including:

[0031] Add the impact duration index, the impact range index and the average pollution degree index to obtain an overall sum index;

[0032] Dividing the impact duration index, the impact range index and the average pollution degree index by the corresponding weights respectively to obtain the corresponding weight adjustment index, and accumulating all the weight adjustment indexes to obtain the sum adjustment index;

[0033] The overall sum index is divided by the sum adjustment index to obtain a comprehensive index for evaluating the intensity of the air pollution process.

[0034] In a second aspect, an embodiment of the present disclosure provides a computing device, including a processor and a memory, wherein the memory is used to store a computer program; when the computer program is loaded by the processor, the processor executes the method for determining the comprehensive index of the intensity of the atmospheric pollution process as described above.

[0035] The embodiment of the present disclosure obtains the corresponding impact duration index, impact range index and average pollution degree index in terms of the impact duration, impact range and pollution degree of the air pollution process, and then integrates the above three indexes to obtain a comprehensive index. The above comprehensive index judges the overall intensity of the air pollution process in a single way, which is convenient for relevant policy decision makers to intuitively understand the severity of the air pollution process and then make reasonable policy guidance countermeasures. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art description. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work, including:

[0038] Figure 1 is a flow chart of a method for determining a comprehensive index of intensity of an atmospheric pollution process provided by an embodiment of the present disclosure;

[0039] Figure 2 is a flow chart of determining the duration of an atmospheric pollution process in some embodiments;

[0040] Figure 3 is a flow chart for determining a reach index in some embodiments;

[0041] Figure 4 It is a schematic diagram of the structure of a computing device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0042] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0043] The term "including" and its variations used in this document are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions of other terms will be given in the description below. In this document, relational terms such as "first" and "second" are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0044] The embodiment of the present disclosure provides a method for evaluating the intensity of an air pollution process by obtaining a single comprehensive index by integrating various indicators. The method for determining the comprehensive index of the intensity of an air pollution process provided by the embodiment of the present disclosure is executed by a computing device.

[0045] Figure 1 : is a flow chart of a method for determining a comprehensive index of air pollution intensity provided by an embodiment of the present disclosure. Figure 1 As shown, the method for determining the comprehensive number of words of the intensity of the air pollution process provided by the embodiment of the present disclosure includes S110-S160.

[0046] S110: Obtaining a pollutant concentration sequence of each point affected by the atmospheric pollution process.

[0047] The point mentioned in the embodiments of the present disclosure is a unit for overall monitoring of pollutant concentrations and determining the pollutant concentration or the mean pollutant concentration within a period of time. In specific implementations, the aforementioned point can be an environmental monitoring site and its surrounding area, or a town, county, city, or district city divided by administrative divisions. In the case where the point is a zoning unit divided based on administrative divisions, the pollutant monitoring data of the environmental monitoring site within a single zoning unit can be integrated to calculate the pollutant concentration of the unit zoning unit within a period of time; by sorting the pollutant concentrations in chronological order, a pollutant concentration sequence can be obtained.

[0048] Points affected by the air pollution process are points where the corresponding pollutant concentration is greater than the excessive concentration due to the air pollution process. Figuratively speaking, points affected by the air pollution process are points where the corresponding pollutant concentration remains high for a period of time due to the accumulation of air pollutants.

[0049] In specific implementation, the point pollutant concentration sequence can be analyzed by sliding window to determine whether the corresponding point is affected by the atmospheric pollution process. For example, after determining that the pollutant concentration of a certain point is greater than the excessive concentration for a continuous set time period through sliding window processing, it is determined that this point is affected by the atmospheric pollution process, and its pollutant concentration sequence needs to be obtained as the basis for subsequent calculations.

[0050] S120: Determine the duration of the air pollution process based on the pollutant concentration monitoring data sequence of each point, and determine the affected time of each point and the pollutant concentration within the affected time based on the pollutant concentration monitoring data sequence of each point.

[0051] The duration in the embodiment of the present disclosure refers to the overall duration of the air pollution process. Assume that the pollution area of ​​the air pollution process includes points A, B and C, where point A is Air pollution begins at 1:00 p.m. and continues until At this time, point B is at Air pollution occurs at all times and continues until At this moment, point C is Air pollution occurs at all times and continues until time, the duration of the atmospheric pollution process is Time has come The duration of the moment.

[0052] Figure 2 The flowchart of determining the duration of the air pollution process in some embodiments. In a specific implementation, the computing device may use the following S121-S123 to determine the duration of the air pollution process.

[0053] S121: Based on the pollutant concentration sequence of each point, the point where the pollutant concentration is greater than the excessive concentration for the first continuous set time period in the air pollution process is taken as the trigger point, and a moment within the first continuous set time period is determined as the start timing moment of the air pollution process.

[0054] As analyzed above, in the process of air pollution monitoring, the pollutant concentration at each point can be obtained, and a pollutant concentration sequence can be constructed in chronological order. After obtaining the pollutant concentration sequence, the computing device can perform sliding window processing on the pollution concentration sequence of each station for a specific duration (here, the first continuous set duration) to determine whether the pollutant concentration at each monitoring point is greater than the excessive concentration for a long time. If it is determined that the pollutant concentration at a certain point is greater than the excessive concentration for a long time, it can be determined that pollutants have accumulated at this point, and an air pollution process may occur due to poor weather diffusion conditions and excessive pollution discharge.

[0055] Based on the analysis in the previous section, if a certain point is determined to be the first point where the pollutant concentration is greater than the excessive concentration within the first continuous set time, then this point is used as the trigger point, and a moment of the trigger point within the aforementioned first continuous set time is used as the start timing moment of the air pollution process. In specific implementation, the initial moment or the middle moment within the aforementioned first continuous set time can be used as the start timing moment of the air pollution process.

[0056] S122: Based on the pollutant concentration sequence of each point, the point where the pollutant concentration is less than the excessive concentration within the second continuous set time in the air pollution process is taken as the end point, and the end timing time of the air pollution process is determined based on the moment when the end point corresponds to the second continuous set time.

[0057] As analyzed in the background technology, a complete air pollution process includes the accumulation, persistence and removal stages of pollutants. In the pollutant removal stage, the pollutant concentration decreases due to improved diffusion conditions or other reasons. Due to the location of each point, terrain characteristics and the influence of the temporal and spatial separation of the reasons for the removal of pollutants, the pollutant removal rate and the end time of the removal at each point are not the same. In order to fully characterize an air pollution process, the last point in the air pollution process that enters the removal stage and achieves pollutant removal can be used as the end point.

[0058] Specifically, the computing device can use sliding window processing to determine which point in the air pollution process is the last point where the pollutant concentration is less than the excessive concentration within the second continuous set time, and then determine the end point. After determining the end point, the end timing moment of the air pollution process can be determined based on the moment corresponding to the second continuous set time. In a specific implementation, the computing device can use the moment before the initial moment corresponding to the second continuous set time as the end timing moment.

[0059] The aforementioned S122 is determined from the perspective of post-analysis, specifically, from the perspective of post-inversion after the air pollution process has ended, and its goal is to perform post-analysis. In practical applications, it is also necessary to judge the intensity of the air pollution process when it is determined that the air pollution process has started but has not yet ended. In this case, the current moment can also be used as the end timing moment. The aforementioned current moment is the moment to determine the cutoff pollutant concentration sequence and perform the estimation calculation of the intensity of the air pollution process.

[0060] Of course, the above method for determining the start timing moment and the end timing moment is only one method, and other methods may be used to determine the start timing moment and the end timing moment in specific implementations. For example, the previous moment determined by the expert and input into the computing device may be used as the start timing moment, and the later moment determined by the expert and input into the computing device may be used as the end timing moment.

[0061] S123: Determine the duration of the air pollution process based on the start timing time and the end timing time.

[0062] After obtaining the aforementioned start timing time and end timing time, the computing device can use Get the duration of the atmospheric pollution process ,in The timing for the end of the air pollution process, The time when the atmospheric pollution process begins.

[0063] S130: Calculate the impact duration index of the air pollution process according to the duration.

[0064] The impact duration index is an index that characterizes the duration of the impact of the atmospheric pollution process. The impact duration index is positively correlated with the duration of the impact of the atmospheric pollution process.

[0065] In a specific implementation, the computing device has pre-determined the conversion relationship between the duration of the air pollution process and the impact duration index. After the duration is obtained, the impact duration index of the air pollution process can be determined through the aforementioned conversion relationship and the duration set.

[0066] In some embodiments, a duration-impact duration index lookup table is configured in the computing device, and the impact duration index can be determined by looking up the aforementioned lookup table based on the duration.

[0067] In some other embodiments, the computing device determines the impact duration index using the following S131.

[0068] S131: Perform normalization processing based on the duration, the predetermined maximum experience duration, and the shortest experience duration to determine an impact duration index.

[0069] In some embodiments, the computing device uses the formula To achieve normalization processing, To influence the duration index, For duration, is the maximum experience duration, is the shortest experience duration (in specific applications Preferably set to 0), and are predetermined (how to determine , ). The above normalization is linear normalization. In other embodiments, according to the specific mathematical relationship between the duration of the air pollution process and the negative impact it brings, a corresponding normalization method can be used to implement normalization processing (such as indicative normalization or logarithmic normalization) to obtain an impact duration index.

[0070] S140: Calculate the impact range index of the atmospheric pollution process based on the duration and the duration of impact at each point.

[0071] The impact range index is an index that characterizes the impact range of a certain air pollution process. The impact range index is positively correlated with the impact range of the air pollution process. The impact range index mentioned here is the impact range normalized by time (for example, by duration), rather than the absolute impact range.

[0072] Figure 3 1 is a flowchart of determining an influence range index in some embodiments. The computing device may determine the influence range index using the following S141-S143.

[0073] S141: Accumulate the affected time of each point to obtain the accumulated affected time.

[0074] The duration of each point being affected can be determined by determining the start time and the end time of each point being affected. The start time and the end time of each point being affected can be determined using the sliding window processing method mentioned above. After obtaining the start time and the end time of each point being affected, the start time of the affected time is subtracted from the end time of the affected time to obtain the duration of the impact of a single point. The cumulative impact duration can be obtained by adding the affected durations of each point.

[0075] S142: Compare the accumulated impact duration with the impact duration to obtain an impact range ratio.

[0076] In specific implementation, the influence range ratio can be adopted Calculated. is the impact range ratio, To accumulate the impact duration, is the duration of the aforementioned air pollution. According to the aforementioned formula, it is equivalent to taking the cumulative impact duration as the overall impact duration within a range, and comparing it with the overall duration of air pollution, the value representing the average affected point is obtained as the impact range ratio.

[0077] S143: Determine an influence range index according to the influence range ratio.

[0078] After obtaining the impact range ratio, the impact range index can be determined according to the impact range ratio. Impact range index The impact duration index is an index that characterizes the relative degree of the impact range of the atmospheric pollution process.

[0079] In a specific implementation, the computing device has predetermined the conversion relationship between the impact range ratio and the impact range index. After obtaining the impact range ratio, the impact duration index of the air pollution process can be determined through the aforementioned conversion relationship and the impact range ratio.

[0080] In some embodiments, an influence range index-influence range index lookup table is configured in the computing device, and the influence range index can be determined by looking up the aforementioned lookup table based on the influence range ratio.

[0081] In some other embodiments, the computing device determines the influence range index using S1431 as follows.

[0082] S1431: Perform normalization processing based on the impact range ratio, the predetermined maximum experience ratio and the minimum experience ratio to determine the impact range index.

[0083] In some embodiments, the computing device uses the formula To achieve normalization processing, is the impact range index, is the influence range ratio, is the maximum experience duration, is the shortest experience duration (in specific applications Preferably set to 0), and are predetermined (how to determine , ). The above normalization is linear normalization. In other embodiments, a nonlinear normalization method may be used to obtain the influence range index.

[0084] S150: Calculate the average pollution degree index of the air pollution process according to the pollutant concentration at each point within the corresponding affected time.

[0085] The average pollution degree index in the embodiment of the present disclosure can have two meanings (it should be noted that only one of the two meanings can be selected, and they cannot coexist): one refers to the index of the cumulative degree of pollution concentration at each point in the entire atmospheric pollution process; the other refers to the index of the average pollutant concentration of all points at each moment. Regardless of which meaning is adopted, the average pollution degree index is positively correlated with the concentration characteristics of the pollutants.

[0086] The computing device uses different calculation methods for the aforementioned different average pollution degree indexes.

[0087] In order to obtain the average pollution degree index in the first sense mentioned above, the computing device executes the following method S150 - S152 .

[0088] S151: Accumulate the pollutant concentrations at each point within the corresponding affected time to obtain a cumulative sum value; compare the cumulative sum value with the duration to obtain a cumulative average concentration.

[0089] In a specific implementation, the computing device may use Get the cumulative sum ,in For a point within the affected time Pollutant concentration at a given moment.

[0090] S152: Determine an average pollution degree index based on the accumulated average concentration.

[0091] In a specific implementation, the computing device may determine the average pollution degree index based on the accumulated average concentration in accordance with the aforementioned lookup table method or data normalization method. Calculate the average pollution index ,in is the cumulative average concentration, is the predetermined maximum cumulative concentration, is a predetermined minimum cumulative concentration.

[0092] In order to obtain the average pollution degree index in the second meaning mentioned above, the computing device executes S153-S155 as follows.

[0093] S153: Calculate the average of the pollutant concentration at each point within the corresponding affected time to obtain the point average concentration.

[0094] S154: The point mean concentrations of all points are used to perform a mean recalculation process to obtain an overall mean concentration.

[0095] S155: Determine an average pollution degree index based on the overall mean concentration.

[0096] Similar to the method mentioned above, S155 can also use the table lookup or data normalization method mentioned above to determine the average pollution index of each point, which will not be repeated here.

[0097] S160: A comprehensive index for evaluating the intensity of the air pollution process is obtained by performing harmonic averaging based on the impact duration index, the impact range index, the average pollution degree index and the corresponding weight coefficients.

[0098] After obtaining the three-dimensional index data of atmospheric pollution impact duration, impact scope, and pollution degree (i.e., impact duration index, impact scope index, and average pollution degree index) according to S110-S150 in the previous text, the aforementioned index data can then be fused to obtain a comprehensive index that characterizes the intensity of the atmospheric pollution process.

[0099] In some embodiments, the computing device may adopt a weighted summation method to add the aforementioned three indexes and corresponding weighted weights to obtain a comprehensive index.

[0100] In some other embodiments, the computing device uses S161-S163 as follows to obtain a comprehensive index.

[0101] S161: Add the impact duration index, the impact range index and the average pollution degree index to obtain an overall sum index.

[0102] S162: Dividing the impact duration index, the impact range index, and the average pollution degree index by the corresponding weights respectively to obtain corresponding weight adjustment indexes, and accumulating all weight adjustment indexes to obtain a sum adjustment index;

[0103] S163: The overall sum index is divided by the sum adjustment index to obtain a comprehensive index for evaluating the intensity of the air pollution process.

[0104] Analyzing the above S161-S163, the computing device obtains the above comprehensive index by weighted harmonic average, and the above processing process is expressed as follows: .in To evaluate the comprehensive index of the intensity of air pollution process, , and They are the weights corresponding to the impact duration index, impact range index and average pollution degree index respectively.

[0105] As analyzed above, the embodiment of the present disclosure obtains the corresponding impact duration index, impact range index and average pollution degree index in the three aspects of the impact duration, impact range and pollution degree of the air pollution process, and then integrates the above three indexes to obtain a comprehensive index. The above comprehensive index judges the overall intensity of the air pollution process in a single way, which is convenient for relevant policy decision makers to intuitively understand the severity of the air pollution process and then make reasonable policy guidance countermeasures.

[0106] As analyzed above, the premise for obtaining a reasonable comprehensive index in the implementation of the present disclosure is to obtain a reasonable impact duration index, impact range index and average pollution degree index, and to set reasonable weights for the aforementioned indexes. According to the normalization method described above, the premise for setting a reasonable impact duration index, impact range index and average pollution degree index is to set reasonable normalization related parameters.

[0107] To achieve the above goals, specifically to set reasonable impact duration index, impact range index and average pollution degree index, we can collect and process the automatic monitoring data of conventional pollutants in ambient air quality in advance, and perform quality control on the automatic monitoring data. Then, experts will analyze and judge the automatic monitoring data, identify the atmospheric pollution process, and create an atmospheric pollution process case library. Using the data in the case library, we can determine the data for normalization (such as the data in the previous article). , and ). In addition, it is also necessary to reasonably set the weight coefficients of time, scope and pollution degree during the pollution process based on expert experience, so as to balance the data of various dimensions and obtain a reasonable comprehensive index.

[0108] The embodiment of the present disclosure also provides a computing device for implementing the aforementioned method. Figure 4 Schematic diagram of the structure of the computing device provided by the embodiment of the present disclosure. Figure 4 , which shows a schematic diagram of the structure of a computing device 400 suitable for implementing the method of the embodiment of the present disclosure. Figure 4 The computing device shown is only an example and should not bring any limitation to the functionality and scope of use of the embodiments of the present disclosure.

[0109] like Figure 4As shown, the computing device 400 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory ROM 402 or a program loaded from a storage device 408 to a random access memory RAM 403. Various programs and data required for the operation of the computing device 400 are also stored in the RAM 403. The processing device 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output I / O interface 405 is also connected to the bus 404.

[0110] Typically, the following devices may be connected to the I / O interface 405: input devices 406 including, for example, a touch screen, a touch pad, a camera, a microphone, etc.; output devices 407 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 408 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 409. The communication devices 409 may allow the computing device 400 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 4 The computing device 400 is shown with various devices, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have instead.

[0111] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 409, or installed from the storage device 408, or installed from the ROM 402. When the computer program is executed by the processing device 401, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0112] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable storage medium, a computer-readable signal medium, or any combination of the above two.

[0113] The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0114] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer readable signal media may also be any computer readable medium other than a computer readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0115] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0116] The computer-readable medium may be included in the computing device, or may exist independently without being incorporated into the computing device.

[0117] Computer program code for performing operations of the present disclosure may be written in one or more programming languages, or a combination thereof, including, but not limited to, object-oriented programming languages ​​such as Java, SMalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the tester's computer, partially on the tester's computer, as a separate software package, partially on the tester's computer and partially on a remote computer, or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the tester's computer through any type of network, including a local area network (LAN). N ) or Wide Area Network (WA N )—connects to the tester computer, or, can connect to an external computer (e.g., via the Internet using an Internet service provider).

[0118] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated system based on hardware that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0119] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware. The name of the unit does not limit the unit itself in some cases. The functions described above in this article may be at least partially performed by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that can be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), and hardware logic components such as CPUs, CPUs, and other hardware components. I C), application-specific standard products (ASSP), system on chip (SOC), complex programmable logic devices (CPLD), etc.

[0120] The above are only specific embodiments of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to these embodiments herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for determining a comprehensive index of air pollution process intensity, characterized in that: include: Obtain the pollutant concentration series of each point affected by the atmospheric pollution process; Determine the duration of the air pollution process based on the pollutant concentration monitoring data sequence of each point, and determine the affected time of each point and the pollutant concentration within the affected time based on the pollutant concentration monitoring data sequence of each point; Calculating the impact duration index of the air pollution process according to the duration, wherein the impact duration index is an index that characterizes the impact duration of the air pollution process; Calculating the impact range index of the air pollution process according to the duration and the affected duration of each point, including: accumulating the affected duration of each point to obtain the accumulated impact duration; comparing the accumulated impact duration with the duration of the air pollution process to obtain an impact range ratio; determining the impact range index according to the impact range ratio; the impact range index is an index that characterizes the size of the impact range of the air pollution process; and calculating the average pollution degree index of the air pollution process according to the pollutant concentration at each point in the corresponding affected time, wherein the average pollution degree index is an index representing the cumulative degree of pollution concentration at each point in the entire air pollution process or an index representing the average pollutant concentration of all points at each time; Based on the harmonic average of the impact duration index, the impact range index, the average pollution degree index and the corresponding weight coefficients, a comprehensive index for evaluating the intensity of the air pollution process is obtained.

2. The determination method according to claim 1, characterized in that: The determining of the duration of the air pollution process based on the pollutant concentration monitoring data sequence at each point includes: Based on the pollutant concentration sequence of each point, the point where the pollutant concentration of the air pollution process is greater than the excessive concentration for the first continuous set time is taken as the trigger point, and a moment within the first continuous set time is determined as the start timing moment of the air pollution process; Based on the pollutant concentration sequence of each point, the point where the pollutant concentration is less than the excessive concentration within the second continuous set time period in the air pollution process is taken as the end point, and the end timing moment of the air pollution process is determined based on the moment when the end point corresponds to the second continuous set time period; or, the current moment of the air pollution process is taken as the end timing moment; The duration of the air pollution process is determined based on the start timing time and the end timing time.

3. The determination method according to claim 2, characterized in that: The calculating the impact duration index of the air pollution process according to the duration includes: The impact duration index is determined by performing normalization processing based on the duration, a predetermined maximum experience duration, and a predetermined shortest experience duration.

4. The determination method according to claim 1, characterized in that: Determining the impact range index according to the impact range ratio includes: The influence range index is determined by performing normalization processing based on the influence range ratio, a predetermined maximum experience ratio and a predetermined minimum experience ratio.

5. The determination method according to claim 1, characterized in that: The calculation of the average pollution degree index of the air pollution process according to the pollutant concentration at each point within the corresponding affected time period includes: Accumulate the pollutant concentrations at each point within the corresponding affected time to obtain a cumulative sum value; compare the cumulative sum value with the duration to obtain a cumulative average concentration; The average pollution degree index is determined based on the accumulated average concentration.

6. The determination method according to claim 1, characterized in that: The calculation of the average pollution degree index of the air pollution process according to the pollutant concentration at each point within the corresponding affected time period includes: The pollutant concentrations at each point within the corresponding affected time are averaged to obtain the point mean concentration; the point mean concentrations of all points are averaged again to obtain the overall mean concentration; The average pollution degree index is determined based on the overall mean concentration.

7. The determination method according to claim 6, characterized in that: The determining the average pollution degree index based on the overall mean concentration comprises: The average pollution degree index is determined by performing normalization processing based on the overall mean concentration, a predetermined maximum mean concentration and a minimum mean concentration.

8. The determination method according to any one of claims 1 to 7, characterized in that: The comprehensive index for evaluating the intensity of the air pollution process is obtained by harmonizing and averaging the impact duration index, the impact range index, the average pollution degree index and the corresponding weight coefficients, including: Add the impact duration index, the impact range index and the average pollution degree index to obtain an overall sum index; Dividing the impact duration index, the impact range index and the average pollution degree index by the corresponding weights respectively to obtain the corresponding weight adjustment index, and accumulating all the weight adjustment indexes to obtain the sum adjustment index; The overall sum index is divided by the sum adjustment index to obtain a comprehensive index for evaluating the intensity of the air pollution process.

9. A computing device, characterized in that It includes a processor and a memory, wherein the memory is used to store a computer program; when the computer program is loaded by the processor, the processor executes the method for determining the comprehensive index of the intensity of the air pollution process as described in any one of claims 1 to 8.

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