Pollution source information display method and device, electronic equipment and computer readable medium

Abstract

The embodiment of the invention discloses a pollution source information display method and device, electronic equipment and a computer readable medium. A specific embodiment of the method comprises the steps of obtaining a predicted meteorological field information sequence and grid region information, and performing downscaling processing on the predicted meteorological field information sequence to obtain a first meteorological information sequence; inputting the first meteorological information sequence and the predicted meteorological field information sequence into a preset downscaling meteorological information generation model to obtain a second meteorological information sequence; generating each piece of backward track information according to the second meteorological information sequence; according to each piece of backward trajectory information, generating a pollutant contribution rate set corresponding to each grid identifier; acquiring a main body information set to which the pollution source belongs; generating a target pollution source information set according to the main body information set to which the pollution source belongs and the pollutant contribution rate set; and controlling an associated display device to display the target pollution source information set. According to the embodiment, the precision of pollution prevention and control can be improved, and the atmospheric pollution degree is reduced.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the technical field of air pollution control, and in particular to a method, device, electronic device, and computer-readable medium for displaying pollution source information. Background Art

[0002] In recent years, severe air pollution events have occurred frequently, which have had an increasingly serious impact on people's daily lives. Finding pollution sources in a timely manner to prevent and control pollution is of great significance for reducing severe air pollution. At present, when displaying pollution source information, the usual method is to generate pollution source information based on atmospheric information and backward trajectory models, and then display the pollution source information for users to view.

[0003] However, the inventors have found that when the above-mentioned method is used to display pollution source information, the following technical problems often occur: the scale of the atmospheric information directly obtained is relatively high, resulting in a low resolution of the backward trajectory generated in combination with the backward trajectory model, resulting in a low accuracy of the pollution source information, thereby resulting in a low accuracy of pollution prevention and control, causing serious atmospheric pollution.

[0004] In the process of adopting technical solutions to solve the technical problems in the background technology, the following problems are often accompanied: How to improve the accuracy of pollutant alarm information monitored by monitoring stations to save alarm resources. In response to the above technical problems, the conventional solution is generally: determine the pollutant alarm threshold through the historical alarm data of the monitoring station, compare the detected pollutant concentration with the pollutant alarm threshold, so as to improve the accuracy of the pollutant alarm information monitored by the monitoring station. However, the above conventional solution still has the following problem 2: the process of detecting pollutant concentration is affected by the external environment (such as weather, detection equipment), resulting in low accuracy of the detected pollutant concentration, resulting in low accuracy of pollutant alarm information, and then causing a waste of alarm resources.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the invention

[0006] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0007] Some embodiments of the present disclosure propose a pollution source information display method, device, electronic device and computer-readable medium to solve one or more of the technical problems mentioned in the above background technology section.

[0008] In a first aspect, some embodiments of the present disclosure provide a method for displaying pollution source information, the method comprising: in response to detecting at least one pollutant alarm information corresponding to a target environmental monitoring site, obtaining a predicted meteorological field information sequence and grid area information corresponding to the target environmental monitoring area, wherein the target environmental monitoring area corresponds to the target environmental monitoring site, and the grid area information includes each grid identifier; downscaling the predicted meteorological field information sequence to obtain a first meteorological information sequence; inputting the first meteorological information sequence and the predicted meteorological field information sequence into a preset downscaling meteorological information generation model to obtain a second meteorological information sequence, wherein the preset downscaling meteorological information generation model includes a data fusion layer, a first downscaling layer, a second downscaling layer and an output layer; based on the second meteorological information sequence, generating each backward trajectory information corresponding to each pollutant identifier; based on the each backward trajectory information, generating a pollutant contribution rate set corresponding to each grid identifier; obtaining a pollution source subject information set corresponding to the target environmental monitoring area; generating a target pollution source information set based on the pollution source subject information set and the pollutant contribution rate set; and controlling an associated display device to display the target pollution source information set.

[0009] In a second aspect, some embodiments of the present disclosure provide a pollution source information display device, the device comprising: a first acquisition unit, configured to acquire a predicted meteorological field information sequence and grid area information corresponding to a target environmental monitoring area in response to detecting at least one pollutant alarm information corresponding to a target environmental monitoring site, wherein the target environmental monitoring area corresponds to the target environmental monitoring site, and the grid area information includes each grid identifier; a downscaling unit, configured to downscale the predicted meteorological field information sequence to obtain a first meteorological information sequence; an input unit, configured to input the first meteorological information sequence and the predicted meteorological field information sequence into a preset downscaled meteorological information generation model to obtain a second meteorological information sequence, wherein the above The preset downscaling meteorological information generation model includes a data fusion layer, a first downscaling layer, a second downscaling layer and an output layer; the first generation unit is configured to generate each backward trajectory information corresponding to each pollutant identification according to the above-mentioned second meteorological information sequence; the second generation unit is configured to generate a pollutant contribution rate set corresponding to the above-mentioned each grid identification according to the above-mentioned each backward trajectory information; the second acquisition unit is configured to acquire the subject information set of the pollution source corresponding to the above-mentioned target environmental monitoring area; the third generation unit is configured to generate a target pollution source information set according to the above-mentioned pollution source subject information set and the above-mentioned pollutant contribution rate set; the display unit is configured to control the associated display device to display the above-mentioned target pollution source information set.

[0010] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner of the above-mentioned first aspect.

[0011] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the above-mentioned first aspect is implemented.

[0012] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: the pollution source information display of some embodiments of the present disclosure can improve the accuracy of pollution prevention and control and reduce the degree of atmospheric pollution. Specifically, the reason for the low accuracy of pollution prevention and control and the serious atmospheric pollution is that the scale of the atmospheric information directly obtained is high, resulting in a low resolution of the backward trajectory generated in combination with the backward trajectory model, resulting in a low accuracy of the pollution source information, thereby resulting in a low accuracy of pollution prevention and control and serious atmospheric pollution. Based on this, the pollution source information display method of some embodiments of the present disclosure, first, in response to detecting at least one pollutant alarm information corresponding to the target environmental monitoring site, obtains the predicted meteorological field information sequence and grid area information corresponding to the target environmental monitoring area. Among them, the above-mentioned target environmental monitoring area corresponds to the above-mentioned target environmental monitoring site, and the above-mentioned grid area information includes each grid identifier. Thus, when the environmental monitoring site detects a pollutant alarm, the meteorological information and each sub-area information of the monitoring area for a period of time in the future can be obtained, which can be used to trace the pollution source. Secondly, the above-mentioned predicted meteorological field information sequence is downscaled to obtain a first meteorological information sequence. Thus, meteorological information with high precision can be obtained, which can be used to improve the accuracy of the pollution source. Then, the first meteorological information sequence and the predicted meteorological field information sequence are input into the preset downscaled meteorological information generation model to obtain the second meteorological information sequence. Among them, the preset downscaled meteorological information generation model includes a data fusion layer, a first downscale layer, a second downscale layer and an output layer. Thus, the meteorological information can be downscaled again to obtain meteorological information with higher precision. Afterwards, according to the second meteorological information sequence, each backward trajectory information corresponding to each pollutant identification is generated. Thus, each backward trajectory information with high accuracy can be obtained, which can be used to trace the pollution source. Then, according to each backward trajectory information, a pollutant contribution rate set corresponding to each grid identification is generated. Thus, each pollutant contribution rate of each sub-area can be obtained, which can be used to locate the pollution source. Next, the pollution source corresponding to the target environmental monitoring area is obtained. Thus, all the pollution sources in the monitoring area can be obtained, which can be used to locate the pollution source. According to the pollution source subject information set and the pollutant contribution rate set, a target pollution source information set is generated. Thus, each pollution source can be traced back to obtain each pollution source information, which can be used for user viewing. Finally, the associated display device is controlled to display the above-mentioned target pollution source information set. In this way, the information of each pollution source with high accuracy can be displayed, so that it is convenient for users to view it for pollution prevention and control. Also, when tracing the pollution source, the meteorological information can be downscaled multiple times to obtain meteorological information with high precision, thereby improving the accuracy of the traced pollution source information, thereby improving the accuracy of pollution prevention and control and reducing the degree of air pollution. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0014] Figure 1 is a flow chart of some embodiments of the pollution source information display method according to the present disclosure;

[0015] Figure 2 is a schematic diagram of the structure of some embodiments of the pollution source information display device according to the present disclosure;

[0016] Figure 3 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0017] 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 set forth herein. On the contrary, these embodiments are provided to provide 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.

[0018] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0019] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0020] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0021] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0022] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0023] Figure 1The process 100 of some embodiments of the pollution source information display method according to the present disclosure is shown. The pollution source information display method comprises the following steps:

[0024] Step 101, in response to detecting at least one pollutant warning information corresponding to a target environmental monitoring site, obtaining a predicted meteorological field information sequence and grid area information corresponding to a target environmental monitoring area.

[0025] In some embodiments, the execution subject (e.g., computing device) of the pollution source information display method may obtain the predicted meteorological field information sequence and grid area information of the corresponding target environmental monitoring area in response to detecting at least one pollutant warning information of the corresponding target environmental monitoring site. Among them, the above-mentioned target environmental monitoring area corresponds to the above-mentioned target environmental monitoring site. The above-mentioned target environmental monitoring area may be an area where environmental monitoring is required. For example, the above-mentioned target environmental monitoring area may be an administrative area of ​​a city. The above-mentioned target environmental monitoring site may be an atmospheric environmental monitoring site that monitors the above-mentioned target environmental monitoring area. The above-mentioned pollutant warning information may characterize that the pollutant concentration of the corresponding target environmental monitoring area is greater than a preset pollutant concentration threshold. The above-mentioned pollutant concentration may be the concentration of the corresponding pollutant. The above-mentioned pollutant may be, but is not limited to, one of the following: ozone, inhalable particulate matter PM10, inhalable particulate matter PM2.5, sulfur dioxide, nitrogen dioxide, carbon monoxide. The above-mentioned preset pollutant concentration threshold may be a pre-set minimum value of the pollutant concentration that characterizes the pollutant concentration that is harmful to human health. The above-mentioned predicted meteorological field information sequence may be a sequence in which each predicted meteorological field information for a period of time in the future is arranged in ascending order of time. The above-mentioned future period of time may be the next 16 days. The forecasted meteorological field information may be the meteorological data of the Global Forecast System (GFS). The above-mentioned grid area information may be the information of the target environmental monitoring area. The above-mentioned grid area information may include but is not limited to each grid identifier. The grid identifier may be a unique identifier of a grid. Each grid corresponds to a sub-area in the target environmental monitoring area. The sub-area may be: an area in which the target environmental monitoring area is evenly divided according to a preset number of divisions. The above-mentioned preset number of divisions may be a preset number of divisions required. The sub-area may also be an administrative sub-area included in the target environmental monitoring area. For example, the above-mentioned target environmental monitoring area may be the area corresponding to the city of xx, and the sub-area may be the area corresponding to the county of yy of the city of xx. "xx" and "yy" may be any characters. In practice, the above-mentioned execution subject may obtain the forecasted meteorological field information sequence and grid area information of the corresponding target environmental monitoring area from the database through a wired connection or a wireless connection in response to detecting at least one pollutant alarm information of the corresponding target environmental monitoring site.

[0026] Optionally, before step 101, the execution entity may further perform the following steps for each pollutant identification included in each pollutant identification:

[0027] The first step is to obtain the first current pollutant concentration and the second current pollutant concentration corresponding to the above-mentioned pollutant identification of the target environmental monitoring site. Among them, the pollutant identification can be a unique identification of the pollutant. The above-mentioned first current pollutant concentration can be the pollutant concentration of the pollutant corresponding to the above-mentioned pollutant identification at the current time. The above-mentioned second current pollutant concentration can be the pollutant concentration of the pollutant corresponding to the above-mentioned pollutant identification at a time close to the current time. The time close to the current time can be: a time point whose interval duration with the current time is a preset interval duration. The above-mentioned preset interval duration can be a preset interval duration approaching zero. In practice, the above-mentioned execution entity can obtain the first current pollutant concentration and the second current pollutant concentration of the target environmental monitoring site from the database by means of a wired connection or a wireless connection.

[0028] In the second step, the time corresponding to the first current pollutant concentration is determined as the first monitoring time.

[0029] The third step is to determine the time corresponding to the second current pollutant concentration as the second monitoring time.

[0030] In the fourth step, the difference between the second monitoring time and the first monitoring time is determined as the time difference.

[0031] In the fifth step, the difference between the first current pollutant concentration and the second current pollutant concentration is determined as the pollutant concentration difference.

[0032] In the sixth step, the ratio of the above pollutant concentration difference to the above time difference is determined as the concentration change rate.

[0033] The seventh step, in response to determining that the above-mentioned concentration change rate meets the preset concentration change rate condition, generates pollutant alarm information corresponding to the above-mentioned pollutant identification according to the above-mentioned pollutant identification. Among them, the above-mentioned preset concentration change rate condition can be that the above-mentioned concentration change rate is greater than the preset concentration change rate. The above-mentioned preset concentration change rate can be a preset concentration change rate that characterizes the change in pollutant concentration and requires an early warning. In practice, the above-mentioned execution entity can fill the above-mentioned pollutant identification into the preset pollutant alarm information template to generate pollutant alarm information corresponding to the above-mentioned pollutant identification. Among them, the above-mentioned preset pollutant alarm information template can be "the pollutant concentration of A exceeds the standard". Among them, A can represent the pollutant identification to be filled.

[0034] In the face of the above technical problem 2, combined with the advantages of big data technology, the following solutions can be adopted:

[0035] Optionally, before step 101, the execution entity may further perform the following steps for each pollutant identification included in each pollutant identification:

[0036] The first step is to obtain the historical pollutant concentration sequence and the historical site alarm information sequence corresponding to the above-mentioned pollutant identification of the target environmental monitoring site. Among them, the above-mentioned historical pollutant concentration sequence can be a sequence in which each historical pollutant concentration is arranged in ascending time order. The historical pollutant concentration can be the pollutant concentration at the corresponding historical time point. The above-mentioned historical site alarm information sequence can be a sequence in which each historical site alarm information is arranged in ascending time order. The historical site alarm information can be the information issued at a historical time point to warn the user that the pollutant concentration of the target environmental monitoring site exceeds the standard. The historical site alarm information may include but is not limited to the pollutant identification and the historical time point. In practice, the above-mentioned execution entity can obtain the historical pollutant concentration sequence and the historical site alarm information sequence corresponding to the above-mentioned pollutant identification of the target environmental monitoring site from the database through a wired connection or a wireless connection.

[0037] In the second step, the historical pollutant concentration sequence and the historical site alarm information sequence are input into the pre-trained pollutant alarm threshold generation model to obtain the pollutant alarm threshold. The pollutant alarm threshold generation model can be a linear function with the historical pollutant concentration sequence and the historical site alarm information sequence as input and the pollutant alarm threshold as output. The pollutant alarm threshold can be the minimum value of the pollutant concentration that needs to remind the user that the pollutant concentration exceeds the standard.

[0038] The third step is to normalize each historical pollutant concentration in the above historical pollutant concentration sequence to obtain a normalized historical pollutant concentration sequence. In practice, first, the above execution entity can determine the maximum value of each historical pollutant concentration in the above historical pollutant concentration sequence as the first historical pollutant concentration. Secondly, the minimum value of each historical pollutant concentration in the above historical pollutant concentration sequence is determined as the second historical pollutant concentration. Then, the difference between the first historical pollutant concentration and the second historical pollutant concentration is determined as the first historical pollutant concentration difference. After that, for each historical pollutant concentration included in the above historical pollutant concentration sequence, the difference between the above historical pollutant concentration and the second historical pollutant concentration is determined as the second historical pollutant concentration difference. Then, for each determined second historical pollutant concentration difference, the ratio of the second historical pollutant concentration difference to the first historical pollutant concentration difference is determined as the normalized historical pollutant concentration. Finally, the determined normalized historical pollutant concentrations are arranged in ascending order according to the position of the corresponding historical pollutant concentration in the above historical pollutant concentration sequence to obtain a normalized historical pollutant concentration sequence.

[0039] The fourth step is to generate a set of historical pollutant concentration correlation coefficients based on the above normalized historical pollutant concentration sequence and the above historical pollutant concentration sequence. In practice, for each normalized historical pollutant concentration in the above normalized historical pollutant concentration sequence, the above execution entity can perform correlation analysis on the above normalized historical pollutant concentration and the above historical pollutant concentration sequence through the CCA (Canonical Correlation Analysis, CCA) typical correlation analysis algorithm to obtain the historical pollutant concentration correlation coefficient. Then, the obtained historical pollutant concentration correlation coefficients are determined as the set of historical pollutant concentration correlation coefficients.

[0040] Step 5: For each historical pollutant concentration correlation coefficient included in the historical pollutant concentration correlation coefficient set, in response to determining that the historical pollutant concentration correlation coefficient satisfies a preset correlation coefficient condition, the historical pollutant concentration corresponding to the historical pollutant concentration correlation coefficient in the historical pollutant concentration sequence is determined as the target historical pollutant concentration. The preset correlation coefficient condition may be that the historical pollutant concentration correlation coefficient is greater than or equal to a preset historical pollutant concentration correlation coefficient. The preset historical pollutant concentration correlation coefficient may be a preset historical pollutant concentration correlation coefficient.

[0041] In the sixth step, the determined historical pollutant concentrations of each target, the pollutant identification and the current time are input into the pre-trained prediction site pollutant concentration generation model to obtain the predicted site pollutant concentration. Among them, the prediction site pollutant concentration generation model can be a time series prediction model with each target historical pollutant concentration, the pollutant identification and the current time as input and the predicted site pollutant concentration as output. The predicted site pollutant concentration can be the predicted pollutant concentration monitored by the corresponding atmospheric environment monitoring station. The prediction site pollutant concentration generation model can include an input layer, a first prediction layer, a second prediction layer, a third prediction layer and an output layer. The input layer can be used to extract feature vectors from the input data. The first prediction layer, the second prediction layer and the third prediction layer can be different types of time series prediction models for predicting site pollutant concentrations. As an example, the first prediction layer can be a model that is good at capturing long-term characteristics of time series. For example, the first prediction layer can be a Transformer model. The second prediction layer can be a model that is good at capturing short-term characteristics of time series. For example, the second prediction layer can be an ARMA model (Auto-Regressive Moving Average Model). The third prediction layer can be a time series prediction model containing seasonal patterns. For example, the third prediction layer may be a seasonal decomposition model (Seasonal Decomposition of Time Series, STL). The output layer may be used to determine the preset first seasonal model coefficient as the third model coefficient in response to the current time and the pollutant identifier satisfying the preset seasonal condition, determine the preset second seasonal model coefficient as the third model coefficient in response to the current time and the pollutant identifier not satisfying the preset seasonal condition, and determine the product of the predicted site pollutant concentration output by the first prediction layer and the preset first model coefficient, the product of the predicted site pollutant concentration output by the second prediction layer and the preset second model coefficient, and the product of the predicted site pollutant concentration output by the third prediction layer and the third model coefficient as the predicted site pollutant concentration. The sum of the preset first model coefficient, the preset second model coefficient and the third model coefficient may be 1. The preset first model coefficient and the preset second model coefficient may be the coefficients of the corresponding time series prediction model set in advance. The preset first model coefficient and the preset second model coefficient may be the same. The preset seasonal condition may be that the pollutant identifier is a pollutant susceptible to seasonal influences, and the season at the current time is the season in which the pollutant corresponding to the pollutant identifier is susceptible to influence. As an example, if the pollutant is identified as PM2.5 and the current time is winter, the preset seasonal condition is met. The preset first seasonal model coefficient and the preset second seasonal model coefficient can both be preset coefficients corresponding to the second prediction layer.It should be noted that the above-mentioned preset first seasonal model coefficient is greater than the above-mentioned preset second seasonal model coefficient. For example, the above-mentioned preset first seasonal model coefficient may be 0.6, and the above-mentioned preset second seasonal model coefficient may be 0.4. The above-mentioned input layer is connected to the above-mentioned first prediction layer, the above-mentioned second prediction layer and the above-mentioned third prediction layer respectively. The above-mentioned first prediction layer, the above-mentioned second prediction layer and the above-mentioned third prediction layer are connected to the above-mentioned output layer.

[0042] The seventh step is to obtain the current site monitoring pollutant concentration corresponding to the above pollutant identification. The above current site monitoring pollutant concentration can be the pollutant concentration monitored by the target environmental monitoring site at the current time. In practice, the above execution entity can obtain the current site monitoring pollutant concentration corresponding to the above pollutant identification from the database through a wired connection or a wireless connection.

[0043] Step 8: Determine the pollutant concentration monitored at the target site based on the predicted site pollutant concentration and the current site pollutant concentration monitored. The pollutant concentration monitored at the target site may be the pollutant concentration actually referenced by the user. In practice, the execution entity may determine the preset initial collection times as the initial collection times, and perform the following determination steps:

[0044] In the first determination step, the difference between the predicted site pollutant concentration and the current site monitored pollutant concentration is determined as the concentration estimation difference. The preset initial acquisition times may be the preset number of times of collecting and detecting pollutant concentrations. For example, the preset initial acquisition times may be 1.

[0045] In the second determination step, in response to determining that the concentration estimation difference is less than a preset concentration estimation difference, the pollutant concentration monitored at the current site is determined as the pollutant concentration monitored at the target site. The preset concentration estimation difference may be a pre-set concentration estimation difference.

[0046] The third determination step, in response to determining that the above-mentioned concentration estimated difference is greater than or equal to the preset concentration estimated difference, and the initial collection number is less than the preset collection number, controls the associated air quality detector to perform a detection operation, obtains the detected pollutant concentration corresponding to the above-mentioned pollutant identification as the current site monitoring pollutant concentration, and determines the sum of the initial collection number and the preset increase step as the updated collection number, and continues to perform the determination step with the updated collection number as the initial collection number. Among them, the above-mentioned preset collection number can be the maximum value of the preset number of times to collect and detect pollutant concentrations. For example, the above-mentioned preset collection number can be 3 or 5. The above-mentioned detection operation can be to detect the pollutant concentration corresponding to the above-mentioned pollutant identification. The above-mentioned preset increase step can be a preset value of the number of collections increased each time. For example, the above-mentioned preset increase step can be 1.

[0047] In the ninth step, in response to the pollutant concentration monitored at the target site being greater than or equal to the pollutant alarm threshold, pollutant alarm information is generated according to the pollutant identifier, and the alarm device corresponding to the pollutant identifier is controlled to perform a pollutant alarm operation. The alarm device may be a device for alerting a user. For example, the alarm device may be an alarm or an indicator light. The pollutant alarm operation may be an operation of alerting a user that the concentration of the corresponding pollutant exceeds the standard. As an example, when the alarm device is an alarm, the pollutant alarm operation may be an operation of the alarm sounding an alarm. As another example, when the alarm device is an indicator light, the pollutant alarm operation may be an operation of turning on the indicator light.

[0048] The above technical solution and its related contents, as an inventive point of the embodiments of the present disclosure, solve the technical problem that "the process of detecting the pollutant concentration is affected by the external environment (such as weather, detection equipment), resulting in low accuracy of the detected pollutant concentration, thereby causing low accuracy of the pollutant alarm information, and further causing waste of alarm resources". The factors that lead to waste of alarm resources are often as follows: the process of detecting the pollutant concentration is affected by the external environment (such as weather, detection equipment), resulting in low accuracy of the detected pollutant concentration, thereby causing low accuracy of the pollutant alarm information, and further causing waste of alarm resources. If the above factors are solved, the effect of saving alarm resources can be achieved. In order to achieve this effect, the pollution source information display method of some embodiments of the present disclosure, while determining the pollutant alarm threshold through the historical alarm data of the monitoring station, verifies the detected current pollutant concentration by comparing the current pollutant concentration obtained by prediction with the current pollutant concentration obtained by detection. When the difference between the current pollutant concentration obtained by prediction and the current pollutant concentration obtained by detection is small, the current pollutant concentration can be used as the actual value to determine whether the pollutant concentration exceeds the standard, thereby improving the accuracy of the pollutant alarm information. Also, because when predicting the current pollutant concentration, the seasonal changes in pollutant concentration and changes in long-term and short-term series are comprehensively considered, the accuracy of the predicted current pollutant concentration can be improved, which in turn further improves the accuracy of the pollutant alarm information, thereby saving alarm resources.

[0049] Step 102, downscaling the predicted meteorological field information sequence to obtain a first meteorological information sequence.

[0050] In some embodiments, the above-mentioned execution entity may downscale the above-mentioned forecast meteorological field information sequence to obtain a first meteorological information sequence. The above-mentioned first meteorological information sequence may be a sequence in which each first meteorological information is arranged in ascending order of time. The first meteorological information may include but is not limited to atmospheric temperature, atmospheric humidity, air pressure, wind speed, wind direction, and precipitation. In practice, the above-mentioned execution entity may downscale the above-mentioned forecast meteorological field information sequence by a preset WRF (Weather Research and Forecasting) downscaling method to obtain a first meteorological information sequence. The above-mentioned preset WRF downscaling method may be a dynamic downscaling method of a preset WRF model, or a statistical downscaling method of a WRF model.

[0051] Step 103: input the first meteorological information sequence and the predicted meteorological field information sequence into a preset downscaled meteorological information generation model to obtain a second meteorological information sequence.

[0052] In some embodiments, the execution subject may input the first meteorological information sequence and the predicted meteorological field information sequence into a preset downscaled meteorological information generation model to obtain a second meteorological information sequence. The preset downscaled meteorological information generation model may be a neural network that takes the first meteorological information sequence and the predicted meteorological field information sequence as input and the second meteorological information sequence as output. The neural network may be a convolutional neural network. The preset downscaled meteorological information generation model may include a data fusion layer, a first downscaling layer, a second downscaling layer and an output layer. The data fusion layer may be used to fuse the first meteorological information and the predicted meteorological field information at the same time. The first downscaling layer may be a hybrid downscaling process for the fused data to obtain the first hybrid downscaled meteorological field information. The first downscaling layer may be a hybrid downscaling model of the WRF mode. The second downscaling layer may be a hybrid downscaling process for the first hybrid downscaled meteorological field information to obtain the second hybrid downscaled meteorological field information. The second downscaling layer may also be a hybrid downscaling model of the WRF mode. The output layer may be used to arrange the obtained second hybrid downscaled meteorological field information as the second meteorological information to obtain the second meteorological information sequence. The data fusion layer is connected to the first downscaling layer. The first downscaling layer is connected to the second downscaling layer. The second downscaling layer is connected to the output layer.

[0053] Step 104: Generate each backward trajectory information corresponding to each pollutant identifier according to the second meteorological information sequence.

[0054] In some embodiments, the above-mentioned execution entity may generate various backward trajectory information corresponding to each pollutant identification according to the above-mentioned second meteorological information sequence. Among them, the pollutant identification and the backward trajectory information may correspond one to one. The backward trajectory information may characterize the trajectory of the transport and diffusion of the pollutant corresponding to the pollutant identification. The backward trajectory information may include but is not limited to a trajectory point coordinate sequence. The above-mentioned trajectory point coordinate sequence may be a sequence in which the coordinates of each trajectory point are arranged in ascending order of time. The trajectory point coordinates may be the longitude and latitude coordinates of the trajectory point. The above-mentioned trajectory point may be a point on the trajectory formed during the diffusion process of the pollutant. In practice, the above-mentioned execution entity may input the above-mentioned second meteorological information sequence into a preset backward trajectory model to obtain various backward trajectory information corresponding to each pollutant identification. Among them, the above-mentioned preset backward trajectory model may be a Hysplit (Hybrid single particle lagrangian integrated trajectory) backward trajectory model.

[0055] Step 105: Generate a pollutant contribution rate set corresponding to each grid mark according to each backward trajectory information.

[0056] In some embodiments, based on the above-mentioned backward trajectory information, a set of pollutant contribution rates corresponding to the above-mentioned grid identifiers is generated. Each grid identifier corresponds to a pollutant contribution rate. In practice, the above-mentioned execution entity can generate a set of pollutant contribution rates corresponding to the above-mentioned grid identifiers based on the above-mentioned backward trajectory information in various ways.

[0057] Optionally, the above-mentioned grid area information may also include the total number of grids. The above-mentioned total number of grids may be the number of each sub-area included in the target environmental monitoring area. The predicted meteorological field information in the above-mentioned predicted meteorological field information sequence may include each predicted pollutant concentration corresponding to each pollutant identification. The pollutant identification and the predicted pollutant concentration may correspond one to one. The predicted pollutant concentration may be the predicted pollutant concentration of the corresponding pollutant identification.

[0058] In some optional implementations of some embodiments, the execution subject may generate a set of pollutant contribution rates corresponding to the above-mentioned each grid mark according to the above-mentioned each backward trajectory information through the following steps:

[0059] In the first step, for each backward trajectory information included in the above backward trajectory information, the following sub-steps are performed:

[0060] The first sub-step is to arrange the predicted pollutant concentrations corresponding to the backward trajectory information included in the predicted meteorological field information sequence to obtain a predicted pollutant concentration sequence. The predicted pollutant concentration corresponding to the backward trajectory information may be: a predicted pollutant concentration whose corresponding pollutant identifier is the same as the pollutant identifier corresponding to the backward trajectory information. In practice, the predicted pollutant concentrations corresponding to the backward trajectory information included in the predicted meteorological field information sequence may be arranged in ascending order of time to obtain a predicted pollutant concentration sequence.

[0061] The second sub-step is to determine the average value of each predicted pollutant concentration included in the above-mentioned predicted pollutant concentration sequence as the predicted pollutant concentration average value.

[0062] The third sub-step is to determine the number of grid trajectories for each grid identifier included in the above-mentioned grid area information according to the above-mentioned backward trajectory information and the above-mentioned grid identifier. In practice, first, the above-mentioned execution subject can obtain the grid area range corresponding to the above-mentioned grid identifier from the database by wired connection or wireless connection. Among them, the above-mentioned grid area range can be the range covered by the sub-area corresponding to the grid identifier. The above-mentioned grid area range can be represented by the longitude and latitude range corresponding to the sub-area. For example, the grid area range can be: "East longitude (112°42′, 114°14′), North latitude (34°16′, 34°58′)". Then, in response to determining that the coordinates of any trajectory point included in the above-mentioned backward trajectory information are included in the above-mentioned grid area range, the preset first trajectory number is determined as the number of grid trajectories. Among them, the above-mentioned preset first trajectory number can represent that the trajectory corresponding to the above-mentioned backward trajectory information passes through the sub-area of ​​the corresponding grid identifier. For example, the above-mentioned preset first trajectory number can be 1. Finally, in response to determining that the coordinates of each trajectory point included in the above-mentioned backward trajectory information are not included in the above-mentioned grid area range, the preset second trajectory number is determined as the number of grid trajectories. The preset second track number may indicate that the track corresponding to the backward track information does not pass through the sub-region marked by the corresponding grid. For example, the preset second track number may be 0.

[0063] In the fourth sub-step, the sum of the numbers of the generated grid trajectories is determined as the total number of pollutant trajectories.

[0064] The fifth sub-step is to determine the number of each generated grid track as a grid track array.

[0065] In a sixth sub-step, in response to determining that the predicted pollutant concentration average value satisfies a preset pollutant concentration condition, the total number of pollutant trajectories is determined as the first total number of pollutant trajectories, and the grid trajectory array is determined as the first grid trajectory array. The preset pollutant concentration condition may be: the predicted pollutant concentration average value is greater than or equal to the preset pollutant concentration. The preset pollutant concentration may be a preset minimum value indicating that the pollutant concentration exceeds the standard.

[0066] In a seventh sub-step, in response to determining that the predicted pollutant concentration average value does not satisfy the preset pollutant concentration condition, the total number of pollutant trajectories is determined as a second total number of pollutant trajectories, and the grid trajectory array is determined as a second grid trajectory array.

[0067] In the second step, the sum of the total number of pollutant trajectories generated is determined as the total number of trajectories.

[0068] In the third step, the ratio of the total number of trajectories to the total number of grids is determined as the average number of trajectories.

[0069] The fourth step is to generate, for each grid identifier included in the grid area information, a pollutant contribution rate corresponding to the grid identifier according to the average trajectory number, wherein the pollutant contribution rate may be the proportion of air pollution generated by the area corresponding to the grid identifier in the target environmental monitoring area.

[0070] The fifth step is to determine the determined contribution rates of each pollutant as a pollutant contribution rate set.

[0071] In some optional implementations of some embodiments, the execution subject may generate the pollutant contribution rate corresponding to the grid mark according to the average trajectory number through the following steps:

[0072] In the first step, for each generated first grid track array, the number of first grid tracks corresponding to the grid identifier in the first grid track array is determined as the first target grid track number.

[0073] In the second step, the sum of the determined numbers of the first target grid tracks is determined as the total number of the first grid tracks.

[0074] The third step is to determine, for each generated second grid track array, the number of second grid tracks corresponding to the grid identifier in the second grid track array as the second target grid track number.

[0075] In the fourth step, the sum of the determined numbers of the second target grid tracks is determined as the total number of the second grid tracks.

[0076] In the fifth step, the sum of the total number of the first grid tracks and the total number of the second grid tracks is determined as the total number of grid tracks.

[0077] In the sixth step, the ratio of the total number of grid trajectories to the average number of trajectories is determined as a grid weight coefficient.

[0078] In the seventh step, the ratio of the total number of the first grid tracks to the total number of the grid tracks is determined as the first pollutant contribution rate.

[0079] In the eighth step, the product of the first pollutant contribution rate and the grid weight coefficient is determined as the pollutant contribution rate.

[0080] Step 106, obtaining a set of information about the entities that own the pollution sources in the target environmental monitoring area.

[0081] In some embodiments, the above-mentioned execution entity may obtain the information set of the pollution source entity corresponding to the above-mentioned target environmental monitoring area. Among them, the pollution source entity information in the above-mentioned pollution source entity information set may be the information of the pollution source entity. The pollution source entity may be the entity that generates pollutants (such as an enterprise). The pollution source entity information may include but is not limited to the pollution source entity identifier. The above-mentioned pollution source entity identifier may be the unique identifier of the pollution source entity. In practice, the above-mentioned execution entity may obtain the pollution source entity information set corresponding to the above-mentioned target environmental monitoring area from the database through a wired connection or a wireless connection.

[0082] Step 107: Generate a target pollution source information set based on the pollution source subject information set and the pollutant contribution rate set.

[0083] In some embodiments, the execution subject may generate a target pollution source information set based on the pollution source subject information set and the pollutant contribution rate set. The target pollution source information in the target pollution source information set may be information of a subject that produces a larger proportion of pollutants. In practice, the execution subject may generate a target pollution source information set based on the pollution source subject information set and the pollutant contribution rate set in various ways.

[0084] Optionally, the pollution source subject information in the pollution source subject information set may further include subject coordinates, wherein the subject coordinates may be the longitude and latitude coordinates of the pollution source subject.

[0085] In some optional implementations of some embodiments, the execution subject may generate a target pollution source information set according to the pollution source subject information set and the pollutant contribution rate set through the following steps:

[0086] In the first step, for each pollution source subject information in the above pollution source subject information set, perform the following sub-steps:

[0087] The first sub-step is to determine the subject grid identifier corresponding to the subject information of the pollution source according to the subject coordinates included in the subject information of the pollution source and the above-mentioned grid identifiers. In practice, the above-mentioned execution entity can determine the grid identifier that meets the preset identification condition among the above-mentioned grid identifiers as the subject grid identifier corresponding to the subject information of the pollution source. Among them, the above-mentioned preset identification condition can be: the grid area range corresponding to the grid identifier contains the subject coordinates included in the subject information of the pollution source.

[0088] The second sub-step is to determine the pollutant contribution rate corresponding to the above-mentioned main grid identifier in the above-mentioned pollutant contribution rate set as the target pollutant contribution rate.

[0089] The third sub-step is to sort the above pollutant contribution rate set to obtain a pollutant contribution rate sequence. In practice, the above execution entity can sort the above pollutant contribution rate set in descending order of numerical value to obtain a pollutant contribution rate sequence.

[0090] In a fourth sub-step, based on the pollutant contribution rate sequence, in response to determining that the target pollutant contribution rate satisfies a preset pollutant contribution rate condition, the subject information of the pollution source is determined as the target pollution source information. The preset pollutant contribution rate condition may be: the rank of the target pollutant contribution rate in the pollutant contribution rate sequence is less than or equal to a preset rank. The preset rank may be a pre-set rank. For example, the preset rank may be 3.

[0091] In the second step, the information of each target pollution source is determined as a target pollution source information set.

[0092] Optionally, the pollutant warning information in the at least one pollutant warning information may further include a pollutant identifier.

[0093] Optionally, the above execution entity may further perform the following steps:

[0094] The first step is to obtain the information set of pollutant emissions corresponding to the above-mentioned information set of the pollution source. Among them, the information of the pollution source and the information of pollutant emissions can correspond one to one. The above-mentioned information of pollutant emissions can be information on pollutants emitted by the corresponding pollution source. The above-mentioned information of pollutant emissions can include but is not limited to each pollutant emission identification corresponding to each pollutant emission and each current pollutant emission. The pollutant emissions can correspond one to one with the pollutant emission identification. The pollutant emissions can correspond one to one with the current pollutant emission. The pollutant emissions can correspond one to one with one: particulate pollutants, sulfur dioxide, nitrogen oxides (NOx), volatile organic compounds (VOCs), carbon monoxide. The pollutant emission identification can be a unique identification of the corresponding pollutant emission. The current pollutant emission can be the emission of the pollutant emission corresponding to the current time.

[0095] The second step is to generate a target pollution source subject identification set based on the above-mentioned subject pollutant emission information set and the above-mentioned at least one pollutant warning information. Among them, the target pollution source subject identification in the above-mentioned target pollution source subject identification set can be the identification of the pollution source subject that emits more pollutants. In practice, first, for each pollutant warning information included in the above-mentioned at least one pollutant warning information, the above-mentioned execution subject can perform the following sub-steps:

[0096] The first sub-step is to obtain the associated emission identification group corresponding to the pollutant identification included in the above-mentioned pollutant alarm information from the database by wired connection or wireless connection. Among them, the associated emission identification included in the above-mentioned associated emission identification group can be the identification of the emission pollutant that has an association relationship or conversion relationship with the corresponding pollutant. As an example, if the pollutant identification is inhalable particulate matter PM2.5, then the associated emission identification can be a particle pollutant. As another example, if the pollutant identification is ozone, then the associated emission identification can be one of the following: nitrogen oxides (NOx), volatile organic compounds (VOCs).

[0097] In the second sub-step, for each associated emission identification included in the associated emission identification group, each current pollutant emission amount corresponding to the associated emission identification in the above-mentioned subject emission pollutant information set is determined as a target current pollutant emission amount group. The current pollutant emission amount corresponding to the above-mentioned associated emission identification can be: the current pollutant emission amount whose corresponding emission pollutant identification is the same as the above-mentioned associated emission identification.

[0098] The third sub-step is to sort each determined target current pollutant emission group in descending order to obtain a target current pollutant emission sequence.

[0099] In the fourth sub-step, for each determined target current pollutant emission amount sequence, each target current pollutant emission amount in the target current pollutant emission amount sequence that meets a preset ranking condition is determined as a target pollutant emission amount group. The preset ranking condition may be that the ranking of the target current pollutant emission amount in the target current pollutant emission amount sequence is less than or equal to a preset ranking.

[0100] The fifth sub-step is to determine, for each determined target pollutant emission group, the subject information of each pollution source corresponding to the target pollutant emission group as the target pollution source subject information group.

[0101] The sixth sub-step is to determine, for each determined target pollution source subject information group, each pollution source subject identifier included in the target pollution source subject information group as a target pollution source subject identifier group.

[0102] Then, the obtained subject identification groups of each target pollution source are deduplicated to obtain a subject identification set of each target pollution source.

[0103] The third step is to send the preset pollution emission warning information to the pollution source entity terminal corresponding to the above-mentioned target pollution source entity identifier for each target pollution source entity identifier included in the above-mentioned target pollution source entity identifier set. The above-mentioned preset pollution emission warning information can be pre-set information that indicates that the pollutant emission exceeds the standard to warn the user. For example, the above-mentioned preset pollution emission warning information can be "pollutant emission exceeds the standard". The above-mentioned pollution source entity terminal can be the terminal of the pollution source entity.

[0104] Step 108: Control the associated display device to display the target pollution source information set.

[0105] In some embodiments, the above-mentioned execution entity can control the associated display device to display the above-mentioned target pollution source information set.

[0106] In some optional implementations of some embodiments, the execution subject may control the associated display device to display the target pollution source information set through the following steps:

[0107] The first step is to control the associated display device to display the regional map corresponding to the target environmental monitoring area. In practice, first, the execution subject can draw the regional map corresponding to the target environmental monitoring area through GIS (Geographic Information System) technology. Then, the associated display device is controlled to display the regional map corresponding to the target environmental monitoring area.

[0108] In the second step, for each target pollution source information included in the target pollution source information set, perform the following sub-steps:

[0109] In a first sub-step, the target pollutant contribution rate corresponding to the target pollution source information is determined as the first pollutant contribution rate.

[0110] The second sub-step is to determine the preset subject display style information corresponding to the first pollutant contribution rate as the subject display style information corresponding to the target pollution source information. The preset subject display style information may be information on the display style of the pollution source subject logo that is preset corresponding to the preset pollutant contribution rate. The preset pollutant contribution rate may be a preset pollutant contribution rate. The preset subject display style information may include but is not limited to logo size and logo color. The logo size may be the size of the pollution source subject logo. The logo color may be the color of the pollution source subject logo.

[0111] The third sub-step is to determine the preset subject location information corresponding to the subject coordinates included in the above-mentioned target pollution source information as the subject display location information. The above-mentioned preset subject location information is the information of the location of the pollution source subject on the above-mentioned regional map. The above-mentioned preset subject location information can be the information of the location of the pollution source subject on the above-mentioned regional map. The preset subject location information can include but is not limited to the subject map coordinates. The above-mentioned subject map coordinates can be the coordinates of the pollution source subject on the above-mentioned regional map.

[0112] The fourth sub-step is to display the subject identification control at the location corresponding to the subject display position information on the regional map according to the subject display style information. The subject identification control may be a control representing the subject identification of the pollution source.

[0113] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: the pollution source information display of some embodiments of the present disclosure can improve the accuracy of pollution prevention and control and reduce the degree of atmospheric pollution. Specifically, the reason for the low accuracy of pollution prevention and control and the serious atmospheric pollution is that the scale of the atmospheric information directly obtained is high, resulting in a low resolution of the backward trajectory generated in combination with the backward trajectory model, resulting in a low accuracy of the pollution source information, thereby resulting in a low accuracy of pollution prevention and control and serious atmospheric pollution. Based on this, the pollution source information display method of some embodiments of the present disclosure, first, in response to detecting at least one pollutant alarm information corresponding to the target environmental monitoring site, obtains the predicted meteorological field information sequence and grid area information corresponding to the target environmental monitoring area. Among them, the above-mentioned target environmental monitoring area corresponds to the above-mentioned target environmental monitoring site, and the above-mentioned grid area information includes each grid identifier. Thus, when the environmental monitoring site detects a pollutant alarm, the meteorological information and each sub-area information of the monitoring area for a period of time in the future can be obtained, which can be used to trace the pollution source. Secondly, the above-mentioned predicted meteorological field information sequence is downscaled to obtain a first meteorological information sequence. Thus, meteorological information with high precision can be obtained, which can be used to improve the accuracy of the pollution source. Then, the first meteorological information sequence and the predicted meteorological field information sequence are input into the preset downscaled meteorological information generation model to obtain the second meteorological information sequence. Among them, the preset downscaled meteorological information generation model includes a data fusion layer, a first downscale layer, a second downscale layer and an output layer. Thus, the meteorological information can be downscaled again to obtain meteorological information with higher precision. Afterwards, according to the second meteorological information sequence, each backward trajectory information corresponding to each pollutant identification is generated. Thus, each backward trajectory information with high accuracy can be obtained, which can be used to trace the pollution source. Then, according to each backward trajectory information, a pollutant contribution rate set corresponding to each grid identification is generated. Thus, each pollutant contribution rate of each sub-area can be obtained, which can be used to locate the pollution source. Next, the pollution source corresponding to the target environmental monitoring area is obtained. Thus, all the pollution sources in the monitoring area can be obtained, which can be used to locate the pollution source. According to the pollution source subject information set and the pollutant contribution rate set, a target pollution source information set is generated. Thus, each pollution source can be traced back to obtain each pollution source information, which can be used for user viewing. Finally, the associated display device is controlled to display the above-mentioned target pollution source information set. In this way, the information of each pollution source with high accuracy can be displayed, so that it is convenient for users to view it for pollution prevention and control. Also, when tracing the pollution source, the meteorological information can be downscaled multiple times to obtain meteorological information with high precision, thereby improving the accuracy of the traced pollution source information, thereby improving the accuracy of pollution prevention and control and reducing the degree of air pollution.

[0114] Further references Figure 2 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a pollution source information display device, and these device embodiments are Figure 1 Corresponding to the method embodiments shown, the device can be specifically applied to various electronic devices.

[0115] like Figure 2 As shown, the pollution source information display device 200 of some embodiments includes: a first acquisition unit 201, a downscaling unit 202, an input unit 203, a first generation unit 204, a second generation unit 205, a second acquisition unit 206, a third generation unit 207 and a display unit 208. The first acquisition unit 201 is configured to acquire the predicted meteorological field information sequence and grid area information corresponding to the target environmental monitoring area in response to detecting at least one pollutant alarm information corresponding to the target environmental monitoring site, wherein the above-mentioned target environmental monitoring area corresponds to the above-mentioned target environmental monitoring site, and the above-mentioned grid area information includes each grid identifier; the downscaling unit 202 is configured to downscale the above-mentioned predicted meteorological field information sequence to obtain a first meteorological information sequence; the input unit 203 is configured to input the above-mentioned first meteorological information sequence and the above-mentioned predicted meteorological field information sequence into a preset downscaled meteorological information generation model to obtain a second meteorological information sequence, wherein the above-mentioned preset downscaled meteorological information generation model includes a number According to the fusion layer, the first downscaling layer, the second downscaling layer and the output layer; the first generating unit 204 is configured to generate each backward trajectory information corresponding to each pollutant identification according to the above-mentioned second meteorological information sequence; the second generating unit 205 is configured to generate a pollutant contribution rate set corresponding to the above-mentioned each grid identification according to the above-mentioned each backward trajectory information; the second acquiring unit 206 is configured to acquire the main information set of the pollution source corresponding to the above-mentioned target environmental monitoring area; the third generating unit 207 is configured to generate a target pollution source information set according to the above-mentioned pollution source main information set and the above-mentioned pollutant contribution rate set; the display unit 208 is configured to control the associated display device to display the above-mentioned target pollution source information set.

[0116] It is understood that the units described in the device 200 are similar to those described in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the device 200 and the units included therein, and will not be described in detail here.

[0117] Reference below Figure 3, which shows a schematic diagram of the structure of an electronic device 300 suitable for implementing some embodiments of the present disclosure. The electronic devices in some embodiments of the present disclosure may include but are not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0118] like Figure 3 As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 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 the bus 304.

[0119] Typically, the following devices may be connected to the I / O interface 305: input devices 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 308 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 309. The communication devices 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0120] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0121] It should be noted that the computer-readable medium recorded in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. 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 of the above. 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 of the above. In some embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium 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.

[0122] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (Hyper Text 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.

[0123] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device: in response to detecting at least one pollutant alarm information corresponding to the target environmental monitoring site, obtains the predicted meteorological field information sequence and grid area information corresponding to the target environmental monitoring area, wherein the target environmental monitoring area corresponds to the target environmental monitoring site, and the grid area information includes each grid identifier; downscales the predicted meteorological field information sequence to obtain a first meteorological information sequence; inputs the first meteorological information sequence and the predicted meteorological field information sequence into a preset downscaled meteorological information generation model to obtain a second meteorological information sequence, wherein the preset downscaled meteorological information generation model includes a data fusion layer, a first downscale layer, a second downscale layer and an output layer; generates each backward trajectory information corresponding to each pollutant identifier according to the second meteorological information sequence; generates a pollutant contribution rate set corresponding to each grid identifier according to each backward trajectory information; obtains a pollution source subject information set corresponding to the target environmental monitoring area; generates a target pollution source information set according to the pollution source subject information set and the pollutant contribution rate set; and controls an associated display device to display the target pollution source information set.

[0124] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including 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 user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0125] 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 hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0126] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The described units may also be provided in a processor, for example, may be described as: a processor comprising a first acquisition unit, a downscaling unit, an input unit, a first generation unit, a second generation unit, a second acquisition unit, a third generation unit and a display unit. Among them, the names of these units do not constitute a limitation on the unit itself under certain circumstances. For example, the first acquisition unit may also be described as "a unit for acquiring a predicted meteorological field information sequence and grid area information of a corresponding target environmental monitoring area in response to detecting at least one pollutant alarm information of a corresponding target environmental monitoring site".

[0127] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0128] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. A method for displaying pollution source information, include: In response to detecting at least one pollutant warning information corresponding to a target environmental monitoring site, obtaining a forecast meteorological field information sequence and grid area information corresponding to a target environmental monitoring area, wherein the target environmental monitoring area corresponds to the target environmental monitoring site, and the grid area information includes each grid identifier; Downscaling the predicted meteorological field information sequence to obtain a first meteorological information sequence; Inputting the first meteorological information sequence and the predicted meteorological field information sequence into a preset downscaling meteorological information generation model to obtain a second meteorological information sequence, wherein the preset downscaling meteorological information generation model includes a data fusion layer, a first downscaling layer, a second downscaling layer and an output layer; generating, according to the second meteorological information sequence, each backward trajectory information corresponding to each pollutant identifier; Generating a pollutant contribution rate set corresponding to each grid mark according to each backward trajectory information; Obtaining a set of information about the entities that own the pollution sources corresponding to the target environmental monitoring area; Generate a target pollution source information set according to the pollution source subject information set and the pollutant contribution rate set; Control an associated display device to display the target pollution source information set.

2. The method according to claim 1, in, Before acquiring the predicted meteorological field information sequence and grid area information of the corresponding target environmental monitoring area in response to detecting at least one pollutant warning information of the corresponding target environmental monitoring site, the method further includes: For each pollutant identification included in each pollutant identification, perform the following steps: Obtaining a first current pollutant concentration and a second current pollutant concentration corresponding to the pollutant identifier at the target environmental monitoring site; Determining a time corresponding to the first current pollutant concentration as a first monitoring time; Determining a time corresponding to the second current pollutant concentration as a second monitoring time; determining a difference between the second monitoring time and the first monitoring time as a time difference; determining a difference between the first current pollutant concentration and the second current pollutant concentration as a pollutant concentration difference; Determine the ratio of the pollutant concentration difference to the time difference as the concentration change rate; In response to determining that the concentration change rate satisfies a preset concentration change rate condition, pollutant warning information corresponding to the pollutant identification is generated according to the pollutant identification.

3. The method according to claim 1, in, The grid area information also includes the total number of grids, and the predicted meteorological field information in the predicted meteorological field information sequence includes each predicted pollutant concentration corresponding to each pollutant identifier; And generating a pollutant contribution rate set corresponding to each grid mark according to each backward trajectory information includes: For each piece of backward trajectory information included in the respective pieces of backward trajectory information, the following steps are performed: Arranging each predicted pollutant concentration corresponding to the backward trajectory information in the predicted meteorological field information sequence to obtain a predicted pollutant concentration sequence; Determining the average value of each predicted pollutant concentration included in the predicted pollutant concentration sequence as the predicted pollutant concentration average value; For each grid identifier included in the grid area information, determining the number of grid tracks according to the backward track information and the grid identifier; The sum of the numbers of each grid track generated is determined as the total number of pollutant tracks; Determine the number of each generated grid track as a grid track array; In response to determining that the predicted pollutant concentration average value satisfies a preset pollutant concentration condition, determining the total number of pollutant trajectories as a first total number of pollutant trajectories, and determining the grid trajectory array as a first grid trajectory array; In response to determining that the predicted pollutant concentration average value does not satisfy the preset pollutant concentration condition, determining the total number of pollutant trajectories as a second total number of pollutant trajectories, and determining the grid trajectory array as a second grid trajectory array; The sum of the total number of each pollutant trajectory generated is determined as the total number of trajectories; The ratio of the total number of trajectories to the total number of grids is determined as the average number of trajectories; For each grid identifier included in the grid area information, generating a pollutant contribution rate corresponding to the grid identifier according to the average number of trajectories; The determined contribution rates of the various pollutants are determined as a pollutant contribution rate set.

4. The method according to claim 3, in, Generating the pollutant contribution rate corresponding to the grid mark according to the average trajectory number includes: For each generated first grid track array, determining the number of first grid tracks corresponding to the grid identifier in the first grid track array as a first target grid track number; Determine the sum of the determined numbers of first target grid tracks as the total number of first grid tracks; For each generated second grid track array, determining the number of second grid tracks corresponding to the grid identifier in the second grid track array as the second target grid track number; Determine the sum of the determined numbers of the second target grid tracks as the total number of the second grid tracks; Determine the sum of the first total number of grid tracks and the second total number of grid tracks as the total number of grid tracks; Determine the ratio of the total number of grid tracks to the average number of tracks as a grid weight coefficient; Determine a ratio of the total number of the first grid tracks to the total number of the grid tracks as a first pollutant contribution rate; The product of the first pollutant contribution rate and the grid weight coefficient is determined as the pollutant contribution rate.

5. The method according to claim 1, in, The pollution source subject information in the pollution source subject information set includes the subject coordinates; And generating a target pollution source information set according to the pollution source subject information set and the pollutant contribution rate set includes: For each pollution source subject information in the pollution source subject information set, perform the following steps: Determine the subject grid identifier corresponding to the subject information of the pollution source according to the subject coordinates and the respective grid identifiers included in the subject information of the pollution source; Determine the pollutant contribution rate corresponding to the subject grid identifier in the pollutant contribution rate set as the target pollutant contribution rate; Sorting the pollutant contribution rate set to obtain a pollutant contribution rate sequence; According to the pollutant contribution rate sequence, in response to determining that the target pollutant contribution rate meets a preset pollutant contribution rate condition, determining the subject information of the pollution source as the target pollution source information; The determined information of each target pollution source is determined as a target pollution source information set.

6. The method according to claim 1, in, The method further comprises: Obtaining a pollutant emission information set of a corresponding entity to the information set of the pollution source; Generate a subject identification set of the target pollution source according to the subject emission pollutant information set and the at least one pollutant warning information; For each target pollution source entity identification included in the target pollution source entity identification set, preset pollution emission warning information is sent to the pollution source entity terminal corresponding to the target pollution source entity identification.

7. The method according to claim 5, in, The controlling the associated display device to display the target pollution source information set includes: Controlling an associated display device to display a regional map corresponding to the target environment monitoring area; For each target pollution source information included in the target pollution source information set, the following steps are performed: Determine the target pollutant contribution rate corresponding to the target pollution source information as the first pollutant contribution rate; Determine the preset subject display style information corresponding to the first pollutant contribution rate as the subject display style information corresponding to the target pollution source information; Determine the preset subject position information corresponding to the subject coordinates included in the target pollution source information as the subject display position information, wherein the preset subject position information is the information of the position of the pollution source subject on the regional map; At a location on the regional map corresponding to the belonging entity display position information, a belonging entity identification control is displayed according to the belonging entity identification display style information.

8. A pollution source information display device, include: A first acquisition unit is configured to acquire, in response to detecting at least one pollutant warning information corresponding to a target environmental monitoring site, a predicted meteorological field information sequence and grid area information corresponding to a target environmental monitoring area, wherein the target environmental monitoring area corresponds to the target environmental monitoring site, and the grid area information includes each grid identifier; A downscaling unit is configured to perform downscaling processing on the predicted meteorological field information sequence to obtain a first meteorological information sequence; An input unit is configured to input the first meteorological information sequence and the predicted meteorological field information sequence into a preset downscaling meteorological information generation model to obtain a second meteorological information sequence, wherein the preset downscaling meteorological information generation model includes a data fusion layer, a first downscaling layer, a second downscaling layer and an output layer; A first generating unit is configured to generate each backward trajectory information corresponding to each pollutant identifier according to the second meteorological information sequence; A second generating unit is configured to generate a pollutant contribution rate set corresponding to each grid mark according to each backward trajectory information; A second acquisition unit is configured to acquire a set of information about entities to which pollution sources corresponding to the target environmental monitoring area belong; A third generating unit is configured to generate a target pollution source information set according to the pollution source subject information set and the pollutant contribution rate set; The display unit is configured to control an associated display device to display the target pollution source information set.

9. An electronic device, include: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer readable medium having a computer program stored thereon, in, When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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