CN116757555B - Method, device, electronic equipment and storage medium for determining pollution characteristic type - Google Patents
Method, device, electronic equipment and storage medium for determining pollution characteristic type Download PDFInfo
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Abstract
The application provides a method, a device, electronic equipment and a storage medium for determining pollution characteristic types, and belongs to the field of environmental science. The method comprises the following steps: determining an air quality index of each time within a target time period; counting the air quality index, and determining a statistic value of the air quality index of the target time period, wherein the statistic value comprises a mean value, an upper limit value and/or a lower limit value; determining an air quality index of any time to be analyzed in the target time period; and determining the target pollution characteristic type of the time to be analyzed based on the air quality index of the time to be analyzed and the statistic value. By adopting the application, the application range of determining the pollution characteristic type can be improved.
Description
Technical Field
The present application relates to the field of environmental science, and in particular, to a method, an apparatus, an electronic device, and a storage medium for determining a type of a contamination feature.
Background
PM is the conventional air quality monitoring index 2.5 、PM 10 、SO 2 、O 3 、NO 2 And when the air pollution occurs, the CO 6 pollutants judge the pollution characteristics through 6 pollutant concentration values, so that a pollution source is deduced, and support is provided for pollution emission reduction and control.
At present, in the process of judging pollution characteristics, the pollutant concentration value is generally subjected to normalization treatment, the pollution characteristics are analyzed through the normalized pollutant concentration value, and the dominant factor of pollution is determined. However, the concentration values of various pollutants are normalized respectively, SO that the characteristic value of the pollution at a specific time is greatly affected by the distribution condition of the sample data values, and the characteristic values of the pollution among different pollutants cannot be compared, for example, the concentration value of CO is 3 mg/cubic meter at a single moment, the concentration values at other moments are small and approach 0, and SO is not available 2 Concentration values at all moments are concentrated near 1000 micrograms/cubic meter, and the pollution characteristic value CO calculated according to concentration normalization is larger than SO 2 CO is the dominant factor in the determination of pollution characteristics, but at this point in time, the pollution level corresponding to CO is good and SO 2 The contamination level is already heavily contaminated.
It follows that methods for determining contamination characteristics based on normalized contaminant concentration values have limitations.
Disclosure of Invention
In order to solve the problems in the prior art, the embodiment of the application provides a method, a device, electronic equipment and a storage medium for determining a pollution characteristic type, which can improve the application range for determining the pollution characteristic type. The technical proposal is as follows:
According to an aspect of the present application there is provided a method of determining a type of contamination feature, the method comprising:
determining an air quality index of each time within a target time period;
counting the air quality index, and determining a statistic value of the air quality index of the target time period, wherein the statistic value comprises a mean value, an upper limit value and/or a lower limit value;
determining an air quality index of any time to be analyzed in the target time period;
and determining the target pollution characteristic type of the time to be analyzed based on the air quality index of the time to be analyzed and the statistic value.
Optionally, the determining the air quality index of each time within the target time period includes:
acquiring concentration sample data of a plurality of pollutants at each time within the target time period;
and calculating the concentration sample data according to an air quality index calculation mode, and respectively determining the air quality index of each pollutant in each time.
Optionally, the contaminants include ozone;
acquiring concentration sample data of ozone at each time within the target time period, comprising:
acquiring initial ozone concentrations of all generation moments generated by the air quality monitoring instrument in each time within the target time period;
For each generation time, acquiring the initial ozone concentration of a preset time before the generation time and obtaining a mean value to be used as the current ozone concentration of the generation time;
for each time in the target time period, the current ozone concentration in the time is averaged to be used as the concentration sample data of the ozone in the time.
Optionally, the counting the air quality index to determine the statistics of the air quality index of the target time period includes:
the following statistical treatments were performed separately for each contaminant:
averaging the air quality index of the pollutants at each time, and determining the average value of the air quality index of the pollutants in the target time period; and/or
Sequencing the air quality index of the pollutants at each time to obtain an air quality index at a first position after sequencing, wherein the air quality index is used as the upper limit value of the air quality index of the pollutants in the target time period; and/or, acquiring the air quality index at the second position after sequencing as a lower limit value of the air quality index of the pollutants in the target time period.
Optionally, the determining the target pollution characteristic type of the time to be analyzed based on the air quality index of the time to be analyzed and the statistical value includes:
determining a judging strategy of each pollution characteristic type, wherein the judging strategy comprises a preset relation between an air quality index and a statistic value in the pollution characteristic type;
and in the judging strategy of each pollution characteristic type, determining a target preset relation which is met by the air quality index and the statistic value of the time to be analyzed, and taking the corresponding pollution characteristic type as the target pollution characteristic type of the time to be analyzed.
Optionally, the pollution characteristic type has a correlation with the air quality index, including a meteorological pollution characteristic type and an emission pollution characteristic type.
Optionally, the pollution characteristic types of the meteorological type at least comprise a stable type and a small wind type, and the pollution characteristic types of the emission type at least comprise a dust type, a compound pollution type, a photochemical pollution type, a partial industrial type and a partial motor vehicle type;
the stationary type judgment strategy comprises the following steps: the air mass fraction index of each contaminant is greater than the upper limit of the air mass fraction index of the contaminant;
The small wind type judging strategy comprises the following steps: the air mass fraction index of each contaminant is greater than the average of the air mass fraction indexes of the contaminants;
the dust type judging strategy comprises the following steps: the only thing is: PM (particulate matter) 10 Is greater than PM 10 Upper limit value of air mass index of (2), and PM 2.5 With PM 10 Air of (2)The mass fraction index ratio is smaller than a preset threshold value;
the determination strategy of the composite pollution type comprises the following steps: PM (particulate matter) 2.5 Is greater than PM 2.5 Upper limit value of air mass index of (2), and O 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
the photochemical pollution type judgment strategy comprises the following steps: o (O) 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
the determination strategy of the partial industry type comprises the following steps: the only thing is: SO (SO) 2 Is greater than SO 2 Upper limit value of air mass index of (2), and NO 2 Is greater than NO 2 The air mass index of CO is greater than the upper limit value of the air mass index of CO;
the judgment strategy of the partial motor vehicle type comprises the following steps: the only thing is: NO (NO) 2 Is greater than NO 2 And the air mass fraction index of CO is greater than the upper limit of the air mass fraction index of CO.
Optionally, the method further comprises:
drawing a pollution characteristic diagram of the time to be analyzed based on the air quality index of the time to be analyzed and the statistic value, wherein the pollution characteristic diagram is used for indicating the primary pollutant of the time to be analyzed and the relative relation between the air quality index of the time to be analyzed and the statistic value;
the pollution characteristic map comprises a statistical value radar map and an air quality index rose map under the same polar coordinate system.
According to another aspect of the present application there is provided an apparatus for determining a type of contamination feature, the apparatus comprising:
the first determining module is used for determining an air quality index of each time within a target time period;
the statistics module is used for carrying out statistics on the air quality index and determining a statistics value of the air quality index of the target time period, wherein the statistics value comprises a mean value, an upper limit value and/or a lower limit value;
the second determining module is used for determining an air quality index of any time to be analyzed in the target time period;
and the judging module is used for determining the target pollution characteristic type of the time to be analyzed based on the air quality index of the time to be analyzed and the statistic value.
Optionally, the first determining module is configured to:
acquiring concentration sample data of a plurality of pollutants at each time within the target time period;
and calculating the concentration sample data according to an air quality index calculation mode, and respectively determining the air quality index of each pollutant in each time.
Optionally, the contaminants include ozone;
the first determining module is configured to:
acquiring initial ozone concentrations of all generation moments generated by the air quality monitoring instrument in each time within the target time period;
for each generation time, acquiring the initial ozone concentration of a preset time before the generation time and obtaining a mean value to be used as the current ozone concentration of the generation time;
for each time in the target time period, the current ozone concentration in the time is averaged to be used as the concentration sample data of the ozone in the time.
Optionally, the statistics module is configured to:
the following statistical treatments were performed separately for each contaminant:
averaging the air quality index of the pollutants at each time, and determining the average value of the air quality index of the pollutants in the target time period; and/or
Sequencing the air quality index of the pollutants at each time to obtain an air quality index at a first position after sequencing, wherein the air quality index is used as the upper limit value of the air quality index of the pollutants in the target time period; and/or, acquiring the air quality index at the second position after sequencing as a lower limit value of the air quality index of the pollutants in the target time period.
Optionally, the determining module is configured to:
determining a judging strategy of each pollution characteristic type, wherein the judging strategy comprises a preset relation between an air quality index and a statistic value in the pollution characteristic type;
and in the judging strategy of each pollution characteristic type, determining a target preset relation which is met by the air quality index and the statistic value of the time to be analyzed, and taking the corresponding pollution characteristic type as the target pollution characteristic type of the time to be analyzed.
Optionally, the pollution characteristic type has a correlation with the air quality index, including a meteorological pollution characteristic type and an emission pollution characteristic type.
Optionally, the pollution characteristic types of the meteorological type at least comprise a stable type and a small wind type, and the pollution characteristic types of the emission type at least comprise a dust type, a compound pollution type, a photochemical pollution type, a partial industrial type and a partial motor vehicle type;
The stationary type judgment strategy comprises the following steps: the air mass fraction index of each contaminant is greater than the upper limit of the air mass fraction index of the contaminant;
the small wind type judging strategy comprises the following steps: the air mass fraction index of each contaminant is greater than the average of the air mass fraction indexes of the contaminants;
the dust type judging strategy comprises the following steps: the only thing is: PM (particulate matter) 10 Is greater than PM 10 Upper limit value of air mass index of (2), and PM 2.5 With PM 10 The air mass fraction index ratio of (2) is smaller than a preset threshold value;
the determination strategy of the composite pollution type comprises the following steps: PM (particulate matter) 2.5 Is greater than PM 2.5 Upper limit value of air mass index of (2), and O 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
the photochemical pollution type judgment strategy comprises the following steps: o (O) 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
the determination strategy of the partial industry type comprises the following steps: the only thing is: SO (SO) 2 Is greater than SO 2 Upper limit value of air mass index of (2), and NO 2 Is greater than NO 2 The air mass index of CO is greater than the upper limit value of the air mass index of CO;
The judgment strategy of the partial motor vehicle type comprises the following steps: the only thing is: NO (NO) 2 Is greater than NO 2 And the air mass fraction index of CO is greater than the upper limit of the air mass fraction index of CO.
Optionally, the device further includes a drawing module, where the drawing module is configured to:
drawing a pollution characteristic diagram of the time to be analyzed based on the air quality index of the time to be analyzed and the statistic value, wherein the pollution characteristic diagram is used for indicating the primary pollutant of the time to be analyzed and the relative relation between the air quality index of the time to be analyzed and the statistic value;
the pollution characteristic map comprises a statistical value radar map and an air quality index rose map under the same polar coordinate system.
According to another aspect of the present application, there is provided an electronic apparatus including:
a processor; and
a memory in which a program is stored,
wherein the program comprises instructions which, when executed by the processor, cause the processor to perform the above-described method of determining a contamination feature type.
According to another aspect of the present application there is provided a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the above method of determining a contamination feature type.
In the application, each time the pollution characteristic type needs to be analyzed for a target time period, the air quality index of each time is determined, the average value, the upper limit value and the lower limit value in the target time period are obtained through statistics, and then the air quality index of the time to be analyzed is compared with the statistics value to determine the target pollution characteristic type of the time to be analyzed. The pollutant concentration is converted into the air quality index for analysis, the air quality index can represent the air quality pollution level, and the air quality pollution levels of different pollutants can be compared, so that the dominant factor of pollution is determined, the national environmental air quality evaluation standard specification is met, and the application range is widened.
Drawings
Further details, features and advantages of the application are disclosed in the following description of exemplary embodiments with reference to the following drawings, in which:
FIG. 1 illustrates a flow chart of a method of determining a type of contamination feature provided in accordance with an exemplary embodiment of the present application;
FIG. 2 illustrates a concentration sample data schematic provided in accordance with an exemplary embodiment of the present application;
FIG. 3 illustrates a schematic diagram of air mass fraction indices for various contaminants provided in accordance with an exemplary embodiment of the application;
FIG. 4 shows a pollution signature pictorial intent provided in accordance with an exemplary embodiment of the present application;
FIG. 5 illustrates a schematic block diagram of an apparatus for determining a type of contamination feature provided in accordance with an exemplary embodiment of the present application;
fig. 6 shows a block diagram of an exemplary electronic device that can be used to implement an embodiment of the application.
Detailed Description
Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. While the application is susceptible of embodiment in the drawings, it is to be understood that the application may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided to provide a more thorough and complete understanding of the application. It should be understood that the drawings and embodiments of the application are for illustration purposes only and are not intended to limit the scope of the present application.
It should be understood that the various steps recited in the method embodiments of the present application may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the application is not limited in this respect.
The term "including" and variations thereof as used herein are intended to be open-ended, i.e., including, but not limited to. The term "based on" is based at least in part on. The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments. Related definitions of other terms will be given in the description below. It should be noted that the terms "first," "second," and the like herein are merely used for distinguishing between different devices, modules, or units and not for limiting the order or interdependence of the functions performed by such devices, modules, or units.
It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those skilled in the art will appreciate that "one or more" is intended to be construed as "one or more" unless the context clearly indicates otherwise.
The names of messages or information interacted between the devices in the embodiments of the present application are for illustrative purposes only and are not intended to limit the scope of such messages or information.
The present application provides a method for determining a type of contamination feature, which may be performed by a terminal, a server, and/or other processing-capable devices. The method provided by the embodiment of the application can be completed by any device or can be completed by a plurality of devices together.
The method of determining the type of contamination feature will be described with reference to the flowchart of the method shown in fig. 1. As shown in fig. 1, the method includes the following steps 101-104.
Step 101, determining an air quality index of each time within a target time period.
In one possible implementation, the air quality index for each time (e.g., daily) may be calculated whenever it is desired to analyze the pollution signature for a target time period for any area (e.g., a city). As an example, if it is desired to analyze pollution characteristics of 1 to 10 days 1 month 2020, the air mass fraction index of 1 to 10 days each may be calculated.
Specifically, the process of step 101 may be as follows:
acquiring concentration sample data of various pollutants at each time within a target time period;
and calculating the concentration sample data according to an air quality index calculation mode, and respectively determining the air quality index of each pollutant in each time.
The analysis index of the pollution characteristic can comprise the following pollutants: PM (particulate matter) 2.5 、PM 10 、SO 2 、NO 2 、O 3 、CO。
In one possible embodiment, air quality data for the area may be generated by an air quality monitoring instrument, which may include measured contaminant concentrations for each of the above-described contaminants at each of the generation times. Further, the air quality data may be subjected to quality control and processing to generate a mean value of the pollutant concentration (for example, a daily average concentration value) of each pollutant, and may be pushed to a database or a file directory designated by the server for storage. In analyzing the contamination characteristics of the target time period, the contaminant concentration average value of each contaminant at each time in the target time period may be obtained from the database or the file catalog as concentration sample data. As shown in the concentration sample data schematic of fig. 2, the concentration sample data of 1 to 10 days of 1 month 2020 may include a mean value of the pollutant concentration of each pollutant per day.
In another possible embodiment, the simulated contaminant concentrations for each contaminant in the region at each time (i.e., the time of generation) may also be generated by an air quality prediction mode. Furthermore, the simulated pollutant concentration can be subjected to quality control and processing treatment to generate a pollutant concentration mean value of each pollutant, and the pollutant concentration mean value is stored in a database or a file catalog corresponding to the air quality forecasting mode. In analyzing the contamination characteristics of the target time period, the contaminant concentration average value of each contaminant at each time in the target time period may be obtained from the database or the file catalog as concentration sample data.
Alternatively, because ozone is strongly correlated with insolation, the variation in one day is large, and it is difficult to analyze the pollution characteristics based on the concentration of ozone at a single moment. Therefore, the present embodiment calculates in a sliding average manner when generating the current ozone concentration. Accordingly, the concentration sample data of ozone can be obtained based on the following manner:
acquiring initial ozone concentration at each generation time in each time within the target time period;
for each generation time, acquiring the initial ozone concentration of a preset time before the generation time and calculating an average value to be used as the current ozone concentration of the generation time;
For each time in the target time period, the current ozone concentration in the time is averaged to be used as the concentration sample data of the ozone in the time.
As an example, the data generated by the air quality monitoring instrument may be initial ozone concentrations at time points of 2020, 1 month, 1 day, 00, 01, … …, 23, 2020, 1 month, 2 day, 00, 01, … …, 23, etc. Taking the example of 2020, 1 month and 2 days 00, the average value of the initial ozone concentration 8 hours before it, that is, the average value of the initial ozone concentrations 16, 17, … … and 23 on 2020, can be taken as the current ozone concentration on 2020, 1 month and 2 days 00. After obtaining the current ozone concentration at each time, the current ozone concentration at each time of day 00 to 23 can be averaged as the daily ozone concentration sample data.
After obtaining the above concentration sample data over the target period, the air quality index (IAQI) for each contaminant at a different time over the target period may be calculated separately. The specific air quality index calculation method may refer to the relevant regulations in the standard of the environmental Air Quality Index (AQI) technical regulation, which will not be described in detail in this embodiment. The air mass index of each contaminant is shown in figure 3.
And 102, counting the air quality index, and determining the statistic value of the air quality index in the target time period.
Wherein the statistics comprise a mean, an upper limit, and/or a lower limit.
Specifically, the following statistical treatments may be performed separately for each contaminant:
averaging the air mass fraction indexes of the pollutants at each time, and determining the average value of the air mass fraction indexes of the pollutants in a target time period; and/or
Sequencing the air quality index of the pollutants at each time, and acquiring the air quality index at the first position after sequencing as the upper limit value of the air quality index of the pollutants in the target time period; and/or, acquiring the air quality index at the second position after sequencing as a lower limit value of the air quality index of the pollutants in the target time period.
The first position and the second position may be preset, and the specific position is not limited in this embodiment, for example, may be 3/4 or 1/4, or may be 4/5 or 1/5.
With SO in FIG. 3 2 For example, the mean value of the air mass fraction index of 1 to 10 days 1 month in 2020 was calculated to obtain 25.7. The air mass index of 1 month 1 day to 10 days in 2020 is ranked from small to large, the air mass index 38 at the 4/5 position is taken as an upper limit value, and the air mass index 18 at the 1/5 position is taken as a lower limit value.
The statistics of the remaining contaminants are similarly calculated, and this example is not listed.
And step 103, determining the air quality index of any time to be analyzed in the target time period.
In one possible implementation, if analysis of the pollution characteristics at a time in the target time period is required, the air quality index at that time may be obtained. If the air mass index at that time is not calculated in the above-described process, the air mass index at that time can be calculated in the same manner as described above.
It should be noted that, the time to be analyzed is generally any time in the target time period, and based on this, the distribution condition of the air mass fraction index of the time in the target time period can be analyzed, so as to reflect the distribution condition of each pollutant in the target time period at this time.
And 104, determining the target pollution characteristic type of the time to be analyzed based on the air quality index and the statistic value of the time to be analyzed.
In one possible implementation manner, the relative relation between the air quality index of the time to be analyzed and the statistical value can be analyzed, so that the corresponding pollutant characteristics are determined according to the relative relation, and the target pollution characteristic type of the time to be analyzed is judged.
Alternatively, the processing of step 104 may be as follows:
determining a judging strategy of each pollution characteristic type, wherein the judging strategy comprises a preset relation between an air quality index and a statistic value in the pollution characteristic type;
in the judging strategy of each pollution characteristic type, determining a target preset relation which is satisfied by the air quality index and the statistic value of the time to be analyzed, and taking the corresponding pollution characteristic type as the target pollution characteristic type of the time to be analyzed.
In one possible implementation, historical pollution data for known pollution signature types may be obtained in advance and corresponding air quality index and statistics calculated. For each pollution characteristic type, the relative relationship between the air quality index and the statistics may be analyzed and summarized, such that the relative relationship is stored as a decision strategy for that pollution characteristic type. That is, if the air mass fraction index and the statistics at a certain time satisfy the relative relationship, the pollutant distribution at that time can be considered to conform to the pollution characteristic type.
Optionally, considering the difficulty of analyzing and summarizing the above relative relationship and the accuracy of the pollution characteristic type determined by the relative relationship, that is, the lower the correlation between the pollution characteristic type and the air quality index is, the higher the analysis difficulty is, and the lower the accuracy of the pollution characteristic type is determined based on the relative relationship. Therefore, the pollution characteristic type to be determined in the present embodiment has a correlation with the air quality index, and includes the pollution characteristic type of the weather type and the pollution characteristic type of the emission type. On this basis, since the pollution characteristic types of the meteorological type and the emission type can be determined simultaneously, the pollution characteristic types to be determined in the embodiment are more abundant. And because the pollution characteristic type and the air quality index have higher relativity, the summarized judgment strategy is more representative, and the accuracy of judging the pollution characteristic type is improved.
Alternatively, the types of pollution characteristics of the meteorological type can at least comprise a stable type and a small wind type, and the types of pollution characteristics of the emission type can at least comprise a dust type, a compound pollution type, a photochemical pollution type, a partial industry type and a partial motor vehicle type.
The decision strategy of the stationarity comprises the following steps: the air mass fraction index of each contaminant is greater than the upper limit of the air mass fraction index of the contaminant;
the judgment strategy of the breeze type comprises the following steps: the air mass fraction index of each contaminant is greater than the average of the air mass fraction indexes of the contaminants;
the dust-type determination strategy comprises the following steps: the only thing is: PM (particulate matter) 10 Is greater than PM 10 Upper limit value of air mass index of (2), and PM 2.5 With PM 10 The air mass fraction index ratio of (2) is smaller than a preset threshold value;
the determination strategy of the composite pollution type comprises the following steps: PM (particulate matter) 2.5 Is greater than PM 2.5 Upper limit value of air mass index of (2), and O 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
photochemical reactionThe determination strategy of the chemical pollution comprises the following steps: o (O) 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
the determination strategies for the partial industry include: the only thing is: SO (SO) 2 Is greater than SO 2 Upper limit value of air mass index of (2), and NO 2 Is greater than NO 2 The air mass index of CO is greater than the upper limit value of the air mass index of CO;
the judgment strategy of the partial motor vehicle type comprises the following steps: the only thing is: NO (NO) 2 Is greater than NO 2 And the air mass fraction index of CO is greater than the upper limit of the air mass fraction index of CO.
The steady middle weather is the main cause of pollution, and under the condition that the emission is approximately unchanged, all pollutants are obviously accumulated; the diffusion condition is poor in the small wind type, and all pollutants are beyond the average value; the dust is obviously affected by the dust process; the atmospheric oxidizing property in the composite pollution type is stronger, and the secondary generation of the particulate matters is stronger; the photochemical pollution type medium-day air is clear, the temperature is high, the illumination condition is good, and the emission of VOCs is high; industrial emissions dominate in the industry; the emission characteristics of the motor vehicle are remarkable in the eccentric motor vehicle type.
In one possible implementation manner, the above determination strategies may be traversed, whether the air quality index and the statistic value of the time to be analyzed meet a preset relative relationship is determined, and if yes, the pollution characteristic type corresponding to the determination strategy is used as the target pollution characteristic type of the time to be analyzed; if not, the next decision strategy is judged until the target pollution characteristic type is determined or the traversal is finished. If none of the above determination strategies is satisfied, the target pollution characteristic type of the time to be analyzed may be determined as other types.
Alternatively, a pollution profile may be plotted by a polar coordinate system, which may be used to indicate the primary pollutant for the time to be analyzed, as well as the relative relationship of the air mass fraction index and the statistics for the time to be analyzed. The corresponding process may be as follows: and drawing a pollution characteristic map of the time to be analyzed based on the air quality index and the statistic value of the time to be analyzed, wherein the pollution characteristic map comprises a statistic value radar map and an air quality index rose map under the same polar coordinate system.
The primary pollutant refers to the pollutant with the air quality index being the maximum value and being larger than the set threshold value.
In one possible embodiment, referring to the pollution signature graphical illustration shown in fig. 4, different angular ranges in the polar coordinate system represent different pollutants, and the polar diameters represent the air mass fraction index or the above-mentioned statistics (i.e., mean, upper limit, or lower limit). The 6 contaminants were uniformly disposed over each angular range of the polar coordinate system.
The statistical value radar map refers to an image partially illustrated by a broken line as shown in fig. 4, in which a first broken line near a polar point of the polar coordinate system represents a lower limit value radar map, a second broken line represents a mean value radar map, and a third broken line represents an upper limit value radar map. Each vertex of the radar chart represents a statistic of the corresponding air mass index of the contaminant.
The air mass fraction index rose refers to an image as illustrated by the hatched portion shown in fig. 4, in which the polar path length of the sector corresponding to any one contaminant represents the air mass fraction index of that contaminant over the time to be analyzed.
Therefore, the relative relation between the primary pollutant and the air quality index and the statistic value of the time to be analyzed can be intuitively displayed through the pollution characteristic diagram, so that a user can quickly acquire the information of the primary pollutant and the relative relation.
For example, PM in FIG. 4 2.5 The PM can be considered to be that the length of the polar diameter of the sector of (a) is the largest and is larger than 50 2.5 Is the first pollutant on the same day; the length of the polar diameter of the sector of each pollutant exceeds the third dotted line (namely the upper limit radar chart) far away from the polar coordinate system pole, and accords with the stationary pollution characteristic. The user can quickly acquire the information from the pollution characteristic diagram.
The embodiment of the application can obtain the following technical effects:
and determining the air quality index of each time when the pollution characteristic type needs to be analyzed in the target time period, counting to obtain the average value, the upper limit value and the lower limit value in the target time period, and comparing the air quality index of the time to be analyzed with the statistic value to determine the target pollution characteristic type of the time to be analyzed. The pollutant concentration is converted into the air quality index for analysis, the air quality index can represent the air quality pollution level, and the air quality pollution levels of different pollutants can be compared, so that the dominant factor of pollution is determined, the national environmental air quality evaluation standard specification is met, and the application range is widened.
The embodiment of the application provides a device for determining the type of a pollution characteristic, which is used for realizing the method for determining the type of the pollution characteristic. As shown in the schematic block diagram of the apparatus for determining a type of contamination feature of fig. 5, the apparatus 500 for determining a type of contamination feature includes: a first determining module 501, a statistics module 502, a second determining module 503, and a decision module 504.
A first determining module 501 configured to determine an air quality index for each time within a target time period;
a statistics module 502, configured to perform statistics on the air quality index, and determine a statistics value of the air quality index in the target period, where the statistics value includes a mean value, an upper limit value, and/or a lower limit value;
a second determining module 503, configured to determine an air quality index of any time to be analyzed in the target time period;
a determining module 504, configured to determine a target pollution characteristic type of the time to be analyzed based on the air quality index of the time to be analyzed and the statistics.
Optionally, the first determining module 501 is configured to:
acquiring concentration sample data of a plurality of pollutants at each time within the target time period;
And calculating the concentration sample data according to an air quality index calculation mode, and respectively determining the air quality index of each pollutant in each time.
Optionally, the contaminants include ozone;
the first determining module 501 is configured to:
acquiring initial ozone concentrations at each generation time in each time within the target time period;
for each generation time, acquiring the initial ozone concentration of a preset time before the generation time and obtaining a mean value to be used as the current ozone concentration of the generation time;
for each time in the target time period, the current ozone concentration in the time is averaged to be used as the concentration sample data of the ozone in the time.
Optionally, the statistics module 502 is configured to:
the following statistical treatments were performed separately for each contaminant:
averaging the air quality index of the pollutants at each time, and determining the average value of the air quality index of the pollutants in the target time period; and/or
Sequencing the air quality index of the pollutants at each time to obtain an air quality index at a first position after sequencing, wherein the air quality index is used as the upper limit value of the air quality index of the pollutants in the target time period; and/or, acquiring the air quality index at the second position after sequencing as a lower limit value of the air quality index of the pollutants in the target time period.
Optionally, the determining module 504 is configured to:
determining a judging strategy of each pollution characteristic type, wherein the judging strategy comprises a preset relation between an air quality index and a statistic value in the pollution characteristic type;
and in the judging strategy of each pollution characteristic type, determining a target preset relation which is met by the air quality index and the statistic value of the time to be analyzed, and taking the corresponding pollution characteristic type as the target pollution characteristic type of the time to be analyzed.
Optionally, the pollution characteristic type has a correlation with the air quality index, including a meteorological pollution characteristic type and an emission pollution characteristic type.
Optionally, the pollution characteristic types of the meteorological type at least comprise a stable type and a small wind type, and the pollution characteristic types of the emission type at least comprise a dust type, a compound pollution type, a photochemical pollution type, a partial industrial type and a partial motor vehicle type;
the stationary type judgment strategy comprises the following steps: the air mass fraction index of each contaminant is greater than the upper limit of the air mass fraction index of the contaminant;
the small wind type judging strategy comprises the following steps: the air mass fraction index of each contaminant is greater than the average of the air mass fraction indexes of the contaminants;
The dust type judging strategy comprises the following steps: the only thing is: PM (particulate matter) 10 Is greater than PM 10 Upper limit value of air mass index of (2), and PM 2.5 With PM 10 The air mass fraction index ratio of (2) is smaller than a preset threshold value;
the determination strategy of the composite pollution type comprises the following steps: PM (particulate matter) 2.5 Is greater than PM 2.5 Upper limit value of air mass index of (2), and O 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
the photochemical pollution type judgment strategy comprises the following steps: o (O) 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
the determination strategy of the partial industry type comprises the following steps: the only thing is: SO (SO) 2 Is greater than SO 2 Upper limit value of air mass index of (2), and NO 2 Is greater than NO 2 The air mass index of CO is greater than the upper limit value of the air mass index of CO;
the judgment strategy of the partial motor vehicle type comprises the following steps: the only thing is: NO (NO) 2 Is of the air quality of (1)The quantitative index is greater than NO 2 And the air mass fraction index of CO is greater than the upper limit of the air mass fraction index of CO.
Optionally, the device further includes a drawing module, where the drawing module is configured to:
Drawing a pollution characteristic diagram of the time to be analyzed based on the air quality index of the time to be analyzed and the statistic value, wherein the pollution characteristic diagram is used for indicating the primary pollutant of the time to be analyzed and the relative relation between the air quality index of the time to be analyzed and the statistic value;
the pollution characteristic map comprises a statistical value radar map and an air quality index rose map under the same polar coordinate system.
The embodiment of the application can obtain the following technical effects:
and determining the air quality index of each time when the pollution characteristic type needs to be analyzed in the target time period, counting to obtain the average value, the upper limit value and the lower limit value in the target time period, and comparing the air quality index of the time to be analyzed with the statistic value to determine the target pollution characteristic type of the time to be analyzed. The pollutant concentration is converted into the air quality index for analysis, the air quality index can represent the air quality pollution level, and the air quality pollution levels of different pollutants can be compared, so that the dominant factor of pollution is determined, the national environmental air quality evaluation standard specification is met, and the application range is widened.
The exemplary embodiment of the application also provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor. The memory stores a computer program executable by the at least one processor for causing the electronic device to perform a method according to an embodiment of the application when executed by the at least one processor.
The exemplary embodiments of the present application also provide a non-transitory computer readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is for causing the computer to perform a method according to an embodiment of the present application.
The exemplary embodiments of the application also provide a computer program product comprising a computer program, wherein the computer program, when being executed by a processor of a computer, is for causing the computer to perform a method according to an embodiment of the application.
Referring to fig. 6, a block diagram of an electronic device 600 that may be a server or a client of the present application will now be described, which is an example of a hardware device that may be applied to aspects of the present application. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the applications described and/or claimed herein.
As shown in fig. 6, the electronic device 600 includes a computing unit 601 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 may also be stored. The computing unit 601, ROM 602, and RAM 603 are connected to each other by a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
A number of components in the electronic device 600 are connected to the I/O interface 605, including: an input unit 606, an output unit 607, a storage unit 608, and a communication unit 609. The input unit 606 may be any type of device capable of inputting information to the electronic device 600, and the input unit 606 may receive input numeric or character information and generate key signal inputs related to user settings and/or function controls of the electronic device. The output unit 607 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, video/audio output terminals, vibrators, and/or printers. Storage unit 608 may include, but is not limited to, magnetic disks, optical disks. The communication unit 609 allows the electronic device 600 to exchange information/data with other devices through a computer network, such as the internet, and/or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth devices, wiFi devices, wiMax devices, cellular communication devices, and/or the like.
The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above. For example, in some embodiments, the method of determining the type of contamination feature may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 600 via the ROM 602 and/or the communication unit 609. In some embodiments, the computing unit 601 may be configured to perform the method of determining the contamination feature type by any other suitable means (e.g., by means of firmware).
Program code for carrying out methods of the present application may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present application, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
Claims (8)
1. A method of determining a type of contamination feature, the method comprising:
determining an air quality index of each time within a target time period;
counting the air quality index, and determining a statistic value of the air quality index of the target time period, wherein the statistic value comprises a mean value, an upper limit value and/or a lower limit value;
determining an air quality index of any time to be analyzed in the target time period;
determining a target pollution characteristic type of the time to be analyzed based on the air quality index of the time to be analyzed and the statistic value;
the determining the target pollution characteristic type of the time to be analyzed based on the air quality index of the time to be analyzed and the statistic value comprises the following steps:
determining a judging strategy of each pollution characteristic type, wherein the judging strategy comprises a preset relation between an air quality index and a statistic value in the pollution characteristic type;
In the judging strategy of each pollution characteristic type, determining a target preset relation which is met by the air quality index and the statistic value of the time to be analyzed, and taking the corresponding pollution characteristic type as the target pollution characteristic type of the time to be analyzed;
the pollution characteristic type has correlation with the air quality index, and comprises a meteorological pollution characteristic type and an emission pollution characteristic type;
the pollution characteristic types of the meteorological type at least comprise a stationary type and a small wind type, and the pollution characteristic types of the emission type at least comprise a dust type, a compound pollution type, a photochemical pollution type, a partial industry type and a partial motor vehicle type;
the stationary type judgment strategy comprises the following steps: the air mass fraction index of each contaminant is greater than the upper limit of the air mass fraction index of the contaminant;
the small wind type judging strategy comprises the following steps: the air mass fraction index of each contaminant is greater than the average of the air mass fraction indexes of the contaminants;
the dust type judging strategy comprises the following steps: the only thing is: PM (particulate matter) 10 Is greater than PM 10 Upper limit value of air mass index of (2), and PM 2.5 With PM 10 The air mass fraction index ratio of (2) is smaller than a preset threshold value;
The determination strategy of the composite pollution type comprises the following steps: PM (particulate matter) 2.5 Is greater than PM 2.5 Upper limit value of air mass index of (2), and O 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
the photochemical pollution type judgment strategy comprises the following steps: o (O) 3 Air quality of (2)Index of division greater than O 3 An upper limit value of the air mass fraction index of (2);
the determination strategy of the partial industry type comprises the following steps: the only thing is: SO (SO) 2 Is greater than SO 2 Upper limit value of air mass index of (2), and NO 2 Is greater than NO 2 The air mass index of CO is greater than the upper limit value of the air mass index of CO;
the judgment strategy of the partial motor vehicle type comprises the following steps: the only thing is: NO (NO) 2 Is greater than NO 2 And the air mass fraction index of CO is greater than the upper limit of the air mass fraction index of CO.
2. The method of claim 1, wherein determining the air mass fraction index for each time during the target time period comprises:
acquiring concentration sample data of a plurality of pollutants at each time within the target time period;
And calculating the concentration sample data according to an air quality index calculation mode, and respectively determining the air quality index of each pollutant in each time.
3. The method of claim 2, wherein the contaminants comprise ozone;
acquiring concentration sample data of ozone at each time within the target time period, comprising:
acquiring initial ozone concentrations at each generation time in each time within the target time period;
for each generation time, acquiring the initial ozone concentration of a preset time before the generation time and obtaining a mean value to be used as the current ozone concentration of the generation time;
for each time in the target time period, the current ozone concentration in the time is averaged to be used as the concentration sample data of the ozone in the time.
4. The method of claim 2, wherein said counting the air mass fraction index to determine a statistic of air mass fraction index for the target time period comprises:
the following statistical treatments were performed separately for each contaminant:
averaging the air quality index of the pollutants at each time, and determining the average value of the air quality index of the pollutants in the target time period; and/or
Sequencing the air quality index of the pollutants at each time to obtain an air quality index at a first position after sequencing, wherein the air quality index is used as the upper limit value of the air quality index of the pollutants in the target time period; and/or, acquiring the air quality index at the second position after sequencing as a lower limit value of the air quality index of the pollutants in the target time period.
5. The method according to claim 1, wherein the method further comprises:
drawing a pollution characteristic diagram of the time to be analyzed based on the air quality index of the time to be analyzed and the statistic value, wherein the pollution characteristic diagram is used for indicating the primary pollutant of the time to be analyzed and the relative relation between the air quality index of the time to be analyzed and the statistic value;
the pollution characteristic map comprises a statistical value radar map and an air quality index rose map under the same polar coordinate system.
6. An apparatus for determining a type of contamination feature, the apparatus comprising:
the first determining module is used for determining an air quality index of each time within a target time period;
The statistics module is used for carrying out statistics on the air quality index and determining a statistics value of the air quality index of the target time period, wherein the statistics value comprises a mean value, an upper limit value and/or a lower limit value;
the second determining module is used for determining an air quality index of any time to be analyzed in the target time period;
the judging module is used for determining the target pollution characteristic type of the time to be analyzed based on the air quality index of the time to be analyzed and the statistic value;
the judging module is specifically configured to:
determining a judging strategy of each pollution characteristic type, wherein the judging strategy comprises a preset relation between an air quality index and a statistic value in the pollution characteristic type;
in the judging strategy of each pollution characteristic type, determining a target preset relation which is met by the air quality index and the statistic value of the time to be analyzed, and taking the corresponding pollution characteristic type as the target pollution characteristic type of the time to be analyzed;
the pollution characteristic type has correlation with the air quality index, and comprises a meteorological pollution characteristic type and an emission pollution characteristic type;
The pollution characteristic types of the meteorological type at least comprise a stationary type and a small wind type, and the pollution characteristic types of the emission type at least comprise a dust type, a compound pollution type, a photochemical pollution type, a partial industry type and a partial motor vehicle type;
the stationary type judgment strategy comprises the following steps: the air mass fraction index of each contaminant is greater than the upper limit of the air mass fraction index of the contaminant;
the small wind type judging strategy comprises the following steps: the air mass fraction index of each contaminant is greater than the average of the air mass fraction indexes of the contaminants;
the dust type judging strategy comprises the following steps: the only thing is: PM (particulate matter) 10 Is greater than PM 10 Upper limit value of air mass index of (2), and PM 2.5 With PM 10 The air mass fraction index ratio of (2) is smaller than a preset threshold value;
the determination strategy of the composite pollution type comprises the following steps: PM (particulate matter) 2.5 Is greater than PM 2.5 Air of (2)Upper limit of mass index, and O 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
the photochemical pollution type judgment strategy comprises the following steps: o (O) 3 Is greater than O 3 An upper limit value of the air mass fraction index of (2);
the determination strategy of the partial industry type comprises the following steps: the only thing is: SO (SO) 2 Is greater than SO 2 Upper limit value of air mass index of (2), and NO 2 Is greater than NO 2 The air mass index of CO is greater than the upper limit value of the air mass index of CO;
the judgment strategy of the partial motor vehicle type comprises the following steps: the only thing is: NO (NO) 2 Is greater than NO 2 And the air mass fraction index of CO is greater than the upper limit of the air mass fraction index of CO.
7. An electronic device, comprising:
a processor; and
a memory in which a program is stored,
wherein the program comprises instructions which, when executed by the processor, cause the processor to perform the method according to any of claims 1-5.
8. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1-5.
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