CN111596012A - Air quality monitoring method, device, equipment and storage medium - Google Patents
Air quality monitoring method, device, equipment and storage medium Download PDFInfo
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Abstract
The application discloses a method, a device, equipment and a storage medium for monitoring air quality, wherein the method comprises the following steps: setting an air quality parameter threshold value; detecting the air quality in real time to obtain an air quality parameter value; judging whether the air quality reaches the standard or not according to the air quality parameter value and the air quality parameter threshold value; if the air quality does not reach the standard, analyzing air pollution condition data; and generating an air pollution treatment scheme according to the result of the air pollution condition data analysis. The monitoring method of the air quality can assist in knowing the parameter value of the air quality, the possibility of reaching the standard and the like in real time, identify key factors influencing the air quality to reach the standard, and timely obtain a corresponding air pollution treatment scheme, so that accurate and timely monitoring of reaching the standard of the air quality is realized.
Description
Technical Field
The application relates to the technical field of environmental monitoring, in particular to a method, a device, equipment and a storage medium for monitoring air quality.
Background
At present, the situation of air pollution in China is still very severe, and the prevention and treatment work is urgent. The state releases relevant assessment methods for preventing and controlling atmospheric pollution every year, and establishes annual average pollutant concentration targets for different regions. There are, however, often limitations to the achievement of annual goals. Such as: due to the large time span of annual targets, there is limited guidance in target management on a monthly or even smaller time scale; limited by the service level, the air quality target in the district cannot be reasonably decomposed, and the current standard reaching condition and the accessibility of the target cannot be quickly known.
The environment of China is increasingly severe, and in order to realize the vision that the environment of China becomes better and better, the environment department can issue environment standard-reaching tasks to various cities every year. However, there are often problems for some users. Such as: the manager faces examination pressure, and often cannot dynamically control the standard difference in real time to support the establishment of a treatment scheme; when a manager wants to know the reason of the exceeding and the pollution source, the reason of the exceeding is difficult to analyze, and under the condition of only six parameter variable type data, the process of judging the type of the pollution source and making auxiliary management and control measures is difficult.
Disclosure of Invention
The application aims to provide a method, a device, equipment and a storage medium for monitoring air quality. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
According to an aspect of an embodiment of the present application, there is provided an air quality monitoring method, including:
setting an air quality parameter threshold value;
detecting the air quality in real time to obtain an air quality parameter value;
judging whether the air quality reaches the standard or not according to the air quality parameter value and the air quality parameter threshold value;
if the air quality does not reach the standard, analyzing air pollution condition data;
and generating an air pollution treatment scheme according to the result of the air pollution condition data analysis.
Further, the determining whether the air quality reaches the standard according to the air quality parameter value and the air quality parameter threshold value includes:
comparing the air quality parameter value to the air quality parameter threshold value;
and if the air quality parameter value is greater than or equal to the air quality parameter threshold value, determining that the air quality does not reach the standard, otherwise, determining that the air quality reaches the standard.
Further, the air pollution condition data analysis includes air pollution pattern recognition and meteorological analysis.
Further, the determining whether the air quality reaches the standard according to the air quality parameter value and the air quality parameter threshold value includes:
according to the air quality parameter value, predicting through an air quality numerical model to obtain an air quality parameter predicted value in a future time period;
and judging whether the air quality reaches the standard or not according to the predicted value of the air quality parameter and the threshold value of the air quality parameter.
Further, the air pollution pattern recognition includes:
comparing the predicted value of the air quality parameter with the grading concentration threshold of each pollutant in the air, and correspondingly calculating the air quality index of each pollutant;
selecting the maximum value of the air quality index according to the obtained air quality index of each pollutant so as to determine the air quality index;
determining an air pollution mode according to the air quality index grading standard;
the weather analysis includes:
acquiring a meteorological data predicted value of a future period of time by adopting a numerical forecasting model, wherein the meteorological data predicted value comprises at least one meteorological parameter;
historical meteorological data over a period of time in the past is acquired.
Inquiring a meteorological threshold interval table according to the meteorological data predicted value, and acquiring a critical value interval corresponding to each meteorological parameter in the meteorological threshold interval table; the meteorological threshold interval table adopts a meteorological threshold range list which is commonly used in the prior art;
and determining a weather tag at the current moment according to each weather parameter in the weather data predicted value, each weather parameter in the historical weather data and a critical value interval corresponding to each weather parameter in the weather threshold interval table.
Further, the air pollution pattern recognition includes:
comparing the air quality parameter value with the grading concentration threshold of each pollutant in the air, and correspondingly calculating the air quality index of each pollutant;
selecting the maximum value of the air quality index according to the obtained air quality index of each pollutant so as to determine the air quality index;
and determining an air pollution mode by contrasting the air quality index grading standard, wherein the air pollution mode comprises two parameters of an air quality category and an air quality grade.
Further, the weather analysis includes:
acquiring real-time meteorological data and historical meteorological data in a past period, wherein the real-time meteorological data comprises at least one meteorological parameter;
inquiring a meteorological threshold interval table according to the real-time meteorological data to obtain critical value intervals corresponding to the meteorological parameters in the meteorological threshold interval table;
and determining a weather tag at the current moment according to each weather parameter in the real-time weather data, each weather parameter in the historical weather data and a critical value interval corresponding to each weather parameter in the weather threshold interval table.
Further, the generating of the air pollution abatement plan according to the result of the air pollution condition data analysis includes:
and calling a historical treatment method corresponding to the air pollution mode and a historical treatment method corresponding to the meteorological analysis result from a database, and combining the historical treatment methods and the meteorological analysis result to obtain the air pollution treatment scheme.
According to another aspect of the embodiments of the present application, there is provided an air quality monitoring apparatus including:
the threshold setting module is used for setting the threshold of the air quality parameter;
the detection module is used for detecting the air quality in real time to obtain an air quality parameter value;
the judging module is used for judging whether the air quality reaches the standard or not according to the air quality parameter value and the air quality parameter threshold value;
the analysis module is used for analyzing air pollution condition data if the air quality does not reach the standard;
and the scheme generating module is used for generating an air pollution treatment scheme according to the result of the air pollution condition data analysis.
Further, the determining module includes:
a comparison module for comparing the air quality parameter value with the air quality parameter threshold value;
and the determining module is used for determining that the air quality does not reach the standard if the air quality parameter value is greater than or equal to the air quality parameter threshold value, and otherwise, determining that the air quality reaches the standard.
According to another aspect of the embodiments of the present application, there is provided an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-mentioned air quality monitoring method.
According to another aspect of embodiments of the present application, there is provided a computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the above-mentioned air quality monitoring method.
The technical scheme provided by one aspect of the embodiment of the application can have the following beneficial effects:
the monitoring method of the air quality provided by the embodiment of the application can assist in knowing the parameter value of the air quality, the possibility of reaching the standard and the like in real time, identify the key factors influencing the air quality to reach the standard, and timely obtain the corresponding air pollution treatment scheme, thereby realizing accurate and timely monitoring of reaching the standard of the air quality.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the application, or may be learned by the practice of the embodiments. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 illustrates a flow diagram of a method for monitoring air quality according to an embodiment of the present application;
FIG. 2 is a flow chart illustrating the determination of whether the air quality is met according to the value of the air quality parameter and the threshold value of the air quality parameter according to an embodiment of the present application;
FIG. 3 illustrates a flow chart of air pollution pattern recognition in one embodiment of the present application;
FIG. 4 shows a flow diagram of weather analysis in one embodiment of the present application;
FIG. 5 shows a flow chart of step 403 in one embodiment of the present application;
fig. 6 shows a block diagram of an air quality monitoring apparatus according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is further described with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It will be understood by those within the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
As shown in fig. 1, one embodiment of the present application provides a method for monitoring air quality, including:
and S10, setting an air quality parameter threshold value.
The air quality parameter threshold may be set based on an air quality target that needs to be achieved as an air quality criterion. Alternatively, the air quality parameter threshold value may be set using a standard such as a relevant international standard, national standard, or industry standard as the air quality standard. For example, in a specific embodiment, the air quality standard may be an air quality secondary standard specified in national standard GB3095-2012 "ambient air quality standard".
And S20, detecting the air quality in real time to obtain the air quality parameter value.
The air quality is detected in real time through various air pollutant detection devices, and the air quality parameter value is obtained.
And S30, judging whether the air quality reaches the standard or not according to the air quality parameter value and the air quality parameter threshold value.
As shown in fig. 2, S30 specifically includes:
s301, comparing the air quality parameter value with an air quality parameter threshold value;
s302, if the air quality parameter value is larger than or equal to the air quality parameter threshold value, determining that the air quality does not reach the standard, otherwise, determining that the air quality reaches the standard.
When the air quality parameter value includes a plurality of index values, the plurality of index values may respectively correspond to an air quality parameter threshold, and at this time, the plurality of index values may be compared with the air quality parameter thresholds corresponding to the plurality of index values to determine whether the plurality of index values reach the standard.
For example, when the air quality parameter value includes 3 index values, which are carbon monoxide, PM2.5 and sulfur dioxide, respectively, and the detected carbon monoxide is 16, the content of PM2.5 is 150, and the content of sulfur dioxide is 80, while the carbon monoxide threshold value is 20, the PM2.5 threshold value is 60, and the sulfur dioxide threshold value is 20, it is determined that the detected carbon monoxide is smaller than the carbon monoxide threshold value, the content of PM2.5 is greater than the PM2.5 threshold value, and the sulfur dioxide content is greater than the sulfur dioxide threshold value, it is determined that carbon monoxide is up to standard, and PM2.5 and sulfur dioxide are not up to standard.
The air quality parameter threshold may be preset, and the air quality parameter threshold may be obtained according to an air quality target that needs to be achieved, or may also be obtained according to a relevant international standard, a national standard, an industry standard, or other standards.
And S40, if the air quality does not reach the standard, analyzing the air pollution condition data. The air pollution condition data analysis includes air pollution pattern recognition and meteorological analysis.
In certain embodiments, as shown in fig. 3, the air pollution pattern recognition comprises:
1) comparing the air quality parameter value with the grading concentration threshold of each pollutant in the air, and correspondingly calculating the air quality index of each pollutant;
the graded concentration threshold may be based on current international universal air pollutant classification standards.
The air quality index is calculated by the formula
IAQIp＝((IAQIHi–IAQIL0)/(BPHi–BPL0))*(Cp–BPL0)+IAQIL0
Among them, IAQIpIs the air quality index of the pollutant project P;
Cpis a pollutant item P mass concentration value; BP (Back propagation) ofHiIn the limit table of pollutant item concentration corresponding to air quality index and CpHigh values of similar contaminant concentration limits; BP (Back propagation) ofL0In the limit table of pollutant item concentration corresponding to air quality index and CpLow values of similar contaminant concentration limits; IAQIHiIn the limit table of pollutant item concentration corresponding to air quality index and BPHiA corresponding air mass fraction index; IAQIL0In the limit table of pollutant item concentration corresponding to air quality index and BPL0Corresponding air mass fraction index.
2) Selecting the maximum value of the air quality index according to the obtained air quality index of each pollutant so as to determine the air quality index;
the air quality index AQI calculation formula is as follows:
AQI＝max{IAQI1、IAQI2、IAQI3、…、IAQIn}
wherein, IAQI is air quality index; and n is a pollutant item.
3) And determining an air pollution mode by contrasting the air quality index grading standard, wherein the air pollution mode comprises two parameters of an air quality category and an air quality grade. The air quality index grading criteria may refer to ambient Air Quality Index (AQI) technical specification (trial) (HJ 633-2012).
In some embodiments, as shown in FIG. 4, the meteorological analysis includes:
s401, acquiring real-time meteorological data and historical meteorological data in a past period, wherein the real-time meteorological data comprises at least one meteorological parameter;
s402, inquiring a meteorological threshold interval table according to the real-time meteorological data, and acquiring critical value intervals corresponding to the meteorological parameters in the meteorological threshold interval table; the meteorological threshold interval table adopts a meteorological threshold range list which is commonly used in the prior art;
s403, determining a weather tag at the current moment according to each weather parameter in the real-time weather data, each weather parameter in the historical weather data and a critical value interval corresponding to each weather parameter in the weather threshold interval table.
As shown in fig. 5, step S403 specifically includes:
s4031, determining weather categories under the weather parameters according to the weather parameters in the real-time weather data.
The weather categories include yin, rain, fog, snow, wind, thunder, and the like. Specifically, when the weather parameter is the fog reduction amount, the weather category corresponding to the weather parameter is fog; when the meteorological parameter is the lightning reduction quantity, the meteorological category corresponding to the meteorological parameter is the lightning; when the meteorological parameter is the wind speed, the corresponding meteorological category is wind; … … are provided.
S4032, determining weather levels under the weather parameters according to the weather parameters in the real-time weather data, the weather parameters in the historical weather data and critical value intervals corresponding to the weather parameters in the weather threshold interval table. The weather level, i.e. the level corresponding to the value of the weather parameter, for example, for the rain weather category, the weather level is divided into: a light rain rating, a daily rainfall of less than 10 mm; medium rain level, daily rainfall interval [10,25) millimeters; heavy rain grade, daily rainfall interval [25,50) millimeters; rainstorm level, daily rainfall interval [50, 100) millimeters; especially heavy rainstorm levels, the daily rainfall is greater than or equal to 200 millimeters.
In certain embodiments, step S4032 specifically includes:
determining a critical value interval in which each meteorological parameter is located according to each meteorological parameter in the real-time meteorological data, and determining a meteorological level corresponding to the critical value interval in which each meteorological parameter is located as the meteorological level of each meteorological parameter; weather grade is the grade corresponding to the numerical value of the weather parameter;
judging whether the difference value of each meteorological parameter in the real-time meteorological data and the corresponding meteorological parameter in the meteorological data at the latest moment before the current moment is greater than a preset threshold value or not;
if the difference value between the earliest weather parameter (called as the earliest weather parameter) in the real-time weather data and the corresponding weather parameter in the weather data at the latest moment before the current moment is greater than a preset threshold value, the weather level under the earliest weather parameter in the real-time weather data is adjusted to be the weather level under the corresponding weather parameter in the weather data at the latest moment before the current moment.
S4033, determining meteorological characteristics under the meteorological parameters according to the meteorological categories and meteorological levels under the meteorological parameters and the meteorological parameters in the historical meteorological data.
In certain embodiments, step S4033 specifically includes:
for each weather parameter, if the weather category and the weather level of the weather parameter in the weather data at all times in the historical weather data are the same as the weather category and the weather level of the weather parameter corresponding to the real-time weather data, the weather characteristic of the weather parameter is continuity;
for each meteorological parameter, if the meteorological category under the meteorological parameter in the meteorological data at all times in the historical meteorological data is the same as the meteorological category under the corresponding meteorological parameter in the real-time meteorological data, and the meteorological level under the meteorological parameter in the meteorological data at all times in the historical meteorological data is not the same as the meteorological level under the corresponding meteorological parameter in the real-time meteorological data, the meteorological characteristics under the meteorological parameter are intermittent.
S4034, determining the weather tag at the current moment according to the weather category, the weather level and the weather characteristics under each weather parameter. Weather tags are used to mark weather conditions and may be used in accordance with standards common in the industry, such as: the weather Label of intermittent heavy snow is Label25, the weather Label of fog is Label32, the weather Label of hail is Label127, and the like. For example, if the weather parameter is snowfall, the weather type is snow, the weather level is three levels (representative level is heavy snow), and the weather characteristic is intermittent, the current weather tag is determined to be intermittent heavy snow, and the weather tag corresponding to the weather data is determined to be Label 25.
The historical meteorological data comprises meteorological data of at least one moment in a past period of time; each meteorological parameter corresponds to at least one critical value interval, and each critical value interval corresponds to a meteorological grade.
The result of the air pollution condition data analysis comprises the result of the air pollution pattern recognition and the result of the meteorological analysis.
And S50, generating an air pollution treatment scheme according to the result of the air pollution condition data analysis.
The air pollution abatement scheme comprises a combination scheme of a historical abatement method corresponding to the air pollution mode and a historical abatement method corresponding to the meteorological analysis result. And executing an air pollution treatment scheme until the air quality reaches the standard.
Generating an air pollution abatement scheme according to the result of the air pollution condition data analysis, comprising:
and calling a historical treatment method corresponding to the air pollution mode and a historical treatment method corresponding to the meteorological analysis result from a database, and combining the historical treatment methods and the meteorological analysis result to obtain the air pollution treatment scheme.
And storing the historical governance method corresponding to the air pollution mode and the historical governance method corresponding to the meteorological analysis result in a database so as to be called. The database is specially used for storing historical treatment methods corresponding to air pollution modes and historical treatment methods corresponding to meteorological analysis results, and the historical treatment methods can be set by workers according to experience.
Another embodiment of the present application provides a method for monitoring air quality, which monitors air quality based on prediction data. The monitoring method comprises the following steps:
and S1, setting an air quality parameter threshold value.
And S2, detecting the air quality in real time to obtain a real-time value of the air quality parameter.
And S3, according to the air quality parameter real-time value, predicting through air quality numerical models such as NAQPMS, CMAQ, CAMx, WRF-chem and the like to obtain an air quality parameter predicted value in the future time period.
And S4, judging whether the air quality reaches the standard or not according to the predicted value of the air quality parameter and the air quality parameter threshold set in the step S1.
S4 specifically includes:
s41, comparing the predicted value of the air quality parameter with an air quality parameter threshold value;
and S42, if the predicted value of the air quality parameter is greater than or equal to the threshold value of the air quality parameter, determining that the air quality does not reach the standard, otherwise, determining that the air quality reaches the standard.
When the predicted value of the air quality parameter includes a plurality of index values, the plurality of index values may respectively correspond to an air quality parameter threshold, and at this time, the plurality of index values may be compared with the air quality parameter threshold corresponding to the plurality of index values to determine whether the plurality of index values reach the standard.
And S5, if the air quality does not reach the standard, analyzing the air pollution condition data. The air pollution condition data analysis includes air pollution pattern recognition and meteorological analysis.
The air pollution pattern recognition step also uses the predicted value of the air quality parameter to carry out recognition.
The air pollution pattern recognition includes:
(1) and comparing the predicted value of the air quality parameter with the grading concentration threshold of each pollutant in the air, and correspondingly calculating the air quality index of each pollutant.
(2) And selecting the maximum value of the air quality index according to the obtained air quality index of each pollutant so as to determine the air quality index.
(3) And determining an air pollution mode by contrasting the air quality index grading standard, wherein the air pollution mode comprises two parameters of an air quality category and an air quality grade.
The meteorological analysis is also realized by adopting a meteorological data predicted value obtained by a WRF and other numerical forecasting models. Specifically, the meteorological analysis includes:
(1) and acquiring a meteorological data predicted value of a future period of time by using a WRF (weighted round robin) and other numerical forecasting models, wherein the meteorological data predicted value comprises at least one meteorological parameter.
(2) Historical meteorological data over a period of time in the past is acquired.
(3) Inquiring a meteorological threshold interval table according to the meteorological data predicted value, and acquiring a critical value interval corresponding to each meteorological parameter in the meteorological threshold interval table; the meteorological threshold interval table adopts a meteorological threshold range list which is commonly used in the prior art;
(4) and determining a weather tag at the current moment according to each weather parameter in the weather data predicted value, each weather parameter in the historical weather data and a critical value interval corresponding to each weather parameter in the weather threshold interval table.
The air quality monitoring method can assist in knowing the air quality parameter value, the standard-reaching possibility analysis and the like in real time, identify key factors influencing the standard reaching of the air quality, and timely obtain a corresponding air pollution treatment scheme by combining with a historical treatment scheme, so that the accurate and timely standard-reaching monitoring of the air quality is realized.
Another embodiment of the present application provides an air quality monitoring apparatus, including:
the threshold setting module is used for setting the threshold of the air quality parameter;
the detection module is used for detecting the air quality in real time to obtain an air quality parameter value;
the judging module is used for judging whether the air quality reaches the standard or not according to the air quality parameter value and the air quality parameter threshold value;
the analysis module is used for analyzing air pollution condition data if the air quality does not reach the standard;
and the scheme generating module is used for generating an air pollution treatment scheme according to the result of the air pollution condition data analysis.
In some embodiments, the determining module includes:
a comparison module for comparing the air quality parameter value with the air quality parameter threshold value;
and the determining module is used for determining that the air quality does not reach the standard if the air quality parameter value is greater than or equal to the air quality parameter threshold value, and otherwise, determining that the air quality reaches the standard.
In some embodiments, the monitoring device further includes a prediction module, configured to predict, according to the air quality parameter real-time value, an air quality parameter predicted value in a future time period through an air quality numerical model such as NAQPMS, CMAQ, CAMx, WRF-chem, and the like.
Furthermore, the prediction module is also used for acquiring a meteorological data prediction value of a future period of time through a WRF and other numerical forecasting models according to the real-time meteorological data.
Another embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-mentioned air quality monitoring method.
Another embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the air quality monitoring method described above.
The method provided by the embodiment of the application can assist a leader decision maker to know the air quality standard-reaching gaps, the ranking, the standard-reaching target decomposition, the standard-reaching task allocation, the standard-reaching possibility analysis, the ranking calculation and the like of a plurality of cities in real time, identify key pollution factors influencing the standard reaching, and realize accurate and timely standard-reaching monitoring on the air quality. Besides, the limitation that the user lacks server resources can be eliminated, and meanwhile, local customized deployment service can be performed according to the actual requirements of the user, so that the diversity requirements of the user are met. The standard can be monitored and calculated according to the standard by national secondary standard or custom standard, and management and control suggestions are provided. Through analysis, pollution source type judgment and control suggestions, meteorological analysis and regional transmission analysis based on the pollution six parameter variables can be realized. The system can also meet the access of PC and APP at the same time, and meet the office and report requirements of users at any time and any place. Most importantly, the method integrates the current situation of air quality, the difference of reaching standards, the calculation of reaching standards, the cause of exceeding standards and the control suggestion in one paper content, and is convenient for leaders to master key information in the shortest time.
It should be noted that:
the term "module" is not intended to be limited to a particular physical form. Depending on the particular application, a module may be implemented as hardware, firmware, software, and/or combinations thereof. Furthermore, different modules may share common components or even be implemented by the same component. There may or may not be clear boundaries between the various modules.
The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose devices may be used with the teachings herein. The required structure for constructing such a device will be apparent from the description above. In addition, this application is not directed to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the present application as described herein, and any descriptions of specific languages are provided above to disclose the best modes of the present application.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the application, various features of the application are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: this application is intended to cover such departures from the present disclosure as come within known or customary practice in the art to which this invention pertains. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this application.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The above-mentioned embodiments only express the embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.
Claims (10)
1. A method of monitoring air quality, comprising:
setting an air quality parameter threshold value;
detecting the air quality in real time to obtain an air quality parameter value;
judging whether the air quality reaches the standard or not according to the air quality parameter value and the air quality parameter threshold value;
if the air quality does not reach the standard, analyzing air pollution condition data;
and generating an air pollution treatment scheme according to the result of the air pollution condition data analysis.
2. The method of claim 1, wherein the determining whether the air quality is up to the standard according to the air quality parameter value and the air quality parameter threshold value comprises:
comparing the air quality parameter value to the air quality parameter threshold value;
and if the air quality parameter value is greater than or equal to the air quality parameter threshold value, determining that the air quality does not reach the standard, otherwise, determining that the air quality reaches the standard.
3. The method of claim 1, wherein the air pollution condition data analysis comprises air pollution pattern recognition and meteorological analysis.
4. The method of claim 1, wherein the determining whether the air quality is up to the standard according to the air quality parameter value and the air quality parameter threshold value comprises:
according to the air quality parameter value, predicting through an air quality numerical model to obtain an air quality parameter predicted value in a future time period;
and judging whether the air quality reaches the standard or not according to the predicted value of the air quality parameter and the threshold value of the air quality parameter.
5. The method of claim 3, wherein the air pollution pattern recognition comprises:
according to the air quality parameter value, predicting through an air quality numerical model to obtain an air quality parameter predicted value in a future time period;
comparing the predicted value of the air quality parameter with the grading concentration threshold of each pollutant in the air, and correspondingly calculating the air quality index of each pollutant;
selecting the maximum value of the air quality index according to the obtained air quality index of each pollutant so as to determine the air quality index;
determining an air pollution mode according to the air quality index grading standard;
the weather analysis includes:
acquiring a meteorological data predicted value of a future period of time by adopting a numerical forecasting model, wherein the meteorological data predicted value comprises at least one meteorological parameter;
historical meteorological data over a period of time in the past is acquired.
Inquiring a meteorological threshold interval table according to the meteorological data predicted value, and acquiring a critical value interval corresponding to each meteorological parameter in the meteorological threshold interval table; the meteorological threshold interval table adopts a meteorological threshold range list which is commonly used in the prior art;
and determining a weather tag at the current moment according to each weather parameter in the weather data predicted value, each weather parameter in the historical weather data and a critical value interval corresponding to each weather parameter in the weather threshold interval table.
6. The method of claim 3, wherein the air pollution pattern recognition comprises:
comparing the air quality parameter value with the grading concentration threshold of each pollutant in the air, and correspondingly calculating the air quality index of each pollutant;
selecting the maximum value of the air quality index according to the obtained air quality index of each pollutant so as to determine the air quality index;
determining an air pollution mode by contrasting with an air quality index grading standard, wherein the air pollution mode comprises two parameters of an air quality category and an air quality grade; the weather analysis includes:
acquiring real-time meteorological data and historical meteorological data in a past period, wherein the real-time meteorological data comprises at least one meteorological parameter;
inquiring a meteorological threshold interval table according to the real-time meteorological data to obtain critical value intervals corresponding to the meteorological parameters in the meteorological threshold interval table;
and determining a weather tag at the current moment according to each weather parameter in the real-time weather data, each weather parameter in the historical weather data and a critical value interval corresponding to each weather parameter in the weather threshold interval table.
7. The method of claim 1, wherein generating an air pollution abatement plan based on the results of the air pollution condition data analysis comprises:
and calling a historical treatment method corresponding to the air pollution mode and a historical treatment method corresponding to the meteorological analysis result from a database, and combining the historical treatment methods and the meteorological analysis result to obtain the air pollution treatment scheme.
8. An air quality monitoring device, comprising:
the threshold setting module is used for setting the threshold of the air quality parameter;
the detection module is used for detecting the air quality in real time to obtain an air quality parameter value;
the judging module is used for judging whether the air quality reaches the standard or not according to the air quality parameter value and the air quality parameter threshold value;
the analysis module is used for analyzing air pollution condition data if the air quality does not reach the standard;
and the scheme generating module is used for generating an air pollution treatment scheme according to the result of the air pollution condition data analysis.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method of monitoring air quality as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor to implement the method of monitoring air quality according to any one of claims 1-7.
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