CN108489875B - Pollutant tracing system and method based on time period statistical analysis - Google Patents
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Abstract
The invention discloses a pollutant traceability system and method based on time period statistical analysis. The pollutant traceability system and method based on time period statistical analysis can realize qualitative and quantitative analysis of regional particulate matter channel transmission based on a low-cost urban air quality monitoring network, can effectively solve the timeliness problem of studying and judging particulate matter transmission channels, is simple and easy to implement, can analyze the possibility of particulate matter transmission channels in each ascending time period in a targeted manner, and provides real-time powerful data support for studying, judging and preventing particulate matters.
Description
Technical Field
The invention relates to an environmental air quality source analysis method, in particular to a pollutant traceability system and a pollutant traceability method based on time interval statistical analysis.
Background
The pollution source analysis technology is helpful for analyzing the pollutant source and the channel transmission condition, improves the scientificity and pertinence in the prevention and control of pollutants (particularly particulate matters), and has important reference significance for decision prediction.
The current source analysis technology of atmospheric pollution mainly comprises three types of methods, namely a source emission list, a diffusion model taking a pollution source as an object, and a receptor model taking a pollution area as an object.
The current source analysis technology depends on a large amount of basic work, for example, an emission inventory method needs to count the total emission amount of particulate matters, all areas, all industries and all types of particulate matters, a CMB model needs to continuously update a source component spectrum and the like, so that the source analysis method does not play an important role in the current grid environment management, particularly the timeliness of the method seriously limits the prejudgment and prevention of particulate matter transmission channels.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a pollutant traceability system and a pollutant traceability method based on time period statistical analysis, and the problem of timeliness of a particulate matter conveying channel can be effectively solved and judged.
The invention adopts the following technical scheme:
the pollutant traceability system based on time period statistical analysis comprises an urban air quality monitoring network and a cloud server, wherein the urban air quality monitoring network comprises a monitoring data communication unit, the cloud server comprises a traceability calculation unit and a visualization unit, the monitoring data communication unit is embedded in an atmospheric monitoring micro-station, and the traceability calculation unit is respectively connected with the data communication unit and the visualization unit;
the urban air quality online monitoring network comprises monitoring micro stations in an urban area, each monitoring micro station comprises a control module, a sensor module, a wireless transmission module, a power supply module and a storage module, and the control module is respectively connected with the sensor module, the wireless transmission module, the power supply module and the storage module;
the control module is used for acquiring data of the sensor module, storing and transmitting the data; the sensor module is used for detecting the concentration of each pollutant in the air; the wireless transmission module is used for transmitting the data of each monitoring micro station to the monitoring terminal, and the transmission frequency is adjustable; the power module converts solar energy and stores the solar energy in the storage battery, is used for supplying power to the control module and can be switched between solar power supply and commercial power at will;
the source tracing calculation unit is used for processing the monitoring data in real time, operating an early warning algorithm and determining early warning equipment and an area; the visualization unit combines the pollution cloud picture and the trend picture with the transmission condition of the particulate matter channel to give quantitative and qualitative analysis results.
The sensor module includes a PM10 sensor, a PM2.5 sensor, an SO2Sensor, NO2Sensor, CO sensor, O3A sensor:
a PM10 sensor for detecting PM10 particulate concentration in air;
the PM2.5 sensor is used for detecting the concentration of PM2.5 particles in the air;
SO2sensor for detecting SO in air2The gas concentration;
NO2sensor for detecting NO in air2The gas concentration;
the CO sensor is used for detecting the concentration of CO gas in the air;
O3sensor for detecting O in air3The gas concentration.
The pollutant tracing method based on the time period statistical analysis comprises the following steps of:
1) data acquisition:
the monitoring data communication unit adopts a SIM928A module containing GPRS communication and is connected with a core mainboard STM32F103 processor of each monitoring micro-station, each atmospheric monitoring micro-station forms an urban air quality online monitoring network, and monitoring data are transmitted to a cloud server Hbase database;
2) data processing:
a source tracing calculation unit reads the Hbase database, performs source tracing statistical analysis on the target site and the pollutant and traces the transmission direction of the pollutant;
3) data presentation:
the visualization unit receives the traceability result from the traceability calculation unit and reflects the transmission condition of the pollution transmission channel in real time in the forms of pollution cloud pictures, trend pictures and the like.
In the step (2), the traceback calculation unit selects a certain key point analysis station and obtains each ascending time period of the station, and then traces back the transmission channel according to the wind direction of each ascending time period, and the specific steps are as follows:
step1, acquiring an initial data segment of a certain site, wherein the time dimension is an hour average value, acquiring a pollution item rising time segment, and judging conditions are as follows:
wherein cumsum is cumulative sum; max, min, maxIx and minIx are respectively a maximum value, a minimum value, a time index when the maximum value is taken and a time index when the minimum value is taken;
respectively counting the time numbers of rising and falling of the ring ratio by nAscent and nDescent;
lambda is a proportionality coefficient, and is given according to a time span, and a transient descending time period is reasonably ignored to a certain extent;
step2, calculating the average angle wdAngle of wind direction in the ascending time period, wdAngle of the site +/-22.5 directions and 10km range as candidate analysis sites, if no candidate site exists, widening the range to wdAngle +/-45 and 20 km;
step3, acquiring the rising time period of each candidate analysis site, and if the candidate sites have rising trend and the starting time is advanced, judging that the pollution item is transmitted by the site;
step4, using the transmission station of the pollution item determined in step3 as the starting station, repeating step2 and step3, and carrying out the next round of tracing.
In step1, nAscent and nDescent are the number of times when the ring ratio rises and falls respectively, and can be calculated by the following formula:
nAscent＝sum(diff>0)
nDescent＝sum(diff<0)
where diff is the differential sequence of the dirty term rising-segment data, i.e. for data segment [ x ]1,x2,…,xi,…,xn]And n is the size of the data sequence, the differential sequence diff is:
diff＝[x2-x1,x3-x2,…,xi+1-xi,…,xn-xn-1]。
the technical scheme obtained by adopting the technical scheme is as follows:
the pollutant traceability system and method based on time period statistical analysis can realize qualitative and quantitative analysis of regional particulate matter channel transmission based on a low-cost urban air quality monitoring network, can effectively solve the timeliness problem of studying and judging particulate matter transmission channels, is simple and easy to implement, can analyze the possibility of particulate matter transmission channels in each ascending time period in a targeted manner, and provides real-time powerful data support for studying, judging and preventing particulate matters.
Drawings
Fig. 1 is a schematic structural diagram of a pollutant tracing method based on time-interval statistical analysis.
FIG. 2 is a flowchart of an algorithm for extracting a rising period of a pollutant tracing method based on period statistical analysis.
FIG. 3 is an effect graph of an extracted ascending period algorithm of a pollutant tracing method based on period statistical analysis.
Fig. 4 is a schematic site distribution map of a pollutant tracing method based on time period statistical analysis.
Fig. 5 is a PM2.5 particulate matter traceability trend graph of a pollutant traceability method based on time period statistical analysis.
Detailed Description
The embodiments of the present invention will be further explained with reference to the accompanying drawings 1 to 5:
pollutant traceability system based on time interval statistical analysis comprises a city air quality monitoring network and a cloud server, wherein the city air quality monitoring network comprises a monitoring data communication unit, the cloud server comprises a traceability calculation unit and a visualization unit, the monitoring data communication unit is embedded into an atmosphere monitoring micro-station, and the traceability calculation unit is respectively connected with the data communication unit and the visualization unit.
The urban air quality online monitoring network comprises monitoring micro stations in an urban range, each monitoring micro station comprises a control module, a sensor module, a wireless transmission module, a power supply module and a storage module, and the control module is connected with the sensor module, the wireless transmission module, the power supply module and the storage module respectively.
The control module is used for acquiring data of the sensor module, storing and transmitting the data; the sensor module is used for detecting the concentration of each pollutant in the air; the wireless transmission module is used for transmitting the data of each monitoring micro station to the monitoring terminal, and the transmission frequency is adjustable; and the power module converts solar energy and stores the solar energy in the storage battery, is used for supplying power to the control module and can be switched between solar power supply and commercial power at will.
The source tracing calculation unit is used for processing the monitoring data in real time, operating an early warning algorithm and determining early warning equipment and an area; the visualization unit combines the pollution cloud picture and the trend picture with the transmission condition of the particulate matter channel to give quantitative and qualitative analysis results.
The sensor module includes a PM10 sensor, a PM2.5 sensor, an SO2Sensor, NO2Sensor, CO sensor, O3A sensor: a PM10 sensor for detecting PM10 particulate concentration in air; the PM2.5 sensor is used for detecting the concentration of PM2.5 particles in the air; SO (SO)2Sensor for detecting SO in air2The gas concentration; NO2Sensor for detecting NO in air2The gas concentration; the CO sensor is used for detecting the concentration of CO gas in the air; o is3Sensor for detecting O in air3The gas concentration.
The pollutant tracing method based on the time period statistical analysis comprises the following steps of:
1) data acquisition:
the monitoring data communication unit adopts a SIM928A module containing GPRS communication and is connected with a core mainboard STM32F103 processor of each monitoring micro-station, each atmospheric monitoring micro-station forms an urban air quality online monitoring network, and monitoring data are transmitted to a cloud server Hbase database;
2) data processing:
a source tracing calculation unit reads the Hbase database, performs source tracing statistical analysis on the target site and the pollutant and traces the transmission direction of the pollutant;
3) data presentation:
the visualization unit receives the traceability result from the traceability calculation unit and reflects the transmission condition of the pollution transmission channel in real time in the forms of pollution cloud pictures, trend pictures and the like.
In the step (2), the traceback calculation unit selects a certain key point analysis station and obtains each ascending time period of the station, and then traces back the transmission channel according to the wind direction of each ascending time period, and the specific steps are as follows:
step1, acquiring an initial data segment of a certain site, wherein the time dimension is an hour average value, acquiring a pollution item rising time segment, and judging conditions are as follows:
wherein cumsum is cumulative sum; max, min, maxIx and minIx are respectively a maximum value, a minimum value, a time index when the maximum value is taken and a time index when the minimum value is taken;
respectively counting the time numbers of rising and falling of the ring ratio by nAscent and nDescent;
lambda is a proportionality coefficient, and is given according to a time span, and a transient descending time period is reasonably ignored to a certain extent; lambda is a proportionality coefficient, and is set to be 0.8 in the method;
λ is a proportionality coefficient, and is set to 0.8 in the method
nAscent and nDescent are the number of times when the ring ratio rises and falls, respectively, and can be calculated by the following formula:
nAscent＝sum(diff>0)
nDescent＝sum(diff<0)
where diff is the differential sequence of the dirty term rising-segment data, i.e. for data segment [ x ]1,x2,…,xi,…,xn]And n is the size of the data sequence, the differential sequence diff is:
diff＝[x2-x1,x3-x2,…,xi+1-xi,…,xn-xn-1]；
step2, calculating the average angle wdAngle of wind direction in the ascending time period, wdAngle of the site +/-22.5 directions and 10km range as candidate analysis sites, if no candidate site exists, widening the range to wdAngle +/-45 and 20 km;
step3, acquiring the rising time period of each candidate analysis site, and if the candidate sites have rising trend and the starting time is advanced, judging that the pollution item is transmitted by the site;
step4, using the transmission station of the pollution item determined in step3 as the starting station, repeating step2 and step3, and carrying out the next round of tracing.
Lambda is a proportionality coefficient, and a transient descending time period is reasonably ignored to a certain extent according to the given time span, for example, in the time period of fig. 3, 11-1416: 00-11-1506: 00, the concentration of PM2.5 tends to decline, but the whole concentration tends to rise.
Fig. 4 and 5 are respectively a site distribution schematic map and a PM2.5 particulate matter tracing trend map of the pollutant tracing method based on time period statistical analysis.
The tracing calculation unit is described by combining example graph analysis, and an example selects "site 1" as a central site, and "site 2", "site 3", and "site 4" as first round candidate analysis sites.
For example, selecting five time points, firstly initiating a section of data, judging whether the data rises, and if the data rises, finding the starting and stopping time of the rising section, such as 10-0101: 00-07: 00; then, considering the data segments 08: 00-12: 00 of the next five time points, if the data segments also rise, the data segments come, and the starting time and the stopping time become 10-0101: 00-12: 00; and sequentially judging the last five time points.
In the 11-0218: 00-11-0306: 00 time period of 2017, the rising amplitude of PM2.5 of the 'site 1' assessment site is 141ug/m3, the average wind direction is northwest wind, the tracing direction is determined to be the northwest direction, for the site located in the northwest direction, the rising trend and the falling trend of the 'site 1' assessment site are relatively delayed, and the specific analysis is as follows:
(1) the station 2 is positioned at 52.76 degrees and 7.5km in the northwest of the station 1, the rising trend of the station starts from 11-0216:00, the station rises 2 hours earlier than that of the station 1, and the average wind direction of the station is northwest wind in a corresponding time range;
(2) the station 4 is located at 40.97 degrees 8.9km north of the station 1, the rising trend of the station starts from 11-0216:00, the station rises 2 hours earlier than the station 1, and the average wind direction of the station is the north wind in a corresponding time range.
(3) The station 3 is positioned at 56.92 degrees and 9.3km off the west of the north of the station 1, the rising trend of the station starts from 11-0216:00, the station rises 2 hours earlier than the station 1, and the average wind direction of the station is the north wind in a corresponding time range.
Therefore, it can be presumed that the rising trend in the site 11-0218: 00-11-0306: 00 of "site 1" keeps higher consistency with the three sites in the northwest direction, and the rising time lags behind the three sites; the station 2 and the station 3 have extremely close ascending trends because the two stations are close to each other and have small difference in the transmission influence of the polluted source; the concentration of PM2.5 at the site "site 4" was kept high at all times, indicating that the site "site 4" was more prominently transported from contaminated sources that were more likely to be in the northwest direction from Wenshun.
It should be understood, however, that the description herein of specific embodiments is not intended to limit the invention to the particular forms disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.
Claims (5)
1. The pollutant traceability system based on time period statistical analysis is characterized by comprising an urban air quality monitoring network and a cloud server, wherein the urban air quality monitoring network comprises a monitoring data communication unit, the cloud server comprises a traceability calculation unit and a visualization unit, the monitoring data communication unit is embedded in an atmospheric monitoring micro-station, and the traceability calculation unit is respectively connected with the data communication unit and the visualization unit;
the urban air quality online monitoring network comprises monitoring micro stations in an urban area, each monitoring micro station comprises a control module, a sensor module, a wireless transmission module, a power supply module and a storage module, and the control module is respectively connected with the sensor module, the wireless transmission module, the power supply module and the storage module;
the control module is used for acquiring data of the sensor module, storing and transmitting the data; the sensor module is used for detecting the concentration of each pollutant in the air; the wireless transmission module is used for transmitting the data of each monitoring micro station to the monitoring terminal, and the transmission frequency is adjustable; the power module converts solar energy and stores the solar energy in the storage battery, is used for supplying power to the control module and can be switched between solar power supply and commercial power at will;
the source tracing calculation unit is used for processing the monitoring data in real time, operating an early warning algorithm and determining early warning equipment and an area; the visualization unit combines the pollution cloud picture and the trend picture with the transmission condition of the particulate matter channel to give quantitative and qualitative analysis results;
the tracing calculation unit selects a certain key analysis station and obtains each ascending time period of the station, and then traces back a transmission channel according to the wind direction of each ascending time period, and the tracing calculation unit comprises the following specific steps:
step1, acquiring an initial data segment of a certain site, wherein the time dimension is an hour average value, acquiring a pollution item rising time segment, and judging conditions are as follows:
wherein cumsum is cumulative sum; max, min, maxIx and minIx are respectively a maximum value, a minimum value, a time index when the maximum value is taken and a time index when the minimum value is taken;
respectively counting the time numbers of rising and falling of the ring ratio by nAscent and nDescent;
lambda is a proportionality coefficient, and is given according to a time span, and a transient descending time period is reasonably ignored to a certain extent;
step2, calculating the average angle wdAngle of wind direction in the ascending time period, wdAngle of the site +/-22.5 directions and 10km range as candidate analysis sites, if no candidate site exists, widening the range to wdAngle +/-45 and 20 km;
step3, acquiring the rising time period of each candidate analysis site, and if the candidate sites have rising trend and the starting time is advanced, judging that the pollution item is transmitted by the site;
step4, using the transmission station of the pollution item determined in step3 as the starting station, repeating step2 and step3, and carrying out the next round of tracing.
2. The pollutant traceability system based on time period statistical analysis, as claimed in claim 1, wherein the sensor module comprises a PM10 sensor, a PM2.5 sensor, a SO2Sensor, NO2Sensor, CO sensor, O3A sensor:
a PM10 sensor for detecting PM10 particulate concentration in air;
the PM2.5 sensor is used for detecting the concentration of PM2.5 particles in the air;
SO2sensor for detecting SO in air2The gas concentration;
NO2sensor for detecting NO in air2The gas concentration;
the CO sensor is used for detecting the concentration of CO gas in the air;
O3sensor for detecting O in air3The gas concentration.
3. The pollutant tracing method based on time interval statistical analysis is characterized in that the pollutant tracing system based on the time interval statistical analysis of claim 2 comprises the following steps:
1) data acquisition:
the monitoring data communication unit adopts a SIM928A module containing GPRS communication and is connected with a core mainboard STM32F103 processor of each monitoring micro-station, each atmospheric monitoring micro-station forms an urban air quality online monitoring network, and monitoring data are transmitted to a cloud server Hbase database;
2) data processing:
a source tracing calculation unit reads the Hbase database, performs source tracing statistical analysis on the target site and the pollutant and traces the transmission direction of the pollutant;
3) data presentation:
the visualization unit receives the traceability result from the traceability calculation unit and reflects the transmission condition of the pollution transmission channel in real time in the forms of pollution cloud pictures, trend pictures and the like.
4. The pollutant tracing method based on time period statistical analysis according to claim 3, wherein in step (2), said tracing calculating unit selects a certain key point analysis station and obtains each ascending time period of the station, and then traces back the transmission channel according to the wind direction of each ascending time period, the specific steps are as follows:
step1, acquiring an initial data segment of a certain site, wherein the time dimension is an hour average value, acquiring a pollution item rising time segment, and judging conditions are as follows:
wherein cumsum is cumulative sum; max, min, maxIx and minIx are respectively a maximum value, a minimum value, a time index when the maximum value is taken and a time index when the minimum value is taken;
respectively counting the time numbers of rising and falling of the ring ratio by nAscent and nDescent;
lambda is a proportionality coefficient, and is given according to a time span, and a transient descending time period is reasonably ignored to a certain extent;
step2, calculating the average angle wdAngle of wind direction in the ascending time period, wdAngle of the site +/-22.5 directions and 10km range as candidate analysis sites, if no candidate site exists, widening the range to wdAngle +/-45 and 20 km;
step3, acquiring the rising time period of each candidate analysis site, and if the candidate sites have rising trend and the starting time is advanced, judging that the pollution item is transmitted by the site;
step4, using the transmission station of the pollution item determined in step3 as the starting station, repeating step2 and step3, and carrying out the next round of tracing.
5. The pollutant tracing method based on time period statistical analysis according to claim 4, characterized in that nAscent and nDescent in step1 are respectively the number of times of ring ratio rise and fall, and are calculated by the following formula:
nAscent＝sum(diff＞0)
nDescent＝sum(diff＜0)
where diff is the differential sequence of the dirty term rising-segment data, i.e. for data segment [ x ]1,x2,…,xi,…,xn]And n is the size of the data sequence, the differential sequence diff is: diff ═ x2-x1,x3-x2,…,xi+1-xi,…,xn-xn-1]。
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