CN105806756A - Method for correcting indoor and outdoor PM2.5 monitoring results by virtue of meteorological parameters - Google Patents
Method for correcting indoor and outdoor PM2.5 monitoring results by virtue of meteorological parameters Download PDFInfo
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- CN105806756A CN105806756A CN201610062947.4A CN201610062947A CN105806756A CN 105806756 A CN105806756 A CN 105806756A CN 201610062947 A CN201610062947 A CN 201610062947A CN 105806756 A CN105806756 A CN 105806756A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 24
- 238000000034 method Methods 0.000 title claims abstract description 17
- 238000012937 correction Methods 0.000 claims abstract description 81
- 238000000752 ionisation method Methods 0.000 claims abstract description 6
- 230000001419 dependent effect Effects 0.000 claims description 18
- 238000012417 linear regression Methods 0.000 abstract description 9
- 238000012935 Averaging Methods 0.000 abstract 1
- 238000003915 air pollution Methods 0.000 abstract 1
- 238000012358 sourcing Methods 0.000 abstract 1
- 238000012806 monitoring device Methods 0.000 description 9
- 238000004581 coalescence Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 239000008187 granular material Substances 0.000 description 3
- 239000013618 particulate matter Substances 0.000 description 3
- 238000005259 measurement Methods 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008021 deposition Effects 0.000 description 1
- 238000002715 modification method Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 239000011882 ultra-fine particle Substances 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/06—Investigating concentration of particle suspensions
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- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
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Abstract
The invention relates to a monitoring data correcting method and particularly relates to a method for correcting indoor and outdoor PM2.5 monitoring results by virtue of meteorological parameters. The method comprises the following steps: acquiring first reference data PE, wherein the first reference data include PM data acquired by virtue of PM monitoring equipment; acquiring relative temperature data and relative humidity data; and establishing a regression correction function by taking the first reference data, the relative temperature data and the relative humidity data as independent variables so as to obtain final corrected PM2.5 data, wherein the first reference data is a PM2.5 data value obtained in a second by second manner by virtue of an ionization method. According to the method, the PM2.5 data obtained by virtue of the ionization method is applied to meteorological parameter correction, and the PM2.5 data obtained in a second by second manner is combined with high-resolution meteorological data, so that the sourcing of PM2.5 is realized, different data presentation manners of minute averaging, moving average and the like are realized, and the instantaneity and locality of air pollution are reflected; and by virtue of linear regression, the relation between the environment and the PM2.5 data is obtained, and therefore, the PM2.5 monitoring accuracy under a certain condition is corrected.
Description
Technical field
The present invention relates to a kind of Monitoring Data modification method, be specially a kind of method utilizing meteorologic parameter correction indoor-outdoor air PM2.5 monitoring result.
Background technology
Pendant card Sol particle sensor technology is based on particulate matter and can be electrically charged the principle of (adsorb and carry electric charge), measures the amount of charge entrained by granule in gas to be measured.Technology itself is all the principles of science known by people, the method being namely commonly referred to as " effusion current measurement ".This measures technology, and the measurement of ultrafine particles thing is most sensitive.But, particulate matter can be subject to the impact of weather environment in atmosphere, it is specially the impact of two kinds of maximum humidity of impact effect and temperature, wherein the impact of humidity is in that, relative humidity increase can change the predominant intermolecular forces of particulate matter collision coalescence, strengthens coalescence effect, more little granule coalescence is made to generate bulky grain, and temperature is in boundary region, nearly cold wall district, axial velocity and the fluctuation velocity of PM2.5 alter a great deal, and granule is because thermophoretic forces effect can be moved to cold wall face and produces deposition.
Exactly because the high sensitivity with monitoring in real time of sensor, so the meteorological sensitivity changed to external world is very big.So the meteorological factor impact on equipment must be considered, with this, device data is revised.
Summary of the invention
In order to solve above technical problem, under real present meteorological conditions, under impact by the such as temperature and humidity affecting monitoring result of attending the meeting, the result that PM2.5 accurately monitors, the invention provides a kind of method utilizing meteorologic parameter correction indoor-outdoor air PM2.5 monitoring result, the following is concrete technical scheme:
A kind of method utilizing meteorologic parameter correction indoor-outdoor air PM2.5 monitoring result, first obtains the first reference data PE, and the first wherein said reference data includes utilizing PM to monitor the PM data that equipment gathers；Obtain relative temperature data and relative humidity data again；And set up recurrence correction function with relative humidity data and relative temperature data for independent variable with the first reference data, and obtain final correction result PM2.5 data, wherein, the first reference data is the PM2.5 data value obtained by the second by ionization method.
Further, return correction function and include with the first reference data and relative humidity for independent variable, correction result is the recurrence correction function of dependent variable and with the first reference data and relative temperature for independent variable, correction result is the recurrence correction function of dependent variable, also including with the first reference data and relative temperature, relative humidity for independent variable, correction result is the recurrence correction function of dependent variable.
Further, with the first reference data and relative humidity for independent variable, the correction function that correction result is dependent variable is:
。
Further, with the first reference data and relative temperature for independent variable, the correction function that correction result is dependent variable is:
。
Further, with the first reference data and relative temperature, relative humidity for independent variable, the recurrence correction function that correction result is dependent variable is:
；
Wherein: PE is the first reference data, RH is relative humidity pa, and tem is relative temperature parameter.
Beneficial effect: the PM2.5 data that the present invention is obtained by ionization method carry out meteorologic parameter correction, can effectively precisely predict the PM2.5 value that regulation detecting instrument obtains, substantially increase the temporal resolution of PM2.5 data on this basis simultaneously, utilize the PM2.5 data by the second in conjunction with high-resolution meteorological data, can realize the north source of PM2.5 and further can obtain minute average from moving average etc. different data presentation modes, effecting reaction air-polluting real-time and local, and pass through linear regression method, obtain the relation between environment and PM2.5 data, thus have modified PM2.5 monitoring accuracy under certain condition.
Accompanying drawing explanation
Fig. 1 is the relative humidity of the present invention scatterplot to monitoring equipment Yu correction result PM2.5 data influence；
Fig. 2 is the regression relation figure monitoring device data and correction result under high low relative humidity of the present invention；
Fig. 3 is the linear regression graph monitoring device data and correction result that difference relative humidity of the present invention is interval；
Fig. 4 is the temperature of the present invention scatterplot to monitoring device data with correction result PM2.5 data influence；
Fig. 5 is the regression relation figure monitoring device data and correction result PM2.5 data under high and low temperature of the present invention；
Fig. 6 is the linear regression graph monitoring device data and correction result PM2.5 data that different temperatures of the present invention is interval.
Detailed description of the invention
A kind of method utilizing meteorologic parameter correction indoor-outdoor air PM2.5 monitoring result, first obtains the first reference data PE, and the first wherein said reference data includes utilizing PM to monitor the PM data that equipment gathers；Obtain relative temperature data and relative humidity data again；And set up recurrence correction function with relative humidity data and relative temperature data for independent variable with the first reference data, and obtain final correction result PM2.5 data, wherein, the first reference data is the PM2.5 data value obtained by the second by ionization method.
Further, return correction function and include with the first reference data and relative humidity for independent variable, correction result is the recurrence correction function of dependent variable and with the first reference data and relative temperature for independent variable, correction result is the recurrence correction function of dependent variable, also including with the first reference data and relative temperature, relative humidity for independent variable, correction result is the recurrence correction function of dependent variable.
Further, with the first reference data and relative humidity for independent variable, the correction function that correction result is dependent variable is:
。
Further, with the first reference data and relative temperature for independent variable, the correction function that correction result is dependent variable is:
。
Further, with the first reference data and relative temperature, relative humidity for independent variable, the recurrence correction function that correction result is dependent variable is:
；
Wherein: PE is the first reference data, RH is relative humidity pa, and tem is relative temperature parameter.
Embodiment 1
Relation between relative humidity and correction result PM2.5 data.
As shown in Figure 2, the scatterplot of device data and correction result PM2.5 data is monitored under high relative humidity on low relative humidity.I.e. correction result PM2.5 data one timing, high than under low relative humidity of the data that under high relative humidity, monitoring equipment records.
By as can be seen from Figure 3, the scatterplot that relative humidity is higher is distributed in above recurrence series lines, and the relatively low scatterplot of relative humidity is distributed in below recurrence series lines.Then it can be seen that the regression slope of monitoring device data and correction result PM2.5 data and intercept exist certain difference.Thus when monitoring device data is calculated correction result PM2.5 data, relative humidity is an important influence factor.
The linear regression statistics of table one PE data and relative humidity and correction data describes
By the statistical method of linear regression, it is possible to the regression function obtained is as follows:
；
Describe the relation that final correction result PM2.5 data exist with humidity.
Embodiment 2
Relation between relative temperature and correction result PM2.5 data.
As shown in Figure 5, under low temperature the scatterplot of correction result PM2.5 data and correction result PM2.5 data on high-temperature.I.e. official's correction result PM2.5 data one timing, low than under low temperature of the data that under high-temperature, Pegasor records.
It will be appreciated from fig. 6 that the relatively low scatterplot of temperature is distributed in above recurrence series lines, the scatterplot that temperature is higher is distributed in below recurrence series lines.Then, there is certain difference with regression slope and the intercept of correction result PM2.5 value in monitoring device data.Thus when monitoring device data is calculated correction result PM2.5 data, temperature is also an important influence factor.
Table two is monitored the linear regression statistics of device data and temperature and correction result PM2.5 data and is described
By the statistical method of linear regression, it is possible to the regression function obtained is as follows:
；
Describe the relation that final correction result PM2.5 data exist with humidity.
Embodiment 3
The impact on correction result PM2.5 data of relative temperature, relative humidity.
The linear regression statistics of table three, monitoring equipment, temperature and relative humidity and official's Monitoring Data describes
The regression function obtained is as follows:
。
Claims (6)
1. the method utilizing meteorologic parameter correction indoor and outdoor PM2.5 monitoring result, it is characterised in that obtain the first reference data PE, the first wherein said reference data includes utilizing PM to monitor the PM data that equipment gathers；
Obtain relative temperature data and relative humidity data；
Set up recurrence correction function with relative humidity data and relative temperature data for independent variable with the first reference data, obtain final correction result PM2.5 data.
2. a kind of method utilizing meteorologic parameter correction indoor and outdoor PM2.5 monitoring result according to claim 1, it is characterised in that the first described reference data is the PM2.5 data value obtained by the second by ionization method.
3. a kind of method utilizing meteorologic parameter correction indoor and outdoor PM2.5 monitoring result according to claim 1, it is characterized in that, described recurrence correction function includes with the first reference data and relative humidity for independent variable, correction result is the recurrence correction function of dependent variable and with the first reference data and relative temperature for independent variable, correction result is the recurrence correction function of dependent variable, also including with the first reference data and relative temperature, relative humidity for independent variable, correction result is the recurrence correction function of dependent variable.
4. a kind of method utilizing meteorologic parameter correction indoor and outdoor PM2.5 monitoring result according to claim 3, it is characterised in that described with the first reference data with relative humidity for independent variable, the correction function that correction result is dependent variable is:
；
Wherein: PE is the first reference data, RH is relative humidity pa.
5. a kind of method utilizing meteorologic parameter correction indoor and outdoor PM2.5 monitoring result according to claim 3, it is characterised in that described with the first reference data with relative temperature for independent variable, the correction function that correction result is dependent variable is:
；
Wherein: PE is the first reference data, tem is relative temperature parameter.
6. a kind of method utilizing meteorologic parameter correction indoor and outdoor PM2.5 monitoring result according to claim 3, it is characterized in that, described with the first reference data with relative temperature, relative humidity for independent variable, the recurrence correction function that correction result is dependent variable is:
；
Wherein: PE is the first reference data, RH is relative humidity pa, and tem is relative temperature parameter.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107884322A (en) * | 2017-10-30 | 2018-04-06 | 重庆广睿达科技有限公司 | The dynamic calibration method and monitor that a kind of chemical constituent for eliminating particulate matter influences |
| CN107941666A (en) * | 2017-10-30 | 2018-04-20 | 重庆广睿达科技有限公司 | The dynamic calibration method and monitor that a kind of humiture for eliminating particulate matter influences |
| CN110785645A (en) * | 2017-06-21 | 2020-02-11 | 皇家飞利浦有限公司 | Particle sensor and particle sensing method |
| CN111103015A (en) * | 2019-12-27 | 2020-05-05 | 重庆诚业建筑工程有限公司 | Building engineering environment monitoring device and method with good stability |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110785645A (en) * | 2017-06-21 | 2020-02-11 | 皇家飞利浦有限公司 | Particle sensor and particle sensing method |
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| CN111103015A (en) * | 2019-12-27 | 2020-05-05 | 重庆诚业建筑工程有限公司 | Building engineering environment monitoring device and method with good stability |
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Denomination of invention: Method for correcting indoor and outdoor PM2.5 monitoring results by virtue of meteorological parameters Effective date of registration: 20190509 Granted publication date: 20190118 Pledgee: Bank of Tai'an, Limited by Share Ltd, Ji'nan branch Pledgor: Jinan Dalu Electromechanical Co., Ltd. Registration number: 2019370000102 |
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Date of cancellation: 20200429 Granted publication date: 20190118 Pledgee: Bank of Tai'an, Limited by Share Ltd, Ji'nan branch Pledgor: JINAN DALU MECHANISM & ELECTRON Co.,Ltd. Registration number: 2019370000102 |
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