CN109932287A - A kind of algorithm of interior PM2.5 mass concentration and number concentration conversion - Google Patents
A kind of algorithm of interior PM2.5 mass concentration and number concentration conversion Download PDFInfo
- Publication number
- CN109932287A CN109932287A CN201711370485.3A CN201711370485A CN109932287A CN 109932287 A CN109932287 A CN 109932287A CN 201711370485 A CN201711370485 A CN 201711370485A CN 109932287 A CN109932287 A CN 109932287A
- Authority
- CN
- China
- Prior art keywords
- formula
- particulate matter
- concentration
- algorithm
- distribution function
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Abstract
The invention discloses the algorithms of a kind of interior PM2.5 mass concentration and number concentration conversion, PM2.5 concentration is tested by PM2.5 detecting instrument or PM2.5 sensor monitoring equipment, using logarithm normal distribution computation model, analytical Calculation gathers a kind of algorithm of the number concentration of the corresponding partial size section particle swarm of state particulate matter, surface area concentration and volumetric concentration.By the algorithm, the exposure level that fine particle under the conditions of varying environment enters human body can be characterized.
Description
Technical field
The present invention relates to the present invention relates to air environment monitoring field, especially a kind of interior PM2.5 mass concentration and meters
The algorithm of Particle density conversion.
Background technique
Room air pollution directly threatens residential environments healthy, influences the working efficiency of personnel, and concerning people's life matter
Happiness is measured, therefore realizes that effective prevention and control of indoor air pollutants are to realize the important ring about healthy building proposition in recent years
Section.
PM2.5 be China in recent years the primary pollutant of main cities and architecture indoor fine particle pollution it is important
Source.It is current portable instrumentation, particulate matter Sensitive Detector based on light scattering principle measurement PM2.5 mass concentration
Main application method is a kind of method for acquiring fine particle quality concentration by measuring signal Parameter Switch.Currently based on light
The PM2.5 measuring technique of scattering principle is used and is promoted in the micro- station of China's outside atmosphere environment, architecture indoor.
As fine particle gos deep into the research of human health effect, fine particle number concentration, area concentration, volume
Concentration etc. becomes the characteristic index of important surrounding air, at present to the dependence test instrument and its test method of this kind of index
It is rare to address.
Summary of the invention
The technical problems to be solved by the invention overcome the deficiencies of the prior art and provide a kind of interior PM2.5 mass concentration
With the algorithm of number concentration conversion, PM2.5 concentration is tested by PM2.5 detecting instrument or PM2.5 sensor monitoring equipment, is utilized
Logarithm normal distribution computation model, number concentration, the surface area that analytical Calculation gathers the corresponding partial size section particle swarm of state particulate matter are dense
A kind of algorithm of degree and volumetric concentration, thus the level of pollution under Efficient Characterization fine particle difference quantitative model.
Technical solution provided by the invention is as follows:
A kind of algorithm of interior PM2.5 mass concentration and number concentration conversion, comprising the following steps:
S01, the test under target environment is carried out using PM2.5 detection/monitoring device, obtains PM2.5 mass concentration；
Particulate matter mono-modal particle size distributed model under S02, setting test surrounding air, establishes the counting logarithm of particulate matter
Normal state spectral distribution functionSuch as formula (1):
In formula, Dp is that particulate emission source migrates partial size；
Dp, i are single mode peak diameter；
NiFor the Particle density distribution density of peak diameter peak diameter；
The dispersion degree of logarithm normal distribution or geometric standard deviation (GSD) under σ i different modalities；
S03, convert particulate matter quality spectral distribution function respectivelyParticulate matter area Spectral structure
FunctionParticulate matter volume spectral distribution functionSuch as formula (2), formula (3), formula
(4):
In formula, ρeFor the particle density under some partial size；
Df is the form factor of particulate matter (as assumed, particulate matter is spherical, then Df=3)；
S04, pass through the quality spectral distribution function to formula (2)Integral (0.1~2.5 μm of grain
Diameter section), the conversion relation of distribution function Yu PM2.5 mass concentration is obtained, such as formula (5)；
S05, to (such as motor-vehicle tail-gas environment, interior uses mosquito-repellent incense environment) under specific environment, according to relevant environment sky
Gas is to particle size distribution tests document, setup algorithm model parameter, includingσi、ρeAnd Df；
S06, according to formula (5) and Ionosphere model calculating formula, integral function formula (5) inverse can be solved, obtain peak value
The Particle density distribution density N of partial sizei, then by formula (1), formula (3), formula (4) Integration Solving, the counting that can calculate particulate matter group is dense
N, area concentration S, volumetric concentration V are spent, such as formula (6), formula (7), formula (8)；
Preferably, in step S02, particulate matter mono-modal particle size distributed model is suitable for 0.1~2.5 μm of accumulation state
Grain object partial size section.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, following embodiment, to the present invention into
Row is further described.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not used to
Limit the present invention.As long as in addition, technical characteristic involved in the various embodiments of the present invention described below each other it
Between do not constitute conflict and can be combined with each other.
The present invention provides the algorithms of a kind of interior PM2.5 mass concentration and number concentration conversion, comprising the following steps:
S01, the test under target environment is carried out using PM2.5 detection/monitoring device, obtains PM2.5 mass concentration；
Particulate matter mono-modal particle size distributed model under S02, setting test surrounding air, the distribution of particulate matter mono-modal particle size
Model is suitable for 0.1~2.5 μm of accumulation state particle size section.Establish the counting lognormal spectral distribution function of particulate matterSuch as formula (1):
In formula, Dp is that particulate emission source migrates partial size；
Dp, i are single mode peak diameter；
NiFor the Particle density distribution density of peak diameter peak diameter；
The dispersion degree of logarithm normal distribution or geometric standard deviation (GSD) under σ i different modalities；
S03, convert particulate matter quality spectral distribution function respectivelyParticulate matter area Spectral structure
FunctionParticulate matter volume spectral distribution functionSuch as formula (2), formula (3), formula
(4):
In formula, ρeFor the particle density under some partial size；
Df is the form factor of particulate matter (as assumed, particulate matter is spherical, then Df=3)；
S04, pass through the quality spectral distribution function to formula (2)Integral (0.1~2.5 μm of grain
Diameter section), the conversion relation of distribution function Yu PM2.5 mass concentration is obtained, such as formula (5)；
S05, to (such as motor-vehicle tail-gas environment, interior uses mosquito-repellent incense environment) under specific environment, according to relevant environment sky
Gas is to particle size distribution tests document, setup algorithm model parameter, includingσi、ρeAnd Df；
S06, according to formula (5) and Ionosphere model calculating formula, integral function formula (5) inverse can be solved, obtain peak value
The Particle density distribution density N of partial sizei, then by formula (1), formula (3), formula (4) Integration Solving, the counting that can calculate particulate matter group is dense
N, area concentration S, volumetric concentration V are spent, such as formula (6), formula (7), formula (8)；
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, not to
The limitation present invention, any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should all wrap
Containing within protection scope of the present invention.
Claims (2)
1. the algorithm of a kind of interior PM2.5 mass concentration and number concentration conversion, comprising the following steps:
S01, the test under target environment is carried out using PM2.5 detection/monitoring device, obtains PM2.5 mass concentration；
Particulate matter mono-modal particle size distributed model under S02, setting test surrounding air, establishes the counting lognormal spectrum of particulate matter
Distribution functionSuch as formula (1):
In formula, Dp is that particulate emission source migrates partial size；
For single mode peak diameter；
NiFor the Particle density distribution density of peak diameter peak diameter；
The dispersion degree of logarithm normal distribution or geometric standard deviation (GSD) under σ i different modalities；
S03, convert particulate matter quality spectral distribution function respectivelyParticulate matter area spectral distribution functionParticulate matter volume spectral distribution functionSuch as formula (2), formula (3), formula (4):
In formula, ρeFor the particle density under some partial size；
Df is the form factor of particulate matter (as assumed, particulate matter is spherical, then Df=3)；
S04, pass through the quality spectral distribution function to formula (2)Integral (0.1~2.5 μm of partial size section),
The conversion relation of distribution function Yu PM2.5 mass concentration is obtained, such as formula (5)；
S05, to (such as motor-vehicle tail-gas environment, interior uses mosquito-repellent incense environment) under specific environment, according to relevant environment air pair
Particle size distribution tests document, setup algorithm model parameter, includingσi、ρeAnd Df；
S06, according to formula (5) and Ionosphere model calculating formula, integral function formula (5) inverse can be solved, obtain peak diameter
Particle density distribution density Ni, then by formula (1), formula (3), formula (4) Integration Solving, number concentration N, the face of particulate matter group can be calculated
Product concentration S, volumetric concentration V, such as formula (6), formula (7), formula (8)；
2. the algorithm of a kind of interior PM2.5 mass concentration and number concentration conversion as described in claim 1, it is characterised in that:
In step S02, particulate matter mono-modal particle size distributed model is suitable for 0.1~2.5 μm of accumulation state particle size section.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711370485.3A CN109932287A (en) | 2017-12-19 | 2017-12-19 | A kind of algorithm of interior PM2.5 mass concentration and number concentration conversion |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711370485.3A CN109932287A (en) | 2017-12-19 | 2017-12-19 | A kind of algorithm of interior PM2.5 mass concentration and number concentration conversion |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109932287A true CN109932287A (en) | 2019-06-25 |
Family
ID=66983244
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711370485.3A Pending CN109932287A (en) | 2017-12-19 | 2017-12-19 | A kind of algorithm of interior PM2.5 mass concentration and number concentration conversion |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109932287A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103245637A (en) * | 2013-04-16 | 2013-08-14 | 北京清风康华科技有限公司 | Method for converting particle number concentration measured by using light scattering method into mass concentration and detector |
| CN104122180A (en) * | 2014-07-21 | 2014-10-29 | 青岛众瑞智能仪器有限公司 | Method for measuring mass concentration of particulate matter |
| CN105300861A (en) * | 2014-05-28 | 2016-02-03 | 富士通株式会社 | Measurement device and method of measuring |
| CN105973768A (en) * | 2016-04-27 | 2016-09-28 | 北京爱空气科技有限公司 | Air particulate matter detection method, system and device |
| CN106338461A (en) * | 2016-08-18 | 2017-01-18 | 王清勤 | Building indoor particle concentration calculating system and implementation method |
| CN107389526A (en) * | 2017-07-24 | 2017-11-24 | 上海市建筑科学研究院(集团)有限公司 | A kind of air filter efficiency evaluation method |
-
2017
- 2017-12-19 CN CN201711370485.3A patent/CN109932287A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103245637A (en) * | 2013-04-16 | 2013-08-14 | 北京清风康华科技有限公司 | Method for converting particle number concentration measured by using light scattering method into mass concentration and detector |
| CN105300861A (en) * | 2014-05-28 | 2016-02-03 | 富士通株式会社 | Measurement device and method of measuring |
| CN104122180A (en) * | 2014-07-21 | 2014-10-29 | 青岛众瑞智能仪器有限公司 | Method for measuring mass concentration of particulate matter |
| CN105973768A (en) * | 2016-04-27 | 2016-09-28 | 北京爱空气科技有限公司 | Air particulate matter detection method, system and device |
| CN106338461A (en) * | 2016-08-18 | 2017-01-18 | 王清勤 | Building indoor particle concentration calculating system and implementation method |
| CN107389526A (en) * | 2017-07-24 | 2017-11-24 | 上海市建筑科学研究院(集团)有限公司 | A kind of air filter efficiency evaluation method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Koehler et al. | New methods for personal exposure monitoring for airborne particles | |
| Sayahi et al. | Development of a calibration chamber to evaluate the performance of low-cost particulate matter sensors | |
| Zikova et al. | Evaluation of new low-cost particle monitors for PM2. 5 concentrations measurements | |
| Volckens et al. | Development and evaluation of an ultrasonic personal aerosol sampler | |
| Duangsuwan et al. | A development on air pollution detection sensors based on NB-IoT network for smart cities | |
| Yanosky et al. | A comparison of two direct-reading aerosol monitors with the federal reference method for PM2. 5 in indoor air | |
| Wang-Li et al. | Techniques for measuring particle size distribution of particulate matter emitted from animal feeding operations | |
| KR20170024300A (en) | Mobile multi-air quality measurement system using a drone | |
| CN106768080A (en) | Many atmospheric parameter Vertical Profiles actual measurement new method that aerostatics is carried | |
| Buonanno et al. | Metrological performances of a diffusion charger particle counter for personal monitoring | |
| CN103954541B (en) | A kind of airborne fine particulate matter stereo monitoring system | |
| KR20170023601A (en) | Real time continuous radon detector | |
| CN108801341A (en) | A kind of Indoor Environment Detection system | |
| CN104568686A (en) | System and method for testing deposition coefficient of sub-micron particles in box body and average coagulation coefficient | |
| CN106979909B (en) | Particulate matter classification and concentration detection sensor and method based on luminous flux ratio | |
| CN203824873U (en) | Atmospheric fine particulate matter stereoscopic monitoring system | |
| Park et al. | The potential of commercial sensors for spatially dense short-term air quality monitoring based on multiple short-term evaluations of 30 sensor nodes in urban areas in Korea | |
| Hernández-Gordillo et al. | Recent advancements in low-cost portable sensors for urban and indoor air quality monitoring | |
| CN109932287A (en) | A kind of algorithm of interior PM2.5 mass concentration and number concentration conversion | |
| KR20200064957A (en) | Ventilation system for predicting indoor radon | |
| KR102101711B1 (en) | Ventilation system for predicting indoor radon | |
| Caya et al. | Air quality monitoring platform with the integration of dual sensor redundancy mechanism through internet of things | |
| Saputra et al. | Digital pulse analyzer for simultaneous measurement of pulse height, pulse width, and interval time on an optical particle counter | |
| Ames et al. | Optical measurements of aerosol size distributions in Great Smoky Mountains National Park: dry aerosol characterization | |
| Miyagawa et al. | Development of a Low-cost Gas Sensor Unit for Wide Area Air Pollution Monitoring System (poster) |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20190625 |
|
| WD01 | Invention patent application deemed withdrawn after publication |