CN107944213A - The online Source Apportionments of PMF, system, terminal device and computer-readable recording medium - Google Patents
The online Source Apportionments of PMF, system, terminal device and computer-readable recording medium Download PDFInfo
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Abstract
The present invention relates to the online Source Apportionments of PMF, system, terminal device and computer-readable recording medium, wherein method includes collection particle material resource, and on-line analysis obtains initial data；Initial data is imported, component selection is carried out according to particulate matter component classification to be detected, data Quality Control flow is enabled and initial data is screened automatically, is handled, obtain valid data；Valid data are inputted into PMF models, select particulate matter classification to be detected, particulate matter component classification to be detected, setting PMF model parameters are calculated, and obtain source resolution result；The automatic progress source class identification of identifing source rule by the source resolution result of acquisition by formulation, obtains pollutant source type.Beneficial effects of the present invention：Initial data obtains valid data according to data Quality Control flow；PMF algorithms calculate the contribution margin and uncertainty of pollution sources, with reference to derived components spectrum and the automatic identification pollutant source type such as interactive relation, factor important component information between relation, the factor between the factor.
Description
Technical field
The invention belongs to Particulate Pollution origin analysis field, more particularly to the online Source Apportionments of PMF, system, terminal
Equipment and computer-readable recording medium.
Background technology
Gray haze pollution is one of main atmospheric problem that current China city and region are faced, and shows generation frequency
It is secondary it is high, into haze region area it is big the characteristics of.Particulate matter origin analysis is science, effectively carries out the basic and preceding of gray haze prevention and cure of pollution
Carry, indispensable scientific basis is provided to formulate urban atmosphere Particulate Pollution control way.
Currently used method mainly passes through manual film sampling, off-line analysis technical limit spacing pollution sources component spectrum, acceptor
Chemical constituent and other auxiliary informations, the origin analysis of particulate matter is carried out using receptor model.This offline analytic method sampling
Time is longer, temporal resolution when small (24) is relatively low, and chemical analysis, data handling procedure are comparatively laborious, and model calculates special
Industry is stronger, it is impossible to meets to carry out quick origin analysis to the heavy air pollution process origin cause of formation occurred within a short period of time；Utilize PMF moulds
The online Source apportionment that type combination online monitoring data is established can realize the fast of particulate matter source in heavily contaminated synoptic process
Speed parsing.Although the technology can automatically obtain high-resolution particulate matter component data by online monitoring instruments, by
Larger in online data amount, it is to rely on manual operation to be calculated from data Quality Control to model, and workload is huge, is unfavorable for heavily contaminated
During particulate matter source fast resolving.The online source resolution skill that positive definite matrix PMF models couplings online monitoring data is established
Data processing, model calculating, the identification of source class in art etc. are required for manual hand manipulation, and time-consuming effort is technical strong, it is difficult to
To being widely popularized.
The content of the invention
To solve the above problems, the present invention provides PMF (Probabilistic Matrix Factorization) online
Source resolution system, has gathered Quality Control, PMF models (probability matrix decomposition model) calculating, the identification of result source class of online data etc.
Plate, realizes online source resolution data processing, the automation mechanized operation of source class identification, convenient and efficient, substantially increases source resolution
The efficiency of work.
The technical solution of invention：The online Source Apportionments of PMF, it is characterised in that comprise the following steps：
Step a:Online acquisition obtains monitoring initial data；
Step b:Monitoring initial data is imported, component selection is carried out according to particulate matter component classification to be detected, enables data
Quality Control flow is automatically screened initial data, is handled, and obtains Quality Control valid data；
Step c:Valid data are inputted into PMF models, select particulate matter classification to be detected, particulate matter component class to be detected
Not, setting PMF model parameters are calculated, and obtain source resolution result；
Step d:The automatic progress source class identification of identifing source rule by the source resolution result of acquisition by formulation, is polluted
Source Type.
Further, the step b specifically includes following steps：
Step 1：Online acquisition is imported to obtain initial data and initialize initial data；
Step 2：Initial data after initialization is subjected to component selection according to particulate matter component classification to be detected, is formed
Sort data；
Step 3：Sorting data are judged whether to enable data Quality Control according to Atmospheric Chemistry mechanism, Monitoring factors relevance
Flow, if being judged as YES, step 4 is performed after enabling data Quality Control flow；If be judged as whether, directly obtain Quality Control significant figure
According to；
Step 4：Judge whether to enable data validity statistical rules, if being judged as YES, enable data validity statistics rule
Step 5 is then performed afterwards；If be judged as whether, directly perform step 5；
Step 5：Judge whether to enable data correlation diagnosis, if being judged as YES, performed after enabling data correlation diagnosis
Step 6；If be judged as whether, directly perform step 6；
Step 6：Judge whether to enable value judgment rule less than normal bigger than normal, if being judged as YES, enable value less than normal bigger than normal and judge rule
Step 7 is then performed afterwards；If be judged as whether, directly perform step 7；
Step 7：Judge whether to enable continuous data processing rule, if being judged as YES, after enabling continuous data processing rule
Obtain data after Quality Control；If be judged as whether, directly obtain Quality Control valid data.
Further, the particulate matter component classification to be detected specifically includes 6 major classes：PM2.5 data：PM2.5；EC/OC：
EC、OC；Anion：SO4 2-、NO3 -、Cl-All inorganic anion data that instrument can measure；Cation：NH4 +、K+、Na+Deng
All inorganic cation data that all appts can measure；Elemental composition：All heavy metal ion that Fe, Ca, K instrument can measure
Data；Gas componant：HCL、HONO、SO2The gas component data that all appts can measure；
Preferably, the parameter of PMF models includes the uncertain relevant parameter of test limit, input data and the factor of identification
Number.
Further, data validity statistical rules includes in the step 4：
A：PM2.5 data, EC/OC, anion, cation, the component of 5 major class of elemental composition have a type not have data,
Default data is lacked, deletes full line；
B：The a certain categorical data effective percentage of EC/OC, anion, cation, elemental composition, the component of gas componant, which is less than, to be set
When definite value, full line is deleted；
C：Statistics miss rate, miss rate are higher than setting value, are calculated without source resolution；
D：For missing data using preceding 6 it is small when sliding average substitute；
Preferably, data correlation diagnostic rule includes in the step 5：
E:Statistics step-length is set：Statistical analysis is carried out to the data in setting according to self-defined setting step-length scope；
F:Three classes material is performed to PM2.5 accounting judgment rules：Analyze PM2.5Concentration, EC/OC, zwitterion, element into
Point, meet three kinds of species concentration addition/PM after 30~50% ＜2.5The requirements of concentration ＜ 60~80%, then the batch data is reasonable, then
EC/OC, anion, cation, the weight of elemental composition are set；For being unsatisfactory for three kinds of species concentration phases after 30~50% ＜
Add/PM2.5The data of the requirements of concentration ＜ 60~80% delete whole section of result；
G:OCEC/ ions/element is performed with respect to accounting judgment rule：EC/OC is analyzed, zwitterion, element three are opposite
Relation, meets 20~30%<Tri- kinds of species concentration adductions of EC/OC/<40~50%, 45~55%<Zwitterion/tri- kind species
Concentration adduction<65~75%, 1~2%<Element/tri- kind species concentration adduction<4~6% require, then the batch data is reasonable；For
It is unsatisfactory for 20~30%<Tri- kinds of species concentration adductions of EC/OC/<40~50%, 45~55%<Zwitterion/tri- kind species concentration
Adduction<65~75%, 1~2%<Element/tri- kind species concentration adduction<4~6% desired data delete whole section of result；
Preferably, value judgment rule less than normal bigger than normal includes in the step 6：
H:Statistics step-length is set：Statistical analysis is carried out to the data in setting according to self-defined setting step-length scope；
I:In statistics step-length, N values are separately provided to each classification respectively, to the value more than average value ± N standard deviations
Rejected；
J:For abnormal data bigger than normal or less than normal using preceding 6 it is small when sliding average substitute；
Preferably, continuous data processing rule includes in the step 7：
K:1/2 detection limit of data less than detection limit substitutes；
L:Continuously judged for the data more than or equal to 3 times of detection limits, if deviation is in certain model when continuous N is small
In enclosing, then by data delete processing；
M:For continuous data using preceding 6 it is small when sliding average substitute.
Further, in the step d identifing source combine based on the recognition methods of ratio characteristics component, based on factor spectrum with
The recognition methods of derived components spectrum correlation and source class identification is carried out based on the factor and the recognition methods of component time series correlation.
Further, the detailed process initialized in the step 1 to initial data：Automatic identification time fences are
The importing data of null value, and delete the row；Automatic identification concentration of component is the importing data of null value, and assignment " 0 ".
The online source resolution systems of PMF, it is characterised in that including：
Data acquisition module, for gathering particle material resource, on-line analysis obtains the module of initial data；
The quality Control module of online data, for importing initial data, component is carried out according to particulate matter component classification to be detected
Choose, enable data Quality Control flow and initial data is screened automatically, is handled, obtain the module of Quality Control valid data；
PMF model computation modules, for valid data to be inputted PMF models, select particulate matter classification to be detected, to be detected
Particulate matter component classification, setting PMF model parameters are calculated, and obtain the module of source resolution result；
As a result source class identification module, the automatic progress source class knowledge of identifing source rule that the source resolution result of acquisition is passed through into formulation
Not, the module of pollutant source type is obtained.
Further, the quality Control module of the online data includes：
Original data units are imported, on-line analysis is imported and obtains initial data and the list initialized to initial data
Member；
Particulate matter component classification to be detected chooses unit, by the initial data after initialization according to particulate matter component to be detected
Classification carries out component selection, forms the unit of sorting data；
Data Quality Control flow elements, for being screened, being handled to initial data automatically, obtain the list of quality inspection valid data
Member.
A kind of online source resolution terminal devices of PMF, including memory, processor and be stored in the memory and can
The computer program run on the processor, it is characterised in that the processor is realized when performing the computer program
The step of PMF online Source Apportionments.
A kind of computer-readable recording medium of the online source resolution programs of storage PMF, the computer-readable recording medium
It is stored with computer program, it is characterised in that the computer program realizes the PMF in line-source solution side when being executed by processor
The step of method.
Present invention has the advantages that：Particulate matter classification to be detected, particulate matter component classification to be detected is selected to carry out source point
Analysis；Data can be realized according to Atmospheric Chemistry mechanism, Monitoring factors relevance data Quality Control flow to the initial data of reception
Automatic examination ＆ verification and optimization, the final quality inspection valid data for obtaining high quality；The contribution margin of all kinds of pollution sources is calculated using PMF algorithms
And uncertainty, and shown with graph mode, including the hour source resolution result of specified time section particulate matter, pollution source time sequence
Row stack figure, pollution sources fingerprints etc.；With reference to derived components spectrum and interactive relation, factor important set between relation, the factor between the factor
Divide the automatic identification pollutant source types such as information.
Brief description of the drawings
Fig. 1 is the data Quality Control flow chart of the online Source Apportionments of PMF of the embodiment of the present invention 1.
Fig. 2 is the online source resolution system architecture diagrams of PMF of the embodiment of the present invention 1.
Fig. 3 is the source class identification process figure of the embodiment of the present invention 1.
Fig. 4 is that the initial data of the embodiment of the present invention 1 imports page figure.
Fig. 5 is 1 original data portion sectional drawing of the embodiment of the present invention.
Fig. 6 is that the initial data of the embodiment of the present invention 1 imports and displaying interface.
Fig. 7 is the essential component of 1 Quality control rules menu item of the embodiment of the present invention and optional component dialogue block diagram.
Fig. 8 is the efficient analysis dialogue block diagram of every class of 1 validity statistical rules of the embodiment of the present invention.
Fig. 9 is the shortage of data rate statistics dialog box of 1 validity statistical rules of the embodiment of the present invention.
Figure 10 be 1 validity statistical rules of the embodiment of the present invention preceding 6 it is small when sliding average replace dialog box.
Figure 11 is that the embodiment of the present invention 1 includes the input data of PMF models calculating and essential chemical constituent sectional drawing.
Figure 12 is that the input data that PMF models calculate in the embodiment of the present invention 1 does not know to set dialogue block diagram.
Figure 13 is the factor spectrum displaying interface that PMF models calculate in the embodiment of the present invention 1.
Figure 14 is 1 source contribution result of the embodiment of the present invention displaying interface.
Figure 15 is 1 source resolution percentage result time series of the embodiment of the present invention and figure source resolution pie chart.
Figure 16 is that the rule one, rule two, regular three interfaces of the embodiment of the present invention 1 provide three introduces a collection recognition rules respectively
The result figure obtained afterwards.
Embodiment
Explain below in conjunction with the accompanying drawings to a kind of embodiment of the present invention.
The online Source Apportionments of PMF, comprise the following steps：
Step a:Online acquisition obtains monitoring initial data；
Step b:Monitoring initial data is imported, component selection is carried out according to particulate matter component classification to be detected, enables data
Quality Control flow is automatically screened initial data, is handled, and obtains Quality Control valid data；
Step c:Valid data are inputted into PMF models, select particulate matter classification to be detected, particulate matter component class to be detected
Not, setting PMF model parameters are calculated, and obtain source resolution result；
Step d:The automatic progress source class identification of identifing source rule by the source resolution result of acquisition by formulation, is polluted
Source Type.
Wherein, step b specifically includes following steps：
Rapid one：Online acquisition is imported to obtain initial data and initialize initial data；
Step 2：Initial data after initialization is subjected to component selection according to particulate matter component classification to be detected, is formed
Sort data；
Step 3：Sorting data are judged whether to enable data Quality Control according to Atmospheric Chemistry mechanism, Monitoring factors relevance
Flow, if being judged as YES, step 4 is performed after enabling data Quality Control flow；If be judged as whether, directly obtain Quality Control significant figure
According to；
Step 4：Judge whether to enable data validity statistical rules, if being judged as YES, enable data validity statistics rule
Step 5 is then performed afterwards；If be judged as whether, directly perform step 5；
Step 5：Judge whether to enable data correlation diagnosis, if being judged as YES, performed after enabling data correlation diagnosis
Step 6；If be judged as whether, directly perform step 6；
Step 6：Judge whether to enable value judgment rule less than normal bigger than normal, if being judged as YES, enable value less than normal bigger than normal and judge rule
Step 7 is then performed afterwards；If be judged as whether, directly perform step 7；
Step 7：Judge whether to enable continuous data processing rule, if being judged as YES, after enabling continuous data processing rule
Obtain data after Quality Control；If be judged as whether, directly obtain Quality Control valid data.
Wherein, particulate matter component classification to be detected specifically includes 6 major classes：PM2.5 data：PM2.5；EC/OC：EC、OC；It is cloudy
Ion：SO4 2-、NO3 -、Cl-All inorganic anion data that instrument can measure；Cation：NH4 +、K+、Na+Deng all appts
All inorganic cation data that can be measured；Elemental composition：All heavy metal ion data that Fe, Ca, K instrument can measure；Gas
Body component：HCL、HONO、SO2The gas component data that all appts can measure；
The parameter of PMF models is including test limit, the uncertain relevant parameter of input data and identification because of subnumber.
Wherein, data validity statistical rules includes in step 4：
A：PM2.5 data, EC/OC, anion, cation, the component of 5 major class of elemental composition have a type not have data,
Default data is lacked, deletes full line；
B：The a certain categorical data effective percentage of EC/OC, anion, cation, elemental composition, the component of gas componant, which is less than, to be set
When definite value, full line is deleted；
C：Statistics miss rate, miss rate are higher than setting value, are calculated without source resolution；
D：For missing data using preceding 6 it is small when sliding average substitute；
Data correlation diagnostic rule includes in step 5：
E:Statistics step-length is set：Statistical analysis is carried out to the data in setting according to self-defined setting step-length scope；
F:Three classes material is performed to PM2.5 accounting judgment rules：Analyze PM2.5Concentration, EC/OC, zwitterion, element into
Point, meet three kinds of species concentration addition/PM after 30~50% ＜2.5The requirements of concentration ＜ 60~80%, then the batch data is reasonable, then
EC/OC, anion, cation, the weight of elemental composition are set；For being unsatisfactory for three kinds of species concentration phases after 30~50% ＜
Add/PM2.5The data of the requirements of concentration ＜ 60~80% delete whole section of result；
G:OCEC/ ions/element is performed with respect to accounting judgment rule：EC/OC is analyzed, zwitterion, element three are opposite
Relation, meets 20~30%<Tri- kinds of species concentration adductions of EC/OC/<40~50%, 45~55%<Zwitterion/tri- kind species
Concentration adduction<65~75%, 1~2%<Element/tri- kind species concentration adduction<4~6% require, then the batch data is reasonable；For
It is unsatisfactory for 20~30%<Tri- kinds of species concentration adductions of EC/OC/<40~50%, 45~55%<Zwitterion/tri- kind species concentration
Adduction<65~75%, 1~2%<Element/tri- kind species concentration adduction<4~6% desired data delete whole section of result；
Value judgment rule less than normal bigger than normal includes in step 6：
H:Statistics step-length is set：Statistical analysis is carried out to the data in setting according to self-defined setting step-length scope；
I:In statistics step-length, N values are separately provided to each classification respectively, to the value more than average value ± N standard deviations
Rejected；
J:For abnormal data bigger than normal or less than normal using preceding 6 it is small when sliding average substitute；
Continuous data processing rule includes in step 7：
K:1/2 detection limit of data less than detection limit substitutes；
L:Continuously judged for the data more than or equal to 3 times of detection limits, if deviation is in certain model when continuous N is small
In enclosing, then by data delete processing；
M:For continuous data using preceding 6 it is small when sliding average substitute.
Identifing source combines based on the recognition methods of ratio characteristics component, is related to derived components spectrum based on factor spectrum in step d
Property recognition methods and source class identification is carried out based on the factor and the recognition methods of component time series correlation.
Wherein, the detailed process processing initialized in step 1 to initial data：Time fences for importing data
For the meeting automatic identification of null value, and delete the row；For importing the meeting automatic identification that concentration of component in data is null value, and assignment
“0”；Unit is uniformly processed, and elemental composition retains after decimal point four, remaining component retains 2 significant digits.
The online source resolution systems of PMF, it is characterised in that including with lower module：
Data acquisition module, for gathering particle material resource, on-line analysis obtains the module of initial data；
The quality Control module of online data, for importing initial data, component is carried out according to particulate matter component classification to be detected
Choose, enable data Quality Control flow and initial data is screened automatically, is handled, obtain the module of valid data；
PMF model computation modules, for valid data to be inputted PMF models, select particulate matter classification to be detected, to be detected
Particulate matter component classification, setting PMF model parameters are calculated, and obtain the module of source resolution result；
As a result source class identification module, the automatic progress source class knowledge of identifing source rule that the source resolution result of acquisition is passed through into formulation
Not, the module of pollutant source type is obtained.
The quality Control module of online data is included with lower unit：
Original data units are imported, on-line analysis is imported and obtains initial data and the list initialized to initial data
Member；
Particulate matter component classification to be detected chooses unit, by the initial data after initialization according to particulate matter component to be detected
Classification carries out component selection, forms the unit of sorting data；
Data Quality Control flow elements, for being screened, being handled to initial data automatically, obtain the unit of valid data.
A kind of online source resolution terminal devices of PMF, including memory, processor and storage in memory and can located
The computer program run on reason device, it is characterised in that processor realizes the online Source Apportionments of PMF when performing computer program
The step of.
A kind of computer-readable recording medium of the online source resolution programs of storage PMF, computer-readable recording medium storage
There is computer program, it is characterised in that realize PMF the line-source solution method the step of when computer program is executed by processor.
Embodiment 1
Fig. 1 is the data Quality Control flow chart of the online Source Apportionments of PMF of the embodiment of the present invention 1.
The online Source Apportionments of PMF, it is characterised in that comprise the following steps：
Step a:Particle material resource is gathered, on-line analysis obtains initial data；Specifically：Analyzed using AMMS atmosphere heavy metals
Instrument, WAGA air water soluble ion components in-line analyzer, the monitoring data of air OCEC in-line analyzers, on-line analysis obtain
Initial data；
Step b:Initial data is imported, component selection is carried out according to particulate matter component classification to be detected, enables data Quality Control
Flow is automatically screened initial data, is handled, and obtains valid data；Enough initial data to reception, according to Atmospheric Chemistry
Mechanism, Monitoring factors relevance etc. realize the automatic examination ＆ verification and optimization of data, the final data set for obtaining high quality；
Fig. 2 is the online source resolution system architecture diagrams of PMF of the embodiment of the present invention 1.Data Quality Control flow includes following
Step：
Step 1：On-line analysis is imported to obtain initial data and initialize initial data；
The detailed process processing that on-line analysis obtains initial data and initialized to initial data is imported in step 1：
Initial data is poured into importing：
Fig. 4 is that the initial data of the embodiment of the present invention 1 imports page figure.Specific find is named as " initial data
.excel file ", clicks on and opens importing file.
Fig. 5 is 1 original data portion sectional drawing of the embodiment of the present invention." initial data .excel " files
" initial data .excel " file explanations：First behavior component information, the capital and small letter of component and Format Reference Quality Control
In rule " essential component " and " optional component ", its bracket is necessary for english font input, and component order is adjustable；First is classified as
Time series, the time can not be sky, otherwise when importing software, meeting automatic identification, and delete the row.If the number of components imported
According to there are null value, program understands automatic identification, and assigns " 0 " value.
Fig. 6 is that the initial data of the embodiment of the present invention 1 imports and displaying interface.Click on " importing ", can be in " original number
According to " interface checks the primary data information (pdi) of loading
Initial data initializes：It is the meeting automatic identification of null value for the time fences for importing data, and deletes the row；For
Import the meeting automatic identification that concentration of component in data is null value, and assignment " 0 "；Unit is uniformly processed, and elemental composition retains decimal
Four after point, remaining component retains 2 significant digits.
Step 2：Component selection is carried out according to particulate matter component classification to be detected；Fig. 7 is 1 Quality Control of the embodiment of the present invention
The essential component of rule menu item and optional component dialogue block diagram.Component is chosen and specifically includes 6 major classes in step 2：PM2.5 data：
PM2.5；EC/OC：EC、OC；Anion：SO4 2-、NO3 -, all inorganic anion data that can measure of Cl- instruments；Cation：
NH4 +、K+、Na+All inorganic cation data that can be measured Deng all appts；Elemental composition：The institute that Fe, Ca, K instrument can measure
There are heavy metal ion data；Gas componant：The gas component data that HCL, HONO, SO2 all appts can measure.Concrete operations：
【Quality control rules】" essential component " and " optional component " provides the function of component selection in menu item, and can customize setting group
" detection limit ", " a " value and " b " value divided, wherein a, b value are used for the calculating of component uncertainty, click on " preservation " button
Complete related set.
Step 3：Judge whether to enable data Quality Control flow, if being judged as YES, step is performed after enabling data Quality Control flow
Four；If be judged as whether, the data after Quality Control.Data Quality Control flow mainly includes data validity statistical rules, data are closed
Connection property diagnostic rule, value judgment rule less than normal bigger than normal and continuous data processing rule；
Step 4：Judge whether to enable data validity statistical rules, if being judged as YES, enable data validity statistics rule
Step 5 is then performed afterwards；If be judged as whether, perform step 5；
Data validity statistical rules is specific as follows in step 4：
A：PM2.5 data, EC/OC, anion, cation, the component of 5 major class of elemental composition have a type not have data,
Default data is lacked, deletes full line：
B：The a certain categorical data effective percentage of EC/OC, anion, cation, elemental composition, the component of gas componant, which is less than, to be set
When definite value, full line is deleted；Fig. 8 is the efficient analysis dialogue of every class of the validity statistical rules of the embodiment of the present invention 1
Block diagram.For example, have chosen 10 elemental compositions, when being non-NULL valid data for wherein 5 groups, efficient data are 50%, at this
In if set effective percentage be less than 50%, the row can be deleted, otherwise retained；Fig. 8 is 1 validity of the embodiment of the present invention system
Count the efficient analysis dialogue block diagram of every class of rule.
C：Statistics miss rate, miss rate are higher than setting value, are calculated without source resolution；Figure is the implementation of 9 present invention
The shortage of data rate statistics dialog box of the validity statistical rules of example 1.
D：For missing data using preceding 6 it is small when sliding average substitute.The embodiment 1 of Figure 10 present invention
Preceding the 6 of validity statistical rules it is small when sliding average replace dialog box.
Step 5：Judge whether to enable data correlation diagnosis, if being judged as YES, performed after enabling data correlation diagnosis
Step 6；If be judged as whether, perform step 6；
Data correlation diagnostic rule is specific as follows in step 5：
E:Statistics step-length is set：Data in setting are carried out statistical analysis by self-defined setting step-length scope；Embodiment 1
Middle step-length is arranged to 1000；
F:Three classes material is to PM2.5 accounting judgment rules：PM2.5Concentration, EC/OC, zwitterion, elemental composition, meets
Three kinds of species concentration addition/PM after 40% (adjustable) ＜2.5Concentration ＜ 70% is (adjustable) to be required, then the batch data is reasonable, while can
EC/OC, anion, cation, the weight of elemental composition are set；For being unsatisfactory for three kinds of species concentration phases after 40% (adjustable) ＜
Add/PM2.5The data for requirement that concentration ＜ 70% is (adjustable) delete whole section of result；
G:OCEC/ ions/element is with respect to accounting judgment rule：EC/OC, zwitterion, element three's relativeness, will
This three major types component normalizes, and meets 25% (adjustable)<Tri- kinds of species concentration adductions of EC/OC/<45% (adjustable), 50% (can
Adjust)<Zwitterion/tri- kind species concentration adduction<70% (adjustable), 1% (adjustable)<Element/tri- kind species concentration adduction<5%
It is (adjustable) to require；Meet 25% (adjustable) for discontented<Tri- kinds of species concentration adductions of EC/OC/<45% (adjustable), 50% (can
Adjust)<Zwitterion/tri- kind species concentration adduction<70% (adjustable), 1% (adjustable)<Element/tri- kind species concentration adduction<5%
The data of (adjustable) requirement delete whole section of result；
Step 6：Judge whether to enable value judgment rule less than normal bigger than normal, if being judged as YES, enable value less than normal bigger than normal and judge rule
Step 7 is then performed afterwards；If be judged as whether, perform step 7；
Value judgment rule less than normal bigger than normal is specific as follows in step 6：
H:Statistics step-length is set：Data in setting are carried out statistical analysis by self-defined setting step-length scope；Embodiment 1
Middle step-length is arranged to 50；
I:In statistics step-length, the value more than average value ± n standard deviations is rejected, and each classification is separately provided N values；
1 Plays deviation n of embodiment is 3；
J:For abnormal data bigger than normal or less than normal using preceding 6 it is small when sliding average substitute.
Step 7：Judge whether to enable continuous data processing rule, if being judged as YES, after enabling continuous data processing rule
Obtain data after Quality Control；If be judged as whether, directly obtain data after Quality Control.
Continuous data processing rule is specific as follows in step 7：
K:1/2 detection limit of data less than detection limit substitutes.
L:Continuously judged for the data more than or equal to 3 times of detection limits, when continuous N is small, deviation within the specific limits,
By data delete processing；When being continuous 6 small in embodiment 1, deviation 5%；
M:For continuous data using preceding 6 it is small when sliding average substitute.
Step c:Valid data are inputted into PMF models, select particulate matter classification to be detected, particulate matter component class to be detected
Not, setting PMF model parameters are calculated, and obtain source resolution result.
Figure 11 is that the embodiment of the present invention 1 includes the input data of PMF models calculating and essential chemical constituent sectional drawing.Structure
PMF mode input data, input data include anion and cation, EC/OC, 5 major class component of elemental composition, PM2.5 data.
PM is measured using particulate matter online monitoring instruments2.5Concentration data.Utilize semicontinuous OC/EC apparatus measures EC/OC carbon components, bag
Include the concentration of OC and EC.Water soluble anion and cation, including NH are measured using online ion-chromatographic analyzer4 +、Na+、Mg2 +、S04 2-、NO3 -、Cl-Concentration.Using heavy metal online analyzer monitoring elements, including Ca, Mn, Fe, Cu, Zn, As, Se,
The concentration of Ba, Hg, Pb.(the component classification of each input data has certain change according to actual monitoring data).Four monitorings
Instrument gathers the sample of continuous a couple of days at the same time, when the data time resolution ratio of monitoring is 1 small.Select sample, the chemical group calculated
Point；The parameter of PMF models is inputted, the parameter for inputting PMF models will be according to the test limit of actual analysis instrument and input data
Uncertainty is configured, including two parameters, one be with the relevant parameter a of analytical instrument test limit, the other is with it is defeated
Enter the relevant parameter b of data uncertainty.Figure 12 is that the input data of PMF model computation modules of the present invention does not know to set dialogue
Block diagram；The factor number of model extraction is arranged to 4；Input identification because of subnumber.Generally it is defaulted as 0.6；Figure 12 is of the invention
The input data that PMF models calculate in embodiment 1 does not know to set dialogue block diagram.
Step d:The automatic progress source class identification of identifing source rule by the source resolution result of acquisition by formulation, is polluted
Source Type.
The result that model calculates can pass through the automatic progress source class identification of identifing source rule of formulation；As a result source class identification mould
Block, which is combined, to be identified based on the identification of ratio characteristics component, based on factor spectrum and derived components spectrum correlation and based on the factor and during component
Between serial correlation identification carry out source class identification.Fig. 3 is the flow chart of the result source class identification of the embodiment of the present invention 1.Rule
One：Identified based on ratio characteristics component
I factor spectrum baseline results laterally normalize；
II recognition rule is as follows：
It is airborne dust that 1. Ca accountings, which are distributed the highest factor,；2. OC and the highest factor of EC accounting adductions are motor vehicle；③OC
The high factor is fire coal with EC accountings adduction time；④SO4 2-It is two sulfoxylates that accounting, which is distributed the highest factor,；⑤NO3 -Accounting point
The highest factor of cloth is two nitroxylates；6. unidentified definition out is " other "
Rule two：Identified based on factor spectrum and derived components spectrum correlation
1. actual measurement derived components are composed in (the local actual measurement source spectrum of selection) embedded software, source spectrum such as table 1 is surveyed：
Table 1
| Airborne dust | It is coal-fired | Building | Two sulphoxylic acid | Two nitroxylic acids | Motor vehicle | |
| Na | 0.0173 | 0.0164 | 0.0156 | 0.0000 | 0.0000 | 0.0030 |
| Mg | 0.0114 | 0.0050 | 0.0137 | 0.0000 | 0.0000 | 0.0022 |
| K | 0.0085 | 0.0059 | 0.0212 | 0.0000 | 0.0000 | 0.0023 |
| Ca | 0.0800 | 0.0300 | 0.3921 | 0.0000 | 0.0000 | 0.0060 |
| Ti | 0.0043 | 0.0092 | 0.0036 | 0.0000 | 0.0000 | 0.0010 |
| Cr | 0.0000 | 0.0001 | 0.0003 | 0.0000 | 0.0000 | 0.0001 |
| Mn | 0.0004 | 0.0002 | 0.0005 | 0.0000 | 0.0000 | 0.0002 |
| Fe | 0.0236 | 0.0284 | 0.0173 | 0.0000 | 0.0000 | 0.0118 |
| Ni | 0.0001 | 0.0001 | 0.0000 | 0.0000 | 0.0000 | 0.0001 |
| Cu | 0.0003 | 0.0001 | 0.0003 | 0.0000 | 0.0000 | 0.0008 |
| Zn | 0.0006 | 0.0002 | 0.0000 | 0.0000 | 0.0000 | 0.0022 |
| Pb | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0003 |
| SO4 2- | 0.0650 | 0.1359 | 0.0160 | 0.7270 | 0.0000 | 0.0387 |
| NO3 - | 0.0030 | 0.0012 | 0.0000 | 0.0000 | 0.7750 | 0.0077 |
| NH4 + | 0.0002 | 0.0028 | 0 | 0.273 | 0.225 | 0.0242 |
| OC | 0.0630 | 0.1181 | 0.0041 | 0.0000 | 0.0000 | 0.3170 |
| EC | 0.0130 | 0.0826 | 0.0045 | 0.0000 | 0.0000 | 0.3020 |
2. extracting the component that factor spectrum is shared with surveying source spectrum, correlation analysis is carried out；
3. analyze related coefficient：Certain source spectrum and the factor significant correlation are preferably and related coefficient>0.6 (adjustable), then know
Not Wei the source class, it is unidentified out definition be " other ".
Rule three：Identified based on the factor and component time series correlation
1. the corresponding factor contributions time series of certain factor and Ca concentration of component time series correlations are best, and phase relation
Number>0.6 (adjustable), the factor are identified as airborne dust source；
2. the corresponding factor contributions time series of certain factor and OC concentration of component time series correlations are best, and phase relation
Number>0.6 (adjustable), the factor are identified as motor vehicle；
3. the corresponding factor contributions time series of certain factor and SO4 2-Concentration of component time series correlation is best, and related
Coefficient>0.6 (adjustable), the factor are identified as two sulphoxylic acid；
5. the corresponding factor contributions time series of certain factor and NO3 -Concentration of component time series correlation is best, and related
Coefficient>0.6 (adjustable), the factor are identified as two nitroxylic acids；
6. the corresponding factor contributions time series of certain factor and SO2Concentration-time serial correlation is best, and related coefficient>
0.6 (adjustable), the factor are identified as coal-fired source；
7. unidentified definition out is " other ".
Export the concentration and percentage of source contribution.Can " factor spectrum ", " source contribution ", " figure displaying ", etc. interface look into
See corresponding as a result, Figure 14 is 1 source contribution result of the embodiment of the present invention displaying interface.Source contribution interface provides the dense of all kinds of factors
Time series is spent, the time after time here and Quality Control is corresponding.
Figure 15 is the source resolution percentage result time series and figure source resolution pie chart of the embodiment of the present invention 1.Figure
Displaying provides all kinds of factor percentage stacking figures, and can customize switching each hour carrys out source contribution pie chart, and is arranged in statistics
The overall percentage accounting situation of all kinds of factors in timing statistics section is provided in table.
Figure 16 is that the rule one, rule two, regular three interfaces of the embodiment of the present invention 1 provide three kinds of identifing source rule respectively
The result figure then obtained afterwards.
A kind of online source resolution terminal devices of PMF, including memory, processor and storage in memory and can located
The computer program run on reason device, it is characterised in that processor realizes the online Source Apportionments of PMF when performing computer program
The step of.
A kind of computer-readable recording medium of the online source resolution programs of storage PMF, computer-readable recording medium storage
There is computer program, it is characterised in that realize PMF the line-source solution method the step of when computer program is executed by processor.
Compared with prior art, particulate matter classification to be detected, particulate matter component classification to be detected is selected to carry out source analysis；
Oneself of data can be realized according to Atmospheric Chemistry mechanism, Monitoring factors relevance data Quality Control flow to the initial data of reception
Dynamic examination ＆ verification and optimization, the final quality inspection valid data for obtaining high quality；Using PMF algorithms calculate all kinds of pollution sources contribution margin and
Uncertainty, and shown with graph mode, include hour source resolution result, the pollution sources time series of specified time section particulate matter
Stack figure, pollution sources fingerprints etc.；With reference to derived components spectrum and interactive relation, factor important component between relation, the factor between the factor
The automatic identification pollutant source type such as information.
An example of the present invention is described in detail above, but content is only presently preferred embodiments of the present invention, no
The practical range of the present invention can be construed as limiting.Any changes and modifications in accordance with the scope of the present application,
Should still it belong within the patent covering scope of the present invention.
Claims (10)
- The online Source Apportionments of 1.PMF, it is characterised in that comprise the following steps：Step a:Online acquisition obtains monitoring initial data；Step b:Monitoring initial data is imported, component selection is carried out according to particulate matter component classification to be detected, enables data Quality Control Flow is automatically screened initial data, is handled, and obtains Quality Control valid data；Step c:Valid data are inputted into PMF models, select particulate matter classification to be detected, particulate matter component classification to be detected, if Determine PMF model parameters to be calculated, obtain source resolution result；Step d:The automatic progress source class identification of identifing source rule by the source resolution result of acquisition by formulation, obtains pollution sources class Type.
- 2. the online Source Apportionments of PMF according to claim 1, it is characterised in that the step b specifically includes following step Suddenly：Step 1：Online acquisition is imported to obtain initial data and initialize initial data；Step 2：Initial data after initialization is subjected to component selection according to particulate matter component classification to be detected, forms sorting Data；Step 3：Sorting data are judged whether to enable data Quality Control flow according to Atmospheric Chemistry mechanism, Monitoring factors relevance, If being judged as YES, step 4 is performed after enabling data Quality Control flow；If be judged as whether, directly obtain Quality Control valid data；Step 4：Judge whether to enable data validity statistical rules, if being judged as YES, after enabling data validity statistical rules Perform step 5；If be judged as whether, directly perform step 5；Step 5：Judge whether to enable data correlation diagnosis, if being judged as YES, step is performed after enabling data correlation diagnosis Six；If be judged as whether, directly perform step 6；Step 6：Judge whether to enable value judgment rule less than normal bigger than normal, if being judged as YES, after enabling value judgment rule less than normal bigger than normal Perform step 7；If be judged as whether, directly perform step 7；Step 7：Judge whether to enable continuous data processing rule, if being judged as YES, obtained after enabling continuous data processing rule Data after Quality Control；If be judged as whether, directly obtain Quality Control valid data.
- 3. the online Source Apportionments of PMF according to claim 1 or 2, it is characterised in that particulate matter component classification to be detected Specifically include 6 major classes：PM2.5 data：PM2.5；EC/OC：EC、OC；Anion：SO4 2-、NO3 -、Cl-Instrument can measure all Inorganic anion data；Cation：NH4 +、K+、Na+All inorganic cation data that can be measured Deng all appts；Element into Point：All heavy metal ion data that Fe, Ca, K instrument can measure；Gas componant：HCL、HONO、SO2All appts can measure Gas component data；Preferably, the parameter of PMF models include the uncertain relevant parameter of test limit, input data and identification because of subnumber.
- 4. the online Source Apportionments of PMF according to claim 3, it is characterised in that data validity is united in the step 4 Meter rule includes：A：As soon as PM2.5 data, EC/OC, anion, cation, the component of 5 major class of elemental composition have type not have data, write from memory Recognize shortage of data, delete full line；B：The a certain categorical data of EC/OC, anion, cation, elemental composition, the component of gas componant is efficient to be less than setting value When, delete full line；C：Statistics miss rate, miss rate are higher than setting value, are calculated without source resolution；D：For missing data using preceding 6 it is small when sliding average substitute；Preferably, data correlation diagnostic rule includes in the step 5：E:Statistics step-length is set：Statistical analysis is carried out to the data in setting according to self-defined setting step-length scope；F:Three classes material is performed to PM2.5 accounting judgment rules：Analyze PM2.5Concentration, EC/OC, zwitterion, elemental composition are full Three kinds of species concentration addition/PM after 30~50% ＜ of foot2.5The requirements of concentration ＜ 60~80%, then the batch data is reasonable, then sets EC/OC, anion, cation, the weight of elemental composition；Be added for being unsatisfactory for three kinds of species concentrations after 30~50% ＜/ PM2.5The data of the requirements of concentration ＜ 60~80% delete whole section of result；G:OCEC/ ions/element is performed with respect to accounting judgment rule：Analysis EC/OC, zwitterion, element three's relativeness, Meet 20~30%<Tri- kinds of species concentration adductions of EC/OC/<40~50%, 45~55%<Zwitterion/tri- kind species concentration adds With<65~75%, 1~2%<Element/tri- kind species concentration adduction<4~6% require, then the batch data is reasonable；For being unsatisfactory for 20~30%<Tri- kinds of species concentration adductions of EC/OC/<40~50%, 45~55%<Zwitterion/tri- kind species concentration adduction< 65~75%, 1~2%<Element/tri- kind species concentration adduction<4~6% desired data delete whole section of result；Preferably, value judgment rule less than normal bigger than normal includes in the step 6：H:Statistics step-length is set：Statistical analysis is carried out to the data in setting according to self-defined setting step-length scope；I:In statistics step-length, N values are separately provided to each classification respectively, to the value progress more than average value ± N standard deviations Reject；J:For abnormal data bigger than normal or less than normal using preceding 6 it is small when sliding average substitute；Preferably, continuous data processing rule includes in the step 7：K:1/2 detection limit of data less than detection limit substitutes；L:Continuously judged for the data more than or equal to 3 times of detection limits, if deviation is in a certain range when continuous N is small It is interior, then by data delete processing；M:For continuous data using preceding 6 it is small when sliding average substitute.
- 5. the online Source Apportionments of PMF according to any one of claims 1 to 4, it is characterised in that identifing source in the step d Combine based on the recognition methods of ratio characteristics component, based on factor spectrum and the recognition methods of derived components spectrum correlation and based on the factor and The recognition methods of component time series correlation carries out source class identification.
- 6. according to any online Source Apportionments of PMF of claim 2 to 4, it is characterised in that to original in the step 1 The detailed process that beginning data are initialized：Automatic identification time fences are the importing data of null value, and delete the row；Automatic identification Concentration of component is the importing data of null value, and assignment " 0 ".
- The online source resolution systems of 7.PMF, it is characterised in that including with lower module：Data acquisition module, for gathering particle material resource, on-line analysis obtains the module of initial data；The quality Control module of online data, for importing initial data, component selection is carried out according to particulate matter component classification to be detected, Enable data Quality Control flow automatically to screen initial data, handle, obtain the module of Quality Control valid data；PMF model computation modules, for valid data to be inputted PMF models, select particulate matter classification to be detected, particle to be detected Thing component classification, setting PMF model parameters are calculated, and obtain the module of source resolution result；As a result source class identification module, the automatic progress source class identification of identifing source rule by the source resolution result of acquisition by formulation, Obtain the module of pollutant source type.
- 8. the online source resolution systems of PMF according to claim 7, it is characterised in that the quality Control module bag of the online data Include with lower unit：Original data units are imported, on-line analysis is imported and obtains initial data and the unit initialized to initial data；Particulate matter component classification to be detected chooses unit, for carrying out the list of component selection according to particulate matter component classification to be detected Member；Data Quality Control flow elements, for being screened, being handled to initial data automatically, obtain the unit of quality inspection valid data.
- 9. a kind of online source resolution terminal devices of PMF, including memory, processor and it is stored in the memory and can be The computer program run on the processor, it is characterised in that the processor is realized such as when performing the computer program The step of online Source Apportionments of PMF described in claim 1-6.
- 10. a kind of computer-readable recording medium of the online source resolution programs of storage PMF, the computer-readable recording medium are deposited Contain computer program, it is characterised in that realized when the computer program is executed by processor as described in claim 1-6 PMF is the line-source solution method the step of.
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