CN109376443A - Regional Atmospheric Pollution environmental simulation dynamic simulator system - Google Patents
Regional Atmospheric Pollution environmental simulation dynamic simulator system Download PDFInfo
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- 238000004088 simulation Methods 0.000 title claims abstract description 21
- 230000007613 environmental effect Effects 0.000 title claims abstract description 16
- 238000012544 monitoring process Methods 0.000 claims description 18
- RAHZWNYVWXNFOC-UHFFFAOYSA-N Sulphur dioxide Chemical compound O=S=O RAHZWNYVWXNFOC-UHFFFAOYSA-N 0.000 claims description 12
- 238000000034 method Methods 0.000 claims description 10
- 238000004458 analytical method Methods 0.000 claims description 6
- 239000003344 environmental pollutant Substances 0.000 claims description 4
- 231100000719 pollutant Toxicity 0.000 claims description 4
- 239000000779 smoke Substances 0.000 claims description 4
- 230000001360 synchronised effect Effects 0.000 claims description 4
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 2
- CBENFWSGALASAD-UHFFFAOYSA-N Ozone Chemical compound [O-][O+]=O CBENFWSGALASAD-UHFFFAOYSA-N 0.000 claims description 2
- 239000000926 atmospheric chemistry Substances 0.000 claims description 2
- 229910002091 carbon monoxide Inorganic materials 0.000 claims description 2
- 239000010419 fine particle Substances 0.000 claims description 2
- 239000011159 matrix material Substances 0.000 claims description 2
- 239000008188 pellet Substances 0.000 claims description 2
- JCXJVPUVTGWSNB-UHFFFAOYSA-N nitrogen dioxide Inorganic materials O=[N]=O JCXJVPUVTGWSNB-UHFFFAOYSA-N 0.000 claims 5
- MGWGWNFMUOTEHG-UHFFFAOYSA-N 4-(3,5-dimethylphenyl)-1,3-thiazol-2-amine Chemical compound CC1=CC(C)=CC(C=2N=C(N)SC=2)=C1 MGWGWNFMUOTEHG-UHFFFAOYSA-N 0.000 claims 1
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- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000003012 network analysis Methods 0.000 description 1
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Abstract
The invention discloses Regional Atmospheric Pollution environmental simulation dynamic simulator systems, pass through the numerical forecasts model such as CAMx, CMAQ, NAQPMS, WRF-Chem, the models such as statistical fluctuation and Application in Potential Prediction, logarithm forecast result is referred to and is rectified a deviation, by adjusting pollution sources digital simulation pollution reduction, simulated air mass change trend, provides foundation for decision.
Description
Technical field
The present invention relates to Regional Atmospheric Pollution environmental simulation dynamic simulation software fields, and in particular to a kind of regional atmospheric is dirty
Contaminate environmental simulation dynamic simulator system.
Background technique
The Scheme for Reducing lacks the computing platform support for meeting local conditions, and data model cannot cover comprehensively
The various aspects of lid Causes for Pollution, resolution execute achievement and can not be expected.
Pollution factor includes following 5 broad aspect: 1, meteorologic factor；2, geomorphic factors；3, energy resource structure；4, the industrial structure；
5, transport structure.
There are currently no any softwares data modeling is carried out in terms of above 5 according to the local situation, will
Monitoring result is contacted with pollution factor, and by adjusting the index value and coefficient of each pollution factor, dynamic analog region
Trend of Environmental Change.
Summary of the invention
It is an object of the invention to provide a kind of Regional Atmospheric Pollution environmental simulation dynamic simulator systems, solve the above-mentioned prior art
One or more in problem.
Regional Atmospheric Pollution environmental simulation dynamic simulator system according to the present invention, by CAMx, CMAQ, NAQPMS,
WRF-Chem numerical forecast model, statistical fluctuation and tendency forecast, logarithm forecast result are referred to and are rectified a deviation, passed through
The pollution reduction of pollution sources digital simulation is adjusted, simulated air mass change trend provides foundation for decision.
In some embodiments, the specific steps are as follows:
1) the synchronous downloading of data and initialization
Synchronous downloading meteorological data, provides input data for Study of Meso Scale Weather Forecast Mode WRF,
Disposal of pollutants inventory is established, a variety of macrostatistics are based on, realizes emission inventories by the means that space-time distributes
Top-down process of refinement, pretreated emission inventories data support sparse matrix to discharge model SMOKE, can be sky
The simulation of makings amount emissions inventory provides initial emission inventories；
2) multi-mode mode operation generates pollutant data
Source model, the multiple dimensioned photochemical patterns of CMAQ/CMAx, WRF- are discharged based on WRF Mesoscale Meteorology, SMOKE
The modelling techniques such as Chem atmospheric chemistry model construct multi-mode prediction of air quality early warning system,
Generate Conventional pollution (pellet PM10, fine particle PM2.5, ozone O3, carbon monoxide CO, titanium dioxide
Nitrogen NO2, sulfur dioxide SO2 etc.) forecast data；
3) build environment forecast analysis figure
Show meteorological and pollution tendencies.
In some embodiments, it also needs to carry out Source Tracing, is directed to city, administrative area, website, region by being supplied to
Monitoring data report (small Times, daily paper, monthly magazine), using list, the exhibition method of chart, provide AQI, SO2, CO, NO2,
The concentration data and variation tendency of O3, PM10, PM2.5.
Of the invention is a little,
1. software data modeling guarantees the authenticity of data according to the real data dynamic generation in actual environment；
2. software is independently simulated tiny grid is divided into region, then carry out summarizing calculating, accuracy is higher；
3. software coefficient calculates data source in monitoring data on the spot, more accurately.
Detailed description of the invention
Fig. 1 is the structural representation of the Regional Atmospheric Pollution environmental simulation dynamic simulator system of one embodiment of the present invention
Figure.
Specific embodiment
With reference to the accompanying drawings of the specification, the present invention is described in more detail.
As shown in fig. 1, system simulation and forecast analysis procedure chart, pass through the method and technology predicted or simulated, assignment
Pilot process exports prediction data result.
Embodiment 1
For simulating Tangshan high and new technology industrial development zone:
1. preparatory condition
A) grid that precision is 2~10 kilometers is divided into inside high and new technology industrial development zone
B) monitoring site is laid inside each grid
C) geomorphic feature in each grid is acquired by map tool
D) production entities in each grid are acquired by third party's map structure and production in grid is generated by network analysis
Industry structured data
E) transport structure characteristic is generated by the analysis of vehicle monitoring point
F) each monitoring site equipment operates normally and generates monitoring data inside high and new technology industrial development zone
2. software workflow
A) each simulation system model data is initialized
B) by monitoring data variation tendency and each model structure situation of change, monitoring index concentration and each mould are calculated
The incidence coefficient of type
C) finger 1, simulated domain real time environment monitoring overview: is monitored according to each coefficient and current data model situation
Environmental monitoring data is calculated in mark concentration of analog
D) 2, in conjunction with existing coefficient: adjustment data model parameters, environmental monitoring overview in simulation adjustment rear region
E) it generates and monitors analogue data in grid
F) each grid monitoring analogue data is summarized, environment analogue data in formation zone, the simulation of build environment overview
Figure
Mathematical model
1. meteorologic model WRF (automatic variation): data source is in monitoring site meteorological data；
2. landform model (fixation): landform data near monitoring point in region；
3. industrial structure model (adjustable): primary ,secondary and tertiary industries' entity in capture area is analyzed in conjunction with map datum,
Carry out industrial analysis classification；
4. energy resource structure model (with industrial structure change): being generated by the variety of energy sources that entity in the industrial structure uses；
5. transport structure model (adjustable): road: road data analysis crawl according to the map in region；The vehicles:
Type；Total flow and pollution vehicles flow: it is grabbed by monitoring site and carries out analytical estimating.
Data modeling is carried out in terms of 5 of pollution, monitoring result and pollution factor is contacted, and by adjusting each
The index value and coefficient of a pollution factor, dynamic analog regional environmental change trend.
Software configuration
1. meteorological simulation system；
2. regional landforms information acquisition system；
3. industry and energy resource structure crawl and management system；
4. transport structure generates and management system；
5. analogue data generates system；
6. environmental simulation dynamic simulator system.
The above is only preferred embodiment of the invention, it is noted that those skilled in the art, not
Under the premise of being detached from the invention design, some similar deformation and improvement can be made, these are also considered as invention protection
Within.
Claims (3)
1. Regional Atmospheric Pollution environmental simulation dynamic simulator system, wherein pass through CAMx, CMAQ, NAQPMS, WRF-Chem numerical value
Forecasting model, statistical fluctuation and tendency forecast, logarithm forecast result are referred to and are rectified a deviation, by adjusting pollution sources number
According to simulating pollution object emission reduction, simulated air mass change trend provides foundation for decision.
2. Regional Atmospheric Pollution environmental simulation dynamic simulator system according to claim 1, wherein specific step is as follows:
1) the synchronous downloading of data and initialization
Synchronous downloading meteorological data, provides input data for Study of Meso Scale Weather Forecast Mode WRF,
Disposal of pollutants inventory is established, a variety of macrostatistics are based on, the means distributed by space-time realize emission inventories from upper
Process of refinement under and, pretreated emission inventories data support sparse matrix to discharge model SMOKE, can be air matter
It measures emissions inventory simulation and initial emission inventories is provided；
2) multi-mode operation generates pollutant data
Source model, the multiple dimensioned photochemical patterns of CMAQ/CMAx, WRF-Chem are discharged based on WRF Mesoscale Meteorology, SMOKE
The modelling techniques such as atmospheric chemistry model construct multi-mode prediction of air quality early warning system,
Generate Conventional pollution (pellet PM10, fine particle PM2.5, ozone O3, carbon monoxide CO, nitrogen dioxide
NO2, sulfur dioxide SO2 etc.) forecast data；
3) build environment forecast analysis figure
Show meteorological and pollution tendencies.
3. Regional Atmospheric Pollution environmental simulation dynamic simulator system according to claim 2, wherein also need trace to the source point
Analysis is directed to the monitoring data report (small Times, daily paper, monthly magazine) in city, administrative area, website, region by being supplied to, using column
The exhibition method of table, chart provides the concentration data and variation tendency of AQI, SO2, CO, NO2, O3, PM10, PM2.5.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109948840A (en) * | 2019-03-08 | 2019-06-28 | 宁波市气象台 | A kind of Urban Air Pollution Methods |
| CN110334438A (en) * | 2019-07-04 | 2019-10-15 | 北京思路创新科技有限公司 | A kind of air pollutant emission inventory inversion method and equipment |
| CN110531029A (en) * | 2019-08-16 | 2019-12-03 | 北京慧辰资道资讯股份有限公司 | A kind of device based on environmentally friendly Internet of Things big data prediction air quality trend |
| CN110569528A (en) * | 2019-07-15 | 2019-12-13 | 北京工业大学 | Numerical simulation quantification method for PM2.5 transmission flux below atmospheric boundary layer of cross-boundary region |
| CN111177982A (en) * | 2019-12-31 | 2020-05-19 | 象辑知源（武汉）科技有限公司 | Emergency decision command system and method |
| CN113419449A (en) * | 2021-06-28 | 2021-09-21 | 中科三清科技有限公司 | Control method and device for cooperative control of fine particulate matters and ozone |
| CN114354841A (en) * | 2020-10-12 | 2022-04-15 | 江苏省环境科学研究院 | Big data and air quality model combined ozone pollution tracing and verifying method |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109948840A (en) * | 2019-03-08 | 2019-06-28 | 宁波市气象台 | A kind of Urban Air Pollution Methods |
| CN109948840B (en) * | 2019-03-08 | 2020-02-21 | 宁波市气象台 | Air quality forecasting method |
| CN110334438A (en) * | 2019-07-04 | 2019-10-15 | 北京思路创新科技有限公司 | A kind of air pollutant emission inventory inversion method and equipment |
| CN110569528A (en) * | 2019-07-15 | 2019-12-13 | 北京工业大学 | Numerical simulation quantification method for PM2.5 transmission flux below atmospheric boundary layer of cross-boundary region |
| CN110531029A (en) * | 2019-08-16 | 2019-12-03 | 北京慧辰资道资讯股份有限公司 | A kind of device based on environmentally friendly Internet of Things big data prediction air quality trend |
| CN110531029B (en) * | 2019-08-16 | 2022-02-25 | 北京慧辰资道资讯股份有限公司 | Device for predicting air quality trend based on environmental protection Internet of things big data |
| CN111177982A (en) * | 2019-12-31 | 2020-05-19 | 象辑知源（武汉）科技有限公司 | Emergency decision command system and method |
| CN114354841A (en) * | 2020-10-12 | 2022-04-15 | 江苏省环境科学研究院 | Big data and air quality model combined ozone pollution tracing and verifying method |
| CN113419449A (en) * | 2021-06-28 | 2021-09-21 | 中科三清科技有限公司 | Control method and device for cooperative control of fine particulate matters and ozone |
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