CN116050612A - Atmospheric chamber gas monitoring site location method and system based on multi-technology integration and storage medium - Google Patents

Atmospheric chamber gas monitoring site location method and system based on multi-technology integration and storage medium Download PDF

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CN116050612A
CN116050612A CN202310013710.7A CN202310013710A CN116050612A CN 116050612 A CN116050612 A CN 116050612A CN 202310013710 A CN202310013710 A CN 202310013710A CN 116050612 A CN116050612 A CN 116050612A
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data
site
point
emission
analysis
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张金文
陈淑青
张雪林
鲁楠
黄颖彦
黄渤
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Guangzhou Hexin Instrument Co Ltd
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/80—Management or planning
    • Y02P90/84—Greenhouse gas [GHG] management systems

Abstract

The invention relates to the technical field of greenhouse gas monitoring, in particular to an atmospheric greenhouse gas monitoring site selection method and system based on multi-technology integration and a storage medium. In the site selection method, a data investigation module is used for obtaining multi-source data to perform data preliminary processing so as to form a basic database; the site selection of the greenhouse gas monitoring site is realized through a plurality of different technical means such as a point position primary screening module, an accurate screening module, an on-site investigation module, a scientific demonstration module and the like, the site selection step is defined, and the site selection flow is standardized. The corresponding storage medium is convenient for storing the operation program for operating the method, and is applied to related equipment. In the prior art, the site selection work is mostly realized by manual work, data arrangement, stepping point investigation and subjective decision, the whole decision process is low in efficiency, and the site selection is very poor possibly caused by factors such as insufficient information acquisition or knowledge level of a decision maker.

Description

Atmospheric chamber gas monitoring site location method and system based on multi-technology integration and storage medium
Technical Field
The invention relates to the technical field of greenhouse gas monitoring, in particular to an atmospheric greenhouse gas monitoring site selection method and system based on multi-technology integration and a storage medium.
Background
Urban atmospheric chamber gas monitoring is mainly used for reflecting the artificial greenhouse gas emission condition of cities by monitoring the urban atmospheric chamber gas concentration. Urban atmospheric chamber gas monitoring is different from the publicly known air quality monitoring. Air quality monitoring is directed to PM10, PM2.5, NO 2 、SO 2 、CO、O 3 6 kinds of atmospheric pollutants are detected, the pollutant concentration monitoring data reflect the urban atmospheric pollution level, and the main function of the air quality monitoring station is to guide urban atmospheric pollution control. The object of urban atmospheric chamber gas monitoring is CO 2 、CH 4 The isothermal chamber gas concentration is monitored, the greenhouse gas emission of the city is calculated and estimated based on greenhouse gas concentration observation data, accurate relevant emission data of the city is obtained, and data support is provided for international performance negotiations in China.
The city atmospheric temperature chamber gas monitoring and air quality monitoring point position layout principles are different. The construction of the air quality monitoring station mainly considers the concentration distribution situation of pollutants and covers the whole built-up area of the city; the arrangement of the urban atmospheric chamber gas monitoring points is based on the accurate emission, the factors such as space coverage rate of the stations, contribution of urban carbon emission to the monitoring points and the like are comprehensively considered, the selected positions are ensured to effectively reflect the current situation and transmission characteristics of urban greenhouse gas emission, the monitoring function of each station is exerted to the maximum extent, redundant station construction is avoided, and the construction cost is reduced.
The point location layout of the urban atmospheric chamber gas monitoring is provided with a plurality of considerations and requirements, and the monitoring point location layout principle determined by the technical guidelines (first edition) of the point location layout of the urban atmospheric chamber gas monitoring comprises representativeness, comparability, integrity and the like. The representative required point can objectively reflect the gas level and space-time change rule of the atmospheric chamber in a certain space range, and meet the requirement of evaluating the emission of urban greenhouse gases; the comparability requires that the setting conditions of the monitoring points of the same type are as consistent as possible, and the comparability comprises a layout principle, a monitoring method, quality control, quality assurance and the like, so that the data among all the points are comparability; the integration requirement considers the comprehensive environmental factors such as urban topography, weather and the like, and the social and economic characteristics such as energy structure, industry layout and the like, and reflects the emission condition of main greenhouse gases in cities.
In addition, although some site layout instructions are proposed in the prior art, such as "technical guidelines for layout of urban atmospheric chamber gas monitoring sites (first edition)", schemes for monitoring urban atmospheric chamber gas are included, so as to obtain greenhouse gas emission flux of the whole urban area through methods of pattern analysis, inversion and the like. The premise of obtaining accurate emission is to obtain an accurate urban basic carbon emission list, and the realization of the part is to monitor heavy-point pollution sources in important industries, such as electric power, steel, coal exploitation and the like, and to find out the emission data of urban emission households, so that the quality of the urban initial emission list can be greatly improved. However, the above method can be used for locating by manually collecting data and analyzing the data, so that the labor cost and the time cost are greatly increased, and the risk of locating errors is increased due to uncertainty of the data and the result, so that the high-efficiency decision requirement of the modern society can not be met.
In the prior art, an optimization method for monitoring point layout is also provided for the defects, for example, a layout optimization method for an on-line detector for the concentration of the particulate matters in the port atmosphere is disclosed in China patent CN201911063520.6, and the patent technology discloses that the concentrations of PM2.5, PM10 and TSP in the port atmosphere environment are continuously detected on line in real time. The method comprises the following steps: dividing a port plane grid; detecting the concentration of atmospheric particulate matters in the vertical space of the port grid; constructing a bad curved surface with the most serious pollution of port space particles; optimizing space aggregation of port grids; and selecting the inferior curved surface of one grid from each determined aggregation grid set as an optimal layout scheme for arranging the online detector. According to the technical scheme, the grids of the port can be aggregated and optimized according to the correlation between the particle concentrations of the adjacent grid spaces, and the optimal layout position of the online detector is determined by comprehensively considering the spatial relationship of different grids on the inferior curved surface with the most serious particle pollution. The effectiveness of the detection result is ensured while the distribution point is reduced, and the input and output benefits of port pollution monitoring are improved.
However, the technology is only a technical proposal proposed for a local small area such as a port area, the factors such as geographical environment, atmospheric environment, air quality regional difference and the like which need to be considered in a specific small area are relatively single, and the places where the monitoring points are arranged are relatively ideal, so that only the air pollution degree under the premise is mainly considered. However, if the monitored space is expanded to the whole city or region and even to a larger range, the geographical environment, the atmospheric environment and the air quality region difference become more complex, and the scheme of the patent obviously does not consider the influence caused by the difference and cannot meet the requirement of large-area monitoring point arrangement.
In summary, the greenhouse gas monitoring site location work is an important premise of the urban carbon monitoring network construction work, and the greenhouse gas monitoring site location scheme design directly influences the performance of the urban carbon monitoring network, thereby influencing the construction of an urban carbon monitoring and evaluating technical method system; in the prior art, the corresponding site selection method and system are still deficient.
In addition, although the carbon monitoring evaluation test point working scheme issued by the ecological environment department, the urban atmospheric chamber gas and ocean carbon sink monitoring test point technical reference scheme issued by the Chinese environment monitoring main station, the urban environmental air greenhouse gas test point monitoring quality management and quality control guide (test run), the urban atmospheric chamber gas monitoring point layout technical guide (first edition) and the like all provide important indication for greenhouse gas monitoring station site selection, and also define 5 principles of monitoring point layout. However, the techniques employed in the prior art still have the following drawbacks:
1. at present, how to realize site selection of greenhouse gas monitoring stations by a plurality of different technical means such as satellite remote sensing, outfield monitoring, numerical simulation, field investigation and the like is not described in detail; different addressing results may exist in the technical means with different emphasis points, and risks of addressing errors exist;
2. At present, the site selection of the urban atmospheric air chamber gas monitoring points mainly relies on manually collecting data and analyzing the data to select the site, so that the workload is large, the working content is complex, and the labor cost and the time cost are relatively high.
At the moment that big data technology is becoming perfect, a method for realizing site selection of atmospheric chamber gas monitoring by comprehensively utilizing big data technology is urgently needed to complement the defects in the prior art.
Disclosure of Invention
The scheme aims to overcome the defects and the defects in the prior art, and provides the atmospheric chamber gas monitoring site location method and the storage medium based on multi-technology integration, which can meet the requirements of large areas such as cities.
The scheme realizes the aim through the following technical means:
the scheme is an atmospheric air chamber gas monitoring station site selection method based on multi-technology integration, and mainly comprises the following steps: s1, data investigation is conducted, basic profiles of areas where sites are located are collected, and a database reflecting local features to the greatest extent is obtained;
s2, performing primary screening on the point positions, namely obtaining carbon emission data according to data in a database and combining short-term on-site monitoring, and primarily screening out the point positions with enough quantity to meet the monitoring requirement; in one or more embodiments of the invention, a point location is also described as a site; primary screening is also described as primary screening; in one or more embodiments of the invention, the point location obtained by the step S2 preliminary screening is described as a preliminary selection point location in some embodiments of the invention;
S3, precisely screening out the most sensitive point positions of the main greenhouse gas emission sources in the region where the site selection is located by adopting a model analysis technology from the point positions of the primary screening; in some embodiments of the present invention, the points screened in step S3 are described as culled points;
s4, performing field investigation to ensure that the site conditions of the selected points meet the requirements of site building, site distribution and the like; screening out the points meeting the requirements as alternative points;
s5, scientifically proving that the greenhouse gas concentration of the candidate point is compared with the observation data of satellite remote sensing through numerical simulation, and outputting the candidate point meeting the condition.
Firstly, basic profile data of a region is collected through data investigation, and the basic profile data comprises information such as geographic positions, administrative regions, geographic topography, population distribution, industry and energy structures, carbon emission status and urban future development planning, and the natural social characteristics are comprehensively combed. And acquiring a database reflecting the local characteristics to the greatest extent.
The database in the step S1 specifically includes a basic profile database of the region where the site is located and a key information investigation analysis database, where the key information investigation analysis database at least includes: meteorological conditions, land utilization, greenhouse gas emission source space-time distribution, greenhouse gas concentration distribution characteristics and point location information data.
And then, carrying out point location preliminary screening, further researching important data closely related to the site selection of the carbon monitoring station, including information such as meteorological conditions, land utilization conditions, emission source data, greenhouse gas satellite remote sensing monitoring data, greenhouse gas ground monitoring data and the like, combining short-term on-site monitoring to obtain carbon emission data, supplementing carbon emission space-time characteristic information, and primarily screening out a sufficient number of points meeting monitoring requirements to finish the point location preliminary screening work.
The step S2 point location preliminary screening at least comprises the following parallel conditions:
s21, according to the investigation result of the step S1, the dominant wind direction and the up-down wind direction of the dominant wind direction in the region are defined by analyzing meteorological conditions such as wind speed, wind direction and the like;
s22, dividing grids on map software of the region where the site is located by using geographic information system software, importing greenhouse gas emission source space distribution data acquired through a greenhouse gas emission list into the geographic information system software, and displaying emission source distribution in a grid chart so as to clearly define the region greatly influenced by each emission source;
s23, through satellite remote sensing and ground monitoring CO2 isothermal chamber gas concentration analysis, a high-value region, a median region and a low-value region of regional CO2 isothermal chamber gas emission are defined;
Based on the conditions, map software is adopted, foundation conditions such as topographical features, land utilization types, future development of urban areas, tower foundations, high-rise buildings and the like are considered, and a certain range of distribution areas are selected in the urban areas and the areas with the dominant wind directions up and down and greatly influenced by emission sources; and screening all the points meeting the conditions in the point distribution area grid according to the source distribution condition of the emission source points.
And then, carrying out accurate screening, and carrying out accurate screening work of the initially selected point positions by adopting a model analysis technology based on the point position initial screening result. The model analysis work comprises the working contents of sensitivity analysis, flux footprint simulation, cluster analysis, observation system simulation experiment and the like, the most sensitive point position to the main greenhouse gas emission source in the city is accurately screened out of the primary screening alternative point positions, the point position layout is optimized, the uncertainty of assimilation inversion of the greenhouse gas emission in the city is greatly reduced, and the accurate point position screening result is clarified.
The model analysis technology specifically comprises the following steps:
s31 sensitivity analysis:
s311, coupling the gas image field with a backward track model, and performing track cluster analysis on the initially selected points;
s312, performing footprint contribution analysis on the initially selected point positions through coupling of the meteorological field and the footprint contribution model;
S313, integrating track cluster analysis and footprint contribution analysis, and identifying whether primary carbon emission information can be captured by the primary selected point; s32 assimilation inversion simulation analysis:
s321, determining pollutant emission sources including greenhouse gases in the region where the site selection is located according to the investigation result of the step S1;
s322, coupling the regional air quality model through an aerial image field, and coupling the regional air quality model with photosynthesis and a respiration model to simulate the concentration distribution of greenhouse gases in the region where the site selection is located;
s323, constructing a column concentration data set of greenhouse gases in the region where the site selection is located according to the investigation result of the step S1, and constructing an input model which is suitable for the atmospheric chemical mode by combining pollutant emission information except the greenhouse gases;
s324, according to the investigation result of the step S1, carrying out assimilation inversion on the basis of the existing emission source by combining the greenhouse gas concentration monitored on the ground and the input model described in the step S323, so as to obtain a dynamic high-resolution greenhouse gas emission source;
s325, updating the greenhouse gas emission source with the dynamic high resolution into the step S321 and re-simulating the concentration distribution of the greenhouse gas in the region where the site is located through the step S322;
s326, comparing the concentration distribution of the greenhouse gas obtained in the step S325 in the region where the site is located with the concentration distribution characteristics of the greenhouse gas obtained in the step S1, and evaluating the influence of the point distribution scheme on the greenhouse gas emission in assimilation inversion;
And (3) precisely screening out the most sensitive point positions of the main greenhouse gas emission sources in the region where the site is located by combining the steps S31 and S32.
The specific process of the sensitivity analysis in the step S31 is as follows:
firstly, coupling high-precision meteorological data constructed by a mesoscale weather pattern WRF with a backward trajectory model HYSPLIT, carrying out cluster analysis on backward air mass trajectories of different heights of initial selection points in different seasons, calculating the incoming percentages of airflows of different heights at the initial selection points, identifying whether the main carbon emission information can be captured by the initial selection points, and determining the representativeness and sensibility of the arrangement heights of the initial selection points and sampling ports;
then coupling high-precision meteorological data constructed by a mesoscale weather pattern WRF with a STILT footprint contribution model, simulating and calculating the footprint weight of all areas through which air flows to the preset monitoring point concentration at different seasons and different sampling heights before the air flows finally reach the initial point under the driving of a meteorological field, identifying whether the initial point can capture main carbon emission information, and determining the representativeness and sensibility of the layout heights of the initial point and a sampling port;
by means of track clustering analysis and footprint contribution analysis on the primary selection points, whether the primary selection points can capture main carbon emission information is identified, whether the primary selection points and the sampling port layout heights are representative and sensitive is determined, and further the primary selection points are screened.
The specific process of the assimilation inversion simulation analysis in the step S32 is as follows:
<1> collecting pollutant emission sources in the finishing research area, and coupling high-precision meteorological data constructed by a mesoscale weather pattern WRF with an area air quality pattern CMAQ; constructing a land ecological system photosynthesis and respiration model VPRM based on time-by-time simulation meteorological parameters, coupling with a regional air quality mode CMAQ, and perfecting the description of CO2 source emission, atmospheric transportation and diffusion processes and vegetation photosynthesis and respiration effects; and simulating the greenhouse gas concentration, and comparing the result with the greenhouse gas concentration distribution characteristics in the data investigation database.
<2> collecting the CO2 concentration data of GOSAT and OCO-2 satellites and performing comparative analysis to construct a CO2 column concentration data set based on satellite remote sensing; combining the satellite pixel scale CO2 column concentration with monitoring data of a foundation verification system, simulating and analyzing the influence of non-uniform earth surface property, forming a space scale effect and time matching relation of a multi-source satellite earth environment parameter data and an atmospheric chemical transmission mode calculation grid by using pollutant concentration data except CO2, and establishing an input model which is adaptive to the atmospheric chemical mode; aiming at the situation of space-time discontinuity of the total data of the CO2 column of ground conventional observation and satellite inversion, a CO2 atmosphere assimilation inversion system is established according to the influence of the optimal set number, false long-distance correlation, mode error and observation error on sample divergence, correction inversion is carried out on the basis of the existing emission source, and then an optimized dynamic high-resolution CO2 emission source list is obtained; inputting the corrected emission source into a model of <1>, simulating the concentration of greenhouse gases, and comparing the result with the distribution characteristics of the concentration of the greenhouse gases in a database of a data investigation module;
Based on the simulation results of the modes <1> and <2> and the comparison of the observation, the influence of the point distribution scheme on the assimilation inversion greenhouse gas emission is evaluated, the uncertainty reduction amplitude of the assimilation inversion on the carbon emission is definitely 30-60%, and the point distribution scheme is further optimized to obtain the carefully selected points.
Secondly, performing field investigation, evaluating the surrounding environment condition of the point location, the position requirement of a sampling port and the condition of a tower foundation platform, ensuring that the field condition of the selected point location meets the requirements of station building and the like, and simultaneously performing field monitoring on the point location based on the technologies of unmanned aerial vehicle remote sensing monitoring, mobile navigation monitoring and the like, and evaluating the effectiveness of the selected point location.
The S4 field investigation comprises S41 field investigation information and S42 field monitoring data;
the S41 field investigation information specifically comprises: emission source conditions, trapped space conditions, geological safety conditions, electromagnetic interference conditions, site topography conditions, site construction conditions, operation and maintenance management conditions and emergency management conditions;
the S42 field monitoring data specifically includes: mobile navigation monitoring and unmanned aerial vehicle remote sensing monitoring.
Finally, scientific demonstration is needed, and the greenhouse gas concentration of the alternative point is simulated through a numerical value, and is compared and verified with the observation data of satellite remote sensing; different alternative point setting conditions are differentiated and contrasted; the alternative point is in the future five years of urban and rural spatial pattern change trend comparison demonstration. Thereby evaluating whether the candidate site is representative, monolithic, comparable, prospective.
The scientific demonstration comprises an S51 representativeness and integrity analysis, wherein the S51 representativeness and integrity analysis is as follows:
s511, according to the emission source information in the step S1, performing emission simulation on the alternative point positions at intervals through coupling of the gas image field and the chemical model, and comparing and qualitatively/quantitatively analyzing the greenhouse gas distribution concentration characteristics in the database;
s512, according to the greenhouse gas emission source with the dynamic high resolution in the step S3, performing emission simulation on the alternative point positions at intervals through coupling of a meteorological field and a chemical model, and comparing the greenhouse gas distribution concentration characteristics in a qualitative/quantitative analysis database;
s513 compares the simulation results before and after the replacement of the emission sources of S511 and S512, and judges whether the point positions can objectively reflect the atmospheric chamber gas level and the space-time change rule in a certain space range, whether the main greenhouse gas emission condition can be reflected, and whether the requirement of evaluating the greenhouse gas emission is met.
The S5 scientific proof also comprises S52 comparability analysis and S53 prospective analysis;
the S52 comparability analysis is specifically as follows:
setting conditions such as the circumferences of different alternative point positions and the ground heights of sampling ports are compared, wherein the setting conditions comprise whether the horizontal plane around the sampling port of the point position meets the wide capturing space, whether the ground height of the sampling port is between 50 and 100m, and whether the sampling height difference of the alternative point positions is not more than 10m;
The S53 prospective analysis is specifically as follows:
and (3) according to urban planning information in the step (S1), determining the future spatial pattern change trend of the alternative point position, and checking whether the alternative point position can give consideration to the future spatial pattern change trend.
Based on the method, the invention also provides an atmospheric chamber gas monitoring station site selection system based on multi-technology integration, which comprises the following steps:
the data investigation module is used for collecting the basic profile of the region where the site selection is located and obtaining a database reflecting the local characteristics to the greatest extent;
the point position primary screening module is used for obtaining carbon emission data by combining short-term on-site monitoring according to the data in the database, and preliminarily screening out a sufficient number of point positions meeting the monitoring requirement; in one or more embodiments of the invention, a point location is also described as a site; primary screening is also described as primary screening; in one or more embodiments of the invention, the point locations obtained by the preliminary screening are described as preliminary selection points in some embodiments of the invention;
the accurate screening module is used for accurately screening out the most sensitive point positions of the main greenhouse gas emission sources in the region where the site selection is positioned from the point positions of the primary screening by adopting a model analysis technology; in some embodiments of the present invention, the points screened in step S3 are described as culled points;
The on-site investigation module is used for collecting investigation information and judging that the site conditions of the selected points meet the requirements of site construction, site distribution and the like; screening out the points meeting the requirements as alternative points;
the scientific demonstration module is used for carrying out comparison verification on the greenhouse gas concentration of the candidate point position and observation data of satellite remote sensing through numerical simulation, and outputting the candidate point position meeting the condition;
the visual expression module is used for outputting contents of the data investigation module, the point position primary screening module, the accurate screening module, the field investigation module and the scientific demonstration module and expressing partial contents in a map display mode.
The scheme still further provides a storage medium which stores a computer program for realizing the atmospheric temperature chamber gas monitoring station site selection method based on the multi-technology integration.
Compared with the prior art, the invention has the beneficial effects that:
according to the technical scheme, the greenhouse gas urban monitoring points, background monitoring points and boundary monitoring points which can reflect the urban artificial greenhouse gas emission condition can be effectively screened out. In addition, the technical scheme has a self-verification process, besides the site selection step given by the guideline, a scientific demonstration module is added, and the site selection accuracy is improved. Solves the problems of time and labor waste, site selection deviation and the like in the site selection decision of greenhouse gas monitoring.
Specifically, the application discloses a greenhouse gas monitoring site selection method, wherein a data investigation module is used for acquiring multi-source data to perform data preliminary processing so as to form a basic database; the site selection of the greenhouse gas monitoring site is realized through a plurality of different technical means such as a point position primary screening module, an accurate screening module, an on-site investigation module, a scientific demonstration module and the like, the site selection step is defined, and the site selection flow is standardized. There is a self-verifying process (scientific proof module) to improve the site selection accuracy.
The technical scheme overcomes the defects of the prior art: the site selection work is mostly realized by manual investigation, data arrangement, stepping point investigation and subjective decision, the whole decision process is low in efficiency, and the site selection is quite low due to factors such as insufficient information acquisition or knowledge level of decision makers. The computer service platform corresponding to the method is used, data processing and integration are mainly completed by a computer, a person can make a decision through a computer output result, the site selection efficiency is improved, the site selection risk is avoided, more valuable site selection decision schemes are provided, and the site selection success rate is improved.
Drawings
FIG. 1 is a block diagram of a computer system constructed by the method of the present embodiment.
FIG. 2 is a diagram of a data investigation module for implementing the data investigation step.
Fig. 3 is a point location screening module implementing the point location screening step.
Fig. 4 is a monitoring point location accurate screening module for implementing the monitoring point location accurate screening step.
Fig. 5 is a monitoring point on-site survey module for implementing the monitoring point on-site survey step.
Fig. 6 is a scientific proof module implementing the scientific proof step.
Fig. 7 is a flow chart of the method of the present embodiment.
FIG. 8 is a visual expression module of an embodiment.
Fig. 9 is a computer device running the system of the present solution.
Detailed Description
The drawings of the present patent are for illustration purposes only and are not to be construed as limiting the patent. For better illustration of the following embodiments, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the actual product dimensions; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
As shown in fig. 7, the greenhouse gas monitoring site selection workflow mainly includes: the method comprises the steps of obtaining multi-source data through a data investigation module, performing data preliminary processing, and forming a basic database; the site selection of the greenhouse gas monitoring site is realized through a plurality of different technical means such as a point position primary screening module, an accurate screening module, a field investigation module, a scientific demonstration module and the like.
The data investigation module mainly collects data to form a database; the databases include a basic profile database 110 and an important information research analysis database 120; the point position primary screening module performs primary screening on the point positions; the accurate screening module performs accurate screening on the point positions of the primary screening, the primary selected point positions which do not meet the accurate screening requirement return to the previous module, subsequent screening work is not performed, and the primary selected point positions which meet the accurate screening requirement are used as the carefully selected point positions for next screening work; the field investigation module carries out further screening aiming at the selected points, the selected points which do not meet the field investigation requirement return to the previous module, the subsequent screening work is not carried out, and the selected points which meet the field investigation requirement are taken as the alternative point positions for the next screening work; the scientific demonstration module carries out scientific demonstration work on the alternative point positions, the alternative point positions which do not meet the scientific demonstration requirement return to the previous module, and the alternative point positions which meet the scientific demonstration requirement are output as the final selected alternative point positions.
The system module adopting the method is shown in fig. 1, and the whole module diagram of the atmospheric temperature chamber gas monitoring station site selection system based on the multi-technology integration is as follows: the data research module 100 acquires multi-source data to perform data preliminary processing to form a basic database; the site selection of the greenhouse gas monitoring site is realized through a plurality of different technical means such as a site location primary screening module 200, an accurate screening module 300, an on-site investigation module 400, a scientific demonstration module 500 and the like.
FIG. 1 is a block diagram of a computer system constructed in accordance with the above method. The operation of each step or module is explained in further detail below with respect to the above methods and systems.
1. Data investigation module 100
1.1 basic case
The data such as statistics annual survey, environment statistics communal publication, information statistics handbook, national economy and society development fourteenth five-year planning and 2035 distant view target outline are published by official websites, so that geographic relief data, population distribution data, industry layout data, energy structure data, carbon emission current situation, future urban development and the like of the region are comprehensively obtained, and a database capable of grasping the basic profile of the region is established as shown in fig. 2, so that basic support is provided for site selection service.
(1) Geographic location and administrative division
(2) And obtaining the geomorphic characteristics in the region based on satellite remote sensing.
(3) Population distribution, obtaining regional resident population related data based on regional statistics annual views, population scale, distribution conditions and the like
(4) The industrial structure obtains the regional production structure data of the region in the last 5 years according to the statistical information handbook and the like.
(5) The energy structure obtains the energy consumption structure conditions of industrial enterprises in the region of nearly three years through statistics annual views and the like.
(6) And (3) distinguishing the carbon emission situations of the departments according to the carbon emission list.
(7) Urban development planning, which depends on the latest release of national economy and society development planning and 2035 perspective target outline of the regional development and reform committee, and defines the future development planning of the region.
1.2 important data investigation
(1) Meteorological conditions
And collecting meteorological data of each ground monitoring station in the region for nearly 3 years, including factors such as wind speed, wind direction, temperature, humidity, air pressure and the like, and analyzing and obtaining the change trend of different time dimensions of the whole ground meteorological in the region.
The global climate fifth generation atmospheric analysis data (ERA 5) based on the European middle weather forecast center (European Centre for Medium-Range Weather Forecasts, ECMWF) acquires data such as 100 m u wind components, 100 m v wind components, boundary layer height, 2 m temperature, humidity, average sea level air pressure and the like of the region for 3 years, and based on ERA5 data obtained by MATLAB programming software processing, the regional weather condition space-time change rule of the region and the surrounding environment is presented in a multi-dimensional mode, and important weather conditions such as the dominant wind direction of the region are defined.
(2) Present of land use
Based on the regional planning and the natural resource bureau official network, the latest national soil investigation result is obtained, and the areas such as regional cultivated land, garden land, forest land, grassland, wetland, town village and construction land, transportation land, water area and water conservancy facility land and the like are counted to comprehensively and objectively reflect the regional land utilization condition.
And further acquiring the overall distribution condition of the main land class based on the satellite remote sensing data, and acquiring a regional land utilization coverage map.
(3) Greenhouse gas emission source analysis
According to the "provincial greenhouse gas inventory making guide (trial run)" and the "provincial and county (district) greenhouse gas inventory making guide" issued by each provincial and city, the greenhouse gas emission source/absorption sink mainly relates to five fields of energy activity, industrial production process, agricultural activity, land utilization change, forestry and waste treatment. According to the results of the regional annual atmospheric air chamber gas emission source list and the atmospheric conventional pollutant emission source list, the latest environmental statistics data and pollution spectrum data are utilized, and the information of regional atmospheric air chamber gas emission source and absorption manifold space-time distribution characteristics, emission intensity, emission port height and the like is comprehensively analyzed and mastered by using the ArcGIS geographic information system, the Orvemap and other drawing software, so that data support is provided for the greenhouse gas monitoring point selection layout area.
According to CO 2 And the same-root and same-process characteristics of the conventional atmospheric pollutants, and based on the regional conventional atmospheric pollutant emission grid list, primarily evaluating regional CO 2 Spatially distributed features of chemical fuel combustion sources, road sources, off-road sources, etc.
(4) Point location information data analysis
And comprehensively collecting and analyzing the information of the point to be selected for monitoring greenhouse gases, evaluating whether the information meets the point distribution principle and the requirement, and providing data reference for the selection of the monitoring points.
Based on Internet big data, building information of the area where the point to be selected is located, which accords with the height of 50-100 meters, is obtained.
Using the Ovidicon drawing software (including a hundred-degree map, a Bing satellite map, an OpenCycle and other high-line map and the like) to preliminarily know the surrounding environment of the point location, if so, checking the distribution condition of enterprises, roads and the like within the range of 1km or 10km of the planned point location by combining the emission source list result and the environment statistics through the hundred-degree map, and determining whether the surrounding emission source is distributed; the land type, vegetation distribution condition, building distribution and the like of the planned selected point can be mastered through the Bing satellite map, whether the surrounding environment is wide or not is checked, and whether the site building construction is convenient or not is judged; the condition of the terrain and the topography of the area where the quasi-selected point is located can be determined through an OpenCycle contour map, whether the area has a certain relative height or not is determined.
The longitude and latitude and the altitude information of the existing tower foundation platform at the point to be selected are collected through a meteorological office, a communication department, an iron tower construction company and the like, such as public facilities such as a meteorological tower and a communication tower which do not influence urban atmospheric circulation, or public facilities such as a radar station and a water tower which are not affected by people, and the like.
(5) Greenhouse gas ground monitoring analysis
Based on the greenhouse gas data of the existing greenhouse gas monitoring stations for nearly 1-3 years, the time change rule of the regional greenhouse gas is obtained.
(6) Satellite remote sensing monitoring analysis
Atmospheric infrared detector AIRS (Atmospheric Infrared Sounder) data carried by Aqua satellite and transmitted by NASA of the U.S. space agency is used for localized optimization of CO 2 And CH (CH) 4 Inversion method (CO based on TANSO-FTS data) 2 、CH 4 Column concentration product inversion model), inversion region atmospheric chamber gas (CO) under sunny conditions of four quarters in three years 2 、CH 4 ) Spatial distribution of satellite remote sensing data image, CO 2 And CH (CH) 4 The space resolution of the satellite remote sensing inversion data image is 3km multiplied by 3km. Regional-based CO for each quarter in the last three years 2 、CH 4 The satellite remote sensing inversion data images comprehensively analyze the spatial distribution characteristics of the atmospheric concentration of main greenhouse gases in different years and seasons in the region, define the distribution condition of the main greenhouse gases in suburban areas, urban areas and other areas and the spatial distribution characteristics of the main wind direction upwards and downwards, and provide support for site selection work of urban carbon monitoring stations.
The inversion algorithm of the satellite remote sensing inversion data image comprises two parts: firstly, build CO 2 、CH 4 The a priori profile, i.e. based on the number of observations Determined near-surface CO 2 、CH 4 Concentration, construction of CO in different regions and seasons 2 、CH 4 The prior profile is integrated into a nonlinear optimization algorithm; secondly, in the definition of CO 2 、CH 4 On the premise of factors such as prior profile, earth surface temperature monitored by satellite remote sensing, atmospheric temperature wet profile, reflectivity and the like, corresponding channels are selected around the absorption characteristics of each gas, scalar scale factors of target gas and interference gas profiles are inverted by using a nonlinear optimization algorithm, and the total amount of the target gas is obtained through scaling and integration.
Data quality control method of satellite remote sensing inversion data image mainly detects data inversion CO by using ground based FTS 2 、CH 4 CO inversion of gross and satellite monitoring data 2 、CH 4 And comparing the total amount to obtain the accuracy of the data product, and verifying other profiles, including verifying the atmospheric temperature and humidity profile by adopting satellite transit time and sounding balloon.
The collected and processed analyzed data is stored in a database.
2. Point location primary screening module 200
Fig. 3 shows that the spot pre-screening module 200 mainly comprises two parts of content, on the one hand, the pre-screening is performed from the overall situation of the area and on the other hand, the screening is performed from the situation of the spot area. The method is particularly divided into five parts, namely, meteorological condition space-time analysis, greenhouse gas emission source space-time distribution analysis, greenhouse gas concentration space-time distribution analysis, basic condition analysis and emission source point source distribution.
(1) Based on the data investigation result, the dominant wind direction and the up-down wind direction of the dominant wind direction in the region are clearly determined by analyzing meteorological conditions such as wind speed, wind direction and the like;
(2) Dividing a regional map into grids of 1km multiplied by 1km by utilizing ArcGIS software, importing greenhouse gas emission source spatial distribution data acquired through a greenhouse gas emission list into the ArcGIS software, and displaying emission source distribution in a grid chart so as to clearly define an area greatly influenced by each emission source;
(3) The high-value area, the medium-value area and the low-value area of the CO2 isothermal chamber gas emission in the region are defined through satellite remote sensing and ground monitoring and CO2 isothermal chamber gas concentration analysis;
(4) Adopting an Aowei map software, comprehensively considering the topography and topography characteristics, land utilization types, future development of urban areas, foundation, high-rise buildings and other basic conditions, and selecting a distribution area with a certain range (such as 10km multiplied by 10km grids) in an area (considering different concentration areas of high, middle and low greenhouse gases) greatly influenced by emission sources in the urban areas and the upwind direction and downwind direction of the dominant wind direction;
(5) According to the distribution condition of emission source point sources (such as power plants, key enterprises and the like), screening all the points meeting various conditions (such as having a certain relative height, being at least 1km away from the emission source and the like) in the grid of the point distribution area.
And preliminarily screening out a sufficient number of initial selection points meeting the monitoring requirement for the subsequent accurate selection points.
3. Accurate screening module 300 for monitoring points
The accurate screening module mainly comprises two parts of contents, as shown in fig. 4, which are respectively sensitivity analysis and observation system simulation experiments.
Based on the point position primary screening result, adopting a model analysis technology to carry out accurate screening work of alternative point positions. The model analysis work comprises the working contents of sensitivity analysis, flux footprint simulation, cluster analysis, observation system simulation experiment and the like, the most sensitive point position to the main greenhouse gas emission source in the city is accurately screened out of the primary screening alternative point positions, the point position layout is optimized, the uncertainty of assimilation inversion of the greenhouse gas emission in the city is greatly reduced, and the accurate point position screening result is clarified.
(1) Sensitivity analysis 310
Firstly, high-precision meteorological data constructed by a mesoscale weather pattern WRF are coupled with a backward trajectory model HYSPLIT, backward air mass trajectories of different heights of a primary selected site in different seasons are subjected to cluster analysis, the airflow incoming percentages of different heights of the primary selected site are calculated, whether the primary selected site can capture main carbon emission information is identified, and the representativeness and sensibility of the distribution heights of the primary selected site and a sampling port are studied.
And then coupling high-precision meteorological data constructed by a mesoscale weather pattern WRF with a STILT (structural Time-Inverted Lagrangian Transport) footprint contribution model, simulating and calculating the influence footprint weights (footprint) of all areas through which air flows to preset monitoring point concentration in different seasons and at different sampling heights before the air flows finally move to a primary selected site under the driving of a meteorological field, identifying whether the primary selected site can capture main carbon emission information, and researching the representativeness and sensibility of the primary selected site and the sampling port layout height.
By means of track clustering analysis and footprint contribution analysis on the primary selected points, whether primary carbon emission information can be captured by the primary selected points is identified, whether the primary selected points and the sampling port layout heights of different primary selected points are representative and sensitive is determined, and further the primary selected points are screened
(2) Assimilation inversion simulation analysis 320 (observation system simulation experiment)
<1>Collecting pollutant emission sources in a finishing research area, and coupling high-precision meteorological data constructed by a mesoscale weather pattern WRF with an area air quality pattern CMAQ; and constructing a land ecological system photosynthesis and respiration model VPRM based on time-by-time simulation meteorological parameters, coupling with a regional air quality mode CMAQ, and perfecting the coupling to CO 2 Description of source emissions, atmospheric transport and diffusion processes, and vegetation photosynthesis and respiration effects. And simulating the concentration of the greenhouse gas, and comparing the result with the concentration distribution characteristics of the greenhouse gas in the database of the data investigation module.
<2>Collecting GOSAT and OCO-2 satellite CO 2 Concentration data are compared and analyzed to construct CO based on satellite remote sensing 2 A column concentration dataset; combining satellite pixel dimensions CO 2 Monitoring data of column concentration and foundation verification system, simulation analysis of influence of non-uniform earth surface property, and CO removal 2 And (3) researching the spatial scale effect and time matching relation of the multi-source satellite land environment parameter data and the atmospheric transmission mode calculation grid in multiple aspects besides the pollutant concentration data, and establishing an input model suitable for the atmospheric transmission mode. CO for routine ground observation 2 Concentration and satellite inverted CO 2 Column total data space-time unconnectedContinuing the problem, researching the influence of factors such as optimal set number, false long-distance correlation, mode error and observation error on sample divergence, and establishing CO 2 Atmospheric assimilation inversion system, which performs correction inversion based on the existing emission source to obtain optimized dynamic high-resolution CO 2 And a source sink list. And (3) inputting the corrected emission source into the model of the step (1), simulating the greenhouse gas concentration, and comparing the result with the greenhouse gas concentration distribution characteristics in the database of the data investigation module 100.
Based on the simulation results of the <1> and the <2> modes and the observation comparison, the influence of the point distribution scheme on the assimilation inversion greenhouse gas emission is evaluated, the uncertainty reduction amplitude (30-60%) of the carbon emission assimilation inversion is clear, and the point distribution scheme is further optimized to obtain the carefully selected points.
4. Monitoring point location field investigation module 400
The field survey module 400 contains two parts, as shown in fig. 5, primarily field surveys and field monitors. And (3) for all the accurately screened points, making a field investigation plan, carrying out field investigation work, ensuring that the field conditions of the selected points meet the site setting requirements, and carrying out field monitoring to evaluate the effectiveness of the selected points.
(1) The field investigation mainly comprises the following contents:
1) Emission source conditions: in-field investigation of whether emission source distribution exists in a monitoring point 1 km range (background point is at least 10 km);
2) Capture space conditions: whether the horizontal plane at the periphery of the sampling port guarantees 360-degree wide capturing space is inspected in the field;
3) Geological safety conditions: photographing and recording a point location eight-direction map, checking whether the environmental conditions around the monitoring point location are relatively stable in the field, evaluating whether the geology is stable and firm for a long time, and judging whether the local disaster influence of mountain floods, mountain forest fires, debris flows and the like can be avoided by the point location, so that the safety and fireproof measures are fully ensured;
4) Electromagnetic interference conditions: whether strong electromagnetic interference exists near a monitoring point or not is inspected in the field, and whether stable and reliable power supply and lightning protection equipment exist at the periphery or not is ensured, so that the communication line is easy to install and overhaul;
5) Site topography: in-situ examining whether the selected site has a certain relative height, and adopting whether the relative height of the mouth to the tower foundation accords with the range of 50-100 meters or not so as to ensure that fully mixed sample gas and the like are collected;
6) The field construction condition is as follows: whether the area of the site meets the construction conditions of constructors or not is inspected in the field, and whether the area meets the requirement of a foundation construction or not is inspected;
7) Operation and maintenance management conditions: in-situ investigation of whether the position of the monitoring point is convenient to manage, whether the equipment operation and maintenance personnel are allowed to enter and exit the maintenance monitoring equipment and the like;
8) Emergency management conditions: the method is characterized in that whether the position of the monitoring point is provided with a smooth and convenient access channel and conditions is examined in the field, and the monitoring point can be timely driven to the field for processing when an emergency occurs.
(2) The field monitoring mainly comprises the following contents:
1) Mobile navigation monitoring
In the range of 1 km of the selected point, non-dispersive infrared absorption method equipment meeting the requirements of the technical reference scheme of urban atmospheric temperature chamber gas and ocean carbon sink monitoring test points issued by the China environmental monitoring total station is used for carrying out the mobile navigation monitoring of the concentration of atmospheric carbon dioxide (CO 2)/methane (CH 4) (columns), and the concentration distribution condition of the carbon dioxide (CO 2)/methane (CH 4) (columns) in the range of 1 km of the horizontal plane of the selected point is comprehensively mastered so as to evaluate the effectiveness of the selected point.
2) Unmanned aerial vehicle remote sensing monitoring
The remote sensing monitoring of unmanned aerial vehicle for atmospheric carbon dioxide (CO 2)/methane (CH 4) concentration is carried out on carefully chosen points by using non-dispersive infrared absorption method equipment meeting the requirements of the technical reference scheme of urban atmospheric temperature chamber gas and ocean carbon sink monitoring test points issued by a China environmental monitoring head office, and CO2 and CH4 concentration characteristics at different heights in the vertical direction are obtained so as to evaluate the effectiveness of the chosen points.
And (3) aiming at the results of evaluating the selected point positions in the steps 1) and 2), and combining the condition of the inspection station in the step (1) to obtain alternative point positions.
5. Scientific proof module 500
The scientific proof module 500 mainly includes three aspects of content, as shown in fig. 6.
Firstly, on one hand, using the collected emission sources, 1, 4, 7 and 10 months and 4 months WRF-Chem simulation is carried out on alternative point positions, and the greenhouse gas distribution concentration characteristics in a database of a qualitative/quantitative analysis data module are compared. On the other hand, the emission sources corrected by the simulation experiment of the observation system in the accurate screening module are used for carrying out WRF-Chem simulation on alternative point positions for 1, 4, 7 and 10 months and 4 months, the distribution concentration characteristics of greenhouse gases in a database of the qualitative/quantitative analysis data module are compared, the simulation results before and after the replacement of the emission sources are compared, whether the point positions can objectively reflect the atmospheric temperature chamber gas level and the time-space change rule in a certain space range or not is further demonstrated, whether the main greenhouse gas emission condition of a city can be reflected or not is reflected, and whether the requirement for evaluating the greenhouse gas emission of the city is met or not is met.
Secondly, setting conditions such as the peripheral edge of different alternative sites and the height of a sampling port from the ground are compared. The perimeter is required to be as broad as possible, avoiding the influence of close to man-made and natural greenhouse gas emissions sources and local circulation. The horizontal plane around the sampling port should ensure 360 degrees of open trapping space. The height of the sampling port from the ground is 50-100 m so as to ensure that the sampling height difference of different alternative sites cannot be too large when the sampling gas is fully mixed with the collected atmosphere. If the alternative site is set with a large difference from other alternative sites, the omission should be considered.
And finally, according to urban planning in the database of the data investigation module 100, determining the change trend of the urban and rural spatial pattern of the candidate point position for 5 years in the future, and investigating whether the candidate point position can consider the change trend of the urban and rural spatial pattern in the future.
And outputting the alternative points meeting the condition.
6. Visual expression module 600
The above five big modules (data investigation module 100, point location preliminary screening module 200, accurate screening module 300, field investigation module 400, scientific proof module 500) can effectively screen the point location, and the visual expression module 600 is for the content (or data) output by the previous five big modules, as shown in fig. 8. For the data investigation module 100, outputting geographic location and administrative division map, elevation map, most 5 years resident population and most recent year town ratio (table), resident population quantity and population density distribution map, most 5 years industry structure, each administrative area industry structure, industrial production value distribution, more than one industrial enterprise energy consumption condition, subdivision gate carbon emission, subdivision data wind field map, boundary layer elevation map, land utilization coverage map, pollutant emission distribution map, different map interfaces (such as hundred degree map, big satellite map, openCycle and other altitude map), greenhouse gas concentration year, season, month change, greenhouse gas satellite remote sensing inversion data image; for the point position preliminary screening module 200, outputting a weather space-time distribution map, an emission space-time distribution map, a greenhouse gas concentration space-time distribution map (high, medium and low value areas), a surrounding terrain, a land utilization type, a tower foundation position, a surrounding emission source distribution condition (such as whether a point source exists in 1 km), a preliminary point position space distribution map and a preliminary point position basic information table; for the accurate screening module 300, outputting a primary selection point sensitivity analysis result, an observation system simulation experiment result, a selection point space distribution diagram and a selection point basic information table; for the field investigation module 400, outputting a field investigation result table, a walking monitoring result diagram, an unmanned aerial vehicle monitoring result diagram, an alternative point position space distribution diagram and an alternative point position basic information table; for the scientific demonstration module 500, the comparison of the space-time distribution diagram of the alternative point greenhouse gas, the setting condition (table) of the alternative point position, the urban and rural planning diagram of the alternative point position in the future five years and the basic information table of the alternative point position meeting the condition are output.
Another embodiment is to provide a computer readable storage medium, as shown in fig. 9, storing computer instructions that when invoked participate in performing the addressing method as described above. Correspondingly, a corresponding computer service platform for storing, operating and displaying is provided.
The multi-source data can be obtained through the input device, the multi-source data is subjected to data processing to form a basic database, and the basic database is stored in the database. According to the five modules, the operation of the site selection module is realized through an operating system and related programs. The contents of the visual expression module 600 are presented in an interactive visual manner.
The following is a supplementary explanation of the above embodiments:
for the data investigation module, specific data and types listed in this embodiment are only a part of examples, and because different cities may have differences, the data can be obtained from various channels according to actual requirements.
In the point position primary screening module, unmanned aerial vehicle remote sensing monitoring and travel vehicle mobile monitoring technology can be adopted in the last step, the selected point positions are further evaluated, and a sufficient number of representative point positions are preliminarily screened out for subsequent accurate point selection. However, considering the cost, the further evaluation process of unmanned aerial vehicle remote sensing monitoring and traveling vehicle mobile monitoring can be selectively executed or omitted according to the actual requirements.
Urban point: the method aims at monitoring the concentration level and the change trend of the atmospheric temperature chamber gas in the city, reflects the artificial greenhouse gas emission condition of the local city, and is arranged at monitoring points in the city.
Background point: the method aims at monitoring the concentration level and the change trend of the urban background atmospheric greenhouse gas, reflects the condition of the influence of the urban background greenhouse gas source, and is arranged at monitoring points in a region far away from a greenhouse gas emission source.
Boundary points: the monitoring points are arranged at the areas far away from the greenhouse gas emission sources at the edges of the cities, and are used for reflecting the influence of external transmission.
ERA5: is the fifth generation atmospheric re-analysis dataset of ECMWF for global climate. The analysis data is a combination of model data and observations from all over the world to form a global complete, consistent data set.
Remote sensing inversion: and (3) reversely pushing the electromagnetic wave condition in the forming process according to the remote sensing image characteristics generated by the electromagnetic wave characteristics of the ground object. The remote sensing image features are formed by the processes of ground reflectivity, atmospheric action and the like, if the remote sensing image is taken as a known quantity, an unknown parameter affecting remote sensing imaging in the atmosphere is calculated, namely, remote sensing data is converted into various characteristic parameters of the ground surface which are actually required by people.
Atmospheric inversion: by utilizing the atmospheric concentration observation data and combining an atmospheric chemical transportation model and adopting an optimization algorithm, the estimation accuracy of the global and regional surface carbon flux can be improved.
WRF: the Weather Research and Forecasting Model, mesoscale weather forecast mode. Is a new generation of mesoscale numerical Model and data assimilation system following PSU/NCAR Meso-scale Model (MM 5) developed by the national atmospheric research center (NCAR) in combination with numerous research institutions and university researchers. WRF mode can be used for weather research and forecasting, with analog scales from a few meters to tens of kilometers.
HYSPLIT: backward trajectory mode. Is a specialized model developed by the united states national marine and atmospheric administration (NOAA) air resource laboratory and australian weather office for the last 20 years to calculate and analyze atmospheric contaminant transport and diffusion trajectories. The model has relatively complete transportation, diffusion and sedimentation modes for handling the input fields of various meteorological elements, various physical processes and different pollutant emission sources, and has been widely applied to the research of the transportation and diffusion of various pollutants in various areas. The HYSPLIT calculation trajectory uses the Lagrangian method, and assuming that the air mass is moving with the wind field, the trajectory of the air mass is its integral over space and time. The vector velocity of the air mass at the location is obtained by linear interpolation both spatially and temporally.
STILT: (Stochastic Time-Inverted Lagrangian Transport) footprint contribution model. The STILT model is a transport model of the lagrangian random walk theory that relates source (sink) flux upstream of the observation point to the concentration variation at the observation point with a footprint weight. The specific principle is that the backward motion track of the gas under the driving of turbulence and average wind direction is simulated by releasing a large amount of air particles backward, and the value of footprint weight is quantitatively calculated by calculating the quantity of all particles in a certain height of a boundary layer in a certain upstream area and the stay time of each particle.
Simulation experiment of observation system: observation System Simulation Experiment (OSSE) is a sensitivity test aimed at answering new observation system-induced impact and value questions, usually referring to the impact in numerical weather forecast. The 'real atmosphere' in the OSSE is free atmosphere generated through high space-time resolution mode simulation, all existing observation systems and future observations are obtained based on the free atmosphere simulation, and the influence of the future observation systems on numerical prediction errors on the basis of the existing observation systems is studied through data assimilation and numerical prediction.
WRF-Chem: weather Research and Forecasting model coupled to Chemistry. The WRF-Chem is a regional air quality model developed by NOAA forecast systems laboratories in the united states, coupling the meteorological model WRF and chemical model Chem, which is issued as part of the WRF model, as it relies on the WRF model to have experience with the use of WRF installation, configuration, use. Compared with the prior atmospheric chemical mode, the WRF-Chem can better reflect the feedback effect between the atmospheric aerosol and the weather, and can simulate a more real atmospheric environment.
CMAQ: an air quality forecasting and assessment system. Third generation air quality forecasting and assessment system (Models-3) developed by the national environmental protection agency. Models-3 is a generic term for third-Generation Air Quality Modeling System, and at the heart of this is a Community Multiscale Air Quality (CMAQ) mode system, and thus may also be referred to as Models-3/CMAQ mode.
Data assimilation: (data assimilation) means a method of fusing new observation data during dynamic operation of a numerical model, taking into account data spatiotemporal distribution and errors of an observation field and a background field. In the dynamic frame of the process model, the model track is automatically adjusted by continuously fusing direct or indirect observation information with different sources and different resolutions of discrete distribution on time and space through a data assimilation algorithm, so that the estimation accuracy of the state of the dynamic model is improved, and the prediction capability of the model is improved.
VPRM: the ecological system photosynthetic and respiratory model Vegetation Photosynthesis and Respiration Model) is a diagnostic model for researching the balance of carbon balance of the land ecological system, and is established based on the vegetation light energy utilization efficiency. Based on a VPM model, a overseas scholars Mahadevan comprehensively considers the semi-saturation value parameter PAR0 reflecting the relation between photosynthetic effective radiation and photosynthesis, the process of ecosystem respiration (Reco) and the like, and finally establishes a VPRM model capable of simulating an ecosystem NEE in 2008. The VPRM model, like other light energy utilization efficiency models, requires fewer parameters and is easy to acquire, supporting continuous long-time series CO2 flux simulation studies. The NEE simulation of the VPRM model mainly consists of two parts, namely temperature-driven calculation, which can obtain ecosystem respiratory terms (Reco), and illumination-driven calculation, which can obtain GPP.
En4DVar: 4-dimensional variation data assimilation, which is a four-dimensional variation data assimilation scheme based on an integrated body. A non-sequence data assimilation technique fits observations throughout an assimilation window (optimal trajectory).
GOSAT satellites: greenhouse gases observe satellites. In 2009, 1 month and 23 days, a rocket of H-2A is used in Japan, and the world first satellite respiratory number IBUKI for monitoring the concentration distribution of greenhouse gases from space is launched in a mode of 'one rocket eight star', which is also called as a 'greenhouse gas observation satellite' (GOSAT). The satellite can collect global carbon dioxide and methane concentration distribution information from space in the next 5 years, provides basis for formulating an emission reduction policy, and can help scientific researchers to further know how much carbon dioxide can be absorbed and released by the ecological system.
OCO-2 satellite: orbiting Carbon Observatory 2 orbital carbon observation satellite-2 (OCO-2) is the first satellite in the United states aerospace agency (NASA) to study carbon dioxide emissions. NASA hopes to understand the uneven distribution of CO2 outside the terrestrial and marine absorption in the global atmosphere through OCO-2 observation, accurately measure carbon emissions, carbon circulation, improve understanding of natural sources and artificial emissions of greenhouse gases, improve global carbon circulation models, better characterize the change of CO2 in the atmosphere, and further more accurately predict global climate change. The OCO-2 will uniformly sample the earth's land and the atmosphere above the ocean, sampling 50 tens of thousands of times per day the half of the earth's sun-exposed area over a period of 2 years, to provide a complete image of the geographic distribution and seasonal variation of the area with determined accuracy, resolution and coverage. The 3 high-resolution spectrometers of the OCO-2 instrument are used for carrying out optical spectrum monitoring on the sun, focusing the sun to different color band ranges, and analyzing and measuring the condition that specific colors are absorbed by CO2 and oxygen molecules. These specific colors are absorbed in amounts proportional to the concentration of CO2 in the atmosphere, and researchers will introduce these new data into a computational model to build a quantified global carbon source and sink. The design goal of an OCO-2 spectrometer is to measure the two passes of sunlight through the earth's atmosphere after the sunlight has been reflected off the earth's surface. The CO2 molecules and the O2 molecules in the atmosphere have very special spectral characteristics, so when light reaches the OCO-2 satellite payload, the sunlight loses corresponding energy in the special spectral regions, and the grating spectrometer of the OCO-2 scatters the sunlight, so that the absorption energy of CO2 and O2 in the corresponding spectral regions can be obtained, and the gas content of the CO2 and the O2 in the local atmosphere can be measured.
It is apparent that the above examples are merely illustrative of the technical solution of the present patent and are not limiting of the specific embodiments of the present patent. Any modification, equivalent replacement, improvement, etc. that comes within the spirit and principles of the present patent claims should be included in the protection scope of the present patent claims.

Claims (10)

1. The atmospheric chamber gas monitoring station site selection method based on the multi-technology integration is characterized by comprising the following steps of:
s1, data investigation is conducted, basic profiles of areas where sites are located are collected, and a database reflecting local features to the greatest extent is obtained;
s2, performing primary screening on the point positions, namely primarily screening out the point positions meeting the monitoring requirements according to data in a database and carbon emission data obtained by short-term on-site monitoring;
s3, precisely screening out the most sensitive point positions of the main greenhouse gas emission sources in the region where the site selection is located by adopting a model analysis technology from the point positions of the primary screening;
s4, performing field investigation, and confirming whether the site conditions of the selected site in the step S3 meet site setting requirements;
s5, scientifically proving that the point greenhouse gas concentration obtained in the step S4 is compared with satellite remote sensing observation data to obtain candidate points meeting the conditions.
2. The method for locating an atmospheric chamber gas monitoring station based on multi-technology integration according to claim 1, wherein the model analysis technology in the step S3 specifically comprises:
s31 sensitivity analysis:
s311, coupling the gas image field with a backward track model, and performing track cluster analysis on the initially selected points;
s312, performing footprint contribution analysis on the initially selected point positions through coupling of the meteorological field and the footprint contribution model;
s313, integrating track cluster analysis and footprint contribution analysis, and identifying whether primary carbon emission information can be captured by the primary selected point;
s32 assimilation inversion simulation analysis:
s321, determining pollutant emission sources including greenhouse gases in the region where the site selection is located according to the investigation result of the step S1;
s322, coupling the regional air quality model through an aerial image field, and coupling the regional air quality model with photosynthesis and a respiration model to simulate the concentration distribution of greenhouse gases in the region where the site selection is located;
s323, constructing a column concentration data set of greenhouse gases in the region where the site selection is located according to the investigation result of the step S1, and constructing an input model which is suitable for the atmospheric chemical mode by combining pollutant emission information except the greenhouse gases;
S324, according to the investigation result of the step S1, carrying out assimilation inversion on the basis of the existing emission source by combining the greenhouse gas concentration monitored on the ground and the input model described in the step S323, so as to obtain a dynamic high-resolution greenhouse gas emission source;
s325, updating the greenhouse gas emission source with the dynamic high resolution into the step S321 and re-simulating the concentration distribution of the greenhouse gas in the region where the site is located through the step S322;
s326, comparing the concentration distribution of the greenhouse gas obtained in the step S325 in the region where the site is located with the concentration distribution characteristics of the greenhouse gas obtained in the step S1, and evaluating the influence of the point distribution scheme on the greenhouse gas emission in assimilation inversion;
and (3) precisely screening out the most sensitive point positions of the main greenhouse gas emission sources in the region where the site is located by combining the steps S31 and S32.
3. The method for locating atmospheric air chamber gas monitoring station based on multi-technology integration according to claim 2, wherein the specific process of the sensitivity analysis in step S31 is as follows:
firstly, coupling high-precision meteorological data constructed by a mesoscale weather pattern WRF with a backward trajectory model HYSPLIT, carrying out cluster analysis on backward air mass trajectories of different heights of initial selection points in different seasons, calculating the incoming percentages of airflows of different heights at the initial selection points, identifying whether the main carbon emission information can be captured by the initial selection points, and determining the representativeness and sensibility of the arrangement heights of the initial selection points and sampling ports;
Then coupling high-precision meteorological data constructed by a mesoscale weather pattern WRF with a STILT footprint contribution model, simulating and calculating the footprint weight of all areas through which air flows to the preset monitoring point concentration at different seasons and different sampling heights before the air flows finally reach the initial point under the driving of a meteorological field, identifying whether the initial point can capture main carbon emission information, and determining the representativeness and sensibility of the layout heights of the initial point and a sampling port;
by means of track clustering analysis and footprint contribution analysis on the primary selection points, whether the primary selection points can capture main carbon emission information is identified, whether the primary selection points and the sampling port layout heights are representative and sensitive is determined, and further the primary selection points are screened.
4. The site selection method for the atmospheric chamber gas monitoring site based on the multi-technology integration according to claim 2, wherein the specific process of the assimilation inversion simulation analysis in the step S32 is as follows:
<1>collecting pollutant emission sources in a finishing research area, and coupling high-precision meteorological data constructed by a mesoscale weather pattern WRF with an area air quality pattern CMAQ; and constructing a land ecological system photosynthesis and respiration model VPRM based on time-by-time simulation meteorological parameters, coupling with a regional air quality mode CMAQ, and perfecting the coupling to CO 2 Description of source emission, atmospheric transport and diffusion processes, and vegetation photosynthesis and respiration effects; simulating the concentration of greenhouse gases, and comparing the result with the concentration distribution characteristics of the greenhouse gases in the data investigation database;
<2>collecting GOSAT and OCO-2 satellite CO 2 Concentration data are compared and analyzed to construct CO based on satellite remote sensing 2 A column concentration dataset; combining satellite pixel dimensions CO 2 Monitoring data of column concentration and foundation verification system, simulation analysis of influence of non-uniform earth surface property, and CO removal 2 Forming a space scale effect and time matching relation between the multi-source satellite land environment parameter data and the atmospheric transmission mode calculation grid by using other pollutant concentration data, and establishing an input model which is suitable for the atmospheric transmission mode; CO for routine ground observation 2 Concentration and satellite inverted CO 2 Establishing CO according to the influence of a plurality of factors including optimal set number, false long-distance correlation, pattern error and observation error on sample divergence under the condition of space-time discontinuity of column total data 2 Atmospheric assimilation inversion system, which performs correction inversion based on the existing emission source to obtain optimized dynamic high-resolution CO 2 An emissions source list; inputting the corrected emission source <1>Simulating the concentration of greenhouse gases, and comparing the result with the distribution characteristics of the concentration of the greenhouse gases in a database of the data investigation module;
based on the simulation results of the modes <1> and <2> and the comparison of the observation, the influence of the point distribution scheme on the assimilation inversion greenhouse gas emission is evaluated, the uncertainty reduction amplitude of the assimilation inversion on the carbon emission is definitely 30-60%, and the point distribution scheme is further optimized to obtain the carefully selected points.
5. The atmospheric chamber gas monitoring site selection method based on multi-technology integration according to claim 2, wherein the S5 scientific proof comprises S51 representativeness and integrity analysis, and the S51 representativeness and integrity analysis is specifically as follows: s511, according to the emission source information in the step S1, performing emission simulation on the point positions at intervals through coupling of the gas image field and the chemical model, and comparing and qualitatively/quantitatively analyzing the distribution concentration characteristics of greenhouse gases in the database;
s512, according to the greenhouse gas emission source with the dynamic high resolution in the step S3, performing emission simulation on the point positions at intervals through coupling of a meteorological field and a chemical model, and comparing and qualitatively/quantitatively analyzing the greenhouse gas distribution concentration characteristics in the database;
s513 compares the simulation results before and after the replacement of the emission sources of S511 and S512, and judges whether the point positions can objectively reflect the atmospheric chamber gas level and the space-time change rule in a certain space range, whether the main greenhouse gas emission condition can be reflected, and whether the requirement of evaluating the greenhouse gas emission is met.
6. The atmospheric chamber gas monitoring site selection method based on multi-technology integration according to claim 5, wherein the S5 scientific proof further comprises S52 comparability analysis and S53 prospective analysis;
the S52 comparability analysis is specifically as follows:
setting conditions such as the circumferences of different point positions and the height between the sampling openings and the ground are compared, wherein the conditions comprise whether the horizontal plane around the sampling openings meets the wide capturing space, whether the height between the sampling openings and the ground is 50-100 m, and whether the difference between the sampling heights of the point positions is not more than 10m;
the S53 prospective analysis is specifically as follows:
and (3) according to urban planning information in the step (S1), determining the future spatial pattern change trend of the point positions, and checking whether the point positions can give consideration to the future spatial pattern change trend.
7. The method for locating atmospheric air monitoring sites based on multi-technology integration according to any one of claims 1 to 6, wherein the databases in step S1 specifically include a basic profile database and an important information investigation analysis database of the region where the site is located, and the important information investigation analysis database at least includes: meteorological conditions, land utilization, greenhouse gas emission source space-time distribution, greenhouse gas concentration distribution characteristics and point location information data.
8. The method for locating an atmospheric air chamber gas monitoring station based on multi-technology integration according to any one of claims 1 to 6, wherein the step S2 point location preliminary screening at least comprises the following parallel conditions:
s21, according to the investigation result of the step S1, the dominant wind direction and the up-down wind direction of the dominant wind direction in the region are defined by analyzing meteorological conditions such as wind speed, wind direction and the like;
s22, dividing grids on map software of the region where the site is located by using geographic information system software, importing greenhouse gas emission source space distribution data acquired through a greenhouse gas emission list into the geographic information system software, and displaying emission source distribution in a grid chart so as to clearly define the region greatly influenced by each emission source;
s23, through satellite remote sensing and ground monitoring CO2 isothermal chamber gas concentration analysis, a high-value region, a median region and a low-value region of regional CO2 isothermal chamber gas emission are defined;
based on the conditions, map software is adopted, foundation conditions such as topographical features, land utilization types, future development of urban areas, tower foundations, high-rise buildings and the like are considered, and a certain range of distribution areas are selected in the urban areas and the areas with the dominant wind directions up and down and greatly influenced by emission sources; and screening all the points meeting the conditions in the point distribution area grid according to the source distribution condition of the emission source points.
9. An atmospheric chamber gas monitoring station site selection system based on multi-technology integration is characterized by comprising:
the data investigation module (100) is used for collecting basic profiles of the region where the site selection is located and obtaining a database reflecting local characteristics to the greatest extent;
the point position primary screening module (200) is used for obtaining carbon emission data by combining short-term on-site monitoring according to data in a database, and primarily screening out point positions meeting monitoring requirements;
the accurate screening module (300) is used for accurately screening out the most sensitive point position of the main greenhouse gas emission source in the region where the site selection is positioned from the point positions of the primary screening by adopting a model analysis technology;
the on-site investigation module (400) is used for collecting investigation information and judging whether the site conditions of the selected points of the accurate screening module (300) meet the site setting requirements;
the scientific demonstration module (500) is used for comparing and verifying the greenhouse gas concentration of the point location obtained by the on-site investigation module (400) with the observation data of satellite remote sensing through numerical simulation and outputting alternative point locations meeting the conditions;
the visual expression module (600) is used for outputting the contents of the data investigation module (100), the point location preliminary screening module (200), the accurate screening module (300), the on-site investigation module (400) and the scientific demonstration module (500) and expressing part of the contents in a map display mode.
10. A storage medium storing a computer program for implementing the multiple technology fusion based atmospheric chamber gas monitoring site selection method of any one of claims 1-8.
CN202310013710.7A 2023-01-05 2023-01-05 Atmospheric chamber gas monitoring site location method and system based on multi-technology integration and storage medium Pending CN116050612A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116562712A (en) * 2023-06-29 2023-08-08 内江师范学院 System and method for predicting air quality
CN116680658A (en) * 2023-05-31 2023-09-01 华南理工大学 Heat wave monitoring station site selection method and system based on risk evaluation
CN117422209A (en) * 2023-12-18 2024-01-19 贵州省公路工程集团有限公司 Road construction forest fire prevention monitoring method and system

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116680658A (en) * 2023-05-31 2023-09-01 华南理工大学 Heat wave monitoring station site selection method and system based on risk evaluation
CN116680658B (en) * 2023-05-31 2024-02-20 华南理工大学 Heat wave monitoring station site selection method and system based on risk evaluation
CN116562712A (en) * 2023-06-29 2023-08-08 内江师范学院 System and method for predicting air quality
CN116562712B (en) * 2023-06-29 2023-09-19 内江师范学院 System and method for predicting air quality
CN117422209A (en) * 2023-12-18 2024-01-19 贵州省公路工程集团有限公司 Road construction forest fire prevention monitoring method and system
CN117422209B (en) * 2023-12-18 2024-03-26 贵州省公路工程集团有限公司 Road construction forest fire prevention monitoring method and system

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