CN-121253702-B - VOCs space-time distribution rule analysis system and method

CN121253702BCN 121253702 BCN121253702 BCN 121253702BCN-121253702-B

Abstract

The invention discloses a system and a method for analyzing the space-time distribution rule of VOCs, and relates to the technical field of air pollution detection, wherein the method for analyzing the space-time distribution rule of the VOCs comprises the steps of arranging a network of VOCs monitoring points; performing multi-period sampling, performing component analysis by adopting a pre-concentration-gas chromatography-mass spectrometry combined technology, constructing a VOCs concentration spatial distribution model to generate a space-time distribution map, analyzing the component sources of the VOCs, identifying the main pollution source types, and constructing a VOCs space-time distribution characteristic index system. The method adopts a spatial distribution strategy to ensure that the coverage of the monitoring points is representative, optimizes the arrangement of sampling time sequences and frequencies, improves the accuracy and the integrity of component analysis, introduces an optimized spatial interpolation algorithm, improves the accuracy and the reliability of a spatial distribution map, integrates various source analysis methods, and eliminates the limitation of a single model through model cross validation.

Inventors

WANG XIN
YU JINGJING
ZHANG MIN
HU YAQIN
WANG XIAOHUI
ZHU CHAO
ZHU QI
ZHANG HONG
WANG SHUIBING

Assignees

安徽省生态环境科学研究院(安徽省生态环境规划院、安徽省生态环境工程咨询设计院)
安徽省生态环境监测中心(安徽省重污染天气预报预警中心、安徽省机动车排气污染监控中心)

Dates

Publication Date: 20260508
Application Date: 20250909

Claims (9)

1. The method for analyzing the space-time distribution rule of the VOCs is characterized by comprising the following steps of: Constructing a layered space point distribution strategy, determining a representative monitoring area based on the topographic feature, the meteorological condition parameters, the pollution source intensity distribution and the sensitive receptor distribution data of the target area, and arranging a VOCs monitoring point network in the target area and the surrounding environment thereof; Designing a time gradient sampling scheme, performing multi-season, multi-period and multi-frequency sampling on each laid monitoring point, collecting VOCs samples, and recording meteorological parameters and peripheral emission activities of the sampling period; Performing component analysis on the collected VOCs sample by adopting a pre-concentration-gas chromatography-mass spectrometry technology, screening analysis data by using multiple quality control standards, establishing a VOCs component concentration matrix, and determining the component spectrum and concentration distribution characteristics of the VOCs in the target area; based on the geographic space coordinate information of the monitoring points and the concentration characteristic data of the VOCs of each point, combining with the geographic information system technology, constructing a VOCs concentration space distribution model by using an optimized inverse distance weight interpolation algorithm, and generating a space-time distribution map; the method for generating the space-time distribution map comprises the following steps: Data preparation, namely importing coordinate information of the monitoring point positions and VOCs concentration data into geographic information system software; parameter optimization, determining optimal distance power by cross-validation Terrain adjustment parameters Wind farm adjustment parameters ; Gridding, namely dividing a research area into a regular grid of 100m multiplied by 100m as a basic unit of interpolation calculation; interpolation calculation, namely applying an optimized inverse distance weight interpolation algorithm to each grid center point to calculate the VOCs concentration estimated value; the optimization of the inverse distance weight interpolation algorithm is that a topography factor and a wind field factor are introduced, and the expression is as follows: ; Wherein, the Representing points to be interpolated A VOCs concentration estimate at the location; Representing known monitoring points A measured value of VOCs concentration at the location; representing monitoring points For interpolation points Is calculated from the following formula: ; Wherein, the Representing monitoring points To the point to be interpolated Is the euclidean distance of (2); representing monitoring points To the point to be interpolated Is the euclidean distance of (2); is the power of the distance; The total number of the point positions is monitored; 、 Respectively are monitoring points And a monitoring point A terrain influencing factor at the location; 、 Respectively are monitoring points And a monitoring point The wind field influence factor is calculated as follows: ; ; Wherein, the And Respectively represent monitoring points And the point to be interpolated Elevation of (2); adjusting parameters for the terrain; representing slave monitoring points To the point to be interpolated Is a direction angle of (2); Representing the wind direction angle; Representing wind speed; adjusting parameters for the wind field; Based on interpolation result, generating visual result of VOCs concentration isosurface map and three-dimensional surface map; integrating principal component analysis and a positive definite matrix factorization model, establishing a multi-model cross validation framework, analyzing source characteristics of VOCs components, calculating contribution rates of each VOCs component to different pollution sources, and identifying main pollution source types; and identifying a VOCs emission mode and a space-time evolution rule by a characteristic species ratio method and pollution source indicator analysis, and constructing a VOCs space-time distribution characteristic index system comprising a component concentration change rate, a space aggregation degree, a time fluctuation index and a source contribution index.
2. The method for analyzing the space-time distribution law of VOCs according to claim 1, wherein said method for laying out a network of VOCs monitoring points comprises: Dividing a monitoring area by adopting a layering design and space balancing principle; and laying out a VOCs monitoring point location network in the target area by applying an optimal space coverage algorithm in space statistics.
3. The method for analyzing the space-time distribution law of VOCs according to claim 2, wherein said time gradient sampling scheme comprises: Sampling for 3 days per week according to a weekly gradient, wherein the sampling is respectively 2 days on working days and 1 day on rest days; sampling for 4 times every day according to daily gradient, namely, morning, noon, evening and night respectively; And in a special period, the sampling frequency is increased in a seasonal production peak period and in heavy polluted weather.
4. A method for analyzing the temporal-spatial distribution law of VOCs according to claim 3, wherein said method for analyzing the components comprises: pre-concentrating the gas sample in the sampling tank by a thermal desorption instrument; chromatographic separation, namely, using a gas chromatograph, equipped with a capillary column, and executing a heating program; mass spectrum detection, namely using a mass spectrometer, and adopting an electron bombardment ionization source to obtain a full-scan mass spectrogram; And (3) data processing, namely performing data processing by using chromatographic workstation software, performing compound qualitative analysis by comparing with a NIST mass spectrum library, and performing quantitative analysis by adopting an internal standard method.
5. The method for analyzing the space-time distribution law of VOCs according to claim 4, wherein said method for screening analysis data using multiple quality control criteria comprises: Removing VOCs components with the detection rate lower than 50 percent; For undetected components, the concentration was calculated as half of the detection limit; samples outside the linear range were diluted and then subjected to component analysis.
6. The method for analyzing the space-time distribution law of VOCs according to claim 5, wherein said principal component analysis is applied to preliminary source analysis, and the method comprises: data preprocessing, namely carrying out standardized processing on VOCs concentration data to eliminate the influence of different dimensions; the principal component extraction, namely calculating a characteristic value and a characteristic vector based on a correlation matrix, and extracting the principal component according to a Kaiser criterion; factor rotation, namely orthogonal rotation is carried out by adopting a maximum variance method, so that the factor load is easier to explain; And (3) identifying the source type by combining the VOCs emission source spectrum characteristics according to the characteristic species with high load in each main component.
7. The method for analyzing the spatial-temporal distribution law of VOCs according to claim 6, wherein said positive definite matrix factorization model is applied to: Data preparation, namely constructing a concentration matrix and an uncertainty matrix; Setting factor number, namely preliminarily trying 3-8 factor numbers, and determining the optimal factor number by analyzing objective function values, residual error distribution and physical meaning of factor interpretation; performing model operation, namely performing multiple operations by using PMF software, and selecting a solution with the minimum objective function value and reasonable physical interpretation; And (3) identifying a source spectrum, namely comparing the characteristic species composition in each factor with a known source spectrum, and determining the pollution source type represented by the factor.
8. The method for analyzing the space-time distribution law of VOCs according to claim 7, wherein the calculation formulas of the component concentration change rate, the spatial concentration, the time fluctuation index and the source contribution index are as follows: Component concentration change rate: ; Wherein, the Represent the first Concentration change rate of seed VOCs component; And Respectively represent the first The VOCs component of the seed is Time of day and time of day The concentration at the moment; Spatial concentration degree: ; Wherein, the A spatial concentration index representing VOCs; Represent the first Monitoring the concentration of VOCs at the point locations; And Respectively representing the minimum and maximum VOCs concentration in all monitoring points; Time fluctuation index: ; Wherein, the Time fluctuation index representing VOCs; standard deviation representing the concentration of VOCs over time series; Mean values representing the concentration of VOCs over time series; Source contribution index: ; Wherein, the Represent the first A contribution index of a seed contamination source; Represent the first Contribution of seed contamination sources; Is the total number of pollution sources; ozone generation contribution rate: ; Wherein, the Represent the first The contribution rate of the seed VOCs component to ozone generation; Represent the first Ozone generation potential of species VOCs components; Is the total number of VOCs components.
9. A system for analyzing the temporal-spatial distribution law of VOCs, which is used for performing the method for analyzing the temporal-spatial distribution law of VOCs according to any one of claims 1 to 8, comprising: the monitoring point determining module is used for constructing a layered space point distribution strategy and laying a VOCs monitoring point network; the multi-period sampling module is used for designing a time gradient sampling scheme and executing multi-period sampling; the component analysis module is used for carrying out component analysis by adopting a pre-concentration-gas chromatography-mass spectrometry technology; The space-time distribution map generation module is used for constructing a VOCs concentration space distribution model by using an optimized inverse distance weight interpolation algorithm to generate a space-time distribution map; The main pollution source type identification module is used for integrating a multi-model source analysis framework, analyzing the sources of VOCs components and identifying the main pollution source type; The space-time distribution characteristic index system construction module is used for identifying the VOCs emission mode and the space-time evolution rule and constructing a VOCs space-time distribution characteristic index system.

Description

VOCs space-time distribution rule analysis system and method Technical Field The invention relates to the technical field of air pollution detection, in particular to a VOCs space-time distribution rule analysis system and method. Background Volatile Organic Compounds (VOCs) are a general term for organic compounds having a relatively high saturated vapor pressure at normal temperature and pressure, and mainly include alkanes, alkenes, alkynes, aromatic hydrocarbons, and heteroatom compounds containing oxygen, nitrogen, sulfur, and the like. VOCs not only can directly harm human health, but also form important precursors of ozone (O3) and Secondary Organic Aerosols (SOA) playing a key role in the atmospheric pollution process. Currently, VOCs research is focused mainly on pollutant concentration levels, component distribution, emissions source resolution, health risk assessment, and the like. Many studies have been limited to large cities or specific areas, and systematic studies on the pollution characteristics of medium and small cities and regional VOCs have been relatively poor. Meanwhile, the space-time distribution research of VOCs generally faces the following technical difficulties: the arrangement of the monitoring points lacks scientificity, so that the distribution characteristics of the VOCs in the area are difficult to comprehensively reflect; The sampling method is insufficient in timeliness, and dynamic changes of the concentration of VOCs are difficult to capture; the component analysis accuracy is not high, especially for the identification and quantification of low concentration components; The spatial interpolation method is single, and the spatial transmission rule of VOCs cannot be accurately described; the results of the multiple source analytical models have large differences and lack a comprehensive evaluation framework; The characteristic index system is imperfect, and VOCs pollution prevention and control are difficult to effectively guide. At present, there is a VOCs analysis method for specific scenes such as a pesticide repair site, for example, a method for analyzing characteristics of VOCs in air of a pesticide repair site and application thereof (bulletin number CN 117269418B), and the method is mainly focused on component analysis and source analysis of VOCs in a contaminated site repair process, but still has the limitations of narrow application range, single analysis means, difficulty in popularization to regional VOCs monitoring, and the like. With the acceleration of the urban process and the adjustment of the industrial structure, the regional atmospheric VOCs pollution presents new space-time distribution characteristics, and how to construct a VOCs space-time distribution rule analysis system applicable to different areas, different seasons and different pollution sources becomes the technical problem to be solved currently. Therefore, the method for analyzing the space-time distribution rule of the VOCs has the advantages of strong systematicness, wide applicability and high accuracy, and has important significance for comprehensively grasping the pollution characteristics of the VOCs in the area, formulating accurate prevention and control measures and guaranteeing the quality of the ambient air. Disclosure of Invention Aiming at the technical defects, the invention aims to provide a system and a method for analyzing the space-time distribution rule of VOCs. In order to solve the technical problems, the invention adopts the following technical scheme that the invention provides a VOCs space-time distribution rule analysis method, which comprises the following steps: Constructing a layered space point distribution strategy, determining a representative monitoring area based on the topographic feature, the meteorological condition parameters, the pollution source intensity distribution and the sensitive receptor distribution data of the target area, and arranging a VOCs monitoring point network in the target area and the surrounding environment thereof; Designing a time gradient sampling scheme, performing multi-season, multi-period and multi-frequency sampling on each laid monitoring point, collecting VOCs samples, and recording meteorological parameters and peripheral emission activities of the sampling period; Performing component analysis on the collected VOCs sample by adopting a pre-concentration-gas chromatography-mass spectrometry technology, screening analysis data by using multiple quality control standards, establishing a VOCs component concentration matrix, and determining the component spectrum and concentration distribution characteristics of the VOCs in the target area; based on the geographic space coordinate information of the monitoring points and the concentration characteristic data of the VOCs of each point, combining with the geographic information system technology, constructing a VOCs concentration space distribution model by using an optimize