Risk-oriented comprehensive VOCs source traceability method and system for industrial parks

Abstract

This invention relates to the field of air pollution control technology, specifically a risk-oriented comprehensive VOCs source tracing method and system for industrial parks. The method includes setting up monitoring points and monitoring elements, and monitoring these elements using pre-defined methods; setting risk elements and assessing them based on the monitored elements; performing quantitative source tracing of risk sources and generating quantitative source tracing results; wherein the quantitative source tracing includes: PMF source apportionment, receptor-pollution source composition spectrum matching, comprehensive risk source contribution assessment, and risk source spatial matching; performing risk assessment uncertainty and sensitivity analysis on the quantitative source tracing results; and, based on the risk assessment uncertainty and sensitivity analysis results and the quantitative source tracing results, using IMTs (Integrated Mine Traceability Methods) to formulate a comprehensive VOCs emission reduction method for industrial parks. This solution enables precise VOCs source tracing in industrial parks, reduces uncertainty, and improves the refined management capabilities of pollutants in industrial parks.

Description

Technical Field

[0001] This invention relates to the field of air pollution control technology, specifically to a risk-oriented method and system for comprehensive VOCs source tracing in industrial parks. Background Technology

[0002] Volatile organic compounds (VOCs) pose a serious threat to ambient air quality, human health, climate change, and the ecological environment through direct or indirect effects. Furthermore, some VOCs emitted by industry (such as benzene compounds, organic sulfur compounds, aldehydes, ketones, and esters) produce foul odors, which have become a major source of public complaints in recent years. With the development of urban industrialization, industrial production activities are widely recognized as the main anthropogenic source of VOCs emissions, accounting for more than 50% of all anthropogenic VOCs emissions. Industrial parks, as the main carriers of modern industrial development, are characterized by huge and concentrated pollutant emissions, making them a very important source of VOCs emissions.

[0003] Industrial parks are home to numerous VOCs-emitting enterprises, with complex and intertwined sources of VOCs emissions. VOCs control policies are typically formulated based on subjective judgments derived from enterprise environmental data, pollution collection and treatment status, and the operational status of treatment facilities, leading to significant uncertainty. Clearly, this approach is insufficient to meet the current needs for refined VOCs control in industrial parks. Furthermore, there are currently no mature VOCs source apportionment technologies applicable to the industrial park scale. Current ambient air VOCs source apportionment technologies only provide a rough and broad-based source apportionment result, which also carries inherent uncertainties, making it difficult for these results to effectively support the formulation of VOCs control policies for industrial parks.

[0004] Therefore, there is an urgent need for a risk-oriented comprehensive VOCs source tracing method for industrial parks, which can accurately trace the sources of VOCs in industrial parks, reduce uncertainty, and improve the ability of industrial parks to refine pollutant management. Summary of the Invention

[0005] One of the objectives of this invention is to provide a risk-oriented comprehensive VOCs source tracing method for industrial parks, which can accurately trace the sources of VOCs in industrial parks, reduce uncertainty, and improve the refined management and control capabilities of pollutants in industrial parks.

[0006] The basic solution provided by this invention is a risk-oriented comprehensive VOCs source tracing method for industrial parks, which includes the following:

[0007] S1. Establish monitoring points in the industrial park to be monitored;

[0008] S2. Set the monitoring elements for the monitoring points, and use the preset monitoring methods to monitor the monitoring points and monitor the monitoring elements.

[0009] S3. Set risk factors, and based on the monitored factors, conduct risk factor assessments and generate risk factor assessment results.

[0010] S4. Conduct quantitative source tracing of risk sources and generate quantitative source tracing results; among which, quantitative source tracing of risk sources includes: PMF source apportionment, receptor and pollutant source component profile matching, comprehensive contribution assessment of risk sources, and spatial matching of risk sources;

[0011] S5. Conduct risk assessment uncertainty and sensitivity analysis on the risk factor assessment results and the quantitative traceability results of risk sources, and generate risk assessment uncertainty and sensitivity analysis results;

[0012] S6. Based on the risk factor assessment results, the quantitative source tracing results of risk sources, and the uncertainty and sensitivity analysis results of risk assessment, adopt IMTs to formulate a comprehensive emission reduction method for VOCs in industrial parks.

[0013] S4 includes: S401, based on the risk factor assessment results, using the PMF model to perform PMF analysis, generating VOCs source composition profiles, and identifying primary pollution sources among the pollution sources; pollution sources include primary pollution sources and secondary pollution sources, where primary pollution sources are industry types; and secondary pollution sources are the various emission links included in the primary pollution sources.

[0014] S403. Using a multiple linear regression model, the VOCs source composition spectrum obtained from PMF analysis is matched twice with the measured VOCs source composition spectrum of each primary pollution source including the secondary pollution sources. The relationship between the VOCs source composition spectrum of each secondary pollution source and the VOCs source composition spectrum obtained from PMF analysis is obtained, and the risk allocation results of the secondary sources are obtained.

[0015] The beneficial effects of this scheme are as follows: Based on the full identification of pollution sources and environmental receptors, this scheme aims to mitigate the health risks, environmental risks, and odor nuisance risks caused by VOCs emissions from industrial parks. It couples multiple VOCs source tracing methods to quantify source apportionment results down to the enterprise's production workshop / production line and calculates the maximum allowable concentration of VOCs at specific locations (without causing the above three risks) to determine the emission reduction rate of VOCs species for enterprises in various industries. This provides data support for the accurate source tracing of VOCs in industrial parks, while adhering to the principles of environmental priority and people-centeredness, and promoting the precise control and refined emission reduction of VOCs in industrial parks.

[0016] Specifically, this plan sets up detailed monitoring points and elements, and sets up corresponding monitoring methods. Based on the monitoring results, various subsequent analyses are conducted, including risk factor assessment, quantitative source tracing, uncertainty and sensitivity analysis. Based on the risk factor assessment results, quantitative source tracing results, and uncertainty and sensitivity analysis results, IMTs are used to formulate a comprehensive VOCs emission reduction method for industrial parks. Among them, the quantitative source tracing also sets up a two-level pollution source analysis. Compared with the traditional analysis that can only determine the industry type (first-level pollution source), this plan also uses a multiple linear regression model to perform a secondary matching between the VOCs source composition spectrum obtained by PMF analysis and the measured VOCs source composition spectrum of each second-level pollution source, to obtain the relationship between the VOCs source composition spectrum of each second-level pollution source and the VOCs source composition spectrum of PMF analysis, and to obtain the risk allocation results of second-level sources, thereby improving the accuracy and pertinence of risk source analysis in industrial parks.

[0017] In summary, this solution enables precise source tracing of VOCs in industrial parks, reduces uncertainty, and improves the ability to manage pollutants in industrial parks with precision.

[0018] The second objective of this invention is to provide a risk-oriented VOCs comprehensive source tracing system for industrial parks, which can accurately trace the sources of VOCs in industrial parks, reduce uncertainty, and improve the refined management and control capabilities of pollutants in industrial parks.

[0019] The present invention provides a second basic solution: a risk-oriented VOCs comprehensive traceability system for industrial parks, which adopts the above-mentioned risk-oriented VOCs comprehensive traceability method for industrial parks. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating an embodiment of the risk-oriented comprehensive VOCs source tracing method for industrial parks according to the present invention.

[0021] Figure 2 This is a schematic diagram of VOCs composition sampling at the emission outlet of a pollution source in an embodiment of the risk-oriented VOCs comprehensive source tracing method for industrial parks of the present invention;

[0022] Figure 3 This is a flowchart illustrating the multiple linear regression model in an embodiment of the risk-oriented VOCs comprehensive source tracing method for industrial parks according to the present invention.

[0023] Figure 4 This is an example diagram of the spatial distribution of CPF in an embodiment of the risk-oriented VOCs comprehensive source tracing method for industrial parks according to the present invention. Detailed Implementation

[0024] The following detailed description illustrates the specific implementation method:

[0025] The basic implementation examples are as follows: Figure 1 As shown: A risk-oriented comprehensive VOCs source tracing method for industrial parks includes the following:

[0026] S1. In the industrial park to be monitored, monitoring points are set up; the monitoring points include: monitoring points for environmental receptors and monitoring points for pollution sources; the monitoring points for environmental receptors also serve as monitoring points for meteorological data.

[0027] Specifically, the monitoring of VOCs, an environmental receptor in the industrial park, adopts high-resolution online monitoring. The monitoring points are set up in a grid pattern according to the relevant requirements in the "Technical Specification for the Layout of Ambient Air Quality Monitoring Points (Trial)" (HJ-664).

[0028] Considering the diffusion and transmission patterns of air pollutants and their impact on ambient air quality, the range of monitoring points set up in pollution accumulation areas is generally 100 to 500 meters in radius; when considering the impact of point sources with higher emission heights on point concentrations, the radius can be expanded to 500 to 4 kilometers.

[0029] The grid-based monitoring network for VOCs (volatile organic compounds) in the industrial park will be deployed based on specific needs, taking into account the following key points:

[0030] (1) In industrial parks where pollution is concentrated, pollution monitoring points should be set up in areas with high concentrations that are likely to cause human health and areas that may have a significant impact on ambient air quality.

[0031] (2) For grid points with high emission intensity and major polluting items, they should be set up in the maximum ground-level concentration area downwind of the dominant wind direction and the second wind direction (generally the dominant risk of the most polluted season).

[0032] (3) Based on the prevailing wind direction of the industrial park, set up background monitoring points at the upwind position of the perimeter of the industrial park.

[0033] The monitoring of pollution sources covers all industry types within the industrial park, selecting representative enterprises from each industry type for monitoring. Sampling methods are divided into organized sampling and fugitive sampling. Organized sampling covers all air emission outlets of polluting enterprises, and the determination of sampling points and locations follows the relevant provisions of GB / T 16157 "Methods for Determination of Particulate Matter and Sampling of Gaseous Pollutants in Exhaust Gas from Stationary Sources" and HJ / T 397 "Technical Specifications for Monitoring Exhaust Gas from Stationary Sources". Fugitive emission sampling covers important fugitive VOC emission points of enterprises, such as workshops, production lines, storage tanks, and wastewater treatment ponds. These sampling points differ from those specified in relevant standards; the purpose of fugitive sampling is to identify the VOC composition characteristics of important fugitive emission points of enterprises. Therefore, fugitive sampling points must be located at the direct occurrence of fugitive VOC emissions, such as workshop ventilation vents, major fugitive emission points on production lines, leaks in storage tanks, and open liquid surfaces in wastewater treatment ponds. In addition, atmospheric VOC samples can be collected at the center of the plant boundary to characterize the atmospheric VOC pollution characteristics of the industry area.

[0034] S2. Set the monitoring elements for the monitoring points, and use the preset monitoring methods to monitor the monitoring points and monitor the monitoring elements.

[0035] The monitoring elements are based on the environmental and health risk characteristics of VOCs components and are monitored in accordance with the VOCs components recommended in the "2018 Monitoring Plan for Volatile Organic Compounds in Ambient Air in Key Areas" issued by the Ministry of Ecology and Environment. These include alkanes, alkenes, alkynes, aromatic hydrocarbons, oxygenated volatile organic compounds (OVOCs), halogenated hydrocarbons, etc. Specifically, a detailed list of monitoring elements is shown in Table 1 below.

[0036] The pre-set monitoring methods include: environmental receptor monitoring methods and pollution source monitoring methods;

[0037] The environmental receptor monitoring methods are as follows:

[0038] The monitoring of VOCs in the industrial park environment utilizes gas chromatography-mass spectrometry (GCMS-FID) or equivalent equipment to carry out high-resolution continuous automatic sample acquisition and analysis over a preset time period; the quality assurance and quality control procedures adopted during the online monitoring process are implemented in accordance with the "Technical Requirements and Test Methods for Continuous Monitoring Systems of Volatile Organic Compounds in Ambient Air by Gas Chromatography" (HJ1010-2018).

[0039] Pollution source monitoring methods include: sample collection methods and sample analysis methods, as detailed below:

[0040] The sample collection method is as follows:

[0041] Pollution source monitoring used Summa tanks and 2,4-dinitrophenylhydrazine derivative (DNPH) absorption tubes / absorption solutions to collect samples from pollution source emission outlets and fugitive emissions;

[0042] Under normal operating conditions of polluting enterprises, emission samples are collected from the sampling port at the back end of the waste gas treatment facility;

[0043] Before sample collection, the initial concentration of TVOCs in the exhaust gas was measured using a portable volatile organic compound (PID) detector.

[0044] When the TVOC concentration is higher than the preset concentration index, the sample in the Summa tank needs to be diluted by a certain factor before component analysis can be performed on GC-MS / FID, in order to avoid excessive TVOC concentration contamination of the analysis system and excessive dilution of VOC concentration below the method detection limit; the preset concentration index is set according to the requirements, and in this embodiment the preset concentration index is 10 ppmv.

[0045] like Figure 2 As shown, organized emissions of waste gas are collected by a sampling gun. The sampling gun should have the functions of removing particles and heating. After the stable organic waste gas flow is filtered and heated, the VOCs in the Summa tank are collected in a timed and quantitative manner by a flow / pressure controller. The VOCs in the DNPH absorbent are collected in a timed and quantitative manner by a flow controller.

[0046] Samples from organized emissions are collected at equal time intervals within a preset time period using a Summa canister and DNPH absorbent solution, with a preset number of samples each. The preset time period and preset number range are set according to requirements. In this embodiment, the preset time period is 1 hour and the preset number range is 3 to 4.

[0047] If the organized emissions are intermittent, a preset number of samples will be collected at equal time intervals during the high-intensity emission period; high-intensity emissions are defined as when the enterprise's production load is higher than 80% and the polluting process continues to operate normally.

[0048] Unorganized emissions and VOCs samples from the center of the plant boundary were collected using a Summa tank and a DNPH absorption tube. Under stable production conditions, the Summa tank was equipped with a flow limiting valve and the DNPH absorption tube was equipped with a flow controller for continuous sampling for a preset time. A preset number of samples were collected from each Summa tank and DNPH absorption tube at each location. The preset time and preset number of samples were set according to requirements. In this embodiment, the preset time was 1 hour and the preset number of samples was 3.

[0049] The sample analysis method is as follows:

[0050] Samples with excessively high VOC concentrations collected by the SUMMA canister must be diluted a certain factor in the laboratory before analysis. The diluted concentration must be controlled within a preset range. The analytical methods and quality assurance and control measures are performed in accordance with HJ 759-2015, "Determination of Volatile Organic Compounds in Ambient Air: Canister Sampling / Gas Chromatography-Mass Spectrometry". The preset concentration range is set according to requirements; in this example, it is 0.1–10 ppmv.

[0051] VOCs samples collected by DNPH adsorption solution / adsorption tube need to be pretreated before analysis on the instrument.

[0052] After pretreatment, a sample of a preset volume is transferred to a vial and then analyzed using HPLC; the preset volume is set according to requirements, and in this example it is 2 mL.

[0053] Sample pretreatment methods and high-performance liquid chromatograph operating conditions shall be performed in accordance with the national standard methods (HJ683-2014 and HJ 1153-2020);

[0054] The pretreated samples were analyzed according to the US Environmental Protection Agency (EPA) TO-11A method and high performance liquid chromatography (HPLC, Shimadzu).

[0055] S3. Set risk factors, and based on the monitored factors, conduct risk factor assessments and generate risk factor assessment results.

[0056] The primary indicators of risk factors are mainly divided into two categories: health risks and environmental effect risks.

[0057] In this plan, health risks refer to the risks to human health caused by the pathogenicity, carcinogenicity, and odor pollution resulting from VOCs emitted from industrial parks into the atmosphere.

[0058] Environmental impact risk refers to the direct or indirect effects of VOCs emissions from industrial parks into the atmospheric environment, leading to risks such as air quality decline, climate change, and ozone layer depletion.

[0059] Secondary indicators of health risk include: hazard entropy (HI), lifetime cancer risk (LCR), and odor activity value (OAV);

[0060] The secondary indicators of environmental impact risk include: ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP).

[0061] The VOC species involved in each secondary indicator and the risks they pose are different. Industrial parks can select secondary indicators as risk assessment elements according to the purpose of VOCs control and the focus of prevention and control. The risk elements involved in the monitored VOC species are shown in Table 1.

[0062] Table 1: List of VOC species and their risk characteristics for environmental receptors and pollution sources.

[0063]

[0064]

[0065]

[0066]

[0067]

[0068]

[0069]

[0070]

[0071]

[0072] This includes risk factor assessment based on the monitored elements, specifically including:

[0073] OFP represents the maximum contribution of different VOC species to ozone formation under optimal reaction conditions, and is calculated using the following formula:

[0074] OFP i =C i ×MIR i ;

[0075] In the formula, OFP i C represents the ozone formation potential of VOCs species i, dimensionless; i Indicates the concentration of VOCs species i during the monitoring period, in μg·m⁻³; MIR i MIR represents the maximum reaction increment of VOC species i. i The values ​​are referenced in Table 2;

[0076] Table 2: MIR values ​​and SOA yields of VOCs species

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083] SOAFP represents the ability of different VOC species to form secondary organic aerosols (SOAs), and the calculation formula is as follows:

[0084] SOAFP i =C i ×Y SOA,i ;

[0085] In the formula, SOAFP i The secondary organic aerosol formation potential of VOCs species i is expressed in μg·m⁻³; C i Y represents the concentration of VOCs species i during the monitoring period, in μg·m⁻³; YSOA,i represents the SOA yield of VOCs species i, in μg·m⁻³. SOA,i The values ​​are referenced in Table 2.

[0086] Hazard entropy (HQ) of specific VOC species i The hazard entropy (HI) of all VOC species accumulation is calculated using the following formula:

[0087]

[0088] In the formula, HQ i The non-cancer inhalation hazard entropy (HQ) for a specific VOC species i is generally considered to be... i A value greater than 1 indicates that inhaling the substance may have adverse health effects; REL i It is the reference exposure level for species i, REL i See Table 3 for reference.

[0089] Table 3: Reference Exposure Levels (REL) for Specific VOC Species

[0090]

[0091]

[0092] Carcinogenic risk of specific VOC species (LCR) i The cumulative carcinogenic risk (LCR) of all VOC species is calculated using the following formula:

[0093]

[0094]

[0095] In the formula, LCR iFor the carcinogenic risk of a specific VOC species i; DOSEdaily represents the daily inhaled dose of harmful VOCs (unit: mg·kg⁻¹·d⁻¹), calculated from the concentration of species i (C i It is obtained by multiplying the normalized respiratory rate (BR / BW, L·kg⁻¹·d⁻¹), inhalation absorption factor (A, dimensionless), and exposure frequency (EF, %); CSF i , where is the inhaled cancer slope factor for species i, dimensionless; ASFa is the sensitivity coefficient, dimensionless; EDa, AT, and FAHa are the exposure duration (years), lifetime exposure time (years), and time at home (dimensionless), respectively; the exposure parameters involved in the formula for each age group a are shown in Appendix 4 and Appendix 5.

[0096] Table 4: Inhalation Cancer Slope Factors of 21 Carcinogenic VOCs

[0097]

[0098] Table 5: Exposure parameters for inhaled carcinogenic risks in different age groups

[0099]

[0100]

[0101] Odor activity value (OAV) describes the odor intensity of a single odor substance; this value is defined as the ratio between the concentration of a compound and its odor threshold.

[0102]

[0103] In the formula, C i The concentration of VOCs odor substances i is 1×10⁻⁶; OT i The threshold value for odor substance i is 1 × 10⁻⁶; OAV i OAV is the odor activity value of odor substance i, dimensionless; sum The sum of odor activity values ​​for all odor substances being evaluated is dimensionless; odor thresholds for VOCs are referenced in Table 6.

[0104] Table 6: 54 Odor-Prone VOCs and Their Odor Thresholds

[0105]

[0106]

[0107] S4. Conduct quantitative source tracing of risk sources and generate quantitative source tracing results; among which, quantitative source tracing of risk sources includes: PMF source apportionment, comprehensive contribution assessment of risk sources, matching of receptor and pollution source composition profiles, and spatial matching of risk sources;

[0108] Specifically, based on the risk factor assessment results, the PMF model is used to perform PMF analysis, generate VOCs source composition profiles, and identify primary pollution sources. These pollution sources include primary and secondary pollution sources. Primary pollution sources are industry types, such as petrochemicals, pharmaceutical manufacturing, and automobile manufacturing. Secondary pollution sources are the various emission stages included in the primary pollution sources, i.e., the emission environment under each industry type (see Table 7). The identification of primary pollution sources is achieved by obtaining VOCs source composition profiles from various sources. Different industries have different pollutant contents in their VOCs source composition profiles, thus determining the industry to which the VOCs source composition profile belongs.

[0109] Based on the VOCs source composition profiles of various pollution sources analyzed by the PMF model, as well as the primary pollution sources, the absolute concentration values ​​of species in each primary pollution source are used to quantify the contribution of primary pollution sources to environmental and health risks.

[0110] A multiple linear regression model was used to perform a secondary matching between the VOCs source composition spectrum obtained from PMF analysis and the measured VOCs source composition spectrum of each primary pollution source, including the secondary pollution sources. This yielded the relationship between the VOCs source composition spectrum of each secondary pollution source (each emission stage of the polluting industry) and the VOCs source composition spectrum obtained from PMF analysis. This further refined the risk sources and obtained the risk allocation results for secondary sources. Pollution sources containing the defined risk elements were identified as risk sources.

[0111] The risk source allocation results were verified by conditional bivariate probability function (CBPF) analysis, and the impact of risk sources under different wind directions and speeds was identified, as well as the spatial distribution of the main sources of different risk factors.

[0112] The risk source allocation results include: the risk allocation results of primary and secondary pollution sources among the identified pollution sources;

[0113] Among them, risk factors are VOC species involved in risk elements; risk sources identified by matching receptors with pollution sources are identified based on the coupling relationship between data; CBPF determines risk sources from meteorological data, the actual spatial distribution of pollution sources, and the spatial distribution of risk factors. The two methods are matched and corroborated to improve the accuracy of risk source identification.

[0114] The details are as follows:

[0115] PMF source resolution:

[0116] The PMF (Orthogonal Matrix Factor) model is a receptor model based on multivariate factor analysis. The model decomposes the receptor sample matrix (i×j dimensions) into a contribution matrix (i×k) and a factor matrix (k×j).

[0117]

[0118] In the formula, x ij It is the contribution of the j-th species in the i-th sample; g ik It is the contribution of the k-th source in the i-th sample; f kj It is the concentration of the j-th species in the k-th source; e ij It is the error fraction;

[0119] The least squares method is used to minimize the objective function Q to derive the factor distribution plot and contribution:

[0120]

[0121] In the formula, U ij It is the uncertainty of each species in each sample.

[0122] To ensure the accuracy and reliability of the model results, the VOC species concentrations input into the PMF model must include all VOC species covered by the selected risk factors. The resulting indicators should meet the following criteria: Qtrue / Qrobust values ​​between 1 and 1.5; a correlation coefficient (R²) greater than 0.6 between monitored and predicted VOC species concentrations; and a normal distribution of VOC species residuals between -3 and 3.

[0123] Receptor-pollution source composition profile matching:

[0124] The PMF model can only obtain preliminary and rough VOCs source allocation results. In order to improve the accuracy and pertinence of risk source analysis in industrial parks, this scheme adopts a multiple linear regression model to perform a secondary matching between the VOCs source composition spectrum obtained by PMF analysis and the VOCs source composition spectrum obtained by actual measurement of pollution sources.

[0125] This scheme quantifies the risk contribution of each primary pollution source to secondary pollution sources (secondary sources include emissions from workshops, production lines, and wastewater treatment, as well as all aspects involving VOCs emissions, including organized and unorganized emissions). It also assesses the accuracy of the PMF model analysis results (i.e., the PMF model execution results) and the representativeness of the VOCs source composition spectrum measurements of the primary pollution sources. The subdivision of secondary pollution sources is determined based on actual emissions; the more comprehensive the coverage of secondary pollution sources by the primary pollution source, the higher the match with the source composition spectrum analyzed from the receptor.

[0126] The role of a multiple linear regression model is to evaluate the effects and contributions of numerous independent variables x to the dependent variable y. In this invention, the VOCs source composition spectrum resolved by the PMF model is used as the dependent variable y, and the VOCs source composition spectra of various secondary pollution sources in the industrial park are used as the dependent variable x. This allows for the assessment of the contribution of each secondary pollution source (e.g., organized and unorganized emissions from workshops, production lines, wastewater treatment plants, boilers, etc.) to environmental receptors. The relationship between the VOCs source composition spectra of each secondary pollution source included in the primary pollution source and the source composition spectra resolved by the PMF can be expressed as:

[0127] y1=a0+a1x 11 +a2x 12 +…+a p x 1p +ε1;

[0128] y2=a0+a1x 21 +a2x 22 +…+a p x 2p +ε2;

[0129] ...

[0130] y n =a0+a1x n1 +a2x n2 +…+a p x np +ε n ;

[0131] In the formula, a0, a1, a2, ..., a p Let ε represent p+1 parameters to be evaluated. i This represents the effect of random factors on y in the i-th trial. i The impact;

[0132] Where a0, a1, a2, ..., a p Estimate using the least squares method, assuming b0, b1, b2, ..., b p They are a0, a1, a2, ..., a p Least squares estimation (regression coefficients) is used to establish a multiple regression equation:

[0133] y1 = b0 + b1x1 + b2x2 + ... + b p x p

[0134] The regression coefficients in the multiple regression equation are calculated using the following formula:

[0135] B = (X'X) -1 X'Y;

[0136] In the formula, B = (b0, b1, b2, ..., b p ) represents the coefficient matrix of the regression equation, and X' is the transpose of X.

[0137] This scheme employs a stepwise regression method to evaluate the relationship between the VOCs source composition spectra of each secondary pollution source in the primary pollution source and the source composition spectra analyzed by PMF. Specifically, the VOCs source composition spectra of each secondary pollution source are introduced one after another as emission variables. When introducing the next emission variable, the previously included variables in the regression model are tested one by one. Variables with minor contributions and significance are removed from the regression model, thus ensuring that each emission variable in the regression model is meaningful to the source composition spectra analyzed by the dependent variable PMF. The stepwise regression model is a type of regression model, and its steps are as follows: Figure 3 As shown:

[0138] The explanatory power parameters of each independent variable (secondary pollution source) obtained by the multiple linear regression model are used to assess the contribution of secondary pollution sources involved in a certain primary pollution source to the VOCs of that primary pollution source identified by environmental receptor sources. Examples of the explanatory power of each dependent variable derived from the multiple linear regression equation are shown in Table 7 below:

[0139] Table 7: Examples of the explanatory power of VOCs source composition profiles on environmental receptors

[0140]

[0141] The regression coefficients are obtained by solving the multiple linear regression model. The absolute value of each VOC species in the source component spectrum representing a certain level of pollution source can be calculated by the following formula, and finally the source component spectrum of the reconstructed first-level pollution source is obtained.

[0142] y i =β0+β1x1+β2x2…+β k x k +ε;

[0143] Correlation analysis between the source component spectra of the reconstructed primary pollution sources and the source component spectra of the primary pollution sources determined by environmental receptor analysis can assess the representativeness of the measured source component spectra of the industry and the accuracy of their contribution to the source component spectra determined by environmental receptor analysis.

[0144]

[0145] In the formula, r(X) sp ,Y sp X represents the source composition spectrum of a reconstructed industry (primary pollution source). sp Source component spectra of Y and environmental receptors sp Correlation coefficient; Cov(X) sp ,Y sp) represents X sp With Y sp covariance; Var[X sp ] and Var[Y sp ] respectively represent X sp With Y sp The variance.

[0146] Comprehensive contribution assessment of risk sources:

[0147] Based on the source composition profiles of various pollution sources analyzed by the PMF model, the absolute concentration values ​​of species in each pollution source are used to quantify the contribution of the pollution source to environmental and health risks:

[0148]

[0149] In the formula, RS k It is the cumulative contribution of risk factor k from a specific pollution source, and can calculate the contributions of five risk factors: OFP, SOAFP, HI, LCR, and OAV. i It is the risk level associated with VOCs species i, V i It is the absolute concentration of VOC species i in the source component spectrum as determined by the PMF model.

[0150] Risk source spatial matching:

[0151] Conditional bivariate probability function (CBPF) analysis was used to verify the risk source allocation results and identify the impact of risk sources under different wind directions and speeds, as well as the spatial distribution of the main sources of different risk factors. The calculations were performed using the following formula:

[0152]

[0153] In the formula, CBPF Δθ,Δu This represents the probability that the risk source contribution exceeds a threshold x within a specific wind direction range Δθ and wind speed range Δu; m Δθ,Δu |C≥x represents the number of instances in the intervals Δθ and Δu where the target parameter exceeds the threshold x; m Δθ,Δu This represents the total number of times the value appears within the interval.

[0154] Based on the results calculated using CBPF, the spatial distribution of various risk sources is allocated onto satellite maps. This allows for a direct visualization of the main sources and pathways of various risk factors at environmental receptor monitoring points, such as... Figure 4 As shown. CPF risk source spatial distribution map drawing method: Taking the environmental receptor VOCs monitoring point as the origin, the risk source spatial distribution map is drawn covering the entire industrial park; the horizontal and vertical axes in the figure represent the four directions of east, south, west and north, the rings (dashed lines) represent the wind speed range, and the darker the color, the greater the risk contribution of the area to the environmental receptor.

[0155] S5. Conduct risk assessment uncertainty and sensitivity analysis on the risk factor assessment results and the quantitative traceability results of risk sources, and generate risk assessment uncertainty and sensitivity analysis results;

[0156] Risk assessments inherently involve uncertainty. The uncertainty of risk sources in the calculation process using the theoretical methods in this scheme includes three aspects of uncertainty transmission: (1) the monitoring concentration of volatile organic compound species (Ci); (2) the parameters used in the risk assessment process; and (3) the source component spectrum (FPi) analyzed by the PMF model.

[0157] Monte Carlo simulation and Crystal Ball software were used to quantify the uncertainty of the results. The VOCs exposure concentrations of environmental receptors are best described by a log-normal distribution, and parameters such as OT, REL, EF, AT, and ED are modeled using a triangular distribution; C i The standard deviation is derived from the monitoring data of environmental receptors. The standard deviations of the VOCs source component spectra obtained from risk factors and PMF are set to 20% and 30% of their average values, respectively. Each simulation is subjected to a preset number of iterations to ensure the convergence and stability of the results. The preset number of iterations is set according to the requirements. In this embodiment, it is set to 10,000. Ten thousand simulation calculations are performed according to the set parameters to ensure the convergence and stability of the results.

[0158] In addition, sensitivity analysis prioritizes the importance of input assumptions in the risk factor assessment results, identifies the most sensitive input variables that have the greatest impact on the results, and provides guidance for developing the best scheme for VOCs control of risk sources.

[0159] Table 8 below shows examples of uncertainties and sensitivities in the health risk assessment of risk sources in industrial parks:

[0160] Table 8: Examples of Uncertainty and Sensitivity in Health Risk Assessment of Risk Sources in Industrial Parks

[0161]

[0162]

[0163] A, B, C, D, E, and F represent the six risk sources identified by the comprehensive source analysis method.

[0164] S6. Based on the risk factor assessment results, the quantitative source tracing results of risk sources, and the uncertainty and sensitivity analysis results of risk assessment, adopt IMTs to formulate a comprehensive emission reduction method for VOCs in industrial parks.

[0165] Using preliminary mitigation targets (IMTs), a comprehensive approach to VOCs emission reduction in industrial parks is developed, providing quantitative emission reduction targets for VOC species, pollution sources, and key VOC emission stages. IMTs can be considered as concentrations calculated backward from risk levels, representing the maximum permissible residence concentration of VOCs on environmental receptors without threatening public health.

[0166] IMTs calculations arbitrarily select risk indicators based on the risk factors that the industrial park itself focuses on.

[0167] The following calculation of IMTs is carried out using health risk indicators and environmental effect risk indicators as examples of VOCs emission reduction objectives.

[0168] If health risk indicators are used as the objective of VOCs emission reduction in industrial parks, then IMTs are calculated using the following formula:

[0169]

[0170] In the formula, OAV target HI target and LCR target These represent the target risk levels for odor pollution, non-carcinogenic risk, and carcinogenic risk, respectively; OAV target HI target and LCR target The values ​​were set to 1, 1, and 1 × 10⁻⁶, respectively, based on the recommendations of the U.S. Environmental Protection Agency (US EPA). –6 ;

[0171] If environmental impact risk indicators are used as the objective of VOCs emission reduction in industrial parks, then IMTs are calculated using the following formula:

[0172]

[0173] In the formula, OFP target and SOAFP target These represent the target risk levels for ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAPF), respectively. Since there are currently no relevant standards, documents, or regulations to define the target values ​​for OFP and SOAPF, therefore... target and SOAFP target The local industrial park environmental management department can set reasonable target values ​​based on the actual situation;

[0174] The IMT of VOC species was calculated. i Then, observations (Obs) that exceeded these targets during the environmental receptor monitoring period were selected;

[0175] The following formula can be used to calculate the emission reduction rate of VOCs species and their sources at the lowest acceptable risk level:

[0176]

[0177] In the formula, R i Indicates the reduction rate of VOCs species i;

[0178] The contribution rate of VOCs emission reduction from each risk source is calculated using the following formula:

[0179] ERS i,j =R i ×P i,j

[0180] In the formula, ERS i,j P represents the emission reduction contribution rate of risk source j to VOCs species i; i,j This represents the percentage of VOC species i identified in the PMF model in the source component spectrum of risk source j;

[0181] Table 9 below shows examples of VOCs control species and their emission reduction contribution rates for the main emission sources in industrial parks:

[0182] Table 9: Examples of VOCs Controlling Species and Emission Reduction Contribution Rates for Major Emission Sources in Industrial Parks

[0183]

[0184]

[0185] Note: A, B, C, D, E, and F represent the six risk sources identified by the integrated source analysis method.

[0186] Based on the emission reduction rates of different VOC species for each risk source obtained from the comprehensive emission reduction method for risk sources, and combined with the matching results of receptor and pollution source composition profiles, targeted reduction and control measures are provided for different VOC emission links of each risk source, that is, reduction and control measures are provided for each secondary pollution source of VOC emissions from each risk source.

[0187] This embodiment also provides a risk-oriented VOCs comprehensive traceability system for industrial parks, which adopts the above-mentioned risk-oriented VOCs comprehensive traceability method for industrial parks.

[0188] The above descriptions are merely embodiments of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A risk-oriented integrated VOCs source apportionment method for industrial parks, characterized in that, The method comprises the following steps: S1. Monitoring points are set in an industrial park to be monitored; S2. Monitoring elements of the monitoring points are set, and the monitoring elements of the monitoring points are monitored by using a preset monitoring method; S3. Risk elements are set, and risk element evaluation is performed according to the monitored monitoring elements, to generate a risk element evaluation result; S4. Risk source quantitative tracing is performed, to generate a risk source quantitative tracing result; The risk source quantitative tracing comprises PMF source analysis, matching of a source component spectrum of a receptor and a pollution source, comprehensive contribution evaluation of a risk source, and spatial matching of a risk source; S5. Risk assessment uncertainty and sensitivity analysis are performed on the risk element evaluation result and the risk source quantitative tracing result, to generate a risk assessment uncertainty and sensitivity analysis result; S6. According to the risk element evaluation result, the risk source quantitative tracing result, and the risk assessment uncertainty and sensitivity analysis result, an IMT is used to develop a comprehensive VOCs emission reduction method for the industrial park; The S4 comprises the following steps: S401. According to the risk element evaluation result, a PMF model is used to perform PMF analysis, to generate a VOCs source component spectrum, and to determine a primary pollution source in the pollution source; the pollution source comprises a primary pollution source and a secondary pollution source, and the primary pollution source is an industry type; the secondary pollution source is each emission link included in the primary pollution source; 2. The risk-oriented industrial park VOCs integrated source apportionment method according to claim 1, wherein, S403. A multiple linear regression model is used to perform secondary matching on the VOCs source component spectrum obtained by the PMF analysis and the VOCs source component spectrum obtained by actually measuring each secondary pollution source included in each primary pollution source, to obtain the relationship between the VOCs source component spectrum of each secondary pollution source and the VOCs source component spectrum obtained by the PMF analysis, and to obtain a secondary source risk allocation result. The monitoring points comprise monitoring points of environmental receptors and monitoring points of pollution sources; The preset monitoring method comprises an environmental receptor monitoring method and a pollution source monitoring method; The environmental receptor monitoring method comprises the following steps: The industrial park environmental receptor VOCs monitoring uses a gas chromatograph-mass spectrometer to perform high-resolution continuous automatic sample collection and analysis for a preset time period; The pollution source monitoring method comprises a sample collection method and a sample analysis method; The sample collection method comprises the following steps: Under normal operating conditions of a pollution enterprise, an emission sample is collected from a sampling port at the back end of a waste gas treatment facility; Before sample collection, a portable volatile organic compound detector is used to detect the initial concentration of TVOCs of the waste gas; When the TVOCs concentration is higher than a preset concentration index, the sample in the canister needs to be diluted by a certain multiple before being analyzed for components on the GC-MS / FID; The organized emission waste gas is collected by a sampling gun, and after the organic waste gas flow is filtered and heated, the canister is controlled by a flow / pressure controller to collect VOCs in a timed and quantitative manner, and the DNPH absorption liquid is controlled by a flow controller to collect VOCs in a timed and quantitative manner; The samples of the organized emission are collected by the canister and the DNPH absorption liquid at equal time intervals within a preset time period, and a preset number of samples are collected. If the organized emission is intermittent, the same number of samples are collected at the same time interval within the preset time period during the high-intensity emission period; The unorganized emission exhaust gas and the VOCs sample of the atmospheric center of the factory boundary are collected by using the canister and the DNPH absorption tube, under the condition that the production working condition of the enterprise is stable, the canister is matched with the flow limiting valve and the DNPH absorption tube is matched with the flow controller for continuous sampling for a preset time, and a preset number of samples are collected by the canister and the DNPH absorption tube at each point respectively; The sample analysis method comprises the following steps: the sample with too high VOCs concentration collected by the canister needs to be diluted by a certain multiple in the laboratory before being analyzed by the machine, and the concentration after the dilution is controlled within a preset concentration range; The VOCs sample collected by the DNPH adsorption liquid / adsorption tube needs to be pretreated before being analyzed by the instrument; After the pretreatment, a sample with a preset capacity is transferred to a sample bottle, and then the HPLC is used for analysis; The pretreated sample is analyzed according to a preset method.

3. The risk-oriented industrial park VOCs integrated source apportionment method according to claim 1, wherein, The first-level indicators of the risk elements are divided into two categories of health risks and environmental effect risks; The health risks refer to the health threats of pathogenicity, carcinogenicity and odor pollution caused by the VOCs emitted by the industrial park into the atmospheric environment; The environmental effect risks refer to the direct or indirect effects of the VOCs emitted by the industrial park into the atmospheric environment, which lead to the risks of air quality decline, climate change and ozone layer depletion; The second-level indicators of the health risks include hazard entropy HI, lifetime cancer risk LCR and odor activity value OAV; The second-level indicators of the environmental effect risks include ozone formation potential OFP and secondary organic aerosol formation potential SOAFP; The risk element evaluation according to the monitored monitoring elements comprises the following steps: The OFP represents the maximum contribution of different VOCs species to the ozone generation under the best reaction condition: ； wherein, represents the ozone formation potential of the VOC species, dimensionless; represents the concentration of the VOC species during the monitoring period, pg-m 3 ; represents the maximum reactivity increment of the VOC species, ;​​ The SOAFP represents the formation ability of the secondary organic aerosol SOA of different VOCs species: ； wherein represents the secondary organic aerosol formation potential of VOCs species , pg m 3 ; represents the concentration of VOCs species , pg m 3 ; Y SOA,i represents the SOA yield of VOCs species ; Hazardous entropy HQ for a specific VOC species i and the hazardous entropy HI for all VOC species combined, calculated by the following equation: ； wherein is the non-cancer inhalation hazard entropy for a particular VOC species is greater than 1 indicates that there is a potential for adverse health effects from inhalation of the substance; is the reference exposure level for species ​​ LCR of carcinogenic risk for specific VOC species i LCR of carcinogenic risk for all VOC species cumulatively, calculated by the following formula: ； ； In the formula, For specific VOC species The carcinogenic risk; DOSE daily This indicates the daily inhalation dose of harmful VOCs, in mg / kg. 1 ·d 1 , by species concentration Unit: μg·m 3 Normalized respiratory rate BR / BW, L·kg 1 ·d 1 The product of the inhalation absorption factor A (dimensionless) and the exposure frequency EF (in %) is obtained. For species Inhaled cancer slope factor, dimensionless; ASF a The sensitivity coefficient is dimensionless; ED a AT and FAH represent the duration of exposure, lifetime exposure time, and time spent at home, respectively. The odor intensity of a single odor material is described by the odor activity value OAV, which is defined as the ratio between the concentration of a compound and its odor threshold value: ； wherein is the concentration of VOCs odorants –6 ; is the threshold value of odorants –6 ; is the odor activity value of odorants ; is the sum of the odor activity values of all odorants evaluated, dimensionless.​​ 4. The risk-oriented industrial park VOCs integrated source apportionment method according to claim 3, characterized in that, The PMF model is a receptor model of multivariate factor analysis, and the model operation can decompose the receptor sample matrix i x j into a contribution matrix i x k and a factor matrix k x j: ； wherein is the contribution of the species in the sample; is the contribution of the source in the sample; is the concentration of the species in the source; is the error score; The factor distribution and the contribution are obtained by using the least square method to minimize the objective function Q: ； wherein is the uncertainty for each species in each sample; The concentration of VOCs species input in the PMF model contains the VOCs species covered by the selected risk factors; the index parameters of the running results should meet the value of Qtrue / Qrobust between 1 and 1.5, the correlation coefficient of the monitored and predicted VOCs species concentration is greater than 0.6, and the normal distribution of the residual of the VOCs species is between 3 and 3. 3~3.

5. The risk-oriented industrial park VOCs integrated source apportionment method according to claim 4, characterized in that, The multivariate linear regression model is used to evaluate the effect and contribution of multiple independent variables x on the dependent variable y; the VOCs source composition spectrum analyzed by the PMF model is taken as the dependent variable y, and the VOCs source composition spectrum of each secondary pollution source in the industrial park is taken as the independent variable x; and the multivariate linear regression model evaluates the contribution of each secondary pollution source to the environmental receptor; The relationship between the VOCs source composition spectrum of the secondary pollution source of the pollution industry and the source composition spectrum analyzed by the PMF is represented as follows: ； ； …… ； wherein represents the parameter to be evaluated, represents the influence of the random factor in the nth experiment on the parameter to be evaluated; the parameter to be evaluated; the parameter to be evaluated; wherein By least square estimation, assuming respectively The least square estimation, then a multiple regression equation is established: ； The regression coefficient in the multivariate regression equation is calculated by the following formula: ； wherein denotes the coefficient matrix of the regression equation, is the transpose matrix of The regression coefficient is solved by the multivariate linear regression model, and the absolute value of each VOCs species representing the source composition spectrum of a certain primary pollution source can be calculated by the following formula, and finally the reconstructed industry source composition spectrum is obtained. ； The source component spectrum of the reconstructed primary pollution source is correlated with the industry source component spectrum resolved by the environmental receptor to evaluate the representativeness of the measured source component spectrum of the primary pollution source and the accuracy of the contribution to the source component spectrum resolved by the environmental receptor; wherein source profile of a certain reconstructed primary pollution source and the source profile resolved from the environmental receptor correlation coefficient of covariance of covariance of covariance of variance of variance of variance of variance of 6. The risk-oriented industrial park VOCs integrated source apportionment method according to claim 5, characterized in that, The S4 further comprises: the VOCs source component spectrum of each type of pollution source resolved according to the PMF model, and the primary pollution source, wherein the concentration absolute value of each species in the primary pollution source is used to quantify the contribution value of the primary pollution source to the environmental effect risk and the health risk: ； wherein, is the cumulative contribution of risk factors from a specific pollution source The contribution of five types of risk factors, OFP, SOAFP, HI, LCR and OAV, is calculated; is the risk level associated with VOCs species , is the absolute concentration of VOCs species in the source profile determined by the PMF model.

7. The risk-oriented industrial park VOCs integrated source apportionment method according to claim 6, characterized in that, The S4 further comprises: the CBPF analysis is used to verify the risk source allocation result, and the influence of the risk source under different wind directions and wind speeds is identified, and the spatial distribution of the main source of different risk factors is identified; wherein the risk source allocation result comprises: the risk allocation result of the primary pollution source and the secondary source in the determined pollution source; wherein the risk factor is the VOCs species involved in the risk element; The calculation is performed by the following formula: ； wherein denotes the probability that the risk source contribution exceeds a threshold in a certain wind direction interval and wind speed interval ; denotes the number of instances in which the target parameter exceeds a threshold in the interval and ; denotes the total number of occurrences in the interval. Based on the result calculated by the CBPF, the spatial distribution of each type of risk source is allocated to the satellite map, and the source path of each type of risk factor of the environmental receptor monitoring point is obtained.

8. The risk-oriented industrial park VOCs integrated source apportionment method according to claim 7, characterized in that, The Monte Carlo simulation and Crystal Ball software were used in S5 to quantify the uncertainty of the evaluation results. The VOCs exposure concentration of the environmental receptors was described by a lognormal distribution, and the OT, REL, EF, AT and ED were modeled by a triangular distribution. The standard deviations of the monitoring data of the environmental receptors, the risk assessment parameters and the VOCs source profile derived from PMF were set as 20% and 30% of their average values, respectively. Each simulation was performed for a preset number of iterations. The sensitivity analysis prioritizes the importance of the input assumptions in the risk assessment result, and determines the most influential sensitive input variable.

9. The risk-oriented industrial park VOCs integrated source apportionment method according to claim 8, characterized in that, The S6 comprises: If the health risk index is used as the purpose of VOCs emission reduction in the industrial park, the IMTs are calculated by the following formula: ； wherein, , and represent the target risk levels for odor pollution, non-carcinogenic risk and carcinogenic risk, respectively; , and are set to 1, 1 and 1 x 10 –6 , respectively; If the environmental effect risk index is used as the purpose of VOCs emission reduction in the industrial park, the IMTs are calculated by the following formula: wherein and respectively represent the target risk level for ozone formation potential and secondary organic aerosol formation potential. The VOCs species are calculated Afterwards, the observations Obs during the monitoring of the environmental receptors that exceed these targets are selected. The reduction rate of the VOCs species and its source under the lowest acceptable risk level is calculated by the following formula: ； wherein represents the reduction rate of VOC species ​ The sharing rate of the VOCs emission reduction of each risk source is calculated by the following formula: wherein, representing the risk source the percentage of the source profile of the VOCs species to which the emission reduction share rate is applied; representing the VOCs species determined in the PMF model in the source profile of the risk source ​ According to the reduction rate of each VOCs species of each risk source obtained by the risk source comprehensive reduction method, combined with the matching result of the receptor and the source component spectrum, the reduction control measures are provided for each secondary pollution source of the VOCs emission of each risk source.

10. A risk-oriented industrial park VOCs integrated tracing system, characterized in that, The risk-oriented industrial park VOCs comprehensive tracing method is used.

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