A method for constructing an industrial source VOCs emission composition spectrum based on headspace analysis and material balance algorithm

Abstract

The application provides a kind of industrial source VOCs emission component spectrum construction method based on headspace analysis and material balance algorithm.The method comprises the following steps: (1) raw material sample collection and pretreatment (2) VOCs component analysis in raw material (3) material balance model establishment (4) enterprise overall emission component spectrum establishment.The application realizes the cross-scale connection from the physical and chemical properties of solvent to enterprise emission spectrum through the coupling of experimental determination and material balance simulation, significantly improves the accuracy, representativeness and operability of industrial VOCs emission source component spectrum, and provides a scientific, systematic new method for industry emission reduction decision and pollution source analysis.

Description

Technical Field

[0001] This invention relates to the field of VOCs monitoring technology, and in particular to a method for constructing the composition spectrum of industrial source VOCs emissions based on headspace analysis and material balance algorithm. Background Technology

[0002] Industrial volatile organic compounds (VOCs) are a significant source of air pollution, posing potential hazards to urban air quality and human health. Source emission composition profiles refer to the proportion of different chemical components in a particular type of pollutant emitted from a pollution source relative to the total amount of pollutants, typically expressed as a mass percentage of the components. Constructing industrial source VOC emission composition profiles for industrial manufacturing enterprises helps them systematically understand the true compositional characteristics of their VOCs, identify highly reactive, highly toxic, and high-contribution pollutants, and provide a scientific basis for shifting pollution control from "total quantity control" to "precise composition control." This work can significantly improve the precision and standardization of enterprise environmental management, enhance emission compliance, risk controllability, and the ability to respond to regulatory inspections and environmental performance assessments.

[0003] Currently, although some studies both domestically and internationally have focused on constructing VOC emission characteristics and source composition profiles for typical industries such as chemical engineering, coatings, printing, and spraying, significant limitations and shortcomings still exist overall. These mainly include the following points:

[0004] First, my country's industrial VOCs monitoring system mainly focuses on organized emission outlets or plant boundary points. However, in most solvent use and chemical production processes, fugitive emissions often account for the majority of total emissions, but monitoring these is difficult and data is scarce, resulting in emission profiles that cannot fully reflect the true emission situation. Furthermore, after waste gas is treated by treatment facilities, the composition and relative proportions of the components change significantly. Relying solely on monitoring data from waste gas outlets to represent the overall emission characteristics of an enterprise or industry lacks scientific validity. Therefore, sampling points should be scientifically deployed based on production processes and emission points, and unified sampling and analysis standards should be established to ensure the representativeness and comparability of the data.

[0005] Secondly, industrial production processes are complex and product types are diverse. Even within the same industry, different companies have variations in raw material composition, solvent usage, and production processes, making existing source composition profiles difficult to apply universally. Obtaining representative profiles often requires repeated sampling and analysis across multiple companies, stages, and operating conditions, resulting in a massive workload and high costs, limiting large-scale adoption. Furthermore, some solvent-using industries (such as automobile manufacturing, painting, ink and adhesive production) have closed production workshops that are not open to the public, restricting sample collection, particularly lacking data on fugitive emissions characteristics, leading to significant data gaps in source composition profile databases.

[0006] Third, different studies exhibit significant differences in sampling and analytical methodologies, primarily in sampling media (SUMMA tanks, adsorption tubes, gas bags, etc.), analytical instruments (GC-MS, GC-FID, etc.), and the number of species measured (16-116). This methodological inconsistency leads to poor comparability and low reproducibility among results. More importantly, most existing studies employ only the arithmetic mean method when constructing source component profiles, simply averaging the proportions of components in each process step without considering the differences in VOC emissions at each stage. This averaging process can easily mask key processes or characteristic components with high emissions, reducing the representativeness and scientific rigor of the source profiles.

[0007] Finally, current VOCs sample collection by enterprises is mostly instantaneous, which is easily affected by the operating time, ventilation status, and ambient background air, resulting in insufficient sample representativeness and low data quality. Therefore, how to establish a method for testing and constructing the composition profile of industrial VOCs emission sources that balances representativeness, accuracy, and operability is a key bottleneck in current research. Summary of the Invention

[0008] Purpose of the invention: This invention addresses the problems of difficulty in obtaining enterprise emission source data, insufficient coverage of fugitive emissions, and insufficient representativeness of source component spectra in the existing technology. It proposes a comprehensive technical route that combines static headspace-GC / MS-FID quantitative analysis with material balance modeling. Specifically, it includes a method for constructing the component spectra of industrial source VOCs emissions based on headspace analysis and material balance algorithm.

[0009] The technical solution of this invention:

[0010] To achieve the above objectives, this invention provides a method for constructing the emission composition profile of industrial VOCs based on headspace analysis and material balance algorithm, the method comprising the following steps:

[0011] (1) Raw material sample collection and pretreatment: Collect raw material samples actually used by the enterprise and put them into sealed headspace bottles;

[0012] (2) VOCs component analysis in raw materials: Static headspace method was used. Samples were taken through a SUMMA tank and detected by gas chromatography-mass spectrometry / flame ionization. The VOCs component analysis in the solvent was performed using a GC-MS / FID system.

[0013] (3) Material balance model establishment: Collect basic parameters of VOCs emissions and process control data of enterprises, and establish a calculation model for the VOCs emissions of each component in the raw material sample:

[0014] (Equation 1)

[0015] (Equation 2)

[0016] (Equation 3)

[0017] In the formula, Y i Is using i VOCs generation from raw materials, t / year; w i yes i Annual consumption of raw materials, t / year; f i yes i VOCs percentage content of raw materials, %; T i This refers to the amount of VOCs removed by waste gas treatment facilities; t / year; R i The amount of VOCs recovered; t / year; O b,i For the process b The volatility coefficient, % η b,i For the process b The exhaust gas collection efficiency is % ɛ b,i For the process b The processing efficiency, % E i For use i VOCs emitted from raw materials, t / year;

[0018] (4) Establishment of overall enterprise emission composition profile: Based on the VOCs emissions of each component calculated from the raw material samples, calculate the VOCs emission model of each component of the enterprise:

[0019] (Equation 4)

[0020] (Equation 5)

[0021] In the formula, m i,k =C i,k ×Q i , m i =C sum,i ×Q i , f i,k yes i species in raw materials k mass percentage, % m i,k yes i species in raw materials k Mass, mg;m i yes i Total mass of VOCs in raw materials, mg; C i,k for i species in raw materials k mass concentration, mg / m³ 3 ; C sum,i for i Mass concentration of total VOCs in raw materials; mg / m³ 3 ; Q i For gas flow rate, m 3 / h; m It refers to the number of VOC components;

[0022] After weighting and normalization, the overall VOCs emission source composition profile of the enterprise is obtained:

[0023] (Equation 6)

[0024] In the formula, X k VOCs species k mass percentage, % E j It is a raw material i VOC emissions, t / a; E It represents the total VOCs emissions of the enterprise, in tons per year (t / a). n The number of VOCs emission points for enterprises.

[0025] In some embodiments, the raw material sample is the raw material used by the company to process its products. Volatile organic compounds are generated during the processing of these raw materials. The raw material sample may specifically be coatings, inks, adhesives, thinners, wetting agents, and cleaning agents, etc., and the raw material type may be water-based, solvent-based, or UV-curable, depending on the company's actual production situation.

[0026] In some implementations, the static headspace method specifically includes headspace balancing and headspace injection;

[0027] The headspace equilibration process includes the following steps: Using a 20 mL headspace vial, add 1.00 mL (±0.01 mL) of the solvent sample to be tested and record the mass. The remaining gas volume in the headspace vial should be approximately 19 mL to ensure a good headspace / liquid volume ratio. Equilibrate by shaking at a constant temperature. After headspace equilibration is complete, connect the upper air layer of the headspace vial to the sampling container.

[0028] Furthermore, the oscillation temperature for isothermal equilibration is 40-100℃, the equilibration time is 20-40 min, and the oscillation speed is 300-600 rpm; even further, the oscillation temperature for isothermal equilibration is 40-80℃, the equilibration time is 20-30 min, and the oscillation speed is 300-500 rpm. Due to the high volatile concentration of the solvent, evacuating the upper air of the headspace vial from the vacuum SUMMA container for approximately 30 seconds is sufficient. In addition, since this method is primarily used to obtain stable relative proportions of components, the sampling volume is allowed to fluctuate within a certain range, provided that headspace equilibrium and the detection linear range are met. Therefore, the sampling time and volume do not need to be strictly controlled. However, an empty headspace vial sample is still required here as a method blank.

[0029] The headspace injection includes the following steps: extracting 0.5-1.0 mL of headspace gas and introducing it into the gas chromatography system, with the injection port temperature at 200-250℃, for component determination.

[0030] In some embodiments, the VOCs component analysis is performed using a SUMMA canister sampling system combined with a pre-concentration-GC-MS / FID system. After collecting the gas sample, it is diluted with high-purity nitrogen using a dynamic dilution gas mixer to ensure the sample volume and concentration meet the instrument's detection range. The canister pressure is adjusted to approximately 15 psi positive pressure. The diluted gas sample is stored at room temperature in the dark and analyzed within 24-48 hours. Before injection, canister blank and method blank tests are performed sequentially. The diluted sample is then subjected to cold trap dehydration and low-temperature enrichment using a pre-concentration system. VOCs are captured at approximately -165 °C, followed by rapid heating and desorption to approximately 100 °C before being introduced into a gas chromatography column for separation. The separated samples are then fed into a mass spectrometer and a flame ionization detector. Mass spectrometry is used for component qualitative analysis, while flame ionization is used for quantitative analysis, thereby obtaining the individual VOCs components and their relative contents in the gas sample.

[0031] The quantitative analysis employed a combined internal and external standard calibration method, using PAMS and TO-15 standard gases as external standards, and bromochloromethane, 1,4-difluorobenzene, deuterated chlorobenzene, and 1-bromo-4-fluorobenzene as internal standards. A standard working curve was established using multiple concentration gradients, and the target compound was quantified when the correlation coefficient R² was greater than 0.99. Each VOC species was qualitatively confirmed using characteristic ion binding retention times, ultimately obtaining the characteristic spectra of VOC components for each solvent or emission gas sample.

[0032] In some implementations, the enterprise's basic VOCs emission parameters and process control data cover key data from three levels: material use, process emissions, and end-of-pipe treatment in the enterprise's VOCs emission process; specifically, the key data includes... i VOCs generation from raw materials ( Yi ), i Annual usage of raw materials ( w i ), i VOCs percentage content of raw materials ( f i The amount of VOCs removed by waste gas treatment facilities (T) i ), the amount of VOCs recovered ( Ri ), process b Volatility coefficient ( O b,i ), process b Waste gas collection efficiency ( η b,i ), process b Processing efficiency ( ɛ b,i ),use i VOCs emitted from raw materials E i ), i species in raw materials k mass percentage ( f i,k ), i species in raw materials k quality ( m i,k ), i The total mass of VOCs in the raw materials ( m i ), i species in raw materials k mass concentration ( C i,k ), gas flow rate ( Q i ), number of VOCs components ( m ), total VOCs emissions from enterprises ( E ), number of VOCs emission points of enterprises ( n ).

[0033] In the technical solution of the present invention, formula (1) uses the amount of raw materials used ( w i ) and VOCs content ( f i Based on ), the calculation uses the first i The theoretical VOCs generation of a raw material under ideal complete release conditions; Equation (2) decomposes the actual production process of an enterprise into multiple process steps. b Through the volatility coefficient O -Collection efficiency η -Processing efficiency εThe third-level parameter provides a quantitative description; Equation (3) is based on the theoretical production amount, minus the recovered portion ( R i ) and the parts removed by the treated facilities ( T i ), to obtain the use of the first i The actual VOC emissions from the raw materials.

[0034] In the technical solution of this invention, the basis and significance of establishing equations (4) and (5) is to determine the "relative composition" of a single raw material. This step addresses which components constitute VOCs in each raw material / emission source and what proportion each component accounts for. Equation (6) is the basis for constructing the overall emission composition spectrum of the enterprise. The overall emission composition spectrum of the enterprise is essentially a mass-weighted average of the composition spectra of multiple emission sources. Therefore, the actual emission amount of each raw material is used. E i As a weight, for each source f i,k Superimpose them. Attached Figure Description

[0035] Picture 1 This invention provides an overall flowchart for the method of constructing the emission composition profile of VOCs from industrial sources;

[0036] Picture 2 This is a schematic diagram of the device connecting the static headspace experiment and the GC-MS / FID analysis system described in this invention;

[0037] Picture 3 This is a schematic diagram of the material balance described in this invention;

[0038] Picture 4 The VOC emissions of various VOCs-related raw and auxiliary materials in the example enterprise are calculated.

[0039] Picture 5 Typical and major VOCs component spectra obtained from GC-MS / FID analysis of the example enterprise.

[0040] The present invention will be further illustrated below through embodiments, but is not limited to these embodiments.

[0041] Beneficial effects:

[0042] This invention addresses the issues of insufficient representativeness and weak engineering relevance in the construction of VOC emission source composition profiles for solvent-using enterprises. It develops a systematic and scalable method for source composition profile construction by combining experimental measurements with material balance modeling. On one hand, a static headspace equilibrium parameter system adapted to solvent systems with different polarities and boiling points is established. Combined with GC-MS and internal standard correction, this achieves high-precision qualitative and quantitative analysis of VOC components in various solvent types, providing reliable basic data for source composition profile construction. On the other hand, a segmented material balance model is introduced, comprehensively considering solvent usage, volatility coefficient, waste gas collection rate, and treatment efficiency to realistically depict the generation and fate of VOCs in each production stage. Based on this, the actual emissions of each process are used as weights to weighted normalize the component characteristic spectra from different sources, constructing the overall VOC emission composition profile for the enterprise, ensuring that high-emission-contributing stages are reasonably represented in the source composition profile. Simultaneously, a standardized parameter system and a portable model framework are formed, supporting large-scale applications in different industries and enterprises. This method enables a quantitative correlation between solvent composition and enterprise emission fingerprints, significantly improving the accuracy, representativeness, and engineering operability of industrial VOCs emission source composition profiles, and providing a scientific basis for precise emission reduction, process optimization, and solvent substitution assessment. Detailed Implementation

[0043] The present invention will be described below with reference to specific embodiments. It should be noted that the following embodiments are examples of the present invention and are used only to illustrate the invention, not to limit it. Other combinations and various modifications within the scope of the present invention can be made without departing from its spirit or scope.

[0044] Unless otherwise specified, all chemical reagents used in this invention are commercially available analytical grade reagents.

[0045] This embodiment provides a method for constructing the emission composition profile of industrial VOCs based on headspace analysis and material balance algorithm, the flowchart of which is shown below. Picture 1 As shown, it includes the following steps:

[0046] (1) Raw material sample collection and pretreatment: 1.00 mL (±0.01 mL) of various solvent samples used in the production process (including water-based ink, water-based laminating adhesive, water-based varnish, and water-based adhesive) were collected from a packaging and printing company; the samples were centrifuged in 50 mL centrifuge tubes to remove non-volatile impurities and stabilize the solvent system; and the usage conditions of the corresponding raw materials and auxiliary materials were recorded.

[0047] (2) VOCs component analysis in raw materials: Use 20 mL headspace vials, add 1.00 mL (±0.01 mL) of the solvent sample to be tested to each vial, leaving approximately 19 mL of gas phase in the headspace vial (ignoring the volume of the cap and the pinhole), to ensure a good headspace / liquid volume ratio. Equilibrate at a constant temperature of 60℃ for 20 min. After headspace equilibration, connect the SUMMA container to the headspace vial pinhole using an external valve, ensuring the valve and interface are clean. Due to the high volatile concentration of the solvent, the upper air of the headspace vial can be extracted by the vacuum SUMMA container for about 30 s. In addition, this is mainly used to obtain stable relative proportions of components. Therefore, under the premise of satisfying headspace equilibration and detection linearity range, the sampling volume is allowed to fluctuate within a certain range. The volatile experiment here is only to obtain the relative proportions of various volatile components in the solvent. The total concentration has no effect on the subsequent establishment of the source component spectrum. Therefore, the sampling time and sampling volume do not need to be strictly controlled. An empty headspace vial sample is also required here as a method blank.

[0048] Since the SUMMA canisters are under negative pressure after gas collection, an Entech 4600 dynamic dilution gas mixer was used for dilution with high-purity nitrogen to ensure that the sample volume and concentration met the requirements of the analytical instrument's volume and detection range. All gas canisters were maintained within a specific pressure range (approximately 15 psi) to ensure positive pressure within the canisters. After dilution, the SUMMA canisters can be stored at room temperature in a dark place for analysis. A schematic diagram of the connection device is shown below. Picture 2 As shown.

[0049] Before injection, a blank sample (i.e., a SUMMA container without any solvent, filled with high-purity nitrogen) and a method blank (i.e., a head-up empty bottle sample) are required. The diluted VOCs sample is analyzed using the ZF-PKU-VOC1007 pre-concentrated-GC-MS / FID atmospheric volatile organic compound measurement system to determine the VOCs components and their relative contents. A "component characteristic spectrum" of the volatile VOCs is obtained for each solvent. This system uses dual-channel injection; the sample is frozen and dehydrated before entering two separate trap columns, where it is cryogenically enriched at -165°C. In both analytical and analytical states, the trap columns are heated to 100°C, and the sample is separated in the chromatographic column and detected by a flame ionization detector (FID) and a mass spectrometer (MS), respectively. A complete analytical process can be divided into four steps: sample acquisition (including internal standard acquisition), analytical treatment, analysis, and heating backflushing. In this study, PAMS and TO-15 were selected as external standard compounds and four internal standard compounds: bromochloromethane, 1,4-difluorobenzene, deuterated chlorobenzene, and 1-bromo-4-fluorobenzene. This study quantitatively analyzed 110 VOC components, including 29 alkanes, 11 alkenes, 1 alkyne, 17 aromatic hydrocarbons, 35 halogenated hydrocarbons, and 22 oxygenated organic compounds (OVOCs).

[0050] In quantitative analysis, internal standard or external standard methods are typically used for instrument calibration. The external standard method establishes a working curve directly from the response value (e.g., peak area) of the target component to its concentration; the internal standard method establishes a working curve from the ratio of the response of the target component to that of the internal standard component, and the ratio of their concentrations. Based on these working curves, quantitative analysis of the target compound can be performed. FID uses the external standard curve method to quantify unknown components, while MS uses the internal standard curve method. The internal standard compound was diluted to 4 ppbv with high-purity nitrogen using an Entech 4600 dynamic dilution gas mixer. Simultaneously, the external standard method was used to quantify the target components. Five concentration points within the range of 0.2 ppbv-16 ppbv were selected to establish a working curve. Specifically, PAMS and TO-15 mixed standard gases were diluted to different concentration levels and placed in separate sampling containers. An equal amount of internal standard was added during injection for GC-MSD / FID analysis, with the same concentration gradient repeated 3-4 times. A graph was plotted with the relative response of each target compound to the internal standard (Ri / Ristd) on the ordinate and the concentration ratio of the standard to the internal standard (Ci / Cistd) on the abscissa. Regression was performed to obtain the calibration working curve. A qualified calibration curve has an R... 2 Value (coefficient of determination) > 0.99. Quantification of VOC species is only permitted if a suitable calibration curve exists. When setting quantitative parameters, one ion is used as the quantitative ion for each compound, and the compound is qualitatively characterized by the relative proportions of two or more ions combined with chromatographic retention time.

[0051] (3) Material balance model establishment: Investigate the annual usage, application process, VOCs control measures, and control efficiency (such as recovery rate and absorption rate) of each solvent in the enterprise. Combine the solvent usage with the control efficiency to calculate the actual VOCs emissions of each solvent. Based on the volatilization experiment and the enterprise's usage, calculate the VOCs emissions per unit weight or volume of each solvent, and establish a VOCs emission calculation model for each component in the sample according to the following formula:

[0052] (Equation 1)

[0053] (Equation 2)

[0054] (Equation 3)

[0055] In the formula, Y i Is using i VOCs generation from raw materials, t / year; w i yes i Annual consumption of raw materials, t / year; f i yes iVOCs percentage content of raw materials, %; T i This refers to the amount of VOCs removed by waste gas treatment facilities; t / year; R i The amount of VOCs recovered; t / year; O b,i For the process b The volatility coefficient, % η b,i For the process b The exhaust gas collection efficiency is % ɛ b,i For the process b The processing efficiency, % E i For use i VOCs emitted from raw materials, t / year;

[0056] (4) Establishment of the overall emission composition profile of the enterprise: Multiply the unit emission profile of all solvents in the enterprise by their actual usage and control efficiency to obtain the emission contribution of each solvent. A weighted average of the VOCs emission contributions of all solvents is then performed to obtain the overall VOCs emission source composition profile of the enterprise. Due to the different emission rates (intensities) of VOCs from different pollution sources and different emission processes from the same emission source, there are significant differences in the VOCs concentrations of each sample. To eliminate the influence of concentration differences between samples on the average value and to establish a source composition profile that reflects the emission characteristics, it is necessary to normalize the mass concentration data of each sample and take the average value of gas samples from the same emission source as the value of the emission source composition profile, expressed as a mass percentage.

[0057] The VOCs emission model for each component of the enterprise is calculated based on the VOCs emissions of each component obtained from the raw material samples using equations (1)-(3):

[0058] (Equation 4)

[0059] (Equation 5)

[0060] In the formula, m i,k =C i,k ×Q i , m i =C sum,i ×Q i , f i,k yes i species in raw materials k mass percentage, % mi,k yes i species in raw materials k Mass, mg; m i yes i Total mass of VOCs in raw materials, mg; C i,k for i species in raw materials k mass concentration, mg / m³ 3 ; C sum,i for i Mass concentration of total VOCs in raw materials; mg / m³ 3 ; Q i For gas flow rate, m 3 / h; m It refers to the number of VOC components;

[0061] Within the same emission source category, the emission intensity (emission rate) of VOCs from different industries or processes can vary significantly. Therefore, weighted averaging of source component characteristics at different emission stages based on emission intensity to obtain a composite source spectrum based on emission intensity can better reflect the actual VOCs emission characteristics. Due to potential difficulties in data or information availability, different weighting factors are often selected for weighted averaging in practical applications. Common weighting factors include sample emission concentration, VOCs emission amount (inventory), raw material usage, product quantity, and output value. However, these weighted average source component spectra are significantly affected by the allocation factors and may only represent specific regions or industries. This study obtained VOCs emission amounts and source spectra at different stages of enterprise operations through field measurements and surveys; then, by using an emission-weighted method, the VOCs source spectrum of each enterprise was obtained, resulting in the overall VOCs emission source component spectrum for the enterprise.

[0062] (Equation 6)

[0063] In the formula, X k VOCs species k mass percentage, % E j It is a raw material i VOC emissions, t / a; E It represents the total VOCs emissions of the enterprise, in tons per year (t / a). n The number of VOCs emission points for enterprises.

[0064] Based on the above principles, enterprise-collected data, and calculation formulas, the material balance diagram is as follows: Picture 3As shown in the table below, the VOCs component data in the sample, the actual solvent emission VOCs data, and the overall emission composition data of the enterprise were obtained.

[0065] Table 1. Data on VOCs components in samples, actual solvent emission VOCs data, and overall emission composition data of enterprises.

[0066]

[0067] Based on the data table above, a VOCs emission map of various VOCs-related raw and auxiliary materials in the enterprise was plotted. Detailed results are as follows: Picture 4 , Picture 5 As shown, establishing VOCs emission composition profiles for industrial enterprises is fundamental to upgrading industrial emission management from "total quantity control" to "structural control," and from "experience-based governance" to "mechanism-based governance." This is essential for achieving precise source tracing, targeted emission reduction, efficient governance, and scientific decision-making. This method organically integrates experimental determination of solvent components with enterprise material balance parameters to quantitatively construct emission source composition profiles. It does not rely on complex on-site sampling and monitoring, and possesses high repeatability, representativeness, and scalability.

[0068] This invention establishes a headspace equilibrium parameter matrix for solvents with different polarities and boiling points, optimizes equilibrium temperature and time, and combines gas chromatography-mass spectrometry (GC-MS) with internal standard quantitative correction to achieve high-precision component determination in different solvent systems. This step can obtain the mass fraction of VOCs components in various solvents, providing basic data for emission source spectrum calculations.

[0069] This invention introduces a staged material balance model into the source composition profile construction of the solvent-using industry. By comprehensively considering solvent usage, waste gas collection rate, and treatment efficiency at each stage, the model quantitatively describes the VOC emissions at different stages, achieving a realistic reproduction of the actual production emission process.

[0070] This invention differs from the traditional arithmetic mean method by using a weighted and normalized approach. By using the VOC emissions of each process as a weighting factor, this invention constructs a weighted source spectrum for an enterprise or industry, thereby reasonably representing the processes with high emission intensity and improving the representativeness of the source spectrum.

[0071] This invention establishes a database of typical process parameters (including solvent type, collection efficiency, treatment efficiency, etc.) through parameter system standardization and portability, forming a parameterized model system that can be promoted and used in different industries and enterprises, supporting batch and automated emission characteristic analysis.

[0072] This invention utilizes a closed-loop design based on source spectrum application. By constructing an emission source composition spectrum, it can further identify highly reactive components (high OFP) or highly toxic species, support the optimization of production processes and the quantitative evaluation of solvent substitution solutions, thereby forming a closed-loop management system of "source spectrum - control - substitution".

[0073] In summary, this invention, through the coupling of experimental measurements and material balance simulation, achieves a cross-scale connection from solvent physicochemical properties to enterprise emission profiles, significantly improving the accuracy, representativeness, and operability of industrial VOCs emission source composition profiles, and providing a scientific and systematic new method for industry emission reduction decisions and pollution source analysis.

[0074] This invention can also be implemented in various other ways. Without departing from the spirit and essence of this invention, those skilled in the art can make various corresponding changes and modifications according to this invention, but these corresponding changes and modifications should all fall within the protection scope of the appended claims.

Claims

1. A method for constructing the emission composition profile of industrial VOCs based on headspace analysis and material balance algorithm, characterized in that, The method includes the following steps: (1) Raw material sample collection and pretreatment: Collect raw material samples actually used by the enterprise and put them into sealed headspace bottles; (2) VOCs component analysis in raw materials: Static headspace method was used. Samples were taken through a SUMMA tank and detected by gas chromatography-mass spectrometry / flame ionization. The VOCs component analysis in the solvent was performed using a GC-MS / FID system. (3) Material balance model establishment: Collect basic parameters of VOCs emissions and process control data of enterprises, and establish a calculation model for the VOCs emissions of each component in the raw material sample: In the formula, Y i Is using i VOCs generation from raw materials, t / year; w i yes i Annual consumption of raw materials, t / year; f i yes i VOCs percentage content of raw materials, %; T i This refers to the amount of VOCs removed by waste gas treatment facilities; t / year; R i The amount of VOCs recovered; t / year; O b,i For the process b The volatility coefficient, % η b,i For the process b The exhaust gas collection efficiency is % ɛ b,i For the process b The processing efficiency, % E i For use i VOCs emitted from raw materials, t / year; (4) Establishment of overall enterprise emission composition profile: Calculate the VOCs emission model for each component of the enterprise based on the VOCs emissions of each component calculated from the raw material samples. In the formula, m i,k =C i,k ×Q i , m i =C sum,i ×Q i , f i,k yes i species in raw materials k mass percentage, % m i,k yes i species in raw materials k Mass, mg; m i yes i Total mass of VOCs in raw materials, mg; C i,k for i species in raw materials k mass concentration, mg / m³ 3 ; C sum,i for i Mass concentration of total VOCs in raw materials; mg / m³ 3 ; Q i For gas flow rate, m 3 / h; m It refers to the number of VOC components; After weighting and normalization, the overall VOCs emission source composition profile of the enterprise is obtained: In the formula, X k VOCs species k mass percentage, % E j It is a raw material i VOCs emissions, t / a; E It represents the total VOCs emissions of the enterprise, in tons per year (t / a). n The number of VOCs emission points for enterprises; The static headspace method specifically includes headspace balancing and headspace injection; The headspace equilibration includes the following steps: using a 20 mL headspace vial, add 1.00 mL (±0.01 mL) of the solvent sample to be tested, record the mass, and equilibrate by shaking at a constant temperature; after headspace equilibration is completed, connect the upper air of the headspace vial to the sampling container; The oscillation temperature for the isothermal oscillation equilibrium is 40-100℃, the equilibrium time is 20-40 min, and the oscillation speed is 300-600 rpm; further, the oscillation temperature for the isothermal oscillation equilibrium is 40-80℃, the equilibrium time is 20-30 min, and the oscillation speed is 300-500 rpm. The headspace injection includes the following steps: extracting 0.5-1.0 mL of headspace gas and introducing it into the gas chromatography system, with the injection port temperature at 200-250℃, for component determination.

2. The method for constructing the emission composition profile of industrial VOCs based on headspace analysis and material balance algorithm according to claim 1, characterized in that, The raw material samples are the raw materials used by the company to be tested for processing products; specifically, the raw material samples are coatings, inks, adhesives, thinners, wetting liquids, or cleaning agents.

3. The method for constructing the emission composition profile of industrial VOCs based on headspace analysis and material balance algorithm according to claim 1, characterized in that, The VOCs component analysis was performed using a SUMMA tank sampling system combined with a pre-concentration-GC-MS / FID system.

4. The method for constructing the emission composition profile of industrial VOCs based on headspace analysis and material balance algorithm according to claim 1, characterized in that, The enterprise's VOCs emission basic parameters and process control data cover key data from three aspects: material use, process emissions, and end-of-pipe treatment in the enterprise's VOCs emission process.

5. The method for constructing the emission composition profile of industrial VOCs based on headspace analysis and material balance algorithm according to claim 4, characterized in that, The key data includes i VOCs generation from raw materials i Annual usage of raw materials i VOCs percentage content of raw materials, amount of VOCs removed by waste gas treatment facilities, amount of recovered VOCs, and process flow. b Volatility coefficient, process b Waste gas collection efficiency and process b Processing efficiency, usage i VOCs emitted from raw materials i species in raw materials k mass percentage i species in raw materials k quality i The total mass of VOCs in the raw materials i species in raw materials k The mass concentration, gas flow rate, number of VOCs components, total VOCs emissions from enterprises, and number of VOCs discharge points from enterprises.

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