Method for on-line monitoring of dioxins by photoionization time-of-flight mass spectrometry

Abstract

The application provides a method for monitoring dioxins in flue gas by photoionization time-of-flight mass spectrometry online, screening volatile organic pollutants with high concentration or high instrument response in flue gas as dioxin indicators, directly monitoring the indicators in flue gas by photoionization time-of-flight mass spectrometry online, establishing the correlation between high-abundance indicators and dioxins by the simultaneous monitoring of indicators online and the offline detection of dioxins, and realizing the indirect online monitoring of dioxins in flue gas. The online monitoring cycle of the application is 20 min, and the offline sampling cycle is 120 min, so that 6 points of online monitoring can be carried out in 1 offline sampling cycle, and the correlation model is established by using 6 online monitoring points corresponding to 1 offline sampling point in the model establishment process. The online monitoring model of dioxins established by the application is a single or multiple correlation model, which guarantees the applicability of the correlation model, and the fault tolerance and risk resistance of the application to complex incineration environment.

Description

Technical Field

[0001] This invention relates to a method for online monitoring of dioxins using photoionization time-of-flight mass spectrometry. Background Technology

[0002] Dioxins (PCDD / Fs) are a collective term for polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). Depending on the number and position of chlorine atoms, they have 75 and 135 isomers, respectively. They are the most toxic substances discovered to date, classified as Group I carcinogens, and are known as the "poison of the century." Solid wastes such as municipal solid waste, medical waste, and hazardous waste have complex compositions, containing abundant inorganic chlorine, organic chlorine, metallic elements, and flammable substances, providing a material basis for the generation and release of dioxins and their analogues. The emission of persistent organic pollutants, represented by dioxins, from solid waste incineration flue gas has attracted widespread attention worldwide.

[0003] The traditional method for dioxin detection is the EPA-1613 method recommended by the U.S. Environmental Protection Agency (EPA), which uses isotope dilution high-resolution gas chromatography / high-resolution mass spectrometry (HRGC / HRMS) to analyze 4-8 chloroPCDD / Fs. Standard methods for determining dioxins from stationary sources involve complex processes such as sampling, Soxhlet extraction, purification, volume adjustment, and analysis. While accurate, this method is time-consuming (over a week) and costly, typically allowing only 1-2 spot checks per year on waste incinerators. It fails to meet the public's demand for real-time information on dioxin emissions and cannot allow for adjustments to incinerators based on real-time data to control emissions. The development of online dioxin monitoring technology is of great significance for the development of dioxin emission monitoring and reduction control technologies.

[0004] Dioxins are present in trace or ultra-trace amounts (1.14–19.77 ng / Nm³) in the complex flue gas from waste incineration. 3 Due to the presence of dioxins, direct online monitoring of dioxins is difficult. Using high-concentration, easily monitored dioxin indicators, a correlation model can be established between indicator concentration and dioxin concentration and toxic equivalent concentration (TEQ). Indirect monitoring of dioxin emissions can be achieved through online monitoring of these indicators. Dioxin indicators documented in the literature include: chlorobenzene (CBz), chlorophenol (CPh), polycyclic aromatic hydrocarbons (PAHs), as well as CO, O2, HCl, and NO. xExtensive research has been conducted both domestically and internationally on the correlation between dioxin indicators and dioxins. However, the amount of data is limited, the correlation varies significantly, and the models lack universality. Therefore, there is still a long way to go before developing commercially available online dioxin monitoring instruments to achieve accurate and stable online monitoring of dioxins.

[0005] High-sensitivity photoionization time-of-flight mass spectrometry (PI-TOFMS) employs a vacuum ultraviolet (VUV) lamp combined with photoionization technology to achieve efficient ionization of volatile organic compounds such as chlorobenzene and chlorophenol in complex matrices, unaffected by atmospheric background interference. It features few fragment ions, easy spectrum interpretation, and ultra-high sensitivity in the order of seconds and ppt. Utilizing high-resolution vertical accelerating reflectance time-of-flight mass spectrometry, it offers advantages such as high mass accuracy, fast analysis speed, and full mass scanning. The high sensitivity, high mass resolution, wide sample detection capability, and broad linear range of PI-TOFMS, along with its advantages of requiring no sample pretreatment, humidity resistance, high stability, and portable field measurement, make it highly promising for online monitoring of dioxin indicators. Summary of the Invention

[0006] The purpose of this invention is to provide a method for online monitoring of dioxins in flue gas using photoionization time-of-flight mass spectrometry. This method screens volatile organic pollutants with high concentrations or high instrument response in flue gas as dioxin indicators, directly monitors the indicators in flue gas online using photoionization time-of-flight mass spectrometry, and establishes the correlation between high-abundance dioxin indicators and dioxins by simultaneously performing online monitoring of dioxin indicators and offline detection of dioxins, thereby achieving indirect online monitoring of dioxins in flue gas.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] A method for online monitoring of dioxins in flue gas using photoionization time-of-flight mass spectrometry (POTFMS) is disclosed. This method screens volatile organic pollutants with high concentrations (high abundance) in flue gas as dioxin indicators, directly monitors the indicators in flue gas online using POTFMS, and establishes a correlation model between high abundance indicators and dioxins in flue gas by simultaneously performing online monitoring of dioxin indicators and offline detection of dioxins, thereby achieving indirect online monitoring of dioxins in flue gas.

[0009] The method is specifically as follows:

[0010] (1) At any sampling point in the incineration system, a photoionization time-of-flight mass spectrometer is used to sample and detect the incineration flue gas sample in real time to obtain the mass spectrum. One or more volatile organic pollutants with high abundance are selected from the mass spectrum as dioxin indicators. The dioxin indicators are qualitatively confirmed according to the accurate mass number, a standard curve of dioxin indicators is established, and the dioxin indicators are quantitatively analyzed.

[0011] (2) Offline sampling of dioxins in flue gas was performed at any sampling point in the incineration system. The collected dioxin samples were analyzed and detected in the laboratory using isotope dilution high-resolution gas chromatography-high-resolution mass spectrometry to obtain the concentration and toxic equivalent concentration of dioxins in flue gas.

[0012] (3) Adjust the incineration conditions of the sampling point in step (1), and obtain the concentration of dioxin indicator under different incineration conditions according to the operation process of step (1). At the same sampling point as in step (2), perform offline sampling and analysis of dioxin in flue gas to obtain the concentration and toxic equivalent concentration of dioxin in flue gas.

[0013] (4) Using the linear regression method, with the concentration of the indicator at the sampling point as the independent variable X and the concentration of dioxin or the dioxin toxicity equivalent at the sampling point as the dependent variable Y, a multivariate correlation model of the same site and / or different site between the concentration of the dioxin indicator at the sampling point and the concentration of dioxin, and between the concentration of the dioxin indicator and the dioxin toxicity equivalent is established to realize indirect online monitoring of dioxins in flue gas.

[0014] The dioxin indicator is one or more of the following: benzene compounds, phenols, chlorocresols, chlorotoluenes, chlorophenols, chlorobenzenes, polycyclic aromatic hydrocarbons, and dioxin parent compounds.

[0015] The benzene compounds are one or more of benzene, toluene, xylene, trimethylbenzene, and tetramethylbenzene; the phenols are one or more of phenol, methylphenol, dimethylphenol, and nitrophenol; the chlorotoluenes are one or more of monochlorotoluene, dichlorotoluene, trichlorotoluene, tetrachlorotoluene, and pentachlorotoluene; the chlorocresols are one or more of monochlorocresol, dichlorocresol, trichlorocresol, and tetrachlorocresol; and the chlorobenzenes are one or more of monochlorobenzene, dichlorobenzene, trichlorobenzene, tetrachlorobenzene, pentachlorobenzene, and hexachlorobenzene. ; Chlorophenols are one or more of monochlorophenol, dichlorophenol, trichlorophenol, tetrachlorophenol, pentachlorophenol, and hexachlorophenol; Polycyclic aromatic hydrocarbons are one or more of naphthalene, acenaphthene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benzo(a)anthene, chrysene, benzo(b) fluoranthene, benzo(k) fluoranthene, benzo(a)pyrene, indole(1,2,3-cd)pyrene, dibenzo(a,n)anthene, and benzo(ghi)pyrene; Dioxin parent compounds are one or more of dibenzo-p-dioxin and dibenzofuran.

[0016] The photoionization time-of-flight mass spectrometer uses a vacuum ultraviolet lamp ionization source, and the experimental conditions are as follows: vacuum ultraviolet lamp voltage 1000–2000 V, ionization region gas pressure 4.0 × 10⁻⁶. 2 ~6.00×10 2 Pa, ion source temperature 100–200℃, MCP voltage 3700–4800V, detection zone gas pressure 7.00 × 10⁻⁶.-6 ~3.00×10 -4 Pa, detection time is 0.5-10 min.

[0017] The incineration conditions include one or more of the following: boiler temperature, primary air temperature, secondary air volume, oxygen content, urea spraying, ammonia water use, activated carbon use, industrial waste ratio, and landfill leachate spraying.

[0018] The boiler temperature is 900–1100℃, the primary air temperature is 150–200℃, and the secondary air volume is 80,000–100,000 m³ / h. 3 One or more of the following: / h, oxygen content of 5% to 15%, urea spraying rate of 50-100 kg / h, ammonia water usage of 0-100 kg / h, activated carbon usage of 100-500 kg / d, industrial waste ratio of 0% to 40%, and leachate spraying rate of 0.1-10 tons.

[0019] Under different incineration conditions, the concentrations of dioxin indicators and dioxins in flue gas varied by 10-100 times.

[0020] Online monitoring of dioxin indicators in flue gas was conducted using photoionization time-of-flight mass spectrometry. By establishing a correlation model between dioxin indicators and dioxins, the dynamic emission characteristics of dioxin concentration and toxic equivalent concentration in flue gas were calculated.

[0021] The online monitoring period of this application is 20 minutes, and the offline sampling period is 120 minutes. Therefore, within one offline sampling period, online monitoring of 6 points can be carried out. In the process of model building, the correlation model is established by using 6 online monitoring points corresponding to 1 offline sampling point.

[0022] A flue gas pipeline is installed at the sampling site of the incineration system, and insulation measures are implemented to efficiently introduce the incineration flue gas into the photoionization source of the photoionization time-of-flight mass spectrometer. Volatile organic pollutants (VOCs) in the flue gas are ionized into molecular or quasi-molecular ions by the photoionization source. These ions are efficiently transmitted to a high-resolution reflective time-of-flight mass analyzer via a radio frequency quadrupole and electrostatic ion transport system. Ions with different mass-to-charge ratios, accelerated to the same energy, are separated and detected based on their different flight velocities and arrival times at the detector. The ion signals are recorded by a high-precision time-to-digital converter (TDC) acquisition card. Qualitative and quantitative analysis of the data is performed using the PIMS ANALYST data processing software. The molecular formula of VOCs in the flue gas can be directly determined using precise mass number information. VOCs with high concentrations or high instrument response in the flue gas are selected as dioxin indicators, and quantitative calculations are performed using indicator standard curves. Online monitoring of indicators and offline dioxin sampling are conducted simultaneously, and a correlation model between indicators and dioxins is established. This enables indirect online monitoring of dioxins in the flue gas.

[0023] The screening criteria for indicators in flue gas are high concentrations of volatile organic pollutants or volatile organic pollutants with strong instrument response. The aim is to ensure the accuracy of online monitoring and improve the stability of the correlation model.

[0024] This application has the following beneficial technical effects:

[0025] 1. This application selects high-abundance volatile organic pollutants with high concentrations or high instrument responses in flue gas as dioxin indicators. Substances with high concentrations and strong signals are more easily detected by instruments, resulting in better detection accuracy and stability, and providing reliable data support for the establishment of online monitoring models.

[0026] 2. The online dioxin monitoring model established in this application is a univariate or multivariate correlation model. In real incineration systems, small molecule volatile organic pollutants interact and transform with each other. The correlation of a single substance is random. The comprehensive correlation of multiple substances ensures the applicability of the correlation model and its fault tolerance and risk resistance in the face of complex incineration environments.

[0027] 3. This application uses indicators at different sites in flue gas to predict dioxins at different sites in flue gas. It takes into account the delayed effect of dioxin formation and transformation in the indicator phase, and the influence of flue gas purification systems, SCR devices, etc. on the correlation between indicators and dioxins, making it easier to screen more favorable online dioxin monitoring models. Attached Figure Description

[0028] Figure 1 This is a flowchart of the method for online monitoring of dioxins using photoionization time-of-flight mass spectrometry, as described in this application.

[0029] Figure 2 This is the online monitoring spectrum of dioxin indicators in flue gas in Example 1 of this application.

[0030] Figure 3 This is a standard curve diagram of eight dioxin indicators in flue gas, as shown in the example.

[0031] Figure 4 This is a schematic diagram of the solid waste incineration system of this application, where ①-boiler, ②-reaction tower, ③-bag filter, ④-SCR, ⑤-chimney, and A and B are sampling points. Detailed Implementation

[0032] Existing research indicates a necessary link between small molecule compounds in incineration flue gas and dioxin formation. Many substances can serve as indicators of dioxin formation, including chlorobenzene, chlorophenols, and polycyclic aromatic hydrocarbons (PAHs). Their concentrations are generally more than 20 times higher than dioxin concentrations, significantly reducing the requirements for detection limits and sensitivity in instruments. However, these indicators still exist in trace amounts in incineration flue gas and have high boiling points, posing challenges to online monitoring instruments and methods. This application takes a different approach, selecting simple aromatic hydrocarbons related to dioxins as dioxin indicators. These substances have concentrations more than 1000 times higher than dioxin concentrations, low boiling points, and high volatility, making them suitable for online monitoring using rapid mass spectrometry. This application screens high-abundance simple aromatic hydrocarbons in flue gas as dioxin indicators and achieves efficient detection of these indicators in flue gas by adjusting photoionization time-of-flight mass spectrometry detection parameters. By adjusting the incineration conditions of the incineration system, a correlation model between online monitoring indicators and offline dioxin detection under different operating conditions is established. In the daily operation of the incineration system, the model is continuously evaluated and optimized to improve its applicability and verify its accuracy and reliability.

[0033] According to this invention, photoionization time-of-flight mass spectrometry (PFOMS) is used as an online monitoring instrument for indicators in flue gas. The instrument includes a sample introduction system, an ionization source, an ion transport system, a mass analyzer, an ion detector, a data acquisition and processing system, and a vacuum system and an electrical control system to maintain the normal operation of the mass spectrometer. The ionization source uses photoionization technology, which produces molecular ion peaks for volatile indicators in flue gas with almost no fragment ions. The resulting spectrum is simple and easy to implement for online monitoring of volatile organic compounds in complex backgrounds.

[0034] This application conducts online monitoring of indicators and offline detection of dioxins at different sites in the incineration system, establishes correlation models between indicators and dioxins at different sites, and compares and evaluates them.

[0035] Example 1

[0036] Use the indicator at sampling point A to predict dioxins at sampling point A.

[0037] Includes the following steps:

[0038] (1) A sampling point A was taken in the incineration system. Using a two-stage sampling pump, a multi-channel sampling system, and automatic analysis and control software, the flue gas sample was passed through a sampling probe, a full-process high-temperature heating (180℃) pipeline, and a high-temperature dehydration (120℃) module before entering a photoionization time-of-flight mass spectrometer. The full-spectrum online monitoring of volatile organic compounds in the flue gas was performed. The mass spectrum is shown below. Figure 1 As shown in Table 1, 24 parallel online monitoring sessions were conducted, and the analytical parameters of the photoionization time-of-flight mass spectrometer were obtained.

[0039] (2) The eight aromatic compounds with the highest intensity in the spectrum were screened as indicators for online dioxin monitoring. Based on the characteristic peaks of the standard gas, the eight aromatic compounds with the highest intensity in the flue gas spectrum were qualitatively identified using the precise mass numbers of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol and dimethylphenol: 78.04695, 92.0626, 106.07825, 120.0939, 134.10955, 94.04187, 108.05752 and 122.07317. The eight aromatic compounds were: benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol and dimethylphenol.

[0040] (3) Establishing indicator standard curves using the online dilution method: Prepare 1 ppm of standard gases for each indicator, including benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol. Use high-purity nitrogen and a high-precision mass flow meter. Employ the online dilution method to dilute the standard gases to 1 ppb, 5 ppb, 10 ppb, 50 ppb, and 100 ppb, respectively. Following the order of concentration from low to high, after the signal reaches equilibrium at each concentration, perform parallel detection five times, take the average value, and calculate the relative standard deviation to establish the relative relationship curve between the peak area and concentration of each standard gas. The specific standard curves are shown below. Figure 3 As shown, V1-V8 represent benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol, respectively.

[0041] (4) Substitute the peak area of ​​the spectrum into the pre-established standard curve, and take the average value of the quantitative results of 24 detections to obtain the concentration values ​​of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol and dimethylphenol in the flue gas under normal working conditions as 0.6ppbv, 2.8ppbv, 11.7ppbv, 0.4ppbv, 1.0ppbv, 1.2ppbv, 1.5ppbv and 2.8ppbv respectively.

[0042] (5) At sampling point A of the incineration system, a flue gas dioxin isodynamic sampler was used to sample dioxins in the flue gas offline according to the national standard method HJ / T397-2007. Four parallel offline samples were collected and brought back to the laboratory for pretreatment according to the national standard method HJ 77.2-2008. Dioxins were analyzed and detected using isotope dilution high-resolution gas chromatography-high-resolution mass spectrometry. The average value of the detection results was taken, and the concentration of dioxins under normal operating conditions was found to be 3.6 ng / m³. 3 The toxic equivalent concentration is 0.23 ng / TEQ m. 3 The analytical parameters of the high-resolution gas chromatography-high-resolution mass spectrometry instrument are shown in Table 2.

[0043] (6) Based on the normal operating conditions, three more incineration conditions were adjusted. The adjusted incineration conditions included increasing the urea content, spraying leachate, and mixing in industrial waste to obtain the concentration values ​​of dioxin indicators and dioxins under different incineration conditions. The detection process was the same as steps (1)-(5). Specifically, the urea content was increased by 20%, and the concentration values ​​of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol were 0.4 ppbv, 0.8 ppbv, 46.4 ppbv, 0.2 ppbv, 0.8 ppbv, 1.2 ppbv, 2.6 ppbv, and 2.3 ppbv, respectively, and the dioxin concentration was 2.0 ng / m³. 3 The toxic equivalent concentration is 0.12 ng / TEQm. 3 One ton of landfill leachate was sprayed, with concentrations of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol of 0.4 ppbv, 2.2 ppbv, 7.2 ppbv, 0.5 ppbv, 0.9 ppbv, 1.1 ppbv, 4.0 ppbv, and 1.8 ppbv, respectively. The dioxin concentration was 4.3 ng / m³. 3 The toxic equivalent concentration is 0.23 ng / TEQ m. 3 The sample contained 20% industrial waste. The concentrations of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol were 0.3 ppbv, 2.6 ppbv, 6.6 ppbv, 0.4 ppbv, 1.0 ppbv, 1.1 ppbv, 1.7 ppbv, and 2.0 ppbv, respectively. The dioxin concentration was 4.1 ng / m³. 3 The toxic equivalent concentration is 0.23 ng / TEQ m. 3 .

[0044] (7) Using linear regression, with the indicator at sampling point A as the independent variable X and the dioxin concentration at sampling point A as the dependent variable Y, a multilocus correlation model of the indicator at sampling point A and the dioxin concentration at sampling point A was established. With the indicator at sampling point A as the independent variable X and the dioxin toxicity equivalent concentration at sampling point A as the dependent variable Y, a multilocus correlation model of the indicator at sampling point A and the dioxin toxicity equivalent concentration at sampling point A was established.

[0045] (8) The obtained correlation model and model validation results are shown in Table 3.

[0046] Table 1. PI-TOFMS instrument parameters for online monitoring of volatile organic compounds (VOCs) in flue gas.

[0047] parameter numerical values VUV lamp voltage 1400V ExtractV1 voltage 16V FocusV2 voltage 14V Skimmer1 voltage 10V Q-offset voltage 4V Skimmer2 voltage 2V Lens1 voltage 120V Lens3 voltage 100V P-offset voltage 25V MCP voltage 4250V Vacuum level (ion source) 584V Vacuum level (detector) <![CDATA[5.2×10 -4 In]]> Heat tracing pipe temperature 150℃ Ion source temperature 100℃

[0048] Table 2. HRGC / HRMS analysis parameters for offline dioxin detection.

[0049]

[0050] Table 3. Indicator prediction model and validation for sampling point A; Dioxin correlation model for sampling point A.

[0051]

[0052] Example 2

[0053] Use the indicator at sampling point A to predict dioxins at sampling point B.

[0054] Includes the following steps:

[0055] (1) A sampling point A was taken in the incineration system. Using a two-stage sampling pump, a multi-channel sampling system and automatic analysis control software, the flue gas sample was passed through a sampling probe, a full-process high-temperature heating (180°C) pipeline and a high-temperature dehydration (120°C) module, and entered the photoionization time-of-flight mass spectrometer to monitor the full spectrum of volatile organic compounds in the flue gas online. The parallel online monitoring was performed 24 times, and the instrument analysis parameters are shown in Table 1 of Example 1.

[0056] (2) The eight aromatic compounds with the highest intensity in the spectrum were screened as indicators for online dioxin monitoring. Based on the characteristic peaks of the standard gas, the eight aromatic compounds with the highest intensity in the flue gas spectrum were qualitatively identified using the precise mass numbers of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol and dimethylphenol: 78.04695, 92.0626, 106.07825, 120.0939, 134.10955, 94.04187, 108.05752 and 122.07317. The eight aromatic compounds were: benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol and dimethylphenol.

[0057] (3) Establishing indicator standard curves using the online dilution method: Prepare 1 ppm indicator standard gases, including benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol. Use high-purity nitrogen gas and a high-precision mass flow meter. Employ the online dilution method to dilute the standard gases to 1 ppb, 5 ppb, 10 ppb, 50 ppb, and 100 ppb, respectively. Following the order of increasing concentration, after the signal reaches equilibrium at each concentration, perform parallel detection five times, take the average value, and calculate the relative standard deviation to establish the relative relationship curve between the peak area and concentration of each standard gas. The specific standard curves are shown below. Figure 3 As shown, V1-V8 represent benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol, respectively.

[0058] (4) Substitute the peak area of ​​the spectrum into the pre-established standard curve, and take the average value of the quantitative results of 24 detections to obtain the concentration values ​​of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol and dimethylphenol in the flue gas under normal working conditions as 0.6ppbv, 2.8ppbv, 11.7ppbv, 0.4ppbv, 1.0ppbv, 1.2ppbv, 1.5ppbv and 2.8ppbv respectively.

[0059] (5) At sampling point B of the incineration system, a flue gas dioxin isodynamic sampler was used to sample dioxins in the flue gas offline according to the national standard method HJ / T397-2007. Four parallel offline samples were collected and brought back to the laboratory for pretreatment according to the national standard method HJ 77.2-2008. Isotope dilution high-resolution gas chromatography-high-resolution mass spectrometry was used to analyze and detect dioxins. The average value of the detection results was taken, and the concentration of dioxins under normal operating conditions was found to be 0.12 ng / m³. 3 The toxic equivalent concentration is 0.007 ng / TEQ m. 3 The instrument analysis parameters are shown in Table 2.

[0060] (6) Based on the normal operating conditions, three more incineration conditions were adjusted. The adjusted incineration conditions included increasing the urea content, spraying leachate, and mixing in industrial waste to obtain the concentration values ​​of dioxin indicators and dioxins under different incineration conditions. The detection process was the same as steps (1)-(5). Specifically, the urea content was increased by 20%, and the concentration values ​​of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol were 0.4 ppbv, 0.8 ppbv, 46.4 ppbv, 0.2 ppbv, 0.8 ppbv, 1.2 ppbv, 2.6 ppbv, and 2.3 ppbv, respectively, and the dioxin concentration was 0.12 ng / m³. 3 The toxic equivalent concentration is 0.008 ng / TEQ m. 3 One ton of landfill leachate was sprayed, with concentrations of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol of 0.4 ppbv, 2.2 ppbv, 7.2 ppbv, 0.5 ppbv, 0.9 ppbv, 1.1 ppbv, 4.0 ppbv, and 1.8 ppbv, respectively. The dioxin concentration was 0.11 ng / m³. 3 The toxic equivalent concentration is 0.01 ng / TEQ m. 3 The mixture contained 20% industrial waste. The concentrations of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol were 0.3 ppbv, 2.6 ppbv, 6.6 ppbv, 0.4 ppbv, 1.0 ppbv, 1.1 ppbv, 1.7 ppbv, and 2.0 ppbv, respectively. The dioxin concentration was 0.10 ng / m³.3 The toxic equivalent concentration is 0.009 ng / TEQ m. 3 .

[0061] (7) Using linear regression, with the indicator at sampling point A as the independent variable X and the dioxin concentration at sampling point B as the dependent variable Y, a multilocus correlation model between the indicator at sampling point A and the dioxin concentration at sampling point B was established. Similarly, with the indicator at sampling point A as the independent variable X and the dioxin toxicity equivalent concentration at sampling point B as the dependent variable Y, a multilocus correlation model between the indicator at sampling point A and the dioxin toxicity equivalent concentration at sampling point B was established.

[0062] (8) The obtained correlation model and model validation results are shown in Table 4.

[0063] Table 4. Sampling Point A: Indicator Prediction; Sampling Point B: Dioxin Correlation Model and Validation

[0064]

[0065] Example 3

[0066] Use the indicator at sampling point B to predict dioxins at sampling point A.

[0067] Includes the following steps:

[0068] (1) A sampling point was taken at sampling point B of the incineration system. Using a two-stage sampling pump, a multi-channel sampling system and automatic analysis control software, the flue gas sample was passed through the sampling probe, the full-process high-temperature heating (180℃) pipeline and the high-temperature dehydration (120℃) module, and entered the photoionization time-of-flight mass spectrometer. The full spectrum of volatile organic compounds in the flue gas was monitored online. 24 parallel online monitoring were performed. The analytical parameters of the photoionization time-of-flight mass spectrometer are shown in Table 1.

[0069] (2) The eight aromatic compounds with the highest intensity in the spectrum were screened as indicators for online dioxin monitoring. Based on the characteristic peaks of the standard gas, the eight aromatic compounds with the highest intensity in the flue gas spectrum were qualitatively identified using the precise mass numbers of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol and dimethylphenol: 78.04695, 92.0626, 106.07825, 120.0939, 134.10955, 94.04187, 108.05752 and 122.07317. The eight aromatic compounds were: benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol and dimethylphenol.

[0070] (3) Establishing indicator standard curves using the online dilution method: Prepare 1 ppm indicator standard gases, including benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol. Use high-purity nitrogen gas and a high-precision mass flow meter. Employ the online dilution method to dilute the standard gases to 1 ppb, 5 ppb, 10 ppb, 50 ppb, and 100 ppb, respectively. Following the order of increasing concentration, after the signal reaches equilibrium at each concentration, perform parallel detection five times, take the average value, and calculate the relative standard deviation to establish the relative relationship curve between the peak area and concentration of each standard gas. The specific standard curves are shown below. Figure 3 As shown, V1-V8 represent benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol, respectively.

[0071] (4) Substitute the peak area of ​​the spectrum into the pre-calculated standard curve, take the average value of the quantitative results of 24 detections, and obtain the concentration values ​​of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol and dimethylphenol in the flue gas under normal working conditions as 0.9ppbv, 3.1ppbv, 3.7ppbv, 0.3ppbv, 0.70ppbv, 1.4ppbv, 1.2ppbv and 1.9ppbv respectively.

[0072] (5) At sampling point A of the incineration system, a flue gas dioxin isodynamic sampler was used to sample dioxins in the flue gas offline according to the national standard method HJ / T397-2007. Four parallel offline samples were collected and brought back to the laboratory for pretreatment according to the national standard method HJ 77.2-2008. Dioxins were analyzed and detected using isotope dilution high-resolution gas chromatography-high-resolution mass spectrometry. The average value of the detection results was taken, and the concentration of dioxins under normal operating conditions was found to be 3.6 ng / m³. 3 The toxic equivalent concentration is 0.23 ng / TEQ m. 3 The analytical parameters of the high-resolution gas chromatography-high-resolution mass spectrometry instrument are shown in Table 2.

[0073] (6) Based on the normal operating conditions, three more incineration conditions were adjusted. The adjusted incineration conditions included increasing the urea content, spraying leachate, and mixing in industrial waste to obtain the concentration values ​​of dioxin indicators and dioxins under different incineration conditions. The detection process was the same as steps (1)-(5). Specifically, the urea content was increased by 20%, and the concentration values ​​of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol were 0.5 ppbv, 1.5 ppbv, 2.4 ppbv, 0.2 ppbv, 0.7 ppbv, 1.3 ppbv, 1.1 ppbv, and 1.4 ppbv, respectively. The dioxin concentration was 2.0 ng / m³. 3 The toxic equivalent concentration is 0.12 ng / TEQm. 3One ton of landfill leachate was sprayed, with concentrations of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol of 0.6 ppbv, 2.5 ppbv, 5.0 ppbv, 0.2 ppbv, 0.7 ppbv, 1.3 ppbv, 1.3 ppbv, and 1.4 ppbv, respectively. The dioxin concentration was 4.3 ng / m³. 3 The toxic equivalent concentration is 0.23 ng / TEQ m. 3 The sample contained 20% industrial waste. The concentrations of benzene, toluene, xylene, trimethylbenzene, tetramethylbenzene, phenol, methylphenol, and dimethylphenol were 0.6 ppbv, 2.1 ppbv, 4.6 ppbv, 0.3 ppbv, 0.7 ppbv, 1.2 ppbv, 1.2 ppbv, and 1.4 ppbv, respectively. The dioxin concentration was 4.1 ng / m³. 3 The toxic equivalent concentration is 0.23 ng / TEQ m. 3 .

[0074] (7) Using linear regression, with the indicator at sampling point B as the independent variable X and the dioxin concentration at sampling point A as the dependent variable Y, a multilocus correlation model between the indicator at sampling point B and the dioxin concentration at sampling point A was established. With the indicator at sampling point B as the independent variable X and the dioxin toxicity equivalent concentration at sampling point A as the dependent variable Y, a multilocus correlation model between the indicator at sampling point B and the dioxin toxicity equivalent concentration at sampling point A was established.

[0075] (8) The obtained correlation model and model validation results are shown in Table 5.

[0076] Table 5. Prediction of Indicators at Sampling Point B and Correlation Model and Validation of Dioxin at Sampling Point A.

[0077]

[0078] Finally, it should be noted that the selection of indicators, the selection of sites, and the establishment of prediction models in the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for online monitoring of dioxins in flue gas using photoionization time-of-flight mass spectrometry, characterized in that, High-concentration (high-abundance) volatile organic pollutants in flue gas were screened as dioxin indicators. Direct online monitoring of these indicators was performed using photoionization time-of-flight mass spectrometry. By simultaneously conducting online monitoring of dioxin indicators and offline detection of dioxins, a correlation model between high-abundance indicators and dioxins in flue gas was established, enabling indirect online monitoring of dioxins in flue gas.

2. The method for online monitoring of dioxins in flue gas by photoionization time-of-flight mass spectrometry according to claim 1, characterized in that, The method is specifically as follows: (1) At the sampling point of the incineration system, a photoionization time-of-flight mass spectrometer is used to sample and detect the incineration flue gas samples in real time to obtain mass spectra. One or more volatile organic pollutants with high abundance are selected from the mass spectra as dioxin indicators. The dioxin indicators are qualitatively confirmed according to the accurate mass number, a standard curve of dioxin indicators is established, and the dioxin indicators are quantitatively analyzed. (2) Offline sampling of dioxins in flue gas was carried out at the sampling point of the incineration system. The collected dioxin samples were analyzed and detected in the laboratory using isotope dilution high-resolution gas chromatography-high-resolution mass spectrometry to obtain the concentration and toxic equivalent concentration of dioxins in flue gas. (3) Adjust the incineration conditions of the sampling point in step (1), and obtain the concentration of dioxin indicator under different incineration conditions according to the operation process of step (1). At the same sampling point as in step (2), perform offline sampling and analysis of dioxin in flue gas to obtain the concentration and toxic equivalent concentration of dioxin in flue gas. (4) Using the linear regression method, with the concentration of the indicator at the sampling point as the independent variable X and the concentration of dioxin or the dioxin toxicity equivalent at the sampling point as the dependent variable Y, a multivariate correlation model of the same site and / or different site between the concentration of the dioxin indicator at the sampling point and the concentration of dioxin, and between the concentration of the dioxin indicator and the dioxin toxicity equivalent is established to realize indirect online monitoring of dioxins in flue gas.

3. The method for online monitoring of dioxins in flue gas by photoionization time-of-flight mass spectrometry according to claim 1 or 2, characterized in that, The dioxin indicator is one or more of the following: benzene compounds, phenols, chlorocresols, chlorotoluenes, chlorophenols, chlorobenzenes, polycyclic aromatic hydrocarbons, and dioxin parent compounds.

4. The method for online monitoring of dioxins in flue gas by photoionization time-of-flight mass spectrometry according to claim 3, characterized in that, The benzene compounds are one or more of benzene, toluene, xylene, trimethylbenzene, and tetramethylbenzene; the phenols are one or more of phenol, methylphenol, dimethylphenol, and nitrophenol; the chlorotoluenes are one or more of monochlorotoluene, dichlorotoluene, trichlorotoluene, tetrachlorotoluene, and pentachlorotoluene; the chlorocresols are one or more of monochlorocresol, dichlorocresol, trichlorocresol, and tetrachlorocresol; and the chlorobenzenes are one or more of monochlorobenzene, dichlorobenzene, trichlorobenzene, tetrachlorobenzene, pentachlorobenzene, and hexachlorobenzene. ; Chlorophenols are one or more of monochlorophenol, dichlorophenol, trichlorophenol, tetrachlorophenol, pentachlorophenol, and hexachlorophenol; Polycyclic aromatic hydrocarbons are one or more of naphthalene, acenaphthene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benzo(a)anthene, chrysene, benzo(b) fluoranthene, benzo(k) fluoranthene, benzo(a)pyrene, indole(1,2,3-cd)pyrene, dibenzo(a,n)anthene, and benzo(ghi)pyrene; Dioxin parent compounds are one or more of dibenzo-p-dioxin and dibenzofuran.

5. The method for online monitoring of dioxins in flue gas by photoionization time-of-flight mass spectrometry according to claim 1, characterized in that, The photoionization time-of-flight mass spectrometer uses a vacuum ultraviolet lamp ionization source, and the experimental conditions are as follows: vacuum ultraviolet lamp voltage 1000–2000 V, ionization region gas pressure 4.0 × 10⁻⁶. 2 ~6.00×10 2 Pa, ion source temperature 100–200℃, MCP voltage 3700–4800V, detection zone gas pressure 7.00 × 10⁻⁶. -6 ~3.00×10 -4 Pa, detection time is 0.5-10 min.

6. The method for online monitoring of dioxins in flue gas by photoionization time-of-flight mass spectrometry according to claim 1, characterized in that, The incineration conditions include one or more of the following: boiler temperature, primary air temperature, secondary air volume, oxygen content, urea spraying, ammonia water use, activated carbon use, industrial waste ratio, and landfill leachate spraying.

7. The method for online monitoring of dioxins in flue gas by photoionization time-of-flight mass spectrometry according to claim 2 or 6, characterized in that, The boiler temperature is 900–1100℃, the primary air temperature is 150–200℃, and the secondary air volume is 80,000–100,000 m³ / h. 3 One or more of the following: / h, oxygen content of 5% to 15%, urea spraying rate of 50-100 kg / h, ammonia water usage of 0-100 kg / h, activated carbon usage of 100-500 kg / d, industrial waste ratio of 0% to 40%, and leachate spraying rate of 0.1-10 tons.

8. The method for online monitoring of dioxins in flue gas by photoionization time-of-flight mass spectrometry according to claim 2, characterized in that, Under different incineration conditions, the concentrations of dioxin indicators and dioxins in flue gas varied by 10-100 times.

9. The method for online monitoring of dioxins in flue gas by photoionization time-of-flight mass spectrometry according to claim 1, characterized in that, Online monitoring of dioxin indicators in flue gas was conducted using photoionization time-of-flight mass spectrometry. By establishing a correlation model between dioxin indicators and dioxins, the dynamic emission characteristics of dioxin concentration and toxic equivalent concentration in flue gas were calculated.

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