A method for source-sink analysis of atmospheric chemical reactant species based on observation-based box model

Abstract

The application discloses an observation-based box model (OBM) source-sink analysis method for atmospheric chemical reaction species, comprising the following steps: S1, initial data input and parameter setting; S2, determining a chemical reaction mechanism simulated based on the observation-based box model, determining an initial simulated chemical reaction mechanism, adding a unique reaction marker in the initial chemical reaction mechanism, and replacing the dilution process of each simulated chemical species with a first-order chemical reaction; S3, running the observation-based box model according to the initial data and parameters in S1 and the reaction mechanism in S2 and outputting a result; and S4, performing source-sink analysis according to the result output in S3 and calculating the generation amount and consumption amount of the species after a preset reaction time. Through improvement of the OBM model mechanism and the atmospheric species source-sink calculation method, the application realizes accurate quantitative analysis of the atmospheric species source-sink by using the OBM, and promotes scientific progress of atmospheric pollution cause research.

Description

Technical Field

[0001] This application relates to the field of atmospheric environmental chemistry monitoring and analysis, specifically to an observation-based box model for source and sink analysis of atmospheric chemical reaction species. Background Technology

[0002] Secondary pollutants, represented by O3, have become a key issue and a major challenge restricting the continuous improvement of air quality in my country. Accurately determining the nonlinear relationship between secondary pollutants and their precursors is a prerequisite for effectively controlling secondary pollution. OBM (Observation-Based Box Model) incorporates atmospheric chemical mechanisms and combines mathematical methods, computer languages, and observational data to simulate and analyze atmospheric chemical reaction rates based on actual atmospheric environments. It is one of the important tools for diagnosing the formation mechanisms of secondary pollution. OBM mainly includes an initialization module (setting the initial concentration of reactants, environmental parameters, and the time step and number of steps in the model simulation), an atmospheric chemistry module (setting the atmospheric chemical mechanisms), an output module (setting the concentrations of output reactants and products and the reaction rates of specific processes), a real-time observation data constraint module (reading in observational data of chemical species to constrain the model's integral calculations in real time), and an atmospheric physics module (used to parameterize key physical processes, such as changes in solar radiation and diurnal variations in temperature, relative humidity, and boundary layer height). OBM comprehensively considers important atmospheric physical and chemical processes and can establish the photosteady-state relationship of any reactive component at any time. Therefore, it can be used for chemical reaction mechanism research, simulation of highly reactive species concentrations and chemical process analysis, and species source-sink analysis.

[0003] Theoretically, the change in concentration of a chemical species over a given time period should equal the difference between its generation and consumption. However, existing techniques for calculating the generation and consumption of chemical species within a time step have certain flaws, leading to inconsistencies between the observed concentration changes and source-sink analysis results. This is because existing techniques do not consider the concentration changes of reactants within a time step, resulting in biased calculations and further impacting the accurate understanding of atmospheric chemical processes. In complex OBM simulations involving tens of thousands of chemical reactions, solving for the reaction amounts of each reaction within each time step through integration is not feasible. Therefore, new techniques are needed to improve source-sink analysis methods.

[0004] Application content

[0005] The purpose of this application is to provide an observation-based box model for the source and sink analysis of atmospheric chemical reactions, and the specific technical solution is as follows:

[0006] A method for source-sink analysis of atmospheric chemical reactions using an observation-based box model includes: S1, initial data input and parameter setting; S2, determining the chemical reaction mechanism simulated by the observation-based box model; S3, running the observation-based box model according to the initial data and parameters in S1 and the reaction mechanism in S2, and outputting the results; S4, performing source-sink analysis based on the results output in S3, and calculating the generation and consumption of species after a preset reaction time.

[0007] The initial data input and parameter settings in S1 include: S1.1, inputting the initial concentration of atmospheric species, temperature, relative humidity, and atmospheric pressure in the reaction system; S1.2, setting the time step and number of steps for the observation-based box model simulation; S1.3, setting the uniform dilution rate constant for each species during the observation-based box model simulation.

[0008] S2, when determining the chemical reaction mechanism simulated by the observation-based box model, includes: S2.1, determining the initial simulated chemical reaction mechanism and adding a unique reaction marker to the initial chemical reaction mechanism; S2.2, representing the dilution process of each participating chemical species using a first-order chemical reaction, where the reactant is a single species and the product is the dilution marker of that species' dilution process; S2.3, setting the reaction rate constant of the first-order chemical reaction in S2.2 to be equal to the dilution rate constant in S1.3, and adjusting the dilution rate constant in S1.3 to 0. That is, when the dilution rate constant in S1.3 is set to M according to the simulation conditions, the reaction rate constant in S2.2 is also set to M; when the reaction rate constant in S2.2 is set to M, the dilution rate constant in S1 is adjusted to 0. During the chemical reaction, within one reaction step time, the concentration increase of the reaction marker corresponding to each reaction is consistent with the change in reactant and product concentrations. The dilution process of the chemical species proceeds normally during the simulation, while the reaction markers of each reaction are not affected by the dilution process.

[0009] The source-sink analysis in S4 includes: S4.1, screening out all chemical reactions related to the target species, including chemical reactions that generate the target species, chemical reactions that consume the target species, and dilution reactions of the target species; S4.2, obtaining the concentration time series of the corresponding reaction markers and dilution markers based on the chemical reactions screened in S4.1; S4.3, calculating the changes of all reaction markers and dilution markers involving the target species at each time step based on the concentration time series obtained in S4.2.

[0010] The beneficial effect of this application is that existing OBM analysis methods calculate the amount of reaction occurring within a time step using the formula "reactant concentration × reaction rate constant × time step." This method ignores the changes in reactant concentration over the time step, leading to either an overestimation or underestimation of the amount of reaction occurring, resulting in errors in the source-sink analysis of atmospheric species and a mismatch with changes in atmospheric species concentration. This application, by improving the OBM model mechanism and the atmospheric species source-sink calculation method, achieves accurate quantitative analysis of atmospheric species sources and sinks in OBM, promoting scientific progress in the study of the causes of air pollution.

[0011] Instruction manual illustrations

[0012] Figure 1 This is a flowchart illustrating the application process.

[0013] Figure 2 This is a diagram showing the source-sink analysis results of MVK in the embodiments of this application. Specific Implementation

[0014] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to specific embodiments and accompanying drawings. It should be understood that these descriptions are merely exemplary and not intended to limit the scope of this application. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0015] like Figure 1 As shown, an observation-based box model method for source-sink analysis of atmospheric chemical reaction species includes:

[0016] S1. Initial data input and parameter settings; specifically including:

[0017] S1.1 Input the initial concentration of atmospheric species, temperature, relative humidity, and atmospheric pressure in the reaction system.

[0018] S1.2 Set the time step (ts) and number of steps for the observation-based box model simulation to control the simulation duration.

[0019] S1.3 Set a uniform dilution rate constant for each species during the observation-based box model simulation.

[0020] S2. Determine the chemical reaction mechanisms simulated using an observation-based box model; specifically including:

[0021] S2.1. Determine the initial chemical reaction mechanism for simulation. Add a unique reaction marker, "mark", to the initial chemical reaction mechanism, designated as "mark1", "mark2", up to "markN". During the chemical reaction, within one reaction step, the concentration increase of the reaction marker corresponding to each reaction is consistent with the change in reactant and product concentrations. The dilution process of chemical species proceeds normally during the simulation, while the reaction markers of each reaction are not affected by the dilution process. Its expression is:

[0022]

[0023] Where A, B, C, D, and R represent the chemical species involved in the reaction mechanism, and k1 (molecule -1 cm 3 s -1 k2(s) -1 ) represents the corresponding reaction rate constant.

[0024] S2.2. Represent the dilution process of each participating chemical species using a first-order chemical reaction, where the reactant is a single species and the product is a dilution marker for that species' dilution process. The expression is:

[0025]

[0026] Where, k dil (s -1 ) represents the rate constant of a first-order chemical reaction.

[0027] S2.3 Set the reaction rate constant of the first-order chemical reaction in S2.2 to be equal to the dilution rate constant in S1.3, and adjust the dilution rate constant in S1.3 to 0. That is, when the dilution rate constant in S1.3 is set to M according to the simulation conditions, the reaction rate constant in S2.2 is set to M, and when the reaction rate constant in S2.2 is set to M, the dilution rate constant in S1 is adjusted to 0.

[0028] S3. Run the observation-based box model based on the initial data and parameters in S1 and the reaction mechanism in S2, and output the results; S4. Perform source-sink analysis based on the results output in S3, and calculate the generation and consumption of species after the preset reaction time.

[0029] S4. Based on the results output in S3, perform source-sink analysis to calculate the generation and consumption of R from time t1, after one reaction time step ts, to time t2. Specifically, this includes:

[0030] S4.1. Screen out all chemical reactions related to the target species, including chemical reactions that generate the target species R, chemical reactions that consume the target species, and dilution reactions of the target species.

[0031] S4.2. Based on the chemical reactions screened in S4.1, obtain the concentration time series of the corresponding reaction markers and dilution markers (mark1, mark2, R_dil).

[0032] S4.3 Calculate the changes in all reaction markers and dilution markers involving the target species at each time step based on the concentration time series obtained in S4.2. That is, subtract the concentration value of the previous time step from the concentration value of the next time step; the increase in marker concentration is the amount of the corresponding reaction that occurred at that time step.

[0033] R is affected by the reaction and dilution processes, and the change in concentration is ΔR. t1-t2 ΔR t1-t2 Through formula:

[0034] ΔR t1-t2 =[R] t2 -[R] t1

[0035] Calculated and obtained. Where, [R] t1 [R] t2 These represent the concentrations of R at times t1 and t2, respectively.

[0036] R has one source and two sinks. In this technical solution, the calculation method for the amount of R generated and consumed between t1 and t2 is shown in the following formula:

[0037] R 生成 =[mark1] t2 -[mark1] t1

[0038] R 消耗 =([mark2]) t2 -[mark2] t1 )+([R_dil] t2 -[R dil ] t1 ),

[0039] Among them, mark1 t1 mark2 t1 、R_dil t1 mark1 t2 mark2 t2 、R_dil t2These represent the concentrations of each marker at times t1 and t2, respectively. This technical solution achieves accurate quantification of the reaction amounts in each reaction pathway, obtaining accurate results from source-sink analysis of R. The change in R is consistent with the results of source-sink analysis, as shown in the following formula:

[0040] ΔR t1-t2 =[R] t2 -[R] t1 =R 生成 -R 消耗 .

[0041] To make this application easier to understand, the following description is provided in conjunction with embodiments:

[0042] This embodiment uses observational data from a certain city to simulate the generation and consumption process of methyl vinyl ketone (MVK), an important precursor of O3 and secondary organic aerosols, and analyzes the source and sink pathways of MVK.

[0043] Step 1: Input the observed atmospheric pollutant species, including NO, NO2, HONO, CO, and the concentration data of 72 VOC species included in the MasterChemical Mechanism v3.3.1 (MCM) mechanism. Input the observed meteorological parameter data, including temperature, relative humidity, and atmospheric pressure. Set the model time step to 1 hour and run for 24 hours. Run continuously for 4 days, with the first 3 days for model warm-up, and use the results from the 4th day for analysis. Set the uniform dilution rate constant for all species during the model simulation to 6.4 × 10⁻⁶. -5 s -1 .

[0044] Step 2: Determine and improve the reaction mechanism. Based on the 72 VOC data input to the model, the corresponding MCM mechanism was selected, including 3834 chemical species and 15341 chemical reactions. The products of each of the 15341 chemical reactions were added as markers, designated "mark1", "mark2", ..., "mark15341". A first-order reaction involving the 3834 chemical species was added, with the reactants being the respective chemical species and the products being diluted markers of those species, with a rate constant of 6.4 × 10⁻⁶. -5 s -1 Adjust the model dilution rate constant in step 1 to 0.

[0045] Step 3: Run OBM: Simulate atmospheric chemical reaction processes.

[0046] Step 4: Output OBM results, including time series data for all atmospheric species, reaction markers, and dilution markers.

[0047] Step 5: Analyze MVK sources and sinks. Reaction(s) related to MVK generation and consumption are identified, as shown in Table 1.

[0048]

[0049]

[0050] Table 1

[0051] MVK has 8 sources and 7 sinks. Among them, mark3751, mark3925, ..., mark3985 are markers for the corresponding chemical reactions, and MVK_dil is a marker for the MVK dilution process.

[0052] The calculation starts from time t1, proceeds for one reaction time step (1 hour), and ends at time t2. The change in MVK concentration is shown in the following formula:

[0053] ΔMVK t1-t2 =MVK t2 -MVK t1 .

[0054] The generation and consumption of MVK are shown in the following formula:

[0055] MVK 生成 =(mark3751) t2 -mark3751 t1 )+…+(mark11136 t2 -mark11136 t1 ),

[0056] MVK 消耗 =(mark3760) t2 -mark3760 t1 )+…+(MVK_dil t2 -MVK_dil t1 ),

[0057] The change in MVK concentration is consistent with its source-sink analysis results, as shown in the following formula:

[0058] ΔMVK t1-t2 =MVK t2 -MVK t1 =MVK 生成 -MVK 消耗 ,

[0059] Table 2 shows the simulation results of MVK and the concentration time series of related source reaction markers in the examples:

[0060]

[0061]

[0062] Tables 2 and 3 show the simulation results of the MVK-related sink reaction markers over time:

[0063]

[0064] Table 3

[0065] Table 4 shows the MVK source-sink analysis results of the embodiments:

[0066]

[0067]

[0068] Table 4

[0069] Tables 2 and 3 above show the concentration time series of MVK and related markers. Table 4 shows the source and sink results of MVK calculated based on Tables 2 and 3. ΔMVK, MVK generation, and MVK consumption were calculated using the above formulas. The equation ΔMVK = MVK generation - MVK consumption holds true, indicating that the improved scheme of this invention successfully obtained accurate analysis results of species sources and sinks in OBM. Figure 2 The diagram shows the source-sink analysis results of MVK.

Claims

1. A method for source-sink analysis of atmospheric chemical reactions using an observation-based box model, characterized in that, include: S1. Initial data input and parameter settings, specifically including: S1.1, Input the initial concentration of atmospheric species, temperature, relative humidity, and atmospheric pressure in the reaction system; S1.2, Set the time step and number of steps for the observation-based box model simulation; S1.3 Set a uniform dilution rate constant for each species during the observation-based box model simulation; S2. Determine the chemical reaction mechanisms simulated by the observation-based box model, specifically including: S2.1 Determine the initial chemical reaction mechanism for simulation. Add a unique reaction marker, "mark", to the initial chemical reaction mechanism, designated as "mark1", "mark2", up to "markN". During the chemical reaction, within one reaction step, the concentration increase of the reaction marker corresponding to each reaction is consistent with the change in reactant and product concentrations. The dilution process of chemical species proceeds normally during the simulation, while the reaction markers for each reaction are not affected by the dilution process. The expression is: ； ； Where A, B, C, D, and R represent the chemical species involved in the reaction mechanism, and k1 (molecule) -1 cm 3 s -1 k2(s) -1 ) represents the corresponding reaction rate constant; S2.

2. Represent the dilution process of each participating chemical species using a first-order chemical reaction, where the reactant is a single species and the product is a dilution marker for that species' dilution process. The expression is: ； ； ； ； ； Where, k dil (s -1 ) represents the rate constant of a first-order chemical reaction; S2.3 Set the reaction rate constant of the first-order chemical reaction in S2.2 to be equal to the dilution rate constant in S1.3, and adjust the dilution rate constant in S1.3 to 0. That is, when the dilution rate constant in S1.3 is set to M according to the simulation conditions, the reaction rate constant in S2.2 is set to M, and when the reaction rate constant in S2.2 is set to M, the dilution rate constant in S1 is adjusted to 0. S3. Run the observation-based box model according to the initial data and parameters in S1 and the reaction mechanism in S2, and output the results; S4. Perform source-sink analysis based on the results output in S3, and calculate the amount of species generated and consumed after a preset reaction time.

2. The observation-based box model method for source-sink analysis of atmospheric chemical reactions as described in claim 1, characterized in that, The source-sink analysis performed in S4 includes: S4.1 Screen out all chemical reactions related to the target species, including chemical reactions that generate the target species, chemical reactions that consume the target species, and dilution reactions of the target species; S4.2 Obtain the concentration time series of the corresponding reaction markers and dilution markers based on the chemical reactions screened in S4.1; S4.3 Calculate the concentration changes of all reaction markers and dilution markers involving the target species at each time step based on the concentration time series obtained in S4.2.

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