Industrial source atmospheric pollutant monthly scale emission quantitative characterization method

Abstract

The invention belongs to the technical field of emission quantitative characterization methods, particularly relates to an industrial source atmospheric pollutant monthly scale emission quantitative characterization method, belongs to the technical field of emission quantitative characterization methods, and discloses an industrial source atmospheric pollutant monthly scale emission quantitative characterization method. The method aims at solving the problems that an existing industrial source emission quantification method is low in time resolution, provincial monthly data adaptability is poor, dynamic changes of emission coefficients are not effectively coupled and the like, and the requirement for monthly-scale emission data of atmospheric pollution refined control is met.

Description

A method for quantitative characterization of monthly emissions of air pollutants from industrial sources Technical Field

[0001] This invention belongs to the technical field of emission quantification and characterization methods, and particularly relates to a monthly-scale emission quantification and characterization method for industrial source air pollutants. Background Technology

[0002] The accurate application of the emission factor method relies on timely and accurate monthly activity levels and emission factor data by province. However, in practice, most industrial sources cannot meet this data requirement: for a few process sources such as pig iron, crude steel, and cement, although monthly product output by province can be obtained through statistics, for process sources such as sintered ore, lime, and bricks and tiles, as well as emission sources such as industrial boilers and furniture coating, the statistics do not directly publish monthly activity level data by province; some emission sources can only obtain national monthly activity level data, which cannot directly reflect the emission differences between provinces; and a large number of emission sources lack directly related monthly statistical data and need to rely on indirect parameters to characterize activity levels, making it difficult for traditional methods to accurately calculate monthly emissions by province.

[0003] The dynamic changes in emission coefficients are not effectively coupled. Industrial source emission coefficients are not fixed values; they are jointly determined by pollutant generation coefficients, collection facility efficiency, treatment facility efficiency, and facility operation rate. Furthermore, they are significantly affected by major emission reduction projects such as industrial restructuring, clean energy substitution, industrial VOCs treatment, and advanced NOx treatment. Traditional annual inventory compilation typically uses fixed emission coefficients or annual average emission coefficients, failing to fully consider the dynamic impact of the monthly implementation pace of emission reduction projects on the emission coefficients. This leads to discrepancies between the quantified emission figures and actual emissions, and makes it particularly difficult to accurately reflect the short-term effects of emission reduction measures.

[0004] The coarse time scale is inadequate for management needs. Existing baseline annual emission inventories, using an annual time unit, can only reflect the total annual emissions and average emission levels from industrial sources, failing to capture monthly emission fluctuations. For example, some industrial sectors experience significant seasonal production fluctuations, with substantial differences in emission intensity from industrial heating boilers during the winter heating season compared to the non-heating season; annual inventories struggle to distinguish these spatiotemporal differences. Furthermore, current air pollution control efforts, including monthly pollution source tracing, emergency response to heavy pollution weather, and the decomposition of monthly emission reduction targets, all require high-temporal-resolution emission data. Traditional methods are no longer sufficient to meet the demands of refined management.

[0005] In summary, existing methods for quantifying industrial air pollutant emissions are inadequate in terms of data adaptability, dynamic factor coupling, and temporal resolution, making it difficult to achieve accurate monthly characterization of industrial air pollutants by province. There is an urgent need to develop a quantitative characterization method that can integrate multi-source macroeconomic statistical data, couple activity levels and dynamic change factors of emission coefficients, and adapt to monthly scale requirements, so as to provide technical support for precise prevention and control of regional air pollution. Summary of the Invention

[0006] The purpose of this invention is to address the aforementioned technical problems by providing a method for quantitative characterization of monthly emissions of industrial air pollutants.

[0007] In view of this, the present invention provides a method for quantitative characterization of monthly emissions of industrial air pollutants, comprising the following steps: Step 1: compiling an inventory of industrial air pollutant emissions for a baseline year; Step 2: constructing a near-real-time emission calculation model; Step 3: calculating the activity level variation factor. Step 4: Calculate the emission factor variation factor .

[0008] Preferably, the baseline year emission inventory mentioned in step one is compiled with reference to the "Technical Guidelines for Compiling Integrated Emission Inventories of Air Pollutants and Greenhouse Gases" and the series of technical guidelines for compiling air pollutant emission inventories issued by the Ministry of Ecology and Environment; in step two, when constructing the near-real-time emission calculation model, the baseline year emission inventory from step one is used as a basis, combined with the activity level change factor. and emission coefficient change factor The near-real-time emissions of industrial air pollutants by province on a monthly basis are calculated using the following formula: In the formula, The emission amount of pollutant of type i from emission source j in province k in month m of year n; The emission amount of pollutant of type i from emission source j in province k in month m of year n-1 (base year); The activity level change factor for emission sources of type j in province k in month m of year n; This is the emission coefficient variation factor for pollutant type i from emission source j in province k in month m of year n; i is the pollutant type, j is the emission source type, k is the province, m is the month, and n is the year.

[0009] Preferably, the step three described For type j emission sources in province k, the year-on-year change in activity level or activity level characterization parameter in month m of year n compared to the same period in month m of year n-1: In the formula, For the activity level or activity level characterization parameter of type j emission source in province k in month m of year n; This refers to the activity level or activity level characterization parameter of type j emission source in province k in month m of year n-1; in step four, the emission coefficient of pollutant i from type j emission source is calculated using the following formula 1. Then calculate using Formula 2. The Let J be the year-on-year change in the emission coefficient of pollutant of type i from emission source j in province k in month m of year n, compared to the same period in month m of year n-1: Formula 1; where, Let be the emission coefficient of pollutant type i from emission source type j; Let be the generation coefficient of pollutant type i from emission source type j; The collection efficiency of a collection facility for type i pollutants from type j emission sources; The removal efficiency of the treatment facility for Class i pollutants from emission source type j, and the overall operational rate of the collection and treatment facilities for Class i pollutants from emission source type j. =100%; Formula 2; where, For the emission coefficient of pollutant of type i from emission source j in province k in month m of year n, Let be the emission coefficient of pollutant type i from emission source j in province k in month m of year n-1.

[0010] Preferably, in step three, based on the availability of provincial monthly activity level data for type j emission sources, type j emission sources are divided into three categories, each represented by different data. Category 1 emission sources: Provincial monthly activity level data can be obtained directly, regularly, and stably. This provincial monthly activity level data will be used as... Category II emission sources: For which provincial monthly activity level data cannot be directly and consistently obtained on a regular basis, but national monthly activity level data is available, if the activity level trend of this category of emission sources in each province is consistent with the national trend, the national monthly activity level data will be used as the basis for determination. Characterization parameters; Category III emission sources: Since it is impossible to directly and regularly obtain stable monthly activity level data for each province, and there is no corresponding national monthly activity level data, monthly electricity consumption data for each province can be used as... The characterization parameters.

[0011] Preferably, among the first type of emission sources, The corresponding provincial monthly activity level data are the statistically released provincial monthly product output data; among the second category of emission sources, The corresponding national monthly activity level data is the statistically released national monthly product output data; among the third category of emission sources, The corresponding monthly electricity consumption data by province is the monthly electricity consumption data by industry.

[0012] Preferably, in step four The influencing factors are determined based on the category of emission source type j: if emission source type j is a stationary combustion source, The emission source is determined by fuel type, combustion technology, and equipment scale; if type j emission source is a process source, The emission source is determined by the product type, production process, equipment scale, and raw material / fuel type; if type j is a solvent-using source, It is determined by the type of solvent, the VOC content in the solvent, and the method of solvent use; and The type of collection facility for pollutants of type i from type j emission sources is determined by the type of emission source. The type of pollution control facility for type i pollutants from type j emission sources is determined by the type of facility used.

[0013] Preferably, in step four The reduction is jointly determined by key emission reduction projects such as industrial structure upgrading, clean energy substitution, VOCs-containing raw and auxiliary material substitution, industrial VOCs treatment, and industrial NOx deep treatment, and is calculated using formulas 3 and 4: Formula 3; where, The annual emission coefficient variation factor for pollutant type i from emission source type j in province k in year n; Let p be the emission coefficient variation factor for pollutant type i from emission source j in province k in year n, corresponding to emission reduction project type p; p is the type of emission reduction project. (Formula 4) In the formula, The emission reduction ratio of pollutant type i from emission source j in province k in year n-1 is the emission reduction ratio of type p corresponding to the emission reduction project. Let p be the percentage of emission reduction projects of type p corresponding to emission source j in province k in year n-1, and The capacity of the p-type emission reduction project carried out in type j emission sources in province k in year n-1; This represents the total production capacity of type j emission sources in province k in year n-1.

[0014] The beneficial effects of this invention are as follows: This method breaks through the time scale limitations of traditional annual emission inventories and, for the first time, achieves a quantitative characterization of monthly emissions of industrial air pollutants by province. By introducing a dynamic calculation model of emissions from the same period of the previous year × activity level change factor × emission coefficient change factor, it can accurately capture the monthly emission fluctuation characteristics of industrial sources—for example, it can distinguish the emission differences between peak and off-peak seasons in the building materials industry, as well as the emission intensity changes of industrial heating boilers during the winter heating season. This provides high temporal resolution data support for monthly pollution source tracing, emergency response to heavy pollution weather, and decomposition of short-term emission reduction targets, filling the gap in existing technologies for monthly emission quantification.

[0015] Addressing the challenge of varying data availability for activity levels across different industrial sources, this method innovatively categorizes emission sources into three classes and matches them with differentiated data characterization schemes: For emission sources such as pig iron and crude steel, where monthly provincial production data is readily available, the activity level change factor is calculated using statistically published monthly provincial product production data; for emission sources such as ferroalloys and primary aluminum, where only national data is available, provincial characterization is achieved using national monthly data based on the reasonable assumption that the change trends in each province are consistent with the national trend; for other emission sources lacking direct statistical data, monthly electricity consumption data by industry is innovatively introduced as an indirect characterization parameter. This scheme enables the calculation of the activity level change factor to cover more than 50 secondary emission sources across three major categories: stationary combustion sources, process sources, and solvent usage sources. It solves the problem of traditional methods failing to quantify some emission sources due to data gaps, thus improving the comprehensiveness of industrial emission characterization.

[0016] This method, for the first time, incorporates major emission reduction projects such as industrial structure upgrading, clean energy substitution, and industrial VOCs treatment into the calculation system of emission coefficient change factors. It constructs a dynamic coupling model of emission reduction ratio × project progress ratio through formula, which is significantly better than the traditional fixed emission coefficient method, and provides accurate data basis for evaluating the effectiveness of emission reduction measures.

[0017] This method uses provinces as the spatial dimension, and all calculation processes retain the independence of provincial administrative units. Attached Figure Description

[0018] Figure 1 is a roadmap of the technical roadmap for quantitative characterization of monthly emissions from industrial sources by province according to the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0020] It should be noted that all directional and positional terms used in this invention, such as "up," "down," "left," "right," "front," "back," "vertical," "horizontal," "inner," "outer," "top," "lower," "lateral," "longitudinal," and "center," are only used to explain the relative positional relationships and connections between components in a specific state (as shown in the accompanying drawings). They are merely for the convenience of describing the invention and do not require the invention to be constructed and operated in a specific orientation; therefore, they should not be construed as limitations on the invention. Furthermore, descriptions involving "first," "second," etc., are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated.

[0021] In the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0022] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0023] The baseline year emission inventory can be compiled with reference to the "Technical Guidelines for Compiling Integrated Emission Inventories of Air Pollutants and Greenhouse Gases" and the series of technical guidelines for compiling air pollutant emission inventories issued by the Ministry of Ecology and Environment. This study constructs a quantitative characterization method for monthly-scale emissions from industrial sources based on the baseline year emission inventory and multi-source macroeconomic statistical data.

[0024] Industrial pollutant emissions can be calculated using the emission factor method, as shown in the following formula: (Equation 2-1); where E is the pollutant emission amount, EF is the emission coefficient, A is the activity level, subscript i is the pollutant type, j is the emission source type, and k is the province (autonomous region, municipality).

[0025] For most industrial sources, timely acquisition of monthly activity levels and emission coefficients by province is extremely difficult. This study characterizes near-real-time emissions based on the changes in monthly emissions by province for each type of emission source in the baseline year inventory in the previous year and the changes in activity levels and emission coefficients in the same period of the current year, as detailed in Equation (2-2). The study focuses on characterizing the activity level change factor α and emission coefficient change factor β for each type of emission source, coupling them to form a near-real-time emission characterization model, thus achieving monthly provincial characterization of industrial source air pollutant emissions.

[0026] (Equation 2-2); where E is the pollutant emission amount, α is the activity level variation factor, β is the emission coefficient variation factor, subscript i is the pollutant type, j is the emission source type, k is the province (autonomous region, municipality), m is the month, and n is the year.

[0027] When studying the factors affecting the change in industrial source activity levels, we first categorize the data types of various industrial source activity levels, and then classify the emission sources according to the availability of provincial monthly activity level data for each type of source. For emission sources for which monthly activity data can be obtained directly, regularly, and stably, the year-on-year change in provincial monthly activity levels can be used to characterize the factor affecting the activity level. For emission sources for which monthly activity data cannot be obtained directly, regularly, and stably, key parameters that can characterize changes in activity levels are selected, and the year-on-year change in these key parameters is used to characterize the factor affecting the activity level. The calculation method for the factor affecting the activity level is shown in (Equation 2-3).

[0028] (Equation 2-3); where α is the activity level variation factor, A is the activity level or activity level characterization parameter, subscript j is the emission source type, k is the province (autonomous region, municipality), m is the month, and n is the year.

[0029] For process sources such as pig iron, crude steel, cement, flat glass, and coking, the activity level is the output of the main products. Statistics are regularly released on a monthly basis by province, so the activity level change factor can be directly calculated using the monthly product output by province.

[0030] For sources of activity from sintered ore, lime, brick and tile processes, and solvent-using sources such as automotive spraying, although the statistics do not directly publish monthly activity level data by province, the activity level data of these sources is closely related to the monthly statistical data of provinces published by the statistics. These related statistical data can be used to characterize the change factors of the activity level of these sources.

[0031] For stationary combustion sources, coal-fired units, natural gas units, and units using other fossil fuels all fall under the category of thermal power. Polyethylene, polyvinyl chloride, polystyrene, and polypropylene are all important primary plastic products, with styrene being the main raw material for polystyrene production. For the above emission sources, the statistics do not publish monthly provincial production data for each product, but they do publish monthly provincial thermal power generation and primary plastic production data. Changes in the activity levels of the above emission sources can be characterized by referring to the year-on-year changes in the monthly statistical data for each province published by the statistics bureau. Detailed information is available regarding the data types for the activity levels of these emission sources, as well as the types of statistical data that can be used to characterize activity levels.

[0032] For emission sources from processes such as ferroalloys, primary aluminum, synthetic rubber, and alcohol production, monthly activity level data for each province is not publicly available, but national monthly product output statistics are provided. In this case, we assume that the activity level trends of these emission sources in each province are consistent with the overall national trend. Therefore, the national monthly product output statistics can be used to approximate the activity level variation factors for each province. For details regarding the scope of the aforementioned emission sources and the corresponding statistical data types, please refer to Table 1.

[0033] Table 1 uses national monthly statistical data to characterize the emission sources of activity level change factors;

[0034] Electricity consumption is a crucial indicator in enterprise production activities and industrial manufacturing processes, often used to assess changes in output. This logic is based on the fact that the continuity of production processes depends on the normal operation of various machines and equipment, which in turn rely heavily on the supply of electricity. As product output increases, total electricity consumption typically rises accordingly. Therefore, industrial electricity consumption data can be considered an effective indirect indicator reflecting the production dynamics of an enterprise or the entire industry.

[0035] Table 2 uses monthly electricity consumption data to characterize the emission sources of the activity level variation factor;

[0036] The emission coefficient of air pollutants from industrial sources reflects the amount of air pollutants emitted per unit activity level. It is mainly determined by the generation coefficient, the collection efficiency of pollutant collection facilities, the removal efficiency of pollution control facilities, and the operational rate of pollutant collection and control facilities. The calculation formula for the emission coefficient is shown in (Equation 2-5). In equation (2-5), Let j be the emission source and i be the emission coefficient of pollutant. Let j be the emission source and i be the generation coefficient of pollutant. Let j be the emission source, and i be the collection efficiency of the pollutant collection facility. Let j be the emission source, and i be the removal efficiency of the pollutant treatment facility. Let i be the combined operational rate of pollutant collection and treatment facilities for emission source j, which is the number of hours that pollutant collection and treatment facilities for emission source j and i are simultaneously operating effectively / the total number of hours that the production unit corresponding to emission source j generates pollutant i.

[0037] It is mainly related to the combustion or production process of the emission source. If it is a stationary combustion source, it is mainly related to factors such as the fuel type, combustion technology, and equipment scale of the source; if it is a process source, it is mainly related to factors such as the product type, production process, equipment scale, and raw material / fuel type of the source; if it is a solvent use source, it is mainly related to factors such as the solvent type, VOCs content in the solvent, and solvent usage method. It is mainly related to the type of pollutant collection facility for emission source j. This is mainly related to the type of pollutant treatment facilities at emission source i. According to the regulations of the Ministry of Ecology and Environment, my country's waste gas collection systems and pollution treatment facilities should operate synchronously with production facilities. Therefore, in this study... Take the value as 100%.

[0038] The calculation method for the industrial source emission coefficient variation factor is shown in (Equation 2-6).

[0039] (Equation 2-6) In the equation, EF is the emission coefficient, the subscript i is the type of pollutant, j is the emission source type, k is the province (autonomous region, municipality), m is the month, and n is the year.

[0040] Combining Equations 2-5 and 2-6, the industrial source emission coefficient variation factor The main factors determining the emission source's emissions are the type of raw materials, fuel, combustion or production process, and the source's pollutant collection and treatment facilities. All of these factors are related to air pollutant emission reduction measures.

[0041] Changes in industrial emission coefficients are mainly caused by the implementation of major emission reduction projects. Industrial air pollutant emission reduction measures can be mainly divided into source substitution, process control, and end-of-pipe treatment. According to my country's current air pollution prevention and control policies, emission reduction measures can be further subdivided into six major emission reduction projects: industrial structure upgrading, clean energy substitution, boiler elimination, substitution of VOCs-containing raw and auxiliary materials, industrial VOCs treatment, and in-depth treatment of industrial NOx.

[0042] The emission coefficient variation factor for key industrial sectors is determined by multiple emission reduction projects, and the calculation method can be expressed by (Equation 2-7): (Equation 2-7) In the equation, β is the emission coefficient variation factor, subscript i is the type of pollutant, j is the emission source type, k is the province (autonomous region, municipality), n is the year, and p is the emission reduction project type.

[0043] (Equation 2-8) In the equation, β is the emission coefficient variation factor, EF is the emission coefficient, P is the proportion of emission reduction projects, that is, the proportion of the capacity of emission reduction projects to the total capacity, the subscript i is the pollutant type, j is the emission source type, k is the province (autonomous region, municipality), n is the year, and p is the emission reduction project type.

[0044] Assuming that the progress of the same emission reduction projects in the same region, industry, and in adjacent years is similar, then (Equation 2-9) (Equation 2-10) (Equation 2-11) (Equation 2-12) In the formula, EF is the emission coefficient, P is the proportion of emission reduction projects, R is the emission reduction ratio, A is the activity level, subscript i is the pollutant type, j is the emission source type, k is the province (autonomous region, municipality), n is the year, and p is the emission reduction project type.

[0045] (Equation 2-13) and Estimates are based on the progress of major emission reduction projects in each province. Obtained from MEIC or the calculation results of this project.

[0046] For clean energy substitution projects, the emission reduction ratio R for SO2, particulate matter, and VOCs is taken as 100%.

[0047] For industrial restructuring and coal-fired boiler replacement projects, the emission reduction ratio R for all pollutants is set at 100%.

[0048] For industrial structure upgrading, clean energy substitution, and boiler elimination, calculate the change factors of all pollutant emission coefficients.

[0049] For industrial NOx deep treatment projects, only the NOx emission coefficient change factor is calculated.

[0050] For the substitution of raw and auxiliary materials containing VOCs and the treatment of industrial VOCs, only the VOCs emission coefficient change factor is calculated.

[0051] The emission coefficient variation factor for coal use in the cement, lime, and brick and tile industries is based on the emission coefficient variation factor for the cement, lime, and brick and tile production process.

[0052] The variation factor of the source emission coefficient of ink cleaning agent is referenced from the variation factor of the source emission coefficient of ink.

[0053] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for quantitative characterization of monthly emissions of air pollutants from industrial sources, characterized in that: The process includes the following steps: Step 1: Compiling an inventory of industrial air pollutant emissions for the baseline year; Step 2: Constructing a near-real-time emission calculation model; Step 3: Calculating the activity level variation factor. Step 4: Calculate the emission factor variation factor 。 2. The method for quantitative characterization of monthly emissions of industrial air pollutants according to claim 1, characterized in that: The baseline year emission inventory mentioned in step one is compiled with reference to the series of technical guidelines for compiling air pollutant emission inventories issued by the Ministry of Ecology and Environment; in step two, when constructing the near-real-time emission calculation model, the baseline year emission inventory from step one is used as a basis, combined with the activity level change factor. and emission coefficient change factor The near-real-time monthly emissions of industrial air pollutants by province were calculated using the following formula: In the formula, The emission amount of pollutant of type i from emission source j in province k in month m of year n; This represents the emission amount of pollutant type i from emission source j in province k in month m of year n-1; The activity level change factor for emission sources of type j in province k in month m of year n; This is the emission coefficient variation factor for pollutant type i from emission source j in province k in month m of year n; i is the pollutant type, j is the emission source type, k is the province, m is the month, and n is the year.

3. The method for quantitative characterization of monthly emissions of industrial air pollutants according to claim 1, characterized in that: The steps described in step three For type j emission sources in province k, the year-on-year change in activity level or activity level characterization parameter in month m of year n compared to the same period in month m of year n-1: In the formula, For the activity level or activity level characterization parameter of type j emission source in province k in month m of year n; This refers to the activity level or activity level characterization parameter of type j emission source in province k in month m of year n-1; in step four, the emission coefficient of pollutant i from type j emission source is calculated using the following formula 1. Then calculate using Formula 2. The Let J be the year-on-year change in the emission coefficient of pollutant of type i from emission source j in province k in month m of year n, compared to the same period in month m of year n-1: Formula 1; where, Let be the emission coefficient of pollutant type i from emission source type j; Let be the generation coefficient of pollutant type i from emission source type j; The collection efficiency of a collection facility for type i pollutants from type j emission sources; The removal efficiency of the treatment facility for Class i pollutants from emission source type j, and the overall operational rate of the collection and treatment facilities for Class i pollutants from emission source type j. =100%； Formula 2; where, For the emission coefficient of pollutant of type i from emission source j in province k in month m of year n, Let be the emission coefficient of pollutant type i from emission source j in province k in month m of year n-1.

4. The method for quantitative characterization of monthly emissions of industrial air pollutants according to claim 1, characterized in that: In step three, based on the availability of provincial monthly activity level data for type j emission sources, type j emission sources are divided into three categories, each represented by different data. Category 1 emission sources: Provincial monthly activity level data can be obtained directly, regularly, and stably. This provincial monthly activity level data will be used as... Category II emission sources: For which provincial monthly activity level data cannot be directly and consistently obtained on a regular basis, but national monthly activity level data is available, if the activity level trend of this category of emission sources in each province is consistent with the national trend, the national monthly activity level data will be used as the basis for determination. Characterization parameters; Category III emission sources: Since it is impossible to directly and regularly obtain stable monthly activity level data for each province, and there is no corresponding national monthly activity level data, monthly electricity consumption data for each province can be used as... The characterization parameters.

5. The method for quantitative characterization of monthly emissions of industrial air pollutants according to claim 4, characterized in that: Among the first category of emission sources, The corresponding provincial monthly activity level data are the statistically released provincial monthly product output data; among the second category of emission sources, The corresponding national monthly activity level data is the statistically released national monthly product output data; among the third category of emission sources, The corresponding monthly electricity consumption data by province is the monthly electricity consumption data by industry.

6. The method for quantitative characterization of monthly emissions of industrial air pollutants according to claim 3, characterized in that: In step four The influencing factors are determined based on the category of emission source type j: if emission source type j is a stationary combustion source, The emission source is determined by fuel type, combustion technology, and equipment scale; if type j emission source is a process source, The emission source is determined by the product type, production process, equipment scale, and raw material / fuel type; if type j is a solvent-using source, It is determined by the type of solvent, the VOC content in the solvent, and the method of solvent use; and The type of collection facility for pollutants of type i from type j emission sources is determined by the type of emission source. The type of pollution control facility for type i pollutants from type j emission sources is determined by the type of facility used.

7. The method for quantitative characterization of monthly emissions of industrial air pollutants according to claim 1, characterized in that: In step four The reduction is jointly determined by key emission reduction projects such as industrial structure upgrading, clean energy substitution, VOCs-containing raw and auxiliary material substitution, industrial VOCs treatment, and industrial NOx deep treatment, and is calculated using formulas 3 and 4: Formula 3; where, The annual emission coefficient variation factor for pollutant type i from emission source type j in province k in year n; Let p be the emission coefficient variation factor for pollutant type i from emission source j in province k in year n, corresponding to emission reduction project type p; p is the type of emission reduction project. In formula 4, The emission reduction ratio of pollutant type i from emission source j in province k in year n-1 is the emission reduction ratio of type p corresponding to the emission reduction project. Let p be the percentage of emission reduction projects of type p corresponding to emission source j in province k in year n-1, and The capacity of the p-type emission reduction project carried out in type j emission sources in province k in year n-1; This represents the total production capacity of type j emission sources in province k in year n-1.

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