Bulk cargo yard pollution analysis method and system based on surface source intensity division

Abstract

The present application provides a bulk cargo yard pollution analysis method and system based on surface source intensity division, relating to the technical field of environmental engineering. In view of the poor accuracy of the pollution analysis results of the bulk cargo yard in the prior art, the present application collects multi-dimensional influence factor data of pollutants in the bulk cargo yard; divides the surface source of the bulk cargo yard into multiple independent units according to the set protection facilities of the pollutants in the bulk cargo yard; for each independent unit, calculates the initial static source intensity and the initial dynamic source intensity according to the relevant parameters of the pollution source; establishes a coupling optimization mechanism, corrects the initial source intensity according to the coupling optimization mechanism, and obtains the final static source intensity and the final dynamic source intensity. According to the final source intensity of each independent unit, a plurality of prediction points corresponding to the independent unit are set; the pollution diffusion related parameters and the final source intensity are imported into an atmospheric diffusion model to simulate the pollutant concentration values of each prediction point. The analysis results of the bulk cargo yard pollution analysis method provided by the present application have high accuracy.

Description

Technical Field

[0001] This invention relates to the field of environmental engineering technology, and in particular to a method and system for analyzing pollution in bulk cargo yards based on area source intensity classification. Background Technology

[0002] Pollutants emitted from bulk cargo storage yards not only reduce regional air quality but also pose potential health hazards to nearby residents and impact the sustainable development of the ecological environment. Therefore, accurately analyzing the pollution diffusion patterns of bulk cargo storage yards and precisely calculating the intensity of pollution sources are core prerequisites for formulating scientific and effective pollution prevention and control plans and ensuring the effective implementation of environmental protection measures. This has significant practical implications for promoting air quality improvement and high-quality economic development.

[0003] Currently, pollution analysis methods for bulk cargo storage yards mainly rely on a combination of numerical simulation and atmospheric diffusion models. This approach treats the storage yard as a single, unified area source for analysis. First, numerical simulations calculate the wind environment of the entire storage yard area to determine the overall dust suppression efficiency. Then, based on parameters such as the overall area of ​​the storage yard, dynamic and static source strengths are calculated. However, existing technologies do not incorporate refined unit breakdown based on the type and layout of protective facilities, failing to accurately reflect the differences in source strength across different protected areas. Furthermore, the calculations of static and dynamic source strengths are independent, lacking a coupling mechanism between the two, resulting in poor accuracy of the analysis results.

[0004] Therefore, developing a pollution analysis method and system for bulk cargo yards based on area source intensity division is of great significance for improving the accuracy of pollution analysis results for bulk cargo yards. Summary of the Invention

[0005] To address the issue of poor accuracy in existing bulk cargo yard pollution analysis results, this invention proposes a method for bulk cargo yard pollution analysis based on area source intensity division, specifically including the following steps:

[0006] S1. Collect multidimensional influencing factors of pollutants in bulk cargo storage yards, including pollution source-related parameters and pollution diffusion-related parameters.

[0007] S2. Based on the set protective facilities for pollutants in the bulk cargo yard, the area source of the bulk cargo yard is divided into multiple independent units;

[0008] S3. For each independent unit, calculate the initial static source strength and the initial dynamic source strength based on the pollution source-related parameters.

[0009] S4. Establish a coupled optimization mechanism for static source strength and dynamic source strength, and correct the initial static source strength and initial dynamic source strength according to the coupled optimization mechanism to obtain the final static source strength and final dynamic source strength.

[0010] In S4, the coupling optimization mechanism includes: correcting the dust generation conditions of dynamic operation based on the material accumulation characteristics, local static wind field and protection status corresponding to the initial static source strength; and correcting the static source strength based on the change in surface moisture content of bulk cargo after dynamic operation.

[0011] S5. Based on the final static source strength and final dynamic source strength of each independent unit, set multiple prediction points corresponding to the independent unit;

[0012] S6. Import the pollution diffusion-related parameters, the final static source strength, and the final dynamic source strength into the atmospheric diffusion model to simulate the pollutant concentration values ​​at each predicted location.

[0013] Furthermore, the set protective facilities include canopies and windbreak nets. In step S2, according to the set protective facilities for pollutants in the bulk cargo yard, the area source of the bulk cargo yard is divided into multiple independent units, including: obtaining a plan of the bulk cargo yard, marking the covered area of ​​the canopy, the protected area of ​​the windbreak net, and the unprotected area on the plan of the bulk cargo yard; dividing the covered area of ​​the canopy, the protected area of ​​the windbreak net, and the unprotected area into independent units respectively; wherein, the boundary of each independent unit is determined by the physical edge of the set protective facilities or the inherent zoning line of the yard.

[0014] Furthermore, in step S3, calculating the initial static source strength based on the pollution source-related parameters includes: determining the wind erosion and dust generation characteristics of the bulk cargo pile based on the material particle size and surface moisture content of the bulk cargo in the pollution source-related parameters; and calculating the initial static source strength based on the wind erosion and dust generation characteristics, meteorological data in the pollution source-related parameters, and the spatial distribution and protection status of the bulk cargo pile.

[0015] Furthermore, in step S3, calculating the initial dynamic source strength based on the pollution source-related parameters includes: determining the operation intensity based on the loading and unloading efficiency in the pollution source-related parameters; determining the dynamic dust generation coefficient based on the bulk cargo type and loading and unloading method in the pollution source-related parameters; correcting the dynamic dust generation coefficient based on the surface moisture content of the bulk cargo; and calculating the initial dynamic source strength by combining the operation intensity with the corrected dynamic dust generation coefficient.

[0016] Furthermore, in step S5, based on the final static source strength and final dynamic source strength of each independent unit, multiple prediction points corresponding to the independent unit are set, including: when the final static source strength and / or the final dynamic source strength is higher than a set threshold, prediction points around the independent unit corresponding to the final static source strength and the final dynamic source strength are set according to a first deployment density; when the final static source strength and the final dynamic source strength are not higher than the set threshold, prediction points around the independent unit corresponding to the static source strength and the dynamic source strength are set according to a second deployment density.

[0017] Furthermore, the coordinates of the predicted points are based on the geometric center of the corresponding independent unit, so that the predicted points cover the pollution diffusion range of the independent unit.

[0018] Furthermore, in step S6, the pollution diffusion-related parameters, the final static source strength, and the final dynamic source strength are imported into the atmospheric diffusion model to simulate the pollutant concentration values ​​at each predicted location. This includes: converting the pollution diffusion-related parameters into a format suitable for the atmospheric diffusion model; importing the converted pollution diffusion-related parameters, along with the final static source strength and final dynamic source strength of each independent unit, into the atmospheric diffusion model; and outputting the simulated pollutant concentration values ​​at each predicted location from the atmospheric diffusion model.

[0019] Furthermore, after simulating the pollutant concentration values ​​at each predicted location, the method also includes: deploying dust monitoring instruments at each predicted location to conduct on-site sampling and acquiring the online monitoring values ​​of pollutant concentrations at each predicted location in real time; calculating the relative deviation between the simulated pollutant concentration values ​​and the online monitoring values ​​at each predicted location within a set time period; and determining that the simulated pollutant concentration values ​​are valid when the relative deviation is less than the set deviation.

[0020] The present invention also provides a bulk cargo yard pollution analysis system based on area source intensity division, the system being used to execute the bulk cargo yard pollution analysis method based on area source intensity division described in any of the preceding claims, the system comprising:

[0021] The data acquisition module is used to collect multidimensional influencing factors of pollutants in bulk cargo storage yards, including pollution source-related parameters and pollution diffusion-related parameters.

[0022] The area source classification module is used to divide the area sources of the bulk cargo yard into multiple independent units according to the set protective facilities for pollutants in the bulk cargo yard;

[0023] The source strength calculation module is used to calculate the initial static source strength and the initial dynamic source strength for each independent unit based on the pollution source-related parameters.

[0024] The source strength correction module establishes a coupled optimization mechanism between static source strength and dynamic source strength, and corrects the initial static source strength and initial dynamic source strength according to the coupled optimization mechanism to obtain the final static source strength and final dynamic source strength.

[0025] The point setting module is used to set multiple predicted points corresponding to each independent unit based on the final static source strength and the final dynamic source strength of each independent unit.

[0026] The simulation calculation module is used to import the pollution diffusion-related parameters, the final static source strength, and the final dynamic source strength into the atmospheric diffusion model to simulate the pollutant concentration values ​​at each predicted location.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0028] This invention collects multidimensional influencing factors of pollutants from bulk cargo storage yards, including pollution source-related parameters and pollution diffusion-related parameters. Based on the established protective facilities for pollutants in the bulk cargo storage yard, the area source pollution is divided into multiple independent units. For each independent unit, the initial static source strength and initial dynamic source strength are calculated based on the pollution source-related parameters. A coupled optimization mechanism for static and dynamic source strengths is established, and the initial static and dynamic source strengths are corrected according to the coupled optimization mechanism to obtain the final static and dynamic source strengths. Based on the final static and dynamic source strengths of each independent unit, multiple prediction points corresponding to the independent unit are set. The pollution diffusion-related parameters, final static source strength, and final dynamic source strength are imported into an atmospheric diffusion model to simulate the pollutant concentration values ​​at each prediction point. Dividing the area source into multiple independent units according to the established protective facilities can accurately match the actual differences in the protective capabilities of different areas. For example, the dust suppression effect of an area fully covered by protective facilities is significantly different from that of an unprotected area. Dividing into independent units avoids the errors caused by averaging in overall area source analysis, improving the accuracy of the analysis results. This classification method allows subsequent source strength calculations and pollution diffusion simulations to focus on specific units. It not only clearly identifies units with weak protection and high pollution emission risks, providing clear direction for targeted pollution prevention and control measures, but also makes pollution concentration predictions more consistent with the actual emission characteristics of each unit, avoiding the obscuring of local high-pollution areas by overall analysis, and significantly improving the spatial accuracy of pollution assessment.

[0029] Furthermore, by calculating static and dynamic source strengths separately, the complete sources of pollution at the storage site can be comprehensively covered. This comprehensive source strength calculation method avoids underestimation or overestimation of pollution due to the omission of certain source strengths. By establishing a two-way correction relationship between static and dynamic source strengths, the source strength distortion problem caused by the separation of the two in traditional analysis is solved. This makes the final static and dynamic source strengths obtained after correction more realistically reflect the actual emission levels of the unit during the operating and non-operating periods, significantly improving the accuracy of source strength calculation. This provides more realistic input parameters for atmospheric diffusion models, making the pollutant concentration simulation results at each prediction point more reliable and contributing to improving the accuracy of the analysis results. Attached Figure Description

[0030] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0031] Figure 1 This is a flowchart of a bulk cargo yard pollution analysis method based on area source intensity division provided by an embodiment of the present invention;

[0032] Figure 2 This is a schematic diagram of the structure of a bulk cargo yard pollution analysis system based on area source intensity division provided in an embodiment of the present invention. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0034] The specific embodiments of the present invention will be described below.

[0035] To address the issue of poor accuracy in existing bulk cargo yard pollution analysis methods, this invention collects multi-dimensional influencing factor data on pollutants in bulk cargo yards. Based on the designated protective facilities for pollutants in the bulk cargo yard, the area source pollution is divided into multiple independent units. For each independent unit, the initial static source strength and initial dynamic source strength are calculated based on relevant pollution source parameters. A coupling optimization mechanism is established to correct the initial source strength, yielding the final static and dynamic source strengths. Based on the final source strength of each independent unit, multiple prediction points corresponding to that unit are set. Pollution diffusion-related parameters and the final source strength are imported into an atmospheric diffusion model to simulate the pollutant concentration values ​​at each prediction point. The pollution analysis method for bulk cargo yards provided by this invention yields highly accurate results.

[0036] Example 1

[0037] This invention provides a method for analyzing pollution in bulk cargo storage yards based on area source intensity partitioning. Figure 1 This is a flowchart of a bulk cargo yard pollution analysis method based on area source intensity division provided by an embodiment of the present invention, such as... Figure 1 As shown, the specific steps include the following:

[0038] S1. Collect multidimensional influencing factors data of pollutants in bulk cargo yards, including pollution source-related parameters and pollution diffusion-related parameters.

[0039] Multidimensional influencing factor data refers to the data supporting the analysis of pollutants in bulk cargo yards. Pollution source-related parameters are parameters that directly reflect the emission characteristics of pollutants from bulk cargo yards. These include basic yard parameters such as pile surface area and the layout and type of protective facilities; operation-related parameters such as port operation frequency and material characteristics; and source strength calculation parameters such as threshold frictional wind speed and ground roughness. Pollution diffusion-related parameters are external environmental parameters that affect the migration and diffusion of pollutants in the atmosphere. These include meteorological parameters such as upper-air meteorological data and hourly surface meteorological data, as well as topographic parameters.

[0040] For example, the layout and type of protective facilities such as the stack surface area and canopies are obtained through on-site statistics, and the number of disturbances is determined in conjunction with port operation records. Daily and hourly surface meteorological data such as wind direction, wind speed, and temperature for a given year are retrieved from local meteorological stations. The retrieved data includes upper-air meteorological data at 0, 4, and 8 o'clock each day, and topographic data covering the study area is also downloaded. These parameters are then correlated and integrated according to time and spatial dimensions to form a structured dataset of multidimensional influencing factors of pollutants in bulk cargo yards.

[0041] S2. Based on the protection facilities set for pollutants in the bulk cargo yard, the area source of the bulk cargo yard is divided into multiple independent units.

[0042] Protective facilities refer to environmental protection facilities planned or constructed in bulk cargo yards to reduce non-point source pollution. Their function is to reduce dust generation by physically blocking or interfering with wind fields. Non-point sources in bulk cargo yards refer to the area-based pollution sources that emit total suspended particulates (TSPs) within the yard. Based on the protective facilities, the non-point source pollution sources in the overall yard are broken down into localized areas, each with independent protective conditions and pollution emission characteristics.

[0043] Specifically, the set protective facilities include canopies and windbreak nets. According to the set protective facilities for pollutants in the bulk cargo yard, the area source of the bulk cargo yard is divided into multiple independent units, including: obtaining a plan of the bulk cargo yard, marking the covered area of ​​the canopy, the protected area of ​​the windbreak net, and the unprotected area on the plan of the bulk cargo yard; dividing the covered area of ​​the canopy, the protected area of ​​the windbreak net, and the unprotected area into independent units respectively; wherein, the boundary of each independent unit is determined by the physical edge of the set protective facilities or the inherent zoning line of the yard.

[0044] Protective facilities include canopies and similar structures such as windbreak and dust suppression nets. Their core function is to reduce static wind erosion and dust generation from dynamic operations in the storage yard by physically blocking or interfering with near-surface wind fields. The bulk cargo storage yard plan is the basic drawing reflecting the overall layout of the storage yard and serves as the spatial basis for subsequently marking the scope of protective facilities and dividing it into independent units. The covered area refers to the storage yard area directly shielded by the physical structure of the canopy. This area receives the strongest protection from the canopy, resulting in a significant reduction in dust generation. Unprotected areas refer to storage yard areas not covered by canopies and not affected by their shielding; these areas lack physical protection and have the highest risk of dust generation. Windbreak and dust suppression net protected areas refer to specific spatial ranges covered by windbreak and dust suppression nets, which reduce wind speed and wind erosion dust pollution. The protective effect is weaker than covered areas but better than unprotected areas.

[0045] First, obtain a plan of the bulk cargo yard. This plan must fully reflect the spatial layout of the yard. On the plan, based on the design drawings or actual construction locations of the canopy and windbreak netting, accurately mark three types of areas: the core area directly covered by the canopy, the area protected by the windbreak netting, and the blank area without canopy protection, clearly defining the spatial boundaries of each area. By dividing the area into independent units, the source strength can be calculated separately for the protection characteristics of each unit, avoiding the distortion of source strength caused by using the overall dust suppression rate to represent the local area, eliminating the averaging error of the overall area source, and accurately matching protection differences. At the same time, it provides clear unit boundaries for subsequent refined simulations, improving calculation accuracy.

[0046] S3. For each independent unit, calculate the initial static source strength and the initial dynamic source strength based on the pollution source-related parameters.

[0047] Initial static source strength refers to the static wind erosion dust source strength generated by natural wind forces in an independent unit of a bulk cargo yard when there are no loading or unloading operations. It represents the amount of dust emitted by materials blown by the wind under natural drying conditions. Initial static source strength is related to the wind field and material characteristics. Initial dynamic source strength refers to the dust source strength generated by mechanical disturbance during loading and unloading operations in an independent unit of a bulk cargo yard. It is directly related to the frequency of operations and represents an additional pollution contribution under operating conditions.

[0048] Specifically, the initial static source strength is calculated based on the pollution source-related parameters, including: determining the wind erosion and dust generation characteristics of the bulk cargo pile based on the material particle size and surface moisture content of the bulk cargo in the pollution source-related parameters; and calculating the initial static source strength based on the wind erosion and dust generation characteristics, meteorological data in the pollution source-related parameters, and the spatial distribution and protection status of the bulk cargo pile.

[0049] Material particle size refers to the size characteristics of bulk cargo particles and is a core parameter determining the ease with which wind erosion generates dust. Bulk cargo surface moisture content refers to the moisture content on the surface of the bulk cargo; both material particle size and surface moisture content are material characteristics. Wind erosion dust generation characteristics refer to the inherent properties of bulk cargo generating dust under wind action, primarily manifested in the critical dust generation conditions and dust generation intensity. For example, the critical dust generation condition includes the threshold frictional wind speed, and the dust generation intensity includes the emission factor. Wind erosion dust generation characteristics are jointly determined by material particle size and moisture content, directly affecting the calculation results of the initial static source strength.

[0050] When the surface moisture content of the bulk cargo determines that the bulk cargo yard is in a naturally dry state, the emission factor E is calculated. w The calculation formula is as follows:

[0051] ;

[0052] ;

[0053] ;

[0054] Where k is the particle size multiplier of the material, and k is taken as 1.0 when calculating TSP, and η is the dust removal efficiency of the pollution control technology. P wi Let u be the maximum wind speed erosion potential observed in the i-th disturbance, and N be the number of disturbances caused by natural wind to the bulk cargo pile. i * represents the frictional wind speed, u t * represents the threshold frictional wind speed, u iz Z represents the average wind speed at height z, where z is the wind speed detection height and z0 is the ground roughness. R is a dimensionless constant. i This represents the ratio of the wind speed at the detected altitude to the wind speed at the reference altitude, where V is the reference wind speed.

[0055] Calculate the initial static source strength based on the emission factor. The calculation formula is:

[0056] ;

[0057] Where A is the surface area of ​​the bulk cargo stack.

[0058] Specifically, the initial dynamic source strength is calculated based on the pollution source-related parameters, including: determining the operation intensity based on the loading and unloading efficiency in the pollution source-related parameters; determining the dynamic dust generation coefficient based on the bulk cargo type and loading and unloading method in the pollution source-related parameters; then correcting the dynamic dust generation coefficient based on the surface moisture content of the bulk cargo; and calculating the initial dynamic source strength by combining the operation intensity with the corrected dynamic dust generation coefficient.

[0059] Loading and unloading efficiency refers to the intensity of loading and unloading operations per unit time in a bulk cargo yard, and is a core parameter reflecting the frequency of operations. Operational intensity is a quantitative indicator that comprehensively reflects the frequency, drop, and total volume of loading and unloading operations. It reflects the intensity of disturbance to bulk cargo due to loading and unloading per unit time and is a scale factor of dynamic source strength. Bulk cargo type refers to the material properties of the bulk cargo; different types have significant differences in particle size and viscosity, directly affecting the dynamic dust generation potential. The dynamic dust generation coefficient refers to the dust emission coefficient generated by dynamic loading and unloading of bulk cargo under a unit operational intensity, and is jointly determined by the bulk cargo type and the loading and unloading method.

[0060] The dynamic source strength of loading and unloading operations is divided into the dynamic source strength of yard operations and the dynamic source strength of terminal loading and unloading operations. The initial dynamic source strength is calculated using the following formula:

[0061] ;

[0062] Q2 is the initial dynamic source strength, α is the cargo type adjustment coefficient, β is the operation mode coefficient, H is the drop of the material being handled, w2 represents the moisture effect coefficient, which is related to the bulk cargo properties and is taken as 0.40 to 0.45; w0 represents the critical value of the moisture effect, that is, when the moisture content is higher than this value, the increase in the moisture effect is not obvious, which is related to the bulk cargo properties, for example, 6% for coal and 5% for ore; w represents the moisture content, Y represents the loading and unloading operation efficiency, v2 represents the wind speed when the dust generation reaches 50% of the maximum dust generation, which is generally taken as 16 m / s; U represents the actual wind speed corresponding to the calculation of the dust generation during loading and unloading operations.

[0063] For an independent unit that experiences both static wind erosion and dynamic loading / unloading, the unit is in operation, and pollution consists of dust from both natural wind and loading / unloading operations. For an independent unit without loading / unloading operations, the unit is in non-operational phase, and only static dust from natural wind exists, with no additional contribution from dynamic operations; pollution is solely from static sources.

[0064] Pollution emissions from bulk cargo storage yards change dynamically depending on operational or non-operational conditions. Calculating dynamic and static source strengths for different scenarios allows for accurate matching of actual emission characteristics. During operational periods, this avoids underestimation of pollution due to neglecting dynamic source strength, while during non-operational periods, it avoids overestimation due to incorrectly adding dynamic source strength. Comprehensive coverage of operational differences improves the accuracy of pollution analysis.

[0065] S4. Establish a coupled optimization mechanism for static and dynamic source strength. Based on this mechanism, correct the initial static and dynamic source strengths to obtain the final static and dynamic source strengths. The coupled optimization mechanism includes: correcting the dust generation conditions for dynamic operations based on the material accumulation characteristics, local static wind field, and protection status corresponding to the initial static source strength; and correcting the static source strength based on the change in surface moisture content of the bulk cargo after dynamic operations.

[0066] The coupling optimization mechanism refers to the technical mechanism of establishing a two-way correlation correction logic between static source strength and dynamic source strength to adapt them to actual working conditions. Material accumulation characteristics refer to the physical distribution characteristics of bulk cargo piles (i.e., the spatial distribution of bulk cargo piles), including packing density, packing height, particle uniformity, etc., which directly affect the difficulty of dust generation during dynamic operations. The local static wind field refers to the near-surface wind environment within an independent unit, influenced by protective facilities and pile layout, determining the basic conditions for dust generation and diffusion during dynamic operations. Protective status refers to the environmental protection configuration of an independent unit, directly weakening or altering the wind field and dust generation path during operations.

[0067] Based on the above embodiments, the initial static source strength and initial dynamic source strength are calculated. The dust-generating baseline conditions of the initial dynamic source strength are adjusted using three parameters corresponding to the initial static source strength: material accumulation characteristics, local static wind field, and protection status. The correction process based on material accumulation characteristics includes: if the material accumulation is dense, the dynamic dust generation coefficient is reduced; if the accumulation is loose, the dynamic dust generation coefficient is increased. The correction process based on local static wind field includes: if the wind speed within the unit is low, the diffusion potential of dynamic dust generation is weakened, and the initial dynamic source strength is reduced; if the wind speed is high, the initial dynamic source strength core is increased. The correction process based on protection status includes: the canopy-covered area directly blocks operational dust, and the dynamic dust generation coefficient is adjusted according to the protection efficiency; no additional adjustment is made for unprotected areas.

[0068] After dynamic operations, data on changes in the surface moisture content of bulk materials are monitored, such as moisture loss due to loading and unloading disturbances or increased moisture content due to dust suppression spraying. This change is used to adjust the initial static source strength. For example, if the moisture content increases, the static wind erosion dust generation characteristics are reduced, thereby decreasing the initial static source strength. If the moisture content decreases, such as moisture evaporation due to material turning, the static wind erosion dust generation characteristics are increased, thereby increasing the initial static source strength.

[0069] The final static and dynamic source strengths fully reflect the actual pollution emission levels of the unit during non-operational and operational periods, serving as core input parameters for the atmospheric diffusion model. By establishing a coupled optimization mechanism, the biases of neglecting post-operational moisture content changes in static source strength and neglecting static environmental influences in dynamic source strength are avoided, making source strength calculations more closely reflect actual emission characteristics. Both the final static and dynamic source strengths simultaneously adapt to static environmental conditions and dynamic operational influences, providing more reliable input parameters for subsequent atmospheric diffusion models and improving the accuracy of source strength calculations.

[0070] S5. Based on the final dynamic source strength and final static source strength of each independent unit, set multiple prediction points corresponding to the independent unit.

[0071] Predicted monitoring sites are specific spatial locations set up to monitor the diffusion concentration of pollutants in an independent unit. The pollution diffusion range of each independent unit is associated with a specific predicted monitoring site; that is, the pollutant concentration at a set of predicted monitoring sites is mainly affected by the dynamic and static source strengths of the corresponding independent unit.

[0072] Specifically, based on the final static source strength and final dynamic source strength of each independent unit, multiple prediction points corresponding to the independent unit are set, including: when the final static source strength and / or the final dynamic source strength is higher than a set threshold, prediction points around the independent unit corresponding to the final static source strength and the final dynamic source strength are set according to a first deployment density; when the final static source strength and the final dynamic source strength are not higher than the set threshold, prediction points around the independent unit corresponding to the static source strength and the dynamic source strength are set according to a second deployment density. The coordinates of the prediction points are based on the geometric center of the corresponding independent unit, so that the prediction points cover the pollution diffusion range of the independent unit.

[0073] The set threshold is a critical value used to distinguish between high and low pollution emission intensity of independent units, and is the core criterion for selecting the density of monitoring points. The first density is a monitoring point layout scheme used for high-pollution-risk units where at least one of the final dynamic source intensity or final static source intensity exceeds the set threshold. The first density is characterized by denser monitoring points, aiming to accurately capture the peak pollution concentration and diffusion details of high-source-intensity units. The second density is a monitoring point layout scheme used for low-pollution-risk units where neither the final dynamic source intensity nor the final static source intensity exceeds the set threshold. It is characterized by sparser monitoring points, reducing redundant points and lowering computational costs while meeting monitoring requirements. The geometric center of an independent unit is the central coordinate point of its spatial range, serving as the reference origin for monitoring point layout. This ensures that predicted monitoring points are distributed around the core pollution area of ​​the unit, avoiding deviations from the actual diffusion range.

[0074] S6. Import the pollution diffusion-related parameters, the final static source strength, and the final dynamic source strength into the atmospheric diffusion model to simulate the pollutant concentration values ​​at each predicted location. Specifically, this includes: converting the pollution diffusion-related parameters into a format compatible with the atmospheric diffusion model; importing the converted pollution diffusion-related parameters, along with the final static source strength and final dynamic source strength of each independent unit, into the atmospheric diffusion model; and outputting the simulated pollutant concentration values ​​at each predicted location from the atmospheric diffusion model.

[0075] The atmospheric diffusion model simulates the atmospheric flow field based on input meteorological data, corrects the local wind field using topographic data, and then calculates the emission, transport, and diffusion processes of TSP based on the final dynamic and static source strengths of each independent unit. The atmospheric diffusion model outputs hourly TSP concentration values ​​point-by-point according to preset prediction locations.

[0076] Based on the above embodiments, after simulating the pollutant concentration values ​​at each predicted point, the method further includes: deploying dust monitoring instruments at each predicted point for on-site sampling and acquiring the online monitoring values ​​of pollutant concentration at each predicted point in real time; calculating the relative deviation between the simulated pollutant concentration values ​​and the online monitoring values ​​at each predicted point within a set time period; and determining that the simulated pollutant concentration values ​​are valid when the relative deviation is less than the set deviation.

[0077] Sampling is conducted within the same time period as the model simulation. This time period can be the same hour, with actual meteorological conditions recorded synchronously. The simulated concentration values ​​for each predicted location from the previous atmospheric diffusion model are retrieved. The relative deviation of each predicted location is compared with the set deviation. For example, if the deviation for a predicted location is less than 10%, the simulated value for that location is considered valid. Verification using measured data confirms whether the model input parameters closely match reality, preventing discrepancies between simulation results and actual field conditions due to parameter errors, and improving the reliability of the simulation results.

[0078] This embodiment collects multidimensional influencing factor data on pollutants from bulk cargo storage yards, including pollution source-related parameters and pollution diffusion-related parameters. Based on the established protective facilities for pollutants in the bulk cargo storage yard, the area source pollution is divided into multiple independent units. For each independent unit, the initial static source strength and initial dynamic source strength are calculated based on the pollution source-related parameters. A coupled optimization mechanism for static and dynamic source strengths is established, and the initial static and dynamic source strengths are corrected according to the coupled optimization mechanism to obtain the final static and dynamic source strengths. Based on the final static and dynamic source strengths of each independent unit, multiple prediction points corresponding to the independent unit are set. The pollution diffusion-related parameters, final static source strength, and final dynamic source strength are imported into an atmospheric diffusion model to simulate the pollutant concentration values ​​at each prediction point. Dividing the area source into multiple independent units according to the established protective facilities can accurately match the actual differences in the protection capabilities of each area. For example, the dust suppression effect of an area fully covered by protective facilities is significantly different from that of an unprotected area. Dividing into independent units avoids the errors caused by averaging in the overall area source analysis, improving the accuracy of the analysis results. This classification method allows subsequent source strength calculations and pollution diffusion simulations to focus on specific units. It not only clearly identifies units with weak protection and high pollution emission risks, providing clear direction for targeted pollution prevention and control measures, but also makes pollution concentration predictions more consistent with the actual emission characteristics of each unit, avoiding the obscuring of local high-pollution areas by overall analysis, and significantly improving the spatial accuracy of pollution assessment.

[0079] Furthermore, by calculating static and dynamic source strengths separately, the complete sources of pollution at the storage site can be comprehensively covered. This comprehensive source strength calculation method avoids underestimation or overestimation of pollution due to the omission of certain source strengths. By establishing a two-way correction relationship between static and dynamic source strengths, the source strength distortion problem caused by the separation of the two in traditional analysis is solved. This makes the final static and dynamic source strengths obtained after correction more realistically reflect the actual emission levels of the unit during the operating and non-operating periods, significantly improving the accuracy of source strength calculation. This provides more realistic input parameters for atmospheric diffusion models, making the pollutant concentration simulation results at each prediction point more reliable and contributing to improving the accuracy of the analysis results.

[0080] Example 2

[0081] This invention also provides a bulk cargo yard pollution analysis system based on area source intensity division. Figure 2 This is a schematic diagram of a bulk cargo yard pollution analysis system based on area source intensity division provided in an embodiment of the present invention, as shown below. Figure 2 As shown, the system includes:

[0082] The data acquisition module is used to collect multidimensional influencing factors of pollutants in bulk cargo storage yards, including pollution source-related parameters and pollution diffusion-related parameters.

[0083] The area source classification module is used to divide the area sources of the bulk cargo yard into multiple independent units according to the set protective facilities for pollutants in the bulk cargo yard;

[0084] The source strength calculation module is used to calculate the initial static source strength and the initial dynamic source strength for each independent unit based on the pollution source-related parameters.

[0085] The source strength correction module establishes a coupled optimization mechanism between static source strength and dynamic source strength, and corrects the initial static source strength and initial dynamic source strength according to the coupled optimization mechanism to obtain the final static source strength and final dynamic source strength.

[0086] The point setting module is used to set multiple predicted points corresponding to each independent unit based on the final static source strength and the final dynamic source strength of each independent unit.

[0087] The simulation calculation module is used to import the pollution diffusion-related parameters, the final static source strength, and the final dynamic source strength into the atmospheric diffusion model to simulate the pollutant concentration values ​​at each predicted location.

[0088] The bulk cargo yard pollution analysis system based on area source intensity division provided in this embodiment executes the bulk cargo yard pollution analysis method based on area source intensity division described in any of the above embodiments, and has the beneficial effects of any of the above embodiments, which will not be repeated here.

[0089] Finally, it should be noted that 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; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for analyzing pollution in bulk cargo storage yards based on area source intensity division, characterized in that, include: S1. Collect multidimensional influencing factors of pollutants in bulk cargo storage yards, including pollution source-related parameters and pollution diffusion-related parameters. S2. According to the set protection facilities for pollutants in the bulk cargo yard, the area source of the bulk cargo yard is divided into multiple independent units, and the set protection facilities include canopies and windbreak nets; Specifically, this includes: obtaining a plan of the bulk cargo yard, marking the covered area of ​​the canopy, the protected area of ​​the windbreak net, and the unprotected area on the plan of the bulk cargo yard; dividing the covered area of ​​the canopy, the protected area of ​​the windbreak net, and the unprotected area into independent units; wherein, the boundary of each independent unit is determined by setting the physical edge of the protective facilities or the inherent zoning line of the yard. S3. For each independent unit, calculate the initial static source strength and the initial dynamic source strength based on the pollution source-related parameters. S4. Establish a coupled optimization mechanism for static source strength and dynamic source strength, and correct the initial static source strength and initial dynamic source strength according to the coupled optimization mechanism to obtain the final static source strength and final dynamic source strength. In S4, the coupling optimization mechanism includes: The dust generation conditions for dynamic operations are adjusted based on the material accumulation characteristics, local static wind field, and protection status corresponding to the initial static source strength. The static source strength is adjusted based on the change in surface moisture content of bulk cargo after dynamic operations. S5. Based on the final static source strength and final dynamic source strength of each independent unit, set multiple prediction points corresponding to the independent unit; S6. Import the pollution diffusion-related parameters, the final static source strength, and the final dynamic source strength into the atmospheric diffusion model to simulate the pollutant concentration values ​​at each predicted location.

2. The method for analyzing pollution in bulk cargo storage yards based on area source intensity division according to claim 1, characterized in that, In step S3, the initial static source strength is calculated based on the pollution source-related parameters, including: The wind erosion and dust generation characteristics of the bulk cargo pile are determined based on the material particle size and surface moisture content of the bulk cargo in the relevant parameters of the pollution source. The initial static source strength is calculated based on the wind erosion dust generation characteristics, meteorological data in the pollution source-related parameters, and the spatial distribution and protection status of the bulk cargo pile.

3. The method for analyzing pollution in bulk cargo storage yards based on area source intensity division according to claim 2, characterized in that, In step S3, calculating the initial dynamic source strength based on the pollution source-related parameters includes: The intensity of operations is determined based on the loading and unloading efficiency in the relevant parameters of the pollution source. The dynamic dust generation coefficient is determined based on the bulk cargo type and loading / unloading method in the relevant parameters of the pollution source. The dynamic dust generation coefficient is corrected based on the surface moisture content of the bulk cargo, and the initial dynamic source strength is calculated by combining the work intensity with the corrected dynamic dust generation coefficient.

4. The method for analyzing pollution in bulk cargo storage yards based on area source intensity division according to claim 1, characterized in that, In step S5, based on the final static source strength and final dynamic source strength of each independent unit, multiple prediction points corresponding to the independent unit are set, including: When the final static source strength and / or the final dynamic source strength are higher than the set threshold, the prediction points around the independent units corresponding to the final static source strength and the final dynamic source strength are set according to the first deployment density. When the final static source strength and the final dynamic source strength are not higher than the set threshold, the prediction points around the independent units corresponding to the static source strength and the dynamic source strength are set according to the second deployment density.

5. The method for analyzing pollution in bulk cargo storage yards based on area source intensity division according to claim 4, characterized in that, The coordinates of the predicted points are based on the geometric center of the corresponding independent unit, so that the predicted points cover the pollution diffusion range of the independent unit.

6. The method for analyzing pollution in bulk cargo storage yards based on area source intensity division according to claim 1, characterized in that, In step S6, the pollution diffusion-related parameters, the final static source strength, and the final dynamic source strength are imported into the atmospheric diffusion model to simulate the pollutant concentration values ​​at each predicted location, including: Convert pollution diffusion-related parameters into a format suitable for atmospheric diffusion models; The pollution diffusion-related parameters after conversion, along with the final static source strength and final dynamic source strength of each independent unit, are imported into the atmospheric diffusion model. The atmospheric diffusion model outputs simulated pollutant concentration values ​​for each predicted location.

7. The method for analyzing pollution in bulk cargo storage yards based on area source intensity division according to claim 6, characterized in that, After simulating the pollutant concentration values ​​at each predicted location, the following is also included: Dust monitoring instruments were deployed at each prediction point to conduct on-site sampling, and the online monitoring values ​​of pollutant concentrations at each prediction point were obtained in real time. Within a set time period, calculate the relative deviation between the simulated pollutant concentration values ​​and the online monitoring values ​​at each predicted location; When the relative deviation is less than the set deviation, the simulated pollutant concentration value is determined to be valid.

8. A bulk cargo yard pollution analysis system based on area source intensity division, characterized in that, The system is used to execute the bulk cargo yard pollution analysis method based on area source intensity division as described in any one of claims 1-7, and the system comprises: The data acquisition module is used to collect multidimensional influencing factors of pollutants in bulk cargo storage yards, including pollution source-related parameters and pollution diffusion-related parameters. The area source classification module is used to divide the area source of the bulk cargo yard into multiple independent units according to the set protective facilities for pollutants in the bulk cargo yard. The set protective facilities include canopies and windbreak nets. Specifically, this includes: obtaining a plan of the bulk cargo yard, marking the covered area of ​​the canopy, the protected area of ​​the windbreak net, and the unprotected area on the plan of the bulk cargo yard; dividing the covered area of ​​the canopy, the protected area of ​​the windbreak net, and the unprotected area into independent units; wherein, the boundary of each independent unit is determined by setting the physical edge of the protective facilities or the inherent zoning line of the yard. The source strength calculation module is used to calculate the initial static source strength and the initial dynamic source strength for each independent unit based on the pollution source-related parameters. The source strength correction module establishes a coupled optimization mechanism between static source strength and dynamic source strength, and corrects the initial static source strength and initial dynamic source strength according to the coupled optimization mechanism to obtain the final static source strength and final dynamic source strength. The point setting module is used to set multiple predicted points corresponding to each independent unit based on the final static source strength and the final dynamic source strength of each independent unit. The simulation calculation module is used to import the pollution diffusion-related parameters, the final static source strength, and the final dynamic source strength into the atmospheric diffusion model to simulate the pollutant concentration values ​​at each predicted location.

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