An environment intelligent management system and method based on multi-source data fusion

Abstract

The application discloses an environment intelligent management system and method based on multi-source data fusion, relates to the technical field of environment monitoring and intelligent management, and comprises the following steps: collecting wind direction, traffic and barrier geometric data, calculating concentration source credibility and standardization; constructing a graph reachable intensity of the end of the barrier to the management unit; calculating the end bypass potential based on the wind direction component and the barrier parameter, generating a pollution corridor; calculating the membership intensity of the sampling point to the corridor and enhancing the fusion weight to obtain the fusion concentration; calculating the management priority by comprehensively considering the bypass potential, the reachable intensity and the fusion concentration; and optimizing the work order scheduling according to the priority under the budget constraint. The application can accurately identify the high pollution area at the end of the barrier by quantifying the end flow mechanism and enhancing the corridor fusion.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring and intelligent governance technology, and in particular to an intelligent environmental management system and method based on multi-source data fusion. Background Technology

[0002] Road traffic emissions are a major source of urban air pollution. To reduce traffic noise and block the diffusion of some near-surface pollutants, linear structures such as noise barriers and retaining walls are often installed along urban expressways and main roads. In reality, due to limitations in road entrances and exits and engineering planning, these linear barriers inevitably have end breaks or maintenance gaps. When airflow passes through these geometrically discontinuous points, due to fluid bypass mechanisms, airflow carrying high concentrations of vehicle exhaust will generate significant lateral flow and bypass phenomena at the barrier ends. This results in pollutants not being effectively blocked by the barrier, but rather overflowing from the ends and forming high-concentration accumulation areas of a specific shape near the ground on the leeward side. The location and intensity of these localized pollution hotspots caused by the barrier end structure dynamically change with wind direction and traffic flow, making them potential hidden danger areas that are easily overlooked in environmental governance.

[0003] Current technologies for environmental monitoring and governance scheduling often employ average value management models based on administrative grids or sparse fixed monitoring points. Because pollutant accumulation at these end-point locations is characterized by its narrow spatial range and dynamic location shifting with wind direction, conventional gridded average calculations easily dilute local high values ​​with surrounding background values, making it difficult for monitoring systems to accurately detect anomalies caused by barrier geometric discontinuities. Furthermore, existing governance resource scheduling typically relies on static plans or regional-wide execution, lacking a comprehensive consideration of the dynamic relationship between barrier geometric parameters, real-time wind fields, and traffic source strength. This makes it impossible to accurately locate and quantify the specific impact range of end-point bypass flow, resulting in excessive investment of governance resources in non-priority areas while genuine high-concentration accumulation areas at the ends fail to receive timely and effective treatment, leading to inefficient resource allocation. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies that fail to effectively consider the airflow bypass and pollutant transport mechanisms caused by geometric discontinuities at the ends of linear structures, resulting in local high-concentration accumulation areas being easily diluted or missed by background values, thus leading to inaccurate identification of key treatment areas and low management efficiency. Therefore, this invention proposes an environmental intelligent management system and method based on multi-source data fusion.

[0005] To address the problems existing in the prior art, the present invention adopts the following technical solution: An intelligent environmental management method based on multi-source data fusion includes: S1. Collect wind direction data, traffic flow, barrier geometry data, and concentration data from concentration data sources. Calculate the basic confidence level of each concentration data source and standardize the concentration data to obtain the basic confidence level and standardized concentration. S2. Divide the governance area into management units. Based on the barrier geometry data, wind direction data, and management units, calculate the achievable intensity of the management unit's map. S3. Determine the unit wind direction based on wind direction data, calculate the end bypass potential based on traffic flow, barrier geometry data, and the components of the unit wind direction in the tangential and normal directions of the barrier, and generate the pollution corridor. S4. Calculate the membership strength of each sampling point within the management unit relative to the pollution corridor. Based on the basic confidence level and membership strength, the standardized concentration is weighted and fused to obtain the fused concentration. S5. Calculate the governance priority of each management unit based on end bypass potential, map reachability, fusion concentration, and membership strength; S6. Under budget constraints, select the work order type for the management unit based on governance priorities.

[0006] Preferably, the barrier geometry data includes: barrier height, barrier end points, end gap width, and local tangential and normal unit vectors of the barrier.

[0007] Preferably, the baseline confidence level of each concentration data source is calculated and the concentration data is standardized, including: Within a set time window, the variance of concentration data from each concentration data source is calculated, and the reciprocal of the variance is used as the basic reliability of the concentration data source. Within a set time window, the mean and standard deviation of concentration data from each concentration data source are statistically analyzed. The concentration data is then subtracted from the mean and divided by the standard deviation to obtain the standardized concentration.

[0008] Preferably, based on barrier geometry data, wind direction data, and management units, the spectral reachability intensity of the management units is calculated, including: Determine the representative point of the management unit, wherein the representative point is the geometric center point of the management unit; Calculate the distance from the end point of the barrier to a representative point of the management unit, and construct a distance attenuation factor based on the distance; The unit wind direction is determined based on the wind direction data. The dot product of the unit wind direction and the unit direction vector of the representative point of the management unit from the end point of the barrier is calculated. The dot product with a value less than zero is truncated to zero to obtain the direction factor. The product of the distance attenuation factor and the direction factor is taken as the single-point influence intensity. When there are multiple barrier end points, the maximum value of the single-point influence intensity is taken as the spectral reachability intensity of the management unit.

[0009] Preferably, the end bypass potential is calculated based on traffic flow, barrier geometry data, and the components of the unit wind direction in the tangential and normal directions of the barrier, and a pollution corridor is generated, including: Emission intensity proxy values ​​are constructed based on traffic flow. The ratio of the absolute value of the unit wind direction in the tangential component of the barrier to the absolute value of the unit wind direction in the normal component of the barrier is used as the wind direction factor. Calculate the ratio of the end notch width to the barrier height, and construct the notch influence factor based on this ratio; Calculate the product of emission intensity proxy value, wind direction factor, and gap influence factor, and divide by barrier height to obtain end bypass potential; Calculate the product of barrier height and wind direction factor, and scale the product based on a set length scaling factor to obtain the length of the pollution corridor; The width of the contaminated corridor is obtained by scaling the barrier height based on a set width scaling factor.

[0010] Preferably, the membership strength of each sampling point within the management unit relative to the pollution corridor is calculated, and the standardized concentration is weighted and fused based on the basic confidence level and membership strength to obtain the fused concentration, including: The longitudinal projection distance of each sampling point within the calculation management unit relative to the barrier end point along the wind direction and the lateral projection distance perpendicular to the wind direction are calculated. If the longitudinal projection distance is greater than zero and less than the length of the contaminated corridor, then an attenuation function value is constructed based on the transverse projection distance and the width of the contaminated corridor, and used as the membership strength; otherwise, the membership strength is set to zero. The basic credibility is corrected based on the membership strength and the preset corridor enhancement coefficient to obtain the corrected weight. The standardized concentration is then weighted and averaged according to the corrected weight to obtain the fusion concentration.

[0011] Preferably, the governance priority of each management unit is calculated based on end bypass potential, spectral reachability, fusion concentration, and membership strength, including: For all sampling points within the management unit, calculate the product of fusion concentration and membership strength, and sum the products within the management unit to obtain the total exposure of the unit; The governance priority of the management unit is obtained by multiplying the end bypass potential, the spectral reachability intensity, and the total unit exposure.

[0012] Preferably, under budget constraints, the work order type is selected for the management unit based on governance priorities, including: Set up a set of work order types for each management unit and configure the cost, input quantity, and input limit for each work order type; Based on the ratio of governance priority to input amount relative to input limit, determine the work order benefits of each work order type for the management unit; Under budget constraints, work order types are selected in descending order of the ratio of work order revenue to configuration cost.

[0013] To address the above problems, the present invention also provides an intelligent environmental management system based on multi-source data fusion, the system comprising: The data preprocessing module is used to collect wind direction data, traffic flow, barrier geometry data, and concentration data from concentration data sources. It calculates the basic confidence level of each concentration data source and standardizes the concentration data to obtain the basic confidence level and standardized concentration. The map reachability module is used to divide the governance area into management units. Based on the barrier geometry data, wind direction data, and management units, it calculates the map reachability intensity of the management units. The bypass corridor module is used to determine the unit wind direction based on wind direction data, calculate the end bypass potential based on traffic flow, barrier geometry data, and the components of the unit wind direction in the tangential and normal directions of the barrier, and generate pollution corridors. The enhanced fusion module is used to calculate the membership strength of each sampling point within the management unit relative to the pollution corridor. Based on the basic confidence level and membership strength, the standardized concentration is weighted and fused to obtain the fused concentration. The priority module is used to calculate the governance priority of each management unit based on the end bypass potential, map reachability, fusion concentration, and membership strength. The work order scheduling module is used to select the work order type for the management unit based on governance priority under budget constraints.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention introduces end bypass potential calculation and pollution corridor generation mechanism, which can dynamically characterize local high pollution areas caused by end geometric discontinuities based on wind direction, traffic flow and barrier geometry data; by calculating the membership strength of sampling points relative to the pollution corridor and using it to enhance fusion weight, it effectively prevents the high concentration of the narrow end band from being diluted by the background value. This corridor enhancement fusion method based on physical mechanism significantly improves the sensitivity and accuracy of the monitoring system in identifying end bypass pollution hotspots.

[0015] 2. This invention constructs a multi-dimensional priority evaluation system based on end-point driving factors, graph reachability, and total unit exposure. It transforms the complex end-point bypass impact into a quantifiable governance urgency indicator. Combined with a work order benefit optimization model under budget constraints, it can automatically select the most cost-effective combination of governance measures, ensuring that limited operation and maintenance resources are prioritized for key management units with the most significant end-point bypass impact and the highest exposure risk. This solves the resource misallocation problem in the traditional static scheduling mode and improves the targeting and execution efficiency of environmental management. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating an intelligent environmental management method based on multi-source data fusion according to the present invention. Figure 2 This is a functional block diagram of an environmental intelligent management system based on multi-source data fusion according to the present invention; Figure 3 This is a schematic diagram illustrating the principle of generating the end bypass pollution corridor according to the present invention. Detailed Implementation

[0017] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0018] Example: This example provides an intelligent environmental management method based on multi-source data fusion. See [link to example]. Figure 1 Specifically, including: S1. Collect wind direction data, traffic flow, barrier geometry data, and concentration data from concentration data sources. Calculate the basic confidence level of each concentration data source and standardize the concentration data to obtain the basic confidence level and standardized concentration. In embodiments of the present invention, wind direction data, traffic flow, barrier geometry data, and concentration data from concentration data sources are collected. The basic reliability of each concentration data source is calculated, and the concentration data is standardized, including: Collect wind direction data, traffic flow, barrier geometry data, and concentration data from concentration data sources; It should be noted that wind direction data is used to characterize the dominant direction of air movement and its spatial orientation, reflecting the control of airflow on pollutant transport paths and dilution conditions; traffic flow is used to characterize the intensity of vehicles passing through a road cross-section per unit time, directly corresponding to the source strength and emission continuity of traffic emissions; barrier geometry data is used to characterize the spatial shape and oriented boundaries of noise barriers or retaining walls, including barrier height, coordinates of barrier end points, and gap scale and local tangential and normal direction information, which determines the conditions for airflow separation and the formation of end bypass channels; concentration data sources are the measurement carriers or deployment points that generate pollutant concentration observations, reflecting sampling... Location and sampling method constrain the representativeness of observations. Concentration data represents the content of managed pollutants in the air, usually corresponding to the mass or volume fraction of pollutants per unit volume of air. Baseline confidence is a measure of the observation stability and noise level of each concentration data source, reflecting the weight that the data source should bear in the fusion calculation. Standardization is the process of unifying the scale and eliminating the dimensions of concentration values ​​from different data sources, transforming them into comparable dimensionless quantities for weighted fusion. Baseline confidence and standardized concentration are used as the weight input and the concentration input to be fused in the subsequent weighted fusion, respectively, thereby ensuring that the fusion result takes into account both observation reliability and cross-source comparability.

[0019] Specifically, the centerline or lane edge of the road corresponding to the noise barrier of the road section to be managed is determined as the data collection baseline. A data collection range covering the area extending outwards from the barrier end is pre-defined on both sides of the baseline. The preferred length of the data collection range is 50 to 300 meters extending from the barrier end along the road direction, preferably 100 to 200 meters, to balance the impact range of the end bypass and deployment costs. The preferred width of the data collection range is 20 to 200 meters extending outwards from the road edge towards the receiver side, preferably 50 to 150 meters, to cover the area that the ground-level corridor may reach. Wind direction data is obtained by setting at least one wind direction observation point within the data collection range. The wind direction observation point is preferably located in an open area near the barrier end, with the sensor probe height set high. The sampling distance for wind direction data is preferably 2 to 10 meters, with a maximum of 5 meters, to reduce interference from near-ground obstacles and maintain representativeness of the pedestrian layer and the incoming flow above the barrier. The sampling period for wind direction data is preferably 1 to 10 seconds, with a maximum of 5 seconds, to capture changes in end-flow conditions without significantly increasing communication overhead. Traffic flow is obtained through road cross-section counting, with the cross-section preferably selected as a single fixed cross-section within a range of 50 to 200 meters upstream of the barrier end, with a maximum of 100 meters, to reduce the disturbance impact of the end-flow area on vehicle queues. The statistical time window for traffic flow is preferably 30 to 5 minutes, with a maximum of 1 minute, to balance instantaneous fluctuations and source strength estimation stability. Barrier geometric data is obtained through a combination of on-site surveying and existing engineering drawings, preferably using a total station or excitation system. Optical ranging is used to measure the barrier height, and the median value of multiple measurements is used as the barrier height to suppress local installation errors. The barrier end point is determined by searching for the end position of the barrier entity along the barrier extension direction and recording the coordinates of the end point in the geographic coordinate system. The width of the end gap is obtained by measuring the minimum clearance of the opening at the barrier end, and when there are multiple openings, the width of the opening with the greatest impact on the receiver side is taken as the end gap width. The tangential unit vector and normal unit vector of the barrier are obtained by selecting two adjacent mapping points near the barrier centerline, calculating their directions, and normalizing them. The normal unit vector is pointed towards the receiver side to ensure that the direction of subsequent component calculations is consistent. The concentration data of the concentration data source is obtained by deploying fixed or moving concentration data points within the acquisition range. The concentration data source is preferably composed of at least one access point near the end of the barrier and one receptor-side point to enhance the spatial characterization of end-bypass pollution. The installation height of the concentration data source is preferably one to two meters above the ground to be close to the breathing height of pedestrians and to reflect the concentration level of the ground corridor. The sampling period of the concentration data is preferably one to thirty seconds, and preferably ten seconds to match the time resolution of the wind direction data and maintain the availability of fusion calculation. During the acquisition process, all types of data are timestamped using the same clock reference and the acquisition location and device identifier are carried in the communication link, thereby forming a data set of the same time window containing wind direction data, traffic flow, barrier geometry data and concentration data from the concentration data source for subsequent calculation.

[0020] Calculate the baseline confidence level for each concentration data source and standardize the concentration data; Specifically, concentration data continuously collected from the same concentration data source within a set time window constitute a window data sequence for that concentration data source. The time window is preferably one to ten minutes, and more preferably five minutes, to account for short-term variations in end-of-pipe pollution conditions and statistical stability. Within this time window, the mean and variance of the window data sequence are calculated, and significant outliers are identified to avoid distortion of the statistics by individual sampling peaks. Outlier identification preferably uses the three-standard-deviation criterion or the percentile cutoff criterion. After outlier processing, a clean window data sequence is obtained. The basic confidence level is used to characterize the observation stability and noise level of the concentration data source within the time window. The smaller the observation fluctuation, the higher its weight should be in subsequent fusion. Therefore, the basic confidence level is set as the reciprocal of the window variance, and can be calculated using the following formula: In the formula, To establish the basic credibility of this concentration data source, To eliminate the dominant influence of differences in concentration data range, sensitivity, and unit variation on the fusion results, the data sequence within the purification window is standardized. The concentration data at each sampling time is subtracted from the mean within that time window and divided by the standard deviation within that time window to obtain the standardized concentration. The standardized concentration is calculated using the following formula: In the formula, To standardize the concentration, This is the concentration data at that sampling time. To clean up the mean of the window data sequence, To clean up the standard deviation of the window data sequence, the baseline offset of different concentration data sources is eliminated by the mean, and the scale difference caused by different ranges is eliminated by the standard deviation. This ensures that the standardized concentration has a uniform dimensionless scale across different concentration data sources, so that the basic confidence can be used as a weight input for subsequent weighted fusion and together with the standardized concentration, it constitutes the stable input data for fusion calculation.

[0021] S2. Divide the governance area into management units. Based on the barrier geometry data, wind direction data, and management units, calculate the achievable intensity of the management unit's map. In an embodiment of the present invention, the governance area is divided into management units. Based on barrier geometry data, wind direction data, and the management units, the spectral reachability of the management units is calculated, including: Determine the representative point of the management unit, wherein the representative point is the geometric center point of the management unit; Calculate the distance from the end point of the barrier to a representative point of the management unit, and construct a distance attenuation factor based on the distance; It should be noted that a management unit is the smallest management object obtained by dividing the treatment area around the barrier end according to spatial location and management granularity. It can correspond to a grid area, a region within a small area boundary, or a functional zone on the receiving side of a road. It is used to accommodate management elements such as the distribution of sensitive points, the set of monitoring sampling points, and subsequent work order assignment, thereby enabling the priority of treatment to be implemented at an executable regional level. The distance attenuation factor is a quantitative factor used to characterize the rapid decrease in the impact of the barrier end on the management unit with increasing distance. It originates from the objective law that the effective influence intensity of pollutants along the propagation path decreases with increasing spatial scale after being subjected to turbulent diffusion, dilution mixing, and obstacle disturbance during near-surface transport. Therefore, by mapping the distance from the end point to the representative point of the management unit into an exponentially decreasing relationship, the distance attenuation factor is determined. Management units that are closer to the source are given a greater weight, while those that are farther away are naturally given a lower weight. This reflects the spatial characteristics of end-bypass pollution, which has a more significant effect on the near-end area and a gradually less significant effect on the far-end area. End-bypass pollution refers to the situation where, under the condition that there are ends or openings in the road noise barrier or retaining wall, the emissions from the near-road traffic are guided by the incoming wind direction and overflow around the end position, causing the pollutants to form a high-concentration strip-shaped area that extends close to the ground on the receiver side. This strip-shaped area usually starts from the end of the barrier and extends outward along the unit wind direction. Its lateral diffusion width is relatively narrow and the concentration peak is more likely to appear near the end rather than in the middle of the barrier, forming a tongue-shaped spatial distribution pattern. This pattern is used to characterize the local exposure hotspots caused by the combined effect of the bypass channel and turbulent backflow due to the geometric discontinuity at the end.

[0022] Specifically, the area surrounding the barrier end is divided into multiple management units using a grid. Each management unit has a closed boundary in the geographic coordinate system. This boundary can be formed by sequentially enclosing several vertex coordinates to create a polygon. The representative point of each management unit is taken as the geometric center of the polygon to ensure that the representative point is located at the overall center of the management unit's spatial range and to reduce the bias of boundary irregularities on distance measurement. In implementation, the boundaries of the management units are standardized so that their vertex coordinates use the same coordinate reference and a projection transformation is performed so that distances can be measured in a plane. The geometric center point is preferably calculated using the area-weighted centroid of the polygon. When the management unit is generated from a regular grid, the grid is directly used. The grid center is used as the geometric center point to simplify calculations and maintain the uniformity of representative points in each unit. The coordinates of the barrier end points in the barrier geometry data are used as the end point positions, and both the end points and the geometric center point of the management unit are represented as two-dimensional coordinates in the same coordinate system. The distance from the end point to the representative point of the management unit is calculated using the Euclidean distance between the two points. This distance form is used because it directly measures the shortest spatial separation scale between the end point and the receptor area on the plane, which corresponds to the ground-level propagation range of end-bypass pollution. After obtaining the distance, a distance attenuation factor is constructed based on this distance to characterize the law that the influence of the end point decreases rapidly with increasing distance. The distance attenuation factor can be expressed as: In the formula, For distance attenuation factor, The distance from the end point of the barrier to the representative point of the management unit. This is a spatial attenuation scale used to control how quickly the influence decays with distance. The preferred value for the distance factor is between 50 and 300 meters. This is because end-bypass pollution is usually most significant within a range of tens to hundreds of meters near the end. Taking this range allows the near-end management unit to receive a significant weight while the far-end unit naturally receives a reduced weight. The reason for using the exponential decay form is that it can continuously and monotonically reflect the trend of the effective influence intensity caused by diffusion dilution and turbulent mixing decreasing with increasing propagation distance, and avoids discontinuous judgment caused by distance thresholds, thereby providing a stable and interpretable distance factor for subsequent calculation of achievable intensity in the map.

[0023] The unit wind direction is determined based on the wind direction data. The dot product of the unit wind direction and the unit direction vector of the representative point of the management unit from the end point of the barrier is calculated. The dot product with a value less than zero is truncated to zero to obtain the direction factor. The product of the distance attenuation factor and the direction factor is taken as the single-point influence intensity. When there are multiple barrier end points, the maximum value of the single-point influence intensity is taken as the spectral reachability intensity of the management unit. Specifically, the direction factor characterizes the degree of symmetry between the wind direction and the end bypass path. It reflects whether the incoming wind direction pushes pollutants released at the end towards a specific management unit. When the wind direction points towards the management unit, a larger direction factor indicates that the pollution is more easily transported along that direction and exposed in that unit. When the wind direction moves away from the management unit, the direction factor is truncated to zero, indicating that the direct contribution of the end bypass to the unit under that wind direction is negligible. The single-point influence intensity characterizes the overall strength of the effect of a barrier end point on a specific management unit. It is determined by both distance attenuation and the direction factor. Distance attenuation reflects the dilution and diffusion of pollution during propagation. The impact caused by mixing weakens as spatial separation increases. The directional factor reflects accessibility driven by wind direction, thus enabling the single-point impact intensity to simultaneously describe the objective law that the impact is strong when the end is close and facing downwind, and weak when it is far away or facing upwind. The map accessibility intensity is used to characterize the maximum extent to which a management unit can be affected by any barrier end bypass channel under the current wind direction conditions. It takes the maximum value among the single-point impact intensities of multiple barrier end points to represent the dominant end source most likely to form end bypass pollution, so that the accessibility evaluation of the management unit focuses on the strongest bypass path and provides an interpretable end-driven term for subsequent governance priority calculation.

[0024] In detail, the wind direction data is converted into a two-dimensional wind direction vector and normalized to obtain the unit wind direction. To ensure consistency with the coordinate reference of the barrier geometry data, the coordinate axis of the wind direction vector is consistent with the plane coordinate axis of the management unit and the barrier end point. The unit wind direction is calculated by dividing each component of the wind direction vector by its modulus. After obtaining the representative point of the management unit, a direction vector is constructed for each barrier end point pointing from the end point to the representative point, and this direction vector is normalized to obtain the unit direction vector. Then, the inner product of the unit wind direction and the unit direction vector is calculated, and the inner product is used as a measure of wind direction unidirectionality. The formula for calculating the inner product value is as follows: In the formula, The inner product value, For unit wind direction, The unit direction vector pointing from the barrier end point to the representative point of the management unit is represented by the inner product. The reason for using the inner product is that it describes the cosine value of the angle between the two directions, which can continuously reflect the downwind degree and take positive when downwind and negative when upwind. In order to ensure that upwind conditions do not have a positive contribution to the management unit by end bypass, the inner product with a value less than zero is truncated to zero to obtain the direction factor, and only the reachability contribution when the wind direction is towards the management unit is retained. After obtaining the distance attenuation factor, the distance attenuation factor is multiplied by the direction factor to obtain the single-point influence intensity of the barrier end point on the management unit. The reason for using the product form is that distance and downwind reachability are indispensable. If either term is zero, it means that the influence of the end point on the management unit is negligible. When there are multiple barrier end points, the single-point influence intensity corresponding to each end point is calculated for the same management unit, and the maximum value is taken as the spectral reachability intensity of the management unit. Taking the maximum value is because end bypass pollution is usually dominated by the strongest bypass path at the same time. Using the maximum value can focus the spectral reachability intensity on the end source that is most likely to have an impact and provide a stable and interpretable end reachability input for subsequent governance priority calculation.

[0025] S3. Determine the unit wind direction based on wind direction data, calculate the end bypass potential based on traffic flow, barrier geometry data, and the components of the unit wind direction in the tangential and normal directions of the barrier, and generate the pollution corridor. In embodiments of the present invention, a unit wind direction is determined based on wind direction data, and an end bypass potential is calculated based on traffic flow, barrier geometry data, and the components of the unit wind direction in the tangential and normal directions of the barrier, and a pollution corridor is generated, including: Emission intensity proxy values ​​are constructed based on traffic flow. The ratio of the absolute value of the unit wind direction in the tangential component of the barrier to the absolute value of the unit wind direction in the normal component of the barrier is used as the wind direction factor. Calculate the ratio of the end notch width to the barrier height, and construct the notch influence factor based on this ratio; Specifically, the emission intensity surrogate value is a quantitative measure used to characterize the scale of air pollutant release from road traffic per unit time. Based on traffic flow, the surrogate value increases with the number of vehicles passing through, thus reflecting the potential emission source intensity level of the road segment in the current period and providing a calculable source intensity input for end bypass potential calculation. The wind direction factor is a quantitative measure used to characterize the strength of the guiding conditions between the incoming wind direction and the barrier geometry. It is composed of the relative magnitudes of the tangential and normal components of the wind direction per unit distance from the barrier. The wind direction factor is larger when the wind component along the barrier direction is more dominant and the normal ventilation component is relatively weaker, thus corresponding to the situation where pollution is more easily transported laterally along the barrier and bypasses at the end. The gap influence factor is a quantitative measure used to characterize the geometric amplification effect of the end gap relative to the barrier height. It is constructed by the ratio of the end gap width to the barrier height. The factor is larger when the gap is wider or the barrier is lower, thus reflecting the trend that the end geometric discontinuity provides a larger channel cross section for pollution bypass and enhances the intensity of end bypass pollution formation.

[0026] Specifically, traffic flow is defined as the ratio of the number of vehicles passing through a specified road section within a set statistical time window to the duration of the time window. The statistical time window is preferably 30 seconds to 5 minutes, and more preferably 1 minute, to reduce the disturbance to the calculation caused by instantaneous traffic flow fluctuations while maintaining the source strength response sensitivity. The emission intensity proxy value is used to characterize the relative scale of pollutant release from road traffic during the current period. The emission intensity proxy value preferably uses the traffic flow itself as the source strength proxy. The emission intensity proxy value can be expressed as E=Q, where E is the emission intensity proxy value and Q is the traffic flow. This form is used because, under the same road segment, changes in vehicle throughput intensity are the main contributor to changes in emission source strength. The wind direction factor is used to characterize the lateral guidance conditions of a unit wind direction relative to the barrier's geometric direction. The unit wind direction obtained by converting wind direction data is multiplied by the barrier's local tangential and normal unit vectors to obtain the tangential and normal components. Their absolute values ​​are taken to retain only the component magnitude. The ratio of the absolute value of the tangential component to the absolute value of the normal component is then used as the wind direction factor. The formula for calculating the wind direction factor is: In the formula, For wind direction factor, This represents the component of the unit wind direction along the tangential direction of the barrier. The wind direction factor represents the component of the wind direction in the normal direction of the barrier. This ratio is used because when the tangential component is relatively larger and the normal component is relatively smaller, it is easier to form conditions for lateral transport along the barrier and bypass at the end. The wind direction factor increases accordingly to reflect this enhanced guiding tendency.

[0027] The notch impact factor is used to quantify the geometric channel amplification effect of the end notch relative to the barrier height. It is constructed by calculating the ratio of the end notch width to the barrier height. The formula for calculating the notch impact factor is as follows: In the formula, As the gap impact factor, The width of the end notch. For the height of the barrier, The gap influence coefficient is used to adjust the degree to which the gap ratio amplifies the bypass. The value is set to 0.5 to 3, with 1 being preferred. The basis for this value is that the larger the gap width is relative to the height, the larger the effective cross section that can be bypassed by pollution and the more significant the bypass. Using a linear gain form can keep the calculation simple and make the gap influence factor close to one when there is no gap or the gap is extremely small. This ensures that the emission intensity proxy value, wind direction factor and gap influence factor are consistent as interpretable inputs for subsequent end bypass potential calculations.

[0028] Calculate the product of emission intensity proxy value, wind direction factor, and gap influence factor, and divide by barrier height to obtain end bypass potential; Calculate the product of barrier height and wind direction factor, and scale the product based on a set length scaling factor to obtain the length of the pollution corridor; The width of the contaminated corridor is obtained by scaling the barrier height based on a set width scaling factor. Specifically, the end bypass potential is a comprehensive indicator used to characterize the strength of bypass at the end of a barrier, forming a local high-exposure zone. It reflects the bypass driving force under the combined effects of road traffic emission source strength, incoming wind guidance conditions, and end geometric channel conditions. Increased traffic flow leads to a greater amount of pollutants available for bypass release, thus increasing this indicator. When the component of the incoming flow along the barrier direction is relatively stronger and the normal ventilation component is relatively weaker, pollutants are more easily transported laterally along the barrier and overflow at the end, further increasing this indicator. A more significant end gap relative to the barrier height results in a more sufficient bypass channel, also pushing up this indicator. Simultaneously, the barrier... Normalizing the barrier height for this indicator can reflect the inhibitory effect of the barrier height on bypass. The pollution corridor is a spatial influence zone inferred based on the end bypass potential and wind guidance conditions. It is used to describe the range that end bypass pollution may cover in the near-surface layer on the receiver side. It extends outward along the unit wind direction from the end of the barrier and has a relatively limited lateral diffusion width. Its length characterizes the sustainable propagation scale of the bypass influence before it decays with distance, and its width characterizes the lateral diffusion scale of the high-concentration zone near the ground. This provides clear spatial constraints for subsequent calculation of the membership strength of sampling points and the priority ranking of remediation.

[0029] Specifically, the emission intensity surrogate value, wind direction factor, and gap influence factor are combined as synchronous inputs within the same statistical time window for calculation. The emission intensity surrogate value characterizes the traffic emission source intensity level per unit time, the wind direction factor characterizes the strength of lateral guidance conditions per unit wind direction relative to the barrier geometry, and the gap influence factor characterizes the geometric channel amplification effect of the end gap relative to the barrier height. To ensure that the end bypass potential increases simultaneously with increasing source intensity, enhanced guidance, and gap amplification, and to reflect the inhibitory effect of barrier height on end bypass, the emission intensity surrogate value is multiplied by the wind direction factor and the gap influence factor, and then normalized by the barrier height to obtain the end bypass potential. The formula for calculating the end bypass potential is as follows: In the formula, For end bypass potential, As a proxy value for emission intensity, For wind direction factor, As the gap impact factor, This refers to the barrier height.

[0030] The length of the pollution corridor is used to characterize the outward propagation scale of end-bypass pollution under dominant wind conditions. To ensure that the length varies synchronously with the barrier size and lateral guidance, the product of the barrier height and the wind direction factor is used as the base scale and scaled based on a set length scaling factor to obtain the length of the pollution corridor. The formula for calculating the length of the pollution corridor is: In the formula, For the length of the polluted corridor, For the height of the barrier, This is the length scaling factor. The values ​​range from one to ten, with four being preferred. The basis for these values ​​is that end bypass pollution is usually most significant on an engineering scale in the range of tens to hundreds of meters. Combining the common barrier height and wind direction factor ranges can ensure that the length falls within this reasonable range and maintains sensitivity to wind direction changes.

[0031] The width of the pollution corridor is used to characterize the lateral diffusion scale of the high-concentration zone close to the ground. To maintain consistency between the width and the barrier scale and to avoid introducing additional difficult-to-obtain parameters, the barrier height is scaled according to a set width scaling factor to obtain the width of the pollution corridor. The key calculation can be expressed as follows: In the formula, To contaminate the width of the corridor, For the height of the barrier, This is the width scaling factor. The value is taken as 0.5 to 2, with a preference for 1. The basis for this value is that the width of the ground-level bypass zone is usually on the same order of magnitude as or slightly smaller than the barrier scale. This range can cover two typical scenarios: narrow corridors and relatively diffusion corridors. This allows the end bypass potential, the length of the pollution corridor, and the width of the pollution corridor to form interpretable calculation results that can be directly used for subsequent membership strength calculations.

[0032] S4. Calculate the membership strength of each sampling point within the management unit relative to the pollution corridor. Based on the basic confidence level and membership strength, the standardized concentration is weighted and fused to obtain the fused concentration. In an embodiment of the present invention, the membership strength of each sampling point within the management unit relative to the pollution corridor is calculated. Based on the basic confidence level and membership strength, the standardized concentration is weighted and fused to obtain the fused concentration, including: The longitudinal projection distance of each sampling point within the calculation management unit relative to the barrier end point along the wind direction and the lateral projection distance perpendicular to the wind direction are calculated. When the longitudinal projection distance is greater than zero and less than the length of the contaminated corridor, an attenuation function value is constructed based on the transverse projection distance and the width of the contaminated corridor, and used as the membership strength; otherwise, the membership strength is set to zero. Specifically, membership strength is a numerical measure used to quantify the degree to which a sampling point is within the pollution corridor. It is defined by taking the end point of the barrier as the starting point and combining the unit wind direction to define the longitudinal position of the sampling point along the wind direction and the lateral deviation in the vertical wind direction. When the longitudinal projection distance of the sampling point falls within the range of zero to the length of the pollution corridor, the membership strength decreases as the lateral projection distance increases relative to the width of the pollution corridor. It is used to characterize that the closer the sampling point is to the center line of the corridor, the more likely it is to be dominated by the end bypass pollution, and the further it is from the center line, the weaker the influence. When the longitudinal projection distance of the sampling point is not within the range of zero to the length of the pollution corridor, the membership strength is zero, which is used to clearly exclude areas outside the corridor. Thus, the membership strength can be used as a continuous determination result of whether the sampling point belongs to the pollution corridor, and also as a weighting factor to distinguish the contribution inside and outside the corridor in the subsequent concentration weighted fusion and treatment priority calculation.

[0033] Specifically, the planar coordinates of the barrier end point and each sampling point are unified to the same coordinate system. For each sampling point, a displacement vector is constructed from the barrier end point to that sampling point, and the unit wind direction is used as the projection reference direction. The longitudinal projection distance is represented by the projection length of the displacement vector in the unit wind direction. The formula for calculating the longitudinal projection distance is as follows: In the formula, This represents the longitudinal projection distance along the wind direction. Let be the displacement vector from the end point of the barrier to the sampling point. For unit wind direction, the dot product directly gives the effective propagation distance of displacement in the wind direction, which can correspond to the propagation scale of end bypass pollution extending outward with the wind direction; The lateral projection distance is used to characterize the degree of lateral deviation of the sampling point relative to the corridor centerline. The displacement vector is decomposed into components orthogonal to the unit wind direction, and their magnitudes are taken as the lateral projection distance. The formula for calculating the lateral projection distance is: In the formula, This represents the lateral projection distance perpendicular to the wind direction. Let be the displacement vector from the end point of the barrier to the sampling point. This represents the longitudinal projection distance along the wind direction. The component with unit wind direction, after removing the wind direction component, precisely describes the lateral deviation, which is convenient for controlling the attenuation range of the membership intensity using the width of the pollution corridor.

[0034] Specifically, after obtaining the longitudinal projection distance, the longitudinal projection distance and the length of the pollution corridor are used for interval determination. When the longitudinal projection distance is greater than zero and less than the length of the pollution corridor, the sampling point is considered to be in the potential influence zone of the pollution corridor. Based on the lateral projection distance and the width of the pollution corridor, an attenuation function value is constructed as the membership strength. An exponential attenuation form that decreases with the square of the lateral projection distance is preferred to reflect the continuous change where the influence is strongest near the corridor centerline and weaker with greater deviation. The attenuation function is as follows: In the formula, For membership strength, To contaminate the width of the corridor, The lateral projection distance is the vertical wind direction. The greater the lateral deviation, the weaker the dominant contribution of the end bypass pollution tongue to the sampling point and the more smoothly it should decay. When the longitudinal projection distance does not meet the requirement of being greater than zero and less than the length of the pollution corridor, the membership strength is set to zero to explicitly exclude the contribution of sampling points located outside the corridor's forward range to the corridor contribution in the subsequent fusion calculation.

[0035] The basic confidence level is corrected based on the membership strength and the preset corridor enhancement coefficient to obtain the corrected weight. The standardized concentration is then weighted and averaged according to the corrected weight to obtain the fusion concentration. Specifically, fused concentration refers to a single concentration characterization obtained by aggregating the standardized concentrations of multiple concentration data sources at the same sampling point according to the corrected weights. It is used to form a consistent concentration input when there are differences in range, noise level, and spatial representativeness among multi-source observations. The corrected weights are jointly determined by the basic reliability and membership strength, so that the concentration data sources with higher observation stability contribute more to the fusion results. At the same time, the information of sampling points located in the pollution corridor and closer to the dominant influence range of end-bypass pollution is enhanced during fusion. Thus, the fused concentration can reflect the common trend of multi-source data and highlight the characteristics of local high exposure zones caused by end-bypass, and serve as a direct concentration basis for subsequent calculation of the governance priority of the management unit.

[0036] Specifically, the baseline confidence level from different concentration data sources at each sampling point is used as the initial weight input for that concentration data source at that sampling point. The membership strength of the same sampling point is used as the quantitative result of the consistency between that sampling point and the pollution corridor. The greater the membership strength, the more the sampling point is located within the dominant influence range of the end bypass pollution tongue. To give the information within the corridor a greater influence during fusion, the corridor enhancement coefficient is set as an amplification factor for the weights within the corridor and works together with the membership strength to form a weight correction term. The corridor enhancement coefficient is preferably set to one to three. Its value is based on the premise of not suppressing the background information outside the corridor, so as to increase the weight of the central region of the corridor relative to the baseline confidence level by one to several times to highlight the spatial mechanism of end bypass pollution. The corrected weight is calculated by multiplying the baseline confidence level by the corridor enhancement term. The formula for calculating the corrected weight is as follows: In the formula, The corrected weights, To establish the basic credibility of this concentration data source, For corridor enhancement coefficient, The membership strength of the sampling point is used because when the sampling point is outside the corridor, the membership strength is zero, thus the weight degenerates to the basic confidence level without changing the original reliability ranking. As the sampling point gradually approaches the center of the corridor, the membership strength increases, causing the weight to be smoothly amplified proportionally, and the amplification is controllable by the corridor enhancement coefficient. After obtaining the corrected weights of each concentration data source at the sampling point, the corresponding standardized concentrations are weighted and averaged according to the weights to obtain the fused concentration. The formula for calculating the fused concentration is: In the formula, The fusion concentration at this sampling point. The corrected weight of the i-th concentration data source at this sampling point. The standardized concentration of the i-th concentration data source at this sampling point is obtained by using a weighted average. This allows the fused concentration to form a single usable value among multi-source observations and should follow the principle that the higher the reliability, the greater the weight. At the same time, the normalization of the denominator ensures that changes in the overall scale of the weights will not cause unbounded amplification of the fused concentration. This ensures that the fused concentration remains consistent between the corridor mechanism's emphasis and the multi-source reliability constraints and can be directly used for subsequent governance priority calculations.

[0037] S5. Calculate the governance priority of each management unit based on end bypass potential, map reachability, fusion concentration, and membership strength; In embodiments of the present invention, the governance priority of each management unit is calculated based on end bypass potential, map reachability, fusion concentration, and membership strength, including: For all sampling points within the management unit, calculate the product of fusion concentration and membership strength, and sum the products within the management unit to obtain the total exposure of the unit; Multiply the end bypass potential, the spectral reachability, and the total exposed unit by the total exposed unit to obtain the governance priority of the management unit; Specifically, the total exposure of a unit refers to the comprehensive amount obtained by summing the products of the fused concentration, membership strength, and sensitivity weight of all sampling points within the same management unit. It is used to aggregate the pollution levels and pollution corridor impact at different locations within the management unit, so that sampling points with high concentrations and close to sensitive receptors in the corridor contribute more to the total, thus forming a quantitative result that can represent the overall exposure burden of the management unit. The governance priority is an indicator used to rank the governance resources of multiple management units. It is obtained by multiplying the end bypass potential, the spectral reachability, and the total exposure of the unit. It is used to simultaneously reflect the driving force of end bypass pollution, the possibility of end impact reaching the management unit under the current wind direction, and the actual exposure burden within the management unit. When the end bypass potential is stronger, the spectral reachability is higher, and the total exposure of the unit is larger, the governance priority increases accordingly, thus providing a direct ranking basis for work order selection and execution order generation under budget constraints.

[0038] Specifically, after calculating the fusion concentration and membership strength for each sampling point, for each management unit, all sampling points within the same statistical time window and spatially within the boundary of that management unit are selected. The fusion concentration of each sampling point is multiplied by its membership strength to obtain the local exposure of that sampling point within the current time window. The local exposures of all sampling points within the same management unit are summed sequentially according to their sampling point numbers to obtain the total unit exposure of that management unit within that time window. After obtaining the total unit exposure of each management unit, the end bypass potential and spectral reachability intensity corresponding to that management unit are used as the end driving factor and reachability factor of that management unit. By combining the end bypass potential, the reachability intensity of the spectrum, and the total exposure of the unit in a product form, the governance priority of the management unit is calculated. Since a larger end bypass potential means that the end release and diversion conditions are more conducive to the formation of a bypass pollution tongue, a larger reachability intensity of the spectrum means that the management unit is more on the dominant influence path of the end bypass, and a larger total exposure of the unit means that the overall exposure burden inside the management unit is higher, the product of the three factors increases with the increase of any one factor. Thus, the governance priority adaptively integrates traffic source strength, wind field structure, end geometry conditions, and receptor exposure level into a single ranking index, providing a direct and interpretable quantitative basis for subsequent work order selection and execution sequence arrangement under budget constraints.

[0039] S6. Under budget constraints, select the work order type for the management unit based on governance priorities; In an embodiment of the present invention, under budget constraints, selecting the work order type for the management unit based on governance priority includes: Set up a set of work order types for each management unit and configure the cost, input quantity, and input limit for each work order type; Based on the ratio of governance priority to input amount relative to input limit, determine the work order benefits of each work order type for the management unit; Under budget constraints, work order types are selected in descending order of the ratio of work order revenue to configuration cost; Specifically, when setting up a set of work order types for each management unit and selecting work order types under budget constraints, the management unit is used as the smallest object for dispatching and resource allocation. A set of work order types is pre-maintained for each management unit. The set of work order types is used to describe the categories of executable governance actions and corresponds one-to-one with the actual operation and maintenance process. At the same time, cost, input quantity, and input limit are configured for each work order type. The configuration cost is the resource consumption of executing the work order type in the management unit and is recorded with a unified measurement caliber. The input quantity is the number of resources planned to be invested in the management unit for the work order type. The input limit is the maximum number of resources that can be effectively invested in the management unit for the work order type. The optimal value of the input limit can be obtained from the saturation point statistics of historical work orders or determined by on-site operation capacity constraints, so that when the input quantity exceeds the input limit, no proportional benefit is generated, thereby avoiding excessive investment in a single management unit and resulting in resource waste.

[0040] Specifically, after configuration, the work order revenue is calculated for each management unit and each work order type in its work order type set. Governance priority is used as the revenue benchmark for that management unit, and the ratio of input to the input limit is used as the resource utilization factor. When the input is less than the input limit, the resource utilization factor increases linearly with the input; when the input is not less than the input limit, the resource utilization factor takes a value of one to indicate that a saturation point has been reached. The work order revenue is obtained by multiplying the governance priority by the resource utilization factor, ensuring that the higher the governance priority and the closer the input is to the input limit, the greater the work order revenue. This allows for a unified mapping of risk level and investability to comparable revenue levels, all within budget constraints. When selecting, the total budget is set as the upper limit of resources available for this scheduling. The ratio of work order benefit to configuration cost is calculated for all management units and all work order types as the unit cost benefit index. Candidate queues are generated by sorting them from largest to smallest according to this index. Work order types are tried to be selected in turn along the candidate queue and their configuration costs are accumulated. When the accumulated cost does not exceed the total budget, the work order type is marked as selected and its corresponding management unit and work order type are written into the work order list. When the accumulated cost is about to exceed the total budget, the candidate is skipped and the next candidate is checked until the candidate queue is traversed or the budget is exhausted. Thus, under the condition of budget constraint, the work order type with higher unit cost benefit is selected first to form an executable dispatch result.

[0041] like Figure 2 The diagram shown is a functional block diagram of an environmental intelligent management system based on multi-source data fusion provided in an embodiment of the present invention.

[0042] In this embodiment, the functions of each module / unit are as follows: The data preprocessing module is used to collect wind direction data, traffic flow, barrier geometry data, and concentration data from concentration data sources. It calculates the basic confidence level of each concentration data source and standardizes the concentration data to obtain the basic confidence level and standardized concentration. The map reachability module is used to calculate the map reachability intensity of the management unit based on barrier geometry data, wind direction data, and management unit. The bypass corridor module is used to determine the unit wind direction based on wind direction data, calculate the end bypass potential based on traffic flow, barrier geometry data, and the components of the unit wind direction in the tangential and normal directions of the barrier, and generate pollution corridors. The enhanced fusion module is used to calculate the membership strength of each sampling point within the management unit relative to the pollution corridor. Based on the basic confidence level and membership strength, the standardized concentration is weighted and fused to obtain the fused concentration. The priority module is used to calculate the governance priority of each management unit based on the end bypass potential, map reachability, fusion concentration, and membership strength. The work order scheduling module is used to select the work order type for the management unit based on governance priority under budget constraints.

[0043] like Figure 3 As shown in the figure, this diagram illustrates the spatial relationship between the pollution tongue formed at the end of a noise barrier and its pollution corridor under the influence of the prevailing wind direction. A noise barrier is set up on one side of the road in the figure, and there is a gap at the end of the barrier. The width of the gap is used to characterize the geometric scale of the end opening. The prevailing wind direction arrow indicates the direction of the incoming wind, and the tangential component arrow indicates the component of the prevailing wind direction along the direction of the barrier. The end point is the end reference position at the geometric termination of the barrier. Driven by the tangential component, pollutants are transported laterally along the barrier and escape around the end, forming a pollution corridor extending outward from the end point on the receiver side. The length of the pollution corridor is defined along the prevailing wind direction, and the width of the pollution corridor is defined along the direction perpendicular to the length. The corridor area is filled with cross-sections to indicate its possible coverage area. Sampling point A is located inside the pollution corridor and corresponds to a higher membership intensity, while sampling points B and C are located outside the pollution corridor and correspond to a lower membership intensity. This is used to explain the basis for calculating the membership intensity of sampling points based on the length and width of the corridor in the end bypass pollution scenario, and for carrying out multi-source concentration fusion and governance decisions accordingly.

[0044] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An intelligent environmental management method based on multi-source data fusion, characterized in that, include: S1. Collect wind direction data, traffic flow, barrier geometry data, and concentration data from concentration data sources. Calculate the basic confidence level of each concentration data source and standardize the concentration data to obtain the basic confidence level and standardized concentration. S2. Divide the governance area into management units. Based on the barrier geometry data, wind direction data, and management units, calculate the achievable intensity of the management unit's map. S3. Determine the unit wind direction based on wind direction data, calculate the end bypass potential based on traffic flow, barrier geometry data, and the components of the unit wind direction in the tangential and normal directions of the barrier, and generate the pollution corridor. S4. Calculate the membership strength of each sampling point within the management unit relative to the pollution corridor. Based on the basic confidence level and membership strength, the standardized concentration is weighted and fused to obtain the fused concentration. S5. Calculate the governance priority of each management unit based on end bypass potential, map reachability, fusion concentration, and membership strength; S6. Under budget constraints, select the work order type for the management unit based on governance priorities.

2. The environmental intelligent management method based on multi-source data fusion according to claim 1, characterized in that, The barrier geometry data includes: barrier height, barrier end points, end gap width, and local tangential and normal unit vectors of the barrier.

3. The environmental intelligent management method based on multi-source data fusion according to claim 1, characterized in that, Calculate the baseline confidence level for each concentration data source and standardize the concentration data, including: Within a set time window, the variance of concentration data from each concentration data source is calculated, and the reciprocal of the variance is used as the basic reliability of the concentration data source. Within a set time window, the mean and standard deviation of concentration data from each concentration data source are statistically analyzed. The concentration data is then subtracted from the mean and divided by the standard deviation to obtain the standardized concentration.

4. The environmental intelligent management method based on multi-source data fusion according to claim 2, characterized in that, Based on barrier geometry data, wind direction data, and management units, the spectral reachability of the management units is calculated, including: Determine the representative point of the management unit, wherein the representative point is the geometric center point of the management unit; Calculate the distance from the end point of the barrier to a representative point of the management unit, and construct a distance attenuation factor based on the distance; The unit wind direction is determined based on the wind direction data. The dot product of the unit wind direction and the unit direction vector of the representative point of the management unit from the end point of the barrier is calculated. The dot product with a value less than zero is truncated to zero to obtain the direction factor. The product of the distance attenuation factor and the direction factor is taken as the single-point influence intensity. When there are multiple barrier end points, the maximum value of the single-point influence intensity is taken as the spectral reachability intensity of the management unit.

5. The environmental intelligent management method based on multi-source data fusion according to claim 2, characterized in that, Based on traffic flow, barrier geometry data, and the components of unit wind direction in the tangential and normal directions of the barrier, the end bypass potential is calculated, and a pollution corridor is generated, including: Emission intensity proxy values ​​are constructed based on traffic flow. The ratio of the absolute value of the unit wind direction in the tangential component of the barrier to the absolute value of the unit wind direction in the normal component of the barrier is used as the wind direction factor. Calculate the ratio of the end notch width to the barrier height, and construct the notch influence factor based on this ratio; Calculate the product of emission intensity proxy value, wind direction factor, and gap influence factor, and divide by barrier height to obtain end bypass potential; Calculate the product of barrier height and wind direction factor, and scale the product based on a set length scaling factor to obtain the length of the pollution corridor; The width of the contaminated corridor is obtained by scaling the barrier height based on a set width scaling factor.

6. The environmental intelligent management method based on multi-source data fusion according to claim 5, characterized in that, The membership strength of each sampling point within the management unit relative to the pollution corridor is calculated. Based on the baseline confidence level and membership strength, the standardized concentrations are weighted and fused to obtain the fused concentration, which includes: The longitudinal projection distance of each sampling point within the calculation management unit relative to the barrier end point along the wind direction and the lateral projection distance perpendicular to the wind direction are calculated. If the longitudinal projection distance is greater than zero and less than the length of the contaminated corridor, then an attenuation function value is constructed based on the transverse projection distance and the width of the contaminated corridor, and used as the membership strength; otherwise, the membership strength is set to zero. The basic credibility is corrected based on the membership strength and the preset corridor enhancement coefficient to obtain the corrected weight. The standardized concentration is then weighted and averaged according to the corrected weight to obtain the fusion concentration.

7. The environmental intelligent management method based on multi-source data fusion according to claim 1, characterized in that, The governance priority of each management unit is calculated based on end bypass potential, map reachability, fusion concentration, and membership strength, including: For all sampling points within the management unit, calculate the product of fusion concentration and membership strength, and sum the products within the management unit to obtain the total exposure of the unit; The governance priority of the management unit is obtained by multiplying the end bypass potential, the spectral reachability intensity, and the total unit exposure.

8. The environmental intelligent management method based on multi-source data fusion according to claim 1, characterized in that, Under budget constraints, select work order types for management units based on governance priorities, including: Set up a set of work order types for each management unit and configure the cost, input quantity, and input limit for each work order type; Based on the ratio of governance priority to input amount relative to input limit, determine the work order benefits of each work order type for the management unit; Under budget constraints, work order types are selected in descending order of the ratio of work order revenue to configuration cost.

9. An intelligent environmental management system based on multi-source data fusion, characterized in that, The system includes: The data preprocessing module is used to collect wind direction data, traffic flow, barrier geometry data, and concentration data from concentration data sources. It calculates the basic confidence level of each concentration data source and standardizes the concentration data to obtain the basic confidence level and standardized concentration. The map reachability module is used to divide the governance area into management units. Based on the barrier geometry data, wind direction data, and management units, it calculates the map reachability intensity of the management units. The bypass corridor module is used to determine the unit wind direction based on wind direction data, calculate the end bypass potential based on traffic flow, barrier geometry data, and the components of the unit wind direction in the tangential and normal directions of the barrier, and generate pollution corridors. The enhanced fusion module is used to calculate the membership strength of each sampling point within the management unit relative to the pollution corridor. Based on the basic confidence level and membership strength, the standardized concentration is weighted and fused to obtain the fused concentration. The priority module is used to calculate the governance priority of each management unit based on the end bypass potential, map reachability, fusion concentration, and membership strength. The work order scheduling module is used to select the work order type for the management unit based on governance priority under budget constraints.

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