Communication-tower-based atmospheric fine particulate matter distributed link monitoring method and system

Abstract

This invention relates to a distributed link monitoring method and system for atmospheric fine particulate matter based on communication towers, belonging to the field of atmospheric environmental monitoring technology. The method involves node selection and deployment within a target area using communication towers, and the construction of laser links. Dual-wavelength lasers at the transmitting end are modulated and emitted in phase and frequency, and optically shaped to form a circular beam with a specific large divergence angle. The receiving end then performs anti-shake reception and extracts the effective amplitude of the dual-wavelength optical signal. The dynamic atmospheric extinction coefficient is then inverted based on the Beer-Lambert law. Dual-wavelength physical defogging and humidity correction are then used to distinguish between coarse and fine particulate matter and correct for hygroscopic growth of particulate matter. Finally, the mass concentration of atmospheric particulate matter is obtained through conversion using the mass extinction efficiency coefficient. This invention, through innovative large divergence angle anti-shake laser link design and dual-wavelength physical defogging and humidity correction technology, achieves low-cost, high spatial resolution, and stable all-weather atmospheric monitoring.

Description

Technical Field

[0001] This invention belongs to the field of atmospheric environment monitoring technology, and relates to a distributed link monitoring method and system for atmospheric fine particulate matter based on communication towers. In particular, it relates to a system and method for deeply reusing existing communication tower infrastructure to construct a large divergence angle laser detection link network, thereby realizing distributed, high spatiotemporal resolution calculation of atmospheric fine particulate matter (PM2.5) concentration field in urban areas. Background Technology

[0002] Currently, the monitoring of fine particulate matter (PM2.5) in the atmosphere mainly relies on the following types of technical methods: 1. National Standard Monitoring Stations: These stations typically employ the TEOM (Temperature Erosion Oscillation) method or the β-ray attenuation method, providing high-precision, legally verifiable monitoring data. However, their equipment and operation / maintenance costs are exorbitant (hundreds of thousands to millions of RMB per station), resulting in extremely sparse station layouts, with distances between stations within cities often exceeding 5 kilometers. This sparse layout fails to effectively capture and monitor the spatiotemporal variations of microscale pollution and sudden pollution events on complex urban underlying surfaces (such as streets, industrial parks, and residential areas).

[0003] 2. Low-cost micro-sensor networks: Micro-sensors based on the principle of laser scattering, which have emerged in recent years, are widely used in grid-based deployments due to their small size and low cost (hundreds to thousands of yuan per unit). However, their core defects are: (1) The measurement principle is easily affected by the relative humidity of the atmosphere, and the value often "overshoots" under high humidity, resulting in poor data reliability; (2) The single-point measurement value only represents the air quality of a very small area around the sensor, which is seriously insufficient in spatial representativeness and is easily affected by local and instantaneous pollution (such as dust from passing vehicles), making it difficult to reflect the overall pollution level of the area.

[0004] 3. LiDAR: LiDAR can scan the atmosphere vertically or horizontally to obtain information on the profile distribution of pollutants. However, its equipment cost is extremely high (usually in the millions of yuan), and it has a near-field detection blind zone (usually tens to hundreds of meters), making it difficult to effectively cover the near-surface layer most closely related to human activities and respiratory health.

[0005] Furthermore, existing open-circuit optical telemetry technologies, such as the OTM 10 protocol recommended by the U.S. Environmental Protection Agency (EPA), typically employ narrow-beam lasers (divergence angle below 1 mrad) and rely on a sophisticated pan-tilt scanning system to align with a remote reflector. This approach cannot be directly applied to communication towers because, as tall, flexible structures, towers experience slight, continuous swaying and torsion under wind loads (peak angular displacement is typically between 0.1 and 0.5 degrees). Such swaying is fatal to narrow-beam laser links, easily causing the beam to deviate from the receiver and resulting in signal interruption, failing to meet the requirements for long-term, stable, and unattended monitoring.

[0006] Therefore, there is an urgent need for a new monitoring technology that can reuse existing urban infrastructure on a large scale, is low in cost, provides reliable data, has high spatiotemporal resolution, and enables pollution detection and precise measurement. Summary of the Invention

[0007] The purpose of this invention is to provide a distributed link monitoring method and system for atmospheric fine particulate matter based on communication towers. It can make deep reuse of massive existing communication tower resources and construct a low-cost, high spatial resolution, all-weather stable urban-level atmospheric monitoring "sensing and identification network" through innovative large divergence angle anti-shaking laser link design, dual-wavelength physical defogging and humidity correction technology.

[0008] This invention provides the following technical solution: On the one hand, a distributed link monitoring method for atmospheric fine particulate matter based on communication towers is provided, which includes the following steps: S1. Select and deploy nodes based on communication towers within the target area, and construct laser links according to the geometric location of the communication towers and the principle of no obstruction. S2. The dual-wavelength laser at the transmitting end is modulated and emitted in the same frequency and phase. The original beam is shaped into a circular beam with a specific large divergence angle by optical shaping. Then, the receiving end performs anti-shake reception and extracts the amplitude of the effective dual-wavelength optical signal. S3. Based on the Beer-Lambert law, the initial calibration reference voltage is extrapolated using the Langley method, and then dynamic calibration is performed by combining historical clean periods and internal parameters to retrieve the dynamic atmospheric extinction coefficient. S4. Based on the dual-wavelength extinction coefficient, the Onstrom index is calculated to distinguish between coarse and fine particulate matter. The Kasten-Hänel model is used to correct the hygroscopic growth of particulate matter, and the final atmospheric particulate matter mass concentration is obtained by converting the mass extinction efficiency coefficient.

[0009] Furthermore, in step S1, a selection is made within the target area. A series of communication towers of similar height, for each communication tower Sensor nodes are installed on it, and the latitude and longitude coordinates of the sensor nodes are recorded. and altitude ; For each communication tower, a laser detection link is established between each pair of towers. length The results were obtained by calculating the coordinates of each tower.

[0010] Furthermore, in step S2, each laser detection link The transmitter uses a dual-wavelength modulation transmission method, transmitting two wavelengths respectively. and The two laser signals are modulated by a high-frequency square wave with the same frequency and phase through the same constant current driving circuit; the transmitting end uses combined optical elements to shape the original elliptical laser beam into a circular beam with a specific large divergence angle.

[0011] Furthermore, in step S2, the receiving end uses a diameter of of The dual-band photodetector receives the beam shaped by the transmitter, ensuring the physical offset of the receiver at the far end. It is still much smaller than the radius of the light spot formed at the receiving end; the electrical signal after photoelectric conversion at the receiving end is sent to the digital signal processor, which calls the digital lock-in amplification algorithm to process it and obtain the effective optical signal voltage amplitudes of two different wavelengths.

[0012] Furthermore, in step S3, for wavelength Its path integral extinction Calculated by the following formula:

[0013] in, It is the length of the laser detection link. It is the current real-time measurement of the corresponding wavelength. The output amplitude of the lock-in amplifier, It is the system calibration voltage, representing the voltage value that the laser detection link should receive under theoretically completely clean, particulate-free atmospheric conditions.

[0014] Furthermore, step S3 also includes: against Initial calibration is performed by conducting continuous measurements at different times under expected ideal atmospheric conditions to establish a linear relationship. And calculate the initial value based on the established linear regression equation. ; against Dynamic calibration is performed using the following method: Historical data is used to select the maximum signal value during the period considered the cleanest, as the baseline. The reference is periodically corrected; at the same time, internal state parameters, including light source power and detector temperature, are monitored, a drift compensation model is established, and quasi-real-time correction is performed.

[0015] Furthermore, in step S4, fine and coarse particulate matter are intelligently distinguished based on the Onstrom index and Mie scattering theory. The process includes: First, based on the calculated two wavelengths and corresponding extinction coefficient and Calculate the Onstrom index of the link in real time. :

[0016] Set the discrimination threshold It is fine-tuned based on local aerosol characteristics; based on the discrimination threshold The method for distinguishing between fine and coarse particulate matter is as follows: like If the current atmospheric extinction is caused by coarse particulate matter, the data for this period will be marked as invalid pollution data and will not be included in the PM2.5 concentration retrieval. like If the result is negative, it is determined to be typical fine particulate matter pollution, and the process proceeds to the next step of humidity correction and concentration inversion.

[0017] Furthermore, in the humidity correction and concentration inversion process of step S4, it includes: First, the wet extinction coefficient is described using the Katen-Hänel model. With dry extinction coefficient The relationship between the measured wet extinction coefficients Corrected to dry extinction coefficient ,Right now:

[0018] in, Relative humidity is expressed as a decimal. It is the key hygroscopic growth index. It is a dimensionless parameter that quantitatively describes the overall moisture absorption capacity of an aerosol. The higher the value, the stronger the hygroscopicity of the particulate matter, and the faster its extinction capacity increases with humidity. The calculation then uses the real-time relative humidity measured by sensors deployed on the same tower. And it uses a locally calibrated one. value; Finally, the dry extinction coefficient and PM2.5 mass concentration were used to determine the optimal values. The approximate linear relationship between them can be converted using the mass extinction conversion efficiency coefficient:

[0019] in, It is the first The average PM2.5 concentration along the entire path; It is the mass extinction efficiency of PM2.5, which is related to the particle size distribution, morphology, and chemical composition of particulate matter.

[0020] Furthermore, a passive statistical method is used in step S4. Localized calibration of values, utilizing long-term accumulated monitoring data. and The logarithm of the Kasten-Hänel formula is transformed into a linear equation. By performing linear regression fitting on data from different seasons and pollution levels, a localized [system / mechanism] was established. Parameterization scheme.

[0021] On the other hand, a system based on the aforementioned distributed link monitoring method for fine particulate matter in the atmosphere based on communication towers is provided. The system includes multiple sensing nodes deployed on different communication towers, a cloud data processing and control center, and supporting power supply and communication modules. Each sensing node includes a laser emitting unit and a receiving unit. The laser links between multiple sensing nodes are intertwined to form a monitoring grid covering the target area. The sensing nodes are directly installed on the platform or pole of the communication tower and transmit the monitoring data to the cloud center in real time. The system's transmitter uses a specially optically designed laser to actively expand the divergence angle of the emitted laser beam, while the receiver uses a large-area photodetector to ensure that the receiver is always within the effective light spot coverage area. The transmitter simultaneously emits two laser beams with the same modulation but different wavelengths. The aerosol type is distinguished in real time by calculating the ratio of the atmospheric extinction coefficients of the two links. For hazy weather, the temperature and humidity sensors deployed on the same tower are combined with the Kasten-Hänel physical model to correct the hygroscopic growth effect of particulate matter caused by relative humidity, and the extinction coefficient of dry particulate matter is inverted. Finally, the corresponding PM2.5 concentration is calculated.

[0022] The beneficial effects of this invention are as follows: This invention uses optoelectronic modules as the core hardware, resulting in significantly lower equipment costs compared to large optical monitoring equipment such as lidar. The system can deeply reuse existing communication tower sites, power supply, and communication networks, eliminating the need for land acquisition, site construction, power supply, and dedicated network laying, thus greatly reducing initial construction investment. Relying on tower resources, it achieves high-density, blind-spot-free networking with extremely low marginal expansion costs, making it technically feasible for city-scale deployment.

[0023] This invention employs kilometer-level path integration monitoring between towers, which differs from the traditional point-based sensor sampling method that "substitutes the area with a point". It achieves spatial averaging of pollutant concentrations within the path, forming a natural physical spatial filtering effect. This effectively filters out local instantaneous interference noise such as vehicle exhaust and road dust, resulting in more stable monitoring results that more accurately reflect the regional background pollution level and atmospheric transport trends, and significantly improves spatial representativeness.

[0024] This invention employs a fixed grid point-to-point link with a large divergence angle of 3-5 mrad, and the diameter of the optical spot reaches 6-10 meters at a distance of 2 kilometers. It is compatible with the torsion and physical displacement of the tower under wind load of ≤0.2°. It completely solves the problem of optical path interruption caused by the swaying of high-altitude towers from the perspective of optical path structure, and realizes stable monitoring with high connectivity, all-weather operation, no manual alignment required.

[0025] This invention employs a 650nm and matching dual-wavelength optical architecture to calculate the Onstrom index (AE) in real time based on the scattering difference between particulate matter and fog droplets. It utilizes the extinction characteristics of dry haze (α>1) and fog (α≈0) to distinguish them, achieving physical-level fog / haze separation. This replaces the traditional empirical formula correction and addresses the industry pain point of inflated monitoring data in high humidity environments from a mechanistic perspective. The accuracy and reliability of the data reach the national standard comparison level.

[0026] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description

[0027] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 This is a flowchart illustrating the distributed link monitoring method for atmospheric fine particulate matter based on communication towers according to an embodiment of the present invention. Figure 2 This is a schematic diagram of distributed link monitoring based on communication towers according to an embodiment of the present invention. Detailed Implementation

[0028] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0029] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0030] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0031] Please see Figures 1-2 This invention relates to a distributed link monitoring method and system for atmospheric fine particulate matter based on communication towers.

[0032] Example 1 This embodiment first describes a distributed link monitoring method for atmospheric fine particulate matter based on communication towers, such as... Figure 1 As shown, it specifically includes the following steps: Step 1: System Initialization and Topology Construction 1) Node selection and deployment: Within the target area, select four communication towers of similar height (e.g., 30-50 meters), denoted as... High-precision GNSS (such as RTK technology) is used to determine the precise latitude and longitude coordinates of the sensing nodes to be installed on each tower. and altitude .

[0033] 2) Link Planning and Construction: Based on the geometric location between towers and the principle of no obstruction, laser links are constructed. For example, a closed quadrilateral monitoring grid can be constructed ( ) and two diagonal links There are a total of 6 detection links. Each link length Based on the coordinates of each tower, the typical length is set between 0.5 km and 3 km.

[0034] Step 2: Acquisition and Extraction of High Signal-to-Noise Ratio Signals 1) Dual-wavelength modulation transmission: A transmitting unit containing two laser diodes (LDs) is installed on the transmitting tower of each link. The wavelengths are respectively... and Two LDs are modulated with high-frequency square waves of the same frequency and phase using the same high-precision constant current drive circuit. The modulation angular frequency is... (For example, corresponding frequency) This effectively avoids interference from natural light (mainly DC and low-frequency components) and 50Hz power frequency and its harmonics.

[0035] 2) Anti-shake stable receiver and optical design: Optical Shaping: The optical section of the emitting unit employs combined optical elements to precisely shape the original elliptical laser beam into a circular beam with a specific large divergence angle. First, one or more aspherical collimating lenses are used to collimate the beam emitted by the laser diode, correcting spherical aberration and improving light energy utilization. Then, the collimated elliptical beam passes through a pair of anamorphic prisms. By precisely adjusting the relative angle of the prisms, the beam is compressed or expanded along one axis, thus shaping it into a circular beam. Finally, a diverging lens with a specific focal length expands the circular collimated beam to a larger divergence angle. The "macro-divergent" beam.

[0036] Anti-sway principle: For a length The link, the diameter of the light spot formed at the receiving end The receiving unit uses a diameter of 5mm Dual-band photodetector. Even if the top of the tower sways due to wind... Angular offset, the physical offset of the receiver at the far end. It is still much smaller than the beam radius (3m), ensuring that the receiver is always within the beam and signal reception is uninterrupted. This design sacrifices some peak power density in exchange for long-term link stability against the effects of atmospheric turbulence and platform sway.

[0037] Digital Lock-in Amplification and Extraction (DLIA): Due to the system's large divergence angle design, the signal acquired by the receiver detector is very weak and superimposed with strong natural background light and broadband noise. To extract the effective light intensity, the system sends the photoelectric converted electrical signal to a digital signal processor (DSP) and calls the Digital Lock-in Amplification (DLIA) algorithm for processing. The system utilizes the same frequency as the transmitter ( The digital reference signal is used to perform phase-sensitive detection (mixing) on ​​the input signal, which is then passed through an extremely narrow-band phase-locked low-pass filter.

[0038] Ultimately, the module is precisely reconstructed and output. and The effective optical signal voltage amplitudes of the two wavelengths (denoted as respectively) These two pure voltage amplitudes will be directly input into the next stage as core foundational data for dynamic atmospheric extinction inversion.

[0039] The entire DLIA process is equivalent to a center frequency at... A bandpass filter with extremely narrow bandwidth can "lock in" and extract the target signal from an environment with extremely low signal-to-noise ratio. Step 3: Dynamic Atmospheric Extinction Coefficient Inversion 1) Application of Beer-Lambert's Law and Reference Signal Calibration: The extinction of particulate matter in the atmosphere follows Beer-Lambert's Law. For wavelength... Its path integral extinction It can be calculated using the following formula:

[0040] in, It is the precise length of the link (in meters). It is the current real-time measurement of the corresponding wavelength. The output amplitude of the lock-in amplifier, It is the system calibration voltage, representing the voltage value that the link should receive under theoretically completely clean, particulate-free atmospheric conditions (i.e., "zero atmosphere" signal). Precise calibration and dynamic adjustment are crucial for ensuring long-term measurement accuracy, and can be achieved through the following methods: Initial calibration Langley extrapolation: On a clear day with extremely stable, cloudless atmospheric conditions, extrapolation is performed at different times (corresponding to different atmospheric masses). Continuous measurements were performed. Based on... The linear relationship was used to extrapolate the measured straight line to atmospheric mass through linear regression. At that point, its y-intercept is... Thus, the initial value can be accurately calculated. .

[0041] Dynamic calibration: Factors such as instrument aging and lens contamination can lead to... Long-term drift necessitates dynamic calibration. A practical method is to utilize historical data, selecting the maximum signal value during a generally accepted "cleanest" period (such as after rain or strong northerly winds) as the baseline. The reference is periodically corrected. Simultaneously, internal state parameters such as light source power and detector temperature can be monitored to establish a drift compensation model and perform near real-time correction.

[0042] Step 4: Dual-wavelength physical defogging and humidity correction This step is one of the key innovations of this invention. It achieves intelligent identification of aerosol types and physical correction of humidity interference through two core physical models.

[0043] 1) Intelligent Fog / Haze Discrimination: Based on Onstrom Index (AE) and Mie Scattering Theory a) Mathematical form: The system uses the extinction coefficients of the two wavelengths calculated in step three. and Calculate the Onstrom index of the link in real time. :

[0044] b) Physical principles: The value can effectively distinguish between fine particulate matter (haze) and coarse particulate matter (fog), and its physical basis is the Mie scattering theory. This theory states that the extinction efficiency of particulate matter... Its dimensional parameters The function, where (r is the particle radius, (Wavelength).

[0045] For fine particulate matter ( Haze (constituting a type of smog): its particle size With the wavelength used in this invention Comparable, dimensional parameters Falling into the sensitive region of Mie scattering In this area, For wavelength It is highly dependent on wavelength, with shorter wavelengths corresponding to higher extinction efficiency. Therefore, It will be much greater than This leads to the calculated The value is significantly greater than 1 (typically up to 2).

[0046] For coarse particles (fog droplets or raindrops): their particle size Much larger than wavelength At this time, the dimensional parameters great , entering the geometric optics region. In this region, It tends to a constant of 2 that is independent of wavelength. Therefore, and The similar sizes lead to the calculated The value approaches 0.

[0047] c) Application of discrimination: like ( The threshold value (which can be fine-tuned based on local aerosol characteristics) indicates that the current atmospheric extinction is mainly caused by large-diameter fog or raindrops. The system marks the data for this period as "invalid pollution data" and does not include it in PM2.5 concentration retrieval, but it can still output meteorological parameters such as visibility.

[0048] like If the result is negative, it is determined to be typical fine particulate matter (haze) pollution, and the process proceeds to the next step of humidity correction and concentration inversion.

[0049] 2) Correction for particulate matter hygroscopic growth: based on the Kasten-Hänel model a) Physical Basis: For data identified as haze, its hygroscopic growth effect must be considered. PM2.5 in the atmosphere (especially secondary inorganic salts such as sulfates and nitrates) is hydrophilic and absorbs moisture from the air, causing it to "expand." This results in a significant increase in its optical extinction capacity with increasing relative humidity (RH). The Kasten-Hänel model is a classic empirical description of this physical process.

[0050] b) Mathematical form: This model describes the wet extinction coefficient. With dry extinction coefficient The relationship between them:

[0051] in, Relative humidity is expressed as a decimal (0-1). It is the key moisture absorption growth index.

[0052] c) Moisture absorption growth index : Physical meaning: It is a dimensionless parameter that quantitatively describes the overall moisture absorption capacity of aerosols. The higher the value, the stronger the hygroscopicity of the particulate matter, and the faster its extinction capacity increases with humidity.

[0053] Influencing factors and typical values: The value is mainly determined by the chemical composition of the aerosol. For example, marine aerosols (rich in sea salt). The highest values ​​(reaching 0.8-1.1); urban pollution aerosols (a mixture of sulfates, nitrates, and organic matter). The values ​​are moderate (0.2-0.7); while dust aerosols (minerals) The value is extremely low (<0.2).

[0054] d) Application: Inversion of dry extinction coefficient: The goal of this invention is to calculate the concentration of particulate matter itself, therefore the measured wet extinction coefficient needs to be... Corrected to dry extinction coefficient By transforming the above formula, we obtain:

[0055] During calculation, the system retrieves real-time relative humidity (RH) measured by sensors deployed on the same tower and uses a locally calibrated [data / method / applicable data]. value.

[0056] e) Local calibration of values: To ensure correction accuracy, The values ​​need to be locally calibrated. This invention can employ a passive statistical method: utilizing monitoring data accumulated over a long period by the system (…). and (This transforms the Kasten-Hänel formula into a linear equation.) The slope can be obtained by performing linear regression fitting on data from different seasons and pollution levels. Thus establishing localization Parameterization scheme.

[0057] 3) Mass concentration conversion: Finally, the dry extinction coefficient and PM2.5 mass concentration were used to determine the optimal values. The approximate linear relationship between them is converted using the Mass Extinction Efficiency (MEE) coefficient:

[0058] in, It is the first Average PM2.5 concentration along the route (unit: ); PM2.5 mass extinction efficiency (unit: It is also related to the particle size distribution, morphology, and chemical composition of particulate matter. The optimal value needs to be calibrated by deploying a standard PM2.5 analyzer (such as BAM-1020) within the monitoring area for long-term parallel observation and linear regression. Typically, for a wavelength of 650 nm, the MEE value of urban PM2.5 is within... Within the range.

[0059] Example 2 This embodiment provides a system based on the distributed link monitoring method for atmospheric fine particulate matter based on communication towers in Embodiment 1 above. The system includes the following core components: System Composition: This system consists of multiple sensing nodes (including laser transmitting and receiving units) deployed on communication towers, a cloud-based data processing and control center, and supporting power supply and communication modules. The laser links between the multiple sensing nodes are interwoven to form a monitoring grid covering the target area.

[0060] Deep infrastructure reuse architecture: Sensing nodes are directly installed on the platform or pole of the communication tower. For power supply, a DC-DC wide voltage conversion module converts the -48V DC power commonly found in base stations to the operating voltage required by the nodes, achieving power reuse. For data backhaul, monitoring data is transmitted in real-time to the cloud center by reusing the FSU (Field Monitoring Unit) port of the tower base station or utilizing a separate 4G / 5G / NB-IoT wireless communication module.

[0061] Anti-sway, large divergence angle link design: The transmitter uses a specially optically designed laser to actively expand the divergence angle (Full Width at Half Maximum, FWHM) of the emitted laser beam to 3-5 milliradians (mrad). Over a typical link distance of 1-2 kilometers, the laser spot diameter can reach 6-10 meters. The receiver uses a large-area photodetector (e.g., diameter ≥3mm) (such as an InGaAs PIN photodiode) to ensure that even if the tower experiences an angular displacement within ±0.2 degrees, the receiver remains within the effective spot coverage area. This physically eliminates link interruptions caused by tower swaying, guaranteeing long-term signal stability.

[0062] Dual-wavelength haze discrimination and humidity correction: The system simultaneously emits two identically modulated laser beams with significantly different wavelengths, for example, one beam of 650nm visible red light and the other of 1550nm near-infrared light. By calculating the ratio of the atmospheric extinction coefficients of the two links, i.e., the Ångström exponent (AE), aerosol types are distinguished in real time. This method utilizes the Mie scattering theory, specifically the ratio of particle extinction efficiency to particle size and wavelength (size parameter). The system exhibits a strong correlation with the wavelength of visible light. For fine particulate matter such as PM2.5, its particle size is comparable to that of visible light, and its extinction effect on short wavelengths (650nm) is much stronger than that on long wavelengths (1550nm), resulting in an AE value significantly greater than 1. However, for fog droplets or raindrops, their particle size is much larger than two wavelengths, and their extinction effect is not sensitive to wavelength (approaching the geometrical optical limit), resulting in an AE value close to 0. Based on this physical principle, the system can effectively eliminate the interference of dense fog on PM2.5 monitoring. For haze, the system further combines temperature and humidity sensors deployed on the same tower and uses the Kasten-Hänel physical model to correct for the hygroscopic growth effect of particulate matter caused by relative humidity, thus retrieving the extinction coefficient of "dry" particulate matter.

[0063] Specifically, this embodiment also installs transmitting and receiving nodes on two communication towers spaced L apart (e.g., 2000m). The transmitting end uses 650nm (visible red light, sensitive to PM2.5) and 1550nm (near-infrared light, insensitive to PM2.5 but sensitive to fog droplets) lasers. Through aspherical lenses, deformable prism pairs, and diverging lenses, the divergence angle of the emitted beam is kept constant at 3-5mrad. At 2km, the spot diameter can reach [missing value]. The receiving end uses a diameter InGaAsPIN photodiodes ensure the integrity of the tower. Under wind-induced angular displacement, the detector remains within the light spot.

[0064] Because the large divergence angle design dilutes the optical power, the signal reaching the detector is extremely weak and submerged in strong solar background light and dark current noise (signal-to-noise ratio can be as low as...). This embodiment constructs the complete process code from signal attenuation, extreme noise addition, DLIA (digital lock-in amplification) extraction, AE exponential defogging to Kasten-Hänel model dehumidification, to verify the reliability of the present invention.

[0065] Simulation scenario setting: tower spacing Relative humidity (High humidity environment); Actual PM2.5 dry concentration set to (Severe haze); baseband modulation frequency Original signal-to-noise ratio .

[0066] Based on the above simulation design, the following simulation results are obtained in this embodiment: Even if the input photoelectric signal is overwhelmed by random noise with an intensity a hundred times greater ( The DLIA algorithm module still precisely locked onto... The small intensity envelope at a specific frequency point. Subsequently, the algorithm calculates... The system intelligently determined that the current atmospheric attenuation was caused by fine particulate matter haze rather than dense fog, based on a concentration threshold above 0.5, successfully avoiding false alarms about foggy weather. During the concentration inversion phase, due to the high relative humidity... The aerosol underwent dramatic hygroscopic expansion. If directly converted using traditional sensor data, the PM2.5 concentration would reach [a certain value]. (The data is nearly 2.8 times inflated). However, the system of this invention automatically triggers the Kasten-Hänel physical dehumidification model, accurately removing optical water shell artifacts, and the final output PM2.5 concentration is... , and environmental truth ( The relative error is controlled within Within.

[0067] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A communication-tower-based method for monitoring distribution of atmospheric fine particulate matter, the method comprising: The method includes the following steps: S1. Select and deploy nodes based on communication towers within the target area, and construct laser links according to the geometric location of the communication towers and the principle of no obstruction. S2. The dual-wavelength laser at the transmitting end is modulated and emitted in the same frequency and phase. The original beam is shaped into a circular beam with a specific large divergence angle by optical shaping. Then, the receiving end performs anti-shake reception and extracts the amplitude of the effective dual-wavelength optical signal. S3. Based on the Beer-Lambert law, the initial calibration reference voltage is extrapolated using the Langley method, and then dynamic calibration is performed by combining historical clean periods and internal parameters to retrieve the dynamic atmospheric extinction coefficient. S4. Based on the dual-wavelength extinction coefficient, the Onstrom index is calculated to distinguish between coarse and fine particulate matter. The Kasten-Hänel model is used to correct the hygroscopic growth of particulate matter, and the final atmospheric particulate matter mass concentration is obtained by converting the mass extinction efficiency coefficient.

2. The method for distributed link monitoring of atmospheric fine particulate matter based on communication towers according to claim 1, characterized in that: In step S1, selecting a target area Communication towers with similar heights, for each communication tower A sensing node is installed thereon, and the latitude and longitude coordinates of the sensing node are recorded and the altitude ; For each communication tower, a laser detection link is established between each pair of towers. length The results were obtained by calculating the coordinates of each tower.

3. The method for distributed link monitoring of atmospheric fine particulate matter based on communication towers according to claim 1, characterized in that: In step S2, each laser detection link The transmitter uses a dual-wavelength modulation transmission method, transmitting two wavelengths respectively. and The two laser signals are modulated by a high-frequency square wave with the same frequency and phase through the same constant current drive circuit; The transmitter uses a combination of optical elements to shape the original elliptical laser beam into a circular beam with a specific large divergence angle.

4. The method for distributed link monitoring of atmospheric fine particulate matter based on communication towers according to claim 1, characterized in that: In step S2, the receiving end uses a diameter of of The dual-band photodetector receives the beam shaped by the transmitter, ensuring the physical offset of the receiver at the far end. It is still much smaller than the radius of the light spot formed at the receiving end; the electrical signal after photoelectric conversion at the receiving end is sent to the digital signal processor, which calls the digital lock-in amplification algorithm to process it and obtain the effective optical signal voltage amplitudes of two different wavelengths.

5. The method for distributed link monitoring of atmospheric fine particulate matter based on communication towers according to claim 1, characterized in that: In step S3, for wavelength Its path integral extinction Calculated by the following formula: in, It is the length of the laser detection link. It is the current real-time measurement of the corresponding wavelength. The output amplitude of the lock-in amplifier, It is the system calibration voltage, representing the voltage value that the laser detection link should receive under theoretically completely clean, particulate-free atmospheric conditions.

6. The method for distributed link monitoring of atmospheric fine particulate matter based on communication towers according to claim 5, characterized in that: Step S3 also includes: against Initial calibration is performed by conducting continuous measurements at different times under expected ideal atmospheric conditions to establish a linear relationship. And calculate the initial value based on the established linear regression equation. ; against Dynamic calibration is performed using the following method: Historical data is used to select the signal maximum value from the period with the cleanest, most generally accepted data, as the baseline. The reference is periodically corrected; at the same time, internal state parameters, including light source power and detector temperature, are monitored, a drift compensation model is established, and quasi-real-time correction is performed.

7. The method for distributed link monitoring of atmospheric fine particulate matter based on communication towers according to claim 1, characterized in that: In step S4, fine and coarse particulate matter is intelligently distinguished based on the Onstrom index and Mie scattering theory. The process includes: First, based on the calculated two wavelengths and corresponding extinction coefficient and Calculate the Onstrom index of the link in real time. : Set the discrimination threshold It is fine-tuned based on local aerosol characteristics; based on the discrimination threshold The method for distinguishing between fine and coarse particulate matter is as follows: like If the current atmospheric extinction is caused by coarse particulate matter, the data for this period will be marked as invalid pollution data and will not be included in the PM2.5 concentration retrieval. like If the result is negative, it is determined to be typical fine particulate matter pollution, and the process proceeds to the next step of humidity correction and concentration inversion.

8. A distributed link monitoring method for atmospheric fine particulate matter based on communication towers according to claim 7, characterized in that: In the humidity correction and concentration inversion process of step S4, it includes: First, the wet extinction coefficient is described using the Katen-Hänel model. With dry extinction coefficient The relationship between the measured wet extinction coefficients Corrected to dry extinction coefficient ,Right now: in, Relative humidity is expressed as a decimal. It is the key hygroscopic growth index. It is a dimensionless parameter that quantitatively describes the overall moisture absorption capacity of an aerosol. The higher the value, the stronger the hygroscopicity of the particulate matter, and the faster its extinction capacity increases with humidity. The calculation then uses the real-time relative humidity measured by sensors deployed on the same tower. And it uses a locally calibrated one. value; Finally, the dry extinction coefficient and PM2.5 mass concentration were used to determine the optimal values. The approximate linear relationship between them can be converted using the mass extinction conversion efficiency coefficient: in, It is the first The average PM2.5 concentration along the entire path; It is the mass extinction efficiency of PM2.5, which is related to the particle size distribution, morphology, and chemical composition of particulate matter.

9. A distributed link monitoring method for atmospheric fine particulate matter based on communication towers according to claim 8, characterized in that: Step S4 employs a passive statistical method. Localized calibration of values, utilizing long-term accumulated monitoring data. and The logarithm of the Kasten-Hänel formula is transformed into a linear equation. By performing linear regression fitting on data from different seasons and pollution levels, a localized [system / mechanism] was established. Parameterization scheme.

10. A system established according to the distributed link monitoring method for atmospheric fine particulate matter based on communication towers as described in any one of claims 1-9, characterized in that: The system includes multiple sensing nodes deployed on different communication towers, a cloud data processing and control center, and supporting power supply and communication modules. Each sensing node includes a laser emitting unit and a receiving unit. The laser links between multiple sensing nodes are intertwined to form a monitoring grid covering the target area. The sensing nodes are directly installed on the platform or pole of the communication tower and transmit the monitoring data to the cloud center in real time. The system's transmitter uses a specially optically designed laser to actively expand the divergence angle of the emitted laser beam, while the receiver uses a large-area photodetector to ensure that the receiver is always within the effective light spot coverage area. The transmitter simultaneously emits two laser beams with the same modulation but different wavelengths. The aerosol type is distinguished in real time by calculating the ratio of the atmospheric extinction coefficients of the two links. For hazy weather, the temperature and humidity sensors deployed on the same tower are combined with the Kasten-Hänel physical model to correct the hygroscopic growth effect of particulate matter caused by relative humidity, and the extinction coefficient of dry particulate matter is inverted. Finally, the corresponding PM2.5 concentration is calculated.

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