An intelligent polycyclic aromatic hydrocarbon passive sampling monitoring system for individual exposure assessment and source resolution

Abstract

The application discloses an intelligent full-state polycyclic aromatic hydrocarbon (PAHs) passive sampling monitoring system for individual exposure assessment and source analysis, and belongs to the technical field of environmental pollution monitoring. The intelligent full-state PAHs passive sampling monitoring system comprises a smart passive sampling unit to be worn; an environment perception and positioning unit for collecting space-time information and environmental information; a data processing and communication unit for processing, storing and transmitting the data collected by the environment perception and positioning unit; a full-state PAHs analysis unit for laboratory analysis of the collected samples; and a data analysis cloud platform for receiving the data transmitted by the data processing and communication unit, calculating individual exposure doses and performing preliminary analysis of pollution sources. The intelligent full-state PAHs passive sampling monitoring system deeply integrates a standardized full-state passive sampler, multi-parameter environment perception, accurate positioning tracking, wireless data transmission and cloud intelligent analysis, can realize accurate assessment of individual full-period and full-path PAHs exposure, and can quickly provide an intelligent monitoring of preliminary clues of pollution sources.

Description

Technical Field

[0001] This invention belongs to the field of environmental pollution monitoring technology, specifically relating to an intelligent full-state passive sampling and monitoring system for polycyclic aromatic hydrocarbons (PAHs) used for individual exposure assessment and source apportionment. Background Technology

[0002] Polycyclic aromatic hydrocarbons (PAHs) are a class of persistent and toxic pollutants widely present in the atmosphere, primarily originating from the incomplete combustion of fossil fuels and biomass. Because many of their components have been proven to have carcinogenic, teratogenic, and mutagenic effects, human exposure to atmospheric PAHs via the respiratory route has become a significant environmental health risk. Atmospheric PAHs exist in the gaseous phase and are adsorbed onto fine particulate matter (such as PM2.5). 2.5 PAHs exist in both gaseous and particulate forms on the surface, and their gas-particle partitioning behavior is significantly affected by factors such as temperature. Therefore, accurately assessing an individual's exposure dose to all states (i.e., the sum of gaseous and particulate phases) of PAHs in the actual living-working microenvironment and rapidly identifying the main sources of pollution are key prerequisites for implementing precise health risk interventions and pollution source control.

[0003] Currently, monitoring technologies for assessing individual PAH exposure are mainly divided into two categories: active sampling and passive sampling. Active sampling requires a sampling pump and can quantitatively collect two-phase PAHs over a specific time period. However, the equipment is bulky, noisy, and dependent on a power source, severely interfering with the wearer's normal activities. It is not suitable for long-term, continuous individual exposure assessment and is mostly used for fixed-point environmental monitoring. Passive sampling technology, based on Fick's diffusion law, requires no power, is lightweight and quiet, and is suitable for long-term cumulative sampling by individuals, making it the mainstream tool for exposure assessment. However, existing passive sampling technologies and equipment still face the following technical bottlenecks that urgently need to be addressed when applied to accurate assessment and rapid source apportionment of individual full-state PAH exposure: 1. The contradiction between "all-state" synchronous sampling and individual adaptability: To achieve simultaneous sampling of gaseous and particulate PAHs, a passive modification of the active sampling structure using a "filter membrane-adsorbent" series connection is typically employed. However, devices directly applying this structure are often bulky, inconvenient to wear, and lack sufficient consideration for airflow distribution and diffusion balance design in two-phase sampling. When individual dynamic activities cause variations in wind speed and direction, the representativeness and accuracy of "all-state" sampling are difficult to guarantee. Currently, there is a lack of a standardized passive sampling device specifically designed for individual exposure monitoring that is compact, comfortable to wear, and ensures stable and balanced two-phase sampling efficiency.

[0004] 2. Fixed sampling rate leads to large errors in exposure concentration estimation: The amount of pollutants adsorbed by a passive sampler needs to be divided by the sampling rate and sampling time to obtain the environmental concentration. Traditional methods use a single sampling rate calibrated under constant laboratory conditions (fixed wind speed, temperature, and humidity). However, the microenvironment experienced by individuals in real-world activities (such as indoors / outdoors, commuting, and in the office) varies significantly in temperature, humidity, and wind speed. These factors significantly affect the diffusion coefficient of pollutants and the sampling rate. Using a fixed rate for conversion introduces huge errors, leading to inaccurate exposure dose assessment. Current technology lacks a micro-environmental sensing system deeply integrated with individual passive samplers, making it impossible to acquire microenvironmental parameters in real time for dynamically correcting the sampling rate.

[0005] The basic conversion formula (traditional method) is as follows: (1); In the formula: : Environmental concentration of target pollutant ; The mass of pollutants adsorbed by the passive sampler was obtained through laboratory analysis. ; Passive sampling rate under standard conditions (fixed temperature, wind speed, etc.) ; Total sampling time .

[0006] 3. Separation of Exposure Spatiotemporal Trajectory from Pollution Information: Traditional passive samplers are merely "black box" sampling devices, providing only the cumulative total amount of pollutants during the sampling period, completely losing the precise time and spatial location information of the exposure. This makes it impossible to correlate high exposure events with specific geographical locations and activity periods (such as the time spent at traffic intersections or food and beverage clusters), greatly weakening the source tracing value and public health guidance significance of exposure assessments. Although GPS technology is widely used, existing solutions do not integrate it with passive samplers in a low-power design to achieve spatiotemporal visualization of exposure concentrations.

[0007] 4. Broken Data Links and Delayed Source Appraisal: From on-site sampling to laboratory analysis, and then to data calculation and report generation, the process is lengthy, making it impossible to provide timely early warnings of exposure risks. Furthermore, source apportionment methods based on the ratios of characteristic components of PAHs are an effective means of rapidly identifying pollution sources from vehicle emissions, coal combustion, and biomass burning. However, this process requires manual calculation and comparison by professionals. Existing passive sampling technology systems have failed to achieve a cloud-based automated closed loop from sampling, data transmission, component analysis to automatic comparison and preliminary analysis of source characteristics, resulting in a severe disconnect between "monitoring" and "analysis," making it difficult to support rapid decision-making. Summary of the Invention

[0008] To overcome the shortcomings of existing technologies, this invention discloses an intelligent all-state PAH passive sampling and monitoring system for individual exposure assessment and source apportionment. This system deeply integrates a standardized all-state passive sampler, multi-parameter environmental perception, precise positioning and tracking, wireless data transmission and cloud-based intelligent analysis, enabling accurate assessment of individual PAH exposure at all times and along all pathways, and providing intelligent monitoring that can quickly provide preliminary clues to pollution sources.

[0009] The core concept of this invention lies in constructing a precise source tracing closed-loop system that enables real-time sensing, dynamic hourly correction, and high temporal resolution inversion. The system not only simultaneously collects gaseous and particulate pollutants, but more importantly, it synchronously and continuously records hourly spatiotemporal environmental information such as temperature, pressure, and location throughout the sampling process. After quantitative analysis of pollutants is completed in the laboratory, the cloud platform utilizes these continuous real-time environmental parameters, based on the theoretical foundation of the diffusion coefficient correction formula (6), to dynamically correct the passive sampling rate hourly according to formula (2). Then, based on formula (7), the accumulated adsorption amount is inverted and reconstructed into a continuous time series of hourly concentrations, thereby restoring the single cumulative total to an exposure concentration process that changes over time. Finally, by combining the spatiotemporal trajectory, an individual exposure dynamic map and source apportionment report with hours as the smallest time unit are generated, completely changing the situation of passive sampling technology having a single information dimension and lagging evaluation results.

[0010] To achieve the above objectives, the technical solution of the present invention is as follows: An intelligent full-state polycyclic aromatic hydrocarbon (PAH) passive sampling and monitoring system for individual exposure assessment and source apportionment includes: an intelligent passive sampling unit worn on the human body; an environmental sensing and positioning unit for collecting spatiotemporal and environmental information of the environment in which the intelligent passive sampling unit is located; a data processing and communication unit for processing, storing, and transmitting the data collected by the environmental sensing and positioning unit; a full-state PAH analysis unit for laboratory analysis of samples collected by the intelligent passive sampling unit; and a data analysis cloud platform for receiving data transmitted by the data processing and communication unit, calculating individual exposure doses, and performing preliminary source apportionment.

[0011] Preferably, the intelligent passive sampling unit includes a sampler housing, a central tube arranged axially inside the housing, a gas phase polycyclic aromatic hydrocarbon adsorption module and a particulate phase polycyclic aromatic hydrocarbon capture module connected in series in the central tube. The two ends of the central tube extend out of the housing, with its windward side forming a gas diffusion inlet and its leeward side forming a gas diffusion outlet. The sampler housing is equipped with accessories for easy wearing by the human body and for fixing the intelligent passive sampling unit.

[0012] Preferably, the environmental sensing and positioning unit is located between the sampler housing and the central tube, and includes a temperature and humidity sensor, an atmospheric pressure sensor, a particulate matter sensor, a positioning module and a real-time clock module. The sampler housing has several through holes to connect the environment inside the sampler housing with the outside world.

[0013] Preferably, the data processing and communication unit is located between the sampler housing and the central tube, and includes a microcontroller, a memory chip and a wireless communication module. The microcontroller is electrically connected to each sensor and module of the environmental perception and positioning unit and the wireless communication module.

[0014] Preferably, the full-state polycyclic aromatic hydrocarbon (PAH) analysis unit includes several devices for laboratory analysis of samples collected by the gas phase PAH adsorption module and the particulate phase PAH capture module.

[0015] Preferably, the data analysis cloud platform has an integrated individual exposure dose assessment model and a pollution source fingerprint database. The individual exposure dose assessment model uses real-time received temperature and air pressure parameters to dynamically correct the passive sampling rate hourly according to formula (2), and uses formula (7) to invert the cumulative adsorption amount obtained from laboratory analysis into an hourly exposure concentration sequence, thereby calculating the individual exposure dose and time-weighted average concentration, and combining it with the pollution source fingerprint database to achieve rapid analysis of pollution sources.

[0016] Preferably, the gas diffusion inlet is equipped with a detachable windproof and rainproof grille and a particulate pre-cutter.

[0017] Preferably, the gas phase polycyclic aromatic hydrocarbon adsorption module is a sampling tube filled with a functionalized adsorbent, the central tube is divided into front and rear sections, the sampling tube is detachably and fixedly connected between the front and rear sections of the central tube, and the particulate phase polycyclic aromatic hydrocarbon capture module is a clamping device loaded with polyurethane foam or quartz fiber filter membrane, which is detachably and fixedly connected to the rear part of the inner hole of the front section of the central tube.

[0018] Preferably, in the environmental sensing and positioning unit, the positioning module is a dual-mode positioning chip integrating GPS and BeiDou; the particulate matter sensor is a laser scattering PM2.5 sensor. 2.5Sensors; the signal output terminals of the temperature and humidity sensor, atmospheric pressure sensor, particulate matter sensor, positioning module, and real-time clock module are all connected to the corresponding input ports of the microcontroller.

[0019] Preferably, the wireless communication module is an NB-IoT communication module or a 4G Cat.1 communication module; the data processing and communication unit also includes a rechargeable lithium battery and a power management circuit for powering each module, and a solar panel is provided on the outside of the sampler housing, which is connected to the rechargeable lithium battery through a charging circuit.

[0020] Preferably, the individual exposure dose assessment model is based on the received real-time environmental parameters (including temperature, humidity, and air pressure), and performs hourly dynamic correction of the passive sampling rate according to the theoretical basis of formula (6) and formula (2). According to formula (7), the cumulative adsorption amount of gaseous and particulate polycyclic aromatic hydrocarbons obtained from laboratory analysis is inverted and reconstructed into an hourly exposure concentration time series. Then, combined with time-location trajectory data, the time-weighted average exposure concentration is calculated according to formula (3), and the individual inhalation dose is calculated according to formula (8).

[0021] The formula for the dynamically corrected sampling rate is as follows: (2); In the formula: The actual sampling rate is corrected based on real-time temperature T and pressure P. ; Sampling rate under standard conditions ; Real-time ambient temperature ; Standard temperature, usually taken as 298 K (25℃); Real-time atmospheric pressure (kPa); Standard atmospheric pressure, 101.325 kPa; The comprehensive correction factor, which includes the effects of humidity and particulate matter settling, is determined by experiments or experience.

[0022] The time-weighted average exposure formula is as follows: (3); In the formula: Time-weighted average exposure concentration ; The number of microenvironments an individual experiences (such as indoor, outdoor, commuting, etc.); The average concentration in the j-th microenvironment ; : Time spent in the j-th microenvironment .

[0023] The pollution source fingerprint database stores the ratio data of characteristic components of polycyclic aromatic hydrocarbons, which is used to compare with the sampling analysis results. The data analysis cloud platform calculates the ratio of characteristic molecules in the sample according to formulas (4) and (5), and then calculates the Euclidean distance and contribution weight between the sample and each pollution source fingerprint according to formulas (9) and (10), thereby realizing the quantitative analysis and contribution assessment of pollution sources.

[0024] The formula for the characteristic molecule ratio is as follows: (4); (5); In the formula: The ratio of fluoranthene to (fluoranthene + pyrene) is used to distinguish between petroleum-based and combustion-based sources. Concentration of fluorescein in the sample or Based on the analysis results; : Concentration of pyrene in the sample or ; : Ratio of indo[1,2,3-cd]pyrene to (indo[1,2,3-cd]pyrene + benzo[ghi]perylene); : The concentration of indo[1,2,3-cd]pyrene in the sample; : The concentration of benzo[ghi]perylene in the sample.

[0025] Preferably, the functionalized adsorbent is XAD-2 resin modified with carboxyl or amino groups, or graphitized carbon black; the particulate pre-cutter is a PM designed based on the impact principle. 2.5 Cutting head.

[0026] Preferably, the microcontroller has pre-stored sampling logic, including timed wake-up, sensor data acquisition cycle, data compression algorithm and low battery warning mechanism, and its signal terminal is connected to the wireless communication module to control the packaging and transmission of data.

[0027] Another objective of this invention is to provide a method for individual full-state polycyclic aromatic hydrocarbon (PAH) exposure assessment and pollution source apportionment. The method employs an intelligent full-state PAH passive sampling and monitoring system for individual exposure assessment and source apportionment, and includes the following steps: Step 1, Deployment and Startup: Wear the intelligent passive sampler on the subject or place it at the target monitoring point. After the system is powered on and performs a self-test, the microcontroller controls the initialization of each sensor, the positioning module begins to acquire initial location information, and the wireless communication module attempts to establish a connection with the data parsing cloud platform. Step Two, Synchronous Sampling and Monitoring: As the wearer begins to move, within a preset sampling period, ambient air passively diffuses through the intelligent passive sampling unit, where gaseous and particulate polycyclic aromatic hydrocarbons (PAHs) passing through the central tube are adsorbed and captured, respectively. Simultaneously, the environmental sensing and positioning unit collects temperature, humidity, atmospheric pressure, and PM2.5 at a set frequency. 2.5 Concentration, precise location, and time data are stored in a memory chip; Step 3, data transmission: The microcontroller packages the collected environmental parameters and spatiotemporal trajectory data, and uploads them to the data analysis cloud platform periodically or triggered by the wireless communication module; Step 4, Sample Recovery and Analysis: After sampling, the gas phase adsorption module and particulate phase trapping module are recovered and sent to the laboratory for qualitative and quantitative analysis using the full-state polycyclic aromatic hydrocarbon analysis unit to obtain the concentration data of each polycyclic aromatic hydrocarbon component in the gas phase and particulate phase. Step 5, data fusion and hourly dynamic inversion: The concentration data of polycyclic aromatic hydrocarbon components obtained from laboratory analysis are uploaded to the data analysis cloud platform. The platform calls the individual exposure dose assessment model, combines the real-time temperature and hourly environmental parameters of air pressure uploaded in Step 3, and corrects the passive sampling rate hourly according to the diffusion coefficient correction formula (6) and the sampling rate correction formula (2). Then, according to the formula (7), the cumulative adsorption amount is inverted and reconstructed into an exposure concentration time series with hourly resolution. On this basis, the time-weighted average exposure concentration is calculated according to the formula (3), and the individual inhalation dose is calculated according to the formula (8). At the same time, the platform calls the pollution source fingerprint database and the fast analysis engine, calculates the characteristic component ratio of polycyclic aromatic hydrocarbons in the sample according to the formulas (4) and (5), and calculates the similarity and contribution weight with the fingerprints of various pollution sources according to the formulas (9) and (10). It automatically gives the quantitative analysis results and contribution assessment of the pollution source, and further analyzes the changes of the main pollution sources in different time periods and different geographical locations. Step 6: Generate a high temporal resolution report: The data analysis cloud platform integrates the hourly exposure concentration sequence obtained by inversion based on formula (7), the time-weighted average exposure concentration calculated based on formula (3), the individual inhalation dose calculated based on formula (8), the spatiotemporal trajectory distribution characteristics and pollution source contribution calculated based on formulas (9) and (10), and generates an individual exposure dynamic map and source apportionment comprehensive analysis report with hourly time units. The report presents the curve of exposure concentration change with time and location, and identifies high-risk periods and areas and their main pollution sources and contribution ratios.

[0028] In the method described, formulas (6)-(10) are detailed in the specific implementation section.

[0029] The beneficial effects of the intelligent full-state polycyclic aromatic hydrocarbon passive sampling and monitoring system for individual exposure assessment and source apportionment of the present invention are as follows: This invention, through deep integration of full-state passive sampling, multi-parameter environmental perception, precise positioning and tracking, wireless communication, and cloud-based intelligent analysis, has for the first time constructed a complete technical solution from on-site sampling to exposure assessment and rapid source apportionment. The system employs a modularly designed gas-particle two-phase series passive sampler, which is compact, easy to wear, and achieves simultaneous and balanced collection of polycyclic aromatic hydrocarbons (PAHs) in both the gas and particulate phases. Built-in temperature, humidity, air pressure, particulate matter sensors and positioning modules can record the exposure microenvironment and spatiotemporal trajectory in real time. The cloud platform uses these hourly time-series data to dynamically correct the standard sampling rate hourly based on the theoretical basis of formula (6) and formula (2). Based on formula (7), the cumulative analysis data of the laboratory is inverted and reconstructed into an hourly exposure concentration continuous sequence. Based on formula (8), the individual inhalation dose is accurately calculated. Based on formulas (9) and (10), the contribution of pollution sources is quantitatively analyzed. This breaks through the limitation of traditional passive sampling, which can only provide total or average concentration. It realizes the refined reconstruction of the exposure process and the quantitative tracing of pollution sources, greatly improving the spatiotemporal accuracy and reliability of exposure dose assessment, and providing unprecedented data support for precise health intervention. Attached Figure Description

[0030] Figure 1 This is a cross-sectional structural diagram of the intelligent passive sampler provided in an embodiment of the present invention.

[0031] Figure 2 This is a system overall structure and data flow diagram provided in the embodiments of the present invention.

[0032] Figure 3 This is a flowchart of the working method provided in the embodiment of the present invention. Detailed Implementation

[0033] The following description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0034] Example 1, combined with Figure 1 An intelligent full-state polycyclic aromatic hydrocarbon passive sampling and monitoring system for individual exposure assessment and source apportionment includes an intelligent passive sampling unit, an environmental sensing and positioning unit 4, a data processing and communication unit 5, a full-state polycyclic aromatic hydrocarbon analysis unit, and a data analysis cloud platform.

[0035] The intelligent passive sampling unit includes a sampler housing 1, a gaseous polycyclic aromatic hydrocarbon (PAH) adsorption module 2, and a particulate PAH collection module 3. The sampler housing 1 houses a central tube 01, which is cylindrical in shape. The central tube 01 has a gas diffusion inlet 101 on its windward side and a gas diffusion outlet 105 on its leeward side. The gas diffusion inlet 101 is equipped with a detachable windproof and rainproof grille 102 and a particulate pre-cutter 103 based on the impact principle (commercially available products can be selected). The gaseous PAH adsorption module 2 and the particulate PAH collection module 3 are sequentially connected in series on the central tube within the sampler housing 1 along the airflow direction. Specifically, the central tube is divided into two sections, front and rear, for the gaseous PAHs. The adsorption module 2 is a sampling tube 201 filled with functionalized adsorbent 202. The sampling tube is detachably connected between the front and rear central tubes. The functionalized adsorbent 202 is a carboxyl-modified XAD-2 resin. The particulate polycyclic aromatic hydrocarbon (PAH) collection module 3 is a clamp for loading and fixing the quartz fiber filter membrane and is fixed at the tail of the front central tube. The sampling tube 201 and the particulate PAH collection module 3 adopt a series modular snap-fit ​​design, which facilitates the overall disassembly and replacement from the outer shell 1. The sampler outer shell and the central tube are also detachably connected. Alternatively, a door 6 can be provided on the sampler outer shell 1 to remove or install the gas phase PAH adsorption module 2 and the particulate PAH collection module 3.

[0036] The environmental sensing and positioning unit 4 is integrated between the sampler housing 1 and the central tube, and includes a temperature and humidity sensor 401, an atmospheric pressure sensor 402, and a laser scattering PM2.5 sensor. 2.5 The sampler includes a sensor 403, a dual-mode positioning module 404 integrating GPS and BeiDou, and a real-time clock module 405. The signal output terminals of the temperature and humidity sensor 401, atmospheric pressure sensor 402, particulate matter sensor 403, positioning module 404, and real-time clock module 405 are all connected to the corresponding input ports of the microcontroller 501. The sampler housing has several through holes to connect the internal environment with the external environment.

[0037] The data processing and communication unit 5 is also integrated between the sampler housing 1 and the central tube, and includes a microcontroller 501, a storage chip 502, a wireless communication module 503, a rechargeable lithium battery 504, and a power management circuit 505. The microcontroller 501 is electrically connected to each sensor and module in the environmental perception and positioning unit and the wireless communication module 503, and is used to control sensor data acquisition, store data in the storage chip 502, and execute data packaging and transmission logic. The wireless communication module 503 is an NB-IoT communication module. A solar panel 6 is provided on the top of the sampler housing 1. The solar panel 6 is connected to the rechargeable lithium battery 504 through a charging circuit to power the system.

[0038] The full-state polycyclic aromatic hydrocarbon (PAH) analysis unit is located in the laboratory and is used to perform qualitative and quantitative analysis on the samples collected by the recovered gas phase PAH adsorption module 2 and particulate phase PAH capture module 3 to obtain the concentration data of each PAH component in the gas phase and particulate phase.

[0039] The data analysis cloud platform is connected to the wireless communication module 503 via the Internet or wireless network 11. The data analysis cloud platform has a built-in individual exposure dose assessment model 802 and a pollution source fingerprint database and a fast analysis engine 803. The individual exposure dose assessment model 802 is used to dynamically correct the passive sampling rate based on the received real-time environmental parameters, and calculate the time-weighted average exposure concentration and individual inhalation dose by combining time-location trajectory data. The pollution source fingerprint database and the fast analysis engine 803 store polycyclic aromatic hydrocarbon (PAH) characteristic component ratio data, which are used to compare with the PAH component spectrum obtained by laboratory analysis to achieve rapid preliminary analysis of pollution sources.

[0040] Additionally, the device includes accessories for securing and wearing the sampler; or a magnetic back clip, one end of which connects to the sampler housing and the other end for securing to the human body; a portable lanyard for attaching to the sampler housing for easy carrying; and a tripod adapter base for supporting the device and facilitating point-to-point testing. To facilitate the use of these accessories, components for easy connection to the accessories can be provided on the surface of the housing, such as connectors for easy binding, magnetic bases, and junction boxes for easy connection to the tripod adapter base. Furthermore, during use, the user may use their hands to prevent the device from falling off or shifting.

[0041] Example 2, combined with Figure 1 , Figure 2 and Figure 3A method for individual exposure assessment and source apportionment of polycyclic aromatic hydrocarbons (PAHs) is disclosed. This method employs an intelligent passive sampling and monitoring system for individual exposure assessment and source apportionment of PAHs as described in Example 1, and includes the following steps:

[0042] Step 1, Deployment and Startup: The intelligent passive sampling unit is worn on the subject 10 by a magnetic back clip, or it is set up at the target monitoring point using a tripod adapter base; after the system is powered on, the microcontroller 501 controls each sensor to perform self-test and initialization, the dual-mode positioning module 404 begins to acquire initial position information, and the wireless communication module 503 attempts to establish a connection with the data analysis cloud platform. Step 2, Synchronous Sampling and Monitoring: Within the preset sampling period, ambient air, driven by concentration difference and the wearer's breathing, passively diffuses from the gas diffusion inlet 101 into the sampler housing 1, flows sequentially through the gas phase polycyclic aromatic hydrocarbon (PAH) adsorption module 2 and the particulate phase PAH capture module 3, and is finally discharged from the gas diffusion outlet 105. During this process, gas phase PAHs are adsorbed by the functionalized adsorbent 202, and particulate phase PAHs are captured by the quartz fiber filter membrane 302. Simultaneously, the environmental sensing and positioning unit synchronously collects temperature, humidity, atmospheric pressure, and PM2.5 at a set frequency. 2.5 Concentration, precise location information, and time data are stored in the storage chip 502; the wearer moves to multiple locations and data is collected using the above method. Step 3, data transmission: The microcontroller 501 collects and packages the environmental parameters and spatiotemporal trajectory data, and periodically uploads them to the data parsing cloud platform through the NB-IoT wireless communication module 503. Step 4, Sample Recovery and Analysis: After the sampling cycle is completed, the gas phase polycyclic aromatic hydrocarbon adsorption module 2 and the particulate phase polycyclic aromatic hydrocarbon collection module 3 are recovered and sent to the laboratory; the full-state polycyclic aromatic hydrocarbon analysis unit (such as gas chromatography-mass spectrometry) is used to process and analyze the sample to obtain accurate concentration data of various polycyclic aromatic hydrocarbon monomers in the gas phase and particulate phase. Step 5, data fusion and hourly dynamic inversion: The concentration data of polycyclic aromatic hydrocarbon components obtained from laboratory analysis is uploaded to the data analysis cloud platform. The platform calls the individual exposure dose assessment model 802, and combines the real-time temperature and atmospheric pressure hourly environmental parameters uploaded in Step 3. The standard passive sampling rate is corrected hourly according to the diffusion coefficient correction formula (6) and the sampling rate correction formula (2). Then, according to the formula (7), the cumulative adsorption amount of pollutants obtained from sample analysis is combined with the hourly environmental parameters and reconstructed into a microenvironmental concentration time series with hourly resolution through the time weighted allocation algorithm. Based on this, the time-weighted average exposure concentration is calculated according to formula (3), and the individual inhalation dose is calculated according to formula (8). At the same time, the platform calls the pollution source fingerprint database and the fast analysis engine 803 to calculate the characteristic component ratio of polycyclic aromatic hydrocarbons in the sample according to formulas (4) and (5), and then calculates the similarity and contribution weight with various pollution source fingerprints according to formulas (9) and (10). The platform automatically gives the preliminary analysis results and contribution assessment of the pollution source. The results can be used as an auxiliary reference. The final judgment is based on the laboratory's comprehensive judgment, and further analysis is conducted on the changes of the main pollution sources in different time periods and different geographical locations.

[0043] The temperature-pressure correction formula for the diffusion coefficient is as follows: (6); In the formula: At temperature ,pressure Molecular diffusion coefficient of pollutants ; Standard state ( , diffusion coefficient under) ; Real-time ambient temperature (K); Standard temperature, 298 K; Real-time atmospheric pressure (kPa); Standard atmospheric pressure, 101.325 kPa.

[0044] The formula for calculating the environmental concentration after dynamic correction is as follows: (7); In the formula: : No. Average environmental concentration over time intervals ; : No. The mass increment of adsorbed pollutants within a time interval The total adsorption amount is obtained by reconstructing the total adsorption amount based on real-time environmental parameters and time allocation. According to the first Average temperature over time intervals and pressure Corrected sampling rate ; : No. Duration of each time interval .

[0045] The individual inhalation dosage formula is as follows: (8); In the formula: Total inhaled dose for an individual during the entire sampling period ; Time-weighted average exposure concentration ; Individual respiratory rate Different values ​​can be set according to the intensity of the activity (such as sitting or walking); Total sampling time ; Lung absorption factor (dimensionless, 0~1) represents the proportion of inhaled pollutants absorbed by the lungs.

[0046] The formula for calculating source contribution is as follows: (9); (10); In the formula: : Sample and the first The Euclidean distance between individual fingerprints indicates that the smaller the distance, the higher the similarity. : Number of diagnostic ratio types used for comparison; The first in the sample Calculated values ​​of each diagnostic ratio; : No. The first in the personal fingerprint database Reference values ​​for each diagnostic ratio; : No. The standard deviation or uncertainty of each diagnostic ratio is used for normalization; : No. The contribution weight of each source; The total number of candidate pollution sources.

[0047] Step 6: Generate a high temporal resolution report: The data analysis cloud platform integrates the hourly exposure concentration sequence (obtained by inversion according to formula (7), time-weighted average exposure concentration (calculated according to formula (3), individual inhalation dose (calculated according to formula (8), spatiotemporal distribution map of exposure concentration (based on location data) and pollution source contribution (calculated according to formulas (9) and (10))) to automatically generate an individual exposure dynamic map and source apportionment comprehensive analysis report with hourly time units. The report presents the curve of exposure concentration change with time and location, and identifies high-risk periods and areas and their main pollution sources and contribution ratios.

[0048] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. An intelligent full-state passive sampling and monitoring system for polycyclic aromatic hydrocarbons (PAHs) for individual exposure assessment and source apportionment, characterized in that, It includes an intelligent passive sampling unit worn on the human body; an environmental sensing and positioning unit for collecting spatiotemporal and environmental information of the environment in which the intelligent passive sampling unit is located; and a data processing and communication unit for processing, storing, and transmitting the data collected by the environmental sensing and positioning unit. A full-state polycyclic aromatic hydrocarbon analysis unit for laboratory analysis of samples collected by the intelligent passive sampling unit, and a data analysis cloud platform for receiving data transmitted by the data processing and communication unit, calculating individual exposure doses, and performing preliminary analysis of pollution sources.

2. The intelligent full-state polycyclic aromatic hydrocarbon passive sampling and monitoring system for individual exposure assessment and source apportionment as described in claim 1, characterized in that: The intelligent passive sampling unit includes a sampler housing, a central tube arranged axially inside the housing, a gas phase polycyclic aromatic hydrocarbon adsorption module and a particulate phase polycyclic aromatic hydrocarbon capture module connected in series in the central tube. The two ends of the central tube extend out of the housing, with its windward side forming a gas diffusion inlet and its leeward side forming a gas diffusion outlet. The sampler housing is equipped with accessories for easy wearing by the human body and for fixing the intelligent passive sampling unit. The environmental sensing and positioning unit is located between the sampler housing and the central tube, and includes a temperature and humidity sensor, an atmospheric pressure sensor, a particulate matter sensor, a positioning module and a real-time clock module. The sampler housing has several through holes to connect the environment inside the sampler housing with the outside world. The data processing and communication unit is located between the sampler housing and the central tube, and includes a microcontroller, a memory chip and a wireless communication module. The microcontroller is electrically connected to each sensor and module of the environmental perception and positioning unit and the wireless communication module. The full-state polycyclic aromatic hydrocarbon analysis unit includes several devices for laboratory analysis of samples collected by the gas phase polycyclic aromatic hydrocarbon adsorption module and the particulate phase polycyclic aromatic hydrocarbon capture module. The data analysis cloud platform has a built-in individual exposure dose assessment model and a pollution source fingerprint database; it is used to calculate the individual exposure dose and time-weighted average concentration, and combined with the pollution source fingerprint database, it enables rapid analysis of pollution sources.

3. The intelligent full-state polycyclic aromatic hydrocarbon passive sampling and monitoring system for individual exposure assessment and source apportionment as described in claim 2, characterized in that: The gas diffusion inlet is equipped with a detachable windproof and rainproof grille and a particulate pre-cutter; the particulate pre-cutter is a PM based on the impact principle. 2.5 Cutting head; The gas-phase polycyclic aromatic hydrocarbon adsorption module is a sampling tube filled with a functionalized adsorbent, which is XAD-2 resin modified with carboxyl or amino groups or graphitized carbon black. The central tube is divided into front and rear sections, and the sampling tube is detachably and fixedly connected between the front and rear sections of the central tube. The particulate phase polycyclic aromatic hydrocarbon capture module is a clamping device loaded with polyurethane foam or quartz fiber filter membrane, which is detachably and fixedly connected to the rear part of the inner hole of the front section of the central tube.

4. The intelligent full-state polycyclic aromatic hydrocarbon passive sampling and monitoring system for individual exposure assessment and source apportionment as described in claim 3, characterized in that: In the environmental perception and positioning unit, the positioning module is a dual-mode positioning chip integrating GPS and BeiDou; the particulate matter sensor is a laser scattering PM sensor. 2.5 Sensors; the signal output terminals of the temperature and humidity sensor, atmospheric pressure sensor, particulate matter sensor, positioning module, and real-time clock module are all connected to the corresponding input ports of the microcontroller.

5. The intelligent full-state polycyclic aromatic hydrocarbon passive sampling and monitoring system for individual exposure assessment and source apportionment as described in claim 4, characterized in that: The wireless communication module is an NB-IoT communication module or a 4G Cat.1 communication module; the data processing and communication unit also includes a rechargeable lithium battery and a power management circuit to power each module, and a solar panel is provided on the outside of the sampler housing, which is connected to the rechargeable lithium battery through a charging circuit.

6. The intelligent full-state polycyclic aromatic hydrocarbon passive sampling and monitoring system for individual exposure assessment and source apportionment as described in claim 5, characterized in that: The microcontroller has pre-stored sampling logic, including timed wake-up, sensor data acquisition cycle, data compression algorithm and low battery warning mechanism. Its signal terminal is connected to the wireless communication module to control the packaging and transmission of data.

7. A method for assessing individual full-state polycyclic aromatic hydrocarbon (PAH) exposure and analyzing pollution sources, characterized in that, The method employs an intelligent full-state polycyclic aromatic hydrocarbon passive sampling and monitoring system for individual exposure assessment and source apportionment as described in any one of claims 1-6, comprising the following steps: Step 1, Deployment and Startup: Wear the intelligent passive sampler on the subject or place it at the target monitoring point. After the system is powered on and performs a self-test, the microcontroller controls the initialization of each sensor, the positioning module begins to acquire initial location information, and the wireless communication module attempts to establish a connection with the data parsing cloud platform. Step Two, Synchronous Sampling and Monitoring: As the wearer begins to move, within a preset sampling period, ambient air passively diffuses through the intelligent passive sampling unit, where gaseous and particulate polycyclic aromatic hydrocarbons (PAHs) passing through the central tube are adsorbed and captured, respectively. Simultaneously, the environmental sensing and positioning unit collects temperature, humidity, atmospheric pressure, and PM2.5 at a set frequency. 2.5 Concentration, precise location, and time data are stored in a memory chip; Step 3, data transmission: The microcontroller packages the collected environmental parameters and spatiotemporal trajectory data, and uploads them to the data analysis cloud platform periodically or triggered by the wireless communication module; Step 4, Sample Recovery and Analysis: After sampling, the gas phase adsorption module and particulate phase trapping module are recovered and sent to the laboratory for qualitative and quantitative analysis using the full-state polycyclic aromatic hydrocarbon analysis unit to obtain the concentration data of each polycyclic aromatic hydrocarbon component in the gas phase and particulate phase. Step 5, Data Fusion and Hourly Dynamic Inversion: Manually enter or upload the polycyclic aromatic hydrocarbon (PAH) component concentration data obtained from laboratory analysis to the data analysis cloud platform. The platform calls the individual exposure dose assessment model and, combined with the real-time environmental parameters and trajectory data uploaded in Step 3, calculates the precise exposure dose for individuals. At the same time, the platform compares the PAH characteristic ratios with the pollution source fingerprint database and automatically provides semi-quantitative analysis results and contribution assessments of the pollution sources for professionals to refer to and verify. Step 6: Generate Report: The data analysis cloud platform integrates exposure dose, spatiotemporal distribution characteristics, and source apportionment results to generate a visualized individual exposure assessment report or regional pollution characteristic report.

8. The method for individual full-state polycyclic aromatic hydrocarbon exposure assessment and pollution source apportionment as described in claim 7, characterized in that, In step five, the concentration data of polycyclic aromatic hydrocarbon components obtained from laboratory analysis are uploaded to the data analysis cloud platform. The platform calls the individual exposure dose assessment model, combines the real-time temperature and hourly environmental parameters of air pressure uploaded in step three, and corrects the passive sampling rate hourly according to the diffusion coefficient correction formula (6) and the sampling rate correction formula (2). Then, according to formula (7), the cumulative adsorption amount is inverted and reconstructed into an exposure concentration time series with hourly resolution. On this basis, the time-weighted average exposure concentration is calculated according to formula (3), and the individual inhalation dose is calculated according to formula (8). At the same time, the platform calls the pollution source fingerprint database and the fast analysis engine, calculates the characteristic component ratio of polycyclic aromatic hydrocarbons in the sample according to formulas (4) and (5), and calculates the similarity and contribution weight with various pollution source fingerprints according to formulas (9) and (10). It automatically gives the quantitative analysis results and contribution assessment of the pollution source, and further analyzes the changes of the main pollution sources in different time periods and different geographical locations. In step six, the data analysis cloud platform integrates the hourly exposure concentration sequence obtained by inversion based on formula (7), the time-weighted average exposure concentration calculated based on formula (3), the individual inhalation dose calculated based on formula (8), the spatiotemporal trajectory distribution characteristics and pollution source contribution calculated based on formulas (9) and (10), and generates an individual exposure dynamic map and source apportionment comprehensive analysis report with hourly time units. The report presents the curve of exposure concentration change with time and location, and identifies high-risk periods and areas and their main pollution sources and contribution ratios. The formulas (2) to (10) are as follows: The formula for the dynamically corrected sampling rate is as follows: （2）； In the formula: The actual sampling rate is corrected based on real-time temperature T and pressure P. ; Sampling rate under standard conditions ; Real-time ambient temperature ; Standard temperature, usually taken as 298 K (25℃); Real-time atmospheric pressure (kPa); Standard atmospheric pressure, 101.325 kPa; The comprehensive correction factor, which includes the effects of humidity and particulate matter settling, is determined by experiments or experience. The time-weighted average exposure formula is as follows: （3）； In the formula: Time-weighted average exposure concentration ; The number of microenvironments an individual experiences (such as indoor, outdoor, commuting, etc.); The average concentration in the j-th microenvironment ; : Time spent in the j-th microenvironment ; The formula for the characteristic molecule ratio is as follows: （4）； （5）； In the formula: The ratio of fluoranthene to (fluoranthene + pyrene) is used to distinguish between petroleum-based and combustion-based sources. Concentration of fluorescein in the sample or Based on the analysis results; : Concentration of pyrene in the sample or ; : Ratio of indo[1,2,3-cd]pyrene to (indo[1,2,3-cd]pyrene + benzo[ghi]perylene); : The concentration of indo[1,2,3-cd]pyrene in the sample; : The concentration of benzo[ghi]perylene in the sample; The temperature-pressure correction formula for the diffusion coefficient is as follows: （6）； In the formula: At temperature ,pressure Molecular diffusion coefficient of pollutants ; Standard state ( , diffusion coefficient under) ; Real-time ambient temperature (K); Standard temperature, 298 K; Real-time atmospheric pressure (kPa); Standard atmospheric pressure, 101.325 kPa; The formula for calculating the environmental concentration after dynamic correction is as follows: （7）； In the formula: : No. Average environmental concentration over time intervals ; : No. The mass increment of adsorbed pollutants within a time interval The total adsorption amount is obtained by reconstructing the total adsorption amount based on real-time environmental parameters and time allocation. According to the first Average temperature over time intervals and pressure Corrected sampling rate ; : No. Duration of each time interval ; The individual inhalation dosage formula is as follows: （8）； In the formula: Total inhaled dose for an individual during the entire sampling period ; Time-weighted average exposure concentration ; Individual respiratory rate Different values ​​can be set according to the intensity of the activity (such as sitting or walking); Total sampling time ; Lung absorption factor (dimensionless, 0~1), representing the proportion of inhaled pollutants absorbed by the lungs; The formula for calculating source contribution is as follows: （9）； （10）； In the formula: : Sample and the first The Euclidean distance between individual fingerprints indicates that the smaller the distance, the higher the similarity. : Number of diagnostic ratio types used for comparison; The first in the sample Calculated values ​​of each diagnostic ratio; : No. The first in the personal fingerprint database Reference values ​​for each diagnostic ratio; : No. The standard deviation or uncertainty of each diagnostic ratio is used for normalization; : No. The contribution weight of each source; The total number of candidate pollution sources.

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