Sewage poison tracing method

Abstract

The invention belongs to a mass spectrum technology, and particularly provides a sewage poison condition tracing method which comprises the following steps: A1, designing a tracing scheme according to poison condition abnormity of sewage sampling nodes, and the scheme comprises sampling nodes of sewage convergence countercurrent upward hierarchy; a2, collecting and analyzing the concentrations of drug protomers and metabolites thereof of raw water samples of all sampling nodes of the previous layer of the sampling nodes with abnormal toxicity conditions, and identifying the sampling nodes with abnormal toxicity conditions of the layer; circulating to the last-stage sampling node; a3, analyzing the sewage collection condition in the last-stage sampling node, and screening out a minimum building unit of a suspected poison source; and A4, entering the minimum building unit, collecting evidences, and determining the drug-related personnel. The method has the advantages of accurate and rapid tracing and the like.

Description

Technical Field

[0001] This invention relates to wastewater detection technology, and in particular to a method for tracing the source of toxicity in wastewater. Background Technology

[0002] By monitoring trace amounts of drugs and their metabolites in wastewater, the drug situation in a city or region can be assessed, and further tracing the source of the drugs can help find the source of the drugs, supporting smart drug control work that monitors the source.

[0003] Existing methods for tracing the source of toxicity in wastewater focus on single-point or localized improvements, lacking a systematic and standardized overall approach.

[0004] CN114324804A provides a detection method based on sewage samples retained at pumping stations. It targets the detection of body fluids or hair samples from people in areas with abnormal detection, screening out suspicious individuals and confirming drug users through laboratory testing. However, it covers a wide range, has poor timeliness, only performs local analysis, and cannot accurately trace the source.

[0005] Although CN114660249A mentions wiping the door handles of residential areas, buildings, and other buildings, its core is a simplified on-site testing device and method. Moreover, its detection sensitivity (reagent plate + spectral technology) is inferior to that of mass spectrometry (refer to the mass spectrometry method in the technical specification JD / Y JY02.15-2023 "Testing of 71 Psychoactive Substances and Metabolites and Cotinine in Water Samples" issued by the Narcotics Control Intelligence Center of the Ministry of Public Security).

[0006] CN115049284B constructs a comprehensive toxicity assessment index system, but it focuses on the macro-level "assessment" and "early warning" of the system itself, without addressing the issue of traceability technology.

[0007] CN117198422B proposes the concept of using multiple model coupling for source tracing. Its core is based on environmental monitoring data such as air quality monitoring data, soil quality monitoring data, water quality monitoring data, and satellite remote sensing data, as well as water quality model calculations. However, the source tracing is complex and does not trace back to the source.

[0008] It is evident that existing technologies suffer from common shortcomings: insufficient source tracing accuracy, lack of systematicity, weak evidence chains, and inadequate precision. Therefore, there is an urgent need in this field for a solution that can systematically integrate reverse tracing, rapid and accurate detection, multi-source evidence fusion, and standardized operations to solve the "last mile" problem of accurate location in wastewater toxicity source tracing. Summary of the Invention

[0009] To address the shortcomings of the existing technical solutions, this invention provides a method for tracing the source of toxicity in wastewater.

[0010] The objective of this invention is achieved through the following technical solution: Wastewater toxicity source tracing method, wherein the source tracing method is as follows: A1. Based on the abnormal toxicity at the wastewater sampling nodes, design a source tracing scheme, which includes sampling nodes at higher levels where wastewater converges and flows backward. A2. Collect and analyze the concentrations of toxic substances and their metabolites in the raw water samples of all sampling nodes at the next higher level of the sampling node with abnormal toxicity, and identify the sampling nodes with abnormal toxicity at that level. Loop through to the last sampling node; A3. Analyze the sewage collection situation within the last-level sampling node to screen out the smallest building unit suspected of being a source of toxicity; A4. Enter the smallest building unit, collect evidence, and identify drug-related personnel and the source of drug emissions.

[0011] Compared with the prior art, the present invention has the following beneficial effects.

[0012] 1. Precise source tracing: Based on the needs of tracing the source of toxic wastewater, a reverse precise source tracing path was established. Combined with the gold standard mass spectrometry method for detection and analysis, the location of the source of toxicity was accurate from a kilometer-level area to a specific room or even a person, which completely solved the problem of precise location of the "last mile" of source tracing. 2. Rapid traceability: Relying on the mobile rapid on-site testing vehicle and the collaborative detection mechanism of miniaturized mass spectrometry on-site rapid screening + large laboratory mass spectrometry verification, a rapid response from sampling to key result output is achieved, which greatly improves the timeliness of the entire traceability process; 3. Systematic Methodological Innovation: The system innovatively integrates wastewater toxicity data, environmental trace enrichment evidence, multi-source public security intelligence, and personnel biological samples into a complete system through standardized procedures, forming an immutable evidence chain of "wastewater-environment-physical evidence-human testimony," which ensures the scientific, standardized, and repeatable nature of the source tracing process. 4. High operability and standardization: By integrating digital solution planning, intelligent sampling equipment, algorithm-assisted judgment (such as suspicion level scoring model) with the Internet of Things platform, the complex traceability work is transformed into an operable, verifiable and repeatable standardized process, which is conducive to large-scale promotion and application. Attached Figure Description

[0013] The disclosure of this invention will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are merely illustrative of the technical solutions of this invention and are not intended to limit the scope of protection of this invention. In the drawings: Figure 1 This is a flowchart illustrating the methods for tracing the source of drug-related incidents. Detailed Implementation

[0014] Figure 1The following description illustrates optional embodiments of the invention to teach those skilled in the art how to implement and reproduce the invention. Some conventional aspects have been simplified or omitted to teach the technical solutions of the invention. Those skilled in the art should understand that variations or substitutions derived from these embodiments will be within the scope of the invention. Those skilled in the art should understand that the following features can be combined in various ways to form multiple variations of the invention. Therefore, the invention is not limited to the optional embodiments described below, but is defined only by the claims and their equivalents.

[0015] Example 1

[0016] The wastewater toxicity source tracing method in this embodiment is as follows: Figure 1 As shown, the steps include: A1. During routine monitoring, the anti-drug department of a certain city discovered that the concentration of methamphetamine and its metabolites in the sewage samples from the inlet of the Chengdong Sewage Treatment Plant had been abnormally high for a week, indicating that there was obvious methamphetamine abuse in its service area, and the department took measures to trace the source.

[0017] The source tracing scheme was designed as follows: Starting with the Chengdong Wastewater Treatment Plant as the initial sampling point, a reverse source tracing path was automatically generated. Three main pumping stations (A, B, C) and the septic tank inlets of eight upstream residential communities (including a certain Liyuan community) were identified as tiered sampling nodes. The scheme clearly defined the sampling sequence, coordinates, and sampling time window for each node.

[0018] A2. The sampling team drove a mobile rapid testing vehicle equipped with an intelligent automatic sampler and a -18℃ frozen storage box to conduct 24-hour mixed sampling (2-hour intervals) at pump stations A, B, and C in sequence according to the traceability plan.

[0019] The collected samples were immediately sent to a large laboratory mass spectrometer in the mobile rapid testing vehicle for analysis (refer to JD / Y JY02.15 Test for 71 psychoactive substances and metabolites, including etomidate and cotinine, in water samples). Preliminary data showed that pump station B had the highest concentration. Simultaneously, rapid screening results were obtained using a miniaturized mass spectrometer, but these could not reach the detection level of the large laboratory mass spectrometer.

[0020] The team then simultaneously sampled eight substations downstream of pump station B. Precise analysis using a large-scale laboratory mass spectrometer confirmed that the methamphetamine concentration at a certain Liyuan substation was significantly higher than in other substations, exhibiting the most pronounced concentration gradient. Simultaneously, rapid screening results were obtained using a miniaturized mass spectrometer, achieving the detection capabilities of a large-scale laboratory mass spectrometer.

[0021] A3. Confirm the flow direction of the sewage pipe network within a certain Liyuan residential community, and conduct intensive sampling and rapid analysis of the sewage wells of 15 buildings in the community using miniaturized mass spectrometry.

[0022] The results showed that the concentration of drugs in the sewage sample from Building 9 was the highest. Therefore, Building 9 was identified as the smallest building unit.

[0023] A4. With the cooperation of the property management, anti-drug police officers collected samples from the door handles of 30 residential units (two apartments per floor) in Building 9 using the electrostatic swabbing method. Rapid analysis was then conducted using a miniaturized mass spectrometer on a mobile testing vehicle. The test revealed an abnormally high level of methamphetamine in the sample taken from the door handle of apartment 3002. Furthermore, police intelligence (such as lists of individuals with a history of drug use and recent drug-related police reports) indicated that the tenant of this apartment, "Zhang," had a prior drug-related conviction and had been frequently active recently. Therefore, he was identified as a highly suspicious individual.

[0024] In order to scientifically identify the most suspicious target from rooms with multiple positive environmental samples, investigators used an algorithmic model. , Standardized evidence scores are assigned to D different dimensions, including environment, intelligence, and spatiotemporal factors. Trigger multiplication factor δ, 1(·) represents the triggering rule, Condition k Rule k, the expert rule, calculates the suspicion level of the above rooms. For example, rooms 3002 (A) and 3004 (B) are considered highly suspicious, and room 3006 (C) has a positive environmental profile but no supporting intelligence.

[0025] 1) Data collection and normalization: The following raw data were extracted from the field detection and intelligence database and normalized to the [0, 100] range or converted into logical values ​​(as shown in the table below).

[0026] 2) Calculate the scores for each item of evidence.

[0027] Environmental evidence score: E i = 0.7 * Conc + 0.3 * Ratio_Score. Wherein, Ratio_Score is judged based on whether the metabolic ratio is close to the typical value of 0.6 (±0.05): Room A (0.58) gets 100 points, and Rooms B and C get 0 points.

[0028] .

[0029] 3) Calculate the initial score for the weighted geometric mean (WGA), assuming the sensitivity index α = β = γ = 1.2 S_initial = (E^α* I^ * C^γ)^{1 / (α+β+γ)}.

[0030] S_initial_A = (93^1.2 * 95.5^1.2 * 86^1.2)^{1 / 3.6} ≈ 94.5.

[0031] S_initial_B = (45.5^1.2 * 9^1.2 * 68^1.2)^{1 / 3.6} ≈ 23.1.

[0032] S_initial_C = (49^1.2 * 0.01^1.2 * 62^1.2)^{1 / 3.6} ≈ 2.5.

[0033] 4) The application of expert rules has increased.

[0034] Rule 1: If E > 70 and Hist == 1, then the multiplication factor δ1 = 0.5 is triggered. Only room A satisfies this rule.

[0035] Rule 2: If I > 60 and Ratio is within the typical range, then the multiplication factor δ2 = 0.4 is triggered. Only room A satisfies this rule.

[0036] The total multiplication factor R_A for room A is (1+0.5)*(1+0.4) = 1.5; rooms B and C are triggered irregularly, so R=1.

[0037] 5) The final suspicion score (S) is obtained: S(A)=141.8, S(B)=23.1, S(C)=2.5.

[0038] Algorithm Output and Investigation Decision: The model outputs the room suspicion ranking as follows: A (Room 3002) >> B (Room 3004) > C (Room 3006). Based on this, Room 3002 is listed as the sole highest-risk target, allowing investigation resources to be focused.

[0039] Police officers entered the residence and collected hair samples from the water glass residue in the living room and the comb in the bathroom. A miniaturized mass spectrometer was used to perform precise mass spectrometry analysis on the hair samples, and a laboratory mass spectrometer was used for comparison and verification. High concentrations of methamphetamine and benzoic acid were detected, and the metabolite ratio chromatogram confirmed repeated use in recent days. Ultimately, the source of the drug emissions was identified as Zhang, the resident of apartment 3002.

[0040] All sampling, testing, and analysis data from this source tracing were uploaded to the blockchain evidence storage platform in real time, generating an tamper-proof electronic source tracing report, providing irrefutable evidence for law enforcement.

[0041] Example 2

[0042] The wastewater toxicity source tracing method in this embodiment is as follows: Figure 1 As shown, the steps include: A1. High concentrations of gamma-hydroxybutyric acid (GHB) were detected at a sewage treatment pumping station in a famous bar district. However, the area is home to many nightclubs, KTVs, and hotels, making it difficult to determine the source. Source tracing is underway.

[0043] By tracing the source in reverse, the source of the toxic substance was quickly narrowed down from the pumping station to a branch of the municipal pipeline in the "bar street" area. This branch also receives sewage from six entertainment venues, including a KTV and a bar.

[0044] A2. Sampling personnel directly and simultaneously sampled the six final-stage sampling nodes (independent sewage outlets of each location) of the branch network. A large mass spectrometer on the mobile rapid detection vehicle provided results within 1.5 hours, showing that the GHB concentration at the sewage outlet of a certain KTV was far higher than other locations, thus designating it as a priority inspection site.

[0045] A3. The smallest building unit is locked to a certain KTV.

[0046] A4. The police then conducted a surprise inspection of a KTV and immediately wiped and sampled the door handles, wine glasses, fruit plates, etc. of all private rooms, and used a miniaturized mass spectrometer to conduct second-level detection on site.

[0047] Rapid testing revealed that multiple items in VIP room 888 tested positive for GHB residue. Simultaneous intelligence indicated that the room was booked that night by a man surnamed Sun, suspected of drug use.

[0048] All personnel in the private room were brought under control, and urine samples were collected for on-site rapid testing using a miniaturized mass spectrometer. Combined with questioning of the personnel, the drug provider and main users were quickly identified.

[0049] Example 3

[0050] The wastewater toxicity source tracing method in this embodiment is as follows: Figure 1 As shown, the steps include: A1. Taking the provincial anti-drug squad receiving intelligence that a certain industrial park might be involved in drug manufacturing and trafficking activities, but the specific location was unknown, traditional investigative methods were insufficient. Therefore, wastewater tracing was employed. Starting with the only wastewater treatment plant in the industrial park as the initial sampling point, the reverse tracing path was clear (simple pipe network). Testing revealed the presence of rare fentanyl-like new psychoactive substances (NPS) at the plant's inlet.

[0051] A2. Secret sampling was conducted at the wastewater outlets of 18 factories within the industrial park. Mass spectrometry analysis revealed that the wastewater outlet of XX Biotechnology Co., Ltd. not only contained high concentrations of the target NPS, but also detected a variety of common precursor substances and byproducts, which highly matched the intelligence report that it was "possibly a drug manufacturing site."

[0052] Given the high risk of directly entering the factory premises, enrichment samples were taken from tire tracks of vehicles entering and exiting the factory and from the factory's drainage ditches on public roads outside the factory area. Mass spectrometry analysis again detected the target substance, further strengthening the suspicion.

[0053] A3. Based on the flow direction of sewage within the factory area, the smallest building unit is identified as the company's production workshop.

[0054] A4. After gathering sufficient evidence regarding wastewater and the environment, a joint law enforcement team conducted a surprise inspection of the company. A large quantity of drug-making equipment and raw materials were seized in the production workshop, and the suspects were apprehended.

[0055] Subsequently, samples were taken from the suspect's mobile phone screen, work uniform cuffs, etc. Mass spectrometry analysis revealed an NPS fingerprint spectrum that was completely consistent with the sewage sample, forming a complete evidence chain of "sewage-environment-physical evidence-human testimony", achieving accurate and rapid source tracing of sewage toxicity.

[0056] Example 4

[0057] The wastewater toxicity tracing method in this embodiment differs from that in Embodiment 1 in the following ways: Step A4 involves environmental sampling and intelligence analysis of two key rooms (Room A and Room B) after identifying Building 9. Suspicion scores are calculated using an algorithm, and these rooms are then ranked. 1. Input data collection and normalization.

[0058] Suppose we have collected the following raw data, which has been normalized to the interval [0, 100].

[0059] .

[0060] 2. Calculate the three levels of evidence (E, I, C).

[0061] (1) Let the weight parameters be as follows: Environmental Evidence E i :ω conc =0.7, ω ratio =0.3.

[0062] Intelligence Evidence I i :ω hist =0.4, ω alert =0.3, ω social =0.3.

[0063] Spacetime Evidence C i :ω loc =0.6, ω time =0.4.

[0064] (2) Define the rule parameters as follows: Typical metabolic value rtypical =0.6, error range ε=0.05.

[0065] Environmental threshold θ E =70, intelligence threshold θ I =60.

[0066] Then, the E, I, and C of rooms A and B can be calculated.

[0067] (3) Algorithm calculation.

[0068] Let the algorithm parameters be: (1) Sensitivity index: α=β=γ=1.2 (i.e., amplifying the impact of high-risk evidence).

[0069] (2) Rule multiplier: δ1=0.5 (rule 1), δ2=0.4 (rule 2).

[0070] Calculate the suspiciousness scores for rooms A and B.

[0071] .

[0072] Therefore, room A was identified as a room involved in drug use.

Claims

1. A method for tracing the source of sewage toxicity, characterized by, The traceability method comprises the following steps: A1. Designing a traceability scheme according to the drug abnormality of the sewage sampling node, wherein the scheme comprises sampling nodes in the upper level of the sewage gathering reverse flow; A2. Collecting and analyzing the drug original body and metabolite concentrations of the raw water samples of all sampling nodes in the upper level of the sampling node with drug abnormality, and identifying the sampling node with drug abnormality in the level; Cycling to the last level of sampling node; A3. Analyzing the sewage collection in the last level of sampling node, and screening out the smallest building unit suspected to be the drug source; A4. Entering the smallest building unit, collecting evidence, and determining the drug-related personnel and drug discharge source.

2. The method of tracing of claim 1, wherein, The sampling and rapid detection in steps A2 and / or A4 are performed by a mobile rapid detection vehicle; the mobile vehicle has an intelligent automatic sampler, a low-temperature storage device, and a miniaturized mass spectrometer, which constitute a mobile rapid response platform.

3. The method of tracing of claim 2, wherein, The detection comprises two stages of on-site rapid screening and laboratory rechecking and confirmation: the miniaturized mass spectrometer is used for rapid screening on site, and the large mass spectrometer is used for rechecking and confirmation of the screening results in the laboratory; the detection method and pretreatment process of the miniaturized mass spectrometer are consistent with those of the large mass spectrometer.

4. The method of tracing of claim 1, wherein, The collection of evidence comprises wiping and sampling the door handle, door frame, gap between the door frame and door lock, or shoe cabinet at the door of all rooms in the smallest building unit.

5. The method of tracing according to claim 1 or 4, characterized in that, In step A4, suspicious drug-related rooms or personnel are determined in combination with public security multi-source intelligence information, wherein the multi-source intelligence information comprises drug use history, drug use history, working environment, social risk, or travel record.

6. The method of tracing according to any one of claims 4 or 5, characterized in that, In step A4, the suspicious degree score of each room in the smallest building unit is calculated and output by an algorithm model to guide the investigation direction; The algorithm model integrates environmental evidence, intelligence evidence, and spatiotemporal evidence, and the parameters thereof are set based on expert experience in the drug control traceability scene and can be dynamically adjusted.

7. The method of tracing of claim 1, wherein, The sampling node comprises a sewage treatment plant, a pump station, a main pipe, a branch pipe, and a last level of sampling node connecting pipe; and the last level of sampling node is a community or a village.

8. The method of tracing of claim 1, wherein, The smallest building unit comprises a building, a hotel, an entertainment place, a factory, a hospital, or a school.

9. The method of tracing of claim 1, wherein, Key data in the whole traceability process are uploaded to a block chain storage platform, wherein the key data comprises sampling time, sampling location, detection raw data, mass spectrometry detection results, intelligence analysis and judgment records, biological sample and object surface residue detection reports, so as to ensure the completeness, authenticity, and non-tamperability of the evidence chain.

10. The method of tracing according to any one of claims 1-9, characterized in that, The detection equipment used in the traceability method is connected to an Internet of Things system, and detection data are uploaded to an intelligent control platform in real time, so as to realize multi-source data integration analysis and dynamic monitoring of the traceability process.

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