CN113034013A - Pollution tracing method and device, electronic equipment and storage medium - Google Patents
Pollution tracing method and device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN113034013A CN113034013A CN202110345382.1A CN202110345382A CN113034013A CN 113034013 A CN113034013 A CN 113034013A CN 202110345382 A CN202110345382 A CN 202110345382A CN 113034013 A CN113034013 A CN 113034013A
- Authority
- CN
- China
- Prior art keywords
- chemical fingerprint
- pollution
- fingerprint data
- data
- verified
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 56
- 238000003860 storage Methods 0.000 title claims abstract description 23
- 239000000126 substance Substances 0.000 claims abstract description 248
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 48
- 238000003911 water pollution Methods 0.000 claims abstract description 36
- 239000000356 contaminant Substances 0.000 claims abstract description 19
- 239000003344 environmental pollutant Substances 0.000 claims description 42
- 231100000719 pollutant Toxicity 0.000 claims description 42
- 230000015654 memory Effects 0.000 claims description 18
- 238000011109 contamination Methods 0.000 claims description 6
- 238000000605 extraction Methods 0.000 claims description 5
- 238000012360 testing method Methods 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000002265 prevention Effects 0.000 abstract description 10
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 12
- 238000004458 analytical method Methods 0.000 description 8
- YMWUJEATGCHHMB-UHFFFAOYSA-N Dichloromethane Chemical compound ClCCl YMWUJEATGCHHMB-UHFFFAOYSA-N 0.000 description 6
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 6
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 6
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 6
- 230000006870 function Effects 0.000 description 6
- 229910052757 nitrogen Inorganic materials 0.000 description 6
- 229910052760 oxygen Inorganic materials 0.000 description 6
- 239000001301 oxygen Substances 0.000 description 6
- 229910052698 phosphorus Inorganic materials 0.000 description 6
- 239000011574 phosphorus Substances 0.000 description 6
- 238000000513 principal component analysis Methods 0.000 description 5
- 230000005540 biological transmission Effects 0.000 description 4
- 238000009826 distribution Methods 0.000 description 4
- 238000002290 gas chromatography-mass spectrometry Methods 0.000 description 4
- 239000005416 organic matter Substances 0.000 description 4
- 239000010865 sewage Substances 0.000 description 4
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 3
- VYZAMTAEIAYCRO-UHFFFAOYSA-N Chromium Chemical compound [Cr] VYZAMTAEIAYCRO-UHFFFAOYSA-N 0.000 description 3
- MMDJDBSEMBIJBB-UHFFFAOYSA-N [O-][N+]([O-])=O.[O-][N+]([O-])=O.[O-][N+]([O-])=O.[NH6+3] Chemical compound [O-][N+]([O-])=O.[O-][N+]([O-])=O.[O-][N+]([O-])=O.[NH6+3] MMDJDBSEMBIJBB-UHFFFAOYSA-N 0.000 description 3
- XKMRRTOUMJRJIA-UHFFFAOYSA-N ammonia nh3 Chemical compound N.N XKMRRTOUMJRJIA-UHFFFAOYSA-N 0.000 description 3
- 229910052785 arsenic Inorganic materials 0.000 description 3
- RQNWIZPPADIBDY-UHFFFAOYSA-N arsenic atom Chemical compound [As] RQNWIZPPADIBDY-UHFFFAOYSA-N 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 3
- 229910052793 cadmium Inorganic materials 0.000 description 3
- BDOSMKKIYDKNTQ-UHFFFAOYSA-N cadmium atom Chemical compound [Cd] BDOSMKKIYDKNTQ-UHFFFAOYSA-N 0.000 description 3
- 229910052799 carbon Inorganic materials 0.000 description 3
- 229910052804 chromium Inorganic materials 0.000 description 3
- 239000011651 chromium Substances 0.000 description 3
- 150000001875 compounds Chemical class 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- -1 etc.) Substances 0.000 description 3
- 229910052742 iron Inorganic materials 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- WPBNNNQJVZRUHP-UHFFFAOYSA-L manganese(2+);methyl n-[[2-(methoxycarbonylcarbamothioylamino)phenyl]carbamothioyl]carbamate;n-[2-(sulfidocarbothioylamino)ethyl]carbamodithioate Chemical compound [Mn+2].[S-]C(=S)NCCNC([S-])=S.COC(=O)NC(=S)NC1=CC=CC=C1NC(=S)NC(=O)OC WPBNNNQJVZRUHP-UHFFFAOYSA-L 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- QSHDDOUJBYECFT-UHFFFAOYSA-N mercury Chemical compound [Hg] QSHDDOUJBYECFT-UHFFFAOYSA-N 0.000 description 3
- 229910052753 mercury Inorganic materials 0.000 description 3
- 229910052751 metal Inorganic materials 0.000 description 3
- 239000002184 metal Substances 0.000 description 3
- 229910052755 nonmetal Inorganic materials 0.000 description 3
- 235000015097 nutrients Nutrition 0.000 description 3
- 239000000575 pesticide Substances 0.000 description 3
- 239000003208 petroleum Substances 0.000 description 3
- 150000003839 salts Chemical class 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- 239000002351 wastewater Substances 0.000 description 3
- 238000009360 aquaculture Methods 0.000 description 2
- 244000144974 aquaculture Species 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000013178 mathematical model Methods 0.000 description 2
- 150000002739 metals Chemical class 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 150000002843 nonmetals Chemical class 0.000 description 2
- 238000010238 partial least squares regression Methods 0.000 description 2
- 238000012567 pattern recognition method Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000004451 qualitative analysis Methods 0.000 description 2
- 238000004445 quantitative analysis Methods 0.000 description 2
- 208000033962 Fontaine progeroid syndrome Diseases 0.000 description 1
- 241000282414 Homo sapiens Species 0.000 description 1
- PMZURENOXWZQFD-UHFFFAOYSA-L Sodium Sulfate Chemical compound [Na+].[Na+].[O-]S([O-])(=O)=O PMZURENOXWZQFD-UHFFFAOYSA-L 0.000 description 1
- 239000002253 acid Substances 0.000 description 1
- 239000003513 alkali Substances 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000012851 eutrophication Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000013401 experimental design Methods 0.000 description 1
- 239000000706 filtrate Substances 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000004817 gas chromatography Methods 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000009364 mariculture Methods 0.000 description 1
- 238000004949 mass spectrometry Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000000491 multivariate analysis Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000012074 organic phase Substances 0.000 description 1
- 239000002957 persistent organic pollutant Substances 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000013535 sea water Substances 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 230000007723 transport mechanism Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 239000003403 water pollutant Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
- G06F18/2135—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on approximation criteria, e.g. principal component analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/12—Fingerprints or palmprints
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
- Y02A20/152—Water filtration
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Human Resources & Organizations (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Educational Administration (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Evolutionary Computation (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Business, Economics & Management (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Biology (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Computational Biology (AREA)
- Marketing (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Health & Medical Sciences (AREA)
- Human Computer Interaction (AREA)
- Multimedia (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a pollution tracing method, a pollution tracing device, electronic equipment and a storage medium, and relates to the technical field of water environment management, wherein the pollution tracing method comprises the following steps: acquiring water pollution data of an offshore area to be detected, wherein the water pollution data comprises: chemical fingerprint data to be detected; extracting chemical fingerprint data to be verified and a pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of contaminants in the offshore area; calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset tracing model; and determining a pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type. The pollution tracing method can trace the source of the pollution rapidly and accurately, and realize the safety guarantee of the water quality of the offshore area and the prevention and control of the water pollution risk of the drainage area.
Description
Technical Field
The invention relates to the technical field of water environment management, in particular to a pollution tracing method, a pollution tracing device, electronic equipment and a storage medium.
Background
The coastal sea area refers to the sea area which is adjacent to continental coast, islands and has the outer boundary of the leading sea towards the land side. In recent years, with the rapid development of coastal areas in China, a large amount of wastewater containing metals (cadmium, chromium, lead, mercury, manganese, iron and the like), non-metals (arsenic and phosphorus), petroleum, organic matters (chemical oxygen demand, organic carbon, dissolved oxygen), nutrient salts (inorganic nitrogen, ammonia nitrogen, total phosphorus, total nitrogen, nitrate nitrogen and the like), pesticides, acid, alkali and the like is discharged, the pollution load is increased continuously when the wastewater enters the sea, seawater eutrophication can be caused, red tide is generated, fishery resources are damaged, and the life health of human beings is harmed.
Chemical fingerprinting is an emerging technology for tracing the source of pollutants, and refers to the identification of the source of pollutants and the contribution of each source by analyzing the relationship between each pollution source and some chemical pollution characteristic factors in a receptor, and is called as "chemical fingerprinting" identification because the characteristic factors are not changed like "fingerprints" in the process of pollutant migration and transformation. The chemical fingerprint identification method is widely concerned by scholars at home and abroad in water pollution source monitoring and early warning, and a lot of research is carried out, but at present, no method for effectively finding pollution sources of illegal pollution discharge exists.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the pollution tracing method provided by the embodiment of the invention can be used for quickly and accurately tracing the pollution source and realizing the water quality safety guarantee of the offshore area and the water pollution risk prevention and control of the watershed.
The embodiment of the invention also provides a pollution tracing device.
The embodiment of the invention also provides the electronic equipment.
The embodiment of the invention also provides a computer readable storage medium.
The pollution tracing method according to the embodiment of the first aspect of the invention comprises the following steps:
acquiring water pollution data of an offshore area to be detected, wherein the water pollution data comprises: chemical fingerprint data to be detected;
extracting chemical fingerprint data to be verified and a pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of contaminants in the offshore area;
calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset tracing model;
and determining a pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type.
The pollution tracing method according to the embodiment of the first aspect of the invention has at least the following beneficial effects: firstly, water pollution data of an offshore area to be detected is obtained, and the water pollution data comprises: chemical fingerprint data to be detected; then extracting chemical fingerprint data to be verified and a pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of the offshore area pollutants; calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset tracing model; and finally, determining a pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type, and quickly and accurately tracing the pollution source, thereby realizing the safety guarantee of the water quality of the offshore area and the prevention and control of the water pollution risk of the drainage basin.
According to some embodiments of the present invention, the determining the pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type includes: comparing the similarity with a preset threshold value; and if the similarity is greater than or equal to the preset threshold, determining a pollution source corresponding to the chemical fingerprint data to be detected according to the pollution type.
According to some embodiments of the invention, the method further comprises: and if the similarity is smaller than the preset threshold, skipping to the step of extracting the chemical fingerprint data to be verified and the pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of the offshore area pollutants.
According to some embodiments of the present invention, the calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset tracing model includes: performing numerical comparison on the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using the tracing model to obtain a comparison result; and obtaining the similarity according to the comparison result.
According to some embodiments of the present invention, the extracting, from a preset chemical fingerprint database of contaminants in the offshore area, chemical fingerprint data to be verified and a contamination type corresponding to the chemical fingerprint data to be verified includes: extracting the chemical fingerprint data to be verified from the chemical fingerprint database of the offshore area pollutants; acquiring label parameters corresponding to the chemical fingerprint data to be verified; and determining the pollution type corresponding to the chemical fingerprint data to be verified according to the label parameters.
According to some embodiments of the invention, the method further comprises establishing the offshore area pollutant chemical fingerprint database, specifically comprising: acquiring water environment data of a target offshore area, wherein the water environment data comprises: offshore area heavy pollution source data; extracting target chemical fingerprint indexes and pollution source sample data from the heavy-point pollution source data; analyzing and testing the target chemical fingerprint index according to the pollution source sample data to obtain target chemical fingerprint data; determining a target pollution source according to the target chemical fingerprint data; and establishing the chemical fingerprint database of the offshore area pollutants according to the target chemical fingerprint data and the target pollution source.
According to some embodiments of the invention, the determining a target contamination source from the target chemical fingerprint data comprises: obtaining traceability label data of the target chemical fingerprint data; and determining the target pollution source according to the source tracing label data.
According to a second aspect of the invention, the pollution source tracing device comprises:
the acquisition module is used for acquiring water pollution data of an offshore area to be detected, and the water pollution data comprises: chemical fingerprint data to be detected;
the extraction module is used for extracting chemical fingerprint data to be verified and a pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of the offshore area pollutants;
the calculation module is used for calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset traceability model;
and the source tracing module is used for determining a pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type.
The pollution tracing device according to the embodiment of the second aspect of the invention has at least the following beneficial effects: by executing the pollution tracing method of the embodiment of the first aspect of the invention, the pollution source can be traced quickly and accurately, and the water quality safety guarantee of the offshore area and the prevention and control of the pollution risk of the watershed water are realized.
An electronic device according to an embodiment of the third aspect of the invention includes: at least one processor, and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions that are executed by the at least one processor to cause the at least one processor to implement the pollution traceability method of the first aspect when executing the instructions.
According to the electronic device of the embodiment of the third aspect of the invention, at least the following beneficial effects are achieved: by executing the pollution tracing method of the embodiment of the first aspect of the invention, the pollution source can be traced quickly and accurately, and the water quality safety guarantee of the offshore area and the prevention and control of the pollution risk of the watershed water are realized.
According to a fourth aspect of the present invention, there is provided a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the pollution tracing method according to the first aspect.
The computer-readable storage medium according to the fourth aspect of the present invention has at least the following advantages: by executing the pollution tracing method of the embodiment of the first aspect of the invention, the pollution source can be traced quickly and accurately, and the water quality safety guarantee of the offshore area and the prevention and control of the pollution risk of the watershed water are realized.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow chart illustrating a pollution tracing method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of creating a chemical fingerprint database of contaminants in offshore areas according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a pollution tracing apparatus according to an embodiment of the present invention;
fig. 4 is a functional block diagram of an electronic device according to an embodiment of the invention.
Reference numerals:
the system comprises an acquisition module 300, an extraction module 310, a calculation module 320, a source tracing module 330, a processor 400, a memory 410, a data transmission module 420, a camera 430 and a display screen 440.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.
First, several terms referred to in the present application are resolved:
1. the Unscrambler: multivariate data analysis software. The Unscrambler is a complete software for multivariate data analysis and experimental design, and contains powerful methods such as PCA, multivariate curve resolution tool (MCR), PLS regression, 3-Way PLS regression, clustering (K-Means), SIMCA, and PLADA classification.
2. SIMCA: the cluster independent soft mode identification (SIMCA) mode is a method for identifying a supervised mode, and belongs to a binary judgment method. The method comprises the steps of firstly, conducting principal component analysis on a measured data matrix of each type of sample in a training set, establishing a mathematical model of the principal component analysis of each type, and then classifying unknown samples on the basis.
3. PCA analysis: principal components Analysis, principal component Analysis, is a dimension reduction method often used in image processing.
4. GC-MS method: namely a gas chromatography and mass spectrometry combined method, GCMS is a GC and MS integrated device, and is a precise analysis instrument for detecting what a compound is (qualitatively) and how much the compound is (quantitatively). GC was separated by passing the vaporized sample into a chromatographic column and the compounds after separation were detected in MS.
Referring to fig. 1, a pollution tracing method according to an embodiment of the first aspect of the present invention includes:
step S100, acquiring water pollution data of an offshore area to be detected, wherein the water pollution data comprises: chemical fingerprint data is detected.
Wherein, the offshore area to be detected can be the offshore area needing to detect the water pollution condition; the water pollution data of the offshore area to be detected can be water pollution data in water environment information; a plurality of indexes of the screened water body can be used as indexes of the chemical fingerprint to be detected, and then the indexes of the chemical fingerprint to be detected are analyzed and tested to obtain data of the chemical fingerprint to be detected. Optionally, the offshore area to be detected can be sampled, and the acquired unknown water sample is subjected to water pollution analysis to obtain a water pollution analysis result, i.e. water pollution data can be extracted from the water pollution analysis result. Several indexes of the water body can be screened from the water pollution data to be used as indexes of the chemical fingerprint to be detected, and the indexes comprise: metals (cadmium, chromium, lead, mercury, manganese, iron, etc.), non-metals (arsenic, phosphorus), petroleum, organic matter (chemical oxygen demand, organic carbon, dissolved oxygen), nutrient salts (inorganic nitrogen, ammonia nitrogen, total phosphorus, total nitrogen, nitrate nitrogen, etc.), pesticides, and other characteristic pollutant indexes, wherein the other characteristic pollutant indexes are pollutant indexes with regional characteristics and optimal pollutant indexes with obvious ecological effect besides the indexes. The indexes can be analyzed and detected according to collected samples of the offshore area water body to be detected and the pollution source, for example, qualitative and quantitative analysis is carried out on the indexes of the chemical fingerprint to be detected by adopting a GC-MS method, so that the data of the chemical fingerprint to be detected are obtained.
Step S110, extracting chemical fingerprint data to be verified and a pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of contaminants in the offshore area.
Wherein, the information in the preset chemical fingerprint database of offshore area pollutants can include: watershed information including geographic location, water background, basic conditions and the like of an offshore watershed; pollution source information including manufacturer address, emission rule, emission characteristics and the like; chemical fingerprint information of pollution sources, harmfulness, physicochemical properties and other information of various kinds of pollution; the water environment basic situation of the offshore area; emission rules, emission characteristics, chemical fingerprint data and other characteristic information of the pollution source. The chemical fingerprint data to be verified can be chemical fingerprint data which are used for being compared with chemical fingerprint data to be detected in a chemical fingerprint database of the offshore area pollutants; the pollution type can be information of various pollution sources stored in a chemical fingerprint database of the offshore area pollutants, and different chemical fingerprint data to be verified correspond to different pollution types. Optionally, the offshore area water environment information may be investigated and evaluated, an offshore area heavy point pollution source is screened out, a plurality of indexes of the water body are screened out as offshore area chemical fingerprint indexes, and then the selected chemical fingerprint indexes are analyzed and tested according to the collected offshore area water body and pollution source samples, so as to obtain chemical fingerprint data to be verified and pollution types corresponding to the chemical fingerprint data, such as land area pollution sources and offshore pollution sources: the land source pollution sources mainly comprise industrial, agricultural and domestic sewage and pollutants input into the ocean through rivers, the marine pollution sources comprise mariculture industry, fishing port pollution and ship pollution discharge, and then the chemical fingerprint database of the pollutants in the offshore area can be established according to the obtained chemical fingerprint data to be verified and the information (namely the pollution types) of various pollution sources corresponding to the chemical fingerprint data.
And step S120, calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset tracing model.
The tracing model can be a preset mathematical model for tracing the chemical fingerprint data to be detected; the similarity may be a degree of similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified. Optionally, the Uscrimbler software can be adopted to construct a traceability model based on the SIMCA pattern recognition method. For example, firstly, PCA analysis is carried out on each type of pollution indexes, a PCA model is independently established for each type during modeling, if it is calculated that a certain offshore area water body is similar to a certain type in a fingerprint database enough, the sample can be classified into the type, and the traceability model is obtained through the method. The chemical fingerprint data to be detected and the chemical fingerprint data to be verified in the chemical fingerprint database of the offshore area pollutants can be compared through a traceability model, for example, the two are compared in numerical value to obtain the similarity of the two.
And S130, determining a pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type.
Optionally, whether the to-be-detected chemical fingerprint data and the to-be-verified chemical fingerprint data are sufficiently similar or not can be judged according to the similarity between the to-be-detected chemical fingerprint data and the to-be-verified chemical fingerprint data. If the chemical fingerprint data to be detected is similar to the chemical fingerprint data to be verified, classifying the sample into a pollution type corresponding to the chemical fingerprint data to be verified, and determining a pollution source corresponding to the chemical fingerprint data to be detected, so that the tracing of pollutants is realized; if the chemical fingerprint data to be detected is not similar to the chemical fingerprint data to be verified, the sample cannot be classified into the pollution type corresponding to the chemical fingerprint data to be verified, so that the chemical fingerprint data to be detected needs to be compared with other chemical fingerprint data to be verified in the offshore area fingerprint database again, and a pollution source corresponding to the chemical fingerprint data to be detected is judged.
According to the pollution tracing method, firstly, water pollution data of an offshore area to be detected are obtained, and the water pollution data comprise: chemical fingerprint data to be detected; then extracting chemical fingerprint data to be verified and a pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of the offshore area pollutants; calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset tracing model; and finally, determining a pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type, and quickly and accurately tracing the pollution source, thereby realizing the safety guarantee of the water quality of the offshore area and the prevention and control of the water pollution risk of the drainage basin.
In some embodiments of the present invention, determining the contamination source corresponding to the chemical fingerprint data to be detected according to the similarity and the contamination type includes:
and comparing the similarity with a preset threshold value. The preset threshold may be a preset critical value corresponding to the similarity. Optionally, the preset threshold may be set according to requirements. Comparing the similarity with a preset threshold value to obtain: the size relationship that the similarity is greater than the preset threshold, the size relationship that the similarity is equal to the preset threshold and the size relationship that the similarity is less than the preset threshold.
And if the similarity is greater than or equal to a preset threshold, determining a pollution source corresponding to the chemical fingerprint data to be detected according to the pollution type. Optionally, when the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified is greater than or equal to a preset threshold, the chemical fingerprint data to be detected and the chemical fingerprint data to be verified are determined to be sufficiently similar, so that the chemical fingerprint data to be detected can be classified into the pollution type corresponding to the chemical fingerprint data to be verified, and the pollution source corresponding to the chemical fingerprint data to be detected is determined, so that the tracing of pollutants is realized, the source of the water pollutants in the offshore area can be traced quickly and accurately, the practicability is high, the pollution source of illegal pollution discharge can be traced quickly, great significance is provided for the water quality safety guarantee of the offshore area and the water pollution risk prevention and control of the drainage area, the popularization and application values are wide, and a reliable technical guarantee is provided for an environment management department to deal with the water pollution accidents and control risks in the.
In some embodiments of the invention, the pollution tracing method further comprises:
and if the similarity is smaller than a preset threshold value, skipping to the step of extracting the chemical fingerprint data to be verified and the pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of the offshore area pollutants. Optionally, when the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified is smaller than the preset threshold, it may be determined that the two are not similar, and therefore, the step of comparing the chemical fingerprint data to be detected with other chemical fingerprint data to be verified in the offshore area fingerprint database again is required (i.e., step S110), that is, the step of extracting the chemical fingerprint data to be verified and the pollution type corresponding to the chemical fingerprint data to be verified from the preset offshore area contaminant chemical fingerprint database is skipped until the chemical fingerprint data to be detected and a certain type of chemical fingerprint data to be verified in the offshore area contaminant chemical fingerprint database are sufficiently similar, and a pollution source corresponding to the chemical fingerprint data to be detected is determined, so that rapid and accurate tracing of the contaminants is achieved.
In some embodiments of the present invention, calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset tracing model includes:
and comparing the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using the tracing model to obtain a comparison result. Optionally, a tracing model based on the SIMCA pattern recognition method may be constructed, and the chemical fingerprint data to be detected and the chemical fingerprint data to be verified in the chemical fingerprint database of the offshore area contaminant are compared by using a numerical value comparison method to obtain a comparison result.
And obtaining the similarity according to the comparison result. Optionally, the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified, which is calculated by the tracing model, may be extracted from the comparison result. And the similarity is calculated by utilizing a tracing model, so that the responsible pollution source can be accurately identified and confirmed, and the identification tracing of the pollution material in the ultra-discharge sewage is realized.
In some embodiments of the present invention, extracting to-be-verified chemical fingerprint data and a pollution type corresponding to the to-be-verified chemical fingerprint data from a preset chemical fingerprint database of contaminants in the offshore area includes:
and extracting chemical fingerprint data to be verified from the chemical fingerprint database of the contaminants in the offshore area. Optionally, a certain type of chemical fingerprint data to be verified can be extracted randomly or according to requirements from the chemical fingerprint database of the contaminants in the offshore area as the chemical fingerprint data to be verified.
And acquiring label parameters corresponding to the chemical fingerprint data to be verified. The tag parameters may include: the type of a pollution source (such as a land source and a sea source) corresponding to the chemical fingerprint data to be verified mainly comprises industrial, agricultural and domestic sewage and pollutants input into the sea through rivers, the sea source comprises marine aquaculture, fishing port pollution and ship pollution discharge), river basin information (such as geographical position, water body background and basic condition of an offshore river basin), chemical fingerprint information of the pollution source (such as information of harmfulness, physicochemical property and the like of various types of pollution) and the like, and parameters of characteristics of the chemical fingerprint data to be verified can be marked. Optionally, in the chemical fingerprint database of contaminants in the offshore area, different chemical fingerprint data to be verified correspond to different tag parameters, and the chemical fingerprint data to be verified in the chemical fingerprint database of contaminants in the offshore area can be distinguished through the tag parameters.
And determining the pollution type corresponding to the chemical fingerprint data to be verified according to the label parameters. Optionally, the information of various pollution sources of the chemical fingerprint data to be verified can be determined according to the tag information, so that the pollution type corresponding to the chemical fingerprint data to be verified is obtained. The pollution type is determined through the label information corresponding to the chemical fingerprint data to be verified, the source of the water body pollutants in the offshore area can be quickly and accurately traced, and the practicability is high.
Referring to fig. 2, in some embodiments of the present invention, the pollution tracing method further includes establishing a chemical fingerprint database of contaminants in the offshore area, specifically including:
step S200, water environment data of the target offshore area are obtained, and the water environment data comprise: and (4) re-point pollution source data of offshore areas.
The preset offshore area can be a preset offshore area needing to investigate the distribution condition of the pollution source; the aquatic environment data may include: presetting characteristic pollutants in the water environment of the offshore area and presetting pollution source types and emission conditions around the offshore area; the offshore area heavy pollution source data can be related data of preset offshore area heavy pollution sources. Optionally, water environment information of each preset offshore area can be collected according to requirements, specifically: through collection, arrangement and analysis of relevant data (such as public complaints, pollution source general survey databases, pollution source files, environment monitoring data, environmental assessment reports and the like), the distribution situation of the pollution sources in the offshore area is mastered and researched, investigation and evaluation are carried out on the water environment in the offshore area, and the obtained water environment information comprises: characteristic pollutants in the water environment of the offshore area and pollution source types and emission conditions around the offshore area. Then, a representative pollution source with a prominent influence is screened out from the data as a heavy-point pollution source to be further investigated, for example, the heavy-point pollution source can be investigated on site (including distribution, sampling and analysis tests), distribution and sampling are performed according to factors such as a production process, a production flow, a pollutant generation mechanism and a discharge form of the pollution source, and the heavy-point pollution source is screened out by a discharge load estimation method, so that the data of the heavy-point pollution source in the offshore area can be extracted.
And step S210, extracting target chemical fingerprint indexes and pollution source sample data from the heavy-point pollution source data.
The target chemical fingerprint index can be a plurality of indexes related to the water body in the important point pollution source data; the pollution source sample data can be related data of a preset offshore area water body and a pollution source sample in the heavy-point pollution source data. Optionally, several indexes of the water body of the heavy pollution source can be screened as target chemical fingerprint indexes, such as metal (cadmium, chromium, lead, mercury, manganese, iron, and the like), nonmetal (arsenic, phosphorus), petroleum, organic matter (chemical oxygen demand, organic carbon, dissolved oxygen), nutrient salt (inorganic nitrogen, ammonia nitrogen, total phosphorus, total nitrogen, nitrate nitrogen, and the like), pesticides and other characteristic pollutant indexes, and the other characteristic pollutant indexes are pollutant indexes with regional characteristics and optimal control pollutant indexes with significant ecological effect besides the indexes, and the indexes can be used as target chemical fingerprint indexes. Sampling and preprocessing can be carried out on a preset offshore area water body and a heavy-point pollution source sample to obtain pollution source sample data.
And step S220, analyzing and testing the target chemical fingerprint indexes according to the pollution source sample data to obtain target chemical fingerprint data.
The target chemical fingerprint data may be fingerprint index data corresponding to a preset offshore area. Optionally, an organic matter index may be selected from the target chemical fingerprint indexes, and a GC-MS method is used to perform qualitative and quantitative analysis on the target chemical fingerprint index and the organic matter in the collected pollution source sample data, so as to obtain target chemical fingerprint data. In some specific embodiments, the above test method is as follows: a50 mL water sample is extracted once with 5mL dichloromethane (volume ratio of filtrate to dichloromethane is 10:1), shaken for 5min, and kept stand for 30 min. The collected organic phase was dried over anhydrous sodium sulfate and transferred to a clean glass vial for testing. And qualitatively analyzing the organic pollutants in the wastewater in a mode of comparing a preset NIST mass spectrogram database with the mass spectrogram of the measured sample. Each organic substance was semi-quantitatively analyzed using different scale lines according to the substance class. For organic matters which do not meet the requirements of semi-quantitative determination and need to be accurately determined, extraction under different pH values can be considered, and the influence of suspended matters on the determination needs to be researched.
And step S230, determining a target pollution source according to the target chemical fingerprint data.
Optionally, the pollution source information corresponding to the water environment data of the target offshore area may be judged according to the target chemical fingerprint data, that is, the target pollution source corresponding to the target chemical fingerprint data is determined.
And step S240, establishing a chemical fingerprint database of the offshore area pollutants according to the target chemical fingerprint data and the target pollution source.
Optionally, an offshore area pollutant chemical fingerprint database may be established according to a one-to-one correspondence relationship between the target chemical fingerprint data and the target pollution sources, where information in the offshore area pollutant chemical fingerprint database includes: watershed information including geographic location, water background, basic conditions and the like of an offshore watershed; pollution source information including manufacturer address, emission rule, emission characteristics and the like; chemical fingerprint information of pollution sources, harmfulness, physicochemical properties and other information of various kinds of pollution; and the water environment basic situation of the offshore area; emission rules, emission characteristics, chemical fingerprint data and other characteristic information of the pollution source. By establishing the chemical fingerprint database of the offshore area pollutants, the frequent offshore area water pollution accidents can be quickly responded, so that the pollution sources can be quickly identified by a system, a complete source analysis method and a corresponding data information system when the offshore area water pollution problem is faced by the environmental management departments in future, and pollution prevention and control are performed.
In some embodiments of the invention, determining a target contamination source from target chemical fingerprint data comprises:
and obtaining the tracing label data of the target chemical fingerprint data. Wherein, the tracing label data may include: the type of a pollution source (such as a land source and a sea source) corresponding to the target chemical fingerprint data mainly comprises industrial, agricultural and domestic sewage and pollutants input into the sea through rivers, the sea source comprises marine aquaculture, fishing port pollution and ship pollution discharge), river basin information (such as geographical position, water body background and basic condition and the like of an offshore river basin), pollution source chemical fingerprint information (such as information of harmfulness, physicochemical property and the like of various types of pollution) and the like, and parameters of characteristics of the target chemical fingerprint data can be marked.
And determining a target pollution source according to the tracing label data. Optionally, the information of various pollution sources of the target chemical fingerprint data can be determined according to the traceable label data, so that the target pollution source corresponding to the target chemical fingerprint data is obtained. The target pollution source is determined through the traceable label data corresponding to the target chemical fingerprint data, the source of the water body pollutants in the offshore area can be rapidly and accurately traced, and the practicability is high.
Referring to fig. 3, a pollution tracing apparatus according to a second aspect of the present invention includes:
an obtaining module 300, configured to obtain water pollution data of an offshore area to be detected, where the water pollution data includes: chemical fingerprint data to be detected;
the extraction module 310 is configured to extract chemical fingerprint data to be verified and a pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of contaminants in the offshore area;
the calculating module 320 is configured to calculate a similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset tracing model;
and the source tracing module 330 is configured to determine a pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type.
By implementing the pollution tracing method of the embodiment of the first aspect of the invention, the pollution tracing device can trace the source of the pollution quickly and accurately, and realize the safety guarantee of the water quality of the offshore area and the prevention and control of the water pollution risk of the watershed.
Referring to fig. 4, an embodiment of the third aspect of the present invention further provides a functional module diagram of an electronic device, including: at least one processor 400, and a memory 410 communicatively coupled to the at least one processor 400; and the system also comprises a data transmission module 420, a camera 430 and a display screen 440.
The processor 400 is configured to execute the pollution tracing method in the first embodiment by calling a computer program stored in the memory 410.
The data transmission module 420 is connected to the processor 400, and is used for implementing data interaction between the data transmission module 420 and the processor 400.
The cameras 430 may include a front camera and a rear camera. Generally, a front camera is disposed at a front panel of the terminal, and a rear camera is disposed at a rear surface of the terminal. In some embodiments, the number of the rear cameras is at least two, and each rear camera is any one of a main camera, a depth-of-field camera, a wide-angle camera and a telephoto camera, so that the main camera and the depth-of-field camera are fused to realize a background blurring function, and the main camera and the wide-angle camera are fused to realize panoramic shooting and VR (Virtual Reality) shooting functions or other fusion shooting functions. In some embodiments, camera 430 may also include a flash. The flash lamp can be a monochrome temperature flash lamp or a bicolor temperature flash lamp. The double-color-temperature flash lamp is a combination of a warm-light flash lamp and a cold-light flash lamp, and can be used for light compensation at different color temperatures.
The display screen 440 may be used to display information entered by the user or provided to the user. The Display screen 440 may include a Display panel, and optionally, the Display panel may be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), or the like. Further, the touch panel may cover the display panel, and when the touch panel detects a touch operation thereon or nearby, the touch panel transmits the touch operation to the processor 400 to determine the type of the touch event, and then the processor 400 provides a corresponding visual output on the display panel according to the type of the touch event. In some embodiments, the touch panel may be integrated with the display panel to implement input and output functions.
The memory, as a non-transitory storage medium, may be used to store a non-transitory software program and a non-transitory computer executable program, such as the pollution tracing method in the embodiment of the first aspect of the present invention. The processor implements the pollution tracing method in the first embodiment by executing the non-transitory software program and the instructions stored in the memory.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store the pollution tracing method in the embodiment of the first aspect. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and these remote memories may be connected to the terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The non-transitory software programs and instructions required to implement the pollution traceability method in the first aspect of the embodiment described above are stored in the memory, and when executed by the one or more processors, perform the pollution traceability method in the first aspect of the embodiment described above.
Embodiments of the fourth aspect of the present invention also provide a computer-readable storage medium storing computer-executable instructions for: the pollution tracing method in the first aspect embodiment is performed.
In some embodiments, the storage medium stores computer-executable instructions, which are executed by one or more control processors, for example, by one of the processors in the electronic device of the third aspect, and may cause the one or more processors to perform the pollution tracing method in the first aspect.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
The above-described embodiments of the apparatus are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (10)
1. The pollution source tracing method is characterized by comprising the following steps:
acquiring water pollution data of an offshore area to be detected, wherein the water pollution data comprises: chemical fingerprint data to be detected;
extracting chemical fingerprint data to be verified and a pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of contaminants in the offshore area;
calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset tracing model;
and determining a pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type.
2. The method according to claim 1, wherein the determining the pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type comprises:
comparing the similarity with a preset threshold value;
and if the similarity is greater than or equal to the preset threshold, determining a pollution source corresponding to the chemical fingerprint data to be detected according to the pollution type.
3. The method of claim 2, further comprising:
and if the similarity is smaller than the preset threshold, skipping to the step of extracting the chemical fingerprint data to be verified and the pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of the offshore area pollutants.
4. The method according to claim 1, wherein the calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset tracing model comprises:
performing numerical comparison on the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using the tracing model to obtain a comparison result;
and obtaining the similarity according to the comparison result.
5. The method according to claim 1, wherein the extracting of the chemical fingerprint data to be verified and the pollution type corresponding to the chemical fingerprint data to be verified from the preset chemical fingerprint database of contaminants in the offshore area comprises:
extracting the chemical fingerprint data to be verified from the chemical fingerprint database of the offshore area pollutants;
acquiring label parameters corresponding to the chemical fingerprint data to be verified;
and determining the pollution type corresponding to the chemical fingerprint data to be verified according to the label parameters.
6. The method according to claim 5, further comprising building the offshore area contaminant chemical fingerprint database, specifically comprising:
acquiring water environment data of a target offshore area, wherein the water environment data comprises: offshore area heavy pollution source data;
extracting target chemical fingerprint indexes and pollution source sample data from the heavy-point pollution source data;
analyzing and testing the target chemical fingerprint index according to the pollution source sample data to obtain target chemical fingerprint data;
determining a target pollution source according to the target chemical fingerprint data;
and establishing the chemical fingerprint database of the offshore area pollutants according to the target chemical fingerprint data and the target pollution source.
7. The method of claim 6, wherein determining a target contamination source from the target chemical fingerprint data comprises:
obtaining traceability label data of the target chemical fingerprint data;
and determining the target pollution source according to the source tracing label data.
8. Pollution traceability device, characterized by includes:
the acquisition module is used for acquiring water pollution data of an offshore area to be detected, and the water pollution data comprises: chemical fingerprint data to be detected;
the extraction module is used for extracting chemical fingerprint data to be verified and a pollution type corresponding to the chemical fingerprint data to be verified from a preset chemical fingerprint database of the offshore area pollutants;
the calculation module is used for calculating the similarity between the chemical fingerprint data to be detected and the chemical fingerprint data to be verified by using a preset traceability model;
and the source tracing module is used for determining a pollution source corresponding to the chemical fingerprint data to be detected according to the similarity and the pollution type.
9. An electronic device, comprising:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions for execution by the at least one processor to cause the at least one processor, when executing the instructions, to implement the pollution traceability method of any one of claims 1 to 7.
10. A computer-readable storage medium, wherein the storage medium stores computer-executable instructions for causing a computer to perform the pollution traceability method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110345382.1A CN113034013A (en) | 2021-03-31 | 2021-03-31 | Pollution tracing method and device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110345382.1A CN113034013A (en) | 2021-03-31 | 2021-03-31 | Pollution tracing method and device, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113034013A true CN113034013A (en) | 2021-06-25 |
Family
ID=76453149
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110345382.1A Pending CN113034013A (en) | 2021-03-31 | 2021-03-31 | Pollution tracing method and device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113034013A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114002403A (en) * | 2021-10-19 | 2022-02-01 | 上海科泽智慧环境科技有限公司 | Ammonia nitrogen automatic analysis method and device, computer equipment and storage medium |
| CN114184751A (en) * | 2021-11-11 | 2022-03-15 | 深圳市宇驰检测技术股份有限公司 | Sectional type pipe network pollutant tracing device and system |
| CN115424143A (en) * | 2022-08-29 | 2022-12-02 | 南方海洋科学与工程广东省实验室(广州) | Water source pollution tracing method and device, storage medium and computer equipment |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102661939A (en) * | 2012-05-15 | 2012-09-12 | 北京化工大学 | Method for rapidly tracing to water pollution source |
| KR20140016031A (en) * | 2012-07-30 | 2014-02-07 | 서울대학교산학협력단 | System and method for identify contaminant sources |
| CN109711674A (en) * | 2018-12-03 | 2019-05-03 | 北京师范大学 | A kind of finger-print base construction method and device traced to the source for lake and reservoir water pollution |
| CN110412006A (en) * | 2018-04-26 | 2019-11-05 | 北京化工大学 | A method of realizing that water pollution is traced to the source online |
| CN111272931A (en) * | 2020-02-17 | 2020-06-12 | 江苏一片叶高新科技有限公司 | Method for tracing origin of tea |
| CN112418426A (en) * | 2020-11-19 | 2021-02-26 | 中科三清科技有限公司 | Drain pollutant emission tracing method and device, computing equipment and storage medium |
| CN112505282A (en) * | 2020-12-25 | 2021-03-16 | 生态环境部南京环境科学研究所 | Real-time accurate tracing early warning method and system for environmental water pollution |
-
2021
- 2021-03-31 CN CN202110345382.1A patent/CN113034013A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102661939A (en) * | 2012-05-15 | 2012-09-12 | 北京化工大学 | Method for rapidly tracing to water pollution source |
| KR20140016031A (en) * | 2012-07-30 | 2014-02-07 | 서울대학교산학협력단 | System and method for identify contaminant sources |
| CN110412006A (en) * | 2018-04-26 | 2019-11-05 | 北京化工大学 | A method of realizing that water pollution is traced to the source online |
| CN109711674A (en) * | 2018-12-03 | 2019-05-03 | 北京师范大学 | A kind of finger-print base construction method and device traced to the source for lake and reservoir water pollution |
| CN111272931A (en) * | 2020-02-17 | 2020-06-12 | 江苏一片叶高新科技有限公司 | Method for tracing origin of tea |
| CN112418426A (en) * | 2020-11-19 | 2021-02-26 | 中科三清科技有限公司 | Drain pollutant emission tracing method and device, computing equipment and storage medium |
| CN112505282A (en) * | 2020-12-25 | 2021-03-16 | 生态环境部南京环境科学研究所 | Real-time accurate tracing early warning method and system for environmental water pollution |
Non-Patent Citations (2)
| Title |
|---|
| 宋雪健等: "近红外光谱技术在食品溯源中的应用进展", 食品研究与开发, no. 12, 20 June 2017 (2017-06-20), pages 197 - 200 * |
| 苏学素;张晓焱;焦必宁;曹维荃;: "基于近红外光谱的脐橙产地溯源研究", 农业工程学报, no. 15, 1 August 2012 (2012-08-01), pages 240 - 245 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114002403A (en) * | 2021-10-19 | 2022-02-01 | 上海科泽智慧环境科技有限公司 | Ammonia nitrogen automatic analysis method and device, computer equipment and storage medium |
| CN114002403B (en) * | 2021-10-19 | 2023-09-01 | 上海科泽智慧环境科技有限公司 | Ammonia nitrogen automatic analysis method, ammonia nitrogen automatic analysis device, computer equipment and storage medium |
| CN114184751A (en) * | 2021-11-11 | 2022-03-15 | 深圳市宇驰检测技术股份有限公司 | Sectional type pipe network pollutant tracing device and system |
| CN114184751B (en) * | 2021-11-11 | 2023-11-21 | 深圳市宇驰检测技术股份有限公司 | Sectional type pipe network pollutant traceability device and system |
| CN115424143A (en) * | 2022-08-29 | 2022-12-02 | 南方海洋科学与工程广东省实验室(广州) | Water source pollution tracing method and device, storage medium and computer equipment |
| CN115424143B (en) * | 2022-08-29 | 2024-05-28 | 南方海洋科学与工程广东省实验室(广州) | Water source pollution tracing method and device, storage medium and computer equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113034013A (en) | Pollution tracing method and device, electronic equipment and storage medium | |
| Corradini et al. | Microplastics occurrence and frequency in soils under different land uses on a regional scale | |
| Li et al. | Using self-organizing map for coastal water quality classification: Towards a better understanding of patterns and processes | |
| Hua | Land use land cover changes in detection of water quality: a study based on remote sensing and multivariate statistics | |
| Li et al. | Integrated assessment of heavy metal contamination in sediments from a coastal industrial basin, NE China | |
| CN110376343B (en) | Method and device for accurately diagnosing pollution source and electronic device | |
| Wang et al. | Assessment of surface water quality via multivariate statistical techniques: a case study of the Songhua River Harbin region, China | |
| Allan et al. | Strategic monitoring for the European water framework directive | |
| Posthuma et al. | Eco-epidemiology of aquatic ecosystems: Separating chemicals from multiple stressors | |
| Angeler et al. | Temporal scales and patterns of invertebrate biodiversity dynamics in boreal lakes recovering from acidification | |
| Mavukkandy et al. | Assessment and rationalization of water quality monitoring network: a multivariate statistical approach to the Kabbini River (India) | |
| Ismail et al. | Chemometric techniques in oil classification from oil spill fingerprinting | |
| Mai et al. | Measurement, quantification, and potential risk of microplastics in the mainstream of the Pearl River (Xijiang River) and its estuary, Southern China | |
| Zhang et al. | Novel method for industrial sewage outfall detection: Water pollution monitoring based on web crawler and remote sensing interpretation techniques | |
| CN113706127B (en) | Water area analysis report generation method and electronic equipment | |
| Aghadadashi et al. | Using GIS, geostatistics and Fuzzy logic to study spatial structure of sedimentary total PAHs and potential eco-risks; An Eastern Persian Gulf case study | |
| Lill et al. | Isolation and connectivity: relationships between periodic connection to the ocean and environmental variables in intermittently closed estuaries | |
| Roig et al. | The use of field studies to establish the performance of a range of tools for monitoring water quality | |
| Anthony et al. | Trends in marine pollution mitigation technologies: Scientometric analysis of published literature (1990-2022) | |
| Parsons et al. | A bioassessment of lakes in the Athabasca Oil Sands Region, Alberta, using benthic macroinvertebrates | |
| Marchant et al. | Evaluation and application of methods for biological assessment of streams: summary of papers | |
| Yilmaz et al. | Marine mucilage mapping with explained deep learning model using water-related spectral indices: a case study of Dardanelles Strait, Turkey | |
| Yang et al. | Method for identifying outliers of soil heavy metal data | |
| CN115855898A (en) | Water quality fingerprint tracing method and system based on big data | |
| Di Lecce et al. | Online wastewater monitoring system using solid state sensor |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |