New pollutant combined ecological risk assessment method based on webpage data crawling

Abstract

The invention provides a new pollutant joint ecological risk assessment method based on webpage data crawling, which comprises the following steps: performing data extraction on a plurality of set data source websites by adopting a web crawler program to obtain toxicity parameters and exposure parameters of new pollutants and interaction among the plurality of new pollutants; respectively obtaining the predicted concentration of each new pollutant; constructing an interaction model of the new pollutants according to the interaction, and acquiring a joint hazard index by adopting the interaction model according to the predicted concentration of the new pollutants with the interaction; and calculating a monomer hazard index according to the predicted concentration and the toxicity parameter of each independent new pollutant, and carrying out weighted summation on the combined hazard index and the plurality of monomer hazard indexes to obtain a comprehensive ecological risk index of the new pollutants. According to the invention, the problem of inaccurate ecological risk assessment in the prior art can be solved.

Description

Technical Field

[0001] This invention relates to the field of ecological risk assessment technology, and in particular to a novel method for joint ecological risk assessment of pollutants based on web crawling. Background Technology

[0002] New pollutants refer to chemical substances or objects that have not been widely recognized or studied in environmental science research, but have potential environmental risks. These pollutants may come from industrial emissions, agricultural activities, urban sewage, and byproducts generated in natural processes, posing a serious threat to ecosystems and human health, and may cause environmental pollution incidents such as eutrophication of water bodies and soil pollution.

[0003] Existing methods for assessing the ecological and environmental hazards of new pollutants assess the hazard of one particular new pollutant without considering the interactions between different new pollutants. Therefore, they cannot provide an accurate and comprehensive assessment of ecological risks. Summary of the Invention

[0004] This invention improves a new method for joint ecological risk assessment of pollutants based on web crawling, which can combine multiple new pollutants to assess ecological risk, thus solving the problem of inaccurate ecological risk assessment in existing technologies.

[0005] Specifically, this invention provides a novel method for joint ecological risk assessment of pollutants based on web page data crawling, including: A web crawler program was used to extract data from multiple designated data source websites to obtain environmental monitoring data, emission source data, and toxicological research data for various new pollutants. The toxicity parameters and exposure parameters of the corresponding new pollutants, as well as the interactions between the multiple new pollutants, are obtained based on the toxicological study data for each of the aforementioned new pollutants. Based on the emission source, environmental monitoring data, and exposure parameters of each new pollutant, the predicted concentration of each new pollutant is obtained, and based on the predicted concentration and toxicity parameters of each new pollutant, the individual hazard index of each new pollutant is predicted. An interaction model for the new pollutants is constructed based on the aforementioned interactions, and the joint hazard index of multiple new pollutants is obtained based on the predicted concentration of each new pollutant using the aforementioned interaction model. The combined hazard index and multiple individual hazard indices are weighted and summed to obtain the comprehensive ecological risk index of the new pollutant.

[0006] Furthermore, prior to the step of obtaining the toxicity parameters and exposure parameters of the corresponding new pollutant based on the toxicological study data for each of the aforementioned pollutants, the method further includes: The environmental monitoring data and toxicology research data are cleaned and then normalized and integrated on a set dimension.

[0007] Furthermore, the step of cleaning the environmental monitoring data and toxicology study data includes: Determine whether there are any conflicts in the toxicological study data for each of the aforementioned new pollutants; If it exists, the priority of the toxicological study data is obtained, and the toxicological study data of the new pollutant is determined according to the priority.

[0008] Further, the step of obtaining the predicted concentration of each new pollutant based on its emission source, environmental monitoring data, and exposure parameters includes: Each new pollutant hazard prediction model is constructed based on each of the aforementioned exposure parameters, and the predicted concentration of each new pollutant is obtained by using each of the aforementioned hazard prediction models based on the corresponding emission sources and environmental monitoring data.

[0009] Further, the step of constructing an interaction model of the new pollutant based on the interaction includes: An antagonistic sub-model is constructed based on the new pollutants with mutual antagonistic effects, and a synergistic sub-model is constructed based on the new pollutants with mutual synergistic effects. The antagonistic sub-model and the synergistic sub-model are then fused to obtain the interaction model.

[0010] Furthermore, prior to the step of weighted summation of the combined hazard index and the plurality of individual hazard indices, the method further includes: Obtain the correlation between the combined hazard index and each of the individual hazard indices and the comprehensive ecological risk index, and obtain the weight values ​​of the combined hazard index and each of the individual hazard indices based on the correlation.

[0011] Furthermore, after the step of weighted summation of the combined hazard index and multiple individual hazard indices to obtain the comprehensive ecological risk index of the new pollutant, the method further includes: Obtain the historical comprehensive ecological risk index of the new pollutant, and determine the ecological risk change rate of the new pollutant based on the historical comprehensive ecological risk index; Determine whether the rate of change of the ecological risk is greater than a set rate of change threshold; If so, the historical monomeric hazard index of each new pollutant is obtained, and an ecological optimization strategy is generated based on the historical monomeric hazard index of each new pollutant and the emission source.

[0012] Furthermore, after the step of weighted summation of the combined hazard index and multiple individual hazard indices to obtain the comprehensive ecological risk index of the new pollutant, the method further includes: Obtain the historical comprehensive ecological risk index of the new pollutant, the historical individual hazard index of each new pollutant, and the historical combined hazard index of multiple new pollutants; An ecological risk index change graph is constructed based on the historical comprehensive ecological risk index, historical individual hazard index, and historical combined hazard index.

[0013] In the technical solution of this invention, web crawlers are used to extract data from designated data source websites, ensuring the breadth of data extraction. This allows for the mining of environmental monitoring data, emission sources, and toxicological research data of new pollutants from the internet. This embodiment also combines interacting new pollutants to obtain a joint hazard index, and acquires the individual hazard index of each independent new pollutant. The joint hazard index and the individual hazard index are then fused using a weighted summation method to obtain a comprehensive ecological risk index for the new pollutants. This comprehensive ecological risk index considers not only the individual impact of each new pollutant but also the interactions between them, thereby improving the accuracy of ecological risk assessment.

[0014] The above and other objects, advantages and features of the present invention will become more apparent to those skilled in the art from the following detailed description of specific embodiments of the invention in conjunction with the accompanying drawings. Attached Figure Description

[0015] The following sections will describe some specific embodiments of the invention in detail by way of example and not limitation, with reference to the accompanying drawings. The same reference numerals in the drawings denote the same or similar parts or portions. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings: Figure 1 This is a flowchart illustrating a new pollutant joint ecological risk assessment method based on web page data crawling, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the data cleaning process for environmental monitoring data and toxicological research data of new pollutants according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the process for obtaining the predicted concentration of each new pollutant according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the process for weighted summation of the joint hazard index of a new pollutant and the individual hazard index of each new pollutant according to an embodiment of the present invention. Figure 5This is a flowchart illustrating a new pollutant joint ecological risk assessment method based on web page data crawling, according to another embodiment of the present invention. Detailed Implementation

[0016] The following reference Figures 1 to 5 This invention describes a novel method for joint ecological risk assessment of pollutants based on web scraping, according to an embodiment of the present invention. In this description, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature, that is, include one or more of that feature. In the description of the present invention, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. When a feature "includes or contains" one or more of the features it encompasses, unless otherwise specifically stated, this indicates that other features are not excluded and may be further included.

[0017] In the description of this embodiment, the terms "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0018] Please see Figure 1 , Figure 1 The diagram shown is a flowchart of a new pollutant joint ecological risk assessment method based on web page data crawling in one embodiment of the present invention. This method can obtain relevant data on new pollutants from multiple data source websites and assess the ecological risks caused by the new pollutants based on the relevant data, so as to solve the data limitations of existing assessment methods and improve the accuracy of assessment results.

[0019] Specifically, in Figure 1 The proposed method for joint ecological risk assessment of new pollutants includes the following steps: Step S101: Use a web crawler program to extract data from multiple designated data source websites to obtain environmental monitoring data, emission sources and toxicological research data of various new pollutants; Step S102: Obtain the toxicity parameters and exposure parameters of each new pollutant, as well as the interactions between each new pollutant, based on the toxicological study data of the new pollutants. Step S103: Based on the emission source, environmental monitoring data and exposure parameters of each new pollutant, obtain the predicted concentration of each new pollutant; Step S104: Construct an interaction model based on the interactions between new pollutants, and use the interaction model to obtain the joint hazard index based on the predicted concentrations of the new pollutants with interactions. Step S105: Calculate the individual hazard index of each new pollutant based on its predicted concentration and toxicity parameters. Step S106: The combined hazard index and individual hazard index of the new pollutant are weighted and summed to obtain the comprehensive ecological risk index of the new pollutant.

[0020] In step S101 above, the data source websites can include those of government environmental protection departments, research institutions, industry associations, and social media platforms. For each data source website, a corresponding web crawler is used to extract data based on its page type, thereby obtaining the text information from each website. For example, if the data source website's page type is a structured report page, XPath is used as the web crawler to extract data from that website; if the data source website's structure type is a dynamic news and information page, Selenium is used to simulate browser operations to load the entire content of the dynamic news and information page and capture its text information.

[0021] After extracting the text information from each designated data source website, a preset semantic recognition model can be used to perform semantic recognition on the extracted text information to obtain environmental monitoring data, emission sources, and toxicological research data of new pollutants.

[0022] In step S102 above, further semantic analysis can be performed on the toxicological study data of each new pollutant to obtain the toxicity parameters and exposure parameters of each new pollutant, and to obtain the interactions between multiple new pollutants.

[0023] In this embodiment, the toxicity parameters of the new pollutants may include organ toxicity, neurotoxicity, reproductive and developmental toxicity, immunotoxicity, endocrine disruption effects, carcinogenicity, teratogenicity, environmental persistence, and bioaccumulation. Among them, organ toxicity refers to substances such as perfluorinated compounds and short-chain chlorinated paraffins, which can damage organs such as the liver and kidneys, manifesting as cellular damage or dysfunction of the organs.

[0024] The neurotoxicity of novel pollutants refers to the potential impact of certain endocrine disruptors and brominated flame retardants on nervous system development or function, leading to behavioral abnormalities or cognitive decline. The reproductive and developmental toxicity of novel pollutants refers to the potential interference with the endocrine system by pollutants such as nonylphenol and antibiotics, causing decreased fertility, developmental abnormalities, or birth defects. The immunotoxicity of novel pollutants refers to the suppression of immune responses by pollutants such as perfluorinated organic compounds, thereby increasing the risk of infection or disease. Endocrine disruption is a typical characteristic of novel pollutants, meaning that endocrine disruptors, for example, can mimic or block hormone effects, leading to metabolic disorders or reproductive abnormalities. The carcinogenicity of novel pollutants refers to the potential for cancer to be caused by disinfection byproducts such as dichloromethane and trichloromethane through DNA damage. The teratogenicity of novel pollutants refers to the potential for embryonic developmental abnormalities at high doses or with prolonged exposure to antibiotics and certain organic compounds. The environmental persistence and bioaccumulation of new pollutants refer to the fact that new pollutants are often difficult to degrade, exist in the environment for a long time, and accumulate through the food chain. Examples include microplastics and persistent organic pollutants, whose toxicity increases with concentration.

[0025] Exposure parameters for new pollutants refer to parameters related to the exposing nature of new pollutants. Exposure nature refers to the characteristics of a new pollutant entering the environment and potentially coming into contact with the ecosystem. Its core aspects include the breadth of exposure pathways, the concealment of exposure levels, and the potential risks of exposure consequences. In this embodiment, the exposure parameters for new pollutants may include the transmission path of the new pollutant and its transmission speed along that path.

[0026] The interactions between new pollutants can include synergistic effects, antagonistic effects, additive effects, and independent effects. Synergistic effects between two new pollutants mean that when these two new pollutants are mixed together, they will react to enhance toxicity. Antagonistic effects between two new pollutants mean that when these two new pollutants are mixed together, they will resist each other and thus reduce toxicity. Additive effects between two new pollutants mean that these two new pollutants will not react with each other, and the resulting toxicity is the sum of the toxicities of the two new pollutants.

[0027] In step S103 above, the existing concentration of new pollutants can be obtained from environmental monitoring data, the concentration increment of each new pollutant can be obtained based on the emission source and exposure parameters of each new pollutant, and the predicted concentration of each new pollutant can be obtained by adding the existing concentration of each new pollutant to its corresponding concentration increment.

[0028] In step S104 above, the interactions between new pollutants can be synergistic, antagonistic, or independent. When new pollutants with synergistic effects are mixed, the toxicity of each new pollutant is enhanced; when new pollutants with antagonistic effects are mixed, the toxicity of each new pollutant is weakened; and when new pollutants with independent effects are mixed with other pollutants, their toxicity remains unchanged.

[0029] In this embodiment, an interaction model can be constructed based on new pollutants that exhibit synergistic or antagonistic effects. The predicted concentration of the new pollutant is then input into the interaction model to obtain the joint hazard index of the new pollutant. For ease of explanation of the technical solution of this invention, new pollutants that exhibit synergistic or antagonistic effects with other new pollutants are considered as interacting new pollutants, while new pollutants that exhibit independent effects with other new pollutants are considered as independent new pollutants.

[0030] In step S105 above, the higher the predicted concentration of a new pollutant, the stronger its ability to cause harm. Therefore, in this embodiment, the correspondence between the concentration and the hazard index of each new pollutant can be determined in advance based on the toxicity parameters of each new pollutant. Using this correspondence, the corresponding monomer hazard index can be obtained based on the predicted concentration of the new pollutant.

[0031] In step S106 above, assuming the number of independent new pollutant types is n, where the individual hazard index of the i-th new pollutant is... There are m pairs of new pollutants that interact with each other, where the joint hazard index between the j-th pair of new pollutants is... And if the comprehensive ecological risk index of the new pollutant is Z, then: in, The weight of the i-th independent new pollutant, Let the joint hazard weights be the values ​​between the j-th pair of new unchromatic individuals that interact with each other. As preset independent weights, The pre-defined joint weights, and As described above, this embodiment employs web crawlers to extract data from designated data source websites, ensuring the breadth of data extraction. This allows for the discovery of environmental monitoring data, emission sources, and toxicological research data on new pollutants from the internet. Furthermore, this embodiment combines interacting new pollutants to obtain a joint hazard index, and acquires the individual hazard index for each new pollutant. The joint hazard index and the individual hazard index are then fused using a weighted summation method to obtain a comprehensive ecological risk index for the new pollutants. This comprehensive ecological risk index considers not only the individual impact of each new pollutant but also the interactions between them, thereby improving the accuracy of ecological risk assessment.

[0032] In some embodiments of the present invention, before obtaining the toxicity parameters and exposure parameters of each new pollutant based on the toxicological study data of each new pollutant in step S102, the method further includes: performing data cleaning on the environmental monitoring data and toxicological study data of each new pollutant, and normalizing and integrating the environmental monitoring data and toxicological study data on a set dimension.

[0033] In this embodiment, data cleaning is performed on the environmental monitoring data and toxicological study data for each new pollutant. This involves removing duplicate data, erroneous data, and data irrelevant to the environment and ecology. For example, if the difference between a data value and its value at a previous or subsequent moment exceeds a set deviation threshold, the data value is determined to be erroneous. Keywords can be extracted from the collected data, and semantic recognition can be used to determine whether the collected data is relevant to the environment and ecology based on these keywords. Semantic recognition can also be used to determine whether the collected data describes the detection results of the same detection area at the same detection time; if so, it is determined that the collected data contains duplicate data.

[0034] After cleaning and processing the environmental monitoring data and toxicological research data for each new pollutant, the data format of each new pollutant is integrated into a unified setting format, which includes the name of the new pollutant, the detection area, and the detection time.

[0035] In this embodiment, after obtaining environmental monitoring data and toxicological study data for each new pollutant, data cleaning was performed to ensure the accuracy and purity of the data, thereby improving the accuracy of risk assessment. Furthermore, the data formats of the new pollutants were integrated into a unified set format, facilitating the analysis of the data to assess the impact of the new pollutants on ecological risks.

[0036] As described above, this embodiment employs web crawlers to extract data from designated data source websites, ensuring the breadth of data extraction. This allows for the discovery of environmental monitoring data, emission sources, and toxicological research data on new pollutants from the internet. Furthermore, this embodiment combines interacting new pollutants to obtain a joint hazard index, and acquires the individual hazard index for each new pollutant. The joint hazard index and the individual hazard index are then fused using a weighted summation method to obtain a comprehensive ecological risk index for the new pollutants. This comprehensive ecological risk index considers not only the individual impact of each new pollutant but also the interactions between them, thereby improving the accuracy of ecological risk assessment.

[0037] In some embodiments of the present invention, methods for data cleaning of environmental monitoring data and toxicological study data for each new pollutant are as follows: Figure 2 As shown, it includes the following steps: Step S201: Determine whether there are logical conflicts in the toxicological study data for each new pollutant; If it exists, proceed to step S202; Step S202: Obtain the priority of the data source website corresponding to the toxicological study data with logical conflicts, and determine the new pollutant toxicological study data according to the priority.

[0038] In this embodiment, if the toxicity parameters or exposure parameters of a new pollutant obtained from different designated data source websites are inconsistent, it can be determined that there is a logical conflict in the toxicological study data of the new pollutant. Therefore, the priority of each designated data source website for the new pollutant is obtained, and the toxicological study data of the new pollutant from the designated data source website with the highest priority is used as the standard to obtain the toxicity parameters and exposure parameters of the new pollutant.

[0039] In this embodiment, new pollutants with conflicting toxicological research data are processed according to the priority of the set data website. This not only prevents logical conflicts in the toxicological research data of each new pollutant, but also ensures the reliability and accuracy of the toxicological research data of each new pollutant.

[0040] In some embodiments of the present invention, step S103, based on the emission source, environmental monitoring data, and exposure parameters of each new pollutant, obtains the predicted concentration of each new pollutant using the following method: Figure 3 As shown, it includes the following steps: Step S211: Construct a hazard prediction model for each new pollutant based on its exposure parameters. Step S212: For each hazard prediction model, the predicted concentration of the corresponding new pollutant is obtained based on the corresponding emission source and environmental monitoring data.

[0041] In this embodiment, since exposure parameters can affect the spread of new pollutants, a hazard prediction model for new pollutants can be constructed based on the exposure parameters. Then, the emission source and environmental monitoring data of each new pollutant are input into its corresponding hazard prediction model to obtain the predicted concentration of each pollutant.

[0042] Assume the predicted concentration of one of the independent new pollutants is x, and the individual hazard index is... The hazard prediction model for this new pollutant is as follows: in, The preset matching coefficient.

[0043] This embodiment employs a hazard prediction model, which can quickly obtain the corresponding predicted concentration based on the emission source of new pollutants and environmental monitoring data, thereby improving the accuracy and efficiency of predicting new pollutant concentrations. In the above embodiments, a specific data model is used as the hazard prediction model for independent new pollutants; it is understood that the above embodiments are exemplary and not restrictive, and in other embodiments, a neural network-based prediction model can be used as the hazard prediction model for new pollutants.

[0044] In some embodiments of the present invention, the method of constructing an interaction model based on the interaction between multiple new pollutants in step S105 includes: constructing a corresponding sub-interaction model based on the interaction between each new pollutant, and merging multiple sub-interaction models to obtain an interaction model.

[0045] In this embodiment, an antagonistic sub-model can be constructed based on new pollutants with antagonistic interactions, and a synergistic sub-model can be constructed based on new pollutants with synergistic interactions. The antagonistic sub-model and the synergistic sub-model can then be fused to obtain an interaction model.

[0046] Assume the predicted concentration of one of the new pollutants is The predicted concentration of another new pollutant is Furthermore, the combined hazard index between these two new pollutants is... If the interaction between these two new pollutants is antagonistic, then the sub-interaction model between them is as follows: If the interaction between these two new pollutants is a synergistic effect, then the sub-interaction model between these two new pollutants is as follows: Where 'a' is the predicted concentration. The matching coefficient for the new pollutant, b is the predicted concentration. The matching coefficients for new pollutants are: c is a preset positive correction coefficient with a value greater than 0, d is a preset positive exponential coefficient, k is a preset negative correction coefficient with a value greater than 0, and r is a preset negative exponential coefficient.

[0047] Let F be the interaction model obtained by fusing multiple sub-action models, then: In this embodiment, constructing an interaction model based on the interactions between new pollutants can improve the accuracy and reliability of predicting the risks of new pollutants.

[0048] In the above embodiments, a specific data model was used as the sub-interaction model between new pollutants; it is understood that the above embodiments are exemplary and not restrictive, and in other embodiments, a neural network-based prediction model can be used as the sub-interaction model between new pollutants.

[0049] In some embodiments of the present invention, the method for weighted summation of the combined hazard index of the new pollutant and the individual hazard index of each new pollutant in step S106 is as follows: Figure 4 As shown, it includes the following steps: Step S221: Calculate the correlation between the individual hazard index of each new pollutant and the comprehensive ecological risk index; Step S222: Based on the correlation between the individual hazard index of each new pollutant and the comprehensive ecological risk index, obtain the combined hazard index and the weight value of each individual hazard index.

[0050] Specifically, the Pearson correlation between each new pollutant and the comprehensive ecological index can be calculated, and each weight value can be obtained based on the Pearson correlation.

[0051] Taking one of the new pollutants as an example, suppose the monomeric hazard index of one of the new pollutants at time t is... And the comprehensive ecological risk index at time t is The correlation L between the new pollutant and the comprehensive ecological risk index is: Where M represents the total number of samples for new pollutants and comprehensive ecological indices.

[0052] In this embodiment, the weight value of each new pollutant is determined based on the correlation between the individual hazard index and the comprehensive ecological risk index of each new pollutant. This ensures the accuracy of the weight value and improves the reliability of the ecological risk assessment.

[0053] In some embodiments of the present invention, such as Figure 5 As shown, after weighted summing of the combined hazard index of the new pollutant and the individual hazard index of each new pollutant in step S106 to obtain the comprehensive ecological risk index of the new pollutant, the process further includes: Step S107: Obtain the historical comprehensive ecological risk index of the new pollutant, and determine the ecological risk change rate of the new pollutant based on the historical comprehensive ecological risk index; Step S108: Determine whether the rate of change of the ecological risk of the new pollutant is greater than the set rate of change threshold; If so, proceed to step S109; Step S109: Obtain the historical single-unit hazard index of each new pollutant, and generate an ecological optimization strategy for emission sources based on the historical single-unit hazard index of each new pollutant.

[0054] In this embodiment, the historical single-item hazard index of each new pollutant and the single-item change rate of each new pollutant can be obtained, and the new pollutants whose single-item change rate is greater than the set single-item change threshold can be identified as target new pollutants. Then, the pollution source of the target new pollutant can be identified as the pollution source that needs to be treated.

[0055] In some embodiments of the present invention, after weighted summing of the combined hazard index of the new pollutant and the individual hazard index of each new pollutant in step S106 to obtain the comprehensive ecological risk index of the new pollutant, the method further includes: First, we obtained the historical comprehensive ecological risk index of multiple new pollutants, the historical individual hazard index of each new pollutant, and the historical combined hazard index of multiple new pollutants. Then, based on the above-mentioned historical comprehensive ecological risk index, historical individual hazard index and historical combined hazard index, an ecological risk index change map is constructed.

[0056] In this embodiment, a two-dimensional coordinate system is first constructed with time as the horizontal axis and the index value as the vertical axis. Then, the historical comprehensive ecological risk index, historical individual hazard index, and historical combined hazard index are loaded into the two-dimensional coordinate system, and adjacent points are connected to obtain the individual index change curve and the combined index change curve for each new pollutant, thereby generating an ecological risk index change map with the individual index change curve and the combined index change curve.

[0057] In this embodiment, after obtaining the comprehensive ecological risk index of the new pollutants, an ecological risk index change map is also constructed to facilitate the observation of the individual and combined change trends of each new pollutant.

[0058] The flowcharts provided in this embodiment are not intended to indicate that the operations of the method will be performed in any particular order, or that all operations of the method are included in all every case. Furthermore, each of the methods described above may include additional operations. Within the scope of the technical concept provided by the methods in this embodiment, additional variations can be made to the methods described above.

[0059] It should be understood that in some embodiments, the components may be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods may be implemented using software or firmware stored in memory and executed by a suitable instruction execution system.

[0060] Therefore, those skilled in the art should recognize that although numerous exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications conforming to the principles of the present invention can be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Thus, the scope of the present invention should be understood and construed as covering all such other variations or modifications.

Claims

1. A novel joint ecological risk assessment method for pollutants based on webpage data crawling, characterized in that, include: A web crawler program was used to extract data from multiple designated data source websites to obtain environmental monitoring data, emission source data, and toxicological research data for various new pollutants. The toxicity parameters and exposure parameters of the corresponding new pollutants, as well as the interactions between the multiple new pollutants, are obtained based on the toxicological study data for each of the aforementioned new pollutants. The predicted concentration of each new pollutant is obtained based on its emission source, environmental monitoring data, and exposure parameters. An interaction model for the new pollutant is constructed based on the interaction, and a joint hazard index is obtained based on the predicted concentration of the new pollutant with interaction using the interaction model. Each individual new pollutant is calculated based on its predicted concentration and toxicity parameters. The combined hazard index and multiple individual hazard indices are then weighted and summed to obtain the comprehensive ecological risk index of the new pollutant.

2. The method for joint ecological risk assessment of new pollutants according to claim 1, characterized in that, Prior to the step of obtaining the toxicity parameters and exposure parameters of the corresponding new pollutant based on the toxicological study data for each of the aforementioned pollutants, the method further includes: The environmental monitoring data and toxicology research data are cleaned and then normalized and integrated on a set dimension.

3. The method for joint ecological risk assessment of new pollutants according to claim 2, characterized in that, The steps for cleaning the environmental monitoring data and toxicology study data include: Determine whether there are any conflicts in the toxicological study data for each of the aforementioned new pollutants; If it exists, the priority of the toxicological study data is obtained, and the toxicological study data of the new pollutant is determined according to the priority.

4. The method for joint ecological risk assessment of new pollutants according to claim 1, characterized in that, The step of obtaining the predicted concentration of each new pollutant based on its emission source, environmental monitoring data, and exposure parameters includes: Each new pollutant hazard prediction model is constructed based on each of the aforementioned exposure parameters, and the predicted concentration of each new pollutant is obtained by using each of the aforementioned hazard prediction models based on the corresponding emission sources and environmental monitoring data.

5. The method for joint ecological risk assessment of new pollutants according to claim 1, characterized in that, The step of constructing an interaction model of the new pollutant based on the interaction includes: An antagonistic sub-model is constructed based on the new pollutants with mutual antagonistic effects, and a synergistic sub-model is constructed based on the new pollutants with mutual synergistic effects. The antagonistic sub-model and the synergistic sub-model are then fused to obtain the interaction model.

6. The method for joint ecological risk assessment of new pollutants according to claim 1, characterized in that, Prior to the step of weighted summation of the combined hazard index and the plurality of individual hazard indices, the method further includes: Obtain the correlation between the combined hazard index and each of the individual hazard indices and the comprehensive ecological risk index, and obtain the weight values ​​of the combined hazard index and each of the individual hazard indices based on the correlation.

7. The method for joint ecological risk assessment of new pollutants according to claim 1, characterized in that, After the step of weighted summation of the combined hazard index and multiple individual hazard indices to obtain the comprehensive ecological risk index of the new pollutant, the method further includes: Obtain the historical comprehensive ecological risk index of the new pollutant, and determine the ecological risk change rate of the new pollutant based on the historical comprehensive ecological risk index; Determine whether the rate of change of the ecological risk is greater than a set rate of change threshold; If so, the historical monomeric hazard index of each new pollutant is obtained, and an ecological optimization strategy is generated based on the historical monomeric hazard index of each new pollutant and the emission source.

8. The method for joint ecological risk assessment of new pollutants according to claim 1, characterized in that, After the step of weighted summation of the combined hazard index and multiple individual hazard indices to obtain the comprehensive ecological risk index of the new pollutant, the method further includes: Obtain the historical comprehensive ecological risk index of the new pollutant, the historical individual hazard index of each new pollutant, and the historical combined hazard index of multiple new pollutants; An ecological risk index change graph is constructed based on the historical comprehensive ecological risk index, historical individual hazard index, and historical combined hazard index.

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