CN113406287A - Regional protection aquatic organism water quality benchmark derivation method for optimally controlling heavy metal pollutant chromium - Google Patents
Regional protection aquatic organism water quality benchmark derivation method for optimally controlling heavy metal pollutant chromium Download PDFInfo
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Abstract
The invention provides a regional protection aquatic organism water quality benchmark derivation method for optimally controlling heavy metal pollutant chromium, which comprises the following steps: collecting and screening toxicity data, screening test species, importing the screened toxicity data into China-WQC, performing model fitting by taking lgSMAV as abscissa and cumulative probability as ordinate, and determining coefficient r according to the model fitting2The root mean square RMSE, the residual sum of squares SSE and the K-S test result to determine an optimal fitting model to obtain 5% species hazard concentration HC5And selecting an evaluation factor of 2, and determining a short-term reference value CMC and a long-term reference value CCC of the freshwater aquatic organisms by combining corresponding slowness ratios. The invention fully considers the difference of water quality standards under different biological systems in the derivation process, and is more in line with the national conditions of ChinaAnd the water environment management criterion can also effectively avoid over protection and under protection. Can provide reference for deducing the water quality standard of the regional heavy metal protection aquatic organisms.
Description
Technical Field
The invention relates to the field of water quality benchmark derivation, and provides a regional protection aquatic organism water quality benchmark derivation method for optimally controlling heavy metal pollutant chromium.
Background
The water quality standard is a scientific basis for determining the water environment management standard and is also a scientific basis for developing water environment quality evaluation and determining a water environment protection target and direction. The water environment reference and the standard jointly form an important guideline for water environment management, so that the aquatic organisms are protected from negative ecological effects caused by pollutants in the water body, and the important role in environmental protection is played. The water quality reference value is regional, the characteristics of biological systems in different regions are different, and the environmental behaviors and the toxicological effects of pollutants can be greatly different, so that the water quality reference value is different.
Although China has successively provided a series of legal rules and documents of relevant water quality standards, most of the derivation of the water quality reference value refers to developed countries such as the United states and Europe, and the toxicity data of local aquatic organisms cannot be systematically and comprehensively utilized to derive the water quality reference value in the selection of the toxicity data. Therefore, when a water quality standard is established, the research on water quality standards cannot be carried out according to the national conditions of China, so that the established water quality standard is difficult to reflect the regional characteristics of China and lacks scientific effectiveness. Moreover, the topography of China is complex, the environmental pollution is diversified, and the water environments of different watersheds have different regional characteristics due to differences of species, climate, geographical positions and the like. Therefore, basin or regional water environment management and pollution control should be established on the basis of national water quality benchmark derivation, so that scientific and effective protection of the water environment can be realized, and a powerful basis is provided for the construction of the ecological risk assessment of the heavy metal in the water body.
Disclosure of Invention
The invention aims to provide a derivation method for the water quality benchmark of regional protection aquatic organisms for optimally controlling heavy metal pollutant chromium, which provides effective protection for watershed or regional aquatic organisms and provides technical support for regional water environment management and water quality benchmark establishment.
In order to achieve the purpose, the invention provides the following technical scheme: a regional protection aquatic organism water quality benchmark derivation method for optimally controlling heavy metal pollutant chromium comprises the following specific steps:
(1) collection and screening of toxicity data
Toxicity data collection is derived from the published reports of toxicity databases at home and abroad and toxicity data obtained by carrying out corresponding heavy metal chromium toxicity experiments on local aquatic organisms. Because the water quality reference derivation needs to meet the biological data of the three-door five-family department, which meets the requirements of the guideline, the toxicity data needs to be supplemented by experiments aiming at the indigenous organisms under the condition that the collected data can not meet the derivation requirements. In the data collection part, after data collection, the obtained data needs to be evaluated and screened, the data of non-selected regional characteristic species are removed, and the data without setting the experiment of a control group and a blank group and the data with excessive difference of the death numbers of the control group are removed;
(2) principle of species selection
The most critical point for establishing regional water quality benchmark is that the aquatic organisms used for benchmark derivation need to be the species in the region. Screening effective data according to the biological system characteristics of the region, selecting representative aquatic organisms to complement the data, and finally using the two groups of data together for deducing the water quality benchmark;
(3) water quality benchmark derivation
Calculating average acute/chronic value
According to the formulas (1) to (2), SMAV and SMCV are calculated in a divided manner,
in the formula: SMAViSpecies mean acute value, μ g/L, for species i;
SMCVispecies mean chronic value, μ g/L, for species i;
m is the number of ATVs of the species i;
n is the number of CTV of the species i;
i-a species, dimensionless;
distribution test of toxicity data
For SMAViAnd SMCViRespectively carrying out normal distribution test, namely K-S test, if the normal distribution is not met, carrying out logarithmic transformation and then carrying out re-test, and carrying out species sensitivity distribution model fitting on data which are in accordance with the normal distribution according to the requirement of 'model fitting and evaluation', namely SSD model fitting;
calculating cumulative probability
The species SMAVi/SMCViOr the logarithm values are respectively sorted from small to large, the toxicity rank R is determined, the rank of the minimum toxicity value is 1, the rank of the second order is 2, the sequence is arranged in sequence, if the toxicity values of two or more species are the same, the two or more species are randomly arranged into continuous ranks, the number of the species under each rank is 1, the cumulative probability P of the species is respectively calculated, and the P is R/(N +1),
model fitting and evaluation
SMAVi/SMCViTaking the logarithm of base 10, and dividing lg (SMAV)i)/lg(SMCVi) As an argument in the model fitting, lg (SMAV)i)/lg(SMCVi) Corresponding P is a dependent variable, China-WQC is introduced to carry out SSD model fitting, and a decision system for model fitting is determinedNumber r2The method comprises the following steps of (1) determining an optimal fitting model according to results of Root Mean Square (RMSE), residual Sum of Squares (SSE) and K-S tests, wherein the independent variables are required to be positive numbers by a lognormal distribution model and a loglogistic distribution model;
(4) determination of a reference
Determining the acute/chronic 5% species hazard concentration HC according to the SSD curve fitted by the best fit model5And dividing the value by the evaluation factor to obtain the short-term water quality reference value of the freshwater aquatic organisms. And under the condition of insufficient chronic toxicity data, deriving and obtaining a long-term water quality reference value according to the acute-chronic ratio.
The toxicity data is collected and screened mainly by the following points:
a. the experimental method of the selected data is consistent with the national standard experimental method, and the selected data has clear physicochemical index measurement data and method requirements;
b. only local aquatic organisms in the region are selected, and species-related toxicity data of non-selected regions are removed;
c. in an acute toxicity experiment, when the tested species is daphnia type organisms, the experiment data with the longest period of 48h LC should be selected50/EC50As an experimental indicator of acute toxicity; the fish and other organisms are in 96h LC50Or EC50Shows that if the data of the same fish experiment is 96 hours, 24 hours, 48 hours and 72 hours are abandoned, the fish experiment is hours, the fish can not be fed during the acute toxicity test period, and LC50At a semi-lethal concentration, EC50Half maximal effect concentration;
d. selecting toxicity data with the lowest affecting concentration LOEC or the largest non-affecting concentration NOEC as the final value of the experiment for more than 14d as an experiment index in a chronic toxicity experiment;
e. in the experiment of aquatic plants, an acute toxicity experiment is used as a standard test of algae, and 96h LC is selected50/EC50Toxicity data of (a); the chronic toxicity test is adopted for the underwater acoustic vascular bundle plants, and long-term LC is selected50/EC50To show the results of toxicity experiments.
The species screening specifically requires the following:
1) carpidae in the class teleost;
2) non-cyprinid in the class teleost;
3) another family in the phylum vertebrates, other than 1) or 2);
4) a zooplankton;
5) a benthic animal;
6) an insect;
7) a family other than the phylum arthropoda or phylum chordata;
8) a member of any order of insects or any member not mentioned above;
9) contains at least one of the most sensitive phytoplankton or aquatic plant.
Compared with the prior art, the invention has the beneficial effects that: according to the method, through screening of local species, representative aquatic organisms are selected for reference derivation, and the toxicity data of local species and local species are highlighted, so that the reference value can be better suitable for water environment protection of watershed places, and the ecological environment can be more scientifically and effectively protected.
Drawings
FIG. 1 is a curve fitted to a model of the distribution of 5 SSD of chromium to lake Taihu aquatic organisms.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The following examples are set forth to provide those of ordinary skill in the art with a more complete understanding of the present invention, and are not to be construed as limiting the invention in any way.
In this embodiment, a water quality reference derivation method of heavy metal chromium is taken as an example, and the specific steps are as follows:
(1) collection and screening of toxicity data
After the toxicity data is collected, the data needs to be screened and removed, and the screening and removing principle is mainly based on the related documents of the United states EPA and the technical guidance of the quality standard of freshwater aquatic organisms issued by the China (HJ 831-2017). The method mainly comprises the following points:
a. the experimental method of the selected data is consistent with the national standard experimental method, and the selected data has definite physicochemical index measurement data and method requirements, such as exposure type, hydration factor, period length, exposure type and the like;
b. only local aquatic organisms in the region are selected, and non-regional species toxicity data are removed;
c. in the acute toxicity test, when the tested species is daphnia species, the test data (48h LC) with the longest period should be selected50/EC50) As an experimental indicator of acute toxicity; the fish and other organisms are in 96h LC50Or EC50The data of 24h, 48h and 72h are abandoned if the data of 96h exist in the same fish experiment. No feeding is needed during acute toxicity experiments;
d. selecting toxicity data with LOEC or NOEC as final value of the experiment for more than 14d as experiment index in chronic toxicity experiment;
e. in the experiment of aquatic plants, an acute toxicity experiment is used as a standard test of algae, and 96h LC is selected50/EC50Toxicity data of (a); the chronic toxicity test is adopted for the underwater acoustic vascular bundle plants, and long-term LC is selected50/EC50To show the results of toxicity experiments;
(2) species screening
The rejected and screened toxicity data meet the requirements of 'three-door eight-family', and according to the regional characteristics of China, the final toxicity data also meet at least three nutrition levels including primary producers, primary consumers and secondary consumers, so that the toxicity data can be used for deducing the water quality standard, and the specific screening requirements are as follows:
a. carpidae in the class teleost;
b. non-cyprinid in Osteichthyes (such as Hemisalanx laticifera, Pelteobagrus fulvidraco, Misgurni anguillicaudati, etc.);
c. another family (not a or b) in the phylum vertebrales (possibly in the class teleostean or in the class amphibian, etc.);
d. a zooplankton (e.g., cheilogramma, cyclopia, etc.);
e. a benthonic animal (such as Exopalaemon modestus, Cipangopaludina chinensis, Corbicula fluminea, Lumbriatus lumbricus, etc.);
f. an insect (such as Chironomus, Rotifer, Brachionus calycinus, and Chitosan);
g. a family other than the phylum Arthropoda or chordata (e.g., Protozoa, Annelida, Mollusca, etc.);
h. a member of any order of insects or any member not mentioned above;
i. contains at least one of the most sensitive phytoplankton or aquatic plant.
(3) Water quality benchmark derivation
54 reliable toxicity data are obtained through literature search collection and screening. These 54 acute data relate to 14 species in total, of which: 14 species of Taihu native soil, including Acute Toxicity Values (ATV) of the screened species such as crucian, pelteobagrus fulvidraco and chub widely distributed in Taihu lake water, and calculating the average acute toxicity value SMAV of the species according to a fitting formula (1). Arranged as in table 1:
TABLE 1 mean acute value and cumulative probability of chromium vs. Taihu lake aquatic species
(4) Model fitting and evaluation
And the normalized SMAV is brought into SPSS 26 software for normal test, and the K-S test result shows that the acute toxicity value data accords with normal distribution and meets the fitting requirement of an SSD model. And substituting the SMAV value into the software China-WQC to obtain the fitting results of the five models. Selecting a best-fit model, R thereof2Maximum, while the RMSE and SSE values are both smaller than the other four models, the simulation of this modelThe resultant is used as the basis for deducing the short-term water quality standard of the aquatic organisms protected by chromium. The fitting results are shown in table 2 below:
TABLE 2 chromium short-term Water quality reference model fitting results
(5) Fiducial determination
Determining the chromium acute 5% species hazard concentration HC according to the SSD curve fitted by the optimal fitting model562.66, and dividing by the evaluation factor 2 to obtain the short-term water quality reference value of 31 mug/L (rounded) for protecting aquatic organisms in the chrome Taihu lake region. According to the USEPA (1995) chromium acute-chronic ratio 2.917, a long-term water quality reference value of 22 mug/L (rounded) for protecting aquatic organisms in the chromium Taihu lake region is obtained.
Those skilled in the art should understand that the water quality monitoring in our country is lack and the local biological toxicity data is less extensive, and the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention; all equivalent changes and modifications made according to the present invention are covered by the claims of the present invention.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (3)
1. A regional protection aquatic organism water quality benchmark derivation method for optimally controlling heavy metal pollutant chromium is characterized by comprising the following specific steps:
(1) collection and screening of toxicity data
The toxicity data collection is from toxicity databases at home and abroad, publicly published file reports and toxicity data obtained by carrying out heavy metal toxicity experiments on the local aquatic organisms, after the data are collected, the obtained data are evaluated and screened, and data of non-regional characteristic species, data without setting a control group and blank group tests and data with overlarge difference of death numbers of the control group are removed;
(2) species screening
Selecting representative aquatic organisms according to the biological characteristics of the region to establish a water quality standard, and performing species inspection and screening on heavy metal toxicity experiments and data collected from a database;
(3) water quality benchmark derivation
Calculating average acute/chronic value
According to the formulas (1) to (2), SMAV and SMCV are calculated in a divided manner,
in the formula: SMAViSpecies mean acute value, μ g/L, for species i;
SMCVispecies mean chronic value, μ g/L, for species i;
ATV-acute toxicity value, μ g/L;
CTV-chronic toxicity value, μ g/L;
m-ATV of species iHThe number of the cells is two;
n-CTV of species iHThe number of the cells is two;
i-a species, dimensionless;
distribution test of toxicity data
For SMAViAnd SMCViRespectively carrying out normal distribution test, namely K-S test, if the normal distribution is not met, carrying out re-test after logarithmic transformation, and according to the requirement of 'model fitting and evaluation' on data meeting the normal distributionPerforming species sensitivity distribution model fitting, namely SSD model fitting;
calculating cumulative probability
The species SMAVi/SMCViOr the logarithm values are respectively sorted from small to large, the toxicity rank R is determined, the rank of the minimum toxicity value is 1, the rank of the second order is 2, the sequence is arranged in sequence, if the toxicity values of two or more species are the same, the two or more species are randomly arranged into continuous ranks, the number of the species under each rank is 1, the cumulative probability P of the species is respectively calculated, and the P is R/(N +1),
model fitting and evaluation
SMAVi/SMCViTaking the logarithm of base 10, and dividing lg (SMAV)i)/lg(SMCVi) As an argument in the model fitting, lg (SMAV)i)/lg(SMCVi) Corresponding P is a dependent variable, China-WQC is led in to carry out SSD model fitting, and the determining coefficient r of the model fitting is used2The method comprises the following steps of (1) determining an optimal fitting model according to results of Root Mean Square (RMSE), residual Sum of Squares (SSE) and K-S tests, wherein the independent variables are required to be positive numbers by a lognormal distribution model and a loglogistic distribution model;
(4) determination of a reference
Determining the acute/chronic 5% species hazard concentration HC according to the SSD curve fitted by the best fit model5And dividing the water quality standard value by the evaluation factor to obtain the water quality standard value of the freshwater aquatic organisms.
2. The method for deducing the water quality benchmark of the regional protection aquatic organism for the optimal control of the heavy metal pollutant chromium according to the claim 1, characterized in that the toxicity data is collected and screened mainly by the following points:
a. the experimental method of the selected data is consistent with the national standard experimental method, and the selected data has clear physicochemical index measurement data and method requirements;
b. only local aquatic organisms in the region are selected, and species-related toxicity data of non-selected regions are removed;
c. in an acute toxicity experiment, when the tested species is daphnia type organisms, the experiment data with the longest period of 48h LC should be selected50/EC50As an experimental indicator of acute toxicity; the fish and other organisms are in 96h LC50Or EC50Shows that if the data of the same fish experiment is 96 hours, 24 hours, 48 hours and 72 hours are abandoned, h is hour, no feeding is carried out during the acute toxicity test period, and LC50At a semi-lethal concentration, EC50Half maximal effect concentration;
d. selecting toxicity data with the lowest affecting concentration LOEC or the largest non-affecting concentration NOEC as the final value of the experiment for more than 14d as an experiment index in a chronic toxicity experiment;
e. in the experiment of aquatic plants, an acute toxicity experiment is used as a standard test of algae, and 96h LC is selected50/EC50Toxicity data of (a); the chronic toxicity test is adopted for the underwater acoustic vascular bundle plants, and long-term LC is selected50/EC50To show the results of toxicity experiments.
3. The derivation method for the water quality standard of the regional protection aquatic organisms with the optimal control of the heavy metal pollutant chromium according to claim 1, wherein the species screening specifically requires the following steps:
1) carpidae in the class teleost;
2) non-cyprinid in the class teleost;
3) another family in the phylum vertebrates, other than 1) or 2);
4) a zooplankton;
5) a benthic animal;
6) an insect;
7) a family other than the phylum arthropoda or phylum chordata;
8) a member of any order of insects or any member not mentioned above;
9) contains at least one of the most sensitive phytoplankton or aquatic plant.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113917101A (en) * | 2021-10-09 | 2022-01-11 | 中国人民大学 | Method for predicting chronic toxicity of copper in watershed water environment and deriving long-term reference |
| CN113917102A (en) * | 2021-10-09 | 2022-01-11 | 中国人民大学 | Method for acquiring copper short-term water quality reference through parameter correction |
| CN117009767A (en) * | 2023-08-10 | 2023-11-07 | 中国环境科学研究院 | Soil benchmark formulation and risk assessment method based on bioavailability |
| CN118150564A (en) * | 2024-05-10 | 2024-06-07 | 哈尔滨工业大学(深圳)(哈尔滨工业大学深圳科技创新研究院) | Toxicity detection method, toxicity detection device, toxicity detection equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106508659A (en) * | 2016-11-08 | 2017-03-22 | 中国科学院水生生物研究所 | Cladophora fast cultivation method and device |
| CN109744177A (en) * | 2019-03-06 | 2019-05-14 | 中国科学院水生生物研究所 | A kind of system and method using separate type biological flocculation reactor for treatment cultivation tail water |
| CN111242442A (en) * | 2020-01-06 | 2020-06-05 | 中国海洋大学 | Method for obtaining water quality standard of estuary aquatic organisms |
| CN111861242A (en) * | 2020-07-28 | 2020-10-30 | 天津大学 | Derivation method for water quality reference value of heavy metal seawater aquatic organisms |
| CN112216342A (en) * | 2020-09-29 | 2021-01-12 | 天津大学 | Seawater aquatic organism water quality reference value derivation method for polybrominated diphenyl ether organic pollutants |
-
2021
- 2021-05-27 CN CN202110586764.3A patent/CN113406287A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106508659A (en) * | 2016-11-08 | 2017-03-22 | 中国科学院水生生物研究所 | Cladophora fast cultivation method and device |
| CN109744177A (en) * | 2019-03-06 | 2019-05-14 | 中国科学院水生生物研究所 | A kind of system and method using separate type biological flocculation reactor for treatment cultivation tail water |
| CN111242442A (en) * | 2020-01-06 | 2020-06-05 | 中国海洋大学 | Method for obtaining water quality standard of estuary aquatic organisms |
| CN111861242A (en) * | 2020-07-28 | 2020-10-30 | 天津大学 | Derivation method for water quality reference value of heavy metal seawater aquatic organisms |
| CN112216342A (en) * | 2020-09-29 | 2021-01-12 | 天津大学 | Seawater aquatic organism water quality reference value derivation method for polybrominated diphenyl ether organic pollutants |
Non-Patent Citations (2)
| Title |
|---|
| 中国环境科学研究院: "《百度文库》", 30 October 2020 * |
| 郭亮亮等: "富营养化湖泊刚毛藻建群特征及其影响因素", 《中国环境科学》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113917101A (en) * | 2021-10-09 | 2022-01-11 | 中国人民大学 | Method for predicting chronic toxicity of copper in watershed water environment and deriving long-term reference |
| CN113917102A (en) * | 2021-10-09 | 2022-01-11 | 中国人民大学 | Method for acquiring copper short-term water quality reference through parameter correction |
| CN113917101B (en) * | 2021-10-09 | 2024-01-12 | 中国人民大学 | Method for predicting chronic toxicity of copper in watershed water environment and deducing long-term reference |
| CN113917102B (en) * | 2021-10-09 | 2024-01-12 | 中国人民大学 | Method for obtaining copper short-term water quality standard through parameter correction |
| CN117009767A (en) * | 2023-08-10 | 2023-11-07 | 中国环境科学研究院 | Soil benchmark formulation and risk assessment method based on bioavailability |
| CN117009767B (en) * | 2023-08-10 | 2024-04-26 | 中国环境科学研究院 | Soil benchmark formulation and risk assessment method based on bioavailability |
| CN118150564A (en) * | 2024-05-10 | 2024-06-07 | 哈尔滨工业大学(深圳)(哈尔滨工业大学深圳科技创新研究院) | Toxicity detection method, toxicity detection device, toxicity detection equipment and storage medium |
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