A method for characterizing the toxicity of water pollutants based on the dose-effect relationship

Abstract

The present invention provides a method for characterizing the toxicity of water pollutants based on the dose-effect relationship. This method is based on the overall change characteristics of the dose-effect quantitative relationship curve between the inhibition rate of the toxicity response index of the test organism under the stress of different concentrations of pollutants and the pollutant concentration. It integrates variables representing the characteristics of the entire curve, such as the slope of the entire curve, the range of inhibition rate changes, the lowest effective concentration, and the highest effective concentration of the pollutant in the dose-effect quantitative relationship curve, to jointly construct a characterization parameter for the toxicity of water pollutants, so as to accurately obtain the toxicity intensity TI of the corresponding pollutant, and achieve a comprehensive and accurate judgment and characterization of the pollutant toxicity and an accurate comparison of the toxicities between different pollutants.

Description

Technical Field

[0001] The present invention belongs to the technical field of water quality detection, and particularly relates to a method for characterizing the toxicity of water pollutants based on the full curve characteristics of the dose-effect relationship Background Art

[0002] Water is the source of life, the key to production, and the foundation of the ecosystem. With the rapid development of China's social economy, industry, and agriculture, a large number of heavy metal pollutants, organic pollutants, pesticides, personal care products, antibiotics, and other new pollutants from industrial production, agricultural production, and people's daily lives enter the environment, resulting in increasingly severe water pollution problems in China. The water quality of various water bodies is deteriorating, and sudden water pollution incidents occur frequently. Different types of pollutants entering the water body will not only change the water environment but also have toxic effects on aquatic organisms, which will have an important impact on the normal growth, reproduction, and various physiological and metabolic processes of aquatic organisms, thus posing a serious threat to the entire aquatic ecosystem. Therefore, the rapid and accurate detection of the toxicity of water pollutants has very important practical significance for ensuring the safety of water environment quality and assessing the risk of the aquatic environment

[0003] In recent years, according to the effects of toxic pollutants on aquatic organisms such as the locomotor performance and mortality of fish, the reproductive rate and mortality of fleas, the luminescence characteristics of luminescent bacteria, the growth rate and photosynthetic activity of algae, and the response characteristics of various physiological indicators of corresponding aquatic organisms to toxic pollutants, a variety of water pollutant toxicity detection methods using fish, fleas, luminescent bacteria, and algae as test organisms have been gradually developed. However, whether it is the locomotor performance or mortality of fish, the reproductive rate or mortality of fleas, the luminescence intensity of luminescent bacteria, or the growth rate or photosynthetic activity of algae as the toxicity response index of pollutants, in the characterization of water pollutant toxicity, usually, the effect concentration ECx at a certain point on the dose-effect relationship curve between the inhibition rate of the toxicity response index of the test organism under the stress of toxic pollutants and the pollutant concentration (i.e., the concentration value of the pollutant corresponding to the occurrence of x% inhibition effect of the toxicity response index) is used to judge the toxicity level of the pollutant, and based on this, the toxicity of different pollutants is compared. However, when different toxicity effect points are selected, the comparison results between toxic pollutants may show inconsistent phenomena. For example, when comparing the toxicity of substance A and substance B, if the EC 20 value is used as the basis for judging the toxicity level, it is possible that the toxicity of substance A is greater than that of substance B (i.e., the EC 20 value of substance A is less than the EC 20 value of substance B), and when the EC 50 value is used as the basis for judging the toxicity level, it is possible that the toxicity of substance A is equal to that of substance B (i.e., the EC 50 value of substance A is equal to the EC 50value), or the toxicity of substance A is less than that of substance B (i.e., the EC 50 value of substance A is greater than the EC 50 value of substance B). Therefore, when different effect points are selected, the characterization results of pollutant toxicity may be inconsistent. Thus, it can be seen that it is somewhat one-sided to characterize the toxicity of pollutants based on the single-point information in the dose-effect relationship curve between the inhibition rate of the toxicity response index of the test organism and the pollutant concentration, and it is impossible to accurately determine the toxicity level of the pollutants, and thus it is impossible to accurately compare and analyze the toxicity strengths between different pollutants.

[0004] Therefore, aiming at the above problems, establishing an accurate method for characterizing the toxicity of water pollutants to accurately judge the toxicity level of pollutants is of great significance for water environment quality detection and evaluation and water ecological environment risk assessment. Summary of the Invention

[0005] The purpose of the present invention is to make up for the deficiencies of the existing technologies and provide a method for characterizing the toxicity of water pollutants based on the dose-effect relationship. This method uses the full-curve characteristics of the dose-effect relationship curve between the inhibition rate of the toxicity response index of the test organism and the pollutant concentration (including the lowest effect concentration, the inhibition rate of the toxicity response index corresponding to the lowest effect concentration, the highest effect concentration, the inhibition rate of the toxicity response index corresponding to the highest effect concentration, and the slope of the full curve between the lowest effect concentration and the highest effect concentration) as variables to jointly construct a toxicity characterization parameter, thereby determining the toxicity level of the pollutants, and solving the problem that it is relatively one-sided to judge the toxicity of pollutants only relying on the single-point effect concentration information in the dose-effect relationship curve and it is impossible to accurately evaluate the toxicity level of the pollution.

[0006] The technical solution of the present invention is: a method for characterizing the toxicity of water pollutants based on the dose-effect relationship, specifically including the following steps:

[0007] Step 1: Conduct exposure experiments of pollutants with different concentrations C1, C2, C3,..., C n on the test organisms, where n is the type of concentration, and the parallel samples of the test organism samples exposed to each concentration of pollutants and the blank control samples without exposure are all set to m; at the exposure time t, accurately measure the toxicity response indexes [(P n , P 1-1 ,..., P 1-2 ) of m parallel samples of the test organisms under the stress of different concentrations C1, C2, C3,..., C 1-m , (P 2-1 , P 2-2 ,..., P 2-m ), (P 3-1 , P 3-2 ,..., P3-m ) and so on, (P n-1 , P n-2 , and so on, P n-m )] and the toxicity response indices P of m parallel samples of the blank control under non-exposure 0-1 , P 0-2 , and so on, P 0-m ; Use the averaging method to calculate the average value of the toxicity response indices of the test organisms under the stress of each concentration C1, C2, C3,......, C n under the stress of pollutants and the average value of the toxicity response indices of the blank control under non-stress

[0008] Step 2: According to the obtained value and value, calculate the inhibition rates IR1, IR2, IR3,......, IR n of the toxicity response indices of the test organisms under the stress of different concentrations C1, C2, C3,......, C n ;

[0009] Step 3: Establish a dose-effect quantitative relationship curve between the pollutant concentration C1, C2, C3,......, C n and the inhibition rates IR1, IR2, IR3......IR n of the toxicity response indices of the test organisms at the exposure time t of the pollutant;

[0010] Step 4: Use one-way analysis of variance and Dunnett's post hoc multiple test methods to obtain the lowest effective concentration EC min of the pollutant and the inhibition rate IR min of the corresponding toxicity response index;

[0011] Step 5: Use one-way analysis of variance and Dunnett's post hoc multiple test methods to obtain the highest effective concentration EC max of the pollutant and the inhibition rate IR max of the corresponding toxicity response index;

[0012] Step 6: Obtain the full curve slope K of the curve between the lowest effective concentration EC min and the highest effective concentration EC max in the dose-effect quantitative relationship curve, which represents the rate of change of the inhibition of the toxicity response index P with the increase of the pollutant concentration;

[0013] Step 7: Take the pollutant concentrations C1, C2, C3,......, C nWith toxicity response indicators inhibition rates IR1, IR2, IR3......IR n The full curve slope K of the dose - effect quantitative relationship curve between them, the lowest effect concentration EC min And the corresponding inhibition rate IR min The highest effect concentration EC max And the corresponding inhibition rate IR max As variables, according to the formula 1, the characterization parameter model of water pollutant toxicity is established to calculate the characterization parameter TI of pollutant toxicity:

[0014]

[0015] Wherein, TI represents the toxicity intensity of the pollutant.

[0016] Beneficial effects:

[0017] Starting from the entire curve change characteristics of the pollutant dose - effect relationship curve, this invention constructs the characterization parameter of water pollutant toxicity jointly with variables representing the entire dose - effect relationship curve characteristics, such as the full curve slope in the whole curve, the change range of the inhibition rate, and the concentration range of the pollutant that causes a significant change in the toxicity response indicator inhibition rate in the curve, to solve the problems that in current toxicity judgment, only using the single - point effect concentration ECx (i.e., the concentration value of the pollutant corresponding to when the toxicity response indicator produces x% inhibition effect) of the dose - effect relationship curve to judge the pollutant toxicity is relatively one - sided, inaccurate, lacks universality, and cannot accurately compare the toxicity magnitudes between different pollutants, and can realize a more comprehensive and accurate judgment and characterization of water pollutant toxicity. Description of the drawings

[0018] Figure 1 Flow chart of the method for characterizing the toxicity of water pollutants based on the dose - effect relationship;

[0019] Figure 2 Toxicity response indicator PI values of three parallel samples of Chlorella pyrenoidosa and blank control samples under different concentrations of heavy metal Cd stress and the average values of the toxicity response indicators of the three parallel samples;

[0020] Figure 3 Toxicity response indicator PI values of three parallel samples of Chlorella pyrenoidosa and blank control samples under different concentrations of heavy metal Cu stress and the average values of the toxicity response indicators of the three parallel samples;

[0021] Figure 4 Inhibition rates of toxicity response indicators of Chlorella pyrenoidosa under different concentrations of heavy metal Cd stress;

[0022] Figure 5 Inhibition rates of toxicity response indicators of Chlorella pyrenoidosa under different concentrations of heavy metal Cu stress;

[0023] Figure 6 Quantitative dose - effect relationship curve of heavy metal Cd;

[0024] Figure 7 Quantitative dose - effect relationship curve of heavy metal Cu. Specific implementation manner

[0025] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0026] In this embodiment, the green alga Chlorella pyrenoidosa in freshwater microalgae in water is used as the test organism. According to the toxic effect that heavy metals inhibit the photosynthesis of microalgae, the chlorophyll fluorescence parameter PI, which characterizes the photosynthetic activity of microalgae, is used as the toxic response index. The effects of heavy metal pollutants Cd and Cu in water on the chlorophyll fluorescence parameter PI of Chlorella pyrenoidosa are studied, so as to obtain the toxic characterization parameters of heavy metals Cd and Cu, judge the toxicity levels of heavy metals Cd and Cu, and compare the toxicity intensities of the two.

[0027] The whole process of this method is as Figure 1 shown, and specifically includes the following steps:

[0028] Step 1: Conduct exposure experiments of pollutants Cd or Cu with different concentrations C1, C2, C3,..., C n on the test organism Chlorella pyrenoidosa. n is the type of concentration, and the parallel samples of the test organism samples exposed to each concentration of the pollutant and the blank control samples without exposure are set to m each; at the exposure time t, accurately measure the toxic response indexes [(P n 、P 1-1 、...、P 1-2 、...、P 1-m )、(P 2-1 、P 2-2 、...、P 2-m )、(P 3-1 、P 3-2 、...、P 3-m )、...、(P n-1 、P n-2 、...、P n-m )] of m parallel samples of the test organism under the stress of different concentrations of pollutants and the toxic response indexes P 0-1 、P0-2 、......、P 0-m ; Calculate the average values of each concentration C1, C2, C3,......, C respectively by using the average value method according to Formulas 1 and 2 n The average value of the toxicity response index of the test organism under pollutant stress And the average value of the toxicity response index of the blank control sample under non-stress

[0029]

[0030]

[0031] Wherein, Is the average value of the toxicity response index of the test organism under the stress of the pollutant with the concentration of C n .

[0032] In this embodiment, exposure experiments of different concentrations of heavy metal Cd and different concentrations of heavy metal Cu on Chlorella pyrenoidosa are firstly carried out. The concentrations of Cd in the Chlorella pyrenoidosa samples under the stress of heavy metal Cd are 0.002, 0.004, 0.009, 0.018, 0.036, 0.071, 0.142, 0.285, 0.570, 1.140 and 2.280 mmol / L respectively, and the concentrations of Cu in the Chlorella pyrenoidosa samples under the stress of heavy metal Cu are 0.004, 0.012, 0.016, 0.020, 0.024, 0.028, 0.032, 0.047, 0.063 and 0.126 mmol / L respectively. The parallel samples of the Chlorella pyrenoidosa samples exposed to each concentration of heavy metal Cd or heavy metal Cu and the blank control samples under non-exposure are 3 respectively, and the cell density of Chlorella pyrenoidosa in each sample is 5×10 5 cell / mL, and the sample volume is 20 mL. At the exposure time of 3 h, the PI values of the toxicity response indexes of the 3 parallel samples of Chlorella pyrenoidosa and the 3 parallel samples of the blank control sample under the stress of different concentrations of heavy metal Cd and the average value Value are as Figure 2 Shown, and the PI values of the toxicity response indexes of the 3 parallel samples of Chlorella pyrenoidosa and the 3 parallel samples of the blank control sample under the stress of different concentrations of heavy metal Cu and the average value Value are as Figure 3 Shown.

[0033] Step 2: According to the obtained Value and Value, calculate different concentrations C1, C2, C3,......, C respectively by using Formula 3 nThe inhibition rates IR1, IR2, IR3,......, IR of the toxicity response indexes of the test organisms under pollutant stress n .

[0034]

[0035] Where IR n is the inhibition rate of the toxicity response index of the test organism under the stress of pollutants with a concentration of C n .

[0036] In this embodiment, when the exposure time is 3 h, the inhibition rates of the toxicity response indexes of Chlorella pyrenoidosa under the stress of heavy metals Cd with concentrations of 0.002, 0.004, 0.009, 0.018, 0.036, 0.071, 0.142, 0.285, 0.570, 1.140, and 2.280 mmol / L are as Figure 4 shown, and the inhibition rates of the toxicity response indexes of Chlorella pyrenoidosa under the stress of heavy metals Cu with concentrations of 0.004, 0.012, 0.016, 0.020, 0.024, 0.028, 0.032, 0.047, 0.063, and 0.126 mmol / L are as Figure 5 shown.

[0037] Step 3: Use the Logistic model to establish the dose-effect quantitative relationship curve between the pollutant concentrations C1, C2, C3,......, C n and the inhibition rates IR1, IR2, IR3......IR n of the toxicity response indexes of the test organisms at the exposure time t.

[0038] In this embodiment, when the exposure time is 3 h, the dose-effect quantitative relationship curve between the concentration of heavy metal pollutant Cd and the inhibition rate of the toxicity response index PI of the test organism Chlorella pyrenoidosa established by the Logistic model is as Figure 6 shown, and the dose-effect quantitative relationship curve between the concentration of heavy metal pollutant Cu and the inhibition rate of the toxicity response index PI of the test organism Chlorella pyrenoidosa is as Figure 7 shown.

[0039] Step 4: Use one-way analysis of variance and Dunnett's post hoc multiple test method to test the toxicity response index values P n of the test organisms under the stress of each concentration C n-1 , P n-2 ,......, P n-m and the toxicity response index values P 0-1 , P 0-2 ,......, P 0-mWhether there is a significant difference to obtain the minimum value of the pollutant concentration when the toxicity response index of the stressed test organism is significantly different from that of the test organism in the blank control sample, which is the lowest effect concentration EC of the pollutant min ; Furthermore, based on the established quantitative dose-effect relationship curve between the pollutant concentrations C1, C2, C3,......, C n and the inhibition rates IR1, IR2, IR3,......, IR n of the toxicity response index, calculate the inhibition rate IR min of the toxicity response index corresponding to the lowest effect concentration EC min .

[0040] In this embodiment, when the exposure time is 3 h, one-way ANOVA and Dunnett's post hoc multiple test methods are used to test the toxicity response indexes PI n-1 , PI n-2 , PI n-3 of the test organism Chlorella pyrenoidosa under the stress of each concentration of heavy metal Cd or Cu and the toxicity response indexes PI 0-1 , PI 0-2 , PI 0-3 of the Chlorella pyrenoidosa in the blank control sample to obtain the lowest effect concentration EC min value of heavy metal Cd as 0.002 mmol / L, and the inhibition rate IR min of the toxicity response index corresponding to this lowest effect concentration calculated according to the dose-effect quantitative relationship curve is 7.01%; the lowest effect concentration EC min value of heavy metal Cu is 0.012 mmol / L, and the inhibition rate IR min of the toxicity response index corresponding to this lowest effect concentration calculated according to the dose-effect quantitative relationship curve is 10.30%.

[0041] Step 5: Use one-way ANOVA and Dunnett's post hoc multiple test methods to test whether there is a significant difference (Sig. < 0.05) between the toxicity response indexes P n and P n-1 of the test organism under the stress of adjacent concentration C n-1 , P n-2 , P n-3 ,......, P n-m and P (n-1)-1 , P (n-1)-2 , P (n-1)-3 ,......, P (n-1)-m to obtain the lowest value of the toxic pollutant concentration corresponding to when there is no significant change in the toxicity response indexes of the test organism under the stress of high-concentration pollutants, which is the highest effect concentration EC of the pollutantmax ; Further, according to the established pollutant concentrations C1, C2, C3,......, C n and the dose-effect quantitative relationship curves between the toxicity response indexes inhibition rates IR1, IR2, IR3,......, IR n calculate the inhibition rate IR of the toxicity response index corresponding to the highest effect concentration EC max . max .

[0042] In this embodiment, when the exposure time is 3 h, one-way ANOVA and Dunnett's post hoc multiple test methods are used to test whether there are significant differences between the toxicity response indexes of the test organism Chlorella pyrenoidosa under the stress of adjacent concentrations of heavy metal Cd and heavy metal Cu in the high concentration ranges of heavy metal Cd and heavy metal Cu, so as to obtain the highest effect concentration EC max of heavy metal Cd is 2.280 mmol / L, and the inhibition rate IR of the toxicity response index corresponding to this highest effect concentration calculated according to the dose-effect quantitative relationship curve max is 93.21%; the highest effect concentration EC max of the obtained heavy metal Cu is 0.063 mmol / L, and the inhibition rate IR of the toxicity response index corresponding to this highest effect concentration calculated according to the dose-effect quantitative relationship curve max is 97.57%.

[0043] Step 6: Divide the dose-effect quantitative relationship curve between the lowest effect concentration EC min and the highest effect concentration EC max of the pollutant into v segments according to the inhibition rate range of the toxicity response index. The pollutant concentration values and the corresponding toxicity response index inhibition rates at the endpoints of each segment of the curve are [(c1, IR'1)~(c2, IR'2)],......, [(c v , IR' v )~(c v+1 , IR' v+1 )]. Calculate the slopes k1, k2, k3,......, k v of each part of the curve according to formula 4 respectively:

[0044]

[0045] In the formula, c h and c h+1 respectively represent the pollutant concentration values at the starting point and the ending point in the h-th segment of the curve, and IR' h and IR' h+1respectively represent the inhibition rates of the toxicity response indicators at the starting point and the ending point in the h-th segment of the curve. Calculate the full curve slope K of the curve between the lowest effect concentration EC min and the highest effect concentration EC max according to Formula 5:

[0046]

[0047] In this embodiment, for the dose-effect quantitative relationship curve of heavy metal Cd and the dose-effect quantitative relationship curve of heavy metal Cu, divide the curve between the lowest effect concentration EC min and the highest effect concentration EC max into 10 segments according to the inhibition rate range of the toxicity response indicators. The concentration values of heavy metal pollutants Cd or Cu and the inhibition rates of the corresponding toxicity response indicators PI at the two endpoints of each segment of the curve are shown in Table 1 below. The slopes of each part of the curve calculated according to Formula 4 are also shown in Table 1 below. Then, in the dose-effect quantitative relationship curve between the heavy metal Cd concentration and the toxicity response indicator PI of Chlorella pyrenoidosa, the full curve slope K value of the curve between the lowest effect concentration EC min and the highest effect concentration EC max is 16.72. In the dose-effect relationship curve between the heavy metal Cu concentration and the toxicity response indicator PI of Chlorella pyrenoidosa, the full curve slope K value of the curve between the lowest effect concentration EC min and the highest effect concentration EC max is 45.55.

[0048] Table 1 Concentration values of pollutants and inhibition rates of corresponding toxicity response indicators PI and slopes of each part of the curve at the two endpoints of each segment of the dose-effect quantitative relationship curve of heavy metal Cd or Cu.

[0049]

[0050] Step 7: Using the full curve slope K of the dose-effect quantitative relationship curve between pollutant concentrations C1, C2, C3,..., C n and toxicity response indicator inhibition rates IR1, IR2, IR3,..., IR n , the lowest effect concentration EC min and its corresponding inhibition rate IR min , the highest effect concentration EC max and its corresponding inhibition rate IR max as variables, calculate the characterization parameter TI of pollutant toxicity according to the characterization parameter model of water pollutant toxicity established by Formula 6:

[0051]

[0052] Among them, TI represents the toxicity intensity of pollutants.

[0053] In this embodiment, when the exposure time is 3 h, the TI value of the toxicity parameter of heavy metal Cd calculated according to Formula 6 is 52.18, and the TI value of the toxicity parameter of heavy metal Cu is 69.62. It can be seen that the toxicity parameter of heavy metal Cu is higher than that of heavy metal Cd. Therefore, when evaluating the toxicity of heavy metals to Chlorella pyrenoidosa with the response index PI, the toxicity intensity of heavy metal Cu to Chlorella pyrenoidosa is higher than that of heavy metal Cd.

[0054] Although the above-described illustrative specific embodiments of the present invention have been described to facilitate the understanding of the present invention by those skilled in the art, and it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions made using the concept of the present invention are within the scope of protection.

Claims

1. A method for characterizing the toxicity of water pollutants based on the dose-effect relationship, characterized in that, Specifically, it includes the following steps: Step 1: Conduct experiments with different concentrations of C1, C2, C3, ..., C n Exposure experiment of pollutants on test organisms, n is the type of concentration, and the parallel samples of the test organism samples exposed to each concentration of pollutants and the blank control samples under non-exposure are set to m; at the exposure time t, accurately measure the different concentrations C1, C2, C3, ..., C n Toxicity response index of m parallel samples of the tested organisms under pollutant stress [(P 1-1 , P 1-2 ,......,P 1-m )、(P 2-1 , P 2-2 ,......,P 2-m )、(P 3-1 , P 3-2 ,......,P 3-m )、......、(P n-1 , P n-2 ,......,P n-m )] and the toxicity response index P of m parallel samples of blank control samples under non-exposure 0-1 , P 0-2 ,......,P 0-m ; Use the average method to calculate each concentration C1, C2, C3, ..., C n The average value of toxicity response index of tested organisms under pollutant stress The average value of toxicity response index of blank control samples under non-stress ; Step 2: According to the obtained value and , calculate the inhibition rates IR1, IR2, IR3,......, IR n of the toxicity response indicators of the test organisms under the stress of pollutants with different concentrations C1, C2, C3,......, C n ; Step 3: Establish a dose-effect quantitative relationship curve between the pollutant concentrations C1, C2, C3,......, C at the exposure time t and the inhibition rates IR1, IR2, IR3......IR of the toxicity response indicators of the test organisms; n n ​​ Step 4: Obtain the lowest effective concentration EC of the pollutant and the inhibition rate IR of the corresponding toxicity response index by using one-way ANOVA and Dunnett's post hoc multiple test method min min ;​ Step 5: Obtain the highest effective concentration EC of the pollutant and the inhibition rate IR of the corresponding toxicity response index by using one-way ANOVA and Dunnett's post hoc multiple test method max and the inhibition rate IR of the corresponding toxicity response index max ; Step 6: Obtain the full curve slope K of the curve between the lowest effect concentration EC min and the highest effect concentration EC max of the dose-effect quantitative relationship curve, which represents the rate of change of the inhibition of the toxicity response index P with the increase in the pollutant concentration; Step 7: Using the full curve slope K, the lowest effective concentration EC min and its corresponding inhibition rate IR min , the highest effective concentration EC max and its corresponding inhibition rate IR max as variables, calculate the characterization parameter TI of pollutant toxicity according to the characterization parameter model of water pollutant toxicity established by Formula 1: (1) Among them, TI represents the toxicity intensity of the pollutant.

2. The method for characterizing the toxicity of water pollutants based on the dose-effect relationship according to claim 1, characterized in that, In step 1, exposure experiments with different concentrations of pollutants are carried out, specifically: The test organisms are evenly divided into m groups, with n + 1 portions in each group. One portion of the test organisms in each group is used to prepare a blank control sample, and the other n portions of the test organisms in each group are respectively exposed to the same pollutant with different concentrations C1, C2, C3......C n . As a result, the number of parallel samples of the test organisms exposed to each concentration of the pollutant is m, and the number of parallel samples of the blank control sample under non-exposure is also m; for the test organism samples and blank control samples under the stress of each concentration of the pollutant, the final volume of the samples is the same, and the number of test organisms in the samples is also the same.

3. A method for characterizing the toxicity of water pollutants based on the dose-effect relationship according to claim 1, characterized in that, In Step 1, each concentration C1, C2, C3,......, C n The average value of the toxicity response index of the test organism under pollutant stress Obtained by calculating according to the following formula 2, the average value of the toxicity response index of the blank control sample under non-stress Obtained by calculating according to the following formula 3: (2) (3) In the formula, is the average value of the toxicity response index of the test organism under the stress of pollutants with a concentration of C n .

4. A method for characterizing the toxicity of water pollutants based on the dose-effect relationship according to claim 1, characterized in that, In the said step 2, different concentrations C1, C2, C3,......, C n The inhibition rates IR1, IR2, IR3,......, IR of the toxicity response indexes of the test organisms under pollutant stress n Are obtained by calculating according to the following formula 4: (4) where, IR n is the inhibition rate of the toxicity response index of the test organism under the stress of the pollutant with a concentration of C n .

5. A method for characterizing the toxicity of water pollutants based on the dose-effect relationship according to claim 1, characterized in that, In step 3, a Logistic model is used to establish a dose-response quantitative relationship curve between the pollutant concentration and the inhibition rate of the toxicity response index at the exposure time t for this pollutant.

6. The method for characterizing the toxicity of water pollutants based on the dose-effect relationship according to claim 1, characterized in that, In step 4, one-way analysis of variance and Dunnett's post hoc multiple test methods are used to test the toxicity response index values P n of the test organisms under pollutant stress n-1 , P n-2 ,......, P n-m and the toxicity response index values P 0-1 , P 0-2 ,......, P 0-m of the blank control sample for significant differences. In this way, the minimum value of the pollutant concentration when the toxicity response index of the stressed test organism is significantly different from that of the test organism in the blank control sample is the lowest effective concentration EC min of the pollutant; furthermore, according to the established quantitative dose-effect relationship curve between pollutant concentrations C1, C2, C3,......, C n and the inhibition rates IR1, IR2, IR3,......, IR n , the inhibition rate IR min of the toxicity response index corresponding to the lowest effective concentration EC min is calculated.

7. The method for characterizing the toxicity of water pollutants based on the dose-effect relationship according to claim 1, characterized in that In step 5, one-way ANOVA and Dunnett's post hoc multiple comparison tests were used to examine the adjacent concentrations C n and C n-1 for significant differences in the toxicity response indices P n-1 , P n-2 , P n-3 ,......, P n-m and P (n-1)-1 , P (n-1)-2 , P (n-1)-3 ,......, P (n-1)-m under pollutant stress. Thus, the lowest value of the toxic pollutant concentration corresponding to no significant change in the toxicity response indices of the test organisms under high-concentration pollutant stress was obtained as the highest effective concentration EC max ; further, based on the established dose-effect quantitative relationship curve between the pollutant concentrations C1, C2, C3,......, C n and the inhibition rates IR1, IR2, IR3,......, IR n , the inhibition rate IR max corresponding to the highest effective concentration EC max was calculated.

8. A method for characterizing the toxicity of water pollutants based on the dose-effect relationship according to claim 1, characterized in that, In step 6, the dose-response quantitative relationship curve between the lowest effective concentration EC min and the highest effective concentration EC max is evenly divided into v segments according to the inhibition rate range of the toxicity response index. The pollutant concentration values and the corresponding inhibition rates of the toxicity response index at the two endpoints of each segment of the curve are [(c1, IR'1)~(c2, IR'2)],......, [(c v , IR' v )~(c v+1 , IR' v+1 )]. The slopes k1, k2, k3,......, k v of each part of the curve are calculated respectively according to formula 5: (5) where c h and c h+1 represent the pollutant concentration values at the starting point and the ending point of the h-th curve segment respectively, and IR' h and IR' h+1 represent the inhibition rates of the toxicity response index at the starting point and the ending point of the h-th curve segment respectively. Calculate the full curve slope K of the curve between the lowest effect concentration EC min and the highest effect concentration EC max in the dose-effect relationship curve according to Equation 6: (6)。

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