Water ecological integrity degradation diagnosis method based on dissolved organic matter chemical diversity

Abstract

The invention belongs to the technical field of water ecology evaluation and water environment analysis, and discloses a dissolved organic matter chemical diversity-based water ecology integrity degradation diagnosis method, which analyzes DOM molecular fingerprints in a water body through an ultrahigh-resolution mass spectrum, realizes fine characterization of DOM molecular composition complexity and change thereof, and improves the water ecology integrity degradation diagnosis accuracy. The limitation that the traditional water ecology evaluation method is difficult to identify the molecular scale recessive degradation is broken through; by constructing a chemical diversity index and introducing an interpretable data driving model, a quantitative corresponding relation between a molecular structure parameter threshold value and water body chemical integrity degradation is established, and a degradation signal of a DOM (Document Object Model) library converted from complex stability to simple activity in a water ecosystem can be stably identified; and a molecular-scale technical support is provided for lake and river water ecological integrity degradation identification and management decision.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of water ecological evaluation and water environment analysis, and particularly relates to a water ecological integrity degradation diagnosis method based on dissolved organic matter chemical diversity. BACKGROUND

[0002] In lakes, C, N, P and other key biogenic elements coexist in the form of NO3 - -N, PO4³ - -P, DOC, POM, DOM and other organic / inorganic forms, and their concentration levels and occurrence forms jointly regulate microbial community structure, primary production and heterotrophic decomposition processes. When exogenous input and endogenous release lead to changes in C-N-P load and ratio, it often triggers the restructuring of phytoplankton and microbial communities, thereby changing the circulation path and distribution pattern of C, N and P between water-particles-sediments, and ultimately feeding back to the changes in the functional integrity of the lake water ecosystem. Among the key biogenic elements, DOM is not only the most active organic carbon pool in water, but also an important "medium" connecting the C-N-P cycle. The molecular composition and chemical diversity of DOM not only reflect its source (terrestrial / endogenous), reactivity and bioavailability, but also can be used as a comprehensive representation of the "chemical integrity" of water. Therefore, starting from the continuous gradient of "element concentration-form composition-molecular properties", and through the molecular fingerprint of DOM to depict the metabolic imbalance of biogenic elements, it is of key significance to understand the process of lake succession from steady state to instability.

[0003] In recent years, chemical diversity, as a molecular analogy of biological diversity, has been proposed to quantitatively describe the complexity of DOM molecular composition. Chemical diversity represents the richness of molecular formula and the uniformity of its relative abundance distribution, reflecting the comprehensive results of molecular generation, preservation and removal processes. High chemical diversity usually indicates a DOM pool with diverse sources, slow degradation and rich functional potential, while low chemical diversity often appears in environments with enhanced primary production or microbial turnover, when a few simple-structured and easily-degradable molecules dominate. The process of DOM transformation from high heterogeneity to low heterogeneity under the background of eutrophication can be regarded as a kind of "chemical diversity erosion", but the molecular driving mechanism still lacks systematic cognition.

[0004] The development of ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) makes it possible to simultaneously resolve thousands of DOM molecular formulas and their structural parameters. However, it is difficult to reveal the overall pattern of chemical diversity change from a single molecule. In contrast, it is more helpful to identify representative structural features associated with high and low chemical diversity from the perspective of molecular group. Machine learning methods such as random forest can effectively capture the non-linear relationship between molecular features and chemical diversity, and combined with explainable frameworks such as SHAP, the contribution of different molecular features to the change of chemical diversity can be quantitatively evaluated.

[0005] Therefore, the present study integrates FT-ICR MS and explainable machine learning methods to identify key molecular features that regulate DOM chemical diversity and extract molecular fingerprints that are stably associated with changes in chemical diversity, thereby building a bridge between "molecular properties-chemical diversity-system integrity". SUMMARY

[0006] In view of the problem that the existing water ecological integrity evaluation method mainly relies on nutrient salt concentration and biomass index, and it is difficult to identify early degradation signals of water ecological system at the molecular and chemical function level, the purpose of the present application is to provide a water ecological integrity degradation diagnosis method based on dissolved organic matter chemical diversity, which realizes the molecular scale quantitative diagnosis of the complexity change of DOM molecular composition in lake and river water body and the chemical integrity degradation state reflected thereby, and provides a technical means for water ecological system degradation identification and repair effect evaluation.

[0007] To achieve the above technical purpose, the technical scheme adopted by the present application is as follows: A water ecological integrity degradation diagnosis method based on dissolved organic matter chemical diversity, comprising the following contents, (1) performing DOM molecular fingerprint analysis on the pretreated collected water sample to construct a DOM molecular fingerprint database; (2) calculating molecular structure parameters according to the obtained DOM molecular formula, and dividing the DOM molecules according to the element ratio and unsaturation degree characteristics; (3) taking the molecular structure parameters as input variables and the chemical diversity index as output variables to construct a DOM chemical diversity prediction model; (4) performing explainability analysis on the DOM chemical diversity prediction model to identify the core molecular structure parameters that regulate the change of chemical diversity and their corresponding threshold values, and on this basis, screening the indicative molecular fingerprints that are stably and significantly related to high chemical diversity and are sensitive to eutrophication process response; (5) grading the water body chemical integrity state based on the threshold value of the core molecular structure parameters and the change of the relative abundance of the indicative molecular fingerprints.

[0008] The application analyzes the DOM molecular fingerprint in the water body, realizes the fine characterization of the complexity and change of the DOM molecular composition, breaks through the limitation that the traditional water ecological evaluation method is difficult to identify the molecular scale implicit degradation; by constructing a chemical diversity index and introducing an interpretable data-driven model, a quantitative corresponding relationship between the molecular structure parameter threshold and the chemical integrity degradation of the water body is established, which can stably identify the degradation signal of the transformation of the DOM library from complex stability to simple activity in the water ecological system, and provide molecular scale technical support for the identification and management decision of the lake and river water ecological integrity degradation.

[0009] In some optional examples, the application collects water samples in a lake or river water body, and filters and pretreats the water samples to obtain dissolved organic matter samples. The pretreatment includes filtering through a glass fiber filter and a microporous filter to remove particles and suspended solids in the collected water samples, so as to avoid interference of the particles and suspended solids with the DOM molecular fingerprint analysis.

[0010] In some optional examples, when the DOM molecular fingerprint analysis is performed, the collected water samples are detected by Fourier transform ion cyclotron resonance mass spectrometry with ultra-high resolution, and not less than 2,000 DOM molecular formulas are synchronously obtained in the same water sample to construct a DOM molecular fingerprint database.

[0011] In some optional examples, the DOM molecular fingerprint analysis is performed in a negative ion electrospray ionization mode, the collected water samples are subjected to multiple cumulative scans by Fourier transform ion cyclotron resonance mass spectrometry, and the molecular formulas of the mass spectrometry peaks meeting the signal-to-noise ratio requirement are identified under the element constraint condition, so as to construct the DOM molecular fingerprint database.

[0012] In some optional examples, the molecular structure parameters in the application include a hydrogen-carbon ratio, an oxygen-carbon ratio, a double bond equivalent, a modified aromaticity index, a nominal oxidation state, and a mass-to-charge ratio.

[0013] In some optional examples, the chemical diversity index in the application is constructed based on the DOM molecular fingerprint and the relative abundance thereof. The construction of the chemical diversity index regards each DOM molecular formula as a chemical species, and uses the relative abundance thereof as a weight for comprehensively characterizing the richness, uniformity and structural heterogeneity of the DOM molecular composition.

[0014] In some optional examples, the DOM chemical diversity prediction model in the application adopts a random forest model, The prediction performance of the DOM chemical diversity prediction model is evaluated by using a training set and an independent test set; By the explainable analysis method based on feature contribution degree, the influence degree of different molecular structure parameters on the chemical diversity change is quantified, and the core molecular structure parameters for regulating the chemical diversity change and the corresponding threshold values are identified.

[0015] In some optional examples, the indicative molecular fingerprint for screening is a lignin-like molecule / carboxyl-rich alicyclic molecule significantly related to high chemical diversity stability.

[0016] In some optional examples, the water body chemical integrity state is divided into a healthy state, a sub-healthy state and a degraded state.

[0017] Advantages of the present application: by analyzing the DOM molecular fingerprint in the water body through ultra-high resolution mass spectrometry, the complexity of the DOM molecular composition and its change are finely characterized, and the limitation that the traditional water ecological evaluation method is difficult to identify the molecular scale implicit degradation is broken; by constructing a chemical diversity index and introducing an explainable data-driven model, a quantitative corresponding relationship between the molecular structure parameter threshold value and the water body chemical integrity degradation is established, which can stably identify the degradation signal of the transformation of the DOM library from complexity stability to simplicity activity in the water ecological system, and provide molecular scale technical support for the identification and management decision of the lake and river water ecological integrity degradation. BRIEF DESCRIPTION OF DRAWINGS

[0018] The present application can be further illustrated by the non-limiting examples shown in the accompanying drawings; Figure 1 The flowchart of the embodiments of the present application is shown. DETAILED DESCRIPTION

[0019] The technical solutions of the present application will be described in detail below in combination with specific embodiments and the accompanying drawings, and it should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from that shown here.

[0020] The embodiments described herein are specific specific embodiments of the present application, which are used to illustrate the concept of the present application; these descriptions are all explanatory and exemplary, and should not be understood as limiting the embodiments of the present application and the protection scope of the present application. In addition to the embodiments described herein, those skilled in the art can also employ other technical solutions that are obvious based on the disclosure of the claims and the specification of the present application, which include technical solutions that make any obvious substitutions and modifications to the embodiments described herein. EMBODIMENT

[0021] As Figure 1As shown, the embodiment provides a water ecological integrity degradation diagnosis method based on dissolved organic matter chemical diversity, which comprises the following contents, Sampling point selection and sample collection (1 in the figure content): Selecting lakes and rivers and other types of water bodies in the Yangtze River Basin as sampling points, covering the nutrient state gradient from oligotrophic to mesotrophic; collecting surface water samples at each sampling point, with a volume of 1.5 L; the samples are immediately sent to the laboratory for filtration treatment after collection.

[0022] Specifically, in the embodiment, after the water sample is sent to the laboratory, it is sequentially passed through a pre-burned glass fiber filter (0.7 μm, GF / F) and a polycarbonate filter (0.22 μm) to remove particulates and suspended solids, and the obtained filtrate is used for subsequent DOM extraction and analysis; Simultaneous determination of total nitrogen (TN), total phosphorus (TP) and chlorophyll a (Chl a) concentrations in water samples: TN and TP are determined by a continuous flow analyzer according to the standard colorimetric method; Chl a is determined in phytoplankton trapped by GF / F filter, extracted with 90% acetone, and centrifuged after freeze-thaw treatment to obtain supernatant, which is calculated by colorimetric method; calculate the trophic state index (TSI) based on TN, TP and Chl a, which is used to determine the eutrophication level of the sample and provide grouping basis for subsequent cross-nutrient gradient comparison; The specific calculation method is as follows: Wherein TSI(∑) is the comprehensive trophic state index; TSI(j) is the trophic state index of j; Wj is the relevant weighted score of the trophic state index of j; Wherein Wj is the relevant weighted score of the trophic state index of j (chlorophyll a, total nitrogen and total phosphorus); rij is the correlation coefficient of water quality parameter j and chlorophyll a, which is calculated based on Chinese survey lakes, and the rij values of Wj(Chl a), Wj(TP) and Wj(TN) are 1, 0.84 and 0.82 respectively, while the Wj values of TSI(Chl a), TSI(TP) and TSI(TN) are 0.42, 0.30 and 0.28 respectively.

[0023] DOM molecular fingerprint analysis (2, 3 in the figure content): DOM is enriched by solid phase extraction after filtration; the molecular composition of DOM is analyzed by ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), and DOM molecular formula is obtained and DOM molecular fingerprint library is constructed.

[0024] Specifically, in the present embodiment, the DOM is enriched by a PPL solid-phase extraction column. Before extraction, the filtered water sample is acidified to pH = 2. The extraction column is pretreated with methanol and acidified pure water in sequence, and the acidified water sample is passed through the extraction column to enrich the organic matter. The enriched organic matter is slowly blown dry under nitrogen, and then eluted with high-purity methanol to obtain the SPE-DOM extract. The extract is stored in a brown glass bottle treated by high-temperature calcination and stored under low-temperature conditions for testing.

[0025] Before FT-ICR MS detection, the methanol extract is uniformly diluted to the same organic carbon concentration level (for example, 40 mg DOC·L-1) to reduce the influence of concentration differences between samples on ionization response. Mass spectrometric analysis is performed in negative ion electrospray ionization mode (ESI-). The sample is introduced by a syringe pump (for example, 2 μL·min-1). The electrospray voltage is, for example, 4 kV. The scan mass range is m / z 100-1000. To improve the signal-to-noise ratio and the reliability of molecular formula identification, each sample is accumulated for multiple consecutive scans (for example, 128 times), and a sufficient number of data points is set to ensure ultra-high mass resolution. To monitor instrument stability and analysis repeatability, standard samples are tested repeatedly every day as quality control.

[0026] The detected mass spectrometric peaks are screened according to a signal-to-noise ratio threshold (for example, S / N>6). The peaks are identified by molecular formula under strict element constraints, and the element range can include C, H, O, N, S, and P to form a DOM molecular fingerprint database.

[0027] Molecular structure parameters (4 and 5 in the attached figure) are calculated to carry out DOM molecular type classification: hydrogen-carbon ratio (H / C), oxygen-carbon ratio (O / C), double bond equivalent (DBE), modified aromaticity index (AImod), nominal oxidation state (NOSC), and mass-to-charge ratio (m / z) molecular descriptors are calculated based on the identified molecular formula, and DOM molecular type classification is carried out accordingly.

[0028] Specifically, in the present embodiment, DBE, AImod, and NOSC parameters are calculated based on the identified molecular formula, and the molecules are classified according to the established element ratio and parameter threshold. For example, the molecules can be classified into lipids, proteins, aliphatic compounds, carbohydrates, lignin, tannins, condensed aromatic compounds, unsaturated hydrocarbons, and others according to the O / C and H / C ranges. At the same time, stable components such as carboxyl-rich alicyclic molecules (CRAM) can be identified according to the comprehensive criterion of DBE and element ratio. This classification is used to explain the molecular basis of the transformation of DOM component structure from complex stability to simple activity under different nutritional conditions. The specific classification criteria are as follows: Lipids (Lipids): 0≤O / C<0.3; 1.5≤H / C≤2.0; Proteins: 0.3≤O / C≤0.67; 1.5≤H / C≤2.2; N≥1; Aliphatics: 0.3≤O / C≤0.67; 1.5≤H / C≤2.2; N=0; Carbohydrates: 0.67 Lignins: 0.1 Tannins: 0.67 Condensed aromatics: 0≤O / C≤0.67; 0.2≤H / C<0.7 Unsaturated hydrocarbons: 0≤O / C≤0.1; 0.7≤H / C<1.5; Others: Not fitting the above classification formulas; Carboxyl-rich alicyclic molecules (CRAM): DBE / C (0.3-0.68), DBE / H (0.2-0.95), and DBE / O (0.77-1.75).

[0029] Chemical diversity index calculation: Each molecular formula is regarded as a “chemical species”, and its relative peak intensity is taken as the abundance of the species. The DOM chemical diversity index (CDI) is calculated as follows: where S represents the total number of molecular formulas detected in the sample, and pi represents the relative abundance of the i-th molecular formula, calculated as pi = ni / N, where ni is the abundance of molecular formula i, and N is the total abundance of all detected molecular formulas.

[0030] To construct a robust machine learning dataset, a representative subset of samples is selected from all samples as the source of training data, and the balanced distribution of different nutritional status samples is ensured. After molecular formula identification in this subset, only common molecular formulas appearing in at least half of the samples can be retained to reduce the noise caused by accidental detection of molecules and improve the model generalization ability. In this embodiment, the number of common molecular formulas finally used for modeling can reach the order of thousands (e.g., 2840), to support high-dimensional molecular feature learning.

[0031] Constructing DOM chemical diversity prediction model (Figures 6, 7, 8): Supervised regression model is constructed to predict CDI using molecular descriptors (e.g. H / C, O / C, DBE, AImod, NOSC, m / z, etc.) as input variables and CDI as output variable, and the model performance is evaluated.

[0032] Specifically, in this embodiment, the molecular descriptors are standardized (e.g. z-score standardization) before modeling to eliminate the dimensional differences. A random forest (RF) regression model can be constructed as the main prediction model, and the model performance is evaluated by cross-validation and independent test set. The evaluation indicators include the coefficient of determination R², the root mean square error RMSE and the mean absolute error MAE. As an example, the RF model in this embodiment can obtain high prediction accuracy (e.g. R²=0.969) on the test set and maintain low error level (e.g. MAE=0.145, RMSE=0.186), indicating that the model can effectively characterize the non-linear relationship between DOM molecular structure parameters and chemical diversity.

[0033] Further, the random forest model integrates the complex relationship between input molecular parameters and CDI through multiple decision trees, and the output results can be used to quantify the comprehensive influence of different molecular structure parameters on the change of chemical diversity, thereby avoiding the limitation of single parameter or linear hypothesis on the diagnosis results.

[0034] Interpretability analysis: SHAP and other methods are used to quantify the contribution of each molecular structure parameter to CDI prediction, identify the core molecular parameters driving CDI change, and determine their corresponding threshold intervals; on this basis, representative molecular fingerprints significantly related to high CDI are screened.

[0035] Specifically, in this embodiment, SHAP analysis can identify H / C, DBE, AImod and NOSC as the core molecular parameters regulating CDI, and further obtain the threshold range with application significance; for example, the typical threshold characteristics related to high CDI state can be identified: H / C is lower than a certain threshold (e.g. H / C<1.5), DBE is higher than a certain threshold (e.g. DBE>5), AImod is higher than a certain threshold (e.g. AImod>0.2), and NOSC is higher than a certain threshold (e.g. NOSC>−1). When the overall distribution of DOM molecular structure parameters in the sample crosses the threshold interval, the corresponding CDI shows significant changes, which can be used as an important criterion for the transformation of water chemical integrity state.

[0036] Molecular fingerprint screening (9 in the attached figure): Based on the SHAP contribution, the most representative molecular formulas that are most related to the high CDI state are selected as "high chemical diversity molecular fingerprints"; for example, the top 20 molecular formulas that are related to high CDI stability are selected as fingerprint sets. This set can be mainly distributed in the lignin-like region and has a high proportion of CRAM determination conditions, thus reflecting its complex structure and relatively stable molecular characteristics.

[0037] Cross-system validation (10 in the figure): Select independent water samples that did not participate in the model construction as the validation set, covering different trophic state gradients, to verify the stability and reproducibility of the screened molecular fingerprints.

[0038] Specifically, in this embodiment, independent validation set samples (e.g., 24 surface water samples) can be selected to cover nutrient states such as oligotrophic, mesotrophic, slightly eutrophic, and moderately eutrophic. The relative abundance of the screened indicative molecular fingerprints under different nutrient states is calculated, and nonparametric tests are used to evaluate the differences. The results show that the relative abundance of this type of lignin / CRAM molecular fingerprint, which is associated with high CDI stability, shows a significant and consistent systematic decreasing trend with increasing nutrient state, indicating that it can serve as a molecular indicator of chemical diversity erosion and chemical integrity degradation.

[0039] Furthermore, this embodiment divides the diagnostic output into at least three levels: "healthy - sub-healthy - deteriorating". As one implementation method, the following information can be used to classify the levels: (1) CDI level (observed CDI or model-predicted CDI); (2) Whether the key molecular structural parameters fall entirely within the high CDI threshold range or exhibit changes that cross the threshold; (3) Whether the relative abundance of highly chemically diverse molecular fingerprint sets shows a systematic decrease.

[0040] In practical applications, the chemical integrity status of water bodies can be determined based on the combined characteristics of the above three types of outputs, which can be used to reflect the chemical integrity of aquatic ecosystems and the trend of changes in their potential functions.

[0041] Furthermore, to meet the needs of regional ecological monitoring and management decision-making, this embodiment applies the method of the present invention to water body monitoring at the watershed scale: periodic sampling is carried out in target lakes and reservoirs or key river sections, and CDI, key molecular parameter threshold discrimination results and molecular fingerprint abundance summary results are obtained according to the steps of this embodiment to form a water body chemical integrity diagnostic report.

[0042] Specifically, in the evaluation of the effectiveness of remediation or restoration measures, this method can be repeated on the same water body before and after remediation or at different time points, and the following results can be compared: the trend of CDI change, whether key molecular structural parameters regress to the high CDI threshold range, and whether the abundance of high chemical diversity molecular fingerprints recovers or rebounds. Through the above comparison, the trend of change in "chemical integrity—related ecological function integrity" can be quantitatively tracked, which can be used to evaluate whether the remediation measures promote the transformation of the aquatic ecosystem from a degraded state to a stable state of restoration.

[0043] In summary, this invention discloses a method for diagnosing water ecological integrity degradation based on dissolved organic matter chemical diversity. By acquiring DOM molecular fingerprints through FT-ICR MS and combining them with interpretable machine learning analysis, the method achieves molecular-scale identification of the degradation state of water body chemical integrity. It can identify latent degradation signals such as DOM chemical diversity erosion and key molecular fingerprint library reduction under eutrophication background, providing molecular-scale technical support for water ecological integrity diagnosis, risk identification, and restoration effect assessment.

[0044] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for diagnosing the degradation of aquatic ecological integrity based on the chemical diversity of dissolved organic matter, characterized in that: Includes the following: (1) Perform DOM molecular fingerprint analysis on the pretreated water samples and construct a DOM molecular fingerprint database; (2) Calculate the molecular structure parameters based on the obtained DOM molecular formula; (3) Using molecular structure parameters as input variables and chemical diversity index as output variables, construct a DOM chemical diversity prediction model; (4) Conduct interpretability analysis on the DOM chemical diversity prediction model, identify the core molecular structure parameters that regulate changes in chemical diversity and their corresponding thresholds, and on this basis, screen out indicative molecular fingerprints that are significantly correlated with high chemical diversity and sensitive to eutrophication processes. (5) The chemical integrity status of water bodies is classified based on the changes in the threshold of core molecular structure parameters and the relative abundance of indicative molecular fingerprints.

2. The method for diagnosing water ecological integrity degradation based on dissolved organic matter chemical diversity according to claim 1, characterized in that: In content (1), DOM molecular fingerprint analysis is performed in negative ion electrospray ionization mode. The collected water samples are scanned multiple times by Fourier transform ion cyclotron resonance mass spectrometry, and molecular formula identification is performed on the mass spectrometry peaks that meet the signal-to-noise ratio requirements under elemental constraints, thereby constructing the DOM molecular fingerprint database.

3. The method for diagnosing water ecological integrity degradation based on dissolved organic matter chemical diversity according to claim 1, characterized in that: The molecular structure parameters in content (2) include hydrogen-to-carbon ratio, oxygen-to-carbon ratio, double bond equivalent, modified aromaticity index, nominal oxidation state, and mass-to-charge ratio.

4. The method for diagnosing water ecological integrity degradation based on dissolved organic matter chemical diversity according to claim 1, characterized in that: Content (2) also includes classifying DOM molecules by structural type based on element ratio and unsaturation characteristics.

5. The method for diagnosing water ecological integrity degradation based on dissolved organic matter chemical diversity according to claim 1, characterized in that: In content (3), the chemical diversity index is constructed based on the molecular fingerprint of DOM and its relative abundance.

6. The method for diagnosing water ecological integrity degradation based on dissolved organic matter chemical diversity according to claim 1, characterized in that: In content (3), the DOM chemical diversity prediction model adopts the random forest model. The predictive performance of the DOM chemical diversity prediction model was evaluated using the training set and independent test set. By using an interpretability analysis method based on feature contribution, we quantify the influence of different molecular structural parameters on changes in chemical diversity, and identify the core molecular structural parameters that regulate changes in chemical diversity and their corresponding thresholds.

7. The method for diagnosing water ecological integrity degradation based on dissolved organic matter chemical diversity according to claim 1, characterized in that: The indicative molecular fingerprints screened in content (4) are lignin-like molecules / carboxyl-rich alicyclic molecules that are significantly associated with high chemical diversity and stability.

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