# Acute toxicity of atrazine degradation solutions via advanced oxidation processes: An experimental and in-silico approach based on mass spectrometry data

Junting Hong, Messika Revel, Nadia Boussetta, Gérald Enderlin, Frederic Nadaud, Clarisse Roig, Lauresse Nguimapi Tsague, Stéphane Firmin, Nabil Grimi, Franck Merlier

► To cite this version:

Junting Hong, Messika Revel, Nadia Boussetta, Gérald Enderlin, Frederic Nadaud, et al. Acute toxicity of atrazine degradation solutions via advanced oxidation processes: An experimental and in-silico approach based on mass spectrometry data. Ecotoxicology and Environmental Safety, 2025, 302, 10.1016/j.ecoenv.2025.118706. [hal-05225312](https://hal.science/hal-05225312v1)

HAL Id: hal-05225312

https://hal.science/hal-05225312v1

Submitted on 27 Aug 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_2.png" /></figure>

# Acute toxicity of atrazine degradation solutions via advanced oxidation processes: An experimental and in-silico approach based on mass spectrometry data.

Junting Hong<sup>a,b,c</sup>, Messika Revel<sup>d</sup>, Nadia Boussetta<sup>b</sup>, Gérald Enderlin<sup>b</sup>, Frederic Nadaud<sup>e</sup>, Clarisse Roig<sup>d</sup>, Lauresse Nguimapi Tsague<sup>d</sup>, Stéphane Firmin<sup>f</sup>, Nabil Grimi<sup>b</sup>, Franck Merlier<sup>a,*</sup>

## ARTICLE INFO

Edited by Dr G Liu

### Keywords:

- Atrazine
- Electrical discharge
- Ultrasound
- Acute toxicity
- QSAR
- LC-HRMS

## ABSTRACT

Although atrazine has been banned, residues of the compound and its metabolites are still detected in certain areas of French groundwater. In response to the European Green Deal, this study focuses on the degradation of atrazine in tap water and the toxicological evolution of different treatments. The degradation efficiency of atrazine in deionized water by high-voltage electrical discharge (HVED) and high-frequency ultrasound (HFUS) was higher than that in tap water with the same initial atrazine concentration, likely due to competition from impurities in tap water, such as ions and other organic compounds. Additionally, acute toxicity testing using *Daphnia magna* was conducted to assess the toxicological impact of the degradation processes. Acute toxicity (LC50) values were used to evaluate the toxicity of the different treatment solutions initially containing atrazine. High-resolution mass spectrometry coupled with liquid chromatography (LC-HRMS) was employed to identify and compare the transformation products generated by each degradation technique. Furthermore, an in-silico toxicity evaluation using the QSAR model was proposed and compared to the experimental data. The in-vivo assessment revealed that atrazine solutions treated with Fenton oxidation (LC50 < 0.1 mg/L) were significantly more toxic than those treated with HFUS (LC50 > 5 mg/L) or HVED (1.5 < LC50 < 2.5 mg/L). However, in the in-silico evaluation, Fenton oxidation appeared less toxic, as residual toxicity from ferrous ions and hydrogen peroxide was not considered. Consequently, the degradation of atrazine by HVED and HFUS proved to be more efficient and environmentally favorable.

## 1. Introduction

In order to meet the increasingly strong global food demand in recent years, pesticides have been widely used in the development of agriculture. But this also brings pesticide pollution, especially when pesticides applied in farmland leak into lakes, rivers and groundwater, which will pose a serious threat to global human freshwater supplies (Baran et al., 2022). One-third of fresh water for human consumption comes from groundwater, and for some countries such as Denmark and Malta it is the

only source of water supply (Zekîsêr and Everett, 2004). Groundwater quality monitoring has attracted attention and water legislation has been introduced. For example, in Europe, the Water Framework Directive was proposed and requires EU member states to achieve good chemical and quantitative status of groundwater, although this goal was not fully achieved due to the presence of persistent pollutants, especially pesticides (Voulvoulis et al., 2017). According to water quality surveys conducted by the European Environment Agency in 27 EU countries between 2013 and 2019, pesticide levels in groundwater were found to

<footnote><sup>a</sup> Université de Technologie de Compègne, UPJV, CNRS, Enzyme and Cell Engineering, Centre de Recherche Royallieu, CEDEX CS 60319, Compègne 60203, France</footnote>

<footnote><sup>b</sup> Université de Technologie de Compègne, ESCOM, TIMR (Integrated Transformations of Renewable Matter), Centre de Recherche Royallieu, CEDEX CS 60319, Compègne 60203, France</footnote>

<footnote><sup>c</sup> GDMPA Key Laboratory for Process Control and Quality Evaluation of Chiral Pharmaceuticals, Guangzhou Key Laboratory of Analytical Chemistry for Biomedicine, School of Chemistry, South China Normal University, Guangzhou 510006, PR China</footnote>

<footnote><sup>d</sup> UniLaSalle - École Des Métiers de L'Environnement, Cyclann, Rennes, Bruz 35170, France</footnote>

<footnote><sup>e</sup> Service d'Analyse Physico-Chimique, Université de Technologie de Compègne, Centre de recherche Royallieu-CS 60319-60 203 CEDEX, Compègne 60200, France</footnote>

<footnote><sup>f</sup> UniLaSalle, AGHYLE Beauvais UP 2018.C101, Beauvais 60000, France</footnote>

<footnote>* Corresponding author.
E-mail address: franck.merlier@utc.fr (F. Merlier).</footnote>
exceed legal limits, especially in France (European Union, Directive, 2006). Atrazine is a commonly used herbicide in agriculture (Hong et al., 2022a).

A report (Baran et al., 2021) on French groundwater quality data over more than 20 years shows that atrazine can still be detected, although it was withdrawn from the market in 2003, and its concentration exceeded 0.1 µg/L in some areas. However, the Groundwater Directive (European Union, Directive, 2006) stipulates that the quality standard for pesticides is set at 0.1 µg/L, and there are obviously hidden dangers in French groundwater. The maximum concentrations of atrazine and its metabolites detected in tap water in the region of Hauts-de-France are shown in Fig. 1, based on the data obtained by the French government “Ministry of Solidarity and Health” on September 2023 (Ministère Des Solidarités Et De La Santé, 2024) The maximum concentrations of atrazine and its metabolites detected in some areas of Hauts-de-France still exceed the quality standards 0.1 µg/L. In addition to atrazine, other pesticides such as chloridazon are also present in French tap water (Baran et al., 2022). To compare and complement our previous work (Hong et al., 2022b, 2023), atrazine (ATZ) was chosen as a model molecule to study in this work.

Potential health problems may occur if people absorb drinking water obtained from groundwater sources that contain excessive levels of atrazine (Rinsky et al., 2012). It is reported that atrazine is one of the most harmful herbicides, with adverse effects on humans, fish, invertebrates and wildlife. The dangers of atrazine to human health include: As an endocrine disruptor, atrazine can disrupt the hormone balance in the human body (Kucka et al., 2012) and may cause altered nervous system function and reproductive dysfunction; Exposure to atrazine in drinking water is associated with an increased risk of adverse pregnancy outcomes (Winchester et al., 2009; Goodman et al., 2014); Atrazine is potentially carcinogenic and increases the incidence of cancers such as breast and ovarian cancer (Hopenhayn-Rich et al., 2002). Exposure to atrazine during embryonic development in zebrafish caused reproductive problems (Wirbisky et al., 2016), and low concentrations of atrazine (≥0.1 ppb) caused hermaphroditism in frogs (Hayes et al., 2002). Considering the above-mentioned hazards caused by atrazine, more and more efforts are made to degrade atrazine into other low-toxic metabolites or non-toxic small molecules such as water and carbon dioxide. Degradation can be achieved through various

processes, whether technical or biological (Hong et al., 2022a), including advanced oxidation processes (AOPs) such as Fenton reactions, HFUS, and HVED. These techniques enable the degradation of the molecule, with the ultimate goal of achieving mineralization. However, AOPs primarily generate transformation products that are oxidized, dechlorinated (or not), and result in very limited mineralization (Hong et al., 2022b). Moreover, Fenton reactions, which require the presence of Fe²⁺ ions (Bondarenko et al., 2020), pose an environmental concern due to the potential toxicity of these ions (Khangarot and Ray, 1989). In these existing degradation works, most of them measured the toxicity of atrazine and its metabolites (Hu et al., 2021; Klementová et al., 2019), and few made toxicity assessment of the degradation system (Jia et al., 2023; Wang et al., 2023). However, there has been no toxicity assessment of different degradation systems. The use of LC-HRMS provides access to qualitative and semi-quantitative molecular knowledge of the solutions generated during the degradation of molecules. In recent years, predictive toxicity models have been developed, based on Quantitative Structure-Activity Relationship (QSAR) (Fujikawa et al., 2007; Qin et al., 2018; Ai et al., 2019) approaches or artificial intelligence (A.I.) (Cavasotto and Scardino, 2022; Balraadsjing et al., 2022), enabling the evaluation of the potential toxicity of each molecule. By combining the molecular knowledge provided by analytical chemistry with toxicity simulations, is it possible to classify the toxicity of the degradation solutions thus produced?

The objective of this work is to qualitatively and quantitatively evaluate the influence of a real aqueous matrix on the degradation of our model molecule, atrazine, using HVED and HFUS processes, which offer the advantage of operating without Fe²⁺, in comparison to a simplified matrix such as deionized water. This evaluation will help determine the relevance of these physical treatments. In the second phase, we will assess the toxicity of the resulting solutions and attempt to correlate this toxicity with molecular identifications performed using LC-HRMS. The ultimate goal is to develop an in-silico model capable of reducing the time and cost associated with toxicity evaluations, ultimately enabling the selection of physical degradation methods without the need for biological testing.

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** The maximum concentrations of atrazine (A) and its metabolites (B) detected in tap water in the region of Hauts-de-France. Data were from the health control of water distributed commune by commune by the French government “Ministry of Solidarity and Health.</figcaption></figure>
## 2. Materials and methods

### 2.1. Chemicals and materials

The used tap water was from the laboratory TIMR (Integrated Transformations of Renewable Matter), *Centre de Recherche Royallieu*, Université de Technologie de Compiègne, *CEDEX CS 60319, 60203 Compiègne, France*. The used deionized water (conductivity 89 µS/cm at 25°C) was acquired from a water purification device Rephile Direct-Pure® UP 10 (MA, USA), which was bought from the distributeur Franceeau. The mobile phrases were of LC-MS grade acetonitrile and formic acid, provided by Biosolve Chimie (Dieuze, France). The substrate atrazine (ATZ) and its deuterium labeled compound ATZ-D5 were supplied by Sigma-Aldrich (St. Quentin Fallavier, France). The solid ferrous sulfate $FeSO_4·7H_2O$ (99.5 %) was from Acros Organics (France). Hydrogen peroxide (35 wt% solution in water) was from Alfa Aesar (France). $NaHCO_3$, $CaCl_2·2H_2O$, $MgSO_4·7H_2O$ and KCl was purchased from ProLabo (Paris, France).

### 2.2. Sample preparation

The four solutions included (1) 20 mg/L ATZ in deionized water; (2) 20 mg/L atrazine in tap water; (3) only deionized water; (4) only tap water. They were treated by HVED and HFUS. For all conditions except for the LC-MS/MS condition, ATZ was dissolved without acetonitrile. For LC-MS/MS 1 mL of acetonitrile is used for initial dissolution of ATZ before final dilution in 500 mL of water.

### 2.3. Sample degradation

The degradations by high-frequency ultrasound (HFUS), high-voltage electrical discharge (HVED), and Fenton oxidation treatments were carried out under the same conditions as described in our previous work (Hong et al., 2023). Briefly, HFUS degradation was performed in a SinapTec (Lezennes, France) reactor (525 kHz, 80 W) on 100 mL of an ATZ or blank solution at 50°C. Samples were collected at 0, 30, 60, 90, and 120 min.

HVED degradation was performed on 250 mL of an ATZ solution using a Basis EP (Saint-Quentin, France) electrical generator (40 kV, 10 kA, 1 Hz) equipped with a 1 L hollow cylinder. The duration of an electrical pulse was 10 µs. For a processing time of 16 min and 40 s (1000 s), the effective time was 10 ms. Samples were collected at 0, 1, 2, 4, 7, and 10 ms of effective time.

The treatment solution for Fenton oxidation was prepared as follows. An initial 50 mL atrazine solution (20 mg/L, initial molar concentration of atrazine [ATZ]<sub>0</sub> = 0.093 mmol/L) with 5 equivalents of Fenton reagents ([FeSO<sub>4</sub>·7H<sub>2</sub>O]<sub>0</sub> = [H<sub>2</sub>O<sub>2</sub>]<sub>0</sub> = 5[ATZ]<sub>0</sub> = 0.467 mmol/L) was added to a 100 mL flask and stirred for 2 h using a magnetic stirrer.

### 2.4. Mass spectrometry detection

#### 2.4.1. HPLC-HRMS

HPLC-HRMS was used to monitor the evolution of atrazine and its metabolites during the degradation processes (Hong et al., 2022b). The Infinity 1290 HPLC system with a diode array detector was combined with the Agilent 6538 Electrospray-ionisation (ESI) quadrupole time-of-flight (Q-TOF) tandem mass spectrometry, purchased from Agilent Technologies (France). The 100 × 2.1 mm Thermo Hypersil Gold C18 column, with particle size 1.9 µm and pore size 175 Å, was used at 40°C. The external mass calibration in ESI+ mode was used to perform compounds' responses. The positive ion ESI mass spectra were acquired using electrospray scan mode at 5 Hz frequency, 50–1200 m/z mass range, 3800 V electrospray voltage and 110 V fragment voltage. The atomizing nitrogen was set at 350°C temperature, 30 psi pressure and 10 L/min flow rate. The mobile phases (0.6 mL/min) consisted of eluent A (0.1 % formic acid in deionized water) and eluent B (100 %

acetonitrile), maintaining 5 % B for 0–0.3 min, linearly changing from 5 % to 30 % B for 0.3–1.7 min, linearly changing from 30 % to 95 % B for 1.7–3.5 min, and holding at 95 % B for 3.5–4 min. In order to determine the concentration of atrazine in the experimental samples, a calibration curve of atrazine was prepared. The internal standard ATZ-D5 was added to the ATZ standard solutions with certain concentrations to reduce the error. Please see Table S1 and Fig. S1 for more details.

#### 2.4.2. HPLC-MS/MS

An Agilent QQQ 6460 mass spectrometer with a jet stream electrospray ion source and an Agilent 1200 series fast resolution LC system (Wilmington, DE) was employed to detect Atrazine water samples. MassHunter software was used for system control, data acquisition, and data processing. LC separation was performed on an Thermo Hypersil Gold C18 column reverse phase column (100 mm × 2.1 mm i.d., 1.9 µm particle size, 175 Å) with a gradient program at a flow rate of 500 µL/min. The mobile phase A consisted of 100 % HPLC grade water with 0.1 % formic acid and mobile phase B consisted of 100 % HPLC grade acetonitrile with 0.1 % formic acid. The gradient started with 10 % solvent B, held at 10 % B for 0.5 min before being increased to 95 % in 3.5 min and was then held at 95 % B for 1 additional minute. The column was re-equilibrated with 10 % B for 0.5 min. Total run time was 5.5 min with a 1 µL injection volume. The mass spectrometer was operated in positive jet stream ESI modes. Nitrogen was used as a nebulizer, turbo (heater) gas, curtain, and collision-activated dissociation gas. The capillary voltage was +3500 V. The ion source gas temperatures were 350 °C with flows of 5 L/min. Jetstream gas temperatures were 250 °C with flows of 11 L/min. ATZ, ATZ-D5 and metabolites were measured by selective reaction monitoring (SRM). The calibration curve was performed with internal calibration using 0.5 µM ATZ-D5 in water. The samples are prepared by taking 180 µL of water and adding 20 µL of the internal standard solution to glass vial before being transferred from a vial with a 200 µL glass insert. Please see Table S2 for more details.

### 2.5. Inductively coupled plasma atomic emission spectrometry

30 elements (Ag, Al, As, B, Ba, Be, Ca, Cd, Co, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, P, Pb, S, Sb, Se, Si, Sn, Sr, Ti, Tl, V, Zn) present in water sample after HVED treatment was quantified by Inductively Coupled Plasma Atomic Emission Spectrometry by Filab (Dijon, France) by means of an internal method with a 0.1 mg/L limit of quantification. Detailed results are reported in Table S3.

### 2.6. Energy dispersive X-ray spectrometer (EDS)

An environmental scanning electron microscope (ESEM; Quanta FEG 250, Thermofisher., OR, USA) equipped with an EDS (XFlash 5010; Bruker AXS Microanalysis, Berlin, Germany) was used to perform EDS. EDS can identify element concentrations of < 0.1 %. ESEM was operated at 20 kV and used a secondary electron detector.

### 2.7. Normalization and statistical analysis

After HVED/HFUS treatment, samples were analyzed LC-HRMS to obtain MS raw data which were converted into ABF (analysis base file) format by the software "AnalysisBaseFileConverter.exe". Normalization and statistical analysis in MS-DIAL version 4.9 software (Tsugawa et al., 2015): LOWESS normalization was performed using the internal standard compound information. All quality control (QC) samples were recognized as 'quality control' and the injection order was set. Output the alignment result and export peak intensity files containing the sample name, metabolite name, *m/z* and retention time in.csv format. Use MetaboAnalyst 6.0 (Pang et al., 2024) to perform visual and statistical analysis and produce principal component analysis (PCA) plots
for estimating differences between sample groups.

## 2.8. Toxicity evaluation by Daphnia magna

The crustacean *Daphnia magna* was used to test the potential toxicity of treatment solutions initially containing atrazine. Daphnia culture and toxicity tests were conducted according to the OECD Acute Immobility Test Report on *Daphnia* (Oecd, 2004). The reconstituted M4 medium was used to culture *Daphnia magna* which consist of 64.8 g/L NaHCO₃, 293.8 g/L CaCl₂·2H₂O, 123.3 g/L MgSO₄·7H₂O and 5.8 g/L KCl (Chadelaud et al., 2023). The medium had moderate pH value (7–8) and hardness (140–250 mg/L CaCO₃). In addition, constant oxygenation of the medium was applied. The *Daphnia magna* culture was placed in a temperature-controlled incubator at 20 ± 2 °C with a 16–8 h (light–dark) photoperiod. The *Daphnia magna* organisms were fed daily with the freshwater algae *Chlorella vulgaris*, and the medium was renewed every week.

All toxicity tests were repeated four times and performed under identical abiotic conditions based on the OECD guidelines. For each repetition, four experiments were conducted by diluting the treatment solution initially containing atrazine (20 mg/L) to 0.1, 0.5, 1.5, 2.5 and 5 mg/L of initial atrazine in 20 mL-M4 medium that included five *Daphnia magna* (age < 24 h). In the control experiment, five *Daphnia magna* (age < 24 h) were placed in 20 mL-M4 medium without the addition of treatment solution. After 48 h of exposure, the number of dead *Daphnia magna* was visually assessed (de, n.d.). Acute toxicity (LC₅₀) in *Daphnia magna* exposed to treatment solutions initially containing atrazine was assessed using Probit analysis. Its value referred to the initial atrazine concentration before degradation operation that induced death in 50 % of the organisms tested. In order not to bias the results, and for economic reasons, only the solutions prepared in MilliQ water were tested.

## 2.9. In silico toxicity

From the list of compounds identified by LC-HRMS during degradation by HFUS, HVED and Fenton oxidation, the 48-h Daphnia magna 50 percent lethal concentration was calculated using the T.E.S.T. software, version 5.1.2 (Martin, 2020) for each molecule from its SMILES molecular description. When a positional isomerism ambiguity remained, the same value was used for the different isomers. From the relative composition of the molecules, a composite LC50 proportional to the area ratios of the compounds and their individual LC50 values was recalculated.

# 3. Results and discussion

## 3.1. Qualitative and quantitative matrix effect on atrazine degradation

The study of the matrix effect is critical to understanding the efficiency and applicability of advanced oxidation processes (AOPs) in real-world scenarios. Atrazine, a model contaminant, was degraded under two different matrix conditions: a simplified system using deionized

water and a complex system employing a real aqueous matrix. The qualitative analysis focuses on identifying degradation by-products (Table1) and assessing differences in degradation pathways induced by the matrix composition. Using LC-HRMS, specific intermediates and transformation products of atrazine were detected and compared across the two matrices. The real aqueous matrix introduces organic and inorganic species (e.g., natural organic matter, salts, or metals) that can act as radical scavengers or participate in secondary reactions. These interactions can alter the degradation pathways and result in the formation of unique by-products not observed in deionized water. Quantitative analysis evaluates the efficiency of atrazine removal under the two matrix conditions. To achieve this, we compared atrazine solutions at a concentration of 20 mg/L, prepared either in raw water intended for human consumption or in deionized water. This concentration, significantly higher than those typically found in natural waters, is justified for two main reasons. First, it facilitates the identification of degradation products during analyses. Second, it meets industrial requirements, where reducing the volume of water to be treated is essential. A preliminary concentration step, such as ultrafiltration (Vahidi-Kolur et al., 2024), could be implemented to achieve such concentrations. It is important to note, however, that the atrazine concentration is not neutral in terms of its effect on the transformation efficiency. A high concentration can influence the degradation kinetics (Iovino et al., 2023) as well as the nature and quantity of the products formed (WU et al., 2015), making it a critical parameter to consider when evaluating the processes.

The results showed that atrazine was degraded more in deionized water than in tap water (Fig. 2), and there are differences in values under different degradation technologies HVED and HFUS. For example, after 120 min of HFUS treatment, the final concentration of ATZ solution in deionized water (9.6 mg/L) was slightly lower than that of atrazine solution in tap water (10.4 mg/L). However, since the measurement error of HPLC-HRMS was about 5 %, the difference was not significant. In addition, after 10 ms (corresponding to 16 min 40 s, 1 Hz) of HVED treatment, the final concentration of ATZ solution in deionized water (1.8 mg/L) was much lower than that in tap water (4.4 mg/L). Furthermore, as shown in Fig. 2-B, despite a significant variation in the final measured C/C₀ values, the same overall trend is observed. These measurements, performed by LC-MS/MS on solutions prepared with 1 mL of acetonitrile, confirm that the presence of this solvent, while improving the solubility of atrazine, ultimately reduces the efficiency of the treatments. This effect is explained by the inhibition of hydroxyl radical (OH) production (Li, 2013), which is essential for the degradation processes.

It can be seen that in HVED treatment, background water had a great impact on ATZ degradation. According to the online health monitoring results of tap water quality in different cities by French government, the conductivity of tap water in Compiègne, Oise, is 780 µS/cm at 25°C (Ministère Des Solidarités Et De La Santé, 2024). In comparison, the used deionized water has lower conductivity of 89 µS/cm at 25°C. The liquid of high conductivity is rich in species, accompanied by more types and numbers of particles, which reduce the collision of active species (e.g. hydroxyl radicals) with the target molecule (Wu et al., 2015). Besides,

<table><caption>**Table 1**
LC-HRMS Information on ATZ and its eight main generated metabolites.</caption><thead><tr><th>Abbreviation</th><th>Formula</th><th>Name</th><th>m/z</th><th>Retention Time (min)</th></tr></thead><tbody><tr><td>ATZ</td><td>C<sub>8</sub>H<sub>14</sub>ClN<sub>5</sub></td><td>Atrazine</td><td>216.1010</td><td>2.53</td></tr><tr><td>DEA</td><td>C<sub>6</sub>H<sub>10</sub>ClN<sub>5</sub></td><td>Deethylatrazine</td><td>188.0698</td><td>1.87</td></tr><tr><td>DIA</td><td>C<sub>5</sub>H<sub>8</sub>ClN<sub>5</sub></td><td>Deisopropylatrazine</td><td>174.0541</td><td>1.59</td></tr><tr><td>CDIT</td><td>C<sub>8</sub>H<sub>12</sub>ClN<sub>5</sub>O</td><td>N-[4-Chloro-6-(isopropylamino)-1,3,5-triazin-2-yl]acetamide</td><td>230.0804</td><td>2.08</td></tr><tr><td>CDET</td><td>C<sub>7</sub>H<sub>10</sub>ClN<sub>5</sub>O</td><td>N-[4-Chloro-6-(ethylamino)-1,3,5-triazin-2-yl]acetamide</td><td>216.0647</td><td>1.79</td></tr><tr><td>ODIT</td><td>C<sub>8</sub>H<sub>13</sub>N<sub>5</sub>O<sub>2</sub></td><td>N-[4-Hydroxy-6-(isopropylamino)-1,3,5-triazin-2-yl]acetamide</td><td>212.1142</td><td>1.19</td></tr><tr><td>HA</td><td>C<sub>8</sub>H<sub>15</sub>N<sub>5</sub>O</td><td>Hydroxyatrazine</td><td>198.1350</td><td>1.29</td></tr><tr><td>DEHA</td><td>C<sub>6</sub>H<sub>11</sub>N<sub>5</sub>O</td><td>Deethylhydroxyatrazine</td><td>170.1037</td><td>0.89</td></tr><tr><td>DIHA</td><td>C<sub>5</sub>H<sub>9</sub>N<sub>5</sub>O</td><td>Deisopropylhydroxyatrazine</td><td>156.0880</td><td>0.67</td></tr></tbody></table>
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** (A) ATZ degradation in deionized water and tap water by HVED and HFUS, the conditions of which are shown in Section 2.3. (B) Final C/C0 for ATZ in same matrix after 2 h. The initial atrazine concentration was 20 mg/L.</figcaption></figure>

the discharge reactor used has two phases, gas and liquid, and the gas phase occupies much more space than the liquid phase. The conductivity in the liquid phase has little effect on the dielectric constant of the entire space, so it has little effect on the overall discharge effect (Grymonpré et al., 2001). Therefore, the use of deionized water with low conductivity is more conducive to the degradation of ATZ than tap water.

In Fig. 3, three principal component analysis (PCA) score plots are presented, where (a) shows all these eight experiments, (b) shows only the four HVED-treated experiments, and (c) shows only the four HFUS-treated experiments. The PCA score plot estimates differences in molecules (235 unassigned molecules) between sample groups of these experiments. A point represents a sample and an ellipse with 95 % confidence interval represents the range of a sample group.

The general distribution of sample groups from these eight experiments is shown in Fig. 3(a). The two largest ellipses belong to

experiments "HVED ATZ DW" and "HVED ATZ TW", and they partially overlap, indicating that there are differences in the generated metabolites during the HVED treatment of ATZ in deionized water and tap water. This result is consistent with the previous large difference in degradation rates of ATZ in deionized water and tap water by HVED. In tap water, other species competed with ATZ for reactive species (e.g. hydroxyl radicals), which not only resulted in a reduction in ATZ degradation efficiency, but also resulted in a complex reaction system that contained both ATZ metabolites and metabolites of other species.

To explore the differences in degradation profiles of atrazine depending on the water matrix, principal component analysis (PCA) was applied to the non-targeted LC-HRMS data (235 unassigned features). PCA score plots allow the visualization of sample group separations based on their molecular composition. Each point represents a sample, and ellipses represent the 95 % confidence interval of replicates for each

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** PCA score plots illustrating differences in metabolite profiles (235 unassigned features) among experimental groups. (a) HVED-treated samples with and without atrazine in deionized water (DW) and tap water (TW). (b) HFUS-treated samples under the same conditions. Each point represents a sample; ellipses correspond to the 95 % confidence interval for each group. Note: Initial atrazine concentration: 20 mg/L. HVED conditions: 40 kV, 10 kA, 1 Hz, 16 min 40 s. HFUS conditions: 50 °C, 25 kHz, 2 h.DW = deionized water; TW = tap water.</figcaption></figure>
experimental group.

The full PCA including all eight experimental conditions is shown in Figure S3. It illustrates the overall distribution of all samples and provides a first insight into the effect of the treatment type and water matrix. In this global view, the two largest ellipses correspond to the

samples treated with HVED in deionized water (HVED ATZ DW) and in tap water (HVED ATZ TW). These ellipses partially overlap, suggesting differences in metabolite profiles depending on the matrix. This is consistent with the degradation data presented in Fig. 2, where the degradation efficiency of atrazine was significantly lower in tap water,

<caption>**Table 2**</caption>

Metabolite distribution and individual toxicity with Predicted toxicity, experimental Toxicity et corrected Toxicity (mg/L) for initial condition (ATZ 20 mg/L), HFUS, HVED and Fenton degradation. Ptox : Predicted composite toxicity; cPTOX : corrected Predicted composite toxicity.

<table><thead><tr><th rowspan="2">Molecules</th><th rowspan="2">LC50<br>Predicted<br>(mg/L)</th><th rowspan="2">Toxicity<br>Variation<br>/ ATZ</th><th rowspan="2">Initial<br>solution</th><th rowspan="2">US (2H)</th><th rowspan="2">HVED</th><th colspan="2">Fenton (2H/ 5Eq)</th></tr><tr><th>OFF<br>LINE</th><th>ON LINE</th></tr></thead><tbody><tr><td>Amino methanol</td><td>6</td><td>+ 66%</td><td></td><td></td><td></td><td>1%</td><td>1%</td></tr><tr><td>DDA</td><td>13</td><td>+ 24%</td><td></td><td></td><td></td><td>1%</td><td>1%</td></tr><tr><td>ATZ</td><td>17</td><td></td><td>100%</td><td>59%</td><td>31%</td><td>14%</td><td>12%</td></tr><tr><td>HA</td><td>23</td><td>- 31%</td><td></td><td></td><td>66%</td><td>0%</td><td>0%</td></tr><tr><td>P_214 P2 (CEPT)</td><td>25</td><td>-44%</td><td></td><td></td><td></td><td></td><td>8%</td></tr><tr><td>DEA</td><td>29</td><td>-66%</td><td></td><td>2%</td><td>0%</td><td>6%</td><td>3%</td></tr><tr><td>DIA</td><td>43</td><td>-145%</td><td></td><td></td><td></td><td>10%</td><td>7%</td></tr><tr><td>ATZ +1O P3 (CNIT)"</td><td>82</td><td>-369%</td><td></td><td></td><td></td><td></td><td>8%</td></tr><tr><td>CDIT</td><td>93</td><td>-430%</td><td></td><td>30%</td><td>0%</td><td>35%</td><td>22%</td></tr><tr><td>DEHA</td><td>95</td><td>-446%</td><td></td><td></td><td>1%</td><td>2%</td><td>1%</td></tr><tr><td>ODIT</td><td>98</td><td>-460%</td><td></td><td>3%</td><td>1%</td><td>13%</td><td>8%</td></tr><tr><td>CDET</td><td>125</td><td>-616%</td><td></td><td>5%</td><td>0%</td><td>6%</td><td>4%</td></tr><tr><td>CDDT</td><td>133</td><td>-660%</td><td></td><td>0%</td><td></td><td>0%</td><td>0%</td></tr><tr><td>ATZ +2O P1 (HAHT)'</td><td>150</td><td>-758%</td><td></td><td></td><td></td><td></td><td>2%</td></tr><tr><td>ATZ +2O P2 (HAHT)"</td><td>150</td><td>-758%</td><td></td><td></td><td></td><td></td><td>15%</td></tr><tr><td>CDAT</td><td>275</td><td>-1472%</td><td></td><td></td><td></td><td>10%</td><td>5%</td></tr><tr><td>AM</td><td>288</td><td>-1546%</td><td></td><td></td><td></td><td>1%</td><td>0%</td></tr><tr><td>DIHA</td><td>412</td><td>-2256%</td><td></td><td></td><td>0%</td><td>0%</td><td>0%</td></tr><tr><td>ATZ +3O P3</td><td>415</td><td>-2273%</td><td></td><td></td><td></td><td></td><td>1%</td></tr><tr><td>ATZ +4O P1</td><td>822</td><td>-4600%</td><td></td><td></td><td></td><td></td><td>2%</td></tr><tr><td>Ptox (mg/L)</td><td></td><td></td><td>17</td><td>49</td><td>24</td><td>92</td><td>108</td></tr><tr><td>Experimental toxicity (mg/L)</td><td></td><td></td><td>3.3</td><td>&gt; 5</td><td>2 ± 0.5</td><td>&lt; 0.1</td><td></td></tr><tr><td>cPtox (mg/L)</td><td></td><td></td><td>3.30</td><td>9.58</td><td>4.57</td><td>17.80</td><td>20.96</td></tr></tbody></table>
likely due to the competition for reactive species (e.g., hydroxyl radicals) from other matrix constituents. This competition may not only reduce degradation efficiency but also lead to the formation of additional transformation products unrelated to atrazine. In contrast, the ellipses representing HFUS-treated samples (*HFUS ATZ DW* and *HFUS ATZ TW*) are much smaller and almost completely overlap, indicating a limited influence of the water matrix on the composition of the degradation products under HFUS conditions. The four control samples (i.e., *HVED DW*, *HVED TW*, *HFUS DW*, and *HFUS TW*, with no atrazine) do not form ellipses and are all clustered near PC2 = 0, showing minimal chemical differences among untreated samples. To focus more specifically on the influence of the matrix within each treatment type, Fig. 3 now presents two separate PCA plots. Fig. 3a shows only the four HVED-treated experiments (with and without atrazine, in deionized and tap water) and Fig. 3b shows only the four HFUS-treated experiments under the same conditions. In Fig. 3a, the *HVED ATZ DW* and *HVED ATZ TW* groups show partial overlap, while the controls (*HVED DW* and *HVED TW*) remain centered near the origin. This highlights the strong effect of the matrix on the degradation of atrazine during HVED treatment. Conversely, Fig. 3b reveals that the samples *HFUS ATZ DW* and *HFUS ATZ TW* cluster more closely, and their respective controls are again centered near the origin. This confirms that, unlike HVED, the HFUS treatment is less sensitive to matrix composition, both in terms of degradation efficiency and metabolite profile, which aligns with the degradation data presented in Fig. 2.

Due to the differences of the sample groups in the PCA score plot (Fig. 3), the atrazine metabolites analysis was performed. Eight main generated metabolites of atrazine (abbreviation shown in Table 2 and chemical structures shown in Fig. 5) were found by HPLC-HRMS. The heatmap of these eight main generated metabolites of atrazine is shown in Fig. 4.

The dechlorination-hydroxylation products HA, DIHA and DEHA were mainly produced in the electrical discharge's experiments. This shows that hydroxylation was the main pathway for atrazine

degradation during high-voltage electrical discharge treatment. Generally, hydroxylation of atrazine was considered as a detoxification method for the treatment of atrazine-contaminated water due to the conversion into non-toxic hydroxylation products (e.g. HA) (Mu et al., 2019). Based on this information and the higher degradation rate of atrazine, one could conclude that HVED treatment is better than HFUS treatment. Besides, impurities in tap water competed with atrazine for reactive oxygen species (hydroxy radicals), causing more HA to be produced in deionized water than in tap water, accompanied by an increase in the production of secondary products DEHA and DIHA. The dechlorination-hydroxylation pathway is shown on Fig. 5, Pathway I.

In addition, the alkyl oxidation products (CDIT and CDET) and the dealkylation products (DEA and DIA), were mainly produced in ultrasound's experiments regardless of the quality of the aqueous matrix. This shows that in ultrasound treatment, the reactive species (e.g. hydroxyl radicals) preferred to attack the alkyl chain on the nitrogen atom rather than the carbon bearing the chlorine atom on the triazine. The alkyl oxidation pathway and the dealkylation pathway are shown on Fig. 5, Pathway II and III. Besides, product ODIT might be from alkyl oxidation of HA in HVED experiments, or from dechlorination-hydroxylation of CDIT in HFUS.

Based on these experiments, it can be concluded that the raw water matrix reduces the efficiency of the HVED treatment and has a minor impact on the performance of HFUS. Qualitative analyses confirmed the formation of major products specific to the mechanisms activated by each technique. However, the products formed were identical regardless of whether they were generated in deionized water or raw water. This observation allows toxicological analyses to be limited to samples prepared in deionized water, ensuring that the degradation effect is highlighted independently of the raw water quality, which can be subject to fluctuations.

<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Heatmap of main generated atrazine metabolites. Sampling times are expressed in min for HFUS and in ms for HEVD.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Fig. 5. Proposed degradation pathway of atrazine.</figcaption></figure>

## 3.2. Toxicity of treatment solutions initially containing atrazine

As demonstrated by our analyses, although atrazine is degraded, it is not fully mineralized and transforms into other compounds. The resulting solutions are intended to be released into the environment and may consequently impact the ecosystem. It therefore becomes essential to assess the toxicity of these solutions. To achieve this, we propose using the Daphnia magna model (Klementová et al., 2019; Méthode d'analyse Détermination de la toxicité létale, 2007), a widely recognized

bioindicator for evaluating the impact of chemical substances on aquatic environments. We compared the toxicity of final treatment solutions from the experiments of atrazine degradation by three treatment technologies: HVED, HFUS, and Fenton oxidation. The test conditions and LC50s are grouped in Table S4 and Fig. 6: The potential toxicity of treatment solutions initially containing Atrazine.LC50 was expressed in mg/L of initial ATZ. The acute toxicity (LC50) in *Daphnia magna* varied from different treatment solutions. The atrazine solution treated by Fenton oxidation (LC50 < 0.1 mg/L) was more toxic than the blank

<figure><img src="image_8.png" /><figcaption>Fig. 6. The potential toxicity of treatment solutions initially containing Atrazine.LC50 was expressed in mg/L initial ATZ. Or Fe²⁺.</figcaption></figure>
initial atrazine solution (LC₅₀ = 3.3 mg/L). Hydrogen peroxide used in Fenton, could be toxic for *Daphnia magna*. Additionally, the toxicity of atrazine solutions treated by US 525 kHz and HVED were LC₅₀ > 5 mg/L and 1.5 < LC₅₀ < 2.5 mg/L, lower than that of atrazine solution treated by Fenton oxidation. Fenton oxidation may be more toxic because of the main generated metabolite ammeline (AM).

Besides, the ferrous ions reagents $Fe^{2+}$ have an impact on the toxicity of treatment solutions. For atrazine solutions treated by US 525 kHz, the addition of ferrous ions $Fe^{2+}$ improved the degradation rate of atrazine, making its degradation go further Conversely, the addition of ferrous ions $Fe^{2+}$ reduced the toxicity of atrazine solutions treated by HVED. What's more, ferrous ions $Fe^{2+}$ alone (without initial atrazine) shows an LC₅₀ greater than other treatment conditions suggesting that the toxicity comes from atrazine or its metabolites.

Measuring the toxicity of a solution is a lengthy and costly procedure. However, with an LC-HRMS separation lasting less than 4 min, it is possible to identify dozens of molecules in a solution. With the emergence of machine learning techniques and QSAR models, it is now feasible to estimate the toxicity of each identified molecule. Recently, Katarzyna (Arturi et al., 2025; Arturi and Hollender, 2023) proposed pre-trained Python scripts capable of directly predicting toxicity from LC-HRMS data preprocessed by specific software. This approach could significantly reduce the time and costs associated with toxicological evaluations while providing accurate results based on the molecular properties of the identified compounds. However, the use of such scripts remains complex. It requires specific skills in programming, LC-HRMS data processing, and a deep understanding of predictive models such as machine learning or QSAR models. Additionally, adapting the scripts to the specificities of experimental data can pose an additional challenge, limiting their accessibility to non-specialized users. In this study, we opted to use the semi-quantitative data extracted from MassHunter Qualitative (Agilent) after identifying the major transformation products. This identification was performed through a dual manual analysis using both MassHunter Qualitative (Agilent) and MSDIAL. In the absence of standards for all molecules, we assumed that the ionization efficiency of each molecule was equivalent, although this hypothesis is not entirely realistic et we determined the proportion of each molecule (Px) identified in positive electrospray mode in a second step, we calculated the toxicity of each molecule (Tx) using the TEST software, based on their SMILES formulas. For this study, we limited ourselves to the Daphnia magna LC50 (48 h) toxicity, corresponding to our previous tests. Based on this data, we recalculated a Predicted Composite Toxicity (Ptox) by summing the toxicities of each molecule (TX), weighted by their proportion (Px), as shown in Eq. 1. Additionally, we calculated a Corrected Predicted Composite Toxicity (cTox), using the toxicity of atrazine at a concentration of 20 mg/L prior to degradation as a reference (Eq. 2).

$$Ptox = \sum PxxTx \qquad (1)$$

$$cPtox = Ptoxx \frac{Ptox(ATZi)}{Experimental\ toxicity(ATZi)} \qquad (2)$$

where *each different molecule*

We also complemented this data with a dataset previously obtained through direct coupling with the mass spectrometer, in order to limit the evolution of the transformation products. Detailed information on the molecular structures is available in Table S5.

The results of these calculations are reported in Table 2. In this table, the molecules are ranked by decreasing in silico toxicity. It is observed that the composite toxicities calculated in silico are less pronounced than the measured toxicities, with a similar trend for ATZ without treatment. The toxicity order increases as follows: Fenton, HFUS, HVED, and untreated ATZ for in silico evaluations, and HFUS, HVED, untreated ATZ, and Fenton for *in vivo* tests. The major discrepancy observed for the

Fenton condition can be explained by the methodology employed. Indeed, Ptox is determined based on the molecules identified by LC-HRMS. Due to technical limitations of chromatographic separation and positive electrospray ionization, certain molecules, such as hydrogen peroxide (present at a concentration of approximately 16 mg/L), are not accounted for. Meinertz reports that hydrogen peroxide has no effect on *Daphnia magna* at concentrations up to 1.25 mg/L but causes 100 % mortality over 19 days at concentrations exceeding 5 mg/L (Meinertz et al., 2008). Additionally, the Quebec Poison Control Center suggests an LC50 of 300 mg/L (SECTION 01-PRODUCT AND COMPANY IDENTIFICATION, n.d) for this molecule. The Fenton 5eq condition also requires the presence of $Fe^{2+}$ ions at a concentration of 33 mg/L, whose toxicity is well-documented, both through our tests and other studies (Bondarenko et al., 2020) with an estimated LC50 at 48H of 7.2 mg/L (Khangarot and Ray, 1989).

When comparing the degradation between HVED and HFUS, a more significant degradation of ATZ is observed under the HVED condition. Although this leads to the majority production of Hydroxyatrazine (HA) with a reduction in toxicity, it still remains relatively toxic compared to the degradation products observed under HFUS and Fenton conditions. HFUS has an advantage over Fenton, mainly due to the toxicity of $H_2O_2$ and $Fe^{2+}$ ions in the Fenton process. The Ptox for the Fenton conditions, whether with real-time sampling or post-reaction sampling, is similar and significantly lower than for the HVED and HFUS conditions. This is mainly explained by the substantial presence of hydroxylated compounds. The contribution of the online sampling method, previously developed by our team, demonstrates its relevance in identifying hydroxylated molecules, such as the isomers of 2-({4-chloro-6-[(1-hydroxyethyl)amino]-1,3,5-triazin-2-yl}amino)propan-2-ol (HAHT).

Furthermore, the formation of insoluble deposits was observed during degradation by HVED. EDS spectroscopy analysis of this powder showed the significant presence of titanium, aluminum, and silicon in addition to the presence of calcium (Figure S2). This observation led us to question the contamination of the solution after treatment. The ICP AOS analysis also showed a significant presence of the same elements in addition to Calcium, Magnesium and Sodium. (Table S3). The presence of Ti and Al can be explained by the degradation of the electrode during HVED treatment. In aqueous solution, we can assume that the titanium observed at a concentration varying from 1 to 2.5 mg/L is probably in the ionic form and does not pose any major toxicological concerns with an LC50 greater than 100 mg/L (Okamoto et al., 2015), we can question its oxidation state in the solid residue. In its $TiO_2$ form, the LC50 at 48 h is between 4.5 and 5.5 mg/L (Kim et al., 2014). In light of the analyses, we can question the contribution of the residues formed during the HVED treatment and in particular of aluminum, the concentration of which between 0.1 and 1 mg is similar to the LC50 for this element (Okamoto et al., 2015). It would be valuable to investigate the impact of electrode composition on the nature and quantity of released ions, through a systematic parametric study. In addition, the discharge configuration—whether applied directly in the liquid phase (submerged) or above the solution (plasma-over-liquid)—could also influence ion release, and optimizing this setup may help minimize contamination from electrode materials. Moreover, the data obtained in this study are limited to compounds that can be separated by reversed-phase liquid chromatography and ionized in positive electrospray mode. This likely excludes small polar molecules such as organic acids (OAs), which are better detected using alternative chromatographic methods and negative ionization mode. However, these OAs are generally considered to be of lower toxicological concern. Future work will focus on quantitative analysis and the assessment of mineralization levels to provide a more comprehensive evaluation of treatment performance.

Based on this information, we can conclude that Ptox is a relevant tool for comparing degradation conditions without the need for in vivo testing. However, it is crucial to consider the limitations of this technique. It relies solely on LC-HRMS data and, in this case, on a single ionization method. It will be necessary to incorporate the reaction
adjuvants, such as Fe²⁺ and H₂O₂, or metals into the calculation, while accounting for ionization modes, which could lead to the omission of certain molecules that are not evaluated. Furthermore, in the absence of quantitative data, the calculation error will be larger

## 4. Conclusion

Through this study, we were able to compare the degradation differences associated with the use of a real matrix during the degradation of a highly concentrated atrazine solution. This evaluation is limited to water from a single catchment point, and treatment performance may vary depending on the specific composition of the water matrix. A broader study involving multiple water sources could complement this initial assessment. We also evaluated the toxicity of both techniques and validated a workflow based on LC-HRMS data and toxicity assessment via the QSAR method. The molecular information, along with the eco-toxicity evaluations of the potential effluents, allows us to conclude that HFUS produces less toxic solutions compared to the Fenton and HVED techniques. While Fenton generates less toxic, primarily hydroxylated compounds, it is necessary to address the presence of H₂O₂, Fe²⁺ ions and other metals in order to achieve acceptable toxicity levels. The implementation of a toxicity evaluation protocol based on LC-HRMS data appears promising for reducing the costs associated with obtaining this information and for guiding technological choices in the use of AOPs for micropollutant degradation. However, certain limitations must be acknowledged. First, the identified transformation products are restricted to compounds that are amenable to reversed-phase chromatography and ionizable under the conditions used in this study. This excludes hydrogen peroxide, small organic acids, and cationic species generated during HVED treatment.

### CRediT authorship contribution statement

**Nabil Grimi:** Writing – review & editing, Writing – original draft, Supervision, Funding acquisition, Conceptualization. **Stéphane Firmin:** Writing – review & editing, Supervision, Conceptualization. **merlier franck:** Writing – review & editing, Writing – original draft, Resources, Methodology, Investigation, Data curation, Conceptualization. **Junting Hong:** Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Data curation. **Nadia Boussetta:** Writing – review & editing, Methodology, Investigation, Data curation, Conceptualization. **Messika Revel:** Writing – review & editing, Data curation, Conceptualization. **Frederic Nadaud:** Writing – review & editing, Investigation, **Gérald Enderlin:** Writing – review & editing, Supervision, Conceptualization. **Lauresse Nguimapi Tsague:** Investigation. **Clarisse Roig:** Investigation.

### Declaration of Generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) used CHAT GPT in order to ensure the translation and improvement of English. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

### Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper

### Acknowledgements

This study was funded by the Investments for the Future of the French Government (ANR-001). The utilized equipment was co-founded by Regional Council of Picardie and European Union (CPER 2007-2020).

The first author gratefully acknowledges the financial support provided by the China Scholarship Council (CSC).

### Electronic Supplementary Material Supplementary

material is available in the online version of this article at "250228_S1.docx", Table S1: Preparation of atrazine stock solutions (L1-L8); Fig. S1: Calibration curve of atrazine with 8 points (L1-L8).; Table S2. SRM for LC-QQQ Atrazine Quantification; Table S3. ICP AOS of Milliq Water and TAP Water after HEVD treatment. Quantification (LOQ 0.1 mg/L) and Daphnia magna (48H) LC50 Toxicity; Figure S2: Energy dispersive X-ray spectrometer (EDS) of back residue of HVED experiment for tap water; Table S4: The potential toxicity of treatment solutions initially containing Atrazine; Table S5: detailed structural information on ATZ and degradation product. Fig. S3: PCA scores

## Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.ecoenv.2025.118706.

### Data availability

Data will be made available on request.

### References

* Organisation for Economic Cooperation and Development (Oecd), 2004. Daphnia sp. Acute Immobilisation Test.

* Ai, H., Wu, X., Zhang, L., Qi, M., Zhao, Y., Zhao, Q., Zhao, J., Liu, H., 2019. QSAR modelling study of the bioconcentration factor and toxicity of organic compounds to aquatic organisms using machine learning and ensemble methods. Ecotoxicol. Environ. Saf. 179, 71–78. https://doi.org/10.1016/j.ecoenv.2019.04.035.

* Arturi, K., Hollender, J., 2023. Machine learning-based hazard-driven prioritization of features in nontarget screening of environmental high-resolution mass spectrometry data. Environ. Sci. Technol. 57, 18067–18079. https://doi.org/10.1021/acs.est.3c00304.

* Arturi, K., Harris, E.J., Gasser, L., et al., 2025. MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data. J. Chemin. 17, 14. https://doi.org/10.1186/s13321-025-00950-4.

* Balraadsing, S., Peijnenburg, W.J.G.M., Vijver, M.G., 2022. Exploring the potential of in silico machine learning tools for the prediction of acute Daphnia magna nanotoxicity. Chemosphere 307. https://doi.org/10.1016/j.chemosphere.2022.135930.

* Baran, N., Surdyk, N., Auterives, C., 2021. Pesticides in groundwater at a national scale (France): impact of regulations, molecular properties, uses, hydrogeology and climatic conditions. Sci. Total Environ. 791. https://doi.org/10.1016/j.scitotenv.2021.148137.

* Baran, N., Rosenbom, A.E., Kozel, R., Lapworth, D., 2022. Pesticides and their metabolites in European groundwater: comparing regulations and approaches to monitoring in France, Denmark, England and Switzerland. Sci. Total Environ. 842. https://doi.org/10.1016/j.scitotenv.2022.156696.

* Bondarenko, L., Kahru, A., Terekhova, V., Dzhardimalieva, G., Uchanov, P., Kydralieva, K., 2020. Effects of humic acids on the ecotoxicity of Fe3O4 nanoparticles and fe-ions: impact of oxidation and aging. Nanomaterials 10, 1–18. https://doi.org/10.3390/nano10102011.

* Cavasotto, C.N., Scardino, V., 2022. Machine learning toxicity prediction: latest advances by toxicity end point. ACS Omega 7, 47536–47546. https://doi.org/10.1021/acsomega.2c05693.

* Chadelaud, T., Zeghioud, H., Reynoso de la Garza, A., Fuerte, O., Benítez-Rico, A., Revel, M., Chávez-Miyauchi, T.E., Djalal, H., 2023. Comparative study of rhodamine B treatment: assessing of efficiency processes and ecotoxicity of by-products. Processes 11. https://doi.org/10.3390/pr11092671.

* M. de, de la Lutte contre les changements climatiques, MA. 500 – D.mag. 1.1 (révision 3). Détermination de la toxicité: létalité (CL50 48h) chez la daphnie Daphnia magna, n. d. (https://www.ceaeq.gouv.qc.ca/methodes/pdf/methode-analyse-500-daphnia-magna.pdf).

* European Union, Directive, 2006. 2006/118/EC of the European Parliament and of the Council of 12 December 2006 on the protection of groundwater against pollution and deterioration. Off. J. Eur. Commun.

* Fujikawa, M., Nakao, K., Shimizu, R., Akamatsu, M., 2007. QSAR study on permeability of hydrophobic compounds with artificial membranes. Bioorg. Med. Chem. 15, 3756–3767. https://doi.org/10.1016/j.bmc.2007.03.040.

* Goodman, M., Mandel, J.S., Desesso, J.M., Scialli, A.R., 2014. Atrazine and pregnancy outcomes: a systematic review of epidemiologic evidence. Birth Defects Res. B Dev. Reprod. Toxicol. 101, 215–236. https://doi.org/10.1002/bdrb.21101.
Grymonpré, D.R., Sharma, A.K., Finney, W.C., Locke, B.R., 2001. The role of Fenton's reaction in aqueous phase pulsed streamer corona reactors. Chem. Eng. J. 82, 189-207. https://doi.org/10.1016/S1385-8947(00)00345-4.

Hayes, T.B., Collins, A., Lee, M., Mendoza, M., Noriega, N., Stuart, A.A., Vonk, A., 2002. Hermaphroditic, demasculinized frogs after exposure to the herbicide atrazine at low ecologically relevant doses. (www.pnas.org/cgidoi10.1073pnas.082121499).

Hong, J., Boussetta, N., Enderlin, G., Grimi, N., Merlier, F., 2022b. Real-time monitoring of the atrazine degradation by liquid chromatography and high-resolution mass spectrometry: effect of fenton process and ultrasound treatment. Molecules 27. https://doi.org/10.3390/molecules27249021.

Hong, J., Boussetta, N., Enderlin, G., Merlier, F., Grimi, N., 2022a. Degradation of residual herbicide atrazine in agri-food and washing water. Foods 11, 2416. https://doi.org/10.3390/foods11162416.

Hong, J., Boussetta, N., Enderlin, G., Merlier, F., Grimi, N., 2023. Degradation of herbicide atrazine in water by high voltage electrical discharge in comparison with Fenton oxidation and ultrasound treatments. RSC Sustain. 1, 1462–1470. https://doi.org/10.1039/D3SU00103B.

Hopenhayn-Rich, C., Stump, M.L., Browning, S.R., 2002. Regional assessment of atrazine exposure and incidence of breast and ovarian cancers in Kentucky. Arch. Environ. Contam. Toxicol. 42, 127–136. https://doi.org/10.1007/s002440010300.

Hu, N., Xu, Y., Sun, C., Zhu, L., Sun, S., Zhao, Y., Hu, C., 2021. Removal of atrazine in catalytic degradation solutions by microalgae Chlorella sp. and evaluation of toxicity of degradation products via algal growth and photosynthetic activity. Ecotoxicol. Environ. Saf. 207. https://doi.org/10.1016/j.ecoenv.2020.111546.

Iovino, P., Chianese, S., Fenti, A., Blotevogel, J., Musmarra, D., 2023. An innovative approach for atrazine electrochemical oxidation modelling: process parameter effect, intermediate formation and kinetic constant assessment. Chem. Eng. J. 474, 146022. https://doi.org/10.1016/j.cej.2023.146022.

Jia, W., Wang, H., Wu, Q., Sun, L., Si, Q., Zhao, Q., Wu, Y., Ren, N., Guo, W., 2023. Insight into Chinese medicine residue biochar combined with ultrasound for persulfate activation in atrazine degradation: Acanthopanax sentosus precursors, synergistic effects and toxicity assessment. Sci. Total Environ. 880, 163054. https://doi.org/10.1016/j.scitotenv.2023.163054.

Khangarot, B.S., Ray, P.K., 1989. Investigation of Correlation between Physicochemical Properties of Metals and Their Toxicity to the Water Flea Daphnia magna Straus.

Kim, K.T., Klaine, S.J., Kim, S.D., 2014. Acute and chronic response of Daphnia magna exposed to TiO2 nanoparticles in agitation system. Bull. Environ. Contam. Toxicol. 93, 456–460. https://doi.org/10.1007/s00128-014-1295-5.

Klementová, S., Hornychová, L., Sorf, M., Zemanová, J., Kahoun, D., 2019. Toxicity of atrazine and the products of its homogeneous photocatalytic degradation on the aquatic organisms Lemna minor and Daphnia magna. Environ. Sci. Pollut. Res. 26, 27259–27267. https://doi.org/10.1007/s11356-019-05710-0.

Kucka, M., Pogrmic-Majkic, K., Fa, S., Stojilkovic, S.S., Kovacevic, R., 2012. Atrazine acts as an endocrine disrupter by inhibiting cAMP-specific phosphodiesterase-4. Toxicol. Appl. Pharmacol. 265, 19–26. https://doi.org/10.1016/j.taap.2012.09.019.

Li, X., 2013. Solvent effects and improvements in the deoxyribose degradation assay for hydroxyl radical-scavenging. Food Chem. 141, 2083–2088. https://doi.org/10.1016/j.foodchem.2013.05.084.

Martin, Todd, User's Guide for T. E. S. T. (Toxicity Estimation Software Tool) Version 5.1 A Java Application to Estimate Toxicities and Physical Properties from Molecular Structure, 2020. https://www.epa.gov/chemical-research/toxicity-estimation-software-tool-test.

Meinertz, J.R., Greseth, S.L., Gaikowski, M.P., Schmidt, L.J., 2008. Chronic toxicity of hydrogen peroxide to Daphnia magna in a continuous exposure, flow-through test

system. Sci. Total Environ. 392, 225-232. https://doi.org/10.1016/j.scitotenv.2007.12.015.

Méthode d'analyse Détérioration de la toxicité létale, 2007. CL 50 48h Daphnia magna. Ministère Des Solidarités Et De La Santé, 2024. Résultats du contrôle sanitaire de l'eau distribuée commune par commune.

Mu, Y., Zhan, G., Huang, C., Wang, X., Ai, Z., Zou, J., Luo, S., Zhang, L., 2019. Dechlorination-hydroxylation of atrazine to hydroxyatrazine with thiosulfate: a detoxification strategy in seconds. Environ. Sci. Technol. 53, 3208–3216. https://doi.org/10.1021/acs.est.8b06351.

Okamoto, A., Yamamoto, M., Tatarazako, N., 2015. Acute toxicity of 50 metals to Daphnia magna. J. Appl. Toxicol. 35, 824–830. https://doi.org/10.1002/jat.3078.

Pang, Z., Lu, Y., Zhou, G., Hui, F., Xu, L., Viau, C., Spigelman, A.F., MacDonald, P.E., Wishart, D.S., Li, S., Xia, J., 2024. MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation. Nucleic Acids Res. 52, W398-W406. https://doi.org/10.1093/nar/gkae253.

Qin, L.T., Chen, Y.H., Zhang, X., Mo, L.Y., Zeng, H.H., Liang, Y.P., 2018. QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide. Chemosphere 198, 122–129. https://doi.org/10.1016/j.chemosphere.2018.01.142.

Rinsky, J.L., Hopenhayn, C., Golla, V., Browning, S., Bush, H.M., 2012. Atrazine exposure in public drinking water and preterm birth. Public Health Rep. 127 (1), 72–80. https://doi.org/10.1177/003335491212700108.

SECTION 01-PRODUCT AND COMPANY IDENTIFICATION-Centre Anti-Poison pour le Québec: (800) 463-5060, n.d. (www.labmat.com).

Tsugawa, H., Cajka, T., Kind, T., Ma, Y., Higgins, B., Ikeda, K., Kanazawa, M., Vandergheynst, J., Fiehn, O., Arita, M., 2015. MS-DIAL: Data-independent MS/MS deconvolution for comprehensive metabolome analysis. Nat. Methods 12, 523–526. https://doi.org/10.1038/nmeth.3393.

Vahidi-Kolur, R., Yazdanbakhsh, A., Hosseini, S.A., Sheikhmohammadi, A., 2024. Photoreduction of atrazine from aqueous solution using sulfite/iodide/UV process, degradation, kinetics and by-products pathway. Sci. Rep. 14, 5217. https://doi.org/10.1038/s41598-024-55585-6.

Voulvoulis, N., Arpon, K.D., Giakoumis, T., 2017. The EU water framework directive: from great expectations to problems with implementation. Sci. Total Environ. 575, 358–366. https://doi.org/10.1016/j.scitotenv.2016.09.228.

Wang, Y., Lin, T., Chen, H., 2023. Degradation of atrazine by a UV-activated organic chloramines process: kinetics, degradation pathways, disinfection by-product formation, and toxicity changes. Chem. Eng. J. 468, 143788. https://doi.org/10.1016/j.cej.2023.143788.

Winchester, P.D., Huskins, J., Ying, J., 2009. Agrichemicals in surface water and birth defects in the United States. Acta Paediatr. Int. J. Paediatr. 98, 664–669. https://doi.org/10.1111/j.1651-2227.2008.01207.x.

Wirbisky, S.E., Weber, G.J., Sepülveda, M.S., Lin, T.L., Jannasch, A.S., Freeman, J.L., 2016. An embryonic atrazine exposure results in reproductive dysfunction in adult zebrafish and morphological alterations in their offspring. Sci. Rep. 6. https://doi.org/10.1038/srep21337.

Wu, H., Fang, Z., Xu, Y., 2015. Degradation of aniline wastewater using dielectric barrier discharges at atmospheric pressure. Plasma Sci. Technol. 17, 228–234. https://doi.org/10.1088/1009-0630/17/3/10.

Wu, H., Fang, Z., Xu, Y., 2015. Degradation of aniline wastewater using dielectric barrier discharges at atmospheric pressure. Plasma Sci. Technol. 17, 228. https://doi.org/10.1088/1009-0630/17/3/10.

Zekfsër, I.S., Everett, L.G., 2004. Groundwater resources of the world and their use. UNESCO.