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# Study of intense pulsed light as a new remediation process for pesticides in water using mass spectrometry and ecotoxicological approaches

François Clavero<sup>a,b,*</sup>, Jérôme Cachot<sup>c</sup>, Christelle Clérandeau<sup>c</sup>, Laure Sandoval<sup>b</sup>, Fanny Meytraud<sup>b</sup>, Nicolas Picard<sup>b</sup>, Warren Albertin<sup>a,†</sup>, Gilles de Revel<sup>a</sup>, Rémy Ghidossi<sup>a</sup>, Céline Franc<sup>a,‡</sup>

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## ARTICLE INFO

### Keywords:

HPLC-MS/MS

Acute toxicity

Phytosanitary products

Photoproducts

Pesticide degradation

## ABSTRACT

Pulsed light (PL) technology was investigated as a pesticide removal process. The degradation of 20 pesticides in water was monitored by mass spectrometry and revealed 74 photoproducts. Structure hypotheses were proposed for 47 photoproducts according to their fragmentation, isotopic pattern, and literature data. This work enabled the development of a LC-MS method for the relative quantification of photoproducts and for the absolute quantification of their parent pesticides.

This analytical method was then applied in optimizing the PL parameters. It was demonstrated that increasing voltage and fluence leads to more efficient pesticide degradation, with concentration reduction of 99 % for 14 pesticides. The compound sensitivity seems to be family dependent. Moreover, PL succeeded in degrading the photoproducts themselves.

Acute toxicity tests were performed on the bacteria *Aliivibrio fischeri*. A significant reduction in toxicity was observed for 10 out of 18 individual pesticides, while no increase was observed for the remaining seven. When applied to a cocktail solution, the toxicity decreased by 7.25-fold between the untreated and the most PL treated solution. This work demonstrates that PL is a promising process for removing pesticides from contaminated water. Further studies are needed to demonstrate the safety of treated wastewater on various trophic links.

## 1. Introduction

Pesticides are used in agriculture to ensure the production of food in sufficient quantity and quality for an ever-increasing world population. Due to their protective function against plant pathogens, phytosanitary products can be harmful to humans and ecosystems (Zhang et al., 2011). According to the FAO (Food and Agriculture Organization) (World Health Organization; Food and Agriculture Organization of the United Nations 2019), the total import and export value of pesticides in Europe has more than doubled in the past two decades compared to the 1990s. The increased use of pesticides has been accompanied by the growing presence of residues in soil (Aktar et al., 2009). In 2022, among the different crops, winegrowing represented 7,200,000 hectares globally according to the OIV (Organisation Internationale de la Vigne et du Vin,

International Organisation of Vine and Wine). Studies have demonstrated that winegrowing is responsible for groundwater and soil contamination. Manjarres-López et al. (2021) revealed the presence of 30 pesticides in waters and soils in the vineyard region of Rioja in Spain. Hildebrandt et al. (2008) noted that 12 % of the samples taken from the Ebro, Duero, and Miño river basins exceeded 0.1 µg/L, which is the European Union (EU) maximum residual pesticide limit in groundwater. Moreover, the 2023 report by the French Ministry of Ecological Transition and Territorial Cohesion reveals that pesticides used in agricultural and non-agricultural areas contaminate nearly all surface waters in France. Furthermore, although decreases in concentration have been observed since 2008, pesticides continue to exert high cumulative toxic pressures on half of the monitoring stations (La pollution chimique des cours d'eau et des plans d'eau en France de 2000 à 2020). The issue of

<footnote><sup>a</sup> Univ. Bordeaux, INRAE, Bordeaux INP, Bordeaux Sciences Agro, UMR 1366, CENO, ISVV, Villenave d'Ornon, France</footnote>

<footnote><sup>b</sup> SANODEV, Limoges, France</footnote>

<footnote><sup>c</sup> Univ. Bordeaux, CNRS, INP Bordeaux laboratoire EPOC, UMR 5805, Pessac, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: francois.clavero@u-bordeaux.fr (F. Clavero), jerome.cachot@u-bordeaux.fr (J. Cachot), christelle.clerandeau@u-bordeaux.fr (C. Clérandeau), laure.sandoval@sanodev.com (L. Sandoval), fanny.meytraud@sanodev.com (F. Meytraud), nicolas.picard@sanodev.com (N. Picard), warren.albertin@ubordeaux.fr (W. Albertin), gilles.de-revel@u-bordeaux.fr (G. de Revel), remy.ghidossi@u-bordeaux.fr (R. Ghidossi), celine.franc@u-bordeaux.fr (C. Franc).</footnote>
water pollution by pesticides is therefore a crucial societal concern. Viticulture generates significant volumes of contaminated wastewater, which are a considerable potential source of pollution. The development of remediation techniques for viticultural effluents to reduce pesticide concentrations and decrease the toxicity of this wastewater is essential to ensure the sustainability of aquatic ecosystems, given the large volumes produced annually.

Over the past decades, interest in physical techniques to degrade phytosanitary products has grown. Indirect photolysis (photocatalysis) showed its efficiency to remove pesticides. The operating principle of this technology is to use UV radiation to photoexcite a catalyst, generally a metallic compound, to produce hydroxyl radicals which then react with the pollutants to degrade them. Photocatalysis experiments made on leaching water had enabled to degrade to 100 % after 30 min of exposure azoxystrobin, hexaconazole, pirimicarb, kresoxim-methyl, pyrimethanil, propyamide, tebuconazole and triadimenol from initial concentrations of 0.5 mg/L using ZnO as photocatalyst (Navarro et al., 2009). Thiamethoxam was totally removed and flonicamid was degraded to 86 % after 90 min in water from concentrations between 1 and 20 mg/L with TiO₂ as photocatalyst (Arfanis et al., 2023). The disadvantage of these processes is that they require the synthesis of photocatalysts, which will generate waste and are most of the time metal oxides known to pose a significant threat to aquatic ecosystems (Noventa et al., 2018; Miller et al., 2012).

Direct photodegradation does not require a photocatalyst. It involves the absorption of photons by organic molecules which induces an increase in the energy level of the treated molecule to an excited state, leading to its photodegradation into photoproducts upon returning to a fundamental state (Patria et al., 1995). The ability of direct photodegradation to degrade pesticides has already been demonstrated. Indeed, Lassalle et al. (2014) obtained 90% of degradation for boscalid after 150 min of irradiation ranging from 200 to 650 nm, from initial concentrations of 5 mg/L. Zeng et al. (2019) showed a total degradation of pyraclostrobin after 30 h exposure to 254 nm irradiation with a UV-C lamp from initial concentrations of 5 mg/L. However, its effectiveness may be limited depending on the compounds studied. Sanches et al. (2010) demonstrated that mercury lamp monochromatic light at 254 nm had almost no effect on the content (initial concentration 1 mg/L) of isoproturon.

More recently, pulsed light (PL) has gained significant attention due to its low-cost, scalability, and easy implementation (Yarali et al., 2020). PL is a non-thermal technology based on the accumulation of high discharge voltage in a capacitor where the stored electrical energy is delivered as intermittent short pulses through a light source filled with xenon gas. PL relies on a wide wavelength range from 200 to 1000 nm. This wide diversity of wavelengths gives a greater probability of interactions with molecules than UV lamps, which generally only irradiate at a few wavelengths, 254 nm (UV-C) and 365 nm (UV-A). In addition, the UV irradiance of PL lamps is about three orders of magnitude higher than mercury lamps (Schaefer et al., 2007). Furthermore, the presence of mercury in the UV-C continuous lamps adds an environmental concern about the production of this process. PL has demonstrated its ability to degrade various pollutants very rapidly. Indeed, the study of Fortunato (2021) showed a degradation above 90 % for 8 out of 11 micropollutants at initial concentrations of 500 µg/L after 20 ms, or approximately 10 J/cm², of exposure with a PL xenon lamp. Only three studies have focused on the degradation of pesticides by PL to our knowledge (Baranda et al., 2012; Baranda and Fundazuri, 2014; Baranda et al., 2017). Baranda and Fundazuri (2014) showed over 80 % degradation of pyrimiphos-methyl, phosmet, azinphos-ethyl, simazine, and atrazine in cocktail solutions at initial concentrations of 500 µg/L after only 15 pulses (10.5 J/cm²). However, chlorpyrifos-ethyl was only degraded to 60 % and parathion-methyl was almost unaffected by PL. These reported studies focused on the degradation of only 7 phytosanitary products and studied the formation of only 17 degradation products. Moreover, these experiments did not study toxicity through in

vivo bioassay. It is important to point out that, as with any technology, the degradation products generated may be more or less toxic than the parent pesticides. Some studies have shown that the use of advanced oxidation technologies such as ozonation can reduce the amount of pollutants released into the environment but neoformed compounds may be more toxic than their parent compounds. Indeed, Cruz-Alcalde et al. (2018) showed that the degradation of dichlorvos could be complete with ozonation, but on the other hand the toxicity of the treated water increased with treatment.

Therefore, the aim of this work was to investigate the PL technology as a new process for the photodegradation of pesticides and evaluate its potential for viticultural wastewater depollution. In this context, it is of prime importance to study the degradability of a large number of widely used pesticides and to have an overview of the photoproducts generated by PL treatments to ensure the safety of the process. Firstly, a qualitative analysis was performed, using HPLC-MS/MS in scan mode, to study the degradation of pesticides and the formation of photoproducts. Secondly, the PL parameters for the degradation of 20 pesticides and the formation of their photoproducts were examined using a LC-MS quantitative analysis method, in MRM (Multiple Reaction Monitoring) mode. The operating parameters, fluence and voltage, were optimized for each pesticide. Finally, the Microtox® assay was conducted on 18 pesticides individually or in cocktail solution, in order to compare the acute toxicity of PL-treated samples with untreated samples on the bioluminescent bacteria Aliivibrio fischeri.

## 2. Materials and methods

### 2.1. Chemicals

Ametoctradin, azoxystrobin, benalaxyl, boscalid, chlorantraniliprole, cyprodinil, difenoconazole, dimethomorph, fenbuconazole, fenhexamid, fludioxonil, iprovalicarb, kresoxim-methyl, manidipamid, metrafenone, pyraclostrobin, pyrimethanil, tebuconazole, tebufenozide, and tetraconazole as well as triphenylphosphate (TPP) used as internal standard (IS), were supplied by Sigma-Aldrich Chimie (St Quentin Fallavier, France). These 20 pesticides were chosen according to their relevance in viticulture. All chemical standards had a purity above 96.6 %. Stock solutions at concentrations between 300 mg/L and 1100 mg/L were prepared in acetonitrile (HPLC grade, VWR International SAS, Rosny-sous-Bois, France) for each single pesticide. Pyraclostrobin-d₆ (99.8 % isotopic purity), fenbuconazole-d₅ (98.8 % isotopic purity), difenoconazole-d₆ (99.4 % isotopic purity), metrafenone-d₉ (99.9 % isotopic purity) tebuconazole-d₆ (97.5 % isotopic purity) and tebufenozide-d₉ (98.9 % isotopic purity) used as IS were obtained from CLUZEAU INFO LABO (Sainte Foy la Grande, France).

Acetonitrile (ACN Optima® LC-MS grade, 100 %) used for chromatographic separation was supplied by Fisher chemical (Illkirch, France). Ultrapure water was obtained with a Milli-Q Reference system (Merck Millipore, Fontenay-sous-Bois, France). The mobile phases used for HPLC separation were acidified with 0.1 % of formic acid (CAS RN: [64-18-6], high purity grade, 100 %, from Amresco Inc., Solon, Ohio, USA).

### 2.2. Pulsed light instrumentation

An LPBox (Sanodev, Limoges, France) was used for pulsed light treatments (Fig. 1). The light pulses were produced by storing electric energy in a capacitor. This energy was then quickly transmitted to a xenon lamp, which allows the emission of pulses. The operating conditions of the LPBox were 4 kV and 3 Hz for the qualitative analysis and between 2 and 4 kV for the optimization step. The principle of pulsed light is based on the emission of polychromatic light covering a wide emission spectrum; the LP spectrum ranges from 200 to 1000 nm. The LPBox spectra are as follows for 2, 3, and 4 kV respectively: UV-C 0.27 %, UV-B 2.49 %, and UV-A 13.15 %; UV-C 1.6 %, UV-B 4.3 %, and UV-A 0.2 %.
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<figure><img src="image_4.png" /><figcaption>Fig. 1. (a) Pulsed light system (LPBox). Lamp at the top, Petri dish at the bottom, delimited area in white. (b) Emission spectrum of LPBox at 2, 3 and 4 kV.</figcaption></figure>

16.3%; UV-C 3.2%, UV-B 6.2%, and UV-A 19% (Fig. 1b). These spectra were measured in the delimited area at 32 cm from the lamp (Fig. 1a) with a spectrometer Ardop Qwave (Pessac, France). The LPBox fluences per flash are 0.01373 J/cm², 0.0316 J/cm², and 0.05723 J/cm² for 2 kV, 3 kV, and 4 kV, respectively, in the delimited area. These fluences were measured with a captor and a monitor from Thorlabs Inc. (Newton, USA). The total fluence (H) was determined by the number of flashes multiplied by the fluence per flash at a given voltage for each sample. The maximum temperature of the sample after a PL treatment was 42 °C for the highest voltage and fluence.

## 2.3. LC-MS analysis

A high-performance liquid chromatograph coupled to a tandem mass spectrometer (HPLC-MS/MS) was used to determine the impact of PL on non-volatile pesticides (HPLC 1260 Infinity coupled to a triple quadrupole 6430 from Agilent Technologies, Massy, France).

The LC consists of a 1260 binary pump, a 1260 high performance degasser, a 1260 autosampler, and a 1290 thermostatted column compartment which was set at 40 °C. The mass spectrometer was equipped with an electrospray ionisation (ESI) source. Nitrogen was produced by a generator NiGen LCMS 40–1 from Gengaz (Wasquehal, France) and used as drying, nebulising, and collision gas. The ESI interface operated simultaneously in positive and negative mode with the capillary voltage set at 3000 V, the nebuliser pressure at 40 psi, the drying gas flow at 11 L/min and the gas temperature at 350 °C. The system operates with the MassHunter Workstation software version B.05.00.

The separation was carried out in reverse phase with a mobile phase system comprising water (A) and acetonitrile (B), each containing 0.1 % formic acid. The gradient was programmed as follows:

0–15 min, 95–0 % A; 15–25 min, 0–0 % A; 25–28 min, 0–95 % A and held for 6 min for column equilibration before the next injection for a run duration of 34 min. Separation was performed on a Poroshell 120 CS-C18 column (2.1 × 150 mm, I.D. × length; 2.7 µm particle size). Electrospray ionization was performed in positive mode (ESI⁺) for all pesticides except fludioxonil, which was analyzed in negative mode (ESI⁻).

### 2.3.1. Qualitative analysis

Untargeted analyses were performed in scan mode on aqueous solutions of single pesticide at approximately 10 mg/L progressively treated by PL in order to observe photoproducts with the following conditions: m/z: 50 to 2000; scan time: 200 ms; fragmentor voltage: 135 V; cell accelerator voltage: 5 V. Only the most abundant peaks were considered as photoproducts.

### 2.3.2. Quantitative analysis

A quantification method was developed using the same chromatographic conditions as for the untargeted analysis but in MRM mode (Multiple Reaction Monitoring). Fragmentation experiments were performed with a fragmentor voltage set at 135 V, a cell accelerator voltage at 5 V, and a collision energy ranging from 5 to 50 eV for each compound. A minimum of two transitions were determined per compound in order to create an absolute quantification method for the 20 pesticides and the internal standards (IS) totalising 64 MRM transitions. A calibration was performed by injecting a dilution range from 1 to 300 µg/L in duplicate. The limits of quantification (LOQs) and detection (LODs) (Table 3) were determined by the regression line method, with five injections of the five lowest concentration levels of the calibration. The determination was carried out using the ratio compound response/internal standard response as Y axis and expected concentration as X axis with following formulas:

$$ LOD = \frac{10*\sigma b}{a} \quad LOD = \frac{3*\sigma b}{a} $$

with a: slope of the calibration line and σb: standard deviation of the intercept.

A relative quantification method was developed for the 74 photoproducts as no commercial standard was available. The photoproducts were monitored with 176 transitions, which were optimized in the same way as explained above. MRM transitions are reported in table S1, quantitative transition appears in first position. Samples were filtered on 0.2 µm PTFE membrane and 1 mL of the filtered sample was precisely withdrawn and transferred to an HPLC vial. Ten µL of IS solution was added and the vial was vortexed before LC injection (10 µL).

## 2.4. Acute toxicity bioassay

The marine bioluminescent bacterium, *Aliivibrio fisheri*, was used as the reference organism for the Microtox® assays. The Microtox® Acute Toxicity Test Reagent was purchased from Modern Water Inc. (New Castle, Delaware, United States). Microtox testing was performed according to the NF EF ISO 11348–3 guidelines (ISO, D. 11348–3 2007). The Microtox reagents were stored at –24 °C. The analyses were executed after rehydration of lyophilized bacteria with 1 mL of osmotic water at 5 °C in test cuvettes for luminescence measurements. The positive control solutions consisted of a saline solution (2 %) supplemented with K₂Cr₂O₇ at 0.2 g/L (25, 50, 100, and 200 mg/L). Bacteria have been exposed for 30 min at 15 °C to the different test solutions. Bioluminescence of the bacterial culture was measured at 5 °C using the luminometer M500 Toxicity Analyzer (Modern Water). The pH of each sample was set to be between 6 and 8.5. Each analysis was performed in
triplicates within 2 h maximum after rehydration and following the protocol of Gómez et al. (2023), in order to obtain robust results.

## 2.5. Sample preparation

The PL treatments were performed on water samples spiked with pesticides. For each treatment, 10 mL of an aqueous solution of pesticides was placed in a glass Petri dish in the centre of the delimited area. Any evaporation caused by the highest PL treatments was compensated for by adding Milli-Q water, with a maximum of 12% of evaporation for the most treated sample.

### 2.5.1. Samples for the untargeted analysis

Each pesticide was diluted in an aqueous solution at a concentration of approximately 10 mg/L from stock solutions. Such a high concentration was chosen to ensure the observation of sufficient abundances for the degradation product signals. PL treatments were increased as follows: 11.4, 22.8, 45.7, and 91.5 J/cm² at 4 kV and 3 Hz. These experiments were carried out in triplicates on each single pesticide solution.

### 2.5.2. Samples for the optimization of voltage and fluence parameters

A cocktail solution of the 20 selected pesticides was prepared in an aqueous solution at concentrations between 296 and 654 µg/L from stock solutions. Increasing PL treatments were applied (11.4, 22.8, 45.7, and 91.5 J/cm²) at 2, 3, and 4 kV at 3 Hz. These experiments were carried out in triplicates on the cocktail mix.

### 2.5.3. Samples for acute toxicity bioassay

In order to respect the maximum ACN percentage (0.01 %) in the samples for acute toxicity bioassays, concentrated solutions (3 g/L in ACN) were prepared for each one of the 18 pesticides studied (azoxystrobin, benalaxyl, boscalid, cyprodinil, difenoconazole, dimethomorph, fenbuconazole, fenhexamid, fludioxonil, iprovalicarb, kresoxim-methyl, mandipropamid, metrafenone, pyraclostrobin, pyrimethanil, tebuconazole, tebufenozide, and tetraconazole). This ACN percentage was previously determined to have an inhibition percentage below 15% on A. fischeri.

For the acute toxicity tests on single pesticides, the 18 concentrated solutions were then diluted to obtain aqueous solutions ranging from 66 to 345 µg/L. A PL treatment at the highest voltage (4 kV) and fluence (91 J/cm²) was applied on each solution as an optimized modality for the treated samples. Due to their very low solubility in water, ametoctradin and chlorantraniliprole were excluded from these experiments.

A concentrated cocktail solution of these 18 pesticides (3 g/L), was also prepared in ACN, and further diluted with milli-Q water to obtain an aqueous solution of pesticides with concentrations ranging from 216 to 406 µg/L. Increasing PL treatments at 11.4, 22.8, 45.7, and 91.5 J/cm² with the highest voltage (4 kV) were applied on this cocktail solution of pesticides.

The acute toxicity of each sample was evaluated after the serial half dilutions of each sample with a 2 % (w/v) sodium chloride aqueous solution to avoid osmotic shock for the bacteria.

Each PL experiment was performed in triplicate. For each acute toxicity analysis, the toxicity was corrected with a negative control made of the corresponding PL-treated 0.01 % ACN solution.

## 2.6. Data analysis

Data collected from the process optimization experiments and acute toxicity bioassays on the cocktail solution were initially checked for normality (Shapiro-Wilk test, *p* > 0.05), and homogeneity of variances (Levene test, *p* > 0.05). If a bimodal repartition of data was observed, the homogeneity of variances and normality were visually checked. Then, an analysis of variance (ANOVA) (*p* < 0.05) followed by the post hoc Tukey test was performed to determine any differences between the treatments.

The evolution of the photoproducts over treatments (Fig. 3 and 8) was studied using k-means clustering (R package ClassDiscovery). This method allows partitioning the kinetic profiles into *k* clusters, where each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid). The number of optimal clusters was assessed visually.

Data on all bioassays of single pesticide solutions were analyzed by *t*-test, with the *p*-value of each sample described as different being lower than 0.05.

Finally, the multivariate analysis (Heatmap) was performed at R studio using the "ggplot2" and "corrplot" packages (Fig. 10).

# 3. Results and discussion

## 3.1. Search for photodegradation products

With the aim of evaluating PL for pesticide degradation, 20 pesticide active substances belonging to 14 families were specifically selected among those commonly used in viticulture and often quantified in wines. Photodegradation of active substances upon increasing fluences was monitored by HPLC-MS/MS in scan mode for each single pesticide in aqueous solution.

For the majority of the active substances studied, a decrease in the peak area of the parent compound was observed concomitantly with the appearance of new peaks, showing that PL was able to degrade pesticides and to form photoproducts which is in accordance with (Baranda and Fundazuri, 2014). Generally, as fluence increases, parent compounds decrease while photoproducts are progressively formed and some degrade in turn with the highest fluences. For the specific cases of dimethomorph, fludioxonil, ametoctradin, and tebufenozide, a decrease of their peak area was also observed, but no new peak appeared in the chromatogram of the treated samples. This implies that no degradation products were observed for these 4 active substances.

In the end, 74 photoproducts were considered, and 47 structural hypotheses could be proposed using the mass-to-charge ratio (m/z) of the molecules, the isotopic pattern of the halogenated compounds, as well as observations from the literature (Table 1). Fragments produced during MS/MS experiments were also used to help establish structural hypotheses.

For example, pulsed-light exposure of an aqueous solution of fenhexamid (m/z 302) (Table 1) generates an ion of m/z 266 i.e. a loss of 36 u, which could be explained by the loss of a chlorine and a hydrogen atom. This hypothesis is supported by the isotopic pattern of the transformation product (TP), which corresponds to the presence of a single chlorine in the molecule, whereas fenhexamid contains two. Moreover, a photodegradation compound of fenhexamid with m/z 266 was already described in the literature (Maheswari et al., 2010).

Some compounds gave rise to several TPs with same m/z and isotopic pattern. They are shown in the same merged cell in Table 1, as they could not be precisely assigned. Proposed structures not referenced in literature are mentioned as "never described".

For the specific case of the halogenated compounds, the main TPs observed come from pathways implying halogen loss and hydroxylation, with 39 probable dehalogenations and 31 hydroxylations. In general, the mass of the compound decreases as the PL treatments increase, suggesting that PL progressively mineralizes the treated compound.

An analytical method for relative quantification of 74 transformation products and absolute quantification of their 20 parent active substances was created to measure the evolution of each compound during PL treatments. The different compounds observed, and their MS fragmentation ions used for the relative quantification method, are listed in Table 1 and Table S1 respectively.
<table><caption>**Table 1**

Transformation products and parent active substances quantified by the MRM method.</caption><thead><tr><th>Compound</th><th>m/z</th><th>Structure</th><th>Formula</th><th>References</th></tr></thead><tbody><tr><td>Ametoctradin</td><td>276</td><td></td><td>C<sub>15</sub>H<sub>25</sub>N<sub>5</sub></td><td></td></tr><tr><td>Axoxystrobin</td><td>404</td><td></td><td>C<sub>22</sub>H<sub>17</sub>N<sub>3</sub>O<sub>5</sub></td><td></td></tr><tr><td>TP azo-404-1</td><td>404</td><td></td><td>C<sub>22</sub>H<sub>17</sub>N<sub>3</sub>O<sub>5</sub></td><td>(Chastain et al., 2013)</td></tr><tr><td>TP azo-404-2</td><td>404</td><td></td><td>C<sub>22</sub>H<sub>17</sub>N<sub>3</sub>O<sub>5</sub></td><td></td></tr><tr><td>TP azo-404-3</td><td>404</td><td></td><td>C<sub>22</sub>H<sub>17</sub>N<sub>3</sub>O<sub>5</sub></td><td></td></tr><tr><td>TP azo-404-4</td><td>404</td><td></td><td>C<sub>22</sub>H<sub>17</sub>N<sub>3</sub>O<sub>5</sub></td><td></td></tr><tr><td>TP azo-404-5</td><td>404</td><td></td><td>C<sub>22</sub>H<sub>17</sub>N<sub>3</sub>O<sub>5</sub></td><td></td></tr><tr><td>TP azo-404-6</td><td>372</td><td></td><td>C<sub>22</sub>H<sub>17</sub>N<sub>3</sub>O<sub>5</sub></td><td></td></tr><tr><td>Benalaxyl</td><td>326</td><td></td><td>C<sub>20</sub>H<sub>23</sub>NO<sub>3</sub></td><td></td></tr><tr><td>TP ben-121</td><td>121</td><td></td><td>C<sub>8</sub>H<sub>8</sub>O</td><td>Never described</td></tr><tr><td>TP ben-208</td><td>208</td><td></td><td>C<sub>12</sub>H<sub>17</sub>NO<sub>2</sub></td><td>(Pirisi et al., 1996)</td></tr><tr><td>TP ben-240</td><td>240</td><td></td><td>C<sub>16</sub>H<sub>17</sub>NO</td><td>Never described</td></tr><tr><td>TP ben-326</td><td>326</td><td></td><td>C<sub>20</sub>H<sub>23</sub>NO<sub>3</sub></td><td></td></tr><tr><td>TP ben-342</td><td>342</td><td></td><td>C<sub>20</sub>H<sub>23</sub>NO<sub>4</sub></td><td>(Wang et al., 2016)</td></tr><tr><td>Boscalid</td><td>343</td><td></td><td>C<sub>18</sub>H<sub>12</sub>Cl<sub>2</sub>N<sub>2</sub>O</td><td></td></tr><tr><td>TP bosca-325-1</td><td>325</td><td></td><td>C<sub>18</sub>H<sub>13</sub>ClN<sub>2</sub>O<sub>2</sub></td><td>(Lassalle et al., 2014, Skanes et al., 2021)</td></tr><tr><td>TP bosca-325-2</td><td>325</td><td></td><td>C<sub>18</sub>H<sub>13</sub>ClN<sub>2</sub>O<sub>2</sub></td><td></td></tr></tbody></table>

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<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Compound</th><th>m/z</th><th>Structure</th><th>Formula</th><th>References</th></tr></thead><tbody><tr><td>Chloranthraniprole</td><td>484</td><td></td><td>C<sub>18</sub>H<sub>14</sub>BrCl<sub>2</sub>N<sub>5</sub>O<sub>2</sub></td><td></td></tr><tr><td>TP chlor-368-1</td><td>368</td><td></td><td></td><td></td></tr><tr><td>TP chlo-368-2</td><td>368</td><td></td><td>C<sub>18</sub>H<sub>14</sub>ClN<sub>5</sub>O<sub>2</sub></td><td>Never described</td></tr><tr><td>TP chlo-446-1</td><td>446</td><td></td><td></td><td></td></tr><tr><td>TP chlo-446-2</td><td>446</td><td></td><td>C<sub>18</sub>H<sub>13</sub>BrClN<sub>5</sub>O<sub>2</sub></td><td>(Sharma et al., 2014)</td></tr><tr><td>Cyprodinil</td><td>226</td><td></td><td>C<sub>14</sub>H<sub>15</sub>N<sub>3</sub></td><td></td></tr><tr><td>TP cypro-226-1</td><td>226</td><td></td><td></td><td></td></tr><tr><td>TP cypro-226-2</td><td>226</td><td></td><td>C<sub>14</sub>H<sub>15</sub>N<sub>3</sub></td><td>(Chen et al., 2016)</td></tr><tr><td>TP cypro-226-3</td><td>226</td><td></td><td></td><td></td></tr><tr><td>TP cypro-242</td><td>242</td><td></td><td>C<sub>14</sub>H<sub>15</sub>N<sub>3</sub>O</td><td>(Schocken et al., 1997)</td></tr><tr><td>Difenoconazole</td><td>406</td><td></td><td>C<sub>19</sub>H<sub>17</sub>Cl<sub>2</sub>N<sub>3</sub>O<sub>3</sub></td><td></td></tr><tr><td>TP difeno-296</td><td>296</td><td></td><td></td><td></td></tr><tr><td>TP dife-350</td><td>350</td><td></td><td>C<sub>19</sub>H<sub>15</sub>N<sub>3</sub>O<sub>4</sub></td><td>(Man et al., 2021)</td></tr><tr><td>TP dife-352-1</td><td>352</td><td></td><td></td><td></td></tr><tr><td>TP dife-352-2</td><td>352</td><td></td><td>C<sub>19</sub>H<sub>17</sub>N<sub>3</sub>O<sub>4</sub></td><td>(Man et al., 2021)</td></tr><tr><td>TP dife-370-1</td><td>370</td><td></td><td>C<sub>19</sub>H<sub>19</sub>N<sub>3</sub>O<sub>5</sub></td><td>(Man et al., 2021)</td></tr></tbody></table>

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<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Compound</th><th>m/z</th><th>Structure</th><th>Formula</th><th>References</th></tr></thead><tbody><tr><td>TP dife-370-2</td><td>370</td><td></td><td>C<sub>19</sub>H<sub>16</sub>ClN<sub>3</sub>O<sub>3</sub></td><td>(Man et al., 2021)</td></tr><tr><td>TP dife-388-1</td><td>388</td><td></td><td>C<sub>19</sub>H<sub>18</sub>ClN<sub>3</sub>O<sub>4</sub></td><td>(Man et al., 2021)</td></tr><tr><td>TP dife-388-2</td><td>388</td><td></td><td></td><td></td></tr><tr><td>Dimethomorph</td><td>388</td><td></td><td>C<sub>21</sub>H<sub>22</sub>ClNO<sub>4</sub></td><td></td></tr><tr><td>Fenbuconazole</td><td>337</td><td></td><td>C<sub>19</sub>H<sub>17</sub>ClN<sub>4</sub></td><td></td></tr><tr><td>TP fenbu-303</td><td>303</td><td></td><td>C<sub>19</sub>H<sub>18</sub>N<sub>4</sub></td><td>Never described</td></tr><tr><td>TP fenbu-319-1</td><td>319</td><td></td><td></td><td></td></tr><tr><td>TP fenbu-319-2</td><td>319</td><td></td><td>C<sub>19</sub>H<sub>18</sub>N<sub>4</sub>O</td><td>(Skanes et al., 2021)</td></tr><tr><td>TP fenbu-337-1</td><td>337</td><td></td><td></td><td></td></tr><tr><td>TP fenbu-337-2</td><td>337</td><td></td><td>C<sub>19</sub>H<sub>17</sub>ClN<sub>4</sub></td><td>(Skanes et al., 2021)</td></tr><tr><td>TP fenbu-351</td><td>351</td><td></td><td>C<sub>19</sub>H<sub>15</sub>ClN<sub>4</sub>O</td><td>(Skanes et al., 2021)</td></tr><tr><td>Fenhexamid</td><td>302</td><td></td><td>C<sub>14</sub>H<sub>17</sub>Cl<sub>2</sub>NO<sub>2</sub></td><td></td></tr></tbody></table>

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<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Compound</th><th>m/z</th><th>Structure</th><th>Formula</th><th>References</th></tr></thead><tbody><tr><td>TP fenhex-142</td><td>142</td><td></td><td>C<sub>8</sub>H<sub>15</sub>NO</td><td>(Maheswari et al., 2010)</td></tr><tr><td>TP fenhex-232</td><td>232</td><td></td><td>C<sub>14</sub>H<sub>17</sub>NO<sub>2</sub></td><td>(Maheswari et al., 2010)</td></tr><tr><td>TP fenhex-266</td><td>266</td><td></td><td>C<sub>14</sub>H<sub>16</sub>ClNO<sub>2</sub></td><td>(Maheswari et al., 2010)</td></tr><tr><td>TP fenhex-268</td><td>268</td><td></td><td>C<sub>14</sub>H<sub>18</sub>ClNO<sub>2</sub></td><td>(Maheswari et al., 2010)</td></tr><tr><td>Fludioxonil</td><td>247</td><td></td><td>C<sub>12</sub>H<sub>6</sub>F<sub>2</sub>N<sub>2</sub>O<sub>2</sub></td><td></td></tr><tr><td>Iprovalicarb</td><td>321</td><td></td><td>C<sub>18</sub>H<sub>28</sub>N<sub>2</sub>O<sub>3</sub></td><td></td></tr><tr><td>TP ipro-335</td><td>335</td><td></td><td>C<sub>18</sub>H<sub>26</sub>N<sub>2</sub>O<sub>4</sub></td><td>Never described</td></tr><tr><td>TP ipro-337-1</td><td>337</td><td></td><td>C<sub>18</sub>H<sub>28</sub>N<sub>2</sub>O<sub>4</sub></td><td>Never described</td></tr><tr><td>TP ipro-337-2</td><td>337</td><td></td><td>C<sub>18</sub>H<sub>28</sub>N<sub>2</sub>O<sub>4</sub></td><td>Never described</td></tr><tr><td>Kresoxim-Me</td><td>314</td><td></td><td>C<sub>18</sub>H<sub>19</sub>NO<sub>4</sub></td><td></td></tr><tr><td>TP kre-282-1</td><td>282</td><td></td><td>C<sub>23</sub>H<sub>22</sub>ClNO<sub>4</sub></td><td></td></tr><tr><td>TP kre-282-2</td><td>282</td><td></td><td>C<sub>23</sub>H<sub>22</sub>ClNO<sub>4</sub></td><td></td></tr><tr><td>TP kre-282-3</td><td>282</td><td></td><td>C<sub>23</sub>H<sub>22</sub>ClNO<sub>4</sub></td><td></td></tr><tr><td>TP kre-282-4</td><td>282</td><td></td><td>C<sub>23</sub>H<sub>22</sub>ClNO<sub>4</sub></td><td></td></tr><tr><td>TP kre-298</td><td>298</td><td></td><td>C<sub>23</sub>H<sub>22</sub>ClNO<sub>4</sub></td><td></td></tr><tr><td>Mandipropamide</td><td>412</td><td></td><td>C<sub>23</sub>H<sub>22</sub>ClNO<sub>4</sub></td><td></td></tr><tr><td>TP man-394-1</td><td>394</td><td></td><td>C<sub>23</sub>H<sub>23</sub>NO<sub>5</sub></td><td>Never described</td></tr><tr><td>TP man-394-2</td><td>394</td><td></td><td>C<sub>23</sub>H<sub>23</sub>NO<sub>5</sub></td><td>Never described</td></tr></tbody></table>

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<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Compound</th><th>m/z</th><th>Structure</th><th>Formula</th><th>References</th></tr></thead><tbody><tr><td>TP man-356</td><td>356</td><td></td><td>C<sub>20</sub>H<sub>21</sub>NO<sub>5</sub></td><td>Never described</td></tr><tr><td>Metrafenone</td><td>409</td><td></td><td>C<sub>19</sub>H<sub>21</sub>BrO<sub>5</sub></td><td></td></tr><tr><td>TP metra-331</td><td>331</td><td></td><td>C<sub>19</sub>H<sub>22</sub>O<sub>5</sub></td><td>(Hong et al., 2021)</td></tr><tr><td>TP metra-345</td><td>345</td><td></td><td>C<sub>19</sub>H<sub>20</sub>O<sub>6</sub></td><td>(Hong et al., 2021)</td></tr><tr><td>TP metra-347</td><td>347</td><td></td><td>C<sub>19</sub>H<sub>22</sub>O<sub>6</sub></td><td>(Hong et al., 2021)</td></tr><tr><td>Pyraclostrobine</td><td>388</td><td></td><td>C<sub>19</sub>H<sub>18</sub>ClN<sub>3</sub>O<sub>4</sub></td><td></td></tr><tr><td>TP pyra-132-1</td><td>132</td><td></td><td></td><td></td></tr><tr><td>TP pyra-132-2</td><td>132</td><td></td><td></td><td></td></tr><tr><td>TP pyra-177</td><td>177</td><td></td><td></td><td></td></tr><tr><td>TP pyra-216</td><td>216</td><td></td><td></td><td></td></tr><tr><td>TP pyra-340-1</td><td>340</td><td></td><td>C<sub>18</sub>H<sub>17</sub>N<sub>3</sub>O<sub>4</sub></td><td>(Zeng et al., 2019)</td></tr><tr><td>TP pyra-340-2</td><td>340</td><td></td><td></td><td></td></tr><tr><td>TP pyra-358</td><td>358</td><td></td><td>C<sub>18</sub>H<sub>16</sub>ClN<sub>3</sub>O<sub>3</sub></td><td>(Skanes et al., 2021)</td></tr><tr><td>Pyrimethanil</td><td>200</td><td></td><td>C<sub>12</sub>H<sub>13</sub>N<sub>3</sub></td><td></td></tr></tbody></table>

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<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Compound</th><th>m/z</th><th>Structure</th><th>Formula</th><th>References</th></tr></thead><tbody><tr><td>TP pyri-124</td><td>124</td><td></td><td>C<sub>6</sub>H<sub>9</sub>N<sub>3</sub></td><td>(Marín-Benito et al., 2012)</td></tr><tr><td>TP pyri-178</td><td>178</td><td></td><td></td><td></td></tr><tr><td>TP pyri-216-1</td><td>216</td><td></td><td></td><td></td></tr><tr><td>TP pyri-216-2</td><td>216</td><td></td><td></td><td></td></tr><tr><td>Tebuconazole</td><td>308</td><td></td><td>C<sub>12</sub>H<sub>13</sub>N<sub>3</sub>O</td><td>(Castro et al., 2020)</td></tr><tr><td>TP tebuc-250</td><td>250</td><td></td><td>C<sub>16</sub>H<sub>22</sub>ClN<sub>3</sub>O</td><td>(Del Puerto et al., 2022)</td></tr><tr><td>TP tebuc-272</td><td>272</td><td></td><td>C<sub>12</sub>H<sub>12</sub>ClN<sub>3</sub>O</td><td>(Del Puerto et al., 2022)</td></tr><tr><td>TP tebuc-290-1</td><td>290</td><td></td><td></td><td></td></tr><tr><td>TP tebuc-290-2</td><td>290</td><td></td><td></td><td></td></tr><tr><td>TP tebuc-290-3</td><td>290</td><td></td><td></td><td></td></tr><tr><td>Tebufenozide</td><td>353</td><td></td><td>C<sub>16</sub>H<sub>23</sub>N<sub>3</sub>O<sub>2</sub></td><td>Never described</td></tr><tr><td>Tetraconazole</td><td>372</td><td></td><td>C<sub>22</sub>H<sub>28</sub>N<sub>2</sub>O<sub>2</sub></td><td></td></tr><tr><td>TP tetra-334</td><td>334</td><td></td><td>C<sub>13</sub>H<sub>11</sub>Cl<sub>2</sub>F<sub>4</sub>N<sub>3</sub>O</td><td>Never described</td></tr></tbody></table>

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<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Compound</th><th>m/z</th><th>Structure</th><th>Formula</th><th>References</th></tr></thead><tbody><tr><td>TP tetra-336-1</td><td>336</td><td></td><td>C<sub>13</sub>H<sub>13</sub>F<sub>4</sub>N<sub>3</sub>O<sub>3</sub></td><td>Never described</td></tr><tr><td>TP tetra-336-2</td><td>336</td><td></td><td>C<sub>13</sub>H<sub>10</sub>ClF<sub>4</sub>N<sub>3</sub>O</td><td>Never described</td></tr><tr><td>TP tetra-354-1</td><td>354</td><td></td><td>C<sub>13</sub>H<sub>12</sub>ClF<sub>4</sub>N<sub>3</sub>O<sub>2</sub></td><td>Never described</td></tr><tr><td>TP tetra-354-2</td><td>354</td><td></td><td></td><td></td></tr></tbody></table>

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Never described means that the proposed photoproduct has never been described in the literature.

## 3.2. Optimization of degradation operating parameters

### 3.2.1. Impact of PL parameters on pesticide concentrations

The degradation was evaluated by subjecting a cocktail solution of the 20 active substances, each compound at a concentration between 296 and 654 µg/L, to three different voltages (2, 3, and 4 kV) with increasing total fluences (Fig. 2, Table S2). All experiments showed statistical differences (ANOVA *p-value* < 0.01) for the variable voltage and fluence for the 20 pesticides in cocktail solutions.

The degradation curves show a significant concentration decrease for all compounds whatever the voltage, except for pyrimethanil at a voltage of 2 kV. This is probably due to the emission spectrum of the lamp at this voltage, that may not include wavelengths with sufficient energy for its degradation (0.27 % of UV-C at 2 kV), contrary to the two other voltages (1.6 % of UV-C at 3 kV and 3.2 % at 4 kV). This efficient degradation for all the compounds demonstrates that the wide variety of wavelengths (between 200 nm and 1000 nm) emitted by PL can interact with all compounds studied, proving the efficiency of PL in degrading compounds. However, differences in efficiency are significant between voltages. Indeed, for the highest fluence, at 2 kV, 10 compounds remained at concentrations higher than 10 % of their initial concentration, and 4 of them remained at concentrations higher than 50 %. At 3 kV, 6 compounds remained at concentrations higher than 10 %, and two compounds remained at concentrations higher than 50 %, while at 4 kV, only two compounds remained at concentrations higher than 10 %, and none remained at concentrations higher than 37 %.

For all compounds and all voltages tested, the degradation also increased with the total fluence (H), following a first-order kinetic. Previous studies reported zero-order and first-order kinetics (Baranda and Fundazuri, 2014). The zero-order kinetic observed could be explained by the maximum fluence applied (11 J/cm²), which is a very low fluence unable to process the degradation of all compounds and thus to determine the right kinetic order. Indeed, if experiments are carried out only at low fluences, only very slight decreases in concentrations are observed for less sensitive compounds. In this case the measurements may fall in the linear part of the curve. Such a decrease would lead to the assumption that degradation follows zero order kinetics corresponding to decreasing affine functions. This could correspond to a zoom effect

that could distort the determination of the reaction order. For first-order kinetics, the degradation rate constant (k) is determined by plotting the logarithm of the ratio of the initial concentration (C₀) to the concentration at a given fluence (C₉) against the total fluence (H), according to the equation:

$$ \ln(C_0 / C_9) = kH $$

Subsequently, the half fluence (H₁/₂), representing the total fluence required for a 50 % concentration reduction of a compound, could be calculated using the equation:

$$ H_{1/2} = Ln 2/k $$

The kinetics parameters k and H₁/₂ are listed in Table 2 for the 3 different voltages and the 20 pesticides.

According to the curves in Fig. 2, the evolution of k in Table 2 follows a progressive increase, whereas H₁/₂ decreases as the voltage increases for all compounds studied, except for ametoctradin and mandipropamid. For mandipropamid, this can be explained by the high sensitivity to PL of the compound. Indeed, mandipropamid was degraded by >99 % at the first fluence tested. In the specific case of ametoctradin, k and H₁/₂ were unaffected by the rise of PL parameters, likely because this compound is sensitive at wavelengths produced by the lamp whatever voltage applied. The rise of the degradation efficiency, which correlates to an increase in the voltage, suggests that the degradation rate is linked with UV radiation for the other compounds. Indeed, the UV part of the spectrum emitted by PL extends as the voltage increases.

Important differences related to the sensitivity to PL were also observed between pesticide active substances. These differences are strictly dependent on the total fluence (H) and their degradation rate constant (k). The classification of compounds from the most sensitive to the least sensitive is as follows: pyraclostrobin, mandipropamid, chlorantraniliprole, difenoconazole, tetraconazole, kresoxim-Me, azoxystrobin, fludioxonil, fenhexamid, metrafenone, benalaxyl, cyprodinil, ametoctradin, iprovalicarb, tebufenozide, pyrimethanil, boscalid, and dimethomorph. Regarding these different compounds, certain families of compounds appear to be generally more sensitive than others, such as strobilurines (azoxystrobin, kresoxim-Me, and pyraclostrobin), which
<figure><img src="image_57.png" /><figcaption>Fig. 2. Degradation curves for 20 pesticides during PL treatment at 2 kV (a), 3 kV (b) and 4 kV (c).</figcaption></figure>

contain compounds with H₁/₂ lower than 2.8 J/cm² at 4 kV. Triazoles (difenoconazole, fenbuconazole, tebuconazole and tetraconazole) also show an important sensitivity with H₁/₂ lower than 7.1 J/cm². On contrary triazolopyrimidines (ametocradin), anilinopyrimidines (cyprodinil, pyrimethanil), carbamates (iprovalicarb), carbohydrazides (tebufenozide), pyridylanilides (boscalid) and cinnamic acid derriva- tives (dimethomorph) are much less sensitive. This is likely due to the high number of conjugated bonds and aromatic rings present in these

molecules which are able to stabilise them. The stability of aromatic cycles in the context of photolysis is well established. Indeed, Zuo et al. (2006) described benzene and toluene as the most difficult compounds to degrade among 5 volatile compounds tested in photocatalysis ex- periments with TiO₂. This assumption is supported by the fact that boscalid, classified as an anilide, is less affected than the other anilides (benalaxyl, fenhexamid) probably because of the direct linkage of the carbonyl group to an aromatic ring. It is also important to note that
<table><caption>**Table 2**
Degradation parameters (rate constant k, half fluence H<sub>1/2</sub>) and pesticide class for the 20 active substances studied.</caption><thead><tr><th rowspan="2">Compound</th><th colspan="2">4kv</th><th colspan="2">3kv</th><th colspan="2">2kv</th><th rowspan="2">Substance family</th></tr><tr><th>k</th><th>H<sub>1/2</sub></th><th>k</th><th>H<sub>1/2</sub></th><th>k</th><th>H<sub>1/2</sub></th></tr></thead><tbody><tr><td>Ametoctradin</td><td>0.042</td><td>16.4</td><td>0.041</td><td>16.9</td><td>0.042</td><td>16.3</td><td>Triazolopyrimidine</td></tr><tr><td>Azoxystrobin</td><td>0.243</td><td>2.8</td><td>0.189</td><td>3.7</td><td>0.125</td><td>5.5</td><td>Strobilurin</td></tr><tr><td>Benalaxyl</td><td>0.076</td><td>9.0</td><td>0.048</td><td>14.5</td><td>0.019</td><td>36.6</td><td>Benzylanilide</td></tr><tr><td>Boscalid</td><td>0.015</td><td>45.9</td><td>0.008</td><td>81.7</td><td>0.004</td><td>169.2</td><td>Pyridylanilide</td></tr><tr><td>Chlorantraniliprole</td><td>0.519</td><td>1.3</td><td>0.485</td><td>1.4</td><td>0.260</td><td>2.7</td><td>Pyridylpyrazolylanilide</td></tr><tr><td>Cyprodinil</td><td>0.043</td><td>15.9</td><td>0.021</td><td>33.3</td><td>0.008</td><td>84.2</td><td>Anilinopyrimidine</td></tr><tr><td>Difenoconazole</td><td>0.331</td><td>2.1</td><td>0.257</td><td>2.7</td><td>0.141</td><td>4.9</td><td>Triazole</td></tr><tr><td>Dimethomorph</td><td>0.010</td><td>63.2</td><td>0.007</td><td>104.8</td><td>0.005</td><td>134.6</td><td>Cinnamic acid amide</td></tr><tr><td>Fenbuconazole</td><td>0.097</td><td>7.1</td><td>0.070</td><td>9.9</td><td>0.029</td><td>24.1</td><td>Triazole</td></tr><tr><td>Fenhexamid</td><td>0.123</td><td>5.6</td><td>0.086</td><td>8.1</td><td>0.035</td><td>19.5</td><td>Cyclohexylanilide</td></tr><tr><td>Fludioxonil</td><td>0.191</td><td>3.6</td><td>0.128</td><td>5.4</td><td>0.062</td><td>11.2</td><td>Phenylpyrrole</td></tr><tr><td>Iprovalicarb</td><td>0.022</td><td>30.8</td><td>0.012</td><td>55.3</td><td>0.005</td><td>135.1</td><td>Carbamate</td></tr><tr><td>Kresoxim-Me</td><td>0.270</td><td>2.6</td><td>0.190</td><td>3.6</td><td>0.088</td><td>7.9</td><td>Strobilurin</td></tr><tr><td>Mandipropamid</td><td>0.616</td><td>1.1</td><td>0.645</td><td>1.1</td><td>0.392</td><td>1.8</td><td>Mandelamide</td></tr><tr><td>Metrafenone</td><td>0.083</td><td>8.3</td><td>0.071</td><td>9.8</td><td>0.034</td><td>19.9</td><td>Benzophenone</td></tr><tr><td>Pyraclostrobin</td><td>1.355</td><td>0.5</td><td>0.570</td><td>1.2</td><td>0.539</td><td>1.3</td><td>Strobilurin</td></tr><tr><td>Pyrimethanil</td><td>0.020</td><td>34.4</td><td>0.007</td><td>92.8</td><td>0.002</td><td>388.8</td><td>Anilinopyrimidine</td></tr><tr><td>Tebuconazole</td><td>0.101</td><td>6.8</td><td>0.057</td><td>12.1</td><td>0.028</td><td>24.4</td><td>Triazole</td></tr><tr><td>Tebufenozide</td><td>0.021</td><td>32.3</td><td>0.012</td><td>57.1</td><td>0.004</td><td>165.7</td><td>Carbohydrazide</td></tr><tr><td>Tetraconazole</td><td>0.273</td><td>2.5</td><td>0.164</td><td>4.2</td><td>0.072</td><td>9.6</td><td>Triazole</td></tr></tbody></table>

<table><caption>**Table 3**
Calibration range, determination coefficient, limits of detection and quantification of the 20 pesticides in the MRM method.</caption><thead><tr><th>Compound</th><th>Calibration range (µg/L)</th><th>R<sup>2</sup></th><th>LOQ</th><th>LOD</th></tr></thead><tbody><tr><td>Ametoctradin</td><td>1–302</td><td>0.98</td><td>7</td><td>2</td></tr><tr><td>Azoxystrobin</td><td>1–297</td><td>0.98</td><td>5</td><td>2</td></tr><tr><td>Benalaxyl</td><td>1–293</td><td>0.99</td><td>5</td><td>2</td></tr><tr><td>Boscalid</td><td>1–301</td><td>0.99</td><td>5</td><td>1</td></tr><tr><td>Chlorantraniliprole</td><td>1–273</td><td>0.99</td><td>10</td><td>3</td></tr><tr><td>Cyprodinil</td><td>1–333</td><td>0.99</td><td>7</td><td>2</td></tr><tr><td>Difenoconazole*</td><td>1–335</td><td>0.91</td><td>8</td><td>2</td></tr><tr><td>Dimethomorph</td><td>1–310</td><td>0.98</td><td>7</td><td>2</td></tr><tr><td>Fenbuconazole*</td><td>1–317</td><td>0.98</td><td>4</td><td>1</td></tr><tr><td>Fenhexamid</td><td>1–299</td><td>0.99</td><td>7</td><td>2</td></tr><tr><td>Fludioxonil*</td><td>1–304</td><td>0.99</td><td>5</td><td>1</td></tr><tr><td>Iprovalicarb</td><td>1–294</td><td>0.99</td><td>6</td><td>2</td></tr><tr><td>Kresoxim-Me</td><td>1–323</td><td>0.99</td><td>6</td><td>2</td></tr><tr><td>Mandipropamid</td><td>1–243</td><td>0.98</td><td>6</td><td>2</td></tr><tr><td>Metrafenone*</td><td>1–310</td><td>0.92</td><td>5</td><td>1</td></tr><tr><td>Pyraclostrobin*</td><td>1–325</td><td>0.90</td><td>15</td><td>5</td></tr><tr><td>Pyrimethanil</td><td>1–302</td><td>0.99</td><td>5</td><td>1</td></tr><tr><td>Tebuconazole*</td><td>1–341</td><td>0.99</td><td>6</td><td>2</td></tr><tr><td>Tebufenozide*</td><td>1–302</td><td>0.97</td><td>20</td><td>6</td></tr><tr><td>Tetraconazole**</td><td>1–294</td><td>0.99</td><td>6</td><td>2</td></tr></tbody></table>

Compounds are quantified with TPP as IS except for compounds with * quantified with their corresponding isotopically labeled IS or ** quantified with tebuconazole-d<sub>6</sub> IS.

boscalid and dimethomorph are the only halogen-containing compounds categorized as least affected by PL.

### 3.2.2. Impact of PL parameters on degradation products

For the specific purpose of studying the degradation products, 74 compounds were monitored by HPLC-MS/MS, and the evolution of their peak area was studied using a clustering method, specifically the k-means methodology. K-means is an iterative algorithm that minimizes the sum of the distances between the centroid and the individual data. It can be used to group individuals with similar characteristics (clusters) by analyzing datasets characterized by a set of descriptors. In this experiment, the trends in the peak areas of degradation products as a function of fluence and voltage were used to categorize the different compounds into four categories (Fig. 3): (i) compounds that form quickly and do not degrade, (ii) compounds that form slowly and do not degrade, (iii) compounds that form quickly and degrade slowly, and (iv) compounds that form quickly and degrade rapidly.

The majority of the compounds for all voltages tested were in the first category, meaning they formed quickly and remained stable. Indeed, between 2 kV and 4 kV, respectively 58 and 47 compounds out of 74 were placed in this category. On the other hand, when raising voltage, a decrease in the number of degradation products in category (ii) was observed, with no more compound classified as “forming slowly and not degrading” for 4 kV, whereas they were 9 for 2 kV. This seems to indicate an acceleration in the rate of formation of degradation products when raising voltage.

Although the majority of the degradation compounds seemed to be stable at all the voltages tested, their proportions reduced as the voltage increased. In fact, a rise in the number of compounds that form quickly and degrade slowly was observed with the increase of voltage from 7 compounds for 2 kV to 12 compounds for 4 kV. Moreover, for the specific case of 4 kV, 20 % of the degradation products were in the group of compounds that form quickly and degrade rapidly, which is the only voltage for which compounds were placed in this category in all the experiments. This shows that the photoproducts described in Table 1 and Table S1 are themselves progressively degraded with the increase of UV radiation exposure. The degradation of the photoproducts correlates with the increase of the total fluence at this voltage, suggesting that a progressive mineralization operates.

The 4 kV modality was thus selected for its higher degradation efficiency based on these results.

### 3.3. Impact of PL on the acute toxicity of pesticides for A. fischeri

To assess the acute toxicity of samples, the A. fischeri bacterium was chosen as it enables rapid and inexpensive testing.

#### 3.3.1. Comparison between chemical and toxicological profiles of PL treatments on aqueous solutions of single pesticide

Pesticide aqueous solutions containing individual active substances between 66 and 345 µg/L were treated by PL, with the highest voltage of 4 kV and the highest fluence (91 J/cm²). LC-MS analyses and ecotoxicological assays were performed on UT (untreated) and T (treated) samples.

In alignment with Section 3.2, Fig. 4 shows that PL was able to significantly degrade all active substances studied. The five compounds that remained above their LOD in treated samples were the five compounds with the lowest k values, which implies a slower degradation. This validates the classification of compounds carried out in the previous section. Again, this experiment has proved the efficiency of PL to
<figure><img src="image_58.png" /><figcaption>Fig. 3. Clustering of the kinetic profiles of formation and degradation of 74 transformation products monitored at 2, 3 and 4 Kv.</figcaption></figure>

<figure><img src="image_59.png" /><figcaption>Fig. 4. Comparison of pesticide concentrations between untreated and treated samples for 18 single pesticides.</figcaption></figure>

degrade individual compounds in aqueous solutions. In fact, the con-
centration was reduced to concentrations below the LOQ for 14 com-
pounds and below the LOD for 13 out of 18 compounds.

In these samples, 32 degradation products were detected in total

(Fig. 5). Fewer compounds were observed in these experiments, and they showed lower peak areas compared to Section 3.2, which is likely due to the fact that only one modality was analysed, the one with the highest voltage and fluence. Indeed, as demonstrated in Section 3.2, the
<figure><img src="image_60.png" /><figcaption>Fig. 5. Peak areas of degradation products in treated samples.</figcaption></figure>

degradation products are progressively formed and then degraded by PL at high fluence and voltage. Therefore, this drop in the number of compounds and in the peak area of the observed TPs may be due to a degradation of first-generation TPs formed between 11 and 45 J/cm².

Furthermore, in these experiments, ametoctradin and chloran-
traniliprole were excluded due to their poor solubility (see Section
2.5.2), and chlorantraniliprole is associated with the formation of 4
degradation products. Lastly, the large variations in pesticide

<figure><img src="image_61.png" /><figcaption>Fig. 6. Comparison of acute toxicity between untreated and treated samples for 18 single pesticides.</figcaption></figure>
concentrations between both experiments, especially for the compounds at low concentrations, necessarily lead to a reduction in the peak areas of the associated degradation products.

The comparison of acute toxicity data (Fig. 6) shows that no treated samples have a toxicity higher than their untreated counterpart for A. fischeri. In other words, no treated samples are more toxic than their parent compound solutions for the bacteria A. fischeri. A reduction of the percentage of toxicity between the treated and untreated samples has even been noted for 11 out of 18 compounds and for the last 7, the toxicity was unchanged (T-test, *p-value* < 0.05). However, an inhibition percentage below 20 % cannot be considered for the Microtox® protocol as this corresponds to a non-toxic effect of the substance. Therefore, acute toxicity for boscalid, fenbuconazole, pyrimethanil, tebuconazole and tetraconazole cannot be considered. Only benalaxyl, metrafenone and pyraclostrobin, which had an inhibition percentage above 20 %, did not show a significant toxicity reduction, even if a downward trend could be observed. Therefore the toxicity decreased for 10 out of 18 compounds for A. fischeri.

These findings support the hypothesis of Baranda et al. (2012), which stated that a reduction in the mass of compounds with PL treatment and the dehalogenation of halogenated pesticides can produce degradation products less toxic than the parent compound.

### 3.3.2. Comparison between chemical and toxicological profiles of PL treatments on a cocktail solution of pesticides

Regarding acute toxicity, synergistic or antagonistic effects may arise when pesticides are together in solutions. For this purpose, the evolution of the acute toxicity as a function of the fluence was studied on a cocktail solution of 18 pesticides. The cocktail solution (concentrations between 216 and 402 µg/L of each pesticide) was treated with the highest voltage of 4 kV, with four increasing fluences applied to the different samples (11, 22, 45, and 91 J/cm²).

The LC-MS analyses (Fig. 7) support the findings of Section 3.2. The concentrations of the 18 pesticides experienced a significant drop (ANOVA *p-value* < 0.05), with only 3 compounds remaining at concentrations above their LOQ at the highest fluence. These compounds are boscalid, dimethomorph, and pyrimethanil, all of which had the lowest degradation rates, indicating slower degradation for these

compounds. Their average remaining concentrations were 6.9, 7.2 and 6 µg/L respectively, i.e. 1.97 %, 2.10 % and 2.17 % of their initial concentrations. This observation clearly demonstrates that the method used to classify the compounds was effective and fair, enabling reproducible experiments. However, the remaining concentrations of these compounds were much lower than observed in Section 3.2, which could be explained by the lower initial concentrations.

For these experiments, only 65 photoproducts were observed compared to the 74 observed in Section 3.2. This difference could be explained partly because of the absence of chlorantraniliprole in the mix, which was responsible for the formation of 4 degradation products and also because of a higher degradation level of all photoproducts which was observed for this experiment (Fig. 8, Table S3). Indeed, the k-means method was also applied for these experiments to determine if each compound was grouped in the same category as before, and it revealed that only 18 compounds remained in the category (i) “form quickly and do not degrade” compared to 47 for the optimization Section 3.2. Respectively, 30 and 17 compounds were in the categories (iii) “compounds that form quickly and degrade slowly” and (iv) “compounds that form quickly and degrade rapidly” compared to 12 and 15 in the experiment of Section 3.2. This could also be explained by the lower concentrations of the initial solution which imply smaller peak areas for the photoproducts and a faster degradation of them. However, the majority of the compounds previously observed were nevertheless detected, demonstrating the reliability of the relative quantification method developed.

The results of the acute toxicity assessments for A. fischeri indicate that the inhibition percentage for the different treatments decreases as fluence increases, suggesting a gradual reduction in acute toxicity with each treatment. This finding is further supported by the EC20 (effective concentrations at 20 %) values, which progressively increase with the treatments (Fig. 9). The EC20 value was chosen because if inhibition is below 20 %, the substance is considered non-toxic according to the Microtox® protocol. The reduction in acute toxicity for A. fischeri was notably greater between the untreated sample and the sample with the highest level of treatment. The toxicity was divided by 7.25, with EC20 mean values respectively equal to 16.8 % and 116.4 % for the untreated and the 91 J/cm² treated samples. Furthermore, it is important to point

<figure><img src="image_62.png" /><figcaption>Fig. 7. Degradation curves in cocktail solution for 18 pesticides applying fluences from 0 to 91 J/cm².</figcaption></figure>
<figure><img src="image_63.png" /><figcaption>Fig. 8. Clustering of degradation products in cocktail solution for 18 pesticides applying fluences from 0 to 91 J/cm².</figcaption></figure>

<figure><img src="image_64.png" /><figcaption>Fig. 9. Acute toxicity results for the cocktail solution of 18 pesticides applying fluences from 0 to 91 J/cm².</figcaption></figure>

out that the inhibition percentage of samples from the most heavily treated modality (91 J/cm²) is below 20 %, expressing the non-toxicity of this modality. In fact, the EC20 calculation for this modality is higher than 100 % (116.4 %), which is a deconvoluted result that makes no

practical sense.

The results of Section 3.3.2 are summarized in Fig. 10. The reduction in the concentrations of each pesticide enabled by PL treatment is accompanied by a gradual reduction in acute toxicity of the solution for

<figure><img src="image_65.png" /><figcaption>Fig. 10. Heat map of the evolution of the different variables monitored on the cocktail solution of 18 pesticides applying fluences from 0 to 91 J/cm².</figcaption></figure>
A. fischeri. This suggests that the pesticide degradation products generated in such proportions by the PL treatment are less toxic than the parent pesticides both in a cocktail solution as observed here, and in solutions with a single pesticide in most cases. These decreases in toxicity can be explained by the hydroxylation reactions observed on most compounds. Indeed, some studies have argued that hydroxylation reduces the toxicity of the parent molecule by increasing its hydrophilicity, which in turn reduces the potential bioaccumulative effects of neoformed compounds (Anagnostopoulou et al., 2022; Zhu et al., 2022).

Although the acute toxicity tests carried out on *A. fischeri* in cocktails or with single pesticide solutions showed reductions in toxicity in the majority of experiments, it is important to note that these reductions in toxicity only concern *A. fischeri*. In fact, the photoproducts formed may be more toxic and bioaccumulative than their parent pesticide, whether in terms of acute or chronic toxicity on other links in the chain. To establish that PL could have a positive impact on the treatment of pesticide-contaminated waters, acute and chronic toxicity studies are needed on different links in the aquatic trophic chain (algae, daphnid and fish).

## 4. Conclusion

These experiments demonstrated the effectiveness of using HPLC-MS/MS, toxicity assay and pulsed light (PL) together to study the formation of pesticide photodegradation products. PL has been demonstrated to be highly effective in degrading the 20 pesticides studied. The untargeted analysis approach conducted using scan mode in HPLC-MS/MS allowed for the observation of 74 degradation compounds and the formulation of 47 structural hypotheses. Predominant transformations observed included 39 dehalogenations and 31 hydroxylations. For only four pesticides out of 20, no degradation products were observed. MS/MS fragmentation has enabled the development of an MRM method for both relative quantification of the 74 photoproducts and absolute quantification of the 20 pesticides.

This MRM method was subsequently employed to study the degradation by PL of the 20 pesticides selected. Optimization revealed that higher voltages and fluences resulted in greater pesticide degradation, with the degradation products themselves also likely to be degraded. The sensitivity of the 20 pesticides to PL was classified, with strobilurins and triazoles being the most sensitive compounds, while cinnamic acid derivatives, amides and triazolopyrimidines were among the less sensitive.

HPLC-MS/MS was employed as an effective tool for optimization and studying the impact of processes on matrices containing numerous compounds. Analysis of 18 single pesticide solutions, treated or untreated by PL, both analytically and toxicologically using Microtox® analysis, validated initial observations. PL efficiently degraded each of the compounds studied, with 32 degradation products observed, likely due to significant degradation at higher voltages and fluences. The acute toxicity for *A. fischeri* of 10 out of 18 solutions decreased with PL treatments at 4 kV and a fluence of 91 J/cm² whereas it remained stable for the other 8.

Similar experiments were conducted on a cocktail solution with progressive fluence. Ultimately, 15 out of 18 compounds were degraded to concentrations below their LOQ, with 65 photoproducts observed. Acute toxicity assessments indicated a progressive reduction in toxicity, with a 7.25-fold reduction observed between the untreated and the most heavily treated condition. Moreover, the most treated sample was considered as non-toxic for *A. fischeri*.

However, further studies are required, particularly on real wine-growing effluents rather than on supplemented solutions. Additionally, toxicity tests on different trophic levels are necessary to validate initial results obtained with acute toxicity assay on *A. fischeri*. Further development should focus on continuous PL treatment reactors, with the analytical and toxicological impacts also requiring study.

This study has showcased the degradation capacity of PL, likely

attributed to its wide emission spectrum and high applicable fluences. Such high degradation capacity significantly reduces the toxicity of pesticide solutions on the bacteria *A. fischeri* both at individual level and in mixture. This technique is promising for reusing wastewater from wine estates for irrigation and facilitating a more ecological approach to winegrowing that respects ecosystem health.

## CRediT authorship contribution statement

François Clavero: Writing – review & editing, Writing – original draft, Methodology, Investigation. Jérôme Cachot: Writing – review & editing, Supervision, Methodology. Christelle Clérandeau: Writing – review & editing, Methodology. Laure Sandoval: Writing – review & editing. Fanny Meytraud: Writing – review & editing. Nicolas Picard: Writing – review & editing. Warren Albertin: Writing – review & editing, Formal analysis. Gilles de Revel: Writing – review & editing, Resources. Rémy Ghidossi: Writing – review & editing, Supervision, Resources, Funding acquisition, Conceptualization. Céline Franc: Writing – review & editing, Validation, Supervision, Resources, Conceptualization.

## Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Clavero Francois reports financial support was provided by Sanodev. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgments

Sanodev Industry and Region Aquitaine are acknowledged for their financial support. The authors would like to thank members of EPOC laboratory (UMR 5805 Univ. Bordeaux) for their collaboration.

Gracie Boland is acknowledged for English proofreading.

## Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.hazadv.2024.100577.

## Data availability

No data was used for the research described in the article.

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