Lucie Judkins
email: lucie.judkins@univ-tlse2.fr

Charlotte Alazard-Guiu
email: charlotte.alazard@univ-tlse2.fr

Corine Astésano
email: corine.astesano@univ-tlse2.fr

How do we chunk and pause in non-native vs native speech?

Keywords: non-native prosody, fluency, pauses, IPU, interlanguage, Second Language Acquisition (SLA)

The present preliminary study looks at speech units and pauses' quantity, duration and distribution in native (L1) vs non-native (L2) spontaneous speech. 6 English L1 -French L2 speakers (2 females) were recorded in their L1 and L2 on a conversation task. 3 speakers had an elementary L2 proficiency level, the other 3 were advanced. We looked at 1) the effect of speaking an L2 vs an L1 (within-speaker analysis) and 2) the effect of the proficiency level (betweenspeaker analysis) on the quantity, distribution and duration of silent and voiced pauses and the quantity and duration of Inter Pausal Units (IPU). Our results show that the IPU tend to be more numerous and shorter in L2 but those differences do not reach significance. Pauses are more numerous in L2 regardless of the proficiency level and the difference between L1 and L2 is less important in the advanced group. These tendencies concern mainly the quantity and less so the duration and distribution. Additionally, we notice a greater diversity in the type of pauses in L2. These observations shed light on the reality of interlanguage and the methodological issues involved in its description. Implications for L2 speech analysis and evaluation are discussed.

Introduction

Studies in Second Language Acquisition (SLA) concerned with the description and perception of non-native prosody are scarce [START_REF] Trouvain | Non-native prosody: Phonetic description and teaching practice[END_REF] but findings on some aspects of non-native prosody are discussed under the scope of fluency studies [START_REF] Kormos | Exploring measures and perceptions of fluency in the speech of second language learners[END_REF] [START_REF] Derwing | The relationship between L1 fluency and L2 fluency development[END_REF]. Such work is becoming more and more numerous as second language learning increases in accessibility and demand and with it, the need to accurately assess learners' oral skills. Fluency measures comprise several temporal variables traditionally assembled into categories: speed measures (such as speech rate, syllable rate, phonation/time ratio etc.), breakdown measures (Mean Length of Run, pauses), and disfluencies (repetitions, false starts, repair). Our study focuses on breakdown measures which are temporal variables that have been identified as relevant indicators of fluency [START_REF] Kormos | Exploring measures and perceptions of fluency in the speech of second language learners[END_REF] and as being acoustic correlates of speech rhythm. Indeed, rhythm being a fundamental and preeminent level of structuration in oral language [START_REF] Arvaniti | Rhythm, timing and the timing of rhythm[END_REF], studying such variables gives us an understanding of how speaking an L2 affects temporal organization of speech, reflecting the underlying cognitive processes involved [START_REF] Segalowitz | Cognitive bases of second language fluency[END_REF]. Silent and voiced pauses have been studied as markers of such processes. Pauses located at speech unit boundaries have been associated with macro-planning processes such as syntactic organization, whereas pauses located inside speech units reflects more local micro-planning processes such as lexical retrieval [START_REF] Duez | Caractéristiques acoustiques et phonétiques des pauses remplies dans la conversation en français[END_REF] [START_REF] Goldman-Eisler | Psycholinguistics[END_REF]. These concepts of macro and micro-planning processes have been developed in Levelt's speech production model ( [START_REF] Levelt | Speaking. From intention to articulation[END_REF]). With such perspective in mind, we used a within-speaker design which contrasts with most studies on fluency/nonnative speech, that are done through between-groups comparison of L2 vs native speech and focus on the "distance" between the groups' performances. To our knowledge, very few studies have focused on the language-dependent withinspeaker variation (except from [START_REF] Derwing | The relationship between L1 fluency and L2 fluency development[END_REF] and [START_REF] Riazantseva | Second language proficiency and pausing a study of Russian speakers of English[END_REF]). However, a between-speaker design is necessary to observe the development of temporal variables variations as learners gain proficiency. Consequently, our study combines both a within-speaker analysis focusing on the effect of the language variable (L1 vs L2) as well as a between-speaker analysis in order to test the proficiency level (elementary vs advanced) effect on chunking and pausing. This is a preliminary study which is part of a larger project involving native and L2 speakers of both French and English. The aim of this project is to compare the L2 effect with the spoken language effect and see how these two variables interact on rhythm patterns [START_REF] Judkins | La prosodie en L2 : le rythme comme composante déterminante de l'accès au sens?[END_REF].

Corpus B-FREN 3 methodology

This study was carried out on speech samples extracted from the corpus B-FREN 3 [START_REF] Judkins | Incidence de la langue parlée sur le registre vocal : étude comparative du français et de l'anglais[END_REF], a bilingual French-English/English-French corpus comprising three speech styles: reading aloud, film extract retelling, and conversation. In this section, we describe the methodology used to collect the data relevant to the present study i.e., the recordings of English L1-French L2 (elementary and advanced proficiency levels) speakers in a conversation task. We hypothesized that in L2, speakers would chunk more and make shorter speech units as well as realizing more and longer pauses. We also expect these tendencies to be more important in the elementary level group than in the advanced group.

Speakers

The speech samples belong to 6 adult native speakers of English, aged between 28 and 41 (average = 33,2) at the time of recording. All are native English speakers of different varieties of English (1 Scottish, 1 Scottish-American, 1 New-Zealander, 3 Americans; 2 females). Although this diversity could impact inter-individual variation, there is to this day no strong evidence that these varieties of English could in fact differ significantly in terms of temporal variables. On the opposite, Bolinger in [START_REF] Hirst | Intonation Systems: A Survey of Twenty Languages[END_REF] has pointed that British and American English share a common prosodic system, where differences appear to be mainly connected to pragmatic choices of the speakers.

Speech Prosody 2022 23-26 May 2022, Lisbon, Portugal All 6 participants speak French as an L2 at different proficiency levels such that we could split them into 2 groups of 3 speakers. One group of elementary (A2) L2 level speakers, and the second of advanced (B2) level speakers (A2 and B2 levels from the Common European Framework of Reference for Languages [START_REF]Council of Europe, Common European Framework of Reference for Languages: Learning, Teaching Assessment[END_REF]). The L2 proficiency levels of the participants were first assessed by the experimenter (first author) on the basis of her expertise as a foreign language teacher, through an informal interview. They were re-assessed post-hoc by anonymous French as a Foreign Language teachers who were asked to evaluate the participants' level on the basis of two recordings from the corpus (retelling and conversation task) and according to the CEFR level descriptors. Each participant was evaluated by 3 different judges and a final score was obtained by combining the 3 ratings into an average. The judges' ratings confirmed the initial assessment.

Task & procedure

The participants were recorded while performing a casual conversation task with the experimenter, on a familiar topic such as their last vacation trip or the last book they read/movie they saw. The task was performed once in their L1 and once in their L2 (with a different topic) and the order of the tasks' language was randomized. The recording sessions took place either at the experimenter or the participant's house guarantying a casual and comfortable setting while assuring adequate acoustic conditions. Each task was recorded separately using a Linear PCM Tascam DR 40 Version 2 recorder. The recordings vary in length between 2 and 5 minutes. For the purpose of this study, the samples used are all between 118 and 123 seconds long, taken in the middle portion of the recordings, when the participant has had time to get used to the task and experimental setup.

Annotation

The 12 selected speech samples (2 per participant, 1 in English (L1), 1 in French (L2)) were manually annotated using Praat. Speech was segmented into Inter Pausal Units (IPU) which are defined as a speech run between silent pauses of at least 250ms [START_REF] Kormos | Exploring measures and perceptions of fluency in the speech of second language learners[END_REF] [START_REF] Bertrand | Le CID -Corpus of Interactional Data -Annotation et Exploitation Multimodale de Parole Conversationnelle[END_REF]. In total, each speech sample comprises on average 2 minutes of speech and 30 IPU. We used the same threshold for all silent pauses [START_REF] Bosker | What makes speech sound fluent? The contributions of pauses, speed and repairs[END_REF] [16] meaning they are de facto external of IPU, marking their boundaries. Voiced pauses are of two sorts: interjections and lengthenings. Interjections are word-external hesitation markers such as [oeː] in French and [mː] in English [START_REF] Laver | Principles of phonetics[END_REF]. As such, they are not defined by a duration threshold but they are easily identifiable on the basis of auditory and visual cues on the spectrograph [START_REF] Duez | Caractéristiques acoustiques et phonétiques des pauses remplies dans la conversation en français[END_REF] [START_REF] Campione | Pauses and hesitations in French spontaneous speech[END_REF]. Lengthenings correspond to word-final syllables lengthened over 200ms, this threshold being generally considered as the pause perception minimum in the speech flow [START_REF] Goldman-Eisler | Psycholinguistics[END_REF] [START_REF] White | Back channeling, repair, pausing, and private speech[END_REF]. Lengthenings are a subcategory of voiced pauses which are more common in French, given the high frequency of word-final open syllables [START_REF] Grosjean | Analyse contrastive des variables temporelles de l'anglais et du français : vitesse de parole et variables composantes, phénomènes d'hésitation[END_REF]. They also occur in English, mainly on mono-syllabic words such as "and" or "the". However, not all lengthenings are hesitation markers. Indeed, some can bear a semantic-pragmatic function [START_REF] Cristo | Les musiques du français parlé. Essais sur l'accentuation, la métrique, le rythme, le phrasé prosodique et l'intonation du français contemporain[END_REF] [START_REF] Johnsen | Étude des contours prosodiques des listes ouvertes dans le corpus «OFROM[END_REF] and therefore not be connected to underlying speech planning cognitive processes. Consequently, these have been excluded from the study in the annotation process. When a voiced pause was realized between two IPU (>250ms silence + voiced pause + >250ms silence) it was labelled as a "mixt pause". Pauses were also labelled according to their distribution: IPU internal vs IPU external and within an IPU according to their position: initial, median, final, although this will not be commented in this paper. Table 1 shows the different types of pauses annotated and their characteristics. Table 1: Annotated pauses characteristics and thresholds

IPU-External Pauses

Respiratory

In our analysis, silent non-respiratory pauses and mixt pauses are combined under the term "external non-respiratory" pauses and internal voiced pauses and lengthenings are combined under the term "internal pauses".

To measure speech chunking, we calculated the ratio of IPU quantity (multiplied by 100 for legibility purposes) relative to the total speech time (number of IPU * 100 / total IPU time) as commonly done [START_REF] Derwing | The relationship between L1 fluency and L2 fluency development[END_REF]. The same formula was used to calculate the pause ratio expect this time the total speech time included IPU-external pauses (number of Pause * 100 / total IPU + total External Pause Time) [START_REF] Bosker | What makes speech sound fluent? The contributions of pauses, speed and repairs[END_REF] [16] [START_REF] De | Predicting pauses in L1 and L2 speech: The effects of utterance boundaries and word frequency[END_REF].

Data processing

A Praat [START_REF] Boersma | Praat: doing phonetics by computer[END_REF] script was used to extract all annotated items' duration (IPU and all types of pauses). We looked at their quantity, raw duration and calculated the variation coefficient (VC) on the duration as an indicator of the dispersion following the formula:

!" = ! " (1)
Where σ is the population standard deviation and µ the population mean.

Statistics: We tested the effects of the language and proficiency level variables separately as the latter is only relevant on the L2 speech samples. We computed linear regression models on all the duration dependent variables (IPU, External Respiratory Pauses, External Non-Respiratory Pauses, Internal Pauses) using R Studio (version 2021.09.0) and use p-value = 0.05 as significance threshold.

These tests were run only on the duration measures, which yielded substantial enough datasets. Statistic tests are not pertinent however on our chunking and pause ratios because of the reduced amount of data. We present our results on duration using medians (med.) which we find more representative of the data tendencies given the amount of variation (see variation coefficients presented in the next section). The results on the quantity ratios are presented using means, more representative of a small sample size.

Results

Language effect (L1 vs L2)

This is a within-speaker analysis comparing speech samples in 6 speakers' L1 (English) and L2 (French).

On IPU

In terms of quantity, the results on the chunking ratio show that speakers tend to chunk more (higher quantity of IPU) in L2 (chunking ratio mean = 44.37) than in L1 (chunking ratio mean = 38.46). The IPU duration (expressed in seconds) seems to be impacted by the language variable, however the effect does not reach significance (p-value = 0.291; F(1;394) = 1.117). IPU tend to be shorter in L2 (med. = 1.85) than in L1 (med. = 2.14) as predicted, with a difference of 292ms. In addition, our measure of the variation coefficient shows that the IPU durations vary a lot in L1 (61.68) as well as in L2 (61.98), which, as stated in the previous section, makes the median a better indicator than the mean.

From these results, it seems like the language variable does not have a strong effect on the IPU quantity and size.

On pauses

Given our definition of the IPU, the external pauses (respiratory and non-respiratory) embody their boundaries. It is therefore logical that in accordance with the results exposed above on the IPU, the quantity of external pauses is not greatly impacted by the language variable either. Both respiratory pauses and non-respiratory pauses are a little more numerous in L2 but again the difference is small (mean respiratory pauses ratio L1 = 13.86, L2 = 15.08; mean non-respiratory pauses ratio L1 = 16.33, L2 = 19.7). The difference in duration is also not significant for both these types of pauses however the tendencies go opposite ways. Indeed, respiratory pauses tend to be longer in L1 (med. = 0.739) than in L2 (med. = 0.654; p-value = 0.219; F(1;195) = 1.517) which follows previous studies' results [START_REF] Fauth | Détails phonétiques dans la réalisation des pauses en Français: étude de parole lue en langue maternelle vs en langue étrangère[END_REF], whereas non-respiratory pauses tend to be longer in L2 (med. = 0.691) than in L1 (med. = 0.525; p-value = 0.078; F(1;240) = 3.122). Noticeably, the variation in duration is much greater in the case of nonrespiratory pauses (see Figure 3 comparing the variation coefficient of all items). This can be explained by the fact that these pauses comprise silent pauses as well as mixt pauses which are longer in essence as they are composed of a voiced section in between silences. The quantity of internal pauses is greatly impacted by the language variable. As shown in Figure 1 below, there are more numerous in L2 (mean = 27.18) than in L1 (mean = 10.2). However, the duration of internal pauses is not significantly different between L1 and L2 (med. L1 = 0.468s; med. L2 = 0.493s; p-value = 0.912; F(1;256) = 0.012) and the variation coefficient is under 50 (L1 = 36.31; L2 = 44.35), so internal pauses are fairly stable in terms of their duration in both L1 and L2.

Figure 1: Internal pause ratio according to language.

Proficiency effect in L2 speech

This is a between speaker analysis comparing 3 anglophones A2 level French and 3 anglophones B2 level French.

On IPU

As shown in Figure 2 below, the A2 group chunks more than the B2 group. However the great between-speakers variability needs to be taken into account. The IPU duration is significantly impacted (p-value = 0.031; F(1;196) = 4.716) and as expected, more advanced learners (B2 level) make longer IPU (B2 med. = 2.371s.; A2 med. = 1.564s.). It is important to note the strong variability in IPU duration, as indicated by the variation coefficient: 66.23 in A2 and 57.72 in B2.

Figure 2: Chunking ratio according to proficiency level.

On pauses

As expected, respiratory pauses remain fairly stable in quantity (mean A2 = 15.59; mean B2 = 14.57) and duration (med. A2 = 0.683s; med. B2 = 0.629s) regardless of the proficiency level. Non-respiratory external pauses are more numerous (mean A2 = 22.91, mean B2 = 16.48) and longer in the A2 group (med. A2 = 0.830s., med. B2 = 0.508s.) but the difference is not significant (p-value = 0.190; F(1;128) = 1.735).

The internal pauses don't vary much in quantity (mean A2 = 27.53, mean B2 = 26.83) but their duration is significantly longer in the A2 group (med. A2 = 0.540s., med. B2 = 0.439s., p-value = 0.001; F(1;183) = 10.28).

Further remarks

Figure 3 below shows the variation coefficient of all dependant variables in both L1and L2, and proficiency levels. This is illustrating the amount of variation in duration for each dependent variable. Clearly, the external non-respiratory pauses, connected to macro-planning processes vary a lot. The IPU duration also varies greatly and this variation does not seem to be imputable to the language nor the proficiency variable (as explained in sections 3.1 and 3.2).

As expected, the respiratory pauses vary much less as they reflect a basic physiological rhythm constraint. However, it is interesting to note that internal pauses, which are the ones impacted by the language variable in terms of quantity, also do not vary as much in duration overall, therefore reflecting a sort of regularity in the shape that take micro-planning related pauses.

Lastly, more detailed data on the types of pauses (nature and distribution) has not been presented here but we observed a greater diversity in L2, meaning that some types of pauses are not used in L1 but appear in L2, such as lengthening in medial and final position within IPU.

Conclusion & discussion

Our results have shown that the language variable has the greatest impact on the internal pauses quantity. This confirms our expectations as we hypothesized that speakers would pause more in L2 and supports the results of [START_REF] De | Predicting pauses in L1 and L2 speech: The effects of utterance boundaries and word frequency[END_REF] as pauses are impacted most dramatically within IPU. This indicates that it is mostly the micro-level of speech planning which is affected when speaking an L2, whereas external (non-respiratory) pauses, reflecting the planning process of the next chunk (macro-level), do not differ as much when speaking an L1 or an L2 (the difference in our results was not significant). The quantity of IPU and external pauses behave similarly given our criteria for defining this speech unit, and even though they follow the expected tendency of being more numerous in L2, the differences are not significant, in contrast with other studies such as [START_REF] Kaglik | Perception d'un accent étranger et part de la prosodie selon l'âge de première exposition à la L2 : transfert ou phénomène universel en acquisition[END_REF]. On a rhythmic perspective, we could infer that speakers tend to keep chunks' size fairly similar but fill them with more voiced pauses, such as the global chunk pattern is not altered. The duration of IPU and all types of pauses is not significantly different from L1 to L2 although the tendencies also follow the literature: shorter IPU in L2, longer external non-respiratory pauses in L2, longer respiratory pauses in L1 ( [START_REF] De | Predicting pauses in L1 and L2 speech: The effects of utterance boundaries and word frequency[END_REF] [25], although [START_REF] Derwing | The relationship between L1 fluency and L2 fluency development[END_REF] and [START_REF] Riazantseva | Second language proficiency and pausing a study of Russian speakers of English[END_REF] obtain different results). On a methodological standpoint, it seems clear that pauses' distribution must be taken into account in fluency and nonnative prosody studies. Indeed, pauses do not vary equally depending on their functions (physiological, macro-planning, micro-planning) and associated positions in the speech flow. As mentioned by [START_REF] Fauth | Détails phonétiques dans la réalisation des pauses en Français: étude de parole lue en langue maternelle vs en langue étrangère[END_REF] the distinction of pauses' types is often unclear or even absent in studies ( [START_REF] Préfontaine | How do utterance measures predict raters' perceptions of fluency in French as a second language?[END_REF]). The effect of the proficiency level is significant on the duration of IPU which are longer in the advanced group (B2), and internal pauses which are longer in the elementary group (A2), as expected. The quantity of IPU and external nonrespiratory pauses behave again hand in hand, following the expected tendency of being more numerous in the A2 group. Interestingly, the quantity of internal pauses is very comparable in the two groups and it is their duration which is affected by the proficiency level since they are significantly longer in the A2 group, in accordance with our hypothesis. This conclusion has to be nuanced though, as previous research on the impact of proficiency level on pauses ( [START_REF] Derwing | The relationship between L1 fluency and L2 fluency development[END_REF]) has shown that this can be influenced by the levels themselves. The difference in pause duration seems accurate to distinguish only between an elementary level and an intermediate or above (which is our case) but it is not as clear in the case of intermediate vs advanced levels. [START_REF] Saito | Acoustic characteristics and learner profiles of low-, mid-and high-level second language fluency[END_REF] have also shown that speech breakdown improvement (longer IPU and less internal pauses) is particularly strong in the first stages of SLA.

Perspectives

As mentioned in our introduction, this paper presents a preliminary study which is to be extended to the entirety of our corpus, allowing us to include speakers of French L1-English L2 as well. We aim to confront the findings on L2 and proficiency effects with the L1 effect. We are also planning further observations on speech rhythm correlates such as the size of rhythmic groups (accentual phrases) within IPU ( [START_REF] Fant | Durational correlates of stress in Swedish, French and English[END_REF]) and the regularity of metrical stress. This work is carried out with the perspective of better understanding speech rhythmic pattern variations accross languages as L1 and L2 but also through the influence of the language itself (here, French and English). The larger aim of this project is to integrate knowledge about rhythm variation accross languages and L1-L2 into L2 prosody teaching methods. We could for example imagine an L2 prosody training that focuses on where and how to chunk and pause in the target language, ideally taking into account the learners' L1.

Figure 3 :

 3 Figure 3: Variation coefficient of all dependent variables (ext = external non-respiratory pauses, ext-re = external respiratory pauses, int = internal pauses)

10.21437/SpeechProsody.2022-161


Lucie Judkins

Charlotte Alazard

Corine Astésano

How do we chunk and pause in non-native vs native speech? Methodological implications for SLA

Introduction

The study of non-native prosody seeks to describe and understand how prosody is impacted when speaking a second language (L2). Some aspects of non-native prosody fall under the scope of fluency studies [START_REF] Kormos | Exploring measures and percep>ons of fluency in the speech of second language learners[END_REF] [START_REF] Derwing | The rela>onship between L1 fluency and L2 fluency development[END_REF], this is especially the case for speech temporal variables. Temporal variables such as speech chunks (later refered to as Inter Pausal Units or IPU) and pauses have been shown to be relevant indicators of fluency as well as correlates of speech rhythm [START_REF] Kormos | Exploring measures and percep>ons of fluency in the speech of second language learners[END_REF]. The temporal organization of speech reflects underlying cognitive planning processes and speaking an L2 is often characterized by shorter and more numerous chunks as well as longer and more numerous pauses, as a consequence of the added cognitive cost it involves [3][4]. Silent and voiced pauses have been studied as markers of such processes. Pauses located at speech unit boundaries have been associated with macro-planning processes such as syntactic organization, whereas pauses located inside a speech chunk reflect more local micro-planning processes such as lexical retrieval [START_REF] Duez | Caractéris>ques acous>ques et phoné>ques des pauses remplies dans la conversa>on en français[END_REF] [START_REF] Goldman-Eisler | Psycholinguis5cs[END_REF]. Temporal variables are usually studied through between-speaker design thus involving strong inter-individual variation, and often don't look closely at variables such as the speakers' L1, the languages involved and the proficiency level in L2. The present study is only preliminary as the full protocole involves 2 groups of speakers: L1 English-L2 French and L1 French-L2 English, in order to observe the impact of the aforementionned variables [START_REF] Judkins | Phénomènes de groupement et pause en parole na>ve vs non[END_REF]. We present here the results obtained on the L1 English-L2 French speakers. This study combines a within-speaker analysis between the speakers' L1 and L2 and a between-speaker comparison to observe the effect of L2 proficiency (elementary/advanced level) on chunks and pauses' duration and quantity.

3.a. Annotation

Þ Manual segmentation and annotation with Praat

4.a. Results -Language effect (L1 vs L2, within-speaker)

-Language variable's greatest impact is on internal voiced pauses' quantity which is higher in L2, indicating a predominent affection of micro-planning processes when speaking an L2 as in [START_REF] De | Predic>ng pauses in L1 and L2 speech: The effects of uperance boundaries and word frequency[END_REF]. -Speakers tend to chunk more in L2 but small difference. On a rythmic perspective we could infer that speakers tend to keep chunks' sizes fairly similar but fill them with more voiced pauses such as the global chunk pattern is not altered much. -Duration of IPU and all types of pauses does not differ significantly although it follows previous studies' results: shorter IPU and longer external nonrespiratory and internal voiced pauses in L2, longer respiratory pauses in L1 [START_REF] Fauth | Détails phoné>ques dans la réalisa>on des pauses en Français: étude de parole lue en langue maternelle vs en langue étrangère[END_REF] How do we chunk and pause in non-native vs native speech? Methodological implications for SLA HYPOTHESES -Speakers make more and shorter chunks and more and longer pauses in L2 -These tendencies will be stronger in the elementary L2 level group lucie.judkins@univ-tlse2.fr, charlotte.alazard@univ-tlse2.fr, corine.astesano@univ-tlse2.fr

6 SPEAKERS L1 English -L2 French 3 A2* level in L2 French 3 B2* level in L2 French

Corpus

  [START_REF] De | Predic>ng pauses in L1 and L2 speech: The effects of uperance boundaries and word frequency[END_REF].-Proficiency level's greatest impact is on IPU and internal voiced pauses' duration. More advanced learners produce longer chunks. -Internal voiced pauses vary across levels in duration but not quantity.-Methodological implication: pauses' function (physiological, macro/microplanning) and distribution (IPU internal/external) must be taken into account in fluency and non-native prosody studies as they do not vary similarly.

-

  French (L2) Corpus = 118 to 123 seconds of speech taken in the middle of each recording in each condition, around 4 minutes per speaker, around 24 minutes of speech analyzed in total Conversations recorded with a Linear PCM Tascam DR40 V.2 audio recording deviceyeild = 2 to 5 minutes of speech IPU (Inter Pausal Unit) Speech run between silent pauses >250ms Results on L1 French-L2 English speakers differ, showing different chunking and pausing strategies (as in [13]) depending on the speakers' L1, which are carried out in L2 speech. -Larger perspective: integrate knowledge about speech rhythm variation across languages and L1-L2 into L2 prosody teaching methods.

  . Further results & Perspectives L. Judkins, C. Alazard, C. Astésano Laboratory of NeuroPsychoLinguistics -University of Toulouse 2, France

Table 2 :

 2 mean quantity and median duration of IPU and pauses in L1 and L2 within-speaker -no significance reached

	-Quantity: ratio of item count/time [2] [10]
	-Duration in ms

-As expected, more and shorter IPU and more and longer pauses are in L2, but respiratory pauses longer in L1 as in

[START_REF] Fauth | Détails phoné>ques dans la réalisa>on des pauses en Français: étude de parole lue en langue maternelle vs en langue étrangère[END_REF]

. -Internal voiced pauses greatly impacted in quantity whereas length remains comparable.

Table 3 :

 3 mean quantity and median duration of IPU and pauses between A2 and B2 level groups between-speaker -significance marked with *

Table 1 :

 1 annotated items and their definition and threshold

	IPU-External Pauses

Non-respiratory Pauses >250ms IPU-Internal Pauses

	*Levels of the CEFR [8] (A2 = elementary, B2 = advanced)
	Voiced Pauses (Including lengthenings >200ms)	No threshold, use of auditory and visual cues
	-Language variable (L1 vs L2) and Proficiency variable (A2 vs B2) tested with
	distinct linear regression models on durations only (R Studio) -significance
	threshold: p-value = .05

-Small dataset on quantity -> no test, presented in means only

-As expected, fewer and longer IPU and fewer and shorter non-respiratory external pauses in B2. -In contrast with results in 4.a., almost no variation in quantity for internal voiced pauses whereas length significantly longer in A2.


domain: chim sde

text:
Tao Luo

Rasesh Pokharel

Tao Chen

Jean-François Boily

Khalil Hanna
email: khalil.hanna@ensc-rennes.fr

Fate and Transport of Pharmaceuticals in Iron and Manganese Binary Oxide Coated Sand Columns

Keywords: pharmaceuticals, goethite, manganese oxide, redox, geomedia filter, transport, modeling

Predicting the fate and transport of pharmaceuticals in terrestrial environments requires knowledge of their interactions with complex mineral assemblages. To advance knowledge along this front, we examined the reactivity of pipemidic acid (PIP), a typical quinolone antibiotic, with quartz particles coated with a mixture of manganese oxide (MnO2) and goethite (α-FeOOH) under static and dynamic flow conditions. Batch and dynamic column experiments showed that PIP binding to MnO2 proceeded through a heterogeneous redox reaction while binding to goethite was not redoxreactive. Mixed columns of aggregated goethite-manganese particles however enhanced redox reactivity because (i) goethite facilitated the transport of dissolved Mn(II) ion and increased the retention of PIP oxidation products, and (ii) MnO2 was protected from passivation. This mobility behavior was predicted using transport models accounting for adsorption and transformation kinetics of PIP on both goethite and MnO2. This work sheds new light on reactivity changes of mixtures of Fe and Mn oxides under flow-through conditions, and will have important implications in predicting the fate and transport of redox-active organic compounds as well as development of new geomedia filters for environmental remediation.

Introduction

Iron (Fe) and manganese (Mn) are the two most common redox-active elements in the Earth's crust. They are present in wide range of environments with different composition, mineralogy, and morphology [START_REF] Post | Manganese Oxide Minerals: Crystal Structures and Economic and Environmental Significance[END_REF][START_REF] Cornell | The Iron Oxides: Structure, Properties, Reactions, Occurrences and Uses[END_REF] . For example, Fe and Mn-oxides may co-exist with each other as discrete particles, mixture of component phases or particulate coatings in soils and sediments [START_REF] Lion | Trace-Metal Adsorption Characteristics of Estuarine Particulate Matter: Evaluation of Contributions of Fe/Mn Oxide and Organic Surface Coatings[END_REF] . In deep sea waters, Mn and Fe are oxidized to form ferromanganese crusts and nodules on the oceans floor, a mineral of immense economic interest. Because of their specific nanoscale properties, high surface area, low cost, strong oxidation and sorption abilities, iron and manganese oxides are widely used in various environmental applications [START_REF] Remucal | A Critical Review of the Reactivity of Manganese Oxides with Organic Contaminants[END_REF][START_REF] Li | Transformation of Tetracycline Antibiotics with Goethite: Mechanism, Kinetic Modeling and Toxicity Evaluation[END_REF][START_REF] Huang | Facet-Specific Photocatalytic Degradation of Organics by Heterogeneous Fenton Chemistry on Hematite Nanoparticles[END_REF][START_REF] Zhou | Water Flow Variability Affects Adsorption and Oxidation of Ciprofloxacin onto Hematite[END_REF][START_REF] Chen | Oxidation of Β-Blockers by Birnessite: Kinetics, Mechanism and Effect of Metal Ions[END_REF] . They play a key role in controlling the fate and mobility of elements and toxic compounds in nature, and can also be used as an environmentally friendly geomedia filter in water treatment technologies and/or aquifer recharge management [START_REF] Liang | Preparation and Characterization of Fe-Mn Binary Oxide/Mulberry Stem Biochar Composite Adsorbent and Adsorption of Cr(VI) from Aqueous Solution[END_REF][START_REF] Ricko | Reductive Transformations of Dichloroacetamide Safeners: Effects of Agrochemical Co-Formulants and Iron Oxide + Manganese Oxide Binary-Mineral Systems[END_REF][START_REF] Zhang | Respective Role of Fe and Mn Oxide Contents for Arsenic Sorption in Iron and Manganese Binary Oxide: An X-Ray Absorption Spectroscopy Investigation[END_REF] .

Goethite (α-FeOOH) is one of the most thermodynamically stable iron oxyhydroxide under ambient conditions, and the most abundant one in natural settings [START_REF] Cornell | The Iron Oxides: Structure, Properties, Reactions, Occurrences and Uses[END_REF][START_REF] Liu | An Overview of the Role of Goethite Surfaces in the Environment[END_REF] . For this reason, numerous theoretical and experimental studies explored organic or inorganic compounds binding mechanisms to goethite surfaces and their impact on migration in nature [START_REF] Evanko | Surface Complexation Modeling of Organic Acid Sorption to Goethite[END_REF][START_REF] Cheng | Effects of Organic Matter-Goethite Interactions on Reactive Transport of Nalidixic Acid: Column Study and Modeling[END_REF] . Birnessite-type layered manganese oxides are, at the same time, of great interest given their strong redox-and cation exchange reactivity [START_REF] Chen | Oxidation of Β-Blockers by Birnessite: Kinetics, Mechanism and Effect of Metal Ions[END_REF][START_REF] Wang | Birnessite (γ-MnO2) Mediated Degradation of Organoarsenic Feed Additive p -Arsanilic Acid[END_REF][START_REF] Zhao | CD-MUSIC-EDL Modeling of Pb 2+ Adsorption on Birnessites: Role of Vacant and Edge Sites[END_REF] . Their interest is also motivated by their structural similarity to the biogenically precipitated natural manganese oxides, which are the most commonly occurring forms of MnO2 in surficial environments [START_REF] Post | Manganese Oxide Minerals: Crystal Structures and Economic and Environmental Significance[END_REF] .

Although the reactivity of each individual or single phase has been widely investigated 7,17- 21 , knowledge is limited on how binary mixture of these two phases, goethite and MnO2, alter the overall reactivity of environmental compounds. Previous studies [START_REF] Anderson | Surface and Bulk Characteristics of Binary Oxide Suspensions[END_REF][START_REF] Anderson | Modeling Adsorption in Aluminum-Iron Binary Oxide Suspensions[END_REF][START_REF] Meng | Effect of Component Oxide Interaction on the Adsorption Properties of Mixed Oxides[END_REF] have reported that binary mixture of Fe(OH)3 with Al(OH)3 or SiO2(am) have exhibited different adsorption properties from their component parts due to changes in surface site availability and surface charge. This has been ascribed to the dissolution of Al(OH)3 or SiO2(am) and sorption/precipitation of the dissolved ions at Fe-oxides surfaces. Other studies [START_REF] Taujale | Impact of Interactions between Metal Oxides to Oxidative Reactivity of Manganese Dioxide[END_REF] have reported that mixtures of MnO2 with other oxides like Al2O3 or SiO2(am) or TiO2 inhibited MnO2 reactivity mainly through heteroaggregation between particles and/or adsorption of metal ions released from the second oxides on the MnO2 surface.

Two recent studies [START_REF] Zhang | Effects of NOM on Oxidative Reactivity of Manganese Dioxide in Binary Oxide Mixtures with Goethite or Hematite[END_REF][START_REF] Huang | Redox Reactions of Iron and Manganese Oxides in Complex Systems[END_REF] even showed that Fe oxides inhibited MnO2 reactivity through heteroaggregation of positively charged Fe oxides particles with negatively charged MnO2 particles, thereby reducing the number of surface sites of MnO2. However, little is known on how this reactivity is affected under dynamic, flow-through, conditions that are far more prevalent in environmental and/or engineered systems than the static (batch) modes more commonly employed in laboratory studies. This is particularly relevant because dissolved ions and/or redox byproducts (e.g. dissolved Mn(II)) concurrently affect surface reactivity of manganese and iron oxides minerals and the mobility of target compounds. As such, experimental work under continuous flow conditions can better emulate natural environments (e.g. geochemical systems containing Fe-and Mn-oxides) or engineered infiltration systems (e.g. managed aquifer recharge (MAR) and water treatment systems), where the target pollutants and the generated reaction products travel through and are then flushed out of the column system. In addition, most traditional environmental models are based on a single phase or simple system, and little is known on the redox reactivity within complex mineral assemblages. Knowledge of the adsorption and redox reactions that take place in the mixed mineral phases or complex environmental systems and under flow-through conditions is consequently needed to explore contaminant transport.

This study aims to assess the roles that co-existing iron and manganese oxides play on the fate and transport of contaminants under conditions of water flow. This was achieved by working with columns packed with sand microparticles (CS) coated by MnO2 (MCS), goethite (GCS), or mixed goethite-MnO2 (MGCS). Pipemidic acid (PIP) was, in turn, chosen as a representative redox-active quinolone antibiotic widely used in human and veterinary medicine [START_REF] Shimizu | Absorption, Distribution and Excretion of Pipemidic Acid[END_REF] , and commonly found in ng/L to µg/L levels [START_REF] Golet | Environmental Exposure and Risk Assessment of Fluoroquinolone Antibacterial Agents in Wastewater and River Water of the Glatt Valley Watershed, Switzerland[END_REF][START_REF] Kolpin | Hormones, and Other Organic Wastewater Contaminants in U.S. Streams, 1999-2000: A National Reconnaissance[END_REF][START_REF] Hartmann | Primary DNA Damage but Not Mutagenicity Correlates with Ciprofloxacin Concentrations in German Hospital Wastewaters[END_REF] in aquatic environments and agricultural settings [START_REF] Weist | ECDC Publishes 2015 Surveillance Data on Antimicrobial Resistance and Antimicrobial Consumption in Europe[END_REF][START_REF] Ma | Occurrences and Regional Distributions of 20 Antibiotics in Water Bodies during Groundwater Recharge[END_REF][START_REF] Manyi-Loh | Antibiotic Use in Agriculture and Its Consequential Resistance in Environmental Sources: Potential Public Health Implications[END_REF] .

Investigation of redox transformation of compounds contacted to reactive minerals is also required for an accurate assessment of ecological impacts of quinolone antibiotics. As the redox reaction is strongly depended on pH value and MnO2/compound ratio, dynamic flow experiments of PIP were performed with two different MnO2 amounts in the MGCS system and at pH 5.2 and 7.0, which are within the typical pH range for shallow groundwater and soil pore waters [START_REF] Sposito | The Surface Chemistry of Soils[END_REF] . A transport model that accounts for adsorption and oxidation kinetics was used to predict changes in PIP transport in coated sands under flow. This work additionally explains how goethite-MnO2 interactions affect PIP reactivity, and potentially how these mechanisms affect similar other environmental emerging contaminants.

Materials and Methods

Synthesis of minerals and coated phases

Pure Fontainebleau quartz sand (200-300 µm; ≤ 0.06 m 2 /g) was chosen as an inert support, due to its very low reactivity and aqueous solubility under our experimental conditions [START_REF] Zhou | Silicate Surface Coverage Controls Quinolone Transport in Saturated Porous Media[END_REF] . The quartz sand was cleaned with HCl, H2O2 and ultrapure water to remove any colloidal or amorphous silica particles and organic/inorganic contaminants (see SI for detailed cleaning procedure). Acid birnessite (MnO2) prepared according to McKenzie 37 was coated on quartz sand (MCS) as in our previous study [START_REF] Pokharel | Water Flow and Dissolved Mn(II) Alter Transformation of Pipemidic Acid by Manganese Oxide[END_REF] , and summarized in the SI. Likewise, goethite (α-FeOOH) goethite-coated quartz sand (GCS) were synthesized as described in previous studies [START_REF] Hanna | Sorption of Two Naphthoic Acids to Goethite Surface under Flow through Conditions[END_REF][START_REF] Gaboriaud | Effects of Different Crystal Faces on the Surface Charge of Colloidal Goethite (α-FeOOH) Particles: An Experimental and Modeling Study[END_REF][START_REF] Hanna | Sorption of Phthalic Acid at Goethite Surfaces under Flow-Through Conditions[END_REF][START_REF] Rusch | Coating of Quartz Silica with Iron Oxides: Characterization and Surface Reactivity of Iron Coating Phases[END_REF] , and summarized in the SI.

The B.E.T. specific surface area of uncoated goethite and birnessite phases was 81 ± 4 and 65 ± 1 m 2 g -1 respectively, and the point of zero charge (PZC) determined at 298 K in 0.01, 0.1 and 1 M NaCl solutions by the potentiometric titration method, was pH 9.1 for goethite and 2.4 for birnessite. Coating coverage was thereafter evaluated by total Mn and Fe concentrations of acid digested MCS and GCS. Concentrations, measured by Inductively Coupled Plasma-atomic Emission Spectrometry (ICP-AES), revealed 0.60 ± 0.02 (SD) mg Mn per 1 g of MCS and 6.2 mg ± 0.20 (SD) Fe per 1 g of GCS. These coating amounts are within the previously reported range for natural coated subsurface materials [START_REF] Sposito | The Surface Chemistry of Soils[END_REF][START_REF] Stumm | Chemistry of the Solid-Water Interface: Processes at the Mineral-Water and Particle-Water Interface in Natural Systems[END_REF] , and they allow stable coated minerals to be achieved.

The possible dissolution of the used quartz sand was, additionally checked in 1 and 10 g/L sand suspensions that were continuously stirred over a range of pH values (4-10) in pure water or 0.01 M NaCl for up to one month. In all cases, the dissolved silicate concentrations were below the detection limit of the molybdenum blue spectrophotometric method (<1 µM) and ICP-AES (<0.2 µM).

Binary mixtures of iron and manganese oxides (MGCS) were prepared by adding different amounts of MnO2 suspension to GCS. Small aliquots of MnO2 suspension were pipetted homogenously over the GCS surface, then mixed with a polypropylene spatula, and dried overnight at room temperature. The resulting solid was thereafter washed four times with 10 mM NaCl to remove any uncoated MnO2, then dried again at room temperature. Two different MGCS were prepared: 1) 0.05 MGCS and 2) 0.1 MGCS, where 0.05 and 0.1 indicate the percentage of MnO2 in the MGCS system.

The Mn content in the MGCS was determined by dissolving in 30 mM ascorbic acid following the protocol of Charbonnet et al. [START_REF] Charbonnet | Chemical Regeneration of Manganese Oxide-Coated Sand for Oxidation of Organic Stormwater Contaminants[END_REF] and analyzed by ICP/AES. The measured amount was 0.29 ± 0.02 (SD) mg of Mn in 1 g of 0.05 MGCS and 0.60 ± 0.02 (SD) mg of Mn in 1 g of 0.1 MGCS. Scanning electron microscopy (SEM) was applied to study the surface morphology of the MGCS matrix. Samples were examined with a JSM JEOL 7100 F microscope with a field emission gun and an OXFORD Genesis energy-dispersive Xray spectrometer at 20 kV at a working distance of 5-10 mm and magnifications from 15000× to 30000×. SEM images of MGCS showed a mixture of goethite and MnO2 particles deposited on the sand (Fig. S1). Due to the extremely low Mn amount in the MGCS, X-ray diffraction could not be used for MGCS characterization.

Batch and column experiments

Three different sets of batch experiments were conducted to determine the 1) pH dependent adsorption of PIP on GCS with or without Mn(II), 2) pH dependent Mn(II) adsorption on GCS with or without PIP, 3) kinetics of PIP removal on 0.05 MGCS at pH 5.2, and 4) kinetic Mn(II) sorption on MCS and MGCS at pH 5.2 under static conditions. Details on the experimental setup are provided in the SI.

Dynamic breakthrough experiments were conducted at room temperature and under watersaturated conditions. Briefly, 15 g of GCS, MCS or MGCS were packed in glass columns with an internal diameter of 1.6 cm and bed length of 4.7 cm. The column was wrapped with aluminum foils to avoid any photo-induced degradation. The bulk density of the packed MGCS was 1.52 ± 0.05 g/cm [START_REF] Lion | Trace-Metal Adsorption Characteristics of Estuarine Particulate Matter: Evaluation of Contributions of Fe/Mn Oxide and Organic Surface Coatings[END_REF] , and the column pore volume (PV or Vp) was 4 ± 0.1 mL. The column was first saturated with a background solution of 10 mM NaCl (previously purged with N2) at pH 5.2 or 7.0 (depending on the experimental pH) with a constant flow rate of 0.5 mL/min (residence time of 8 min). A bromide tracer experiment was performed using an input solution containing 10 mM NaBr in 10 mM NaCl at pH 5.2 or 7.0. Br -breakthrough curves for different columns (GCS, MCS, 0.05 MGCS, 0.1 MGCS) were obtained by analysis of the effluent solution using ion chromatography (Fig. S2).

Different column experiments were performed by injecting input solutions consisting of a constant amount of 10 mM NaCl and 10 μM PIP but at two different pH values, 5.2 (± 0.1) or 7.0 (± 0.1). The investigated inflow concentration of PIP may appear higher than the level amounts of pharmaceuticals commonly detected in environmental systems [START_REF] Golet | Environmental Exposure and Risk Assessment of Fluoroquinolone Antibacterial Agents in Wastewater and River Water of the Glatt Valley Watershed, Switzerland[END_REF][START_REF] Kolpin | Hormones, and Other Organic Wastewater Contaminants in U.S. Streams, 1999-2000: A National Reconnaissance[END_REF][START_REF] Hartmann | Primary DNA Damage but Not Mutagenicity Correlates with Ciprofloxacin Concentrations in German Hospital Wastewaters[END_REF] , but close to total dose of organic compounds found in industrial effluents or urban stormwater and municipal wastewater used in aquifer recharge [START_REF] Charbonnet | Chemical Regeneration of Manganese Oxide-Coated Sand for Oxidation of Organic Stormwater Contaminants[END_REF] . Furthermore, since the Mn-based redox reaction is strongly dependent on red/ox ratio, different MnO2 amounts and thus different PIP/MnO2 ratio were investigated. The experimental flow-rate was constant throughout the course of the experiment at 0.5 ml/min. The input solution was purged with N2 to avoid CO2 contamination and to maintain the experimental pH throughout the course of the experiment. Flow interruption method was applied in selected experiments to check the occurrence of kinetic limitations. All effluent solutions were collected using a fractional collector. The pH of the effluent solution was determined through the experiment by using an online pH meter. The effluent solution was also analysed for PIP and by-products with high-performance liquid chromatography (HPLC) and an ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) system, and for dissolved metal ions using ICP-AES. More details about experimental conditions and measurements are reported in the SI (Table S1).

Transport modeling

First, the hydrodynamic parameters were obtained by fitting the bromide breakthrough data using classical Advection Dispersion Equation (ADE):

𝜕𝐶 𝜕𝑡 = 𝐷 𝜕 2 𝐶 𝜕𝑥 2 -𝑣 𝜕𝐶 𝜕𝑥 (1)
Breakthrough curves (BTC) for Br -suggest the absence of great dispersion/diffusion or physical nonequilibrium effect (Fig. S2 in the SI). Macroscopic dispersivity (~ 1.89 mm) was obtained by the ratio of the dispersion coefficient (D) and of pore velocity (v). Molecular diffusion was considered negligible with respect to the dynamic dispersion. The Péclet number (Pe = vL/D) was ~25 in the column, suggesting the predominance of a convective regime, and the flow can be assumed to be homogeneous. During water saturation and tracer experiments, total dissolved Mn, Fe and Si in the outflow was below the ICP-AES detection limit (0.1 μM for Mn, 0.2 μM for Fe and 0.2 μM of Si), and therefore the possibility of mobilization and/or dissolution of minerals can be excluded. Blank tests conducted also confirmed no adsorption of Mn(II) ions to the quartz sand (≤ 0.06 m 2 /g).

The reactive transport model is based on a two-site, advective-dispersive transport model with degradation and Freundlich-Langmuir kinetic sorption. The liquid and sorbed concentrations are ruled by the following differential equation that governs the chemical non-equilibrium transport for a homogeneous system under steady-state water flow [START_REF] Šimůnek | Modeling Nonequilibrium Flow and Transport Processes Using HYDRUS[END_REF][START_REF] Van Genuchten | Two-Site/Two-Region Models for Pesticide Transport and Degradation: Theoretical Development and Analytical Solutions[END_REF] :

𝜕𝐶 𝜕𝑡 + 𝜌𝜕(𝑆) 𝜃𝜕𝑡 = 𝐷 𝜕 2 𝐶 𝜕𝑥 2 -𝑣 𝜕𝐶 𝜕𝑥 -𝜇 l 𝐶 - 𝜌 𝜃 𝜇 𝑠 𝑆 ( 2
)
where θ is the volumetric water content (L 3 /L 3 ), C is the volume-averaged solution concentration (M/L 3 ), t is time (T), ρ is solid bulk density, S is the sorbed concentration (M/M), D is the dispersion coefficient in the liquid phase (L 2 /T), v is the water velocity (L/T), μl and μs are first-order degradation rate constants (T -1 ) for the liquid and sorbed phases.

Because quinolones binding to oxide surfaces may proceed through a non-specific and fast surface complexation reaction, such as outer-sphere or hydrogen-bound, and a specific surface complexation reaction, generally slower, such as metal-bound complexes, we assume that adsorption sites can be divided into two fractions, instantaneous (Type-1) and kinetic (Type-2) sites [START_REF] Van Genuchten | Two-Site/Two-Region Models for Pesticide Transport and Degradation: Theoretical Development and Analytical Solutions[END_REF] .

𝑆 = 𝑆 1 + 𝑆 2 (3)
Where S1 and S2 are solid phase concentrations associated with Type-1 and Type-2 sites respectively. Considering Type-1 adsorption sites are always at equilibrium, S1 can be expressed as:

𝑆 1 = 𝑓𝐾 𝐶 𝛽 1+𝜂𝐶 𝛽 (4)
The Type-2 adsorption sites are assumed to be a first-order kinetic rate process:

𝜕𝑆 2 𝜕𝑡 = 𝛼 [(1 -𝑓)𝐾 𝐶 𝛽 1+𝜂𝐶 𝛽 -𝑆 2 ] -𝜇 𝑠 𝑆 2 (5)
where α is a first-order kinetic rate coefficient (T -1 ), f is the fraction of instantaneous adsorption sites (Type-1), and K, β and η are empirical coefficients.

Transport modeling was performed with HYDRUS 1D [START_REF] Šimůnek | Modeling Nonequilibrium Flow and Transport Processes Using HYDRUS[END_REF] . This code allows for the numerical resolution of equations 2-5 for several boundary and initial conditions: concentration flux at the inlet, zero concentration gradient at the outlet, and no solute at time zero. By using a least-squares optimization routine, HYDRUS 1D also allows inverse modeling to fit the model solution to the data to estimate fate and transport parameters [START_REF] Šimůnek | Modeling Nonequilibrium Flow and Transport Processes Using HYDRUS[END_REF] . Because of PIP transformation reactions only occurred at MnO2 surfaces and not in solution, μl was set to 0. This also allows reducing the number of estimated parameters, and thus avoiding non-uniqueness issues (a sensitivity analysis has been done in previous work [START_REF] Zhou | Water Flow Variability Affects Adsorption and Oxidation of Ciprofloxacin onto Hematite[END_REF] ). Values for the sorption parameter K, fraction of equilibrium sites f, kinetics adsorption α and the first-order degradation rate μs were determined through fitting the breakthrough curves of PIP, and are reported in Table S2. MnO2 in MGCS columns strongly slows down PIP mobility with respect to the (MnO2-free) GCS column (Figure 1). This can be appreciated by extensive tailing of the breakthrough curve (BTC) and incomplete breakthrough of PIP in the MCS column (0.60 mg Mn/g 0.1 MCS), compared to the GCS column with a sigmoidal-shaped low-tailing BTC with total breakthrough (C/C0 = 1) by 60 PV. In strong contrast, the 0.1 MGCS with the same Mn loading as MCS (0.60 mg Mn/g 0. The pH of the output solution from the GCS column initially slightly decreased by ~ 0.4 unit but finally returned to 5.5 when steady-state breakthrough was reached (Fig. S3). However, the transformation of PIP on MnO2 or the reductive conversion of MnO2 released Mn(II) through:

MnO2 + 2e -+ 4H + → Mn 2+ + 2H2O (6)
As this is a proton-promoted process, pH initially increased to 5.9 and then decreased to initial pH value on MCS column (Fig. S3). In the MGCS column, no pH changes in 0.05 MGCS, while pH followed the same behavior as for the MCS column in 0.1 MGCS (Fig. S3). As PIP was mostly present in the zwitterionic form (pKa1 = 5.20, pKa2 = 6.38) (Fig. S4), adsorption to goethite occurred via surface complexation reactions involving carboxylic and keto groups, with a possibility of oxidation reaction involving the piperazine ring. [START_REF] Zhang | Adsorption and Oxidation of Fluoroquinolone Antibacterial Agents and Structurally Related Amines with Goethite[END_REF] However, the BTC shape and the lack of by-products in the effluent did not provide evidence for PIP oxidation by goethite. The modeling results also support the absence of PIP oxidation since no heterogeneous degradation rate (μs) was required to fit the BTC of PIP (Fig. 1, Table S2). Conversely, modeling of the partial PIP breakthrough in the Mn-bearing MCS and MGCS columns did require μs (Fig. 1, Table S2).

The total amount of PIP removal (by adsorption and/or oxidation) was calculated by integrating of the area above the BTC of PIP. In the MCS column, the total PIP removal was ~5 μmol at ~800 PV, while the same Mn loadings in the 0.1 MGCS column removed ~11 μmol PIP at the same breakthrough time. This consequently implies that the 0.1 MGCS column removed almost twice the amount of PIP than in the MCS column despite having the same Mn loading. As the 0.1 MGCS and GCS columns contained the same goethite loadings, the contribution of goethite in PIP removal can be estimated at ~1.5 μmol.

Enhanced MnO2 content not only improved PIP removal in the MGCS column (3.2 μmol

PIP removal in 0.05 MGCS column vs 11 μmol in 0.1 MGCS column), but also modified the breakthrough behavior. Indeed, a two-step behavior, two fronts and two plateaus, was observed corresponding to the pH variation during the transport experiment (Fig. S3). This breakthrough behavior can be described by considering three stages, and different parameters are necessary to describe each stage of the full BTC of PIP (Table S2). If the same adsorption and oxidation parameters (i.e. α, K, f, μs) were used for full BTC description, the calculated curve failed to describe the transport process of PIP, especially for the transitional plateau (Fig. S5). This mobility behavior could be explained by the pH impact on heterogeneous redox reaction and/or (re)adsorption of redox products. It has been reported that fluoroquinolone binding to negatively charged Mn-oxide surfaces proceeds through a heterogeneous redox reaction, whereby two oneelectron-transfer or a single two-electron transfer oxidize PIP and reduce surface-bound metal sites 17,19,46 . This will be investigated in the next section.

Impact of manganese oxide content on PIP oxidation in column

To further investigate PIP transport in MGCS columns, redox by-products (dissolved Mn(II) and oxidized by-product of PIP) were monitored in the outflow solution throughout the breakthrough experiment and upon flow interruption. Our flow/no flow/flow sequence protocol allowed us to check kinetic limitations through determination of BTC of species before interruption and after resumption of flow. In the 0.05 MGCS column, Mn(II) was detected in the effluent solution at the same time as PIP, then reached a steady-state concentration of 1.2 μM. Increasing the residence time of PIP in the 0.05 MGCS column by interrupting the flow for 24 h (376 PV) did not influence the incomplete breakthrough as the same partial breakthrough (C/C0 = 0.94) was still observed upon flow resumption (Fig. 2a). This flow interruption period allowed species to react over a longer period during flow-through conditions. Here, relative concentrations of PIP dropped from 0.94 to 0.76 while those of Mn(II) increased sharply from 1.2 to 5 μM, yet solution pH values were stable throughout the course of the experiment (Fig. 2b). This behavior pointed to rate-limited sorption/redox processes from co-occurring adsorption reactions and heterogeneous redox reactions. Note that BTC curves in separate bromide tracer experiments did not change following a flow/no-flow/flow sequence, thereby excluding the possibility of physical non-equilibrium or diffusive mass transfer that might cause changes in PIP and Mn(II) concentrations. Upon flow resumption, both PIP and Mn(II) concentrations reached the steady-state concentrations prior to the stop-flow. Although Mn(II) was detected by ICP-AES as the reduced by-product, no oxidized by-product of PIP (hereafter referred as PIPox) was detected in the effluent throughout the course of the experiment (Fig. 2a). This could be explained by the very low concentrations of generated redox products and/or strong binding to minerals at the working pH value (5.2). In the 0.1 MGCS column, redox products (Mn(II) and PIPox) were detected throughout the course of the experiment (Fig. 3a). LC/MS analysis confirmed the PIPox had a m/z value of 227 (M-26), formed through N-dealkylation of the piperazine ring of PIP (Fig. S6). As previously observed for quinolone compounds [START_REF] Pokharel | Water Flow and Dissolved Mn(II) Alter Transformation of Pipemidic Acid by Manganese Oxide[END_REF][START_REF] Zhang | Oxidative Transformation of Fluoroquinolone Antibacterial Agents and Structurally Related Amines by Manganese Oxide[END_REF] , one electron is transferred from sorbed compound to the surface-bound Mn IV , yielding radical intermediates, and Mn III that can be further reduced to give Mn II as follows:

≡Mn IV + PIP→ ≡Mn IV -PIPad → ≡Mn III /Mn II -PIP + → Mn II + PIPox (7) As seen in Figure 3a, PIPox concentration in the effluent solution reached its maximum, and then decreased after ∼175 PV. Prior to flow-interruption, the BTC of PIPox followed the outflow pH values, as PIPox binding to minerals is pH-dependent. However, the peak area of LC/MS data corresponding to PIPox was not constant (no-steady-state values) during the course of the experiment. Increasing the residence in the column with flow-interruption, decreased PIP concentration but increased that of PIPox. When the flow was resumed, PIP concentration reached again a plateau, with a steady-state value lower than that before flow interruption (0.9 to 0.8). High

MnO2 content exhibited greater removal ability of PIP and more Mn(II) generation. For example, a higher k value, first-order degradation rate coefficient (including sorption and oxidation), was obtained in the 0.1 MGCS (k =2.1×10 -4 min -1 ) compared to 0.05 MGCS (k =1.4×10 -4 min -1 ), by:

𝑘 = - 𝐼𝑛( 𝐶𝑎 𝐶 𝑏 ) 𝑡 (8)
Here, C is the PIP effluent concentration before (Cb) and after (Ca) flow-interruption, and t is the duration of interruption (24 h).

The shape of the breakthrough curve of Mn(II) in the 0.1 MGCS column was similar to that of 0.05 MGCS column. However, Mn(II) did not exhibit breakthrough with PIP (as the 0.05 MGCS column) and was only detected after injection of ~300 PV. This delayed Mn(II) breakthrough corresponds to an increase in the outflow pH value (see Fig. 3b), and thus can be explained by increasing in Mn(II) binding onto goethite with increasing pH (See batch data in Fig. S7). The effluent concentration of Mn(II) thereafter reached a plateau-like, steady-state, value when the pH decreased down to the inflow pH (~5.2). In MCS no Mn(II) desorbed into the effluent solution (Fig. S8). The presence of dissolved Mn(II) in outflow solutions of MGCS columns (0 μM in MCS column vs. 2.5 μM in 0.1 MGCS column at pH 5.2) suggests that the presence of goethite altered Mn(II) uptake by MnO2 at this pH value, and thus increased its mobility through the column system.

This was confirmed further by Mn(II) batch adsorption data on MCS and MGCS (Fig. S9), where 70% of dissolved Mn(II) were removed by MCS while only 40% was removed with MGCS under the same experimental conditions (See Fig. S9). Additional batch experiments showed that PIP was continuously removed (sorption + oxidation) by MGCS, yet only Mn(II) (no PIPox) was detected in solution (Fig. S10). As observed in the column system, the presence of goethite likely ensured preferential adsorption of PIP or PIPox over Mn(II) onto MGCS at pH 5.2. This aligns with our batch adsorption tests (Fig. S7) revealing strong PIP and weak Mn(II) loadings at this pH value.

PIP binding was also lower and Mn(II) binding greater at larger pH, and even because competitive sorption at pH > 6. Taken together, these findings confirmed that interactions between positively charged goethite (PZC 9.1) and negatively charge MnO2 (PZC 2.4) particles decreased overall cation adsorption in the MGCS system. As a result, dissolved Mn(II) ion was flushed out of the column, thus preventing further interactions with MnO2 and mitigating surface passivation, which is generally observed in MnO2-based redox reactions (e.g. as in MCS column) [START_REF] Remucal | A Critical Review of the Reactivity of Manganese Oxides with Organic Contaminants[END_REF][START_REF] Pokharel | Water Flow and Dissolved Mn(II) Alter Transformation of Pipemidic Acid by Manganese Oxide[END_REF][START_REF] Charbonnet | Chemical Regeneration of Manganese Oxide-Coated Sand for Oxidation of Organic Stormwater Contaminants[END_REF] . Indeed, it has been reported that Mn(II) binding at the MnO2 surface may decrease the oxidation rate of organic compounds because (i) Mn(II) may block redox reactive sites on the oxide surface, preventing adsorption of the organic compound or competitively reacting with MnO2 and (ii) surface bound Mn(II) may decrease the average oxidation state of MnO2, and therefore slow the rate of electron transfer [START_REF] Remucal | A Critical Review of the Reactivity of Manganese Oxides with Organic Contaminants[END_REF][START_REF] Pokharel | Water Flow and Dissolved Mn(II) Alter Transformation of Pipemidic Acid by Manganese Oxide[END_REF][START_REF] Charbonnet | Chemical Regeneration of Manganese Oxide-Coated Sand for Oxidation of Organic Stormwater Contaminants[END_REF][START_REF] Li | Coupled Effects of Mn(II), pH and Anionic Ligands on the Reactivity of Nanostructured Birnessite[END_REF] . This may explain the higher reactivity of the MGCS system in total PIP removal with respect to MCS. This observation is consistent with our modeling result since setting μs = 0 can well fit the BTC of PIP at pH 7 (Table S2).

PIP transport at two pH values

No oxidation occurred during the first stage, but when the residence time is increased, Mn(II)

and PIPox were detected upon flow resumption. The PIP relative concentration drops to 0.6 at pH 7 but only to 0.8 at pH 5.2 when the flow was resumed (Fig. 4a). According to Eq. 8, more PIP was removed and a higher k value was obtained during flow interruption period at pH 7 (1.4×10 -4 min - 1 at pH 5.2, 3.5×10 -4 min -1 at pH 7, Table S3). As only sorption happened in the first step, we suppose that the pristine MnO2 surfaces may enable more PIP oxidation during flow interruption period. Furthermore, less MnO2 passivation can be expected, as more Mn(II) can be adsorbed by goethite at pH 7 (see batch data in Fig. S7).

In summary, both experimental and modeling results show that binary mixtures of manganese oxides and goethite are capable of oxidizing and removing PIP more efficiently than in the single phase. MGCS may overcome the major drawbacks of MCS to be used as a potential geomedia for antibiotic removal. Indeed, preferential adsorption of Mn(II) on negatively charged MnO2, and the progressive build-up of Mn(II) in the column decreased the reactivity of the MCS column over breakthrough time. However, MGCS preferential adsorbed PIP or PIPox over Mn(II) and thereby reduced the passivation effect by dissolved Mn(II).

Environmental significance

This study contributed to mounting evidences that the environmental fate of pollutants can not be predicted based on the sorption/oxidation data of single minerals. A thorough examination of the redox reactivity within complex mineral assemblages under both batch and continuous flow conditions is necessary for an accurate assessment of contaminant transport in natural environments (e.g. soils and sediments) or engineered infiltration systems (e.g. MAR). Here, we showed that coexisting minerals, in our case goethite, can alter the overall reactivity of the redox-active MnO2.

In particular, interactions between the positively charged goethite and the negatively charged MnO2 particles decreased Mn(II) surface loadings, thus facilitating its mobility through the column. In addition to advancing ideas on environmental processes, knowledge that goethite-MnO2 interactions decrease MnO2 passivation could be used to design novel geomedia filters. Fe and Mn binary oxide may overcome the major drawbacks of Mn-oxides to be used as a potential geomedia for antibiotic removal. As manganese oxides have the potential to be applied as filter to prevent organic contaminants from percolating into the groundwater sources in both natural soils and artificial infiltration systems, this work could help in designing efficient geomedia in treatment technologies (industrial and/or municipal wastewater, agricultural runoff, stormwater, etc.). Those contaminated systems contain diverse organic groups such as pharmaceuticals and personal care products, pesticides and detergents, with varying concentrations. Therefore, the amount MnO2 and/or goethite coated on sand should be optimized to further enhance the reactivity and longevity of geomedia, and prior to the application of GMCS in infiltration systems. Finally, as Fe and Mnoxides may co-exist with each other as particulate coatings, the transport model developed here will help in understanding fate and transformation of emerging compounds in natural environments such as soils and sediments.

Supporting Information

Synthesis of minerals and coatings materials; pH dependent PIP and Mn(II) adsorption onto GCS;

Kinetics of PIP removal with 0.05 GMCS; Kinetic sorption of Mn(II) on MCS and 0.05 GMCS;

PIP and PIPox detection methods; SEM images of GCS, 0.05 MGCS, 0.1 MGCS; Breakthrough curves of pH in the different MnO2 content packed columns.

Author Contributions † T.L. and R.P. contributed equally to this work.

Notes

3. Results and Discussion 3 . 1 .Figure 1 .

 311 Figure 1. PIP Breakthrough curves MnO2-bearing columns (0.60 mg Mn/g MCS; 0.29 mg Mn/g

Figure 2 .

 2 Figure 2. Breakthrough curves of a) PIP, Mn(II), and b) pH in the 0.05 MGCS column. The

Figure 3 .

 3 Figure 3. Breakthrough curves of (a) PIP and PIPox (peak area of PIP by-product; M-26) and (b)

Figure 4 .

 4 Figure 4. Breakthrough curves of (a) PIP and PIPox (peak area of PIP by-product; M-26) and (b)

  1 MGCS) exhibited breakthrough at 81 PV, achieved a brief steady-state just below ~200 PV at C/C0 ~ 0.45 and a final steady-state at C/C0 ~ 0.91, just as in MCS, after 744 PV. However, halving Mn loadings to 0.29 mg Mn/g in 0.05 MGCS produced BTC attributes intermediate to those of GCS and MCS, with the breakthrough point of PIP at 45 PV and a steady breakthrough at C/C0 ~ 0.94 at 308 PV.

The authors declare no competing financial interest.

Acknowledgements

The authors acknowledge the support of the Institut Universitaire de France, the Swedish Research Council (2020-04853), the French National Research Agency via the INFLOW project (ANR-21-CE29-0008-01) and the CNRS (IEA 2018-2020). We also thank the China Scholarship Council for a Ph.D. grant and Région Bretagne for a mobility grant for an extended research stay at Umeå University.