Dr Daniel Lee

Dr Małgorzata Wolska-Pietkiewicz

Saumya Badoni

Dr Agnieszka Grala

Janusz Lewiński

Gaël De Paëpe
email: gael.depaepe@cea.fr

Dr G De

Prof. J Lewiński

Disclosing Interfaces of ZnO Nanocrystals Using Dynamic Nuclear Polarization: Sol-Gel versus Organometallic Approach

Keywords: dynamic nuclear polarization, nuclear magnetic resonance, surface characterization, synthesis, zinc oxide

The unambiguous characterization of the coordination chemistry of nanocrystal surfaces that have been produced by a wetchemical synthesis presently remains a highly challenging issue. Here, zinc oxide nanocrystals (ZnO NCs) coated by monoanionic diphenyl phosphate (DPP) ligands were derived by a traditional sol-gel process and a one-pot self-supporting organometallic (OSSOM) procedure, and advanced atomic-scale characterization through dynamic nuclear polarization (DNP-)enhanced solid-state nuclear magnetic resonance (ssNMR) spectroscopy has notably enabled resolving their vastly different surface-ligand interfaces. For the OSSOM-derived NCs, DPP moieties form stable and strongly-anchored µ2-and µ3-bridgingligand pairs that are resistant to competitive ligand exchange processes. Contrastingly, the sol-gel-derived NCs contain a wide variety of coordination modes of DPP ligands and a ligand exchange process takes place between DPP ligands and glycerol molecules. This highlights the power of DNP-enhanced ssNMR for detailed NC surface analysis and the superiority of the OSSOM approach for the preparation of high quality ZnO NCs.

Zinc oxide (ZnO) is a versatile material of long-standing interest due to its unique catalytic and electro-optical characteristics. 1 The inherent and distinctive physicochemical properties of ZnO nanocrystals (NCs) are dependent on a variety of factors that are largely determined by the applied synthetic procedure and the character of the resulting nanocrystal-ligand interface including intimate interactions on NC surfaces, the surface ligand dynamics, ligand packing density, and their binding mode and/or affinity. In this regard, classical wet-inorganic sol-gel methodology has played a key role in advancing ZnO NC science by providing access to a multitude of tailored nanostructures. 2 While this process is versatile, it showcased some significant drawbacks. Erreur ! Signet non défini.b, 3 For instance, the reproducibility of this method can be hardly regulated as the formation of quantum-sized ZnO NC is kinetically controlled. The lack of direct control over the fast NC formation at the stage of quantum-sized crystals 2a,b likely inhibits both the uniformity of particle morphology and nanocrystal-ligand interface composition, including the density and homogeneity of any ligand shell. [START_REF] Sakohara | Note that colloidal surfaces structure of ZnO NCs derived from sol-gel methodology is not yet well understood and its determination is still challenging[END_REF] It could also be related with an inherently highly-defected and corrugated surface structure, and an unstable resulting nanocrystal-ligand interface (e.g., Gong et al. demonstrated that sol-gel derived ZnO NCs with a stable surface structure could be achieved after a one-month aging process 4f ). An alternative to the omnipresent sol-gel method are highly promising wet-organometallic approaches. 5,6 In this regard, Chaudret and co-workers pioneered the preparation of ZnO NCs, utilizing dicyclohexylzinc as the precursor in the presence of long-chain amines acting as L-type ligands, 5 where the resulting amine-stabilizing layer has the 'dynamic structure '. 5d,7 More recently, we have elaborated the one-pot selfsupporting organometallic (OSSOM) procedure based on the controlled exposition of a [EtZn(X)]-type precursor (X = monoanionic organic ligand) to air leading to ZnO NCs coated with an organic shell composed of surface-anchored X-type ligands. 8 The OSSOM process is thermodynamically controlled and affords stable, bio-safe 8e and well-passivated ZnO NCs with ultra-long-lived luminescence. 8e,9 To gain a better understanding of how the interface between the inorganic core and the organic shell relates to observed synthetic procedure-driven properties, ZnO NCs coated with monoanionic diphenyl phosphate (DPP) ligands were prepared by both the OSSOM and sol-gel methods as representative nanosystems (abbreviated as OM NCs and SG NCs, respectively; for experimental details see the Supporting Information). We selected the diorganophosphate anchoring ligand due to intriguing structural properties and the 100 % naturally abundant NMR-active nucleus of phosphorus, 31 P. Then we applied 9.4 T solid-state NMR combined with magic angle sample spinning and dynamic nuclear polarization (MAS-DNP), 10 which has recently proven invaluable for specialized surface studies, 11 including for quantum dots. 12 In addition, to test the stability of the ZnO NCs toward chemical environment, a solvent matrix containing glycerol was chosen for the MAS-DNP experiments.

STEM micrographs and DLS analysis of the OM NCs show well-dispersed and nearly spherically shaped particles with a core mean diameter of 4.8±0.5 nm (the average NC's size calculated from PXRD is equal to 4.4±1 nm) and a hydrodynamic diameter of 9.6 nm (PDI = 0.083) (see Figure S1 and Figure S2 in the Supporting Information). In contrast, the standard sol-gel method provided significantly larger NCs with a core size of 10-12 nm (10±1.8 nm calculated from PXRD), though their aggregation and irregular shape prevented a more exact size distribution analysis (note that the aggregation and formation of a colloidal suspension of the SG NCs prevented reliable DLS measurements). The PXRD patterns for OM and SG NCs are consistent with a hexagonal wurtzite-type ZnO phase (see Figure S3). Both sets of NCs revealed a broad absorption in the UV region and emission maxima centered at 525 and 555 nm, respectively (see Figure S4 and Figure S5). The FTIR spectra confirm that DPP passivating moieties are deprotonated (see Figure S6), which corroborate the thermogravimetric analysis (see Figure S7). In the TGA profile of the OM NCs only one main decomposition step in the range from 0°C to 500°C is present. On the contrary, the SG system shows a significantly more complex decomposition path. This observation substantiates the different nanocrystal-ligand interfaces for NCs derived from the OSSOM and sol-gel methods, and indicates a more complex structure of organic ligand shell for the SG NCs. The TGA-determined surface coverage of OM and SG NCs were ca. 4-5 ligands/nm 2 and 12 ligands/nm 2 , respectively. [START_REF]Note that higher ligand packing density for the-SG NCs could be defined by both roughness of surface structure and/or[END_REF] A comparison of the characteristic properties of the OM and SG NCs is presented in Figure S8 in the SI.

Subsequently, the structures of the organic ligand shells were compared using NMR spectroscopy, which has recently been shown to be particularly powerful in this regard. 14 Figure 1 shows the { 1 H-} 31 P cross-polarization (CP) MAS NMR spectra of OM and SG NCs (Figure 1a and1d) and corresponding DNPenhanced spectra recorded for freshly wetted samples (Figure 1b and 1e) as well as after sample storage at -18 °C for 5 and 3 days, respectively (Figure 1c and1f). The NMR spectra highlight that the surface of the OM NCs is indeed functionalized by monoanionic diphenyl phosphate ligands, evidenced by 31 P NMR signals at { 31 P} ≈ -11 and -12 ppm (F.W.H.H. ~120 Hz) that are inconsistent with pure DPP-H (see Figure S9a), whereas they are consistent with the chemical shift of bridging DPP, as observed in model organozinc molecular complexes. 15 The relatively narrow linewidth of the two 31 P peaks indicates a rather ordered structure at the surface. In addition, the time-dependent spectra show that the OM NCs remain stable (Figure 1b and1c), which indicates that the resulting nanocrystal-ligand interface is robust.

In contrast, the respective spectra of the SG NCs (Figure 1d-f) are far more complex. The initial, "pre-wetting" spectrum (Figure 1d) features unsymmetrical broad signals ranging from approximately 15 to -15 ppm, indicating a dramatically different organic-inorganic interface to that in OM NCs. Furthermore, the spectrum of the "just-wetted" SG NCs (Figure 1e) consists of evolving broad contributions (ranging from { 31 P} ≈ -5 to -15 ppm) and also the emergence of narrow peaks at { 31 P} ≈ -11 and -12 ppm (corresponding to those observed for the OM NCs) along with an additional signal at ≈ -9 ppm (Figure 1e). After 3 days' storage at -18 ºC, the spectrum has significantly evolved (Figure 1f) to leave the narrow signals at { 31 P} ≈ -11 and -12 ppm (as a minor component) and to produce a separate intense signal at ≈ -10 ppm (as a major component). The latter signal is associated with the solvent-matrix-induced release of DPP species from the surface of the SG NCs in the protonated form as DPP-H (Figure 2), which results in the same { 31 P} as observed for the pure DPP-H pro-ligand (see Figure S9a).The relatively narrow linewidth of the signal at { 31 P} ≈ -10 ppm suggests that although the ligand has been detached from the surface, it is in an ordered environment (i.e. DPP-H molecules interact with the solvent matrix). A broad peak would be expected for a lessordered environment, such as found in a DPP-H solution (see Figure S9a). A large range of 31 P chemical shifts and the observed changes in the time-dependent { 1 H-} 31 P cross-polarization (CP) MAS NMR spectra data clearly indicate that SG NCs possess a corrugated NC surface structure composed of islands and ridges with variously coordinated, and potentially multi-layered, organic ligands (Figure 2). Moreover, the data demonstrate that the organic-inorganic interface of these NCs is not stable toward chemical environment and a ligand exchange process takes place between DPP ligands and glycerol molecules (see Figure 2). [START_REF] Lin | Potentially glycerol might play an analogous role as catechol molecules, which provide an effective and versatile way to modify sol-gel derived zinc oxide surfaces by means of ligand exchange reactions a)[END_REF] Possible hydrogen-bond formation between the resulting anionic glycerol species and DPP-H molecules as well as between glycerol and the residual DPP ligands present on the surface could force some short range order. The next-and second nextneighboring molecules probably also align similarly, leading to the formation of a multi-layered structure described previously as a 'swollen' shell (i.e. the organic shell is not built up by a closelypacked monolayer of DPP molecules but is rather a swollen coating composed of DPP and solvent molecules). 4e Moreover, for the time-evolved SG NCs, the small relative intensities of the narrow signals from the remaining surface-bound DPP ligands compared to the signal from the surface-detached DPP-H moieties suggests that the ZnO surface produced from the sol-gel synthesis is characterized by the presence of only very limited and randomly distributed robust surface islands with an ordered and stable ligand arrangement, which we have termed "cold spots". These sparse and relatively stable spots then have a similar local structure to that of the entire surface of the ZnO NCs derived from the OSSOM approach (Figure 2). An estimation of the amount of detached DPP-H molecules can be obtained from the 31 P NMR spectrum of Figure 1f (assuming that the CP dynamics are similar for surface-bound and free ligand moieties). This analysis (see Figure S10) shows that approximately one quarter of the ligands remain surface-bound, half are in the semi-ordered swollen shell, and the remaining quarter are randomly distributed in the solvent.

To further characterize the effect of the glycerol/water solvent matrix on the DPP ligand shell in the SG and OM NCs, time-dependent DNP-enhanced { 1 H-} [START_REF]Note that higher ligand packing density for the-SG NCs could be defined by both roughness of surface structure and/or[END_REF] C CPMAS NMR spectra (Figure 3 and Figure S11) along with DNP-enhanced 2D 13 C-31 P correlation spectra (Figure S13) were acquired. The 13 C NMR data indicate that the OM sample remained unaffected during sample storage and the surface-bound DPP ligands are highly ordered, with at least 20 [START_REF]Note that higher ligand packing density for the-SG NCs could be defined by both roughness of surface structure and/or[END_REF] C resonances for the DPP moieties of OM NCs (suggesting more than one DPP environment, see Figure 3). In contrast, the respective spectra of the SG NCs (Figure 1d) are far more complex. There is a change in the [START_REF]Note that higher ligand packing density for the-SG NCs could be defined by both roughness of surface structure and/or[END_REF] C NMR signals stemming from glycerol for the SG sample with time (Figures 3c and3d). Two narrow peaks (denoted by asterisks on Figure 3d) are observed to evolve from the broad peaks typical of a glycerol/water glassy matrix. These narrow peaks together with the pattern characteristic for DPP-H molecules (particularly when compared to pure pro-ligand, see Figure S9b) infer the presence of an ordered system within a 'swollen' shell around SG NCs. Furthermore, a close proximity is detected between 31 P from surface-detached DPP-H moieties ({ 31 P} ≈ -10 ppm) and [START_REF]Note that higher ligand packing density for the-SG NCs could be defined by both roughness of surface structure and/or[END_REF] C of ordered glycerol in 2D [START_REF]Note that higher ligand packing density for the-SG NCs could be defined by both roughness of surface structure and/or[END_REF] C-31 P correlation spectra (see Figure S13) but this is not the case for surface-bound DPP species, which strongly supports this concept of a 'swollen' organic shell 4e surrounding SG NCs. Strikingly, the [START_REF]Note that higher ligand packing density for the-SG NCs could be defined by both roughness of surface structure and/or[END_REF] C NMR data also shows that the sol-gel approach, which used zinc acetate as a precursor, results in residual acetate as well as DPP ligands on the surface of ZnO NCs (see Figure S11). The DPP ligands occupy the anticipated cold spot and residual acetates are likely encapsulated in niches on corrugated surface structures of the SG NCs. The latter observation corroborates earlier studies reported by Peukert et al. 4b in which it was evidenced that acetate moieties could be continuously detached from organic coatings upon purification and only a small amount of coordinated acetate remains at ZnO NC surfaces.

The intimate interactions between organic ligands and NC surfaces (binding mode and/or affinity etc.) are crucial for the structure-property relationship of ZnO NCs. Thus, for a more detailed study of the organic ligand shell, 2D NMR spectroscopy was employed. Figure 4 shows DNP-enhanced 2D 31 P homonuclear dipolar correlation spectra of the wetted and aged OM NCs, recorded using the S3 recoupling sequence 17 with short (Figure 4a) and long (Figure 4b) dipolar recoupling times. This experiment produces peaks that share a common frequency (or double-quantum (DQ) chemical shift) in the horizontal dimension for nuclei that are spatially close to one another. Interestingly, a short recoupling time (Figure 4a) shows that the two 31 P signals with { 31 P} ≈ -11 and -12 ppm stem from two discrete but adjacent DPP bridging ligands, denoted here as P1 and P2. Moreover, there is no evidence in this spectrum of these sites showing autocorrelation peaks, i.e. a surface-bound DPP is not spatially close to another DPP moiety with the same conformational environment (and thus chemical shift). Therefore, the surfacebound DPP is only spatially very close to a second DPP moiety that has a different conformation, likely resulting from pairs on polar facets of the NCs. At longer recoupling times (Figure 4b) connections between P1 and another P1 site as well as P2 and other P2 sites become present. This means that there is some proximity between P1/P2 and other P1/P2 environments but that P1 environments are much closer to dissimilar P2 environments. Comparative 2D 31 P homonuclear dipolar correlation spectra for the SG NCs (i) show that the surface-dissociated (solvated or swollen shell) DPP-H moieties with { 31 P} = -10 ppm display an autocorrelation peak (at { 31 PDQ} = -20 ppm, see Figure S14) arising from a proximity between these released molecules and (ii) exhibit P1-P2 connections at short recoupling times as well as P1-P1 and P2-P2 connections at longer recoupling times, as found for the OM NCs. This latter observation substantiates the conclusion of sparse cold spots on the surface of the SG NCs having the same stable ligand arrangement as the ZnO NC surfaces produced from the OSSOM approach.

For the estimation of distances between 31 P nuclei, and thus between DPP moieties, multiple 2D 31 P homonuclear dipolar correlation experiments were performed with varying dipolar recoupling times (mix). Plotting the intensity of the OM NC P1-P2 correlation peaks (at { 31 PDQ} = -23.4 ppm) as a function of mix and comparing the resulting curve to numerical simulations using SPINEVOLUTION 18 software gives a good fit for a discrete internuclear P-P distance of 4.1±0.2 Å (see Figure S15a). The presence of surface dianionic tetraphenyl pyrophosphate moieties (resulting from a condensation reaction between two DPP-H pro-ligands) can be ruled out since this would result in a 31 P-31 P internuclear distance of approximately 3 Å. The presence of monoanionic ligands, either monodentate or bidentate (, 2- 1 : 1 or 3-2: 1 bridging coordination modes), would result in 31 P internuclear distances either <3.5 or >4.9 Å between DPP ligands on wurtzite NCs, except if pairs of 2-3 ligands are formed on wurtzite (0001) surfaces (see Figure S16). Therefore, with the estimated P1-P2 distance of ~4.1 Å, some surface DPP moieties must be arranged close together, forming these 2-3 pairs (on wurtzite (0001) surfaces), possibly stabilized through - interactions of the DPP aromatic rings. Accordingly, P1 and P2 must be from 2- 1 : 1 and 3-2: 1 ligands (not necessarily respectively). Taking this surface structure, depicted in Figure 4d, for the numerical simulations (rather than simple P-P pairs) results in a revised estimate for the P3-P2 internuclear distance, giving 4.4±0.2 Å (see Figure 4c). A P1-P1 (or P2-P2) distance from the proposed wurtzite (0001) ZnO-DPP surface configuration would be >6 Å and from other polar surfaces (such as (101 ̅ 1 ̅ ), see Figure S16) it would be at least 5 Å. This is what is found from comparing numerical simulations to experimental data (see Figure 4c), using a similar correlation peak analysis as above. This surface characterization indicates that a very compact coverage is possible for the OM NCs, in agreement with the TGA analysis that gives 4-5 ligands per nm 2 . It could thus be proposed that the thermodynamically-controlled OSSOM approach and the utility of monoanionic stabilizing ligands, which could strongly and formation-selectively adsorb to the polar (0001) face, allow for lower aspect-ratio (i.e. quasi-spherically shaped) ZnO NCs with significantly more [0001] planes present. This is consistent with the literature 19 and the observed relatively high surface coverage of the ZnO NCs derived from the organometallic approach, with this type of information being a considerable challenge to currently obtain for organic-ligand-coated small-sized NCs using electron microscopy techniques.

The same correlation peak analysis was also performed for the surface-detached DPP-H observed for the SG NCs, which indicates one large internuclear P-P distance of ~10 Å (see Figure S15b). This is consistent with an ordered swollen shell containing glycerol molecules hydrogen-bonded between DPP molecules (see schematic in Figure S17). It should be noted that no interactions between detached and surface-bound species were observed. The surface characterization of the wetted SG NCs then indicates that a mixture of sparse, randomly distributed surface cold spots containing stable µ2-and µ3-DPP-bridgingligand pairs, and above-surface ordered DPP-H molecules in probable multi-layers, consistent with the TGA analysis that gives the large number of 12 ligands per nm 2 of NC surface.

In conclusion, DNP-enhanced solid-state NMR spectroscopy proves extremely pertinent for detailed characterization of nanocrystal-ligand interfaces, here highlighting large differences between DPP-coated ZnO NCs prepared by the organometallic approach and the traditional solgel procedure. It has been shown that the OSSOM approach provides ZnO NCs with a highly-ordered surface ligand arrangement of µ2- 1 : 1 -DPP1 and µ3-µ2: 1 -DPP2 bridging ligands, which are paired-up on the surface and which remain unaffected during sample storage and even in the presence of glycerol as a highly competitive capping ligand. In contrast, ZnO NCs produced via the sol-gel method exhibit variously-coordinated DPP ligands and a time-dependent surface restructuring process with a displacement of the majority of the ligands from the surface, creating an ordered swollen shell containing DPP-H and solvent molecules, signifying a corrugated surface morphology of these NCs and substantially labile surface-ligand interactions. Moreover, in the case of SG NCs, the presence of randomly distributed robust surface islands with an ordered and stable ligand arrangement were evidenced.

Figure 1 .

 1 Figure 1. Time-dependent room temperature (a, d) and 105 K DNP-enhanced (b, c, e, f) { 1 H-} 31 P CPMAS NMR spectra of (a, b, c) organometallic and (d, e, f) sol-gel derived ZnO NCs. (b, e) Spectra recorded within 30 minutes of addition of glycerol/water (g/w) solution and (c, f) after storage at -18 °C.

Figure 2 .

 2 Figure 2. Schematic representation of the organic ligand shell of OM and SG NCs before (a) and after (b) wetting and aging with a glycerol-based matrix. The snowflake represents a surface portion with an ordered and stable ligand arrangement (i.e. stable µ2-and µ3-DPP-bridging-ligand pairs), termed here as cold spots. Residual acetate moieties present on the surface of SG NCs are omitted for clarity.

Figure 3 .

 3 Figure 3. Time-dependent 105 K DNP-enhanced { 1 H-} 13 C CPMAS NMR spectra. (a, b) Organometallic and (c, d) sol-gel derived ZnO NCs. "G" and "*" denote signals from amorphous and crystalline glycerol, respectively, and " †" denotes spinning side bands. The MAS frequency for (a) was 10 kHz, whereas 13.889 kHz was used for (b-d).

Figure 4 .

 4 Figure 4. Representative DNP-enhanced 31 P-31 P S3 dipolar correlation spectra recorded with a total S3 recoupling time, mix, of (a) 2.3 ms and (b) 23 ms, along with (c) a plot showing the relative intensities of P1-P2 and P1-P1 and P2-P2 correlations peaks as a function of mix, with corresponding SPINEVOLUTION simulations (dashed lines) based on the internuclear distances given and on the schematic wurtzite (0001) surface structure shown in (d).

Acknowledgements

J.L. and M.W.-P. acknowledge the Foundation for Polish Science Team Program co-financed by the European Union under the European Regional Development Fund POIR.04.04.00-00-20C6/16-00 (TEAM/2016-2/14) and G.D.P. acknowledges the French National Research Agency (ANR-12-BS08-0016-01, ANR-11-LABX-0003-01 and RTB) and the European Research Council (ERC-CoG-2015, No. 682895), for financial support. We thank Dr. J. Grzonka (Faculty of Materials Science and Engineering, Warsaw University of Technology) for assistance with STEM imaging.

COMMUNICATION

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COMMUNICATION

Strong and stable. ZnO nanocrystals derived through a one-pot self-supporting organometallic (OSSOM) approach produce a stable and organized surfaceligand union. Conversely, a more traditional sol-gel approach provides a limited presence of random but stable cold spots with the majority of native ligands having their surface-supporting roles taken by foreign solvent molecules, resulting in a swollen shell around the ZnO. This highlights the superiority of the OSSOM approach for the preparation of high quality quantum-sized ZnO crystals.


Bénédicte Lebret

Sihem Lhuisset

Etienne Labussiere

Anne Connan

Isabelle Louveau

Combining genetic and nutritional strategies

come   L'archive ouverte pluridisciplinaire


Behshad Koohbor

Jacques Deparis

Hossein Davarzani

Philippe Leroy

Stéfan Colombano

Modeling coupled DNAPL migration and complex resistivity evolution in saturated porous media

Keywords: Induced Polarization, Dense Non-Aqueous Phase Liquid (DNAPL), Two-Phase flow in porous media, COMSOL Multiphysics®, Complex resistivity

Abstract

Induced Polarization (IP) is the measurement of the response of electrical conductivity (or resistivity) to an applied range of frequency (usually between a few millihertz to a few tens of kilohertz). It can be applied as a non-intrusive method to investigate Dense Non-Aqueous Phase Liquid (DNAPL) contamination/remediation process. Multiphase flow in porous media can be coupled with the electrical current to simulate the process of DNAPL migration and deliver a broader view in space and time esp. when the results are supported by field measurements or laboratory experiments. In addition to previous works in the literature regarding the coupled simulations of two-phase flow and in-phase electrical resistivity, in this work, we aimed to perform coupled simulations of two-phase flow in porous media and sinusoidal electrical current (i.e. frequency ranging from 0.7Hz to 3000Hz) via the application of complex electrical resistivity.

The domain and the scenarios of the simulations (i.e. fill-up and pumping) are based on previously published laboratory experiments [START_REF] Colombano | Comparison of thermal and chemical enhanced recovery of DNAPL in saturated porous media: 2D tank pumping experiments and two-phase flow modelling[END_REF][START_REF] Colombano | Comparison of thermal and chemical enhanced recovery of DNAPL in saturated porous media: 2D tank pumping experiments and two-phase flow modelling[END_REF]. The simulations are developed in 3D and are performed in COMSOL Multiphysics®. The fluid flow equations are, first, discretized (i.e. by Finite Element Method) and solved using the pressure-saturation approach and by application of the Van Genuchten-Mualem constitutive relationships. Then, the saturation of water and the DNAPL is translated into in-phase and quadrature conductivities via the chosen petrophysical relationships [START_REF] Vinegar | Induced polarization of shaly sands[END_REF][START_REF] Glover | A generalized Archie's law for n phases[END_REF] and then the system of partial differential equations governing the electrical current (i.e. Amper's law) is solved and the electrical potential is calculated in the domain for each time-step. The electrical potential, then, can be translated into complex resistance and then to complex resistivity. The results of the fluid flow and the phase transport are validated against the results of laboratory experiment measurement. Figure 1 shows selected results of the phase transport validation for the pumping scenario. The results of the complex resistivity measurements and simulations are validated and one of the electrical injection configurations for the fill-up scenario is selected and shown in Figure 2.

The used formulation and tool for simulation of the fluid flow (i.e. pressure-saturation in 3D) has been discussed briefly to give insights regarding the application of three-phase flow in future studies. The choice of petrophysical relationships for in-phase and quadrature conductivity are verified and are consistent with the experimental study, yet the exponents of the water in the petrophysical relationship were estimated to be lower than those reported previously by the experimental study [START_REF] Colombano | Comparison of thermal and chemical enhanced recovery of DNAPL in saturated porous media: 2D tank pumping experiments and two-phase flow modelling[END_REF]. The simulations and the experiments are in complete accordance with each other in the parts of the domain where the saturation of DNAPL is relatively low (esp. in the cone of depression in the pumping scenario). The simulations also predict the time of evolution of in-phase and quadrature resistivity (i.e. when DNAPL front passes the injection and potential electrodes) with satisfying accuracy. However, the points associated with high saturation of DNAPL (i.e. close to Sn=1-Srw) show high errors between the results of in-phase resistivity calculated simulations and the previously reported experiments. Yet, this error is decreased when comparing the quadrature resistivities. The present study can be regarded as a preliminary study toward further applications of coupled IP-Multiphase flow for more accurate detection and monitoring of non-aqueous phase liquids. We suggest that our choice of tool/approach can be extended to larger-scale studies for further investigation.

Figure 1 .Figure 2 .

 12 Figure 1. Simultaneous representation of experimental measurements and two simulation approaches for the 150 ml.min -1 flowrate for: (a) distribution of water and DNAPL at the end of pumping scenario and (b) temporal evolution of the retrieved DNAPL


Honoré Houéménou
email: houemenou.honore@univ-avignon.fr

Sarah Tweed

Gauthier Dobigny

Daouda Mama

Abdoukarim Alassane

Roland Silmer

Milanka Babic

Stephane Ruy

Alexis Chaigneau

Philippe Gauthier

Stéphane Ruy

Akilou Socohou

Henri-Joël Dossou

Sylvestre Badou

Marc Leblanc

Affiliations

Degradation of groundwater quality in expanding cities in West Africa. A case study of the unregulated shallow aquifer in Cotonou

Keywords: Groundwater, sewerage and septic tank contamination, salinization, urbanization, recharge and discharge

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

With cities in developing countries expanding at unprecedented rates, ensuring clean water supplies for all inhabitants is becoming increasingly more challenging. This is particularly the case in more impoverished urban areas, where infrastructure development often lags behind population growth [START_REF] Lapworth | Urban Groundwater Quality in Sub-Saharan Africa: Current Status and Implications for Water Security and Public Health[END_REF]. In addition, there often exist two types of water supplies: firstly, there is the official water supply that is monitored, treated and comes at a cost for consumers; and then there is the second unregulated water supply that is often sourced from wells accessing shallow groundwater that is unmonitored, untreated but free.

The health risks in using the unregulated groundwater resource for domestic purposes, including drinking water supplies, is high due to water quality issues in many urban areas (e.g. [START_REF] Ouedraogo | Mapping the groundwater vulnerability for pollution at the pan African scale[END_REF][START_REF] Hassane | Aquifères superficiels et profonds et pollution urbaine en Afrique : Cas de la communauté urbaine de Niamey[END_REF]. The same factors driving the demand for water supplies, accelerated urban growth and the expansion of informal settlements, are also significant drivers of groundwater pollution (UNESCO, 2017). One of the many threats to shallow groundwater quality in cities is from sanitary wastewater and solid waste disposal [START_REF] Lu | Impacts of Soil and Water Pollution on Food Safety and Health Risks in China[END_REF]. Uncontrolled seepage of wastewater from septic tanks and human activities as well as infiltration of urban stormwater lead to groundwater contamination [START_REF] Dhanasekarapandian | Spatial and temporal variation of groundwater quality and its suitability for irrigation and drinking purpose using GIS and WQI in an urban fringe[END_REF]. Many parts of the world are now reporting groundwater and surface water nitrate pollution issues [START_REF] Roy | Identifying the significant factors that influence temporal and spatial trends in nitrate concentrations in the Dorset and Hampshire Basin Chalk aquifer of Southern England[END_REF][START_REF] Stuart | Screening for long-term trends in groundwater nitrate monitoring data[END_REF]Zhang et al., 2014;[START_REF] Ogrinc | Evaluation of geochemical processes and nitrate pollution sources at the Ljubljansko polje aquifer (Slovenia): A stable isotope perspective[END_REF]. For example, in the Coimbatore city, India, population growth, pit latrines and septic tanks, industrial effluents, and irrigation water return flows are the main sources of groundwater contamination [START_REF] Selvakumar | Hydrogeochemical characteristics and groundwater contamination in the rapid urban development areas of Coimbatore, India[END_REF]. In Florida, the proximity of wells to septic tanks contributes to increasing fecal coliform, nitrate and phosphate concentrations during wet season compared with the dry season [START_REF] Arnade | Seasonal Correlation of Well Contamination and Septic Tank Distance[END_REF]. Many studies have identified sewerage and latrine contamination as a significant public health issue due to the resultant presence of faecal bacteria in waters such as Escherichia coli, faecal Streptococci, Salmonella and Shigella [START_REF] Boukari | Fonctionnement du système aquifère exploité pour l'approvisionnement en eau de la ville de Cotonou sur le littoral béninois[END_REF][START_REF] Odoulami | Qualité de l'eau de consommation et maladies hydriques dans la commune de Ze[END_REF][START_REF] Yadouléton | Assainissement environnemental à Cotonou et lutte contre le choléra[END_REF]. During this study, for the first time, the seasonal variation in the contamination of waters by sewerage and latrine contaminantion is investigated using environmental tracers.

In addition, shallow groundwater resources in coastal cities are particularly vulnerable to salinity problems due to mixing with saline surface waters and seawater intrusion [START_REF] Barker | Processes affecting groundwater chemistry in a zone of saline intrusion into an urban sandstone aquifer[END_REF][START_REF] Cary | Origins and processes of groundwater salinization in the urban coastal aquifers of Recife (Pernambuco, Brazil): A multi-isotope approach[END_REF][START_REF] Petelet-Giraud | Coastal Groundwater Salinization: Focus on the Vertical Variability in a Multi-Layered Aquifer through a Multi-Isotope Fingerprinting (Roussillon Basin, France)[END_REF][START_REF] Najib | Contribution of hydrochemical and geoelectrical approaches to investigate salinization process and seawater intrusion in the coastal aquifers of Chaouia, Morocco[END_REF][START_REF] Liu | Hydrogeochemical Characteristics in Coastal Groundwater Mixing Zone[END_REF]. For example, in Ho Chi Minh city, Vietnam, the groundwater resources are under threat due to saltwater intrusion in the shallow aquifer [START_REF] Ngo | The sustainability risk of Ho Chi Minh City, Vietnam, due to saltwater intrusion[END_REF].

In this study, we use the example from Cotonou, Benin, to identify processes resulting in nitrate and salinity contamination of a city's unmonitored and untreated shallow groundwater resource. The complexity of contamination processes in evolving urban environments makes it difficult to study the risks of shallow groundwater quality. This can be due to both natural seasonal shifts from climatic and environmental influences, and significant anthropogenic influences on the hydrogeological system. In this study, we analyse the distribution and concentration of major ions and stable isotopes (δ²H and δ 18 O) to investigate the temporal variation in groundwater quality across 3 sites in Cotonou. These 3 neighbourhoods were selected to represent contrasting hydrogeological environments: (i) a neighbourhood (St Jean) where there is no surface inundation; (ii) a neighbourhood (Ladji) bordering Lake Nokoué which overflows towards the end of the wet season; and (iii) a neighbourhood (Agla) located in a swamp low land and is subject to inundation during both the small and large wet seasons. In doing so, we identify hydrological conditions and seasons when groundwater is at its greatest vulnerability in terms of salinization and latrine contamination. At each site, there are wells where local inhabitants have access to unmonitored and untreated shallow groundwater for domestic consumption.

Study Area

Location and climate

The city of Cotonou is bordered by Lake Nokoué to the north, and the Atlantic Ocean to the south. The location of Cotonou and the average monthly interannual rainfall at Cotonou station from 1971 to 2016 are shown in Figures 1 and2. The topography of the city is relatively flat with an altitude varying between 0 m and 6 m [START_REF] Boukari | Fonctionnement du système aquifère exploité pour l'approvisionnement en eau de la ville de Cotonou sur le littoral béninois[END_REF]. The average annual rainfall for Cotonou is 1,300 mm (Yabi et al. 2006). The city's climate is characterised by 4 seasons; main dry season (average rainfall is 25 mm from mid-November to mid-March), main wet season (average rainfall is 152 mm from mid-March to mid-July), small dry season (average rainfall is 55 mm in mid-July to mid-September), and small wet season (average rainfall is 75 mm from mid-September to mid-Novembre).

Aquifer geology

Cotonou is located in the coastal sedimentary basin comprised of Quaternary (Holocene) sediments, which include facies of the littoral plain (sands) and alluvial deposits, underlain by sediments from the Mio-Pliocene (Continental Tenninal), Paleocene and Upper Cretaceous [START_REF] Maliki | Etude hydrogéologique du littoral béninois dans la région de Cotonou (A.O)[END_REF]. Previous studies by [START_REF] Oyédé | Dynamique sédimentaire actuelle et messages enregistrés dans les séquences quartenaires et néogènes du domaine margino littoral du Bénin (l'Afrique de l'Ouest)[END_REF], [START_REF] Maliki | Etude hydrogéologique du littoral béninois dans la région de Cotonou (A.O)[END_REF], [START_REF] Alidou | Rapport technique final du projet "hydrogéologie du quaternaire du sud-bénin[END_REF] and [START_REF] Boukari | Fonctionnement du système aquifère exploité pour l'approvisionnement en eau de la ville de Cotonou sur le littoral béninois[END_REF] have described in detail the different sedimentary units of this coastal sedimentary basin and the distribution are presented in Figure 1. The shallow Quaternary sediments consist predominantly of fine to medium sands (85.5%), silts (5.5%) and clays (9%) [START_REF] Oyédé | Dynamique sédimentaire actuelle et messages enregistrés dans les séquences quartenaires et néogènes du domaine margino littoral du Bénin (l'Afrique de l'Ouest)[END_REF]. The low clay content in these sediments results in the high permeability of the shallow sandy soils [START_REF] Maliki | Etude hydrogéologique du littoral béninois dans la région de Cotonou (A.O)[END_REF], and therefore a high vulnerability of the aquifers to the transfer of surficial pollutants. The clays in Quaternary sediments are constituted by smectite and a kaolinite content, which increases with depth.

The traditional domestic wells were sampled in this study so that we could analyse the water consumed and used by local residents. However, due to the intense pumping of these wells, the fluctuations in hydraulic head are heavily influenced by pumping, therefore we were unable to use the hydraulic head data to infer subsurface flow directions. There has however been previous work that has addressed this question, the work of [START_REF] Maliki | Etude hydrogéologique du littoral béninois dans la région de Cotonou (A.O)[END_REF] and [START_REF] Boukari | Fonctionnement du système aquifère exploité pour l'approvisionnement en eau de la ville de Cotonou sur le littoral béninois[END_REF] focused on the piezometry of the Cotonou water table during the flood and low water periods, and the interactions with the Lake.

It appears from these studies that during the flood period, there is a flow direction of groundwater from the center of Cotonou (piezometric dome) to outlets such as Lake Nokoué, the lagoon, the Atlantic Ocean and swamps. In comparison, during the low-water period it was observed that water from the Lake Nokoué flows into the groundwater aquifer

Sewerage and waste

The city of Cotonou has about 166,433 households and the population evaluated at 679 012 inhabitants in 2013 [START_REF] Insae | Quatrième Recensement Général de la Population et de l'Habitat, mai 2013[END_REF] and is subject to increasing urbanization. The poorer dwellings are located in the neighborhoods along the coastline, along the edges of the Cotonou Channel and Lake Nokoué, and in the swamp areas. In these neighbourhoods, solid and liquid wastes are released into the immediate environment without treatment as illustrated in the Figure 1(c). In addition, they are also scattered in various places of the city where garbage heaps have formed. 78.5% of household wastewater and 33 % of solid wastes are ejected in gardens, streets, gutters, unused wells and empty blocks [START_REF] Insae | Principaux indicateurs socio-demographiques et economiques, mai 2013, synthèse des résultats d'analyse. Rapport[END_REF]. These poorer neighborhoods are also without adequate sanitation systems. In Cotonou 64.9% of households use latrines that are reportedly leak-proof, whereas 13.5% adopt unsafe and non-hygienic practices such as stilt latrines and open defecation. Only 20.8% of the population use septic tanks, which are generally evacuated by drainage structures [START_REF] Insae | Principaux indicateurs socio-demographiques et economiques, mai 2013, synthèse des résultats d'analyse. Rapport[END_REF]. Since there are few market gardens in this heavily urbanised city, the potential sources of nitrate in the study area are predominantly from wastewater, solid waste and septic tanks. Therefore, the risk of pollutant transfers to the shallow aquifers is high in the poorer neighbourhoods because they are exposed to both (i) frequent episodes of inundation and (ii) high levels of pollutants from poorly constructed landfills and latrines.

Groundwater quality and use

Several studies have evaluated the impact of human activities on the quality of the shallow groundwater in the Cotonou region and have reported relatively high levels of nitrates (e.g. up to 100 mg/L; [START_REF] Maliki | Etude hydrogéologique du littoral béninois dans la région de Cotonou (A.O)[END_REF][START_REF] Boukari | Fonctionnement du système aquifère exploité pour l'approvisionnement en eau de la ville de Cotonou sur le littoral béninois[END_REF][START_REF] Odoulami | Qualité de l'eau de consommation et maladies hydriques dans la commune de Ze[END_REF][START_REF] Totin | Groundwater Pollution and the Safe Water Supply Challenge in Cotonou Town[END_REF]). In addition, the vulnerability of this groundwater resource is also related to its proximity to the Atlantic Ocean and the saltwater or brackish lakes [START_REF] Boukari | Fonctionnement du système aquifère exploité pour l'approvisionnement en eau de la ville de Cotonou sur le littoral béninois[END_REF][START_REF] Totin | Groundwater Pollution and the Safe Water Supply Challenge in Cotonou Town[END_REF]. Data from previous studies have shown an increase in salinity levels in groundwater near Lake Nokoué. The salinity of the Lake Nokoué also exhibits a marked seasonal cycle (0 psu during the small wet season in October and 25-30 psu at the end of the dry season) [START_REF] Stephen | Issues of Sustainability of Coastal Groundwater Resources: Benin, West Africa[END_REF][START_REF] Mcinnis | Combined Application of Electrical Resistivity and Shallow Groundwater Sampling to Assess Salinity in a Shallow Coastal Aquifer in Benin, West Africa[END_REF][START_REF] Totin | Groundwater Pollution and the Safe Water Supply Challenge in Cotonou Town[END_REF]. The coastal groundwater system in Cotonou has relatively high chloride (23.6 to 160 mg/L) and sulphate (6.4 to 25.7 mg/L) concentrations [START_REF] Alassane | Chemical evolution of the continental terminal shallow aquifer in the south of the coastal sedimentary basin of Benin (West Africa) using multivariate factor analysis[END_REF][START_REF] Nlend | The Impact of Urban Development on Aquifers in Large Coastal Cities of West Africa: Present Status and Future Challenges[END_REF]. Lake Nokoué and the Atlantic Ocean are therefore a major concern in terms of the source of salinization of groundwater resources in the coastal zone [START_REF] Alassane | Chemical evolution of the continental terminal shallow aquifer in the south of the coastal sedimentary basin of Benin (West Africa) using multivariate factor analysis[END_REF].

Due to the groundwater pollution problems, shallow groundwater is excluded from the official supply of drinking water to the city of Cotonou. However, the low rate of services to the public water supply network in the neighborhoods of peri-urban areas (51%) leads the population to use the groundwater from the shallow Quaternary aquifer for their various domestic uses [START_REF] Insae | Principaux indicateurs socio-demographiques et economiques, mai 2013, synthèse des résultats d'analyse. Rapport[END_REF]. This is despite the fact that the Quaternary aquifer is not part of the official monitoring services of the National Water Company of Benin, the only legal water distribution structure.

Groundwater from the shallow Quaternary aquifer, is accessed by the residents of Cotonou via large-diameter wells installed on private household property. These large-diameter wells are shallow and are designed to pump groundwater from the water table surface so as not to pump deeper saline groundwater [START_REF] Maliki | Etude hydrogéologique du littoral béninois dans la région de Cotonou (A.O)[END_REF]. The Quaternary aquifer sands have a high permeability (in the order of 10 -2 to 10 -4 m/s) and locally contains fresh to brackish groundwater whose exploitation is related to the position of the lake water and seawater instrusions, and to the replenishment of freshwater lenses.

In Cotonou, 81% of the neighbourhoods have wells, and whilst 9% have not any water supply (no wells nor stand pipe for drinking water supply) for domestic purposes, they sometimes buy water for drinking purposes from neighbours (Hounkpè et al., 2014). Furthermore, the groundwater from the large-diameter private wells is used in households for drinking, cooking, laundry, bathing and washing dishes [START_REF] Yadouléton | Assainissement environnemental à Cotonou et lutte contre le choléra[END_REF]EAA, 2018).

In this study, we expand on previous work to elucidate the seasonality of hydrogeological processes resulting in the contamination of groundwater from latrine waste (notably nitrate and nitrite concentrations, herein referred to as NOx) and from salinization.

Methods

Three neighbourhoods in Cotonou were selected for sampling based on differences in their hydrogeological environments: (i) St Jean, where there is no long-term surface inundation and the heavy rainfall infiltrates the soils or leaves the site via overland flow; (ii) Ladji, which is located at the shore of Lake Nokoué and is inundated towards the small wet season; and (iii) Agla, which is located in a flood plain and is inundated early during both the small and large wet seasons. The locations of these three neighbourhoods and sampling sites are presented in Figure 1. In each neighbourhood, groundwater wells were selected for sampling and, where/when possible, surface water samples (permanent and temporary pools, as well as Lake Nokoué) were also included. The depths to the water table and the electrical conductivity (EC) of groundwater in the Quaternary aquifer were monitored monthly at 9 wells and 3 piezometers from each of the 3 neighbourhoods from June 2017 to June 2018. The wells are separated by an average distance of ~200 m within the same neighbourhood probe.

The hydrochemistry of waters were analysed 6 times between November 2016 to June 2018 during the months of February (main dry season), June (main wet season) and November (small wet season), resulting in a total of 127 groundwater, and 60 surface water samples. In addition, for the period from June 2017 to June 2018, 13 rainfall samples were analysed to determine water stable isotopes (δ²H and δ 18 O). Lastly, 2 water samples from atlantic ocean (AO) were collected of the periods from January 2019 (main dry season). Groundwater was sampled from the Quaternary aquifer via the large-diameter wells. Groundwater and surface water temperature, EC, and dissolved oxygen (DO) were measured in-situ using a WTW 3430i portable digital multiparameter.

Water samples were collected for the analyses of cations (filtered at 0.45 µm and acidified with HNO3), anions and stable isotopes, that were conducted at the Laboratory of Hydrogeology of the University of Avignon, France. Major ions were analysed using ion chromatography (Dionex; ICS1100 and autosampler AS-AP). Ion analysis uncertainty is in the order of 3 %, and all ionic balances were ≤ 5 %. The alkalinity was measured using a HACH digital titrator, and stable isotopes were analysed using a Picarro Analyser L 2130-I. For the stable isotopes of waters, the error is ±0.1‰ for δ 18 O and ±1‰ δ²H. The results are presented in Tables 1 and2. The mixing ratio between lake and shallow groundwater is calculated by using stable isotopes values according to [START_REF] Paran | Caracterisation Des Échanges Nappes/Rivieres En Milieu Alluvionnaire Guide Méthodologique[END_REF]:

= .
+ 1 -. .

The same equation is used with δ 2 H to compute the δ 2 Hm mixing ratio. Om is water sample isotope composition where groundwater (GW) and Lake (L) mixing is supposed. OL is Lake isotope composition. OGW is groundwater isotope composition and F is mixing fraction.

One questionnaire in each sampling site was administered, 10 per study area (Ladji, Agla and St. John). A total of thirty (30) questionnaires were administered through an interview with households in each study area. Main information such as the the source of drinking water supply, groundwater use, waste and wastewater management are mentioned in the questionnaire (supplementary data).

Results

Seasonal variations of the water table and groundwater EC

The monthly monitoring of the depth to water table and EC over a one-year period highlights the variations in seasonal fluctuations of the aquifers between the sites. Typical of unconfined shallow aquifers, the Quaternary aquifer shows marked spatial and seasonal variations and is in phase with the monthly rainfall. The seasonal variations of the water table and groundwater EC in each of the neighbourhoods are illustrated in Figures 3 and5.

Between the neighbourhoods, St Jean has a maximum depth to water table (1.5 m at site J5) corresponding with the dry season (February) that is relatively deep compared with the depths of 1.4 m and 1.0 m observed in Ladji (site L7) and Agla (site A4), respectively (Fig. 5). In addition, at 2 of the 4 sites in Agla, the negative depth values indicate that the water table is above the land surface during the wet season (thus contributing to the floods), whereas groundwater at St Jean and Ladji remains below the surface. The seasonal fluctuation amplitudes also vary. In St Jean, the maximum change between wet and dry season water table depth is of 1.2 m. Here the water table fluctuations also vary between wells. Well J5 strongly reacts to the increased rainfall in October (small wet season)

whereas the deepening of the water table in wells J1 and J2 remain relatively weak (Fig. 5). These relatively low water table values can be attributed to the use of wells by households [START_REF] Boukari | Fonctionnement du système aquifère exploité pour l'approvisionnement en eau de la ville de Cotonou sur le littoral béninois[END_REF][START_REF] Kadjangaba | Impact des Processus Hydrochimique sur la Qualité des Eaux souterraines de la Ville de N'Djaména-Tchad[END_REF]. Similar to St Jean, in Ladji, the seasonal fluctuations in the water table

between the wet and dry seasons vary by 1.3 m (Fig. 5). In comparison, in Agla, the seasonal amplitude of the water table variation is lower (0.5 m). Since Ladji is located on the shore of Lake Nokoué, the lake fluctuations likely influence the variation of the water table depths. An increase of about 90 cm in the water table is observed at Ladji between the wet and dry seasons is consistent with the observed elevation of the lake level during the same period (IRD/IRHOB, unpublished data). The rise in water level starts in January and increases gradually to April/May, which is a 2-month time lag from Agla and St Jean.

With seasonal variations in the water table depth, the groundwater EC also shows varying trends (Fig. 3). In St Jean, the groundwater EC values (297-1,285 μS/cm) are relatively weak compared to Agla and Ladji, and show variable seasonal changes (Fig. 3). Wells J1 and J2 recorded higher EC values in the dry season (511-1,285 μS/cm) when groundwater levels were low compared with the wet season (297-799 μS/cm). In comparison, the well J5 and the piezometer had higher EC values (444-1,169 μS/cm) in the rainy season (rise of the water table) compared with the dry season (497-685 μS/cm). In Agla, the groundwater EC ranges between 353-1,468 μS/cm, which is low compared with local surface waters (including temporary ponds and swamps; 2,800-2,900 μS/cm). EC values are similar during the rainy season and the dry season (Fig. 3). In Ladji, the groundwater EC values are higher than in the other neighbourhoods (633-5,340 μS/cm) and similar to the local temporary ponds (480-4,090 μS/cm), but strongly lower than the Lake Nokoué (up to 49,700 μS/cm during dry season). With the exception of well L2, no difference was observed in the variation of the EC during the dry season and the rainy season (1,478-5,340 μS/cm).

Seasonal variations of major ions

The composition of major ion concentrations of waters is different in each of the neighbourhoods as highlighted in Figure 4. In St Jean, the groundwater is of Na-Ca-HCO3-Cl type. In comparison, the groundwater in Ladji is of Na-HCO3-Cl type, and Agla groundwater is more of the Na-Ca-HCO3-SO4-HCO3 type (Fig. 4). The ponds sampled in both Ladji and Agla show some similarities in major ion compositions with local groundwater, thus indicating a potential connection between surface and subsurface waters. However, this connection is spatially and/or temporally variable, in particular in Agla, since some of the pond samples have a greater concentration of HCO3 relative to Cl and SO4, and increased Ca relative to Na and Mg compared with groundwater. In addition, in Ladji, the Lake Nokoué has a greater ratio of Cl to SO4 and HCO3 compared with groundwater.

The temporal evolution of these major ions at each site is presented in Figure 5 and, similar to EC values, the seasonal changes vary both between sites and between neighbourhoods. Greatest seasonal variations are observed in Ladji, and particularly for groundwater sampled at L6 and L7

where dry season conditions results in increases in Na (by 244-374 mg/L), Ca (by 76-81 mg/L), Cl (by 301-447 mg/L) and HCO3 (by 530-622 mg/L). These sites are located between 100 to 150 m from the Lake shore. The increase of the ions' concentration during dry season is associated with a deepening of the water table and may therefore indicate influences of lake infiltration. The Lake Nokoué has greater concentrations of Na (3,168-12,219 mg/L), Ca (146-419 mg/L), Cl (6,166-1,9310mg/L), and HCO3 (73-110 mg/L) compared with all groundwater samples (Tables 1 and2).

In Agla, the seasonal variations in major ions remain relatively stable except for HCO3 and SO4 concentrations (Fig. 5). However, between sites, there are large differences in seasonal trends. 1 and2).

In St Jean, groundwater at seven of the ten wells sampled (J1, J2, J10, J3, J4, J6 and J9) show an increase in Na (by 36-115 mg/L), Ca (by 49-114 mg/L), HCO3 (by 119-439 mg/L) and Cl (by 42-111 mg/L) concentrations during the dry season (February and March, Fig. 5). This occurs at the time when the water table is at its deepest level. In addition, small wet season peaks in major ion concentrations are also observed in groundwater from wells J5, J7 and J8. [START_REF] Craig | Standards for reporting concentrations of deuterium and oxygen-18 in natural waters[END_REF] in Figure 6. These data were also used to calculate the mean weighted average values of δ 18 O and δ²H for different ranges in monthly rainfall. The results

show that when monthly rainfall is < 50 mm, the isotope values are greater compared with monthly rainfall ranging from 50 mm to 500 mm (Fig. 6a). The isotope values of rainfall collected in Cotonou show an overall mass effect; a depletion in heavy isotopes correlates with an increase in rainfall amounts. In Cotonou, the local rainfall has stable isotope values covering a large range; from -5.4 to 0.8 ‰ for δ 18 O, and from -30.9 to 14.5 ‰ for δ²H (Fig. 6a, black crosses). The groundwater values from the three sites are also presented in Figure 6a, which also highlights a large range in values (from -4.17 to 0.35 ‰ for δ 18 O, and from -21.9 to 4.3 ‰ for δ²H).

In St Jean, the stable isotope values for groundwater vary between -4.17 and -2. Like in Ladji, groundwater in Agla is also enriched in δ 18 O and δ²H (-3.57 to -0.03, and -18.22 to 2.78 ‰, respectively) compared with St Jean. Some samples from Agla (mostly during the dry season) lie to the right of the MWL with a slope of 5.4 (Fig. 6c). Therefore, these groundwaters may also be subject to evaporation and mixing with enriched surface waters such as the lake water (via the lowlands) and the pond water. In addition, groundwaters (e.g., wells A9 and A10) that are close to lake water are located in discharge areas. δ 18 O and δ²H mixing ratios indicate ranges from 54% to 62% of shallow groundwater mixing with lake water in Agla.

Nitrogen

The Beninese quality standard for drinking water for nitrogen is 45 mg/L (0.70 mmol/L) for NO3, 3.2 mg/L (0.07 mmol/L) for NO2, and 250 mg/L (7.0 mmol/L) for Cl (Decree N ° 2001-094 of February 20 th ). In this study, 26 % (values of 0.73-5.06 mmol/L) of the groundwater sampled exceeds these limits in terms of NO3, and 7.0 % (values of 0.12-2.04 mmol/L) for NO2 ( As described by [START_REF] Katz | Using Cl/Br ratios and other indicators to assess potential impacts on groundwater quality from septic systems: A review and examples from principal aquifers in the United States[END_REF], the Cl/Br ratio can be a valuable first assessment of septic tank contamination of shallow groundwater. This is based on the assumption that sewerage waters and septic tank effluent exhibit distinct ranges and higher values of Cl/Br molar ratios and Cl concentrations compared with rainwater [START_REF] Davis | Uses of Chloride/Bromide Ratios in Studies of Potable Water[END_REF], as observed in many samples form this study (Fig. 7a). Elevated Cl/Br ratios may also result from the dissolution of halite. However, halites

have not been reported in the local Quaternary aquifer. In addition, many of the groundwater values correspond to ranges reported for sewerage and septic tank effluent [START_REF] Davis | Uses of Chloride/Bromide Ratios in Studies of Potable Water[END_REF]Vengosh and Pankrativ, 1998;[START_REF] Katz | Using Cl/Br ratios and other indicators to assess potential impacts on groundwater quality from septic systems: A review and examples from principal aquifers in the United States[END_REF]) compared with waters with halite dissolution [START_REF] Davis | Uses of Chloride/Bromide Ratios in Studies of Potable Water[END_REF][START_REF] Pastén-Zapata | Assessment of sources and fate of nitrate in shallow groundwater of an agricultural area by using a multi-tracer approach[END_REF][START_REF] Panno | Characterization and Identification of Na-Cl Sources in Ground Water[END_REF], rainwater from coastal areas, and seawater [START_REF] Alcalá | Using the Cl/Br ratio as a tracer to identify the origin of salinity in aquifers in Spain and Portugal[END_REF][START_REF] Davis | Uses of Chloride/Bromide Ratios in Studies of Potable Water[END_REF]). According to Figure 7b, groundwater values with similar Cl/Br ratios and Cl concentrations than sewerage wastewater also show higher concentrations of NOx. Three samples (wells J2, L9 and A6) plot above the Cl/Br ratios for sewage or septic tank effluent (Cl/Br molar ratios 676-1350; Cl <1000 ml/L), likely indicating animal manure. As evidenced in Figure 7b, values that fall into the animal manure/animal urine (Cl/Br molar ratios, 2,810-3,730; Cl <1000 mg/L) also have high NOx concentrations (0.76-0.81 mmol/L). Other evidence for a septic tank and animal manure influence are the corresponding elevated dissolved organic carbon (DOC) concentrations (Table 1). However, not all the groundwater samples have high DOC concentrations. According to for well A4).

Discussion

Variations in the drivers of groundwater degradation

The vulnerability of groundwater degradation from either salinization or sewage leakage in (1993), denitrification tends to occur in aquifers with very shallow groundwater compared to aquifers with deeper groundwater (more than 2 m). Low dissolved oxygen levels combined with low NOx levels in shallow wells (even less than 1.0 m) in the study area (Fig. 8) where higher levels can be expected, may be related to biodegradation or denitrification processes [START_REF] Postma | Nitrate Reduction in an Unconfined Sandy Aquifer: Water Chemistry, Reduction Processes, and Geochemical Modeling[END_REF][START_REF] Jorgensen | Transport and Reduction of Nitrate in Clayey till underneath Forest and Arable Land[END_REF][START_REF] Hassane | Impacts of a Large Sahelian City on Groundwater Hydrodynamics and Quality: Example of Niamey (Niger)[END_REF][START_REF] Kadjangaba | Impact des Processus Hydrochimique sur la Qualité des Eaux souterraines de la Ville de N'Djaména-Tchad[END_REF]. Either by reducing NO3 to HCO3 (1) or N2 (2). According to [START_REF] Postma | Nitrate Reduction in an Unconfined Sandy Aquifer: Water Chemistry, Reduction Processes, and Geochemical Modeling[END_REF] and [START_REF] Anornu | Tracking nitrate sources in groundwater and associated health risk for rural communities in the White Volta River basin of Ghana using isotopic approach (δ15N, δ18ONO3 and 3H)[END_REF], the absence or low concentrations of NO2 and NH4 in groundwater is probably related to the reduction of NO3 to N2. The overall denitrification process can be described as [START_REF] Berner | Early Diagenesis: A Theoretical Approach[END_REF]:

5CH2O + 4NO3 - 2N2 + 4HCO3 -+ CO2 + 3H2O (1) 2NO3 -+ 12H + + 10e- N2 + 6H2O (2)
However, denitrification may not be the only process that contributes to the increase of HCO3 in shallow groundwater, which probably also results from the decomposition of organic matter and mineral dissolution reactions (e.g. [START_REF] Alassane | Chemical evolution of the continental terminal shallow aquifer in the south of the coastal sedimentary basin of Benin (West Africa) using multivariate factor analysis[END_REF].

In Ladji, the main influence on groundwater salinization (EC up to 5,340 µS/cm) is the mixing with the Lake Nokoué waters. This was obvious during the dry season where both stable isotopes values and major ion concentrations clearly highlight mixing, and the water level also shows an early dry season rise in values due to lake infiltration. In comparison, the sewerage contamination of groundwater is mostly evidenced during the wet season (groundwater NOx up to 2.5 mmol/L).

During et al. 2014;[START_REF] Yadouléton | Assainissement environnemental à Cotonou et lutte contre le choléra[END_REF]. In St Jean, the maximum depth to water table is observed at 1.53 m in the dry season, which means that dry season saturated zones remain close to leaking sewerage sources.

Periods of increased risk due to groundwater degradation

Generally speaking, groundwater samples with nitrate levels that exceed the Beninese quality standards for drinking water originated from wells J1, J3, J6, J7, J8, J9 and J11 (piezometer) during the dry season (February and March) in St Jean, from wells L7 and L11 during the rainy season (June and October) in Ladji, and from wells A2, A6 in the dry season (February and November) in Agla.

Thus, risk for nitrate pollution in shallow groundwater shows high seasonal variation between sites.

Similar results were obtained by [START_REF] Boukari | Fonctionnement du système aquifère exploité pour l'approvisionnement en eau de la ville de Cotonou sur le littoral béninois[END_REF] and [START_REF] Totin | Groundwater Pollution and the Safe Water Supply Challenge in Cotonou Town[END_REF] at different sites in Cotonou with higher NO3 levels (up to 1,61 mmol/L) observed during recharge of the wet season.

The measured EC values show a large amplitude of spatial and temporal variation. The EC values in Agla and St Jean are in the same order of variations (200-1,800 μS/cm) whereas the groundwater in Ladji records EC values in the order of 750-5,340 μS/cm. In St Jean, the waters are more saline during the dry season. Unlike St Jean, the wells in Agla and Ladji are saline during both the dry and the rainy seasons due to mixing processes with lake water.

Shallow groundwater, an unregulated water resource in expanding urban environments

In urban areas of sub-saharan Africa, groundwater from shallow wells is commonly used to partially or fully supply drinking water resources [START_REF] Okotto | Socio-economic aspects of domestic groundwater consumption, vending and use in Kisumu, Kenya[END_REF]. In major cities, such official groundwater resources are monitored and treated. For example, in the coastal city of Douala (Cameroon), shallow groundwater is the main source for domestic and drinking purposes [START_REF] Takem | Acidification of Shallow Groundwater in the Unconfined Sandy Aquifer of the City of Douala, Cameroon, Western Africa: Implications for Groundwater Quality and Use[END_REF]. Likewise, in Bamako (Mali), around 55 % of the population uses water from aquifer resources (British Geological Survey, 2002). Where shallow groundwater is not the official resource, the shallow groundwater usually free and therefore commonly used in the impoverished areas of urban sprawls, including for domestic uses. Normally this resource is meant for washing only, but it commonly ends up for drinking, dish washing, shower and cooking water supplies. For example, the interviews conducted during this study showed that 10 on 10 of the households in St Jean, 9 on 10 in Agla, and 4 on 10 in Ladji reported to use well water only for dish washing. In St Jean, 1 on 10 households declared to use well water for drinking water supply compared with Agla and Ladji where no households have reported such use. The results of the interviews have therefore showed that there are differences in groundwater use between St Jean, Ladji and Agla. The underprivileged areas of the city are subject to greater groundwater quality issues, and this also correspond to the parts of the city where the residents are more dependent on the groundwater as a domestic water resource. This is the case in Kinshasa (Democratic Republic of Congo) where in peri-urban and rural inhabitants widely use the unregulated and untreated shallow groundwater resources for drinking water supply [START_REF] Ndembo | Apport des outils hydrogeologiques et isotopiques à la gestion de l'aquifère du Mont Amba[END_REF].

Unfortunately, as seen in this case study of Cotonou, the shallow groundwater in urban environments is often contaminated. This was also observed in Blantyre (Malawi) where drinking water from shallow groundwater was heavily polluted by a lack of sanitation facilities and indiscriminate waste disposal [START_REF] Mkandawire | Quality of groundwater from shallow wells of selected villages in Blantyre District, Malawi[END_REF]. Likewise, high NO3 concentrations in urban In many urban cases, the nitrate contamination of shallow groundwatear is from anthropogenic sources [START_REF] Martínez-Santos | A survey of domestic wells and pit latrines in rural settlements of Mali: Implications of on-site sanitation on the quality of water supplies[END_REF]. This was also observed in this study and previous work in Cotonou [START_REF] Boukari | Fonctionnement du système aquifère exploité pour l'approvisionnement en eau de la ville de Cotonou sur le littoral béninois[END_REF][START_REF] Maliki | Etude hydrogéologique du littoral béninois dans la région de Cotonou (A.O)[END_REF][START_REF] Boukari | The Impact of Urban Development on Coastal Aquifers near Cotonou, Benin[END_REF][START_REF] Totin | Groundwater Pollution and the Safe Water Supply Challenge in Cotonou Town[END_REF], and as also noted in other major sub-saharan cities such as N'djaména, Tchad, [START_REF] Kadjangaba | Impact des Processus Hydrochimique sur la Qualité des Eaux souterraines de la Ville de N'Djaména-Tchad[END_REF]Djibouti (Ahmed et al. 2017). As highlighted in the study of Ouagadougou, Burkina Faso (Yaméogo, 2008), such nitrate contamination is linked to the high population density that relies on archaic or nonexistent sanitation systems. This is a particularly significant challenge in informal settlements, like in the cities of Douala [START_REF] Takem | Pollution Characteristics of Alluvial Groundwater from Springs and Bore Wells in Semi-Urban Informal Settlements of Douala, Cameroon, Western Africa[END_REF][START_REF] Ketchemen-Tandia | Factors Influencing the Shallow Groundwater Quality in Four Districts with Different Characteristics in Urban Area (Douala, Cameroon)[END_REF]) and Kampala, Ouganda [START_REF] Nyenje | Nutrient pollution in shallow aquifers underlying pit latrines and domestic solid waste dumps in urban slums[END_REF] where the increase in nitrates and chlorides in shallow groundwater are related to faeces from pit latrines, sewages, landfills, surface discharges and droppings from domestic animals.

Conclusion

Although pollution sources are identical for each of the three neighbourhoods studied, the resultant transfers and reactions controlling concentrations are distinct. In the neighbourhood where there is no surface inundation and acts as a local recharge area, the groundwater salinity values remain low (EC < 1285 µS/cm), however NOx concentrations are the highest recorded in this study (up to 5.1 mmol/L). In the neighbourhood bordering a lake where there is seasonal inundation and groundwater discharge, the dry season interaction with lake water results in groundwater with highest observed EC values (up to 5340 μS/cm). Stable isotope (δ 2 H and δ 18 O) mixing ratios indicate mixing of up to 74 % with lake water; In the neighbourhood located in a swamp that is subject to inundation during both the small and large wet seasons also shows mixing with lake water (up to 62 % using δ 2 H and δ 18 O values) resulting in groundwater EC values up to 1468 µS/cm. This discharge site notably has lower NOx concentrations (up to 0.86 mmol/L), however this is not indicative of less sewerage contamination only greater degradation processes. Understanding the seasonal changes in processes controlling groundwater quality between each site is key to identifying risks to the residents who use this unregulated shallow groundwater resource for domestic purposes, including drinking water supplies. Seasonal variations highlight heightened risks from sewerage and septic tank leakage during the wet season in neighbourhoods located in discharge areas compared with increased risk during the dry season in the recharge area. In addition, there are increased risks of shallow groundwater salinization during both the small wet and dry seasons in discharge areas.

Stable water isotopes showed a direct relationship between local rainfall water and groundwater at St Jean compared with Ladji and Agla where groundwaters are also be subjected to mixing with enriched surface waters such as the lake water (via the lowlands) and the pond water, particularly during the dry and small wet seasons.

Groundwaters

Four

  of the eight groundwater wells (A4, A5, A9 and A10) show an increase in Na (by 47-128 mg/L), Ca (by 20-88 mg/L), HCO3 (by 155-750 mg/L) and Cl (by 61-155 mg/L) during the month of February (dry season). During the wet seasons (June and October/November), the remaining four wells (A2, A6, A8 and A7) show an increase in Na (by 93-158 mg/L), Ca (by 34-78 mg/L), HCO3 (by 99-436 mg/L), Cl (by 110-176 mg/L), and SO4 (by 75-276 mg/L) concentrations. These trends correspond to changes in the water table depths, where the increasing wet season major ion concentrations occurs in wells where the groundwater is (sub)artesian during the wet season (A2 and A8), compared to wells where groundwater remains well below the surface and has increased dry season major ion concentrations (A4). These trends may highlight the influence of groundwater mixing with pond water in the discharge areas, compared with infiltrating rainfall diluting groundwater in other areas during the wet season. The temporary and permanent pond waters have similar concentrations of Na (56-166 mg/L), Ca (34-147 mg/L), Cl (43-240 mg/L), and HCO3 (97-738 mg/L) compared with Agla groundwater samples (Tables

  37 ‰ for δ 18 O and between -21.87 and -8.98 ‰ for δ²H. These values show that the groundwater in St Jean is depleted at δ¹⁸O and δ²H. The linear regression between δ 18 O and δ 2 H values (slope of 7.5) lie close to the LMWL (Fig.6a), suggesting that groundwater likely originates from local rainfall. the recharge of relatively low volume rainfall events (< 50 mm/month) in Ladji compared with St Jean; (ii) evaporation effects (some values lie to the right of the LMWL indicating a slope of 5.2), or (iii) groundwater mixing with lake water. During the dry season, groundwater isotopic values are close to the lake Nakoue values (Fig.6b), which suggests a strong mixing between the lake and groundwater during this season. There are also a number of groundwater samples whose δ 18 O and δ²H values remain close to those of the temporary and permanent ponds. δ 18 O and δ²H mixing ratios indicate ranges from 72 to 74 % of shallow groundwater mixing with lake water during the dry season in Ladji.

  Broun et al. (2009), rapid oxidation of DOC into carbon dioxyde may account for the low DOC concentration in groundwater.Alternatively, samples with low NOx concentrations and relatively low Cl/Br ratios, such as groundwater from Agla (Fig.7b), can indicate areas of organic biodegradation (e.g.[START_REF] Mcarthur | Waste-water impacts on groundwater: Cl/Br ratios and implications for arsenic pollution of groundwater in the Bengal Basin and Red River Basin[END_REF]. The relationship between HCO3, NOx and DO for all groundwater sampled at Agla is shown in Figure8. The samples where dissolved oxygen (DO) and NOx are low compared with HCO3 correspond to discharge areas. This is especially the case for groundwater sampled during the dry season at wells A10, A9 and piezometers A11, J11 where HCO3 values increases (4.80-12.31 mmol/L) and NOx decreases (0.0-0.40 mmol/L) with low DO values (0.06-4.22 mg/L). However, this may also indicate areas of recent rainfall infiltration resulting in a dilution of NOx concentrations (e.g.

  shallow groundwater resources have been observed in Dakar, Senegal (NO3 > 100 mg/L; Ndeye et al. 2017); Douala, Cameroon (NO3 up to 241 mg/l; Ketchemen-Tandia et al. 2017) and in different regions of Ghana (NO3 up to 507 mg/L; Rossiter et al. 2010).

Figure 1 .Figure 2 :

 12 Figure 1. (a) Location of Cotonou and sampling sites in the three neighbourhoods; (b) Sedimentary unit cross section (A-B) of marginal-littoral area of Benin (modified from Boukari, 1998); and (c) Environmental situation at Agla (A9 site)

Figure 6 .

 6 Figure 6. Relationship between 18 O and 2 H with Global Meteoric Water Line (GMWL) and Local Meteoric Water Line (GMWL).

Figure 7 .

 7 Figure 7. (a) Groundwater, pond and lake water Cl/Br molar ratios with changes in Cl concentrations highlights different sources of Cl in the waters. (b) Relationship between Cl/Br ratios and Cl concentrations showing higher concentrations in NOx (circle sizes are relative to NOx concentrations).

Figure 8 .Figure 9 .

 89 Figure 8. Relationship between HCO3, NOx and DO for all groundwater sampled at Agla

Table 1

 1 Two sites (J6 and J8) have elevated NOx concentrations in both the wet and dry seasons (1.15-5.06 and 0.99-2.58 mmol/L, respectively). NOx in St Jean groundwater may originate from natural fixation of nitrogen in the soil and human pollution via leaky latrines and human defacation in the streets. The wet season increase in NOx of groundwater in Ladji may either be due to infiltration of anthropogenic pollution, or nitrogen fixed by vegetation in the soils. The NOx

	).

concentrations remain low (up to 0.80 mmol/L, average of 0.04 mmol/L). The highest concentrations of NOx are observed during the dry season (> 3 mmol/L) compared with wet season samples (NOx < 3.37 mmol/L). concentrations are low in the permanent ponds and the lake (<0.01 mmol/L). However, the wet season temporary ponds have high concentrations of NH4 (up to 1.55 mmol/L), which may undergo nitrification during infiltration and may also result in the NOx contaminantion of groundwater.

The highest value of NH4 in groundwater is observed in Agla, but only at one site (A10: 4.91 mmol/L). All other sites have NH4 concentrations in groundwater ranging from 0.00 to 0.52 mmol/L (average of 0.17 mmol/L). Compared with Ladji and St Jean, groundwater NOx concentrations in Agla are low, with a maximum of 0.86 mmol/L (average of 0.15 mmol/L). In contrast, permanent ponds in the Agla lowlands have high NOx levels only at one site (A13: 17.50 mmol/L), particularly in the dry season.

  Cotonou is temporally and spatially variable. The Quarternary aquifer is exposed to large fluctuations in the water table in response to rainfall changes; all sites show seasonal water table fluctuations higher than 0.5 m. However, both the timing of the water table fluctuations and the seasonal changes in groundwater quality varies between urban areas.In Agla, a strong driver of groundwater quality is the proximity to lowlands. Agla is scattered by these low elevation zones, which have either temporary or permanent ponds where groundwater seasonally discharges. As highlighted by the major ion results, wet season increases in the water table can either result in increased groundwater salinity (EC up to 1,468 µS/cm) in these lowland discharge areas due to mixing with pond water, or can result in lower groundwater salinity (EC < 842 µS/cm) due to the dilution effect from infiltrating rainfall. During the dry season, the groundwater stable isotope values also highlight increased mixing with pond water and saltier Lake Nokoué water. Elevated NOx concentrations in groundwater at Agla is due to sewerage contamination and was recordered during both dry and wet seasons (NOx concentrations up to 0.86 mmol/L). Groundwater contamination from sewerage may infiltrate direcly from leaky latrines or from mixing with the permanent ponds, which have accumulated NOx concentrations up to 17.50 mmol/L. According toStarr et al.

  the wet season, increases in NOx from sewerage sources may result from both (i) rises in the water table mobilising NOx in the unsaturated zone, and/or (ii) infiltrating rainfall and temporary ponds recharging the shallow groundwater (as suggested by stable isotope results) and therefore transporting NOx to the saturated zone.

	St Jean is the only studied neighbourhood that does not have any surface water bodies and no
	groundwater discharge sites. Therefore, the wet and dry season variations in groundwater degradation
	are potentially due to variations in the composition of infiltrating water, mixing between subsurface
	waters, and reactions during water table fluctuations. Although St Jean has low groundwater salinity

levels (EC up to 1,285 uS/cm), this area has the highest NOx concentrations recorded in this study (NOx up to 5.06 mmol/L). Since the local rainfall is the only origin of the shallow groundwater (as seen from stable isotope values), it is expected that either recharging rainfall or rising water tables transfers NOx from the sewerage sources to the groundwater system during the wet season. However, at St Jean, groundwater NOx concentrations are greater during the dry season (up to 5.06 mmol/L) compared with the wet season (up to 2.58 mmol/L). So, instead, the contamination may be constant leakage from latrines throughout the year and wet season rainfall may act to dilute this contamination. Almost all the pit latrines and septic tanks in Cotonou have depths between 1.50 and 2.50 m (Hounkpè

Table 1 :

 1 Chemical parameters and isotopic values in shallow groundwater

	ID	Sampli ng month	Origin	Dept h	T°C	pH	DO	EC	NOx	HCO3 -	Cl -	NO2 -	Br -	NO3 -	PO4 --	SO4 --	Na +	NH4 +	K +	Mg ++	Ca ++	DOC	d 18 O	d 2 H
									meq/
	Units			m			mg/l	µS/cm	l							mg/l							‰
	J1	Nov-16	well		29.50	6.97		590	0.67	221.49	27.59	DBL	DBL	37.68	8.69	3.90	47.20	DBL	19.57	5.42	58.13		-3.07	-14.04
		Mar-17	well		29.70	7.24	2.59	998	1.84	244.00	74.90	0.80	0.97	66.12	8.26	85.49	86.41	0.25	29.43	9.19	93.52		-2.85	-12.48
		Jun-17	well	0.80	28.20	7.45	3.60	1002		318.12	77.18	DBL	DBL	DBL	6.99	115.78	94.37	DBL	3.86	9.99	89.42	10.85	-2.94	-12.61
		Oct-17	well	0.90	27.90	7.57	3.93	799	0.44	314.76	28.52	7.13	DBL	17.67	5.68	4.87	44.68	DBL	22.27	9.69	92.45	5.89	-3.89	-21.22
		Feb-18	well	1.23	29.10	7.16	2.35	1285	1.18	384.30	85.78	DBL	DBL	73.45	8.34	8.62	14.51	13.65	35.65	8.76	79.28	6.80	-3.36	-16.10
		Jun-18	well	0.88	29.20	7.40	3.24	731	1.16	152.50	57.74	1.19	DBL	7.37	4.97	54.63	68.32	0.58	19.86	5.16	53.95		-3.22	-13.37
	J2	Nov-16	well		29.00	6.92		502	0.76	99.56	34.52	0.12	0.28	46.95	6.93	36.23	45.47	0.28	12.67	2.80	44.77		-2.81	-11.64
		Mar-17	well		29.90	6.93	2.42	552	0.70	113.46	42.75	0.17	0.65	37.70	7.13	31.75	41.98	0.30	18.60	3.24	49.58		-3.35	-15.40
		Jun-17	well	0.59	28.60	7.04	3.13	347		128.10	25.67	DBL	DBL	DBL	5.27	17.90	31.66	DBL	7.32	1.94	33.24	8.30	-3.65	-16.31
		Oct-17	well	0.77	28.60	7.36	5.13	297		121.60	15.94	DBL	DBL	DBL	6.52	13.00	22.97	DBL	7.66	1.56	28.22	6.31	-4.17	-21.87
		Feb-18	well	1.04	29.70	6.88	2.56	586	0.50	119.56	52.64	0.43	DBL	3.49	6.40	49.37	37.97	0.62	13.28	3.14	46.95	5.55	-3.39	-15.90
		Jun-18	well	0.75	29.03	7.06	3.39	341	0.24	86.93	2.19	DBL	DBL	12.43	3.77	26.87	22.87	0.22	8.45	1.79	31.72		-3.54	-15.48
	J3	Nov-16	well		29.70	7.02		658	0.74	125.58	46.97	0.53	0.61	45.39	9.82	54.88	62.97	1.64	17.99	3.46	53.96		-3.01	-13.16
		Mar-17	well		29.20	7.15	4.61	891	1.59	191.54	81.73	0.31	0.13	98.13	6.28	53.17	86.30	2.25	21.71	4.96	68.47		-3.02	-12.99
		Jun-17	well		27.60	7.35	7.85	822	0.63	254.68	75.52	DBL	0.18	0.39	5.25	52.61	84.25	DBL	22.82	4.27	63.45	1.17	-3.19	-13.76
		Oct-17	well		29.00	5.91	3.55	630		29.84	56.65	DBL	DBL	DBL	5.19	4.84	51.28	DBL	13.35	4.54	6.62	4.53	-3.56	-16.94
		Feb-18	well		29.20	7.00	3.61	791	1.18	156.16	74.76	0.29	DBL	73.98	4.26	61.19	62.85	0.33	15.11	6.18	79.89	5.37	-3.19	-13.90
		Jun-18	well		29.40	6.90	3.90	792	1.12	158.60	7.88	DBL	DBL	69.65	3.83	41.29	66.47	0.38	14.90	5.79	63.11		-3.38	-15.19
	J4	Nov-16	well		29.80	7.11		500	0.22	18.45	27.63	0.77	0.45	13.48	2.47	36.46	37.84	0.31	17.42	3.77	51.35		-2.37	-8.98
		Mar-17	well		29.90	7.15	4.95	572	0.31	195.20	33.68	0.11	0.79	18.69	2.36	37.86	41.44	0.12	13.45	6.22	57.91		-2.58	-9.93
		Jun-17	well		27.90	7.63	3.98	368	0.33	132.37	2.34	0.15	DBL	DBL	1.99	23.22	29.65	DBL	15.53	2.62	31.66	14.96	-3.23	-14.08
		Oct-17	well		28.70	8.06	5.35	342		81.74	29.18	DBL	DBL	DBL	2.45	24.79	25.31	DBL	7.95	2.97	29.79	4.24
		Feb-18	well		29.20	7.15	3.33	434	0.22	96.38	47.54	DBL	DBL	13.85	2.27	27.26	28.87	0.81	3.52	3.64	36.94	3.79	-3.07	-13.61
		Jun-18	well		28.80	7.41	4.08	379	0.33	122.00	25.24	DBL	DBL	18.82	2.37	28.23	24.75	0.48	16.77	3.00	36.36		-3.52	-15.23
	J5	Nov-16	well		29.70	6.83		642	0.45	28.68	38.17	DBL	0.82	0.28	0.82	3.38	46.38	DBL	43.42	6.31	56.38		-3.22	-14.19
		Mar-17	well		29.70	6.89	3.25	715	0.69	17.80	57.97	0.43	0.96	42.66	0.21	59.64	72.32	0.34	37.83	3.69	49.65		-3.06	-13.09
		Jun-17	well	1.05	28.50	7.03	1.96	798	0.48	193.22	79.80	0.22	DBL	DBL	DBL	89.97	72.19	0.58	35.18	6.18	65.25	11.57	-3.17	-13.43
		Oct-17	well	0.43	27.10	7.03	1.31	630		272.60	37.12	DBL	0.19	DBL	DBL	26.37	43.66	DBL	19.78	5.82	65.35	4.93	-3.61	-17.56
		Feb-18	well	1.53	28.60	6.96	2.34	558	0.46	164.70	38.37	DBL	DBL	2.89	DBL	44.12	34.22	0.50	16.46	3.98	46.12	8.59	-2.89	-12.01
		Jun-18	well	0.66	27.80	6.97	2.03	639	0.25	265.35	35.12	DBL	DBL	1.53	DBL	31.40	44.85	0.62	19.72	5.49	62.37		-3.46	-15.23
	J6	Nov-16	well		29.10	6.76		548	1.15	66.49	41.99	DBL	0.49	71.59	5.27	51.16	47.46	0.65	21.98	3.87	4.27		-3.24	-15.12
		Mar-17	well		29.40	6.99	3.60	1326	5.67	85.40	111.13	1.95	0.18	311.33	2.68	91.61	115.00	0.73	37.66	13.4 6	17.85		-2.85	-11.68
												54.7
		Jun-17	well		29.20	7.06	5.12	1129	3.80	154.79	99.84	9	DBL	157.26	2.57	87.74	99.79	0.39	4.98	1.37	87.46	16.65	-2.60	-10.19
		Oct-17	well		28.50	6.99	4.40	637	1.94	54.90	44.28	2.28	DBL	117.19	2.33	53.18	46.00	DBL	21.69	4.32	48.44	8.31	-3.28	-15.11
																				15.1
		Feb-18	well		29.00	6.97	4.35	961	3.37	439.20	51.14	0.17	DBL	28.87	2.62	47.94	93.79	0.16	29.53	3	114.74	8.63	-3.32	-15.88
		Jun-18	well		29.00	7.17	5.96	346	0.43	54.90	29.35	DBL	DBL	24.95	4.54	2.49	26.22	0.27	11.87	2.27	24.73		-3.23	-13.82
	J7	Nov-16	well		30.10	6.87		431	0.74	93.25	26.42	0.19	0.40	45.76	3.19	27.42	34.79	0.39	13.95	2.89	36.26		-2.85	-12.03
		Mar-17	well		29.90	7.05	5.12	695	0.87	184.22	44.50	0.22	0.11	53.78	0.79	44.46	53.47	0.18	2.82	4.77	55.50		-3.08	-12.98
		Jun-17	well		30.20	7.00	3.78	742	0.56	22.36	61.44	0.26	DBL	DBL	1.14	68.21	63.46	DBL	22.43	5.45	63.31	6.80	-2.61	-9.98
												13.1
		Oct-17	well		28.90	7.14	4.20	652	1.29	16.14	38.98	5	DBL	57.27	0.73	59.96	4.94	DBL	15.58	5.28	62.60	4.59	-3.13	-14.66
		Feb-18	well		29.00	6.90	4.19	647	1.55	113.46	3.99	0.49	DBL	95.59	1.18	59.66	38.17	0.23	24.95	4.69	48.66	7.08	-3.04	-13.22
		Jun-18	well		29.40	7.08	4.19	616	0.66	14.30	37.00	DBL	DBL	4.89	1.87	56.59	47.58	0.24	31.95	4.20	43.35		-3.38	-14.29
	J8	Nov-16	well		29.40	6.99		701	2.21	126.41	4.12	0.58	0.66	136.47	4.61	32.89	38.52	0.32	18.17	5.39	78.67		-3.35	-15.92
		Mar-17	well		29.70	6.78	3.62	885	2.58	115.90	72.18	0.48	0.16	159.26	5.87	36.16	74.78	2.78	29.87	4.94	61.28		-2.77	-11.16
												93.7
		Jun-17	well		29.20	7.27	4.67	894	2.56	128.86	79.23	0	DBL	32.54	4.43	54.90	8.34	0.71	25.57	5.65	72.48	5.82	-2.92	-11.84
												45.5
		Oct-17	well		27.80	7.49	4.75	564	0.99	128.10	22.92	7	DBL	DBL	5.67	3.47	36.54	DBL	19.17	3.18	53.58	5.54	-3.64	-17.99
		Feb-18	well		28.50	6.91	3.30	840	2.60	118.34	56.71	0.46	DBL	16.63	6.20	6.15	59.92	0.32	25.37	4.63	59.75	4.09	-3.12	-13.91
		Jun-18	well		28.40	7.65	4.56	377	0.62	128.10	14.14	DBL	DBL	38.59	4.18	18.97	19.89	0.46	1.39	2.17	38.72		-3.55	-13.45
	J9	Nov-16	well		29.50	7.19		448	0.34	213.58	25.43	0.23	0.47	0.18	DBL	16.48	18.58	4.60	2.88	3.11	49.79		-2.96	-12.98
		Mar-17	well		30.10	6.98	4.82	461	0.88	82.96	42.48	0.69	0.19	54.42	DBL	21.57	36.85	0.33	11.14	2.94	41.27		-2.64	-9.55
		Jun-17	well		29.10	7.20	4.06	437	0.49	126.58	24.64	8.35	DBL	19.20	DBL	26.35	29.73	0.26	1.53	3.20	46.72	8.89	-3.06	-12.08
		Oct-17	well		28.10	7.21	4.04	323	0.46	97.60	27.93	1.56	DBL	0.42	DBL	11.57	17.19	0.58	5.12	2.22	36.84	0.41	-3.44	-15.80
		Feb-18	well		28.60	7.00	4.63	242	0.13	56.12	28.38	DBL	DBL	8.23	DBL	11.53	14.34	0.60	7.64	1.82	26.23	4.58	-3.74	-18.62
		Jun-18	well		28.60	7.04	3.67	251	0.15	122.00	14.44	DBL	DBL	9.45	DBL	15.59	11.91	0.43	5.34	1.62	38.59		-3.43	-13.35
	J10	Nov-16	well		29.20	6.95		572	0.75	13.63	41.52	0.32	0.49	43.32	2.64	38.84	56.63	0.45	26.72	2.86	42.15		-3.44	-16.28
		Mar-17	well		28.50	6.89	2.37	615	0.39	173.24	42.31	0.86	0.96	23.27	DBL	48.34	42.65	1.74	37.39	4.64	52.68		-3.17	-14.39
		Jun-17	well		29.50	7.13	3.43	770	1.12	163.18	65.67	DBL	DBL	69.32	DBL	61.25	72.53	1.46	33.84	4.70	57.83	11.67	-3.17	-13.29
		Oct-17	well		29.30	8.03	4.94	481		98.82	39.22	DBL	DBL	DBL	2.51	47.65	28.13	DBL	13.14	3.82	47.88	3.81	-3.17	-14.61
		Feb-18	well		29.60	6.90	2.77	943	0.99	229.36	8.94	0.56	DBL	6.44	0.52	47.17	6.59	14.36	28.62	5.34	56.68	7.19	-3.14	-13.91
		Jun-18	well		30.50	6.75	0.73	878	0.90	25.10	65.43	DBL	DBL	55.54	1.52	47.69	66.77	5.41	27.62	6.57	65.57		-3.28	-14.91
			Piezo
	J11	Feb-18	meter	1.40	31.30	7.21		497	0.89	92.72	57.13	DBL	0.60	55.30	4.48	27.92	42.63	2.29	11.97	4.67	46.88	13.50	-3.09	-15.03
			Piezo
		Jun-18	meter	0.88	29.40	7.33	6.79	444	0.65	141.52	13.61	DBL	DBL	4.26	6.47	22.82	13.44	0.15	12.46	4.81	49.92		-3.73	-17.66
	A2	Nov-16	well		28.60	6.60		1164	0.72	432.95	118.77	DBL	0.38	0.44	DBL	33.32	15.85	0.25	35.77	1.85	8.73		-1.81	-5.39
		Mar-17	well		29.90	6.28	3.32	990	0.87	13.70	123.64	0.39	0.22	53.39	DBL	136.56	125.35	0.23	28.66	7.45	49.37		-2.72	-10.94
																				17.4
		Jun-17	well	-0.01	27.30	7.21	2.42	1273		435.85	16.53	DBL	0.35	DBL	DBL	74.85	147.93	DBL	35.17	6	78.28	22.27	-2.32	-9.17
																				15.2
		Oct-17	well	0.04	26.50	7.02	2.33	1150		441.64	14.00	DBL	0.53	DBL	DBL	1.45	111.34	DBL	29.87	7	81.80	25.62	-2.02	-7.51
																				14.7
		Feb-18	well	0.69	28.30	6.96	2.83	733	0.83	22.52	97.21	DBL	0.40	0.51	DBL	32.23	86.88	0.32	15.55	5	41.54	14.65	-2.90	-12.08
		Jun-18	well	0.04	28.90	7.02	1.61	959		292.80	111.26	DBL	DBL	DBL	DBL	3.56	93.69	DBL	24.14	1.24	68.46		-2.75	-11.56
	A4	Nov-16	well		29.60	6.02		326	0.27	31.95	17.78	0.35	0.12	1.63	DBL	78.71	29.22	0.16	6.91	3.73	16.65		-3.22	-14.01
		Mar-17	well		30.90	5.85	2.95	269	0.39	27.00	27.70	0.57	0.17	2.32	DBL	44.29	29.25	0.38	6.53	3.67	13.12		-3.12	-14.05
		Jun-17	well	0.47	30.70	6.01	5.34	353	0.43	37.82	56.98	DBL	0.23	2.52	DBL	38.15	32.98	0.54	8.24	5.30	2.99	9.86	-2.96	-12.84
		Oct-17	well	0.29	28.00	5.95	4.53	497	0.18	54.90	69.62	DBL	0.35	1.95	DBL	61.86	46.93	DBL	1.46	6.77	27.46	8.79	-2.68	-10.44

Table 2 :

 2 Chemical parameters and isotopic values in surface water

	ID	Samplin g month	Origin	T°C	pH	DO	EC	NOx	HCO3 -	Cl -	NO2 -	Br -	NO3 -	PO4 --	SO4 --	Na +	NH4 +	K +	Mg ++	Ca ++	DOC	d 18 O	d 2 H
	Units					mg/L	µS/c m	meq/L							mg/L							‰
	A2	Nov-16	pond	32.40	7.02		818		287.54	82.19	BDL	0.26	BDL	1.98	19.41	76.54	0.26	14.21	7.84	62.59		-1.51	-3.18
		Jun-17	pond	25.20	8.72	7.77	113		41.02	5.19	BDL	BDL	BDL	0.60	4.27	6.27	0.41	3.47	0.74	1.79	10.91	-2.13	-12.69
		Oct-17	pond	26.20	7.25	4.65	970		358.68	108.79	BDL	0.57	BDL	4.49	16.65	96.12	BDL	22.87	1.32	84.99	25.43	-2.65	-12.20
		Jun-18	pond	28.80	6.96	1.51	740	0.02	380.03	95.54	0.74	BDL	BDL	2.26	11.58	79.57	1.22	52.62	14.61	63.34		-2.89	-12.18
	A3	Nov-16	pond	34.10	7.51		1242	0.02	459.10	149.59	0.39	0.43	0.99	2.92	24.29	128.17	1.78	58.34	13.90	59.61		-0.96	-0.63
		Jun-17	pond	29.10	8.24	9.53	1619		408.70	249.90	BDL	0.39	BDL	1.53	154.25	26.27	BDL	67.54	16.88	89.66	36.99	-2.26	-8.64
		Oct-17	pond	29.80	8.43	11.61	346		137.86	24.35	BDL	0.18	BDL	3.41	0.69	29.56	BDL	14.22	4.19	26.47	18.45	-2.41	-14.50
		Jun-18	pond	30.10	7.05	1.07	998		256.20	62.27	BDL	BDL	BDL	0.57	47.74	64.51	0.18	22.14	7.55	57.43		-3.74	-17.80
	A6	Jun-17	pond	28.40	8.67	7.45	75		26.00	4.50	0.20	BDL	BDL	BDL	7.13	6.83	BDL	4.84	0.39	5.39	8.12	-1.30	-0.28
	A7	Nov-16	pond	28.70	6.20		504		498.68	127.55	BDL	0.37	BDL	4.53	17.86	174.65	BDL	8.33	9.77	37.36		3.88	24.74
		Jun-17	pond	28.00	8.04	6.66	250		103.85	13.47	0.37	BDL	BDL	BDL	15.79	17.78	BDL	6.42	1.99	27.58	7.86	-2.74	-15.01
		Oct-17	pond	35.70	9.05	15.70	1070		470.31	92.01	BDL	0.24	BDL	4.50	42.50	117.64	BDL	83.62	17.53	41.35	39.75	-0.01	-6.12
		Jun-18	pond	30.70	8.46	4.33	534		173.85	38.68	BDL	BDL	BDL	5.77	18.98	49.25	BDL	35.93	7.92	21.97		-4.27	-23.07
	A8	Nov-16	pond	30.20	6.48		700		218.23	74.45	BDL	0.32	0.12	1.18	77.43	77.99	6.43	19.18	4.98	48.18		-2.97	-11.99
		Jun-17	pond	35.90	9.64	12.38	1278	0.05	97.60	116.75	0.67	0.16	1.89	BDL	395.69	113.71	0.30	39.75	9.80	131.91	26.26	-0.33	-1.29
		Oct-17	pond	29.70	6.38	2.34	659		147.62	62.96	BDL	0.45	BDL	BDL	8.25	73.47	BDL	13.73	6.78	38.46	15.41	-2.63	-11.50
		Jun-18	pond	26.90	6.80	0.08	695	0.08	253.15	43.38	3.46	BDL	BDL	1.85	52.53	56.39	0.39	24.74	8.47	47.66		-3.45	-16.37
	A9	Nov-16	pond	31.10	6.88		764		305.53	74.35	BDL	0.24	BDL	2.13	4.88	71.43	BDL	19.62	12.90	44.65		0.35	5.38
		Jun-17	pond	29.40	7.07	0.01	1643		738.10	102.81	BDL	0.17	BDL	BDL	0.73	75.29	3.32	145.23	33.92	147.66	25.28	-2.09	-11.65
		Oct-17	pond	28.00	8.41	2.40	1620		581.33	240.73	BDL	0.56	BDL	5.25	11.54	166.41	BDL	162.78	26.22	38.85	51.75	-0.09	-6.20
		Jun-18	pond	31.20	8.58	10.72	711		260.47	69.58	BDL	BDL	BDL	0.40	16.46	7.35	BDL	35.68	12.37	34.24		-3.29	-16.12
	A10	Nov-16	pond	30.10	6.69		1310	0.02	544.58	127.78	BDL	0.44	1.51	0.50	2.21	12.24	0.18	4.32	14.42	73.28		-0.93	-1.43
		Jun-17	pond	31.40	7.48	2.07	1114		314.15	124.09	BDL	0.18	0.42	5.99	136.62	92.28	BDL	5.32	13.56	95.61	43.28	-2.55	-11.18
		Oct-17	pond	28.70	6.96	1.82	621		250.71	69.50	BDL	0.19	BDL	0.85	6.44	62.84	BDL	21.67	7.69	41.23	27.14	-3.30	-16.92
		Jun-18	pond	28.70	7.17	3.29	758		271.45	75.47	BDL	BDL	0.25	BDL	15.37	72.84	0.37	23.60	8.97	54.34		-2.90	-11.70
	A12	Feb-18	pond	28.80	6.03	5.72	768		42.70	153.98	BDL	0.99	BDL	BDL	254.62	162.77	3.64	12.15	13.69	27.38	18.06	-2.71	-11.35
		Jun-18	pond	28.10	6.69	0.17	605		176.90	53.70	BDL	BDL	BDL	1.47	19.75	63.75	0.25	15.75	6.33	35.76		-3.98	-19.48
	A13	Feb-18	pond	31.90	4.12	6.77	2900	17.55	0.00	256.87	0.59	BDL	188. 27	12.8 9	24.59	219.67	28.2 3	95.68	68.63	221.89	55.14	-2.44	-9.10

Acknowledgements

The authors owe much gratitude to hydrogeology laboratory of Avignon University, EPAC/LARBA and IRD/CBGP for the full financial and logistical support of this work. We are grateful to neighbourhood chiefs and people who kindly authorized us to sample in their districts and households.

We thank the reviewers whose comments improved this paper.


Michel Visalli
email: michel.visalli@inrae.fr

Benjamin Mahieu

Pascal Schlich

Time periods segmentation in TDS and TCATA

• Duration based analysis and maps (ANOVA, PCA or CVA) + global test, easy to interpret -sequentiality of perceived sensations is only taken into account when continuous time is divided into periods -subjective choice of the number and the frontiers of periods (except with semi-Markov chains)

• Trajectory maps (PCA, CA) + "within" and "between" product evolution representation -subject heterogeneity not taken into account -no test -CA is not the best framework for TCATA because of multiple responses

• What about interpretability and actionability for product design?

Objectives

• Automatically determine the number and frontiers of periods that best represent the breaks in the temporal perception of products (at panel level) • Simplify and objectify product temporal characterization using an unified multidimensional approach • Study key moments in perception

Material and methods

• 6 methods: TDS, TCATA, (AEF-dominance, AEF-applicability, FC-AEFdominance, FC-AEF-applicability) • 6 groups of 64 consumers, each group using 1 method • Each consumer participated in 3 separated sessions (1 in lab, 2 at home) and tasted a total of 20 samples:

• 4 dark chocolate + 1 replicate (home)

• 4 guacamole + 1 replicate (lab)

• 4 iced tea + 1 replicate (lab)

• 4 crisps + 1 replicate (home)
Number and frontiers of periods determination

• For each product:

• Standardize and discretize time in 100 points between 0.01 (1st perception) and 1 (end of perception) • Compute a mrCA considering discretized time as observations • Carry out an agglomerative clustering on mrCA row coordinates (axes 1&2, agglomeration method=Ward) with a constraint of temporal contiguity • Determine periods based on clusters, suggested partition:

• with the higher relative loss of inertia between clusters (min.

A01 C3 0.01 1 0 0 0 A01 C3 0.02 0 1 0 0 A01 C3 0.03 1 0 0 0 … C3 A01 C3 1.00 0 0 0 1 … C3
Example on crisps C3 (TDS)

 Clustering on mrCA row coordinates with constraint of temporal contiguity (adespatial)  Suggested partition with the higher relative loss of inertia between clusters

Example on crisps C3 (TDS)

Projection of periods on TDS curves

Within product discrimination

• Discretized times replaced by periods • New contingency table, with 2 possible methods of aggregation at subject level:

• score = 1 if an attribute has been cited during the period, 0 otherwise • score = mean over period (weighting by duration) No weighting: cells = proportion of citations in period Green cells = significant differences (5%) Orange cells = significant differences (15%) Within product discrimination (C3, TCATA) Differences between TDS and TCATA:

Subject Product Discretized time Collant Pateux Craquant Dur Croustillant … Sale A01 C3 0.01 1 0 0 0 A01 C3 0.02 0 1 0 0 A01 C3 0.03 1 0 0 0 … C3 A01 C3 1.00 0 0 0 1 … C3 Subject Product Discretized time Collant Pateux Craquant Dur Croustillant … Sale A01 C3 1 1 0 0 0 A01 C3 2 0 1 0 0 A01 C3 3 0 0 0 1 … C3
• TDS: breaks in perception • TCATA: changes in citation rates

Non-uniform and product-dependent periods:

• More changes at the beginning of tasting (textures)



  Objective description, more agreement within periods  Attributes never reaching significance in discretized times highlighted in mrCA  Time lag in perception  Changes in proportions of citations between periods

  Introduction • Numerous statistical analyzes for TDS/TCATA data, many commonalities • Curves of attribute proportions of citations + closest representation of raw data at panel level -lack of global test, several types of tests (binomial, multinomial, proportion test) at each time, unidimensional tests

Different levels of product characterization

• Within product evolution: mrCA on observations = periods, restricted to a given product • But also:

• within period differences: mrCA on observations = products*period • all products • restricted to a given pair of products

• between products and periods differences (trajectories): mrCA on observations = products x periods  Differences between products during first period of tasting

Between products and periods differences (trajectories)

Between products and periods differences (trajectories)

Conclusions

• Common analyses for TDS and TCATA:

• Unique multidimensional paradigm adapted to multiple responses • Subject heterogenity taken into account • Number and frontiers of periods not dependent on tests • Tests at different levels (within/between, all products/pairwise)

• Possibility of reducing temporal signal in a limited number of periods:

• Simplification and objectivation of the interpretation of temporal data • Useful information on the key moments of the temporal sensory perception of the products (product formulation)

• Never more than 4 periods:

• Comparability with AEF • Resolution of temporal methods and granularity of temporal data • Sequentiality of sensations based on periods more appropriate than durations to study temporality?