Mathieu Cladière
email: mathieu.cladiere@leesu.enpc.fr

Céline Bonhomme

Lauriane Vilmin

Johnny Gasperi
email: gasperi@u-pec.fr

Nicolas Flipo

Bruno Tassin

Modelling the fate of nonylphenolic compounds in the Seine River -part 1: Determination of in-situ attenuation rate constants

Keywords: Nonylphenol and nonylphenol ethoxylates, attenuation rate constant, endocrine disrupting compounds modelling, surface water

Assessing the fate of endocrine disrupting compounds (EDC) in the environment is currently a key issue for determining their impacts on aquatic ecosystems. The 4-nonylphenol (4-NP) is a well known EDC and results from the biodegradation of surfactant nonylphenol ethoxylates (NPnEO). Fate mechanisms of NPnEO are well documented but their rate constants have been mainly determined through laboratory experiments. This study aims at evaluating the in-situ fate of 4-NP, nonylphenol monoethoxylate (NP 1 EO) and nonylphenolic acetic acid (NP 1 EC). Two sampling campaigns were carried out on the Seine River in July and September 2011, along a 28 km-transect downstream Paris City. The field measurements are used for the calibration of a submodel of NPnEO fate, included into a hydro-ecological model of the Seine River (ProSe). The timing of the sampling is based on the Seine River velocity in order to follow a volume of water. Based on our results, in-situ attenuation rate constants of 4-NP, NP 1 EO and NP 1 EC for both campaigns are evaluated. These rate constants vary greatly. Although the attenuation rate constants in July are especially high (higher than 1 d -1 ), those obtained in September are lower and consistent with the literature. This is probably due to the biogeochemical conditions in the Seine River. Indeed, the July sampling campaign took place at the end of an algal bloom leading to an unusual bacterial biomass while the September campaign was carried out during common biogeochemical status. Finally, the uncertainties on measurements and on the calibration parameters are estimated through a sensitivity analysis. This study provides relevant information regarding the fate of biodegradable pollutants in an aquatic environment by coupling field measurements and a biogeochemical model. Such data may be very helpful in the future to better understand the fate of nonylphenolic compounds or any other pollutants at the basin scale.

Introduction

Over the last 20 years, the scientific community paid a special attention to endocrine disrupting compounds (EDC) due to their toxicity on aquatic wildlife [START_REF] Petrovic | Endocrine disrupting compounds and other emerging contaminants in the environment: A survey on new monitoring strategies and occurrence data[END_REF]. Among these compounds, the nonylphenol ethoxylates (NPnEO), and especially the 4-nonylphenol (4-NP), are of prime interest since concentrations of several hundred nanogrammes per liter were measured in all environmental and urban waters [START_REF] Giger | 4-nonylphenol in sewage sludge -Accumulation of toxic metabolites from nonionic surfactants[END_REF][START_REF] Ahel | Behaviour of alkylphenol polyethoxylate surfactants in the aquatic environment--II. Occurrence and transformation in rivers[END_REF]. 4-NP is more estrogenic and more toxic than NPnEO [START_REF] Soto | Para-nonyl-phenol -An estrogenic xenobiotic released from modified polystyrene[END_REF]. [START_REF] Jugan | In vitro assessment of thyroid and estrogenic endocrine disruptors in wastewater treatment plants, rivers and drinking water supplies in the greater Paris area (France)[END_REF] and [START_REF] Fenet | Estrogenic activity in water and sediments of a French river: Contribution of alkylphenols[END_REF] have reported the role played by the 4-NP in the estrogenic activity occurring in both surface water and sediment compartments. Due to its toxicity, the 4-NP have been included in the list of the 33 priority pollutants in the European water framework Directive 2000/60/EC (European Commission, 2000). More recently the European Directive 2008/105/EC established the environmental quality standard for 4-NP at 300 ng/L in surface water (European Commission, 2008). The 4-NP mainly originates from the biodegradation of NPnEO (readily biodegradable compounds) which are used as non-ionic surfactants in many industrial and domestic applications. The worldwide production of NPnEO reached 500,000 tons in 2000 and is decreasing because of regulations [START_REF] Ying | Environmental fate of alkylphenols and alkylphenol ethoxylates--a review[END_REF]. The biodegradation pathways of NPnEO are currently well known [START_REF] John | Mechanism for Biotransformation of Nonylphenol polyethoxylates to xenoestrogens in Pseudomonas putida[END_REF][START_REF] Jonkers | Aerobic biodegradation studies of nonylphenol ethoxylates in river water using liquid chromatography-electrospray tandem mass spectrometry[END_REF][START_REF] Giger | Environmental fate of phenolic endocrine disruptors: field and laboratory studies[END_REF]. Basically, the NPnEO can be biodegraded into 4-NP through an oxidative pathway leading to nonylphenolic acids (e.g. nonylphenol acetic acid: NP 1 EC) as biodegradation intermediates, or through a non-oxydative pathway leading to short chain nonylphenol ethoxylates (e.g. nonylphenol mono ethoxylates: NP 1 EO) as intermediates [START_REF] Giger | Environmental fate of phenolic endocrine disruptors: field and laboratory studies[END_REF]. Finally, the 4-NP can be mineralized under well oxygenated conditions [START_REF] Gabriel | A novel metabolic pathway for degradation of 4-nonylphenol environmental contaminants by Sphingomonas xenophaga Bayramipso-hydroxylation and intramolecular rearrangement[END_REF]. The biodegradation rate constants of NPnEO have been mostly determined through bioreactor laboratory experiments [START_REF] Staples | Ultimate biodegradation of alkylphenol ethoxylate surfactants and their biodegradation intermediates[END_REF][START_REF] Jurado | Aerobic Biodegradation of a Nonylphenol Polyethoxylate and Toxicity of the Biodegradation Metabolites[END_REF][START_REF] Karahan | Modelling biodegradation of nonylphenol ethoxylate in acclimated and non-acclimated microbial cultures[END_REF]. However, such experiments fail to represent the complexity of freshwater ecosystems, including the spatial and temporal heterogeneity and the numerous biological, physical and chemical parameters which may interfere with the dynamics of the NPnEO degradation. [START_REF] Jurado | Aerobic Biodegradation of a Nonylphenol Polyethoxylate and Toxicity of the Biodegradation Metabolites[END_REF] used NPnEO mixture as the sole source of carbon for microorganisms and found biodegradation rate constants of NPnEO about 0.2 h -1 , while [START_REF] Staples | Ultimate biodegradation of alkylphenol ethoxylate surfactants and their biodegradation intermediates[END_REF] used synthetic river water to perform a river die-away experiment (closer to in-situ conditions) and found biodegradation rate constants ranging from 0.04 d -1 to 0.10 d -1 for NP 9 EO and from 0.08 to 0.09 d -1 for 4-NP. The difficulty to assess the NPnEO concentrations and their biodegradation relies in the fact that there is a lack of commercial pure reference standards which can be used for a reliable analysis, and that various commercial mixtures exist with different chain lengths according to their use [START_REF] Ayorinde | Molecular distribution of some commercial nonylphenol ethoxylates using matrix-assisted laser desorption ionization time-of-flight mass spectrometry[END_REF].

To date, only one study focuses on the determination of in-situ attenuation rate constants of NPnEO and 4-NP based on a hydrodynamic and biogeochemical model [START_REF] Jonkers | Fate modeling of nonylphenol ethoxylates and their metabolites in the Dutch Scheldt and Rhine estuaries: validation with new field data[END_REF]. However, these attenuation rate constants have to be confirmed since: i)

In-situ biodegradation was determined in estuarine saline water. Authors suggest that biodegradation may significantly change in freshwater;

ii) The knowledge of biodegradation pathways has been updated; NP 1 EC is now recognized as a biodegradation precursor of 4-NP [START_REF] Montgomery-Brown | NP1EC degradation pathways under oxic and microxic conditions[END_REF][START_REF] Giger | Environmental fate of phenolic endocrine disruptors: field and laboratory studies[END_REF].

Thus, it is crucial to assess the in-situ biodegradation of short chain nonylphenol and 4-NP in surface water in order to evaluate their environmental fate and their impact on aquatic wildlife surrounding heavily urbanized area such as the Seine River downstream of Paris, France.

A global project on modelling NPnEO was launched in 2009. The first part aims at evaluating the attenuation rate constants; the second aims at modelling the fate of nonylphenolic compounds at the annual scale in order to validate the parameters calibrated in the first part and forecast future profiles of the Seine River. This study deals with the first part of the NPnEO modelling project, while the second part is handled in a companion paper with the simulation of annual time series of NPnEO and 4-NP concentrations for a reference year (2010) in the Seine River. At last, a forecast of nonylphenolic compound concentrations in the Seine River is attempted for the 21 st century according to global changes scenarios (Cladière et al., 2013a).

Therefore the goal of this first part is to determine the in-situ attenuation rate constants of 4-NP, NP 1 EC and NP 1 EO in the Seine River. To achieve this goal, two sampling campaigns are carried out and the data are used to calibrate a hydro-ecological model implemented for the Seine River. A special attention has been paid to the small scale spatial and temporal variabilities of the concentrations which are firstly in-situ assessed and then used in the model calibration procedure. Finally, the sensitivity analysis of the model to the biodegradation parameters is performed based on an approach "one factor at a time" (OFAT).

The calibrated parameters are then validated in the companion paper according to 11 monthly sampling campaigns carried out in 2010 at 3 sites on the Seine River and the Oise River as well as the effluent of the largest WWTP of the Parisian Metropolitan Area (Cladière et al. 2013a).

Materials and methods

Study site

This study focuses on the Seine River, downstream of Paris City (annual average flow in Paris = 300 m 3 /s, 120 m 3 /s in summer). The investigated transect of the Seine River is 28 km long from Maisons-Laffite to Trielsur-Seine (Fig. 1). This transect is selected based on two major criteria. First, there are only two significant tributaries in the Seine River between Maisons-Laffite and Triel-sur-Seine, i.e. the effluents of Seine Aval WWTP and the Oise River (Fig. 1). The Seine Aval WWTP is the biggest treatment plant of the Parisian Metropolitan Area and treats approximately 1,666,000 m 3 per day (70 % of Parisian wastewater) with an average effluent flow of 19 m 3 /s. The Oise River is one of the largest tributaries of the Seine River with an average discharge flow of 95 m 3 /s (30 m 3 /s in summer). These two inflows account for 30 % to 40 % of the Seine River flow at Triel-sur-Seine during lowflow conditions. The small number of lateral inflows along this transect simplifies the determination of the boundary conditions for the modelling procedure. The second criterion is the distance between Maisons-Laffite and Triel-Sur-Seine. According to the average Seine River velocity (≈ 0.15 m/s) during low-flow conditions (< 150 m 3 /s), the transit time along this transect is approximately 60 h. This duration is similar to the half-lives of 4-NP and NPnEO found in the literature: between 2 and 7 days [START_REF] Staples | Ultimate biodegradation of alkylphenol ethoxylate surfactants and their biodegradation intermediates[END_REF][START_REF] Jonkers | Fate modeling of nonylphenol ethoxylates and their metabolites in the Dutch Scheldt and Rhine estuaries: validation with new field data[END_REF].

Maisons-Laffitte

Conflans

Sampling campaigns

Two sampling campaigns were carried out in July and September 2011. These campaigns are designed to acquire data for the calibration of the ProSe model and the assessment of attenuation rate constants of nonylphenolic compounds in the Seine River. The timing of the sampling is estimated according to the Seine River flow velocity in order to collect samples in the same water volume from Maisons-Laffitte to Triel-sur-Seine (Lagrangian approach). The Seine River velocity is simulated using the hydrodynamic module of the ProSe model (see section 2.3), with measured upstream boundary conditions (national discharge gauging station located in Paris City). The description of the sampling campaigns (kilometre points, hours of sampling and flows) are provided in Table 1. The sampling campaigns were exclusively carried out under dry weather conditions in order to ensure that the Seine Aval WWTP and the Oise River are the sole lateral inflows (no wet weather sources). Due to an unexpected rain event, the July campaign was stopped at Poissy (45 h). The July sampling campaign was stopped at Poissy due to a rain event. Tw = water temperature Samples are collected from bridges in the middle of the river with 2 L glass bottles. The analytical protocol is described in details by Cladière et al., (2013b). Briefly, the water samples are filtered through a 0.45 µm porosity glass fiber filter (GF/F, Whatmann). Only the dissolved phase is kept and analyzed as the suspended particles account approximately for 5 % of total concentrations of NP 1 EO, NP 1 EC and 4-NP within the Seine River (Cladiere et al., 2010). After a spiking with a surrogate mixture (octylphenol-d17, NP 1 EO-d2), 250 mL of dissolved phase is extracted by solid phase extraction on OASIS ® HLB cartridges (200 mg/6 mL; Waters © ).

Finally, the extracts are analyzed by means of an ultra-performance liquid chromatography coupled to a tandem mass spectrometer (UPLC-MS-MS; Waters © ) using an internal standard mixture (linear compounds: 4-nNP, nNP 1 EO and nNP 2 EC). Based on this analytical protocol, the concentrations of 4-NP, NP 1 EC and NP 1 EO are quantified for surface water and WWTP effluents. Given that no pure standard is commercially available for NP 3 EO to NP 15 EO, only semi-quantitative analyses are performed for these compounds. A semi-quantitative analysis does not provide the real value of compound concentration but a concentration equivalent value proportional to the real concentration (the factor is not known because of the lack of pure standard). For each n (from 3 to 15), dividing the NPnEO peak area by the peak area of the relative internal standard nNP 1 EO give the concentration equivalent of the NPnEO. These concentration equivalent values enable comparisons from one site to another but not between compounds (e.g. the factor of proportionality of NP 3 EO is different from that of NP 15 EO).

Modelling tool: the ProSe model

The hydrodynamic and biogeochemical model ProSe was firstly developed to simulate the impacts of human activities on nitrogenous and phosphorous pollutions in the Seine River and its tributaries [START_REF] Even | River ecosystem modelling: Application of the PROSE model to the Seine river (France)[END_REF][START_REF] Flipo | Primary production in headwater streams of the Seine basin: the Grand Morin case study[END_REF][START_REF] Even | New tools for modelling water quality of hydrosystems: An application in the Seine River basin in the frame of the Water Framework Directive[END_REF]. All mathematical equations used by the ProSe model to simulate the river flowing, pollutant advection and other biogeochemical parameters are provided by [START_REF] Even | River ecosystem modelling: Application of the PROSE model to the Seine river (France)[END_REF]. For this study the biogeochemical module is updated to take into account the biodegradation pathways of NPnEO following [START_REF] Giger | Environmental fate of phenolic endocrine disruptors: field and laboratory studies[END_REF] scheme (Fig. 2). In the Figure 2, the attenuation rate constants K 1 , K 1 ' and K 2 only represent the biodegradation of NP 1 EO or NP 1 EC into their products (NP 1 EC or 4-NP). On the contrary, K 3 represent the global attenuation of 4-NP due to biodegradation, volatilisation and adsorption onto particles.

Assuming first-order kinetics (Jonkers et al., 2003;[START_REF] Jurado | Aerobic Biodegradation of a Nonylphenol Polyethoxylate and Toxicity of the Biodegradation Metabolites[END_REF], the attenuation rate constants K 1 , K 1 ', K 2 and K 3 are calibrated using a trial-error procedure to optimise the matching of the modelled longitudinal profiles of 4-NP, NP 1 EO and NP 1 EC with the measured ones. [START_REF] Jonkers | Fate modeling of nonylphenol ethoxylates and their metabolites in the Dutch Scheldt and Rhine estuaries: validation with new field data[END_REF] suggest, during the sensitivity analysis of their model, that the sorption onto particles have a very limited influence on the fate of nonylphenolic compounds in estuarine water. Indeed, set sorption to 0 or multiply their optimum value by 5 lead to small variations of NP 1 EO and NP 1 EC dissolved concentrations. In addition, Cladiere et al. (2010) showed that the particulate concentrations of nonylphenolic compounds account for less than 5% of the total concentration.

Therefore, the sorption onto particles of NP 1 EO and NP 1 EC has been considered as negligible. Similarly to [START_REF] Jonkers | Fate modeling of nonylphenol ethoxylates and their metabolites in the Dutch Scheldt and Rhine estuaries: validation with new field data[END_REF], the water-air exchange of the nonylphenolic compounds (except for 4-NP) has been considered as insignificant due to very low Henry's constants (e.g. NP 1 EO and NP 2 EO ≈ 0.0003 Pa.m 3 /mole).

Consequently, three equations are implemented in the biogeochemical module of the ProSe model:

inputs precursor + EO] [NP ' K EO] [NP K = dt EO] d[NP 1 1 1 1 1 - - Equation 1 inputs precursor + EC] [NP K EO] [NP ' K + = dt EC] d[NP 1 1 1 2 1 - Equation 2 NP] [ K EC] [NP K + EO] [NP K + = dt NP] d[ 1 1 - - - 4 4 3 2 1

Equation 3

Due to the lack of suitable information for NP 1 EO degradation and in order to reduce the number of parameters to calibrate, we assume that the oxidation and the biodegradation of NP 1 EO are equal (K 1 = K 1 '). Moreover, data on long chain nonylphenol ethoxylates are scarce and their attenuation rate constants are not determined. The semi-quantitative analyses reveal that the effluent of Seine Aval WWTP is from 2 (NP 3 EO) to 11 (NP 8 EO) times more concentrated than the upstream of the Seine River. In addition, by comparing the concentration equivalents found at Poissy to the expected ones (combining of Conflans-s t -Honorine and the Oise River), discrepancies of -39 % (NP 3 EO) to -64 % (NP 8 EO) are noticed. These discrepancies give evidence of the disappearance of these compounds in the Seine River due to biodegradation processes. In order to take into account the biodegradation of long chain ethoxylates within the Seine River, "precursor inputs" terms are considered in the ProSe model scheme as linear sources, also being calibrated during the calibration process (Equations 1 and 2). Based on the disappearance of long chain nonylphenol ethoxylate along the Seine River (revealed by semi-quantitative analyses), the precursor inputs are assumed to decrease along the simulated transect. The highest precursor inputs are estimated close to the Seine Aval discharge and decrease until Triel-sur-Seine following natural logarithm shape representative of first-order kinetics. These precursor inputs take into account the appearing of NP 1 EC or NP 1 EO along the studied transect due to the biodegradation of long chain compounds and they are expressed in nanogram per litter of water and per day (ng/L/d).

The scheme in Fig. 3 shows the layout and input parameters of the model. In the ProSe model, it is necessary to define the boundary conditions such as the upstream river flow (national discharge gauging station) and the upstream compound concentrations [C] (field measurements). The attenuation rate constants and precursor inputs are calibrated according to the concentrations at Conflans-S t -Honorine, Poissy and Triel-sur-Seine.

Calibrated variables

Oise River

Flow; [C] Upstream Flow; [C] WWTP Flow; [C] Seine River (hydrodynamic module) K 1 , K 1 ', K 2 , K 3 Conflans-s t -Honorine [C] Poissy [C] Triel-sur-Seine [C]

Boundary conditions

Data for calibration

Precursor inputs Precursor inputs

Precursor inputs

Calibrated variables

Oise River

Flow; [C] Upstream Flow; [C] WWTP Flow; [C] WWTP Flow; [C] Seine River (hydrodynamic module) K 1 , K 1 ', K 2 , K 3 Conflans-s t -Honorine [C] Conflans-s t -Honorine [C] Poissy [C] Triel-sur-Seine [C] Triel-sur-Seine [C]

Boundary conditions

Data for calibration

Precursor inputs Precursor inputs Precursor inputs Precursor inputs

Precursor inputs Precursor inputs

Sampling strategy for determining small scale spatial and temporal variabilities

Small scale variabilities are crucial since they have a direct impact on the calibration process and the assessment of the attenuation rate constants [START_REF] Beven | Preferential flows and travel time distributions: Defining adequate hypothesis tests for hydrological process models[END_REF]. The spatial and temporal variabilities of 4-NP, NP 1 EC and NP 1 EO concentrations are assessed at Conflans-s t -Honorine (during September campaign) as depicted in Fig. 4 and are assumed to be representative of variabilities along the whole Seine River transect. The concentrations of 4-NP and NP 1 EC found in the Seine River (≈ 100 ng/L) are far higher than their limits of quantification (4-NP: 24.5 ng/L; NP 1 EC: 1.7 ng/L) except for NP 1 EO (NP 1 EO: 9.8 ng/L). The repeatability is taken into account in the assessment of spatial and temporal variabilities by selecting the highest value between the relative standard deviation of samples and the analytical repeatability. The small scale variabilities (sum of spatial and temporal) of 4-NP, NP 1 EC and NP 1 EO concentrations in the Seine River reach respectively 14 %, 11 % and 37 %. These results provide quantification errors due to the sampling protocol, which are usually not reported in most of articles dealing with pollutants in receiving surface water.

Right bank

Results

Small scale variabilities

The sampling strategy is thus applicable to 4-NP and NP 1 EC measurements, but is less accurate for NP 1 EO.

Therefore, the variabilities on Seine River profiles are plotted as error bars for the measured concentrations. In addition, the variabilities on boundary conditions are considered on the modelled profiles.

Attenuation rate constants

The concentrations of 4-NP, NP 1 EC and NP 1 EO found in the Seine and Oise Rivers and the effluents of Seine

Aval WWTP as well as the biogeochemical parameters (water temperature, dissolved organic carbon (DOC), dissolved oxygen and pH) are exhibited in Table 3. All concentrations found during July and September sampling campaigns are consistent with the literature and previous results found in the Seine River (Jonkers et al., 2009;[START_REF] Loos | Occurrence of polar organic contaminants in the dissolved water phase of the Danube River and its major tributaries using SPE-LC-MS2 analysis[END_REF]Cladière et al., 2013b). The concentrations found during July in the Seine River are higher than those found during September, mainly due to the significant higher concentrations of Seine Aval WWTP and the Oise River (Table 3). Whatever the sampling campaign, no exceedance of the European Quality Standard (300 ng/L) is observed along the 28 km transect of the Seine River even downstream of Seine Aval WWTP. Before calibrating the attenuation rate constants in the Seine River, a first simulation is performed considering nonylphenolic compounds as a conservative tracer for July and September campaigns. Results (data not shown) underscore that the modelled trends do not fit the observed ones indicating that only physical processes (transport and lateral inflows) do not explain the fate of 4-NP, NP 1 EC and NP 1 EO along the Seine River.

Attenuation rate constants and precursor inputs are, thereafter, calibrated (Fig 5). In parallel, small scale 1 variability intervals are used to assess uncertainties around the optimal values of attenuation rate constants. Table 4 shows the minimum, optimal and maximum attenuation rate constants as well as precursor inputs for 11 July and September sampling campaigns. 12 13 For July, Table 4 discloses high values for K 2 (3.14 to 3.47 d -1 ) and K 3 (2.38 to 2.75 d -1 ). These rate constants are far higher than those reported by [START_REF] Jonkers | Fate modeling of nonylphenol ethoxylates and their metabolites in the Dutch Scheldt and Rhine estuaries: validation with new field data[END_REF] in the Rhine estuary and [START_REF] Staples | Ultimate biodegradation of alkylphenol ethoxylate surfactants and their biodegradation intermediates[END_REF] in laboratory batch reactor (Table 4). In parallel, the precursor inputs were estimated between 7.84 ng/L/d and 3.44 ng/L/d for NP 1 EC and between 0.4 ng/L/d and 0.06 ng/L/d for NP 1 EO. In the case of NP 1 EC, the total precursor flux along the Seine River transect (33.6 g/d) accounts for 10 % of the upstream load (370 g/d) and only for 2.4 % of the Seine Aval input (1,480 g/d) which means that they are not main sources of NP 1 EC and NP 1 EO into the Seine River. However, the precursors inputs are crucial in the fate of NP 1 EC and NP 1 EO since neglect them during the calibration process does not allow a good fit between modelled and observed profiles.

Calibration parameters for the September campaign are much lower (Table 4). Mean values of K 2 and K 3 are respectively 17 and 33 times lower than those estimated for the July campaign. In parallel, the maximum precursor inputs for NP 1 EC drops by a factor 26. The decreases of K 2 , K 3 and NP 1 EC precursor inputs suggest that the aerobic biodegradation was significantly higher in July compared to September. Moreover, the rate constants estimated in September are consistent with the literature [START_REF] Jonkers | Fate modeling of nonylphenol ethoxylates and their metabolites in the Dutch Scheldt and Rhine estuaries: validation with new field data[END_REF][START_REF] Staples | Ultimate biodegradation of alkylphenol ethoxylate surfactants and their biodegradation intermediates[END_REF].

The July and September sampling campaigns enable to calibrate of attenuation rate constants but not to validate them. Validation of the parameter sets is done at the annual scale based on 11 monthly sampling campaigns performed at the Maisons-Laffitte, Seine Aval WWTP effluent, the Oise River and Meulan (downstream Trielsur-Seine). The validation is provided in the companion paper: "Modelling the fate of nonylphenolic compounds in the Seine River -part 2: assessing the impact of global change on daily concentrations" (Cladière et al. 2013a).

Discussion

Influence of biogeochemical conditions of the Seine River

In order to understand the significant differences between July and September, the biogeochemical conditions of the Seine River are examined (e.g. temperature, pH, chlorophyll a, dissolved O 2 , Seine River flow). [START_REF] Manzano | The effect of temperature on the biodegradation of a nonylphenol polyethoxylate in river water[END_REF] highlight the impact of temperature on biodegradation rates of nonylphenolic compounds and report that the higher the temperature, the higher the biodegradation rate. Water temperature is similar in July (21°C)

and September (20°C) and cannot explain such differences of the attenuation rate constants. Furthermore, pH, conductivity, meteorological and hydrological conditions of the Seine River were quite similar during both campaigns.

Chlorophyll a concentrations are continuously monitored in the middle of the considered transect and exhibit high values (up to 20 µg/L representative of an algal bloom in the Seine River) one week before the July sampling campaign (data not shown). On the contrary, during September, low concentrations of chlorophyll a (≈ 5 µg/L) are noticed.

The link between an algal bloom and the growth of heterotrophic bacteria has been reported by [START_REF] Kisand | Seasonal dynamics of bacterio-and phytoplankton in large and shallow eutrophic Lake Vortsjarv, Estonia[END_REF] in lake Vortsjarv (Estonia) and by [START_REF] Hygum | Dissolved organic carbon released by zooplankton grazing activity -A high-quality substrate pool for bacteria[END_REF] for laboratory experiments. Both studies reported a significant increase of the bacteria growth during the decline of an algal bloom. The high activity of heterotrophic bacteria is also visible on dissolved O 2 since the concentrations measured in July are close to 4 mg/L and saturation about 75 % while in September the concentration are far higher at 9 mg/L and saturation at 100 % (Table 3). Based on this conclusion, the decline of the algal bloom during the July campaign favours the increase of heterotrophic bacterial biomass, and consequently enhances the biodegradation of organic matters such as nonylphenolic compounds since [START_REF] Corvini | Microbial degradation of nonylphenol and other alkylphenols -our evolving view[END_REF] reported that various environmental bacteria species can biodegrade them. Thus, in July the half-life times of 4-NP and NP 1 EC vary between 5 and 7 hours, while in September they are longer and reach 7 days. The half-life time of NP 1 EO remains constant in July and September and is close to 2 days.

Finally, the differences between July and September campaigns suggest that the bacterial biomass of the Seine River influences the oxidative biodegradation of NPnEO (K 2 , K 3 , NP 1 EC precursors inputs), especially after an algal bloom. The first-order kinetic approach used in this study seems reliable to describe a punctual state of biodegradation in the Seine River (constant bacterial biomass) but does not take into account the variabilities generated by the fluctuation of bacterial biomass. In order to clarify the impacts of heterotrophic bacteria on nonylphenolic compounds biodegradation, further studies should focus on coupling the modelling of NPnEO biodegradation and bacterial biomass using biogeochemical models such as ProSe.

In contrast, the non oxidative biodegradation of NPnEO is not impacted by the heterotrophic bacterial biomass of the Seine River since the attenuation rate constants of NP 1 EO do not significantly evolve and the NP 1 EO precursor inputs remain constant between both campaigns. However, this result must be considered carefully according to the lower confidence on NP 1 EO concentration profiles (small scale variability = 37 % and concentrations close to the quantification limit).

Sensitivity analysis

In order to assess the significance of each process in the biodegradation pathway, a sensitivity analysis is performed using an approach "one factor at a time" (OFAT) [START_REF] Félix | Sensitivity analysis of the mathematical model "Erosion Productivity Impact Calculator" (EPIC) by approach One-Factor-At-A-Time (OAT)[END_REF]. Input parameters of the model are modified by -10 % and +10 % around its optimised value one after the other. The effect of each modification is analyzed on the outputs by the means of a sensitivity index (SI, Equation 4). The sensitivity index weights the impacts of input parameters such as attenuation rate constants or precursor inputs on model outputs (concentrations of 4-NP, NP 1 EC and NP 1 EO at Conflans-s t -Honorine, Poissy and Trielsur-Seine). A positive SI means that input and outputs vary in a similar way while a negative SI means that inputs and outputs vary inversely. In addition, the higher the absolute value of SI, the higher the impact of input parameter on the considered output. The sensitivity indexes of nonylphenolic compound concentrations in the Seine River towards attenuation rate constants (SI K1 , SI K1' , SI K2 and SI K3 ) and precursor inputs (SI NP1EO , SI NP1EC ) are shown in Fig. 6. During this study, an increase or a decrease of the considered inputs give similar results of sensitivity and hence results are compiled in Fig. 6. Whatever the sampling campaign, SI K1(K1') , SI K2 and SI K3 are negative meaning that an increase of attenuation rate constants leads to a decrease of modelled concentrations. As underscored in the Fig. 6, the sensitivity indexes of biodegradation processes in July and September are not similar confirming that campaigns occur in different conditions.

SI

In July, high values of SI K2 (varying from -0.8 -to -1.2) and SI K3 (ranging from -0.8 to -1.0) are noticed for NP 1 EC and 4-NP concentrations. On the contrary, the SI K1 (from -0.18 to -0.26) for NP 1 EO concentrations is smaller but still significant. In September, the SI K2 and SI K3 are smaller (around -0.25 for NP 1 EC and 4-NP concentrations). This observation confirms that the aerobic biodegradation process is important in July while its significance is lower in September. These results corroborate the hypothesis of an enhanced aerobic biodegradation at the end of an algal bloom. A similar conclusion is highlighted for SI NP1EC between July (SI NP1EC ≈ 1) and September (SI NP1EC ≈ 0.2).

Despite a significant role of K 2 to determine NP 1 EC concentrations, it has a very limited impact on 4-NP concentrations (biodegradation product), as confirmed by the SI K2 for 4-NP concentrations (0.09 in July and September). A similar result is noticed for SI K1(K1') for NP 1 EC or 4-NP concentrations (≈ 0.007). As a conclusion, according to these sensitivity indexes, a variation of attenuation rate constants K 1 and K 2 has a weak influence on 4-NP concentrations along the simulated transect and points out the need to extend the scale of modelling (spatial and temporal) to better understand the impact of biodegradation processes.

Conclusions

This study assesses the in-situ attenuation rate constants of 4-NP, NP 1 EC and NP 1 EO within surface water in a heavily urbanized area such as Paris. Based on a coupling between sampling campaigns and hydraulic and biogeochemical simulations, this study provides the first real case study of the environmental fate of 4-NP, NP 1 EC and NP 1 EO in freshwater. This study is of prime interest since it proves the possibility to simulate the fate of readily biodegradable pollutants such as 4-NP and its precursors within surface water. Based on the toxicity of these compounds, the assessment of their environmental fate is a key issue to understand their persistence and their possible impacts on aquatic wildlife. Results highlight a strong temporal variability of rate constants between July and September campaigns. While the rate constants evaluated for July are higher than 1 d -1 and NP 1 EC precursor inputs higher than 344 ng/L/d, the rate constants and precursor inputs assessed for September are smaller (K ≈ 0.1 d -1 and precursors inputs ≈ 2 ng/L/d) but consistent with the literature. The variability of rate constants seems to be linked to the heterotrophic bacterial biomass and highlights that the firstorder kinetic approach used in this study is reliable to describe punctual conditions of the Seine River (with a constant bacterial biomass) but not to describe the complexity of biogeochemical processes at larger temporal scale. Consequently, the coupling between attenuation rate constants and bacterial biomass should be more intensively investigated to definitely validate the impact of biogeochemical conditions of surface water on biodegradation of nonylphenolic compounds.

The sensitivity analysis of the ProSe model points out that the aerobic biodegradation processes are important inputs for the ProSe model and reinforces the hypothesis of the large influence of the biogeochemical conditions of the Seine River. However, this sensitivity analysis also highlights that biodegradation processes are not a key input for 4-NP fate along the 28 km transect, and points out the need to lengthen the transect in order to confirm or contradict this last conclusion at the basin scale.

In order to validate the modelling parameter values, the attenuation rate constants assessed during both sampling campaigns will be applied to simulate daily of concentrations of 4-NP, NP 1 EC and NP 1 EO for 2010 and compared to monthly sampling campaigns. To this end, 11 sampling campaigns were carried out from February

to December 2010 at Maisons-Laffite, Seine Aval WWTP effluent, the Oise River, and Meulan (downstream of Triel-sur-Seine).

At last, the impact of global changes (global warming, population growth, optimisation of WWTP) on daily concentrations will be studied for the middle and the late 21 st century. This is presented in a companion paper entitled: "Modelling the fate of nonylphenolic compounds in the Seine River -part 2: assessing the impact of global change on daily concentrations" (Cladière et al., 2013a).

  Fig. 1 Investigated transect of the Seine River (28 km-long) downstream of Paris and sampling sites

Fig. 2

 2 Fig. 2 Fate schema of nonylphenolic compounds in a well oxygenated surface water. The attenuation rate constant K 1 , K 1 ', K 2 and K 3 are determined by the ProSe model. The biodegradation of NPnEO and NPnEC is introduced in the ProSe model as precursor inputs of NP 1 EO and NP 1 EC along the Seine River.

Fig. 3

 3 Fig. 3 Scheme of the ProSe model and the required input parameters. ([C] =concentrations of 4 NP, NP 1 EO and NP 1 EC in ng/L)

  Fig. 4 Sampling strategy to determine the small scale variabilities of concentrations. The sampling points are indicated by stars. Middle 1, 2 and 3 were sampled with an interval of 10 minutes.

  Modelled (optimised rate constants) and actual profiles of 4-NP, NP 1 EC and NP 1 EO concentrations in the 5 Seine River. The points exhibited are Maisons-Laffite (715.4 km), Conflans-st-Honorine (728.2 km), 6 Poissy (734.9 km) and Triel-sur-Seine (743.6 km). The y error bars represented on the actual profile 7 indicate the total variabilities linked to in-situ sampling while they represent the uncertainties attached to 8 boundary conditions on modelled profile 9 10

  the optimised value of input; I Test is the tested value of input (+10 % or -10 %); I mean is the mean of I opt and I Test ; O Test and O Opt are the outputs respectively related to I Test and I Opt ; O mean is the mean of O Test and O opt .

Fig. 6

 6 Fig. 6 Sensitivity indexes of simulated concentrations of 4-NP, NP 1 EO and NP 1 EC at Conflans-st-Honorine, Poissy and Triel-sur-Seine towards attenuation rate constants and precursor inputs

Table 1

 1 Sampling campaign description for July 2011 and September 2011.

			July 2011 (Tw = 21°C)	September 2011 (Tw = 19°C)
	Sampling points	Kilometre point	Hours of sampling	Flow (m 3 /s)	Hours of sampling	Flow (m 3 /s)
		(km)
	Maisons-Laffitte	715.4	10/07	8:42	72	29/09	8:00	97
	Seine Aval (WWTP)	720.1	10/07 19:24	16	29/09	15:30	18
	Conflans-s t -Honorine	728.2	11/07 16:30	88	30/09	7:00	115
	Oise River	728.7	11/07 17:06	32	30/09	7:30	28
	Poissy	734.9	12/07	5:35	120	30/09	19:00	143
	Triel-sur-Seine	743.6	*		-	01/10 18 :50	143
	Total sampling time		45 h			59 h
	*:

  Table2exhibits the concentrations of 4-NP, NP 1 EC and NP 1 EO within the Seine River as well as small scale spatial and temporal variabilities.

Table 2

 2 Concentrations (ng/L) of left bank, middle and right bank of the Seine River and small scale variabilities The concentrations for Middle used for the spatial variability are the averages of Middle 1, 2 and 3. ** The spatial and temporal variabilities are determined by the relative standard deviation of samples (%RDS). The total variabilities are calculated by the sum of spatial and temporal variabilites (we assume that analytical uncertainties are included in spatial and temporal variabilities).

			Dissolved concentrations (ng/L) Spatial variability Temporal variability	Small scale variabilities (%) **
		Left bank	Middle (average * )	Right bank	Middle 1	Middle 2	Middle 3	Spatial Temporal	Total
	4-NP	55	57	63	58	57	57	7	7	14
	NP 1 EC	129	123	118	125	128	115	5	6	11
	NP 1 EO	10	9	11	11	7	10	14	23	37

*

Table 3

 3 Biogeochemical parameters and nonylphenolic compound concentrations measured in July and September sampling campaigns

				July					September
	Parameters *	Upstream	Seine Aval WWTP	Conflans-st-Honorine	Oise river	Poissy Upstream	Seine Aval WWTP	Conflans-st-Honorine	Oise river	Poisy	Triel-sur-Seine
	Flow (m 3 /s)	72	17	89	32	121	97	18	115	28	143	143
	Tw (°C)	20.8	20.9	22.2	21.4	21.0	19.3	ND	19.1	17.5	20.8	ND
	σ (µS/cm)	600	1195	693	690	699	612	720	635	739	666	ND
	pH	8.0	ND **	7.5	7.8	7.6	7.6	ND	7.6	8.0	7.6	ND
	O2 (mg/L)	4.9	ND	4.0	5.0	ND	ND	ND	9.3	11.3	7.7	ND
	DOC (mg/L)	2.95	11.60	4.08	2.74	3.83	2.84	8.97	3.74	3.32	3.37	3.63
	4-NP (ng/L)	102	320	201	138	143	53	136	57	35	45	70
	NP1EC (ng/L)	52	751	159	66	137	49	616	123	76	114	102
	NP1EO (ng/L)	19	80	35	17	30	19	43	9	20	11	14

* σ: conductivity, O2: dissolved oxygen, DOC: dissolved organic carbon. ** ND: not determined.

Table 4

 4 Attenuation rate constants (d -1 ) and precursor inputs (ng/L/d)

		Attenuation rate constants (d -1 )	Precursor inputs (ng/L/d)
		K1 = K1'	K2	K3	NP1EC	NP1EO
		min -opt -max	min -opt -max	min -opt -max	min -max	min -max
	July 2011	0.05 -0.10 -0.15 3.14 -3.30 -3.47 2.38 -2.50 -2.75 3.44 -7.84 0.06 -0.4
	September 2011	0.29 -0.30 -0.33 0.08 -0.10 -0.14 0.09 -0.15 -0.19 0.01 -0.3	0.04 -0.4
	Jonkers et al., 2005 (estuary)	0.060 -0.089	0.019 -0.020	0.024 -0.043	-	-
	Jonkers et al., 2005 (estimation river)	0.18 -0.21	0.048 -0.159	0.072 -0.21	-	-
	Staples et al., 2001 (laboratory)	0.065	0.099	0.076 -0.092	-	-
	Min and max values were assessed according to the small scale variabilities. Optimised values (opt) enable the best fit between simulated
	and observed profiles.

Acknowledgments

The authors want to gratefully acknowledge the Paris public sanitation service (SIAAP) and especially Vincent Rocher and Céline Briand for their valuable assistance for sampling the effluent of Seine Aval WWTP. The authors kindly thank Alexis Groleau and Nicolas Escoffier, who provided access to the 15min-chloropyll a monitoring data of the Seine River. The authors also acknowledge Mohamed Saad for his technical assistance.

This study was supported by the PIREN-Seine research programme.

We thank Science of the Total Environment to permit us to publish the post-print of the manuscript.


Mathieu Cladière
email: mathieu.cladiere@leesu.enpc.fr

Céline Bonhomme

Lauriane Vilmin

Johnny Gasperi
email: gasperi@u-pec.fr

Nicolas Flipo

Florence Habets

Bruno Tassin

Modelling the fate of nonylphenolic compounds in the Seine River -part 2: assessing the impact of global change on daily concentrations

Keywords: Nonylphenol, nonylphenol ethoxylate, endocrine disrupting compounds, global change

This study aims at modelling the daily concentrations of nonylphenolic compounds such as 4-nonylphenol (4-NP), nonylphenol monoethoxylate (NP 1 EO) and nonylphenoxy acetic acid (NP 1 EC) within the Seine River downstream of Paris City over a year, firstly in the present state (year 2010) and for years 2050 and 2100 in order to assess the consequences of global change on the fate of nonylphenolic compounds in the Seine river. Concentrations were first simulated for the year 2010 and compared to monthly measured values downstream of Paris. To achieve this goal, the hydrodynamic and biogeochemical model, ProSe, was updated to simulate the fate of 4-NP, NP 1 EO and NP 1 EC. The Seine upstream and Oise Rivers (tributaries of the Seine River) concentrations are estimated according to concentrations -flow relationships. For Seine Aval wastewater treatment plan (SA-WWTP), the concentrations are considered constant and the median values of 11 campaigns are used. The biodegradation kinetics of 4-NP, NP 1 EO and NP 1 EC in the Seine River were deduced from the results of the companion paper. The Nash-Sutcliffe coefficient indicates a good efficiency to simulate the concentrations of 4-NP, NP 1 EC and NP 1 EO over an entire year. Eight scenarios were built to forecast the impacts of global warming (flow decrease), population growth (SA-WWTP flow increase) and optimisation of wastewater treatment (improvement of the quality of effluents) on annual concentrations of 4-NP, NP 1 EO and NP 1 EC at Meulan by 2050 and 2100. As a result, global warming and population growth may increase the concentrations of 4-NP, NP 1 EC and NP 1 EO, especially during low-flow conditions, while the optimisation of wastewater treatment is an efficient solution to balance the global change by reducing WWTP outflows.

Introduction

Climate change at the scale of Europe is expected to increase the frequency of extreme events such as dry periods or storms [START_REF] Christensen | Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF]. These extreme events have significant influence on river flow rates such as long low-water periods or river flooding [START_REF] Habets | Impact of climate change on surface water and groundwater of two basins in Northern France: analysis of the uncertainties associated with climate and hydrological models, emission scenarios and downscaling methods[END_REF]. In addition to climate change, population growth and economic development of urbanized area are forecasted by the 21 st century [START_REF] Biasi | Parliament and of the Council of 23 October 2000 establishing a framework for Community action in the[END_REF].

Combining both aspects suggest that the European cities will likely put a higher pressure on receiving surface water during the 21 st century than at the end of 20 th century.

Global change on European river basins may lead to a disruption of the biogeochemical status of river as already predicted for nitrogen and phosphorus concentrations [START_REF] Andersen | Climate-change impacts on hydrology and nutrients in a Danish lowland river basin[END_REF][START_REF] Hadjikakou | Modelling nitrogen in the Yeilirmak River catchment in Northern Turkey: Impacts of future climate and environmental change and implications for nutrient management[END_REF][START_REF] Wilson | Simulating the impacts of future land use and climate changes on surface water quality in the Des Plaines River watershed[END_REF]. Despite the significant concern no study deals with the modelling of the global change influence on endocrine disruptor concentrations in surface water. Among the endocrine disruptors, nonylphenol ethoxylates NPnEO and especially 4-nonylphenol (4-NP) hold an important place due to their widespread presence all over the world [START_REF] Ahel | Behaviour of alkylphenol polyethoxylate surfactants in the aquatic environment--I. Occurrence and transformation in sewage treatment[END_REF][START_REF] Vethaak | An integrated assessment of estrogenic contamination and biological effects in the aquatic environment of The Netherlands[END_REF][START_REF] Bergé | Meta-analysis of environmental contamination by alkylphenols[END_REF] and their proved toxicity. 4-NP mainly originates from the biodegradation of non-ionic surfactants nonylphenol polyethoxylate (NPnEO) through anaerobic [START_REF] John | Mechanism for Biotransformation of Nonylphenol polyethoxylates to xenoestrogens in Pseudomonas putida[END_REF] or aerobic [START_REF] Jonkers | Aerobic biodegradation studies of nonylphenol ethoxylates in river water using liquid chromatography-electrospray tandem mass spectrometry[END_REF] processes. NPnEO are used in a large range of domestic and industrial detergents, as emulsifier or wetting agents with a world annual consumption of 500,000 tons in 2000 [START_REF] Ying | Environmental fate of alkylphenols and alkylphenol ethoxylates--a review[END_REF]. The fate of NPnEO in the environment is a important issue since their biodegradation products (nonylphenol monoethoxylate -NP 1 EO -nonylphenol acetic acid -NP 1 are recognized as being more toxic and estrogenic than the longer NPnEO [START_REF] Soto | Para-nonyl-phenol -An estrogenic xenobiotic released from modified polystyrene[END_REF]. [START_REF] Jugan | In vitro assessment of thyroid and estrogenic endocrine disruptors in wastewater treatment plants, rivers and drinking water supplies in the greater Paris area (France)[END_REF] reported that the 4-NP significantly contributes to the estrogenic activities found in surface water. Based on the toxicity of 4-NP on the aquatic wildlife, it has been added to the 33 priority pollutants of the Water Framework Directive 2000/60/EC (European Commission, 2000). The European directive 2008/105/EC (European Commission, 2008) fixed its annual average environmental quality standard (AA-EQS) within surface water at 300 ng/L.

The occurrence and fate of endocrine disrupting compounds such as 4-NP in river water are of concern for aquatic wildlife as well as regarding the capacity of European cities to provide safe drinkable freshwater to their residents. Therefore decision makers need reliable information to select the most efficient solutions to reach or maintain the good ecological status of water bodies as defined by the Water Framework Directive, in the upcoming years and decades. This issue is more crucial for the largest European cities such as London, Moscow or Paris since they are built in basins of very small rivers.

A modelling project was intended in 2010 to assess the long-term fate of nonylphenolic compounds in the Seine River was carried out in order to forecast the impacts of global change on the Parisian Metropolitan Area and it describes in two successive papers. Beyond studied compounds, this modelling project also attempts to give guidelines and methodology for fate modelling of other pollutants included in the list of priority pollutants (European Commission, 2000) or for emerging pollutants with close behaviours as regards their sources, transfer and biodegradability in surface water.

The first step, performed in a companion paper [START_REF] Cladière | Modelling the fate of nonylphenolic compounds in the Seine River -part 1: determination of in-situ attenuation rate constants[END_REF], aimed at setting up an efficient model by determining the in-situ attenuation rate constants of 4-NP, NP 1 EC and NP 1 EO within the Seine River. This first part provides relevant information on attenuation constant rates and reveals that the calibrated parameters vary significantly according to the biogeochemical conditions of the Seine River. Two parameter sets have been calculated from July and September 2011 campaigns and need to be tested over longer periods of time.

In this paper, this model is firstly validated over a complete year ( 2010 and at Meulan (downstream point) for the transect and in the Oise River at its confluence with the Seine River and SA-WWTP effluents for the tributaries, in 2L amber glass bottles (Fig. 1). These four sampling points provide all boundary conditions required to simulate this transect. The analytical procedure, including sample preparations and analyses (liquid chromatography coupled to a tandem mass spectrometry, UPLC-MS-MS), is described in details by Cladière et al., (2013b). This method enables the quantification of 4-NP, NP 1 EC and NP 1 EO concentrations in the dissolved phase of water samples.

Material and methods

Studying sites

Modelling tool: ProSe model

The hydrodynamic and biogeochemical ProSe model was firstly developed to simulate the impacts of human activities on the carbon, nitrogen, and phosphorus cycles in the Seine River and its tributaries [START_REF] Even | River ecosystem modelling: Application of the PROSE model to the Seine river (France)[END_REF][START_REF] Flipo | Biogeochemical modelling at the river scale: Plankton and periphyton dynamics: Grand Morin case study, France[END_REF][START_REF] Flipo | Primary production in headwater streams of the Seine basin: The Grand Morin river case study[END_REF]. For this study the biogeochemical module is updated to take into account the biodegradation pathways of NPnEO lastly updated in the literature by [START_REF] Giger | Environmental fate of phenolic endocrine disruptors: field and laboratory studies[END_REF]. The conceptual scheme of the modelling attempt and the input parameters needed to simulate daily concentrations of nonylphenolic compounds at Meulan are depicted in the Fig. 2. 2 Conceptual scheme of the modelling approach and the required inputs parameters.

[C]: concentrations of 4-NP, NP 1 EC and NP 1 EO As previously explained in the companion paper [START_REF] Cladière | Modelling the fate of nonylphenolic compounds in the Seine River -part 1: determination of in-situ attenuation rate constants[END_REF], the nonylphenol polyethoxylate biodegradation scheme [START_REF] Giger | Environmental fate of phenolic endocrine disruptors: field and laboratory studies[END_REF] and two sampling campaigns are used to determine biodegradation parameters. The attenuation rate constants K 1 , K 1 ' and K 2 represent the biotransformation of NP 1 EO and NP 1 EC into their products (NP 1 EC or NP) while K 3 represents the global disappearance of 4-NP from the dissolved phase and takes into account biodegradation, volatilisation and sorption onto particles without possibility to differentiate the processes [START_REF] Cladière | Modelling the fate of nonylphenolic compounds in the Seine River -part 1: determination of in-situ attenuation rate constants[END_REF]. Jonkers et al. (2005)

Determination of model efficiency

The efficiency of an annual simulation is evaluated by calculation of the Nash-Sutcliffe coefficient [START_REF] Nash | River flow forecasting through conceptual models part I : A discussion of principles[END_REF]) (NS, Equation 1)

( ) ( )         ∑ - ∑ - - = °°°°2 2 1 Avg Mes Sim Mes C C C C NS Equation 1
Where:

NS is the Nash-Sutcliffe efficiency coefficient C°M es is the measured concentration C°S im is the simulated concentration C°A vg is the average value of measured concentrations

The NS can range from -∞ to 1. A positive NS coefficient means that the model gives more accurate prediction than the average value of measured concentrations. The higher the value, the better the model. Commonly, a model could be considered as accurate if NS is higher than 0.4 [START_REF] Nash | River flow forecasting through conceptual models part I : A discussion of principles[END_REF].

Boundary conditions for 2010

Calculation methods for daily concentrations of boundary conditions

The boundary conditions such as flow rates and concentrations of nonylphenolic compounds (at Bougival, SA-WWTP and Oise River) are calculated on a daily basis. The river flow rates are extracted from national discharge gauging stations (supplementary data, Fig. S1) and the SA-WWTP flow rate is provided by the Paris public sanitation service. Concentrations of nonylphenolic compounds measured at Bougival, the Oise River, Seine Aval WWTP and Meulan as well as biogeochemical parameters are available in the supplementary material Table S1.

Concentration-flow relationships

[C] = a x Q -b
, where [C] is the concentration and Q the river flow rate were adjusted for year 2010 to the monthly sampling campaigns, for NP 1 EC and NP 1 EO at Bougival (Fig. 3) and for the NP 1 EC in the Oise River (supplementary data, Fig. S2).

NP1EC NP1EO

[ The coefficients of determination (R²), higher than 0.75 and a p value < 0.05, suggest that these relations are robust enough to estimate daily concentrations. The concentrations -flow relationship of 4-NP and NP 1 EO in the Oise River are based on linear correlations between fluxes (g/d) and river flow rate (Fig. S2). No concentration -flow relationship exists for 4-NP at Bougival and a polynomial interpolation of concentrations between two sampling campaigns has been used. The empirical correlations between concentrations and river flows are not designed to explain all processes involved in the fate of nonylphenolic compound but are intended to simplify building of daily concentrations in the Seine River.

Concerning SA-WWTP effluent quality and flow, no seasonal variation is observed. Flow rates (19.3 m 3 /s) and concentrations are, therefore, considered as constant and equal to their median values (n = 11, 4-NP: 133 ng/L; NP 1 EC: 842 ng/L and NP 1 EO: 120 ng/L).

Upstream daily concentrations in 2010

Based on the relationships between flow rate and compound concentrations, daily concentrations of 4-NP, NP 1 EC and NP 1 EO are built at Bougival and downstream the Oise River. These concentrations are compared to the measured ones at Bougival (Fig. 4) and downstream the Oise River (Fig. S3 in the supplementary data). , where large combined sewer overflows occurred (1,000,000 m 3 ), (Fig. 4). 5

The NS for the estimated boundary conditions are exhibited in Table 2. 6 The NS for NP 1 EC and NP 1 EO at Bougival and the Oise River are higher than 0.60, validate the methodology 9 used to define the model inputs. Concerning the 4-NP; for Bougival (NS = 1) by construction while the result for 10 the Oise River shows the low efficiency of our approach (NS = 0.03). 11

Scenarios of global change and boundary conditions for 2050 and 2100

12 Different projections of global changes in the Seine River basin are built for the middle and the late 21 st century 13 to assess their role on the evolution of concentrations in surface water. Three main drivers are considered for the 14 building of scenario: i) climate change, ii) growth of the Parisian population, iii) wastewater treatment 15 optimisation at SA-WWTP. 16

Currently no reliable information is available concerning the evolution of the European consumption of 17 nonylphenolic compounds in the future, and especially during the 21 st century. However a decrease of 18 consumption could be expected as a result of the European legislation on these compounds (Directive 19 2003/53/EC) and the availability of substitutes (U.S EPA, 2012). Forecasting the impacts of consumption 20 decrease of nonylphenolic compounds is a hard task due to their miscellaneous uses such as urban uses 21 (industrial wetting agent, detergent) and agricultural uses (pesticides). Actually, decrease of consumption would 22 influence concentrations of the upstream part of river basins (commonly used for agriculture) as well as urban discharges. Given the impossibility of currently modelling the impacts of consumption decrease of nonylphenolic compounds on the upstream part of the Seine River basin, their consumption is considered as constant during the 21 st century and this study will focus on the impacts of climate change, growth of the Parisian population and wastewater treatment optimisation.

Climate projections from CMIP3 (Coupled Model Intercomparison Project Phase 3) over Europe presents important variability [START_REF] Christensen | Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF]. In order to limit the number of simulations, two of these climate projections downscaled by a weather typing approach [START_REF] Boé | Projected changes in components of the hydrological cycle in French river basins during the 21st century[END_REF], which give contrasted results on the Seine River flow rate [START_REF] Habets | Impact of climate change on surface water and groundwater of two basins in Northern France: analysis of the uncertainties associated with climate and hydrological models, emission scenarios and downscaling methods[END_REF], are used. They are the ARP_CONT_A1B (ARP) and MPI_ECHAM5_A1B (MPI) and use the SRES-A1B gas emission scenario for the 21 st century [START_REF] Randall | Climate Models and Their Evaluation[END_REF]. ARP projects important decrease of rainfall by 2050 (-13.7 %) and 2100 (-21.8 %) while MPI projects less pronounced decrease (2050: +0.1 % and 2100: -6.9 %). Both models are in accordance with increases of potential evaporation and air temperature by 2050 and 2100 (supplementary data, Table S2).

The impacts of climate change on Seine and Oise River flows are estimated by the hydrogeological model MODCOU in the framework of the REXHYSS project [START_REF] Habets | Impact of climate change on surface water and groundwater of two basins in Northern France: analysis of the uncertainties associated with climate and hydrological models, emission scenarios and downscaling methods[END_REF] using these two downscaled climate projections (ARP and MPI). Thus, two projections of the monthly river flow rates are available for three different periods, the reference decade (2000 -2010), the middle (2045 -2055) and the late 21 st century (2090 -2100). The anomalies of river flow rates induced by climate change are calculated for every month by dividing the flow rates predicted in 2045 -2050 or 2090 -2100 by those simulated for the reference decade (2000 -2010). The ratios, thereby calculated, are exhibited in Table 3. According to these anomalies, daily river flows can be estimated for one dry year or one wet year in the decades All scenarios considered, are summarised in the Table 4. They are similar for a dry and a wet year in 2050 and 2100.

Results and discussion

3

Modelling of daily concentrations at Meulan over the reference year 2010

4

Based on the boundary conditions and the biodegradation parameters (July and September), daily concentrations 5 of 4-NP, NP 1 EC and NP 1 EO are modelled at Meulan and compared with the monthly sampling campaigns in 6 order to test the robustness of both biodegradation sets (July and September). 7

The simulation using the September biodegradation parameters are displayed in Fig. 5 while simulations using 8 the July biodegradation parameters are shown in Fig. S5 (supplementary data). With July parameters, the 9 simulated concentrations are far lower than the measured concentrations, likely due to the high attenuation rate 10 constants (about 1 d -1 ), and the seasonal cycle of concentrations is not reproduced (Fig. S5). The negative values 11 of NS (Table 5) confirm the inefficiency of these parameters to simulate concentrations at the annual scale and 12 reinforce the hypothesis of the disruption of the biogeochemical status of the Seine River in July 2011 (Cladière 13 et al., 2014). 14 As exhibited in Fig. 5 the simulated concentrations modelled by coupling the boundary conditions and the September biodegradation parameters, are close to the measured concentrations and reproduce the annual variation of concentrations of 4-NP, NP 1 EC and to a lesser extend NP 1 EO (previously underlined by Cladière et al., (2013b). The NS determined for this simulation range from 0.44 for NP 1 EC to 0.61 for NP 1 EO (Table 5) and suggest that the model, using September biodegradation parameters is efficient to predict annual concentrations in the Seine River at Meulan.

Moreover, the 4-NP AA-EQS (300 ng/L) is never exceeded in the Seine River at Meulan downstream of all urban discharges. This observation likely results from the low concentrations in SA-WWTP effluent (133 ng/L) and the biodegradation occurring within the Seine River.

This modelling approach has, however, three possibility of improvement for modelling of daily concentrations of nonylphenolic compounds. First, this study focuses on dry weather conditions which represent the most important part of the year but cause punctual underestimations of NP 1 EO concentrations at Bougival and Meulan. Indeed, combined sewer overflows may constitute significant alkylphenol inputs into the Seine River during wet weather conditions (Cladière et al., 2013b). Second, SA-WWTP effluent is assumed to remain constant all over the year which is not entirely representative since variabilities of concentrations are observed from a campaign to another. Finally, the biodegradation parameters remain constant in the model over the year, while the water temperature variability between summer and winter (± 10°C) may affect the biodegradation constant rates [START_REF] Manzano | The effect of temperature on the biodegradation of a nonylphenol polyethoxylate in river water[END_REF]. Moreover, the results between July and September 2011 highlight discrepancies according to the biogeochemical status of the Seine River [START_REF] Cladière | Modelling the fate of nonylphenolic compounds in the Seine River -part 1: determination of in-situ attenuation rate constants[END_REF]. However, despite these deficiencies, the current simulations are satisfying to predict the annual concentrations of 4-NP, NP 1 EC and NP 1 EO in the Seine River. Therefore, in the context of the parsimony of our approach, these deficiencies are not determining for modelling the daily concentrations of nonylphenolic compounds in the Seine River and could be neglected.

Forecasted concentrations in the middle of 21 st century (2045 -2055)

The 4-NP and NP 1 EC concentrations were simulated at Meulan for one dry or wet year in the decade 2045 -2055 (Fig. 6). NP 1 EO concentrations are not discuss because of their significant variability (± 37 %) pointed out in [START_REF] Cladière | Modelling the fate of nonylphenolic compounds in the Seine River -part 1: determination of in-situ attenuation rate constants[END_REF]. In addition, the increase of air temperature by 2050 (+ 2 K) or 2100 (+ 3 K) (probably lower for water temperature) is not considered since the variability intra-annual in 2010 (± 10 K) seems not influence the modelling of the fate of nonylphenolic compounds in the Seine River.

The forecasted concentrations for the middle of the 21 st century are compared with the ones of 2010 hereafter.

Dry year

As underscored by the scenario ARP_base_2050 and MPI_base_2050 during one dry year (Fig. 6), the long lowwater period has a significant influence on NP 1 EC concentrations and to a lesser extent on 4-NP concentrations.

Without optimisation of Seine Aval WWTP (baseline scenario), the concentrations of NP 1 EC reach 300 ng/L in July and exceed 250 ng/L from June to December according to the ARP_base_2050 scenario (against 200 ng/L for MPI_base_2050). Although the current concentrations are about 150 ng/L, it may become a concern in the future if the SA-WWTP does not improve its efficiency.

Wet year 3

Fig. 6 shows that during one wet year in the decade 2045 -2055 the concentrations of NP 1 EC and 4-NP are not 4 higher than concentrations simulated for 2010, even without optimisation of SA-WWTP. 5

Both ARP and MPI scenarios predict similar drops of 4-NP and NP 1 EC concentrations during Seine River 6 flooding (from March to May). The decreases of concentrations are more significant for the MPI projection 7

(NP 1 EC < 20 ng/L from 18 th March to 6 th May) than for the ARP projection (NP 1 EC < 20 ng/L from 15 th March to 1 st April). However, the wet weather urban sources, which may play a significant role during a wet year, are not taken into account in this forecast. The concentrations of nonylphenolic compounds predicted during the river flooding are, therefore, likely underestimated. This has to be confirmed or contradicted by further studies.

At last, the optimisation of SA-WWTP has a smaller influence during a wet year than a dry year (Fig. 6), mainly explained by effluent dilution factor during a wet year (about 37) against a dry year (about 11).

Forecasted concentrations in the late 21 st century (2090 -2100)

4-NP and NP 1 EC concentrations at Meulan are simulated for one dry or wet year in the decade 2090 -2100 (Fig. 7).

Dry year

The observations are similar to 2050 but the trends are reinforced especially at the end of autumn (November).

Indeed, without optimisation of SA-WWTP, the ARP_base_2100 scenario projects that the NP 1 EC concentrations may reach 350 ng/L in July and exceed 250 ng/L during 7 months. For MPI_base_2100 scenario, the highest concentration (350 ng/L) is reached in November and the concentrations exceed 300 ng/L from October to December. To a lesser extent, similar observations are noticeable for 4-NP concentrations. Despite the long low-water period forecasted for a dry year by 2100, no exceedance of the current AA-EQS is pointed out for both baseline scenarios. However, like for 2050, the NP 1 EC concentration is of concern for downstream stations due to biodegradation processes.

As previously observed for 2050, the optimisation of SA-WWTP may counterbalance the impacts of climate change coupled to the growth of the Parisian population from January to October (ARP and MPI projections).

During this period the concentrations of 4-NP and NP 1 EC are close to those simulated for 2010. Nevertheless, despite the significant decrease of 4-NP and NP 1 EC concentrations due to SA-WTTP optimisation, the latter may exceed concentrations of 2010 from October to December. These differences are likely due to the long lowwater period (June to December).

Dry year

Wet year

Conclusions

A global project of modelling the fate of nonylphenolic compounds in river water was launched in 2010 with the objectives to determine in-situ attenuation rate constants and to apply them to simulate their annual behaviour for present and upcoming years [START_REF] Cladière | Modelling the fate of nonylphenolic compounds in the Seine River -part 1: determination of in-situ attenuation rate constants[END_REF] and this paper).

In pursuit of the first part paper, this study aimed at testing the biodegradation parameters and at using them to forecast the fate of nonylphenolic compounds in the Seine River in the middle and the late 21 st century.

In a first step, the modelling of annual concentrations of 4-NP, NP 1 EC and NP 1 EO at Meulan in the Seine River reveals that the biodegradation parameters calibrated in September 2011 have been validated for the year 2010 and can be used to forecast the fate of nonylphenolic compounds in the middle and the late 21 st century. Although the assessed changes are the most important expected on the Seine River basin, the parsimony of our approach leads to disregard others significant factors such as evolution of nonylphenolic compound consumption or the intra-annual variability of concentrations because of the scarcity of reliable information. In addition, all annual simulations are performed under dry weather conditions and do not considered the wet weather urban sources. Thus, the concentrations forecasted for the 21 st century could be punctually underestimated since combined sewer overflows and urban runoff are significant sources of nonylphenolic compounds in the Seine River during storm events, as previously demonstrated for 2010 by Cladière et al., (2013b).

Ultimately, the two parts of this study highlight that the coupling between analytical chemistry, biogeochemical modelling is, despite its limits, a key tool to understand and forecast the fate of nonylphenolic compounds in surface waters and the influence of global change. This study gives the first guidelines and considerations for forecasting the fate of pollutants in surface water during the 21 st century. Therefore, this kind of approach could be applied to other pollutants such as priority pollutants (European Commission, 2000) or emerging pollutants.

  ) by comparing results to data collected monthly at different locations on the Seine River catchment. Then, the impact of global change in the Seine River basin on daily concentrations of nonylphenolic compounds is assessed over one year in the middle (2045 -2055) and the late (2090 -2100) 21 st century. Two aspects of the global change are considered: i) the climate change (based on two contrasted projections), ii) the growth of the Parisian population and iii) the wastewater treatment optimisation in the Parisian largest plant.

  Fig. 1 Simulated transect downstream of Paris City and sampling sites

  Fig. 3 Relationships between NP 1 EC and NP 1 EO concentrations and Seine River flow at Bougival

  Daily concentrations of 4 NP, NP 1 EC and NP1EO at Bougival in the Seine River in 2010 versus measured 2 concentrations 3 Modelled concentrations match concentrations measured at Bougival, except for the March campaign (23 March 4 2010)

  2045 -2055 or 2090 -2100. The present day proxy of a dry year is based on the year 2005 which had a pronounced low-water period (from June to October 2005) and the present day proxy of the wet year is 2001 which had a significant river flooding during spring. Thus, for instance; a dry year (wet year) in the middle and late 21 st century is estimated to have the daily river flow rate of2005 (2001) corrected by the monthly ratios calculated (Table3). The Seine and Oise River flow rates predicted for a dry and a wet year in 2045 -2050 and 2090 -2100 are shown in Fig. S4 (supplementary data). The estimate of the Parisian population growth by 2050 was provided by the French National Institute of Statistics and Economic Studies (INSEE). By 2050, the Parisian population should reach between 11 millions (low hypothesis) and 15 millions (high hypothesis) of inhabitants with a median hypothesis of 13 millions of inhabitants, which means an increase of 11.7 % compared to 2009 (De Biasi, 2010). No study focuses on the Parisian population growth by 2100; however by linear extrapolation of the median hypothesis for 2050 the population could be estimated about 14.7 millions of inhabitants (+26 % compared with 2009). Assuming that the water consumption per capita remains constant during the 21 st century, the growth of the Parisian population leads to an increase of wastewater volume treated daily. Therefore, the SA-WWTP flow rate is estimated at 22.6 m 3 /s in 2050 and 24.3 m 3 /s in 2100 (2010 flow rate: 19.3 m 3 /s).Finally, the optimisation of wastewater treatment of SA-WWTP is also taken into account. Currently this WWTP uses activated sludge coupled to a single stage biofiltration. In the upcoming years, the treatment will be optimised by implementing essentially a three stage biofiltration. Consequently, two scenarios for SA-WWTP are simulated: 1) the wastewater treatment remains similar (baseline scenario) and 2) the wastewater treatment is optimised (optimised scenario). For the first scenario, SA-WWTP effluent concentrations in 2010 (4-NP: 133 ng/L, NP 1 EC: 842 ng/L and NP 1 EO: 120 ng/L) are considered. For the second scenario, concentrations found at the most efficient WWTP in 2010 in Paris Metropolitan Area, where the three stage biofiltration is already implemented, are applied (4-NP: 85 ng/L, NP 1 EC: 214 ng/L et NP 1 EO: 74 ng/L)(Cladière et al., 2013b).

  Simulated concentrations of 4 NP, NP 1 EC and NP 1 EO at Meulan using the Prose model (September 16 parameter set) versus measured concentrations 17 18

Fig. 6

 6 Fig. 6 Forecasted concentrations of 4 NP and NP 1 EC for one dry and wet year in the decade 2045 -2055 1 2

Fig. 7

 7 Fig. 7 Forecasted concentrations of 4 NP and NP 1 EC for one dry or wet year in the decade 2090 -2100

For

  the first time, this study provides relevant results on the fate of micropollutants in river water with regard to global change. In this study, climate change, the growth of the Parisian population and the optimisation of Seine Aval wastewater treatment plant for the middle (2050) and the late (2100) 21 st century were considered.The first forecasts by 2050 and 2100 underscore the key impact of low-water periods on NP 1 EC and 4-NP concentrations downstream of Paris City. These longer and more pronounced low water periods (according to the climate change projections ARP_CONT_A1B and MPI_ ECHAM5_A1B) combined with the growth of the Parisian population, could lead to significant concentration increases in autumn. Wastewater treatment optimisation (currently in progress for SA-WWTP) appears to be an efficient solution to limit the impacts of population growth and low-water periods by 2050 and to a lesser extent by 2100.

Biodegradation parameters BOUGIVAL Flow rate [C] time series SA-WWTP Flow rate [C] time series Seine River (hydrodynamic module) K 1 , K 1 ', K 2 , K 3 Meulan [C] time series Boundary conditions Results Precursor inputs Precursor inputs Precursor inputs OISE RIVER Flow rate [C] time series Biodegradation parameters BOUGIVAL Flow rate [C] time series BOUGIVAL Flow rate [C] time series SA-WWTP Flow rate [C] time series SA-WWTP Flow rate [C] time series Seine River (hydrodynamic module) K 1 , K 1 ', K 2 , K 3 K 1 , K 1 ', K 2 , K 3 Meulan [C] time series Meulan [C] time series Boundary conditions Results Results Precursor inputs Precursor inputs Precursor inputs Precursor inputs Precursor inputs Precursor inputs OISE RIVER Flow rate [C] time series OISE RIVER Flow rate [C] time series Fig.

Table 2

 2 Nash-Sutcliffe efficiency coefficients for boundary conditions 7

	Site	Simulation type	4-NP	NP1EC	NP1EO
	Bougival	Boundary condition building	1,00	0,83	0,69
	Oise	Boundary condition building	0,03	0,78	0,61
	8

Table 3

 3 Impact of the climate change scenario ARP and MPI on the Seine River flow at Bougival and the Oise River flow

				Seine River					Oise River
		Reference	ARP	MPI	Reference	ARP	MPI
		2000-2010 2045-2055 2090-2100 2045-2055 2090-2100 2000-2010 2045-2055 2090-2100 2045-2055 2090-2100
		Flow	Anomalies	Anomalies	Anomalies	Anomalies	Flow	Anomalies	Anomalies	Anomalies	Anomalies
		(m 3 /s)	ratio	ratio	ratio	ratio	(m 3 /s)	ratio	ratio	ratio	ratio
	January	515	1.0	1.0	0.7	0.6	179	0.9	1.0	0.9	0.7
	February	487	1.1	1.3	0.8	0.8	175	1.1	1.4	0.9	0.9
	March	433	1.3	1.0	1.0	1.1	154	1.2	1.0	1.0	1.0
	April	338	0.8	0.7	1.4	1.1	127	0.8	0.7	1.2	1.0
	May	239	0.5	0.5	1.2	0.7	88	0.6	0.5	1.0	0.7
	June	153	0.6	0.5	1.0	0.8	64	0.6	0.5	1.0	0.7
	July	144	0.8	0.6	1.1	0.7	51	0.7	0.6	1.1	0.7
	August	126	0.7	0.5	1.1	0.7	39	0.6	0.6	1.0	0.7
	September	146	0.6	0.6	0.8	0.6	41	0.6	0.6	0.9	0.7
	October	211	0.6	0.6	0.8	0.4	50	0.7	0.6	0.8	0.5
	November	314	0.7	0.6	0.9	0.5	81	0.7	0.7	0.9	0.6
	December	439	0.8	0.7	1.2	0.9	148	0.7	0.7	1.1	0.9

Table 4 Description of changes considered for one dry or wet year in periods 2050 and 2100 and their

 4

	1
	2	corresponding name
		Year	Climate change model	Population growth	Seine Aval WWTP	Name of scenario
		2050	ARP_CONT_A1B	+ 11.7 %	Baseline scenario	ARP_base_2050
		2050	ARP_CONT_A1B	+ 11.7 %	Optimised scenario	ARP_opt_2050
		2050	MPI_ECHAM5_A1B	+ 11.7 %	Baseline scenario	MPI_base_2050
		2050	MPI_ECHAM5_A1B	+ 11.7 %	Optimised scenario	MPI_opt_2050
		2100	ARP_CONT_A1B	+ 26 %	Baseline scenario	ARP_base_2100
		2100	ARP_CONT_A1B	+ 26 %	Optimised scenario	ARP_opt_2100
		2100	MPI_ECHAM5_A1B	+ 26 %	Baseline scenario	MPI_base_2100
		2100	MPI_ECHAM5_A1B	+ 26 %	Optimised scenario	MPI_opt_2100

Table 5

 5 Nash-Sutcliffe efficiency coefficients for annual modelling at Meulan

	Site	Simulation type	4-NP	NP1EC	NP1EO
	Meulan	ProSe modelling (July constants)	-0,25	-1,64	-0,44
	Meulan	ProSe modelling (September constants)	0,55	0,44	0,61

Moreover, this study could support the implementation of the Water Framework Directive and its daughter Directives in surface water in the upcoming years and decades.

Acknowledgment

The authors want to thank Science of the Total Environment for the permission to archive the post-print version of the manuscript.