Kelsey Flanagan
email: kelsey.flanagan@enpc.fr

Philippe Branchu
email: philippe.branchu@cerema.fr

Lila Boudahmane

Emilie Caupos

Dominique Demare

Steven Deshayes

Philippe Dubois

Laurent Meffray

Chandirane Partibane

Mohamed Saad

Marie- Christine Gromaire

Field performance of two biofiltration systems treating micropollutants from road runoff

Keywords: Biofiltration, swale, vegetative filter strip, road runoff, micropollutant, low impact development

The treatment efficiency of a vegetative filter strip and a biofiltration swale treating heavily loaded road runoff are evaluated. Concentrations measured in water drained from the two systems are compared to those in untreated road runoff collected from a reference catchment for a wide range of contaminants including organic carbon, nutrients (N and P), metallic trace elements, and organic micropollutants (polycyclic aromatic hydrocarbons (PAH), total petroleum hydrocarbons (TPH), alkylphenols, bisphenol-A, phthalates), in both total and dissolved phases. Predominantly particulate pollutants, including Pb, Zn and PAH, were very efficiently removed (around 90%) for most events. However, poor particulate removal was observed during a winter period. Relatively few pollutants were significantly removed in the dissolved phase and observed concentration reductions tended to be lower than those of suspended solids and associated pollutants; as such, lower removals were observed for total concentrations of moderately particulate micropollutants, including bisphenol-A, alkylphenols and phthalates. In addition, some pollutants appear to be emitted from various biofilter components (filter media, drainage and lining materials), as low or negative concentration removals were observed during the first months of operation of the biofiltration swale.

Introduction

The creation of impermeable surfaces associated with urbanization poses a threat to aquatic ecosystems due to both increased runoff flows and water quality degradation. Road runoff, in particular, has long been considered to be particularly polluted by a range of contaminants including total suspended solids (TSS), nutrients, total petroleum hydrocarbons (TPH), trace metals and polycyclic aromatic hydrocarbons (PAH) [START_REF] Brown | Sources of heavy metals and polycyclic aromatic hydrocarbons in urban stormwater runoff[END_REF][START_REF] Huber | Critical review of heavy metal pollution of traffic area runoff: Occurrence, influencing factors, and partitioning[END_REF][START_REF] Kayhanian | Review of highway runoff characteristics: Comparative analysis and universal implications[END_REF].

More recently, research has demonstrated the presence of a wider range of organic micropollutants, including alkylphenols, phthalates, bisphenol-A (BPA) and pesticides, some of which are considered priority substances in the European Water Framework Directive (EC, 2013), in urban [START_REF] Bressy | Towards the determination of an optimal scale for stormwater quality management: Micropollutants in a small residential catchment[END_REF][START_REF] Gasperi | Micropollutants in urban stormwater: occurrence, concentrations, and atmospheric contributions for a wide range of contaminants in three French catchments[END_REF][START_REF] Zgheib | Priority pollutants in urban stormwater: Part 1 -Case of separate storm sewers[END_REF] and road runoff [START_REF] Björklund | Phthalates and nonylphenols in urban runoff: Occurrence, distribution and area emission factors[END_REF].

Within this context, new paradigms, referred to as low impact development (LID), sustainable drainage systems (SuDS) or water sensitive urban design (WSUD), have emerged for managing urban stormwater close to the source. These approaches often rely on localized, vegetated systems that are designed to achieve multiple objectives, such as restoring the hydrologic balance of a site to that before development, improving water quality and contributing to the urban landscape and biodiversity [START_REF] Fletcher | SUDS, LID, BMPs, WSUD and more -The evolution and application of terminology surrounding urban drainage[END_REF].

One technique often employed when water quality improvement is a priority is that of bioretention or biofiltration, consisting of a vegetated depression that receives and stores runoff water, which then filters through a filter media made of engineered soil, before being collected by an underdrain or exfiltrated to the surrounding soil [START_REF] Davis | Bioretention technology: Overview of current practice and future needs[END_REF][START_REF] Roy-Poirier | Review of bioretention system research and design: past, present, and future[END_REF]. These systems may also be referred to as rain gardens or, if in a linear form, as biofiltration swales or bioswales.

In other LID devices, such as vegetative filter strips and grassed swales, generally designed to transport and pretreat water at the surface but in which large proportions of runoff may infiltrate for common, low-intensity rain events [START_REF] Flanagan | Evaluation of the relative roles of a vegetative filter strip and a biofiltration swale in a treatment train for road runoff[END_REF], infiltrated water is depolluted by processes analogous to those occurring in bioretention systems. In all of these systems, which for the purposes of this paper will both be regrouped under the term biofilter, particulate pollutants are expected to be removed through sedimentation and physical filtration and dissolved pollutants through various processes, including sorption, biodegradation, volatilization and plant uptake [START_REF] Lefevre | Review of Dissolved Pollutants in Urban Storm Water and Their Removal and Fate in Bioretention Cells[END_REF].

The efficiency of these systems at treating conventional pollutants, such as TSS, nitrogen, phosphorus and trace metals, has been well documented [START_REF] Brown | Underdrain Configuration to Enhance Bioretention Exfiltration to Reduce Pollutant Loads[END_REF][START_REF] Davis | Field Performance of Bioretention: Water Quality[END_REF][START_REF] Hatt | Hydrologic and pollutant removal performance of stormwater biofiltration systems at the field scale[END_REF][START_REF] Hsieh | Multiple-event study of bioretention for treatment of urban storm water runoff[END_REF][START_REF] Hunt | Evaluating Bioretention Hydrology and Nutrient Removal at Three Field Sites in North Carolina[END_REF][START_REF] Hunt | Pollutant Removal and Peak Flow Mitigation by a Bioretention Cell in Urban Charlotte, N.C[END_REF][START_REF] Li | Water Quality Improvement through Reductions of Pollutant Loads Using Bioretention[END_REF][START_REF] Trowsdale | Urban stormwater treatment using bioretention[END_REF]. However, only a few of these studies [START_REF] David | Removal Efficiencies of a Bioretention System for Trace Metals, PCBs, PAHs, and Dioxins in a Semiarid Environment[END_REF][START_REF] Li | Water Quality Improvement through Reductions of Pollutant Loads Using Bioretention[END_REF][START_REF] Trowsdale | Urban stormwater treatment using bioretention[END_REF] distinguish the dissolved phase of any trace metals. While the generally efficient removal of TSS indicates that the particulate fractions of pollutants are likely to be well removed, the in situ behavior of dissolved pollutants, which are more biologically available, subject to different removal processes and likely more mobile than their particulate counterparts, remains obscure [START_REF] Lefevre | Review of Dissolved Pollutants in Urban Storm Water and Their Removal and Fate in Bioretention Cells[END_REF].

In addition, relatively few studies have considered the treatment efficiency of organic micropollutants. Although two biofiltration systems evaluated by [START_REF] Zhang | The validation of stormwater biofilters for micropollutant removal using in situ challenge tests[END_REF] demonstrated high removal efficiencies for a wide range of organic micropollutants, including TPH, PAH, herbicides, phthalates, trihalomethanes and phenols, using in situ columns and synthetic runoff, few micropollutants have been studied in biofiltration systems using real runoff. Indeed, among a hierarchy of priority micropollutants associated with road runoff (PAH>alkanes (C 20 -C 40 ) > alkylphenols > phthalates > aldehydes > phenolic antioxidants > bisphenol A (BPA) > oxygenated PAH > naphtha C 5 -C 12 > amides > amines) identified by [START_REF] Markiewicz | Emissions of organic pollutants from traffic and roads: Priority pollutants selection and substance flow analysis[END_REF], only PAH have been addressed by in situ studies of biofiltration treatment efficiency for real rain events [START_REF] David | Removal Efficiencies of a Bioretention System for Trace Metals, PCBs, PAHs, and Dioxins in a Semiarid Environment[END_REF][START_REF] Diblasi | Removal and Fate of Polycyclic Aromatic Hydrocarbon Pollutants in an Urban Stormwater Bioretention Facility[END_REF][START_REF] Leroy | Performance of vegetated swales for improving road runoff quality in a moderate traffic urban area[END_REF]. Beyond this list, [START_REF] David | Removal Efficiencies of a Bioretention System for Trace Metals, PCBs, PAHs, and Dioxins in a Semiarid Environment[END_REF] also considered the behavior of polychlorinated biphenyls and dioxin. None of these studies distinguished the dissolved fraction of organic micropollutants.

The goal of the present work is to evaluate the in situ treatment performance of two biofilters receiving road runoff, a biofiltration swale and a vegetative filter strip, for previously studied pollutants (TSS, nutrients, trace metals, major elements and PAH) as well as emerging micropollutants as yet uncharacterized by field studies of biofiltration (BPA, alkylphenols, and phthalates). In order to improve scientific understanding of biofiltration performance for dissolved pollutants, efficiencies are reported for both the total and dissolved phases of pollutants.

Material and Methods

Experimental site description

The experimental site consists of a heavily trafficked (11 000 vehicles/day/direction) 4-lane highway and its drainage systems (Figure 1). The road, RD 212, was redeveloped in 2012, is made of asphalt sealed with bitumen and is in good condition. It is located in an industrial zone of Compans, France, a community near Charles de Gaulle Airport in the Paris metropolitan area and has a speed limit of 90 km/h. The industrial zone includes gas storage and conditioning, hydrocarbon storage and distribution, polymer fabrication and dangerous waste treatment activities, all of which are separated from the study site by several hundred meters and a line of trees. This region has a warm temperate climate with no dry season [START_REF] Peel | Updated world map of the Köppen-Geiger climate classification[END_REF], receives an average of 637 mm of rainfall per year over an average of 111 days of precipitation (>1 mm) and experiences 25 days of freezing temperatures per year (Agence Parisienne du Climat and Météo-France, 2015). Two linear biofilters, a vegetative filter strip (VFS) and a biofiltration swale (BFS), are studied (Figure 2). Both are located on the road shoulder and receive direct runoff from a single direction of traffic.

The VFS was constructed in September 2012 and planted with a floral prairie seed mixture. Infiltrated water is drained at a depth of 15 cm using a sheet drain. The BFS was constructed in March 2016 and planted with Carex gracilis. The swale is separated into three sections using small, concrete check dams; the average ponding depth is 17 cm. It is lined with a geomembrane and drained with an agricultural drain wrapped in synthetic fabric located at the base of its filter medium at a depth of 50 cm. The filter media of both devices were prepared by mixing 40% silt loam topsoil with 60% 0-4 mm limestone sand by volume. Therefore, the two media have similar properties (Table 1), although higher organic content and lower pH are observed in the VFS, likely an effect of system aging. Another portion of the RD 212, where runoff is directed towards a manhole along a concrete curb, is studied as a reference catchment. This portion, located on the same side of the road, 68 m from the edge of the BFS catchment, is made of the same asphalt in similar condition, has a similar slope, identical traffic and is subject to similar rain and sun exposure as the other catchments. Runoff from this segment represents untreated road runoff in a traditional drainage system.

Vegetative filter strip

Field methods

Stormwater was collected at three points representing untreated road runoff (RR) from the reference watershed, water drained from the vegetative filter strip (VFS) and water drained from the biofiltration swale (BFS).

At each point, flow was continuously measured using a tipping bucket flow meter (17L bucket volume at RR and 1L volume at BFS and VFS). Flow proportional event mean samples were collected using two refrigerated automatic samplers at RR and passive flow dividers (tubes placed so as to collect a known fraction of each bucket tip) at VFS and BFS (see Supplementary Information for further description).

Materials in contact with sampled water were chosen carefully to avoid contamination. All tubing was coated in Teflon, and for each event, samples were collected in plastic bottles for metal, major element, nutrient and global parameter analyses, and in glass bottles for organic micropollutant analyses. Between each event, all bottles were washed with detergent (Extran for plastic bottles, TDF4 for glass bottles), rinsed several times with tap water, thrice with deionized water and twice with ultrapure water.

Field blanks were analyzed to verify that sampling equipment or procedures did not lead to sample contamination (Supplementary Data). While contamination was negligible for most species, slight but analytically significant increases (5-13% of median dissolved concentration) in As, Cu, V, Zn and NP 1 EC and a larger increase (67%) of Mo were observed from RR sampling equipment. Although an initial RR campaign during which water was left to stagnate 4h in the equipment showed contamination by all phthalate molecules, a second campaign, conducted under more realistic flow conditions, showed no contamination.

Sampling equipment was deployed in response to meteorological predictions of significant (>2mm) rainfall and samples collected within 36h of the beginning of rainfall for the targeted runoff event, with the exception of one exceptionally long, continuous event lasting 40h, and within 24h of the end of RR runoff to ensure adequate sample conservation.

A total of 19 sampling campaigns were undertaken between February 2016 and July 2017, covering all four seasons and various hydrologic conditions (Table 2). While the goal was to collect inlet and outlet samples simultaneously, due to the later construction of the BFS and various technical difficulties, not all samples were available for each sampling period: 14, 15, and 18 samples were collected for RR, BFS and VFS, respectively. Sampling efficiency (the proportion of each event volume represented in the event mean sample) is discussed in Supplementary Information.

Median (min, max) Total Rainfall (mm) 7.

Analytical methods

Samples were analyzed for a range of global parameters, including pH, electrical conductivity (EC), turbidity, total suspended solids (TSS), organic carbon (OC), nutrients (N and P forms), as well as 12 trace metals, 9 major elements, C 10 -C 40 hydrocarbons (TPH), 19 polycyclic aromatic hydrocarbons (PAH), bisphenol-A (BPA), 7 alkylphenols (AP) and 5 phthalates (PAE) (for detailed list see Table 3).

Nutrients were analyzed in the total and dissolved phases, while OC, metals, major elements and organic micropollutants were analyzed in the particulate and dissolved phases.

Upon reception, samples were divided into aliquots for the analysis of different pollutants. Aliquots used for the analysis of TSS, OC, BPA, AP and PAE were filtered immediately; the filtrate was extracted within 24h, while filters were freeze-dried before extraction. Other aliquots were put on ice and sent to partner laboratories within 24h of collection for the analysis of nutrients, TPH, PAH (Cerema in Trappes, France), trace and major elements (IFSTTAR in Nantes, France). These samples were filtered upon arrival at the partner laboratory.

Extraction and analytical methods are summarized in Table 3. Dissolved and Total: 1 (KN), 0.1 (P) mg/L Dissolved: 0.04 (N-NH4 + ), 0.08 (N-NO2 -), 0.05 (N-N03 -), 0.16 (P-PO4 3-) mg/L CL: 95% Specified level (SL): 5 (KN), 0.2 (P), 0.08 (N-NH4 + ), 0.08 (N-NO2 - ), 0.11 (N-N03 -), 0.16 (P-PO4 3-) mg/L Absolute uncertainty between LQ and SL: ± 0.5 (KN), 0.04 (P), 0.02 (N-NH4 + ), 0.05 (N-NO2 -), 0.01 (N-N03 -), 0.07 (P-PO4 3-) mg/L Relative uncertainty beyond SL: ±10 (KN), 20 (P), 20 (N-NH4 + ), 20 (N-NO2 -), 10 (N-N03 -), 10 (P-PO4 Dissolved: 100 (Al), 0.1 (As), 5 (Ba), 100 (Ca), 0.1 (Cd), 2 (Co), 0.1 (Cr), 0.2 (Cu), 5 (Fe), 100 (K), 10 (Mg), 1 (Mn), 2 (Mo), 100 (Na), 0.2 (Ni), 0.1 (Pb), 0.06 (Si) , 1 (Sr), 2 (Ti), 0.1 (V), 0.3 (Zn) µg/L Particulate: 20 (Al), 1 (As), 1 (Ba), 20 (Ca), 0.1 (Cd), 0.4 (Co), 1 (Cr), 0.4 (Cu), 1 (Fe), 20 (K), 2 (Mg), 0.2 (Mn), 0.4 (Mo), 20 (Na), 1 (Ni), 1 (Pb), 200 (Si), 0.1 (Sr), 0.4 (Ti), 0.4 (V), 1 (Zn) mg/kg CL: 95% Dissolved: ± 7 (Al), 9 (As), 9 (Ba), 8 (Ca), 8 (Cd), 6 (Co), 11 (Cr), 9 (Cu), 6 (Fe), 10 (K), 6 (Mg), 7 (Mn), 9 (Mo), 9 (Na), 11 (Ni), 9 (Pb), 8 (Sr), 8 (Ti), 10 (V), 14 (Zn) % Particulate: ± 10 (Al), 11 (As), 10 (Ba), 9 (Ca), 24 (Cd), 14 (Co), 13 (Cr), 14 (Cu), 11 (Fe), 9 (K), 10 (Mg), 13 (Mn), 23 (Mo), 9 (Na), 15 (Ni), 16 (Pb), 10 (Sr), 12 (Ti),13 (V), 13 (Zn) %

TPH

Total petroleum hydrocarbons C10-C40 (TPH) Table 3: Summary of employed analytical methods. M is the mass of TSS extracted in mg, which varied according to the concentration of TSS in the water sample and the filtered volume.

Filter
Abbreviations: ICP-OES (inductively coupled plasma optical emission spectroscopy), ICP-MS (inductively coupled plasma mass spectrometry), GC-MS (gas chromatography coupled with mass spectrometry), UPLC-MSMS (ultra performance liquid chromatography with tandem mass spectrometry); GC-FID (gas chromatography -flame ionization detector)

Calculation of performance indicators, uncertainty propagation and statistical methods

All statistical calculations were carried out using the software environment, R.

The significance of differences between inlet and outlet concentrations, taking into account interevent variability was evaluated using the Wilcoxon Signed-Rank Test, a non-parametric, paired test.

Correlations between parameters were tested using the Spearman Rank Correlation Test, also a nonparametric method.

The studied biofiltration devices, installed to treat water from a catchment expected to generate highly polluted runoff, were designed with a specific objective of improving water quality to protect the quality of groundwater. Therefore, its efficiency at achieving this objective was evaluated according to concentration reduction (E c ), which was calculated according to Equation 1 for events for which (1) both RR and the outlet were sampled and (2) RR and/or the outlet concentrations were superior to the limit of quantification (LQ). When one of the concentrations was below the LQ, it was set equal to the LQ, making the E c a lower bound if the pollutant was below the LQ at the outlet and an upper bound if it was below the LQ only at the inlet.

(Eq. 1)

where E c is the event concentration reduction efficiency in %, C RR is the road runoff concentration and C outlet is the BFS or VFS concentration.

As analytical uncertainties were sometimes large, especially for organic micropollutants, the analytical significance of each calculated E c was considered. E c was considered to be analytically significant if its efficiency was greater than the uncertainty in E c , propagated from the concentrations used in its calculation according to the rules of uncertainty propagation [START_REF] Taylor | An Introduction to Error Analysis[END_REF], assuming their errors to be independent. Uncertainty calculations are further detailed in Supplementary Information. Results were summarized with the indicator F sig , the fraction of events with a significant concentration reduction, calculated for each pollutant.

Concentration probability distributions at each point were visualized using a logarithmic scale on the concentration axis, according to the recommendations of GeoSyntec Consultants et al. (2002).

Results

Characterization of road runoff

The characteristics of the untreated road runoff (RR) are summarized in Tables 4-7 and described below. Results for TSS, organic carbon, trace metals and organic micropollutants are described below while those for other global parameters (pH, EC, nutrients) are presented in Supplementary Information.

Global Parameters TSS concentrations (median 291 mg/L, Table 4) always exceeded the national objective concentration of 50 mg/L for surface waters (MEEM, 2016) and were higher than most chronic contamination concentrations from the scientific literature [START_REF] Helmreich | Runoff pollutants of a highly trafficked urban road -Correlation analysis and seasonal influences[END_REF][START_REF] Kayhanian | Review of highway runoff characteristics: Comparative analysis and universal implications[END_REF][START_REF] Lundy | Risk prioritisation of stormwater pollutant sources[END_REF]. These higher concentrations may be due to a high production of wear particles at this site compared to traffic due to its location in an acceleration zone following a roundabout and a relatively high proportion of heavy trucks, both factors associated with higher production of wear particles (US EPA, 2014). Another factor may be the relatively low rainfall over the period studied (917 mm of rainfall over about 1.5 years), leading to more concentrated runoff than at sites with higher rainfall.

TOC concentrations (median 49 mg/L) were also found to be on the high end of those previously reported. Although DOC (median 6.1 mg/L) frequently exceeded the objective concentration of 5 mg/L (MEEM, 2016), organic carbon was mainly particulate, a notable difference from previous studies with higher DOC concentrations, which found organic carbon in road runoff to be mainly dissolved [START_REF] Kayhanian | Review of highway runoff characteristics: Comparative analysis and universal implications[END_REF]. The sorption of organic carbon to the relatively plentiful TSS particles is likely responsible for this disparate partitioning.

Trace Metals

Total trace metal concentrations (Table 5) fell within the range of concentrations found in the scientific literature [START_REF] Huber | Critical review of heavy metal pollution of traffic area runoff: Occurrence, influencing factors, and partitioning[END_REF][START_REF] Kayhanian | Review of highway runoff characteristics: Comparative analysis and universal implications[END_REF][START_REF] Lundy | Risk prioritisation of stormwater pollutant sources[END_REF]. Pb and Zn median concentrations (62.9 and 693 µg/L, respectively) were found to be above the 90 th percentile of recently measured concentrations, while Cu concentrations were among the highest previously observed (median 258 µg/L).

All trace metals were mainly associated with the particulate phase. Cu, Pb and Zn were all found to be more particulate in this study (median 92, 99, 95%, respectively) than in most previous studies from similar highway surfaces, for which median particulate fractions were found to be 62, 96 and 69% [START_REF] Huber | Critical review of heavy metal pollution of traffic area runoff: Occurrence, influencing factors, and partitioning[END_REF]. Particle concentrations of both Cu and Zn (median 628 and 1790 µg/g, respectively) were high compared to previously reported road debris concentrations [START_REF] Brown | Sources of heavy metals and polycyclic aromatic hydrocarbons in urban stormwater runoff[END_REF], while dissolved concentrations were normal or low (25 and 32 µg/L) compared to those in the literature [START_REF] Huber | Critical review of heavy metal pollution of traffic area runoff: Occurrence, influencing factors, and partitioning[END_REF]; the production of high levels of particulate metals at this site therefore appears to be responsible for this partitioning, rather than sorption of dissolved pollutants to the relatively abundant TSS. Another explanation may be the total mineralization of the solid phase used in this study, while for many road runoff studies the particulate phase is obtained by difference between HNO 3 /HCl extraction of total and dissolved samples. Both Cu and Zn systematically exceeded environmental quality standards (EQS) applicable in France for dissolved trace metal concentrations, while As surpassed its EQS for about half of the rain events and Cd, Cr, Ni and Pb were always below the EQS.

Total petroleum hydrocarbon and polycyclic aromatic hydrocarbons

Total petroleum hydrocarbon (TPH) concentrations ranged from 0.29 to 3.96 mg/L with a median of 1.12 mg/L for the total concentration (Table 6). This concentration is similar to medians observed in previous studies of road runoff [START_REF] Kayhanian | Characterization and prediction of highway runoff constituent event mean concentration[END_REF]. This parameter was never quantified in the dissolved phase.

The sum of the 16 US EPA priority PAH varied from 1.3 µg/L to 11.5 µg/L with a median concentration of 4.9 µg/L, within the range predicted for major roads by [START_REF] Lundy | Risk prioritisation of stormwater pollutant sources[END_REF]. Compared to recent studies in France, this is higher than concentrations measured in runoff from an industrial and two residential urban catchments [START_REF] Gasperi | Micropollutants in urban stormwater: occurrence, concentrations, and atmospheric contributions for a wide range of contaminants in three French catchments[END_REF] and lower than those observed from a roadway in a commercial sector with lower traffic [START_REF] Leroy | Performance of vegetated swales for improving road runoff quality in a moderate traffic urban area[END_REF]. The PAH fingerprint and possible sources of these pollutants are discussed in Supplementary Information.

Only three PAH were quantified in the dissolved phase for all events: Phen, Fluo and Pyr, and even these species were found to be predominantly particulate (median 93, 98 and 99%, respectively). By contrast, [START_REF] Nielsen | Effect of Disc Filtration with and without Addition of Flocculent on Nano-and Micro-Particles and Their Associated Polycyclic Aromatic Hydrocarbons in Stormwater[END_REF] quantified the majority of PAH in stormwater from a mixed urban catchment in the dissolved phase and observed an average particulate ratio of only 82%, a difference possibly explained by lower TSS concentrations (median 31 mg/L for samples analyzed for PAH) than in the present study.

Among the PAH molecules considered priority pollutants in the European Union Water Framework Directive (EC, 2013), only Nap was always below the annual mean EQS; respective EQS were often surpassed by A and systematically exceeded for Fluo and BaP.

Bisphenol-A and Alkylphenols

Observed BPA concentrations (median 412 ng/L, Table 7) were on the order of those previously measured in urban runoff in France [START_REF] Gasperi | Micropollutants in urban stormwater: occurrence, concentrations, and atmospheric contributions for a wide range of contaminants in three French catchments[END_REF][START_REF] Sebastian | Bassin de retenue des eaux pluviales en milieu urbain : performance en matière de piégeage des micropolluants[END_REF] and in the lower range of those observed in road runoff [START_REF] Stachel | Treatment Techniques and Analysis of Stormwater Run-off from Roads in Hamburg, Germany[END_REF].

Among alkylphenols, 4-NP was found at the highest concentrations (median 1647 µg/L), followed by OP, NP 1 EO, NP 2 EO, NP 1 EC, and OP 2 EO (430,366,220,113, and 29 ng/L, respectively). OP 1 EO, only quantified in 42% of RR samples, was the least abundant molecule in the family. NP and OP were similar to previously reported concentrations in road runoff [START_REF] Bressy | Flux de micropolluants dans les eaux de ruissellement urbaines: Effets de différents modes de gestion des eaux pluviales[END_REF][START_REF] Stachel | Treatment Techniques and Analysis of Stormwater Run-off from Roads in Hamburg, Germany[END_REF] and distinctly higher than those resulting from the study of runoff from mixed urban catchments [START_REF] Bressy | Towards the determination of an optimal scale for stormwater quality management: Micropollutants in a small residential catchment[END_REF][START_REF] Gasperi | Micropollutants in urban stormwater: occurrence, concentrations, and atmospheric contributions for a wide range of contaminants in three French catchments[END_REF][START_REF] Sebastian | Bassin de retenue des eaux pluviales en milieu urbain : performance en matière de piégeage des micropolluants[END_REF][START_REF] Zgheib | Priority pollutants in urban stormwater: Part 1 -Case of separate storm sewers[END_REF]. The ranks of molecules within the NP and OP families concord with those observed in mixed urban runoff [START_REF] Gasperi | Micropollutants in urban stormwater: occurrence, concentrations, and atmospheric contributions for a wide range of contaminants in three French catchments[END_REF][START_REF] Sebastian | Bassin de retenue des eaux pluviales en milieu urbain : performance en matière de piégeage des micropolluants[END_REF], with the exception of NP 1 EC, which had a higher rank in previous studies than in the present study. Both NP and OP concentrations systematically exceeded the EQS.

Besides OP 1 EO and OP 2 EO, which were rarely quantified in the dissolved phase, most molecules of this family were quantified in both dissolved and particulate phase. They were also found to be less strongly associated with the particulate phase than the trace metals and PAH with median particulate proportions of 28, 73, 67, 72, 33, and 5% for BPA, NP, OP, NP 1 EO, NP 2 EO and NP 1 EC, respectively.

Phthalates

Phthalate concentrations were on the same order of magnitude as other urban and road runoff concentrations from the scientific literature. For example, the median DEHP concentration in RR was 14 µg/L compared to concentrations between 0.1-24 µg/L [START_REF] Clara | Occurrence of phthalates in surface runoff, untreated and treated wastewater and fate during wastewater treatment[END_REF], <1 to 5 µg/L [START_REF] Björklund | Phthalates and nonylphenols in urban runoff: Occurrence, distribution and area emission factors[END_REF]) and 3-58 µg/L [START_REF] Zgheib | Priority pollutants in urban stormwater: Part 1 -Case of separate storm sewers[END_REF]. Similarly, the relative abundance of molecules (DEHP>DiBP>DBP>DMP>DNP) corroborated the previous observations of DEHP>DMP [START_REF] Björklund | Phthalates and nonylphenols in urban runoff: Occurrence, distribution and area emission factors[END_REF] and DEHP>DBP>DMP [START_REF] Clara | Occurrence of phthalates in surface runoff, untreated and treated wastewater and fate during wastewater treatment[END_REF]. The EQS concentration of 1.3 µg/L for DEHP was exceeded for all events.

DMP, DiBP, DBP, DEHP, DNP were quantified in 45, 85, 100, 100, 8% of samples in the dissolved phase and 33, 100, 100, 100 and 50% of samples in the particulate phase, respectively. Phthalates were found to be moderately to highly particulate depending on the compound (27,56,40,72

Treatment efficiency

Treatment efficiency results for TSS, OC, trace metals and organic micropollutants are presented below; those for other global parameters are presented in Supplementary Information.

Global Parameters

TSS concentrations (Table 4) were significantly reduced for both VFS and BFS (Wilcoxon P<0.01).

Outlet VFS TSS concentrations were generally lower than those from BFS (median concentration reductions, E c50 , of 94 and 92% respectively, Table S3 in Supplementary Information). While previous studies have shown that biofiltration tends to have high TSS removals, these are among the best removal rates reported in the literature [START_REF] Brown | Underdrain Configuration to Enhance Bioretention Exfiltration to Reduce Pollutant Loads[END_REF][START_REF] Davis | Field Performance of Bioretention: Water Quality[END_REF][START_REF] Diblasi | Removal and Fate of Polycyclic Aromatic Hydrocarbon Pollutants in an Urban Stormwater Bioretention Facility[END_REF][START_REF] Hsieh | Multiple-event study of bioretention for treatment of urban storm water runoff[END_REF][START_REF] Leroy | Performance of vegetated swales for improving road runoff quality in a moderate traffic urban area[END_REF].

However, degraded performance was observed for three events, which can be observed in the TSS probability distribution (Figure 3) as a discontinuity between the majority of the series and the three highest concentrations for both BFS and VFS. These events all occurred in winter 2017 (Figure S12, Supplementary Data), a period when road salt was frequently applied. One possible explanation for this behavior is the dispersion and erosion of clay particles under sodic conditions introduced by NaCl-rich runoff water, a phenomenon which has been previously observed in both field [START_REF] Winston | Field Evaluation of Storm-Water Control Measures for Highway Runoff Treatment[END_REF] and column [START_REF] Mcmanus | Impact of periodic high concentrations of salts on bioretention nutrients performance[END_REF] studies of LID devices. However, because colloid dispersion generally occurs under sodic conditions with low salinity [START_REF] Shainberg | Response of Soils to Sodic and Saline Conditions[END_REF], this effect is generally not expected for events immediately following salt application but in later events when low-salinity water is filtered through the sodic soils [START_REF] Norrström | Metal mobility by de-icing salt from an infiltration trench for highway runoff[END_REF]. Alternatively, this performance may be caused by a degradation in the efficiency of filtration of road runoff TSS particles, due to cracks in the filter media or less treatable particles during this period. Total concentrations of OC were significantly reduced at both outlets (Wilcoxon P<0.01), while dissolved OC concentrations were significantly higher at both outlets than in RR (Wilcoxon P<0.01 for VFS and P<0.05 for BFS). Dissolved OC concentrations were higher at VFS than BFS, probably due to an accumulation of organic material over time and more biological activity leading to its degradation in the older system.

Trace metals

In the total phase, all trace metal concentrations were significantly reduced (Wilcoxon: P<0.01, except As for the BFS for which P<0.05). Removals were also usually analytically significant (i.e. superior to analytical uncertainty) with the exception of 33% of events for As and 11% of events for Cr and V at BFS. VFS removed total trace metals better than BFS, likely due to better removal of particles (Table S3). Pb and Zn were the best removed species, while As was the least well removed in both systems. Cu, Zn and Pb E c50 (77, 93 and 90% and 76, 89 and 89% for the VFS and BFS, respectively) were higher than those previously reported for similar systems [START_REF] Davis | Field Performance of Bioretention: Water Quality[END_REF][START_REF] Leroy | Performance of vegetated swales for improving road runoff quality in a moderate traffic urban area[END_REF].

The treatment of dissolved trace metals was shown to be much less effective. Negative E c50 were observed for VFS for As, Cr, Cu, Ni and Pb. Although many of these concentration increases were analytically significant for certain events, none were significant for the full series (Wilcoxon P>0.05). At BFS, negative E c for As, Cr and V were analytically significant for most events as well as for the full series (Wilcoxon P<0.05). Analytically significant, positive E c were often observed for dissolved Cu, Pb and Zn for BFS and for V and Zn for VFS, though the removal was not significant across the full series (Wilcoxon P>0.05) due to inter-event variability. As a results of this low performance, the EQS was systematically surpassed for Cu at both treatment sites, and 70% and 87% of events for zinc in the BFS and VFS, respectively.

Probability distributions of most total trace metals tend to closely resemble those of TSS, particularly in the case of Zn (Figure 4). An exception to this is the lower portion of the BFS distribution, for which Zn concentrations are especially low. These concentrations were measured during the earliest period of BFS functioning (Figure S12, Supplementary Information) when uncontaminated, fine soil particles were probably being washed out from the new filter media; as such, particle concentrations of Zn were particularly low during this period. Distributions of other elements, such as Cu, had a less marked discontinuity in the VFS distribution. In both of these cases, dissolved distributions show quite different behavior, with higher concentrations observed in VFS than BFS, possibly due to the leaching of pollutants accumulated over time in the filter media.

The probability distribution of As demonstrates behavior indicative of emissions from the filter media. Although the highest total concentrations at BFS are below those observed in RR, no improvement is observed at lower levels, as As levels in outlet water appear to approach a irreducible concentrations due to equilibrium with the soil. Dissolved BFS concentrations always exceed those in RR. The lower dissolved concentrations observed at VFS indicate that leaching from the filter media may decrease over time.

TPH and PAH

TPH were significantly removed across events (E c50 71 and 64% for the VFS and BFS, respectively, Table S4) in the total phase and were never quantified in the dissolved phase.

Overall, both systems were shown to significantly remove total PAH (Wilcoxon: P<0.01 for Ʃ16 PAH).

Very high E c50 (91% for both systems for Ʃ16 PAH) were observed, consistent with concentration reductions observed by [START_REF] Diblasi | Removal and Fate of Polycyclic Aromatic Hydrocarbon Pollutants in an Urban Stormwater Bioretention Facility[END_REF] and [START_REF] David | Removal Efficiencies of a Bioretention System for Trace Metals, PCBs, PAHs, and Dioxins in a Semiarid Environment[END_REF], both systems in which high TSS retention was also observed, but differing greatly from the results of [START_REF] Leroy | Performance of vegetated swales for improving road runoff quality in a moderate traffic urban area[END_REF], who observed low removal or even increases of PAH concentration from vegetative infiltration swales which also exhibited remarkably poor TSS removal.

In both systems at the event scale, most individual PAH molecule total E c were analytically significant, despite high analytical uncertainty, due to large differences between inlet and outlet concentrations. E c50 were lower (47-88%) for several low molecular weight (LMW) PAH (Nap, 1MN, 2MN, Acy, Acen, F, A) as well as one high molecular weight (HMW) molecule (DahA). These molecules are those present at the lowest proportions in RR (Figure S2, Supplementary Information), which explains, at least partially, the lower efficiency, due both to limitations in observed E c from the LQ and to the fact that irreducible environmental concentrations may be closer to those observed in runoff. In addition, LMW PAH are expected to be more mobile in soil than their more hydrophobic, HMW counterparts.

Across events, concentrations of all molecules in the VFS and most molecules in the BFS were significantly lower than those in RR (Wilcoxon P<0.01). However, as total BFS outlet concentrations of Nap, 1MN, 2MN and Acen were higher than those in RR for some events, their reduction was not found to be significant (P>0.05). Nap, 1MN and 2MN concentrations were only elevated in this way for a single event, likely due to a one-time, local leak or spill of a petroleum product from a vehicle [START_REF] Stogiannidis | Source Characterization of Polycyclic Aromatic Hydrocarbons by Using Their Molecular Indices: An Overview of Possibilities[END_REF], while those of Acen were high for all events sampled in the first three months of operation.

Among the pollutants regulated by the European Water Framework Directive, Nap was always below the EQS at both sites, while A exceeded its standard for a single event at BFS and both Fluo and BaP systematically exceeded the EQS at both sites.

In the dissolved phase, only Phen, Fluo and Pyr were systematically quantified in RR. As many outlet concentrations were below the LQ, calculated event E c were often lower bounds and found to be analytically insignificant. For VFS, all three molecules, and for BFS, only Phen were significantly removed across events (Wilcoxon: P<0.01). BFS dissolved Acen concentrations were actually found to be significantly higher (P<0.05) than those in RR.

Probability distributions of total and dissolved PAH (Figure 5) demonstrate the variety of behaviors observed. The distribution of Acen, both in the total and dissolved phases, is dominated by the high concentrations of dissolved Acen in the first period of operation of the BFS (Figure S12, Supplementary Information), after which total outlet concentrations were lower than those in RR.

Lower outlet concentrations compared to RR are observed for total Fluo, BaP and BkF across the full distribution for both VFS and BFS, with lower performance for the highest three outlet concentrations, which correspond to the winter 2017 period (Figure S12). However, while a clear discontinuity is visible for BaP between these concentrations and the rest of the distribution, it is less marked than that observed for TSS, Zn and Pb; such a discontinuity is even less visible for Fluo and BkF.

Like Acen, the highest dissolved BFS concentrations of Fluo exceeded those in RR, again during the first period of operation (Figure S12), as did those of Pyr. A possible explanation observation is the emission of these pollutants from materials used to construct the BFS, most likely the new strip of asphalt. Bitumen, the sealant used in this asphalt, has been shown to contain PAH, albeit at lower levels than in coal tar (IARC Working Group on the Evaluation of Carcinogenic Risks to Humans et al., 2013). Other PAH molecules are also likely to be present in this material; the observation of emissions for only Acen, Fluo and Pyr may mean that other molecules (especially heavier, more hydrophobic PAH molecules) are less easily leached from the material or better retained by the filter media before collection in the drain.

Alkylphenols and Bisphenol-A

In the VFS, total concentrations of BPA and all analyzed alkylphenols were found to be significantly reduced across events (Wilconxon P<0.01 for all except OP 1 EO and NP 2 EO, for which P<0.05). However, as analytical uncertainties were high and the differences between RR and VFS drainage concentrations were less marked than for PAH, only BPA and OP displayed analytically significant removals for all events, while between 45-91% of removals were significant for the other alkylphenols (Table S5). The least well-retained species was NP 1 EC (E c50 32%), likely due to its more dissolved character than the other pollutants as well as the fact that it may be the product of degradation of more abundant ethoxylated nonylphenols [START_REF] Bergé | Meta-analysis of environmental contamination by alkylphenols[END_REF]. BPA and OP were found to be very well removed (median E c 86 and 93%, respectively).

Total E c tended to be lower for BFS, and the only statistically significant concentration reduction across events was found for BPA (Wilcoxon P<0.05). Again, negative E c were sometimes observed. Most notably, NP 1 EC concentrations significantly increased over the full series (Wilcoxon P<0.05).

The concentrations of other molecules only increased for one or two events, most commonly in May 2016 or winter 2017. Again, BPA and OP were the best removed contaminants of this family (E c50 57 and 76% respectively).

In the dissolved phase, significant removals of BPA, NP 1 EC and OP were observed over the full series for VFS (Wilcoxon P<0.01 and E c50 of 79, 27 and 74%, respectively). Again, for most molecules in this family, removals were not analytically significant for all events. In the dissolved phase, negative E c were more often observed than in the total phase.

As in the total phase, concentrations of dissolved NP 1 EC increased significantly at the outlet of BFS (Wilcoxon P<0.05). Removals of dissolved OP, NP 1 EO and NP 2 EO were significant (P<0.05). At the event scale, the proportions of analytically significant reductions were relatively small, and negative E c were occasionally observed for all pollutants in this family besides OP 1 EO and OP 2 EO, which were rarely quantified.

The EQS for NP and OP were exceeded for 73 and 20% of events for the VFS and 75 and 33% for the BFS.

Probability distributions of BPA, OP and NP (Figure 6) differ from the forms observed for other pollutant families. BPA, much less particulate than trace metals or PAH, has a similar behavior in the dissolved and total phases, with slightly higher removals in the total phase. BFS dissolved concentrations appear to approach a non-reducible level at around 100 ng/L, which may be indicative of emissions from synthetic materials used in the construction of this system (the asphalt, geomembrane, drain or drain filter fabric). VFS concentrations are consistently lower than those in RR, with slightly less difference at the highest concentrations. BFS concentrations follow a similar distribution, albeit with higher concentrations, approaching those in RR at the highest levels. While total NP concentrations are strongly reduced over the whole distribution range for VFS and over the lower half of the distribution range for BFS, little improvement is seen in the dissolved phase. Indeed, the highest and lowest concentrations at both VFS and BFS exceed those of RR. Besides this, outlet concentrations from BFS and VFS are very similar and consistently slightly lower than those in RR, though within in the range of its uncertainty.

Phthalates

All E c50 for total phthalates were positive (Table S5), though lower than those observed for metals and PAH. Outlet concentrations were only significantly below those in RR across the series for DNP (Wilcoxon P<0.01), DMP and DBP (P<0.05) at VFS and DNP (P<0.05) at BFS. In addition, the proportion of events with analytically significant reductions were low (<70%) for all pollutants except DNP. Higher E c tended to be observed for the heavier, more particulate molecules. An exception to this is DEHP in the BFS, which has the lowest E c50 of any phthalate, despite its mainly particulate nature in RR. Concentrations of DEHP always exceeded the EQS, even in outlet water.

No significant reductions of dissolved concentrations were observed for the full series, and negative E c were observed sporadically for all phthalates. Dissolved concentrations of DEHP actually increased significantly (Wilcoxon P<0.05), which indicates that a source of DEHP is present in the BFS, likely materials used in its construction: asphalt [START_REF] Markiewicz | Emissions of organic pollutants from traffic and roads: Priority pollutants selection and substance flow analysis[END_REF], a HDPE drain, the drain's synthetic filter fabric or a PVC geomembrane [START_REF] Bergé | Meta-analysis of environmental contamination by phthalates[END_REF].

E c50 for DEHP and DBP (47 and 69% for VFS and 8 and 48% for BFS) were lower than those observed by [START_REF] Zhang | The validation of stormwater biofilters for micropollutant removal using in situ challenge tests[END_REF] (>97 and >92%, respectively) for synthetic runoff. Besides the possibility of phthalate sources among construction materials, this may be due to the less reactive (colloidal, for example) form of these pollutants in real rather than synthetic runoff [START_REF] Kalmykova | Partitioning of polycyclic aromatic hydrocarbons, alkylphenols, bisphenol A and phthalates in landfill leachates and stormwater[END_REF].

The probability distribution of DEHP (Figure 7) demonstrates the observed variability of treatment efficiency. VFS concentrations tend to be lower than those at BFS and RR, demonstrating that the system is capable of reducing concentrations. However, at low exceedance probabilities, VFS concentrations begin to overlap those in BFS and RR. In the dissolved phase, while VFS and BFS concentrations are of the same order as those in RR in the lower range of the probability distribution, peak concentrations exceed those in RR. This variable performance is visible to a lesser extent for DBP and DiBP, while those of DNP and DMP (Supplementary Data) show more consistent water quality improvement at the outlets, although the observation of the extent of treatment of these two compounds is limited by their proximity to the LQ. Considering all trace metals and organic micropollutants, total E c50 were found to be significantly correlated with the median fraction of each species found in the particulate phase (F p50 ) (Spearman P<0.01 for VFS and BFS), highlighting the generally more efficient removal of particles than the dissolved phase of pollutants. BPA is an outlier in this relationship as it is relatively well removed despite its mainly dissolved character. This relationship was more dispersed in the BFS than the VFS (Figure 8), apparently due to the dissolved phase emissions of certain species in this system (As, Ba, V, Acen, DEHP).

For organic pollutants, F p50 was found to be significantly correlated with the pollutants' hydrophobicity, represented by its octanol-water partition coefficient, K ow (Spearman P<0.01). However, partitioning varied greatly between events for many pollutants (Figure S13 in Supplementary Information); one reason for this is likely to be variations in TSS concentrations. In addition, some molecules were systematically more particulate than others with a similar K ow . This was notably the case for PAH, which were more particulate than alkylphenols or phthalates with similar K ow , possibly indicating PAH to have more particulate sources that are not readily exchanged with the dissolved phase. On the other hand, pollutants which were particularly dissolved for a given K ow , may be in the colloidal rather than truly dissolved phase [START_REF] Kalmykova | Partitioning of polycyclic aromatic hydrocarbons, alkylphenols, bisphenol A and phthalates in landfill leachates and stormwater[END_REF]. 546.

Although K ow was also found to be significantly correlated with total E c50 for organic micropollutants (Spearman P<0.01 for VFS, P<0.05 for BFS), this relationship is quite dispersed, with different behavior exhibited for different pollutant families and between the two systems (Figure 8). The correlation which does exist appears to be mainly driven by the more particulate nature of more hydrophobic compounds, both because the relationship between K ow and E c50 (Figure 8) strongly resembles that between K ow and F p50 in RR (Figure S13) and because no significant correlation was observed between K ow and dissolved E c50 in either system (Spearman P>0.05, Figure S14).

The limited relationship between K ow and E c50 (Figure 8) indicates that other factors besides the pollutant's hydrophobicity determine its partitioning and fate in biofiltration systems. One reason for this may be the chemical speciation of pollutants; indeed, Kalmakova et al. (2013) demonstrated that alkylphenols, phthalates, BPA and PAH may all be present in the colloidal phase in stormwater. Chemical speciation may also explain relatively low adsorption of dissolved metals. Other explanations may be the irreducible concentrations of some pollutants due to background filter media concentrations (this is the case of PAH), emissions of certain pollutants from synthetic materials used to construct the systems (asphalt, geomembrane, drain or drain filter fabric) or other fate processes which might also lead to concentration reduction. For example, the high removals of dissolved phase BPA despite its relatively hydrophilic nature may be due to its biodegradability. Indeed, previously reported biodegradation half-lives between 2.5-4 days (U.S. National Library of Medicine, 2018), this process could be important at the time scale of filtration (residence times typically 12-72 hours in the BFS and 14-58 hours in the VFS).

Comparison of the two biofiltration systems

Many of the differences observed between the VFS and BFS systems can be attributed to age differences. This is notably the case for the slightly higher TSS concentrations at the BFS outlet, which may be attributed to the wash out of fine particles from the not yet stabilized filter media, as well as the emissions of some dissolved trace metals from the initial filter media in the BFS (As, Ba, Sr, V). In this case, the differences observed between the BFS and VFS systems demonstrate improvements in performance as the filter media stabilizes. On the other hand, higher concentrations of dissolved OC, Cu, Pb and Zn concentrations at the VFS outlet may indicate decreased performance as these elements accumulate in the filter media over time.

Most organic micropollutants (some PAH, BPA, alkylphenols and phthalates) were observed in higher concentrations in the BFS than the VFS, especially early on in the study. While the evolution in BFS outlet concentrations over the course of the study shows that performance may improve as materials reach equilibrium with their environment over time, this result highlights the fact that including synthetic materials in a biofiltration system designed to treat organic micropollutants which are ubiquitous in such materials [START_REF] Björklund | Substance flow analyses of phthalates and nonylphenols in stormwater[END_REF][START_REF] Lamprea | Alkylphenol and bisphenol A contamination of urban runoff: an evaluation of the emission potentials of various construction materials and automotive supplies[END_REF] is counterproductive. As the VFS only contains a sheet drain, as opposed to the asphalt, drain with filter fabric and geomembrane in the BFS, its better performance with respect to organic micropollutants is likely more representative of that which might be observed in a system without such materials.

When choosing a treatment device, it is also important to remember that a vegetative filter strip treats only water which infiltrates during its flow across the surface, while a biofiltration swale is designed to store runoff at the surface before its filtration. As such, for an identical surface area and filter media, a biofiltration swale may be expected to treat a greater volume than a vegetative filter strip. In addition, a design with surface storage is likely to be more resilient to the accumulation of sediment, which may compromise flow on vegetative filter strips after only a short period of operation on sites with high TSS concentrations [START_REF] Flanagan | Evaluation de la rétention et du devenir d'un panel diversifié de micropolluants dans un ouvrage de biofiltration des eaux de ruissellement de voirie[END_REF].

Uncertainties and challenges in data interpretation

The evaluation of the efficiency of LID devices involves challenges in data acquisition and interpretation. First of all, each measured concentration includes uncertainties associated with both sampling and analysis, the latter of which may be particularly large for organic micropollutants and have thus been thoroughly accounted for throughout the present article. The use of a reference catchment for estimating inlet water quality is an additional source of uncertainty and potential bias.

In the present case, the reference catchment was nearly identical to the BFS and VFS catchments, with the exception of the presence of a concrete border. While pollutant buildup processes are likely to be similar, the border modifies flow conditions and may modify the dynamics of pollutant washoff. As such, annual loads from each catchment should be similar, but event mean concentrations for each rain event could vary. Given these various issues, comparison of distributions of pollutant concentrations at each point for several events is a more robust tool for evaluating efficiency than comparing concentrations for each rain event, as such distributions include not only inter-event variability but also variability due to uncertainties.

Concerning treatment efficiency of dissolved pollutants and dissolved concentration levels, it is important to keep in mind that samples were filtered within 24 hours from the end of RR runoff. While it would have been very difficult to reduce this delay, especially given the time necessary for water to filter through the system (average residence time> 12 hours), there is a possibility of some transfer between dissolved and particulate phases in the sample before analysis. Sansalone and Buchberger's work (1997) show that metals in road runoff can become more particulate after about a duration of 6 hours, which could lead to a underestimation of dissolved removal rates. On the other hand, some desorption of particulate pollutants in VFS and BFS samples after filtration is possible. It will however be limited by the low TSS concentrations in these samples.

Conclusions

The performance of two stormwater biofiltration systems treating road runoff were evaluated for a wide range of conventional pollutants and micropollutants for both total and dissolved concentrations. Key findings are as follows.

 Concentrations reductions of TSS and highly particulate contaminants (including zinc, copper, lead, TPH and PAH) were high (E c >90%) for most events, though a period of poor performance was observed over a particularly cold winter period.  Treatment of dissolved-phase pollutants was less efficient, with relatively few significant dissolved pollutant concentrations observed. This performance was not correlated with hydrophobicity for organic micropollutants. Although median E c approached 80% for some pollutants, the majority were much lower, sometimes even negative. As such, removal of moderately particulate pollutants (BPA, alkylphenols, and phthalates) tended to be lower than the aforementioned highly particulate pollutants.  Many pollutants (including some nutrients, PAH molecules, trace elements, BPA, alkylphenols and phthalates) demonstrate low or negative E c during the first months of operation of the BFS system. A major cause of this is thought to be emissions from components of the biofiltration system. While the filter medium is the most likely source of leached nutrients and trace metals, man-made materials including geomembranes, asphalt, drains and associated filter fabrics are potential sources of organic micropollutants, a fact while should be taken into account when designing biofilters for the treatment of micropollutants.

The present research has raised questions as to the mechanisms underlying the retention and transport of pollutants in stormwater biofilters, especially during winter. Better understanding these processes, as well as the fate of retained pollutants in these systems and long-term evolutions in performance, are important subjects for future research, which could improve recommendations for the conception and maintenance of biofiltration systems.

Figure 1 :

 1 Figure 1: Map of the Compans study site location

Figure 2 :

 2 Figure 2: Schema of the Compans study site

Filter

Figure 3 :

 3 Figure 3: Probability distribution of TSS concentrations in road runoff (RR), the vegetative filter strip (VFS) and the biofiltration swale (BFS); Y-axis represents the experimentally observed probability of not exceeding the associated observed concentration (X-axis). Error bars represent analytical uncertainty while the dotted black line represents the water quality objective.

Figure 4 :

 4 Figure 4 : Probability distributions of total and dissolved Zn, Cu and As concentrations in road runoff (RR), the vegetative filter strip (VFS) and the biofiltration swale (BFS). Y-axis represents the experimentally observed probability of not exceeding the associated observed concentration (X-axis). Error bars represent analytical uncertainty while the dotted black line represents the EQS.

Figure 5 :

 5 Figure 5: Probability distribution of total and dissolved Acen and Fluo and total BaP and BkF concentrations in road runoff (RR), the vegetative filter strip (VFS) and the biofiltration swale (BFS). Yaxis represents the experimentally observed probability of not exceeding the associated observed concentration (X-axis). Error bars represent analytical uncertainty while the dotted black line represents the EQS.

Figure 6 :

 6 Figure 6: Probability distribution of total and dissolved BPA, OP and NP concentrations in road runoff (RR), the vegetative filter strip (VFS) and the biofiltration swale (BFS). Y-axis represents the experimentally observed probability of not exceeding the associated observed concentration (X-axis). Error bars represent analytical uncertainty while the dotted black line represents the EQS.

Figure 7 :

 7 Figure 7: Probability distribution of total and dissolved DEHP concentrations in road runoff (RR), the vegetative filter strip (VFS) and the biofiltration swale (BFS). Y-axis represents the experimentally observed probability of not exceeding the associated observed concentration (X-axis). Error bars represent analytical uncertainty while the dotted black line represents the EQS. 4. Discussion 4.1. Relationship between performance and pollutant properties

Figure 8 :

 8 Figure 8: Relationships between total median concentration reduction (E c50 ) and median particulate fraction (F p50 ) in (a) the vegetative filter strip, VFS and (b) the biofiltration swale, BFS and between total E c50 and octanol water partition coefficient (K ow ) in (c) VFS and (d) BFS

Table 1 :

 1 Filter media and geometric properties of the two sustainable drainage systems

	Biofiltration swale

Table 2 :

 2 Sampled rain event characteristics

	8 (1.6, 47.2)

Parameter Substances and abbreviations Method Limit of quantification (LQ) Uncertainty

	solids Suspended	Total suspended solids (TSS)	Standard : NF EN 872 Method: Filtration Filter : 0.7 µm fiberglass	2 mg/L	Confidence level (CL) : 95%
			Filter : 0.7 µm fiberglass	Dissolved:
	Organic carbon	Total organic carbon (TOC), Dissolved organic carbon (DOC)	Method: Thermal combustion-Infrared detector Standard : NF EN (dissolved) 1484	mg/g 0.3 mg/L Particulaire:	CL: 95%	± 10%
			Filter : 0.7 µm fiberglass
			Extraction: Mineralization and
			distillation (KN), mineralization
			(P)
	Nutrients	Kjehldahl Ammonium (NH4 + ), Nitrite (NO2 -), nitrogen (KN), Nitrate (NO3 -), Phosphorus (P),	Methods: Colorimetry (P, NH4 + ) , Ion Titration (KN), chromatography (NO2 -, NO3 -,
		Phosphate (PO4 3-)	PO4 3-)
			Standards: NP EN 25663 (KN),
			NF EN ISO 6878 (P), NF T 90-015
			2 (NH4 + ), NF T 90-015 2 (NO2 -, NO3 -, PO4 3-)

  3-) %

	Trace metals and Major elements	Aluminum (Al), Arsenic (As), Barium (Ba), Calcium (Ca), Cadmium (Cd), Cobalt (Co), Chromium (Cr), Copper (Cu), Iron (Fe), Potassium (K), Magnesium (Mg), Manganese (Mn), Molybdenum (Mo), Sodium (Na), Nickel (Ni), Lead (Pb), Silicon (Si), Strontium (Sr), Titanium (Ti), Vanadium (V), Zinc (Zn)	Filter: 0.45 µm cellulose acetate Extraction: Acidification to 1% HNO3 (dissolved), Total solubilization by HF and HClO4 acid digestion, evaporation and resuspension with HNO3 (particulate) Methods: ICP-MS and ICP-OES Standards: NF X31-147 (acid digestion), NF EN ISO 17294 (ICP-MS), NF EN ISO 11885 (ICP-OES)

Absolute uncertainty between LQ and SL: ±

						Dissolved:
						11 (BPA), 79 (NP), 31
	BPA/AP	Bisphenol-A nonylphenol (NP), Nonylphenol (BPA), Para-monoethoxylate (NP1EO), Nonylphenol diethoxylate (NP2EO), Nonylphenol monocarboxylate (NP1EC), 4-tert-octylphenol (OP), Octylphenol	Filter: 0.7 µm fiberglass Extraction: Solid-phase (dissolved), Microwave (particulate) Method: UPLC-MSMS	(NP1EO), 62 (NP2EO), 2 (NP1EC), 7 (OP), 17 (OP1EO), 5 (OP2EO) ng/L Particulate: (BPA), (NP), (NP1EO), (NP2EO),	CL: 80% Dissolved : ± 28 (BPA), 37 (NP), 91 (NP1EO), 67 (NP2EO), 29 (NP1EC), 61 (OP), 25 (OP1EO), 32 (OP2EO) % Particulate: ± 25 (BPA), 44 (NP), 43 (NP1EO), 56 (NP2EO),
		monoethoxylate	(OP1EO),		49 (NP1EC), 48 (OP), 40
		Octylphenol diethoxylate (OP2EO)		(NP1EC),	(OP) ,	(OP1EO), 19 (OP2EO) %
						(OP1EO),	(OP2EO) µg/g
		Dimethyl	phthalate	(DMP),
		Diisobutyl	phthalate	(DiBP),
	PAE	Dibutyl phthalate (DBP), Bis(2-
		ethylhexyl) phthalate (DEHP),
		Dinonyl phthalate (DNP)
						CL: 95%
					: 0.7 µm fiberglass	SL: 0.3 mg/L (dissolved), 75
					Extraction: (dissolved), ultrasound solid-Liquid-liquid liquid (particulate) Method: GC-FID	Dissolved: 0.2 mg/L Particulate:	µg/g (particulate) (dissolved), 30	0.12 mg/L mg/kg
					Standard: NF EN ISO 9377-2	mg/g	(particulate)
					(dissolved), NP ISO 16703	Relative uncertainty beyond
					(particulate)	SL: ± 40% (dissolved and
						particulate)
		1-methyl Naphthalene (1MN), 2-
		methyl-Naphthalene	(2MN),
		Acenaphthene	(Acen),
	PAH	Acenaphthylene Anthracene Benzo[a]anthracene Benzo[a]pyrene Benzo[b]fluoranthene Benzo[g,h,i]perylene Benzo[k]fluoranthene Chrysene (Chry), Coronene (Cor), (Acyl), (A), (BaA), (BaP), (BbF), (BPer), (BkF), Dibenzo[a,h]anthracene (DahA), Fluoranthene (Fluo), Fluorene (F),	Filter: 0.7 µm fiberglass Extraction: Liquid-liquid (dissolved), ultrasound solid-liquid (particulate) Method: GC-MS Standard: XP ISO-TS 28581 and NF ISO 28540 (dissolved), XP X33-012 and NF EN 15527 (particulate)	Dissolved: 10 ng/L Particulate: µg/g	CL: 95% SL: 20 ng/L (dissolved), 0.03 µg/g (particulate) Absolute uncertainty between LQ and SL: ± 6 ng/L (dissolved), 0.006 µg/g (particulate) Relative uncertainty beyond SL: ± 40 (dissolved), 20 (particulate) %
		Indeno(1,2,3-cd]pyrene	(IP),
		Naphthalene (Nap), Phenanthrene
		(Phen), Pyrene (Pyr)

n VFS n BFS n RR n VFS n BFS

									Water
		Parameter		Total Phase			Dissolved Phase		Quality Objective
			RR						n
		pH	8.02 (7.62, 8.41)	14 7.77 (7.40, 7.98)*	18 7.98 (7.76, 8.81)	15			6.5-8.2
		Conductivity (µS/cm)	234 (88, 1950)	14 437 (188, 6585)°	18 467 (250, 5365)°	15	-		-
		Turbidity	291 (60, >1000)	14 30 (6, 324)*	18 37 (12, 878)*	15			-
	Nutrients	TSS (mg/L) OC (mg/L) 92% for DMP, DiBP, DBP, DEHP, DNP) with the highest particulate ratios corresponding to those 291 (70, 933) 14 18 (2.9, 154)* 18 18 (8.7, 520)* 15 -and 49 (14, 111) 13 14 (3.8, 31)* 16 15 (4.6, 82)* 13 6.1 (1.7, 14.7) molecules with the highest molecular KN (mg/L -N) 2.92 (<1, 5.58) 13 1.07 (<1, 5.03)* 16 1.63 (<1, 3.93)* <1 (<1, 1.33) weight. NH 4 + (mg/L -0.20 (<0.04, 0.48) N) --(mg/L -N) 0.47 (<0.05, 1.84) NO 3 NO 2 -(mg/L -N) <0.08 (<0.08, 0.27) P (mg/L -P) 0.48 (0.13, 2.05) 13 0.18 (<0.1, 0.65)** 16 0.25 (<0.1, 0.89)** 13 <0.1 (<0.1, 0.14) PO 4 3-(mg/L -P) -<0.16	50 14 10.5 (3.2, 23.9)° 13 <1 (<1, 1.79) 13 <0.04(<0.04,0.32)** 13 0.40 (<0.05, 1.94) 13 <0.08 (<0.08, 0.24) 13 0.11 (<0.1, 0.20)°° 13 <0.16	18 9.8 (3.3, 16.1)°° 16 <1 (<1, 2.02) 16 0.06 (<0.04, 0.29)** 16 0.85 (<0.05, 2.16) 13 0.08 (<0.08, 0.20) 16 0.13 (<0.1, 0.22) 16 <0.16	15 13 13 13 13 13 13	5 D -0.4 11 0.09 0.2 0.16
	Elements Mineral Major	Al (mg/L) Fe (mg/L) Mn (mg/L) Ti (mg/L) Na (mg/L) K (mg/L) Mg (mg/L) Ca (mg/L) Si (mg/L)	14.4 (3.8, 34.6) 13.8 (3.9, 32.7) 0.26 (0.06, 0.61) 0.82 (0.21, 2.01) 30.2 (10.3, 377.5) 4.73 (2.34, 11.67) 5.20 (1.68, 11.97) 61.0 (21.3, 145.2)	12 1.0 (0.1, 6.5)* 12 0.9 (0.1, 5.6)* 12 0.014 (0.003, 0.089)* 16 0.02 (0.01, 0.34)* 16 1.5 (0.3, 24.6)* 16 1.2 (0.2, 21.7)* 12 0.05 (0.01, 0.31)* 16 0.07 (0.02, 1.30)* 12 46.6 (7.7, 1355.8)° 16 45.0 (9.3, 891.4)° 12 2.12 (0.42,7.91)* 16 3.76 (2.14, 13.77) 12 2.10 (1.18, 6.59)* 16 2.93 (1.40, 15.54) 12 40.4 (22.4, 154.5) 16 57.5 (32.2, 248.9) -	14 <0.1 (<0.1, 0.12) 14 0.06 (0.03, 0.10) 14 0.003 (0.001,0.016) 14 0.002 (<0.002, 0.004) 14 30.5 (6.5, 374.0) 14 1.22 (0.68, 4.01) 14 0.68 (0.33, 1.07) 14 17.6 (11.8, 23.9) 13 1.27 (0.76, 18.70)	11 <0.1 (<0.1, 0.23) 11 0.07 (0.01, 0.19) 11 0.003(<0.001,0.015)** 15 0.002(<0.001,0.050) 15 <0.1 (<0.1, 0.24) 15 0.05 (0.01, 0.23) 11 0.004(<0.002,0.008) 15 0.004(<0.002,0.019) 11 48.8 (7.7, 1353.3)° 15 38.4 (9.3, 886.9)° 11 1.54 (0.32, 6.55)* 15 3.00 (2.03, 7.89)° 11 1.60 (0.91, 5.20)° 15 2.58 (1.33, 9.36)° 11 36.7 (21.6, 144.5)° 15 52.6 (29.3, 197.6)° 10 2.60 (0.84, 3.67) 14 3.54 (2.58, 5.08)°°	13 13 13 13 13 13 13 13 12	---------

Table 4 :

 4 Median (minimum, maximum) values observed for total and dissolved phase global parameters in untreated road runoff (RR), drained water from the vegetative filter strip (VFS) and drained water from the biofiltration swale (BFS), compared to French objectives for good quality surface water[START_REF] Meem | Guide technique relatif à l'évaluation de l'état des eaux de surface continentales (cours d'eau, canaux[END_REF]. Outlet (VFS or BFS) values significantly lower than those in RR represented by *(P<0.01) or **(P<0.05); significantly higher by °(P<0.01) or °°(P<0.05).

								EQS
			Total Concentrations			Dissolved Concentrations		(dissolved
	Trace Metals							phase)
		RR	VFS	BFS	RR	VFS	BFS
		n=12	n=16	n=14	n=11	n=15	n=13
	As (µg/L)	4.99 (2.13, 12.11)	1.26 (0.39, 4.72)*	3.16(1.81,11.02)**	0.79 (0.57, 1.41)	0.88 (0.39, 2.91)	2.23 (1.33, 3.39)°°	0.83 Δ
	Ba (µg/L)	170 (60, 430)	40 (20, 250)*	50 (30, 440)	13 (9, 30)	25 (15, 184)°	41 (25, 188)°	-
	Cd (µg/L)	0.30 (0.11, 0.72)	<0.1 (<0.1, 0.14)*	0.11 (<0.1, 0.48)*	<0.1	<0.1	<0.1	0.15 ΔΔ, ΔΔΔ
	Co (µg/L)	4.93 (<2, 12.20)	<2*	<2 (<2, 7.3)*	<2	<2	<2	-
	Cr (µg/L)	37.2 (12.3, 83.3)	3.2 (0.9, 15.8)*	5.5 (2.2, 57.7)*	0.63 (<0.1, 1.83)	0.82 (0.28, 1.90)	1.38 (0.64, 2.70)°°	3.4 Δ
	Cu (µg/L)	258 (98, 546)	39 (11, 114)*	35 (9, 280)*	24.9 (13.5, 42.2)	28.9 (9.1, 71.2)	24.5 (6.8, 43.6)	1 Δ
	Mo (µg/L)	9 (2, 62)	4 (2, 35)**	4 (2, 36)*	<2 (<2, 36)	4 (<2, 12)	4 (<2, 36)	-
	Ni (µg/L)	16.2 (1.9, 38.9)	2.7 (1.0, 8.1)*	2.7 (0.9, 26.0)*	0.90 (0.57, 1.45)	0.97 (0.60, 7.81)	1.31 (0.54, 2.48)	4 ΔΔ
	Pb (µg/L)	62.9 (15.8, 139.2)	4.1 (1.2, 22.1)*	4.2 (1.4, 100.8)*	0.43 (0.19, 0.90)	0.48 (0.26, 1.61)	0.38 (0.18, 1.08)	1.2 ΔΔ
	Sr (µg/L)	170 (80, 330)	140 (80, 660)	270 (120, 1020)	100 (57, 117)	133 (76, 631)°	261 (110, 907)°	-
	V (µg/L)	27.1 (11.2, 70.4)	3.4 (1.0, 12.9)*	9.3 (4.3, 54.6)*	1.83 (1.00, 3.16)	1.47 (0.84, 0.304)	4.45 (1.08, 10.35)°°	-
	Zn (µg/L)	693 (236, 1653)	64 (11, 325)*	53 (9, 1057)*	32.3 (16.0, 65.9)	27.7 (7.5, 127.0)	16.4 (2.9, 54.1)	7.8

Δ

Table

5

: Median (minimum, maximum) total and dissolved concentrations in road runoff (RR), the vegetative filter strip (VFS) and the biofiltration swale (BFS), compared to Δ French (MEEM, 2016) or ΔΔ European (EC, 2013) annual mean environmental quality standards (EQS), ΔΔΔ concentrations for Class 4 water hardness. Significant concentration reductions at BFS or VFS outlets compared to RR represented by *(P<0.01) or **(P<0.05); increases by °(P<0.01) or °°(P<0.05).

Table 7 :

 7

Median (minimum, maximum)

total and dissolved concentrations observed for BPA, alkylphenol (AP) and phthalate (PAE) in road runoff (RR), the vegetative filter strip (VFS) and the biofiltration swale (BFS), compared to European (EC, 2013) annual mean environmental quality standards. Octanol-water partition coefficient (log K OW ), median a (U.S. National Library of Medicine, 2018), b

[START_REF] Mackay | Handbook of physical-chemical properties and environmental fate for organic chemicals[END_REF]

, c (European Chemicals Agency, 2018), d

[START_REF] Bergé | Meta-analysis of environmental contamination by alkylphenols[END_REF]

. Significant concentration reductions at BFS or VFS outlets compared to RR represented by *(P<0.01) or **(P<0.05); increases by °(P<0.01) or °°(P<0.05).

Acknowledgements

We also acknowledge the Seine-et-Marne Departmental Council, and especially Eric Thomas and Tina Ratovelomanana, for their partnership and technical support, as well as Tianran Dong, Delphine Truong, Thi Kim Phung Nguyen, Meriem Kajeiou and Maria Vitart de Abreu Lima for their help with sampling campaigns.

Funding

This work was supported by funding for the Roulépur research program (AFB and AESN), the Observatory of Urban Pollutants in Paris (OPUR) (AESN, SIAAP, CD92, CD93, CD94 and Ville de Paris), and a PhD scholarship from ENPC.


Marion Blondel

Dominique Boutet

Fanny Catteau

Coralie Vincent

Signing amplitude and other prosodic cues in older signers: Insights from motion capture from the SignAge Corpus

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

The literature indicates that elderly people use gestures with reduced amplitude (Carmeli et al. 2003). Any adaptive strategies? Hypotheses -Reduced ranges of motion of degrees of freedom (=> more transfer of the movement?) -Finger selection: lower ratio of the inertial mass between the hand and the forearm (=> a motion further on the forearm and a smoother gesture?) Proximal-distal flow: proportionally less movement on the hand? Distal-proximal flow: more developed movement of the forearm?

Corpus

♦

  Short term: to complete annotations and measures for the older corpus ; to build the younger corpus for comparison ♦ Longer term: to study (i) the linguistic specificities in the productions collected in interaction (speech turn, signing space, lexical and morphosyntactic variations, prosody in LSF), (ii) the possible markers of aging, whether ordinary or disturbed, in connection with existing studies on the articulatory manifestations of language or cognitive disorders(Tyrone & Woll, 2008; Tyrone, 2014) and (iii) adaptive strategies of elderly signers.Natacha Hébert, Marie-Anne Note, SCOP LIESSE, our participants from Rouen and LeHavre (Normandy), Le Havre IUT, Fabien Lienard Q1) Older signers: any systematic 'phonetic' and prosodic differences?

  themes of the evolution of transport, access to care, culture and new technologies First results encourage us to use signing rate, movement amplitude and segment distribution as measurements of prosodic characterization for the older signers' production. Methodological protocol adapted from CorpAGEst (relatives or friends as interviewers) ddl for blue) and orange) RANGE for each ddl MART (65y) RANGE for each ddl of NAT (45y) Q2) Older signers and motion capture setting? SignAge = corpus of interactions between or with older deaf signers in LSF • to test motion capture systems to complement analysis on the basis of video recordings (3D data; descriptors such as speed or acceleration of the different body parts) • a step forward to get semi-automatic annotation A kinesiological model based on linguistics: • variation of the signing amplitude for each degree of freedom • global movement quantity • possible correlation with some articulatory segments C. T. & Boutet, D. 2018. The multimodal CorpAGEst corpus: Keeping an eye on pragmatic competence in later life. Corpora 13 (2). • Carmeli, Eli, Hagar Patish, et Raymond Coleman. « The aging hand ». The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 58, no 2 (2003): M146-M152. • Luna S. 2015. Variation syntaxique de la langue de signes québécoise chez les ainés sourds, Actes du congrès annuel de l'Association canadienne de linguistique 2015 Proceedings of the annual conference of the Canadian Linguistic Association. • Meurant, L. 2015, Corpus LSFB. Un corpus informatisé en libre accès de vidéos et d'annotations de la langue des signes de Belgique francophone (LSFB). Laboratoire de Langue des signes de Belgique francophone (LSFB-Lab). FRS-F.N.R.S et Université de Namur. URL: http://www.corpus-lsfb.be • Parisot, AM & J. Rinfret. 2015. "Morphosyntactic variation in the use of space in Langue des signes québécoise (LSQ): a pilot study on verb agreement among two generations of signers" TISLR12, Melbourne. • Parisot, AM. 2017. Intergenerational variation in the use of space in Langue des Signes Québécoise (LSQ) The case of verb agreement marking. International Conference CLARe3 Encounters in Language and Aging Research: Pragmatic Spaces, Longitudinal Studies and Multilingualism, March 6-8, 2017, Freie Universität Berlin • Tyrone, M.E. 2014. Sign dysarthria: A speech disorder in signed language. In D. Quinto-Pozos (ed.) Multilingual Aspects of Signed Language Communication and Disorder (pp. 162-185). Bristol, UK: Multilingual Matters. • Tyrone, M.E. & Woll, B. 2008. Sign phonetics and the motor system: Implications from Parkinson disease. In J. Quer (ed.) Signs of the Time: Selected Papers from TISLR 2004. Seedorf: Signum, 43 &8211; 68.


Coralie Vincent

Fanny Catteau

Dominique Boutet

Marion Blondel

The SignAge Corpus: Recording older signers with low cost motion capture devices

come   L'archive ouverte pluridisciplinaire

Acknowledgements

+ Low cost, portability, ease to get accustomed to wearing the body straps -Limits in space resolution (Neuron) and time resolution (Kinect) → need more data to confirm Kinect and Neuron might still be an interesting choice to get usable additional 3D data in aging studies

In progress:

Building the SignAge corpus

Websites (equipment, softwares and corpus)

• Noitom Perception Neuron: https://neuronmocap.com/products/perception_neuron



Impact on sign language studies

Up to now, a (preferably multi-)camera setup was considered a basic requirement in sign language studies, sometimes completed with much more intrusive or expensive equipment such as data gloves, optical motion capture systems (Channon, 2015, p. 132-133). But latest technology advancements allow us to quantify 3D-motions and their time derivatives at a reasonable price. Our newly built SignAge corpus of interactions between older deaf signers in LSF takes advantage of such advancements.

  video (2D) and biomechanical (3D) data Bibliography • Bolly, C. T. & Boutet, D. 2018. The multimodal CorpAGEst corpus: Keeping an eye on pragmatic competence in later life. Corpora 13 (2). • Channon, R. (2015). Research Methods for Studying the Form of Signs. In E. Orfanidou, B. Woll, & G. Morgan (Eds.), Research Methods in Sign Language Studies: A Practical Guide (p. 123-140). Hoboken, NJ: Wiley-Blackwell. • Meredith, M., & Maddock, S. (2001). Motion Capture File Formats Explained (No. CS-01-11). Sheffield, UK: Department of Computer Science, University of Sheffield. • Mousavi Hondori, H., & Khademi, M. (2014). A Review on Technical and Clinical Impact of Microsoft Kinect on Physical Therapy and Rehabilitation. Journal of Medical Engineering, 1-16. • Rougier, C., Auvinet, E., Rousseau, J., Mignotte, M., & Meunier, J. (2011). Fall Detection from Depth Map Video Sequences. In Toward Useful Services for Elderly and People with Disabilities (p. 121-128). Springer, Berlin, Heidelberg. • Sarasúa, Á., & Guaus, E. (2014). Dynamics in Music Conducting: A Computational Comparative Study Among Subjects. In Proceedings of the International Conference on New Interfaces for Musical Expression (pp. 195-200). London, UK. • Sloetjes, H., & Seibert, O. (2016). Measuring by marking; the multimedia annotation tool ELAN. In A. Spink, G. Riedel, L. Zhou, L. Teekens, R. Albatal, & C. Gurrin (Eds.), Proceedings of Measuring Behavior 2016 (pp. 492-495). Dublin, Ireland. • Springer, S., & Yogev Seligmann, G. (2016). Validity of the Kinect for Gait Assessment: A Focused Review. Sensors , 16(2), 194. • Webster, D., & Celik, O. (2014). Systematic review of Kinect applications in elderly care and stroke rehabilitation. Journal of NeuroEngineering and Rehabilitation , 11, 108.

  For almost ten years, the marketing of low cost motion capture devices such as the Microsoft Kinect sensor has enabled numerous studies in real-life settings(Mousavi Hondori & Khademi, 2014; Webster & Celik, 2014; Springer & Yogev Seligmann, 2016). Whereas most of this work with older people is studying gait and fall risks (see Rougier, Auvinet, Rousseau, Mignotte, & Meunier, 2011 for example), we propose to focus on the building of the SignAge corpus dedicated to the study of signing in older deaf participants with low cost motion capture devices.

♦ Short term: Compare accuracy of Neuron mocap data with simultaneously recorded OptiTrack Prime 13 mocap data ♦ Longer term: Develop annotation support tools; use OpenPose detection library Natacha Hébert, Marie-Anne Note, SCOP LIESSE, our participants from Rouen and Le Havre (Normandy), Le Havre IUT, Fabien Lienard, Gilles Dietrich Low cost motion capture (mocap) devices


Kelsey Flanagan
email: kelsey.flanagan@enpc.fr

Steven Deshayes

Mohamed Saad

Emilie Caupos

Lila Boudahmane

Chandirane Partibane

Philippe Dubois

Laurent Meffray

Philippe Branchu
email: philippe.branchu@cerema.fr

Marie-Christine Gromaire

Water quality performance of road runoff biofilters : retention of particulate and dissolved phase micropollutants

Introduction

As awareness of the chronic contamination of road runoff by suspended solids, metals, nutrients and various organic micropollutants [START_REF] Markiewicz | Emissions of organic pollutants from traffic and roads: Priority pollutants selection and substance flow analysis[END_REF] has grown, so has interest in strategies for its treatment. Notably, various soil-based, vegetated sustainable urban drainage systems (SUDS) are designed to reduce pollutant loads reaching water bodies [START_REF] Ciria | The SuDS Manual (C753)[END_REF]. While studies have shown such systems to be effective in reducing macropollutants and trace metals, relatively few have addressed the retention organic micropollutants or distinguished between the dissolved and particulate phases, for which retention processes are different [START_REF] Lefevre | Review of Dissolved Pollutants in Urban Storm Water and Their Removal and Fate in Bioretention Cells[END_REF].

The present study seeks to characterize the in situ water quality improvement achieved by filtration of road runoff through the media of two soil-based SUDS for the particulate and dissolved phases of a wide range of macropollutants and micropollutants.

Materials and Methods

Site Description:

The study site includes a vegetative filter strip (VFS) and a biofiltration swale (BFS), both of which drain water from the RD 212, a highway located in Compans, France in the Paris region. At both of these sites, water is collected from a drain beneath the filter media (a sandy loam) at a depth of 15 and 50 cm, respectively. Water quality is compared to untreated road runoff (RR) collected at another section of the same road (Fig. 1).

Fig. 1: The Compans experimental site

Sampling and analysis:

Water is collected in proportion to flow volume in order to achieve an event mean concentration (EMC). Sampling began in February 2016 for VFS and RR and in May 2016 for BFS; 12 events have been sampled thus far. While simultaneous sampling of all points was attempted, different starting dates and technical difficulties mean that not all data is paired. Samples are collected within 24h of each rain event and sent to partner laboratories within 24h of collection where they are immediately filtered to distinguish between dissolved and particulate phases. They are analyzed for pH, conductivity, turbidity, suspended solids (TSS), organic carbon, nutrients, 13 trace metals, 9 major ions, total hydrocarbons, 19 polycyclic aromatic hydrocarbons (PAH), bisphenol-A (BPA), 7 alkylphenols and 12 phthalates.

Results and Discussions

Metals were found to be largely particulate in RR (medians of 95, 93 and 99% for Zn, Cu and Pb). Total EMCs in treated water were both much lower and less variable than those in found in RR (Fig. 2 a-c). However, retention of dissolved pollutants seems to be much less effective (Fig. 2 d-f). Indeed, dissolved VFS EMCs were often found to be higher than paired RR EMCs, indicating that the filter is actually leaching rather than retaining dissolved metals. BFS, a newer system (constructed in March 2016 v. September 2012 for VFS) with a greater media depth, does not show this effect. Total EMC reductions are thus driven by the retention of particulate pollutants. Three PAHs were quantified at RR in both the particulate and dissolved phases for all events: Fluoranthene (Fluo), Pyrene (Pyr) and Phenanthrene (Phen). These contaminants are all mainly particulate in RR (97, 96 and 91% respectively), and total EMCs are found to decrease significantly in VFS and BFS (Fig. 3, a-c). VFS effectively reduces dissolved PAH EMCs (Fig. 3 d-f), though our evaluation is limited by the limit of quantification (LOQ). However, while BFS seems to retain Phen, both Fluo and Pyr EMCs increase drastically, likely due to leaching from construction materials, a hypothesis supported by decreases in these concentrations over time.

BPA, a more hydrophilic molecule, was found to be well retained in the dissolved fraction, with a reduction in median EMCs of 85% for VFS and 60% for BFS from those at RR (Fig. 4). Particulate analyses are in progress.

Conclusions

EMCs of various pollutants were studied in road runoff and following filtration through the soil of a vegetative filter strip and a biofiltration swale. Both systems were found to be very effective for the mechanical filtration of particulate pollutants, which translated to greatly improved water quality in terms of total concentrations for the pollutants studied. However, retention of the dissolved fraction was less efficient, despite the fact that laboratory batch tests have shown the ability of the media to sorb both metallic and organic pollutants. Indeed, dissolved concentrations sometimes increased at the outlet, due to leaching from the accumulated stock of contaminated particles or from construction materials. Future work will seek to better understand the retention and fate processes of each pollutant through the use of a mathematical model and to establish long-term mass balances by combining water quality data with hydrologic and soil quality measurements.

Fig. 2 :Fig. 3 :

 23 Fig. 2: Heavy metal event mean concentrations (EMCs)

Acknowledgments

This research was conducted as part of the ROULEPUR project, within the frame of the OPUR Observatory of Urban Pollutants in the Paris conurbation. We acknowledge AFB (formerly ONEMA), Seine Normandie Water Agency, and OPUR partners for financial support and the Seine-et-Marne Department, especially Eric Thomas and Tina Ratovelomanana, for their partnership.