Gladys Barragan-Jason
email: gladys.barraganson@gmail.com

Claire De Mazancourt

Camille Parmesan

Michael C Singer

Michel Loreau

Human-nature connectedness as a pathway to sustainability: A global meta-analysis

Keywords: environmental education, human health, human-nature connectedness, meta-analysis, nature conservation, nature-based solutions, people and nature, proenvironmental behavior, sustainability

Internationally agreed sustainability goals are being missed. Here, we conduct global meta-analyses to assess how the extent to which humans see themselves as part of nature-known as human-nature connectedness (HNC)-can be used as a leverage point to reach sustainability. A meta-analysis of 147 correlational studies shows that individuals with high HNC had more pronature behaviours and were significantly healthier than those with low HNC. A meta-analysis of 59 experimental studies shows significant increases in HNC after manipulations involving contact with nature and mindfulness practices. Surprisingly, this same meta-analysis finds no significant effect of environmental education on HNC. Thus, HNC is positively linked to mind-sets that value sustainability and behaviours that enhance it. Further, we argue that HNC can be enhanced by targeted practices, and we identify those most likely to succeed. Our results suggest that enhancing HNC, via promotion of targeted practices, can improve sustainability and should be integrated into conservation policy.

INTRODUCTION

Anthropogenic climate change and biodiversity loss are major threats not only to nonhuman living beings but also to our own survival [START_REF] Brondizio | Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services[END_REF][START_REF] Díaz | Pervasive human-driven decline of life on Earth points to the need for transformative change[END_REF][START_REF] Pachauri | Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF][START_REF] Shukla | management, food security, and greenhouse gas fluxes in terrestrial ecosystems[END_REF]). There appears to be international consensus to better preserve nature (e.g., the Convention on Biological Diversity; CBD, 2011), to limit global warming (e.g., the Paris Agreements) and to create a sustainable, equitable world (e.g., the Sustainable Development Goals). Despite this appearance, actions on all three fronts remain limited and sustainability targets have so far failed to be achieved [START_REF] Adenle | Failure to achieve 2010 biodiversity's target in developing countries: How can conservation help?[END_REF][START_REF] Buchanan | Assessment of national-level progress towards elements of the Aichi Biodiversity Targets[END_REF]. Why do citizens and governments still find it hard to consider that the health and well-being of humans depends upon the health of the natural world [START_REF] Brondizio | Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services[END_REF][START_REF] Pachauri | Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change[END_REF][START_REF] Shukla | management, food security, and greenhouse gas fluxes in terrestrial ecosystems[END_REF]? One possible explanation is cultural [START_REF] Mayer | Transforming psychological worldviews to confront climate change: A clearer vision, a different path[END_REF]. Humans in many societies perceive a clear discontinuity between the inner worlds of themselves and those Conservation Letters. 2022;15:e12852. wileyonlinelibrary.com/journal/conl 1 of 7 https://doi.org/10.1111/conl.12852 F I G U R E 1 Hypothetical representation of a vicious circle generated by a detrimental worldview (left) and a virtuous circle generated by a sustainable worldview (right). We assess whether and how human-nature connectedness can be used to switch from a detrimental to a sustainable worldview at both individual and societal levels of other living beings. This view, explicitly advocated by influential modern philosophers such as [START_REF] Kant | Idea for a universal history with a cosmopolitan purpose[END_REF], has led people to consider themselves disconnected from, and dominant over, the rest of nature. Another explanation is urbanization of the world's human population. Today, more than 55% of people live in urban areas (https://www.un.org/en/sections/issuesdepth/population/index.html), a major consequence of which is disconnection of people from experience of natural habitats [START_REF] Miller | Biodiversity conservation and the extinction of experience[END_REF]. The combination of psychological and physical disconnects from the natural world can result in devaluation of nature [START_REF] Mayer | Transforming psychological worldviews to confront climate change: A clearer vision, a different path[END_REF], thereby legitimizing and facilitating destructive practices toward nature by individuals and societies (Figure 1).

What can be done to modify these destructive trends? International scientific assessments, such as the MA, IPCC, and IPBES, indicate that healthy natural systems are crucial to reach sustainability [START_REF] Brondizio | Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services[END_REF][START_REF] Shukla | management, food security, and greenhouse gas fluxes in terrestrial ecosystems[END_REF][START_REF] Watson | Living beyond our means: Natural assets and human well-being: Statement from the board[END_REF]. The IPBES further claims that sustainable goals will not be achieved without a "transformative change" including an increase in "awareness of connectivity in the environmental crisis and new norms regarding interactions between humans and nature" (Figure 1). A key societal trait that is relevant to achieving sustainability [START_REF] Riechers | Human-nature connectedness as leverage point[END_REF] is Human-Nature Connectedness (HNC). [START_REF] Leopold | A Sand County almanac, and sketches here and there[END_REF] gave one of the first definitions of HNC when writing: "We abuse land because we regard it as a commodity belonging to us. When we see land as a community to which we belong, we may begin to use it with love and respect" (see Appendix 1). HNC has been described [START_REF] Schultz | Inclusion with nature: The psychology of human-nature relations[END_REF], defined and conceptualized in different, often complex, ways (Supplementary information [SI] Appendices 1 and 2). Despite these differences, robust and validated HNC metrics have been shown to be highly correlated with one another [START_REF] Balund Ė | Exploring the relationship between connectedness with nature, environmental identity, and environmental self-identity: A systematic review and meta-analysis[END_REF][START_REF] Brügger | One for all? European Psychologist[END_REF][START_REF] Mayer | The connectedness to nature scale: A measure of individuals' feeling in community with nature[END_REF][START_REF] Nisbet | The nature relatedness scale: Linking individuals' connection with nature to environmental concern and behavior[END_REF][START_REF] Perrin | The connectedness to nature scale: A measure of emotional connection to nature[END_REF][START_REF] Tam | Concepts and measures related to connection to nature: Similarities and differences[END_REF], which suggests that they are different expressions of a common underlying construct [START_REF] Capaldi | The relationship between nature connectedness and happiness: a meta-analysis[END_REF][START_REF] Tam | Concepts and measures related to connection to nature: Similarities and differences[END_REF]. Here we define HNC as the extent to which humans see themselves as part of nature, and we use it as an umbrella term for the different concepts and metrics that address this relatively simple and broad definition.

A number of recent studies found that estimates of HNC were positively correlated both with proenvironmental behaviour [START_REF] Mackay | Do people who feel connected to nature do more to protect it? A meta-analysis[END_REF][START_REF] Vesely | Climate change action as a project of identity: Eight meta-analyses[END_REF][START_REF] Whitburn | Meta-analysis of human connection to nature and proenvironmental behavior[END_REF] and with human welfare [START_REF] Capaldi | The relationship between nature connectedness and happiness: a meta-analysis[END_REF][START_REF] Pritchard | The relationship between nature connectedness and eudaimonic well-being: A meta-analysis[END_REF]. Due to paucity of data, however, prior syntheses of the roles of HNC were forced to lump studies with disparate methodologies, whether they be experimental or correlational, and whether or not they used metrics of HNC that had been validated. Here, we take advantage of the rapidly increasing literature to restrict our database to studies using at least one of the validated quantitative metrics of HNC [START_REF] Clayton | Environmental identity: A conceptual and an operational definition[END_REF][START_REF] Dunlap | New trends in measuring environmental attitudes: Measuring endorsement of the new ecological paradigm: A revised NEP scale[END_REF][START_REF] Mayer | The connectedness to nature scale: A measure of individuals' feeling in community with nature[END_REF][START_REF] Nisbet | The nature relatedness scale: Linking individuals' connection with nature to environmental concern and behavior[END_REF][START_REF] Schultz | Inclusion with nature: The psychology of human-nature relations[END_REF] and to distinguish between experimental and correlational studies. Thus, for the first time, we provide a robust, coherent, and global synthesis of the HNC literature with separate meta-analyses of experimental and correlational studies (Figure S1 and Table S1). This allows us to identify practices that have the potential for increasing HNC, and investigate whether HNC is a key element of sustainability, in particular nature conservation and human welfare.

METHODS

Data search and inclusion

We followed the PRISMA guidelines to conduct a systematic review of the literature [START_REF] O'dea | Preferred reporting items for systematic reviews and metaanalyses in ecology and evolutionary biology: a PRISMA extension[END_REF]. We searched previous papers assessing HNC on Web of Science (WoS) and PubMed from 1900 to 2020 with search terms corresponding to the various HNC metrics used in previous published reviews, opinions and meta-analyses (see details in Table S1), and obtained 2098 citations (see Figure S1 for PRISMA flow diagram).

Only empirical, quantitative and peer-reviewed published papers that were written in English were made eligible for inclusion. Researchers have developed several hundred constructs and metrics of HNC that tackle one or several aspects of HNC (e.g., cognitive and affective components). Despite differences in how HNC is conceptualized, five metrics have been shown to robustly assess HNC and to be highly correlated with one another [START_REF] Balund Ė | Exploring the relationship between connectedness with nature, environmental identity, and environmental self-identity: A systematic review and meta-analysis[END_REF][START_REF] Brügger | One for all? European Psychologist[END_REF][START_REF] Mayer | The connectedness to nature scale: A measure of individuals' feeling in community with nature[END_REF][START_REF] Nisbet | The nature relatedness scale: Linking individuals' connection with nature to environmental concern and behavior[END_REF][START_REF] Perrin | The connectedness to nature scale: A measure of emotional connection to nature[END_REF][START_REF] Tam | Concepts and measures related to connection to nature: Similarities and differences[END_REF]. We focused on these five metrics (for a detailed description of HNC scales, see SI Appendices 2 and 3): the New Environmental Paradigm (NEP; [START_REF] Dunlap | New trends in measuring environmental attitudes: Measuring endorsement of the new ecological paradigm: A revised NEP scale[END_REF], the Inclusion of Nature in the Self (INS; [START_REF] Schultz | Inclusion with nature: The psychology of human-nature relations[END_REF], the Environmental Identity Scale (EID; [START_REF] Clayton | Environmental identity: A conceptual and an operational definition[END_REF], the Connectedness to Nature Scale (CNS; [START_REF] Mayer | The connectedness to nature scale: A measure of individuals' feeling in community with nature[END_REF], and the Nature Relatedness scale (NR; [START_REF] Nisbet | The nature relatedness scale: Linking individuals' connection with nature to environmental concern and behavior[END_REF]. While NEP, INS, and CNS attempt to measure the cognitive dimension of HNC, NR, and EID include both cognitive and affective components [START_REF] Clayton | Environmental identity: A conceptual and an operational definition[END_REF][START_REF] Nisbet | The nature relatedness scale: Linking individuals' connection with nature to environmental concern and behavior[END_REF]. Papers measuring at least one widely used and repeatable HNC measure (NEP, INS, EID, CNS, or NR) and at least one factor (correlational and/or experimental studies) were included.

At the end of the screening, 124 publications met the eligibility criteria. For all studies, we extracted the number of participants, region (Africa, Asia, Europe, North America, South America, and Oceania), country, gender ratio (>60% female, between 40 and 60% female, <40 % female) and age group (<18 years, between 18 and 25 years, between 26 and 40 years, >40 years) as well as duration of the intervention (≤1 day, ≥2 days) and time of posttest (immediately after intervention, ≥2 weeks after intervention) when appropriate. For correlational studies (107 papers), we extracted Pearson's correlation coefficients between HNC and the factors of interest. For experimental studies (35 papers), we extracted HNC means and standard deviations for treatment and control groups. When correlations, means, or SDs were missing from the paper, we emailed the corresponding author. Overall, we obtained a total of 1080 effects sizes from 198 studies (i.e., sample) from 124 papers involving 69,763 participants to perform the meta-analyses.

Statistical analysis

All statistical analyses were performed in R (4.0). For experimental data, we performed the meta-analysis on Standardized Means Difference (SMD; Hedges' g). For correlational data, meta-analyses were done on Pearson's correlations after Fisher transformations. All estimates were calculated for each factor with the rma.mv function from the metaphor package [START_REF] Viechtbauer | Package 'metafor'. The Comprehensive R Archive Network. Package 'metafor[END_REF] in R, which permits to fit meta-analytic multivariate fixedand random/mixed-effects models with or without factors via linear (mixed-effects) models.

We accounted for nonindependence of data by including random effects at the article level (multiple data from the same paper), at the study level (multiple data from the same participant) and at the estimate level (multiple estimates within a study within a paper). Then, we transformed mean effect sizes (SMD and Fisher's Z) into mean R effect sizes. Z tests and omnibus tests were performed when appropriate. We provide additional methods and results in SI (i.e., funnel and forest plots in Figure S5 and Appendices 4-6).

RESULTS

Experimental studies

Existing experimental studies are strongly biased toward adults rather than children and high-income industrialized countries (Figure S2). We combined two types of comparison: (1) sequential comparison of trait measurements made on the same participants before and after experimental treatment and (2) simultaneous comparison of control and treatment groups (see Methods and SI Appendix 4).

All experimental designs, except environmental education, affected HNC significantly and positively (Figure 2 and Table S2). The clearest positive effects on HNC were those of mindfulness, with or without experience of real nature, while the estimated positive effects of environmental education were low. Importantly, while both short (≤1 day) and long (≥2 days) interventions enhanced HNC in the short term (i.e., immediately after the intervention), long-term effects (i.e., retention test after 2 weeks or more) were only observed after long interventions (Appendix 5 and Figure S3). Effect sizes did not differ significantly between HNC measures in experimental studies (Appendix 5, Figure S4, and Table S4).

Thus, experimental studies show that exposing individuals to nature, either real or virtual, does improve HNC. They also suggest exciting lines of future research to improve the efficiency of experimental programs designed to raise HNC by including mindfulness practices.

Correlational studies

Like experimental studies, correlational studies are strongly biased toward adults from industrialized countries. Our meta-analysis shows that HNC is negatively correlated with materialism/consumerism and political conservatism, and positively correlated with the following suite of behaviours, opinions and personality traits: naturalist knowledge; time spent in natural outdoor spaces; engagement in mindfulness practices; proenvironmental values; humanistic values; happiness; and good health. In sum, individuals with high HNC had a deeper knowledge of nature, spent more time in natural outdoor spaces, engaged more in mindfulness practices and were happier and healthier than those with low HNC. It is not surprising, then, that individuals with high HNC displayed more proenvironmental values, expressed as concerns and attitudes toward their natural environment. They were also more humanistic, in the sense of more strongly expressing their moral responsibilities to other humans, and their sense of being part of communities within society (Figure 2; see Methods, SI Appendix 4 for detailed categories, Table S3 and Figures S4-S7).

Additionally, one-third of the correlational papers (26 out of 108) addressed causal hypotheses using either structural equation models or path analysis. Although these approaches have limited ability to infer causality, these studies nonetheless suggest impacts of both contact with nature and mindfulness on HNC, in agreement with experimental studies (Figure 2 and Table S2). In the opposite direction of causality, they also suggest impacts of HNC on proenvironmental values, human well-being, and health and proenvironmental behaviours.

Unlike experimental studies, effect sizes from correlational studies differed significantly between HNC metrics (Appendix 5 and Figure S4). Notably, HNC metrics that include both cognitive and affective aspects of HNC (i.e., EID, NR) showed significantly higher effect sizes than did HNC metrics with only cognitive components (i.e., CNS, NEP, INS; see Appendix 5, Figure S4, and Table S4).

Taken together, correlational studies support conclusions from experimental studies, but they further show that HNC is positively linked to values and behaviours that enhance ecological sustainability and well-being, and neg-atively linked to nonenvironmental or antienvironmental values. Future experimental research contrasting the effects of interventions that do enhance or do not enhance HNC is needed to test causal relationships, particularly the hypothesis suggested by our meta-analysis that raising HNC would enhance both human welfare and nature conservation.

DISCUSSION

Our meta-analyses robustly show that the extent to which people feel part of nature can be enhanced by simple interventions involving contact with nature and mindfulness practices, at least in industrialized countries, which form the bulk of existing studies. They also show that validated HNC indices are positively linked to human welfare and nature conservation. Thus, improving HNC through contact with nature and mindfulness can be a valuable way to help individuals to understand and experience how much human welfare and nature conservation are interconnected [START_REF] Rabinowitz | A planetary vision for one health[END_REF][START_REF] Wang | Mindfulness increases the belief in climate change: The mediating role of connectedness with nature[END_REF]. By promoting targeted and long-term interventions (e.g., weekly mindfulness sessions, outdoor education) to governmental and nongovernmental institutions (UNESCO, OECD, school organisations, environmental education groups) and by training those who educate young people in these practices (teachers, educators, and parents), we believe that the desired outcomes (nature conservation and human well-being) could be achieved at a moderate cost. As an example, "greening" schoolyards could improve people's HNC and well-being and thereby foster support for sustainable policies, adding to its known positive effects on urban biodiversity and climate adaptation (the virtuous circle in Figure 1). Surprisingly, we found little impact of environmental education on HNC, and we assume that this is due to the traditional anthropocentric, "rational" transmission of scientific knowledge, which has delegitimized and suppressed its emotional content [START_REF] Buijs | Emotional conflicts in rational forestry: Towards a research agenda for understanding emotions in environmental conflicts[END_REF]. Accordingly, and in line with previous studies [START_REF] Tam | Concepts and measures related to connection to nature: Similarities and differences[END_REF], we found that HNC metrics that include multifaceted measures of HNC (i.e., both cognitive and affective) show the highest effect sizes. While this result remains to be further tested, studies in nonindustrialized populations [START_REF] Atran | Folkecology, cultural epidemiology, and the spirit of the commons: A garden experiment in the Maya Lowlands[END_REF] and children [START_REF] Moore | Healthy planet, healthy children: Designing nature into the daily spaces of childhood. Biophilic Design: The Theory[END_REF] suggest that modifying the way scientific information is transmitted using nonanthropocentric knowledge about nonhuman species can have a positive impact on HNC. Examples of nonanthropocentric approaches, which would likely foster empathy and compassion toward the natural world [START_REF] Mayer | Transforming psychological worldviews to confront climate change: A clearer vision, a different path[END_REF], include teaching children about the similarities between humans and other species [START_REF] Clay | Development of socio-emotional competence in bonobos[END_REF][START_REF] Yokawa | Anesthetics, anesthesia, and plants[END_REF] and employing techniques to induce empathy toward all living beings [START_REF] Berenguer | The effect of empathy in proenvironmental attitudes and behaviors[END_REF].

If we are to develop effective research and conservation programmes that simultaneously support both people and nature worldwide, we urgently need longitudinal studies in children and in nonindustrial traditional cultures. Children from industrialized societies are known to show a strong affinity for nonhuman organisms [START_REF] Moore | Healthy planet, healthy children: Designing nature into the daily spaces of childhood. Biophilic Design: The Theory[END_REF], but this affinity tends to fade with age [START_REF] Hughes | Age and connection to nature: when is engagement critical?[END_REF] and develop into low ecological concern at adulthood [START_REF] Rosa | Nature experiences and adults' self-reported pro-environmental behaviors: The role of connectedness to nature and childhood nature experiences[END_REF] along with the acquisition of anthropocentric cultural norms [START_REF] Wilks | Children prioritize humans over animals less than adults do[END_REF]. We know much less about equivalent developmental changes in traditional societies, although proenvironmental behaviours may be more likely to persist into adulthood in societies with a high interdependency between humans and nature [START_REF] Atran | Folkecology, cultural epidemiology, and the spirit of the commons: A garden experiment in the Maya Lowlands[END_REF]. Increased knowledge and appreciation of cultural norms and values and their development in diverse societies, both traditional and industrial, should contribute to better international environmental and educational policies and empower citizens and governments to achieve sustainable goals on a global scale.

A C K N O W L E D G M E N T S

This work was supported by the TULIP Laboratory of Excellence (ANR-10-LABX-41) and was conducted within the framework of the BIOSTASES Advanced Grant, funded by the European Research Council under the European Union's Horizon 2020 research and innovation programme (No 666971). Parmesan, Singer and Barragan-Jason were funded by a French Make Our Planet Great Again award (project CCISS, number ANR-17-MPGA-0007). We thank Dr Florian Arendt, Dr. Alexia Barrable, Dr. Nicolette L. Cagle, Dr. Susan Clayton, Dr. Paul W. Dierkes, Dr. Matthias Forstmann, Dr. Christian Martin, Dr. Kirsten McEwan, Dr. Marijn Meijers, Dr. Lisa K. Nisbet, Dr. Helen Perkins, Dr. Miles Richardson, Alyssa San Jose Abrams (M.Ed), Dr. Markus Schwab and Dr. Daniela Sellmann-Risse for providing additional information and data from their studies. We also thank researchers from the https://stat.ethz.ch/mailman/listinfo/r-sig-metaanalysis// mailing list for providing feedback on statistical analysis especially on the implementation of random effects in the meta-analysis.

A U T H O R C O N T R I B U T I O N S

GBJ: conceptualization, methodology, analysis, writingoriginal draft preparation, writing-reviewing, and editing. CM: conceptualization, writing-reviewing, and editing. CP: writing-reviewing and editing, funding acquisition. MS: writing-reviewing and editing. ML: conceptualization, writing-reviewing, and editing, funding acquisition.

E T H I C S S TAT E M E N T

This study complies with ethical scientific standards.

D ATA AVA I L A B I L I T Y S TAT E M E N T

Data and code are freely available in the OSF repository at https://osf.io/ytrcn/?view_only=636530a6baab48 cf9b8ac4f5daa204aa.

C O N F L I C T O F I N T E R E S T

The authors declare no conflict of interest.

O R C I D

Gladys Barragan-Jason https://orcid.org/0000-0002-8002-6643

R E F E R E N C E S

F

  Results from meta-analyses of experimental (blue background and text) and correlational (green and orange backgrounds and text) studies. Each dot represents the average R estimate for each factor obtained after transforming averaged standardized effect sizes (Fisher's Z for correlational data and Hedges' g for experimental data) with n, k, and s referring to the number of papers, number of effect sizes and number of participants, respectively. Horizontal lines indicate the 95% confidence intervals for each factor and cross the vertical dot lines when nonsignificant (i.e., environmental education in experimental studies). Single-headed arrows refer to causal relationships while double-headed arrows refer to correlational links. Overall R estimates from each broad category are in bold. Details are provided in Methods, Appendix 5, TablesS2-S4, and FigureS4. Experimental studies show that exposure to nature and mindfulness practices improve HNC. Correlational studies confirmed experimental studies and show that HNC is positively linked to nature conservation and human welfare and negatively linked to nonenvironmental values. **p < 0.001; ***p <

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Funding information

TULIP Laboratory of Excellence, Grant/Award Number: ANR-10-LABX-41; European Research Council under the European Union's Horizon 2020 research and innovation programme, Grant/Award Number: 666971; Make Our Planet Great Again award, Grant/Award Number: ANR-17-MPGA-0007


Audrey Breton

Claire Vialle

Mireille Vignoles

Christine Cecutti

Christian Vignoles

Caroline C Sablayrolles

Mireille Montrejaud-Vignoles

Contribution of car, truck, bus and subway wash station discharges to stormwater pollution (Toulouse, France)

Keywords: Organic compounds, concentrations, separated sewage system, water quality, run-off waters

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

Introduction

Stormwater is known to be an important source of received water pollution [START_REF] Clark | Water supply and pollution control, 2 nd ed[END_REF]. With regard to the European Water Directive [START_REF]Water Framework Directive 2000/60/EC[END_REF], it is necessary to monitor a wide range of organic micropollutants in addition to classical water quality parameters.

Concentrations of classical parameters observed in urban runoff are listed in Table 1. The values observed in the literature for classical parameters show an average pH around 7.5 ([3], [START_REF] Legret | Effets d'une chaussée poreuse à structure réservoir sur la qualité des eaux pluviales[END_REF]). The COD values varied according to the type of surface considered ( [START_REF] Gromaire-Mertz | Characterisation of urban runoff pollution in Paris[END_REF]; [START_REF] Legret | Evaluation of pollutant loadings in the runoff waters from a major rural highway[END_REF]). Organic micropollutants in the environment originate from anthropogenic activities. Their concentrations observed in urban runoff are listed in Table 2. The main sources of polycyclic aromatic hydrocarbons originate from pyrolysis of organic matter under high temperature [START_REF] Moilleron | Aromatic and aliphatic hydrocarbons distribution (in french)[END_REF]. Actually, urban surfaces can receive deposits of PAHs from different sources via both atmospheric transport and local activity [START_REF] Cailleaud | Seasonal variations of hydrophobic organic contaminant concentrations in the water-column of the Seine estuary and their transfer to a planktonic species Eurytemora affinis (Calanoïd, copepod). Part 1: PCBs and PAHs[END_REF]. Methyltertbutylether is a volatile organic compound produced from natural gas. It is introduced into the environment via leaking petroleum storage tanks, urban runoff, and motorized watercraft [START_REF] Achten | Methyl tert-butyl ethet (MTBE) in urban and rural precipitation in Germany[END_REF]. The case of Toulouse in France is particularly interesting since the town has a separated sewer system where organic micropollutants in the wastewater system cannot mix with the stormwater [START_REF] Xaumier | Study of the Toulouse (France) urban runoff (in french)[END_REF]. However, water in the latter system comes not only from runoffs but also from wash station discharges. Indeed, industrial waters can be discharged into sewers under a permission of discharge from the community [START_REF]Public health code[END_REF]. Wash stations can discharge their waters after pre-treatment through two structures (figure 1). Waters go through the scrubber, where the solids are removed, then through the oil separator to remove hydrocarbons. These systems should be in accordance with French norm XP P 16-441 [START_REF]Scrubber, separator of light liquids and metal combined apparatus[END_REF] and require regular maintenance to keep up their efficiency [START_REF]III-Industrial wastewater -Article 26[END_REF].

The aim of this work was to study the efficiency of these pre-treatment processes and the rejects from wash stations upstream of the stormwater network to accurately evaluate the impact of this source of pollution on stormwater quality.

Materials and Methods

Sampling sites

The pre-treatment efficiency was evaluated at three points for the subway and three points for bus wash stations. For the subway station, the three points tested were: machine parts washing (site A), vehicle washing (site B) and rail washing (site C). The selected points for bus stations were the large workshop wash (site D), vehicle wash station (site E) and the machine parts washing (site F).

One subway, one bus, one truck and two car wash stations were selected to evaluate pollution. On Site 1, trucks only, were washed manually. The second site chosen was for cars and motorcycles with a self-service high-pressure water jet (Site 2). Site 3 was in a petrol station and comprised a self-service high-pressure water jet and roller brush washing. Site A was a subway wash station (machine parts washing). Site E was a bus wash station. These five sites discharged wastewater into the stormwater network downstream of a pretreatment system composed of a scrubber and an oil separator.

Figure 2 shows the sampling site locations.

Sampling method

Concerning sites selected to evaluate pre-treatment efficiency, samples were collected and analysed between September 2002 and September 2003. Five samples per site were taken during the year. Samples were taken manually upstream and downstream of the pre-treatment system. Each time, around 15L of discharge was collected and then homogenized in order to obtain a representative sample.

Concerning sites 1, 2 and 3, samples were collected and analysed between December 2006 and December 2007. For sites A and E samples were collected and analysed between September 2002 and September 2003. Five samples per site were taken during the year. Samples were taken manually from a conveyance at the pre-treatment process exit. Each time, around 15L of discharge was collected and then homogenized in order to obtain a representative sample.

Analysis

Conductivity, pH and turbidity of total water samples were checked and measured. Commercial tests (Spectroquant ®, Merck) were used to analyze chemical oxygen demand (COD), nitrogen (tot-N), phosphorus (tot-P) on raw and filtered samples. Suspended solid (SS) was investigated by filtration using NF-T90-105-1 and NF-T90-029 respectively.

To complete the common characterization, organic micropollutants were analyzed. Polycyclic aromatic hydrocarbons (PAHs) were analysed using liquid-liquid extraction with Hexane followed by liquid chromatography with fluorescence detection according to NF EN ISO 17993. The elution was made with mobile phase consisted of acetonitrile and water. A mixed of two deuterated compounds was used as internal standard. Detection was performed with a fluorescence detector at emission and excitation wavelengths of studied compounds. The 16 PAHs from the United States Environmental Protection Agency were targeted. Limit of quantification (LOQ) for the sum of PAHs was 0.01 µg/L. Methyl tert-butyl ether (MTBE) was analysed with gas chromatography-mass spectrometry after head-space extraction with a limit of quantification of 1 µg/L. A deuterated compound (MTBE-d 3 ) was used as internal standard. Mass chromatography of m/z 73 (MTBE) and m/z 76 (MTBE-d 3 ) in full scan mode was used for quantification. Total hydrocarbons (TH) were analysed using liquid-liquid extraction with oil ether and a gas chromatograph equipped with a flame ionization detector according to NF EN ISO 9377-2. Two compounds were used as references for the retention time: n-Decane and n-Tetracontane. Limit of quantification was 0.10 mg/L.

Table 3 and 4 resume analytical method.

To complete the study, subway wash station effluents (site A) were tested using a biodegradability test according to the standardised OCDE 301 B test. This test is based on the modified Sturm method. Principle of the method is to quantify the CO 2 release by the effluent during 28 days. This is a respirometric method. In the modified Sturm test, we consider that we have an easily biodegradable effluent if produced CO 2 reaches 60% in ten days after the rate of produced CO 2 reaches 10%.

Results and discussion

Pre-treatment system efficiency

The concentrations of classical parameters were determined upstream and downstream of the pre-treatment for the bus and subway wash stations selected. Table 5 shows concentrations for raw and filtered samples.

From Table 5 it can be seen that concentrations of COD, Tot-P, Tot-N and SS, for the three sites (A, B, C) of subway wash stations and for site D, are less downstream of pre-treatment than upstream. The Pretreatments for these sites seem to be efficient since a reduction of pollution is observed. On the other hand, concentrations of classical parameters are higher in downstream samples than in upstream ones for sites E and F, and no reduction of pollution is observed. Therefore pre-treatment systems seem to be inefficient to treat the wastewater from the bus wash stations. This can be explained by the fact that either the pretreatment is not adapted to this type of effluent, or there is insufficient maintenance. On account of the high COD concentration of subway wash effluent, a biodegradability test was performed on site A effluent. Figure 3 shows the results obtained for the biodegradability test. As can be seen in Figure 3, the curve reaches 60% of produced CO 2 at the 10 th day of the test. According to the modified Storm method, the subway wash effluent was easily biodegradable. Moreover, the curve reaches 100% biodegradability after 25 days. The subway effluent rejected a lot of pollution into the stormwater network but considering its biodegradability this effluent rejected into the stormwater network, was an acceptable effluent. This result showed that the pollution covering classical parameters is not sufficient to characterize the effluent considered and the biodegradability should also be tested to evaluate the quality of the effluent rejected. Concentrations of Tot-P and Tot-N are almost equal between raw and filtered samples. These types of pollutant are more concentrated in aqueous phase than in particulate phase. The values of COD decrease between the raw and filtered samples for sites A, B, C, D and F. For site E, COD values are higher in filtered samples than in raw samples. The difference between raw and filtered samples corresponds to suspended solids (SS). The pollutants (tot-N, tot-P and COD) are fixed on the suspended solids and consequently they transport most of the pollution. This result agrees with the studies of [START_REF] Xaumier | The effectiveness of two urban runoff pre-treatment systems, situated before introduction into the storm sewer network[END_REF], [START_REF] Aires | Les séparateurs à hydrocarbures et la dépollution des eaux pluviales[END_REF], and [START_REF] Chebbo | La pollution des rejets urbains par temps de pluie : flux, nature et impacts[END_REF]. They explain that more than 80% of pollution is conveyed by suspended solids.

Concentrations in wash station samples

Minimum, maximum, mean, median and standard deviation values were calculated for each parameter for the six wash stations selected (Table 6). Values less than the quantification limit were taken as zero for statistical calculations. According to Table 6, pH of water seems to be constant during the study for each site. It satisfies the legislation which requires a value between 5.5 and 9.5 for discharge in surface water [START_REF]Water sampling and consumption. Pollutants emissions of industries[END_REF] and corresponds to the values found in the literature ( [START_REF] Legret | Effets d'une chaussée poreuse à structure réservoir sur la qualité des eaux pluviales[END_REF], [START_REF] Xaumier | Study of the Toulouse (France) urban runoff (in french)[END_REF], [START_REF] Barraud | The impact of intentional stormwater infiltration on soil and groundwater[END_REF]). Conductivity is high and variable over the sampling period with mean values from 490 to 4 360 µS/cm according to type of wash station. Globally, the observed values are higher than those found in urban runoff literature ([3], [START_REF] Xaumier | Study of the Toulouse (France) urban runoff (in french)[END_REF]). Mean values of COD (from 227 to 949 mg/L) are always above the required threshold of 125 mg/L [START_REF]Water sampling and consumption. Pollutants emissions of industries[END_REF] and these observed values are higher than those found in the literature ( [START_REF] Xaumier | Study of the Toulouse (France) urban runoff (in french)[END_REF], [START_REF] Boisson | Impacts des eaux de ruissellement de chaussées sur les milieux aquatiques. 3 ème conférence internationale Novatec[END_REF], [START_REF] Balades | Contribution des apports routiers aux rejets urbains de temps de pluie rôle de la conception et de la gestion de la voirie[END_REF], [START_REF] Barraud | Caractérisation des eaux pluviales et risques sanitaires. Conférence ASTEE, Eau et santé, Eaux pluviales et assainissement : nouvelles préoccupations sanitaires[END_REF]). The mean values for SS from 45 to 869 mg/L do not conform to the legislation which requires a value below 35 mg/L. Concerning tot-P, only Site 3 and Site 5 satisfy the limit value of 10 mg/L. Concentrations of tot-N for the five sites are lower than the limit value of 30 mg/L. For conventional water parameters, Site 1 (manual truck wash) and 4 (subway wash station) appear to be much more polluted overall than Sites 6, 2, 4 and 3. Nevertheless, classical parameters give values with an order of magnitude closer to wastewater than urban runoff and these results show that the pre-treatment processes of at least one of these wash stations are not sufficient to justify discharge into the storm water network. Mean values for the sum of PAHs was higher than values found in the literature for urban runoffs ( [START_REF] Fernandes | Polyaromatic hydrocarbon (PAH) distributions in the Seine River and its estuary[END_REF], [START_REF] Popp | Application of stir bar sorptive extraction in combination with column liquid chromatography for the determination of polycyclic aromatic hydrocarbons in water samples[END_REF]). MTBE mean concentrations correspond to German and Italian drinking water values for instance ( [START_REF] Kolb | Methyl tert-butyl ether (MTBE) in finished drinking water in Germany[END_REF], [START_REF] Piazza | A rapid and sensitive method for methyl tert-butyl ether analysis in water samples by use of solid microextraction and gas chromatography-mass spectrometry[END_REF]). Total Hydrocarbons were always under the 10 mg/L fixed by the discharge license. Results overall show that Site 1 is the most polluted in the organic compounds analyzed.

Conclusions

This study aims to evaluate the efficiency of pre-treatment systems of wash stations and the impact of their discharges on the stormwater quality in a city equipped with a separated sewer system. Screening of classical parameters upstream and downstream of pre-treatment was performed. It reveals that this system is not adapted to treat water from bus wash stations unlike the subway wash stations. It was noticeable that suspended solids transport a lot of pollutants. The screening of classical parameters and organic micropollutants in wash station wastewaters reveals that measured concentrations in wash station discharges were closer to values found in wastewater than in runoff water. According to this observation and the directive, pre-treatment processes are not sufficient to justify discharge into the stormwater network. 9/13

Figure 1 .

 1 Figure 1. Pre-treatment diagram.

Figure 2 .

 2 Figure 2. Location of sampling sites.

Figure 3 .

 3 Figure 3. Biodegradability curve of subway wash effluent.

Table 1 .

 1 Reported concentrations of classical parameters in waters.

	Concentrations	References

Table 2 .

 2 Reported concentrations of organic pollutants in waters.

	Concentrations

Table 3 .

 3 Analytical methods for classical parameters.

	Parameters	Standard	Spectroquant ® test	Measuring range	Method
			reference
	pH	NFT 90-008	-	-	potentiometric
	Conductivity	NF EN 27888	-	-	condutimetric
	Turbidity	NF EN ISO 7027	-	-	optical
	SS	NF EN ISO 872	-	-	filtration
	COD	NFT 90-101	1.14541.0001	100 -1500 mg/L	Photometry (593 nm)
	tot-P	NF EN ISO 11905-1	1.14543.0001	0.05 -5 mg/L	Photometry (710 nm)
	tot-N	NF EN ISO 6878	1.14763.0001	10 -150 mg/L	Photometry (338nm)

Table 4 .

 4 Analytical methods for organic micropollutants.

	Organic	Standard	Extraction	Analyse	LOQ
	micropollutants
	PAH	NF EN ISO 17993	Liquid -Liquid	HPLC -FLD	0.01 µg/L
			with Hexane	(Acetonitrile/Water)	(sum of 16 PAHs
					from EPA)
	MTBE	-	Head-space	GC -MS	1.0 µg/L
	TH	NF EN ISO 9377-2	Liquid-Liquid	GC -FID	0.1 mg/L
			with oil ether

Table 5 .

 5 Concentration of classical parameters for the bus and subway wash stations studied.

		Units	n	Raw samples	Filtered samples
			Upstream of	Downstream of	Upstream of	Downstream of
			pre-treatment	pre-treatment	pre-treatment	pre-treatment
	Site A: machine parts washing -Subway
	COD	mg/L	5	3290 ±329	1790 ±179	2200 ±220	1172 ±117
	Tot-P	mg/L	5	108 ±10.8	42.9 ±4.3	47.5 ±4.8	42.9 ±4.3
	Tot-N	mg/L	5	31 ±3.1	22 ±2.2	31 ±3.1	24 ±2.4
	pH	-	5	10.3 ±0.1	10.1 ±0.1	10.2 ±0.1	9.9 ±0.1
	Conductivity	µS/cm 5	2820 ±10	1906 ±10	2670 ±10	1789 ±10
	Turbidity	NTU	5	950 ±95	870 ±87	-	-
	SS	mg/L	5	1136 ±114	790 ±79	-	-
	Site B: vehicle washing -Subway
	COD	mg/L	5	106 ±11	38 ±4	43 ±4	21 ±2
	Tot-P	mg/L	5	1.9 ±0.2	0.8 ±0.1	0.6 ±0.1	0.6 ±0.1
	Tot-N	mg/L	5	7.0 ±0.7	5.0 ±0.5	6 ±0.6	2 ±0.2
	pH	-	5	8.7 ±0.1	8.5 ±0.1	8.4 ±0.1	8.4 ±0.1
	Conductivity	µS/cm 5	255 ±10	230 ±10	236 ±10	233 ±10
	Turbidity	NTU	5	81.5 ±8.2	27.5 ±2.8	-	-
	SS	mg/L	5	314 ±31	20 ±2	-	-
	Site C: rail washing -Subway
	COD	mg/L	5	1148 ±115	51 ±5	372 ±37	25 ±3
	Tot-P	mg/L	5	1.5 ±0.2	0.7 ±0.1	0.4 ±0.1	0.4 ±0.1
	Tot-N	mg/L	5	22 ±2.0	11 ±1.0	16 ±2.0	11 ±1.0
	pH	-	5	9.7 ±0.1	9.2 ±0.1	8.4 ±0.1	8.1 ±0.1
	Conductivity	µS/cm 5	1395 ±10	234 ±10	1129 ±10	227 ±10
	Turbidity	NTU	5	958 ±96	59 ±6	-	-
	SS	mg/L	5	1252 ±125	81 ±8	-	-
	Site D: large workshop wash -Bus
	COD	mg/L	5	413 ±41	285 ±29	298 ±30	144 ±14
	Tot-P	mg/L	5	0.6 ±0.1	0.2 ±0.1	0.1 ±0.1	0.1 ±0.1
	Tot-N	mg/L	5	<10	<10	<10	<10
	pH	-	5	7.6 ±0.1	7.4 ±0.1	6.7 ±0.1	6.9 ±0.1
	Conductivity	µS/cm 5	534 ±10	540 ±10	518 ±10	512 ±10
	Turbidity	NTU	5	203 ±20	79 ±8	-	-
	SS	mg/L	5	318 ±32	77 ±8	-	-
	Site E: vehicle wash station -Bus
	COD	mg/L	5	129 ±13	349 ±35	190 ±19	1119 ±112
	Tot-P	mg/L	5	0.17 ±0.1	0.3 ±0.1	0.13 ±0.1	0.34 ±0.1
	Tot-N	mg/L	5	<10	<10	<10	<10
	pH	-	5	7.6 ±0.1	7.0 ±0.1	6.2 ±0.1	6.8 ±0.1
	Conductivity	µS/cm 5	255 ±10	222 ±10	237 ±10	199 ±10
	Turbidity	NTU	5	76 ±8	59 ±6	-	-
	SS	mg/L	5	94 ±9	73 ±7	-	-
	Site F: machine parts washing -Bus
	COD	mg/L	5	669 ±67	786 ±79	233 ±23	209 ±21
	pH	-	5	7.5 ±0.1	7.5 ±0.1	7.8 ±0.1	7.6 ±0.1
	Turbidity	NTU	5	252 ±25	324 ±32	-	-
	SS	mg/L	5	420 ±42	869 ±87	-	-

Table 6 .

 6 Statistical data on water quality of the three carwashes studied.

		*Environmental standards under French legislation (Decree February 2 nd , 1998)
		Units	n	Min.	Max.	Mean	Median	Standard deviation	Environmental standards
	Site 1: truck carwash
	COD	mg /L	5	539	1 506	949	654	462	125*
	Tot-P	mg/L	5	16.5	53.2	35.5	29.6	15.6	10*
	Tot-N	mg/L	5	8	19	12	11	4	30*
	pH	-	5	4.9	6.9	6.0	5.8	0.8	5.5-9.5*
	Conductivity	µS/cm	5	687	8450	4357	3849	2884	-
	Turbidity	NTU	5	60	152	126	133	38	-
	SS Σ Σ Σ Σ PAHs (16)	mg/L µg/L	5 5	46 1.002	518 2.740	302 1.778	236 1.726	208 0.638	35* -
	MTBE	µg/L	5	<LOQ	12.0	2.4	<LOQ	5.4	-
	TH	mg/L	5	<LOQ	0.92	0.56	0.58	0.34	10*
	Site 2: self-service carwash
	COD	mg/L	5	80	421	239	185	145	125*
	Tot-P	mg/L	5	4.0	99	28	5.4	41	10*
	Tot-N	mg/L	5	6	14	9	8	3	30*
	pH	-	5	8.6	9.6	9.1	9.2	0.4	5.5-9.5*
	Conductivity	µS/cm	5	562	2880	1457	1273	958	-
	Turbidity	NTU	5	42	203	100	80	68	-
	SS Σ Σ Σ Σ PAHs (16)	mg/L µg/L	5 5	35 0.016	223 0.826	130 0.372	124 0.361	67 0.318	35* -
	MTBE	µg/L	5	<LOQ	1.5	0.3	<LOQ	0.7	-
	TH	mg/L	5	<LOQ	0.12	0.02	<LOQ	0.05	10*
	Site 3: petrol station carwash
	COD	mg/L	5	144	301	227	235	59	125*
	Tot-P	mg/L	5	0.3	0.8	0.5	0.5	0.2	10*
	Tot-N	mg/L	5	6	13	10	9	3	30*
	pH	-	5	6.7	7.5	7.0	7.1	0.3	5.5-9.5*
	Conductivity	µS/cm	5	254	638	490	523	153	-
	Turbidity	NTU	5	23	43	32	27	9	-
	SS Σ Σ Σ Σ PAHs (16)	mg/L µg/L	5 5	13 0.101	90 0.731	45 0.319	51 0.170	32 0.276	35* -
	MTBE	µg/L	5	<LOQ	1.3	0.3	<LOQ	0.6	-
	TH	mg/L	5	<LOQ	0.24	0.09	0.11	0.10	10*
	Site A: subway wash station
	COD	mg /L	5	38	1790	626	51	1008	125*
	Tot-P	mg/L	5	0.7	42	14	0.8	24	10*
	Tot-N	mg/L	5	5	22	13	11	9	30*
	pH	-	5	8.5	10.1	9.3	9.2	0.8	5.5-9.5*
	Conductivity	µS/cm	5	230	1906	790	234	966	-
	Turbidity	NTU	5	28	870	319	59	478	-
	SS Σ Σ Σ Σ PAHs (16)	mg/L µg/L	5 5	20	790	297 <LOQ	81	428	35* -
	MTBE	µg/L	5			<LOQ			-
	TH	mg/L	5			<LOQ			10*
	Site E: bus wash station
	COD	mg/L	5	285	349	317	317	45	125*
	Tot-P	mg/L	5	0.2	0.3	0.2	0.2	0.1	10*
	Tot-N	mg/L	5	<10	<10	<10	<10	<10	30*
	pH	-	5	7.0	7.4	7.2	7.2	0.3	5.5-9.5*
	Conductivity	µS/cm	5	222	540	381	381	225	-
	Turbidity	NTU	5	58.6	79	68.8	68.8	14.4	-
	SS Σ Σ Σ Σ PAHs (16)	mg/L µg/L	5 5	73	77	75 0.037	75	3	35* -
	MTBE	µg/L	5			<LOQ			-
	TH	mg/L	5			0.47			10*

Email address: caroline.sablayrolles@ensiacet.fr


Guillaume Busset

Claire Vialle
email: claire.vialle@ensiacet.fr

Mireille Montréjaud-Vignoles

Mariechristine Huau

Séverine Jacob

Caroline Sablayrolles

HEALTH RISK ASSESSMENT CASE STUDY OF TRACE METALS IN COLLECTED RAINWATER FOR DOMESTIC USES

Keywords: heavy metals, ingestion, monte-carlo simulation, reuse, risk assessment, roof run-off

A health risk assessment methodology based on modelling with a Monte Carlo simulation was applied to harvested rainwater that could be used for domestic use in southern France. Firstly a pilot roof run-off collection system was installed and trace metals analysis in collected rainwater were developed. Next, a model of exposure was built based only on chronic ingestion of rainwater during domestic activities. For exposure scenarios, three type of population were investigated: infants, children, and adults. A fourth scenario was used to determine an average risk for an entire lifetime. A Monte Carlo simulation was carried out to assess uncertainty propagation. The preponderant trace metals in reused rainwater were zinc, iron, aluminium and copper, with average concentrations equal to 4.40x10 -1 mg.L -1 , 5.43x10 -2 mg.L -1 , 5.27x10 -2 mg.L -1 and 2.06x10 -2 mg.L -1 , respectively. When maximum concentration values were used in calculations, hazard quotients did not exceed 6.4x10 -2 , i.e., about 10% of the risk limit. The highest hazard quotients observed for a person during his or her entire lifespan were found for zinc (6.4x10 -2 ) and lead (4.5x10 -2 ). These health risk assessment results showed that no risk of non-carcinogenic effects from trace metals could be expected from the harvest and reuse of rainwater for domestic activities.

INTRODUCTION

A potential lack of fresh water is one of the major issues facing mankind today. This predicament can be attributed to several complex causes, including world population increases, urbanisation, land use transformations, and pollution [START_REF]The United Nations World Water Development. Report 3: Water in a Changing World[END_REF]. Hence, harmful consequences could occur, including both health problems and social conflicts. Among existing solutions, a major interest seems to be given to the use of roof-collected rainwater. Consequently, it would be necessary to measure the amount of available rainwater and its quality. This interest has been shown in numerous recent studies in countries such as Jordan, Canada, Australia, Brazil, and Greece [START_REF] Al-Khashman | Chemical characteristics of rainwater collected at a western site of Jordan[END_REF][START_REF] Despins | Assessment of rainwater quality from rainwater harvesting systems in Ontario, Canada[END_REF][START_REF] Evans | Identifying the major influences on the microbial composition of roof harvested rainwater and the implications for water quality[END_REF][START_REF] Ghisi | Potential for potable water savings by using rainwater: Analysis over 62 cities in southern Brazil[END_REF][START_REF] Melidis | Characterization of rain and roof drainage water quality in Xanthi, Greece[END_REF][START_REF] Sazakli | Rainwater harvesting, quality assessment and utilization in Kefalonia Island, Greece[END_REF]. As in many countries, France must conserve its water resources and thus has taken an interest in harvesting rainwater for domestic activities for many years. However, even though there are investigations about rainwater reuse at a large scale, French law currently forbids the use of this water for drinking and for washing the body or clothes [START_REF]Arrêté du 21 août 2008 relatif à la récupération des eaux de pluie et à leur usage à l'intérieur et à l'extérieur des bâtiments[END_REF]. Indeed, it is essential to be certain that there is no health risk before using water for these activities, especially when the collected rainwater is to be drunk. Now, some data are available on this subject. Although some metals, such as iron (Fe), copper (Cu), manganese (Mn), and zinc (Zn), are essential for living or-ganisms at specific concentrations, toxic effects are observed when these concentrations increase. Ingestion of drinking water containing significant amounts of metals may result in adverse health effects, from a shortness of breath to several types of cancer. Currently, agricultural runoff [START_REF] Ritter | Sources, pathways, and relative risks of contaminants in surface water and groundwater: a perspective prepared for the Walkerton Inquiry[END_REF] and corrosion of household plumbing systems are important sources of trace metals. Our study is designed to meet the specific need to assess the possible human health risk linked to the reuse of roofcollected water. Thus, we present here a complete system of harvesting and reuse of rainwater in a house in southern France, and we assess the health risks incurred by a typical family by examining the trace metals that are measured. An important aspect of this health risk assessment lies in the modelling of water ingestion, whose uncertainty is taken into account with a Monte Carlo simulation.

MATERIAL AND METHODS

Study Area

The pilot house is located in Rabastens in southwestern France. The village is situated in country at an average altitude of 174 m. The climate is oceanic with a warm summer. Every year, approximately 760 mm of rain falls in this region, and the average temperature spread is from 7.9 °C to 18.3 °C. The house under study is occupied by a family consisting of two parents and two children. The family uses tap water from the public network for all of their activities that necessitate water (flushing, watering, and drinking). Wastewater is sent to a septic tank for individual treatment. A commercially available rainwater collection system (Sotralentz Habitat) was used in this study. Rainwater is first collected from the tiled roof (204 m 2 ). This water is then channelled via open zinc gutters and downpipes to a mesh wire filter before entering an underground PEHD storage tank (5 m 3 capacity) through a calm inlet. Any overflow is fed into a nearby canal. The pumping system used a submerged intake with an inlet filter attached to a float, which pumped the water inside the house through a treatment process composed of a 25-µm filter and an active carbon filter. When insufficient water was available in the tank, a probe activates a valve to allow pumping from a backup drinking water tank. The rainwater collected is available for toilet flushing and can supply two WCs and an outside tap. Figure 1 shows the general system scheme.

FIGURE 1 -System of rainwater harvesting

Sampling and analysis

Sampling was carried out from January 2009 to January 2010. Water samples were collected monthly from the outside tap, which results in twelve samples. Samples were taken after water had been running into the waste stream for at least one minute. All samples were placed in 120 mL polyethylene bottles that had been previously washed with 10 % nitric acid and rinsed with de-ionised water. Samples were acidified on site with 1 mL of nitric acid and then transported to the laboratory in a chilled cold-box. Metals under investigation were Al, Cd, Cr, Cu, Fe, Ni, Zn, Pb, and Hg. Elemental analyses were performed by inductively coupled plasma mass spectrometry. The analysis method was based on ISO 17294.

Health risk assessment methodology

Health risk assessment (HRA) is a decision-support tool developed by several international organisations, including the World Health Organization (WHO) and the United Nations Environment Programme. This standard is applied by different national organisations, such as the Environment Protection Agency (EPA) and the Agency for Toxic Substances and Disease Registry (ATSDR) in the United States, the National Institute of Risks and the Industrial Environment in France (INERIS), and the National Institute for Public Health and the Environment in Netherlands (RIVM). HRA results can be used to reduce and prevent risks to human health. Indeed, this methodology enables one to determine the risk incurred by human beings if they are exposed to different toxic agents [START_REF] Ruden | Principles and practices of health risk assessment under current EU regulations[END_REF]. The different types of toxic effects are divided into two categories, carcinogenic and non-carcinogenic. Non-carcinogenic effects occur from a threshold of concentration of an agent, whereas carcinogenic effects manifest themselves with a certain probability as soon as they are in contact [START_REF] Ineris | Evaluation des risques sanitaires dans les études d'impact des ICPE[END_REF]. These effects can appear with oral or dermal exposure or by the inhalation of an agent. Exposure can be acute when it lasts for few hours or few days or chronic if it occurs over several years. Although no international standardisation has yet been established, HRA is mostly carried out in the same way [START_REF]Principles for the assessment of risks to human health from exposure to chemicals[END_REF]. Hence, we follow this method, which is usually realised in four steps: hazard characterisation, choice of toxicological reference values, exposure scenarios determination, and, finally, risk assessment [START_REF] Ruden | Principles and practices of health risk assessment under current EU regulations[END_REF].

Hazard characterisation: The first step of an HRA aims to identify the hazardous agents, taking into account their adverse effects on human health. In this study, the substances subject to the risk assessment are the trace metals that were measured during the monitoring campaign, namely aluminium, cadmium, chromium, copper, iron, lead, mercury, nickel and zinc. Moreover, as low concentrations and exposure times affect the entire lifespan, only effects due to chronic exposure are considered. Furthermore, only oral exposure is taken into account, as dermal exposure is underdeveloped in HRA, and the experimental difficulty does not allow us to quantify the number of aerosols that are inhaled. No scientific study on this matter has yet been realised. For these reasons, the adverse effects taken into account in our considerations come from the oral route for a chronic exposure.

Acceptable Daily Intake selection: For all of the targeted substances, a dose below which no risk will occur is the Acceptable Daily Intake (ADI). It is expressed in milligrams of agent per kilogram of body weight per day. Generally, this reference dose is established by the EPA, RIVM, ATSDR or WHO and based on several scientific studies on animals or on epidemiologic human data. The ADI only concerns non-carcinogenic effects and are derived from the No-Observed-Adverse-Effect Level (NOAEL) or from the Benchmark Dose (BMD). The NOAEL is defined as the highest observed dose of a substance without adverse effect occurrence. As for the BMD, it is the dose that produces the critical effects with an increase above control levels [START_REF]Principles for the assessment of risks to human health from exposure to chemicals[END_REF]. Then, ADI is estimated by applying different uncertainty factors, which accounts for the weakest populations or simply allows extrapolation of results on animals to humans [START_REF]Principles for the assessment of risks to human health from exposure to chemicals[END_REF]. Finally, different ADI can be determined for a substance per type and route of exposure. In accordance to the organisation, the ADI is called a Minimum Reference Dose by the US EPA, Minimal Risk Levels by the US ATSDR and Tolerable Daily Intake by WHO and RIVM. Most ADIs are gathered in the ITER table available on the website of the US National Medicine Library [START_REF]Toxnet: International Toxicity Estimates for Risk[END_REF]. In this study, the lowest values of ADI have been selected in order to maximise risk evaluation. Table 1 gives these ADI values.

Exposure: Exposure scenarios assessment is probably the most important step to assess the overall health risk. Theoretically, it depends on four parameters: route of exposure, activity, type of exposure, and type of population. As decided previously, the route of exposure and type of exposure are respectively limited to ingestion and to chronic exposure. As for activities, six, encompassed by five more general activities, are considered here. Thus, reused rainwater is supposed to be potentially ingested during watering garden, consumption of crude vegetables from garden, floor washing and cross-connection to water supplies. Finally, the type of population is usually divided into three categories by age: infants, children, and adults, being defined by birth to 3 years old, from 4 to 14 years old and from 15 to 79 years, respectively [START_REF] Afssa | [END_REF]. For infants and children, corresponding average weights have been estimated from individual growth curves (resp. 5 kg and 25 kg). According to the French National Institute of Statistics and Economic Studies, adults are supposed to weigh 70 kg [START_REF]L'obésité en France : les écarts entre catégories sociales s'accroissent[END_REF]. Exposure is then quantified through the Average Daily Dose (ADD) given by equation 1 (Table 2) [START_REF] Ineris | Evaluation des risques sanitaires dans les études d'impact des ICPE[END_REF]. It is then convenient to aggregate all the results for one type of population. The ADD ing,p,chronic is given by the equation 2 (Table 2). In order to calculate an average risk for the entire life of a person, it is possible to evaluate an average ADD because exposure is chronic [START_REF] Ineris | Evaluation des risques sanitaires dans les études d'impact des ICPE[END_REF]. This value is directly calculated with the weighted mean shown in equation 3 (Table 2). As exposure parameters are very uncertain because of their dependence on behaviour and statistical hypotheses, we built a model based on average and extreme values of volume ingested and frequency of exposure. Then, a triangular density is used to describe each sensitive parameter in order to apply a Monte Carlo simulation.

Risk assessment: The last step of HRA is the risk calculation with the hazard quotient (HQ). It has been observed that carcinogenic effects have not yet been shown or quantified for the trace metals under investigation, so the health risk is not calculated for this type of effects. Non-carcinogenic health risks for the ingestion of trace metals are given by the equation 4 (Table 2). Similar to ADD, it is possible to calculate the average hazard quotient ( HQ ing,chronic ) for a person during his or her entire life (equation 5 (Table 2)). A hazard quotient equal or above unity (≥ 1) means that population is exposed to a risk, whereas if this quotient is below unity, no risks are likely to occur. Calculation of hazard quotients is attained through use of a Monte Carlo simulation. Despite uncertainty on inputs, this tool permits one to obtain a model that represents a pertinent and realistic system profile. Algorithms generate random values that are then applied to the system. From this methodology, a statistical profile of the system is obtained that gives average (most probable value), minimum, and maximum values. For these calculations, we used the software "Simulación 4.0," de-veloped by José Ricardo Varela (Universidad del CEMA, Argentine)

ADD

Where ADDing,p,a,chronic is the Average Daily Dose for an agent ingested (ing) by the population p, who realises the activity a, during the entire life (chronic), Cing,p,a,chronic is the concentration of the substance in water, Qing,p,a is the quantity of ingested water, Fing,p,a is the daily frequency and Wp is the body weight of the population p. Where ADD ing,chronic is the average ADD for a person during its entire life, ADDing,p,chronic is the ADD for a type of population, Tp,chronic the period of exposure of the population p for a chronic exposure, Tµ,p,chronic, the period on which ADI are calculated (in general, the entire life of a person, i.e. 79 years [START_REF] Afssa | [END_REF].

=

Where HQing,p,chronic is the quotient risk for an agent ingested (ing) by the population p, during the entire life (chronic), ADDing,p,chronic the corresponding average daily dose and ADIing,p,chronic the corresponding acceptable daily intake.

=

Where HQing,p,chronic is the quotient risk for an agent ingested (ing) by the population p, during the entire life (chronic), ADDing,p,chronic the corresponding average daily dose and ADIing,p,chronic the corresponding acceptable daily intake.

RESULTS AND DISCUSSION

Trace metal concentrations

After collecting data from one year of exposure to trace metals, a representative profile of the real concentrations of metals under investigation was obtained. Table 3 shows the minimum, average and maximum measured concentrations and compares them to the normal values seen in French drinking water [START_REF]Arrêté du 11 janvier 2007 relatif aux limites et références de qualité des eaux brutes et des eaux destinées à la consommation humaine[END_REF]. Limits are exceeded for the maximum concentration measure of iron and aluminium. Moreover, the highest concentrations of lead and zinc are only slightly under the limit. These preliminary results have confirmed that we can analyse the risk incurred by people who would be exposed to these concentrations of metals. Mercury minimum, maximum and average con-centrations are the same because as the amount of this metal in the water was under the detection limit, the value chosen was the half of the limit of quantification. With these experimental values, a triangular distribution of concentration is created by the Monte Carlo simulation. 2.83x10 -3 5.50x10 -4 6.97x10 -3 Mercury 10 1.0x10 -6 5.00x10 -5 5.00x10 -5 5.00x10 -5

Exposure modelling

Exposure modelling is based on our own suppositions about the plausible lifestyle of a French family under these conditions. Nevertheless, uncertainties from this hypothesis are compensated by the choice of a realistic and very large range of values.

Garden watering: Infants are not involved in watering the garden, whereas children and adults are supposed to participate in this activity 1 day out of 4 (respectively 1 day of 2) during the 6 month dry period, i.e., 45 (respectively 90) days a year. The uncertainty in these data is represented by a variation of the duration of the activity from 4 months to 8 months.

Next, we defined two ways for rainwater in-gestion during watering, namely usual and accidental in-gestion. One corresponds to ingesting a few drops and the other corresponds to ingesting many drops, equivalent to a sip. In order to estimate the amount of ingested water, it was necessary to calculate the standard volume of a drop. We considered that a drop of water is the same as one of rain, whose diameter is known as 2 millimetres [START_REF] Jacobson | Fundamentals of atmospheric modelling[END_REF]. Considering a spherical form, volume of a drop is approximately 33 mm 3 . We supposed that drops are absorbed during usual ingestion every day of watering, whereas accidental ingestion occurs from one to ten times a year. For a triangular distribution, the number of drops was estimated to spread from 1 to 20 with an average value of 5 for usual ingestion and from 100 to 1000 with an average value of 500 for accidental ingestion.

Crude vegetables consumption: Exposure from the consumption of crude vegetables concerns children and adults only. We assume that 100 g of salad retains 10.8 mL of reused rainwater and other vegetables (broccoli and cabbages) retain approximately 4.7 mL [START_REF] Nrmmc | Natural Resource Management Ministerial Council, Environment Protection and Heritage Council Australian Health Ministers' Conference[END_REF]. According to investigations on French eating behaviour, an adult eats 142 portions of 40 g of salad per year and 48 portions of 250 g of vegetables per year [START_REF] Afssa | [END_REF]. As for children, they ingest 51 portions of 40 g of salad and 31 portions of 250 g of vegetables [START_REF] Afssa | [END_REF]. An uncertainty of 50% was applied.

Floor washing: Accidental ingestion during floor washing is assumed to occur in the case of splashing and only concerns adults. We assumed one cleaning per week with an accident frequency from 0 to 52 times a year, with the average value being 5 times a year. The volume of drops is again taken as 33 mm 3 , and the number of ingested drops is 5, 50, and 100 for the minimum, average and maximum values, respectively. Risks due to detergents mixed with water are not taken into account, even though they are probably the most important consideration in this activity.

Cross-connection to water supply: Cross-connection with the public network can cause the blend of drinking water with rainwater. Few studies have been led, with the exception of Australia, where some hypotheses have been made. Thus, when this phenomenon occurs, it is supposed that 50% of drunken water comes from the network and 50% from reused rainwater. However, only one home in thousand would be hit by this accident [START_REF] Nrmmc | Natural Resource Management Ministerial Council, Environment Protection and Heritage Council Australian Health Ministers' Conference[END_REF]. Given that such a problem can lead to the ingestion of a large amount of rainwater, extreme scenarios have been established: either there is no mix between different waters, or all the water comes from recuperation system.

Table 4 contains the uncertainty parameters used for exposure calculations. Exposure results for all metals appear in Table 5. Ingestion via crude salad 5.0x10 -3 2.5x10 -3 7.5x10 -3 1.3x10 -1 6.5x10 -2 2.0x10 -1

Accidental ingestion from garden watering 1.7x10 -2 3.4x10 -3 3.4x10 -2 5.5x10 -3 1.4x10 -3 1.4x10 -2

Children

Usual ingestion -from garden watering 1.7x10 -4 3.4x10 -5 6.7x10 -4 1.2x10 -1 8.2x10 -2 1.6x10 -1

Accidental network -drinking water 1.0x10 0 0.0x10 0 2.0x10 0 1.0x10 -3 0.0x10 0 1.0x10 0 Ingestion via crude vegetables 1.0x10 -3 5.0x10 -4 1.5x10 -3 1.3x10 -1 6.5x10 -2 2.0x10 -1

Ingestion via crude salad 5.0x10 -3 2.5x10 -3 7.5x10 -3 3.8x10 -1 1.9x10 -1 5.7x10 -1

Accidental ingestion from soil cleaning 1.7x10 -3 1.7x10 -4 3.4x10 -3 1.4x10 -2 0.0x10 0 1.4x10 -1

Accidental ingestion from garden watering 1.7x10 -2 3.4x10 -3 3.4x10 -2 5.5x10 -3 2.7x10 -3 8.2x10 -3

Adults

Usual ingestion -from garden watering 1.7x10 -4 3.4x10 -5 6.7x10 -4 2.5x10 -1 1.6x10 -1 3.3x10 -1 HQ ing,chronic Mercury 2.9x10 -3 5.2x10 -5 1.2x10 -2 1.8x10 -3

Risk characterisation

Table 5 also presents the results of the health risk assessment of reused rainwater for trace metals in the case of chronic ingestion. Figure 2 illustrates these results for a person during his or her entire life. Error bars come from the Monte Carlo simulations. Under the meteorological conditions of the Rabastens site, the maximum risks were found for zinc and lead, 5.0x10 -2 and 4.1x10 -2 , respectively. Furthermore, the risks for iron and zinc, whose maximum concentrations were found to be higher than those seen in normal French drinking water (table 3), are still lower than the risk limit. The average risk for the maximum concentrations of metals does not exceed 1.1 % of the risk threshold. The possibility of cross-contamination between collected rainwater and normal water greatly influences the maximum daily exposure dose because the volume and frequency of exposure are higher than those seen for other activities (Table 4). The extreme scenario, which consists of a complete connection to the potable network, was therefore tested. Such a scenario would consider that people only drink collected rainwater for their entire lifespan. Even with these rough hypotheses, we find that hazard quotients remain under the risk limit, with the highest equal to 5.0x10 -2 for zinc. From these results, inhabitants who reuse rainwater are mainly exposed to zinc, iron, aluminium and copper. High concentrations of these contaminants may be due to the chemical composition of major components of the system. Indeed, gutters are made with zinc, and some pipes are made with copper. Iron may come from terra cotta tile.

  ,a,chronic is the Average Daily Dose for an agent ingested (ing) by the population p during the entire life (chronic)

FIGURE 2 .

 2 FIGURE 2. Hazard quotients for a person for chronic exposure during his or her entire life

TABLE 1 -Acceptable daily intakes selected [13].

 1

		ADI (mg.kg -1 body weight .day -1 )	Origin (year of determination)
	Aluminium	1.0	ATSDR (2008)
	Cadmium	1.0x10 -4	ATSDR (2008)
	Chromium	1.0x10 -3	ATSDR (2008)
	Copper	1.4x10 -1	RIVM (2000)
	Iron	8.0x10 -1	WHO (1996)
	Lead	3.5x10 -3	WHO (1993) -RIVM (1999)
	Mercury (methyl mercury)	1.0x10 -4	RIVM (2000) -US EPA (2001)
	Nickel	8.0x10 -3	ITER (1999)
	Zinc	3.0x10 -1	US EPA -ATSDR (2005)

TABLE 2 -

 2 HRA equations.

	Equation 1 , p ing	,	a	,	chronic	=	C	ing,	p,	a	×	p p, ing, W Q	a	×	ing, F	p,	a

TABLE 3 -Concentrations of trace metals in reused rainwater (mg.L -1 ) Cing,p,a ( mg.L -1 ) Substance Number of samples French norm

 3

	Average	Min	Max

TABLE 4 -Parameters used for exposure calculation: water volume (Qing,p,a ), frequency (Fing,p,a).

 4

	Type of population	Activities		Qing,p,a (in L)			Fing,p,a
			Average	Min	Max	Average	Min	Max
	Infants	Accidental network -drinking water	3.8x10 -1	0.0x10 0	7.5x10 -1	1.0x10 -3	0.0x10 0	1.0x10 0
		Accidental network -drinking water	5.0x10 -1	0.0x10 0	1.0x10 0	1.0x10 -3	0.0x10 0	1.0x10 0
		Ingestion via crude vegeta-bles	1.0x10 -3	5.0x10 -4	1.5x10 -3	8.0x10 -2	4.0x10 -2	1.2x10 -1

TABLE 5 -Exposure (ADD) and health risk (HQ) results with the Monte Carlo simulation applied to our modelling

 5

		Trace metal	Average	Min	Max	Standard devia-
						tion
	ADD ing,chronic (mg.kg -1 .d -1 )	Aluminium Cadmium Chromium	5.5x10 -4 1.5x10 -7 1.1x10 -6	1.0x10 -5 7.6x10 -10 2.0x10 -8	4.4x10 -3 9.5x10 -7 7.7x10 -6	4.6x10 -4 1.1x10 -7 8.6x10 -7
		Copper	1.4x10 -4	1.9x10 -6	9.9x10 -4	1.0x10 -4
		Iron	6.0x10 -4	4.9x10 -6	4.4x10 -3	5.2x10 -4
		Nickel	1.3x10 -5	1.1x10 -7	8.2x10 -5	1.0x10 -5
		Zinc	2.5x10 -3	2.8x10 -5	1.5x10 -2	1.9x10 -3
		Lead	2.0x10 -5	3.2x10 -7	1.4x10 -4	1.5x10 -5
		Mercury	2.9x10 -7	5.2x10 -9	1.2x10 -6	1.8x10 -7
		Aluminium	5.5x10 -4	1.0x10 -5	4.4x10 -3	4.6x10 -4
		Cadmium	1.5x10 -3	7.6x10 -6	9.5x10 -3	1.1x10 -3
		Chromium	1.1x10 -3	2.0x10 -5	7.7x10 -3	8.6x10 -4
		Copper	1.0x10 -3	1.4x10 -5	7.1x10 -3	7.4x10 -4
		Iron	7.5x10 -4	6.1x10 -6	5.5x10 -3	6.4x10 -4
		Nickel	1.6x10 -3	1.4x10 -5	1.0x10 -2	1.3x10 -3
		Zinc	8.5x10 -3	9.2x10-5	5.0x10 -2	6.4x10 -3
		Lead	5.7x10 -3	9.1x10 -5	4.1x10 -2	4.4x10 -3

CONCLUSIONS

Our modelling of exposure to recuperated rainwater combined with a Monte Carlo simulation has shown that there is no health risk from trace metals in these experimental conditions. Whatever the scenario of exposure, the population is not endangered by the ingestion of rainwater during activities that do not include drinking water and in case of crossconnection. The concentration of trace metals highlighted that some elements with the highest concentrations must come from the system and not from rainwater itself. Other metals may be from atmospheric leaching by rainwater. However, only trace metals were taken into account. This modelling for HRA should be applied to other trace pollutants, such as PAHs or pesticides, and to microbiological parameters, as microbiologic risk is one of the most important risks to be considered.

ACKNOWLEDGEMENT

The authors would like to thank Sotralentz Habitat for their provision of the rainwater-harvesting equipment.