Effect of substrate depth and rain-event history on the pollutant abatement of green roofs

Environmental Pollution 183 (2013) 195e203

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Effect of substrate depth and rain-event history on the pollutant abatement of green roofs Martin Seidl a, *, Marie-Christine Gromaire a, Mohamed Saad a, Bernard De Gouvello a, b a

University Paris-Est, LEESU, UMR-MA-102, Ecole des Ponts ParisTech, 6-8 Avenue Blaise Pascal, Cité Descartes, Champs-sur-Marne, 77455 Marne la Vallée cedex 2, France b CSTB, 84 avenue Jean Jaurès, Champs-sur-Marne, 77447 Marne-la-Vallée Cedex 2, France

a r t i c l e i n f o

a b s t r a c t

Article history: Received 20 October 2012 Received in revised form 12 April 2013 Accepted 10 May 2013

This study compares the effectiveness of two different thickness of green roof substrate with respect to nutrient and heavy metal retention and release. To understand and evaluate the long term behaviour of green roofs, substrate columns with the same structure and composition as the green roofs, were exposed in laboratory to artificial rain. The roofs act as a sink for C, N, P, zinc and copper for small rain events if the previous period was principally dry. Otherwise the roofs may behave as a source of pollutants, principally for carbon and phosphorus. Both field and column studies showed an important retention for Zn and Cu. The column showed, however, lower SS, DOC and metal concentrations in the percolate than could be observed in the field even if corrected for run-off. This is most probably due to the difference in exposition history and weathering processes. Ó 2013 Elsevier Ltd. All rights reserved.

Keywords: Vegetated roofs Nutrients Heavy metals Emission Retention Columns experiments

1. Introduction Vegetated roofs offer multiple environmental benefits, both at building scale e thermal insulation, roofing membrane protection (Wong et al., 2003; Teemusk and Mander, 2006), and at urban scale e improvement of urban climate, positive effect on air pollution and carbon sequestration (Getter et al., 2009; Susca et al., 2011). Green roofs are also more and more perceived as a viable approach to improve urban storm-water management (Mentens et al., 2006; Teemusk and Mander, 2006; Rowe, 2010). Numerous studies have highlighted the important modification of the hydrological behaviour of green roofs compared to traditional flat roofs, with increased water retention capacity, delayed runoff and reduction of peak flows. (Czemiel Berndtsson, 2010) showed in her literature review that the effectiveness of extensive green roofs to reduce the storm water volumes may range from 34% to 69% of annual precipitation depending on the green roof characteristics. However, the amount of precipitation retained by a green roof during a rain event varies in a wide range from one event to another as a function of the initial wetness of the substrate and the rain event characteristics. Lower rainfall amount, higher evapo-transpiration and higher retention capacity of growing media increase the number of

* Corresponding author. E-mail address: [email protected] (M. Seidl). 0269-7491/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.envpol.2013.05.026

events retained (Teemusk and Mander, 2007; Berghage et al., 2009; Czemiel Berndtsson, 2010). Less attention has been given up to now to the incidence of roof greening on storm water contamination. Water quality studies performed on runoff from conventional roofs reveal the presence of numerous pollutants, either washed out from the atmosphere (Van Metre and Mahler, 2003; Seidl et al., 2011) or leached from the roofing materials (Gromaire et al., 2011). On one hand green roofs might act as a filter and retain a part of the atmospheric fall out. On the other hand nutrients present in the substrate to sustain the vegetation growth, as well as micropollutants contained in the construction materials of the different green roof layers might be washed out (Hunt et al., 2006; Emilsson et al., 2007; Teemusk and Mander, 2007; Beck et al., 2011). Studies of nutrient release from green roofs give mixed findings. A majority of authors conclude that green roofs act as a source of phosphorus (Berndtsson et al., 2006; Hathaway et al., 2008; Czemiel Berndtsson, 2010). (Van Seters et al., 2009) observed however a significant decrease of phosphorous levels after one year of exposition, suggesting a fast initial release. Studies on heavy metals (Steusloff, 1998; Berndtsson et al., 2006; Berghage et al., 2009; Berndtsson et al., 2009; Van Seters et al., 2009; Czemiel Berndtsson, 2010) show on the contrary a possible retention. Resumed, the quality of green roof runoff is dependent on numerous factors such as substrate composition, substrate depth, plant selection, age of the roof, fertilization and maintenance practices, volume of rainfall, local

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pollution sources, and physical and chemical properties of the considered pollutants. This study is a part of the French research project for green roofs and rain water management, TVGEP, which aims an objective evaluation of the benefits of extensive roof greening for the management of urban storm waters. The main objective of this paper is to evaluate the release/retention e behaviour of actually constructed green roofs, towards common pollutants and metals in comparison with standard roofs and other urban surfaces. The specific objectives were to see how the substrate thickness impacts the concentration and the fluxes and whether accelerated laboratory column experiment can predict the field behaviour. 2. Materials and methods 2.1. In situ test bench Two different types of green roof surfaces were evaluated in the spring and in the summer of 2011 in the east suburb of Paris, and compared to a conventional flat roof. The tested roofs were 2 m by 2 m pilots build by the French national centre for building research and certification (CSTB) in 2009 for heat transfer testing. The reference roof consists of a concrete desk, situated 1 m above the ground, covered with an SBS (styrene-butadien-styrene) modified bitumen roofing membrane, autoprotected with mineral particles. The green roof pilots were built according to the technical prescription of CSTB 5/03-1733 for the roof garden system GRAVIÔ. They consist of 4 layers, with the following characteristics from bottom to top: - SBS roofing membrane. - Drainage layer made of five centimetre thick expanded polystyrene; - Geo-textile, made of 2.4 mm thick non woven polyester (200 g/m2) to prevent the loss of soil particles. - Growth substrate, 6 cm respectively 16 cm of a commercial substrate, complying with the French professional rules for extensive vegetated roofs (Adivet et al., 2007). This substrate consists for 70% of its volume from volcanic rock (pouzzolane) and for 30% of bark and peat. Its organic matter content is of 6.84% of the total dry weight, and of 19.5% for the size fraction <250 mm (Table 1). The maximum water retention capacity is of 48% in volume, equivalent to 29 mm rain for the 6-cm roof. - Vegetation layer, implemented under the form of commercially pre-grown sedum carpets. The pre-cultivated carpets comprise a biodegradable mat of natural fibres lined with a polypropylene mesh, holding 1e2 cm of substrate and covered for more than 80% of the surface with a sedum mixture. The sedum population in the pre-cultivated carpet consists of a mixture of Sexangulare, Floriferum, Reflexum, Lydium and Album coral carpet, with the later as the principal component. In the case of the 16 cm thick green roof common perennial grasses were added on 10% of the sedum carpet surface. A unique dose of manure granulates was added during the implementation of the vegetated roofs in June 2009 according to the prescriptions of the manufacturer. In the picture (1) one can see from the front to behind the three roofs used: 16-cm vegetated roof with sedum and grasses, 6-cm vegetated roof with sedum and the reference roof without vegetation. At the beginning of the measurements the roofs were 20 month old and had already received about 1000 mm of rain. Roof runoff was collected at event scale, defined as a laps of time between the first run-off from the reference roof and end of the run-off from the green roof for the same rain event. For each event studied with the entire runoff was collected in a plastic container, which were weighted in order to evaluate runoff volume. A total atmospheric fallout collector consisting of a 1 m by 1 m polyethylene sheet, placed at 1 m above the ground and perforated in the centre to collect the runoff in a plastic container, was positioned a few metres of the rain gauge (RG, photo 1A). The sampling period covered both the studied rainfall event and preceding dry weather period. The rainfall was measured on site. In the case of data gaps on site, a mean from two other stations situated at 3 km east and west of the experimental site were used. The mean of the distant stations was in good agreement with the local one. (Fig. 1)

Table 1 Size distribution and organic matter content of the substrate used. Particle diameter

d > 2.5 mm

0.25 < d < 2.5 mm

d < 0.25 mm

Total solids Volatile solids

80.4% 1.3%

13.5% 34.4%

5.9% 19.5%

2.2. Sampled rain events Over the period MarcheJuly 2011, 10 rain events were collected and analysed. The complete set of water quality analyses could be performed only for precipitations generating at least 500 mL of runoff on the 6-cm green roof. The first event was sampled on 18 March 2011 after a period of 20 days without rainfall. The spring 2011 was exceptionally dry in France, and hotter than usual, whereas June and July 2011 were relatively wet with important storm events. 70% of the total of 188 mm of precipitation of the evaluation period, were sampled. Table 2 shows that the events occurring in the spring (events A to G) are small events with high water retention in the roofs and therefore with run-off coefficients of only few percents. After an extremely long dry period in April and May, frequent heavy rain events were observed in June and July leading to substrate saturation (event H and I, Table 2). In consequence these events were hardly retained, giving run-off coefficients around 60% and representing the majority of percolate volume collected. To better understand the evolution of substrate conditions over the whole study period the moisture content of the substrate was roughly estimated using daily precipitation (Ht) and potential evapo-transpiration (ET0). The roof water content (wt) was estimated as wt ¼ wt-1 þ (Ht  ETt), with a maximum water content for the 6 cm roof of 29 mm (measured field capacity) and a minimum value set to 20% of the field capacity. The real evapo-transpiration (ETt), was than estimated according to the relation ETt ¼ a * ET0 t given by (Allen et al., 1998). As crop coefficient for sedum was used the value a ¼ 0.35, given in the literature (Lazzarin et al., 2005; Berghage et al., 2009; Sherrard and Jacobs, 2012). The water content simulation starts on 10/01/2011, after a heavy rain period, with w0 ¼ 29 mm. The values are only a rough estimate as the real plant evapotranspiration depends also on the water content in the substrate and will be closer to zero in periods of extreme drought. (Fig. 2) The evolution of the soil moisture shows that rainfalls leading to runoff on the green roofs are situated in periods when the substrate is close to saturation. The rain event “D” at the end of May was an isolated event and the outflow was most probably due to preferential paths as a consequence of substrate shrinking at the end of the extremely dry period. 2.3. Column experiments In order to better understand the retention/release behaviour of the substrate, non-vegetated substrate columns (d ¼ 30 cm and A ¼ 700 cm2) of the same structure, composition and thickness as the experimental roofs (substrate laid on geotextile and drainage layer), were exposed to an artificial rain. This approach was already applied with success by authors like Buccola and Spolek (2011) and Alsup et al. (2011). The columns were disposed on a platform side by side and received synthetic rain water from a rain simulator (Sprai SAS France). The rain source was placed at 1 m above the columns, with a rainfall intensity of 8 mm/h, during 12 h a day and for a period of 4 weeks. A full description of the methodology is given by Van de Voorde (2012). The total rain depth of 2000 mm applied, corresponds roughly to 3 years rainfall in the region of Paris. Taking into account the difference of runoff coefficient between these very accelerated rainfall simulations (w100%) and the annual runoff coefficient under natural conditions (w50%), the simulation covers more than 5 years of runoff The total daily volume of percolate was collected from each column to perform chemical analysis. An empty column was used as a reference. The artificial rain water had similar ionic composition to the total atmospheric deposit collected in the field (Table 3). It was constituted from demineralised water issued from reverse osmosis, and re-mineralised 1:20 with commercially available mineral water Volvic (Volvic, 2013). To study possible heavy metal retention the solution was spiked with zinc sulphate (300 ppb) and copper sulphate (30 ppb). 2.4. Sample analysis Field samples were collected within 24 h after the end of each rain event and transported to the nearby university laboratory, where the samples were separated and preserved for each specific parameter as indicated by APHA recommendations (2005). Samples were analysed for: conductivity, turbidity, suspended solids (Whatmann GF/F), dissolved and total carbon (C-analyzer, Analytical), total nitrogen (N-analyzer, Analytical), anions and cations (Ion Chromatography, Metrohm) and total metals (Digestion Digiprep HNO3/H2O2/HCl eanalysis Varian ICP-AES). For carbon and nutrients all laboratory vessels were soaked over night in 2% TFD4 detergent (Franklab SA, France) solution and rinsed abundantly with tap and distilled water and air dried. For metal analysis, disposable tubes (Digiprep SA, France) including PTF filters were used. The GF/F filters and vessels used for carbon analysis were heat cleaned at 500  C for 2 h. Any vessel used for the metal analysis were soaked over night in Extran detergent (Merck) followed by 24 h in 3% HNO3 solution and rinsed with tap, distilled and ultra pure water (12 MU). All analysis were done following the US (APHA, 2005) and French (AFNOR, 2002) analytical recommendations. For the metal analysis certified reference material were used for result verification. In the paper “Ref” will be used as the abbreviation for the run-off of the reference roof, “6-cm” and “16-cm” will stand for the percolates of the green roofs with

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Fig. 1. View of the experimental roofs in June 2009 after the construction (left) and in March 2011 at the beginning of the test (right) at Champs-sur-Marne, 20 km east of the centre of Paris. PhotoÓ CSTB (left) and authors (right).

specific substrate thickness. “Atmo” will represent the total atmospheric fall out. In total 9 events were sampled, though only 4 gave percolate in the “16-cm”.

3. Results 3.1. Pollutant concentrations in atmospheric fallout, reference roof and green roof run-off Fig. 3 compares the distributions of event mean concentrations over the 10 sampled rain events, for the total atmospheric fallout, the reference roof runoff and the two green roofs (6-cm and 16cm). A high dispersion of event mean concentrations (EMC) can be observed for all parameters, reflecting the naturally high variability of rain events and the complexity of processes involved. Runoff quality from the reference roof and from the 6-cm green roof was compared with a non parametric statistical test on paired observations (Wilcoxon, significance level p ¼ 0.05). For solids and heavy metals, no statistically significant difference was observed between the two types of roof runoff. For nutrients and carbon however, green roof concentrations were statistically superior to reference roof concentrations. The small number of runoff samples (n ¼ 4) for the 16 cm roof does not allow any statistical treatment. Yet, for the last 3 rainfall events, characterized by high runoff rates, the 16 cm roof systematically showed higher nutrient and organic carbon concentrations than the 6 cm roof and lower SS, whereas no trend was noticed for metals. The concentrations of phosphate, carbon (Fig. 3) and nitrogen (Fig. 4) increased in the order: atmospheric deposition < reference roof <6-cm roof <16-cm roof). The fall out contains only traces of

air pollution, whereby the 6- and 16-cm roof carry impact of the substrate layer. These trends as well as similar pollutants levels were also observed for phosphate and carbon by other authors (Hathaway et al., 2008; Berghage et al., 2009; Berndtsson et al., 2009). However for nitrogen and zinc the literature gives contradictory results: some like (Moran and Hunt, 2005) find higher concentration in effluents than in atmospheric deposit, others like (Berndtsson et al., 2009) find lower concentrations. In reality it’s not easy to compare the results because of the difference in age, type, fertilizer load and hydrological antecedents of the different green roofs studied. If the concentration of all components measured are compared through the Pearson matrix test of correlation to rain variables like depth, duration and number of preceding days without rain, significant correlation (correlation coefficient of de Pearson, r  0.7) is only obtained between the number of days without rain preceding the event and conductivity (r ¼ 0.7), NH4þ (r ¼ 0.8) Ca2þ (r ¼ 0.8) and total copper concentration (r ¼ 0.9). Zinc is only correlated to particulate organic carbon, whereas copper is correlated to dissolved organic matter (r ¼ 0.78), NH4þ (r ¼ 0.98) and conductivity. (r ¼ 0.88). A difference in the speciation of nitrogen can be noticed between the different roof surfaces in Fig. 4. Atmospheric fall out contains mainly inorganic nitrogen (nitrate and ammonium) whereby the organic forms prevail in the green roof percolates. The nitrogen speciation ratio NO3: NH4: Norg expressed as percentage of total nitrogen equals to 43:22:35 for the reference and to, 10:5:85 for the 6-cm roof respectively to 28:5:67 for the 16-cm roof. The organic nitrogen is most probably produced by the sedum layer as

Table 2 Main characteristics of the rain events collected. The percolate volumes were converted to “mm” using the roof surface of 4 m2. Event n Begin of the event

A B C D E F G H I Sum

Event Total event S(H  0.35 ETP) Number of days Return period Percolate high Runoff Percolate high Runoff duration precipitation over 14 days without precipitation of the event collected 6-cm coefficient collected 16-cm coefficient (min) (mm) preceding the preceding the event (total depth) roof (mm) of the 6-cm roof (mm) of the 16-cm event (mm) roof roof

18/3/11 17 h 310 26/3/11 17 h 275 3/4/11 6 h 85 19/5/11 17 h 1440 4/6/11 20 h 1080 12/7/11 0 h 591 16/7/11 18 h 540 19/7/11 5 h 1320 20/7/11 15 h 660

5.9 7.1 4.1 2.8 31.2 12.4 24.8 39.1 4.4 131.8

8 3 10 21 23 18 13 13 49

20 8 7 46 15 21 3 1 0.1

2 Month 2 Month Week Week Year 2 Month Year 2 Year Week

0.14 0.08 0.10 0.03 0.68 0.35 1.53 15.8 2.25 20.9

2.4% 1.2% 2.5% 1.1% 2.2% 2.8% 6.1% 40% 51% 15.9%

0 0.01 0.04 0 1.53 0 1.40 16.00 2.50 21.5

0% 0.2% 0.9% 0% 4.9% 0% 5.6% 41% 57% 16.3%

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M. Seidl et al. / Environmental Pollution 183 (2013) 195e203

50

120% B

C

D

E

F GHI

Rain high (mm)

100% 80% 60%

25

40% 20% 0 16-Mar-11 31-Mar-11 15-Apr-11 30-Apr-11 15-May-11 30-May-11 14-Jun-11 29-Jun-11

Estimated roof water content

A

0% 14-Jul-11

Fig. 2. Hydrology of the sampling period. The bars indicate all rain events during the sampling period. The red ones indicate rains sampled and analysed, the orange one rains sampled but without sufficient volume for chemical analysis. The blue line gives an estimate in %, for the 6-cm roof water content using citied equations. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

the substrate is nitrogen poor and as the fertilizer was added only during the roof construction, two years before. The results of (Berndtsson et al., 2009) for roofs in Sweden and Japan, showing the same shift from inorganic to organic nitrogen forms seem to confirm this hypothesis. The excess of nitrate in the green roof percolate, compared to reference roof, is probably due to aerobic condition stimulating biodegradation of organic matter and nitrification, as well as to plant preference for ammonium (Thornton and Robinson, 2005). 3.2. Pollutant loads To see if the green roofs act as a sink or as a source of contaminants, pollutants loads have to be considered and not only concentrations. The pollutant loads used for this purpose are calculated as a product of event mean concentration and the volume of percolate, and are thus strongly dependent on the hydrological behaviour of the roof. Fig. 5 presents for each rain event, the ratio “R” between the pollutant mass issued from the 6-cm roof and the mass collected from the reference roof. A ratio under 1 means retention and a ratio above 1 means increased release compared to classical flat roof. Release was observed for events occurring during rainy periods and having run-off coefficients over 40% (events H and I, visualized in Fig. 5 by blue rectangles). Rain event “I” totalizing only 4 mm of rain, but occurring after two weeks with 66 mm of precipitation, is such example. On the contrary retention was observed for events occurring during dry periods. Event “E” totalizing 31 mm but falling after two weeks with only 9 mm of precipitations gave no release. The two last events, occurring while substrate was already soaked with precipitation, produced high loads of organic nitrogen and nitrate, as well as phosphorus and organic carbon. The retention is net for heavy metals (R<<1), but for carbon and phosphorus the retention in dry periods is compensated by release in rainy period (Rw1). More observations are needed to confirm this tendency and calculate long term mass balances The terms

retention and release indicate an overall effect and within this study it was not possible to distinguish between the allochthonous forms coming from atmosphere and autochthonous forms being produced within the system. Fig. 6 shows in analogy to Fig. 5, for each event sampled, the ratio of mass emitted by the 6-cm roof and the 16-cm one. A ratio of one, means that the emissions are the same. A ratio of less than one, means that there is some level of proportionality between the layer thickness and the flux emitted. For example a ratio of 6/16 or 0.375 means a strict proportionality to the substrate depth i.e. the load per centimetre of substrate is the same for both roofs (blue line in the Fig. 6). N, P and C release appears dependant of the substrate thickness. For metals however, the impact of thickness is less pronounced. If the ratio is more than one, the flux of the thinner layer is more important than that of the thicker one. This is surprisingly the case of suspended solids. The higher retention might be explained by the difference in the soil structure: the 16-cm roof has beside sedum also grasses with longer roots, and the thinner layer is more exposed to preferential channels due to heavy drying. The behaviour of lead might be explained in similar way as lead is known to be strongly associated to particles (Gromaire-Mertz et al., 1999). More data would be needed and especially for particulate matter to determine where the particles come from. 3.3. Substrate behaviour The retention capacity of green roofs substrate was studied under laboratory conditions on columns constructed in the same way as the roof structures in the field. Fig. 7 gives a typical evolution of the common quality parameters like suspended solids (a) and dissolved organic carbon (b). The decay of global quality parameters can be fitted with an exponential function using a constant end value. The bend point and the end point are values characteristic for each parameter and give specific information about the leaching process. The end value is achieved for all parameters between 500 and 1000 mm applied. The concentration of 6 and 16-cm is strongly

Table 3 Average composition of artificial rain and components used for its preparation. (*)(mg/l) (**)Volvic (2013). n.a.: not available. (mg/l), (*)(mg/l)

HCO 3

Ca2þ

Mg2þ

NHþ 4

Naþ

Kþ

Cl

SO2 4

NO 3

HPO2 4

Zn(t*)

Cu(t*)

Osmosed water VolvicÔ(**) Artificial rain Fall out EMC

0 71 3.38 n.a.

0.00053 11.5 0.55 1.38

0.000059 8 0.38 0.04

0 n.a. 0.00 0.87

0.00074 11.6 0.55 0.19

0.00012 6.2 0.30 0.14

0.429 13.5 1.05 0.81

0.199 8.1 1.06 1.06

0.304 6.3 0.59 2.16

0 n.a. <0.05 0.11

0.30 n.a. 301 35.0

0.03 n.a. 28.0 8.29

M. Seidl et al. / Environmental Pollution 183 (2013) 195e203

200

300 269

200 142

S.S. (mg/l)

Conductivity (µS/cm)

400

199

100

100 23

0

24

46

9

0

16

5

150

15

9

8.51

6

5.46

DOC (mg-C/l)

PO4 (mg/l)

12 103

100

52

50

3 0.15

0

14

0.59

0

100

5

300 maximum 75% median 25% minimum

Zn total (µg/l)

Cu total (µg/l)

250

50 29.8 12.5

10.4

9.0

200 150 100 50 30

29

31

0

0 atmo.

ref

6-cm

16-cm

atmo.

ref

6-cm

18

16-cm

Fig. 3. Distributions of runoff concentration as a function of the roof cover type. The median is marked with a red dot. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

significant difference could be observed between the two different substrate thicknesses. The metals show an important and constant retention till the end of the test. Though the applied concentration was 4 times (copper) to 10 times (zinc) higher than the measured wet-dry deposit, the saturation of the retention capacity of the substrate used, was not achieved. About 86% of incoming copper and 99% of added zinc were retained during the test period.

6 NO3 NH4

4

Norg

2

16-cm

6-cm

ref.

0 atmo

concentration (mg-N/l)

correlated but in the example given (Fig. 7) are significantly different (Wilcoxon, p ¼ 0.05) only for the organic carbon. The heavy metals, being of particular concern in this paper, do not fit the exponential decay (Fig. 7c and d). No clear decline pattern could be observed during the first 500 mm applied and no

12 25 39 4.4 . 12 25 39 4.4 . 12 25 39 4.4 . 25 39 4.4 Fig. 4. Composition of dissolved nitrogen for the last events sampled in July (F, G, H and I Table 2). The numbers below give the total depth of precipitations in (mm).

4. Discussion Table 4 compares three green roofs from tempered climate zone: north of France (this study), North-East of United States and Canada, regions with comparable seasonal variations and similar human development index, but different precipitation and temperature patterns. The annual precipitation of Paris is half of that of Storrs and 25% lower than that of Toronto. Concentrations in reference roofs runoff reflect both the differences in atmospheric fallout between the three sites, probably linked with the degree of urbanisation and the differences in roof construction and drainage materials. The much higher copper concentrations and lower zinc concentrations of the reference roof in Toronto might be linked to the use of copper elements in the roof structure.

200

M. Seidl et al. / Environmental Pollution 183 (2013) 195e203

100.00

6-cm / ref.

10.00 1.00 0.10

0.92

1.33

1.01

0.36

0.16

0.10 0.04

0.04

0.03

0.04 0.01 0.00 VOL

S.S.

DOC

PO4

Pb

N_tot

Zn

Fe

Cu

Ni

Fig. 5. Emission of nutrients and heavy metals of the 6-cm roof compared to the reference roof for each event. Heavy metals are total contents. Blue points represent rain events with run-off coefficient above 40% and red ones, mean values based on total mass emitted during the period. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

The 3 green roofs show similar trends for metal retention. Reduction of zinc loads in the green roof, compared to the reference roof, varies from 98% in France to 70% in Toronto. The good performance of the green roof in Paris drops however to 73% if calculated only for events with runoff coefficients comparable to that of the two other cities. Copper behaviour is less uniform, showing good retention in Paris (86%) and Toronto (87%) but no retention in Storrs, were Cu emission by the fertilizer has been suspected (Gregoire and Clausen, 2011). The effect of runoff coefficient for Paris is even more important in the case of copper, decreasing the retention efficiency to 29% for rainy periods (blue squares in Fig. 5 Cu). This underlines the importance that should be given to hydrological regime in the abatement calculation. The better retention of zinc compared to copper is particular, because copper is generally better fixed by organic matter. The differences may not only be due to substrate composition, age and fertilization rate, but also to the underlying structure (tightness elements, gutters,.), releasing heavy metals. The global runoff coefficient in Paris for the sampled rain events was 16%, which is rather inferior to the annual runoff coefficients, measured for similar roofs in the region (20%e40%, (Gromaire et al., 2013)). So if annual loads were calculated they might be underestimated. The last two rain events with the highest run-off coefficients (>40%) give the major contribution to the total flux and are therefore preponderant for the calculation of the total flux. For carbon, these two events contribute for 92% to the total flux of the 6-cm roof, while it’s only 4% for the reference roof.

To see if green roofs can make a significant contribution to urban storm-water contamination, the measured green roof runoff concentrations and loads per mm of rainfall were compared with literature data for other types of urban surfaces. Contaminant loads per mm of rainfall for conventional roofs and street runoff were evaluated as F (mg/m2/mm) ¼ C (mg/l)* Cr, with "C" the concentration value found in the literature and "Cr" and average runoff coefficient taken as Cr ¼ 0.9 for conventional roofs and Cr ¼ 0.8 for streets. It can be noticed that the solid emission of the green roofs is up to ten times lower than that of all other surfaces so that green roofs act in fact as a filter towards particulate matter from fall out. This might be particularly interesting in urban areas with high densities of black carbon. The roofs retain also heavy metals and may reduce their flux towards the ecosystem. However, it has to be noted that atmospheric fallout makes only a minor contribution to the metal contamination of storm waters, the main sources being the corrosion of metal surfaces as well as traffic. On the other hand as green roofs are living systems, their DOC emissions are higher than that of other urban surfaces. This may have an effect on the BOD5 flux if the carbon emitted is easily biodegradable. Though the phosphate flux generated by green roof run-off remains low compared to agriculture and waste water treatment (Crouzet et al., 1999), it should be observed carefully by the designers and managers in order to limit possible eutrophication of receiving water bodies, especially if the green roof runoff is collected in small closed water bodies like urban ponds.

6-cm / 16-cm

10.0

1.54 1.0

1.32

0.88 0.49

0.56

0.85

0.76

0.57

0.79 0.49

0.1 VOL

S.S.

DOC

PO4

N_tot

Pb

Zn

Fe

Cu

Ni

Fig. 6. Emission of common pollutants and heavy metals of the 6-cm roof compared to the 16-cm roof for the 4 events sampled simultaneously in both roofs. Blue points represent rain events with run-off coefficient above 40% and red ones mean values based on total mass emitted during the period. Blue line indicate 6/16 ratio or proportionality. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

M. Seidl et al. / Environmental Pollution 183 (2013) 195e203

100

10.0

1.0

10

(a)

0.1 100

1000

(c)

10

(b)

1

Zn_tot (µg/l)

Cu_tot (µg/l)

C16 C6

DOC (mg/l)

Suspended solids (mg/l)

100.0

201

(d)

C16 C6 0

100

10

1 0

500

1000

1500

0

2000

500

High applied (mm)

1000

1500

2000

High applied (mm)

Fig. 7. Concentration versus hydraulic load plots. (a) Suspended solids and (b) dissolved organic carbon with symbols for measured data and solid lines for exponential curve fitting. (c) Total copper and (d) total zinc, with measured data and continue grey line for artificial rain.

Table 5 aims at comparing field results with laboratory results obtained for the column study under artificial rainfall. The concentrations given for columns are mean values for the period between 500 and 2000 mm, not including the fast initial decay. For suspended solids and dissolved organic carbon they are roughly the same as the simulated end point (Fig. 7). For the roofs, the average concentrations were calculated as the quotient of the total mass divided by the total volume. So in both approaches the concentration corresponds to an average proportional to the hydraulic load. The green roofs tested, had received about 1000 mm at the beginning of the test and 1130 mm at the end. This should in theory correspond to the “bent point” estimated by non linear regression in Fig. 7a,b. In consequence the end point concentrations should represent the concentration observed in the field.

Table 5 shows that though metal retention has been observed in both cases, there are some important differences between field and laboratory results. The runoff concentrations from the field green roofs are globally 5 times higher than those from the columns. In the field the concentrations during dry periods tend to be higher than during rainy periods, with exception of dissolved carbon and nitrogen which behave the other way round, but even during wet periods the mean event concentrations remained higher than the column run-off. Two explications are possible. The columns used fresh material whereas the roofs posses a weathered one. The exposition of the substrate during one and half year to dryinge wetting cycles and oxidation - reduction changes of the substrate’s organic matter, could degrade the organic matter making it leach particles and organic carbon. Another explanation might be the

Table 4 Comparison of pollutants concentrations and fluxes of different urban surfaces. This studya

Similar studiesb Storrs, USA

Runoff coefficient Conc. mg/l, (*)mg/l

Load per mm rain mg/m2/mm, (**)mg/m2/mm

DOC S.S. NO3 PO4 Copper(*) Zinc(*) DOC S.S. NO3 PO4 Copper(**) Zinc(**)

Ref

6-cm

16-cm

9 51 1.9 0.6 17 71 8 45 1.7 0.5 15 63

0.16 50 12 1.1 3.8 11 17 8 2 0.2 0.6 1.8 2.7

0.16 93 6 5 6.0 10 17 16 1 0.9 1.0 1.6 2.8

Ref

Other types of urban surfaces Toronto

10 cm

Ref

14 cm

0.58

0.98

0.38

3.1 0.48 e 64

1.64 0.06 6 11

5.8 1.8 0.03 108 9.9

<2.5 0.7 0.72 45 6.9

3.3 0.44 2.6 56.3

1.1 0.05 2.6 11.3

6 1.8 0.1 103 10

1 0.2 0.6 14 3

Conventional roofc

Streetd

0.9 4e14 3e64 0.2e3.4 0.09e0.3 4e166 10e3700 4e13 3e58 0.2e3.1 0.04e0.27 3.6e149 9e3330

0.8 7e21 60e355 2.5e5 1.5 47e143 129e1956 6e17 48e208 2e4 38e114 103e1565

Concentration in mg/l and where noted with (*) in mg/l, copper and zinc are always in “mg” and other parameters in “mg”. a Mean concentrations and mass per m2 and per mm of rainfall, over the sum of the 10 sampled rain events. b Storrs, USA (Gregoire and Clausen, 2011): 280 m2 new extensive green roof, 19 rain events sampled over a 5 month period corresponding to 481 mm (annual 1312 mm). Toronto, Canada (Van Seters et al., 2009): 241 m2 extensive green roof, 1 year old, 21 rain events sampled over a 13 month period corresponding to 1078 mm (annual 834 mm). Geometric mean concentrations and total mass per m2 and per mm of rainfall over the study periods. c Range of site mean concentrations for conventional roofs (tiles, slat, shingle, metal), excluding copper roofs for Cu and zinc roofs for Zn (Xanthopoulos and Hahn, 1992; Quek and Forster, 1993; Boller, 1997; Förster, 1998; Gromaire-Mertz et al., 1999; Chang et al., 2004; Scholz, 2004; Gnecco et al., 2005; Göbel et al., 2007; Huang et al., 2007; Rosillon et al., 2007; Bressy, 2010; Tsakovski et al., 2010; Vialle et al., 2012). d Range of site mean concentrations for streets (Danneker and Stechmann, 1990; Boller, 1997; Gromaire-Mertz et al., 1999; Gnecco et al., 2005; Göbel et al., 2007; Bressy, 2010; Helmreich et al., 2010).

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Table 5 Concentrations and abatements for roofs and column experiments. The error corresponds to standard deviation. The efficiency is calculated as the difference between the emission of green- and reference roof related to the reference. Positive sign means release, negative sign means retention. As the artificial rain is solid- and carbon- free only metal efficiencies are given. S.S (mg/l)

Roof Efficiency Column Efficiency

Total copper (mg/l)

DOC (mg/l)

Totals zinc (mg/l)

C6

C16

C6

C16

Fall out

C6

C16

Fall out

C6

C16

12.5 96% 2.16 e

7.86 98% 2.05 e

49.9 8% 3.50 e

98.8 þ88% 5.65 e

8.29  0.92

10.9  1.88 90% 2.94  0.83 88%

13.5  4.17 87% 3.97  1.36 84%

35.0  4.24

16.9  3.09 95% 3.26  0.84 99%

21.6  6.23 96% 4.28  2.26 99%

25.4  0.63 e

intensity of leaching. The columns have received 2000 mm with a runoff coefficient of almost 100%. In the practice the green roofs show a average run off coefficient about 50% (Table 3), so 2000 mm would correspond to 4000 mm applied or more than 6 years. The exposition of one and a half year would therefore correspond rather to “500 mm” than to the end of the curve. The S.S. and DOC would be around 10 ppm. This explanation holds for solids but not for carbon, which is probably liberated due to weathering processes and biological action of sedum (Speak et al., 2012). For both type of test we observe a high retention of metals with no significant difference (Student, p ¼ 0.05) between the copper and zinc nor between the two thickness. As for carbon the weathering of substrate might contribute to substrate metal release in the field situation. The metal incoming is than different from the one out coming. The difference of Zn/Fe ratio is pointing in this direction. It’s in average 1.1 for the fall out, 0.26 for the 6-cm roof and 0.16 for the 16-cm roof. The ratios for the columns are even lower, ranging from 0.05 to 0.09. For copper these differences are less pronounced: 0.18 for the fall-out and 6-cm, 0.09 for the 16-cm roof and 0.05 for the columns. The hypothesis of different metal mobility between fall-out and substrate would need more research. 5. Conclusion and perspectives The runoff from two vegetated pilot roofs with different substrate thickness (6 cm and 16 cm) was studied over a half year period and compared to a reference flat roof. The vegetated roofs produced generally higher phosphate, carbon and organic nitrogen concentrations but lower metal concentrations than the reference roof. These effects are more pronounced for the roof with the thicker substrate layer. The observed nutrient and organic matter concentration levels remain however in the same range as the event average concentration for wet-weather run-off in an urbanised watershed established by National Runoff Program of EPA for more than 2000 events (Field and Sullivan, 2003). If we consider the fluxes, green roofs studied are sinks for C, N, P principally if the previous period was dry. In other cases the roofs might act as a temporally source of C and P. For all species of heavy metals studied, the roofs act as a sink. Metals like copper are better retained, others like nickel are less. There was no statistical difference between the layers of 6 and 16 cm respectively for metal retention. Column tests were performed to evaluate the long eterm metal retention capacity for green roof substrates. Both field and column study showed important retention for Cu and Zn. This retention capacity is stable over time. However column studies led to lower SS, DOC and metal concentrations than observed in the field, probably due to the difference in hydrologic regime and the role of the vegetation layer. If we compare the pollutant fluxes measured to literature data for urban surfaces and especially if we take in to account the small proportion of urban area which could be equipped with green roofs, the roofs could play only a minor role in the mitigation of

303  5.56

runoff pollution in urban areas. Their benefits for urban climate and well being might be more important. The main difficulty in the evaluation of green roofs is the variability of meteorological events, and lack of sufficient sampling volume at the outflow of roofs with important substrate layer. An important number of events should be sampled to give statistically satisfactory results and to be able to compare different types of roof. A long term study on real scale roofs is on going to confirm the above findings. Acknowledgements The authors acknowledge the French network for research on civil engineering, RGCU for their financial support and Laurene Ghiglia for her contribution during her master project. References Adivet, FFB, CSFE, SNPPA, UNEP, 2007. Règles professionnelles pour la conception et la réalisation des toitures terrasses végétalisées. Report, second ed., p. 37 AFNOR, 2002. Qualité De L’eau e Recueil De Normes. Afnor Editions. Allen, R., Pereira, L., Raes, D., Smith, M., 1998. Crop Evapo-transpiration: Guidelines for Computing Crop Requirements. FAO e Food and Agriculture Organization of the United Nations, Rome. Alsup, S., Ebbs, S., Retzlaff, W., 2011. The exchangeability and leachability of metals from select green roof growth substrates. Urban Ecosystems 13, 91e111. APHA, 2005. Standard Methods for the Examination of Water and Wastewater. American Water Works Association Ed. Beck, D.A., Johnson, G.R., Spolek, G.A., 2011. Amending greenroof soil with biochar to affect runoff water quantity and quality. Environmental Pollution 159, 2111e 2118. Berghage, R.D., Beattie, D., Jarrett, A.R., Thuring, C., Razaei, F., O’Connor, T.P., 2009. Green Roofs for Stormwater Runoff Control. U.S. Environmental Protection Agency Report EPA/600/R-09/026 February, 2009, p. 81. Berndtsson, J.C., Bengtsson, L., Jinno, K., 2009. Runoff water quality from intensive and extensive vegetated roofs. Ecological Engineering 35, 369e380. Berndtsson, J.C., Emilsson, T., Bengtsson, L., 2006. The influence of extensive vegetated roofs on runoff water quality. Science of the Total Environment 355, 48e63. Boller, M., 1997. Tracking heavy metals reveals sustainability deficit of urban drainage system. Water Science and Technology 35, 77e87. Bressy, A., 2010. Flux de micropolluants dans les eaux de ruissellement urbaines: effets de différents modes de gestion à l’amont. PhD thesis. University Paris Est. Buccola, N., Spolek, G., 2011. A pilot-scale evaluation of greenroof runoff retention, detention, and quality. Water, Air, and Soil Pollution 216, 83e92. Chang, M., McBroom, M.W., Scott Beasley, R., 2004. Roofing as a source of nonpoint water pollution. Journal of Environmental Management 73, 307e315. Crouzet, P., Leonard, J., Nixon, S., Rees, Y., Parr, W., Laffon, L., Bøgestrand, J., Kristensen, P., Lallana, C., Izzo, G., Bokn, T., Bak, J., Lack, T.J., 1999. Nutrients in European Ecosystems. Czemiel Berndtsson, J., 2010. Green roof performance towards management of runoff water quantity and quality: a review. Ecological Engineering 36, 351e 360. Danneker, W., Stechmann, H., 1990. Substance load in rainwater runoff from different streets in Hamburg. The Science of the Total Environment 93, 385e392. Emilsson, T., Czemiel Berndtsson, J., Mattsson, J.E., Rolf, K., 2007. Effect of using conventional and controlled release fertiliser on nutrient runoff from various vegetated roof systems. Ecological Engineering 29, 260e271. Field, R., Sullivan, D., 2003. Wet-weather Flow in the Urban Watershed: Technology and Management. CRC Press LLC, Lewis Publishers. Förster, J., 1998. The influence of location and season on the concentrations of macroions and organic trace pollutants in roof runoff. Water Science and Technology 38, 83e90.

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